Machine readable Codebook - Carleton University...The annual plenary meeting of the ISSP then adopts the final questionnaire. ISSP questions have to be relevant to all countries and

GESIS Zentralarchiv fürEmpirische Sozialforschung

Codebook ZA Study 3910

I S S P 2 0 0 3

N a t i o n a l I d e n t i t y I I

Participating Nations: Austria Australia Bulgaria Canada Chile Czech Republic Denmark Finland France Germany Great Britain Hungary Ireland Israel Japan Latvia New Zealand Norway Philippines Poland Portugal Russia Slovakian Republic Slovenia South-Africa South-Korea Spain Sweden Switzerland Taiwan Uruguay United States Venezuela

Zentralarchiv fuer Empirische Sozialforschung an der Universitaet zu Koeln Bachemer Str. 40 D-50931 Koeln Tel: (+) 49 221-4 7694 - 0 Fax: (+) 49 221-4 7694 - 44 e-mail: [email protected] URL: http://www.gesis.org/ZA/ First complete edition: October 2005

mailto:[email protected]

ZA-No. 3910 I S S P 2003 National Identity II Page I - 1

Table of Contents Preface Acknowledgement of Assistance ............................................................................................... 3

An Introduction to the ISSP ....................................................................................................... 5

The International Social Survey Programme ............................................................... 5

ISSP Modules 1985 - 2003........................................................................................... 6

The ISSP Members Institute Addresses & ISSP Contacts ........................................... 7

Study Descriptions.................................................................................................................... 17

Study Description: Australia ................................................................................... 18

Study Description: Austria ...................................................................................... 21

Study Description: Bulgaria .................................................................................... 23

Study Description: Canada ...................................................................................... 26

Study Description: Chile ......................................................................................... 29

Study Description: Czech Republic......................................................................... 38

Study Description: Denmark ................................................................................... 40

Study Description: Finland...................................................................................... 44

Study Description: France ....................................................................................... 48

Study Description: Germany ................................................................................... 50

Study Description: Great Britain ............................................................................ 53

Study Description: Hungary .................................................................................... 56

Study Description: Ireland....................................................................................... 60

Study Description: Israel ......................................................................................... 63

Study Description: Japan ......................................................................................... 65

Study Description: Latvia ........................................................................................ 70

Study Description: New Zealand............................................................................. 72

Study Description: Norway ..................................................................................... 79

Study Description: Philippines ................................................................................ 82

Study Description: Poland ....................................................................................... 91

Study Description: Portugal..................................................................................... 96

Study Description: Russia ..................................................................................... 103

Study Description: Slovakian Republic.................................................................. 106

Study Description: Slovenia................................................................................... 108

Study Description: South-Africa ............................................................................ 110


Study Description: South-Korea ............................................................................ 114

Study Description: Spain ....................................................................................... 117

Study Description: Sweden ................................................................................... 119

Study Description: ...................................................................................Switzerland

125

Study Description: Taiwan .................................................................................... 129

Study Description: Uruguay .................................................................................. 131

Study Description: USA ........................................................................................ 136

Study Description: Venezuela ............................................................................... 138

Codebook Information............................................................................................................ 141

Explanations ........................................................................................................................... 142

Codebook Part

Data adocumentation and Cross-national Frequencies............................................................... 1

Socio-demographic variables ................................................................................................ 167

Appendix: Notes ..................................................................................................................... 296

International Occupation Codes: ILO/ISCO 1988 ................................................................. 296

Variable List ........................................................................................................................... 306

JaimeDiez

Note

Accepted set by JaimeDiez

JaimeDiez

Note

MigrationConfirmed set by JaimeDiez

JaimeDiez

Note

MigrationConfirmed set by JaimeDiez

JaimeDiez

Note

Completed set by JaimeDiez


Acknowledgement of Assistance All manuscripts utilizing data made available through the “Zentralarchiv fuer empirische Sozialforschung“ should acknowledge that fact as well as identify the original collectors of the data. We kindly ask all users to follow some adaptation of the following statement: The data utilized in this (publication) were documented and made available by the

ZENTRALARCHIV FUER EMPIRISCHE SOZIALFORSCHUNG, KOELN. The data for the 'ISSP' were collected by independent institutions in each country (see principal investigators in the study-description-schemes for each participating country). Neither the original data collectors nor the ZENTRALARCHIV bear any responsibility for the analyses or conclusions presented here

In order to provide funding agencies with essential information about the use of archival resources and to facilitate the exchange of information about research activities based on the ZENTRALARCHIV's holdings, each user is expected to send two copies of every completed manuscript to the ZENTRALARCHIV. The production and documentation of the annual ISSP integrated files are done in alternating years by the Zentralarchiv fuer empirische Sozialforschung as the archive of the ISSP, Cologne, Germany, and by ASEP/JDS, Madrid, Spain. The present codebook and data file for the ISSP module 2003 (National Identity II) were produced by ASEP/JDS.


Please note All marginal frequencies in this documentation are calculated from unweighted data! Please also consider that - especially in the section of the background variables – identical value codes of certain variables may not always have the same meaning for each country. Such country-specific differences are documented in this codebook.


An Introduction to the ISSP - the International Social Survey Programme The ISSP is a continuing annual programme of cross-national collaboration on surveys covering topics which are important for social science research. It brings together existing social science projects and coordinates research goals. Thereby the ISSP adds a cross-national, cross-cultural perspective to the national studies. As of 2004, thirty-nine countries are members of the ISSP. The founding stones of the ISSP were laid in 1983 when SCPR, London, secured funds from the Nuffield Foundation to hold meetings to further international collaboration between four existing surveys - the General Social Survey, conducted by NORC in the USA, the British Social Attitudes Survey, conducted by SCPR in Great Britain, the Allgemeine Bevölkerungsumfrage der Sozialwissenschaften, conducted by ZUMA in West Germany and the National Social Science Survey, conducted by ANU in Australia. Prior to this, NORC and ZUMA had been collaborating bilaterally on a common set of questions since 1982. The founding members agreed (1) to jointly develop modules addressing important areas of social science, (2) to field the modules as fifteen-minute supplements to the regular national surveys (or a special survey if necessary), (3) to include an extensive common core of background variables and (4) to make the data available to the social science community as quickly as possible. Each research organisation funds its own costs, there are no central funds. Merging and archiving of the data into a cross-national data set is performed by the Zentralarchiv fuer Empirische Sozialforschung, University of Cologne. Since 1997, the Zentralarchiv and the Spanish institute ASEP (Análisis Sociológicos Económicos y Políticos) share the task of merging the national data sets. Since its conception in 1984, 40 nations have participated in the ISSP: the founding four - Australia, Germany, Great Britain and the United States - plus Austria, Bangladesh, Brazil, Bulgaria, Canada, Chile, Cyprus, the Czech Republic, Denmark, Finland, Flanders, France, Hungary, Israel, Ireland, Italy, Japan, Latvia, Mexico, the Netherlands, New Zealand, Norway, the Philippines, Poland, Portugal, Russia, the Slovakian Republic, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Uruguay and Venezuela. The topics for each ISSP survey are developed over several years by a committee and are pre-tested in various countries. The annual plenary meeting of the ISSP then adopts the final questionnaire. ISSP questions have to be relevant to all countries and must be expressed in an equivalent manner in all languages. The questionnaire is originally drafted in British English and then translated to the languages of the member countries. The ISSP marks several new departures in the area of cross-national research: (1), the collaboration between members is organised in a stable framework.(2), the ISSP makes cross-national research an integral part of the research agendas of participating countries. (3), by combining a cross-time perspective with a cross-national perspective, two powerful research designs can be used to study societal processes.


ISSP Modules 1985 - 2007 Surveys Already Fielded and Archived ISSP 1985 Role of Government I ZA No. 1490 ISSP 1986 Social Networks and Support Systems ZA No. 1620 ISSP 1987 Social Inequality I ZA No. 1680 ISSP 1988 Family and Changing Gender Roles I ZA No. 1700 ISSP 1989 Work Orientations I ZA No. 1840 ISSP 1990 Role of Government II ZA No. 1950 ISSP 1991 Religion I ZA No. 2150 ISSP 1992 Social Inequality II ZA No. 2310 ISSP 1993 Environment I ZA No. 2450 ISSP 1994 Family and Changing Gender Roles II ZA No. 2620 ISSP 1995 National Identity ZA No. 2880 ISSP 1996 Role of Government III ZA No. 2900 ISSP 1997 Work Orientations II ZA No. 3090 ISSP 1998 Religion II ZA No. 3190 ISSP 1999 Social Inequality III ZA No. 3430 ISSP 2000 Environment II ZA No. 3440 ISSP 2001 Social Relations and Support Systems ZA No. 3680 ISSP 2002 Family and Changing Gender Roles III ZA No. 3880 ISSP 2003 National Identity II ZA No. 3910 Currently Conducted or Planned Surveys ISSP 2004 Citizenship ISSP 2005 Work Orientation III ISSP 2006 Role of Government IV ISSP 2007 Leisure Time and Sports


The ISSP Members Institute Addresses & ISSP Contacts An up to date list of member organisations is always available at the ISSP World Wide Web site: http://www.issp.org Secretariat Knut Kalgraff Skjåk,

Bjørn Henrichsen, Kirstine Kolsrud, NSD (Norwegian Social Science Data Services) Hans Holmboesgate 22 N - 5007 Bergen NORWAY

• Tel: 0047-55-583-246 • Fax: 0047-55-589-650

Archive Markus Quandt,

Wolfgang Jagodzinski Zentralarchiv für Empirische Sozialforschung (ZA) Universitaet zu Koeln Bachemer Str. 40 50931 Koeln GERMANY

• Tel: 0049-221-47694-0 • Fax: 0049-221-47694-44

Australia Rachel Gibson,

ACSPRI Centre for Social Research (ACSR) Research School of Social Sciences Canberra, ACT 0200 The Australian National University AUSTRALIA

• Tel: +61-(0)2-6125-3111/2136 • Fax: +61-(0)2-6125-2992

Austria Max Haller,

Franz Hoellinger, Markus Hadler, Institute of Sociology University of Graz Universitaetsstraße 15/G4 A-8010 Graz AUSTRIA

• Tel: 0043-316-380-3541 • Fax: 0043-316-380-9515

http://www.issp.org/


Brazil Maria Celi Scalon, Instituto Universitario de Pesquisas do Rio de Janeiro Rua da Matriz, 82 22260-100 Botafago Rio de Janeiro BRAZIL

• Tel: +0055-21-2537-8020 • Fax: +0055-21-2286-7146

Bulgaria Lilia Dimova,

Agency for Social Analyses 1 Macedonia Sq. 1040 Sofia BULGARIA

• Tel: 00359-2-917-0455 • Fax: 00359-2-986-1072

Canada Heather Pyman,

Jon Pammett, Carleton University Survey Centre Carleton University 346 St. Patrick's Building Ottawa CANADA KIS 5B6

• Tel: 001-613-520-2600 • Fax: 001-613-520-6690

Chile Carolina Segovia,

Centro de Estudios Publicos Monsenor Sótero Sanz 175 Providencia Santiago CHILE

• Tel: 0056-2-231-5324 • Fax: 0056-2-233-5253

Cyprus Bambos Papageorgiou,

Centre of Applied Research Cyprus College 6 Diogenes Street Engomi P.O. Box 2006 Nicosia CYPRUS

• Tel: 00357-2-713-175 • Fax: 00357-2-664-531


Czech Republic Petr Mateju, Institute of Sociology Academy of Sciences of the Czech Republic Jilska 1 110 00 Praha 1 CZECH REPUBLIC

• Tel: 0042-2-2222-0678 • Fax: 0042-2-2222-1658

Denmark Jørgen Goul Andersen,

Johannes Andersen, Mette Tobiasen Department of Economics, Politics and Public Administration Aalborg University Fibigerstraede 1 DK-9220 Aalborg DENMARK

• Tel: 0045-9635-8173 • Fax: 0045-9815-5346

Finland Professor Raimo Blom,

Professor Harri Melin, Department of Sociology and Social Psychology FIN-33014 University of Tampere FINLAND

• Tel: 00358-3-215-6566/7019 • Fax: 00358-3-215-6080

Eero Tanskanen, Survey Research Unit FIN-00022 Statistics Finland FINLAND

• Tel: 00358-9-1734-2549 • Fax: 00358-9-1734-3562

Sami Borg, FSD Finnish Social Science Data Archive FIN-33014 University of Tampere FINLAND

• Tel: 00358-3-215-8519 • Fax: 00358-3-215-8520


Flanders Ann Carton, Administration of Planning and Statistics – Ministry of Flanders Boudewijnlaan 30 1000 Brussel Belgium

• Tel: 0032-2-553-5687 • Fax: 0032-2-553-5808

Jaak Billiet, Department of Sociology Katholic Universiteit Leuven E.Van Evenstraat 2B B-3000 Leuven BELGIUM

• Tel: 0032-16-323157 • Fax: 0032-16-323365

France Yannick Lemel,

FRANCE-ISSP Association (Centre de Rechere en Économie et Statistique) Laboratorie de Sociologie Quanitative Timbre J350-Bureau E33 bis 92240 Malkoff Cedex FRANCE Pierre Bréchon, Bruno Cautres CIDSP (Centre d'Infomatisation des Données Socio-Politiques) Institut d'Études Politiques de Grenoble Domaine Universitaire BP 45 38402 St. Martin D'Heres Cedex FRANCE

L. Chauvel, M. Forsé OFCE (Observatorie Français des Conjonctures Économiques) 69, Quai d'Orsay 75340 Paris Cedex 07 FRANCE A. Degenne

LASMAS (Laboratoire d'Analyse Secondaire et de Méthodes Appliquées en Sociologie) 59-61, rue Pouchet 75849 Paris Cedex 07 FRANCE


Germany Janet Harkness, Prof. Dr. Peter Mohler Evi Scholz, Sabine Klein ZUMA (Zentrum für Umfragen, Methoden, und Analysen) P. O. Box 12 21 55 68072 Mannheim GERMANY

• Tel: 0049-621-1246-284 • Fax: 0049-621-1246-100

Great Britain Alison Park,

Roger Jowell, National Centre for Social Research 35 Northampton Square London, EC1V OAX GREAT BRITAIN

• Tel: 0044-171-250-1866 • Fax: 0044-171-250-1524

Hungary Peter Robert,

TÁRKI RT Social Research Institute Budaorsi ut. 45 H-1112 Budapest HUNGARY

• Tel: 0036-1-309-7676 • Fax: 0036-1-309-7666

Ireland Marie Nic Ghiolla Phadraig (Director SSRC)

Conor Ward, Philippa Caithness (Senior Executive Assistant), SSRC (Social Science Research Centre) University College Dublin Dublin 4 IRELAND

• Tel: 00353-1-7167001 • Fax: 00353-1-7161125

Israel Noah Lewin-Epstein,

Eppie Yuchtman-Yaar Dept. of Sociology and Anthropology Tel Aviv University P.O. Box 39040, Ramat Aviv 69978 Tel Aviv ISRAEL

• Tel: 00972-3-6409-271/762 • Fax: 00972-3-6409-215


Italy Luca Diotallevi, CENSIS Piazza di Novella, 2 00199 Roma ITALY

• Tel: 0039-6-860911 • Fax: 0039-6-86211367

Japan Hiroshi Aramaki,

NHK, Broadcasting Culture Research Institute Public Opinion Research Division 2-1-1 Atago, Minato-ku Tokyo 105-0002 JAPAN

• Tel: 0081-3-5400-6800 • Fax: 0081-3-3438-4375

Latvia Aivars Tubuns,

Ausma Tabuna, Institute of Philosophy and Sociology Akademijas 1 LV-1940, Riga LATVIA

• Tel: 00371-7-227110 • Fax: 00371-7-210806

Mexico Federico Curiel Gutierrez,

Institute of Marketing and Opinion Paseo de la Reforma 90, Cuarto piso Mexico, D.F. 06600 MEXICO

• Tel: 0052-55-5535-6239 • Fax: 0052-33-3915-2626

Netherlands Harry Ganzeboom,

SCP (Sociaal en Cultureel Planbureau) Parnassusplein 5 PO Box 16164 2500 BD Den Haag THE NETHERLANDS

• Tel: 0031-70-340-7000 • Fax: 0031-70-340-7044


New Zealand Philip Gendall, Department of Marketing Massey University Private Bag 11222 Palmerston North NEW ZEALAND

• Tel: 0064-6-350-5582 • Fax: 0064-6-350-2260

Norway Knut Kalgraff Skjåk,

Bjørn Henrichsen, Kirstine Kolsrud, NSD (Norwegian Social Science Data Services) Hans Holmboesgate 22 N - 5007 Bergen NORWAY

• Tel: 0047-55-583-246 • Fax: 0047-55-589-650

Philippines Mahar Mangahas,

52 Malingap Street Sikatuna Village Quezon City 1101 PHILIPPINES

• Tel: 0063-2-926-4308 • Fax: 0063-2-920-2181

Poland Bogdan Cichomski,

ISS (Institute for Social Studies) University of Warsaw Stawki 5/7 00-183 Warsaw POLAND

• Tel: 0048-22-315-153 • Fax: 0048-22-315-153

Portugal Manuel Villaverde Cabral,

Alice Ramos, Instituo de Ciências Sociais University of Lisbon Av. Prof. Anibal Bettencourt, 9 1600-189 Lisbon PORTUGAL

• Tel: 00351-21-780-4700 • Fax: 00351-21-794-0274


Russia Ludmila Khakhulina, Levada Analytic Center 17, Nikolskaya str. Moscow 103829 RUSSIA

• Tel: 007-95-229-5545 • Fax: 007-95-200-4648

Slovakian Republic Magdalena Piscova,

Institute for Sociology Slovak Academy of Science Klemensova 19 81364 Bratislava SLOVAK REPUBLIC

• Tel: 00421-2-5296-4355 • Fax: 00421-2-5296-2315

Slovenia Mitja Hafner-Fink,

Public Opinion and Mass Communications Research Centre Faculty of Social Sciences University of Ljubljana Kardeljeva ploscad 5 1000 Ljubljana SLOVENIA

• Tel: 00386-1-580-5105 • Fax: 00386-1-580-5106

South Africa Jare Struwig,

Human Science Research Council Private Bag X41 Pretoria 0001 SOUTH AFRICA

• Tel: 0027-12-302-2487 • Fax: 0027-12-302-2525


Spain Juan Díez-Nicolás, ASEP (Análisis Sociológicos Económicos y Políticos) Po de la Castellana 173, 5o Izquierda 28046 Madrid SPAIN

• Tel: 0034-91-570-5107 • Fax: 0034-91-579-4073

Natalia Garcia Pardo,

CIS (Centro de Investigaciones Sociológicas) Montalbán 8 28014 Madrid SPAIN

• Tel: 0034-91-580-7664 • Fax: 0034-91-580-7619

South Korea Professor Sang-Wook Kim (Principle), Survey Research Center, Sungyunkwan University 53, Myungryun-Dong 3-Ga, Jongno-Gu Seoul, 110-745 Korea

• Tel: 0082-2-760-0412 • Fax: 0082-2-744-6169

Dr. Sook Hee, Choi, Samsung Economic Research Institute 7th Floor, Kukje Center Bldg. 191 hangangro 2-Ga, Yongsan-Gu Seoul, 140-702 Korea

• Tel: 0082-2-3780-8065 • Fax: 0082-2-3780-8008

Sweden Jonas Edlund,

Dept. of Sociology University of Umeå 901 87 Umeå SWEDEN

• Tel: 0046-90-786-7822 • Fax: 0046-90-786-6694

Switzerland Dominique Joye,

SIDOS (Swiss Information and Data Archive for the Social Sciences) Ruelle Vaucher 13 CH-2000 Neuchâtel SWITZERLAND

• Tel: 0041-32-721-2002 • Fax: 0041-32-721-2074


Taiwan Yang-chih Fu, Institute of Sociology Academica Sinica Nankang, Taipei TAIWAN 11529

• Tel: 00886-2-2652-3359/3402 • Fax: 00886-2-2653-6488 • Fax: 00886-2-2651-0415

Uruguay Giorgina Piani,

Departamento de Economia, Facultad de Ciencias Sociales, Universidad de la Republica J. E. Rodo 1854 Montevideo Uruguay

• Tel: (734) 647-9255 (office) • Fax: (734) 332-7916 (home)

Maximo Rossi, Departamento de Economia, Facultad de Ciencias Sociales, Universidad de la Republica J. E. Rodo 1854 Montevideo Uruguay

• Tel: (598-2) 409-2973 (office)

U.S.A. Tom W. Smith, National Opinion Research Center (NORC) 1155 East 60th Street Chicago, IL 60637 U.S.A.

• Tel: 001-773-256-6288 • Fax: 001-773-753-7886

Venezuela Roberto Briceno-Leon,

LACSO (Laboratorio de Ciencias Sociales) Research School of Social Sciences Apartado Postal 47.795 Caracas 1041-A VENEZUELA

• Tel: 0058-212-6931765 0058-212-6619752

• Fax: 0058-414-6931765 0058-414-7534941


Study Descriptions To differentiate countries in the cross tabulations within this codebook we have decided to use the international ISO codes: Australia AU Austria AT Bulgaria BG Canada CA Chile CL Czech Republic CZ Denmark DK Finland FI France FR Germany (West) DE-W Germany (East) DE-E Great Britain GB Hungary HU Ireland IE Israel IL Japan JP Latvia LV New Zealand NZ Norway NO Philippines PH Poland PL Portugal PT Russia RU Slovakian Republic SK Slovenia SI South Korea KR South Africa ZA Spain ES Sweden SE Switzerland CH Taiwan TW Uruguay UY USA US Venezuela VE


Study Description: Australia Study title:

ISSP 2003 National Identity

Fieldwork dates:

Start: 27 August 2003 Finish: 24 December 2003

Principal investigators:

Rachel Gibson, Australian National University Shaun Wilson, Australian National University

Sample type:

The sample was stratified by Australian states and territories using population counts from the 2001 Census. The selection of individuals within the stratified sample was random using the Electoral Roll for Australia produced by the Australian Electoral Commission (AEC). The 2001 version of the Electoral Roll was updated for 2002 where state and territory elections had taken place. This frame includes all registered voters who must be citizens of Australia (or a British subject on a Commonwealth electoral roll as at 25 January 1984). Since voting in Australia is compulsory, there is a very high proportion of the adult Australia population covered by this frame— approximately 92 percent in 2003. The sampling method used a random number generator inserted as a field in the electoral roll database; individuals were sorted using the

random number and then selected in order. The sampled units were named individuals.

Fieldwork Institute:

Australian Social Science Data Archive

Fieldwork methods:

Self-completion, paper and pencil, mailed to, mailed back by respondent

Sample size: 2183 Response rates: 5696 A - Total issued 796 B – Not eligible (ill, dead, non-English speaking, not at this address ) 4900 C - Total eligible 2183 D - Total ISSP questionnaires received 2717 E - non-responses (including non-contact; see note above

under “sample type”) 283 F - Refusals (including questionnaires less than half filled in) 2374 G - Non-contact (included in “E”) 60 H - Other non-response (included in “E”) Language:

English

Weighted:

No

Weighting Procedure:


Known Systematic Properties:

Gross sample Using a sampling frame derived from the AEC Electoral Roll (2001) excludes permanent and temporary residents of Australia (who are not citizens) and any othe r adults in Australia who are non-citizens except for British subjects on a Commonwealth electoral roll as at 25 January 1984. These exclusions amount to approximately 8 percent of the adult population. Net sample The AUSSA 2003 sample demographics were compared with statistics available from the Australian Bureau of Statistics (ABS) including the 2001 Census. The major biases are: age (median age is older than the Census population), education (over-representation of persons with post-secondary school qualifications), and gender (slightover-representation of women).

Deviations from ISSP-questionnaire:

For V4-V6 “Most important group R identifies with”, the response categories were converted from numbers to letters (A, B, C….) after a piloting experiment revealed greater respondent accuracy with the latter. V8 “How close do you feel…”: response category was State or territory (appropriate internal regional breakdown for Australia. V10 “How close do you feel…”: response category was Asia (since Australia is both a continent and country)

All changes were approved by the ISSP prior to the fielding of the Survey.

Publications: Gibson, R. et al. The Australian Survey of Social Attitudes, 2003 [computer file]. Canberra: Australian Social Science Data Archive, The Australian National University, 2004.


ISSP Characteristics of National Population: Australia The following data are made available to the ISSP from statistics derived from the Australian Bureau of Statistics (ABS) publications including the June 2001 Census. Please note that the ABS does not compile data on years of schooling completed. In its place, we have used educational attainment data (see Table 3) to provide meaningful comparisons between the AuSSA 2003 sample and ABS data. For further information, please contact Shaun Wilson at [email protected] Table 1: Sex distribution of AuSSA sample versus Australian population (18 years and over)

AuSSA 2003 ABS – Census June 2001

difference

Male 46.9 49.1 -2.2Female 53.1 50.9 +2.2

n=4,224 n=14,343,846 Source: Australian Survey of Social Attitudes, 2003; Australian Bureau of Statistics Pub. No. 3105.0.65.001 Australian Historical Population Statistics: TABLE 19 (Population age and sex, Australia, year ended 30

Table 2: Age distribution *


difference

18-34 years 17.1 31.0 -13.935-49 30 30.2 -0.250-64 30.1 21.8 -5.9

65 and over 22.9 17.0 +5.9 n=4,212 n=14,343,846 Source: Australian Survey of Social Attitudes, 2003; Australian Bureau of Statistics Pub. No. 3105.0.65.001 Australian Historical Population Statistics: TABLE 19 (Population age and sex, Australia, year ended 30 June 2001) * 18-34 year statistic for ABS data calculated using linear interpolation methods

Table 3: Educational attainment *


difference

Bachelor degree and higher

25.7 14.6 +11.1

Certificate or diploma

34.5 38.5 -4.0

Year 12 and less 39.8 46.9 -7.1 n=3,267 n=11,578,000 Source: Australian Survey of Social Attitudes, 2003; Australian Bureau of Statistics Pub. No. 1301.0-2004 Year Book Australia: TABLE 10.36 (Level of highest non-school qualification, by age group, May 2002) * 20 – 64 years

Table 4: Labour force participation rate (employment rate)


difference

In labour force 60.4 63.6 -3.2Not in labout force 39.6 36.4 +3.2

n=4,207 n/a Source: Australian Survey of Social Attitudes, 2003; Australian Bureau of Statistics Pub. No. 6202.0.55.001 Labour Force, Australia, Spreadsheets: TABLE 01 (Labour force status by Sex - Trend, June 2001)


Study Description: Austria

Study title:

ISSP-Studie 2004: Nationale Identität; Bürger/innen und Staat (National Identity; Citizenship)

Fieldwork dates:

Nov. and Dec. 2004


Dr. Max Haller, Dr. Markus Hadler, Mag. Regina Ressler Institut für Soziologie, Karl-Franzens-Universität Graz, Austria

Sample type:: Stratified Multistage Clustered Random Sampling

Fieldwork institute: Institute for Empirical Social Research (IFES), Vienna

Fieldwork methods: Face-to-face interviews with trained interviewers

Sample size: 1006

Context of ISSP Questionnaire:

Social Survey Austria

Response rates: 2200 A – Total issued (total sample) 76 B – Ineligible (address vacant, wrong ages..)

2124 C – (=A – B) Total eligible (in scope sample) 1669 D – Total ISSP questionnaires received 663 E – (= C – D; = F + G + H) Total no response 278 F – Refusals (refusing to take part) 385 G – Non-contact (never contacted)

- H – Other non-response Language:

German

Weighted: Yes

Weighting procedure: A weighting variable was computed, taking into account sex, age group and province of residence.


ISSP Characteristics of National Population: Austria SOURCE

Census 2001 Statistics Austria

2004

SEX Male 48,4% Female 51,6% AGE (groups) 0-14 14,4% 15-19 5,2% 20-24 5,0% 25-29 5,7% 30-34 7,1% 35-39 7,5% 40-44 6,7% 45-49 5,6% 50-54 5,5% 55-59 4,8% 60-64 4,8% 65-69 3,5% 70-74 3,5% 75-79 3,1% 80-84 1,6% 85+ 1,5% EDUCATION (15 years and older)

Years of schooling University compl. (Universitaet oä.) 6,8% 15 Secondary compl. (hoehere Schule) 14,6% 12

Secondary incompl. (Lehre, Fachschule) 45,1% 11 Primary compl. (Pflichtschule) 33,5% 9

EMPLOYMENT STATUS (15-59 years) Employed (Erwerbsquote) 48,8% Unemployed 6,9% (annual average 2002) Not in labour force 24,7%


Study Description: Bulgaria Study title:

Social survey

Fieldwork dates:

April-May 2003


Dr. Lilia Dimova, Agency for Social Analyses (ASA)

Sample type:

Two-stage cluster sample, representative for the whole adult population of Bulgaria over 18 year of old.

Context of ISSP questionnaire how it is in the hard copy questionnaire

Qs A1,A2B – A15 = National Identity module (B 1-12; C 1 - 23; E 1 - 5, F 1 - 13, G 1 -6 = Roma issues) D1 – D12, D14 – D16, D17A, D18A, D19 – D20, D23 – D24, D28 - D30, D32, T2 –T4 = The ISSP Standard Background Variables (D13, D21- D22 = Roma issues)

Fieldwork methods:

Face-to-face interview at respondent’s home

Sample size: Achieve sample 1069 cases Response rates: 1200 A - Total issued (total sample) 17 B - Ineligible (address empty) 1183 C - (= A - B) Total eligible (in-scope sample) 1069 D - Total ISSP questionnaires received 114 E - (= C - D; = F + G + H) Total non-response 35 F - Refusals (refusing to take part) 73 G - Non-contact (never contacted, away for long) 6 H - Other (too sick) Language:

Bulgarian

Weighted:

No

Weighting Procedure: Deviations from ISSP-questionnaire:

Missing questions V18, V23, V24 – because of technical reasons.


ISSP Characteristics of National Population: Bulgaria Table 1. comparisons between population by administrative centres and the sample data

Administrative centres Hard data * Hard data structure (%)

Sample data (N=1 069)(%)

Blagoevgrad 343370 4,31 4,5 Burgaz 426028 5,34 5,2 Varna 465012 5,83 5,7 Veliko Turnovo 294790 3,70 3,6 Vidin 131215 1,65 1,5 Bratza 244881 3,07 2,8 Gabrovo 144849 1,82 2,2 Dobrich 217012 2,72 2,7 Kardjali 164958 2,07 3,6 Kustendil 163388 2,05 2,2 Lovech 171236 2,15 2,2 Montana 183353 2,30 2,2 Pazardjik 313059 3,93 4,2 Pernik 150318 1,89 1,5 Pleven 313630 3,93 4,8 Plovdiv 721905 9,05 8,6 Razgrad 153156 1,92 2,2 Ruse 267618 3,36 3,1 Silistra 142815 1,79 2,2 Sliven 220273 2,76 3,0 Smolian 140664 1,76 1,5 Sofia - City 1173811 14,72 11,2 Sofia- Region 273882 3,43 3,8 Stara Zagora 372849 4,68 5,2 Targoviste 138703 1,74 1,4 Haskovo 279067 3,50 3,9 Shumen 205198 2,57 2,5 Yambol 156631 1,96 2,2 Total 7973671 100 100

Source: National Census, March 2001. Table 2. Ethnic distribution

National Census March 2001 Ethnic groups

Total %

Sample data % (N=1069)

Bulgarians 5705887 85,3 86,2 Turks 590022 8,8 7,3 Rma people/ Gypsi 249286 3,7 4,9 Others 100129 1,5 1,1 No answer 45961 0,7 0,6 Total 6691285 100 100


Table 3. gender distribution

Hard data* March 2001

Hard data (%)

Hard data**End of 2002

Hard data (%)

Sample data (%)

Male 3 888 441 48.766 3 816 162 48.639 48.7 Female 4 085 232 51.234 4 029 679 51.361 51.3 Total 7 973 673 100 7 845 841 100 100

* Source: National Statistical Institute, National Census 2001 – 2% sample distribution ** Source: www.nsi.bg/Population/Population.htm

Table 4. characteristics of national population form

Demographics Hard data March 2001 (%)*

Hard data (%) End of 2002** Sample data (%)

Sex 100 100 100 Male 48,8 48.6 48.7 Female 51,2 51.4 51.3 Urban/Rural distribution 100 100 100 Urban 69,0 69.6 68.8 Rural 31,0 30.4 31.2

Employment status 100 100 100

Employment rate 40.3 40.8 Unemployment rate 16.8 13.1 Not labor force 46.1 * National Statistical Institute, National Census 2001 – 2% sample distribution ** Source: www.nsi.bg/Population/Population.htm , www.nsi.bg/Labour/Labour.htm Table 4. urban distribution

March 2001*(%) Sample data N=1069 (%) Total 100 100 City 68,4 68,8 Village 31,6 31,2 Male 100 100 City 32,5 33,8 Village 15,6 15,0 Female 100 100 City 35,6 35,0 Village 16,3 16,3 * National Statistical Institute, National Census 2001 – 2% sample distribution

http://www.nsi.bg/Population/Population.htm

http://www.nsi.bg/Population/Population.htm

http://www.nsi.bg/Labour/Labour.htm


Study Description: Canada Study title:

2003 National Identity 2004 Citizenship

Fieldwork dates:

January 29th, 2004 – March 31st, 2004


Carleton University Survey Centre

Sample type:

Stratified Random


National Identity with Citizenship

Fieldwork methods: Self-completion Mail Sample size: Achieve sample 1069 cases Sampling method A stratified random sample (by province by gender) of 3,000

Canadian residents was purchased from Cornerstone List Brokerage, based on residential phone listings. (% of Canadians without phones < 2%) The design consisted of two mailouts and 1 reminder notice. The first mailout of 3,000 packages was mailed on January 29, 2004 and included a questionnaire, explanatory letter printed on the front cover and a postage paid return envelope. On February 10th a reminder postcard was mailed out to the entire sample. On February 26th a second mailout was sent to the respondents who had not returned their survey along with a additional letter explaining the importance of their participation in the project.

Response rates: Process

1st wave -Initial mailout -January 29th 3000 Returned as of Feb.24th 678 2nd wave – reminder cards -February 10th 3000 3rd wave – 2nd full mailout -February 26th 2322

Returned as of March 31st 600 Total Returned Surveys 1278

Composition 40 returned refused 27 incomplete 1211 complete

Sample report


Sampling Frame 3,000 Returned to sender • address incomplete 60 • moved/not picked up 55 • deceased 11 Total viable sample 3,000-126 = 2,874 Response rate 43%

Language:

French and English

Weighted:

Yes


Weighted by province and age

Publications: None


ISSP Characteristics of National Population: Canada Source: Statistics Canada Gender Male 49.52 Female 50.48 Employment Employed 62.4 Unemployed 7.5 Not in labour force 30.10 Total years of schooling (population 18+) 1-9yr. 20.5 10-11yr. 19.0 12-13yr. 30.1 14+yr. 30.1 Population by sex and age group

2003 Canada Male Female Canada Male Female

Age group Persons (thousands) % of total of each group Total 31,629.7 15,661.7 15,967.9 100.0 100.0 100.00–4 1,714.3 877.3 837.0 5.4 5.6 5.25–9 1,949.7 998.6 951.1 6.2 6.4 6.010–14 2,117.6 1,084.8 1,032.9 6.7 6.9 6.515–19 2,120.5 1,088.8 1,031.8 6.7 7.0 6.520–24 2,188.5 1,119.0 1,069.5 6.9 7.1 6.725–29 2,118.1 1,074.0 1,044.2 6.7 6.9 6.530–34 2,228.7 1,124.8 1,103.9 7.0 7.2 6.935–39 2,481.2 1,247.4 1,233.8 7.8 8.0 7.740–44 2,719.3 1,364.3 1,355.0 8.6 8.7 8.545–49 2,515.7 1,251.6 1,264.2 8.0 8.0 7.950–54 2,176.5 1,078.8 1,097.7 6.9 6.9 6.955–59 1,842.5 913.9 928.5 5.8 5.8 5.860–64 1,396.8 684.8 712.0 4.4 4.4 4.565–69 1,147.9 552.2 595.7 3.6 3.5 3.770–74 1,039.1 484.2 554.9 3.3 3.1 3.575–79 839.4 358.8 480.7 2.7 2.3 3.080–84 583.7 221.6 362.0 1.8 1.4 2.385–89 297.0 97.2 199.7 0.9 0.6 1.390 and over 153.1 39.8 113.3 0.5 0.3 0.7Note: Population as of July 1. Source: Statistics Canada, CANSIM II, table 051-0001. Last modified: 2003-11-06.

http://cansim2.statcan.ca/cgi-win/cnsmcgi.exe?Lang=E&RootDir=CII/&ResultTemplate=CII/CII_pick&Array_Pick=1&ArrayId=510001


Study Description: Chile Study title:

Second National Public Opinion Study 2003

Fieldwork dates:

December 6th to 24th 2003


Carolina Segovia, Carla Lehmann and Paulina Valenzuela of Centro de Estudios Públicos

Sample type:

The guiding methodological principle underlying CEP's public opinion surveys is that effective and accurate survey research must be based on a truly representative sample of the universe in question. For CEP’s purpose, this universe is made up of Chilean adults 18 years of age and older. Our studies use a probability multistage cluster sample of 1,505 individuals.

The sample is designed in three stages, such that all adult individuals throughout the country have a calculable probability of being included. The 2002 Census data is consulted to determine the regional population structure of people 18 years of age and older. This makes it possible firstly to establish regional stratification and then each region is stratified by rural and urban zone. Table I shows the regional structure of the Chilean population.

Table I

Regional Breakdown of Population (%)

Region

% Population 18 years of age and older1

Region

% Population 18 years of age and older1

I Tarapacá 2,8 VII Maule 5,9

II Antofagasta 3,2 VIII Bío Bío 12,2

III Atacama 1,6 IX La Araucanía 5,6

IV Coquimbo 3,9 X Los Lagos 7,0

V Valparaíso 10,4 XI Aisén 0,6

VI Libertador Bdo.

O'Higgins 5,1

XII Magallanes and

Antarctic 1,0

XIII Metropolitan

(Santiago)

40,7

1Source: 2002 Census Data National Institute of Statistics.

Sampling Stages

First Stage

The first stage of the sampling process sets the number of completed interviews per cluster at 5; a cluster is defined as a block (manzana) or populated entity (entidad).1 The application of 5 interviews per cluster to the total number of interviews targeted in the sample (1,505) yields

1 Blocks (manzanas) are used in urban areas, while in rural areas the census equivalent is the entity (entidad).


301 primary sampling units (PSUs) to be identified in the first stage of sample selection.

The PSUs are proportionally distributed throughout the regions of the country, taking into account the region's contribution to population (both urban and rural), as described in Table II.

TABLE 2

Number of Clusters per Region Number of clusters Region Urban Rural Total

I Tarapacá 7 1 8 II Antofagasta 10 0 10 III Atacama 5 0 5 IV Coquimbo 9 3 12 V Valparaíso 28 3 31 VI Libertador Bdo. O'Higgins 10 5 15 VII Maule 12 6 18 VIII Bío Bío 30 7 37 IX La Araucanía 11 6 17 X Los Lagos 14 7 21 XI Aisén 2 0 2 XII Magallanes and Antarctic 3 0 3 XIII Metropolitan (Santiago) 118 4 122

TOTAL 259 42 301

Using the most reliable digital information on hand, i.e. 2002 census data, a cumulative listing of population by province (provincia), borough (comuna), district (distrito), zone (zona) and block (manzana) was prepared in the urban case; and by province, borough, district, locality (localidad) and entity (entidad) in the rural case (geographically arranged).

In both the rural and the urban case a fixed interval is set for each region by dividing the total population for that region by the number of PSU’s assigned to it. Within each region, a purely random selection process is followed, such that each individual (as represented by population statistics) has a calculable probability of being selected as the reference point for a PSU.

This is carried out through a computerised, random, proportionate-to-population process to select blocks in the urban areas and entities in the rural areas. A computer program is developed to select the 259 urban blocks and the 42 rural entities for the sample. All the blocks and entities are identified by number and located on a census map.


Second Stage

The second stage in the sampling process is to select households (dwellings) within PSUs. Selection rules for households within chosen blocks and entities are provided to interviewers, to enable them to select households randomly within each cluster. After taking a census of each selected block and entity, a random walk or systematic sampling2 procedure is followed, whereby every nth dwelling is included in the sample until a total of 5 households are identified.

Third Stage

The third stage is to select, within each household, a person to be interviewed. Interviewers are instructed to apply a random selection process (random number table) to identify the person to be interviewed.

Other Important Aspects in the CEP Sample Design

In the second and third stages, the interviewer has to make a minimum of three attempts on three different days to try to reach the original house or person to be interviewed. In these attempts the interviewer must deliver a letter signed by the CEP director explaining the nature of CEP and the aims of the study.

If the original household or person finally cannot be contacted, they are replaced. The rules for replacement are as follows:

A. Blocks and Entities

The replacement of a block or entity will occur only in the following situations:

1) Vacant lots that could not be detected prior to sample selection

2) Areas which are almost inaccessible

3) Entities and/or blocks intended basically for commercial use

4) Parks or stadiums

5) Areas belonging to the armed forces

Blocks and entities are randomly replaced: the original selection is replaced with the one whose identification number comes immediately before that of the original. If this is not successful, the block/entity with the identification number immediately following the original selection is taken.

2 The total number of numbered dwellings was divided by 5 (the number of interviews per cluster); this gave an interval length, such that if it was 43/5 =

8, starting from the point randomly pre-assigned as the first dwelling, the interviewers went to dwelling No 9, then to No 17, and so on until 5 interviews were completed.


B. Households

Failed dwellings are accounted for as follows:

1) by outright refusal to receive the interviewer, even having received the letter from the CEP director.

2) by the absence of occupants at a house after three visits on three different days (vacations or other reasons).

3) the house is unoccupied.

4) access denied (condominiums or buildings with security guards)

5) other special cases (foreigners with whom it is impossible to communicate, etc.)

Each failed dwelling is randomly replaced by another one from the same block/entity. The replacement interval is defined as (k-1), where k= the original selection interval. Starting from the last house originally selected, the interval (k-1) is added to select the first replacement house, and so on. The fieldwork treatment of replacement houses as regards the number of repeat visits is the same as for the original houses.

C. Individuals

Individuals are replaced under the following circumstances:

1) when the person selected refuses to answer the questionnaire, even after receiving the letter from the CEP director.

2) when the person selected cannot be located after three attempts on three different days, or will be away for a period longer than the duration of fieldwork.

3) the person offers to respond on a date long after the closing date of the field work.

4) individuals with serious physical or psychological handicaps which prevent them from responding (mentally handicapped, deaf and dumb, etc..)

5) the individual is physically and psychologically fit, but is ill, in bed and does not want, or is unable to respond to the survey.

6) the selected individual is a foreigner with less than 5 years in the country (unable to vote).

7) the person starts to answer but he/she does not want to finish the interview.


8) other specific cases.

In replacing individuals, the dwelling is replaced according to the rules explained above, and a random selection process chooses an individual from the new household.

It is important to bear in mind that, by using these replacement rules, the sample size achieved is always very close to 1505 (issued sample size).


The National Identity 2003 module of the ISSP was carried out in conjunction with 24 questions relating to Chilean political, economic and social attitudes and tendencies. The questionnaire was structured as follows: firstly, the 24 questions mentioned above, the complete National Identity ISSP module, and, finally, demographic variables.

Fieldwork methods:

The surveys are carried out through personal interview.

Sample size: The sample size finally achieved was 1505 interviews Response rates:

As was explained above in the section “Sample type”, the sampling method used by CEP involves the random replacement of those blocks/entities, dwellings or individuals, which for the reasons described above cannot in the end be contacted. Accordingly, keeping this in mind and using the method for counting the response rate established by the ISSP, we have that: A = 1,505 = Issue sample B = 0 = Ineligible A-B = 1,505 = C= Total eligible D =1,505= Sample achieved E = C-D= 0 Response rate = A/D = 1505/1505 = 100% Non-response rate = 0/1505 = 0.0% However, for the type of sampling used by CEP, these data are not real. CEP uses the following method for calculating the response rate. Let A = Number of original interviews achieved (not replaced) = 1,308 Let B = Number of non-original interviews achieved (replaced) = 197 Let C = Number of questionnaires received = A+B = Total sample = 1,505 B = D1 + E1 + F1 + D2 + E2 + G + F2 = 197 where :


D1 = Number of interviews replaced due rejection of household = 63 E1 = Number of interviews replaced due to no contact in house (empty house + nobody comes to the door) = 59 F1 = Number of interviews replaced for other household reasons = 11 D2 = Number of interviews replaced due to individual rejection = 28 E2 = Number of interviews replaced due to failure to make contact with selected individual = 24 G = Number of interviews replaced due to physical or psychological impediment of selected individual = 12 F2 = Number of interviews replaced for other individual reasons = 0 No-response rate = Number of non-original interviews achieved (replaced) / total number of interviews (replaced + original) = B / C = 197 / 1,505 =13,1%

Language:

Spanish

Weighted:

No

Weighting procedure: A weighting procedure is applied in order to correct for distortions in the representativeness of the sample as regards three variables of interest: Gender, Age, (grouped in five categories: 18-24 years, 25-34, 35-44, 45-54, 55 or older) and Urbanity (classification of place of residence as urban or rural). This makes it possible to obtain a sample with characteristics similar to those of the population. The weights are constructed by calculating the quotient between the expected distribution and that observed in the cross between Urbanity, Gender and Age. The expected distribution is obtained from the 2002 census data provided by the National Institute of Statistics. The result of the weighting slightly corrects for problems of under- and over-representation among certain specific groups of the population.

Known systematic properties:

The sample design described above has been used in the last 17 surveys and has given good results, so it can be stated that it does not have properties that might be causing some type of bias in the results.


Deviations from ISSP- questionnaire:

The questionnaire was translated as closely as possible from English to Spanish, maintaining the meaning and significance of each sentence and word. Some general comments: • In questions Q2, Q3, Q4, Q5, Q6, Q7, Q9, Q10, Q11, Q15 and

Q16 the code “can´t choose” was replaced wiyh “don´t know” (8) and “no answer”.(9)

• Due to problems detected in the pre-test, the question Q12 was finally translated as follows “From what country/countries or part(s) of the world did your direct ancestors, loke your parents, grand parents, or great grand parents, come?”.

• Q12 is an open-ended questions, thus the data submitted present a very wide range of codes, so researchers can group them as they want to.

• Q8 was not included in the final version of the questionnaire due to translation problems detected in the pretest.

• Regarding Q1: Due to problems detected in the pre-test this question was asked at the end of the National Identity Module.

DEMOGRAPHICS VARIABLES: • MARITAL : The code 3 is "ANULADO": In Chile we don't have

divorce • UNION : The code 2 was not included. • INCOME and RINCOME : In these questions, incomes were

measured like monthly net - income. • ISCO88 and SPISCO88 : The answers were coded with 4 digit

when it was possible. • RCH_PRTY : The codes are : VALUE LABELS RCH_PRTY 01 Independent National Alliance 02 Communist Party of Chile 03 Christian Democratic Party' 04 'Humanist Party 05 Democracy Party PPD 06 Radical Social Democratic 07 'Chilean Socialist Party 08 National Renewal Party 09 Independent Democratic Union'

10 Other party 11 No party, no preference 98 Don´t know 99 'NA'.

• URBRURAL: It was added new codes, 6 for “Urban, RP total urban” and 7 for “Rural, RP total rural”.

Publications: -



ISSP Characteristics of National Population: Chile (%) Gender Male 48,5 Female 51,5 Age Group 18 - 24 16,3 25 - 34 22,9 35 - 54 38,6 55 or older 22,2 Years of Schooling - Group 0 - 3 years 11,0 4 - 8 years 26,1 9 -12 years 38,9 13 or more years 24,0 Employment Status Employed (5.675.130) 92,6 Unemployed (453.070) 7,4 Total Labour force (6.128.190) 100,0 Not in Labour Force (5.419.180) 47,0 Sources: For Gender, age group and year of schooling: Census 2002 by National Institute of Statistics. Considers population 18 years of age or older. For employment status: Estimated by National Institute of Statistics. Oct-Dec 2003. Percentage “Not in labour force” is based on population 15 years of age or older.


Study Description: Czech Republic Study title:

National identity II, ISSP 2003

Fieldwork dates:

26.09.2003 – 19.10.2003


Klara Plecita, Institute of Sociology, Academy of Sciences of the Czech Republic

Sample type:

Three stage stratified probability sampling: 1) Stratified probability sampling of election districts 2) Probability sampling of households in selected district 3) Sampling of household members based on a Kish grid

Fieldwork institute:

SC&C

Fieldwork methods:

Face-to-face

Sample size: 1276 Response rates: 2441 A - Total issued (total sample) 52 B - Ineligible (address vacant, wrong ages,...) 2389 C - (= A - B) Total eligible (in scope sample) 1276 D - Total ISSP questionnaires received 1113 E - (= C - D; = F + G + H) Total non-response 617 F - Refusals (refusing to take part) 297 G - Non-contact (never contacted) 199 H – Other non-response Language:

Czech

Weighted: Yes

Weighting procedure: Total weight is constructed from: 1) design weights based on proportion of household sizes 2) post-stratification weights based on region, sex, education, age, economical activity, and size of the community. The weights were derived from data of the Czech Statistical Office. Method: raking based on loglinear modelling

Known systematic properties of the sample:

Due to sampling design the probability of selecting a respondent is 1 / No. of members of his/her household. Due to response differences sex and education significantly differ from the know population characteristics. The biases was corrected by weighting.

Deviations from ISSP questionnaire:

All the core ISSP module and background questions were included. Please see the technical report (cz03info.doc) for specifications of selected country specific backgroun variables.

Publications: not yet ISSP Characteristics of National Population: Czech Republic


ISSP 2003 data are weighted by the design weight (number of household members - see Weighting). Czech Republic

(December 2003) age 18 +; in %

ISSP 2003 in %

Difference in %

SEX Male 48,1 48,0 -0,1 Female 51,9 52,0 0,1 AGE 18 – 29 23,2 24,2 1,0 30 – 44 25,5 25,5 0,0 45 – 59 27,4 26,6 -0,8 60 and higher 23,9 23,7 -0,2 MARITAL STATUS single 23,3 23,8 0,5 married 56,6 58,0 1,4 divorced 10,8 9,7 -1,1 widowed 9,3 8,5 -0,8 Source of data for the Czech Republic: Statistical Yearbook of the Czech Republic 2003. Czech Republic

(July 2003) age 15 +; in %

ISSP 2003 in %

Difference in %

REGION Prague 11,6 10,6 -1,0 Central Bohemia 11,1 11,1 0,0 South Bohemia 6,1 6,2 0,1 Pilsen 5,4 5,6 0,2 Carlsbad 3 2,9 -0,1 Usti n/L 8 8,2 0,2 Liberec 4,2 4,3 0,1 Hradec Kralove 5,4 5,3 -0,1 Pardubice 4,9 5,1 0,2 Vysocina 5 5,3 0,3 South Moravia 11 11,0 0,0 Olomouc 6,2 6,3 0,1 Zlin 5,8 6,0 0,2 Moravia-Silesia 12,3 12,2 -0,1 Source of data for the Czech Republic: Statistical Yearbook of the Czech Republic 2003 Czech Republic

(December 2002) age 15+; in %

ISSP 2002 in %

Difference in %

EDUCATION Basic 22 18,5 -3,5 Secondary 68,2 70,2 2,0 University 9,5 8,9 -0,6 Without education 0,2 0,9 0,7 Not identified 0,1 1,4 1,3 Source of data for the Czech Republic: Statistical Yearbook of the Czech Republic 2002.


Study Description: Denmark Study title:

Danish National Identity II 2003 ISSP-module

Fieldwork dates:

The fieldwork was conducted from 10. October 2003 to 31. January 2004.


Aalborg University: Department of Economics, Politics and Public Administration. Fibigerstraede 1, 9220 DK-Aalborg Oe: Prof. Jørgen Goul Andersen (Director of the Danish ISSP programme) Associate Prof. Johannes Andersen Associate Prof. Lars Torpe Associate Prof. Henrik Lolle Associate Prof. Mette Tobiasen

Department of Social Studies and Organization Kroghstraede 5, DK-Aalborg Oe: Prof. Jens Christian Tonboe University of Aarhus: Department of Political Science DK-8000 Aarhus C: Prof. Emeritus Ole Borre Prof. Lise Togeby

University of Copenhagen: Associate prof. Hans Jørgen Nielsen Department of Political science Rosenborggade 15, DK-1130 Copenhagen K Associate prof. Bjarne Hjorth Andersen Department of Sociology Linnésgade 22 DK-1361 Copenhagen K. University of Southern Denmark: Assistant prof. Ulrik Kjær Department of Political Science Campusvej 55 DK-5230 Odense M. Senior Researcher & International Consultant Torben Fridberg The Danish National Institute of Social Research Herluf Trolles Grade 11 DK-1052 Copenhagen K

Sample type: Sampling-procedure: A representative sample (simple random


sample) was drawn from the Central Population Register (CPR) – which is a national register of all Danish citizens – from which respondent’s name and address were identified. Thus, the sampled unit was ’named individuals’. No stratification, clustering etc. was employed. The fieldwork method was postal survey (self-completion). One reminder was send out to respondents who had not returned the questionnaire. After this telephone interviews were attempted. If respondents were not reached, they were contacted at least five times before given up as “not meet”. In total 88,0 percent of the interviews where completed by mail and 12,0 percent were completed as telephone interviews (cf. MODE-variable). No substitutions were permitted at any stage of the selection process or during the fieldwork. The questions in the module were asked in the prescribed order.

Sample size:

Issued: 2000 Achieved: 1322

Response rates: The response rate is calculated to 66,4 percent. Full productive interviews / (Issued names – (respondents moved, no forwarding address + respondents deceased)): 1322/(2000-(6+2)) x 100= 66,4 percent. Description (N) Issued names 2000 Selected respondent moved, no forwarding address 6 Selected respondent too sick/incapacitated to participate 43 Selected respondent deceased 2 Personal refusal by selected respondent 430 Other type of unproductive reaction 197 Full productive interviews 1322

Language:

Danish

Danish study title:

”Om det at være Dansk”

Known systematic properties:

None known.

Fieldwork Institute: SFI SURVEY Herluf Trolles Gade 11 1052 Copenhagen K Denmark Tel: (+45) 3348 0900 E-mail: [email protected]

ISSP Characteristics of National Population: Denmark


Source no. 1 SEX

Male 49,47 % Female 50,53 % AGE (groups)

0-9 12,6 % 10-19 11,8 % 20-29 12,1 % 30-39 15,0 % 40-49 14,0 % 50-59 14,0 % 60-69 10,0 % 70-79 6,5 % 80-89 3,4 % 90- 0,6 %

YEARS OF SCHOOLING (groups)

Basic school and no answer

9 years 32,1 %

Gymnasium and basic vocational courses

12 years 43,1 %

Short more advanced studies

14 years 4,4 %

Medium length more advanced studies and bachelor

15 years 14,3 %

Long more advanced studies

17 years 6,1 %

EMPLOYMENT STATUS

Employed 50,92 % Unemployed 2,22 % Not in labor force 46,86 %

• Source to sex and age: Statistical Yearbook (Statistisk tiårsoversigt 2004 – tema

om arbejdsstyrken). August 2004, 45. årgang, Danmarks statistik. Page 29, table of agedistribution 1. January 2004.

• Source to years of schooling: Statistical Yearbook (Statistisk årbog 2004). June

2004, 108. årgang, Danmarks statistik. Table 98 page 105, highest completed education distributed after age and sex 2003. The years of schooling of the different educations are from the figure 1 on page 89.


• Source to employment status: Statistical Yearbook (Statistisk tiårsoversigt 2004 –

tema om arbejdsstyrken). August 2004, 45. årgang, Danmarks statistik. Page 47, table of the population distributed after sex and affiliation to the labour market 2003. It is based on the population as of 1. January and the labour affiliation the last week of November the year before.


Study Description: Finland Study title:

Suomi ja suomalaisuus (in Finnish) Finland och att vara finländare (in Swedish)

Fieldwork dates:

September 12th – November 28th, 2003 12th of Sep, 2003 questionnaires mailed 19th of Sep, 2003 thank you/reminder postcard sent to all

respondents 8th of Oct, 2003 dead line of answering the questionnaire 13th of Oct, 2003 replacement questionnaires sent to non-

respondents 5th of Nov, 2003 dead line of answering the replacement

questionnaire 28th of Nov, 2003 last questionnaire received


Raimo Blom, University of Tampere Harri Melin, University of Tampere

Sample type:

Target population: household population aged 15 to 74. Sampling design: a systematic random sample of individuals. Sampling frame: population register, sorting order: domicile code and birth date. Stratification: implicit geographic stratification. No clustering.

Fieldwork Institute: Statistics Finland, Helsinki

Fieldwork methods:

Postal (both direction), self-completion, paper and pencil

Sample size:

Issued: 2500

Response rates: A – Total issued 2500 B – Ineligible (address unknown or living abroad 6 C – Total eligible 2494 D – Total ISSP questionnaires received 1379 E – Total non-response 1115 F – Refusals 4 G – Non-contact - H – Other non-response 1111 Language:

Questionnaires in Finnish and Swedish. Information on language from the population register. Finnish (2 362; 94,5 % of total sample) and Swedish (138; 5,5 % of total sample)

Weighted:

Weight variables are included in the data-set. Basic data is unweighted.

Weighting procedure: The design of the survey was systematic sampling. In order to improve the efficiency of estimation and to reduce bias due to non-


response a calibration method was used for the creation of the weights. The following marginal distributions of the population were used: 1) gender (male, female), 2) age classes (15–24,25–34,…, 65–74), 3) NUTS3 regions with following modifications: the Greater Helsinki Area was dealt as a separate region, 4) type of community (urban - semi-urban - rural). There are two weights available for calculations: 1) a weight that expands the results to the population level (the sum of the weights is the size of the population) and 2) a weight that doesn't have the expansion property (the mean of the weights is 1 and the sum of the weights is the number of accepted responses, i.e. the size of the data). Both of the weights are based on the same calibration process, only the scale differs.


Sampling frame is updated and covers total population. A cross-sectional sample does not contain attrition by definition. After having used our standard sampling procedures for over 20 years we have not encountered any bias due to using systematic sampling. Design effect of the sampling procedure<=1 by definition.


Deviations from ISSP-questionnaire:

The questionnaire included ISSP module with necessary background variables. List of deviations and coding specifications compared to ISSP source questionnaire: 1) Age Age is computed from a variable for year of birth in the Finnish questionnaire (FQ). 2) Marital FQ asked separately a category for those living together (married or not married). They were recoded into same category. Added one code, 0 meaning other (FQ). 3) Wrktype Added one code, 8 meaning don’t know (FQ). 4) Spwrktyp Added one code, 8 meaning don’t know (FQ). 5) Hhcycle The FQ asked separately on how many persons in the household, how many of them are 7-17 years old and how many children under 7 years of age there are in the household. Hhcycle includes combined information from these variables. 6) SF_reg Added from register data describing the regions. FQ did not include question for this. 7) SF_size Added from register data describing the population of the municipality. FQ did not include question for this. 8) Weight and weight_2 As described in the study description, -[weight]is a weight that expands the results to the population level (the sum of the weights is the size of the population) and -[weight_2] is a weight that doesn't have the expansion property (the mean of the weights is 1 and the sum of the weights is the number of accepted responses, i.e. the size of the data). 9) SF_ethn Added from register data describing the ethnic identity (language code). FQ did not include question for this.


ISSP Characteristics of National Population: Finland Source no. 1 Source no. 2 Source no. 3 Source no. 4 31.12.2002 Statistics

Finland Ministry of Labour

SEX

Male 2 544 916 Female 2 661 379 AGE (groups)

- 14 927 009 15 - 29 969 877 30 - 39 695 102 40 - 49 769 644 50 - 64 1 046 099 65 – 74 440 655 75 - 357909


1 – 9 1 697 326 10 – 12 1 555 070 13 - 1 010 918 EMPLOYMENT STATUS

Employed

2 372 000

Unemployed

237 000 304 086

Not in labor force

1 308 000


Study Description: France Study title:

National Identity II

Fieldwork dates:

01-09-2003 to 01-12-2003


Michel Forse, Yannick Lemel

Sample type:

Equal probability sampling on the whole French European territory amongpersons older than fifteen years living in the household.

Fieldwork Institute: France-ISSP

Fieldwork methods:

Postal (both direction), self-completion, paper and pencil

Sample size:

Issued: 10000

Response rates: A – Total issued 10000 B – Ineligible (address unknown or living abroad 128 C – Total eligible 9872 D – Total ISSP questionnaires received 1669 E – Total non-response 8203 F – Refusals 8148 G – Non-contact - H – Other non-response 55 Language:

French

Weighted:

Yes

Weighting procedure: Post-stratification weighting by age and occupation


Under representation of youngest people because of responses rates differential


ISSP Characteristics of National Population: France Data Source: INSEE 2002 Labour force survey Random sample of the population being more than 17 years old; sample size is 136,780

Labour force survey 2001 Gender

Male 47.9% Female 52.1%

Age Group 18-29 years old 19.8% 30-39 years old 18.7% 40-49 years old 18.4% 50-59 years old 16.5% 60-69 years old 11.3%

70 years old and more 15.3% Levels of Education

University or College 18.5% High School completed 11.4% Secondary uncompleted 32.6%

Primary or None 37.5% Employment Status

Employed 52.4% Unemployed 5.1%

Not in labour force 42.5%


Study Description: Germany Study title:

ISSP 2003 Germany – National Identity II

Fieldwork dates:

2.3.2003-12.7.2003


Dr. Janet Harkness, Prof. Dr. Peter Ph. Mohler

Sample type:

Two stage random sample. Names and addresses from registers of inhabitants kept by municipalities. Adults of 18 and older living in private accommodation


TNS Infratest Sozialforschung (Germany)

Fieldwork methods:

Self-completion questionnaire, interviewer in attendance. Background variables were asked face-to-face (CAPI).

Sample size:

1287 (ISSP 2003 and ISSP 2004 were fielded in split together with ALLBUS, the German General Social Survey; number of ALLBUS 2004 interviews: 2946; number of ISSP 2004 interviews: 1332)

Response Rates:

N=3580 W=2450 E=1130 A – Total issued (total sample)

N=391 W=264 E=127 B – Ineligible (address vacant, wrong ages, etc.) N=3189 W=2186 E=1003 C – (=A−B) Total eligible (in scope sample) N=1287 W=850 E=437 D – Total ISSP interviews received N=1902 W=1336 E=566 E – = C - D; = F + G + H) Total non-response N=1339 W=924 E=415 F – Refusals (refusing to take part) N=216 W=153 E=63 G – Non-contact (never contacted) N=347 W=259 E=88 H – Other non-response Language: German Weighted: No Weighting procedure: Sample for eastern Germany deliberately over-samples the five

eastern federal states. If all of Germany is taken as the unit of analysis (rather than the eastern and western states) weighting is necessary. Weighting factor for West Germany: 1,232524; weighting factor for East Germany: 0,547722; (recoding of the country variable is necessary)


None for the total sample


ISSP substantive questionnaire: no deviations; Background variables: no deviations

Publications: ALLBUS Methods Report 2004 (forthcoming); ISSP Methods Report on the German Study (forthcoming)


ISSP Characteristics of National Population: Germany Gender3 Male 40356000Female 42175700Total 82531700 Age group4 Under 6 4519300 6-15 7642800 15-25 9621700 25-45 24461100 45-65 21426800 65 and above 14860000 total 82531700 Education5 Without general school-leaving certificate 1890000Still at school 2992000Secondary general school certificate 29391000Certificate of ten-grad school of general education in the former GDR 4807000Intermediate school-leaving certificate or equivalent 12732000"Fachhochschule" entrance qualification/university entrance qualification

14092000

No data on type of education 669000Respondents providing data on general school education 66574000

"Fachhochschule" degree6 2868000University degree 3758000Doctor's degree 853000Respondents providing data on vocational qualification7 65575000 Employment Status8 Employed 36172000 Unemployed9 4022000 Not in labour force10

42307000

3 Population 31.12.2003, updated 20th December 2004. 4 Population 2003, updated 3. August 2004. 5 Persons who provided data on their general school education; persons aged 51 years and above are not obliged to respond; results from Microcensus May 2003. 6 Degree from specialised college of higher education; including engineering qualification and college of public administration degree. 7 Other types of vocational education not listed here. 8 Results from Microcensus May 2003. 9 Unemployed persons are looking for a job and immediately available.


Region11 Baden-Württemberg 10693000Bayern 12423000Berlin 3388000Brandenburg 2575000Bremen 663000Hamburg 1734000Hessen 6089000Mecklenburg-Vorpommern 1732000Niedersachsen 7993000Nordrhein-Westfalen 18080000Rheinland-Pfalz 4059000Saarland 1061000Sachsen 4321000Sachsen-Anhalt 2523000Schleswig-Holstein 2823000Thüringen 2373000Total 82532000 Source: Statistisches Bundesamt, www.destatis.de (14.03.0505)

10 The inactive population includes persons not engaged in economic activity who are looking for a job but are not immediately available. 11 Population from 31.12.2003. Results of current population statistics.


Study Description: Great Britain Study title:

British Social Attitudes 2003

Fieldwork dates:

June to September 2003


National Centre for Social Research

Sample type:

Clustered random sample: addresses were selected with equal probability in a stratified clustered design. One person aged 18+ was interviewed per address.


National Centre for Social Research

Fieldwork methods:

The ISSP module is implemented as a self-completion questionnaire, completed by the respondent after the main face-to-face interview and collected by the interviewer.

Sample size:

873

Response rates: 2062 A - Total issued (total sample) 182 B - Ineligible (address vacant, wrong ages,...) 1880 C - (= A - B) Total eligible (in scope sample) 873 D - Total ISSP questionnaires received 1007 E - (= C - D; = F + G + H) Total non-response 569 F - Refusals (refusing to take part) 260 Face-to-face interview but no self-completion 79 G - Non-contact (never contacted) 99 H - Other non-response Language:

English

Weighted: Yes

Weighting procedure: Addresses were selected with equal probability (except in Scotland where allowance was made for MOI – see below) but only one person interviewed at each address. Therefore weights need to be applied to correct for different number of adults at each address. The weights are calculated by the following formula: weight = (number of households at the address * number of adults in selected household) / MOI where MOI is the Multiple Output Indicator (MOI>1 indicates more than one household at the address). Very large weights were capped and the weights were scaled to make the


weighted sample size equal to the unweighted sample size.


Sample excludes Scotland north of the Great Glen.


V64 to V74, Ethnic and TopBot are not available. The following variables were collected only if the respondent was not economically active/retired and the spouse partner was economically active/retired : SPISCO88, SpWrkTyp.

Publications: Park, A. et al (eds) (2004 forthcoming) British Social Attitudes: the 21st Report , in particular chpaters by Tilley at al. and by McLaren and Johnson


ISSP Characteristics of National Population: Great Britain Source no. 1 Source no. 2 Source no. 3 Source no. 4 2001 UK

Census BSA 2003

weightedBSA 2003 un-

weighted

SEX

Male 49% 46.7% 44.2% Female 51% 53.3% 55.8% Source no. 1 Source no. 2 Source no. 3 Source no. 4 National Statistics

2003 mid-year population estimates

BSA 2003 weighted

BSA 2003 un-weighted

AGE (groups)

18-24 11.3% 10.4% 7.9% 25-34 17.4% 16.9% 16.9% 35-44 19.7% 19.0% 19.8% 45-54 16.4% 19.1% 17.1% 55-64 14.6% 15.4% 15.1% 65+ 20.6% 19.1% 23.2%


Not available Source no. 1 Source no. 2 Source no. 3 Source no. 4 2001 UK

Census BSA 2003

weightedBSA 2003 un-

weighted

EMPLOYMENT STATUS

Employed

60.2% 56.5% 52.6%

Unemployed

4.5% 4.1% 4.4%

Not in labor force

36.3% 39.4% 43.0%


Study Description: Hungary Study title:

National Identity II.

Fieldwork dates:

2003.02.28 – 2003.03.12.


Antal Örkény, ELTE University Budapest

Sample type:

We used probability sample, which was selected in multiple stages with proportional stratification. In the first stage, localities were chosen. In the second stage, the respondents were chosen from the localities with simple random sampling. Creating the sample of localities: The regions formed the first strata, type of settlements were the second. The localities were chosen from these strata by random sampling. For every county at least 2 towns and 3 villages were selected. The 23 districts of Budapest formed a separate sampling unit. Creating the sample of individuals: After creating the locality sample, and deciding the required number of respondents for every locality, we used ‘pre-selected addresses’ sampling methods for selection of respondents. The number of respondents in the previously chosen localities was defined in accordance with the proportion of the population of the given strata – regions, and different types of localities (towns and villages) within the region. The names and addresses were obtained from the Central Registry and Electoral Office with the help of simple random sampling. To replace dropped-out addresses subsidiary addresses were chosen with ‘random walk’ method, based on the Leslie-Kish—key.


TÁRKI RT Social Research Centre

Fieldwork methods:

mode of interview: face to face

Sample size:

number of respondents in the final ISSP file:1021

Response rates: 1684 A - Total issued (total sample) 109 B - Ineligible (address vacant, wrong ages,...) 1575 C - (= A - B) Total eligible (in scope sample) 1021 D - Total ISSP questionnaires received 554 E - (= C - D; = F + G + H) Total non-response


282 F - Refusals (refusing to take part) 96 G - Non-contact (never contacted) 176 H - Other non-response Language:

Hungarian

Weighted: yes or no, whether a weighting factor exists in the data-set: YES

Weighting procedure: Exact description of the weighting procedure / algorithm In order to correct the sampling error we computed a weighting variable taking into account the type of residence (Budapest, other city, village), sex (male, female), age (18- 29, 30- 39, 40- 49, 50- 59, 60- 69, 70- x) and highest level of educational (primary , secondary, tertiary). The weight of each cases was computed as WEIGHT = (n/n’)* (N’/N), where N = respondent above the age of 18 in the sample of 2001 census, N’ = 1000, n = frequency of the population category in the census sub-sample the case belongs to, n’ = parallel frequency in the 2003 National Identity II module of TARKI.


Description of biases or other deviations of the sample Table. 1. Crosstabulation of year of birth, type of residence, highest educational level and sex in the sample of 1000 in compare with the sample of Population Census Data in Hungary of 2000. Table.1.a. Sex

Sample (unweighted data) Census

Male 44.2 48.8 Female 55.8 53.2 Total 100.0 100.0

Table 1.b. Type of residence Sample (unweighted

data) Census

Budapest 17.5 18.5 Other city 45.7 45.1 Village 36.7 36.4 Total 100.0 100.0

Table 1.c. Age categories Sample (unweighted

data) Census

18- 39 29.4 39.6 40- 59 36.7 35.5 60- x 34.0 24.9 Total 100.0 100.0

Table 1.d. Highest educational level


Sample (unweighted

data) Census

Primary level 58.8 60.8 Secondary level 23.3 27.2 Tertiary level 17.9 12.2 Total 100.0 100.0

Table 1.e. Sex by age by residence by education (see in apendix1)


None

Publications: Csepeli, Gy. Örkény A. Székelyi M. Poór J. 2004 Nemzeti identitás Magyarországon az ezredfordulón. (National identity in Hungary at the Millenium) In: Kolosi, T. Tóth, I. Gy. Vukovich gy (eds): Társadalmi Riport (Social Report) Budapest: TÁRKI

Appendix 1. Budapest Other city Village

Highest educational level sex age N Sample Census N Sample Census N Sample Census

18-39 43 4,2% 1,5% 30 3,0% 5,6% 4 0,40% 5,2%

40-59 58 5,7% 1,1% 44 4,3% 4,6% 7 0,7% 4,8% male

60-xx 48 4,7% 0,9% 40 3,9% 3,0% 12 1,2% 3,2%

18-39 29 2,8% 1,0% 33 3,2% 4,1% 6 0,6% 3,9%

40-59 44 4,3% 1,1% 37 3,6% 4,4% 7 0,7% 4,3%

Primary level

female

60-xx 64 6,3% 2,1% 69 6,8% 5,6% 23 2,3% 5,4%

18-39 4 0,4% 1,5% 19 1,9% 2,9% 8 0,80% 1,3%

40-59 12 1,2% 0,9% 17 1,7% 1,9% 6 0,6% 1,0% male

60-xx 1 0,0% 0,4% 9 0,9% 0,8% 5 0,5% 0,3%

18-39 16 1,6% 1,8% 33 3,2% 3,9% 15 1,50% 2,0%

40-59 20 1,9% 1,5% 24 2,4% 3,1% 16 1,6% 1,4%

Secondary level

female

60-xx 2 0,2% 0,8% 17 1,7% 1,0% 9 0,9% 0,3%

18-39 4 0,4% 0,6% 12 1,2% 1,0% 12 1,2% 0,3%

40-59 7 0,7% 0,8% 18 1,8% 1,3% 9 0,9% 0,4% male

60-xx 2 0,2% 0,6% 10 1,0% 0,6% 7 0,7% 0,1%

18-39 6 0,6% 0,8% 17 1,7% 1,3% 7 0,7% 0,5%

40-59 9 0,9% 0,8% 23 2,3% 1,3% 12 1,2% 0,4%

Tertiary level

female

60-xx 5 0,5% 0,3% 10 1,0% 0,3% 11 1,10% 0,1%


ISSP Characteristics of National Population: Hungary Source no. 1 (N) Source no. 2 (N) Source no. 1 (%) Source no. 2 (%)

Census 2001 (full population)

10,198,315

Census 2001 (only aged over 18)

8,111,555

Census 2001 all (total population)

100%

Census 2001 (only aged over 18)

100% SEX

Male 4,850,650 3,783,988 47.6 46.6 Female 5,347,665 4,327,567 52.4 53.4 AGE (groups)

0 - 17 2,086,760 - 20.5 - 18-29 1,873,078 1,873,078 18.4 23.1 30-39 1,309,591 1,309,591 12.8 16.1 40-49 1,533,309 1,533,309 15.0 18.9 50-59 1,314,018 1,314,018 12.9 16.2 60-69 1,025,606 1,025,606 10.0 12.6 70- 1,055,953 1,055,953 10.4 13.1


Primary (max 8 years) 7,101,283 5,014,523 69.6 61.8 Secondary (9-12 years)

2,162,996 2,162,996 21.2 26.7

Tertiary (13 years +) 934,036 934,036 9.2 11.5 EMPLOYMENT STATUS

(aged over 15) 8,479,163

Employed 3,690,269 3,696,928 36.2 43.6 Unemployed 416,210 417,762 4.1 4.9 Not in labor force 6,091,836 4,364,473 59.7 51.5


Study Description: Ireland Study title:

National Identity II 2003

Fieldwork dates:

1st Oct 2003 to 15th Nov 2003


Economic and Social Research Institute (ESRI)


Nic Ghiolla Phádraig, Máire; Watson, Iarfhlaith Social Science Research Center, University College, Dublin

Sample type:

The sample used in the ISSP survey was selected as a three-stage clustered probability sample of the adult population drawn from the electoral register.

First stage of sample selection

At the first stage of sample selection the national population on the register was grouped into clusters with a minimum population size of 1,000 adults. (These clusters were based on the most geographically disaggregated areal units available in the country – the so-called District Electoral Divisions (DEDs)). These clusters with a minimum population size of 1,000 persons constituted the primary sampling units (PSUs). The PSUs were selected with a probability proportionate to size (PPS). A total of 100 sampling points was selected.

Second stage of sample selection

At the second stage of selection the target household was selected from within each PSU on a systematic basis using a random start.

Third stage of sample selection to identify the respondent

At the third stage we selected the target person for interview within household from within the set of persons aged 18 years or more using a so-called 'next birthday' rule. The next birthday' rule is a simple randomisation procedure which provides a randomly selected respondent in much the same way as a Kish grid etc.

Fieldwork methods:

Face-to-face

Sample size:

1000

Known limitations:

Using the Electoral Register as the population frame means that very recently generated households which are not yet registered on the list have, by definition, a zero probability of selection. This is not a major issue and is, in fact, common to all population lists. The data were reweighted using a minimum information loss program which controls, inter alia, for age; gender; household size (number of adults in the household); marital status; level of educational attainment; region; principal economic status. This reweighting scheme addresses any such small bias as may emerge from frame effects.


Response rates:

Total number of starting or issued names / addresses (gross sample size) 1,648

addresses which could not be traced at all / selected respondents who could not be traced 48

addresses established as empty, demolished or containing no private dwellings 40

selected respondent too sick / incapacitated to participate selected respondent away during survey period selected respondent had inadequate understanding of language of survey no contact at selected address no contact with selected person personal refusal by selected respondent 252proxy refusal (on behalf of selected respondent) other refusal at selected address other type of unproductive reaction (please write in full details in the box below) [Most of these were 'soft' refusals where the respondent was not available for interview throughout the fieldwork period despite repeated call-back]

220

full productive interview (net sample size) 1,065partial productive interview 23

Language:

English

Weighted:

Yes

Weighting procedure: The data were re-weighted using a minimum information loss algorithm called Gross. This is used in almost all surveys carried out by the Economic and Social Research Institute in Dublin. It is similar to the Calmar software prepared by Insee and is based on reconciling distributions in the data to column marginals. The control variables used in reweighting the ISSP were: number of adult sin the household, gender, age cohort (8 categories), marital status, level of educational attainment, principal economic status, and planning region.


ISSP Characteristics of National Population: Ireland


Study Description: Israel Study title:


Fieldwork dates:

14th Dec 2003 to 29th Feb 2004


Noah Lewin-Epstein

Fieldwork Institute: B.I.and Lucille Cohen

Sample type:

First Stage: Division into strata (based of geographic location, community size and socioeconomic characteristics). Second Stage: Sampling of statistical areas (the smallest ecological unit) within strata. Third Stage: Sampling of starting point within statistical areas for the interviewing. Fourth Stage: Interviewing of specified number persons within statistical unit based on kishgrid.

Fieldwork methods:

Face-to-face

Sample size:

1066

Response rates: 1850 A - Total issued (total sample) 125 B - Ineligible (address vacant, wrong ages,...) 1725 C –(A - B) Total eligible 1066 D - Total ISSP questionnaires received 659 E - (=C – D; = F + G + H) Total non-response 452 F – Refusals 193 G - Non-contact (never contacted) 14 H - Other non-response Language:

Hebrew and Arabic

Weighted:

None

Context of ISSP questionnaire:

-


ISSP Characteristics of National Population: Israel Source no. 1 Source no. 2 Source no. 3 Source no. 4 SEX Total Jews only Arabs only

Male 49.34 49.1 50.8 Female 50.66 50.9 49.2 AGE (groups) Total Jews only Arabs only

0-19 37.0 33.9 50.3 20-24 8.2 8.0 8.8 25-29 8.1 7.9 8.5 30-34 7.0 6.7 7.3 35-44 11.8 11.7 11.3 45-54 11.1 12.3 6.5 55-64 7.0 7.8 4.0 65-74 5.5 6.3 2.2 75+ 4.2 5.4 1.1


Total Jews only Arabs only

0 3.2 2.5 6.2 1-8 11.0 8.6 22.6 9-12 47.2 46.8 49.0 13-15 21.3 23.0 13.2 16+ 17.2 19.0 8.9 EMPLOYMENT STATUS Total Jews only Arabs only

Employed 48.5 51.2 33.8 Unemployed 5.6 5.6 5.2 Not in labor force 45.9 43.2 61.0 Unemployment rate* 10.3 9.8 13.3 *unemployment/ total labor force


Study Description: Japan Study title:

ISSP National Identity

Fieldwork dates:

November 29 to December 7, 2003


ARAMAKI Hiroshi, KOBAYASHI Toshiyuki (NHK Broadcasting Culture Research Institute)

Sample type:

Two-stage stratified random sample of Japanese 16 or older First, urban and rural areas are divided into a number of groups (strata) based on similarities in local features and industrial structures. From each of those groups, streets and village-sections are again grouped together to form sampling units. From among such sampling units, 150 survey spots are selected at random. Then, from the Basic Resident Registers for these spots, 12 sample individuals aged 16 or over are selected according to a fixed random number.


Central Research Services, Inc.

Fieldwork methods:

Face-to-Face

Sample size: Issued 1.800, Achieved 1.102 Response rates: 1.800 A - Total issued (total sample) 103 B - Ineligible (address vacant, wrong ages,...)

18 respondents were not found 81 respondents moved somewhere else 4 respondents died

1.697 C - (= A - B) Total eligible (in scope sample) 1.102 D - Total ISSP questionnaires received 595 E - (= C - D; = F + G + H) Total non-response 272 F - Refusals (refusing to take part) 311 G - Non-contact (never contacted)

23 respondents had not lived at home for one year or more 46 respondents had not lived at home for 10~364 days 46 respondents had not lived at home for 9 days or less 48 respondents came home at midnight 134 respondents were not at home temporarily 14 respondents were ill in bed at home

12 H - Other non-response Language: Japanese Weighted: No Deviations from ISSP questionnaire:

SPISCO88 is not available.


Classification of Occupations (country specific) 1. Agricultural, Forestry or Fishery workers

Those who are engaged mainly in agriculture, forestry or fishery and family workers

2. The Self-Employed Those who operate shops, restaurants, plants, etc. each with 9 employees or less, as well as their family workers

3. Sales or Service Workers Employees or sales persons at shops, restaurants, department shores, etc. Employees at barber shops, beauty parlors, places of amusement, etc. Waiters and waitresses, housekeepers, transport conductors, station clerks, travel attendants Sales persons, canvassers, bill collectors

4. Industrial Workers (Skilled Workers) Locomotive-engine and motor-vehicle drivers Those engaged in such work as manufacturing, repairs, assembly, processing, printing, spinning, sewing, tailoring, packing and bailing Carpenters, joiners, plasterers, cabinetmakers (Manual/Unskilled Workers) Laborers in mining, construction, manufacturing and transport Street vendors, deliverymen, garbage collectors

5. Clerical and Technical workers Clerical and technical employees of business firm, public organizations and governmental agencies Section and division chiefs of business firms and organizations with 49 employees or less Those engaged in transportation, such as pilots and navigators Education-related personnel such as college lecturers, teachers and nursery governesses Medical-related persons such as pharmacists and nurses

6. Business operators or Managers Directors and managers with the post of section chief or above of government offices Directors and managers of business firms and organizations with 50 employees or more Those who operate business firms and organizations with 10 to 49 employees Directors of a kindergarten, headmasters, chief teachers, college presidents Captains and crew chief of ocean-going vessels and aircraft and of craft serving major domestic routes

7. Specialists, Free-lancers, etc. Medical doctors, lawyers, judges, certified public accountants, college (assistant) professors Artists (painters, performers, etc.) and masters of various arts Those related to professional sports, religious activities, politics Self-Defense force personnel, policemen


8. Housewives

Women engaged mainly in housework ×Women who live alone are put in category 10 (Jobless)

9. Students High school students Higher professional school students, junior college students, university students, graduate school students, special school students and miscellaneous school students ×Those who attend night high school or colleges, while working in the daytime, are put in categories 1 to 7

10. Jobless Those who are not now employed and those who live on pension, etc.

97. Refused 99. No Answer *Job-holders Total of those listed in the items numbered 1 to 7 *Employed persons Total of those mentioned in the items numbered 3, 4, 5 and 6


National Population Characteristics: Japan

Gender Source; the latest National Population Census conducted in 2000

Total population 16 years and more Total 125.386.737 100,0% Total 105.635.374 100,0%Female 64.045.210 51,1% Female 54.408.084 51,5%Male 61.341.527 48,9%

Male 51.227.290 48,5%

Age Group Source; the latest National Population Census conducted in 2000

Total population 16 years and more Total 125.386.737 100,0% Total 105.635.374 100,0% 0- 4 5.849.380 4,7% 16-17 2.978.891 2,8% 5-14 12.469.928 9,9% 18-24 11.292.627 10,7%15-24 15.703.573 12,5% 25-34 18.199.941 17,2%25-34 18.199.941 14,5% 35-44 15.655.391 14,8%35-44 15.655.391 12,5% 45-54 19.202.009 18,2%45-54 19.202.009 15,3% 55-64 16.380.461 15,5%55-64 16.380.461 13,1% 65-74 12.959.760 12,3%65-74 12.959.760 10,3% 75+ 8.966.294 8,5%75+ 8.966.294 7,2%

Schooling Group (15 years old and more, includes 1.157.354 foreigners) Source; the latest National Population Census conducted in 2000 Total 108.224.783 100,0%Compulsory completed (9-11years) 23.807.854 22,0%High school completed (12,13years) 45.024.501 41,6%Junior college completed (14,15years) 11.923.625 11,0%University or graduate school completed (16years and more) 14.651.266 13,5%Type of last school completed not reported 3.813.474 3,5%Student 8.845.172 8,2%None 158.891 0,1%


Marital Status (16 years old and more) Source; the latest National Population Census conducted in 2000 Total 105.635.374 100,0% Male 51.227.290 48,5%

-Never married 15.743.202 14,9% -Married 32.145.058 30,4%

-Widowed 1.391.347 1,3% -Divorced 1.401.888 1,3%

-Not reported 545.795 0,5% Female 54.408.084 51,5%

-Never married 12.330.416 11,7% -Married 32.067.911 30,4%

-Widowed 7.197.680 6,8% -Divorced 2.398.609 2,3%

-Not reported 413.468 0,4%

Employment Status (16age and more, includes 1.146.481 foreigners) Source; the latest National Population Census conducted in 2000 Total 106.781.855 100,0% Employed 62.956.553 59,0%

-Mostly worked 53.316.101 49,9% -Worked besides doing housework 7.845.763 7,3% -Worked besides attending school 971.916 0,9%

-Absent from work 822.773 0,8% Unemployed 3.114.584 2,9% Not in Labor force 38.973.659 36,5%

-Did housework 19.803.786 18,5% -Attending school 6.510.747 6,1%

-Others 12.659.126 11,9% Not reported 1.737.059 1,6%


Study Description: Latvia Study title:


Fieldwork dates:

10.12.2003 – 29.12.2003


Aivars Tabuns, University of Latvia; Ilze Koroleva, Institute of Philosophy and Sociology, University of Latvia

Sample type:

Multistage stratified random sample

Fieldwork methods:

Face-to-face interview

Context of ISSP- questionnaire:

ISSP module was fielded together with ISSP module “Family and changing gender roles” (topic A) and it included the 3rd topic of questions (C) on medical care.

Sample size:

N = 1000

Response rates: Real numbers N = 1805 A - Total issued (total sample) N = 96 B - Ineligible (address vacant, wrong ages,...) N = 1709 C –(A - B) Total eligible N = 1000 D - Total ISSP questionnaires received N = 709 E - (=C – D; = F + G) Total non-response N = 285 F – Refusals N = 391 G - Non-contact (never contacted) N = 33 H - Other non-response Language:

Latvian, Russian

Weighted: No


Known Systematic Properties in Sample:

No

Deviations from ISSP Questionnaire:

No

Publications: No


ISSP Characteristics of National Population: Latvia Source No.1 Central Statistical Bureau of Latvia (2003): Statistical Yearbook of Latvia 2003. Source No.2 Central Statistical Bureau of Latvia (2002): Results of the 2000 Population Census in Latvia. Collection of statistical data. Source No.3 (2003.) Macroeconomics of Latvia in figures 2003. Statistical yearbook. Source No.4 Labour force survey results on the 4th quarter 2002. Central Statistical Bureau of Latvia (http://www.csb.lv) Year 2000 2001 2002 2003

SEX Male 1094964

(46.1%) 1088853 (46.1%)

1080116 (46.0%)

1073057 (46.0%)

Female 1282419 (53.9%)

1275401 (53.9%)

1265652 (54.0%)

1258423 (54.0%)

AGE (groups) 0-14 428088 (17.8%) 409760 (17.3%) 390478 (16.6%) 372641 (16.0%) 15-29 504637 (21.2%) 504992 (21.3%) 507662 (21.7%) 512012 (22.0%) 30-44 511478 (21.6%) 506751 (21.4%) 504198 (21.5%) 500202 (21.3%) 45-64 584202 (24.6%) 582481 (24.7%) 579541 (24.7%) 577077 (24.8%)

SOURCE 1

65+ 353316 (14.8%) 360270 (15.3%) 363889 (15.5%) 369548 (15.9%) YEARS OF SCHOOLING (groups) (Education level of population aged 15 and over) Primary 103749 (8.4%) Basic 464665 (26.5%) Secondary 544221 (31%) Secondary specialised

355044 (20.2%)

SOURCE 2

Higher 244228 (13.9%) EMPLOYMENT STATUS Employed persons /economically active population; /all population

944000 91.0% 39.6%

965000 91.3% 40.8%

991000 91.7% 42.2%

SOURCE 3

Registered unemployed persons /economically active population

93283 9%

91642 8.7%

89735 8.3%

SOURCE 2* and 4**

Economically inactive /all population

851900* 43.4%

689300** 29.38%

http://www.csb.lv/


Study Description: New Zealand Study title:

National Identity II: New Zealand

Fieldwork dates:

11 September 2003 to 28 November 2003


Professor Philip Gendall, Department of Marketing, Massey University, Palmerston North, New Zealand

Sample type:

Systematic random sample from electoral rolls


Mail survey in four waves


Dedicated survey, with ISSP questions preceding non-ISSP questions and demographics.

Sample size:

2200

Response rates: 2200 A - Total issued (total sample) 313 B - Ineligible (address vacant, wrong ages,...) 1887 C –(A - B) Total eligible 1038 D - Total ISSP questionnaires received 849 E - (=C – D; = F + G) Total non-response 70 F – Refusals - G - Non-contact (never contacted) 779 H - Other non-response

Language:

English

Weighted: No


Weighting Procedure: None

Known Systematic Properties in Sample:


See notes

Publications: Sampling procedure: The sample was randomly selected from the 2002 New Zealand

electoral roll, which contains the names of all registered voters over the age of 18 years. The achieved sample is generally representative of the New Zealand population over 18 years of age, but people under 30 are underrepresented in the sample, while those over 30 are overrepresented, and the proportion of women is higher than in the population whereas the proportion of men is lower. The data have not been weighted to correct this biases. However, comparisons of unweighted survey results with results obtained from the sample weighted so that its age-sex distribution matched that of the New Zealand population over 18 (taken from the 2001 Census), showed only minor differences between estimates.

Survey administration procedure:

The questionnaire together with a covering letter was sent to the 2200 selected participants on 11 September 2003. A reminder letter and another questionnaire were mailed to participants whose questionnaire had not been returned by 25 September. A second reminder and another questionnaire were sent to those who had not returned their questionnaires by 16 October. A final reminder letter (without an accompanying questionnaire) was sent to all remaining non-respondents on 4 November. The survey was closed off on 28 November, 12 weeks after the initial mailing.


National Population Characteristics: New Zealand 1. Age and Sex distribution of population

Source: NZ Department of Statistics, 2001 Census, National Summary.

2. Education of population is based on “highest school qualification”. The New Zealand Census does not contain any questions about years of schooling and this information is not available from any government source. Source: NZ Department of Statistics, 2001 Census, National Summary.

3. Employment rate of population Source: NZ Department of Statistics, 2001 Census, National Summary.

Age Group by Sex For the Census Usually Resident Population Count, 1991 1996 and 2001

Census Year

1991 1996 2001 Age Group Male Female Total Male Female Total Male Female Total

0 – 4 Years 141,492 135,654 277,146 144,111 135,489 279,603 138,693 132,108 270,801 5 – 9 Years 128,703 122,475 251,178 147,720 140,574 288,291 147,363 138,837 286,203 10 – 14 Years 130,272 125,046 255,318 135,663 128,523 264,186 148,632 142,107 290,739 15 – 19 Years 145,005 139,986 284,988 133,572 129,405 262,977 134,949 130,332 265,281 20 – 24 Years 135,978 135,117 271,095 134,832 136,926 271,758 118,791 120,993 239,784 25 – 29 Years 133,086 139,266 272,352 132,453 140,850 273,303 118,008 128,892 246,903 30 – 34 Years 133,728 138,627 272,355 142,452 151,032 293,484 132,198 147,081 279,276 35 – 39 Years 121,941 124,926 246,867 139,293 145,923 285,216 142,680 154,785 297,462 40 – 44 Years 118,272 118,986 237,261 125,436 129,600 255,036 138,501 147,120 285,618 45 – 49 Years 93,672 93,156 186,825 120,249 120,939 241,191 123,528 128,256 251,787 50 – 54 Years 79,833 79,893 159,726 93,351 93,366 186,717 116,955 119,217 236,169 55 – 59 Years 69,525 68,610 138,135 78,783 79,821 158,604 90,180 92,082 182,262 60 – 64 Years 70,611 70,302 140,913 67,422 67,845 135,264 75,840 78,729 154,569 65 – 69 Years 60,207 66,549 126,756 65,184 67,788 132,972 62,478 65,433 127,914 70 – 74 Years 43,401 55,830 99,228 51,759 61,902 113,661 56,145 62,112 118,257 75 – 79 Years 30,987 45,093 76,077 33,561 48,726 82,290 40,740 53,766 94,506 80 – 84 Years 16,890 29,847 46,737 20,409 34,869 55,281 22,803 38,310 61,110 85 – 89 Years 6,861 15,189 22,050 8,385 18,645 27,030 10,818 22,866 33,684 90 – 94 Years 1,779 5,355 7,131 2,382 6,840 9,225 3,042 8,763 11,805 95 – 99 Years 273 1,218 1,488 393 1,557 1,950 561 2,193 2,751 100 Years and over 48 249 294 33 225 261 99 303 399

Total 1,662,555 1,711,371 3,373,926 1,777,461 1,840,839 3,618,303 1,823,007 1,914,273 3,737,277 Under 15 Years 400,467 383,175 783,642 427,500 404,583 832,080 434,688 413,055 847,740

15-64 Years 1,101,648 1,108,869 2,210,517 1,167,849 1,195,707 2,363,553 1,191,630 1,247,481 2,439,111 65 years and over 160,440 219,330 379,767 182,115 240,552 422,667 196,686 253,737 450,426

Median Age

30.6

32.0 31.3 32.2 33.6 33.0 34.0 35.6 34.8

All cells in this table have been randomly rounded to base 3.



Highest Qualification and Sex by Age Group For the Census Usually Resident Population Count

Aged 15 Years and over, 2001

Age Group Highest Qualification and Sex 15-19

Years 20-24 Years

25-29 Years

30-34 Years

35-39 Years

40-44 Years

45-49 Years

Male 37,782 18,339 18,723 26,124 29,253 29,457 27,498 Female 30,084 13,974 16,476 24,168 26,949 28,374 28,467 No Qualification Total 67,866 32,313 35,199 50,292 56,202 57,828 55,968 Male 29,529 14,106 15,285 17,463 18,738 17,583 15,927 Female 28,329 11,799 16,203 24,696 26,211 24,786 22,128 Fifth Form

Qualification Total 57,858 25,905 31,488 42,162 44,949 42,366 38,055 Male 22,596 14,391 14,139 13,578 14,265 12,396 10,038 Female 24,705 14,883 18,345 21,138 22,053 17,217 10,878 Sixth Form

Qualification Total 47,301 29,271 32,484 34,719 36,321 29,613 20,913 Male 18,138 22,203 9,828 5,349 4,431 3,888 3,726 Female 21,312 21,615 9, 087 4,707 4,041 2,952 2,514

Higher School Qualification Total 39,447 43,815 18,915 10,056 8,472 6,840 6,240

Male 147 84 63 84 84 96 81 Female 105 69 72 81 90 75 69 Other NZ School

Qualification Total 252 156 135 165 171 171 150 Male 2,805 4,104 4,395 5,985 7,395 7,170 6,699 Female 2,883 4,785 5,889 8,151 9,786 9,315 8,352 Overseas School

Qualification Total 5,691 8,889 10,287 14,136 17,181 16,485 15,048 Male 3,678 7,989 5,694 5,022 4,965 4,680 4,035 Female 4,245 9,888 8,526 7,050 6,966 6,453 4,779

Basic Vocational Qualification Total 7,923 17,874 14,220 12,075 11,931 11,133 8,814

Male 912 4,308 8,772 12,960 14,304 14,460 11,556 Female 861 2,742 4,011 4,947 6,063 6,150 4,464

Skilled Vocational Qualification

Total 1,776 7,047 12,780 17,904 20,370 20,610 16,020 Male 1,278 2,994 3,012 3,906 4,809 4,848 3,765 Female 2,145 4,752 3,417 2,901 2,577 2,097 1,467

Intermediate Vocational Qualification Total 3,426 7,746 6,426 6,804 7,389 6,945 5,232

Male 624 4,758 6,855 7,941 9,225 9,663 9,186 Female 1,053 6,663 10,977 13,746 15,525 18,189 16,866

Advanced Vocational Qualification Total 1,677 11,421 17,829 21,690 24,753 27,852 26,049

Male 114 9,615 13,425 13,164 13,296 12,294 10,290 Female 162 15,672 18,690 15,867 14,718 12,270 9,267

Bachelors Degree

Total 273 25,287 32,115 29,037 28,011 24,567 19,557 Male 24 2,061 4,605 5,871 6,888 7,026 6,543 Female 33 2,655 5,757 6,363 6,297 5,874 5,337 Higher Degree Total 57 4,719 10,359 12,237 13,182 12,900 11,880 Male 17,328 13,842 13,215 14,742 15,027 14,940 14,190 Female 14,406 11,502 11,445 13,257 13,509 13,365 13,668 Not Elsewhere Total 31,734 25,344 24,663 28,002 28,536 28,305 27,861 Male 134,949 118,794 118,011 132,198 142,680 138,501 123,528 Female 130,332 120,990 128,892 147,081 154,785 147,117 128,256 Total Total 265,284 239,784 246,900 279,276 297,462 285,618 251,784

(1) Includes Highest Qualification Unidentifiable and Not Stated.




Highest Qualification and Sex by Age Group For the Census Usually Resident Population Count


Age Group 50-54 Years

55-59 Years

60-64 Years

65-69 Years

70-74 Years

75-79 Years

80-84 Years

85 Years and over Total

32,412 28,332 25,152 21,273 19,404 12,765 6,477 4,197 337,188 35,502 30,693 27,657 23,583 21,789 17,220 12,033 12,075 349,038 67,914 59,025 52,806 44,856 41,190 29,982 18,510 16,272 686,223 13,008 9,105 6,936 5,439 4,155 3,117 2,067 1,173 173,631 17,940 12,687 9,405 6,492 4,998 4,209 3,390 2,346 215,628 30,951 21,792 16,344 11,934 9,153 7,326 5,457 3,522 389,259 6,234 4,131 3,390 3,069 3,177 3,189 2,058 1,233 127,881 6,147 4,083 3,216 2,598 2,844 3,231 2,349 1,908 155,604

12,381 8,214 6,603 5,667 6,021 6,420 4,410 3,144 283,482 3,411 2,181 1,530 1,254 1,263 1,077 696 450 79,425 2,226 1,473 1,353 1,176 1,458 1,626 1,122 903 77,553 5,634 3,657 2,883 2,433 2,718 2,706 1,818 1,353 156,981

81 87 105 96 60 60 30 30 1,191 96 84 105 90 93 123 63 69 1,287

177 174 207 186 153 183 93 99 2,478 7,218 6,210 6,390 5,877 4,887 2,901 1,302 714 74,061 8,205 7,029 6,852 5,979 4,920 3,966 2,091 1,434 89,637

15,423 13,239 13,245 11,859 9,807 6,867 3,387 2,148 163,695 3,408 2,364 1,821 1,287 915 525 246 147 46,776 3,954 2,502 1,821 1,128 846 633 369 255 59,415 7,365 4,866 3,642 2,412 1,761 1,155 615 402 106,188 9,897 7,323 5,862 4,008 2,964 1,650 705 366 100,044 3,228 1,788 1,212 771 579 384 240 144 37,587

13,122 9,111 7,074 4,776 3,543 2,034 942 510 137,628 3,321 2,190 1,398 918 678 345 141 51 33,642 999 438 204 90 63 42 27 24 21,249

4,317 2,625 1,602 1,008 741 387 165 75 54,891 8,052 5,433 3,870 2,844 2,310 1,614 654 300 73,326

14,850 10,776 8,643 6,621 5,157 3,528 1,929 1,335 135,855 22,899 16,209 12,513 9,468 7,467 5,139 2,583 1,632 209,181 8,634 5,310 3,729 2,532 2,349 1,728 867 531 97,881 6,306 3,372 2,109 1,365 999 633 342 276 102,051

14,940 8,682 5,841 3,897 3,348 2,361 1,209 804 199,932 6,096 3,909 2,379 1,563 1,266 936 519 300 49,983 4,179 2,328 1,311 666 558 396 228 186 42,168

10,272 6,234 3,690 2,229 1,824 1,335 750 486 92,154 15,186 13,602 13,275 12,318 12,720 10,839 7,041 5,025 193,287 15,582 14,832 14,838 14,871 17,811 17,775 14,127 13,161 214,155 30,771 28,431 28,116 27,189 30,528 28,611 21,168 18,186 407,439

116,952

90,180

75,840

62,481

56,148

40,740

22,803

14,517

1,388,319

119,217 92,082 78,726 65,433 62,112 53,766 38,307 34,122 1,501,221 236,169 182,262 154,569 127,914 118,257 94,503 61,110 48,636 2,889,534



Work and Labour Force Status and Sex by Age Group For the Census Usually Resident Population Count


Age Group Work and Labour Force Status and Sex 15-19

Years 20-24 Years

25-29 Years

30-34 Years

35-39 Years

40-44 Years

Labour Force Employed Full-time Male 31,023 67,935 85,491 101,199 111,426 109,284 Female 18,210 51,819 63,876 61,839 63,201 70,008 Total 49,230 119,754 149,367 163,041 174,630 179,289 Employed Part-time Male 30,699 12,774 6,633 6,189 6,654 6,615 Female 37,827 20,754 19,047 30,720 40,341 37,776 Total 68,526 33,531 25,683 36,912 46,995 44,391 Total Employed Male 61,719 80,712 92,124 107,391 118,083 115,899 Female 56,037 72,573 82,926 92,562 103,542 107,781 Total 117,756 153,285 175,050 199,953 221,625 223,683 Unemployed Male 15,897 11,793 8,067 7,239 6,618 5,706 Female 17,271 11,442 8,307 7,854 7,575 6,240 Total 33,168 23,238 16,374 15,093 14,196 11,946 Total Labour Force Male 77,619 92,505 100,191 114,630 124,698 121,605 Female 73,311 84,015 91,233 100,416 111,120 114,021 Total 150,924 176,520 191,427 215,046 235,821 235,629 Not in the Labour Force Male 54,015 22,302 13,680 13,062 13,518 12,576 Female 53,877 33,081 33,432 41,886 38,919 28,557 Total 107,892 55,383 47,115 54,948 52,437 41,133 Work and Labour Force Status Male 3,318 3,984 4,137 4,506 4,461 4,317 Female 3,144 3,894 4,224 4,779 4,746 4,542 Total 6,465 7,881 8,361 9,285 9,207 8,862 Total Male 134,949 118,794 118,011 132,195 142,680 138,501 Female 130,332 120,990 128,892 147,081 154,785 147,117 Total 265,284 239,784 246,900 279,279 297,462 285,618 Labour Force Participation Rate Male 59.0 80.6 88.0 89.8 90.2 90.6 Female 57.6 71.7 73.2 70.6 74.1 80.0 Total 58.3 76.1 80.2 79.6 81.8 85.1 Unemployment Rate Male 20.5 12.7 8.1 6.3 5.3 4.7 Female 23.6 13.6 9.1 7.8 6.8 5.5 Total 22.0 13.2 8.6 7.0 6.0 5.1




Work and Labour Force Status and Sex by Age Group For the Census Usually Resident Population Count


Age Group 45-49 Years

50-54 Years

55-59 Years

60-64 Years

65 Years and over

Total

97,335 89,655 62,406 38,070 17,916 811,740 68,475 60,534 35,949 16,959 5,508 516,378

165,813 150,189 98,355 55,026 23,424 1,328,118

6,132 6,561 6,531 7,398 15,030 111,219 29,025 26,283 20,592 14,082 11,478 287,934 35,160 32,847 27,123 21,477 26,508 399,153

103,467 96,216 68,937 45,468 32,946 922,959 97,503 86,817 56,541 31,041 16,989 804,312

200,973 183,036 125,478 76,506 49,935 1,727,271

4,512 4,053 3,036 2,283 537 69,738 4,566 3,459 2,109 1,062 276 70,170 9,081 7,512 5,145 3,342 813 139,908

107,979 100,269 71,970 47,751 33,483 922,697 102,072 90,279 58,650 32,100 17,265 874,479 210,051 190,545 130,623 79,848 50,745 1,867,179

11,649 12,954 15,411 25,689 157,509 352,371 22,203 25,251 30,555 44,151 229,632 581,541 33,852 38,205 45,969 69,840 387,144 933,909

3,900 3,732 2,796 2,403 5,694 43,251 3,981 3,687 2,877 2,478 6,843 45,198 7,884 7,419 5,670 4,881 12,534 88,449

123,528 116,952 90,180 75,840 196,686 1,388,316 128,526 119,217 92,082 78,729 253,737 1,501,221 251,784 236,172 182,262 154,569 450,423 2,889,537

90.3 88.6 82.4 65.0 17.5 73.8 82.1 78.1 65.7 42.1 7.0 60.1 86.1 83.3 74.0 53.3 11.6 66.7

4.2 4.0 4.2 4.8 1.6 7.0 4.5 3.8 3.6 3.3 1.6 8.0 4.3 3.9 3.9 4.2 1.6 7.5



Study Description: Norway Study title:

National Identity

Fieldwork dates:

8 October – 5 December 2003


Knut Kalgraff Skjåk, NSD Oddbjørn Knutsen, Department of Political Science, University of Oslo Olav Aagedal, Diaconia College Centre Ole Gunnar Winsnes and Paal Ketil Botvar, Centre for Church Research

Sample type:

The sample was a simple random sample of individuals from the Central Register of Persons, aged 18-79 years.


TNS Gallup

Fieldwork methods:

The survey was conducted as a mail survey. The fieldwork included one reminder and two follow-ups with questionnaires

Sample size:

1469

Response rates: 2500 A - Total issued (total sample) 50 B - Ineligible (address vacant, wrong ages,...) 2450 C - (= A - B) Total eligible (in scope sample) 1469 D - Total ISSP questionnaires received 981 E - (= C - D; = F + G + H) Total non-response 82 F - Refusals (refusing to take part) 862 G - Non-contact (never contacted) 37 H - Other non-response Language:

Norwegian

Weighted: No

Weighting procedure:


Net sample: Women in paid work slightly over-represented


Spouse's work status (SPWRKST) missing

Publications:


National Population Characteristics: Norway Sex and age, %: Population

18-79 years January 1, 2003. Central Register

of Persons12

Net sample Norwegian

Survey, ISSP 2003

Female 50.0 52.6 18 – 24 5.7 5.1 25 – 34 9.9 10.6 35 – 44 10.0 12.1 45 - 54 9.2 11.3 55 - 64 7.4 7.9 65 - 79 7.8 5.7

Male 50.0 47.4 18 - 24 5.9 4.8 25 – 34 10.2 8.3 35 – 44 10.4 10.5 45 – 54 9.5 8.5 55 – 64 7.5 8.0 65 – 79 6.5 7.3 Region,%: Central east counties 2 & 3 22.5 21.6 East counties 1, 4 - 8 27.7 28.6 South counties 9 - 10 5.7 5.3 West counties 11 - 15 25.3 26.0 Middle counties 16 & 17 8.6 9.5 North counties 18 - 20 10.1 9.1 N 3 271 478 1 469

12 Source: Statistics Norway


Labour force status,%:13 Labour Force

Surveys 4. quarter 2003, 18-74 years14

Net sample Norwegian Survey

ISSP 2003, 18-74 years

Female Male Female Male Employed (>= 1 hr a week) 69.2 74.5 79.4 78.5 In school (pupil/student) 5.4 4.5 3.3 3.3 Retired 8.0 8.8 8.2 11.0 Social welfare, perm. disabled 8.8 7.0 5.8 4.7 Home working 4.8 0.1 2.0 0.3 Unemployed 2.7 3.6 1.2 1.5 Other 1.1 1.5 0.0 0.6 Missing 0.3 0.2 Education,%: Primary school 16.8 16.1 18.7 13.7 Secondary 52.7 54.7 41.7 46.3 University/college, >= 1 year 30.1 28.9 38.1 35.9 Missing 0.3 0.2 0.8 1.4 N 10 284 10 453 665 754

13 Deviation from WRKST variable in dataset, due to different recodings 14 Source: Statistics Norway


Study Description: Philippines Study title:

ISSP 2003 Module on National Identity in the Philippines

Fieldwork dates:

March 10 – 25, 2003

Fieldwork:

Location: The ISSP 2003 Module on Identity survey covers the entire Philippines and had four major study areas: National Capital Region (NCR), Balance Luzon (outside NCR), Visayas and Mindanao.

Timetable:

National Capital Region - March 10 - 25, 2003 Balance Luzon - March 14 - 25, 2003 Visayas - March 15 - 23, 2003 Mindanao - March 15 - 24, 2003

Respondents: The gathered data through on voting-age through face-to-face interviews

of voting-age adults (18 years old and above). It asked a host of questions about political, social and economic issues, some undertaken as regular indicators monitored over time and others reflective of current concerns as well as specific personal information. It also obtained information and background characteristics about the household, the household head and family members.

Sampling Method:

Sampling Sizes and Error Margins. An indicator of data quality used is the standard error of the estimate, on which the margin for sampling error is based. As survey statistics are mostly proportions, the key measure of data precision is the standard error of a proportion taken from a sample. It is computed as follows:

Where Z, at 95% confidence level is 1.96; p is the sample proportion estimate and n is the sample size. The overall sample size of 1,200 voting-age adults for each of the questionnaires gives a maximum error margin of ±2.83% at the 95% confidence level, assuming a simple random sampling design. The sampling error is at its highest when the true proportion being estimated is close to 50%. The following approximate 95%-confidence margins for sampling error should be made when aggregating data at various levels:

Sample Size Error margin Philippines 1200 ±3% National Capital Region 300 ±6% Balance Luzon 300 ±6%

± Z * p(1-p)/n


Visayas 300 ±6% Mindanao 300 ±6%

However, somewhat higher error margins should be expected since multi-stage cluster sampling was used; this design-effect is not readily measurable through established statistical software. Sampling scheme. The Philippines were divided into four study areas: National Capital Region(NCR), Balance Luzon, Visayas, and Mindanao. The sample size for each of the four study areas was 300 voting-age adults. Multi-stage probability sampling was used in the selection of sample spots. The allocation of sample units in each stage was as follows:

Sample

Prov. Sample Mun.

Spots

Probability Respondents

National Capital Region - 17 60 300 Balance. Luzon 10 15 60 300

Visayas 5 15 60 300 Mindanao 5 15 60 300

20 62 240 1200 For the National Capital Region

Stage 1. Selection of sample Precincts For NCR’s first stage, 60 precincts were distributed among the 17 NCR cities and municipalities in such a way that each city/municipality was assigned a number of precincts that was roughly proportional to its population size. An additional provision was that each municipality must receive at least one precinct. Precincts were then selected at random from within each municipality with probability proportional to population size. Stage 2. Selection of Sample Households In each sample precinct, interval sampling was used to draw 5 sample households: A starting street corner in the precinct map was drawn at random. The first sample household was selected randomly from the households nearest to the starting street corner. Subsequent sample households were chosen using a fixed interval of 6 households in between the sample ones; i.e. every 7th household was sampled. Stage 3. Selection of Sample Adult For the third stage, in each selected household, a respondent was randomly chosen among the household members who were 18 years of age and older, using a probability selection table. In selecting the probability respondent in a household, only male family members were


pre-listed in the probability selection table of odd-numbered questionnaires; only female family members were pre-listed for even-numbered questionnaires; In case where there was no qualified probability respondent of a given gender, the interval sampling of households would continue until five sample respondents were identified. For the rest of the Philippines Stage 1. Allocation and selection of sample provinces Balance Luzon was further divided into 5 regions: CAR + Region II, Region I, Region III, Region IV and Region V; Visayas into 3 regions: Region VI, Region VII and Region VIII; and Mindanao into 5 regions: Region IX, Region X + CARAGA, Region XI, Region XII and ARMM. Using probability proportional to population size (PPS) of the region, the allocation of 10 provinces in Luzon, and 5 each in Visayas and Mindanao were as follows:

Luzon Visayas Mindanao CAR/REG II 1 Region VI 2 Region IX 1 Region I 1 Region VII 1 RegX+CARAGA 1 Region III 2 Region VIII 1 Region XI 1 Region IV 3 Region XII 1 Region V 1 ARMM 1 Non-quota 2 1 0 Total 10 5 5

The non-quota provinces were selected without replacement using probability proportional to their remainders. The remainders are the fractions derived when the proportion of the regions (based on their respective study area) are multiplied by 10 for Luzon, and 5 each for Visayas and Mindanao. For instance, if 1.45 is obtained for Region I, then 1 province is assigned to this region and the remaining fraction of 0.45 is included for the allocation of the non-quota province. Given the quota for each region, sample provinces were then selected by PPS, without replacement. An additional provision is that each region must receive at least one province. Stage 2. Allocation and selection of sample municipalities Within each study area, 15 municipalities were allocated among the sample provinces. 15 were multiplied by the proportion of the provinces. The resulting integers became the number of municipalities in that province. If there were remaining municipalities to be allocated, they were distributed using probability proportional to the remainders. Sample municipalities were then selected from within each sample province with probability proportional to population size, without


replacement. An additional provision was that each province must receive at least one municipality. Stage 3. Allocation and selection of sample spots Once the sample municipalities were selected, 60 spots for each of the major areas were allocated among the sample municipalities. Using the quota set for spots in each region, the spots were distributed in such a way that each municipality was assigned a number of spots roughly proportional to its population size.

Luzon Visayas Mindanao CAR/REG II 8 Region VI 25 Region IX 10 Region I 8 Region VII 21 RegX+CARAGA 16 Region III 14 Region VIII 14 Region XI 17 Region IV 21 Region XII 9 Region V 9 ARMM 8 Total 60 60 60

If the chosen sample municipality/city is 100% urban based on the 1990 (latest) NSO classification, then sample precincts were systematically drawn from this city/municipality. Otherwise, sample barangays within each sample municipality were selected using simple random sampling without replacement. If based on the National Statistics Office categorization, the chosen sample municipality/city was 100% urban in 1990 (latest), then sample precincts were systematically drawn from this municipality/city. Otherwise, sample barangays within each sample municipality were selected with equal probabilities. In the effort to update the urban-rural classification of barangays, the survey adopted a classification scheme slightly different from the official NSO definition. The interviewers were instructed to ascertain whether the barangay has the following: A. Street patterns, i.e. network of streets in either parallel or right angle orientation B. At least 6 establishments (commercial, manufacturing, recreational and/or personal services) C. At least three of the following:

1. Town/Barangay Hall/Church/Chapel 2. Public Plaza/Park/Cemetery 3. Market Place 4. Public building like school, hospital, health centre or library

If the barangay has all categories as A, B or C, then the barangay were classified as urban. Otherwise, the barangay was classified as rural.

Stage 4. Selection of Sample Households


For the fourth stage, within each sample spot, five households were established by systematic sampling. In sample (urban) precincts, a random corner was identified; a random start generated; and the interval was seven. In ascertained urban barangays (with no precinct maps), the designated starting point was the same as in rural barangays – it was a school, the barangay captain’s house, a church/chapel or a barangay/municipal hall. The sampling interval for urban barangays was seven, while for rural barangays it was two. Stage 5. Selection of Sample Respondents For the fifth and final stage, as discussed earlier, a respondent was randomly chosen from among the voting-age adults in each selected household using a probability respondent selection table.

Research Methodology:

a. Preparation

1. Questionnaire The definitive language-version of the questionnaire, Tagalog, was translated into English, Cebuano, Ilonggo, Ilocano and Bicolano by language experts. Then the language translation was translated back to Tagalog by another set of experts to make sure that the messages were conveyed accurately.

2. Pre-Testing and finalizing the questionnaire

SWS pre-tested the questionnaire on 10 voting-age adults from different socio-economic classes in order to:

• Determine the time length of the interview • Improve the wording of the questions, if necessary • Eliminate unnecessary questions or add new items, as the

case may be • Test question sequence and identify biases • Correct and improve translation • Change open-ended questions into multiple choice

questions • Find out which items are conceptually vague • Check accuracy and adequacy of the questionnaire

instructions • Determine whether the focus of the question is clear • Identify interviewer’s recording difficulties

3. Training (a) Training was conducted in 3 central locations: Manila, Iloilo city

and Cebu City. The interviewers needed to cover Luzon were trained in Manila. They implemented the Tagalog and Ilocano versions of the questionnaire. Those trained in Iloilo covered Ilonggo-speaking regions, while those in Cebu City covered all of Cebuano-speaking areas (Central & Eastern Visayas and Mindanao).


(b) Training time – The minimum training time for group supervisors and interviewers was 3 days prior to field implementation.

(c) Training Activities – These mainly consisted of: One or two day’s office training to learn the basics of the project. Mock interviews with co-workers to get accustomed to the flow of interviewing and questionnaire format. Practice interviews with a supervisor until the interviewer could be left on her own.

(d) Evaluation of interviewer’s work – The interviewer was left to interview on her own only after she has conducted 3 successive interviews without committing any error in interviewing and recording.

b. Field Work

1. Supervision Supervisors reporting to the field manager monitored the study full-time. They observed interviewers, (at least 10% of total interviewers were observed by supervisors), followed-up and did surprise checks on the field interviewers. They also ensured that field logistics were received promptly and administered properly.

2. Spot-checking

Spot-checking was done at various stages of fieldwork. The first one took place after about 30% of interviews were completed. The second spot-checking was conducted after 60% completion and the last one, immediately after 90% completion of interviewing. During spot-checking, at least 20% of the unsupervised interviews were reinterviewed/backchecked.

c. Number of calls and Substitution

A respondent not contacted during the first attempt was visited for a second time. If the respondent remained unavailable, a substitute who possessed the same qualities (in terms of gender, age bracket, and socio-economic class) as the original respondent was interviewed. The substitute respondent was taken from another household beyond the covered intervals in the sample precinct/barangay.

d. Field Editing

(a). After each interview, the interviewer was asked to go over her own work and check for consistency.

(b). All accomplished interview sheets were submitted to the assigned group supervisor who, in turn, edited every interview.

(c). Data Processing (1) An office editor conducted a final consistency check on all

interviews prior to coding. (2) Interview sheets were edited/checked twice by office

editors before the information was encoded into diskettes. (3) A data entry computer program verified and checked the

consistency of the encoded data before data tables were generated.


Weighting procedure: To yield representative figures at the national level, census-based

population weights were applied to the survey data. The weight projection was computed by dividing the projected population in the area by the sample size of the same area. Appropriate projected factors were applied so that original population proportion were reflected in the data tables using this formula: Population Projection factors = ----------------------- (Weight) No. of Interview For questions answered by the sample voting-age adults, the following projection factors were used:

2002 NSO Projected population Aged 18

and above

Total Sample

size

Projection factor for 1 Probability Respondent

(000)

Projection factor for 2 Probability Respondent

(000) NCR 6,926,430 300 23.0881014336 11.5440507168

Balance Luzon

19,631,544 300 65.4384809797 32.7192404898

Visayas 9,281,157 300 30.9371910397 15.4685955199

Mindanao 10,634,787 300 35.4492909369 17.7246454685

TOTAL 46,473,919 1,200

The SPSS version of the data file is already weighted according to the above projection factors. As the data are weighted, the total number of cases that appear is 46,474. This figure is in thousands, i.e., 46,473,919 persons representing NSO’s projected number of adults (18 years old and above) for year 2002 based on the 1995 Census. Researchers who are defining data using the ASCII files should apply these projection factors.


ISSP Characteristics of National Population: Philippines I. Gender and Age DEMOGRAPHY (Source: Census of Population and Housing)

DATA REFERENCE PERIOD Both Sexes Male Female INDICATOR

Year Number Percent Number Percent Number Percent Total

Population 76,504,077 100.00 38,524,267 100.00 37,979,810 100.00

0 – 4 years 9,669,502 12.64 4,951,932 12.85 4,717,570 12.42 5 – 9 years 9,694,781 12.67 4,962,013 12.88 4,732,768 12,46

10 – 14 years 8,949,614 11.70 4,541,197 11.79 4,408,417 11.61 15 – 19 years 8,017,298 10.48 4,017,830 10.43 3,999,468 10.53 20 – 24 years 7,069,403 9.24 3,522,518 9.14 3,546,885 9.34 25 – 29 years 6,071,089 7.94 3,053,616 7.93 3,017,473 7.94 30 – 34 years 5,546,294 7.25 2,804,522 7.28 2,741,772 7.22 35 – 39 years 4,901,023 6.41 2,496,821 6.48 2,404,202 6.33 40 – 44 years 4,163,494 5.44 2,120,314 5.50 2,043,180 5.38 45 – 49 years 3,330,054 4.35 1,696,712 4.40 1,633,342 4.30 50 – 54 years 2,622,316 3.43 1,318,632 3.42 1,303,684 3.43 55 – 59 years 1,903,649 2.49 943,133 2.45 960,516 2.53 60 – 64 years 1,633,150 2.13 786,137 2.04 847,013 2.23 65 – 69 years 1,138,843 1.49 533,469 1.38 605,374 1.59 70 – 74 years 797,970 1.04 361,614 0.94 436,356 1.15 75 – 79 years 505,356 0.66 218,622 0.57 286,734 0.75 80 and over

May 2000

490,241 0.64 195,185 0.51 295,056 0.78 Source: http://www.census.gov.ph/data/quickstat/qsgender.html (as of March 31, 2003)

http://www.census.gov.ph/data/quickstat/qsgender.html


II. Employment Status LABOR AND EMPLOYMENT (Source: Labour Force Survey)

DATA REFERENCE PERIOD Both Sexes Male Female INDICATOR

Year Number Percent Number Percent Number Percent

Household Population 15 Years Old and Over 50,841 100.00 25,387 100.00 25,454 100.00

Labour Force Employed – Employed persons include all those who, during the reference period are 15 years and

over as of their last birthday are reported

either at work or with a job but not at work.

(In thousands)

30,252 59.50 18,439 72.63 11,812 46.41

Unemployed – it includes all those who, during the reference period are 15 years old and over as of their last birthday who

have no job/business and actively looking for work.

(In thousands)

3,423 6.73 2,076 8.18 1,347 5.29

Not in Labour Force (In thousands)

Oct 2002

17,166 33.76 4,872 19.19 12,295 48.30

Source: http://www.census.gov.ph/data/quickstat/qsgender.html (as of March 31, 2003) III. Educational Attainment

Educational Attainment* Number Percent Household Population 5 Years Old or Over 59,071,714 100.00 No Grade Completed 4,394,719 7.44 Pre-school 1,931,882 3.27 Elementary 25,620,407 43.37

1st – 4th Grade 12,641,243 21.40 5th – 7th Grade 12,979,164 21.97

High School 16,448,857 27.85 Undergraduate 8,409,260 14.24

Graduate 8,039,597 13.61 Post-secondary 1,340,813 2.27

Undergraduate 263,303 0.45 Graduate 1,077,510 1.82

College Undergraduate 4,071,236 6.89 Academic Degree Holder 4,380,472 7.42 Post-Baccalaureate 114,839 0.19 Not Stated 768,489 1.30

*Source: National Statistics Office 1995 Census of Population, Report No.2, Socio-Economic and Demographic Characteristics

http://www.census.gov.ph/data/quickstat/qsgender.html


Study Description: Poland Study title:

Polish General Social Survey/ISSP, 2003

Fieldwork dates:

January, 2005


Bogdan Cichomski, Institute for Social Studies, Warsaw University (ISS UW) and Warsaw School of Social Psychology (SWPS)

Sample type:

Multi-stage area probability sample. The sample was drawn from The Common Electronic Population Evidence System - PESEL (a governmental agency). Sampling procedure consists of the three stages: 1. In each of the 16 voivodships in Poland places of living were divided up into three categories 1) capital of the region 2) other cities 3) villages In voivodships with the higher number of people the class “cities” was additionally divided up into 2-6 smaller categories. In Mazowieckie and Slaskie voivodships there was also a division into two strata in the “villages” class. As an effect there was 65 strata taking into consideration the administrative division of the country and type and size of the place of living. Assumed sample size was divided up into the strata taking into consideration different completion rates in classes of places of living in voivodships. It means that from classes of places of living where the completion rates are known to be lower then in other there was an over-representative sub-sample sampled. 2. Then in CBOS (Public Opinion Research Center) cities and villages communes were sampled. After that in PESEL data-base some small areas of the cities and villages communes were sampled. Persons to be interviewed were chosen also from the PESEL data-base from the previously selected areas. In cities, small areas covered some streets and it’s neighborhood and in villages the areas of one village and/or some of it’s streets. 3. In each stratum at least two small areas were sampled. From each small area six adults living in different locations and in different households were sampled.


Public Opinion Research Center (CBOS), Warsaw


Fieldwork methods:

Self-administered supplement completed after the PGSS and face-to-face interview and after ISSP 2004 Citizenship which was also face-to-face (self-administered/interviewer attending =76,6%) + (face-to-face interview = 23,3%) and in one case the way stays unknown (that is 0.1%) [see MODE-variable in the Polish data file]

Sample size:

1277 = number of respondents achieved on ISSP 2003


Polish

Weighted: YES

Weighting procedure: Weighting procedure assumes that after weighting the sample size is equal to the number of completed interviews.

weight: W1 is = ∑=

n

iis

is

r

r

1

*n

where: i – record ID , i=1,2,.......n n – the number of completed questionnaires N – the number of inhabitants who are 18 or older. r is - completion rate in the class of place of living s where the i interview was conducted. LW s r is ------------- LZR s LW s - sample size drawn in the class of the place of living s, proportional allocation assumed LZR s - number of completed interviews in the class of the place of living s s – class of the place of living (s=1,2,….,6) s=1 - village s=2 – cities up to 19999 inhabitants


s=3 – cities 20000-49999 inhabitants s=4 – cities 50000-99999 inhabitants s=5 – cities 100000-499999 inhabitants s=6 – cities 500000 and more inhabitants After stratification „ex post” for k-categories weights were calculated taking into consideration the structure of polled population on the basis of statistical data coming from the Central Statistical Office (GUS) in division for villages and cities, sex and age category.

W2ki=

XX

W

W

k

kk

isi

n

isi

n

k

k

k

∑

∑

∑

⎛

⎝

⎜⎜⎜

⎞

⎠

⎟⎟⎟

⎛

⎝

⎜⎜⎜⎜

⎞

⎠

⎟⎟⎟⎟

=

=

*

*

100

1

11001

1

n nkk

=⎛⎝⎜

⎞⎠⎟∑

n W isi

n

=⎛⎝⎜

⎞⎠⎟

=∑ 1

1

where: X k - number of people in k-category according to GUS data X= X k

k∑

i k - questionnaires by record ID which belong to the k-category n k - total number of questionnaires which are rated to k-category WX isk = W1 is * W2

ki

WX isk weight for i-respondent belonging to the k-category and drawn in s-class of the place of living.


No biases or other deviation of the sample (after weighting) (see: National Population Characteristics, 18 years or older; POLAND). You can observe in the National Population Characteristics for Poland some deviations in two highest age categories which is caused by different age grouping for men and women and used for weight calculation.

Deviations from ISSP not asked: V58 (question 14), and ETNIC (background question).


questionnaire: Publications: None


ISSP Characteristics of National Population: Poland Central

Statistical Office (GUS) December 2002

Polish General Social Survey January 2005 (unweighted)

Polish General Social Survey January 2005 (weighted)

SEX (population 18+ years old)

Male 47.6 47.5 47.6 Female 52.4 52.5 52.4

N(100%) 29554846 1277 1277 AGE GROUPS (population 18+ years old)

18-24 15.5 14.3 15.5 25-34 18.4 17.3 18.4 35-49 28.3 26.9 28.3 50-59 15.9 19.0 16.6 60+ 21.9 22.6 21.2

N(100%) 29554846 1277 1277 YEARS OF SCHOOLING GROUPS (population 18+ years old)

No formal schooling ND: no data 0.4 0.3 Incomplete elementary (LT 8yr) ND 3.3 3.1 Elementary completed (8yr) ND 21.8 21.2 Basic vocational (10-11yr) ND 27.6 28.1 Incomplete secondary (LT 12yr) ND 4.0 4.1 Secondary general (12yr) ND 7.4 7.6 Secondary vocational (12yr) ND 18.2 18.2 Post secondary (14yr) ND 3.4 3.6 Incomplete higher (14yr) ND 2.0 2.0 Higher completed at Bachelor level (15yr) ND 2.8 2.8 Higher completed at Master level (17yr) ND 9.0 8.9

N(100%) 29554846 1277 1277 EMPLOYMENT STATUS (population 18+ years old)

Employed ND 43.7 44.7 Unemployed ND 13.3 13.8 Not in labor force ND 43.0 41.5

N(100%) 29554846 1277 1277


Study Description: Portugal Study title:

Portuguese Social Attitudes 2003/2004

Fieldwork dates:

April to September 2004


Manuel Villaverde Cabral, Jorge Vala, Alice Ramos, all at Instituto de Ciências Sociais da Universidade de Lisboa.

Sample type:

Stratified random probability. The sample is designed to be representative of adults aged 18 or over living in private accommodation in Portugal. The sample method involved a multi-stage design: stratification by region and habitat; Selection of sampling units (100); selection or streets: selection of addresses by random root; selection of individuals by the last birthday method.

Stratification factors used:

- NUTES (North, Center, Lisbon and Tagus Valley, Alentejo and Algarve)

- HABITAT (less than 2.000 hab.; 2 - 10 thousand hab; 10 - 30 thousand hab; 30 - 100 thousand hab; more than 100 thousand hab) In order to get a representative sample, near 50% of the interviews were made in habitats with less than 2000hab. Some problems came up, such us, a level of non-responses and refusals higher than expected.


TNS-Euroteste

Fieldwork methods:

face-to-face interview with visuals

Context of ISSP Questionnaire:

Atitudes Sociais dos Portugueses (Portuguese Social Attitudes)

Response rates: 2907 A - Total issued (total sample)

145 B - Ineligible (address vacant, wrong ages,...)

2762 C - (= A - B) Total eligible (in scope sample)

1602 D - Total ISSP questionnaires received 1160 E - (= C - D; = F + G + H) Total non-response 955 F - Refusals (refusing to take part)

200 G - Non-contact (never contacted)

5 H - Other non-response Language:

Slovak and Hungarian languages

Weighted: Yes

Sampling procedure: Sampling procedure:


Table 1 - Resident population with 18 or more years old excluding localities with less than 10 dwelings

Less than 2.000 inhab.

From 2.000 to 10.000 inhab.

From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total

North 1361798 397718 244921 389899 119913 309996 2824245Centre 1235049 231291 132496 161030 0 83844 1843710Lisbon 304730 461580 292317 258828 215364 625759 2158578Alentejo 264543 207806 42209 74318 0 0 588876Algarve 150861 40135 62763 50818 0 0 304577Total 3316981 1338530 774706 934893 335277 1019599 7719986

Table 2 - Number of localities by stratum



From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total

North 14124 117 23 18 2 2 14286Centre 7434 61 5 6 1 7507Lisbon 3685 179 34 13 4 2 3917Alentejo 1140 38 3 2 1183Algarve 1046 13 6 2 1067Total 27429 408 71 41 6 5 27960

Table 3 - Number of localities by stratum selected



From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total

North 19 6 3 5 2 2 37,0Centre 18 3 2 2 1 26,0Lisbon 12 20 11 10 4 2 59,0Alentejo 4 3 1 1 9,0Algarve 2 1 1 1 5,0Total 55 33 18 19 6 5 136


Table 4 - Number of interviews by stratum



From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total


Table 5 - Predicted response rate by stratum



From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total

North 85% 80% 75% 70% 65% 60% 73%Centre 80% 75% 75% 65% 45% 68%Lisbon 65% 60% 50% 45% 45% 35% 50%Alentejo 75% 75% 70% 65% 71%Algarve 70% 70% 55% 50% 61%Total 75% 72% 65% 59% 55% 47% 65%

Table 6 - Distribution of contacts by stratum



From 10.000 to

20.000 inhab.

From 20.000 to

50.000 inhab.

From 50.000 to 100.000 inhab.

More than

100.000 inhab.

Total



Weighting procedure: Data were weighted in order to reproduce the population distribution according to the following variables: NUTSII, size of locality, age groups, gender and educational level. Bellow we present the distribution by gender, age and educational level for the population and for the sample (not weighted and weighted).

RESIDENT POPULATION, BY AGE GROUP, LEVEL OF ACADEMIC

QUALIFICATIONS AND SEX (TOTAL)

Geographic area, Level of Academic Qualification Sex 18-24 25-34 35-44 45-54 55-64 65-74 75 or

more N2:Total MF 1027112 1500736 1427556 1274953 1079933 953558 675038 M 519869 750821 701148 612557 506495 424828 257853 F 507243 749915 726408 662396 573438 528730 417185 Without academic qualifications MF 7078 17114 22835 32067 130782 267081 283953 M 3746 9250 11753 13573 42460 86584 80225 F 3332 7864 11082 18494 88322 180497 203728 Primary (incomplete) MF 17508 45263 66479 96268 174709 191052 123412 M 10524 25934 34625 34530 46988 68135 46277 F 6984 19329 31854 61738 127721 122917 77135 Primary (complete) MF 36174 179968 420423 637994 488073 325008 179446 M 20131 89536 201299 308328 259768 180913 87846 F 16043 90432 219124 329666 228305 144095 91600 Secondary (incomplete) MF 560138 690187 548793 264871 156800 89562 48199 M 316242 379321 284243 137170 85238 47015 21802 F 243896 310866 264550 127701 71562 42547 26397 Secondary (complete) MF 110940 219318 164742 93341 46747 24710 14400 M 49450 100957 79438 48522 27479 15149 6996 F 61490 118361 85304 44819 19268 9561 7404 Higher Degree (incomplete) MF 256650 113101 49611 37796 28387 25276 11670 M 107822 40891 26197 21077 15996 11334 5862 F 148828 72210 23414 16719 12391 13942 5808 Higer Degree (complete) MF 38624 235785 154673 112616 54435 26557 13958 M 11954 87080 63593 53457 28566 15698 8845 F 26670 148705 91080 59159 25869 10859 5113 Source: National Institute of Statistics (NIE), Population and Residence General Census - 2001 (Final Results)


Sex_age_educ.level_sample ISSP PT (not weighted)

Age groups Country specific education: Portugal 18-24 25-34 35-44 45-54 55-64 65-74 75 or more

Group Total

'No formal qualification'

Male 1 1 4 12 8 26

Female 1 1 4 32 37 75 Group Total 2 1 1 8 44 45 101Basic -level 1 Male 3 17 36 44 66 57 40 263 Female 3 18 60 102 92 98 57 430 Group Total 6 35 96 146 158 155 97 693Basic-levels 2 and 3 Male 17 22 40 20 19 6 3 127 Female 9 42 49 27 11 12 6 156 Group Total 26 64 89 47 30 18 9 283Secondary incomplete

Male 16 34 26 6 7 5 1 95

Female 21 33 17 17 4 4 4 100 Group Total 37 67 43 23 11 9 5 195Complete secondary Male 5 14 12 4 2 37 Female 8 17 11 6 4 2 48 Group Total 13 31 23 10 6 2 85'University incomplete

Male 11 13 8 7 2 2 1 44

Female 21 17 6 4 4 2 1 55 Group Total 32 30 14 11 6 4 2 99Complete university Male 1 20 20 15 7 2 65 Female 5 37 16 5 7 2 3 75 Group Total 6 57 36 20 14 4 3 140Table Total 120 289 304 259 233 236 161 1602


Sex_age_educ.level_sample ISSP PT (weighted)

Age groups Country specific education: Portugal 18-24 25-34 35-44 45-54 55-64 65-74 75 or more

Group Total

'No formal qualification'

Male 4 4 18 44 18 88

Female 9 2 15 61 62 150 Group Total 13 2 4 33 105 80 237Basic -level 1 Male 7 24 40 61 53 35 33 253 Female 6 19 53 89 80 38 21 306 Group Total 13 43 93 150 133 73 54 559Basic-levels 2 and 3 Male 30 25 38 20 22 2 1 137 Female 13 37 36 18 6 4 1 115 Group Total 43 62 74 38 28 6 2 252Secondary incomplete

Male 26 31 24 10 4 2 0 96

Female 34 21 16 9 3 1 1 87 Group Total 60 53 40 19 7 3 2 183Complete secondary Male 18 28 17 9 1 73 Female 13 19 16 5 4 1 59 Group Total 31 47 33 14 5 1 132'University incomplete

Male 22 13 8 7 1 1 0 52

Female 30 14 5 5 2 1 1 58 Group Total 51 27 13 12 3 2 2 110Complete university Male 2 26 14 13 3 1 60 Female 6 31 17 6 3 0 2 66 Group Total 8 57 31 20 6 1 2 126Table Total 207 303 287 257 216 191 141 1602


National Population Characteristics: Portugal Sex and age Note: The data concerns only the population resident in the Mainland (excluding Azores and Madeira) Total M F n % n n 18-24 years 1027112 12,9 519869 507243 25-34 years 1500736 18,9 750821 749915 35-44 years 1427556 18 701148 726408 45-54 years 1274953 16,1 612557 662396 55-64 years 1079933 13,6 506495 573438 65-74 years 953558 12 424828 528730 75 and more 675038 8,5 257853 417185 Source: Instituto Nacional de Estatística, Censos 2001 Education Note: The data concerns all the population (including Azores and Madeira) Total (>18 years) % None 760910 9,6Basic Primary incomplete 714691 9Basic Primary complete1 2267086 28,6Secondary incomplete2 2358550 29,7Secondary complete3 674198 8,5University incomplete 522491 6,6University complete 636648 8Source: Instituto Nacional de Estatística, Censos 2001 1 4 years 2 10-11 years 3 12 years Note: The data concerns only the population resident in the Mainland (excluding Azores and Madeira)


Study Description: Russia Study title: ‘ISSP-2003 Module “National Identity II” Fieldwork dates: July,01.-15,2003 Principal investigators:

L.Khakhulina, Levada-Center

Sample type:

Description of the sampling procedure Stratification procedure. Nationwide sample (N=2100) was divided among: a) 10 large economico-geographical macro regions proportionate to

the size of the local population aged 16+ of each macro region b) 5 strata of rural districts and urban settlements* in each of 10

macro regions proportionate to the size of the local population aged 16+ of each stratum.

* 1)less than 10,000; (rural districts & small urban settlements) 2)from 10,000 – to100,000; 3)from 100,000 – to 500,000; 4)from 500,000 – to 750,000; 5)over 750,000 inhabitants Selection primary sampling units (PSUs). All cities over 500, 000 inhabitants were included in the sample as self-representative units. Urban and rural settlements were considered as primary sample units (PSUs). In each stratum (except strata of cities over 500,000 and 2 capital cities) the number of PSUs was calculated on the limitation of 15 interviews per PSU and the PSUs as well were selected with the probability to its sizes (the number of its inhabitants). The total numbers of interviews accounted for a stratum was distributed approximately equally among selected PSUs. Totally 101 PSUs were selected. Selection of secondary sampling points (SSUs). Electoral districts were used as secondary sampling points In the cities over 500,000 inhabitants the number of surveyed SSUs was defined by condition of 7 interviews per SSU.. In the rest of selected PSU two sampling points were randomly selected from the list of all electoral districts of this PSU. Totally 240 sample points were selected.

Selection of households. The households were selected by a random route method. If a household or a respondent refused to participate in the survey or not been achieved for 4 visits an interviewer should visit the next address from the rout in the selected districts. Selection of respondents. Within a household a member with the nearest birthday was selected for interviewing. In order to reach a selected respondent an interviewer visited each address up to 3 times in different days of a week and at different time of a day.

The following categories were excluded from the gross sample: a)persons doing their military service by draft (about 1%) b) persons under imprisonment (about 0,8%) c)population of the areas under the war conflict in North Caucasus (1,9%) d) population of remote or difficult to access regions of Far North (0,9) e) rural localities with less then 50 inhabitants (0,8%)

Fieldwork institute: Levada-Center


Fieldwork methods: Self-completion Sample size: N=2400( 2100 + 300 extra sample in Moscow) Response rates: 5902 A - Total issued (total sample) 182 B - Ineligible (address vacant, wrong ages,...) 5720 C - (= A - B) Total eligible (in scope sample) 2408 D - Total ISSP questionnaires received 3367 E - (= C - D; = F + G + H) Total non-response 1653 F - Refusals (refusing to take part) 1328 G - Non-contact (never contacted) 331 H - Other non-response Language: Russian Weighted: yes, a weighting factor exists in the data set Weighting procedure: exact description of the weighting procedure / algorithm

a) Main principles of weighting procedure The total expected number N of respondents for a certain region being treated equal N = N0 * P , where N0 denotes the size of total sample, P - the share of the region population in the entire population. As a result of correction, every respondent X[k] has the definite weight W[k], within the limits 0 < W[k] < ~10 , so that the following conditions were valid : 1)the value of sum(W[k]) for the region concerned was equal to N 2)for every controlled group G[i] the value Q[i] being equal to Q[i] = sum( W[k] | X[k].belong to G[i] ) / N, was closed to a proportion P[i] of group G[i] in the region population i.e. Q[i] ~ P[i], i=1,2,...,16. The value of J being equal to J = sum( (Q[i]-P[i])**2 ) + (sum(W[k])/N - 1)**2 , was used as the criterion for minimization on the weights` sets variety. Quality of corrections male fem <25 <40 <55 >54 H S P 1 2 3 4 5 6 7 8 9* Survey: 3785 6214 1590 2490 2549 3370 2553 5371 2075 Weighted : 4578 5421 1719 2709 2761 2810 1541 5444 3014 State Statistics : 4579 5420 1718 2710 2762 2809 1542 5444 3013 * 1-2 –sex 3-6 –age 7-9 – education (higher, secondary, primary) Weights coefficients sum is equal 2107 . Mean values: ZERO 0 -.1 .1- . .2 .2 - .5 .5- 1 1-2 2- 5 5-10 >10 Number: 0 0 291 1021 489 330 266 12 0


ISSP Characteristics of National Population (Russia) Source: the data of the State Statistics Committee of Russia, 2000 Source no. 1 Source no. 2 Source no. 3 Source no. 4 SEX

Male 45,57 Female 54,43 AGE (groups)

18-24 13,53 25-39 28,12 49-54 28,90 55+ 29,45

YEARS OF SCHOOLING (groups)*

Higher 16,28 Secondary 55,80 Incomplete secondary 27,92 EMPLOYMENT STATUS (1.02.04)**

Employed

58.6

Unemployed

9.5

Not in labor force

31.9

Source – Census , 2002 , Russian State Statistical Committee (Rosstat). *)Data of years of education are not available. **) Social and economic situation in Russia. Rosstat. 2004.


Study Description: Slovakian Republic Study title:

ISSP Identity 2003

Fieldwork dates:

April 20 – May 17, 2004


Comenius university in Bratislava, Department of Sociology (Slovakia)

Sample type:

Three stage stratified probability sampling: 1. Stratified probability sampling of election districts 2. Probability sampling of households in selected districts 3. Sampling of household members based on nearest birth-date


ASA, s.r.o, Palisády 26, 811 06 Bratislava, Slovakia

Fieldwork methods:

Interview face to face

Sample size:

1152

Response rates: 1475 A - Total issued (total sample)

16 B - Ineligible (address vacant, wrong ages,...)

1459 C - (= A - B) Total eligible (in scope sample)

1152 D - Total ISSP questionnaires received 307 E - (= C - D; = F + G + H) Total non-response 307 F - Refusals (refusing to take part)

G - Non-contact (never contacted)

H - Other non-response Language:

Slovak and Hungarian languages

Weighted: Yes

Weighting procedure: Total weight is constructed from stratification weights based on sex, education and age.

The weights were derived from data of Slovak Statistical Office (Census 2001)


Due to response differences the basic socio-demographic characteristics – sex and level of education – are significantly different from the known population characteristics. The problem was corrected by the post-stratification weights (see above).


22 questions were added in the questionnaire – answers are not included in the data-file sent to the archive.

Publications:


ISSP Characteristics of National Population: Slovak Republic Source no. 1 Source no. 2 Source no. 3 Source no. 4 ISSP 2003

(unweightened) ISSP 2003 (weightened)

Census 2001

SEX

Male 39,9 47,1 48,6 Female 60,1 52,9 51,4 Source: Population and Housing Census 2001, Statistical Office of the Slovak Republic

AGE (groups)

18 - 29 25,8 23,3 26,3 30 - 39 21,4 18,6 18,0 40 - 49 22,2 20,7 19,7 50 - 59 18,4 15,9 14,6 60 - 12,3 21,5 20,2

Source: Population and Housing Census 2001, Statistical Office of the Slovak Republic


No formal qualification

0,8 0,4 0,4

Lowest formal qualification

7,7 21,6 26,4

Above lowest qualification

29,4 29,4 30,2

Higher secondary completed

31,7 26,8 32,0

Above higher secondary level

7,8 5,8 1,0

University degree completed

17,0 11,1 9,8


EMPLOYMENT STATUS

Employed

60,1 52,2 66,8

Unemployed

9,2 10,2 13,9

Not in labor force

30,5 37,4 19,3



Study Description: Slovenia Study title:

Slovene Public Opinion Survey 2003/2: International Survey on Family and National Identity and Attitudes on Local Democracy

Fieldwork dates:

February 2003 – March 2003


Niko Toš, Public Opinion and Mass Communication Research Centre (CJMMK), Ljubljana.

Sample type:

Universe: The adult residents of SR Slovenia, older then 18 years, living on permanent address. Excluded: Institutionalised people. Central Register of Population (a list of names and addresses constantly undated by public administration) is employed as a sampling frame. Sampling procedure: The sample is two-stage stratified random sample from Central Register of Population , where every population unit has equal probability of selection. First stage PSU selection is made by probability proportional to size of CEA (Clusters of Enumeration Areas). CEA are stratified according to 12 regions*6 type of settlement. At second stage systematic random selection inside CEA brings fixed numbers of persons with name and address. Spilit-halves samples were used for parallel SJM surveys.

Fieldwork methods: Personal interviews with trained interviewers

Fieldwork institute: Public Opinion and Mass Communication Research Centre (CJMMK), Ljubljana

Context of ISSP- questionnaire:

ISSP 2002 questionnaire lie at the beginning of the SJM 2003/2 questionnaire. Then follows the ISSP 2003.

Sample size: 1093 Response rates: 1612 A - Total issued 0 B – Not eligible 1612 C - Total eligible 1093 D - Total SJM2003/2 questionnaires received 519 E – Non-response 204 F – Refusals 254 G – Non-contact 61 H - Other non-response Language:

Slovenian

Weighted:

No


ISSP Characteristics of National Population: Slovenia

Source no.1 Source no.2 Source no.3 Source no.4 Census 2002, Population 15+ years at years of schooling

Labour Force Survey, 2002 2nd quarter

SEX Male 48,8% Female 51,2% AGE (groups) 0 – 14 15,3% 15 – 29 21,5% 30 – 44 22,7% 45 – 64 25,8% 65+ 14,7% YEARS OF SCHOOLING (groups) 0-7 years of elementary school

7%

Elementary school 26% Completed vocational school

27%

Completed middle school

27%

University degree 12% EMPLOYMENT STATUS (in 1000 of persons) Employed 922 Unemployed 58 Not in labour force 707


Study Description: South-Africa Study title:

‘official’ title of the study/survey South African Social Attitude Survey

Fieldwork dates:

start and end date of field-work August-September 2003


Dr Stephen Rule Human Sciences Research Council

Sample type:

description of the sampling procedure A sample of 3 500 respondents was selected throughout South Africa in groupings of seven and situated in 500 census enumerator areas (EAs) as determined in the 2001 census. Each EA was classified in terms of the dominant lifestyle category by the Human Sciences Research Council (HSRC) in its analysis of the 1996 census data. In order to ensure adequate representation in the sample from each province and from each of the four dominant population groups, the sample was stratified by province and by population group. Disproportionately large samples were selected from areas know to be inhabited by the two smallest components of the population, namely (i) areas with dominantly Indian populations and (ii) the Northern Cape. Within the EAs, the seven households were randomly selected and within the household, the respondent were selected using a Kish grid.


Human Sciences Research Council

Fieldwork methods:

Face-to-face

Sample size:

number of respondents in the final ISSP file


English, Afrikaans, Tswana, Xhosa, Venda, Zulu

Weighted: Yes

Weighting procedure: Basic sampling weight bas3d on SAS Procedure Survey Select


compensating for unit non-response by dividing the sampling weights by the response rate per EA.


Disproportionately large samples were selected from areas know to be inhabited by the two smallest components of the population, namely (i) areas with dominantly Indian populations and (ii) the Northern Cape


Q 6b ; Q7b o ; Q10 ; Q11 ; Q13 Ommitted due to difficult phrasing and confusion with concept of immigrants

Publications:


ISSP Characteristics of National Population: South-Africa SEX Male 19 520 887 Female 21 062 685 Total 40 583 573 AGE (Distribution in 5 year intervals) 0 - 4 4 443 621 5 - 9 4 668 722 10 - 14 4 654 100 15 - 19 4 180 716 20 - 24 3 982 353 25 - 29 3 455 728 30 - 34 3 074 201 35 - 39 2 653 755 40 - 44 2 138 626 45 - 49 1 677 525 50 - 54 1 268 895 55 - 59 1 069 936 60 - 64 890 536 65 - 69 758 887 70 - 74 482 163 75 - 79 377 428 80 - 84 178 902 85 + 24 137 284 Unspecified 490 194 Total 40 583 573 YEARS OF SCHOOLING (GROUPS) No schooling 7,672,762 Grade 0 35,108 Grade 1 565,080 Grade 2 749,002 Grade 3 1,678,309 Grade 4 1,965,454 Grade 5 1,948,356 Grade 6 2,150,362 Grade 7 2,599,776 Grade 8 2,963,287 Grade 9 2,133,308 Grade 10 2,740,619 Grade 11 1,725,736 Less than matric & certif/dip 420,685


Matric only 3,779,481 Matric & certificate 199,028 Matric & diploma 645,553 Matric & Bachelors degree 324,633 Matric & Bachelors & diploma 39,252 Matric & Bachelors & honours 41,979 Matric & Masters degree 45,716 Matric & Doctors degree 21,148 Matric & Other qual 226,783 Unspecified 1,468,394 NA: Aged <5 4,439,089Total 40,578,899 Employment status Employment 7 913 796 Unemployment 15 381 174 Not econ. Active 17 288 603


Study Description: South-Korea Study title:

Korean General Social Survey

Fieldwork dates:

July 1, 2003 ~ August 30, 2003


Hyunho Seok, Survey Research Center at Sungkyunkwan Univ.

Sample type:

Multi-stage Area Probability Sampling

Fieldwork methods: Interview face to face

Fieldwork institute: Survey Research Center at Sungkyunkwan Univ.

Sample size: 2000 Response rates: 2000 A - Total issued (total sample) 30 B – Ineligible (address vacant, wrong ages, …) 1970 C – (=A – B) Total eligible (in scope sample) 1315 D - Total ISSP questionnaires received 655 E – (=C – D; =F + G + H) Total non-response 591 F – Refusals (refusing to take part) 64 G – Non-contact (never contacted) H - Other non-response Language:

Korean

Weighted: no Weighting procedure: - Known systematic properties of the sample:

-


In question WRKHRS: Those who are self-employed or helping family member are not asked about their work hour. We modified code:

KR: 95. Those who are self-employed or helping family member. In question WRKTYPE & SPWKRTYP: ‘0’ include those

who are helping family member. In question WRKSUP: Those who have no current job are not

asked about their supervisory experiences. They are coded on ‘3’ (KR: 3).

In question ATTEND: we modified code: KR: 00 Those who have no religion

Publications:

Not yet


ISSP Characteristics of National Population: South-Korea Source: 2000 Census Gender

Male 16914865 49% Female 17384074 51%

AGE(groups)

18-19 1643990 5% 20-29 7945164 23% 30-39 8280181 24% 40-49 6948359 20% 50-59 4318722 13% 60-69 3164971 9% 70-79 1518719 4% 80- 476965 1%

Total 34297071 100%

YEARS OF SCHOOLING (15 years or older)

1~6 (elementary school) 5206862 15%

7~9 (middle school) 3913610 11%

10~12 (High school) 14586820 42% 13~16 (University) 10192349 29% 17~21 (Graduate school) 799861 2%

Total 34699502 100% EMPLOYMENTS STATUS (15 years or older)

Status Percentage Employed 21936000 58.4% Unemployed 854000 3.7% Not in labor Force 14755000 39.3%


NATIONAL STATISTICS ON DISTRIBUTION OF INCOME (National survey of household income and expenditure 2000)

Less than200 -

200 � 400 - 400 � 600 6.2 600 � 800 4.2

800 � 1,000 5.6 1,000 � 1,200 6.8 1,200 � 1,500 9.9 1,500 � 2,000 18.8 2,000 � 2,500 15.0 2,500 � 3,000 11.3 3,000 � 4,000 12.2

More than 4,000 10.0 Total 100.0


Study Description: Spain Study title:


Fieldwork dates:

From 23 to 30 June, 2003


Juan Díez Nicolás

Sample type:

Representative Sample of Adults Aged 18 Years and over Living Private Households in Spain

Fieldwork Institute:

ASEP, S.A.

Fieldwork methods:

Personal interview at R'S home


Regular Monthly Omnibus

Sample size:

1212

Response rates: (real numbers)

1230 A - Total issued (total sample)

0 B - Ineligible (address vacant, wrong ages,...) 1230 C - (= A - B) Total eligible (in scope sample) 1212 D - Total ISSP questionnaires received 18 E - (= C - D; = F + G + H) Total non-response 9 F - Refusals (refusing to take part) 7 G - Non-contact (never contacted) 2 H - Other non-response Language:

Spanish

Weighted:

Yes

Weighting procedure: Optional : According to sex and age groups

Known Systematic Properties of the sample:

None


Publications: None, yet


ISSP Characteristics of National Population: Spain

Source no.1 Source no.2 Source no.3 Source no.4 Pop. Census 2001 E.P.A. 2001

Work. Pop Sur

SEX Male 20.021.850 Female 20.825.521 AGE (groups) 18-24 years 4.240.700 25-34 6.875.075 35-44 6.319.966 45-54 5.042.813 55-64 4.063.263 65 years and over 6.964.267 YEARS OF SCHOOLING (groups)

No school 5.211,90 4-10 years 8.775,10

11-14 7.847,00 15-18 5.604,70 19-21 3.976,30

22 years and over 2.273,50 EMPLOYMENT STATUS Employed 15.945,60 Unemployed 1.869,10 Not in labour force 15.834,40


Study Description: Sweden Study title: National Identity II

Fieldwork dates: February 2003 to April 2003


Prof. Stefan Svallfors and Dr.Lonas Edlund, Department of Sociology, Umeå University, Umeå, Sweden

Sample type: Two representative samples of the Swedish population 17-79 years. The samples were subjected to different fieldwork methods, with obvious implications for the response rate.

Fieldwork institute: SIFO

Fieldwork methods: Separate postal survey with several reminders. Sample 1 received an introductory letter and a gift. The gift was free and was not associated with any obligations. See the below table for a detailed description.

The samples can be separated by using the variable: S_MODE Fieldwork details

Sample 1 Sample 2

29/1 Introductory letter about the survey X 3/2 Postal survey X 4/2 Postal survey + lottery ticket X

10/2 Postal reminder X 11/2 Postal reminder + questionnaire X 24/2 Postal reminder + questionnaire X 25/2 Postal reminder + questionnaire X 14/3 Postal reminder (+ questionnaire to those

with unknown telephone numbers) X

17-27/3 Reminder by telephone X 17-31/3 Reminder by telephone (+ questionnaire to

those wishing a questionnaire) X


Separate survey

Language: Swedish

Weighted: No

Sample size: 1186 Known bias in data The response patterns for all variables have been subjected to χ2 tests

in order to track significant differences between samples 1 and 2 (not controlling for demographic differences). Differences in response patterns between the two samples are generally small. For all variables: p > 0.10, except v17 (p=0.01) and v39 (p=0.07).

Response rates in different demographic groupings are relatively


evenly distributed. However, the following may be noted: women and the young (higher than average response rate); men, the elderly, those living in Stockholm (lower than average response rate). Special note on background variables referring to occupation 1. All occupational variables refer to the respondent’s present or (if

the respondent is currently not working) last occupation. 2. ISCO. 4-digit. Where information for 4-digit coding is not

available, 3- or 2-digit codings have been applied, using zeros for the missing digits. Examples: isco code 733 is coded as 7330 in the datafile, isco code 73 is coded as 7300 in the datafile.

Response rates:

Sample 1 1000 A – Total issued (total sample)

38 B – Ineligible 962 C – (=A-B) Total eligible (in scope sample) 674 D – Total ISSP questionnaires received (70%) 288 E – (=C-D;=F+G+H) Total non-response 62 F – Refusals (refusing to take part)

185 G – Non-contact (never contacted) 41 H – Other non-response

Sample 2 1000 A – Total issued (total sample)

47 B – Ineligible 953 C – (=A-B) Total eligible (in scope sample) 512 D – Total ISSP questionnaires received (54%) 441 E – (=C-D;=F+G+H) Total non-response 110 F – Refusals (refusing to take part) 266 G – Non-contact (never contacted) 65 H – Other non-response

Samples 1+2 2000 A – Total issued (total sample)

85 B – Ineligible 1915 C – (=A-B) Total eligible (in scope sample) 1186 D – Total ISSP questionnaires received (62%) 729 E – (=C-D;=F+G+H) Total non-response 172 F – Refusals (refusing to take part) 451 G – Non-contact (never contacted) 106 H – Other non-response

Response rates in different groups (percent):

Sample 1 Sample 2 Samples 1+2SEX Men 65 53 59

Women 75 54 65


AGE

17-24 72 58 6525-34 63 41 5235-44 71 52 6145-54 70 53 6255-64 75 63 6965-79 70 56 63

REGION(*)

North 79 61 69Mid North 74 52 62

Mid East 69 53 61Stockholm 64 48 56

West 76 55 64Göteborg 77 60 69

Småland+Gotland 60 57 59South 71 40 58

Malmö 66 67 67

URBAN-RURAL(**) Stockholm 64 48 56

Urban 1 72 51 62Urban 2 66 54 60Rural 1 77 54 66Rural 2 74 62 68

Göteborg region 77 60 69Malmö etc. region 66 67 67


ISSP Characteristics of National Population: Sweden Register for the total

population (2003) Age 17-79

ISSP Sample (2003) age 17-79

Education Employment

Sample 1

Sample 2

Samples 1+2

Sample 1

Sample 2

Samples 1+2

SEX Men 49 52 50 46 51 48 Women 51 48 50 54 49 52 AGE 17-24 11 11 11 12 12 12 25-34 18 18 18 16 13 15 35-44 19 19 19 20 19 19 45-54 18 18 18 18 18 18 55-64 18 18 18 19 21 20 65-79 16 16 15 15 17 16 REGION(*) North 10 12 11 11 13 12 Mid North 10 12 11 10 11 11 Mid East 16 16 16 16 16 16 Stockholm 21 19 20 19 17 18 West 8 10 9 9 10 9 Göteborg 10 9 9 11 10 10 Småland+Gotland 9 9 9 8 9 9 South 11 8 9 11 6 9 Malmö 5 6 5 5 8 6 URBAN-RURAL(**) Stockholm 21 19 20 19 17 18 Urban 1 35 35 35 36 34 35 Urban 2 18 20 19 17 20 18 Rural 1 6 6 6 7 6 6 Rural 2 5 5 5 6 6 6 Göteborg region 10 9 9 11 10 10 Malmö region 5 6 5 5 8 6 EDUCATION(***)

No information available

2

Primary school 26Secondary school 2 years

27

Secondary school 3 years

18

University Less than 3 years

13

University 3 years or more

15

EMPLOYMENT


STATUS (****) Employed 74Unemployed 4Not in labour force

22

(***) Education register (SUN2000 adjusted to ISCED) age 16-74 (2002). (****) Labour force surveys (AKU) age 16-64 (2003). (*) Region description Codes Administrative provinces (“län” approximative to english “county”) AB Stockholms län C Uppsala län D Södermanlands län E Östergötlands län F Jönköpings län G Kronobergs län H Kalmar län I Gotlands län K Blekinge län M Skåne län N Hallands län O Västra Götalands län S Värmlands län T Örebro län U Västmanlands län W Dalarnas län X Gävleborgs län Y Västernorrlands län Z Jämtlands län AC Västerbottens län BD Norrbottens län REGION 1 North (AC, BD, Y, Z) 2 Mid North (S, W, X) 3 Mid East (AB, C, D, E, T, U, except 4 Stockholm) 4 Stockholm 5 West (N, O, except 6 Göteborg) 6 Göteborg 7 Småland Gotland (F, G, H, I) 8 South (K, L, M, except 9 Malmö) 9 Malmö (**) Urban-rural description


Stockholm (including the suburb municipalities)

Urban 1 (Municipalities (MC) with more than 90 000 inhabitants within an area of 30 kilometres radius from the MC centre)

Urban 2 (MC:s with more than 27 000 inhabitants and less than 90 000 inhabitants within an area of 30 kilometres radius of the MC centre and in the same time with more than 300 000 inhabitants within 100 kilometres radius of the MC centre)

Rural 1 (MC:s with more than 27 000 inhabitants and less than 90 000 inhabitants within an area of 30 kilometres radius of the MC centre and in the same time with less than 300 000 inhabitants within 100 kilometres radius of the MC centre)

Rural 2 (MC:s with less than 27 000 inhabitants within an area of 30 kilometres radius of the centre)

Göteborg region (Göteborg including the suburb municipalities)

Malmö region (Malmö, Lund, Trelleborg including the suburb municipalities)


Study Description: Switzerland Study title:

ISSP 2003 National Identity'

Fieldwork dates:

May the 6th 2002 until August the 25th 2003


Institut SIDOS, Ruelle Vaucher 13, CH-2000 Neuchâtel

Sample type:

The ISSP 2003 survey was combined with the „Eurobarometer in Switzerland“ (EBCH) survey. The questions related to the „Eurobarometer in Switzerland“ were first asked followed by those of the ISSP 2003 using the CAPI method. The sampling procedure was the following:

- Stratification of the households into 6 regions (Espace Mittelland, North of Switzerland, East of Switzerland, Center of Switzerland and Italian-speaking part of Switzerland)

- Random selection of households from the extended phone register

- Sending of an information letter - One half of the sample was contacted by the telephone

central of the fieldwork institute and the other half per telephone or face to face from the interviewer to fix a date for the interview

- Random selection of one person in each household with the KISH method

- EBCH and ISSP Interview (CAPI)


MIS Trend, Institut pour l’étude des marchés et les sondages d’opinion, Pont-Bessières 3, 1005 Lausanne

Fieldwork methods:

CAPI

Sample size:

1037

Response rates: A - 3640 (total sample) B - 497 (address vacant, wrong ages, sick, language,...) C - (= A - B) 3143 (in scope sample) D - 1037 E - (= C - D; = F + G + H) 2106 F - 1735 (refusing to take part) G - 224 (never contacted) H - 147 Language:

German, French and Italian

Weighted: yes


Weighting procedure: The weights were defined according to the following criteria: - Size of household - Age - Gender - Language - Employment status The estimation of size of household, age, gender, language is based on the Swiss federal census 2000 and the estimation of the employment status on the Swiss Labour Force Survey 2002. The size of the household was recoded into the following four categories: 1) Household with 1 person 2) Household with 2 persons 3) Household with 3 persons 4) Household with 4 persons and more The age was recoded into the following six categories: 1) 18-24 years 2) 25-34 years 3) 35-44 years 4) 45-54 years 5) 55-64 years 6) 65 and older

The language was recoded into the following five categories: 1) German 2) French 3) Italian 4) Rheto-roman 5) Other

The employment status was recoded into the following two categories: 1) Active 2) Non active

The weights result from the division of the expected through the observed value. This process was repeated until convergence.


Under representation of young people and over representation of german speaking people.


None

Publications: -


ISSP Characteristics of National Population: Switzerland Swiss federal Census

2000 SAKE 2002 (Swiss labour force survey)

SEX

Male 48.4 Female 51.6 AGE (groups)

18-24 Jahre 10.4 25-34 Jahre 18.6 35-44 Jahre 20.6 45-54 Jahre 17.3 55-64 Jahre 13.7 65 Jahre und mehr 19.3

YEARS OF SCHOOLING (groups, approximation, see details next page)

0-8 3.0 9 21.6

12-13 49.4 14 9.5 16 1.1 19 6.8

No indication 8.6

YEARS OF SCHOOLING (total)15

Mean 12.07 12.7 EMPLOYMENT STATUS

Employed 64.8 Unemployed 1.5 Not in labor force 33.7 Note: Indications for population 18 years and older Approximation of years of schooling in Switzerland, population 18 years and older The Swiss federal Census asks for the highest achiedved education, not for the years of schooling. Therefore they make an approximate calculation of the years of schooling.

OFS (Swiss federal statistics office)

Years of schooling (approximation of

ISCED code

ISCED

15 Indications for population 15 years and older


A. Borkowski, OFS)

Aucune formation achevée 0-8 0 Not completed primary education Scolarité obligatoire 9 2 Lower secondary Ecole de culture générale ou préparant à une formation

12 3 Upper secondary

Apprentissage, école professionnelle à plein temps

12 3

Maturité 13 3 Ecole normale 13 3 Formation professionnelle supérieure 14 4 Post secondary Ecole professionnelle supérieure 14 5 Haute école spécialisée 16 5 First stage of tertiary Université, haute école 19 5-6 First and second stage of tertiary

education Sans indication No indication

ISCED % Approximate years of schooling

Total 100 Not completed primary education 3.0 0-8 Lower secondary or second stage of basic education

21.6 9

Upper secondary education 49.4 12-13 Post secondary, non tertiary education 9.5 14 First stage of tertiary education 1.1 16 First and second stage of tertiary education 6.8 19 No indication 8.6


Study Description: Taiwan Study title: Taiwan Social Change Survey: the Fourth Survey of the Fourth Cycle Fieldwork dates: 08/10/2003~for about one month Principal investigators:

Chang, Ying-hwa Institute of Sociology, Academia Sinica

Sample type:

Three-stage Stratified PPS Sampling (1) PSU=township, (2) Li (administrative unit under township, (3) respondent

Fieldwork institute: Center for Survey Research, Academia Sinica Fieldwork methods Face-to-face interview Sample size: 2016 Response rates: 4391 A - Total issued (total sample) 138 B - Ineligible (address vacant, wrong ages,...) 4253 C - (= A - B) Total eligible (in scope sample) 2016 D - Total ISSP questionnaires received 2237 E - (= C - D; = F + G + H) Total non-response 594 F - Refusals (refusing to take part) 56 G - Non-contact (never contacted) 1587 H - Other non-response Language: Manderin, Taiwanese, or Hakka Weighted: no Weighting procedure: Known systematic properties of the sample:

A non-response bias comes from the use of household registration data in which some household members in fact do not live in the household.


Some variables are not included in the data� V65, ETHNIC, V68-V74(optional)

Publications: Report for Taiwan Social Change Survey (2004), Institute of Sociology


ISSP Characteristics of National Population: Taiwan Source no. 1 Source no. 2 Source no. 3 Source no. 4 SEX

Male 51.0% Female 49.0% AGE (groups)

Less than 14 19.8% 15�64 70.9%

65 and more 9.2%

YEARS OF SCHOOLING (for those more than 15 years old only)

None 4.0% Primary & junior high 36.2% Senior high 33.8% College and more 26.0% EMPLOYMENT STATUS (for those more than 15 years old only)

Employed

75.92%

Unemployed

5.17%

Not in labor force

18.91%

Source no. 1: "Taiwan-Fukien Demographic Fact Book, R.O.C.," by the Ministry of Interior;

" Agricultural Statistics Yearbook," by Council of Agriculture, Executive Yuan.

Source no. 2: "Taiwan-Fukien Demographic Fact Book, R.O.C.," by the Ministry of Interior. Source no. 3: "Yearbook of Manpower Survey Statistics, Taiwan Area, R.O.C.," by

Directorate-General of Budget, Accounting and Statistics, Executive Yuan.


Study Description: Uruguay Study title: National Identity - (ISSP 2003 Module)

Fieldwork dates: From July 12 to August 16, 2004


Zuleika Ferre, Giorgina Piani, Máximo Rossi from Department of Economics and Juan José Goyeneche, Guillermo Zoppolo from Institute of Statistics from University of Uruguay

Sample type:

The sampling frame used was the 1996 Population Census. The Universe population are adults (18 year-old or more) that reside in Urban areas. The design is stratified multistage. Two major regions are represented: Montevideo Metropolitan Area (strata 1-7) and Urban population in the rest of the Country (5000 or more inhabitants cities, strata 11-13). In strata 1 to 7, Census Zones (usually one block) are selected by a systematic proportional to size (pps) scheme (“size” being the number of people on each block), then four households are selected on each block, and one person per household is selected via the “next birthday” rule. In strata 11 to 13, four cities are selected per stratum via systematic pps sampling. Size again being number of people residing on each city. Census Zones, households and persons are selected in the same way as in strata 1 to 7. Sample allocation: Table 1

Stratum Population Sample 1 224.396 96 2 367.513 156 3 428.118 184 4 286.499 120 5 78.576 32 6 191.474 80 7 21.368 12 11 349.935 144 12 325.190 144 13 317.427 140

Total 2.590.496 1.108


Fieldwork institute: Department of Economics – Faculty of Social Sciences, University of

Uruguay Fieldwork methods: Face to face interviews


The National Identity 2003 module was carried out in conjunction with de Citizenship 2004 module. The questionnaire was structured as follows: firstly, the Citizenship module, the National Identity module, and finally, demographic variables.

Sample size: 1108

Response rates: CONCEPT Total A - Total issued (total sample) 1389 B - Ineligible (address vacant, wrong ages,...) 0 C - (= A - B) Total eligible (in scope sample) 1389 D – Total ISSP questionnaires received 1108 E - (= C - D; = F + G + H) Total non-response 281 F - Refusals (refusing to take part) 176 G - Non-contact (never contacted) 72 H - Other non-response (incomplete questionnaires) 33 Language:

Spanish

Weighted: The data submitted are not weighted Weighting procedure: The weight is computed as the inverse of the selection probability for

each person. The steps concerning the household selection are done with pps sampling, so the household weights are equal to number of households on stratum divided by the number of households selected on each stratum. The household weight is then expanded by the person weight, which corresponds to the number of adults on the household. On some households the number of adults goes up to 10, as a conservative measure we reduced these weights considering a maximum number of 5 for the person weight. Since we estimated the number of household per stratum, we finally adjusted the weights in order to match the number of people per stratum that appear on the previous table 1.


None that we are aware.


The questionnaire was translated as closely as possible from English to Spanish, maintaining the meaning and significance of each sentence and word. Some general comments: • In questions V58: we opened this question in v58_a and v58_b. The

reason for that was: in Uruguay commonly family are formed with people from different countries (mainly from Spain and Italy)


• DEMOGRAPHICS VARIABLES:

• UNION: The code 2 was not included. • INCOME and RINCOME: In these questions, incomes were

measured in categories and we coded them. • URBRURAL: It was not self assessement. Was coded by the

field supervisor. The value labels for UY_DEGR, INCOME, RINCOME, UY_PRTY, UY_REG AND UY_SIZE are: VALUE LABELS UY_DEGR 01 'None' 02 'Incomplete primary school' 03 'Completed primary school' 04 'Incomplete secondary' 05 'Completed secondary' 06 'Incomplete technical education' 07 'Completed technical education' 08 'Incomplete university' 09 'Completed university' 10 'Incomplete non university high education' 11 'Completed non university high education' 99 'NA' 00 'Not available'. VALUE LABELS INCOME RINCOME 01 'Less than $3.000' 02 '$3.00 to $5.999' 03 '$6.000 to $7.499' 04 '$7.500 to $9.499' 05 '$9.500 to $11.499' 06 '$11.500 to $13.499' 07 '$13.500 to $16.499' 08 '$16.500 to $20.499' 09 '$20.500 to $26.499' 10 '$26.500 to $38.999' 11 'More than $39.000' 999997 'Refused' 999998 'Dont know' 999999 'NA' 000000 'No own income, not in paid'. VALUE LABELS UY_PRTY 01 'Red Party' 02 'National Party' 03 'Wide front Party'


04 'Independent Party' 05 'Liberal Party' 06 'Other Party' 96 'No party preference' 99 'NA'. VALUE LABELS UY_REG 01 'Metropolitan statistical area of Montevideo' 02 'Rest of urban population'. VALUE LABELS UY_SIZE 01 '1.597.943 urban population' 02 '992.552 urban population'.

Publications:


ISSP Characteristics of National Population: Uruguay Source: National Survey of Households 2003 - INE SEX Population >= 18 Total población

Male 45,2 %

46,9 %

Female 54,8 % 53,1 %

N 1.722.921 2.365.492

AGE - Group

18 - 29 23,3 %

30 - 39 15,9 %

40 - 49 17,3 %

50 - 59 14,8 % 60 - 69 12,7 %

70 + 16,0 %

N 1.722.921

YEARS OF SCHOOLING - Group

None 1,5 %

1 - 6 37,7 %

6 -12 37,6 %

12 7,6 %

13 - 15 7,6 %

16 + 8,0 %

N 1.722.921

EMPLOYMENT STATUS Population >= 14

Economically Active Population 62,0 %

58,1 %

Employed (% EAP) 83,9 % 83,1 %

Unemployed (% EAP) 16,1 % 16,9 %

Not in labor force 38,0 % 41,9 %

N 1.722.921 1.877.497 Note: The information is only about urban population in cities greater than 5.000 inhabitants.


Study Description: USA Study title:

General Social Survey - National Identity

Fieldwork dates:

8/05-12/05


Tom W. Smith and James A. Davis, NORC/University of Chicago and Peter V. Marsden, Harvard University

Sample type:

Multi-stage, area probability sample


NORC

Fieldwork methods:

In-person with self-completion on laptop of ISSP module

Sample size:

1216

Response rates: 2587 A - Total issued (total sample) 792 B - Ineligible (address vacant, wrong ages,...) 1795 C - (= A - B) Total eligible (in scope sample) 1216 D - Total ISSP questionnaires received E - (= C - D; = F + G + H) Total non-response 514 F - Refusals (refusing to take part) 49 G - Non-contact (never contacted) 16 H - Other non-response Language:

English

Weighted: Yes

Weighting procedure: the weight takes into consideration three factors: 1) a sub-sampling of temporray, non-response cases, 2) differential final non-response by area, and 3) number of adults in the household to make representative of individuals rather than households


Men and resdients of large central cities ar eunderrepresented due to higher nonresponse in the unweighted data


None

Publications: None


National Population Characteristics: USA

Table 1 A Detailed Comparison of the 2002 Current Population Survey (CPS) and the Weighted and Unweighted 2002 General Social Survey (GSS) A. AGE

CPS GSS Unweighted

GSS Weighted*

18 – 24 13.7 9.9 12.125 – 29 8.6 9.3 9.730 – 34 10.1 11.2 10.435 – 39 11.3 10.2 9.840 – 44 12.0 9.7 10.045 – 49 10.5 10.1 10.450 – 54 8.5 9.0 9.455 – 59 6.4 6.8 6.860 – 64 4.9 6.0 5.965 + 14.1 17.7 15.6N 2751 2751

B. Gender

Female 51.2 55.6 54.2n 2765 2765

C. YEARS OF SCHOOLING, 25 YEARS AND OLDER

0 – 8 6.6 5.6 5.69 – 11 7.5 9.7 9.612 33.2 29.6 29.513 – 15 25.6 27.6 28.516 + 27.1 27.2 26.8n 2469 2413

D. Labour Force Participation, 16 years or older**

Employed 63.6 65.0 65.6Unemployed 4.2 4.4 4.4Not in labour force 32.2 30.7 30.0n 2765 2765 * Weighted by number of eligible respondents (i.e. 18+) in the household. ** The GSS figures are based on 18+.


Study Description: Venezuela Study title:

General Social Survey - National Identity

Fieldwork dates:

22-3-2004 to 08-04-2004


Roberto Briceño León

Sample type:

The stratification variable used was the political and administrative division consisting of 23 states. But 2 states ( Amazonas and Delta Amacuro with lesser population) were joined together, so that there was 22 instead of 23 strata. The sampling frame was the list of censal segments used to carry out the XIII Venezuelan National Census. It included demographic and mapping information prepared by the National Institute of Statistics (Instituto Nacional de Estadística) for the 2001 census. The sampling method was carried out in three satges. In the first stage we selected censal segments from each stratum with proportional probability to their number of dwellings In the second stage were selected two "blocks" from each censal segment using a systematic geographical order selection technique with a random start. The selection of blocks was with probability proportional to the number of dwellings in each block. Finally a person was selected according to a quota by sex and age. Five persons were selected from each block with one person selected from each household. The start in each block to get the first dwelling was random. The quota was established using sex and age groups accordingly to the national distribution of people by sex and age revealed in the 2001 National Census.


Laboratorio de Ciencias Sociales, LACSO

Fieldwork methods:

Face to face personal interview

Sample size:

1199

Response rates: 1337 A - Total issued (total sample) 43 B - Ineligible (address vacant, wrong ages,...) 1294 C - (= A - B) Total eligible (in scope sample) 1199 D - Total ISSP questionnaires received 95 E - (= C - D; = F + G + H) Total non-response 54 F – Refusals (refusing to take part) 29 G - Non-contact (never contacted) 12 H - Other non-response


Language:

Spanish

Weighted: Yes

Weighting procedure: Post-stratification was carried out by standard of living groups (slg), based on similar previous studies. Final sample weights were adjusted by a factor obtained using the next equation: Fe = Expected % slg “e” / observed % slg “e”


The isolated indigenous population living in the Amazon (Yanomami, Warao, etc) was excluded, but they represented less than 1% of total population. There were limitations reaching people from High Class areas.


None

Publications: None


ISSP Characteristics of National Population: Venezuela


Codebook Information The example below is a reproduction of information appearing in the machine readable codebook. The numbers in angular brackets < > do not appear in the codebook, but are references to the descriptions which follow the example. Example: <1> <2> <3> Missing Values: 8;9

<4> Q.8 In general, would you say that people should obey the law without exception, or are there exceptional occasions on which people should follow their consciences even if it means breaking the law? (Please tick one box only) <5> <-----> <6> <7> 1. Obey the law without exception 2. Follow own conscience on occasions 8. Can't choose, don't know 9. NA, refused <8>

1 2 3 4 5 8 9 V20 (N) % % % % % % %

255 754 428 485 174Australia (AU) 2183 12,20% 36,00% 20,40% 23,10% 8,30% 37M 50M

90 248 170 283 175Austria (AT) 1006 9,30% 25,70% 17,60% 29,30% 18,10% 40M

279 463 130 66 70Bulgaria (BG) 1069 27,70% 45,90% 12,90% 6,50% 6,90% 38M 23M

145 436 269 242 89Canada (CA) 1211 12,30% 36,90% 22,80% 20,50% 7,50% 21M 9M

201 627 277 314 52Chile (CL) 1505 13,70% 42,60% 18,80% 21,30% 3,50% 27M 7M

389 511 227 87 18Czech Republic (CZ) 1276 31,60% 41,50% 18,40% 7,10% 1,50% 11M 33M

266 440 196 143 227Denmark (DK) 1322 20,90% 34,60% 15,40% 11,20% 17,80% 29M 21M

121 424 344 278 83Finland (FI) 1379 9,70% 33,90% 27,50% 22,20% 6,60% 69M 60M

375 477 284 216 194France (FR) 1669 24,30% 30,90% 18,40% 14,00% 12,50% 27M 96M

80 324 136 194 76Germany-West (DE-W) 850 9,90% 40,00% 16,80% 24,00% 9,40% 36M 4M

47 207 63 70 30Germany-East (DE-E) 437 11,30% 49,60% 15,10% 16,80% 7,20% 18M 2M

153 479 141 58 12Great Britain (GB) 873 18,10% 56,80% 16,70% 6,90% 1,40% 10M 20M

73 235 289 231 173Hungary (HU) 1021 7,30% 23,50% 28,90% 23,10% 17,30% 15M 5M

158 590 127 159 20Ireland (IE) 1065 15,00% 56,00% 12,00% 15,10% 1,90% 9M 2M

281 410 174 123 74Israel Jews (IL-J) 1066 26,50% 38,60% 16,40% 11,60% 7,00% 3M 1M

28 54 47 19 4Israel Arabs (IL-A) 152 18,40% 35,50% 30,90% 12,50% 2,60%

344 383 173 69 74Japan (JP) 1102 33,00% 36,70% 16,60% 6,60% 7,10% 54M 5M

138 459 209 134 18Latvia (LV) 1000 14,40% 47,90% 21,80% 14,00% 1,90% 42M New Zealand (NZ) 1036 162 437 207 148 49 13M 20M …

V4 Obey laws without exception


Explanations <1> A variable (and reference) number have been assigned to each item in the study. In the present codebook which documents the archived data set, these numbers are identical. Should the data set be subsetted or rearranged the variable numbers might change to reflect the order of the new data set while the reference numbers would remain unchanged to provide a link to the archived data set. <2> Indicates the abbreviated variable label used within OSIRIS or SPSS system files. <3> "Missing Values" indicates the designation of the missing data codes. <4> Indicates the full question text taken from the British questionnaire. Wherever possible the original sequence of questions has been retained, although some changes were necessary to integrate the different national questionnaires. <5> Indicates commentaries and explanations added during the processing of the study. < within question or answer texts may indicate whether the questionnaire in a particular country is deviating from the general format. <6> Indicates the code value for the single answer category. <7> Indicates the textual definition of the codes. Abbreviations commonly used are DK (don't know), NA (no answer), Can't choose, Not applicable and Not available. <8> Indicates percentage frequencies by country. This form is used whenever code categories have the same meaning for all countries. Column percentages are based only on "valid cases". Missing data values were excluded from percentages.

V1 ISSP Study Number

V2 Respondent ID Number Respondent Number This number uniquely identifies each respondent. The first two digits are identical with the country code, the next five digits contain the original identification number.

ZA - No. 3910 I S S P 2003 - National Identity II Page II - 1

V3 Country

Country: (N)

1 Australia (AU) 2183 2 Germany-West (DE-W) 850 3 Germany-East (DE-E) 437 4 Great Britain (GB) 873 6 United States (US) 1216 7 Austria (AT) 1006 8 Hungary (HU) 1021 10 Ireland (IE) 1065 12 Norway (NO) 1469 13 Sweden (SE) 1186 14 Czech Republic (CZ) 1276 15 Slovenia (SI) 1093 16 Poland (PL) 1277 17 Bulgaria (BG) 1069 18 Russia (RU) 2383 19 New Zealand (NZ) 1036 20 Canada (CA) 1211 21 Philippines (PH) 1200 22 Israel Jews (IL-J) 1066 23 Israel Arabs (IL-A) 152 24 Japan (JP) 1102 25 Spain (SP) 1212 26 Latvia (LV) 1000 27 Slovak Republic (SK) 1152 28 France (FR) 1669 30 Portugal (PT) 1602 31 Chile (CL) 1505 32 Denmark (DK) 1322 33 Switzerland (CH) 1037 36 Venezuela (VE) 1199 37 Finland (FI) 1379 40 Southafrica (ZA) 2483 41 Taiwan (TW) 2016 42 South Korea (KR) 1315 43 Uruguay (UY) 1108


V4 Most important group R identifies with Missing Values: 98; 99 Q. 1. We are all part of different groups. Some are more important to us than others when we think of ourselves. In

general, which in the following list is most important to you in describing who you are? and the second most important? and the third most important?1 Q1a First most important, Q1b Second most important, Q1c Third most important.

1. Your current or previous occupation (or being a homemaker) 2. Your race/ethnic background 3. Your gender (that is, being a man/woman) 4. Your age group (that is, Young, Middle, Age, Old) 5. Your religion (or being agnostic or atheist) 6. Your preferred political party, group, or movement. 7. Your nationality

8. Your family or marital status (that is , son/daughter, mother/father, grandfather/grandmother, husband/wife, widower/widow, nor married, or other similar).

9. Your social class (that is upper, moddle, lower, working, or similar categories) 10. The part of [COUNTRY] that you live in 11. [ES]:None 98. Can´t choose 99. Na, refused Notes: [HU]: Did not include code 7 [KR]: Did not include code 2 (1) In oral interviews, use card with choices


1 2 3 4 5 6 7 8 9 10 11 98 99

V4 (N) % % % % % % % % % % % % % 336 56 137 95 101 12 180 1108 32 68

Australia (AU) 2183 15,80% 2,60% 6,40% 4,50% 4,80% 0,60% 8,50% 52,10% 1,50% 3,20% - 58M174 46 96 29 38 12 71 402 28 57

Austria (AT) 1006 18,30% 4,80% 10,10% 3,00% 4,00% 1,30% 7,50% 42,20% 2,90% 6,00% - 53M 225 120 61 101 12 1 151 287 25 29

Bulgaria (BG) 1069 22,20% 11,90% 6,00% 10,00% 1,20% 0,10% 14,90% 28,40% 2,50% 2,90% - 46M 11M132 32 89 34 66 8 113 566 15 63

Canada (CA) 1211 11,80% 2,90% 8,00% 3,00% 5,90% 0,70% 10,10% 50,60% 1,30% 5,60% - 93M297 122 359 60 44 9 184 316 30 50

Chile (CL) 1505 20,20% 8,30% 24,40% 4,10% 3,00% 0,60% 12,50% 21,50% 2,00% 3,40% - 25M 9M340 45 191 107 25 8 110 333 43 64

Czech Republic (CZ) 1276 26,90% 3,60% 15,10% 8,50% 2,00% 0,60% 8,70% 26,30% 3,40% 5,10% - 10M98 11 45 27 18 6 46 546 13 16

Denmark (DK) 1322 11,90% 1,30% 5,40% 3,30% 2,20% 0,70% 5,60% 66,10% 1,60% 1,90% - 9M 487M190 14 75 76 34 14 167 145 18 20

Finland (FI) 1379 25,20% 1,90% 10,00% 10,10% 4,50% 1,90% 22,20% 19,30% 2,40% 2,70% - 567M 59M232 112 326 91 76 34 259 297 89 96

France (FR) 1669 14,40% 6,90% 20,20% 5,60% 4,70% 2,10% 16,10% 18,40% 5,50% 6,00% - 57M125 43 113 35 26 9 26 236 17 32

Germany-West (DE-W) 850 18,90% 6,50% 17,10% 5,30% 3,90% 1,40% 3,90% 35,60% 2,60% 4,80% - 188M78 18 80 24 7 23 107 15 25

Germany-East (DE-E) 437 20,70% 4,80% 21,20% 6,40% 1,90% - 6,10% 28,40% 4,00% 6,60% - 60M84 14 61 22 19 2 60 340 11 15

Great Britain (GB) 873 13,40% 2,20% 9,70% 3,50% 3,00% 0,30% 9,60% 54,10% 1,80% 2,40% - 245M133 84 72 108 38 12 327 58 121

Hungary (HU) 1021 14,00% 8,80% 7,60% 11,30% 4,00% 1,30% - 34,30% 6,10% 12,70% - 68M154 31 84 30 79 5 159 397 7 40

Ireland (IE) 1065 15,60% 3,10% 8,50% 3,00% 8,00% 0,50% 16,10% 40,30% 0,70% 4,10% - 79M179 32 99 57 140 13 193 249 54 32

Israel Jews (IL-J) 1066 17,10% 3,10% 9,40% 5,40% 13,40% 1,20% 18,40% 23,80% 5,20% 3,10% - 14M 4M30 42 12 7 27 4 20 3 5 2

Israel Arabs (IL-A) 152 19,70% 27,60% 7,90% 4,60% 17,80% 2,60% 13,20% 2,00% 3,30% 1,30% - 220 90 113 68 17 11 149 220 18 71

Japan (JP) 1102 22,50% 9,20% 11,60% 7,00% 1,70% 1,10% 15,30% 22,50% 1,80% 7,30% - 13M 112M224 122 80 101 29 12 353 41 26

Latvia (LV) 1000 22,70% 12,30% 8,10% 10,20% 2,90% - 1,20% 35,70% 4,10% 2,60% - 12M52 10 43 11 25 4 37 175 4 8

New Zealand (NZ) 1036 14,10% 2,70% 11,70% 3,00% 6,80% 1,10% 10,00% 47,40% 1,10% 2,20% - 667M123 19 162 41 46 9 111 628 16 33

Norway (NO) 1469 10,40% 1,60% 13,60% 3,50% 3,90% 0,80% 9,30% 52,90% 1,30% 2,80% - 1M 280M202 22 120 48 125 4 158 374 29 50

Poland (PL) 1277 17,80% 1,90% 10,60% 4,20% 11,00% 0,40% 14,00% 33,00% 2,60% 4,40% - 1M 144M207 49 336 106 54 9 196 479 36 63

Portugal (PT) 1602 13,50% 3,20% 21,90% 6,90% 3,50% 0,60% 12,80% 31,20% 2,30% 4,10% - 58M 9M186 74 51 40 138 6 76 538 55 36

Philippines (PH) 1200 15,50% 6,20% 4,20% 3,30% 11,50% 0,50% 6,30% 44,80% 4,60% 3,00% - 608 244 202 191 49 15 69 655 154 171

Russia (RU) 2383 25,80% 10,30% 8,60% 8,10% 2,10% 0,60% 2,90% 27,80% 6,50% 7,30% - 25M 188 20 120 45 132 6 45 491 11 58

Slovak Republic (SK) 1152 16,80% 1,80% 10,80% 4,00% 11,80% 0,50% 4,00% 44,00% 1,00% 5,20% - 36M191 125 107 65 31 3 109 267 17 127

Slovenia (SI) 1093 18,30% 12,00% 10,30% 6,20% 3,00% 0,30% 10,50% 25,60% 1,60% 12,20% - 51M265 394 162 64 183 12 141 597 24 61

South Africa (ZA) 2483 13,90% 20,70% 8,50% 3,40% 9,60% 0,60% 7,40% 31,40% 1,30% 3,20% - 580M251 103 116 57 2 83 584 40 68

South Korea (KR) 1315 19,20% - 7,90% 8,90% 4,40% 0,20% 6,40% 44,80% 3,10% 5,20% - 11M249 37 166 253 22 36 78 182 44 36 74

Spain (ES) 1212 21,20% 3,10% 14,10% 21,50% 1,90% 3,10% 6,60% 15,50% 3,70% 3,10% 6,30% 35M83 5 77 25 13 8 33 292 5 15

Sweden (SE) 1186 14,90% 0,90% 13,80% 4,50% 2,30% 1,40% 5,90% 52,50% 0,90% 2,70% - 1M 629M227 123 90 90 20 6 56 269 18 60

Switzerland (CH) 1037 23,70% 12,80% 9,40% 9,40% 2,10% 0,60% 5,80% 28,10% 1,90% 6,30% - 48M 30M603 61 38 442 149 123 81 62 161 170

Taiwan (TW) 2016 31,90% 3,20% 2,00% 23,40% 7,90% 6,50% 4,30% 3,30% 8,50% 9,00% - 64M 62M186 52 103 42 132 5 29 581 25 46

United States (US) 1216 15,50% 4,30% 8,60% 3,50% 11,00% 0,40% 2,40% 48,40% 2,10% 3,80% - 11M 4M229 34 223 60 25 13 161 258 19 65

Uruguay (UY) 1108 21,10% 3,10% 20,50% 5,50% 2,30% 1,20% 14,80% 23,70% 1,70% 6,00% - 1M 20M223 28 57 53 126 17 187 260 100 136

Venezuela (VE) 1199 18,80% 2,40% 4,80% 4,50% 10,60% 1,40% 15,80% 21,90% 8,40% 11,50% - 2M 10MSum 44170 7324 2331 4253 2764 2123 438 3573 12924 1277 2030 74 939M 4120M


V5 Second most important group R identifies with Missing Values: 98; 99 Q1.- We are all part of different groups. Some are more important to us than others when we think of ourselves. In general, which in the following list is most important to you in describing who you are? Please tick one box in the first column. And which is the second most important? And the third most important?

Q1a First most important, Q1b Second most important, Q1c Third most important. 1. Your current or previous occupation (or being a homemaker) 2. Your race/ethnic background 3. Your gender (that is, being a man/woman) 4. Your age group (that is, Young, Middle, Age, Old) 5. Your religion (or being agnostic or atheist) 6. Your preferred political party, group, or movement. 7. Your nationality


9. Your social class (that is upper, moddle, lower, working, or similar categories) 10. The part of [COUNTRY] that you live in 11. [ES]:None 98. Can´t choose 99. Na, refused, no second response Notes: [KR]: Did not include code 2 [HU]: Did not include code 7


1 2 3 4 5 6 7 8 9 10 11 98 99

V5 (N) % % % % % % % % % % % % % 457 103 208 220 110 18 258 326 116 286

Australia (AU) 2183 21,70% 4,90% 9,90% 10,50% 5,20% 0,90% 12,30% 15,50% 5,50% 13,60% - 81M221 79 102 40 44 18 119 153 126 93

Austria (AT) 1006 22,20% 7,90% 10,30% 4,00% 4,40% 1,80% 12,00% 15,40% 12,70% 9,30% - 11M 185 94 63 146 47 12 107 181 64 94

Bulgaria (BG) 1069 18,60% 9,50% 6,30% 14,70% 4,70% 1,20% 10,80% 18,20% 6,40% 9,50% - 55M 21M203 44 92 98 96 8 162 178 82 144

Canada (CA) 1211 18,30% 4,00% 8,30% 8,90% 8,70% 0,70% 14,60% 16,10% 7,40% 13,00% - 104M207 93 261 125 93 10 226 284 58 101

Chile (CL) 1505 14,20% 6,40% 17,90% 8,60% 6,40% 0,70% 15,50% 19,50% 4,00% 6,90% - 36M 11M238 80 173 173 41 24 146 171 103 102


Denmark (DK) 1322 37,50% 2,50% 8,70% 7,60% 2,20% 2,60% 12,60% 10,80% 7,10% 8,30% - 10M 497M136 19 78 101 25 30 108 113 43 55

Finland (FI) 1379 19,20% 2,70% 11,00% 14,30% 3,50% 4,20% 15,30% 16,00% 6,10% 7,80% - 607M 64M257 80 170 203 63 46 225 270 126 148

France (FR) 1669 16,20% 5,00% 10,70% 12,80% 4,00% 2,90% 14,20% 17,00% 7,90% 9,30% - 81M118 52 60 77 48 15 56 104 65 62

Germany-West (DE-W) 850 18,00% 7,90% 9,10% 11,70% 7,30% 2,30% 8,50% 15,80% 9,90% 9,40% - 193M51 25 35 55 5 5 44 70 45 35

Germany-East (DE-E) 437 13,80% 6,80% 9,50% 14,90% 1,40% 1,40% 11,90% 18,90% 12,20% 9,50% - 67M150 10 97 54 31 8 86 104 39 60


Hungary (HU) 1021 11,90% 6,70% 9,00% 15,80% 5,50% 2,90% - 17,10% 12,20% 18,80% - 92M159 42 92 79 140 13 173 150 24 100

Ireland (IE) 1065 16,40% 4,30% 9,50% 8,10% 14,40% 1,30% 17,80% 15,40% 2,50% 10,30% - 93M155 37 72 97 128 38 170 174 106 58


Israel Arabs (IL-A) 152 11,80% 17,10% 11,80% 12,50% 18,40% 7,90% 13,20% 2,60% 1,30% 3,30% - 123 70 119 146 18 22 89 163 35 140

Japan (JP) 1102 13,30% 7,60% 12,90% 15,80% 1,90% 2,40% 9,60% 17,60% 3,80% 15,10% - 3M 174M187 144 116 118 49 13 31 196 68 60

Latvia (LV) 1000 19,00% 14,70% 11,80% 12,00% 5,00% 1,30% 3,20% 20,00% 6,90% 6,10% - 18M75 27 44 26 18 3 60 72 13 26

New Zealand (NZ) 1036 20,60% 7,40% 12,10% 7,10% 4,90% 0,80% 16,50% 19,80% 3,60% 7,10% - 672M311 36 133 106 41 25 160 207 35 132

Norway (NO) 1469 26,20% 3,00% 11,20% 8,90% 3,50% 2,10% 13,50% 17,50% 3,00% 11,10% - 3M 280M213 62 111 110 128 13 149 168 66 112

Poland (PL) 1277 18,80% 5,50% 9,80% 9,70% 11,30% 1,10% 13,20% 14,80% 5,80% 9,90% - 1M 144M234 63 274 177 80 26 213 273 65 97

Portugal (PT) 1602 15,60% 4,20% 18,20% 11,80% 5,30% 1,70% 14,20% 18,20% 4,30% 6,50% - 77M 23M243 90 84 57 239 30 94 216 95 52

Philippines (PH) 1200 20,20% 7,50% 7,00% 4,80% 19,90% 2,50% 7,80% 18,00% 7,90% 4,30% - 396 278 216 295 108 59 123 442 252 166

Russia (RU) 2383 17,00% 11,90% 9,30% 12,60% 4,60% 2,50% 5,30% 18,90% 10,80% 7,10% - 48M 225 31 93 82 91 5 179 160 57 118


Slovenia (SI) 1093 13,50% 9,40% 7,00% 10,60% 7,40% 1,50% 15,00% 16,40% 5,00% 14,30% - 67M191 271 216 181 336 72 216 270 98 128

South Africa (ZA) 2483 9,70% 13,70% 10,90% 9,10% 17,00% 3,60% 10,90% 13,60% 5,00% 6,50% - 504M209 129 250 90 11 97 223 112 174

South Korea (KR) 1315 16,10% - 10,00% 19,30% 6,90% 0,80% 7,50% 17,20% 8,60% 13,40% - 20M150 82 189 179 29 46 79 148 57 83 90

Spain (ES) 1212 13,30% 7,20% 16,70% 15,80% 2,60% 4,10% 7,00% 13,10% 5,00% 7,30% 8,00% 80M172 13 64 68 13 18 58 66 23 55

Sweden (SE) 1186 31,30% 2,40% 11,60% 12,40% 2,40% 3,30% 10,50% 12,00% 4,20% 10,00% - 7M 629M172 122 85 132 25 17 68 164 47 92


Taiwan (TW) 2016 16,40% 3,20% 2,40% 12,30% 14,90% 8,80% 8,00% 9,00% 12,20% 12,70% - 69M 66M236 74 102 118 158 14 63 236 75 120


Uruguay (UY) 1108 12,50% 4,30% 15,60% 10,40% 5,30% 3,50% 16,30% 20,60% 3,80% 7,70% - 13M 20M161 45 68 85 125 27 176 216 128 144



V6 Third most important group R identifies with Missing Values: 98; 99 Q1.- We are all part of different groups. Some are more important to us than others when we think of ourselves. In general, which in the following list is most important to you in describing who you are? Please tick one box in the first column. And which is the second most important? And the third most important?

Q1a First most important, Q1b Second most important, Q1c Third most important. 1. Your current or previous occupation (or being a homemaker) 2. Your race/ethnic background 3. Your gender (that is, being a man/woman) 4. Your age group (that is, Young, Middle, Age, Old) 5. Your religion (or being agnostic or atheist) 6. Your preferred political party, group, or movement. 7. Your nationality


9. Your social class (that is upper, moddle, lower, working, or similar categories) 10. The part of [COUNTRY] that you live in 11. [ES]:None 98. Can´t choose 99. Na, refused, no third response Notes: [KR]: Did not include code 2 [HU]: Did not include code 7


1 2 3 4 5 6 7 8 9 10 11 98 99

V6 (N) % % % % % % % % % % % % % 351 100 175 253 99 43 240 144 136 541

Australia (AU) 2183 16,90% 4,80% 8,40% 12,20% 4,80% 2,10% 11,50% 6,90% 6,50% 26,00% - 101M106 65 69 70 62 20 131 100 177 169

Austria (AT) 1006 10,90% 6,70% 7,10% 7,20% 6,40% 2,10% 13,50% 10,30% 18,30% 17,40% - 37M 116 94 53 106 42 23 108 149 89 149

Bulgaria (BG) 1069 12,50% 10,10% 5,70% 11,40% 4,50% 2,50% 11,60% 16,00% 9,60% 16,00% - 96M 44M176 44 91 110 73 21 127 77 99 279

Canada (CA) 1211 16,00% 4,00% 8,30% 10,00% 6,70% 1,90% 11,60% 7,00% 9,00% 25,40% - 114M171 77 192 135 94 15 195 256 98 186

Chile (CL) 1505 12,10% 5,40% 13,50% 9,50% 6,60% 1,10% 13,70% 18,00% 6,90% 13,10% - 72M 14M144 48 152 142 59 37 134 138 108 227


Denmark (DK) 1322 16,00% 4,40% 8,40% 10,10% 4,50% 6,80% 16,20% 4,60% 10,70% 18,20% - 16M 486M93 26 75 90 38 46 98 82 46 97

Finland (FI) 1379 13,50% 3,80% 10,90% 13,00% 5,50% 6,70% 14,20% 11,90% 6,70% 14,00% - 598M 90M241 104 115 179 84 54 204 188 210 187

France (FR) 1669 15,40% 6,60% 7,30% 11,40% 5,40% 3,40% 13,00% 12,00% 13,40% 11,90% - 103M90 50 67 74 30 17 70 59 93 98

Germany-West (DE-W) 850 13,90% 7,70% 10,30% 11,40% 4,60% 2,60% 10,80% 9,10% 14,40% 15,10% - 202M45 29 40 45 6 7 36 39 41 75

Germany-East (DE-E) 437 12,40% 8,00% 11,00% 12,40% 1,70% 1,90% 9,90% 10,70% 11,30% 20,70% - 74M108 24 71 74 36 28 100 38 61 91


Hungary (HU) 1021 10,10% 6,70% 9,60% 16,80% 4,50% 4,30% - 14,00% 12,30% 21,80% - 111M133 42 89 91 120 25 157 92 43 177

Ireland (IE) 1065 13,70% 4,30% 9,20% 9,40% 12,40% 2,60% 16,20% 9,50% 4,40% 18,30% - 96M151 48 80 87 71 55 104 165 134 116


Israel Arabs (IL-A) 152 2,70% 14,70% 3,30% 3,30% 16,70% 14,00% 22,70% 12,70% 6,70% 3,30% - 2M 84 48 102 131 22 29 72 155 46 162

Japan (JP) 1102 9,90% 5,60% 12,00% 15,40% 2,60% 3,40% 8,50% 18,20% 5,40% 19,00% - 9M 242M126 156 112 120 45 10 34 122 110 136

Latvia (LV) 1000 13,00% 16,10% 11,50% 12,40% 4,60% 1,00% 3,50% 12,60% 11,30% 14,00% - 29M66 26 45 26 17 8 63 31 21 59

New Zealand (NZ) 1036 18,20% 7,20% 12,40% 7,20% 4,70% 2,20% 17,40% 8,60% 5,80% 16,30% - 674M206 40 134 121 28 38 207 107 64 231

Norway (NO) 1469 17,50% 3,40% 11,40% 10,30% 2,40% 3,20% 17,60% 9,10% 5,40% 19,60% - 13M 280M120 60 123 100 134 104 143 99 93 188

Poland (PL) 1277 10,30% 5,20% 10,60% 8,60% 11,50% 8,90% 12,30% 8,50% 8,00% 16,20% - 1M 112M163 83 211 166 65 30 205 207 115 173

Portugal (PT) 1602 11,50% 5,90% 14,90% 11,70% 4,60% 2,10% 14,50% 14,60% 8,10% 12,20% - 151M 33M135 121 106 67 222 46 139 134 125 103

Philippines (PH) 1200 11,30% 10,10% 8,80% 5,60% 18,50% 3,80% 11,60% 11,20% 10,40% 8,60% - 2M284 230 181 234 117 112 157 276 293 391

Russia (RU) 2383 12,50% 10,10% 8,00% 10,30% 5,10% 4,90% 6,90% 12,10% 12,90% 17,20% - 108M 161 19 67 74 50 24 114 95 64 262


Slovenia (SI) 1093 10,80% 8,30% 8,00% 10,30% 6,90% 2,80% 11,40% 13,50% 6,90% 20,90% - 85M194 281 197 154 197 173 226 193 143 264

South Africa (ZA) 2483 9,60% 13,90% 9,70% 7,60% 9,70% 8,60% 11,20% 9,50% 7,10% 13,10% - 461M183 132 240 55 19 78 144 131 294

South Korea (KR) 1315 14,30% - 10,30% 18,80% 4,30% 1,50% 6,10% 11,30% 10,30% 23,00% - 39M122 53 116 164 36 55 81 120 66 123 108

Spain (ES) 1212 11,70% 5,10% 11,10% 15,70% 3,40% 5,30% 7,80% 11,50% 6,30% 11,80% 10,30% 168M88 19 67 64 15 29 75 49 36 99

Sweden (SE) 1186 16,30% 3,50% 12,40% 11,80% 2,80% 5,40% 13,90% 9,10% 6,70% 18,30% - 16M 629M97 110 68 120 32 28 109 127 48 121


Taiwan (TW) 2016 12,30% 3,30% 2,70% 8,90% 12,30% 9,40% 7,50% 10,90% 15,50% 17,20% - 74M 68M165 72 140 128 94 32 64 124 122 242


Uruguay (UY) 1108 12,10% 3,30% 11,60% 9,60% 4,90% 3,60% 17,80% 16,30% 7,20% 13,60% - 29M 20M153 43 65 103 114 26 125 177 153 210



V7 How close do you feel to: Your town - city Missing Values: 8; 9 Q2.- How close do you feel to1... (Please, tick one box on each line) a) Your town or city 1. Very close. 2. Close. 3. Not very close. 4. Not close at all. 8. Can´t choose. 9. Na, refused.

Notes: (1) Precode: “Feel close to” is to be understood as “emotionally attached to” or “identifying with”.


V7 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 524 1189 302 73 54M 41M

25,10% 56,90% 14,50% 3,50%Austria (AT) 1006 578 323 90 10 5M

57,70% 32,30% 9,00% 1,00%Bulgaria (BG) 1069 594 350 103 16 5M 1M

55,90% 32,90% 9,70% 1,50%Canada (CA) 1211 305 615 230 45 14M 2M

25,50% 51,50% 19,20% 3,80%Chile (CL) 1505 764 523 190 24 1M 3M

50,90% 34,80% 12,70% 1,60%Czech Republic (CZ) 1276 583 485 120 26 3M 59M

48,00% 40,00% 9,90% 2,10%Denmark (DK) 1322 396 575 267 47 9M 28M

30,80% 44,70% 20,80% 3,70%Finland (FI) 1379 369 644 261 41 25M 39M

28,10% 49,00% 19,80% 3,10%France (FR) 1669 516 636 300 107 24M 86M

33,10% 40,80% 19,20% 6,90%Germany-West (DE-W) 850 283 382 150 23 6M 6M

33,80% 45,60% 17,90% 2,70%Germany-East (DE-E) 437 160 216 47 8 1M 5M

37,10% 50,10% 10,90% 1,90%Great Britain (GB) 873 273 400 125 45 6M 24M

32,40% 47,40% 14,80% 5,30%Hungary (HU) 1021 568 323 93 34 1M 2M

55,80% 31,70% 9,10% 3,30%Ireland (IE) 1065 439 442 141 33 4M 6M

41,60% 41,90% 13,40% 3,10%Israel Jews (IL-J) 1066 487 316 152 105 4M 2M

45,90% 29,80% 14,30% 9,90%Israel Arabs (IL-A) 152 98 38 13 3

64,50% 25,00% 8,60% 2,00%Japan (JP) 1102 421 539 106 21 12M 3M

38,70% 49,60% 9,80% 1,90%Latvia (LV) 1000 278 468 200 37 15M 2M

28,30% 47,60% 20,30% 3,80%New Zealand (NZ) 1036 276 517 168 38 20M 17M

27,60% 51,80% 16,80% 3,80%Norway (NO) 1469 324 699 376 31 10M 29M

22,70% 48,90% 26,30% 2,20%Poland (PL) 1277 416 603 197 29 32M

33,40% 48,40% 15,80% 2,30%Portugal (PT) 1602 702 654 176 64 3M 3M

44,00% 41,00% 11,00% 4,00%Philippines (PH) 1200 401 592 185 13 9M

33,70% 49,70% 15,50% 1,10%Russia (RU) 2383 664 862 564 181 112M

29,20% 38,00% 24,80% 8,00%Slovak Republic (SK) 1152 510 516 90 20 15M 1M

44,90% 45,40% 7,90% 1,80%Slovenia (SI) 1093 522 443 106 19 2M 1M

47,90% 40,60% 9,70% 1,70%South Africa (ZA) 2483 1531 638 177 70 34M 33M

63,40% 26,40% 7,30% 2,90%South Korea (KR) 1315 414 612 253 27 9M

31,70% 46,90% 19,40% 2,10%Spain (ES) 1212 613 554 28 8 9M

51,00% 46,10% 2,30% 0,70%Sweden (SE) 1186 294 527 271 34 26M 34M

26,10% 46,80% 24,10% 3,00%Switzerland (CH) 1037 372 414 210 38 1M 2M

36,00% 40,00% 20,30% 3,70%Taiwan (TW) 2016 711 884 345 57 18M 1M

35,60% 44,30% 17,30% 2,90%United States (US) 1216 268 540 283 84 41M

22,80% 46,00% 24,10% 7,10%Uruguay (UY) 1108 550 387 143 22 5M 1M

49,90% 35,10% 13,00% 2,00%Venezuela (VE) 1199 636 376 132 49 4M 2M

53,30% 31,50% 11,10% 4,10%Sum 44170 16840 18282 6594 1482 530M 442M


V8 How close do you feel to: Your [county] Missing Values: 8; 9 Q2.- How close do you feel to1... (Please, tick one box on each line) b) Your [county]2 1. Very close. 2. Close. 3. Not very close. 4. Not close at all. 8. Can´t choose. 9. Na, refused. Notes: (1) Precode: “Feel close to” is to be understood as “emotionally attached to” or “identifying with”. (2) [county] (or province, state, etc.): to be understood as the most relevant administrative unit smaller than the entire country/nation.


1 2 3 4 8 9

V8 (N) % % % % % % 448 1147 390 80

Australia (AU) 2183 21,70% 55,50% 18,90% 3,90% 60M 58M565 335 95 9

Austria (AT) 1006 56,30% 33,40% 9,50% 0,90% 2M 500 410 106 24

Bulgaria (BG) 1069 48,10% 39,40% 10,20% 2,30% 20M 9M362 632 165 38

Canada (CA) 1211 30,20% 52,80% 13,80% 3,20% 12M 2M725 558 198 23

Chile (CL) 1505 48,20% 37,10% 13,20% 1,50% 1M411 615 156 39

Czech Republic (CZ) 1276 33,70% 50,40% 12,80% 3,20% 3M 52M214 501 435 128

Denmark (DK) 1322 16,70% 39,20% 34,00% 10,00% 13M 31M159 531 443 121

Finland (FI) 1379 12,70% 42,30% 35,30% 9,60% 43M 82M550 630 270 106

France (FR) 1669 35,30% 40,50% 17,40% 6,80% 22M 91M180 418 201 32

Germany-West (DE-W) 850 21,70% 50,30% 24,20% 3,90% 7M 12M107 226 76 13

Germany-East (DE-E) 437 25,40% 53,60% 18,00% 3,10% 4M 11M227 396 157 48

Great Britain (GB) 873 27,40% 47,80% 19,00% 5,80% 9M 36M541 335 103 37

Hungary (HU) 1021 53,20% 33,00% 10,10% 3,60% 3M 2M446 441 129 30

Ireland (IE) 1065 42,60% 42,20% 12,30% 2,90% 5M 14M340 354 230 133

Israel Jews (IL-J) 1066 32,20% 33,50% 21,80% 12,60% 2M 7M92 41 14 5

Israel Arabs (IL-A) 152 60,50% 27,00% 9,20% 3,30% 368 569 139 12

Japan (JP) 1102 33,80% 52,30% 12,80% 1,10% 12M 2M157 384 336 66

Latvia (LV) 1000 16,60% 40,70% 35,60% 7,00% 55M 2M218 499 228 45

New Zealand (NZ) 1036 22,00% 50,40% 23,00% 4,50% 19M 27M329 721 332 39

Norway (NO) 1469 23,20% 50,70% 23,40% 2,70% 12M 36M228 603 345 59

Poland (PL) 1277 18,50% 48,80% 27,90% 4,80% 41M 1M725 723 114 27

Portugal (PT) 1602 45,60% 45,50% 7,20% 1,70% 2M 11M381 561 206 39

Philippines (PH) 1200 32,10% 47,30% 17,40% 3,30% 13M 364 856 721 263

Russia (RU) 2383 16,50% 38,80% 32,70% 11,90% 179M 286 678 134 33

Slovak Republic (SK) 1152 25,30% 59,90% 11,80% 2,90% 21M 394 504 151 36

Slovenia (SI) 1093 36,30% 46,50% 13,90% 3,30% 4M 4M1234 840 265 72

South Africa (ZA) 2483 51,20% 34,80% 11,00% 3,00% 36M 36M260 572 399 63

South Korea (KR) 1315 20,10% 44,20% 30,80% 4,90% 21M 593 544 56 10

Spain (ES) 1212 49,30% 45,20% 4,70% 0,80% 1M 8M224 551 311 50

Sweden (SE) 1186 19,70% 48,50% 27,40% 4,40% 30M 20M293 500 211 30

Switzerland (CH) 1037 28,30% 48,40% 20,40% 2,90% 3M540 987 378 78

Taiwan (TW) 2016 27,20% 49,80% 19,10% 3,90% 32M 1M281 548 280 75

United States (US) 1216 23,70% 46,30% 23,60% 6,30% 31M 1M339 450 250 53

Uruguay (UY) 1108 31,00% 41,20% 22,90% 4,90% 14M 2M563 403 166 60

Venezuela (VE) 1199 47,20% 33,80% 13,90% 5,00% 6M 1MSum 44170 13644 19063 8190 1976 734M 563M


V9 How close do you feel to: [country] Missing Values: 8; 9 Q2.- How close do you feel to1... (Please, tick one box on each line) c) [COUNTRY] 1. Very close. 2. Close. 3. Not very close. 4. Not close at all. 8. Can´t choose. 9. Na, refused. Notes: (1) Precode: “Feel close to” is to be understood as “emotionally attached to” or “identifying with”.


1 2 3 4 8 9

V9 (N) % % % % % % 1078 884 126 27

Australia (AU) 2183 51,00% 41,80% 6,00% 1,30% 38M 30M600 332 68 4

Austria (AT) 1006 59,80% 33,10% 6,80% 0,40% 2M 689 291 49 14

Bulgaria (BG) 1069 66,10% 27,90% 4,70% 1,30% 9M 17M567 471 113 47

Canada (CA) 1211 47,30% 39,30% 9,40% 3,90% 10M 3M869 507 103 20

Chile (CL) 1505 58,00% 33,80% 6,90% 1,30% 1M 5M479 625 97 24


Denmark (DK) 1322 56,10% 35,90% 7,10% 0,90% 6M 24M634 570 93 12

Finland (FI) 1379 48,40% 43,50% 7,10% 0,90% 27M 43M914 537 120 32

France (FR) 1669 57,00% 33,50% 7,50% 2,00% 15M 51M212 481 119 18




Hungary (HU) 1021 75,00% 22,20% 2,30% 0,60% 1M 2M561 411 60 13

Ireland (IE) 1065 53,70% 39,30% 5,70% 1,20% 5M 15M848 154 41 18


Israel Arabs (IL-A) 152 25,70% 43,40% 20,40% 10,50% 527 461 79 10

Japan (JP) 1102 48,90% 42,80% 7,30% 0,90% 23M 2M272 505 170 33

Latvia (LV) 1000 27,80% 51,50% 17,30% 3,40% 18M 2M622 338 39 9

New Zealand (NZ) 1036 61,70% 33,50% 3,90% 0,90% 12M 16M616 662 135 15

Norway (NO) 1469 43,10% 46,40% 9,50% 1,10% 10M 31M572 601 83 10

Poland (PL) 1277 45,20% 47,50% 6,60% 0,80% 11M 820 659 95 18

Portugal (PT) 1602 51,50% 41,40% 6,00% 1,10% 3M 7M425 583 153 30

Philippines (PH) 1200 35,70% 49,00% 12,80% 2,50% 9M 599 921 512 234

Russia (RU) 2383 26,40% 40,60% 22,60% 10,30% 117M 451 575 98 19


Slovenia (SI) 1093 46,70% 47,80% 4,30% 1,20% 1M 1M1470 649 221 78


South Korea (KR) 1315 40,40% 44,00% 13,70% 2,00% 14M 530 565 83 26

Spain (ES) 1212 44,00% 46,90% 6,90% 2,20% 8M476 524 140 16

Sweden (SE) 1186 41,20% 45,30% 12,10% 1,40% 19M 11M423 532 73 7

Switzerland (CH) 1037 40,90% 51,40% 7,10% 0,70% 2M639 993 316 42

Taiwan (TW) 2016 32,10% 49,90% 15,90% 2,10% 23M 3M623 442 102 23


Uruguay (UY) 1108 56,40% 33,20% 8,60% 1,80% 3M 1M698 336 118 38



V10 How close do you feel to: continent Missing Values: 8; 9 Q2.- How close do you feel to1... (Please, tick one box on each line) d) [Continent; e.g. Europe]2 1. Very close. 2. Close. 3. Not very close. 4. Not close at all. 8. Can´t choose. 9. Na, refused. Notes: (1) Precode: “Feel close to” is to be understood as “emotionally attached to” or “identifying with”. (2) [Europe]: give relevant continent or subcontinent: Europe, North America, East Asia/Southeast Asia]


1 2 3 4 8 9

V10 (N) % % % % % % 42 269 682 991

Australia (AU) 2183 2,10% 13,60% 34,40% 49,90% 117M 82M281 415 258 38

Austria (AT) 1006 28,30% 41,80% 26,00% 3,80% 14M 308 381 168 93

Bulgaria (BG) 1069 32,40% 40,10% 17,70% 9,80% 88M 31M280 521 273 95

Canada (CA) 1211 24,00% 44,60% 23,40% 8,10% 33M 9M530 535 316 82

Chile (CL) 1505 36,20% 36,60% 21,60% 5,60% 36M 6M252 608 270 69


Denmark (DK) 1322 18,20% 35,80% 34,90% 11,20% 30M 37M94 390 567 156

Finland (FI) 1379 7,80% 32,30% 47,00% 12,90% 88M 84M317 537 419 255

France (FR) 1669 20,70% 35,10% 27,40% 16,70% 48M 93M107 385 266 45




Hungary (HU) 1021 65,60% 28,30% 5,00% 1,10% 13M 2M108 369 410 154

Ireland (IE) 1065 10,40% 35,40% 39,40% 14,80% 9M 15M222 249 303 277


Israel Arabs (IL-A) 152 12,50% 25,70% 34,20% 27,60% 145 419 254 83

Japan (JP) 1102 16,10% 46,50% 28,20% 9,20% 194M 7M31 150 385 359

Latvia (LV) 1000 3,40% 16,20% 41,60% 38,80% 73M 2M136 307 325 189

New Zealand (NZ) 1036 14,20% 32,10% 34,00% 19,70% 41M 38M260 532 436 94

Norway (NO) 1469 19,70% 40,20% 33,00% 7,10% 63M 84M239 525 380 58

Poland (PL) 1277 19,90% 43,70% 31,60% 4,80% 74M 1M357 698 396 95

Portugal (PT) 1602 23,10% 45,10% 25,60% 6,10% 33M 23M129 358 431 229

Philippines (PH) 1200 11,20% 31,20% 37,60% 20,00% 52M 1M67 178 648 1152

Russia (RU) 2383 3,30% 8,70% 31,70% 56,30% 338M 193 564 208 94


Slovenia (SI) 1093 21,20% 45,50% 23,60% 9,70% 32M 4M913 739 452 253


South Korea (KR) 1315 6,00% 24,40% 45,60% 24,00% 29M 205 722 206 59

Spain (ES) 1212 17,20% 60,60% 17,30% 4,90% 5M 15M157 381 461 104

Sweden (SE) 1186 14,20% 34,50% 41,80% 9,40% 63M 20M222 591 194 23

Switzerland (CH) 1037 21,60% 57,40% 18,80% 2,20% 5M 2M23 184 630 990

Taiwan (TW) 2016 1,30% 10,10% 34,50% 54,20% 182M 7M317 461 292 89


Uruguay (UY) 1108 21,40% 31,70% 36,30% 10,50% 23M 1M339 319 278 223



V11 Important: to have been born in [Country] Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) a. to have been born in [COUNTRY] 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”.


1 2 3 4 8 9

V11 (N) % % % % % % 692 539 568 295

Australia (AU) 2183 33,00% 25,70% 27,10% 14,10% 31M 58M468 264 167 73

Austria (AT) 1006 48,10% 27,20% 17,20% 7,50% 34M 559 378 86 19

Bulgaria (BG) 1069 53,60% 36,30% 8,30% 1,80% 18M 9M553 344 178 119

Canada (CA) 1211 46,30% 28,80% 14,90% 10,00% 13M 4M1035 308 136 18

Chile (CL) 1505 69,10% 20,60% 9,10% 1,20% 5M 3M459 488 198 62


Denmark (DK) 1322 37,30% 30,20% 26,20% 6,30% 12M 18M528 397 300 111

Finland (FI) 1379 39,50% 29,70% 22,50% 8,30% 12M 31M536 410 299 304

France (FR) 1669 34,60% 26,50% 19,30% 19,60% 11M 109M218 250 256 92




Hungary (HU) 1021 34,60% 36,50% 20,60% 8,20% 21M 4M561 334 117 45

Ireland (IE) 1065 53,10% 31,60% 11,10% 4,30% 4M 4M355 256 240 208


Israel Arabs (IL-A) 152 63,80% 28,30% 4,60% 3,30% 480 340 212 40

Japan (JP) 1102 44,80% 31,70% 19,80% 3,70% 23M 7M320 391 212 75

Latvia (LV) 1000 32,10% 39,20% 21,20% 7,50% 2M512 263 156 77

New Zealand (NZ) 1036 50,80% 26,10% 15,50% 7,60% 10M 18M462 469 363 143

Norway (NO) 1469 32,20% 32,60% 25,30% 10,00% 9M 23M601 505 132 22

Poland (PL) 1277 47,70% 40,10% 10,50% 1,70% 17M 617 746 106 32

Portugal (PT) 1602 41,10% 49,70% 7,10% 2,10% 6M 95M928 212 45 7

Philippines (PH) 1200 77,90% 17,80% 3,80% 0,60% 8M 1295 684 236 116

Russia (RU) 2383 55,60% 29,30% 10,10% 5,00% 52M 294 379 311 134

Slovak Republic (SK) 1152 26,30% 33,90% 27,80% 12,00% 26M 8M402 336 222 120

Slovenia (SI) 1093 37,20% 31,10% 20,60% 11,10% 10M 3M1328 904 75 131


South Korea (KR) 1315 42,10% 38,40% 18,10% 1,40% 4M 452 607 103 36

Spain (ES) 1212 37,70% 50,70% 8,60% 3,00% 6M 8M259 301 344 259

Sweden (SE) 1186 22,30% 25,90% 29,60% 22,30% 12M 11M212 300 313 160


Taiwan (TW) 2016 33,70% 32,40% 24,60% 9,30% 41M 16M679 245 196 74


Uruguay (UY) 1108 67,50% 20,80% 10,40% 1,40% 7M 1M886 247 39 21



V12 Important: To have [Country nationality] citizenship Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) b. to have [COUNTRY NATIONALITY] citizenship 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”.


1 2 3 4 8 9

V12 (N) % % % % % % 1205 683 157 54

Australia (AU) 2183 57,40% 32,50% 7,50% 2,60% 23M 61M625 271 76 20

Austria (AT) 1006 63,00% 27,30% 7,70% 2,00% 14M 522 403 95 19

Bulgaria (BG) 1069 50,20% 38,80% 9,10% 1,80% 21M 9M923 224 43 12

Canada (CA) 1211 76,80% 18,60% 3,60% 1,00% 6M 3M1025 350 110 14

Chile (CL) 1505 68,40% 23,30% 7,30% 0,90% 2M 4M552 496 126 35


Denmark (DK) 1322 51,40% 33,70% 12,20% 2,70% 6M 21M649 445 163 44

Finland (FI) 1379 49,90% 34,20% 12,50% 3,40% 13M 65M872 443 145 74

France (FR) 1669 56,80% 28,90% 9,50% 4,80% 12M 123M322 334 125 46




Hungary (HU) 1021 41,90% 35,50% 16,70% 5,90% 16M 5M636 328 64 24

Ireland (IE) 1065 60,50% 31,20% 6,10% 2,30% 6M 7M632 292 89 50


Israel Arabs (IL-A) 152 58,60% 30,30% 10,50% 0,70% 566 365 115 28

Japan (JP) 1102 52,70% 34,00% 10,70% 2,60% 20M 8M366 341 217 71

Latvia (LV) 1000 36,80% 34,30% 21,80% 7,10% 3M 2M626 275 79 27

New Zealand (NZ) 1036 62,20% 27,30% 7,80% 2,70% 7M 22M819 473 112 40

Norway (NO) 1469 56,70% 32,80% 7,80% 2,80% 3M 22M666 487 95 15

Poland (PL) 1277 52,70% 38,60% 7,50% 1,20% 14M 652 737 101 16

Portugal (PT) 1602 43,30% 48,90% 6,70% 1,10% 1M 95M883 268 38 9

Philippines (PH) 1200 73,70% 22,40% 3,20% 0,80% 2M 1334 706 202 81

Russia (RU) 2383 57,40% 30,40% 8,70% 3,50% 60M 372 429 240 90


Slovenia (SI) 1093 46,80% 35,30% 12,40% 5,60% 10M 3M1321 950 82 83


South Korea (KR) 1315 48,10% 39,60% 11,50% 0,80% 9M 438 614 109 31

Spain (ES) 1212 36,70% 51,50% 9,10% 2,60% 8M 12M600 357 151 61

Sweden (SE) 1186 51,30% 30,50% 12,90% 5,20% 3M 14M411 376 151 53


Taiwan (TW) 2016 44,60% 35,40% 14,70% 5,30% 36M 19M999 159 37 11


Uruguay (UY) 1108 64,10% 23,70% 11,00% 1,20% 6M 1M874 279 34 10

Venezuela (VE) 1199 73,00% 23,30% 2,80% 0,80% 2M Sum 44170 23365 14272 4124 1341 420M 648M


V13 Important: To have lived in [Country] for most of one’s life Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) c. to have lived in [COUNTRY] for most of one’s life 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”.


1 2 3 4 8 9

V13 (N) % % % % % % 739 691 522 136

Australia (AU) 2183 35,40% 33,10% 25,00% 6,50% 26M 69M453 311 172 49

Austria (AT) 1006 46,00% 31,60% 17,50% 5,00% 21M 563 331 97 14

Bulgaria (BG) 1069 56,00% 32,90% 9,70% 1,40% 42M 22M572 386 202 43

Canada (CA) 1211 47,50% 32,10% 16,80% 3,60% 5M 3M967 390 123 14

Chile (CL) 1505 64,70% 26,10% 8,20% 0,90% 7M 4M506 491 175 45


Denmark (DK) 1322 35,00% 38,10% 23,30% 3,50% 8M 24M333 508 352 97

Finland (FI) 1379 25,80% 39,40% 27,30% 7,50% 13M 76M510 554 293 149

France (FR) 1669 33,90% 36,80% 19,50% 9,90% 22M 141M195 347 214 63




Hungary (HU) 1021 35,80% 40,80% 19,30% 4,10% 24M 6M417 392 183 48

Ireland (IE) 1065 40,10% 37,70% 17,60% 4,60% 8M 17M586 290 132 49


Israel Arabs (IL-A) 152 49,00% 37,70% 10,60% 2,60% 1M 407 379 232 49

Japan (JP) 1102 38,10% 35,50% 21,70% 4,60% 27M 8M364 438 144 44

Latvia (LV) 1000 36,80% 44,20% 14,50% 4,40% 8M 2M420 358 188 45

New Zealand (NZ) 1036 41,50% 35,40% 18,60% 4,50% 7M 18M466 566 337 58

Norway (NO) 1469 32,70% 39,70% 23,60% 4,10% 9M 33M564 484 182 26

Poland (PL) 1277 44,90% 38,50% 14,50% 2,10% 19M 2M561 770 152 21

Portugal (PT) 1602 37,30% 51,20% 10,10% 1,40% 4M 94M764 310 103 15

Philippines (PH) 1200 64,10% 26,00% 8,60% 1,30% 8M 1297 685 266 84

Russia (RU) 2383 55,60% 29,40% 11,40% 3,60% 51M 324 387 287 114


Slovenia (SI) 1093 34,00% 38,90% 19,80% 7,30% 11M 7M1095 1002 172 158


South Korea (KR) 1315 32,10% 36,40% 28,20% 3,30% 5M 384 649 133 26

Spain (ES) 1212 32,20% 54,40% 11,20% 2,20% 6M 14M254 394 362 151

Sweden (SE) 1186 21,90% 33,90% 31,20% 13,00% 7M 18M253 420 265 77

Switzerland (CH) 1037 24,90% 41,40% 26,10% 7,60% 22M 684 760 429 93

Taiwan (TW) 2016 34,80% 38,70% 21,80% 4,70% 32M 18M706 271 200 28


Uruguay (UY) 1108 65,90% 24,30% 9,00% 0,70% 6M 1M888 283 18 8

Venezuela (VE) 1199 74,20% 23,60% 1,50% 0,70% 2MSum 44170 18073 15459 7406 1998 518M 716M


V14 Important: To be able to speak [Country language] Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) d. to be able to speak [COUNTRY LANGUAGE] 2 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”. 2 [dominant language(s)] If two or more languages are recognized nationwide both are included in the question. However, if there is one national lingua franca (Spanish, Russian) just give this language.


V14 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 1354 602 143 28 9M 47M

63,70% 28,30% 6,70% 1,30%Austria (AT) 1006 687 229 70 14 6M

68,70% 22,90% 7,00% 1,40%Bulgaria (BG) 1069 633 351 37 16 13M 19M

61,00% 33,80% 3,60% 1,50%Canada (CA) 1211 833 279 62 26 7M 4M

69,40% 23,20% 5,20% 2,20%Chile (CL) 1505 926 377 162 32 4M 4M


58,30% 33,70% 6,70% 1,40%Denmark (DK) 1322 988 278 26 6 5M 19M

76,10% 21,40% 2,00% 0,50%Finland (FI) 1379 629 488 131 51 12M 68M

48,40% 37,60% 10,10% 3,90%France (FR) 1669 1031 415 65 28 8M 122M




65,10% 25,70% 6,20% 3,00%Hungary (HU) 1021 722 242 33 7 13M 4M

71,90% 24,10% 3,30% 0,70%Ireland (IE) 1065 138 265 378 261 5M 18M

13,20% 25,40% 36,30% 25,00%Israel Jews (IL-J) 1066 759 220 63 22 2M

71,30% 20,70% 5,90% 2,10%Israel Arabs (IL-A) 152 37 40 45 30

24,30% 26,30% 29,60% 19,70%Japan (JP) 1102 492 350 173 59 20M 8M

45,80% 32,60% 16,10% 5,50%Latvia (LV) 1000 522 334 101 41 2M

52,30% 33,50% 10,10% 4,10%New Zealand (NZ) 1036 698 247 51 18 22M

68,80% 24,40% 5,00% 1,80%Norway (NO) 1469 1107 289 35 11 2M 25M

76,80% 20,00% 2,40% 0,80%Poland (PL) 1277 790 405 54 13 12M 3M

62,60% 32,10% 4,30% 1,00%Portugal (PT) 1602 709 716 68 12 97M

47,10% 47,60% 4,50% 0,80%Philippines (PH) 1200 908 237 46 5 4M

75,90% 19,80% 3,80% 0,40%Russia (RU) 2383 1422 556 250 117 38M


55,20% 30,90% 10,20% 3,60%Slovenia (SI) 1093 724 308 37 16 4M 4M


44,60% 43,80% 5,10% 6,40%South Korea (KR) 1315 659 491 146 14 5M

50,30% 37,50% 11,10% 1,10%Spain (ES) 1212 402 602 146 43 4M 15M

33,70% 50,50% 12,20% 3,60%Sweden (SE) 1186 824 303 29 14 3M 13M


51,90% 40,90% 6,90% 0,30%Taiwan (TW) 2016 470 702 607 191 29M 17M

23,90% 35,60% 30,80% 9,70%United States (US) 1216 1011 166 28 8 2M 1M

83,30% 13,70% 2,30% 0,70%Uruguay (UY) 1108 713 241 118 26 7M 3M

64,90% 21,90% 10,70% 2,40%Venezuela (VE) 1199 843 300 37 15 4M

70,50% 25,10% 3,10% 1,30%Sum 44170 25337 12853 3641 1383 286M 670M


V15 Important: To be a [religion] Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) e. to be a [religion] 2

1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”. 2 The dominant religion or denomination in your country should be given (eg. Christian in the US and Canada, Catholic in Ireland and Italy, Russian Orthodox in Russia)].


V15 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 419 349 531 780 51M 53M

20,20% 16,80% 25,50% 37,50%Austria (AT) 1006 282 235 232 224 33M

29,00% 24,20% 23,80% 23,00%Bulgaria (BG) 1069 413 342 142 94 48M 30M

41,70% 34,50% 14,30% 9,50%Canada (CA) 1211 374 268 242 304 19M 4M

31,50% 22,60% 20,40% 25,60%Chile (CL) 1505 526 273 300 377 14M 15M


13,20% 16,10% 30,20% 40,50%Denmark (DK) 1322 207 215 450 398 30M 22M

16,30% 16,90% 35,40% 31,30%Finland (FI) 1379 139 153 309 671 42M 65M

10,90% 12,00% 24,30% 52,80%France (FR) 1669 138 118 236 971 53M 153M




17,90% 16,90% 25,30% 40,00%Hungary (HU) 1021 201 226 334 228 26M 6M

20,30% 22,90% 33,80% 23,10%Ireland (IE) 1065 316 285 212 227 11M 14M


66,40% 17,60% 10,60% 5,30%Israel Arabs (IL-A) 152 17 19 47 69

11,20% 12,50% 30,90% 45,40%Japan (JP) 1102 98 157 382 368 86M 11M

9,80% 15,60% 38,00% 36,60%Latvia (LV) 1000 60 155 382 358 43M 2M

6,30% 16,20% 40,00% 37,50%New Zealand (NZ) 1036 214 156 223 395 19M 29M

21,70% 15,80% 22,60% 40,00%Norway (NO) 1469 118 157 397 682 69M 46M

8,70% 11,60% 29,30% 50,40%Poland (PL) 1277 553 384 202 113 22M 3M

44,20% 30,70% 16,10% 9,00%Portugal (PT) 1602 404 577 246 269 7M 99M

27,00% 38,60% 16,40% 18,00%Philippines (PH) 1200 765 227 98 85 25M

65,10% 19,30% 8,30% 7,20%Russia (RU) 2383 765 544 475 462 137M


24,00% 25,70% 24,00% 26,20%Slovenia (SI) 1093 170 181 293 437 8M 4M


45,10% 33,90% 6,60% 14,40%South Korea (KR) 1315 160 373 517 251 14M

12,30% 28,70% 39,70% 19,30%Spain (ES) 1212 166 358 326 340 7M 15M

13,90% 30,10% 27,40% 28,60%Sweden (SE) 1186 75 118 281 651 32M 29M


16,40% 22,80% 27,30% 33,50%Taiwan (TW) 2016 152 360 769 682 39M 14M


49,60% 16,30% 17,70% 16,40%Uruguay (UY) 1108 183 133 351 432 8M 1M

16,70% 12,10% 31,90% 39,30%Venezuela (VE) 1199 568 283 157 185 4M 2M

47,60% 23,70% 13,20% 15,50%Sum 44170 10721 8887 10047 12614 1131M 770M


V16 Important: To respect [Country nationality] political institutions and laws Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) f. to respect [COUNTRY NATIONALITY] political institutions and laws 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”.


V16 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 1024 874 123 68 35M 59M

49,00% 41,80% 5,90% 3,30%Austria (AT) 1006 440 414 97 24 31M

45,10% 42,50% 9,90% 2,50%Bulgaria (BG) 1069 537 399 71 21 28M 13M

52,20% 38,80% 6,90% 2,00%Canada (CA) 1211 788 369 32 10 6M 6M

65,70% 30,80% 2,70% 0,80%Chile (CL) 1505 906 446 108 29 9M 7M


32,40% 48,50% 14,20% 4,90%Denmark (DK) 1322 876 360 37 11 13M 25M

68,20% 28,00% 2,90% 0,90%Finland (FI) 1379 670 475 119 39 17M 59M

51,40% 36,50% 9,10% 3,00%France (FR) 1669 1183 325 39 19 12M 91M




50,40% 36,00% 9,20% 4,40%Hungary (HU) 1021 392 452 119 26 27M 5M

39,60% 45,70% 12,00% 2,60%Ireland (IE) 1065 379 444 131 79 18M 14M


63,60% 24,30% 8,40% 3,60%Israel Arabs (IL-A) 152 90 51 9 2

59,20% 33,60% 5,90% 1,30%Japan (JP) 1102 240 437 247 83 83M 12M

23,80% 43,40% 24,50% 8,20%Latvia (LV) 1000 359 444 139 44 12M 2M

36,40% 45,00% 14,10% 4,50%New Zealand (NZ) 1036 530 358 68 40 13M 27M

53,20% 35,90% 6,80% 4,00%Norway (NO) 1469 1039 349 38 11 4M 28M

72,30% 24,30% 2,60% 0,80%Poland (PL) 1277 433 590 177 41 32M 4M

34,90% 47,50% 14,30% 3,30%Portugal (PT) 1602 649 729 102 22 5M 95M

43,20% 48,50% 6,80% 1,50%Philippines (PH) 1200 700 378 95 15 12M

58,90% 31,80% 8,00% 1,30%Russia (RU) 2383 1108 765 268 130 112M


23,80% 43,70% 20,30% 12,20%Slovenia (SI) 1093 449 455 122 51 11M 5M


33,70% 45,70% 11,40% 9,20%South Korea (KR) 1315 364 647 245 46 13M

28,00% 49,70% 18,80% 3,50%Spain (ES) 1212 411 672 82 19 8M 20M

34,70% 56,80% 6,90% 1,60%Sweden (SE) 1186 925 206 28 15 7M 5M


35,40% 60,70% 3,00% 0,90%Taiwan (TW) 2016 1085 690 121 41 61M 18M


72,20% 23,90% 3,00% 0,90%Uruguay (UY) 1108 618 335 113 28 11M 3M

56,50% 30,60% 10,30% 2,60%Venezuela (VE) 1199 734 375 64 20 2M 4M

61,50% 31,40% 5,40% 1,70%Sum 44170 21201 16287 3807 1477 764M 634M


V17 Important: To feel [Country nationality] Missing Values: 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) g. to feel [COUNTRY NATIONALITY] 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”.


V17 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 1322 623 103 48 38M 49M

63,10% 29,70% 4,90% 2,30%Austria (AT) 1006 583 287 79 34 23M

59,30% 29,20% 8,00% 3,50%Bulgaria (BG) 1069 798 213 9 3 24M 22M

78,00% 20,80% 0,90% 0,30%Canada (CA) 1211 765 336 77 20 8M 5M

63,90% 28,00% 6,40% 1,70%Chile (CL) 1505 1120 318 46 8 7M 6M


49,60% 38,70% 9,50% 2,20%Denmark (DK) 1322 755 409 116 14 6M 22M

58,30% 31,60% 9,00% 1,10%Finland (FI) 1379 713 412 136 33 22M 63M

55,10% 31,80% 10,50% 2,60%France (FR) 1669 1010 406 82 41 12M 118M




44,00% 35,40% 13,40% 7,20%Hungary (HU) 1021 732 239 23 6 16M 5M

73,20% 23,90% 2,30% 0,60%Ireland (IE) 1065 530 385 95 37 10M 8M


66,40% 24,30% 5,50% 3,90%Israel Arabs (IL-A) 152 42 52 46 12

27,60% 34,20% 30,30% 7,90%Japan (JP) 1102 569 366 104 28 28M 7M

53,30% 34,30% 9,70% 2,60%Latvia (LV) 1000 510 378 81 26 3M 2M

51,30% 38,00% 8,10% 2,60%New Zealand (NZ) 1036 636 279 65 22 12M 22M

63,50% 27,80% 6,50% 2,20%Norway (NO) 1469 710 490 174 50 17M 28M

49,90% 34,40% 12,20% 3,50%Poland (PL) 1277 832 399 35 3 7M 1M

65,60% 31,40% 2,80% 0,20%Portugal (PT) 1602 765 643 84 15 3M 92M

50,80% 42,70% 5,60% 1,00%Philippines (PH) 1200 875 277 37 6 5M

73,20% 23,20% 3,10% 0,50%Russia (RU) 2383 1526 608 119 62 68M


43,70% 30,10% 17,40% 8,80%Slovenia (SI) 1093 562 418 70 32 8M 3M


43,20% 44,40% 6,80% 5,60%South Korea (KR) 1315 742 465 97 8 3M

56,60% 35,40% 7,40% 0,60%Spain (ES) 1212 438 614 106 33 8M 13M

36,80% 51,60% 8,90% 2,80%Sweden (SE) 1186 523 419 139 65 29M 11M


31,30% 43,90% 19,40% 5,30%Taiwan (TW) 2016 1140 665 116 35 40M 20M


68,20% 23,80% 6,80% 1,20%Uruguay (UY) 1108 889 179 20 11 8M 1M

80,90% 16,30% 1,80% 1,00%Venezuela (VE) 1199 912 259 21 5 1M 1M

76,20% 21,60% 1,80% 0,40%Sum 44170 24713 13790 3225 1177 608M 657M


V18 Important: To have [country nationality] ancestry Missing Values: 0; 8; 9 Q3.- Some people say that the following things are important for being truly [NATIONALITY]1. Others say they are not important. How important do you think each of the following is... (Please, tick one box on each line) h. to have [COUNTRY NATIONALITY] ancestry 2 1. Very important. 2. Fairly important. 3. Not very important. 4. Not important at all. 0. Not available (not asked) 8. Can´t choose. 9. Na, refused. Notes: 1 Precode “truly [COUNTRY NATIONALITY]” E.g. “truly British”, American “a true American”. 2 Question not asked in Bulgaria and Latvia


0 1 2 3 4 8 9

V18 (N) % % % % % % % 410 370 667 623

Australia (AU) 2183 19,80% 17,90% 32,20% 30,10% 52M 61M324 231 213 196

Austria (AT) 1006 33,60% 24,00% 22,10% 20,30% 42M

Bulgaria (BG) 1069 1069M - - - - 311 337 362 180

Canada (CA) 1211 26,10% 28,30% 30,40% 15,10% 12M 9M840 380 206 67

Chile (CL) 1505 56,30% 25,50% 13,80% 4,50% 6M 6M347 491 263 92


Denmark (DK) 1322 32,60% 25,70% 31,90% 9,80% 12M 20M344 336 417 200

Finland (FI) 1379 26,50% 25,90% 32,20% 15,40% 21M 61M385 357 384 382

France (FR) 1669 25,50% 23,70% 25,50% 25,30% 27M 134M170 225 256 165




Hungary (HU) 1021 45,40% 33,80% 16,30% 4,50% 19M 4M494 361 137 59

Ireland (IE) 1065 47,00% 34,30% 13,00% 5,60% 6M 8M302 250 294 208


Israel Arabs (IL-A) 152 18,40% 21,70% 30,90% 28,90% 448 320 211 86

Japan (JP) 1102 42,10% 30,00% 19,80% 8,10% 30M 7M

Latvia (LV) 1000 1000M - - - - 347 251 246 152

New Zealand (NZ) 1036 34,80% 25,20% 24,70% 15,30% 16M 24M418 356 409 234

Norway (NO) 1469 29,50% 25,10% 28,90% 16,50% 23M 29M609 455 164 28

Poland (PL) 1277 48,50% 36,20% 13,10% 2,20% 21M 532 727 188 59

Portugal (PT) 1602 35,30% 48,30% 12,50% 3,90% 2M 94M861 276 53 7

Philippines (PH) 1200 71,90% 23,10% 4,40% 0,60% 3M 1032 741 364 181

Russia (RU) 2383 44,50% 32,00% 15,70% 7,80% 65M 240 324 359 192


Slovenia (SI) 1093 24,00% 30,60% 27,00% 18,40% 10M 6M1025 986 189 204


South Korea (KR) 1315 36,10% 37,20% 23,20% 3,50% 6M 293 648 181 67

Spain (ES) 1212 24,60% 54,50% 15,20% 5,60% 4M 19M163 186 348 466

Sweden (SE) 1186 14,00% 16,00% 29,90% 40,10% 16M 7M132 259 339 241


Taiwan (TW) 2016 22,30% 29,00% 34,30% 14,30% 48M 17M388 267 368 164


Uruguay (UY) 1108 45,50% 23,70% 23,50% 7,40% 8M 1M721 313 103 43

Venezuela (VE) 1199 61,10% 26,50% 8,70% 3,60% 12M 7MSum 44170 2069M 14046 12115 9217 5342 694M 687M


V19 I would rather be a citizen of [Country] than of any other country in the world Missing Values: 8; 9 Q. 4. How much do you agree or disagree with the following statements? (Please, tick one box on each line) a. I would rather be a citizen of [COUNTRY] than of any other country in the world 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused


V19 (N) 1 2 3 4 5 8 9

% % % % % % % Australia (AU) 2183 1345 486 209 65 17 22M 39M

63,40% 22,90% 9,80% 3,10% 0,80%Austria (AT) 1006 498 270 104 65 48 21M

50,60% 27,40% 10,60% 6,60% 4,90%Bulgaria (BG) 1069 568 265 109 59 34 21M 13M

54,90% 25,60% 10,50% 5,70% 3,30%Canada (CA) 1211 704 330 130 24 13 6M 4M

58,60% 27,50% 10,80% 2,00% 1,10%Chile (CL) 1505 666 589 148 68 14 16M 4M

44,80% 39,70% 10,00% 4,60% 0,90%Czech Republic (CZ) 1276 371 463 261 73 29 11M 68M

31,00% 38,70% 21,80% 6,10% 2,40%Denmark (DK) 1322 721 341 130 42 44 27M 17M

56,40% 26,70% 10,20% 3,30% 3,40%Finland (FI) 1379 753 344 162 55 17 17M 31M

56,60% 25,80% 12,20% 4,10% 1,30%France (FR) 1669 547 387 427 75 114 34M 85M

35,30% 25,00% 27,50% 4,80% 7,40%Germany-West (DE-W) 850 182 289 174 99 57 44M 5M

22,70% 36,10% 21,70% 12,40% 7,10%Germany-East (DE-E) 437 75 171 87 47 37 18M 2M

18,00% 41,00% 20,90% 11,30% 8,90%Great Britain (GB) 873 348 268 172 57 8 9M 11M

40,80% 31,40% 20,20% 6,70% 0,90%Hungary (HU) 1021 517 355 107 25 4 9M 4M

51,30% 35,20% 10,60% 2,50% 0,40%Ireland (IE) 1065 426 445 124 60 8 1M 1M

40,10% 41,90% 11,70% 5,60% 0,80%Israel Jews (IL-J) 1066 591 250 136 61 22 2M 4M

55,80% 23,60% 12,80% 5,80% 2,10%Israel Arabs (IL-A) 152 54 51 29 17 1

35,50% 33,60% 19,10% 11,20% 0,70%Japan (JP) 1102 667 233 91 45 46 16M 4M

61,60% 21,50% 8,40% 4,20% 4,30%Latvia (LV) 1000 120 295 306 169 44 66M

12,80% 31,60% 32,80% 18,10% 4,70%New Zealand (NZ) 1036 542 287 149 31 5 6M 16M

53,50% 28,30% 14,70% 3,10% 0,50%Norway (NO) 1469 440 517 344 119 28 10M 11M

30,40% 35,70% 23,80% 8,20% 1,90%Poland (PL) 1277 520 467 173 64 18 35M

41,90% 37,60% 13,90% 5,20% 1,40%Portugal (PT) 1602 540 701 164 80 15 9M 93M

36,00% 46,70% 10,90% 5,30% 1,00%Philippines (PH) 1200 580 440 124 39 11 6M

48,60% 36,90% 10,40% 3,30% 0,90%Russia (RU) 2383 1002 761 305 107 87 121M

44,30% 33,60% 13,50% 4,70% 3,80%Slovak Republic (SK) 1152 281 315 364 125 32 30M 5M

25,20% 28,20% 32,60% 11,20% 2,90%Slovenia (SI) 1093 426 339 169 110 41 8M

39,30% 31,20% 15,60% 10,10% 3,80%South Africa (ZA) 2483 1023 1012 165 160 47 49M 27M

42,50% 42,00% 6,90% 6,60% 2,00%South Korea (KR) 1315 488 438 258 118 11 2M

37,20% 33,40% 19,60% 9,00% 0,80%Spain (ES) 1212 243 645 212 71 23 7M 11M

20,40% 54,00% 17,80% 5,90% 1,90%Sweden (SE) 1186 338 372 346 63 33 30M 4M

29,30% 32,30% 30,00% 5,50% 2,90%Switzerland (CH) 1037 198 348 183 185 59 60M 4M

20,30% 35,80% 18,80% 19,00% 6,10%Taiwan (TW) 2016 527 1024 276 120 6 50M 13M

27,00% 52,40% 14,10% 6,10% 0,30%United States (US) 1216 896 183 85 27 8 16M 1M

74,70% 15,30% 7,10% 2,30% 0,70%Uruguay (UY) 1108 475 367 168 65 18 12M 3M

43,50% 33,60% 15,40% 5,90% 1,60%Venezuela (VE) 1199 479 591 14 86 19 5M 5M

40,30% 49,70% 1,20% 7,20% 1,60%Sum 44170 18151 14639 6405 2676 1018 796M 485M


V20 There are some things about [Country] today that make me feel ashamed of [Country] Missing Values: 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) b. There are some things about [COUNTRY] today that make me feel ashamed of [COUNTRY] 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V20 (N) % % % % % % % 255 754 428 485 174

Australia (AU) 2183 12,20% 36,00% 20,40% 23,10% 8,30% 37M 50M90 248 170 283 175

Austria (AT) 1006 9,30% 25,70% 17,60% 29,30% 18,10% 40M 279 463 130 66 70

Bulgaria (BG) 1069 27,70% 45,90% 12,90% 6,50% 6,90% 38M 23M145 436 269 242 89

Canada (CA) 1211 12,30% 36,90% 22,80% 20,50% 7,50% 21M 9M201 627 277 314 52

Chile (CL) 1505 13,70% 42,60% 18,80% 21,30% 3,50% 27M 7M389 511 227 87 18

Czech Republic (CZ) 1276 31,60% 41,50% 18,40% 7,10% 1,50% 11M 33M266 440 196 143 227

Denmark (DK) 1322 20,90% 34,60% 15,40% 11,20% 17,80% 29M 21M121 424 344 278 83

Finland (FI) 1379 9,70% 33,90% 27,50% 22,20% 6,60% 69M 60M375 477 284 216 194

France (FR) 1669 24,30% 30,90% 18,40% 14,00% 12,50% 27M 96M80 324 136 194 76

Germany-West (DE-W) 850 9,90% 40,00% 16,80% 24,00% 9,40% 36M 4M47 207 63 70 30

Germany-East (DE-E) 437 11,30% 49,60% 15,10% 16,80% 7,20% 18M 2M153 479 141 58 12

Great Britain (GB) 873 18,10% 56,80% 16,70% 6,90% 1,40% 10M 20M73 235 289 231 173

Hungary (HU) 1021 7,30% 23,50% 28,90% 23,10% 17,30% 15M 5M158 590 127 159 20

Ireland (IE) 1065 15,00% 56,00% 12,00% 15,10% 1,90% 9M 2M281 410 174 123 74

Israel Jews (IL-J) 1066 26,50% 38,60% 16,40% 11,60% 7,00% 3M 1M28 54 47 19 4

Israel Arabs (IL-A) 152 18,40% 35,50% 30,90% 12,50% 2,60% 344 383 173 69 74

Japan (JP) 1102 33,00% 36,70% 16,60% 6,60% 7,10% 54M 5M138 459 209 134 18

Latvia (LV) 1000 14,40% 47,90% 21,80% 14,00% 1,90% 42M 162 437 207 148 49

New Zealand (NZ) 1036 16,20% 43,60% 20,60% 14,80% 4,90% 13M 20M199 650 324 199 34

Norway (NO) 1469 14,20% 46,20% 23,00% 14,20% 2,40% 37M 26M278 660 154 88 31

Poland (PL) 1277 23,00% 54,50% 12,70% 7,30% 2,60% 65M 1M280 636 274 226 77

Portugal (PT) 1602 18,80% 42,60% 18,40% 15,10% 5,20% 14M 95M155 372 324 226 95

Philippines (PH) 1200 13,20% 31,70% 27,60% 19,30% 8,10% 28M 917 952 255 112 39

Russia (RU) 2383 40,30% 41,80% 11,20% 4,90% 1,70% 108M 328 486 235 62 18

Slovak Republic (SK) 1152 29,10% 43,00% 20,80% 5,50% 1,60% 18M 5M56 241 215 415 143

Slovenia (SI) 1093 5,20% 22,50% 20,10% 38,80% 13,40% 22M 1M510 1120 239 397 101

South Africa (ZA) 2483 21,50% 47,30% 10,10% 16,80% 4,30% 89M 27M230 626 224 131 88

South Korea (KR) 1315 17,70% 48,20% 17,20% 10,10% 6,80% 16M 52 374 280 375 103

Spain (ES) 1212 4,40% 31,60% 23,60% 31,70% 8,70% 12M 16M257 605 211 51 18

Sweden (SE) 1186 22,50% 53,00% 18,50% 4,50% 1,60% 36M 8M57 551 139 214 41

Switzerland (CH) 1037 5,70% 55,00% 13,90% 21,40% 4,10% 34M 1M190 963 385 315 48

Taiwan (TW) 2016 10,00% 50,70% 20,30% 16,60% 2,50% 94M 21M219 455 228 197 103

United States (US) 1216 18,20% 37,90% 19,00% 16,40% 8,60% 13M 1M241 532 96 179 44

Uruguay (UY) 1108 22,10% 48,70% 8,80% 16,40% 4,00% 14M 2M84 342 10 571 174

Venezuela (VE) 1199 7,10% 29,00% 0,80% 48,30% 14,70% 5M 13MSum 44170 7638 17523 7484 7077 2769 1104M 575M


V21 The world would be a better place if people from other countries were more like the [Country nationality] Missing Values: 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) c. The world would be a better place if people from other countries were more like the [COUNTRY NATIONALITY] 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V21 (N) % % % % % % % 292 634 719 353 81

Australia (AU) 2183 14,00% 30,50% 34,60% 17,00% 3,90% 53M 51M152 323 263 129 79

Austria (AT) 1006 16,10% 34,10% 27,80% 13,60% 8,40% 60M 81 198 288 187 142

Bulgaria (BG) 1069 9,00% 22,10% 32,10% 20,90% 15,80% 150M 23M217 464 342 129 32

Canada (CA) 1211 18,30% 39,20% 28,90% 10,90% 2,70% 23M 4M164 523 382 344 44

Chile (CL) 1505 11,30% 35,90% 26,20% 23,60% 3,00% 39M 9M56 233 482 298 120


Denmark (DK) 1322 14,50% 26,70% 26,00% 14,30% 18,40% 53M 21M78 208 456 358 120

Finland (FI) 1379 6,40% 17,00% 37,40% 29,30% 9,80% 100M 59M103 185 543 306 390

France (FR) 1669 6,70% 12,10% 35,60% 20,00% 25,50% 48M 94M31 122 271 228 120




Hungary (HU) 1021 8,10% 22,60% 37,60% 23,20% 8,50% 91M 6M59 281 316 349 36

Ireland (IE) 1065 5,70% 27,00% 30,40% 33,50% 3,50% 22M 2M78 156 320 322 172


Israel Arabs (IL-A) 152 10,50% 26,30% 40,80% 17,80% 4,60% 142 151 396 120 192

Japan (JP) 1102 14,20% 15,10% 39,60% 12,00% 19,20% 95M 6M15 95 302 333 137

Latvia (LV) 1000 1,70% 10,80% 34,20% 37,80% 15,50% 118M 116 286 389 180 31

New Zealand (NZ) 1036 11,60% 28,50% 38,80% 18,00% 3,10% 21M 13M57 217 495 461 166

Norway (NO) 1469 4,10% 15,50% 35,50% 33,00% 11,90% 56M 17M79 257 456 289 52

Poland (PL) 1277 7,00% 22,70% 40,20% 25,50% 4,60% 143M 1M112 515 431 292 76

Portugal (PT) 1602 7,90% 36,10% 30,20% 20,50% 5,30% 74M 102M233 370 360 179 36

Philippines (PH) 1200 19,80% 31,40% 30,60% 15,20% 3,10% 22M 229 452 619 485 260

Russia (RU) 2383 11,20% 22,10% 30,30% 23,70% 12,70% 338M 30 184 405 363 71


Slovenia (SI) 1093 6,20% 20,10% 26,50% 36,20% 10,90% 49M 1M473 908 394 428 74


South Korea (KR) 1315 7,00% 17,60% 38,30% 31,00% 6,20% 22M 101 431 334 273 45

Spain (ES) 1212 8,50% 36,40% 28,20% 23,10% 3,80% 15M 13M50 161 412 300 179

Sweden (SE) 1186 4,50% 14,60% 37,40% 27,20% 16,20% 79M 5M30 174 182 483 120


Taiwan (TW) 2016 5,90% 29,80% 28,70% 31,20% 4,50% 90M 18M190 296 419 224 68


Uruguay (UY) 1108 13,00% 29,20% 27,30% 25,00% 5,50% 33M 5M126 475 28 455 89



V22 Generally speaking, [Country] is a better country than most other countries Missing Values: 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) d. Generally speaking, [COUNTRY] is a better country than most other countries 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V22 (N) % % % % % % % 758 993 274 83 12

Australia (AU) 2183 35,80% 46,80% 12,90% 3,90% 0,60% 23M 40M237 416 194 77 41

Austria (AT) 1006 24,60% 43,10% 20,10% 8,00% 4,20% 41M 144 279 223 178 131

Bulgaria (BG) 1069 15,10% 29,20% 23,40% 18,60% 13,70% 99M 15M364 586 178 54 12

Canada (CA) 1211 30,50% 49,10% 14,90% 4,50% 1,00% 14M 3M244 606 347 241 19

Chile (CL) 1505 16,70% 41,60% 23,80% 16,50% 1,30% 42M 6M72 277 495 257 96


Denmark (DK) 1322 29,60% 38,10% 18,20% 8,50% 5,70% 32M 21M260 601 282 112 27

Finland (FI) 1379 20,30% 46,90% 22,00% 8,70% 2,10% 44M 53M178 465 511 211 172

France (FR) 1669 11,60% 30,30% 33,20% 13,70% 11,20% 33M 99M56 261 238 157 85




Hungary (HU) 1021 7,80% 25,90% 34,50% 24,30% 7,60% 63M 7M106 471 218 225 16

Ireland (IE) 1065 10,20% 45,50% 21,00% 21,70% 1,50% 21M 8M230 281 258 205 73


Israel Arabs (IL-A) 152 19,10% 42,10% 26,30% 9,90% 2,60% 420 396 177 33 45

Japan (JP) 1102 39,20% 37,00% 16,50% 3,10% 4,20% 28M 3M29 227 302 275 84

Latvia (LV) 1000 3,20% 24,80% 32,90% 30,00% 9,20% 83M 289 467 187 62 4

New Zealand (NZ) 1036 28,60% 46,30% 18,50% 6,10% 0,40% 12M 15M202 675 372 139 28

Norway (NO) 1469 14,30% 47,70% 26,30% 9,80% 2,00% 36M 17M81 302 405 338 41

Poland (PL) 1277 6,90% 25,90% 34,70% 29,00% 3,50% 109M 1M138 486 362 346 90

Portugal (PT) 1602 9,70% 34,20% 25,50% 24,30% 6,30% 75M 105M263 380 317 179 41

Philippines (PH) 1200 22,30% 32,20% 26,90% 15,20% 3,50% 20M 424 628 539 392 168

Russia (RU) 2383 19,70% 29,20% 25,10% 18,20% 7,80% 232M 32 185 426 349 83


Slovenia (SI) 1093 6,50% 23,50% 32,00% 30,40% 7,60% 25M 4M603 1024 317 314 51


South Korea (KR) 1315 10,90% 33,30% 29,20% 23,40% 3,10% 9M 126 451 303 256 46

Spain (ES) 1212 10,70% 38,20% 25,60% 21,70% 3,90% 16M 14M106 359 417 175 81

Sweden (SE) 1186 9,30% 31,50% 36,60% 15,40% 7,10% 43M 5M35 220 173 436 136


Taiwan (TW) 2016 9,00% 52,50% 22,20% 15,00% 1,20% 64M 18M487 456 187 58 9


Uruguay (UY) 1108 13,60% 36,20% 23,60% 22,60% 4,10% 24M 3M379 613 13 150 20



V23 People should support their country even if the country is in the wrong. Missing Values: 0; 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) e. People should support their country even if the country is in the wrong1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (not asked). 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Bulgaria because of technical reasons


0 1 2 3 4 5 8 9

V23 (N) % % % % % % % % 151 418 540 780 194

Australia (AU) 2183 7,20% 20,10% 25,90% 37,40% 9,30% 50M 50M93 231 206 237 187

Austria (AT) 1006 9,70% 24,20% 21,60% 24,80% 19,60% 52M

Bulgaria (BG) 1069 1069M - - - - - 44 182 228 596 134

Canada (CA) 1211 3,70% 15,40% 19,30% 50,30% 11,30% 20M 7M290 645 242 246 40

Chile (CL) 1505 19,80% 44,10% 16,50% 16,80% 2,70% 33M 9M128 384 371 226 68


Denmark (DK) 1322 14,60% 29,20% 12,40% 19,30% 24,40% 24M 21M61 145 271 569 218

Finland (FI) 1379 4,80% 11,50% 21,40% 45,00% 17,20% 54M 61M127 251 285 416 476

France (FR) 1669 8,20% 16,10% 18,30% 26,80% 30,60% 21M 93M44 163 133 273 196




Hungary (HU) 1021 17,50% 47,70% 23,40% 9,80% 1,60% 37M 5M35 180 151 570 100

Ireland (IE) 1065 3,40% 17,40% 14,60% 55,00% 9,70% 23M 6M288 346 177 181 69


Israel Arabs (IL-A) 152 12,60% 15,90% 29,80% 35,10% 6,60% 1M114 143 252 182 350

Japan (JP) 1102 11,00% 13,70% 24,20% 17,50% 33,60% 56M 5M26 144 185 435 148

Latvia (LV) 1000 2,80% 15,40% 19,70% 46,40% 15,80% 62M 61 151 202 458 135

New Zealand (NZ) 1036 6,10% 15,00% 20,10% 45,50% 13,40% 13M 16M52 208 291 621 270

Norway (NO) 1469 3,60% 14,40% 20,20% 43,10% 18,70% 13M 14M136 368 251 394 62

Poland (PL) 1277 11,20% 30,40% 20,70% 32,50% 5,10% 65M 1M193 516 306 335 88

Portugal (PT) 1602 13,40% 35,90% 21,30% 23,30% 6,10% 63M 101M108 183 234 419 239

Philippines (PH) 1200 9,10% 15,50% 19,80% 35,40% 20,20% 17M 580 693 410 333 185

Russia (RU) 2383 26,40% 31,50% 18,60% 15,10% 8,40% 182M 60 260 301 383 72


Slovenia (SI) 1093 13,00% 37,40% 20,00% 23,10% 6,50% 22M 1M367 785 261 620 314


South Korea (KR) 1315 23,80% 33,00% 16,80% 21,30% 5,10% 11M 83 403 245 378 79

Spain (ES) 1212 7,00% 33,90% 20,60% 31,80% 6,60% 8M 16M30 130 280 463 235

Sweden (SE) 1186 2,60% 11,40% 24,60% 40,70% 20,70% 40M 8M65 537 126 244 45


Taiwan (TW) 2016 3,70% 22,70% 14,00% 47,40% 12,20% 114M 22M135 299 268 382 109


Uruguay (UY) 1108 14,60% 32,90% 14,10% 29,70% 8,70% 28M 3M266 651 6 219 30

Venezuela (VE) 1199 22,70% 55,50% 0,50% 18,70% 2,60% 14M 13MSum 44170 1069M 4653 11110 7740 12667 4998 1329M 604M


V24 When my country does well in international sports, it makes me proud to be [Country nationality] Missing Values: 0; 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) f. When my country does well in international sports, it makes me proud to be [COUNTRY NATIONALITY]1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Bulgaria because of technical reasons


0 1 2 3 4 5 8 9

V24 (N) % % % % % % % % 732 933 341 75 36

Australia (AU) 2183 34,60% 44,10% 16,10% 3,50% 1,70% 19M 47M431 301 116 67 71

Austria (AT) 1006 43,70% 30,50% 11,80% 6,80% 7,20% 20M

Bulgaria (BG) 1069 1069M - - - - - 469 551 144 26 11

Canada (CA) 1211 39,10% 45,90% 12,00% 2,20% 0,90% 7M 3M552 660 206 52 10

Chile (CL) 1505 37,30% 44,60% 13,90% 3,50% 0,70% 19M 6M637 417 127 26 12


Denmark (DK) 1322 53,00% 25,40% 14,00% 2,60% 4,90% 18M 19M393 549 264 63 31

Finland (FI) 1379 30,20% 42,20% 20,30% 4,80% 2,40% 28M 51M439 551 369 60 126

France (FR) 1669 28,40% 35,70% 23,90% 3,90% 8,20% 38M 86M135 317 193 99 64




Hungary (HU) 1021 56,30% 34,20% 7,70% 1,10% 0,70% 8M 4M590 414 39 12

Ireland (IE) 1065 55,90% 39,20% 3,70% 1,10% - 6M 4M546 267 142 50 45



Japan (JP) 1102 62,10% 28,30% 4,60% 2,50% 2,60% 21M 5M353 521 84 15 8

Latvia (LV) 1000 36,00% 53,10% 8,60% 1,50% 0,80% 19M 423 433 124 25 9

New Zealand (NZ) 1036 41,70% 42,70% 12,20% 2,50% 0,90% 6M 16M317 701 297 82 43

Norway (NO) 1469 22,00% 48,70% 20,60% 5,70% 3,00% 15M 14M619 524 88 17 3

Poland (PL) 1277 49,50% 41,90% 7,00% 1,40% 0,20% 25M 1M633 681 136 32 12

Portugal (PT) 1602 42,40% 45,60% 9,10% 2,10% 0,80% 12M 96M544 464 135 38 11

Philippines (PH) 1200 45,60% 38,90% 11,30% 3,20% 0,90% 8M 1329 697 186 31 20

Russia (RU) 2383 58,70% 30,80% 8,20% 1,40% 0,90% 120M 531 442 125 21 4


Slovenia (SI) 1093 49,00% 40,40% 6,60% 3,00% 1,00% 9M 1M1075 1113 144 40 11


South Korea (KR) 1315 49,90% 40,40% 7,80% 1,50% 0,50% 7M 207 667 218 75 18

Spain (ES) 1212 17,50% 56,30% 18,40% 6,30% 1,50% 11M 16M335 558 217 30 25

Sweden (SE) 1186 28,80% 47,90% 18,60% 2,60% 2,10% 19M 2M204 375 155 187 56


Taiwan (TW) 2016 48,30% 47,20% 3,20% 1,10% 0,10% 18M 14M415 494 246 28 14


Uruguay (UY) 1108 43,20% 44,90% 7,90% 3,00% 1,00% 9M 4M636 531 2 23 3

Venezuela (VE) 1199 53,20% 44,40% 0,20% 1,90% 0,30% 3M 1MSum 44170 1069M 17415 17191 5046 1435 793 701M 520M


V25 I am often less proud of [Country] than I would like to be Missing Values: 8; 9 Q4.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) g. I am often less proud of [COUNTRY] than I would like to be. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V25 (N) % % % % % % % 103 397 467 841 270

Australia (AU) 2183 5,00% 19,10% 22,50% 40,50% 13,00% 50M 55M55 191 250 288 166

Austria (AT) 1006 5,80% 20,10% 26,30% 30,30% 17,50% 56M 308 381 143 108 55

Bulgaria (BG) 1069 31,00% 38,30% 14,40% 10,90% 5,50% 47M 27M54 314 292 445 79

Canada (CA) 1211 4,60% 26,50% 24,70% 37,60% 6,70% 21M 6M139 556 328 396 55

Chile (CL) 1505 9,40% 37,70% 22,30% 26,90% 3,70% 26M 5M164 432 416 162 36


Denmark (DK) 1322 11,40% 28,10% 22,20% 17,80% 20,50% 65M 20M174 371 458 190 49

Finland (FI) 1379 14,00% 29,90% 36,90% 15,30% 3,90% 84M 53M241 542 420 217 96

France (FR) 1669 15,90% 35,80% 27,70% 14,30% 6,30% 51M 102M39 215 273 178 62




Hungary (HU) 1021 7,20% 31,10% 35,80% 19,40% 6,50% 42M 5M78 465 161 316 24

Ireland (IE) 1065 7,50% 44,50% 15,40% 30,30% 2,30% 18M 3M220 460 163 150 60

Israel Jews (IL-J) 1066 20,90% 43,70% 15,50% 14,20% 5,70% 6M 7M22 56 54 18

Israel Arabs (IL-A) 152 14,70% 37,30% 36,00% 12,00% - 1M 1M364 379 174 53 67

Japan (JP) 1102 35,10% 36,50% 16,80% 5,10% 6,50% 60M 5M86 406 305 112 23

Latvia (LV) 1000 9,20% 43,60% 32,70% 12,00% 2,50% 68M 41 245 258 379 78

New Zealand (NZ) 1036 4,10% 24,50% 25,80% 37,90% 7,80% 18M 17M35 299 509 482 79

Norway (NO) 1469 2,50% 21,30% 36,30% 34,30% 5,60% 44M 21M617 566 56 9

Poland (PL) 1277 49,40% 45,40% 4,50% 0,70% - 29M 550 710 170 53 8

Portugal (PT) 1602 36,90% 47,60% 11,40% 3,60% 0,50% 13M 98M156 313 357 248 93

Philippines (PH) 1200 13,40% 26,80% 30,60% 21,30% 8,00% 33M 938 869 273 121 44

Russia (RU) 2383 41,80% 38,70% 12,20% 5,40% 2,00% 138M 101 401 376 186 26


Slovenia (SI) 1093 9,50% 35,30% 26,50% 24,80% 3,90% 26M 1M336 849 360 624 179


South Korea (KR) 1315 9,80% 50,10% 27,00% 10,80% 2,30% 14M 59 351 352 322 94

Spain (ES) 1212 5,00% 29,80% 29,90% 27,30% 8,00% 12M 22M38 273 496 251 68

Sweden (SE) 1186 3,40% 24,20% 44,00% 22,30% 6,00% 55M 5M26 437 237 253 22


Taiwan (TW) 2016 10,30% 54,40% 22,80% 11,60% 0,90% 145M 23M71 314 256 453 107


Uruguay (UY) 1108 15,30% 39,80% 16,60% 23,30% 5,00% 20M 3M76 399 11 539 135



V26 How proud: The way democracy works Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). a. the way democracy works 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


1 2 3 4 8 9

V26 (N) % % % % % % 521 1130 277 58

Australia (AU) 2183 26,20% 56,90% 13,90% 2,90% 144M 53M156 505 215 47

Austria (AT) 1006 16,90% 54,70% 23,30% 5,10% 83M 8 82 325 550

Bulgaria (BG) 1069 0,80% 8,50% 33,70% 57,00% 87M 17M224 726 172 34

Canada (CA) 1211 19,40% 62,80% 14,90% 2,90% 50M 5M177 582 550 103

Chile (CL) 1505 12,50% 41,20% 39,00% 7,30% 72M 21M37 303 585 286


Denmark (DK) 1322 24,80% 56,90% 17,00% 1,20% 54M 16M162 646 356 71

Finland (FI) 1379 13,10% 52,30% 28,80% 5,70% 88M 56M111 764 419 210

France (FR) 1669 7,40% 50,80% 27,90% 14,00% 76M 89M88 363 251 69




Hungary (HU) 1021 2,10% 34,60% 52,10% 11,10% 77M 8M158 501 275 72

Ireland (IE) 1065 15,70% 49,80% 27,30% 7,20% 57M 2M120 309 415 210


Israel Arabs (IL-A) 152 24,30% 40,80% 19,10% 15,80% 89 515 285 50

Japan (JP) 1102 9,50% 54,80% 30,40% 5,30% 156M 7M78 252 406 218

Latvia (LV) 1000 8,20% 26,40% 42,60% 22,90% 45M 1M121 547 212 55

New Zealand (NZ) 1036 12,90% 58,50% 22,70% 5,90% 73M 28M176 757 389 66

Norway (NO) 1469 12,70% 54,50% 28,00% 4,80% 57M 24M25 233 656 230

Poland (PL) 1277 2,20% 20,40% 57,30% 20,10% 131M 2M68 509 594 290

Portugal (PT) 1602 4,70% 34,80% 40,70% 19,80% 50M 91M211 423 391 156

Philippines (PH) 1200 17,90% 35,80% 33,10% 13,20% 19M 55 303 811 770

Russia (RU) 2383 2,80% 15,60% 41,80% 39,70% 444M 9 170 589 350


Slovenia (SI) 1093 4,40% 23,30% 58,10% 14,20% 53M 3M595 793 534 336


South Korea (KR) 1315 4,20% 29,10% 55,60% 11,20% 42M 154 625 287 115

Spain (ES) 1212 13,00% 52,90% 24,30% 9,70% 19M 12M145 613 320 50

Sweden (SE) 1186 12,90% 54,30% 28,40% 4,40% 55M 3M220 612 141 17


Taiwan (TW) 2016 9,10% 31,70% 30,80% 28,40% 205M 37M379 640 109 22


Uruguay (UY) 1108 20,00% 40,20% 32,30% 7,50% 24M 1M260 362 332 219



V27 How proud: Its political influence in the world Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). b. its political influence in the world 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


1 2 3 4 8 9

V27 (N) % % % % % % 186 971 600 186

Australia (AU) 2183 9,60% 50,00% 30,90% 9,60% 176M 64M79 370 333 70

Austria (AT) 1006 9,30% 43,40% 39,10% 8,20% 154M 15 144 378 372

Bulgaria (BG) 1069 1,70% 15,80% 41,60% 40,90% 140M 20M160 665 268 41

Canada (CA) 1211 14,10% 58,60% 23,60% 3,60% 73M 4M241 553 437 105

Chile (CL) 1505 18,00% 41,40% 32,70% 7,90% 137M 32M24 301 596 247


Denmark (DK) 1322 8,40% 49,10% 37,50% 5,00% 135M 24M69 457 507 140

Finland (FI) 1379 5,90% 39,00% 43,20% 11,90% 140M 66M127 864 319 112

France (FR) 1669 8,90% 60,80% 22,40% 7,90% 142M 105M60 356 273 62




Hungary (HU) 1021 2,80% 30,20% 53,50% 13,40% 160M 13M159 557 211 60

Ireland (IE) 1065 16,10% 56,40% 21,40% 6,10% 74M 4M100 278 451 196


Israel Arabs (IL-A) 152 15,80% 30,30% 38,80% 15,10% 45 276 435 156

Japan (JP) 1102 4,90% 30,30% 47,70% 17,10% 184M 6M27 218 391 273

Latvia (LV) 1000 3,00% 24,00% 43,00% 30,00% 90M 1M112 502 235 72

New Zealand (NZ) 1036 12,20% 54,50% 25,50% 7,80% 85M 30M85 673 492 113

Norway (NO) 1469 6,20% 49,40% 36,10% 8,30% 85M 21M38 423 539 121

Poland (PL) 1277 3,40% 37,70% 48,10% 10,80% 155M 1M62 464 581 276

Portugal (PT) 1602 4,50% 33,60% 42,00% 20,00% 119M 100M115 294 498 264

Philippines (PH) 1200 9,80% 25,10% 42,50% 22,50% 29M 135 627 762 476

Russia (RU) 2383 6,80% 31,40% 38,10% 23,80% 383M 17 214 595 253


Slovenia (SI) 1093 3,70% 30,90% 52,10% 13,30% 80M 1M490 834 527 257


South Korea (KR) 1315 1,90% 15,20% 58,40% 24,50% 54M 114 525 355 115

Spain (ES) 1212 10,30% 47,30% 32,00% 10,40% 82M 21M45 435 485 88

Sweden (SE) 1186 4,30% 41,30% 46,10% 8,40% 127M 6M53 461 356 66


Taiwan (TW) 2016 3,50% 19,60% 31,10% 45,80% 246M 42M263 632 220 36


Uruguay (UY) 1108 7,90% 27,10% 44,00% 21,00% 64M 4M250 373 301 218



V28 How proud: [Country’s] economic achievements Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). c. [COUNTRY’s] economic achievements 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


1 2 3 4 8 9

V28 (N) % % % % % % 448 1249 261 43

Australia (AU) 2183 22,40% 62,40% 13,00% 2,10% 124M 58M200 530 159 29

Austria (AT) 1006 21,80% 57,70% 17,30% 3,20% 88M 7 56 283 611

Bulgaria (BG) 1069 0,70% 5,90% 29,60% 63,80% 95M 17M170 759 187 23

Canada (CA) 1211 14,90% 66,60% 16,40% 2,00% 66M 6M360 694 316 49

Chile (CL) 1505 25,40% 48,90% 22,30% 3,50% 72M 14M23 162 535 463


Denmark (DK) 1322 12,70% 55,90% 27,60% 3,80% 149M 30M171 675 306 61

Finland (FI) 1379 14,10% 55,60% 25,20% 5,00% 95M 71M32 428 662 312

France (FR) 1669 2,20% 29,80% 46,20% 21,80% 115M 120M91 354 253 87




Hungary (HU) 1021 3,60% 34,90% 48,70% 12,80% 73M 8M348 549 103 33

Ireland (IE) 1065 33,70% 53,10% 10,00% 3,20% 29M 3M91 248 356 352


Israel Arabs (IL-A) 152 14,50% 22,40% 32,90% 30,30% 122 464 279 94

Japan (JP) 1102 12,70% 48,40% 29,10% 9,80% 138M 5M38 183 447 295

Latvia (LV) 1000 3,90% 19,00% 46,40% 30,60% 36M 1M128 575 197 45

New Zealand (NZ) 1036 13,50% 60,80% 20,80% 4,80% 71M 20M272 717 339 51

Norway (NO) 1469 19,70% 52,00% 24,60% 3,70% 66M 24M18 298 599 213

Poland (PL) 1277 1,60% 26,40% 53,10% 18,90% 147M 2M31 286 669 457

Portugal (PT) 1602 2,10% 19,80% 46,40% 31,70% 66M 93M168 372 380 262

Philippines (PH) 1200 14,20% 31,50% 32,10% 22,20% 18M 59 326 878 860

Russia (RU) 2383 2,80% 15,40% 41,40% 40,50% 260M 18 237 497 331


Slovenia (SI) 1093 5,20% 41,60% 42,60% 10,60% 62M 4M565 911 447 226


South Korea (KR) 1315 6,30% 39,10% 45,40% 9,20% 21M 156 653 259 62

Spain (ES) 1212 13,80% 57,80% 22,90% 5,50% 63M 19M42 387 450 180

Sweden (SE) 1186 4,00% 36,50% 42,50% 17,00% 123M 4M127 560 250 34


Taiwan (TW) 2016 11,80% 37,40% 26,20% 24,50% 110M 24M462 562 132 25


Uruguay (UY) 1108 4,80% 21,40% 43,70% 30,00% 28M 1M293 446 272 168



V29 How proud: Its social security system Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). d. Its social security system 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


1 2 3 4 8 9

V29 (N) % % % % % % 260 943 587 225

Australia (AU) 2183 12,90% 46,80% 29,10% 11,20% 109M 59M275 448 175 49

Austria (AT) 1006 29,00% 47,30% 18,50% 5,20% 59M 5 56 282 610

Bulgaria (BG) 1069 0,50% 5,90% 29,60% 64,00% 98M 18M284 636 191 53

Canada (CA) 1211 24,40% 54,60% 16,40% 4,60% 44M 3M137 459 603 198

Chile (CL) 1505 9,80% 32,90% 43,20% 14,20% 82M 26M30 215 499 461


Denmark (DK) 1322 26,30% 51,10% 19,20% 3,40% 36M 23M336 681 200 76

Finland (FI) 1379 26,00% 52,70% 15,50% 5,90% 30M 56M454 738 219 123

France (FR) 1669 29,60% 48,10% 14,30% 8,00% 48M 87M93 407 205 85




Hungary (HU) 1021 1,60% 17,20% 56,10% 25,00% 157M 5M155 472 283 73

Ireland (IE) 1065 15,80% 48,00% 28,80% 7,40% 74M 8M57 232 371 385


Israel Arabs (IL-A) 152 28,50% 44,40% 15,90% 11,30% 1M51 337 404 167

Japan (JP) 1102 5,30% 35,10% 42,10% 17,40% 137M 6M10 81 325 550

Latvia (LV) 1000 1,00% 8,40% 33,60% 56,90% 33M 1M106 396 321 129

New Zealand (NZ) 1036 11,10% 41,60% 33,70% 13,60% 60M 24M195 707 394 116

Norway (NO) 1469 13,80% 50,10% 27,90% 8,20% 33M 24M12 136 545 513

Poland (PL) 1277 1,00% 11,30% 45,20% 42,50% 69M 2M26 257 644 525

Portugal (PT) 1602 1,80% 17,70% 44,40% 36,20% 50M 100M156 362 433 210

Philippines (PH) 1200 13,40% 31,20% 37,30% 18,10% 39M 49 180 641 1390

Russia (RU) 2383 2,20% 8,00% 28,40% 61,50% 123M 3 83 400 641


Slovenia (SI) 1093 3,90% 30,30% 48,00% 17,90% 42M 437 751 576 351


South Korea (KR) 1315 1,50% 15,80% 55,60% 27,10% 23M 209 606 299 59

Spain (ES) 1212 17,80% 51,70% 25,50% 5,00% 24M 15M145 547 311 122

Sweden (SE) 1186 12,90% 48,60% 27,60% 10,80% 51M 10M224 482 210 84


Taiwan (TW) 2016 6,00% 30,00% 36,20% 27,80% 118M 24M150 488 397 132


Uruguay (UY) 1108 8,80% 28,80% 35,80% 26,60% 29M 2M160 387 363 266



V30 How proud: Its scientific and technological achievements Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). e. its scientific and technological achievements 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


1 2 3 4 8 9

V30 (N) % % % % % % 1014 914 93 19

Australia (AU) 2183 49,70% 44,80% 4,60% 0,90% 74M 69M299 447 108 26

Austria (AT) 1006 34,00% 50,80% 12,30% 3,00% 126M 105 350 207 167

Bulgaria (BG) 1069 12,70% 42,20% 25,00% 20,10% 215M 25M387 682 70 12

Canada (CA) 1211 33,60% 59,30% 6,10% 1,00% 58M 2M295 703 302 58

Chile (CL) 1505 21,70% 51,80% 22,20% 4,30% 111M 36M137 647 245 82


Denmark (DK) 1322 22,20% 57,30% 18,50% 2,00% 172M 26M410 646 144 10

Finland (FI) 1379 33,90% 53,40% 11,90% 0,80% 107M 62M360 920 160 31

France (FR) 1669 24,50% 62,50% 10,90% 2,10% 86M 112M162 450 114 28




Hungary (HU) 1021 33,90% 55,60% 8,60% 1,90% 66M 4M278 504 125 24

Ireland (IE) 1065 29,90% 54,10% 13,40% 2,60% 115M 19M573 396 50 16


Israel Arabs (IL-A) 152 34,40% 43,70% 15,90% 6,00% 1M429 491 62 16

Japan (JP) 1102 43,00% 49,20% 6,20% 1,60% 98M 6M65 367 322 146

Latvia (LV) 1000 7,20% 40,80% 35,80% 16,20% 99M 1M446 468 42 10

New Zealand (NZ) 1036 46,20% 48,40% 4,30% 1,00% 47M 23M141 749 344 51

Norway (NO) 1469 11,00% 58,30% 26,80% 4,00% 158M 26M123 663 270 55

Poland (PL) 1277 11,10% 59,70% 24,30% 5,00% 165M 1M84 594 490 152

Portugal (PT) 1602 6,40% 45,00% 37,10% 11,50% 187M 95M248 523 319 87

Philippines (PH) 1200 21,10% 44,40% 27,10% 7,40% 23M 508 1052 390 164

Russia (RU) 2383 24,00% 49,80% 18,40% 7,80% 269M 50 449 374 125


Slovenia (SI) 1093 9,80% 55,30% 30,90% 4,00% 88M 3M637 941 297 129


South Korea (KR) 1315 11,40% 54,70% 29,40% 4,50% 38M 179 668 203 61

Spain (ES) 1212 16,10% 60,10% 18,30% 5,50% 85M 16M240 631 121 21

Sweden (SE) 1186 23,70% 62,30% 11,90% 2,10% 160M 13M314 562 65 16


Taiwan (TW) 2016 14,20% 46,80% 30,40% 8,60% 206M 29M691 433 38 14


Uruguay (UY) 1108 21,40% 46,10% 22,20% 10,30% 145M 3M383 492 166 115



V31 How proud: Its achievements in sports Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). f. its achievements in sports 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


V31 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 1213 738 85 38 56M 53M

58,50% 35,60% 4,10% 1,80%Austria (AT) 1006 463 367 81 28 67M

49,30% 39,10% 8,60% 3,00%Bulgaria (BG) 1069 469 374 45 33 124M 24M

50,90% 40,60% 4,90% 3,60%Canada (CA) 1211 372 641 108 33 52M 5M

32,20% 55,50% 9,40% 2,90%Chile (CL) 1505 391 659 313 72 45M 25M


41,10% 48,70% 8,60% 1,60%Denmark (DK) 1322 296 618 218 45 123M 22M

25,10% 52,50% 18,50% 3,80%Finland (FI) 1379 182 531 403 145 57M 61M

14,40% 42,10% 32,00% 11,50%France (FR) 1669 143 871 241 83 225M 106M




18,10% 50,80% 24,80% 6,40%Hungary (HU) 1021 453 467 53 8 36M 4M

46,20% 47,60% 5,40% 0,80%Ireland (IE) 1065 631 378 27 9 14M 6M


10,10% 32,50% 38,30% 19,10%Israel Arabs (IL-A) 152 16 44 68 24

10,50% 28,90% 44,70% 15,80%Japan (JP) 1102 389 533 97 17 60M 6M

37,50% 51,40% 9,40% 1,60%Latvia (LV) 1000 394 468 69 34 34M 1M

40,80% 48,50% 7,20% 3,50%New Zealand (NZ) 1036 614 350 26 9 19M 18M

61,50% 35,00% 2,60% 0,90%Norway (NO) 1469 388 706 214 69 76M 16M

28,20% 51,30% 15,50% 5,00%Poland (PL) 1277 177 682 284 49 82M 3M

14,80% 57,20% 23,80% 4,10%Portugal (PT) 1602 521 739 166 30 48M 98M

35,80% 50,80% 11,40% 2,10%Philippines (PH) 1200 475 526 149 37 13M

40,00% 44,30% 12,60% 3,10%Russia (RU) 2383 562 1060 400 120 241M


37,70% 49,60% 10,70% 2,00%Slovenia (SI) 1093 352 561 136 13 31M


47,20% 40,50% 9,00% 3,30%South Korea (KR) 1315 391 763 129 16 16M

30,10% 58,70% 9,90% 1,20%Spain (ES) 1212 245 737 133 26 54M 17M

21,50% 64,60% 11,70% 2,30%Sweden (SE) 1186 387 575 126 39 52M 7M


19,30% 52,80% 21,70% 6,20%Taiwan (TW) 2016 181 769 669 237 132M 28M


44,70% 45,50% 7,70% 2,00%Uruguay (UY) 1108 306 491 195 88 26M 2M

28,30% 45,50% 18,10% 8,10%Venezuela (VE) 1199 817 292 42 37 6M 5M

68,80% 24,60% 3,50% 3,10%Sum 44170 13974 19457 6012 1839 2229M 659M


V32 How proud: Its achievements in the arts and literature Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). g. its achievements in the arts and literature 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


V32 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 658 1077 201 39 149M 59M

33,30% 54,50% 10,20% 2,00%Austria (AT) 1006 303 435 96 24 148M

35,30% 50,70% 11,20% 2,80%Bulgaria (BG) 1069 303 378 103 50 206M 29M

36,30% 45,30% 12,40% 6,00%Canada (CA) 1211 289 653 103 24 138M 4M

27,00% 61,10% 9,60% 2,20%Chile (CL) 1505 609 621 146 24 86M 19M


29,50% 54,20% 12,60% 3,70%Denmark (DK) 1322 179 571 270 48 228M 26M

16,80% 53,50% 25,30% 4,50%Finland (FI) 1379 205 613 308 74 116M 63M

17,10% 51,10% 25,70% 6,20%France (FR) 1669 349 834 136 43 180M 127M




24,50% 55,60% 15,40% 4,50%Hungary (HU) 1021 440 455 56 6 60M 4M

46,00% 47,50% 5,90% 0,60%Ireland (IE) 1065 551 381 36 11 75M 11M


20,60% 45,60% 25,90% 7,80%Israel Arabs (IL-A) 152 20 47 65 19 1M

13,20% 31,10% 43,00% 12,60%Japan (JP) 1102 407 485 80 13 111M 6M

41,30% 49,20% 8,10% 1,30%Latvia (LV) 1000 220 486 157 66 70M 1M

23,70% 52,30% 16,90% 7,10%New Zealand (NZ) 1036 376 475 83 21 61M 20M

39,40% 49,70% 8,70% 2,20%Norway (NO) 1469 184 745 296 55 163M 26M

14,40% 58,20% 23,10% 4,30%Poland (PL) 1277 162 678 224 32 179M 2M

14,80% 61,90% 20,40% 2,90%Portugal (PT) 1602 466 777 168 28 67M 96M

32,40% 54,00% 11,70% 1,90%Philippines (PH) 1200 373 547 207 50 23M

31,70% 46,50% 17,60% 4,20%Russia (RU) 2383 641 1005 324 97 316M

31,00% 48,60% 15,70% 4,70%Slovak Republic (SK) 1152 275 575 192 40 70M

25,40% 53,10% 17,70% 3,70%Slovenia (SI) 1093 165 566 224 32 100M 6M


35,00% 47,40% 13,10% 4,50%South Korea (KR) 1315 121 655 440 60 39M

9,50% 51,30% 34,50% 4,70%Spain (ES) 1212 237 752 108 20 81M 14M

21,20% 67,30% 9,70% 1,80%Sweden (SE) 1186 162 569 215 37 194M 9M


17,20% 60,00% 19,90% 2,90%Taiwan (TW) 2016 125 650 691 227 286M 37M


41,40% 51,20% 6,30% 1,10%Uruguay (UY) 1108 365 460 106 29 144M 4M

38,00% 47,90% 11,00% 3,00%Venezuela (VE) 1199 578 444 90 51 20M 16M

49,70% 38,20% 7,70% 4,40%Sum 44170 11009 20117 6357 1551 4385M 751M


V33 How proud: [Country’S] armed forces Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). h. [COUNTRY’S] armed forces 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


V33 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 862 928 197 61 84M 51M

42,10% 45,30% 9,60% 3,00%Austria (AT) 1006 104 321 215 163 203M

13,00% 40,00% 26,80% 20,30%Bulgaria (BG) 1069 62 184 269 257 264M 33M

8,00% 23,80% 34,80% 33,30%Canada (CA) 1211 329 459 255 105 58M 5M

28,70% 40,00% 22,20% 9,10%Chile (CL) 1505 405 580 336 99 62M 23M


5,40% 27,90% 41,00% 25,70%Denmark (DK) 1322 87 429 391 216 178M 21M

7,70% 38,20% 34,80% 19,20%Finland (FI) 1379 306 507 267 115 123M 61M

25,60% 42,40% 22,30% 9,60%France (FR) 1669 200 623 276 167 293M 110M




53,10% 37,60% 6,70% 2,60%Hungary (HU) 1021 31 203 391 215 174M 7M

3,70% 24,20% 46,50% 25,60%Ireland (IE) 1065 341 459 127 49 81M 8M


61,00% 27,20% 7,60% 4,20%Israel Arabs (IL-A) 152 44 38 33 37

28,90% 25,00% 21,70% 24,30%Japan (JP) 1102 83 286 339 124 260M 10M

10,00% 34,40% 40,70% 14,90%Latvia (LV) 1000 54 222 308 317 98M 1M

6,00% 24,60% 34,20% 35,20%New Zealand (NZ) 1036 294 397 170 74 75M 26M

31,40% 42,50% 18,20% 7,90%Norway (NO) 1469 46 391 517 273 217M 25M

3,70% 31,90% 42,10% 22,20%Poland (PL) 1277 147 619 268 75 167M 1M

13,30% 55,80% 24,20% 6,80%Portugal (PT) 1602 183 541 445 217 118M 98M

13,20% 39,00% 32,10% 15,70%Philippines (PH) 1200 250 416 338 179 17M

21,10% 35,20% 28,60% 15,10%Russia (RU) 2383 322 651 667 516 227M


8,00% 35,90% 37,30% 18,80%Slovenia (SI) 1093 82 402 378 151 77M 3M


27,90% 43,30% 19,20% 9,60%South Korea (KR) 1315 76 352 636 210 41M

6,00% 27,60% 49,90% 16,50%Spain (ES) 1212 159 569 304 118 42M 20M

13,80% 49,50% 26,40% 10,30%Sweden (SE) 1186 33 214 445 246 239M 9M


11,20% 36,20% 32,90% 19,80%Taiwan (TW) 2016 89 401 628 546 311M 41M


75,80% 18,10% 4,50% 1,60%Uruguay (UY) 1108 128 280 266 341 91M 2M

12,60% 27,60% 26,20% 33,60%Venezuela (VE) 1199 389 394 191 188 17M 20M

33,50% 33,90% 16,40% 16,20%Sum 44170 7936 13895 10864 6234 4522M 719M


V34 How proud: Its history Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). i. its history 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


V34 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 734 874 314 106 101M 54M

36,20% 43,10% 15,50% 5,20%Austria (AT) 1006 273 422 147 40 124M

31,00% 47,80% 16,70% 4,50%Bulgaria (BG) 1069 588 302 55 27 73M 24M

60,50% 31,10% 5,70% 2,80%Canada (CA) 1211 502 558 80 15 53M 3M

43,50% 48,30% 6,90% 1,30%Chile (CL) 1505 605 594 212 30 49M 15M


38,30% 46,30% 12,30% 3,10%Denmark (DK) 1322 367 610 182 27 115M 21M

30,90% 51,40% 15,30% 2,30%Finland (FI) 1379 432 613 155 28 86M 65M

35,20% 49,90% 12,60% 2,30%France (FR) 1669 573 709 114 31 139M 103M




49,60% 38,40% 9,60% 2,30%Hungary (HU) 1021 301 489 149 27 49M 6M

31,20% 50,60% 15,40% 2,80%Ireland (IE) 1065 532 421 61 13 23M 15M


62,70% 28,10% 7,50% 1,70%Israel Arabs (IL-A) 152 17 47 58 28 1M 1M

11,30% 31,30% 38,70% 18,70%Japan (JP) 1102 252 462 195 36 147M 10M

26,70% 48,90% 20,60% 3,80%Latvia (LV) 1000 135 337 254 140 133M 1M

15,60% 38,90% 29,30% 16,20%New Zealand (NZ) 1036 283 432 185 39 68M 29M

30,10% 46,00% 19,70% 4,20%Norway (NO) 1469 297 778 234 42 98M 20M

22,00% 57,60% 17,30% 3,10%Poland (PL) 1277 343 685 142 20 85M 2M

28,80% 57,60% 11,90% 1,70%Portugal (PT) 1602 790 570 94 15 36M 97M

53,80% 38,80% 6,40% 1,00%Philippines (PH) 1200 538 454 138 41 29M

45,90% 38,80% 11,80% 3,50%Russia (RU) 2383 910 887 272 107 207M


31,50% 48,20% 16,00% 4,30%Slovenia (SI) 1093 262 586 151 35 59M


41,30% 35,60% 14,10% 8,90%South Korea (KR) 1315 347 614 284 52 18M

26,80% 47,30% 21,90% 4,00%Spain (ES) 1212 282 659 168 46 38M 19M

24,40% 57,10% 14,50% 4,00%Sweden (SE) 1186 172 543 290 42 130M 9M


21,90% 57,10% 17,20% 3,80%Taiwan (TW) 2016 356 700 485 185 247M 43M


61,40% 30,80% 5,90% 1,90%Uruguay (UY) 1108 532 435 83 26 31M 1M

49,40% 40,40% 7,70% 2,40%Venezuela (VE) 1199 813 302 27 38 9M 10M

68,90% 25,60% 2,30% 3,20%Sum 44170 15044 17843 6030 1836 2713M 704M


V35 How proud: Its fair and equal treatment of all groups in society Missing Values: 8; 9 Q5.- How proud are you of [COUNTRY] in each of the following? (Please, tick one box on each line). j. Its fair and equal treatment of all groups in society 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


V35 (N) 1 2 3 4 8 9

% % % % % % Australia (AU) 2183 385 843 564 223 110M 58M

19,10% 41,80% 28,00% 11,10%Austria (AT) 1006 145 420 277 78 86M

15,80% 45,70% 30,10% 8,50%Bulgaria (BG) 1069 155 318 239 156 176M 25M

17,90% 36,60% 27,50% 18,00%Canada (CA) 1211 298 579 210 67 51M 6M

25,80% 50,20% 18,20% 5,80%Chile (CL) 1505 171 503 505 249 58M 19M


2,20% 19,60% 47,50% 30,70%Denmark (DK) 1322 131 474 461 150 87M 19M

10,80% 39,00% 37,90% 12,30%Finland (FI) 1379 147 440 448 193 95M 56M

12,00% 35,80% 36,50% 15,70%France (FR) 1669 111 526 491 276 162M 103M




15,80% 43,70% 30,00% 10,60%Hungary (HU) 1021 37 349 412 86 131M 6M

4,20% 39,50% 46,60% 9,70%Ireland (IE) 1065 157 428 334 111 29M 6M


6,40% 19,70% 38,40% 35,40%Israel Arabs (IL-A) 152 16 61 31 44

10,50% 40,10% 20,40% 28,90%Japan (JP) 1102 75 383 339 114 185M 6M

8,20% 42,00% 37,20% 12,50%Latvia (LV) 1000 11 101 306 511 70M 1M

1,20% 10,90% 32,90% 55,00%New Zealand (NZ) 1036 137 427 244 143 62M 23M

14,40% 44,90% 25,70% 15,00%Norway (NO) 1469 89 499 572 190 95M 24M

6,60% 37,00% 42,40% 14,10%Poland (PL) 1277 53 226 520 356 121M 1M

4,60% 19,60% 45,00% 30,80%Portugal (PT) 1602 89 386 572 366 92M 97M

6,30% 27,30% 40,50% 25,90%Philippines (PH) 1200 202 400 372 194 32M

17,30% 34,20% 31,80% 16,60%Russia (RU) 2383 63 203 655 1199 263M

3,00% 9,60% 30,90% 56,60%Slovak Republic (SK) 1152 31 185 482 400 54M

2,80% 16,80% 43,90% 36,40%Slovenia (SI) 1093 88 288 473 184 60M


27,30% 35,80% 19,40% 17,60%South Korea (KR) 1315 28 186 666 401 34M

2,20% 14,50% 52,00% 31,30%Spain (ES) 1212 141 657 269 91 36M 18M

12,20% 56,70% 23,20% 7,90%Sweden (SE) 1186 81 367 431 213 85M 9M


16,60% 52,90% 22,20% 8,40%Taiwan (TW) 2016 164 564 515 550 193M 30M


25,20% 49,40% 20,10% 5,30%Uruguay (UY) 1108 254 383 270 166 32M 3M

23,70% 35,70% 25,20% 15,50%Venezuela (VE) 1199 441 457 171 105 14M 11M

37,60% 38,90% 14,60% 8,90%Sum 44170 5006 13668 13359 8330 3143M 664M


V36 [Country] should limit the import of foreign products in order to protect its national economy. Missing Values: 8; 9 Q6.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) a. [COUNTRY] should limit the import of foreign products in order to protect its national economy. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V36 (N) % % % % % % % 525 862 407 267 37

Australia (AU) 2183 25,00% 41,10% 19,40% 12,70% 1,80% 44M 41M285 276 169 140 84

Austria (AT) 1006 29,90% 28,90% 17,70% 14,70% 8,80% 52M 439 283 114 67 42

Bulgaria (BG) 1069 46,50% 29,90% 12,10% 7,10% 4,40% 103M 21M176 421 260 256 49

Canada (CA) 1211 15,10% 36,20% 22,40% 22,00% 4,20% 42M 7M288 601 205 282 24

Chile (CL) 1505 20,60% 42,90% 14,60% 20,10% 1,70% 95M 10M221 378 263 226 95


Denmark (DK) 1322 9,40% 26,10% 16,40% 21,30% 26,80% 72M 18M160 270 348 381 104

Finland (FI) 1379 12,70% 21,40% 27,60% 30,20% 8,20% 79M 37M391 425 323 280 159

France (FR) 1669 24,80% 26,90% 20,50% 17,70% 10,10% 31M 60M93 252 175 204 71




Hungary (HU) 1021 29,50% 35,80% 21,40% 9,80% 3,50% 48M 3M171 430 153 267 21

Ireland (IE) 1065 16,40% 41,30% 14,70% 25,60% 2,00% 23M 288 334 154 186 75


Israel Arabs (IL-A) 152 25,50% 56,40% 14,80% 3,40% - 1M 2M196 222 315 114 177

Japan (JP) 1102 19,10% 21,70% 30,80% 11,10% 17,30% 75M 3M304 352 169 139 17

Latvia (LV) 1000 31,00% 35,90% 17,20% 14,20% 1,70% 19M 203 365 216 185 27

New Zealand (NZ) 1036 20,40% 36,60% 21,70% 18,60% 2,70% 19M 21M134 352 394 399 104

Norway (NO) 1469 9,70% 25,50% 28,50% 28,90% 7,50% 67M 19M357 520 194 132 16

Poland (PL) 1277 29,30% 42,70% 15,90% 10,80% 1,30% 58M 217 673 203 254 47

Portugal (PT) 1602 15,60% 48,30% 14,60% 18,20% 3,40% 119M 89M393 465 185 101 36

Philippines (PH) 1200 33,30% 39,40% 15,70% 8,60% 3,10% 20M 771 636 358 308 139

Russia (RU) 2383 34,90% 28,80% 16,20% 13,90% 6,30% 171M 355 403 284 89 21

Slovak Republic (SK) 1152 30,80% 35,00% 24,70% 7,70% 1,80% 221 338 198 250 49

Slovenia (SI) 1093 20,90% 32,00% 18,80% 23,70% 4,60% 37M 553 995 215 270 116


South Korea (KR) 1315 15,50% 37,10% 22,70% 21,60% 3,10% 20M 94 596 299 146 24

Spain (ES) 1212 8,10% 51,40% 25,80% 12,60% 2,10% 42M 11M71 248 394 261 128

Sweden (SE) 1186 6,40% 22,50% 35,80% 23,70% 11,60% 78M 6M76 299 203 386 57


Taiwan (TW) 2016 11,10% 37,90% 18,90% 28,60% 3,60% 75M 23M271 453 253 180 23


Uruguay (UY) 1108 33,20% 39,90% 13,90% 11,40% 1,50% 57M 2M215 549 7 312 61



V37 For certain problems, like environment pollution, international bodies should have the right to enforce solutions Missing Values: 0; 8; 9 Q6.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) b. For certain problems, like environment pollution, international bodies should have the right to enforce solutions 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa


0 1 2 3 4 5 8 9

V37 (N) % % % % % % % % 352 991 352 294 79

Australia (AU) 2183 - 17,00% 47,90% 17,00% 14,20% 3,80% 66M 49M294 388 129 101 42

Austria (AT) 1006 - 30,80% 40,70% 13,50% 10,60% 4,40% 52M 319 315 125 46 37

Bulgaria (BG) 1069 - 37,90% 37,40% 14,80% 5,50% 4,40% 199M 28M269 525 180 145 38

Canada (CA) 1211 - 23,20% 45,40% 15,60% 12,50% 3,30% 46M 8M399 695 218 58 5

Chile (CL) 1505 - 29,00% 50,50% 15,90% 4,20% 0,40% 119M 11M260 520 222 108 31

Czech Republic (CZ) 1276 - 22,80% 45,60% 19,50% 9,50% 2,70% 47M 88M353 432 140 148 159

Denmark (DK) 1322 - 28,70% 35,10% 11,40% 12,00% 12,90% 71M 19M184 536 293 167 60

Finland (FI) 1379 - 14,80% 43,20% 23,60% 13,50% 4,80% 85M 54M706 638 129 66 33

France (FR) 1669 - 44,90% 40,60% 8,20% 4,20% 2,10% 29M 68M192 438 80 60 14

Germany-West (DE-W) 850 - 24,50% 55,90% 10,20% 7,70% 1,80% 62M 4M74 246 54 31 4

Germany-East (DE-E) 437 - 18,10% 60,10% 13,20% 7,60% 1,00% 23M 5M178 374 154 96 7

Great Britain (GB) 873 - 22,00% 46,20% 19,00% 11,90% 0,90% 41M 23M334 391 171 39 15

Hungary (HU) 1021 - 35,20% 41,20% 18,00% 4,10% 1,60% 69M 2M130 558 115 197 23

Ireland (IE) 1065 - 12,70% 54,50% 11,20% 19,30% 2,20% 41M 1M257 365 166 181 75

Israel Jews (IL-J) 1066 - 24,60% 35,00% 15,90% 17,30% 7,20% 15M 7M41 69 39 2

Israel Arabs (IL-A) 152 - 27,20% 45,70% 25,80% 1,30% - 1M314 332 208 44 39

Japan (JP) 1102 - 33,50% 35,40% 22,20% 4,70% 4,20% 161M 4M110 379 228 193 25

Latvia (LV) 1000 - 11,80% 40,50% 24,40% 20,60% 2,70% 65M 147 393 168 218 48

New Zealand (NZ) 1036 - 15,10% 40,30% 17,20% 22,40% 4,90% 39M 23M229 682 264 147 44

Norway (NO) 1469 - 16,80% 49,90% 19,30% 10,80% 3,20% 78M 25M176 609 227 107 13

Poland (PL) 1277 - 15,50% 53,80% 20,10% 9,50% 1,10% 144M 1M293 769 244 65 16

Portugal (PT) 1602 - 21,10% 55,40% 17,60% 4,70% 1,20% 122M 93M320 526 218 96 17

Philippines (PH) 1200 - 27,20% 44,70% 18,50% 8,20% 1,40% 23M 920 806 262 83 25

Russia (RU) 2383 - 43,90% 38,50% 12,50% 4,00% 1,20% 287M 264 553 256 68 11

Slovak Republic (SK) 1152 - 22,90% 48,00% 22,20% 5,90% 1,00% 222 611 143 58 5

Slovenia (SI) 1093 - 21,40% 58,80% 13,80% 5,60% 0,50% 52M 2M2483M

South Africa (ZA) 2483 - - - - - 375 637 208 59 11

South Korea (KR) 1315 - 29,10% 49,40% 16,10% 4,60% 0,90% 25M 163 571 350 56 3

Spain (ES) 1212 - 14,30% 50,00% 30,60% 4,90% 0,30% 54M 15M246 566 202 84 17

Sweden (SE) 1186 - 22,10% 50,80% 18,10% 7,50% 1,50% 68M 3M200 592 87 118 8

Switzerland (CH) 1037 - 19,90% 58,90% 8,70% 11,70% 0,80% 31M 1M365 1126 219 135 20

Taiwan (TW) 2016 - 19,60% 60,40% 11,70% 7,20% 1,10% 122M 29M225 501 245 141 56

United States (US) 1216 - 19,30% 42,90% 21,00% 12,10% 4,80% 47M 1M326 485 137 40 12

Uruguay (UY) 1108 - 32,60% 48,50% 13,70% 4,00% 1,20% 104M 4M316 645 3 172 24

Venezuela (VE) 1199 - 27,20% 55,60% 0,30% 14,80% 2,10% 19M 20MSum 44170 2483M 9553 18264 6236 3623 1016 2406M 589M


V38 [Country] should follow its own interests, even if this leads to conflicts with other nations Missing Values: 8; 9 Q6.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) c. [COUNTRY] should follow its own interests, even if this leads to conflicts with other nations. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V38 (N) % % % % % % % 253 702 504 540 77

Australia (AU) 2183 12,20% 33,80% 24,30% 26,00% 3,70% 62M 45M240 350 202 122 53

Austria (AT) 1006 24,80% 36,20% 20,90% 12,60% 5,50% 39M 433 312 122 41 20

Bulgaria (BG) 1069 46,70% 33,60% 13,10% 4,40% 2,20% 120M 21M161 450 257 247 30

Canada (CA) 1211 14,10% 39,30% 22,40% 21,60% 2,60% 56M 10M399 687 211 117 16

Chile (CL) 1505 27,90% 48,00% 14,80% 8,20% 1,10% 66M 9M190 349 332 230 72


Denmark (DK) 1322 21,90% 36,00% 16,40% 17,00% 8,70% 48M 20M192 454 340 232 33

Finland (FI) 1379 15,30% 36,30% 27,20% 18,50% 2,60% 75M 53M403 540 303 233 92

France (FR) 1669 25,70% 34,40% 19,30% 14,80% 5,90% 35M 63M84 269 175 204 66




Hungary (HU) 1021 15,70% 34,40% 30,40% 15,80% 3,70% 75M 2M99 490 159 272 11

Ireland (IE) 1065 9,60% 47,50% 15,40% 26,40% 1,10% 33M 1M421 347 160 93 27



Japan (JP) 1102 10,10% 13,80% 30,20% 18,40% 27,50% 109M 4M73 269 305 245 38

Latvia (LV) 1000 7,80% 28,90% 32,80% 26,30% 4,10% 70M 177 374 228 189 22

New Zealand (NZ) 1036 17,90% 37,80% 23,00% 19,10% 2,20% 22M 24M75 333 396 501 87

Norway (NO) 1469 5,40% 23,90% 28,40% 36,00% 6,20% 48M 29M172 446 252 270 30

Poland (PL) 1277 14,70% 38,10% 21,50% 23,10% 2,60% 106M 1M300 635 237 198 24

Portugal (PT) 1602 21,50% 45,60% 17,00% 14,20% 1,70% 116M 92M145 272 295 372 92

Philippines (PH) 1200 12,30% 23,10% 25,10% 31,60% 7,80% 24M 669 669 365 265 113

Russia (RU) 2383 32,10% 32,10% 17,50% 12,70% 5,40% 302M 152 315 390 257 38


Slovenia (SI) 1093 8,10% 19,80% 23,20% 41,40% 7,50% 44M 2M401 839 310 442 173


South Korea (KR) 1315 17,40% 38,80% 25,50% 16,30% 2,00% 14M 78 490 328 227 31

Spain (ES) 1212 6,80% 42,50% 28,40% 19,70% 2,70% 41M 17M88 320 398 257 63

Sweden (SE) 1186 7,80% 28,40% 35,30% 22,80% 5,60% 54M 6M96 463 181 240 17


Taiwan (TW) 2016 7,20% 34,30% 19,50% 33,50% 5,50% 109M 25M152 402 291 294 40


Uruguay (UY) 1108 28,60% 43,40% 13,70% 12,50% 1,90% 51M 3M140 520 10 421 59



V39 Foreigners should not be allowed to buy land in [Country] Missing Values: 8; 9 Q6.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) d. Foreigners should not be allowed to buy land in [COUNTRY] 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V39 (N) % % % % % % % 379 521 504 554 111

Australia (AU) 2183 18,30% 25,20% 24,40% 26,80% 5,40% 67M 47M122 170 205 262 199

Austria (AT) 1006 12,70% 17,70% 21,40% 27,30% 20,80% 48M 432 188 126 107 93

Bulgaria (BG) 1069 45,70% 19,90% 13,30% 11,30% 9,80% 105M 18M125 228 313 425 74

Canada (CA) 1211 10,70% 19,60% 26,90% 36,50% 6,40% 38M 8M417 532 239 216 33

Chile (CL) 1505 29,00% 37,00% 16,60% 15,00% 2,30% 60M 8M420 279 228 149 95


Denmark (DK) 1322 28,30% 23,40% 14,70% 16,90% 16,80% 51M 18M151 218 351 369 137

Finland (FI) 1379 12,30% 17,80% 28,60% 30,10% 11,20% 108M 45M198 173 406 336 447

France (FR) 1669 12,70% 11,10% 26,00% 21,50% 28,70% 46M 63M34 90 124 305 231




Hungary (HU) 1021 40,50% 31,00% 18,60% 7,70% 2,30% 44M 3M57 207 163 534 70

Ireland (IE) 1065 5,50% 20,10% 15,80% 51,80% 6,80% 28M 6M374 249 180 178 65


Israel Arabs (IL-A) 152 44,40% 33,80% 14,60% 6,00% 1,30% 1M 145 129 277 136 271

Japan (JP) 1102 15,10% 13,50% 28,90% 14,20% 28,30% 142M 2M252 340 184 142 20

Latvia (LV) 1000 26,90% 36,20% 19,60% 15,10% 2,10% 62M 276 214 236 228 36

New Zealand (NZ) 1036 27,90% 21,60% 23,80% 23,00% 3,60% 22M 24M149 264 349 470 154

Norway (NO) 1469 10,80% 19,00% 25,20% 33,90% 11,10% 62M 21M288 349 262 252 62

Poland (PL) 1277 23,70% 28,80% 21,60% 20,80% 5,10% 62M 2M119 241 272 585 221

Portugal (PT) 1602 8,30% 16,80% 18,90% 40,70% 15,40% 66M 98M286 316 279 218 86

Philippines (PH) 1200 24,10% 26,70% 23,50% 18,40% 7,30% 15M 1572 360 142 120 68

Russia (RU) 2383 69,50% 15,90% 6,30% 5,30% 3,00% 121M 249 312 338 215 37

Slovak Republic (SK) 1152 21,60% 27,10% 29,40% 18,70% 3,20% 1M180 264 250 297 72

Slovenia (SI) 1093 16,90% 24,80% 23,50% 27,90% 6,80% 29M 1M531 785 281 466 172


South Korea (KR) 1315 24,00% 34,40% 23,60% 14,20% 3,90% 21M 37 224 346 431 102

Spain (ES) 1212 3,20% 19,60% 30,40% 37,80% 8,90% 56M 16M88 159 353 355 172

Sweden (SE) 1186 7,80% 14,10% 31,30% 31,50% 15,30% 57M 2M33 144 168 551 109


Taiwan (TW) 2016 11,60% 35,40% 23,70% 26,70% 2,50% 121M 20M139 216 277 446 110


Uruguay (UY) 1108 18,00% 23,00% 20,80% 30,70% 7,50% 40M 2M78 309 20 621 130



V40 [Country’s] television should give preference to [Country] films and programmes Missing Values: 8; 9 Q6.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) e. [COUNTRY’S] television should give preference to [COUNTRY] films and programmes 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V40 (N) % % % % % % % 309 685 594 447 69

Australia (AU) 2183 14,70% 32,60% 28,20% 21,20% 3,30% 38M 41M150 244 225 213 137

Austria (AT) 1006 15,50% 25,20% 23,20% 22,00% 14,10% 37M 406 308 135 83 52

Bulgaria (BG) 1069 41,30% 31,30% 13,70% 8,40% 5,30% 61M 24M156 360 289 315 71

Canada (CA) 1211 13,10% 30,20% 24,30% 26,40% 6,00% 16M 4M402 643 233 150 21

Chile (CL) 1505 27,70% 44,40% 16,10% 10,40% 1,40% 50M 6M293 386 296 164 43


Denmark (DK) 1322 21,00% 24,00% 19,20% 18,60% 17,30% 38M 16M125 184 334 454 188

Finland (FI) 1379 9,70% 14,30% 26,00% 35,30% 14,60% 47M 47M262 370 355 312 281

France (FR) 1669 16,60% 23,40% 22,50% 19,70% 17,80% 35M 54M74 161 171 230 178




Hungary (HU) 1021 30,50% 33,80% 23,60% 10,00% 2,10% 30M 2M135 419 160 293 32

Ireland (IE) 1065 13,00% 40,30% 15,40% 28,20% 3,10% 24M 2M165 242 257 254 108


Israel Arabs (IL-A) 152 14,50% 35,50% 38,80% 8,60% 2,60% 165 178 301 154 229

Japan (JP) 1102 16,10% 17,30% 29,30% 15,00% 22,30% 71M 4M151 280 245 223 64

Latvia (LV) 1000 15,70% 29,10% 25,40% 23,20% 6,60% 37M 87 218 306 327 61

New Zealand (NZ) 1036 8,70% 21,80% 30,60% 32,70% 6,10% 15M 22M56 193 315 582 282

Norway (NO) 1469 3,90% 13,50% 22,10% 40,80% 19,70% 22M 19M217 446 280 233 28

Poland (PL) 1277 18,00% 37,00% 23,30% 19,40% 2,30% 72M 1M374 714 237 149 16

Portugal (PT) 1602 25,10% 47,90% 15,90% 10,00% 1,10% 22M 90M379 470 215 92 26

Philippines (PH) 1200 32,10% 39,80% 18,20% 7,80% 2,20% 18M 1283 470 279 200 69

Russia (RU) 2383 55,80% 20,40% 12,10% 8,70% 3,00% 82M 211 293 374 235 39


Slovenia (SI) 1093 15,80% 31,30% 23,00% 23,60% 6,30% 22M 1M609 893 330 236 98


South Korea (KR) 1315 19,00% 38,50% 25,10% 14,30% 3,20% 19M 83 475 320 244 43

Spain (ES) 1212 7,10% 40,80% 27,50% 20,90% 3,70% 31M 16M61 122 252 406 324

Sweden (SE) 1186 5,20% 10,50% 21,60% 34,80% 27,80% 19M 2M25 226 169 494 103


Taiwan (TW) 2016 12,30% 39,50% 25,20% 20,50% 2,60% 56M 21M105 292 350 362 79


Uruguay (UY) 1108 29,90% 45,00% 14,70% 7,50% 2,90% 14M 2M305 696 12 146 17



V41 Large international companies are doing more and more damage to local businesses in [Country]. Missing Values: 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) a. Large international companies are doing more and more damage to local businesses in [COUNTRY]. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V41 (N) % % % % % % % 700 917 351 118 10

Australia (AU) 2183 33,40% 43,80% 16,70% 5,60% 0,50% 66M 21M234 330 193 100 39

Austria (AT) 1006 26,10% 36,80% 21,50% 11,20% 4,40% 110M 171 235 168 128 98

Bulgaria (BG) 1069 21,40% 29,40% 21,00% 16,00% 12,20% 240M 29M271 464 257 134 20

Canada (CA) 1211 23,60% 40,50% 22,40% 11,70% 1,70% 56M 9M344 655 215 174 11

Chile (CL) 1505 24,60% 46,80% 15,40% 12,40% 0,80% 102M 4M327 450 240 119 31


Denmark (DK) 1322 13,20% 35,30% 21,80% 19,10% 10,50% 117M 19M224 424 321 207 26

Finland (FI) 1379 18,60% 35,30% 26,70% 17,20% 2,20% 130M 47M668 563 205 93 32

France (FR) 1669 42,80% 36,10% 13,10% 6,00% 2,00% 46M 62M107 299 172 134 29




Hungary (HU) 1021 33,50% 38,80% 20,60% 6,00% 1,20% 83M 4M120 386 138 350 34

Ireland (IE) 1065 11,70% 37,50% 13,40% 34,00% 3,30% 37M 136 284 268 226 71


Israel Arabs (IL-A) 152 25,80% 44,40% 25,20% 4,60% - 1M196 243 243 110 137

Japan (JP) 1102 21,10% 26,20% 26,20% 11,80% 14,70% 166M 7M198 418 214 101 6

Latvia (LV) 1000 21,10% 44,60% 22,80% 10,80% 0,60% 63M 173 343 295 144 14

New Zealand (NZ) 1036 17,90% 35,40% 30,40% 14,90% 1,40% 52M 15M166 464 402 237 32

Norway (NO) 1469 12,80% 35,70% 30,90% 18,20% 2,50% 143M 25M265 530 236 116 9

Poland (PL) 1277 22,90% 45,80% 20,40% 10,00% 0,80% 120M 1M367 753 181 115 14

Portugal (PT) 1602 25,70% 52,70% 12,70% 8,00% 1,00% 83M 89M232 378 295 227 44

Philippines (PH) 1200 19,70% 32,10% 25,10% 19,30% 3,70% 24M 813 601 325 229 75

Russia (RU) 2383 39,80% 29,40% 15,90% 11,20% 3,70% 340M 276 433 275 88 7

Slovak Republic (SK) 1152 25,60% 40,10% 25,50% 8,20% 0,60% 73M 182 412 229 197 21

Slovenia (SI) 1093 17,50% 39,60% 22,00% 18,90% 2,00% 52M 443 749 255 423 117


South Korea (KR) 1315 9,60% 35,80% 32,10% 19,80% 2,70% 49M 164 593 291 100 7

Spain (ES) 1212 14,20% 51,30% 25,20% 8,70% 0,60% 48M 9M81 333 382 156 34

Sweden (SE) 1186 8,20% 33,80% 38,70% 15,80% 3,40% 190M 10M85 504 160 211 12


Taiwan (TW) 2016 6,70% 40,50% 22,20% 28,80% 1,80% 166M 32M272 435 287 150 17


Uruguay (UY) 1108 31,90% 43,80% 14,10% 8,30% 1,80% 73M 2M141 448 9 468 77



V42 Free trade leads to better products becoming available in [Country]. Missing Values: 0; 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) b. Free trade leads to better products becoming available in [COUNTRY]. 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked). 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa


0 1 2 3 4 5 8 9

V42 (N) % % % % % % % % 147 896 607 322 65

Australia (AU) 2183 - 7,20% 44,00% 29,80% 15,80% 3,20% 111M 35M130 336 239 162 67

Austria (AT) 1006 - 13,90% 36,00% 25,60% 17,30% 7,20% 72M 245 399 153 97 50

Bulgaria (BG) 1069 - 26,00% 42,30% 16,20% 10,30% 5,30% 103M 22M89 435 299 257 59

Canada (CA) 1211 - 7,80% 38,20% 26,30% 22,60% 5,20% 62M 10M335 765 215 72 6

Chile (CL) 1505 - 24,00% 54,90% 15,40% 5,20% 0,40% 108M 4M270 549 280 65 14


Denmark (DK) 1322 - 26,30% 41,60% 17,70% 9,90% 4,50% 144M 19M79 376 435 274 35

Finland (FI) 1379 - 6,60% 31,40% 36,30% 22,90% 2,90% 128M 52M174 613 436 214 73

France (FR) 1669 - 11,50% 40,60% 28,90% 14,20% 4,80% 73M 86M59 325 225 118 19




Hungary (HU) 1021 - 23,80% 42,00% 26,60% 6,40% 1,10% 57M 2M100 720 123 84 6

Ireland (IE) 1065 - 9,70% 69,70% 11,90% 8,10% 0,60% 32M 305 510 141 68 16


Israel Arabs (IL-A) 152 - 28,50% 44,40% 24,50% 2,60% - 1M 344 405 171 41 33

Japan (JP) 1102 - 34,60% 40,70% 17,20% 4,10% 3,30% 105M 3M52 438 276 186 17

Latvia (LV) 1000 - 5,40% 45,20% 28,50% 19,20% 1,80% 31M 103 531 212 118 17

New Zealand (NZ) 1036 - 10,50% 54,10% 21,60% 12,00% 1,70% 38M 17M84 667 378 168 36

Norway (NO) 1469 - 6,30% 50,00% 28,40% 12,60% 2,70% 114M 22M145 761 192 54 9

Poland (PL) 1277 - 12,50% 65,50% 16,50% 4,70% 0,80% 115M 1M208 761 255 133 39

Portugal (PT) 1602 - 14,90% 54,50% 18,30% 9,50% 2,80% 114M 92M204 479 314 145 24

Philippines (PH) 1200 - 17,50% 41,10% 26,90% 12,40% 2,10% 34M 651 948 343 151 63

Russia (RU) 2383 - 30,20% 44,00% 15,90% 7,00% 2,90% 227M 104 446 391 167 30

Slovak Republic (SK) 1152 - 9,10% 39,20% 34,40% 14,70% 2,60% 14M 222 649 115 64 10

Slovenia (SI) 1093 - 20,90% 61,20% 10,80% 6,00% 0,90% 32M 1M2483M

South Africa (ZA) 2483 - - - - - 144 633 346 138 17

South Korea (KR) 1315 - 11,30% 49,50% 27,10% 10,80% 1,30% 37M 117 684 257 84 6

Spain (ES) 1212 - 10,20% 59,60% 22,40% 7,30% 0,50% 55M 9M97 534 307 63 14

Sweden (SE) 1186 - 9,60% 52,60% 30,20% 6,20% 1,40% 157M 14M70 547 168 171 11


Taiwan (TW) 2016 - 15,60% 69,60% 9,70% 4,80% 0,30% 84M 26M134 525 297 188 23


Uruguay (UY) 1108 - 10,10% 53,40% 20,30% 12,80% 3,30% 75M 5M156 750 9 202 33



V43 In general, [Country] should follow the decisions of international organizations to which it belongs, even if the government does not agree with them. Missing Values: 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) c. In general, [COUNTRY] should follow the decisions of international organizations to which it belongs, even if the government does not agree with them. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V43 (N) % % % % % % % 79 484 678 670 107

Australia (AU) 2183 3,90% 24,00% 33,60% 33,20% 5,30% 128M 37M54 221 224 275 127

Austria (AT) 1006 6,00% 24,50% 24,90% 30,50% 14,10% 105M 126 274 176 125 70

Bulgaria (BG) 1069 16,30% 35,50% 22,80% 16,20% 9,10% 260M 38M43 335 337 370 33

Canada (CA) 1211 3,80% 30,00% 30,10% 33,10% 3,00% 81M 12M118 506 390 255 37

Chile (CL) 1505 9,00% 38,70% 29,90% 19,50% 2,80% 184M 15M75 289 412 259 77


Denmark (DK) 1322 13,50% 37,10% 15,30% 20,70% 13,30% 94M 22M44 320 429 312 42

Finland (FI) 1379 3,80% 27,90% 37,40% 27,20% 3,70% 168M 64M168 480 387 340 129

France (FR) 1669 11,20% 31,90% 25,70% 22,60% 8,60% 80M 85M30 209 222 214 42




Hungary (HU) 1021 7,00% 25,20% 39,70% 21,20% 7,00% 153M 6M22 356 231 340 30

Ireland (IE) 1065 2,20% 36,40% 23,60% 34,70% 3,10% 83M 3M112 322 282 220 89


Israel Arabs (IL-A) 152 21,20% 39,70% 27,80% 10,60% 0,70% 1M 128 198 358 117 122

Japan (JP) 1102 13,90% 21,50% 38,80% 12,70% 13,20% 172M 7M58 260 344 218 14

Latvia (LV) 1000 6,50% 29,10% 38,50% 24,40% 1,60% 106M 36 193 291 373 54

New Zealand (NZ) 1036 3,80% 20,40% 30,70% 39,40% 5,70% 67M 22M51 504 387 325 63

Norway (NO) 1469 3,80% 37,90% 29,10% 24,40% 4,70% 112M 27M46 367 420 197 15

Poland (PL) 1277 4,40% 35,10% 40,20% 18,90% 1,40% 231M 1M113 511 405 246 26

Portugal (PT) 1602 8,70% 39,30% 31,10% 18,90% 2,00% 208M 93M69 203 336 436 120

Philippines (PH) 1200 5,90% 17,40% 28,90% 37,50% 10,30% 36M 313 640 524 261 67

Russia (RU) 2383 17,30% 35,50% 29,00% 14,50% 3,70% 578M 46 260 467 231 47


Slovenia (SI) 1093 8,00% 40,80% 33,40% 16,50% 1,30% 125M 2M251 711 346 536 161


South Korea (KR) 1315 5,00% 26,90% 34,40% 29,50% 4,20% 41M 83 449 377 226 19

Spain (ES) 1212 7,20% 38,90% 32,70% 19,60% 1,60% 49M 9M63 361 367 243 41

Sweden (SE) 1186 5,90% 33,60% 34,10% 22,60% 3,80% 96M 15M31 418 226 256 26


Taiwan (TW) 2016 6,80% 43,60% 24,00% 24,10% 1,40% 173M 35M53 286 392 342 65


Uruguay (UY) 1108 5,40% 28,60% 26,70% 32,20% 7,20% 156M 4M201 632 17 243 38



V44 International organizations are taking away too much power from the [Country nationality] government. Missing Values: 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) d. International organizations are taking away too much power from the [COUNTRY NATIONALITY] government. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V44 (N) % % % % % % % 201 643 678 450 45

Australia (AU) 2183 10,00% 31,90% 33,60% 22,30% 2,20% 122M 44M158 345 195 164 41

Austria (AT) 1006 17,50% 38,20% 21,60% 18,20% 4,50% 103M 160 276 171 85 39

Bulgaria (BG) 1069 21,90% 37,80% 23,40% 11,60% 5,30% 305M 33M83 270 433 292 17

Canada (CA) 1211 7,60% 24,70% 39,50% 26,70% 1,60% 105M 11M137 604 321 238 17

Chile (CL) 1505 10,40% 45,90% 24,40% 18,10% 1,30% 177M 11M139 379 370 186 28


Denmark (DK) 1322 23,90% 33,60% 18,50% 15,80% 8,20% 108M 28M137 400 379 253 13

Finland (FI) 1379 11,60% 33,80% 32,10% 21,40% 1,10% 144M 53M266 491 390 290 69

France (FR) 1669 17,70% 32,60% 25,90% 19,30% 4,60% 85M 78M41 216 201 220 36




Hungary (HU) 1021 11,70% 32,00% 30,00% 22,30% 4,10% 204M 4M84 448 144 308 16

Ireland (IE) 1065 8,40% 44,80% 14,40% 30,80% 1,60% 62M 3M183 366 247 170 49



Japan (JP) 1102 10,20% 18,20% 41,60% 13,50% 16,50% 300M 7M52 231 321 180 16

Latvia (LV) 1000 6,50% 28,90% 40,10% 22,50% 2,00% 200M 114 260 315 237 9

New Zealand (NZ) 1036 12,20% 27,80% 33,70% 25,30% 1,00% 81M 20M141 452 424 270 23

Norway (NO) 1469 10,80% 34,50% 32,40% 20,60% 1,80% 130M 29M75 347 360 226 16

Poland (PL) 1277 7,30% 33,90% 35,20% 22,10% 1,60% 251M 2M185 587 298 203 24

Portugal (PT) 1602 14,30% 45,30% 23,00% 15,70% 1,90% 211M 94M106 296 348 336 63

Philippines (PH) 1200 9,20% 25,80% 30,30% 29,20% 5,50% 51M 345 514 431 264 90

Russia (RU) 2383 21,00% 31,30% 26,20% 16,10% 5,50% 739M 99 362 373 159 18


Slovenia (SI) 1093 8,20% 37,20% 31,10% 21,50% 2,00% 107M 5M250 797 364 395 83


South Korea (KR) 1315 13,20% 47,10% 30,60% 7,90% 1,10% 61M 57 387 434 187 27

Spain (ES) 1212 5,20% 35,40% 39,70% 17,10% 2,50% 100M 20M83 393 356 161 28

Sweden (SE) 1186 8,10% 38,50% 34,90% 15,80% 2,70% 154M 11M23 292 188 405 16


Taiwan (TW) 2016 8,60% 48,30% 25,80% 16,10% 1,20% 282M 42M112 303 377 329 28


Uruguay (UY) 1108 19,90% 46,10% 16,70% 15,10% 2,20% 117M 3M103 414 9 502 88



V45 Increased exposure to foreign films, music, and books is damaging our national and local cultures. Missing Values: 0; 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) e. Increased exposure to foreign films, music, and books is damaging our national and local cultures. 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in New-Zealand


0 1 2 3 4 5 8 9

V45 (N) % % % % % % % % 165 339 454 889 249

Australia (AU) 2183 - 7,90% 16,20% 21,70% 42,40% 11,90% 52M 35M107 185 170 253 234

Austria (AT) 1006 - 11,30% 19,50% 17,90% 26,70% 24,70% 57M 256 303 138 134 108

Bulgaria (BG) 1069 - 27,30% 32,30% 14,70% 14,30% 11,50% 101M 29M60 170 235 561 143

Canada (CA) 1211 - 5,10% 14,50% 20,10% 48,00% 12,20% 31M 11M278 585 253 264 36

Chile (CL) 1505 - 19,60% 41,30% 17,90% 18,60% 2,50% 81M 8M220 436 259 232 52


Denmark (DK) 1322 - 9,00% 19,10% 17,00% 24,70% 30,20% 46M 19M64 164 304 552 195

Finland (FI) 1379 - 5,00% 12,80% 23,80% 43,20% 15,20% 48M 52M304 369 305 388 202

France (FR) 1669 - 19,40% 23,50% 19,50% 24,70% 12,90% 27M 74M58 139 176 247 182




Hungary (HU) 1021 - 20,60% 32,90% 22,30% 18,90% 5,30% 67M 3M129 305 105 425 70

Ireland (IE) 1065 - 12,50% 29,50% 10,20% 41,10% 6,80% 31M 157 191 172 342 176

Israel Jews (IL-J) 1066 - 15,10% 18,40% 16,60% 32,90% 17,00% 21M 7M42 51 36 19 4

Israel Arabs (IL-A) 152 - 27,60% 33,60% 23,70% 12,50% 2,60% 81 177 240 160 314

Japan (JP) 1102 - 8,30% 18,20% 24,70% 16,50% 32,30% 127M 3M221 312 209 211 22

Latvia (LV) 1000 - 22,70% 32,00% 21,40% 21,60% 2,30% 25M 1036M

New Zealand (NZ) 1036 - - - - - 49 221 325 607 179

Norway (NO) 1469 - 3,50% 16,00% 23,50% 44,00% 13,00% 61M 27M102 319 238 421 64

Poland (PL) 1277 - 8,90% 27,90% 20,80% 36,80% 5,60% 132M 1M198 611 249 315 56

Portugal (PT) 1602 - 13,90% 42,80% 17,40% 22,00% 3,90% 84M 89M165 395 289 271 54

Philippines (PH) 1200 - 14,10% 33,60% 24,60% 23,10% 4,60% 26M 1000 619 282 216 107

Russia (RU) 2383 - 45,00% 27,80% 12,70% 9,70% 4,80% 159M 234 357 275 209 46


Slovenia (SI) 1093 - 11,00% 30,60% 19,60% 32,10% 6,70% 31M 2M424 796 338 412 88

South Africa (ZA) 2483 - 20,60% 38,70% 16,40% 20,00% 4,30% 393M 32M163 444 292 330 60

South Korea (KR) 1315 - 12,60% 34,40% 22,70% 25,60% 4,70% 26M 69 412 301 306 69

Spain (ES) 1212 - 6,00% 35,60% 26,00% 26,40% 6,00% 45M 10M25 146 277 416 236

Sweden (SE) 1186 - 2,30% 13,30% 25,20% 37,80% 21,50% 74M 12M21 153 116 566 141

Switzerland (CH) 1037 - 2,10% 15,30% 11,60% 56,80% 14,10% 40M 72 487 432 787 92

Taiwan (TW) 2016 - 3,90% 26,00% 23,10% 42,10% 4,90% 114M 32M43 127 257 533 217


Uruguay (UY) 1108 - 19,30% 36,40% 14,10% 24,00% 6,30% 36M 2M138 421 11 510 73



V46 A benefit of the Internet is that it makes information available to more and more people worldwide. Missing Values: 8; 9 Q7.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) f. A benefit of the Internet is that it makes information available to more and more people worldwide. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


V46 (N) 1 2 3 4 5 8 9

% % % % % % % Australia (AU) 2183 613 1210 167 41 18 88M 46M

29,90% 59,10% 8,20% 2,00% 0,90%Austria (AT) 1006 580 253 71 32 16 54M

60,90% 26,60% 7,50% 3,40% 1,70%Bulgaria (BG) 1069 510 190 24 3 1 296M 45M

70,10% 26,10% 3,30% 0,40% 0,10%Canada (CA) 1211 485 596 59 24 11 29M 7M

41,30% 50,70% 5,00% 2,00% 0,90%Chile (CL) 1505 508 665 164 34 5 122M 7M

36,90% 48,30% 11,90% 2,50% 0,40%Czech Republic (CZ) 1276 537 384 135 29 8 83M 100M

49,10% 35,10% 12,40% 2,70% 0,70%Denmark (DK) 1322 945 214 58 9 12 64M 20M

76,30% 17,30% 4,70% 0,70% 1,00%Finland (FI) 1379 530 612 107 23 9 47M 51M

41,40% 47,80% 8,40% 1,80% 0,70%France (FR) 1669 716 548 158 65 47 61M 74M

46,70% 35,70% 10,30% 4,20% 3,10%Germany-West (DE-W) 850 253 402 68 24 11 90M 2M

33,40% 53,00% 9,00% 3,20% 1,50%Germany-East (DE-E) 437 107 223 35 11 6 51M 4M

28,00% 58,40% 9,20% 2,90% 1,60%Great Britain (GB) 873 276 414 100 16 4 48M 15M

34,10% 51,10% 12,30% 2,00% 0,50%Hungary (HU) 1021 336 354 147 27 5 149M 3M

38,70% 40,70% 16,90% 3,10% 0,60%Ireland (IE) 1065 371 546 58 30 7 52M 1M

36,70% 54,00% 5,70% 3,00% 0,70%Israel Jews (IL-J) 1066 609 308 67 15 18 35M 14M

59,90% 30,30% 6,60% 1,50% 1,80%Israel Arabs (IL-A) 152 67 54 21 7 2 1M

44,40% 35,80% 13,90% 4,60% 1,30%Japan (JP) 1102 644 245 71 13 22 103M 4M

64,70% 24,60% 7,10% 1,30% 2,20%Latvia (LV) 1000 383 409 96 22 8 82M

41,70% 44,60% 10,50% 2,40% 0,90%New Zealand (NZ) 1036 390 533 55 9 3 29M 17M

39,40% 53,80% 5,60% 0,90% 0,30%Norway (NO) 1469 469 814 95 23 7 38M 23M

33,30% 57,80% 6,70% 1,60% 0,50%Poland (PL) 1277 350 606 114 24 6 176M 1M

31,80% 55,10% 10,40% 2,20% 0,50%Portugal (PT) 1602 483 575 171 36 7 238M 92M

38,00% 45,20% 13,40% 2,80% 0,60%Philippines (PH) 1200 223 426 293 155 38 65M

19,60% 37,50% 25,80% 13,70% 3,30%Russia (RU) 2383 917 635 179 66 41 545M

49,90% 34,50% 9,70% 3,60% 2,20%Slovak Republic (SK) 1152 565 444 90 18 1 34M

50,50% 39,70% 8,10% 1,60% 0,10%Slovenia (SI) 1093 454 494 48 21 9 65M 2M

44,20% 48,10% 4,70% 2,00% 0,90%South Africa (ZA) 2483 690 811 217 55 7 670M 33M

38,80% 45,60% 12,20% 3,10% 0,40%South Korea (KR) 1315 378 644 203 43 11 36M

29,60% 50,40% 15,90% 3,40% 0,90%Spain (ES) 1212 204 611 244 58 4 81M 10M

18,20% 54,50% 21,80% 5,20% 0,40%Sweden (SE) 1186 470 539 97 12 11 47M 10M

41,60% 47,70% 8,60% 1,10% 1,00%Switzerland (CH) 1037 265 626 62 23 4 56M 1M

27,00% 63,90% 6,30% 2,30% 0,40%Taiwan (TW) 2016 684 1074 105 43 7 74M 29M

35,80% 56,10% 5,50% 2,20% 0,40%United States (US) 1216 574 519 79 20 6 17M 1M

47,90% 43,30% 6,60% 1,70% 0,50%Uruguay (UY) 1108 301 576 67 34 15 111M 4M

30,30% 58,00% 6,70% 3,40% 1,50%Venezuela (VE) 1199 397 647 5 96 13 23M 18M

34,30% 55,90% 0,40% 8,30% 1,10%Sum 44170 16284 18201 3730 1161 400 3759M 635M


V47 It is impossible for people who do not share [Country’s] customs and traditions to become fully [Country’s nationality] Missing Values: 0; 8; 9 Q8.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) a. It is impossible for people who do not share [COUNTRY’s] customs and traditions to become fully [COUNTRY’S NATIONALITY] 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Chile


0 1 2 3 4 5 8 9

V47 (N) % % % % % % % % 280 633 357 676 188

Australia (AU) 2183 - 13,10% 29,70% 16,70% 31,70% 8,80% 34M 15M295 290 135 160 93

Austria (AT) 1006 - 30,30% 29,80% 13,90% 16,40% 9,60% 33M 624 233 67 38 38

Bulgaria (BG) 1069 - 62,40% 23,30% 6,70% 3,80% 3,80% 48M 21M194 297 146 429 115

Canada (CA) 1211 - 16,40% 25,10% 12,40% 36,30% 9,70% 26M 4M1505M

Chile (CL) 1505 - - - - - 238 381 270 221 64


Denmark (DK) 1322 - 30,10% 31,30% 8,00% 16,90% 13,90% 32M 20M311 476 262 242 23

Finland (FI) 1379 - 23,70% 36,20% 19,90% 18,40% 1,80% 29M 36M559 405 247 223 170

France (FR) 1669 - 34,90% 25,20% 15,40% 13,90% 10,60% 12M 53M147 280 147 153 50




Hungary (HU) 1021 - 24,00% 36,90% 21,50% 13,90% 3,70% 47M 3M105 441 94 366 37

Ireland (IE) 1065 - 10,10% 42,30% 9,00% 35,10% 3,50% 21M 1M203 296 187 263 103


Israel Arabs (IL-A) 152 - 11,20% 22,40% 18,40% 32,20% 15,80% 302 272 191 113 188

Japan (JP) 1102 - 28,30% 25,50% 17,90% 10,60% 17,60% 36M 216 397 202 145 24

Latvia (LV) 1000 - 22,00% 40,30% 20,50% 14,70% 2,40% 16M 121 248 177 372 81

New Zealand (NZ) 1036 - 12,10% 24,80% 17,70% 37,20% 8,10% 22M 15M306 572 244 265 49

Norway (NO) 1469 - 21,30% 39,80% 17,00% 18,50% 3,40% 21M 12M139 442 276 273 25

Poland (PL) 1277 - 12,00% 38,30% 23,90% 23,60% 2,20% 121M 1M239 640 205 325 74

Portugal (PT) 1602 - 16,10% 43,20% 13,80% 21,90% 5,00% 28M 91M177 495 300 178 35

Philippines (PH) 1200 - 14,90% 41,80% 25,30% 15,00% 3,00% 15M 1229 772 171 91 41

Russia (RU) 2383 - 53,30% 33,50% 7,40% 3,90% 1,80% 79M 132 245 331 334 62


Slovenia (SI) 1093 - 21,00% 31,70% 17,30% 25,90% 4,10% 25M 1M463 922 253 468 146


South Korea (KR) 1315 - 15,40% 40,20% 21,20% 20,80% 2,40% 13M 75 541 290 222 42

Spain (ES) 1212 - 6,40% 46,20% 24,80% 19,00% 3,60% 32M 10M186 395 286 194 85

Sweden (SE) 1186 - 16,20% 34,50% 25,00% 16,90% 7,40% 35M 5M78 408 159 322 45


Taiwan (TW) 2016 - 1,70% 18,10% 18,00% 53,40% 8,70% 68M 25M109 281 252 437 110


Uruguay (UY) 1108 - 11,70% 41,40% 16,60% 25,50% 4,80% 44M 3M143 445 14 477 97



V48 Ethnic minorities should be given government assistance to preserve their customs and traditions Missing Values: 0; 8; 9 Q8.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) b. Ethnic minorities should be given government assistance to preserve their customs and traditions1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Chile


0 1 2 3 4 5 8 9

V48 (N) % % % % % % % % 59 296 417 876 457

Australia (AU) 2183 - 2,80% 14,10% 19,80% 41,60% 21,70% 59M 19M86 268 200 246 161

Austria (AT) 1006 - 8,90% 27,90% 20,80% 25,60% 16,80% 45M 342 303 159 94 96

Bulgaria (BG) 1069 - 34,40% 30,50% 16,00% 9,50% 9,70% 66M 9M37 157 204 503 269

Canada (CA) 1211 - 3,20% 13,40% 17,40% 43,00% 23,00% 33M 8M1505M

Chile (CL) 1505 - - - - - 105 320 367 215 144


Denmark (DK) 1322 - 2,80% 12,10% 10,20% 21,00% 53,70% 30M 23M107 470 337 254 96

Finland (FI) 1379 - 8,50% 37,20% 26,70% 20,10% 7,60% 73M 42M83 225 374 443 439

France (FR) 1669 - 5,30% 14,40% 23,90% 28,30% 28,10% 40M 65M29 205 220 220 100




Hungary (HU) 1021 - 23,90% 44,10% 23,70% 6,40% 1,90% 33M 4M41 377 187 360 71

Ireland (IE) 1065 - 4,00% 36,40% 18,10% 34,70% 6,90% 27M 2M230 395 213 142 69


Israel Arabs (IL-A) 152 - 52,00% 30,90% 11,20% 3,90% 2,00% 201 318 245 99 123

Japan (JP) 1102 - 20,40% 32,30% 24,80% 10,00% 12,50% 115M 1M111 417 233 147 54

Latvia (LV) 1000 - 11,50% 43,30% 24,20% 15,30% 5,60% 38M 38 140 199 408 213

New Zealand (NZ) 1036 - 3,80% 14,00% 19,90% 40,90% 21,30% 21M 17M34 204 302 539 334

Norway (NO) 1469 - 2,40% 14,40% 21,40% 38,10% 23,60% 42M 14M136 723 240 67 8

Poland (PL) 1277 - 11,60% 61,60% 20,40% 5,70% 0,70% 102M 1M194 663 327 182 44

Portugal (PT) 1602 - 13,80% 47,00% 23,20% 12,90% 3,10% 94M 98M434 530 178 42 10

Philippines (PH) 1200 - 36,30% 44,40% 14,90% 3,50% 0,80% 6M 764 731 325 175 109

Russia (RU) 2383 - 36,30% 34,70% 15,40% 8,30% 5,20% 279M 97 367 390 184 58


Slovenia (SI) 1093 - 19,50% 55,60% 15,50% 7,60% 1,80% 29M 3M492 1042 321 254 88


South Korea (KR) 1315 - 14,60% 47,80% 24,90% 10,00% 2,60% 16M 41 434 426 209 44

Spain (ES) 1212 - 3,60% 37,60% 36,90% 18,10% 3,80% 43M 15M43 225 399 299 143

Sweden (SE) 1186 - 3,90% 20,30% 36,00% 27,00% 12,90% 70M 7M29 398 187 345 55


Taiwan (TW) 2016 - 26,70% 63,70% 6,40% 2,70% 0,40% 51M 24M50 222 300 455 160


Uruguay (UY) 1108 - 10,40% 48,50% 22,60% 15,30% 3,20% 104M 4M448 649 4 57 8



V49 Help minorities to preserve traditions Missing Values: 8; 9 Q9.- Some people say that it is better for a country if different racial and ethnic groups maintain their distinct customs and traditions. Others say that it is better if these groups adapt and blend into the larger society. Which of these views comes closer to your own? 1. It is better for society if groups maintain their distinct customs and traditions. 2. It is better if groups adapt and blend into the larger society. 8. Can´t choose. 9. Na, refused.


1 2 8 9

V49 (N) % % % % 336 1515

Australia (AU) 2183 18,20% 81,80% 278M 54M280 582

Austria (AT) 1006 32,50% 67,50% 144M 576 312

Bulgaria (BG) 1069 64,90% 35,10% 166M 15M296 727

Canada (CA) 1211 28,90% 71,10% 188M891 535

Chile (CL) 1505 62,50% 37,50% 55M 24M393 578

Czech Republic (CZ) 1276 40,50% 59,50% 134M 171M138 1011

Denmark (DK) 1322 12,00% 88,00% 159M 14M387 629

Finland (FI) 1379 38,10% 61,90% 344M 19M364 996

France (FR) 1669 26,80% 73,20% 215M 94M210 377

Germany-West (DE-W) 850 35,80% 64,20% 257M 6M128 209

Germany-East (DE-E) 437 38,00% 62,00% 95M 5M158 481

Great Britain (GB) 873 24,70% 75,30% 212M 22M482 348

Hungary (HU) 1021 58,10% 41,90% 107M 84M312 604

Ireland (IE) 1065 34,10% 65,90% 144M 5M611 382

Israel Jews (IL-J) 1066 61,50% 38,50% 41M 32M97 44

Israel Arabs (IL-A) 152 68,80% 31,20% 3M 8M728 91

Japan (JP) 1102 88,90% 11,10% 275M 8M613 245

Latvia (LV) 1000 71,40% 28,60% 142M 273 597

New Zealand (NZ) 1036 31,40% 68,60% 119M 47M258 1018

Norway (NO) 1469 20,20% 79,80% 163M 30M660 274

Poland (PL) 1277 70,70% 29,30% 330M 13M566 746

Portugal (PT) 1602 43,10% 56,90% 167M 123M550 597

Philippines (PH) 1200 48,00% 52,00% 53M 1412 522

Russia (RU) 2383 73,00% 27,00% 449M 566 347

Slovak Republic (SK) 1152 62,00% 38,00% 239M 587 416

Slovenia (SI) 1093 58,50% 41,50% 88M 2M1170 834

South Africa (ZA) 2483 58,40% 41,60% 434M 45M567 626

South Korea (KR) 1315 47,50% 52,50% 122M 345 736

Spain (ES) 1212 31,90% 68,10% 91M 40M151 839

Sweden (SE) 1186 15,30% 84,70% 166M 30M413 485

Switzerland (CH) 1037 46,00% 54,00% 100M 39M1423 531

Taiwan (TW) 2016 72,80% 27,20% 26M 36M554 615

United States (US) 1216 47,40% 52,60% 28M 19M407 625

Uruguay (UY) 1108 39,40% 60,60% 73M 3M947 214

Venezuela (VE) 1199 81,60% 18,40% 27M 11MSum 44170 17849 19688 5446M 1187M


V50 Immigrants increase crime rates Missing Values: 0; 8; 9 Q10.- There are different opinions about immigrants from other countries living in [COUNTRY]. (By “immigrants” we mean people who come to settle in [COUNTRY])1. How much do you agree or disagree with each of the following statements? (Please, tick one box on each line) a. Immigrants increase crime rates1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa

1 The preceding parenthetical comment is part of the question wording


0 1 2 3 4 5 8 9

V50 (N) % % % % % % % % 222 509 602 615 150

Australia (AU) 2183 - 10,60% 24,30% 28,70% 29,30% 7,10% 47M 38M354 321 133 108 65

Austria (AT) 1006 - 36,10% 32,70% 13,60% 11,00% 6,60% 25M 153 318 140 128 68

Bulgaria (BG) 1069 - 19,00% 39,40% 17,30% 15,90% 8,40% 241M 21M91 226 315 418 113

Canada (CA) 1211 - 7,80% 19,40% 27,10% 35,90% 9,70% 43M 5M114 409 228 556 86

Chile (CL) 1505 - 8,20% 29,40% 16,40% 39,90% 6,20% 100M 12M422 430 217 79 13


Denmark (DK) 1322 - 36,50% 36,10% 11,30% 10,30% 5,70% 30M 16M215 408 390 235 36

Finland (FI) 1379 - 16,70% 31,80% 30,40% 18,30% 2,80% 69M 26M312 371 321 282 282

France (FR) 1669 - 19,90% 23,70% 20,50% 18,00% 18,00% 40M 61M136 356 164 101 29




Hungary (HU) 1021 - 31,70% 35,90% 20,30% 10,00% 2,10% 35M 4M79 318 190 394 55

Ireland (IE) 1065 - 7,60% 30,70% 18,30% 38,00% 5,30% 28M 1M183 288 213 254 107


Israel Arabs (IL-A) 152 - 50,30% 35,80% 7,30% 4,00% 2,60% 1M498 277 187 66 52

Japan (JP) 1102 - 46,10% 25,60% 17,30% 6,10% 4,80% 22M 83 239 244 308 40

Latvia (LV) 1000 - 9,10% 26,10% 26,70% 33,70% 4,40% 86M 83 218 332 312 50

New Zealand (NZ) 1036 - 8,30% 21,90% 33,40% 31,40% 5,00% 21M 20M452 682 215 70 18

Norway (NO) 1469 - 31,50% 47,50% 15,00% 4,90% 1,30% 21M 11M143 461 284 251 14

Poland (PL) 1277 - 12,40% 40,00% 24,60% 21,80% 1,20% 123M 1M212 656 204 328 59

Portugal (PT) 1602 - 14,50% 45,00% 14,00% 22,50% 4,00% 53M 90M110 241 324 386 115

Philippines (PH) 1200 - 9,40% 20,50% 27,60% 32,80% 9,80% 24M 812 652 294 220 102

Russia (RU) 2383 - 39,00% 31,30% 14,10% 10,60% 4,90% 303M 176 305 374 177 37


Slovenia (SI) 1093 - 18,40% 35,30% 19,80% 22,20% 4,20% 34M 1M2483M

South Africa (ZA) 2483 - - - - - 90 337 375 397 93

South Korea (KR) 1315 - 7,00% 26,10% 29,00% 30,70% 7,20% 23M 132 539 217 214 61

Spain (ES) 1212 - 11,30% 46,30% 18,70% 18,40% 5,20% 29M 20M221 430 281 142 65

Sweden (SE) 1186 - 19,40% 37,80% 24,70% 12,50% 5,70% 37M 10M130 451 174 223 29


Taiwan (TW) 2016 - 13,70% 48,30% 16,50% 20,70% 0,80% 66M 16M83 235 345 437 84


Uruguay (UY) 1108 - 2,90% 12,00% 18,70% 48,60% 17,70% 74M 2M87 321 9 601 145



V51 Immigrants are generally good for [Country’s] economy Missing Values: 0; 8; 9 Q10.- There are different opinions about immigrants from other countries living in [COUNTRY]. (By “immigrants” we mean people who come to settle in [COUNTRY])2. How much do you agree or disagree with each of the following statements? (Please, tick one box on each line) b. Immigrants are generally good for [COUNTRY’S] economy1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa



0 1 2 3 4 5 8 9

V51 (N) % % % % % % % % 215 1262 443 151 23

Australia (AU) 2183 - 10,30% 60,30% 21,20% 7,20% 1,10% 57M 32M68 294 277 221 88

Austria (AT) 1006 - 7,20% 31,00% 29,20% 23,30% 9,30% 58M 22 90 244 207 199

Bulgaria (BG) 1069 - 2,90% 11,80% 32,00% 27,20% 26,10% 281M 26M132 598 289 132 14

Canada (CA) 1211 - 11,30% 51,30% 24,80% 11,30% 1,20% 41M 5M69 397 418 453 47

Chile (CL) 1505 - 5,00% 28,70% 30,20% 32,70% 3,40% 110M 11M37 139 358 441 184


Denmark (DK) 1322 - 8,30% 22,40% 23,40% 22,30% 23,60% 96M 16M22 232 409 400 156

Finland (FI) 1379 - 1,80% 19,00% 33,60% 32,80% 12,80% 121M 39M109 433 449 320 235

France (FR) 1669 - 7,10% 28,00% 29,00% 20,70% 15,20% 63M 60M11 208 302 186 59




Hungary (HU) 1021 - 2,20% 10,30% 37,70% 35,40% 14,40% 47M 4M37 371 218 361 43

Ireland (IE) 1065 - 3,60% 36,00% 21,20% 35,00% 4,20% 32M 3M169 369 226 194 78



Japan (JP) 1102 - 8,10% 28,00% 38,20% 10,20% 15,40% 149M 1M14 165 329 344 57

Latvia (LV) 1000 - 1,50% 18,20% 36,20% 37,80% 6,30% 91M 57 536 260 128 24

New Zealand (NZ) 1036 - 5,70% 53,30% 25,90% 12,70% 2,40% 16M 15M21 390 517 300 120

Norway (NO) 1469 - 1,60% 28,90% 38,40% 22,30% 8,90% 105M 16M20 215 449 359 38

Poland (PL) 1277 - 1,90% 19,90% 41,50% 33,20% 3,50% 195M 1M143 649 298 239 51

Portugal (PT) 1602 - 10,40% 47,00% 21,60% 17,30% 3,70% 126M 96M92 391 386 244 57

Philippines (PH) 1200 - 7,90% 33,40% 33,00% 20,90% 4,90% 30M 85 313 482 651 382

Russia (RU) 2383 - 4,40% 16,40% 25,20% 34,00% 20,00% 470M 9 81 406 433 92


Slovenia (SI) 1093 - 4,10% 27,00% 34,10% 30,00% 4,80% 46M 1M2483M

South Africa (ZA) 2483 - - - - - 81 614 392 181 22

South Korea (KR) 1315 - 6,30% 47,60% 30,40% 14,00% 1,70% 25M 61 506 395 167 24

Spain (ES) 1212 - 5,30% 43,90% 34,30% 14,50% 2,10% 39M 20M65 408 379 142 75

Sweden (SE) 1186 - 6,10% 38,20% 35,50% 13,30% 7,00% 104M 13M44 493 229 229 11


Taiwan (TW) 2016 - 1,70% 34,00% 23,00% 36,00% 5,20% 89M 19M80 458 355 236 55


Uruguay (UY) 1108 - 5,70% 34,00% 37,80% 19,50% 2,90% 86M 4M111 541 16 437 38



V52 Immigrants take jobs away from people who were born in [Country] Missing Values: 0; 8; 9 Q10.- There are different opinions about immigrants from other countries living in [COUNTRY]. (By “immigrants” we mean people who come to settle in [COUNTRY])3. How much do you agree or disagree with each of the following statements? (Please, tick one box on each line) c. Immigrants take jobs away from people who were born in [COUNTRY] 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa



0 1 2 3 4 5 8 9

V52 (N) % % % % % % % % 137 400 529 880 168

Australia (AU) 2183 - 6,50% 18,90% 25,00% 41,60% 7,90% 34M 35M142 248 223 220 142

Austria (AT) 1006 - 14,60% 25,40% 22,90% 22,60% 14,60% 31M 252 291 143 104 65

Bulgaria (BG) 1069 - 29,50% 34,00% 16,70% 12,20% 7,60% 191M 23M85 233 280 482 99

Canada (CA) 1211 - 7,20% 19,80% 23,70% 40,90% 8,40% 27M 5M353 602 213 248 24

Chile (CL) 1505 - 24,50% 41,80% 14,80% 17,20% 1,70% 57M 8M285 399 284 153 43


Denmark (DK) 1322 - 6,00% 9,80% 17,60% 26,40% 40,10% 47M 16M116 238 326 480 124

Finland (FI) 1379 - 9,00% 18,50% 25,40% 37,40% 9,70% 51M 44M188 216 327 397 446

France (FR) 1669 - 11,90% 13,70% 20,80% 25,20% 28,30% 28M 67M93 210 229 182 69




Hungary (HU) 1021 - 23,90% 32,20% 25,50% 15,50% 2,90% 29M 4M89 381 132 413 39

Ireland (IE) 1065 - 8,40% 36,10% 12,50% 39,20% 3,70% 9M 2M257 237 155 249 150


Israel Arabs (IL-A) 152 - 55,60% 30,50% 6,00% 4,00% 4,00% 1M 115 164 303 202 227

Japan (JP) 1102 - 11,40% 16,20% 30,00% 20,00% 22,50% 91M 120 338 224 235 25

Latvia (LV) 1000 - 12,70% 35,90% 23,80% 24,90% 2,70% 58M 110 248 248 361 47

New Zealand (NZ) 1036 - 10,80% 24,50% 24,50% 35,60% 4,60% 10M 12M62 148 332 699 171

Norway (NO) 1469 - 4,40% 10,50% 23,50% 49,50% 12,10% 39M 18M172 541 248 226 15

Poland (PL) 1277 - 14,30% 45,00% 20,60% 18,80% 1,20% 72M 3M238 588 183 408 74

Portugal (PT) 1602 - 16,00% 39,40% 12,30% 27,40% 5,00% 20M 91M161 383 306 260 71

Philippines (PH) 1200 - 13,60% 32,40% 25,90% 22,00% 6,00% 19M 733 669 362 297 116

Russia (RU) 2383 - 33,70% 30,70% 16,60% 13,60% 5,30% 206M 134 302 392 248 25


Slovenia (SI) 1093 - 13,30% 34,70% 21,70% 26,10% 4,20% 29M 3M2483M

South Africa (ZA) 2483 - - - - - 61 243 370 505 111

South Korea (KR) 1315 - 4,70% 18,80% 28,70% 39,10% 8,60% 25M 88 384 221 378 93

Spain (ES) 1212 - 7,60% 33,00% 19,00% 32,50% 8,00% 25M 23M28 60 308 496 241

Sweden (SE) 1186 - 2,50% 5,30% 27,20% 43,80% 21,30% 44M 9M33 144 166 603 75

Switzerland (CH) 1037 - 3,20% 14,10% 16,30% 59,10% 7,30% 16M 473 1127 169 173 20

Taiwan (TW) 2016 - 24,10% 57,40% 8,60% 8,80% 1,00% 40M 14M153 363 274 343 67


Uruguay (UY) 1108 - 7,00% 30,30% 18,90% 35,00% 8,80% 27M 2M101 426 7 551 95



V53 Immigrants improve [Country nationality] society by bringing in new ideas and cultures Missing Values: 0; 8; 9 Q10.- There are different opinions about immigrants from other countries living in [COUNTRY]. (By “immigrants” we mean people who come to settle in [COUNTRY])4. How much do you agree or disagree with each of the following statements? (Please, tick one box on each line) d. Immigrants improve [COUNTRY NATIONALITY] society by bringing in new ideas and cultures1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa



0 1 2 3 4 5 8 9

V53 (N) % % % % % % % % 361 1231 366 143 29

Australia (AU) 2183 - 16,90% 57,80% 17,20% 6,70% 1,40% 30M 23M104 347 232 196 89

Austria (AT) 1006 - 10,70% 35,80% 24,00% 20,20% 9,20% 38M 93 273 199 109 104

Bulgaria (BG) 1069 - 12,00% 35,10% 25,60% 14,00% 13,40% 267M 24M162 627 239 119 27

Canada (CA) 1211 - 13,80% 53,40% 20,40% 10,10% 2,30% 32M 5M78 469 389 411 56

Chile (CL) 1505 - 5,60% 33,40% 27,70% 29,30% 4,00% 93M 9M30 167 386 380 186


Denmark (DK) 1322 - 19,80% 40,10% 16,90% 10,60% 12,60% 40M 16M90 510 362 206 99

Finland (FI) 1379 - 7,10% 40,30% 28,60% 16,30% 7,80% 71M 41M165 480 386 287 244

France (FR) 1669 - 10,60% 30,70% 24,70% 18,40% 15,60% 41M 66M56 387 195 102 44




Hungary (HU) 1021 - 3,30% 21,20% 34,50% 31,10% 10,00% 102M 5M59 534 160 242 43

Ireland (IE) 1065 - 5,70% 51,40% 15,40% 23,30% 4,10% 24M 3M181 338 198 218 119



Japan (JP) 1102 - 4,50% 14,90% 44,50% 14,30% 21,80% 153M 3M36 256 321 234 67

Latvia (LV) 1000 - 3,90% 28,00% 35,10% 25,60% 7,30% 86M 104 508 232 144 24

New Zealand (NZ) 1036 - 10,30% 50,20% 22,90% 14,20% 2,40% 12M 12M68 532 432 275 107

Norway (NO) 1469 - 4,80% 37,60% 30,60% 19,40% 7,60% 39M 16M28 271 414 308 46

Poland (PL) 1277 - 2,60% 25,40% 38,80% 28,90% 4,30% 207M 3M134 621 347 264 54

Portugal (PT) 1602 - 9,40% 43,70% 24,40% 18,60% 3,80% 90M 92M115 400 375 223 65

Philippines (PH) 1200 - 9,80% 34,00% 31,80% 18,90% 5,50% 22M 121 390 474 505 358

Russia (RU) 2383 - 6,50% 21,10% 25,60% 27,30% 19,40% 535M 25 195 446 315 83


Slovenia (SI) 1093 - 5,90% 38,60% 28,00% 24,00% 3,60% 49M 4M2483M

South Africa (ZA) 2483 - - - - - 50 316 571 302 42

South Korea (KR) 1315 - 3,90% 24,70% 44,60% 23,60% 3,30% 34M 73 615 315 131 15

Spain (ES) 1212 - 6,40% 53,50% 27,40% 11,40% 1,30% 38M 25M118 543 305 108 55

Sweden (SE) 1186 - 10,50% 48,10% 27,00% 9,60% 4,90% 46M 11M121 660 137 90 9


Taiwan (TW) 2016 - 7,10% 49,30% 17,30% 24,40% 1,90% 117M 23M119 563 294 176 40


Uruguay (UY) 1108 - 6,80% 47,20% 28,30% 15,70% 2,10% 44M 4M97 654 17 342 40



V54 Government spends too much money assisting immigrants. Missing Values: 0; 8; 9 Q10.- There are different opinions about immigrants from other countries living in [COUNTRY]. (By “immigrants” we mean people who come to settle in [COUNTRY])5. How much do you agree or disagree with each of the following statements? (Please, tick one box on each line) e. Government spends too much money assisting immigrants1. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa



0 1 2 3 4 5 8 9

V54 (N) % % % % % % % % 361 552 616 431 110

Australia (AU) 2183 - 17,40% 26,70% 29,80% 20,80% 5,30% 82M 31M286 259 156 130 68

Austria (AT) 1006 - 31,80% 28,80% 17,40% 14,50% 7,60% 107M 96 156 162 73 52

Bulgaria (BG) 1069 - 17,80% 28,90% 30,10% 13,50% 9,60% 489M 41M200 329 340 220 30

Canada (CA) 1211 - 17,90% 29,40% 30,40% 19,70% 2,70% 85M 7M134 533 319 274 26

Chile (CL) 1505 - 10,40% 41,40% 24,80% 21,30% 2,00% 205M 14M276 352 319 132 17


Denmark (DK) 1322 - 25,00% 22,80% 20,60% 16,60% 15,10% 65M 15M312 348 321 197 50

Finland (FI) 1379 - 25,40% 28,30% 26,10% 16,00% 4,10% 126M 25M418 346 366 201 207

France (FR) 1669 - 27,20% 22,50% 23,80% 13,10% 13,50% 73M 58M216 301 127 92 24




Hungary (HU) 1021 - 28,20% 36,70% 21,40% 11,70% 2,00% 168M 4M231 421 159 189 29

Ireland (IE) 1065 - 22,40% 40,90% 15,50% 18,40% 2,80% 35M 1M143 190 262 288 127



Japan (JP) 1102 - 17,10% 16,10% 33,30% 16,50% 17,10% 360M 3M42 178 295 168 56

Latvia (LV) 1000 - 5,70% 24,10% 39,90% 22,70% 7,60% 261M 216 306 284 157 23

New Zealand (NZ) 1036 - 21,90% 31,00% 28,80% 15,90% 2,30% 37M 13M360 467 333 165 43

Norway (NO) 1469 - 26,30% 34,10% 24,30% 12,10% 3,10% 87M 14M80 321 367 211 21

Poland (PL) 1277 - 8,00% 32,10% 36,70% 21,10% 2,10% 276M 1M105 294 293 514 84

Portugal (PT) 1602 - 8,10% 22,80% 22,70% 39,80% 6,50% 220M 92M90 289 322 337 120

Philippines (PH) 1200 - 7,80% 25,00% 27,80% 29,10% 10,40% 42M 512 473 353 218 130

Russia (RU) 2383 - 30,40% 28,10% 20,90% 12,90% 7,70% 697M 146 306 283 146 23


Slovenia (SI) 1093 - 15,20% 32,60% 27,00% 21,10% 4,10% 93M 2M2483M

South Africa (ZA) 2483 - - - - - 36 137 452 497 133

South Korea (KR) 1315 - 2,90% 10,90% 36,00% 39,60% 10,60% 60M 42 347 371 253 74

Spain (ES) 1212 - 3,90% 31,90% 34,10% 23,30% 6,80% 97M 28M184 254 354 188 96

Sweden (SE) 1186 - 17,10% 23,60% 32,90% 17,50% 8,90% 101M 9M109 334 168 303 29


Taiwan (TW) 2016 - 11,80% 41,90% 22,30% 22,10% 1,90% 182M 28M243 365 319 208 44


Uruguay (UY) 1108 - 3,80% 17,20% 23,50% 43,00% 12,50% 279M 8M74 355 16 575 93



V55 Number of immigrants coming to country Missing Values: 0; 8; 9 Q11.- Do you think the number of immigrants to [COUNTRY] nowadays should be1... 1. Increased a lot. 2. Increased a little. 3. Remain the same. 4. Reduced a little. 5. Reduced a lot. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in South-Africa


0 1 2 3 4 5 8 9

V55 (N) % % % % % % % % 123 350 758 426 361

Australia (AU) 2183 - 6,10% 17,30% 37,60% 21,10% 17,90% 151M 14M10 55 308 264 319

Austria (AT) 1006 - 1,00% 5,80% 32,20% 27,60% 33,40% 50M 9 24 216 203 172

Bulgaria (BG) 1069 - 1,40% 3,80% 34,60% 32,50% 27,60% 419M 26M75 239 418 225 123

Canada (CA) 1211 - 6,90% 22,10% 38,70% 20,80% 11,40% 127M 4M26 73 442 558 341

Chile (CL) 1505 - 1,80% 5,10% 30,70% 38,80% 23,70% 52M 13M10 40 289 369 467


Denmark (DK) 1322 - 1,30% 8,50% 38,80% 23,40% 28,00% 91M 8M44 261 506 213 216

Finland (FI) 1379 - 3,50% 21,00% 40,80% 17,20% 17,40% 133M 6M38 72 372 355 584

France (FR) 1669 - 2,70% 5,10% 26,20% 25,00% 41,10% 200M 48M7 34 185 202 334




Hungary (HU) 1021 - 0,40% 1,80% 28,90% 32,40% 36,50% 52M 7M13 80 325 307 289

Ireland (IE) 1065 - 1,30% 7,90% 32,10% 30,30% 28,50% 48M 3M170 142 304 146 256


Israel Arabs (IL-A) 152 - - 2,70% 14,70% 36,70% 46,00% 1M 1M26 93 315 246 222

Japan (JP) 1102 - 2,90% 10,30% 34,90% 27,30% 24,60% 193M 7M5 15 333 216 224

Latvia (LV) 1000 - 0,60% 1,90% 42,00% 27,20% 28,20% 207M 34 118 268 279 267

New Zealand (NZ) 1036 - 3,50% 12,20% 27,70% 28,90% 27,60% 53M 17M17 78 290 434 522

Norway (NO) 1469 - 1,30% 5,80% 21,60% 32,40% 38,90% 113M 15M22 45 370 264 248

Poland (PL) 1277 - 2,30% 4,70% 39,00% 27,80% 26,10% 327M 1M9 36 592 530 289

Portugal (PT) 1602 - 0,60% 2,50% 40,70% 36,40% 19,80% 55M 91M67 138 452 235 215

Philippines (PH) 1200 - 6,10% 12,50% 40,80% 21,20% 19,40% 93M 40 39 246 598 929

Russia (RU) 2383 - 2,20% 2,10% 13,30% 32,30% 50,20% 531M 24 82 290 180 304


Slovenia (SI) 1093 - 0,50% 2,60% 45,70% 33,60% 17,60% 54M 1M2483M

South Africa (ZA) 2483 - - - - - 70 231 454 307 120

South Korea (KR) 1315 - 5,90% 19,50% 38,40% 26,00% 10,20% 133M 29 81 433 419 158

Spain (ES) 1212 - 2,60% 7,20% 38,70% 37,40% 14,10% 66M 26M29 98 323 319 298

Sweden (SE) 1186 - 2,70% 9,20% 30,30% 29,90% 27,90% 107M 12M4 52 487 270 167


Taiwan (TW) 2016 - 1,20% 3,80% 20,30% 35,90% 38,80% 220M 12M45 78 354 338 278


Uruguay (UY) 1108 - 6,60% 14,30% 50,50% 21,90% 6,70% 79M 13M35 49 514 332 232



V56 Are you a citizen of [Country] Missing Values: 8; 9 Q12.- Are you a citizen of [COUNTRY]? 1. Yes. 2. No. 8. Can´t choose. 9. Na, refused.


V56 (N) 1 2 9

% % % Australia (AU) 2183 2115 51 17M

97,60% 2,40% Austria (AT) 1006 972 34

96,60% 3,40% Bulgaria (BG) 1069 1061 5 3M

99,50% 0,50% Canada (CA) 1211 1158 26 27M

97,80% 2,20% Chile (CL) 1505 1487 17 1M

98,90% 1,10% Czech Republic (CZ) 1276 7 1234 35M

0,60% 99,40% Denmark (DK) 1322 1316 - 6M

100,00% Finland (FI) 1379 1351 21 7M

98,50% 1,50% France (FR) 1669 1601 32 36M

98,00% 2,00% Germany-West (DE-W) 850 785 65

92,40% 7,60% Germany-East (DE-E) 437 432 5

98,90% 1,10% Great Britain (GB) 873 844 22 7M

97,50% 2,50% Hungary (HU) 1021 1021 -

100,00% Ireland (IE) 1065 1035 27 3M

97,50% 2,50% Israel Jews (IL-J) 1066 1054 11 1M

99,00% 1,00% Israel Arabs (IL-A) 152 152 -

100,00% Japan (JP) 1102 1102 -

100,00% Latvia (LV) 1000 793 207

79,30% 20,70% New Zealand (NZ) 1036 968 55 13M

94,60% 5,40% Norway (NO) 1469 1396 53 20M

96,30% 3,70% Poland (PL) 1277 1277 -

100,00% Portugal (PT) 1602 1514 88

94,50% 5,50% Philippines (PH) 1200 1200 -

100,00% Russia (RU) 2383 2379 4

99,80% 0,20% Slovak Republic (SK) 1152 1149 3

99,70% 0,30% Slovenia (SI) 1093 1088 4 1M

99,60% 0,40% South Africa (ZA) 2483 2389 30 64M

98,80% 1,20% South Korea (KR) 1315 1315 -

100,00% Spain (ES) 1212 1181 23 8M

98,10% 1,90% Sweden (SE) 1186 1135 43 8M

96,30% 3,70% Switzerland (CH) 1037 940 97

90,60% 9,40% Taiwan (TW) 2016 2015 1

100,00% % United States (US) 1216 1168 47 1M

96,10% 3,90% Uruguay (UY) 1108 1086 22

98,00% 2,00% Venezuela (VE) 1199 1138 61

94,90% 5,10% Sum 44170 41624 2288 258M


V57 Parents citizen of [country] at birth Missing Values: 0; 8; 9 Q13.- At the time of your birth, were both, one or neither of your parents citizens of [COUNTRY]1,2? 1. Both were citizens of. 2. Only father was a citizen of. 3. Only mother was s citizen of. 4. Neither parent was a citizen of. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: 1 If your country was recently part of a larger political union (e.g. Russia, Slovenia, and the Czech and Slovak Republics), parental citizenship should refer to the preceding national state that your country devolved from. 2 Question not asked in Slovenia


0 1 2 3 4 9

V57 (N) % % % % % % 1481 51 54 569

Australia (AU) 2183 68,70% 2,40% 2,50% 26,40% 28M860 18 23 103

Austria (AT) 1006 85,70% 1,80% 2,30% 10,30% 2M1047 4 3 6

Bulgaria (BG) 1069 98,80% 0,40% 0,30% 0,60% 9M999 33 16 154

Canada (CA) 1211 83,10% 2,70% 1,30% 12,80% 9M1471 8 12 13

Chile (CL) 1505 97,80% 0,50% 0,80% 0,90% 1M1148 30 37 13

Czech Republic (CZ) 1276 93,50% 2,40% 3,00% 1,10% 48M1259 7 15 32

Denmark (DK) 1322 95,90% 0,50% 1,10% 2,40% 9M1335 3 12 24

Finland (FI) 1379 97,20% 0,20% 0,90% 1,70% 5M1484 11 22 95

France (FR) 1669 92,10% 0,70% 1,40% 5,90% 57M715 6 13 109

Germany-West (DE-W) 850 84,80% 0,70% 1,50% 12,90% 7M422 2 12

Germany-East (DE-E) 437 96,80% - 0,50% 2,80% 1M796 8 13 49

Great Britain (GB) 873 91,90% 0,90% 1,50% 5,70% 7M1005 4 1 11

Hungary (HU) 1021 98,40% 0,40% 0,10% 1,10% 1009 11 11 34

Ireland (IE) 1065 94,70% 1,00% 1,00% 3,20% 526 13 10 509

Israel Jews (IL-J) 1066 49,70% 1,20% 0,90% 48,10% 8M148 2

Israel Arabs (IL-A) 152 98,70% 1,30% - - 2M1084 4 2 3

Japan (JP) 1102 99,20% 0,40% 0,20% 0,30% 9M606 67 80 244

Latvia (LV) 1000 60,80% 6,70% 8,00% 24,50% 3M794 24 16 180

New Zealand (NZ) 1036 78,30% 2,40% 1,60% 17,80% 22M1339 12 25 72

Norway (NO) 1469 92,50% 0,80% 1,70% 5,00% 21M1258 6 6 7

Poland (PL) 1277 98,50% 0,50% 0,50% 0,50% 1466 26 9 9

Portugal (PT) 1602 97,10% 1,70% 0,60% 0,60% 92M1189 5 6

Philippines (PH) 1200 99,10% 0,40% 0,50% - 2319 7 10 11

Russia (RU) 2383 98,80% 0,30% 0,40% 0,50% 36M1106 20 14 10

Slovak Republic (SK) 1152 96,20% 1,70% 1,20% 0,90% 2M

Slovenia (SI) 1093 1093M - - - - 2264 165

South Africa (ZA) 2483 93,20% 6,80% - - 54M1315

South Korea (KR) 1315 100,00% - - - 1165 14 10 12

Spain (ES) 1212 97,00% 1,20% 0,80% 1,00% 11M1017 9 27 131

Sweden (SE) 1186 85,90% 0,80% 2,30% 11,10% 2M789 27 35 186

Switzerland (CH) 1037 76,10% 2,60% 3,40% 17,90% 2001 3 10

Taiwan (TW) 2016 99,40% 0,10% - 0,50% 2M1065 18 17 113

United States (US) 1216 87,80% 1,50% 1,40% 9,30% 3M991 28 39 48

Uruguay (UY) 1108 89,60% 2,50% 3,50% 4,30% 2M1045 27 40 86

Venezuela (VE) 1199 87,20% 2,30% 3,30% 7,20% 1MSum 44170 1093M 38518 671 580 2855 453M


V58 Racial-ethnic group of R Missing Values: 0; 998; 999 Q14.- (Racial/ethnic (linguistic, religious) group of respondent. No extra question needed if you have the information in your demographics part. 1

1. Africa,Mandinka,Somalia,Sudan,Yoruba 49. German,Germany (CZ:Nemec) 96. Ozamisnon 2. Afrikaan 50. German+Danish 97. Pacific,Polynesian,Chamorro Guam 3. Aklanon,Romblon 51. Greek,Greece 98. Pakistan,Panjab/Punjabi,Pashto 4. Albanian 52. Hebrew/Ivrit 99. Panggalatok Pangasinan,Pangasinense 5. Alsacien, France 53. Hungarian,Hungary (CZ:Magyar) 100. Philippines,Tagalog,Filippino 6. American Indian,Navajo,Ind.Dialect 54. Ibanag 101. Pidgin, PNG Pidgin 7. American,American only,America,USA 55. Ifugao 102. Polish,Pole,Poland 8. Antiqueño 56. Igorot 103. Portuguese, Portugal 9. Arab,Arabic,Muslim 57. Ilocano 104. Provençal, France 10. Armenian,Transcaucasian 58. Ilonggo 105. Romani,Gipsy ,Tzyganes 11. Asian,Asia,other Asian 59. French+English 106. Romanian/Rumanian 12. Australian,Oceanian,Australia 60. Indian,Hindi,Urdu,Gujarati,Tamil 107. Romblonon 13. Austrian,Austria 61. Indonesian,Malay/Malaysian 108. Russian,Russia,USSR&Rep. 14. Bangladeshi,Bengali,Bangladesh 62. Inuit, Eskimo 109. Samic,Lapp 15. Basque/Vasco 63. Iranian,Persian/Farsi,Dari 110. Samoan,Tokelauan 16. Belgian,Belgium 64. Iraq 111. Scotland,Scots Gaelic,Scottish 17. Belorussian,Bialorussian 65. Irish/Irish Gaelic,Ireland 112. Sepedi 18. Bicolano/Bikol 66. Isindebele 113. Serbia,Serbian,Serb, Yugoslavian 19. Bilaan 67. Isixhosa 114. Sesotho 20. Black/African/Carribean,No-Spanish 68. Isizulu 115. Setswana 21. Bosnian, SLO:ethn.Muslim 69. Italian,Italy 116. Silesian 22. Breton, France 70. Itawis 117. Siswati 23. Bul-anon 71. Itneg 118. Slovakia,Slovak 24. Bulgarian 72. Japanese,Japan 119. Slovenia,Slovenian,Slovene 25. Cajun French 73. Jordan 120. Somalia 26. Catalan,Valencian,Balear/Mallorquin 74. Kapampangan' 121. Spanish,Castilian,Castellano 27. Coloured 75. Karay-a 122. Subanen 28. Cook Island Maori 76. Korean 123. Surigaonon 29. Corse, France 77. Kurdish,Assyrian,Lebanese 124. Swedish (both citizen) 30. Creole,Surinam/Sranan,Metis,Chavacano 78. Latin-American, South America,

Spanish Origin western countries 125. Switzerland,Rheto-roman

31. Jewish/Yiddish 79. Latvian,Estonian,Lith.,Baltic 126. Tatar 32. Croatian 80. Lithuanian 127. Thai,Khmer,Vietnamese,Cont.Southeast 33. Czech-Czechia,Czech Republic 81. Luxemborger, Luxemburg 128. Tongan,Niuean 34. Chinese-Cantonese,Hakka,Mandarin 82. Philippine other (Maguindanao,

Kuyonin, Tangadanon, Zambaleño) 130. Tshivenda/Lemba

35. Danish,Denmark 83. Maori,NZ Maori 131. Turkey,Turkish 36. Danish+English 84. Maranaw/Maranao 132. Ukraine,Ukrainian 37. English + Persian 85. Masbateño 133. Visayan/Cebuano,Boholano,Leyteno 38. English + Tai 86. Metis 134. Waray 39. English,England&Wales,UK,England 87. Montenegro 135. Welsh 40. Esperanto,Latin,Slavonik,Celtic 88. Moravian 136. Whites (all) 41. Estonia 89. Netherlands,Dutch,Flemish 137. Xitsonga 42. Ethiopia 990. No languages at all 138. Zamboangeño 43. European,White/European,Europe 90. Nordic,Scandinavian other 980. Other African language 44. Europeans Mediterranean 91. North Africans 981. Other,East European 45. Finnish,Finland 92. Norwegian,Norway 982. Other,Middle East 46. French,France 93. Occitan, France 983. Other,Mixed origin 47. Gallego 94. One non-Swedish,both non-Swedish 984. Other,Western European 48. Georgian 95. Oriental

0. Not available (Not asked) 998. Don’t know. 999. No answer. NOTES: (1) Not asked in Australia, Chile, Great Britain, Israel, Poland, South-Africa and Venezuela


0 1 3 4 6 7 8 9 10 11 12 13

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 2183M - - - - - - - - - - -3 1 773

Austria (AT) 1006 - - - - - - 0,30% - 0,10% - 76,80%1

Bulgaria (BG) 1069 - - - - - - - 0,10% - - -23 6

Canada (CA) 1211 1,90% - - 0,50% - - - - - - -

Chile (CL) 1505 1505M - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - -3 9

Denmark (DK) 1322 181M 0,30% - - - - - - - 0,80% - -

Finland (FI) 1379 - - - - - - - - - - -8 2

France (FR) 1669 - - - 0,50% - - - - 0,10% - -1 2 2 3

Germany-West (DE-W) 850 0,10% - - - 0,20% - 0,20% 0,40% - - -2

Germany-East (DE-E) 437 0,50% - - - - - - - - - -

Great Britain (GB) 873 873M - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - -2 2 2

Ireland (IE) 1065 0,20% - - - 0,20% - - - - 0,20% -

Israel Jews (IL-J) 1066 1066M - - - - - - - - - - -

Israel Arabs (IL-A) 152 152M - - - - - - - - - - -1

Japan (JP) 1102 - - - - - - - - 0,10% - -

Latvia (LV) 1000 - - - - - - - - - - -13

New Zealand (NZ) 1036 - - - - - - - - - 1,30% -2 2

Norway (NO) 1469 0,10% - - - - - 0,10% - - - -

Poland (PL) 1277 1277M - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - -1 5

Philippines (PH) 1200 - 0,10% - - - 0,40% - - - - -66

Russia (RU) 2383 - - - - - - - 2,80% - - -

Slovak Republic (SK) 1152 - - - - - - - - - - -4

Slovenia (SI) 1093 - - - - - - - - - - 0,40%

South Africa (ZA) 2483 2483M - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - -5

Spain (ES) 1212 0,40% - - - - - - - - - -1 2 1

Sweden (SE) 1186 0,10% - 0,20% - - - 0,10% - - - -6 1 10

Switzerland (CH) 1037 0,60% - 0,10% - - - - - - - 1,00%

Taiwan (TW) 2016 - - - - - - - - - - -164 12 3

United States (US) 1216 13,50% - - 1,00% - - - - 0,20% - -2

Uruguay (UY) 1108 0,30% - - - - - - - - - -

Venezuela (VE) 1199 1199M - - - - - - - - - - -Sum 44170 10919M 211 1 3 26 4 5 8 70 16 15 787


14 16 17 18 19 20 21 23 24 28 30 31

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -14

Austria (AT) 1006 - - - - - - 1,40% - - - - -921

Bulgaria (BG) 1069 - - - - - - - - 86,60% - - -17 4

Canada (CA) 1211 - - - - - 1,40% - - - - - 0,30%

Chile (CL) 1505 - - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - -1

Denmark (DK) 1322 - - - - - - 0,10% - - - - -

Finland (FI) 1379 - - - - - - - - - - - -10 18

France (FR) 1669 - - - - - 0,60% - - - - - 1,10%1

Germany-West (DE-W) 850 - - - - - - - - 0,10% - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -1

Hungary (HU) 1021 - - - - - - - - - - - 0,10%

Ireland (IE) 1065 - - - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -20

Latvia (LV) 1000 - - 2,00% - - - - - - - - -8

New Zealand (NZ) 1036 - - - - - - - - - 0,80% - -1 4

Norway (NO) 1469 0,10% - - - - - 0,30% - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -60 4 5 1

Philippines (PH) 1200 - - - 5,00% 0,30% - - 0,40% - - 0,10% -14 12

Russia (RU) 2383 - - 0,60% - - - - - - - - 0,50%

Slovak Republic (SK) 1152 - - - - - - - - - - - -15

Slovenia (SI) 1093 - - - - - - 1,40% - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -4 1

Sweden (SE) 1186 - - - - - - 0,30% - - - - 0,10%2

Switzerland (CH) 1037 - 0,20% - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -

United States (US) 1216 - - - - - - - - - - - -2

Uruguay (UY) 1108 - 0,30% - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 1 4 34 60 4 27 38 5 922 8 1 36


32 33 34 35 39 41 42 43 44 45 46 49

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -7 44

Austria (AT) 1006 0,70% 4,40% - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -6 416 396 116

Canada (CA) 1211 - - 0,50% - 35,20% - - - - - 33,50% 9,80%

Chile (CL) 1505 - - - - - - - - - - - -1069 10

Czech Republic (CZ) 1276 - 87,00% - - - - - - - - - 0,80%2 1091 1 3 8

Denmark (DK) 1322 - - 0,20% 95,60% 0,10% - - 0,30% - - - 0,70%1379

Finland (FI) 1379 - - - - - - - - - 100,00% - -106 1449

France (FR) 1669 - - - - - - - - 6,40% - 86,80% -1 1 1 651

Germany-West (DE-W) 850 - 0,10% - - - - - - - 0,10% 0,10% 78,30%387

Germany-East (DE-E) 437 - - - - - - - - - - - 89,80%

Great Britain (GB) 873 - - - - - - - - - - - -1 5

Hungary (HU) 1021 0,10% - - - - - - - - - - 0,50%21 2

Ireland (IE) 1065 - - - - 2,00% - - - - - 0,20% -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -1

Japan (JP) 1102 - - 0,10% - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -19 45 675

New Zealand (NZ) 1036 - - 1,80% - 4,30% - - 65,20% - - - -2 2 1 3 3

Norway (NO) 1469 - - - 0,10% 0,10% - - 0,10% - 0,20% - 0,20%

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -2 2 7

Russia (RU) 2383 - - 0,10% - - - - - - 0,10% - 0,30%7

Slovak Republic (SK) 1152 - 0,60% - - - - - - - - - -30

Slovenia (SI) 1093 2,80% - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -1 4 2 1 2 1 3 14 1 1

Sweden (SE) 1186 0,10% - 0,30% 0,20% 0,10% 0,20% 0,10% 0,30% - 1,20% 0,10% 0,10%2 3 3 1 11 32

Switzerland (CH) 1037 - 0,20% 0,30% - 0,30% - - - - 0,10% 1,10% 3,10%2005

Taiwan (TW) 2016 - - 99,60% - - - - - - - - -12

United States (US) 1216 - - 1,00% - - - - - - - - -1 1 8 30 18

Uruguay (UY) 1108 - 0,10% - 0,10% 1,00% - - - - - 3,90% 2,30%

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 39 1124 2054 1096 497 2 1 682 106 1400 1890 1238


50 51 52 53 54 55 56 57 58 60 61 62

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -22 1

Austria (AT) 1006 - - - 2,20% - - - - - 0,10% - -

Bulgaria (BG) 1069 - - - - - - - - - - - -2 17

Canada (CA) 1211 - - - - - - - - - 0,20% - 1,40%

Chile (CL) 1505 - - - - - - - - - - - -1

Czech Republic (CZ) 1276 - - - 0,10% - - - - - - - -1

Denmark (DK) 1322 - - - 0,10% - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -4 3

Germany-West (DE-W) 850 - - - 0,50% - - - - - 0,40% - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -1001

Hungary (HU) 1021 - - - 98,00% - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -1 9

Latvia (LV) 1000 0,10% - 0,90% - - - - - - - - -11

New Zealand (NZ) 1036 - - - - - - - - - 1,10% - -1 2

Norway (NO) 1469 - - - 0,10% - - - - - 0,10% - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -10 1 3 156 195

Philippines (PH) 1200 - - - - 0,80% 0,10% 0,30% 13,00% 16,30% - - -2

Russia (RU) 2383 - 0,10% - - - - - - - - - -100

Slovak Republic (SK) 1152 - - - 8,70% - - - - - - - -2

Slovenia (SI) 1093 - - - 0,20% - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -1 1

Sweden (SE) 1186 0,10% - - - - - - - - 0,10% - -4 1 2 1

Switzerland (CH) 1037 - 0,40% - 0,10% - - - - - 0,20% 0,10% -4

Taiwan (TW) 2016 - - - - - - - - - - 0,20% -8

United States (US) 1216 - - - - - - - - - 0,70% - -3

Uruguay (UY) 1108 - 0,40% - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 2 9 9 1133 10 1 3 156 195 30 5 17


63 64 65 69 70 71 72 73 74 75 76 77

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -


Denmark (DK) 1322 - - - - - - - - - - 0,10% -

Finland (FI) 1379 - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -1 6 1

Germany-West (DE-W) 850 0,10% - - 0,70% - - - - - - 0,10% -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -1025 1

Ireland (IE) 1065 - - 96,80% 0,10% - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -1090

Japan (JP) 1102 - - - - - - 99,80% - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -7

New Zealand (NZ) 1036 - - 0,70% - - - - - - - - -4 1

Norway (NO) 1469 0,30% - - - - - - - - - - 0,10%

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -1 1 18 4

Philippines (PH) 1200 - - - - 0,10% 0,10% - - 1,50% 0,30% - -1 1

Russia (RU) 2383 - - - % - - - - - - - %


Slovenia (SI) 1093 - - - 0,30% - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -1315

South Korea (KR) 1315 - - - - - - - - - - 100,00% -

Spain (ES) 1212 - - - - - - - - - - - -2 1 1 1 4

Sweden (SE) 1186 0,20% 0,10% - 0,10% - - - 0,10% - - - 0,30%1 63

Switzerland (CH) 1037 0,10% - - 6,10% - - - - - - - -1 1

Taiwan (TW) 2016 - - - - - - % - - - % -3

United States (US) 1216 - - - - - - 0,20% - - - - -179

Uruguay (UY) 1108 - - - 23,00% - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 8 1 1032 254 1 1 1094 1 18 4 1318 6


78 79 82 83 84 85 86 87 88 89 90 91

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -3 6

Canada (CA) 1211 0,30% - - - - - 0,50% - - - - -

Chile (CL) 1505 - - - - - - - - - - - -111

Czech Republic (CZ) 1276 - - - - - - - - 9,00% - - -1 2

Denmark (DK) 1322 0,10% - - - - - - - - - 0,20% -

Finland (FI) 1379 - - - - - - - - - - - -25

France (FR) 1669 - - - - - - - - - - - 1,50%2 1

Germany-West (DE-W) 850 0,20% - - - - - - - - 0,10% - -1

Germany-East (DE-E) 437 - - - - - - - - - 0,20% - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -600

Latvia (LV) 1000 - 60,70% - - - - - - - - - -172 11

New Zealand (NZ) 1036 - - - 16,60% - - - - - 1,10% - -1 5

Norway (NO) 1469 0,10% - - - - - - - - - 0,30% -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -50 1 13

Philippines (PH) 1200 - - 4,20% - 0,10% 1,10% - - - - - -4 2

Russia (RU) 2383 - 0,20% - 0,10% - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - - -

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -1 1 2 3

Sweden (SE) 1186 0,10% - - - - - - 0,10% - 0,20% 0,30% -3 5

Switzerland (CH) 1037 0,30% - - - - - - - - 0,50% - -1

Taiwan (TW) 2016 - - - - % - - - - - - -33

United States (US) 1216 2,70% - - - - - - - - - - -127

Uruguay (UY) 1108 16,30% - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 171 604 50 174 2 13 6 1 111 20 10 25


92 95 96 97 98 99 100 102 103 105 106 107

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -14 4

Austria (AT) 1006 - - - - - - - 1,40% - - 0,40% -52

Bulgaria (BG) 1069 - - - - - - - - - 4,90% - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -4 7

Czech Republic (CZ) 1276 - - - - - - - 0,30% - 0,60% - -4 4

Denmark (DK) 1322 0,40% - - - - - - 0,40% - - - -

Finland (FI) 1379 - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -2 2 11 3

Germany-West (DE-W) 850 0,20% - - - 0,20% - - 1,30% - - 0,40% -7 1

Germany-East (DE-E) 437 - - - - - - - 1,60% - - 0,20% -

Great Britain (GB) 873 - - - - - - - - - - - -11

Hungary (HU) 1021 - - - - - - - - - 1,10% - -1 1

Ireland (IE) 1065 - - - - - - 0,10% - - - 0,10% -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -19 2 1

Latvia (LV) 1000 - - - - - - - 1,90% - 0,20% 0,10% -

New Zealand (NZ) 1036 - - - - - - - - - - - -1374 3 1

Norway (NO) 1469 95,30% - - - 0,20% - 0,10% - - - - -

Poland (PL) 1277 - - - - - - - - - - - -1394

Portugal (PT) 1602 - - - - - - - - 92,90% - - -1 10 288 4

Philippines (PH) 1200 - - 0,10% - - 0,80% 24,00% - - - - 0,30%1

Russia (RU) 2383 - - - - - - - % - - - -2

Slovak Republic (SK) 1152 - - - - - - - 0,20% - - - -

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -1

Spain (ES) 1212 - 0,10% - - - - - - - - - -6

Sweden (SE) 1186 0,50% - - - - - - - - - - -2 1 3 5

Switzerland (CH) 1037 - - - - 0,20% - 0,10% 0,30% 0,50% - - -

Taiwan (TW) 2016 - - - - - - - - - - - -2 7

United States (US) 1216 - - - 0,20% - - 0,60% - - - - -7 19 1

Uruguay (UY) 1108 - - - - - - - 0,90% 2,40% 0,10% - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 1386 1 1 2 7 10 298 72 1418 73 10 4


108 109 110 111 113 116 118 119 120 121 122 123

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -30

Austria (AT) 1006 - - - - 3,00% - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -65

Canada (CA) 1211 - - - 5,50% - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -9 16

Czech Republic (CZ) 1276 - - - - - 0,70% 1,30% - - - - -

Denmark (DK) 1322 - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -11 12 3

Germany-West (DE-W) 850 1,30% - - - 1,40% - - - - 0,40% - -9

Germany-East (DE-E) 437 2,10% - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -1

Hungary (HU) 1021 0,10% - - - - - - - - - - -2

Ireland (IE) 1065 - - - - - - - - - 0,20% - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -315

Latvia (LV) 1000 31,90% - - - - - - - - - - -16 7

New Zealand (NZ) 1036 - - 1,50% 0,70% - - - - - - - -2 3 1

Norway (NO) 1469 0,10% 0,20% - - 0,10% - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -3 2

Philippines (PH) 1200 - - - - - - - - - - 0,30% 0,20%2129

Russia (RU) 2383 89,60% - - - - - - - - - - -1029

Slovak Republic (SK) 1152 - - - - - - 89,50% - - - - -25 1000

Slovenia (SI) 1093 - - - - 2,30% - - 92,10% - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -3 1 1 1

Sweden (SE) 1186 - - - - 0,30% - - 0,10% 0,10% 0,10% - -3 26 5

Switzerland (CH) 1037 0,30% - - - 2,50% - - - - 0,50% - -

Taiwan (TW) 2016 - - - - - - - - - - - -

United States (US) 1216 - - - - - - - - - - - -5 372

Uruguay (UY) 1108 0,60% - - - - - - - - 47,80% - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 2475 3 16 72 97 9 1045 1001 1 383 3 2


124 125 126 127 128 131 132 133 134 136 138 981

V58 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -14

Austria (AT) 1006 - - - - - 1,40% - - - - - -78

Bulgaria (BG) 1069 - - - - - 7,30% - - - - - -54

Canada (CA) 1211 - - - - - - - - - - - 4,60%

Chile (CL) 1505 - - - - - - - - - - - -1

Czech Republic (CZ) 1276 - - - 0,10% - - - - - - - -2 1 5

Denmark (DK) 1322 0,20% - - 0,10% - 0,40% - - - - - -

Finland (FI) 1379 - - - - - - - - - - - -15

France (FR) 1669 - - - - - - - - - - - 0,90%1 33

Germany-West (DE-W) 850 - - - 0,10% - 4,00% - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -1 19

Latvia (LV) 1000 - - 0,10% - - - 1,90% - - - - -7

New Zealand (NZ) 1036 - - - - 0,70% - - - - - - -13 1 3 1

Norway (NO) 1469 0,90% 0,10% - 0,20% - 0,10% - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -313 47 1

Philippines (PH) 1200 - - - - - - - 26,10% 3,90% - 0,10% -96 28

Russia (RU) 2383 - - 4,00% - - - 1,20% - - - - -12

Slovak Republic (SK) 1152 - - - - - - 1,00% - - - - -

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -1192

Spain (ES) 1212 - - - - - - - - - 99,20% - -1098 1

Sweden (SE) 1186 94,00% - - 0,10% - - - - - - - -1 821 1 4

Switzerland (CH) 1037 0,10% 79,60% - 0,10% - 0,40% - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -966

United States (US) 1216 - - - - - - - - - 79,60% - -3

Uruguay (UY) 1108 - - - - - 0,40% - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 1114 822 97 8 7 138 59 313 47 2158 1 69


982 983 984 999

V58 (N) % % % %

Australia (AU) 2183 - - - 79

Austria (AT) 1006 - 7,90% - 11

Bulgaria (BG) 1069 - 1,00% - 6M1 27 22

Canada (CA) 1211 0,10% 2,30% 1,90% 30M

Chile (CL) 1505 - - - 1

Czech Republic (CZ) 1276 - 0,10% - 47M2

Denmark (DK) 1322 - 0,20% -

Finland (FI) 1379 - - - 36

France (FR) 1669 - 2,20% - 72

Germany-West (DE-W) 850 - 8,70% - 19M24

Germany-East (DE-E) 437 - 5,60% - 6M

Great Britain (GB) 873 - - - 1

Hungary (HU) 1021 - 0,10% -

Ireland (IE) 1065 - - - 6M

Israel Jews (IL-J) 1066 - - -

Israel Arabs (IL-A) 152 - - -

Japan (JP) 1102 - - - 10M1

Latvia (LV) 1000 - 0,10% - 12M45

New Zealand (NZ) 1036 - 4,30% - 6

Norway (NO) 1469 - 0,40% - 27M

Poland (PL) 1277 - - - 106

Portugal (PT) 1602 - 7,10% - 102M

Philippines (PH) 1200 - - - 2M10

Russia (RU) 2383 - 0,40% - 6M

Slovak Republic (SK) 1152 - - - 2M7

Slovenia (SI) 1093 - 0,60% - 7M

South Africa (ZA) 2483 - - -

South Korea (KR) 1315 - - - 4

Spain (ES) 1212 - 0,30% - 10M

Sweden (SE) 1186 - - - 18M8

Switzerland (CH) 1037 - 0,80% - 6M2

Taiwan (TW) 2016 - 0,10% - 2M4

United States (US) 1216 - 0,30% - 2M

Uruguay (UY) 1108 - - - 330M

Venezuela (VE) 1199 - - - Sum 44170 1 446 22 650M


V59 Children born in [Country] of parents who are not citizens should have the right to become [Country Nationality] citizens. Missing Values: 8; 9 Q15.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) a. Children born in [COUNTRY] of parents who are not citizens should have the right to become [COUNTRY NATIONALITY] citizens. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V59 (N) % % % % % % % 559 1115 190 211 42

Australia (AU) 2183 26,40% 52,70% 9,00% 10,00% 2,00% 36M 30M339 345 99 121 53

Austria (AT) 1006 35,40% 36,10% 10,30% 12,60% 5,50% 49M 474 231 80 44 43

Bulgaria (BG) 1069 54,40% 26,50% 9,20% 5,00% 4,90% 185M 12M393 570 112 94 16

Canada (CA) 1211 33,20% 48,10% 9,50% 7,90% 1,40% 19M 7M553 819 61 39 2

Chile (CL) 1505 37,50% 55,60% 4,10% 2,60% 0,10% 26M 5M292 465 236 145 47


Denmark (DK) 1322 39,00% 26,00% 12,20% 11,40% 11,40% 42M 18M213 398 259 317 74

Finland (FI) 1379 16,90% 31,60% 20,50% 25,10% 5,90% 88M 30M575 477 225 171 139

France (FR) 1669 36,20% 30,10% 14,20% 10,80% 8,80% 26M 56M198 455 55 66 16




Hungary (HU) 1021 33,30% 41,60% 14,00% 7,50% 3,70% 43M 1M92 512 85 286 65

Ireland (IE) 1065 8,80% 49,20% 8,20% 27,50% 6,20% 25M 354 381 101 131 84


Israel Arabs (IL-A) 152 30,30% 28,30% 21,10% 17,80% 2,60% 419 177 186 50 141

Japan (JP) 1102 43,10% 18,20% 19,10% 5,10% 14,50% 125M 4M394 405 104 63 7

Latvia (LV) 1000 40,50% 41,60% 10,70% 6,50% 0,70% 26M 1M136 390 133 252 92

New Zealand (NZ) 1036 13,60% 38,90% 13,30% 25,10% 9,20% 18M 15M217 624 241 267 59

Norway (NO) 1469 15,40% 44,30% 17,10% 19,00% 4,20% 37M 24M273 734 104 69 9

Poland (PL) 1277 23,00% 61,70% 8,70% 5,80% 0,80% 87M 1M610 668 98 90 15

Portugal (PT) 1602 41,20% 45,10% 6,60% 6,10% 1,00% 29M 92M400 483 152 128 33

Philippines (PH) 1200 33,40% 40,40% 12,70% 10,70% 2,80% 4M 765 718 236 235 151

Russia (RU) 2383 36,30% 34,10% 11,20% 11,20% 7,20% 278M 347 498 149 78 25


Slovenia (SI) 1093 31,50% 45,80% 11,00% 9,90% 1,80% 30M 1M808 1024 109 306 107


South Korea (KR) 1315 26,40% 43,90% 13,80% 12,60% 3,20% 17M 150 670 197 114 41

Spain (ES) 1212 12,80% 57,20% 16,80% 9,70% 3,50% 34M 6M316 531 193 81 24

Sweden (SE) 1186 27,60% 46,40% 16,90% 7,10% 2,10% 36M 5M310 511 82 104 11


Taiwan (TW) 2016 10,80% 61,50% 16,00% 10,40% 1,20% 88M 13M326 576 127 113 51

United States (US) 1216 27,30% 48,30% 10,60% 9,50% 4,30% 22M 1M546 519 21 9

Uruguay (UY) 1108 49,90% 47,40% 1,90% 0,80% - 12M 1M466 677 3 42 8



V60 Children born abroad should have the right to become [Country Nationality] citizens if at least one of their parents is a [Country Nationality] citizen. Missing Values: 8; 9 Q15.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) b. Children born abroad should have the right to become [COUNTRY NATIONALITY] citizens if at least one of their parents is a [COUNTRY NATIONALITY] citizen. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V60 (N) % % % % % % % 462 1371 185 78 11

Australia (AU) 2183 21,90% 65,10% 8,80% 3,70% 0,50% 35M 41M305 413 108 97 33

Austria (AT) 1006 31,90% 43,20% 11,30% 10,10% 3,50% 50M 654 243 33 10 9

Bulgaria (BG) 1069 68,90% 25,60% 3,50% 1,10% 0,90% 109M 11M303 679 114 76 10

Canada (CA) 1211 25,60% 57,40% 9,60% 6,40% 0,80% 19M 10M477 786 128 60 3

Chile (CL) 1505 32,80% 54,10% 8,80% 4,10% 0,20% 45M 6M361 603 200 52 13


Denmark (DK) 1322 50,30% 31,70% 8,40% 5,20% 4,50% 47M 18M250 651 246 112 21

Finland (FI) 1379 19,50% 50,90% 19,20% 8,80% 1,60% 66M 33M488 664 215 118 84

France (FR) 1669 31,10% 42,30% 13,70% 7,50% 5,40% 41M 59M148 499 78 48 13




Hungary (HU) 1021 33,20% 46,40% 16,20% 3,60% 0,60% 44M 2M125 683 91 127 17

Ireland (IE) 1065 12,00% 65,50% 8,70% 12,20% 1,60% 22M 363 428 132 97 33


Israel Arabs (IL-A) 152 26,30% 38,20% 16,40% 16,40% 2,60% 498 308 136 19 36

Japan (JP) 1102 49,90% 30,90% 13,60% 1,90% 3,60% 101M 4M277 447 157 63 9

Latvia (LV) 1000 29,10% 46,90% 16,50% 6,60% 0,90% 46M 1M149 677 109 58 11

New Zealand (NZ) 1036 14,80% 67,40% 10,90% 5,80% 1,10% 20M 12M225 844 209 103 21

Norway (NO) 1469 16,00% 60,20% 14,90% 7,30% 1,50% 38M 29M225 856 96 20 3

Poland (PL) 1277 18,80% 71,30% 8,00% 1,70% 0,20% 76M 1M679 692 79 31 7

Portugal (PT) 1602 45,60% 46,50% 5,30% 2,10% 0,50% 23M 91M382 586 154 59 12

Philippines (PH) 1200 32,00% 49,10% 12,90% 4,90% 1,00% 7M 817 879 245 116 46

Russia (RU) 2383 38,80% 41,80% 11,70% 5,50% 2,20% 280M 391 516 146 35 11


Slovenia (SI) 1093 25,00% 56,30% 12,50% 5,80% 0,50% 33M 1M773 1105 201 198 51


South Korea (KR) 1315 26,40% 54,10% 12,00% 6,20% 1,30% 10M 170 628 262 90 5

Spain (ES) 1212 14,70% 54,40% 22,70% 7,80% 0,40% 48M 9M287 622 191 42 11

Sweden (SE) 1186 24,90% 53,90% 16,60% 3,60% 1,00% 29M 4M210 650 72 85

Switzerland (CH) 1037 20,60% 63,90% 7,10% 8,40% - 19M 1M137 1178 365 212 19

Taiwan (TW) 2016 7,20% 61,60% 19,10% 11,10% 1,00% 92M 13M311 713 124 43 6


Uruguay (UY) 1108 43,00% 51,10% 2,90% 2,70% 0,30% 18M 1M256 720 5 188 13



V61 Legal immigrants to [Country] who are not citizens should have the same rights as [Country Nationality] citizens. Missing Values: 8; 9 Q15.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) c. Legal immigrants to [COUNTRY] who are not citizens should have the same rights as [COUNTRY NATIONALITY] citizens. 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused.


1 2 3 4 5 8 9

V61 (N) % % % % % % % 205 645 359 699 196

Australia (AU) 2183 9,70% 30,70% 17,10% 33,20% 9,30% 40M 39M155 269 131 242 166

Austria (AT) 1006 16,10% 27,90% 13,60% 25,10% 17,20% 43M 284 266 125 109 96

Bulgaria (BG) 1069 32,30% 30,20% 14,20% 12,40% 10,90% 176M 13M121 331 210 418 84

Canada (CA) 1211 10,40% 28,40% 18,00% 35,90% 7,20% 38M 9M221 573 209 361 71

Chile (CL) 1505 15,40% 39,90% 14,60% 25,20% 4,90% 63M 7M186 366 319 233 117


Denmark (DK) 1322 22,20% 27,30% 11,80% 17,40% 21,30% 42M 16M101 360 281 385 117

Finland (FI) 1379 8,10% 28,90% 22,60% 30,90% 9,40% 96M 39M296 428 232 316 302

France (FR) 1669 18,80% 27,20% 14,70% 20,10% 19,20% 43M 52M67 245 123 222 126




Hungary (HU) 1021 9,40% 20,70% 28,60% 28,00% 13,10% 45M 2M43 534 125 274 64

Ireland (IE) 1065 4,10% 51,30% 12,00% 26,30% 6,20% 24M 1M143 302 189 267 150



Japan (JP) 1102 40,10% 26,50% 19,50% 4,80% 9,20% 112M 4M122 169 215 346 89

Latvia (LV) 1000 13,00% 18,00% 22,80% 36,80% 9,50% 58M 1M97 332 171 312 86

New Zealand (NZ) 1036 9,70% 33,30% 17,10% 31,30% 8,60% 20M 18M85 436 295 443 132

Norway (NO) 1469 6,10% 31,30% 21,20% 31,80% 9,50% 45M 33M86 484 263 267 35

Poland (PL) 1277 7,60% 42,60% 23,20% 23,50% 3,10% 141M 1M494 678 143 135 32

Portugal (PT) 1602 33,30% 45,70% 9,60% 9,10% 2,20% 29M 91M197 395 273 248 74

Philippines (PH) 1200 16,60% 33,30% 23,00% 20,90% 6,20% 13M 323 575 399 420 298

Russia (RU) 2383 16,00% 28,50% 19,80% 20,80% 14,80% 368M 192 401 286 155 62


Slovenia (SI) 1093 10,00% 27,80% 17,30% 36,80% 8,10% 32M 1M380 631 252 722 319


South Korea (KR) 1315 23,90% 44,90% 17,10% 12,20% 1,90% 9M 232 641 210 86 7

Spain (ES) 1212 19,70% 54,50% 17,90% 7,30% 0,60% 26M 10M143 329 289 267 103

Sweden (SE) 1186 12,60% 29,10% 25,60% 23,60% 9,10% 50M 5M52 316 173 422 51


Taiwan (TW) 2016 3,50% 37,20% 18,70% 34,70% 5,90% 116M 23M139 319 186 418 128


Uruguay (UY) 1108 26,20% 43,10% 13,30% 15,60% 1,90% 28M 1M183 589 11 349 53



V62 [Country] should take stronger measures to exclude illegal immigrants? Missing Values: 8; 9 Q15.- How much do you agree or disagree with the following statements? (Please, tick one box on each line) d. [COUNTRY] should take stronger measures to exclude illegal immigrants? 1 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 8. Can´t choose. 9. Na, refused. Notes: (1) Translation note: “Exclude” means “Keep out” and/or “Expel”


1 2 3 4 5 8 9

V62 (N) % % % % % % % 892 628 264 189 122

Australia (AU) 2183 42,60% 30,00% 12,60% 9,00% 5,80% 52M 36M516 233 102 84 34

Austria (AT) 1006 53,30% 24,00% 10,50% 8,70% 3,50% 37M 656 213 40 5 3

Bulgaria (BG) 1069 71,50% 23,20% 4,40% 0,50% 0,30% 137M 15M585 400 135 40 10

Canada (CA) 1211 50,00% 34,20% 11,50% 3,40% 0,90% 30M 11M406 614 233 171 19

Chile (CL) 1505 28,10% 42,60% 16,10% 11,90% 1,30% 55M 7M778 312 99 25 15


Denmark (DK) 1322 56,50% 20,90% 10,00% 4,80% 7,80% 46M 19M536 452 207 62 15

Finland (FI) 1379 42,10% 35,50% 16,30% 4,90% 1,20% 79M 28M705 389 208 147 126

France (FR) 1669 44,80% 24,70% 13,20% 9,30% 8,00% 50M 44M345 313 75 48 13




Hungary (HU) 1021 57,40% 32,20% 8,10% 1,50% 0,80% 30M 1M330 492 103 104 12

Ireland (IE) 1065 31,70% 47,30% 9,90% 10,00% 1,20% 22M 2M541 273 124 85 27


Israel Arabs (IL-A) 152 48,00% 36,20% 12,50% 3,30% - 685 212 91 23 30

Japan (JP) 1102 65,80% 20,40% 8,70% 2,20% 2,90% 57M 4M380 425 103 27 15

Latvia (LV) 1000 40,00% 44,70% 10,80% 2,80% 1,60% 49M 1M537 342 86 26 13

New Zealand (NZ) 1036 53,50% 34,10% 8,60% 2,60% 1,30% 14M 18M773 503 94 30 17

Norway (NO) 1469 54,60% 35,50% 6,60% 2,10% 1,20% 19M 33M188 527 257 146 18

Poland (PL) 1277 16,50% 46,40% 22,60% 12,90% 1,60% 140M 1M444 483 224 215 85

Portugal (PT) 1602 30,60% 33,30% 15,40% 14,80% 5,90% 52M 99M460 455 163 84 30

Philippines (PH) 1200 38,60% 38,20% 13,70% 7,00% 2,50% 8M 1202 617 175 90 56

Russia (RU) 2383 56,20% 28,80% 8,20% 4,20% 2,60% 243M 551 366 125 35 11


Slovenia (SI) 1093 32,80% 46,40% 12,80% 6,10% 1,80% 40M 2M1054 772 203 185 112


South Korea (KR) 1315 26,70% 35,40% 22,10% 13,20% 2,60% 20M 127 485 283 206 62

Spain (ES) 1212 10,90% 41,70% 24,30% 17,70% 5,30% 37M 12M387 380 232 68 49

Sweden (SE) 1186 34,70% 34,10% 20,80% 6,10% 4,40% 62M 8M332 452 121 105 11


Taiwan (TW) 2016 31,70% 47,40% 12,20% 7,60% 1,10% 74M 17M394 434 214 113 32


Uruguay (UY) 1108 8,40% 24,50% 19,60% 32,80% 14,80% 65M 2M482 561 10 105 17



V63 How proud are you being country national Missing Values: 0; 8; 9 Q16.- How proud are you of being [COUNTRY NATIONALITY]? (Please, tick one box on each line) 0. I am not [COUNTRY NATIONALITY]. 1. Very proud. 2. Somewhat proud. 3. Not very proud. 4. Not proud at all. 8. Can´t choose. 9. Na, refused.


0 1 2 3 4 8 9

V63 (N) % % % % % % % 1445 541 70 15

Australia (AU) 2183 32M 69,80% 26,10% 3,40% 0,70% 24M 56M468 382 56 23

Austria (AT) 1006 34M 50,40% 41,10% 6,00% 2,50% 43M 307 414 238 72

Bulgaria (BG) 1069 5M 29,80% 40,20% 23,10% 7,00% 17M 16M815 316 25 12

Canada (CA) 1211 32M 69,80% 27,10% 2,10% 1,00% 11M 1144 282 55 9

Chile (CL) 1505 8M 76,80% 18,90% 3,70% 0,60% 3M 4M266 701 190 41

Czech Republic (CZ) 1276 13M 22,20% 58,50% 15,90% 3,40% 17M 48M430 700 118 20

Denmark (DK) 1322 1M 33,90% 55,20% 9,30% 1,60% 37M 16M548 647 106 16

Finland (FI) 1379 12M 41,60% 49,10% 8,00% 1,20% 42M 8M472 864 109 57

France (FR) 1669 21M 31,40% 57,50% 7,30% 3,80% 124M 22M110 335 169 67

Germany-West (DE-W) 850 63M 16,20% 49,20% 24,80% 9,80% 97M 9M45 194 100 29

Germany-East (DE-E) 437 4M 12,20% 52,70% 27,20% 7,90% 65M 379 340 89 17

Great Britain (GB) 873 17M 45,90% 41,20% 10,80% 2,10% 19M 12M463 486 53 8

Hungary (HU) 1021 45,80% 48,10% 5,20% 0,80% 7M 4M755 241 14 3

Ireland (IE) 1065 29M 74,50% 23,80% 1,40% 0,30% 8M 15M580 322 113 37

Israel Jews (IL-J) 1066 2M 55,10% 30,60% 10,70% 3,50% 6M 6M33 68 36 15

Israel Arabs (IL-A) 152 21,70% 44,70% 23,70% 9,90% 453 496 84 14

Japan (JP) 1102 43,30% 47,40% 8,00% 1,30% 51M 4M319 383 179 47

Latvia (LV) 1000 7M 34,40% 41,30% 19,30% 5,10% 65M 692 268 26 3

New Zealand (NZ) 1036 29M 70,00% 27,10% 2,60% 0,30% 5M 13M480 717 134 24

Norway (NO) 1469 48M 35,40% 52,90% 9,90% 1,80% 34M 32M583 550 86 20

Poland (PL) 1277 47,10% 44,40% 6,90% 1,60% 36M 2M846 574 75 8

Portugal (PT) 1602 56,30% 38,20% 5,00% 0,50% 7M 92M967 185 33 12

Philippines (PH) 1200 1M 80,80% 15,50% 2,80% 1,00% 2M 864 1084 258 75

Russia (RU) 2383 4M 37,90% 47,50% 11,30% 3,30% 98M 342 546 115 27


Slovenia (SI) 1093 1M 53,30% 43,10% 2,80% 0,90% 5M 1735 544 107 38

South Africa (ZA) 2483 6M 71,60% 22,40% 4,40% 1,60% 26M 27M343 627 305 17

South Korea (KR) 1315 26,50% 48,50% 23,60% 1,30% 23M 535 620 30

Spain (ES) 1212 7M 45,10% - 52,30% 2,50% 9M 11M370 565 158 13

Sweden (SE) 1186 40M 33,50% 51,10% 14,30% 1,20% 32M 8M335 434 114 35

Switzerland (CH) 1037 82M 36,50% 47,30% 12,40% 3,80% 28M 9M937 652 254 74

Taiwan (TW) 2016 48,90% 34,00% 13,20% 3,90% 93M 6M937 210 23 4

United States (US) 1216 25M 79,80% 17,90% 2,00% 0,30% 15M 2M794 254 36 8

Uruguay (UY) 1108 12M 72,70% 23,30% 3,30% 0,70% 4M 1047 73 11 2

Venezuela (VE) 1199 54M 92,40% 6,40% 1,00% 0,20% 12MSum 44170 589M 21418 15463 4189 902 1174M 435M


V64 What language speak at home 1st mention Missing Values: 00;998;999 Q17.- What languages do you speak most often at home? At home, I speak: [write down up to two choices]

1. Africa,Mandinka,Somalia,Sudan,Yoruba 49. German,Germany (CZ:Nemec) 97. Pacific,Polynesian,Chamorro Guam 2. Afrikaan 50. German+Danish 98. Pakistan,Panjab/Punjabi,Pashto 3. Aklanon,Romblon 51. Greek,Greece 99. Panggalatok Pangasinan,Pangasinense 4. Albanian 52. Hebrew/Ivrit 100. Philippines,Tagalog,Filippino 5. Alsacien, France 53. Hungarian,Hungary (CZ:Magyar) 101. Pidgin, PNG Pidgin 6. American Indian,Navajo,Ind.Dialect 54. Ibanag 102. Polish,Pole,Poland 7. American,American only,America,USA 55. Ifugao 103. Portuguese, Portugal 8. Antiqueño 56. Igorot 104. Provençal, France 9. Arab,Arabic,Muslim 57. Ilocano 105. Romani,Gipsy ,Tzyganes 10. Armenian,Transcaucasian 58. Ilonggo 106. Romanian/Rumanian 11. Asian,Asia,other Asian 59. French+English 107. Romblonon 12. Australian,Oceanian,Australia 60. Indian,Hindi,Urdu,Gujarati,Tamil 108. Russian,Russia,USSR&Rep. 13. Austrian,Austria 61. Indonesian,Malay/Malaysian 109. Samic,Lapp 14. Bangladeshi,Bengali,Bangladesh 62. Inuit, Eskimo 110. Samoan,Tokelauan 15. Basque/Vasco 63. Iranian,Persian/Farsi,Dari 111. Scotland,Scots Gaelic,Scottish 16. Belgian,Belgium 64. Iraq 112. Sepedi 17. Belorussian,Bialorussian 65. Irish/Irish Gaelic,Ireland 113. Serbia,Serbian,Serb, Yugoslavian 18. Bicolano/Bikol 66. Isindebele 114. Sesotho 19. Bilaan 67. Isixhosa 115. Setswana 20. Black/African/Carribean,No-Spanish 68. Isizulu 116. Silesian 21. Bosnian, SLO:ethn.Muslim 69. Italian,Italy 117. Siswati 22. Breton, France 70. Itawis 118. Slovakia,Slovak 23. Bul-anon 71. Itneg 119. Slovenia,Slovenian,Slovene 24. Bulgarian 72. Japanese,Japan 120. Somalia 25. Cajun French 73. Jordan 121. Spanish,Castilian,Castellano 26. Catalan,Valencian,Balear/Mallorquin 74. Kapampangan' 122. Subanen 27. Coloured 75. Karay-a 123. Surigaonon 28. Cook Island Maori 76. Korean 124. Swedish (both citizen) 29. Corse, France 77. Kurdish,Assyrian,Lebanese 125. Switzerland,Rheto-roman 30. Creole,Surinam/Sranan,Metis,Chavacano 78. Latin-American, South America,

Spanish Origin western countries 126. Tatar

31. Jewish/Yiddish 79. Latvian,Estonian,Lith.,Baltic 127. Thai,Khmer,Vietnamese,Cont.Southeast 32. Croatian 80. Lithuanian 128. Tongan,Niuean 33. Czech-Czechia,Czech Republic 81. Luxemborger, Luxemburg 130. Tshivenda/Lemba 34. Chinese-Cantonese,Hakka,Mandarin 82. Philippine other (Maguindanao,

Kuyonin, Tangadanon, Zambaleño) 131. Turkey,Turkish

35. Danish,Denmark 83. Maori,NZ Maori 132. Ukraine,Ukrainian 36. Danish+English 84. Maranaw/Maranao 133. Visayan/Cebuano,Boholano,Leyteno 37. English + Persian 85. Masbateño 134. Waray 38. English + Tai 86. Metis 135. Welsh 39. English,England&Wales,UK,England 87. Montenegro 136. Whites (all) 40. Esperanto,Latin,Slavonik,Celtic 88. Moravian 137. Xitsonga 41. Estonia 89. Netherlands,Dutch,Flemish 138. Zamboangeño 42. Ethiopia 90. Nordic,Scandinavian other 980. Other African language 43. European,White/European,Europe 91. North Africans 981. Other,East European 44. Europeans Mediterranean 92. Norwegian,Norway 982. Other,Middle East 45. Finnish,Finland 93. Occitan, France 983. Other,Mixed origin 46. French,France 94. One non-Swedish,both non-

Swedish 984. Other,Western European

47. Gallego 95. Oriental 990. No languages at all 48. Georgian 96. Ozamisnon

0. Not available (Not asked) 998. Don’t know.

999. No answer. NOTES: (1) Not asked in Austria, Bulgaria, Chile, Germany, Great Britain, Hungary, Norway, Portugal, Philippines, Slovenia, Sweden,Uruguay and Venezuela


0 1 2 4 5 7 9 10 11 12 14 15

V64 (N) % % % % % % % % % % % % 1 1 9 5 1

Australia (AU) 2183 % - % - - 0,40% - - 0,20% % -

Austria (AT) 1006 1006M - - - - - - - - - - -

Bulgaria (BG) 1069 1069M - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - -

Chile (CL) 1505 1505M - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - -2 2

Denmark (DK) 1322 34M - - - - - 0,20% - 0,20% - - -

Finland (FI) 1379 - - - - - - - - - - -3 4

France (FR) 1669 - - 0,20% 0,20% - - - - - - -

Germany-West (DE-W) 850 850M - - - - - - - - - - -

Germany-East (DE-E) 437 437M - - - - - - - - - - -


Hungary (HU) 1021 1021M - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - -5 29 11

Israel Jews (IL-J) 1066 2M 0,50% - - - 2,70% 1,00% - - - - -147

Israel Arabs (IL-A) 152 - - - - - 96,70% - - - - -

Japan (JP) 1102 - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - -1

New Zealand (NZ) 1036 - 0,10% - - - - - - - - -

Norway (NO) 1469 1469M - - - - - - - - - - -

Poland (PL) 1277 1M - - - - - - - - - - -

Portugal (PT) 1602 1602M - - - - - - - - - - -

Philippines (PH) 1200 1200M - - - - - - - - - - -36

Russia (RU) 2383 - - - - - - 1,50% - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - -

Slovenia (SI) 1093 1093M - - - - - - - - - - -653

South Africa (ZA) 2483 - 26,50% - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - -9

Spain (ES) 1212 - - - - - - - - - - 0,70%

Sweden (SE) 1186 1186M - - - - - - - - - - -5

Switzerland (CH) 1037 - - 0,50% - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - -2

United States (US) 1216 - - - - - 0,20% - - - - -

Uruguay (UY) 1108 1108M - - - - - - - - - - -



16 21 22 24 26 28 29 31 32 33 34 35

V64 (N) % % % % % % % % % % % % 1 1 8 1 37

Australia (AU) 2183 - % - - - - - % 0,40% % 1,70% -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -1263

Czech Republic (CZ) 1276 - - - - - - - - - 99,30% - -1 1272

Denmark (DK) 1322 - - - - - - - - - - 0,10% 98,80%1

Finland (FI) 1379 - - - - - - - - - - 0,10% -2 2 1

France (FR) 1669 - - 0,10% - 0,10% - 0,10% - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -1 1 11

Israel Jews (IL-J) 1066 0,10% - - 0,10% - - - 1,00% - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -2 6

New Zealand (NZ) 1036 - - - - - 0,20% - - - - 0,60% -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -

Russia (RU) 2383 - - - - - - - - - - - -3

Slovak Republic (SK) 1152 - - - - - - - - - 0,30% - -

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -83

Spain (ES) 1212 - - - - 6,90% - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -8

Switzerland (CH) 1037 - - - - - - - - 0,80% - - -2016

Taiwan (TW) 2016 - - - - - - - - - - 100,00% -3

United States (US) 1216 - - - - - - - - - - 0,20% -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 1 1 2 1 85 2 1 12 16 1267 2064 1272


39 43 45 46 47 49 51 52 53 59 60 61

V64 (N) % % % % % % % % % % % % 1851 1 7 22 22 1 5 16 2

Australia (AU) 2183 86,00% - % 0,30% - 1,00% 1,00% % 0,20% - 0,70% 0,10%

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -815 299 37

Canada (CA) 1211 69,10% - - 25,40% - - - - - 3,10% - -

Chile (CL) 1505 - - - - - - - - - - - -2

Czech Republic (CZ) 1276 - - - - - 0,20% - - - - - -3 2

Denmark (DK) 1322 0,20% - - - - - - - - - 0,20% -5 1269 1 2 1

Finland (FI) 1379 0,40% - 92,00% 0,10% - 0,10% - - 0,10% - - -6 1587 6

France (FR) 1669 0,40% - - 97,90% - 0,40% - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -1053 1

Ireland (IE) 1065 98,90% - - 0,10% - - - - - - - -9 1 821 1 1

Israel Jews (IL-J) 1066 - - - 0,80% - - 0,10% 77,20% 0,10% - 0,10% -4 1

Israel Arabs (IL-A) 152 - - - - - - - 2,60% - - 0,70% -

Japan (JP) 1102 - - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -982 5

New Zealand (NZ) 1036 96,20% - - - - - - - - - 0,50% -

Norway (NO) 1469 - - - - - - - - - - - -1

Poland (PL) 1277 0,10% - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -1

Russia (RU) 2383 - - - - - % - - - - - -83

Slovak Republic (SK) 1152 - - - - - - - - 7,20% - - -

Slovenia (SI) 1093 - - - - - - - - - - - -337 1 15

South Africa (ZA) 2483 13,70% % - - - - - - - - 0,60% -

South Korea (KR) 1315 - - - - - - - - - - - -66

Spain (ES) 1212 - - - - 5,50% - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -7 191 741

Switzerland (CH) 1037 0,70% - - 18,40% - 71,50% - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -1154 1 2

United States (US) 1216 95,90% - - 0,10% - - - - - - 0,20% -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 6214 1 1270 2096 66 774 23 826 90 37 42 2


63 65 66 67 68 69 72 76 77 79 89 90

V64 (N) % % % % % % % % % % % % 1 55 1 1 1 2 8

Australia (AU) 2183 % - - - - 2,60% % % % 0,10% 0,40% -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -


Denmark (DK) 1322 - - - - - - - - - - - 0,10%

Finland (FI) 1379 - - - - - - - - - - - -1

France (FR) 1669 - - - - - - - - - - 0,10% -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -8

Ireland (IE) 1065 - 0,80% - - - - - - - - - -4 1

Israel Jews (IL-J) 1066 0,40% - - - - - - - - - 0,10% -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -1079

Japan (JP) 1102 - - - - - - 100,00% - - - - -672

Latvia (LV) 1000 - - - - - - - - - 67,20% - -1

New Zealand (NZ) 1036 - - - - - - - - - - 0,10% -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -

Russia (RU) 2383 - - - - - - - - - - - -


Slovenia (SI) 1093 - - - - - - - - - - - -35 316 332

South Africa (ZA) 2483 - - 1,40% 12,80% 13,50% - - - - - - -1315

South Korea (KR) 1315 - - - - - - - 100,00% - - - -

Spain (ES) 1212 - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -55

Switzerland (CH) 1037 - - - - - 5,30% - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -

United States (US) 1216 - - - - - - - - - - - -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 5 8 35 316 332 110 1080 1316 1 674 11 1


98 100 101 102 103 105 106 108 110 112 113 114

V64 (N) % % % % % % % % % % % % 1 16 1 17 2 1 3 11

Australia (AU) 2183 % 0,70% % 0,80% 0,10% - % 0,10% - - 0,50% -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -7

Czech Republic (CZ) 1276 - - - - - 0,60% - - - - - -1

Denmark (DK) 1322 - - - - - - - - - - 0,10% -5

Finland (FI) 1379 - - - - - - - 0,40% - - - -5 1 2

France (FR) 1669 0,30% - - 0,10% - - - - - - 0,10% -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -1 1

Ireland (IE) 1065 - 0,10% - - - - 0,10% - - - - -3 4 141

Israel Jews (IL-J) 1066 - - - - 0,30% - 0,40% 13,30% - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -328

Latvia (LV) 1000 - - - - - - - 32,80% - - - -3

New Zealand (NZ) 1036 - - - - - - - - 0,30% - - -

Norway (NO) 1469 - - - - - - - - - - - -1275

Poland (PL) 1277 - - - 99,90% - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -2297

Russia (RU) 2383 - - - - - - - 96,60% - - - -4

Slovak Republic (SK) 1152 - - - - - 0,30% - - - - - -

Slovenia (SI) 1093 - - - - - - - - - - - -192 207

South Africa (ZA) 2483 - - - - - - - - - 7,80% - 8,40%

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -2 5

Switzerland (CH) 1037 - - - - 0,20% - - - - - 0,50% -

Taiwan (TW) 2016 - - - - - - - - - - - -2 1 2 1 1

United States (US) 1216 - 0,20% 0,10% 0,20% 0,10% - - 0,10% - - - -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 6 19 2 1295 8 11 6 2775 3 192 19 207


115 117 118 119 121 124 125 126 127 128 129 130

V64 (N) % % % % % % % % % % % % 1 1 6 8 1

Australia (AU) 2183 - - % % 0,30% - - - 0,40% - % -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -


Denmark (DK) 1322 - - - - - - - - 0,10% - - -1 86

Finland (FI) 1379 - - - - 0,10% 6,20% - - - - - -

France (FR) 1669 - - - - - - - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -1

Ireland (IE) 1065 - - - - 0,10% - - - - - - -11

Israel Jews (IL-J) 1066 - - - - 1,00% - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -2 2

New Zealand (NZ) 1036 - - - - 0,20% - - - - 0,20% - -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -41

Russia (RU) 2383 - - - - - - - 1,70% - - - -1050

Slovak Republic (SK) 1152 - - 91,10% - - - - - - - - -

Slovenia (SI) 1093 - - - - - - - - - - - -211 55 33

South Africa (ZA) 2483 8,50% 2,20% - - - - - - - - - 1,30%

South Korea (KR) 1315 - - - - - - - - - - - -1013

Spain (ES) 1212 - - - - 83,90% - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -8 2

Switzerland (CH) 1037 - - - - 0,80% - 0,20% - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -25

United States (US) 1216 - - - - 2,10% - - - - - - -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 211 55 1051 1 1067 86 2 41 9 2 1 33


131 132 135 137 980 983 999

V64 (N) % % % % % % % 3 2 1 17

Australia (AU) 2183 0,10% 0,10% % - - 0,80% 30M

Austria (AT) 1006 - - - - - -

Bulgaria (BG) 1069 - - - - - - 28

Canada (CA) 1211 - - - - - 2,40% 32M

Chile (CL) 1505 - - - - - -

Czech Republic (CZ) 1276 - - - - - - 4M3

Denmark (DK) 1322 0,20% - - - - - 8

Finland (FI) 1379 - - - - - 0,60% 1

France (FR) 1669 0,10% - - - - - 48M

Germany-West (DE-W) 850 - - - - - -

Germany-East (DE-E) 437 - - - - - -

Great Britain (GB) 873 - - - - - -

Hungary (HU) 1021 - - - - - -

Ireland (IE) 1065 - - - - - - 1 7

Israel Jews (IL-J) 1066 0,10% - - - - 0,70% 1M

Israel Arabs (IL-A) 152 - - - - - -

Japan (JP) 1102 - - - - - - 23M

Latvia (LV) 1000 - - - - - - 17

New Zealand (NZ) 1036 - - - - - 1,70% 15M

Norway (NO) 1469 - - - - - -

Poland (PL) 1277 - - - - - -

Portugal (PT) 1602 - - - - - -

Philippines (PH) 1200 - - - - - - 1 2

Russia (RU) 2383 - % - - - 0,10% 5M12

Slovak Republic (SK) 1152 - 1,00% - - - -

Slovenia (SI) 1093 - - - - - - 67 5 9

South Africa (ZA) 2483 - - - 2,70% 0,20% 0,40% 15M

South Korea (KR) 1315 - - - - - - 37

Spain (ES) 1212 - - - - - 3,10% 4M

Sweden (SE) 1186 - - - - - - 13

Switzerland (CH) 1037 - - - - - 1,30%

Taiwan (TW) 2016 - - - - - - 2 7

United States (US) 1216 - 0,20% - - - 0,60% 13M

Uruguay (UY) 1108 - - - - - -

Venezuela (VE) 1199 - - - - - - Sum 44170 8 17 1 67 5 145 190M


V65 What language speak at home 2nd mention Missing Values: 00;99 Q17.- What languages do you speak most often at home? At home, I speak: [write down up to two choices]

1. Africa,Mandinka,Somalia,Sudan,Yoruba 49. German,Germany (CZ:Nemec) 96. Ozamisnon 2. Afrikaan 50. German+Danish 97. Pacific,Polynesian,Chamorro Guam 3. Aklanon,Romblon 51. Greek,Greece 98. Pakistan,Panjab/Punjabi,Pashto 4. Albanian 52. Hebrew/Ivrit 99. Panggalatok Pangasinan,Pangasinense 5. Alsacien, France 53. Hungarian,Hungary (CZ:Magyar) 100. Philippines,Tagalog,Filippino 6. American Indian,Navajo,Ind.Dialect 54. Ibanag 101. Pidgin, PNG Pidgin 7. American,American only,America,USA 55. Ifugao 102. Polish,Pole,Poland 8. Antiqueño 56. Igorot 103. Portuguese, Portugal 9. Arab,Arabic,Muslim 57. Ilocano 104. Provençal, France 10. Armenian,Transcaucasian 58. Ilonggo 105. Romani,Gipsy ,Tzyganes 11. Asian,Asia,other Asian 59. French+English 106. Romanian/Rumanian 12. Australian,Oceanian,Australia 60. Indian,Hindi,Urdu,Gujarati,Tamil 107. Romblonon 13. Austrian,Austria 61. Indonesian,Malay/Malaysian 108. Russian,Russia,USSR&Rep. 14. Bangladeshi,Bengali,Bangladesh 62. Inuit, Eskimo 109. Samic,Lapp 15. Basque/Vasco 63. Iranian,Persian/Farsi,Dari 110. Samoan,Tokelauan 16. Belgian,Belgium 64. Iraq 111. Scotland,Scots Gaelic,Scottish 17. Belorussian,Bialorussian 65. Irish/Irish Gaelic,Ireland 112. Sepedi 18. Bicolano/Bikol 66. Isindebele 113. Serbia,Serbian,Serb, Yugoslavian 19. Bilaan 67. Isixhosa 114. Sesotho 20. Black/African/Carribean,No-Spanish 68. Isizulu 115. Setswana 21. Bosnian, SLO:ethn.Muslim 69. Italian,Italy 116. Silesian 22. Breton, France 70. Itawis 117. Siswati 23. Bul-anon 71. Itneg 118. Slovakia,Slovak 24. Bulgarian 72. Japanese,Japan 119. Slovenia,Slovenian,Slovene 25. Cajun French 73. Jordan 120. Somalia 26. Catalan,Valencian,Balear/Mallorquin 74. Kapampangan' 121. Spanish,Castilian,Castellano 27. Coloured 75. Karay-a 122. Subanen 28. Cook Island Maori 76. Korean 123. Surigaonon 29. Corse, France 77. Kurdish,Assyrian,Lebanese 124. Swedish (both citizen) 30. Creole,Surinam/Sranan,Metis,Chavacano 78. Latin-American, South America,


31. Jewish/Yiddish 79. Latvian,Estonian,Lith.,Baltic 126. Tatar 32. Croatian 80. Lithuanian 127. Thai,Khmer,Vietnamese,Cont.Southeast 33. Czech-Czechia,Czech Republic 81. Luxemborger, Luxemburg 128. Tongan,Niuean 34. Chinese-Cantonese,Hakka,Mandarin 82. Philippine other (Maguindanao,


35. Danish,Denmark 83. Maori,NZ Maori 131. Turkey,Turkish 36. Danish+English 84. Maranaw/Maranao 132. Ukraine,Ukrainian 37. English + Persian 85. Masbateño 133. Visayan/Cebuano,Boholano,Leyteno 38. English + Tai 86. Metis 134. Waray 39. English,England&Wales,UK,England 87. Montenegro 135. Welsh 40. Esperanto,Latin,Slavonik,Celtic 88. Moravian 136. Whites (all) 41. Estonia 89. Netherlands,Dutch,Flemish 137. Xitsonga 42. Ethiopia 990. No languages at all 138. Zamboangeño 43. European,White/European,Europe 90. Nordic,Scandinavian other 980. Other African language 44. Europeans Mediterranean 91. North Africans 981. Other,East European 45. Finnish,Finland 92. Norwegian,Norway 982. Other,Middle East 46. French,France 93. Occitan, France 983. Other,Mixed origin 47. Gallego 94. One non-Swedish,both non-Swedish 984. Other,Western European 48. Georgian 95. Oriental

0. Not available (Not asked) 998. Don’t know. 999. No answer. NOTES:

(1) Not asked in Australia, Austria, Bulgaria, Canada, Chile, Finland, Germany, Great Britain, Hungary, Israel, Japan, Latvia, Norway, Poland, Portugal, Philippines, Russia, South-Africa, Slovenia, Sweden,Taiwan, United States, Uruguay and Venezuela


0 1 2 4 5 7 9 10 11 12 15 16

V65 (N) % % % % % % % % % % % %

Australia (AU) 2183 2183M - - - - - - - - - - -

Austria (AT) 1006 1006M - - - - - - - - - - -

Bulgaria (BG) 1069 1069M - - - - - - - - - - -

Canada (CA) 1211 1211M - - - - - - - - - - -

Chile (CL) 1505 1505M - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - -1 1 2 1

Denmark (DK) 1322 1229M 1,10% - - - 1,10% 2,20% - - 1,10% - -

Finland (FI) 1379 1379M - - - - - - - - - - -14 9 2

France (FR) 1669 - - 7,40% 4,70% - - - - - 1,10% -

Germany-West (DE-W) 850 850M - - - - - - - - - - -

Germany-East (DE-E) 437 437M - - - - - - - - - - -


Hungary (HU) 1021 1021M - - - - - - - - - - -1

Ireland (IE) 1065 - - - - - 0,60% - - - - -3 78 60 3

Israel Jews (IL-J) 1066 616M 0,70% - - - 18,00% 13,90% - - - - 0,70%1 22

Israel Arabs (IL-A) 152 64M - - - - 1,10% 25,00% - - - - -

Japan (JP) 1102 1045M - - - - - - - - - - -1 2

Latvia (LV) 1000 854M - - - - - - 0,70% 1,40% - - -5

New Zealand (NZ) 1036 - 3,90% - - - - - - - - -

Norway (NO) 1469 1469M - - - - - - - - - - -

Poland (PL) 1277 1271M - - - - - - - - - - -

Portugal (PT) 1602 1602M - - - - - - - - - - -

Philippines (PH) 1200 1200M - - - - - - - - - - -4

Russia (RU) 2383 2350M - - - - - - 12,10% - - - -


Slovenia (SI) 1093 1093M - - - - - - - - - - -

South Africa (ZA) 2483 2483M - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - -30

Spain (ES) 1212 - - - - - - - - - 8,40% -

Sweden (SE) 1186 1186M - - - - - - - - - - -2

Switzerland (CH) 1037 - - 0,60% - - - - - - - -

Taiwan (TW) 2016 2016M - - - - - - - - - - -

United States (US) 1216 1052M - - - - - - - - - - -

Uruguay (UY) 1108 1108M - - - - - - - - - - -



22 24 25 26 28 29 30 31 32 33 34 35

V65 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -29

Czech Republic (CZ) 1276 - - - - - - - - - 31,50% - -1 22

Denmark (DK) 1322 - - - - - - - - - - 1,10% 23,70%

Finland (FI) 1379 - - - - - - - - - - - -9 2 1

France (FR) 1669 4,70% - - - - 1,10% 0,50% - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -3 25

Israel Jews (IL-J) 1066 - 0,70% - - - - - 5,80% - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -3

Japan (JP) 1102 - - - - - - - - - - 8,80% -

Latvia (LV) 1000 - - - - - - - - - - - -64 15

New Zealand (NZ) 1036 - - - - 50,40% - - - - - 11,80% -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -1

Russia (RU) 2383 - - - - - - - 3,00% - - - -1 24

Slovak Republic (SK) 1152 - - - - - - - - 0,40% 10,30% - -

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -79

Spain (ES) 1212 - - - 22,20% - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -4

Switzerland (CH) 1037 - - - - - - - - 1,20% - - -

Taiwan (TW) 2016 - - - - - - - - - - - -1 6

United States (US) 1216 - - 0,70% - - - - - - - 4,00% -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 9 3 1 79 64 2 1 26 5 53 25 22


36 37 38 39 43 46 47 49 50 51 52 53

V65 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -12 3 10 4

Czech Republic (CZ) 1276 - - - 13,00% - 3,30% - 10,90% - - - 4,30%1 1 1 43 5 7 1 1

Denmark (DK) 1322 1,10% 1,10% 1,10% 46,20% - 5,40% - 7,50% 1,10% - - 1,10%

Finland (FI) 1379 - - - - - - - - - - - -56 20 18

France (FR) 1669 - - - 29,50% - 10,50% - 9,50% - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -9 9

Ireland (IE) 1065 - - - 5,60% - 5,60% - - - - - -20 4 1 129 9

Israel Jews (IL-J) 1066 - - - - - 4,60% - 0,90% - 0,20% 29,80% 2,10%65

Israel Arabs (IL-A) 152 - - - - - - - - - - 73,90% -30

Japan (JP) 1102 - - - 88,20% - - - - - - - -2

Latvia (LV) 1000 - - - 1,40% - - - - - - - -2

New Zealand (NZ) 1036 - - - - - - - 1,60% - - - -

Norway (NO) 1469 - - - - - - - - - - - -1 3

Poland (PL) 1277 - - - 20,00% - - - 60,00% - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -2 1

Russia (RU) 2383 - - - 6,10% 3,00% - - - - - - -8 72

Slovak Republic (SK) 1152 - - - - - - - 3,40% - - - 30,80%

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -25

Spain (ES) 1212 - - - - - - 7,00% - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -36 85 85

Switzerland (CH) 1037 - - - 11,00% - 26,10% - 26,10% - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -32 6 4 3 2

United States (US) 1216 - - - 21,20% - 4,00% - 2,60% - 2,00% 1,30% -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 1 1 1 223 1 148 25 141 1 4 196 86


60 63 65 69 72 76 79 81 89 90 92 93

V65 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -


Denmark (DK) 1322 - - - - - - - - - 1,10% - -

Finland (FI) 1379 - - - - - - - - - - - -7 1 10

France (FR) 1669 - - - 3,70% - - - 0,50% - - - 5,30%

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -136 3

Ireland (IE) 1065 - - 84,00% 1,90% - - - - - - - -4 10 2

Israel Jews (IL-J) 1066 0,90% 2,30% - 0,50% - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -3 1 2 3 8

New Zealand (NZ) 1036 2,40% - - 0,80% 1,60% 2,40% - - 6,30% - - -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -1

Russia (RU) 2383 - - - - - - 3,00% - - - - -


Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -1315

South Korea (KR) 1315 - - - - - 100,00% - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -39

Switzerland (CH) 1037 - - - 12,00% - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -2 2 1 1

United States (US) 1216 1,30% - - 1,30% 0,70% - - - - - 0,70% -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 9 10 136 54 3 1318 1 1 8 1 1 10


98 99 100 102 103 104 105 106 108 110 113 118

V65 (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -8 2 1 13

Czech Republic (CZ) 1276 - - - 8,70% - - 2,20% - 1,10% - - 14,10%

Denmark (DK) 1322 - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - -14 5 4

France (FR) 1669 7,40% - - - 2,60% 2,10% - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -2 1 12 41

Israel Jews (IL-J) 1066 - - - 0,50% 0,20% - - 2,80% 9,50% - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -4 1 134

Latvia (LV) 1000 - - - 2,70% - - 0,70% - 91,80% - - -7

New Zealand (NZ) 1036 - - - - - - - - - 5,50% - -

Norway (NO) 1469 - - - - - - - - - - - -1

Poland (PL) 1277 - - - - - - - - 20,00% - - -

Portugal (PT) 1602 - - - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -12

Russia (RU) 2383 - - - - - - - - 36,40% - - -3 27 55

Slovak Republic (SK) 1152 - - - 1,30% - - 11,50% - - - - 23,50%

Slovenia (SI) 1093 - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -3 1

Switzerland (CH) 1037 - - - - 0,90% - - - - - 0,30% -

Taiwan (TW) 2016 - - - - - - - - - - - -1 2 1 1 1 1

United States (US) 1216 - 0,70% 1,30% 0,70% 0,70% - - 0,70% 0,70% - - -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 14 1 2 18 10 4 30 13 190 7 1 68


121 124 125 126 127 131 132 133 983 999

V65 (N) % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - -

Austria (AT) 1006 - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - -

Canada (CA) 1211 - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - 1 9

Czech Republic (CZ) 1276 1,10% - - - - - - - 9,80% 1184M 1 3

Denmark (DK) 1322 1,10% - - - - 3,20% - - -

Finland (FI) 1379 - - - - - - - - - 15 1 2

France (FR) 1669 7,90% - - - 0,50% 1,10% - - - 1479M

Germany-West (DE-W) 850 - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - 3 1

Ireland (IE) 1065 1,90% - - - - 0,60% - - - 903M 17 9

Israel Jews (IL-J) 1066 3,90% - - - - - - - 2,10% 17M

Israel Arabs (IL-A) 152 - - - - - - - - - 1

Japan (JP) 1102 - - - - 2,90% - - - - 23M 2

Latvia (LV) 1000 - - - - - - 1,40% - - 2 15

New Zealand (NZ) 1036 1,60% - - - - - - - 11,80% 909M

Norway (NO) 1469 - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - 1M

Portugal (PT) 1602 - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - 10 2

Russia (RU) 2383 - - - 30,30% - - 6,10% - - 44

Slovak Republic (SK) 1152 - - - - - - 18,80% - - 918M

Slovenia (SI) 1093 - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - 169 53

Spain (ES) 1212 47,50% - - - - - - - 14,90% 856M

Sweden (SE) 1186 - - - - - - - - - 11 11 49

Switzerland (CH) 1037 3,40% - 3,40% - - - - - 15,00% 711M

Taiwan (TW) 2016 - - - - - - - - - 71 2 1 10

United States (US) 1216 47,00% 1,30% - - - - - 0,70% 6,60% 13M

Uruguay (UY) 1108 - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - Sum 44170 290 2 11 10 2 6 48 1 145 7014M


V66 One nation - Separate nation Missing Values: 0; 8; 9 Q18.- Which of these two statements comes closer to your own view?1 1. It is essential that [COUNTRY] remains one [nation/state/country]2

2. Parts of [Country] should be allowed to become fully separate [nations/states/countries] if they choose to 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes (1) Not asked in Austria, Bulgaria, Chile, Finland, Germany, Great Britain, Hungary, Ireland, Israel, Norway, Philippines, Portugal, Slovenia, South Africa, South Korea, Sweden, United States, Uruguay and Venezuela. (2) Whichever word best applies to COUNTRY


0 1 2 8 9

V66 (N) % % % % % 2035 44

Australia (AU) 2183 97,90% 2,10% 68M 36M

Austria (AT) 1006 1006M - -

Bulgaria (BG) 1069 1069M - - 944 191

Canada (CA) 1211 83,20% 16,80% 69M 7M

Chile (CL) 1505 1505M - - 992 136

Czech Republic (CZ) 1276 87,90% 12,10% 148M1042 198

Denmark (DK) 1322 84,00% 16,00% 68M 14M

Finland (FI) 1379 1379M - - 1341 188

France (FR) 1669 87,70% 12,30% 125M 15M

Germany-West (DE-W) 850 850M - -

Germany-East (DE-E) 437 437M - -

Great Britain (GB) 873 873M - -

Hungary (HU) 1021 1021M - -

Ireland (IE) 1065 1065M - -

Israel Jews (IL-J) 1066 1066M - -

Israel Arabs (IL-A) 152 152M - - 909 75

Japan (JP) 1102 92,40% 7,60% 110M 8M757 136

Latvia (LV) 1000 84,80% 15,20% 107M 963 25

New Zealand (NZ) 1036 97,50% 2,50% 30M 18M

Norway (NO) 1469 1469M - - 849 149

Poland (PL) 1277 85,10% 14,90% 278M 1M

Portugal (PT) 1602 1602M - -

Philippines (PH) 1200 1200M - - 1851 247

Russia (RU) 2383 88,20% 11,80% 285M 1013 35

Slovak Republic (SK) 1152 96,70% 3,30% 104M

Slovenia (SI) 1093 1093M - -

South Africa (ZA) 2483 2483M - -

South Korea (KR) 1315 1315M - - 893 167

Spain (ES) 1212 84,20% 15,80% 77M 75M

Sweden (SE) 1186 1186M - - 928 66


Taiwan (TW) 2016 84,10% 15,90% 381M 29M

United States (US) 1216 1216M - -

Uruguay (UY) 1108 1108M - -

Venezuela (VE) 1199 1199M - - Sum 44170 24294M 15868 1912 1739M 357M


V67 How close do you feel to your ethnic group Missing Values: 0; 8; 9 Q19a.- How close do you feel to your ethnic group? 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes (1) Not asked in Australia, Austria, Bulgaria, Canada, Chile, Finland, Germany, Great Britain, Hungary, Ireland, Norway, Philippines, Portugal, Slovenia, South Korea, Sweden, Switzerland, Uruguay and Venezuela.


0 1 2 3 4 8 9

V67 (N) % % % % % % %

Australia (AU) 2183 2183M - - - -

Austria (AT) 1006 1006M - - - -

Bulgaria (BG) 1069 1069M - - - -

Canada (CA) 1211 1211M - - - -

Chile (CL) 1505 1505M - - - - 560 581 59 13


Denmark (DK) 1322 31,40% 40,80% 16,50% 11,30% 69M

Finland (FI) 1379 1379M - - - - 407 545 158 190

France (FR) 1669 31,30% 41,90% 12,20% 14,60% 235M 134M

Germany-West (DE-W) 850 850M - - - -

Germany-East (DE-E) 437 437M - - - -

Great Britain (GB) 873 873M - - - -

Hungary (HU) 1021 1021M - - - -

Ireland (IE) 1065 1065M - - - - 500 312 124 94

Israel Jews (IL-J) 1066 48,50% 30,30% 12,00% 9,10% 7M 29M91 44 16

Israel Arabs (IL-A) 152 60,30% 29,10% 10,60% - 1M557 452 56 6

Japan (JP) 1102 52,00% 42,20% 5,20% 0,60% 27M 4M256 493 181 42

Latvia (LV) 1000 26,30% 50,70% 18,60% 4,30% 28M 274 440 174 58

New Zealand (NZ) 1036 29,00% 46,50% 18,40% 6,10% 59M 31M

Norway (NO) 1469 1469M - - - - 251 591 156 89

Poland (PL) 1277 23,10% 54,40% 14,40% 8,20% 189M 1M

Portugal (PT) 1602 1602M - - - -

Philippines (PH) 1200 1200M - - - - 606 921 497 147

Russia (RU) 2383 27,90% 42,40% 22,90% 6,80% 212M 532 523 49 5


Slovenia (SI) 1093 1093M - - - - 1531 708 81 15

South Africa (ZA) 2483 65,60% 30,30% 3,50% 0,60% 109M 39M

South Korea (KR) 1315 1315M - - - - 370 739 38 19

Spain (ES) 1212 31,70% 63,40% 3,30% 1,60% 31M 15M

Sweden (SE) 1186 1186M - - - -

Switzerland (CH) 1037 1037M - - - - 293 1170 207 5

Taiwan (TW) 2016 17,50% 69,90% 12,40% 0,30% 325M 16M467 410 205 50

United States (US) 1216 41,30% 36,20% 18,10% 4,40% 79M 5M

Uruguay (UY) 1108 1108M - - - -

Venezuela (VE) 1199 1199M - - - - Sum 44170 23808M 7088 8440 2208 875 1383M 368M


V68 R: More regional or national identity Missing Values: 0; 8; 9 Q19b.- Some people think of themselves first as [COUNTRY NATIONALITY]. Others may think of themselves first as [region] 1. Which if any, of the following best describes how you see yourself? 2 1. Only [regional identity]. 2. More [regional identity] than [COUNTRY NATIONALITY]. 3. As [regional identity] as [COUNTRY NATIONALITY]. 4. More [COUNTRY NATIONALITY] than [regional identity]. 5. Only [COUNTRY NATIONALITY]. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes (1) “Region” should be replaced by the appropriate subnational category in each COUNTRY (e.g. “Scotland” in Britain; “Catalonia” in Spain). If it is a face-to-face interview, insert the name of the appropriate subnational unit where the interview is being conducted; if it is a self-completion questionnaire, all the relevant subnational units should be mentioned (e.g. “see themselves first as Scottish, English, or Welsh”; “see themselves as only Scottish, English, or Welsh”). (2)Not asked in Australia, Austria, Bulgaria, Canada, Chile, Denmark, Finland, Germany, Great Britain, Hungary, Ireland, Israel, Japan, Latvia, Norway, Philippines, Portugal, Slovenia, South Africa, South Korea, Sweden, Taiwan, United States, Uruguay and Venezuela.


0 1 2 3 4 5 6 7 8 9

V68 (N) % % % % % % % % % %

Australia (AU) 2183 2183M - - - - - - -

Austria (AT) 1006 1006M - - - - - - -

Bulgaria (BG) 1069 1069M - - - - - - -

Canada (CA) 1211 1211M - - - - - - -

Chile (CL) 1505 1505M - - - - - - - 249 126 365 121 352 10 12

Czech Republic (CZ) 1276 20,20% 10,20% 29,60% 9,80% 28,50% 0,80% 1,00% 41M

Denmark (DK) 1322 1322M - - - - - - -

Finland (FI) 1379 1379M - - - - - - - 29 99 544 401 458 44 76

France (FR) 1669 1,80% 6,00% 32,90% 24,30% 27,70% 2,70% 4,60% 18M

Germany-West (DE-W) 850 850M - - - - - - -

Germany-East (DE-E) 437 437M - - - - - - -

Great Britain (GB) 873 873M - - - - - - -

Hungary (HU) 1021 1021M - - - - - - -

Ireland (IE) 1065 1065M - - - - - - -

Israel Jews (IL-J) 1066 1066M - - - - - - -

Israel Arabs (IL-A) 152 152M - - - - - - -

Japan (JP) 1102 1102M - - - - - - -

Latvia (LV) 1000 1000M - - - - - - - 13 89 292 595

New Zealand (NZ) 1036 1,30% 9,00% - 29,50% 60,20% - - 24M 23M

Norway (NO) 1469 1469M - - - - - - - 54 45 398 186 483 26

Poland (PL) 1277 4,50% 3,80% 33,40% 15,60% 40,50% 2,20% - 85M

Portugal (PT) 1602 1602M - - - - - - -

Philippines (PH) 1200 1200M - - - - - - - 260 139 885 287 578 15

Russia (RU) 2383 12,00% 6,40% 40,90% 13,30% 26,70% 0,70% - 219M 45 29 74 154 792 17 41

Slovak Republic (SK) 1152 3,90% 2,50% 6,40% 13,40% 68,80% 1,50% 3,60%

Slovenia (SI) 1093 1093M - - - - - - -

South Africa (ZA) 2483 2483M - - - - - - -

South Korea (KR) 1315 1315M - - - - - - - 36 169 696 136 150

Spain (ES) 1212 3,00% 14,20% 58,60% 11,50% 12,60% - - 5M 20M

Sweden (SE) 1186 1186M - - - - - - - 57 128 201 100 438 56 46

Switzerland (CH) 1037 5,60% 12,50% 19,60% 9,70% 42,70% 5,50% 4,50% 8M 3M

Taiwan (TW) 2016 2016M - - - - - - -

United States (US) 1216 1216M - - - - - - -

Uruguay (UY) 1108 1108M - - - - - - -

Venezuela (VE) 1199 1199M - - - - - - - Sum 44170 33128M 743 824 3163 1677 3846 168 175 341M 105M


V69 Heard-read about [the European Union] Missing Values: 0; 8; 9 Q20.- How much have you heard or read about [the European Union] 1,2? 1. A lot. 2. Quite a bit. 3. Not much. 4. Nothing at all. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes (1) Not asked in Australia, Bulgaria, Chile, Denmark, Germany, Great Britain, Hungary, Ireland, Israel, Japan, New Zealand, Philippines, Portugal, Slovenia, South Africa, South Korea, Sweden, Taiwan, Venezuela. (2) Precode: [the European Union]: Take the appropriate association for your continent/subcontinent—EU, NAFTA, etc... Uruguay: refers to MERCOSUR Canada, United States: refers to NAFTA


0 1 2 3 4 8 9

V69 (N) % % % % % % %

Australia (AU) 2183 2183M - - - - 145 478 348 25

Austria (AT) 1006 14,60% 48,00% 34,90% 2,50% 10M

Bulgaria (BG) 1069 1069M - - - - 186 425 510 79

Canada (CA) 1211 15,50% 35,40% 42,50% 6,60% 11M

Chile (CL) 1505 1505M - - - - 101 618 466 50

Czech Republic (CZ) 1276 8,20% 50,00% 37,70% 4,00% 41M

Denmark (DK) 1322 1322M - - - - 327 817 209 21

Finland (FI) 1379 23,80% 59,50% 15,20% 1,50% 5M718 634 278 31

France (FR) 1669 43,20% 38,20% 16,70% 1,90% 8M

Germany-West (DE-W) 850 850M - - - -

Germany-East (DE-E) 437 437M - - - -

Great Britain (GB) 873 873M - - - -

Hungary (HU) 1021 1021M - - - -

Ireland (IE) 1065 1065M - - - -

Israel Jews (IL-J) 1066 1066M - - - -

Israel Arabs (IL-A) 152 152M - - - -

Japan (JP) 1102 1102M - - - - 158 480 350 12

Latvia (LV) 1000 15,80% 48,00% 35,00% 1,20%

New Zealand (NZ) 1036 1036M - - - - 437 802 195 14

Norway (NO) 1469 30,20% 55,40% 13,50% 1,00% 21M96 596 530 55

Poland (PL) 1277 7,50% 46,70% 41,50% 4,30%

Portugal (PT) 1602 1602M - - - -

Philippines (PH) 1200 1200M - - - - 90 362 1061 870

Russia (RU) 2383 3,80% 15,20% 44,50% 36,50% 131 535 436 47


Slovenia (SI) 1093 1093M - - - -

South Africa (ZA) 2483 2483M - - - -

South Korea (KR) 1315 1315M - - - - 113 559 462 59

Spain (ES) 1212 9,50% 46,90% 38,70% 4,90% 19M

Sweden (SE) 1186 1186M - - - - 379 475 172 10

Switzerland (CH) 1037 36,60% 45,80% 16,60% 1,00% 1M

Taiwan (TW) 2016 2016M - - - - 143 289 554 221


Uruguay (UY) 1108 12,30% 32,40% 42,40% 12,90% 2M

Venezuela (VE) 1199 1199M - - - - Sum 44170 25775M 3160 7428 6040 1637 15M 115M


V70 Benefits from being member of [the European Union] Missing Values: 0; 8; 9 Q21.- Generally speaking, would you say that [COUNTRY] benefits or does not benefit from being a member of [the European Union]? (Non-members “would benefit” or “would not benefit”)1,2 1. Greatly benefits. 2. Largely benefits. 3. Somewhat benefits. 4. Only a little. 5. Not at all benefit. 0. Not available (Not asked); not applicable, never heard 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Australia, Bulgaria, Chile, Denmark, Germany, Great Britain, Ireland, Israel, Japan, Latvia, New Zealand, Norway, Philippines, Portugal, Slovenia, South Africa, South Korea, Sweden, Taiwan, Venezuela. (2) Precode: take the appropriate association, as in Q20. Scale for non-members of whatever association is used: Would benefit/Would not benefit/Don’t know/Have never heard of [the European Union] Uruguay: refers to MERCOSUR Canada, United States: refers to NAFTA


0 1 2 3 4 5 8 9

V70 (N) % % % % % % % %

Australia (AU) 2183 2183M - - - - - 400 414

Austria (AT) 1006 49,10% - - - 50,90% 192M

Bulgaria (BG) 1069 1069M - - - - - 68 154 458 193 56

Canada (CA) 1211 7,30% 16,60% 49,30% 20,80% 6,00% 225M 57M

Chile (CL) 1505 1505M - - - - - 49 183 309 330 167

Czech Republic (CZ) 1276 2M 4,70% 17,60% 29,80% 31,80% 16,10% 197M 39M

Denmark (DK) 1322 1322M - - - - - 35 187 581 306 110

Finland (FI) 1379 1M 2,90% 15,30% 47,70% 25,10% 9,00% 154M 5M 227 483 559 161 39

France (FR) 1669 4M 15,50% 32,90% 38,10% 11,00% 2,70% 184M 12M

Germany-West (DE-W) 850 850M - - - - -

Germany-East (DE-E) 437 437M - - - - -

Great Britain (GB) 873 873M - - - - - 30 272 293 163 111

Hungary (HU) 1021 3,50% 31,30% 33,70% 18,80% 12,80% 152M

Ireland (IE) 1065 1065M - - - - -

Israel Jews (IL-J) 1066 1066M - - - - -

Israel Arabs (IL-A) 152 152M - - - - -

Japan (JP) 1102 1102M - - - - -

Latvia (LV) 1000 1000M - - - - -

New Zealand (NZ) 1036 1036M - - - - -

Norway (NO) 1469 1469M - - - - - 65 339 401 213 84

Poland (PL) 1277 3M 5,90% 30,80% 36,40% 19,30% 7,60% 172M 153 390 643 213 79

Portugal (PT) 1602 3M 10,40% 26,40% 43,50% 14,40% 5,30% 118M 3M

Philippines (PH) 1200 1200M - - - - - 52 220 414 141 166

Russia (RU) 2383 870M 5,20% 22,20% 41,70% 14,20% 16,70% 520M 58 210 473 261 59

Slovak Republic (SK) 1152 3M 5,50% 19,80% 44,60% 24,60% 5,60% 84M 4M

Slovenia (SI) 1093 1093M - - - - -

South Africa (ZA) 2483 2483M - - - - -

South Korea (KR) 1315 1315M - - - - - 101 479 410 94 48

Spain (ES) 1212 8M 8,90% 42,30% 36,20% 8,30% 4,20% 72M

Sweden (SE) 1186 1186M - - - - - 14 143 360 262 178

Switzerland (CH) 1037 1M 1,50% 14,90% 37,60% 27,40% 18,60% 73M 6M

Taiwan (TW) 2016 2016M - - - - - 52 105 360 144 104

United States (US) 1216 112M 6,80% 13,70% 47,10% 18,80% 13,60% 332M 7M 48 199 417 194 108

Uruguay (UY) 1108 10M 5,00% 20,60% 43,20% 20,10% 11,20% 132M

Venezuela (VE) 1199 1199M - - - - - Sum 44170 26638M 1352 3364 5678 2675 1723 2455M 285M


V70b Would benefit from being member of [the European Union] Missing Values: 0; 8; 9 Q21.- Generally speaking, would you say that [COUNTRY] would benefit or would not benefit from being a member of [the European Union]? 1,2 1. Would benefit 2. Would not benefit 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Asked only in Latvia and Norway


0 1 2 8 9

V70B (N) % % % % % 2183M

Australia (AU) 2183 - - 1006M

Austria (AT) 1006 - - 1069M

Bulgaria (BG) 1069 - - 1211M

Canada (CA) 1211 - - 1505M

Chile (CL) 1505 - - 1276M

Czech Republic (CZ) 1276 - - 1322M

Denmark (DK) 1322 - - 1379M

Finland (FI) 1379 - - 1669M

France (FR) 1669 - - 850M

Germany-West (DE-W) 850 - - 437M

Germany-East (DE-E) 437 - - 873M

Great Britain (GB) 873 - - 1021M

Hungary (HU) 1021 - - 1065M

Ireland (IE) 1065 - - 1066M

Israel Jews (IL-J) 1066 - - 152M

Israel Arabs (IL-A) 152 - - 1102M

Japan (JP) 1102 - - 2M 413 212

Latvia (LV) 1000 66,10% 33,90% 373M1036M

New Zealand (NZ) 1036 - - 600 495

Norway (NO) 1469 - 54,80% 45,20% 351M 23M1277M

Poland (PL) 1277 - - 1602M

Portugal (PT) 1602 - - 1200M

Philippines (PH) 1200 - - 2383M

Russia (RU) 2383 - - 1152M

Slovak Republic (SK) 1152 - - 1093M

Slovenia (SI) 1093 - - 2483M

South Africa (ZA) 2483 - - 1315M

South Korea (KR) 1315 - - 1212M

Spain (ES) 1212 - - 1186M

Sweden (SE) 1186 - - 1037M

Switzerland (CH) 1037 - - 2016M

Taiwan (TW) 2016 - - 1216M

United States (US) 1216 - - 1108M

Uruguay (UY) 1108 - - 1199M

Venezuela (VE) 1199 - - Sum 44170 41703M 1013 707 351M 396M


V71 [Country] should follow decisions of EU Missing Values: 0; 8; 9 Q22.- How strongly do you agree or disagree with the following statement? (Please, tick one box) 1. Agree strongly. 2. Agree. 3. Neither agree nor disagree. 4. Disagree. 5. Disagree strongly. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Australia, Bulgaria, Canada, Chile, Denmark, Germany, Great Britain, Hungary, Ireland, Israel, Japan, New Zealand, Philippines, Portugal, Russia, Slovenia, South Africa, South Korea, Switzerland, Taiwan and Venezuela. (2) Precode: take the appropriate association, as in 20 Uruguay: refers to MERCOSUR United States: refers to NAFTA


0 1 2 3 4 5 8 9

V71 (N) % % % % % % % %

Australia (AU) 2183 2183M - - - - - 57 187 215 289 159

Austria (AT) 1006 6,30% 20,60% 23,70% 31,90% 17,50% 99M

Bulgaria (BG) 1069 1069M - - - - -

Canada (CA) 1211 1211M - - - - -

Chile (CL) 1505 1505M - - - - - 52 212 291 350 185

Czech Republic (CZ) 1276 4,80% 19,40% 26,70% 32,10% 17,00% 111M 75M

Denmark (DK) 1322 1322M - - - - - 56 328 313 417 108

Finland (FI) 1379 4,60% 26,80% 25,60% 34,10% 8,80% 150M 7M 180 455 376 379 201

France (FR) 1669 11,30% 28,60% 23,60% 23,80% 12,60% 66M 12M



Great Britain (GB) 873 873M - - - - -

Hungary (HU) 1021 1021M - - - - -

Ireland (IE) 1065 1065M - - - - -

Israel Jews (IL-J) 1066 1066M - - - - -


Japan (JP) 1102 1102M - - - - - 38 174 268 336 48

Latvia (LV) 1000 4,40% 20,10% 31,00% 38,90% 5,60% 136M

New Zealand (NZ) 1036 1036M - - - - - 48 256 334 530 217

Norway (NO) 1469 3,50% 18,50% 24,10% 38,30% 15,70% 59M 25M 37 234 297 440 72

Poland (PL) 1277 3,40% 21,70% 27,50% 40,70% 6,70% 196M 1M

Portugal (PT) 1602 1602M - - - - -

Philippines (PH) 1200 1200M - - - - -

Russia (RU) 2383 2383M - - - - - 39 165 369 363 149

Slovak Republic (SK) 1152 3,60% 15,20% 34,00% 33,50% 13,70% 64M 3M

Slovenia (SI) 1093 1093M - - - - -

South Africa (ZA) 2483 2483M - - - - -

South Korea (KR) 1315 1315M - - - - - 60 486 346 205 33

Spain (ES) 1212 5,30% 43,00% 30,60% 18,10% 2,90% 61M 21M 63 379 342 236 95

Sweden (SE) 1186 5,70% 34,00% 30,70% 21,20% 8,50% 62M 9M

Switzerland (CH) 1037 1037M - - - - -

Taiwan (TW) 2016 2016M - - - - - 22 163 319 297 64

United States (US) 1216 3M 2,50% 18,80% 36,90% 34,30% 7,40% 338M 10M 57 280 160 380 74

Uruguay (UY) 1108 6,00% 29,40% 16,80% 40,00% 7,80% 155M 2M



V72 EU should have more power than national government Missing Values: 0; 8; 9 Q23.- Generally, do you think that the European Union should have... Much more, more, as much, less, or much less power than the national governments of its member states?1,2 1. Much more. 2. More. 3. As much. 4. Less. 5. Much less. 0. Not available (Not asked) ; Not applicable 8. Can´t choose. 9. Na, refused. Notes: (1) Not asked in Australia, Bulgaria, Canada, Chile, Germany, Great Britain, Ireland, Israel, Japan, New Zealand, Philippines, Russia, Slovenia, South Africa, South Korea, Taiwan, United States, Uruguay and Venezuela. (2) Precode: take the appropriate association, as in 20


0 1 2 3 4 5 8 9

V72 (N) % % % % % % % %

Australia (AU) 2183 2183M - - - - - 10 81 386 326 79

Austria (AT) 1006 1,10% 9,20% 43,80% 37,00% 9,00% 124M

Bulgaria (BG) 1069 1069M - - - - -

Canada (CA) 1211 1211M - - - - -

Chile (CL) 1505 1505M - - - - - 23 145 544 257 100

Czech Republic (CZ) 1276 2,20% 13,60% 50,90% 24,00% 9,40% 139M 68M 10 92 356 486 219

Denmark (DK) 1322 0,90% 7,90% 30,60% 41,80% 18,80% 142M 17M 14 78 315 595 164

Finland (FI) 1379 1,20% 6,70% 27,00% 51,00% 14,10% 203M 10M 78 233 661 368 159

France (FR) 1669 5,20% 15,50% 44,10% 24,50% 10,60% 149M 21M



Great Britain (GB) 873 873M - - - - - 39 248 333 135 51

Hungary (HU) 1021 4,80% 30,80% 41,30% 16,70% 6,30% 5M 210M

Ireland (IE) 1065 1065M - - - - -

Israel Jews (IL-J) 1066 1066M - - - - -


Japan (JP) 1102 1102M - - - - - 9 118 386 188 85

Latvia (LV) 1000 1,10% 15,00% 49,10% 23,90% 10,80% 214M

New Zealand (NZ) 1036 1036M - - - - - 13 142 355 558 190

Norway (NO) 1469 1,00% 11,30% 28,20% 44,40% 15,10% 187M 24M 52 125 528 237 69

Poland (PL) 1277 5,10% 12,40% 52,20% 23,40% 6,80% 266M 66 386 672 198 21

Portugal (PT) 1602 4,90% 28,70% 50,00% 14,70% 1,60% 251M 8M

Philippines (PH) 1200 1200M - - - - -

Russia (RU) 2383 2383M - - - - - 26 150 578 195 44

Slovak Republic (SK) 1152 2,60% 15,10% 58,20% 19,60% 4,40% 156M 3M

Slovenia (SI) 1093 1093M - - - - -

South Africa (ZA) 2483 2483M - - - - -

South Korea (KR) 1315 1315M - - - - - 19 235 666 119 30

Spain (ES) 1212 1,80% 22,00% 62,30% 11,10% 2,80% 118M 25M 19 96 315 431 178

Sweden (SE) 1186 1,80% 9,20% 30,30% 41,50% 17,10% 142M 5M 8 114 332 307 50

Switzerland (CH) 1037 1,00% 14,10% 40,90% 37,90% 6,20% 218M 8M

Taiwan (TW) 2016 2016M - - - - -

United States (US) 1216 1216M - - - - -

Uruguay (UY) 1108 1108M - - - - -



V73 Vote if referendum to become new member Missing Values: 0; 8; 9 Q24.- [For prospective EU members only]. If there were a referendum1 today to decide whether [COUNTRY] does or does not become a member of the European Union, would you vote in favor or would you vote against? 2,3

1. Vote in favor 2. Vote against

0. Not available (Not asked); Not applicable 8. Can´t choose. 9. Na, refused. Notes: (1) If Referenda are not possible in COUNTRY, use the word “vote” (2) Not asked in Australia, Austria, Bulgaria, Canada, Chile, Denmark, Finland, France, Germany, Great Britain, Ireland, Japan, New Zealand, Poland, Portugal, Philippines, Russia, Slovenia, South Africa, South Korea, Sweden, Switzerland, Taiwan, United States, Uruguay and Venezuela. (3) Precode: take the appropriate association, as in 20


0 1 2 8 9

V73 (N) % % % % %

Australia (AU) 2183 2183M - -

Austria (AT) 1006 1006M - -

Bulgaria (BG) 1069 1069M - -

Canada (CA) 1211 1211M - -

Chile (CL) 1505 1505M - - 655 291

Czech Republic (CZ) 1276 69,20% 30,80% 164M 166M

Denmark (DK) 1322 1322M - -

Finland (FI) 1379 1379M - -

France (FR) 1669 1669M - -



Great Britain (GB) 873 873M - - 626 165

Hungary (HU) 1021 79,10% 20,90% 56M 174M

Ireland (IE) 1065 1065M - - 768 187

Israel Jews (IL-J) 1066 80,40% 19,60% 91M 20M121 11

Israel Arabs (IL-A) 152 91,70% 8,30% 6M 14M

Japan (JP) 1102 1102M - - 560 308

Latvia (LV) 1000 64,50% 35,50% 131M 1M

New Zealand (NZ) 1036 1036M - - 587 573

Norway (NO) 1469 50,60% 49,40% 284M 25M

Poland (PL) 1277 1277M - -

Portugal (PT) 1602 1602M - -

Philippines (PH) 1200 1200M - -

Russia (RU) 2383 2383M - - 744 194

Slovak Republic (SK) 1152 79,30% 20,70% 211M 3M

Slovenia (SI) 1093 1093M - -


South Korea (KR) 1315 1315M - - 919 96

Spain (ES) 1212 90,50% 9,50% 166M 31M

Sweden (SE) 1186 1186M - -

Switzerland (CH) 1037 1037M - -

Taiwan (TW) 2016 2016M - -

United States (US) 1216 1216M - -

Uruguay (UY) 1108 1108M - -



V74 EU members: Referendum to remain member Missing Values: 0; 8; 9 Q24b.- [For current EU members only]. If there were a referendum1 today to decide whether [COUNTRY] does or does not remain a member of the European Union, would you vote in favor or would you vote against? 2,3 1. Vote in favour. 2. Vote against. 0. Not available (Not asked) 8. Can´t choose. 9. Na, refused. Notes: (1) If Referenda are not possible in COUNTRY, use the word “vote” (2) Not asked in Australia, Austria, Bulgaria, Canada, Chile, Denmark, Finland, France, Germany, Great Britain, Ireland, Japan, New Zealand, Poland, Portugal, Philippines, Russia, Slovenia, South Africa, South Korea, Sweden, Switzerland, Taiwan, United States, Uruguay and Venezuela. (3) Precode: take the appropriate association, as in 20 Uruguay: refers to MERCOSUR


0 1 2 8 9

V74 (N) % % % % %

Australia (AU) 2183 2183M - - 507 326

Austria (AT) 1006 60,90% 39,10% 173M

Bulgaria (BG) 1069 1069M - -

Canada (CA) 1211 1211M - -

Chile (CL) 1505 1505M - -

Czech Republic (CZ) 1276 1276M - -

Denmark (DK) 1322 1322M - - 704 378

Finland (FI) 1379 65,10% 34,90% 293M 4M1167 320

France (FR) 1669 78,50% 21,50% 177M 5M



Great Britain (GB) 873 873M - -

Hungary (HU) 1021 1021M - -

Ireland (IE) 1065 1065M - -

Israel Jews (IL-J) 1066 1066M - -

Israel Arabs (IL-A) 152 152M - -

Japan (JP) 1102 1102M - -

Latvia (LV) 1000 1000M - -

New Zealand (NZ) 1036 1036M - -

Norway (NO) 1469 1469M - - 857 188

Poland (PL) 1277 82,00% 18,00% 230M 2M

Portugal (PT) 1602 1602M - -

Philippines (PH) 1200 1200M - -

Russia (RU) 2383 2383M - -

Slovak Republic (SK) 1152 1152M - -

Slovenia (SI) 1093 1093M - -


South Korea (KR) 1315 1315M - -

Spain (ES) 1212 1212M - - 518 460

Sweden (SE) 1186 53,00% 47,00% 203M 5M

Switzerland (CH) 1037 1037M - -

Taiwan (TW) 2016 2016M - -

United States (US) 1216 1216M - - 750 151

Uruguay (UY) 1108 83,20% 16,80% 206M 1M



SEX R: Sex Missing Values: 9 SEX. Sex of respondent 1. Male. 2. Female. 9. Na, refused.


1 2 9

SEX (N) % % % 1008 1163

Australia (AU) 2183 46,40% 53,60% 12M463 543

Austria (AT) 1006 46,00% 54,00% 521 548

Bulgaria (BG) 1069 48,70% 51,30% 654 544

Canada (CA) 1211 54,60% 45,40% 13M584 921

Chile (CL) 1505 38,80% 61,20% 555 721

Czech Republic (CZ) 1276 43,50% 56,50% 646 676

Denmark (DK) 1322 48,90% 51,10% 618 761

Finland (FI) 1379 44,80% 55,20% 881 788

France (FR) 1669 52,80% 47,20% 440 410

Germany-West (DE-W) 850 51,80% 48,20% 209 228

Germany-East (DE-E) 437 47,80% 52,20% 363 510

Great Britain (GB) 873 41,60% 58,40% 451 570

Hungary (HU) 1021 44,20% 55,80% 462 603

Ireland (IE) 1065 43,40% 56,60% 526 539

Israel Jews (IL-J) 1066 49,40% 50,60% 1M81 71

Israel Arabs (IL-A) 152 53,30% 46,70% 532 570

Japan (JP) 1102 48,30% 51,70% 424 576

Latvia (LV) 1000 42,40% 57,60% 461 571

New Zealand (NZ) 1036 44,70% 55,30% 4M696 773

Norway (NO) 1469 47,40% 52,60% 607 670

Poland (PL) 1277 47,50% 52,50% 660 942

Portugal (PT) 1602 41,20% 58,80% 600 600

Philippines (PH) 1200 50,00% 50,00% 849 1534

Russia (RU) 2383 35,60% 64,40% 460 692

Slovak Republic (SK) 1152 39,90% 60,10% 497 593

Slovenia (SI) 1093 45,60% 54,40% 3M988 1493

South Africa (ZA) 2483 39,80% 60,20% 2M579 736

South Korea (KR) 1315 44,00% 56,00% 582 630

Spain (ES) 1212 48,00% 52,00% 569 617

Sweden (SE) 1186 48,00% 52,00% 497 540

Switzerland (CH) 1037 47,90% 52,10% 1049 967

Taiwan (TW) 2016 52,00% 48,00% 536 680

United States (US) 1216 44,10% 55,90% 451 657

Uruguay (UY) 1108 40,70% 59,30% 599 600

Venezuela (VE) 1199 50,00% 50,00% Sum 44170 20098 24037 35M


AGE R's age Missing Values: 99 AGE. Age of respondent (nn) number of years 99. Na, refused.

AGE (N) Minimum Maximum Mean Std Deviation Valid N

Australia (AU) 2183 18 96 50,46402214 16,23732609 2168 Austria (AT) 1006 18 98 46,16699801 17,31780622 1006 Bulgaria (BG) 1069 18 89 49,84037559 17,98842735 1065 Canada (CA) 1211 18 94 53,87245841 14,93093565 1082 Chile (CL) 1505 18 96 44,37009967 16,83609294 1505 Czech Republic (CZ) 1276 18 89 45,21468927 16,42692962 1239 Denmark (DK) 1322 18 92 47,35779123 16,70331042 1322 Finland (FI) 1379 15 75 44,1457578 16,50961154 1379 France (FR) 1669 18 98 49,67645297 17,43135362 1669 Germany-West (DE-W) 850 18 91 47,02473498 16,68197538 849 Germany-East (DE-E) 437 18 91 47,35469108 17,87251124 437 Great Britain (GB) 873 18 90 48,90034364 17,26859887 873 Hungary (HU) 1021 18 97 50,8137931 17,42608529 1015 Ireland (IE) 1065 18 92 46,64037559 17,58602016 1065 Israel Jews (IL-J) 1066 18 96 45,94886364 17,25348344 1056 Israel Arabs (IL-A) 152 18 80 34,82236842 16,31929016 152 Japan (JP) 1102 16 93 50,75589837 18,27490491 1102 Latvia (LV) 1000 18 75 42,683 16,17653211 1000 New Zealand (NZ) 1036 18 94 50,46341463 16,91860333 1025 Norway (NO) 1469 18 79 45,06262764 15,46742728 1469 Poland (PL) 1277 18 93 45,79718089 17,80379987 1277 Portugal (PT) 1602 18 92 49,07133917 17,87534004 1598 Philippines (PH) 1200 18 85 39,46833333 15,12116194 1200 Russia (RU) 2383 16 90 45,58833403 18,57870855 2383 Slovak Republic (SK) 1152 17 90 41,65864528 15,35428358 1122 Slovenia (SI) 1093 18 94 46,54212454 17,58694683 1092 South Africa (ZA) 2483 16 96 38,75191919 15,60550551 2475 South Korea (KR) 1315 18 93 41,91832061 15,34782019 1310 Spain (ES) 1212 18 92 45,5519802 18,33984452 1212 Sweden (SE) 1186 17 79 46,45784148 16,38606983 1186 Switzerland (CH) 1037 18 96 49,74131274 17,02855436 1036 Taiwan (TW) 2016 19 97 44,3655754 16,9113815 2016 United States (US) 1216 18 89 45,30205761 16,35716834 1215 Uruguay (UY) 1108 18 93 46,06504065 18,55881899 1107 Venezuela (VE) 1199 17 86 36,64285714 14,94107333 1190 Sum 44170 15 98 45,87 17,28 43897


MARITAL R's marital status Missing Values: 9 Marital. Marital status of respondent (legal status) 1. Married. 2. Widowed. 3. Divorced. 4. Separated, but married1 5. Single, never married. 9. Na, refused. NOTES: (1)Category 4 not asked in Sweden


1 2 3 4 5 9

MARITAL (N) % % % % % % 1373 141 191 59 393

Australia (AU) 2183 63,70% 6,50% 8,90% 2,70% 18,20% 26M559 88 102 9 245

Austria (AT) 1006 55,70% 8,80% 10,20% 0,90% 24,40% 3M707 150 46 3 159

Bulgaria (BG) 1069 66,40% 14,10% 4,30% 0,30% 14,90% 4M918 72 57 29 127

Canada (CA) 1211 76,30% 6,00% 4,70% 2,40% 10,60% 8M795 113 14 145 432

Chile (CL) 1505 53,00% 7,50% 0,90% 9,70% 28,80% 6M650 137 155 17 245

Czech Republic (CZ) 1276 54,00% 11,40% 12,90% 1,40% 20,30% 72M748 75 103 8 353

Denmark (DK) 1322 58,10% 5,80% 8,00% 0,60% 27,40% 35M908 36 90 7 322

Finland (FI) 1379 66,60% 2,60% 6,60% 0,50% 23,60% 16M942 127 145 29 390

France (FR) 1669 57,70% 7,80% 8,90% 1,80% 23,90% 36M513 57 58 13 207

Germany-West (DE-W) 850 60,50% 6,70% 6,80% 1,50% 24,40% 2M258 34 29 3 113

Germany-East (DE-E) 437 59,00% 7,80% 6,60% 0,70% 25,90% 487 91 95 29 171

Great Britain (GB) 873 55,80% 10,40% 10,90% 3,30% 19,60% 570 163 105 16 165

Hungary (HU) 1021 55,90% 16,00% 10,30% 1,60% 16,20% 2M619 88 8 39 311

Ireland (IE) 1065 58,10% 8,30% 0,80% 3,70% 29,20% 681 68 66 8 241

Israel Jews (IL-J) 1066 64,00% 6,40% 6,20% 0,80% 22,70% 2M71 5 3 73

Israel Arabs (IL-A) 152 46,70% 3,30% 2,00% - 48,00% 785 78 28 1 202

Japan (JP) 1102 71,80% 7,10% 2,60% 0,10% 18,50% 8M531 98 119 19 233

Latvia (LV) 1000 53,10% 9,80% 11,90% 1,90% 23,30% 640 80 70 43 192

New Zealand (NZ) 1036 62,40% 7,80% 6,80% 4,20% 18,70% 11M801 39 124 24 481

Norway (NO) 1469 54,50% 2,70% 8,40% 1,60% 32,70% 801 142 46 12 276

Poland (PL) 1277 62,70% 11,10% 3,60% 0,90% 21,60% 972 195 98 17 315

Portugal (PT) 1602 60,90% 12,20% 6,10% 1,10% 19,70% 5M879 75 2 11 233

Philippines (PH) 1200 73,20% 6,20% 0,20% 0,90% 19,40% 1148 430 252 34 519

Russia (RU) 2383 48,20% 18,00% 10,60% 1,40% 21,80% 682 81 87 6 284

Slovak Republic (SK) 1152 59,80% 7,10% 7,60% 0,50% 24,90% 12M657 87 32 305

Slovenia (SI) 1093 60,80% 8,00% 3,00% - 28,20% 12M1006 204 75 62 1103

South Africa (ZA) 2483 41,10% 8,30% 3,10% 2,50% 45,00% 33M880 91 26 4 312

South Korea (KR) 1315 67,00% 6,90% 2,00% 0,30% 23,80% 2M741 81 16 27 345

Spain (ES) 1212 61,20% 6,70% 1,30% 2,20% 28,50% 2M520 55 72 524

Sweden (SE) 1186 44,40% 4,70% 6,10% - 44,70% 15M586 77 107 22 235

Switzerland (CH) 1037 57,10% 7,50% 10,40% 2,10% 22,90% 10M1258 150 51 9 548

Taiwan (TW) 2016 62,40% 7,40% 2,50% 0,40% 27,20% 644 80 183 42 267

United States (US) 1216 53,00% 6,60% 15,00% 3,50% 22,00% 490 139 90 45 344

Uruguay (UY) 1108 44,20% 12,50% 8,10% 4,10% 31,00% 340 36 30 64 728

Venezuela (VE) 1199 28,40% 3,00% 2,50% 5,30% 60,80% 1MSum 44170 25160 3663 2775 856 11393 323M


COHAB: R: Steady life-partner Missing Values: 0;9 Cohab:. (If 'not married and living together with spouse'). Do you have/live together with a partner? 1 1. Yes. 2. No. 0. Not available (Not asked) 9. Na, refused. NOTES: (1) Not asked in South Korea


0 1 2 9

COHAB (N) % % % % 158 629

Australia (AU) 2183 1373M 20,10% 79,90% 23M79 362

Austria (AT) 1006 559M 17,90% 82,10% 6M36 316

Bulgaria (BG) 1069 707M 10,20% 89,80% 10M36 223

Canada (CA) 1211 918M 13,90% 86,10% 34M113 585

Chile (CL) 1505 801M 16,20% 83,80% 6M114 455

Czech Republic (CZ) 1276 650M 20,00% 80,00% 57M218 326

Denmark (DK) 1322 747M 40,10% 59,90% 31M10 428

Finland (FI) 1379 901M 2,30% 97,70% 40M192 445

France (FR) 1669 942M 30,10% 69,90% 90M114 220

Germany-West (DE-W) 850 513M 34,10% 65,90% 3M53 126

Germany-East (DE-E) 437 258M 29,60% 70,40% 386

Great Britain (GB) 873 487M - 100,00% 58 390

Hungary (HU) 1021 570M 12,90% 87,10% 3M49 397

Ireland (IE) 1065 619M 11,00% 89,00% 40 285

Israel Jews (IL-J) 1066 685M 12,30% 87,70% 56M73

Israel Arabs (IL-A) 152 71M - 100,00% 8M6 275

Japan (JP) 1102 785M 2,10% 97,90% 36M68 401

Latvia (LV) 1000 531M 14,50% 85,50% 92 292

New Zealand (NZ) 1036 640M 24,00% 76,00% 12M253 405

Norway (NO) 1469 801M 38,40% 61,60% 10M200

Poland (PL) 1277 1077M - 100,00% 61 516

Portugal (PT) 1602 977M 10,60% 89,40% 48M7 314

Philippines (PH) 1200 879M 2,20% 97,80% 110 1125

Russia (RU) 2383 1148M 8,90% 91,10% 34 73

Slovak Republic (SK) 1152 1001M 31,80% 68,20% 44M76 350

Slovenia (SI) 1093 657M 17,80% 82,20% 10M210 1137

South Africa (ZA) 2483 1136M 15,60% 84,40%

South Korea (KR) 1315 1315M - - 51 409

Spain (ES) 1212 741M 11,10% 88,90% 11M269 382

Sweden (SE) 1186 520M 41,30% 58,70% 15M97 352

Switzerland (CH) 1037 586M 21,60% 78,40% 2M29 728

Taiwan (TW) 2016 1258M 3,80% 96,20% 1M72 481

United States (US) 1216 644M 13,00% 87,00% 19M147 471

Uruguay (UY) 1108 490M 23,80% 76,20% 315 543

Venezuela (VE) 1199 340M 36,70% 63,30% 1MSum 44170 26327M 3167 14100 576M


EDUCYRS: R's Education I: years in school Missing Values: 00;98;99 Educyrs. Education I - years (of full time) schooling including university but not vocational training. 00. Not available. nn. Number of years 95. Still at school,N:+uni. 96. Still at college,uni. 97. No form school. 98. Don't know 99. No answer, refused

EDUCYEARS (N) Minimum Maximum Mean Std Deviation Valid N Australia (AU) 2183 1 30 13,06084017 3,974820151 N=2071 Austria (AT) 1006 5 96 16,91146881 21,55991696 N=994 Bulgaria (BG) 1069 1 96 13,2164751 13,7477995 N=1044 Canada (CA) 1211 2 40 13,50714967 3,698591177 N=1049 Czech Republic (CZ) 1276 6 96 17,5467128 19,95593582 N=1156 Chile (CL) 1505 1 97 13,63502674 16,07600519 N=1496 Denmark (DK) 1322 5 95 22,25909879 25,90491536 N=1154 Finland (FI) 1379 1 97 26,28843106 31,72981461 N=1262 France (FR) 1669 3 96 17,59031657 17,66073669 N=1611 Germany-East (DE-E) 437 7 97 16,91513761 21,67396129 N=436 Germany-West (DE-W) 850 7 97 13,98822144 17,27380372 N=849 Great Britain (GB) 873 6 96 13,41743119 11,60357714 N=872 Hungary (HU) 1021 6 17 10,74361493 2,8842098 N=1018 Ireland (IE) 1065 2 97 18,34055118 20,71952434 N=1016 Israel Arabs (IL-A) 152 4 97 16,24827586 16,81497804 N=145 Israel Jews (IL-J) 1066 1 97 14,82088123 10,74499615 N=1044 Japan (JP) 1102 2 96 17,14312268 20,19016475 N=1076 Latvia (LV) 1000 1 96 22,1975435 26,77989509 N=977 New Zealand (NZ) 1036 3 97 14,00868726 7,950020315 N=1036 Norway (NO) 1469 9 24 13,4713056 2,980355908 N=1394 Philippines (PH) 1200 1 97 12,05166667 14,60810829 N=1200 Poland (PL) 1277 4 97 19,10806578 25,35214506 N=1277 Portugal (PT) 1602 1 97 16,65766332 26,25471645 N=1592 Russia (RU) 2383 1 97 19,67627119 24,9230156 N=2360 Slovak Republic (SK) 1152 3 97 20,54056518 23,14588857 N=1097 Slovenia (SI) 1093 2 97 19,84728611 25,69674846 N=1087 South Africa (ZA) 2483 , , , , N=0 South Korea (KR) 1315 1 97 25,98076923 31,16617804 N=1300 Spain (ES) 1212 1 97 17,55879828 24,73719639 N=1165 Sweden (SE) 1186 1 97 12,51702509 6,672121003 N=1116 Switzerland (CH) 1037 1 96 12,91312741 12,17648726 N=1036 Taiwan (TW) 2016 1 97 18,91364764 24,64779686 N=2015 United States (US) 1216 1 97 14,00986842 4,360492438 N=1216 Uruguay (UY) 1108 1 97 21,37815884 30,5163417 N=1108 Venezuela (VE) 1199 , , , , N=0


0 1 2 3 4 5 6 7 8 9 10 11

EDUCYRS (N) % % % % % % % % % % % % 6 6 9 22 16 17 46 77 120 268 179

Australia (AU) 2183 0,30% 0,30% 0,40% 1,10% 0,80% 0,80% 2,20% 3,70% 5,80% 12,90% 8,60%5 1 138 285 28 97

Austria (AT) 1006 - - - - 0,50% - 0,10% 13,90% 28,70% 2,80% 9,80%1 3 14 40 16 15 98 132 12 23 250

Bulgaria (BG) 1069 0,10% 0,30% 1,30% 3,80% 1,50% 1,40% 9,40% 12,60% 1,10% 2,20% 23,90%5 3 4 9 9 16 29 31 73 60

Canada (CA) 1211 - 0,50% 0,30% 0,40% 0,90% 0,90% 1,50% 2,80% 3,00% 7,00% 5,70%18 19 46 51 41 121 31 150 51 90 55

Chile (CL) 1505 1,20% 1,30% 3,10% 3,40% 2,70% 8,10% 2,10% 10,00% 3,40% 6,00% 3,70%1 2 39 58 25 158

Czech Republic (CZ) 1276 - - - - - 0,10% 0,20% 3,40% 5,00% 2,20% 13,70%12 8 64 24 43 82 67

Denmark (DK) 1322 - - - - 1,00% 0,70% 5,50% 2,10% 3,70% 7,10% 5,80%2 20 23 16 17 22 38 89 80 83 71

Finland (FI) 1379 0,20% 1,60% 1,80% 1,30% 1,30% 1,70% 3,00% 7,10% 6,30% 6,60% 5,60%1 1 4 14 26 135 42 106 144

France (FR) 1669 - - 0,10% 0,10% 0,20% 0,90% 1,60% 8,40% 2,60% 6,60% 8,90%27 375 246

Germany-West (DE-W) 850 - - - - - - 3,20% 44,20% - - 29,00%4 126 199

Germany-East (DE-E) 437 - - - - - - 0,90% 28,90% - - 45,60%3 3 6 83 213 220

Great Britain (GB) 873 - - - - - 0,30% 0,30% 0,70% 9,50% 24,40% 25,20%99 248 35 217

Hungary (HU) 1021 - - - - - 9,70% - 24,40% - 3,40% 21,30%2 3 8 16 53 72 87 70

Ireland (IE) 1065 - 0,20% - - 0,30% 0,80% 1,60% 5,20% 7,10% 8,60% 6,90%1 3 3 2 5 6 45 12 51 51

Israel Jews (IL-J) 1066 0,10% - 0,30% 0,30% 0,20% 0,50% 0,60% 4,30% 1,10% 4,90% 4,90%1 1 1 7 3 6 7

Israel Arabs (IL-A) 152 - - - 0,70% 0,70% - 0,70% 4,80% 2,10% 4,10% 4,80%1 2 23 3 49 161 33 19

Japan (JP) 1102 - 0,10% - - 0,20% 2,10% 0,30% 4,60% 15,00% 3,10% 1,80%1 2 2 4 35 28 29 81 149

Latvia (LV) 1000 0,10% - - 0,20% 0,20% 0,40% 3,60% 2,90% 3,00% 8,30% 15,30%9 69 14 292

New Zealand (NZ) 1036 - - 0,90% - - - - 6,70% 1,40% - 28,20%129 126 123

Norway (NO) 1469 - - - - - - - - 9,30% 9,00% 8,80%42 279 360

Poland (PL) 1277 - - - 3,30% - - - 21,80% - 28,20% -16 20 79 414 48 127 51 39 118 52 62

Portugal (PT) 1602 1,00% 1,30% 5,00% 26,00% 3,00% 8,00% 3,20% 2,40% 7,40% 3,30% 3,90%10 23 27 30 34 146 35 60 58 331 62

Philippines (PH) 1200 0,80% 1,90% 2,20% 2,50% 2,80% 12,20% 2,90% 5,00% 4,80% 27,60% 5,20%1 1 16 35 35 17 149 126 47 357 272

Russia (RU) 2383 % % 0,70% 1,50% 1,50% 0,70% 6,30% 5,30% 2,00% 15,10% 11,50%2 2 1 2 1 27 25 15 69

Slovak Republic (SK) 1152 - - 0,20% 0,20% 0,10% 0,20% 0,10% 2,50% 2,30% 1,40% 6,30%2 6 21 11 21 27 179 15 46 185

Slovenia (SI) 1093 - 0,20% 0,60% 1,90% 1,00% 1,90% 2,50% 16,50% 1,40% 4,20% 17,00%

South Africa (ZA) 2483 2483M - - - - - - - - - - -4 9 4 3 92 9 112 12 3

South Korea (KR) 1315 0,30% 0,70% 0,30% 0,20% - 7,10% 0,70% - 8,60% 0,90% 0,20%5 24 23 54 59 80 37 181 64 150 40

Spain (ES) 1212 0,40% 2,10% 2,00% 4,60% 5,10% 6,90% 3,20% 15,50% 5,50% 12,90% 3,40%2 9 3 4 9 18 72 56 85 56 156

Sweden (SE) 1186 0,20% 0,80% 0,30% 0,40% 0,80% 1,60% 6,50% 5,00% 7,60% 5,00% 14,00%1 1 3 5 3 4 88 397 86 59

Switzerland (CH) 1037 0,10% 0,10% - 0,30% 0,50% 0,30% 0,40% 8,50% 38,30% 8,30% 5,70%4 14 17 17 7 303 16 12 253 26 35

Taiwan (TW) 2016 0,20% 0,70% 0,80% 0,80% 0,30% 15,00% 0,80% 0,60% 12,60% 1,30% 1,70%1 2 1 2 8 6 15 25 27 65

United States (US) 1216 0,10% 0,20% 0,10% - 0,20% 0,70% 0,50% 1,20% 2,10% 2,20% 5,30%9 14 47 38 30 209 32 63 100 103 54

Uruguay (UY) 1108 0,80% 1,30% 4,20% 3,40% 2,70% 18,90% 2,90% 5,70% 9,00% 9,30% 4,90%



12 13 14 15 16 17 18 19 20 21 22 23

EDUCYRS (N) % % % % % % % % % % % % 248 135 174 178 185 124 92 52 54 20 14 13

Australia (AU) 2183 12,00% 6,50% 8,40% 8,60% 8,90% 6,00% 4,40% 2,50% 2,60% 1,00% 0,70% 0,60%140 62 41 37 25 22 21 10 8 1 1 1

Austria (AT) 1006 14,10% 6,20% 4,10% 3,70% 2,50% 2,20% 2,10% 1,00% 0,80% 0,10% 0,10% 0,10%150 31 44 38 40 40 33 16 5 1 7 4

Bulgaria (BG) 1069 14,40% 3,00% 4,20% 3,60% 3,80% 3,80% 3,20% 1,50% 0,50% 0,10% 0,70% 0,40%245 87 92 85 87 77 63 26 20 9 5 3

Canada (CA) 1211 23,40% 8,30% 8,80% 8,10% 8,30% 7,30% 6,00% 2,50% 1,90% 0,90% 0,50% 0,30%348 68 84 68 46 86 42 16 8 2 1

Chile (CL) 1505 23,30% 4,50% 5,60% 4,50% 3,10% 5,70% 2,80% 1,10% 0,50% - 0,10% 0,10%380 223 37 26 30 52 43 2 6 2 1 1

Czech Republic (CZ) 1276 32,90% 19,30% 3,20% 2,20% 2,60% 4,50% 3,70% 0,20% 0,50% 0,20% 0,10% 0,10%107 123 126 102 90 68 53 32 25

Denmark (DK) 1322 9,30% 10,70% 10,90% 8,80% 7,80% 5,90% 4,60% 2,80% 2,20% - - -112 82 77 89 55 68 42 24 19 2 7 2

Finland (FI) 1379 8,90% 6,50% 6,10% 7,10% 4,40% 5,40% 3,30% 1,90% 1,50% 0,20% 0,60% 0,20%220 85 168 90 94 117 82 88 36 20 19 8

France (FR) 1669 13,70% 5,30% 10,40% 5,60% 5,80% 7,30% 5,10% 5,50% 2,20% 1,20% 1,20% 0,50%55 44 67

Germany-West (DE-W) 850 - 6,50% - - 5,20% - 7,90% - - - - -14 20 43

Germany-East (DE-E) 437 - 3,20% - - 4,60% - 9,90% - - - - -92 73 19 16 56 29 13 13 11 4 1

Great Britain (GB) 873 10,60% 8,40% 2,20% 1,80% 6,40% 3,30% 1,50% 1,50% 1,30% 0,50% - 0,10%237 52 80 50

Hungary (HU) 1021 23,30% - 5,10% 7,90% - 4,90% - - - - - -105 132 137 64 57 53 49 19 7 4 5 4

Ireland (IE) 1065 10,30% 13,00% 13,50% 6,30% 5,60% 5,20% 4,80% 1,90% 0,70% 0,40% 0,50% 0,40%329 49 90 121 115 47 33 14 28 5 3 5

Israel Jews (IL-J) 1066 31,50% 4,70% 8,60% 11,60% 11,00% 4,50% 3,20% 1,30% 2,70% 0,50% 0,30% 0,50%54 4 14 17 18 4 1 1

Israel Arabs (IL-A) 152 37,20% 2,80% 9,70% 11,70% 12,40% 2,80% 0,70% 0,70% - - - -420 17 108 20 132 10 5 2 4

Japan (JP) 1102 39,00% 1,60% 10,00% 1,90% 12,30% 0,90% 0,50% - 0,20% - 0,40% -135 89 88 78 74 36 12 5 5 5 3

Latvia (LV) 1000 13,80% 9,10% 9,00% 8,00% 7,60% 3,70% 1,20% 0,50% 0,50% 0,50% - 0,30%272 206 166

New Zealand (NZ) 1036 - 26,30% - - 19,90% - 16,00% - - - - -222 170 129 133 123 83 75 45 19 11 4 1

Norway (NO) 1469 15,90% 12,20% 9,30% 9,50% 8,80% 6,00% 5,40% 3,20% 1,40% 0,80% 0,30% 0,10%279 51 141

Poland (PL) 1277 21,80% - 4,00% - - 11,00% - - - - - -150 41 31 30 43 66 27 13 7 2 2

Portugal (PT) 1602 9,40% 2,60% 1,90% 1,90% 2,70% 4,10% 1,70% 0,80% 0,40% 0,10% 0,10% -102 60 141 29 12 2 3 1 1

Philippines (PH) 1200 8,50% 5,00% 11,80% 2,40% 1,00% 0,20% 0,20% 0,10% 0,10% - - -272 202 104 289 118 42 27 12 7 1 1

Russia (RU) 2383 11,50% 8,60% 4,40% 12,20% 5,00% 1,80% 1,10% 0,50% 0,30% % % -269 217 92 48 42 88 58 24 10 10 1

Slovak Republic (SK) 1152 24,50% 19,80% 8,40% 4,40% 3,80% 8,00% 5,30% 2,20% 0,90% 0,90% 0,10% -214 48 52 33 45 42 14 7 1 1 1 2

Slovenia (SI) 1093 19,70% 4,40% 4,80% 3,00% 4,10% 3,90% 1,30% 0,60% 0,10% 0,10% 0,10% 0,20%

South Africa (ZA) 2483 - - - - - - - - - - - -423 6 127 1 242 1 40

South Korea (KR) 1315 32,50% 0,50% 9,80% 0,10% 18,60% 0,10% 3,10% - - - - -92 26 44 43 22 25 35 14 34 2 3 2

Spain (ES) 1212 7,90% 2,20% 3,80% 3,70% 1,90% 2,10% 3,00% 1,20% 2,90% 0,20% 0,30% 0,20%159 107 93 73 79 71 27 14 10 4 2 2

Sweden (SE) 1186 14,20% 9,60% 8,30% 6,50% 7,10% 6,40% 2,40% 1,30% 0,90% 0,40% 0,20% 0,20%93 54 40 35 34 29 33 18 12 9 4 3

Switzerland (CH) 1037 9,00% 5,20% 3,90% 3,40% 3,30% 2,80% 3,20% 1,70% 1,20% 0,90% 0,40% 0,30%487 54 244 57 226 7 45 4 2 1 5

Taiwan (TW) 2016 24,20% 2,70% 12,10% 2,80% 11,20% 0,30% 2,20% 0,20% 0,10% % - 0,20%298 114 179 78 229 50 53 18 43

United States (US) 1216 24,50% 9,40% 14,70% 6,40% 18,80% 4,10% 4,40% 1,50% 3,50% - - -95 16 19 37 27 22 16 3 8 3 2 1

Uruguay (UY) 1108 8,60% 1,40% 1,70% 3,30% 2,40% 2,00% 1,40% 0,30% 0,70% 0,30% 0,20% 0,10%

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 6477 2716 2697 1995 2616 1552 1313 491 388 117 88 62


24 25 26 27 28 29 30 31 32 33 34 39

EDUCYRS (N) % % % % % % % % % % % % 6 4 2 1 1 2

Australia (AU) 2183 0,30% 0,20% 0,10% % % - 0,10% - - - - -3

Austria (AT) 1006 0,30% - - - - - - - - - - -2 1 2

Bulgaria (BG) 1069 0,20% - - 0,10% 0,20% - - - - - - -3 4 2 1

Canada (CA) 1211 0,30% 0,40% 0,20% 0,10% - - - - - - - -3 1

Chile (CL) 1505 0,20% 0,10% - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - -

Denmark (DK) 1322 - - - - - - - - - - - -3 3

Finland (FI) 1379 0,20% 0,20% - - - - - - - - - -13 2 4 2 2 2 3 1 2 1 1 1

France (FR) 1669 0,80% 0,10% 0,20% 0,10% 0,10% 0,10% 0,20% 0,10% 0,10% 0,10% 0,10% 0,10%

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -1

Great Britain (GB) 873 - - 0,10% - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -2 1

Ireland (IE) 1065 0,20% - 0,10% - - - - - - - - -2 3 3 1

Israel Jews (IL-J) 1066 0,20% 0,30% 0,30% - - - - - - - 0,10% -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -1

Japan (JP) 1102 0,10% - - - - - - - - - - -1 1 1

Latvia (LV) 1000 - 0,10% 0,10% - - - 0,10% - - - - -

New Zealand (NZ) 1036 - - - - - - - - - - - -1

Norway (NO) 1469 0,10% - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -2 1

Portugal (PT) 1602 - 0,10% 0,10% - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - - - -1

Russia (RU) 2383 - % - - - - - - - - - -


Slovenia (SI) 1093 0,10% - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - -1 1 1 1

Spain (ES) 1212 0,10% 0,10% 0,10% - - - 0,10% - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -2 2 1

Switzerland (CH) 1037 0,20% 0,20% 0,10% - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -

United States (US) 1216 - - - - - - - - - - - -2 2

Uruguay (UY) 1108 0,20% 0,20% - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 45 26 17 5 5 2 7 1 2 1 2 1


40 41 42 44 47 53 63 65 82 94

EDUCYRS (N) % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - 1

Canada (CA) 1211 0,10% - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - -

Denmark (DK) 1322 - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - 1 1 1 1

France (FR) 1669 - 0,10% 0,10% 0,10% - 0,10% - - - -

Germany-West (DE-W) 850 - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - 1

Great Britain (GB) 873 - - - - - - - - - 0,10%

Hungary (HU) 1021 - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - 1

Israel Jews (IL-J) 1066 - - - - 0,10% - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - -

New Zealand (NZ) 1036 - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - -

Philippines (PH) 1200 - - - - - - - - - -

Russia (RU) 2383 - - - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - 1 1 1 2

Slovenia (SI) 1093 0,10% - - - - - 0,10% 0,10% 0,20% -

South Africa (ZA) 2483 - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - -

United States (US) 1216 - - - - - - - - - -

Uruguay (UY) 1108 - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - Sum 44170 2 1 1 1 1 1 1 1 2 1


95 96 97 98 99

EDUCYRS (N) % % % % %

Australia (AU) 2183 - - - 112M21 47

Austria (AT) 1006 2,10% 4,70% - 2M 10M12 14

Bulgaria (BG) 1069 1,10% 1,30% - 25M

Canada (CA) 1211 - - - 162M50

Chile (CL) 1505 - - 3,30% 9M28 42

Czech Republic (CZ) 1276 2,40% 3,60% - 5M 115M128

Denmark (DK) 1322 11,10% - - 3M 165M102 113 1

Finland (FI) 1379 8,10% 9,00% 0,10% 117M73

France (FR) 1669 - 4,50% - 58M5 29 1

Germany-West (DE-W) 850 0,60% 3,40% 0,10% 1M8 20 2

Germany-East (DE-E) 437 1,80% 4,60% 0,50% 1M15

Great Britain (GB) 873 - 1,70% - 1M

Hungary (HU) 1021 - - - 3M9 51 6

Ireland (IE) 1065 0,90% 5,00% 0,60% 8M 41M9 7

Israel Jews (IL-J) 1066 - 0,90% 0,70% 2M 20M1 4 1

Israel Arabs (IL-A) 152 0,70% 2,80% 0,70% 7M38 28

Japan (JP) 1102 3,50% 2,60% - 1M 25M24 89

Latvia (LV) 1000 2,50% 9,10% - 23M 8

New Zealand (NZ) 1036 - - 0,80%

Norway (NO) 1469 - - - 75M63 57 5

Poland (PL) 1277 4,90% 4,50% 0,40% 24 26 101

Portugal (PT) 1602 1,50% 1,60% 6,30% 3M 7M4 5 24

Philippines (PH) 1200 0,30% 0,40% 2,00% 175 39 14

Russia (RU) 2383 7,40% 1,70% 0,60% 23M 37 56 1

Slovak Republic (SK) 1152 3,40% 5,10% 0,10% 20M 35M38 63 7

Slovenia (SI) 1093 3,50% 5,80% 0,60% 3M 3M

South Africa (ZA) 2483 - - - 13 141 58

South Korea (KR) 1315 1,00% 10,80% 4,50% 15M9 71 22

Spain (ES) 1212 0,80% 6,10% 1,90% 42M 5M5

Sweden (SE) 1186 - - 0,40% 70M20

Switzerland (CH) 1037 - 1,90% - 1M 179

Taiwan (TW) 2016 - - 8,90% 1M 2

United States (US) 1216 - - 0,20% 1 137 18

Uruguay (UY) 1108 0,10% 12,40% 1,60%

Venezuela (VE) 1199 - - - Sum 44170 740 1149 512 137M 1082M


DEGREE: R's Education II: categories Missing Values: 8;9 Degree. Education II - highest education level / degree. 1. Lowest formal qualification. 2. Above lowest qualification. 3. Higher secondary completed. 4. Above higher secondary level. 5. University degree completed. 7. [CH]: Other education. 0. No formal qualification (GB,IRL: No secondary education). 8. Don't know. 9. No answer.


0 1 2 3 4 5 7 8 9

DEGREE (N) % % % % % % % % % 337 342 255 728 473

Australia (AU) 2183 15,80% 16,00% - 11,90% 34,10% 22,20% - 48M 202 506 190 106

Austria (AT) 1006 - 20,10% 50,40% 18,90% - 10,60% - 2M 20 99 265 487 180 13

Bulgaria (BG) 1069 1,90% 9,30% 24,90% 45,80% 16,90% 1,20% - 5M 7 77 136 299 357 315

Canada (CA) 1211 0,60% 6,50% 11,40% 25,10% 30,00% 26,40% - 20M 50 480 194 382 255 136

Chile (CL) 1505 3,30% 32,10% 13,00% 25,50% 17,00% 9,10% - 8M 6 158 484 443 31 134

Czech Republic (CZ) 1276 0,50% 12,60% 38,50% 35,30% 2,50% 10,70% - 20M 70 88 489 437 172

Denmark (DK) 1322 - 5,60% 7,00% 38,90% 34,80% 13,70% - 66M 68 273 297 135 371 207

Finland (FI) 1379 5,00% 20,20% 22,00% 10,00% 27,50% 15,30% - 28M 32 316 425 181 243 451

France (FR) 1669 1,90% 19,20% 25,80% 11,00% 14,70% 27,40% - 21M 32 378 257 69 44 68

Germany-West (DE-W) 850 3,80% 44,60% 30,30% 8,10% 5,20% 8,00% - 2M 12 126 207 26 20 43

Germany-East (DE-E) 437 2,80% 29,00% 47,70% 6,00% 4,60% 9,90% - 3M 228 115 163 122 115 129

Great Britain (GB) 873 26,10% 13,20% 18,70% 14,00% 13,20% 14,80% - 1M 99 248 252 237 132 50

Hungary (HU) 1021 9,70% 24,40% 24,80% 23,30% 13,00% 4,90% - 3M 268 177 301 156 163

Ireland (IE) 1065 25,20% 16,60% - 28,30% 14,60% 15,30% - 19 52 230 219 244 295

Israel Jews (IL-J) 1066 1,80% 4,90% 21,70% 20,70% 23,00% 27,90% - 7M 1 10 29 43 45 22

Israel Arabs (IL-A) 152 0,70% 6,70% 19,30% 28,70% 30,00% 14,70% - 2M 286 508 135 151

Japan (JP) 1102 - 26,50% - 47,00% 12,50% 14,00% - 22M 18 69 98 220 424 171

Latvia (LV) 1000 1,80% 6,90% 9,80% 22,00% 42,40% 17,10% - 250 265 228 101 97 62

New Zealand (NZ) 1036 24,90% 26,40% 22,70% 10,10% 9,70% 6,20% - 33M 145 239 481 161 421

Norway (NO) 1469 - 10,00% 16,50% 33,20% 11,10% 29,10% - 22M 5 321 404 371 25 151

Poland (PL) 1277 0,40% 25,10% 31,60% 29,10% 2,00% 11,80% - 101 693 478 85 99 140

Portugal (PT) 1602 6,30% 43,40% 29,90% 5,30% 6,20% 8,80% - 1M 5M 24 269 160 314 255 178

Philippines (PH) 1200 2,00% 22,40% 13,30% 26,20% 21,20% 14,80% - 16 103 376 731 662 495

Russia (RU) 2383 0,70% 4,30% 15,80% 30,70% 27,80% 20,80% - 9 89 347 365 91 196

Slovak Republic (SK) 1152 0,80% 8,10% 31,60% 33,30% 8,30% 17,90% - 55M 58 248 276 349 51 106

Slovenia (SI) 1093 5,30% 22,80% 25,40% 32,10% 4,70% 9,70% - 5M 200 570 871 578 216

South Africa (ZA) 2483 8,20% 23,40% 35,80% 23,70% - 8,90% - 27M 21M 58 112 149 423 266 292

South Korea (KR) 1315 4,50% 8,60% 11,50% 32,50% 20,50% 22,50% - 15M 18 705 204 91 93 99

Spain (ES) 1212 1,50% 58,30% 16,90% 7,50% 7,70% 8,20% - 2M 255 345 190 115 262

Sweden (SE) 1186 - 21,90% 29,60% 16,30% 9,90% 22,50% - 19M 7 110 506 91 186 129 6

Switzerland (CH) 1037 0,70% 10,60% 48,90% 8,80% 18,00% 12,50% 0,60% 1M 1M 179 363 343 479 390 262

Taiwan (TW) 2016 8,90% 18,00% 17,00% 23,80% 19,30% 13,00% - 9 29 97 321 391 369

United States (US) 1216 0,70% 2,40% 8,00% 26,40% 32,20% 30,30% - 18 348 346 186 102 108

Uruguay (UY) 1108 1,60% 31,40% 31,20% 16,80% 9,20% 9,70% - 48 604 242 46 133 113

Venezuela (VE) 1199 4,00% 50,90% 20,40% 3,90% 11,20% 9,50% - 13M Sum 44170 2197 8707 9242 9808 7034 6698 6 29M 449M


XX_DEGR: Country Specific Education Degree Missing Values: Education Country Specific - highest education level / degree. 0. Not available (Not asked) xx. Country specific code 97. None, No formal education, 98. Don’t know 99. No answer Australia

AU_DEGR n % 1. Did not complete High School to Year 10 337 15,4 2. Completed High School to Year 10 342 15,7 3. Completed High School to Year 12 255 11,7 4. Trade qualification or apprenticeship 263 12,0 5. Certificate or Diploma (TAFE or business college) 465 21,3 6. Bachelor Degree (including Honors) 279 12,8 7. Postgraduate Degree or Postgraduate Diploma 194 8,9 99. NA 48 2,2 (N) 2183 100% Austria (Note: Labels not available) AT_DEGR n % 1. Compulsory school without apprenticeship 202 20,1 2. Compulsory school with apprenticeship 358 35,6 3. Middle school vocational 148 14,7 4. Secondary general completed, Matura 88 8,7 5. Higher vocational, technical school 102 10,1 6. University 106 10,5 99. NA 2 0,2 (N) 1006 100% Bulgaria BG_DEGR n % 2. Primary 99 9,3 3. Lower secondary 265 24,8 4. Upper secondary 187 17,5 5. Secondary technical 300 28,1 6. College 50 4,7 7. Higher 130 12,2 8. University and higher 13 1,2 97. No formal schooling 20 1,9 99. NA 5 0,5 (N) 1069 100%


Canada CA_DEGR n % 2. Some grade school 25 2,1 3. Finshed grade school 52 4,3 4. Some high school 136 11,2 5. Finished high school 299 24,7 6. College/CEGEP/some university 357 29,5 7. Completed university 205 16,9 8. Graduate studies 110 9,1 97. None, still at school, university 7 0,6 99. NA,refused 20 1,7 (N) 1211 100% Chile CL_DEGR n % 2. Incomplete primary 331 22,0 3. Primary completed 149 9,9 4. Incomplete secondary 194 12,9 5. Secondary completed 382 25,4 6. University incompleted 87 5,8 7. University completed 136 9,0 8. Incompl non-university higher 43 2,9 9. Completed non-university higher 125 8,3 97. None 50 3,3 99. NA 8 0,5 (N) 1505 100%

Czech Republic CZ_DEGR n % 1. Incomplete primary 6 0,5 2. Primary completed 158 12,4 3. Lower vocational 364 28,5 4. General sec.,no diploma 120 9,4 5. Vocational, upper diploma 65 5,1 6. Technical secondary 262 20,5 7. Academic secondary 116 9,1 8. Higher education 31 2,4 9. Tertiary,bachelor 28 2,2 10. Tertiary,master degree 95 7,4 11. Post-graduate education 11 0,9 99. NA 20 1,6 (N) 1276 100%


Denmark DK_DEGR n % 1. 7 years primary school or shorter 197 14,9 2. 8 years primary school 64 4,8 3. 9 years primary school or similar 138 10,4 4. 10 years primary school or similar 308 23,3 5. Gymnasium, general 350 26,5 6. Gymnasium, technical & commercial 151 11,4 7. Other 85 6,4 99. No Answer 29 2,2 (N) 1322 100% Finland FI_DEGR n % 2. Primary school 175 12,7 3. Comprehensive (primary + lower secondary) school 98 7,1 4. Post-comprehensive vocational school or course 297 21,5 5. Post-comprehensive upper secondary school 135 9,8 6. Post-comprehensive vocational college 305 22,1 7. Polytechnic 66 4,8 8. University, lower academic degree (BA) 60 4,4 9. University, higher academic degree (MA) 147 10,7 97. None; still at school (comprehensive,upper second., vocat.) 68 4,9 99. Na 28 2,0 (N) 1379 100% France FR_DEGR n % 2. Primary incomplete 44 2,6 3. Primary completed 161 9,6 4. Gen. sec. lev 1 111 6,7 5. Vocat.sec. lev 1 300 18,0 6. Voc. sec. lev 2 68 4,1 7. Incpl gen.sec. lev 2 125 7,5 8. Gen.sec.lev 2 115 6,9 9. College 241 14,4 10. University 451 27,0 97. None 32 1,9 99. NA 21 1,3 (N) 1669 100%


Germany - West DE_DEGR n % 2. School left without qualification 27 3,23. Lower secondary (Hauptschule) 378 44,54. Middle school (Mittlere Reife) 216 25,45. Secondary technical (Fachhochschulreife) 41 4,86. Higher secondary (Abitur) 69 8,17. Special university qualification (Fachhochschulabschluss) 44 5,28. University 68 8,09. Other qualification 1 0,197. Still at school 5 0,699. Na, refused 1 0,1(N) 850 100%

Germany - East DE_DEGR n % 2. School left without qualification 4 0,93. Lower secondary (Hauptschule) 126 28,84. Middle school (Mittlere Reife) 199 45,55. Secondary technical (Fachhochschulreife) 8 1,86. Higher secondary (Abitur) 26 5,97. Special university qualification (Fachhochschulabschluss) 20 4,68. University 43 9,89. Other qualification 2 0,597. Still at school 8 1,899. Na, refused 1 0,9(N) 437 100%

Great Britain GB_DEGR n % 2. CSE or equilvalent 104 11,9 3. O-level or equivalent 163 18,7 4. A-level or equivalent 122 14,0 5. Higher below degree level 115 13,2 6. Degree, university o CNAA o diploma 129 14,8 7. Foreign or other 11 1,3 97. No sec. qualifications 228 26,1 99. DK, NA 1 0,1 (N) 873 100% Hungary HU_DEGR n % 2. Less than primary 99 9,7 3. 8 years elementary 248 24,3 4. Vocational 252 24,7 6. Sec. technical+matura 137 13,4 7. Gymnasium, matura 100 9,8 8. College 132 12,9 9. University 50 4,9 99. NA 3 0,3 (N) 1021 100%


Ireland IE_DEGR n % 2. Incomplete primary 31 2,9 3. Primary complete 167 15,7 4. Incomplete first cycle secondary 63 5,9 5. Complete first cycle secondary 177 16,6 6. Secondary complete 301 28,3 7. Incomplete third level 53 5,0 8. Cert or Diploma 103 9,7 9. University first degree 98 9,2 10. University degree Masters or higher 65 6,1 97. None 7 0,7 (N) 1065 100%

Israel - Jews IL_DEGR n % 1. primary 52 4,92. Incpl vocational 41 3,83. Vocational compl 75 7,04. Vocational with matriculation 74 6,95. Incpl academic 44 4,16. academic compl 60 5,67. academic with matriculation 142 13,38. Yeshiva 10 0,99. Yeshiva with matriculation 3 0,310. post secondary 182 17,111. Incpl university 62 5,812. university compl (BA or more) 295 27,797. No formal education 19 1,899. NA 7 0,7(N) 1066 100% Israel - Arabs IL_DEGR n % 1. primary 10 6,62. Incpl vocational 3 2,03. Vocational compl 8 5,34. Vocational with matriculation 13 8,65. Incpl academic 13 8,66. academic compl 4 2,67. academic with matriculation 30 19,78. Yeshiva 1 0,79. Yeshiva with matriculation 10. post secondary 17 6,611. Incpl university 28 18,412. university compl (BA or more) 22 14,597. No formal education 1 0,799. NA 2 1,3(N) 152 100%


Japan JP_DEGR n % 1. Secondary completed 248 22,5 2. High school completed 483 43,8 3. Junior college compl 135 12,3 4. Finished university 148 13,4 5. Still at High school 38 3,4 6. Still at Junior college 28 2,5 7. Others 1 0,1 99. NA 21 1,9 (N) 1102 100% Latvia LV_DEGR n % (N) 0 100% New Zealand NZ_DEGR n % 2. School qualifications only 265 25,6 3. Trade or professional cert 228 22,0 4. Diploma below Bachelors 101 9,7 5. Bachelors degree 97 9,4 6. Post-grad or higher 62 6,0 97. No formal qualification 250 24,1 99. NA 33 3,2 (N) 1036 100% Norway NO_DEGR n % 1. Primary 145 9,9 2. Sec. vocational, inc 91 6,2 3. Sec. academic, inc 148 10,1 4. Sec. voc., compl 225 15,3 5. Sec. acad., compl 256 17,4 6. Univ.,coll. 43 2,9 7. Univ., coll. 1-2 yrs 118 8,0 8. Univ., coll. 3-4 yrs 274 18,7 9. Univ., coll. >= 5 yrs 147 10,0 99. NA 22 1,5 (N) 1469 100%


Poland PL_DEGR n % 2. Incomplete elementary 42 3,3 3. Elementary 279 21,8 4. Basic vocational 353 27,6 5. Incomplete secondary 51 4,0 6. Secondary general 95 7,4 7. Secondary vocational 232 18,2 8. Post secondary 44 3,4 9. Incomplete higher 25 2,0 10. Completed higher 151 11,8 97. No formal schooling 5 0,4 (N) 1277 100% Portugal PT_DEGR n % 1. Basic -level 1 693 43,3 2. Basic-levels 2 and 3 283 17,7 3. Secondary incomplete 195 12,2 4. Complete secondary 85 5,3 5. University incomplete 99 6,2 6. Complete university 140 8,7 97. No formal qualification 101 6,3 98. DK 1 0,1 99. NA 5 0,3 (N) 1602 100% Philippines PH_DEGR n % 2. Incomplete primary 121 10,1 3. Primary completed 148 12,3 4. Incomplete secondary 160 13,3 5. Secondary completed 314 26,2 6. Some Vocational 26 2,2 7. Completed vocational 59 4,9 8. Some college 170 14,2 9. Completed college 169 14,1 10. Post college 9 0,8 97. None 24 2,0 (N) 1200 100% Russia RU_DEGR n % 2. Incompleted primary 2 0,1 3. Primary completed 103 4,3 4. Incompleted secondary 355 14,9 5. Secondary completed 1148 48,2 6. Semi-higher, incompleted university 57 2,4 7. University comleted 490 20,6 97. None, still at school, university 228 9,6 (N) 2383 100%


Slovakia SK_DEGR n % 1. Incomplete primary 89 7,7 2. Primary completed 347 30,1 3. General sec.,no diploma 365 31,7 4. General secondary 91 7,9 5. Tertiary,master degree 196 17,0 97. No formal education 9 0,8 99. No answer 55 4,8 (N) 1152 100% Slovenia SI_DEGR n % 1. Incomplete primary 58 5,3 2. Primary completed 221 20,2 3. Incomplete vocational 27 2,5 4. 2-3 yrs vocational 276 25,3 5. 4 yrs middle school 322 29,5 6. Incomplete university 27 2,5 7. Higher degree compl 51 4,7 8. University compl 106 9,7 99. NA 5 0,5 (N) 1093 100% South Africa ZA_DEGR n % 1. Grade 0 5 0,2 2. Sub A/Grade 1 29 1,2 3. Sub B/Grade 2 25 1,0 4. Grade 3/Standard 1 54 2,2 5. Grade 4/Standard 2 65 2,6 6. Grade 5/Standard 3 102 4,1 7. Grade 6/Standard 4 122 4,9 8. Grade 7/Standard 5 168 6,8 9. Grade 8/Standard 6/Form 1 230 9,3 10. Grade 9/Standard 7/Form 2 168 6,8 11. Grade 10/Standard 8/Form 3 273 11,0 12. Grade 11/Standard 9/Form 4 188 7,6 13. Grade 12/Standard 10/Form 5/Matric 534 21,5 14. NTC I 5 0,2 15. NTC II 7 0,3 16. NTC III 9 0,4 17. Diploma/certificate with 35 1,4 18. Diploma/certificate with Grade 12/Std 10 80 3,2 19. Degree 71 2,9 20. Postgraduate degree or diploma 65 2,6 21. Other, specify 26 1,0 97. No schooling 200 8,1 98. Do not know 1 99. NA, NAP, NAV 21 0,8 (N) 2483 100%


South Korea KR_DEGR n % 1. Elementary incompleted 22 1,7 2. Elementary completed 85 6,8 3. Middle school incompleted 16 1,3 4. Middle school completed 107 8,5 5. High school incompleted 33 2,6 6. High school completed 405 32,2 7. Junior college incompleted 42 3,3 8. Junior college completed 125 9,9 9. University incompleted 117 9,3 10. University completed 242 19,2 11. Graduate school incompleted 10 0,8 12. Graduate school completed 40 3,2 99. NA 15 1,2 (N) 1259 100% Spain ES_DEGR n % 1. Incpl primary 162 13,4 2. Primary compl 224 18,5 3. Incpl secondary 319 26,3 4. Vocational school 116 9,6 5. Secondary compl 88 7,3 6. COU - PREU 91 7,5 7. Incpl university 93 7,7 8. University compl 99 8,2 97. None 18 1,5 99. NA 2 0,2 (N) 1212 100% Sweden SE_DEGR n % 1. Primary or comprehensive 255 21,5 2. Vocational school (1972-92) 137 11,6 3. Vocational school (post 1992) 50 4,2 4. Vocational school (pre 1972) 86 7,3 5. Alternative secondary school 24 2,0 6. Lower secondary school 48 4,0 7. 3 o 4 yr gymnasium 130 11,0 8. Gymnasium (academic) 28 2,4 9. Higher sec. school 32 2,7 10. University studies without degree 115 9,7 11. University degree 262 22,1 99. NA 19 1,6 (N) 1186 100%


Switzerland CH_DEGR n % 1. Incomplete compulsory education 7 0,7 2. Compulsory education 110 10,6 3. Elementary vocational training (enterprise + school) 36 3,5 4. Secondary education (maturity, teacher training college) 72 6,9 5. Graduation diploma school (vocational maturity) 19 1,8 6. 1 year: trade school,adm educ,domestic science/ling course 33 3,2 7. Apprenticeship 361 34,8 8. 2 to 3 years: general training school, administrative edu 23 2,2 9. 2 to 3 years: full time vocational education 53 5,1 10. Higher vocational education, federal diploma 90 8,7 11. Tech or vocational college (2 yrs full time/3 yrs part time) 24 2,3 12. Advanced tech college (3 yrs full time/4 yrs part time) 72 6,9 13. University (3 years, short bachelor´s degree) 12 1,2 14. University, tech uni (4 yrs and more, bachelor´s degree) 71 6,8 15. University, tech higher spec uni (masters, post-grade) 46 4,4 97. Other education 6 0,6 98. Don´t know 1 0,1 99. NA 1 0,1 (N) 1037 100% Taiwan TW_DEGR n % 2. Self-study 21 1,0 3. Elementary school 363 18,0 4. Junior high school¡BVocational junior high school 281 13,9 5. High school(general subject)¡BHigh school(vocational subject 540 26,8 6. Five-year vocational school(after junior high) 72 3,6 7. two-year vocation school(after vocational high school) 208 10,3 8. Three-year vocational school(after high school of general su 24 1,2 9. Cadet school 4 0,2 10. Military/Police training course 5 0,2 11. Military/Police specialist course¡BMilitary/Police officers 24 1,2 12. College 252 12,5 13. Graduate school(M.A. degree) 54 2,7 14. Graduate school(Ph.D degree) 9 0,4 15. other 1 97. None 158 7,8 (N) 2016 100% United States US_DEGR n % 1. LT high school 135 11,1 2. High school 608 50,0 3. Junior college 104 8,6 4. Bachelor 249 20,5 5. Graduate 120 9,9 (N) 1216 100%


Uruguay UY_DEGR n % 2. Incomplete primary school 139 12,5 3. Completed primary school 209 18,9 4. Incomplete secondary 289 26,1 5. Completed secondary 112 10,1 6. Incomplete technical education 57 5,1 7. Completed technical education 74 6,7 8. Incomplete university 88 7,9 9. Completed university 69 6,2 10. Incomplete non university high education 14 1,3 11. Completed non university high education 39 3,5 97. None 18 1,6 (N) 1108 100% Venezuela VE_DEGR n % 1. Before primary school 4 0,3 2. Basic school (1-9) / Primary (1-6) 608 50,7 3. Special education 1 0,1 4. High school (1-2) 209 17,4 5. Technical school (1-3) 34 2,8 6. Secondary school (1-5) 46 3,8 7. University Technician 92 7,7 8. University 157 13,1 97. None 45 3,8 98. Dont know 2 0,2 99. Na 1 0,1 (N) 1199 100%


WRKST: R's current employment status Missing Values: 97;98;99 Wrkst. Current employment status, current economic position, main source of living. . 01. Employed-full time. 02. Employed-part time. 03. Employe less than part-time. 04. Helping family member. 05. Unemployed. 06. Student,school,vocational training 07. Retired. 08. Housewife,home duties. 09. Permanently disabled. 10. Other,not in labour force. 97. Refused. 98. Don't know. 99- No answer.


1 2 3 4 5 6 7 8 9 10 97 99

WRKST (N) % % % % % % % % % % % % 917 289 83 28 38 56 416 212 84 38

Australia (AU) 2183 42,40% 13,40% 3,80% 1,30% 1,80% 2,60% 19,30% 9,80% 3,90% 1,80% - 22M447 81 31 3 43 42 255 78 3 21

Austria (AT) 1006 44,50% 8,10% 3,10% 0,30% 4,30% 4,20% 25,40% 7,80% 0,30% 2,10% - 2M405 14 15 139 12 401 5 12 61

Bulgaria (BG) 1069 38,10% 1,30% 1,40% - 13,10% 1,10% 37,70% 0,50% 1,10% 5,70% - 5M544 99 27 11 20 18 353 71 21 17 30

Canada (CA) 1211 44,90% 8,20% 2,20% 0,90% 1,70% 1,50% 29,10% 5,90% 1,70% 1,40% 2,50% 555 100 53 8 60 91 172 453 7 2

Chile (CL) 1505 37,00% 6,70% 3,50% 0,50% 4,00% 6,10% 11,50% 30,20% 0,50% 0,10% - 4M679 26 6 2 65 74 277 51 57 11


Denmark (DK) 1322 53,80% 5,40% 2,30% 0,10% 3,60% 8,90% 19,50% 1,40% 3,90% 1,10% - 31M648 77 10 10 88 168 282 25 30

Finland (FI) 1379 48,40% 5,80% 0,70% 0,70% 6,60% 12,60% 21,10% 1,90% - 2,20% - 41M750 96 14 4 85 69 540 70 9 31

France (FR) 1669 45,00% 5,80% 0,80% 0,20% 5,10% 4,10% 32,40% 4,20% 0,50% 1,90% - 1M359 77 45 34 196 103 35

Germany-West (DE-W) 850 42,30% 9,10% - - 5,30% 4,00% 23,10% 12,10% - 4,10% - 1M186 20 59 28 127 6 11

Germany-East (DE-E) 437 42,60% 4,60% - - 13,50% 6,40% 29,10% 1,40% - 2,50% - 334 107 12 34 23 204 104 49 6

Great Britain (GB) 873 38,30% 12,30% 1,40% - 3,90% 2,60% 23,40% 11,90% 5,60% 0,70% - 415 11 13 53 27 434 39 26

Hungary (HU) 1021 40,80% 1,10% 1,30% - 5,20% 2,70% 42,60% 3,80% - 2,60% - 3M414 129 9 7 34 62 173 216 13 8

Ireland (IE) 1065 38,90% 12,10% 0,80% 0,70% 3,20% 5,80% 16,20% 20,30% 1,20% 0,80% - 412 128 35 2 65 59 196 81 24 51 3

Israel Jews (IL-J) 1066 39,00% 12,10% 3,30% 0,20% 6,20% 5,60% 18,60% 7,70% 2,30% 4,80% 0,30% 10M53 24 3 1 8 31 3 24 1 4

Israel Arabs (IL-A) 152 34,90% 15,80% 2,00% 0,70% 5,30% 20,40% 2,00% 15,80% 0,70% 2,60% - 437 80 14 75 21 73 145 206 21

Japan (JP) 1102 40,80% 7,50% 1,30% 7,00% 2,00% 6,80% 13,50% 19,20% 2,00% - - 30M561 53 18 8 22 70 175 54 24 15

Latvia (LV) 1000 56,10% 5,30% 1,80% 0,80% 2,20% 7,00% 17,50% 5,40% 2,40% 1,50% - 623 57 43 8 38 18 210 16 2

New Zealand (NZ) 1036 61,40% 5,60% 4,20% 0,80% 3,70% 1,80% 20,70% 1,60% 0,20% - - 21M820 79 8 2 36 120 198 45 101 14

Norway (NO) 1469 57,60% 5,60% 0,60% 0,10% 2,50% 8,40% 13,90% 3,20% 7,10% 1,00% - 46M480 44 34 170 81 410 55 3

Poland (PL) 1277 37,60% 3,40% 2,70% - 13,30% 6,30% 32,10% 4,30% - 0,20% - 823 77 12 7 88 57 399 114 11 13

Portugal (PT) 1602 51,40% 4,80% 0,70% 0,40% 5,50% 3,60% 24,90% 7,10% 0,70% 0,80% - 1M427 185 25 5 21 60 44 346 82

Philippines (PH) 1200 35,70% 15,50% 2,10% 0,40% 1,80% 5,00% 3,70% 29,00% - 6,90% - 5M1067 137 31 4 140 162 636 113 81 12

Russia (RU) 2383 44,80% 5,70% 1,30% 0,20% 5,90% 6,80% 26,70% 4,70% 3,40% 0,50% - 648 38 6 3 106 93 202 15 9 7


Slovenia (SI) 1093 48,00% 1,90% 0,20% 0,30% 6,10% 9,80% 29,80% 3,30% 0,30% 0,30% - 14M771 205 858 220 278 109 24 18

South Africa (ZA) 2483 31,10% 8,30% - - 34,60% 8,90% 11,20% 4,40% 1,00% 0,70% - 623 82 35 44 127 123 235 4 38

South Korea (KR) 1315 47,50% 6,30% - 2,70% 3,40% 9,70% 9,40% 17,90% 0,30% 2,90% - 4M486 56 11 4 75 93 211 270 5 1

Spain (ES) 1212 40,10% 4,60% 0,90% 0,30% 6,20% 7,70% 17,40% 22,30% 0,40% 0,10% - 572 141 12 1 38 130 178 6 64 36

Sweden (SE) 1186 48,60% 12,00% 1,00% 0,10% 3,20% 11,00% 15,10% 0,50% 5,40% 3,10% - 8M460 207 12 5 23 19 209 75 6 14

Switzerland (CH) 1037 44,70% 20,10% 1,20% 0,50% 2,20% 1,80% 20,30% 7,30% 0,60% 1,40% - 7M1014 70 66 80 116 115 187 270 63 30

Taiwan (TW) 2016 50,40% 3,50% 3,30% 4,00% 5,80% 5,70% 9,30% 13,40% 3,10% 1,50% - 5M663 154 43 44 171 115 25

United States (US) 1216 54,60% 12,70% - - 3,50% 3,60% 14,10% 9,50% - 2,10% - 1M467 101 57 3 79 46 221 125 7 2

Uruguay (UY) 1108 42,10% 9,10% 5,10% 0,30% 7,10% 4,20% 19,90% 11,30% 0,60% 0,20% - 357 97 54 1 223 91 37 314 9 14

Venezuela (VE) 1199 29,80% 8,10% 4,50% 0,10% 18,60% 7,60% 3,10% 26,20% 0,80% 1,20% - 2MSum 44170 19630 3231 746 321 3089 2634 8637 4075 764 693 33 317M


SPWRKST: R's Spouse-Partner Current employment status Missing Values: 00;97;98;99 Spwrkst. Spouse / partner: current employment status, current economic position, main source of living. (1) 01. Employed-full time. 02. Employed-part time. 03. Employe less than part-time. 04. Helping family member. 05. Unemployed. 06. Student,school,vocational training 07. Retired. 08. Housewife,home duties. 09. Permanently disabled. 10. Other,not in labour force. 0. NAV;Not married;no spouse/partner, Not asked 97. Refused. 98. Don't know. 99. No asnwer. Notes: (1) Not asked in Norway and Venezuela


0 1 2 3 4 5 6 7 8 9 10 97 98 99

SPWRKST (N) % % % % % % % % % % % % % % 681 201 30 8 21 14 270 204 46 15

Australia (AU) 2183 688M 45,70% 13,50% 2,00% 0,50% 1,40% 0,90% 18,10% 13,70% 3,10% 1,00% - 5M338 59 20 1 8 11 103 83 2 10

Austria (AT) 1006 368M 53,20% 9,30% 3,10% 0,20% 1,30% 1,70% 16,20% 13,10% 0,30% 1,60% - 3M290 22 19 129 2 245 14 4 7

Bulgaria (BG) 1069 317M 39,60% 3,00% 2,60% - 17,60% 0,30% 33,50% 1,90% 0,50% 1,00% - 2M 18M460 97 30 2 14 3 250 78 8 15 28

Canada (CA) 1211 226M 46,70% 9,80% 3,00% 0,20% 1,40% 0,30% 25,40% 7,90% 0,80% 1,50% 2,80% 465 32 34 4 30 5 78 253 1 2

Chile (CL) 1505 592M 51,40% 3,50% 3,80% 0,40% 3,30% 0,60% 8,60% 28,00% 0,10% 0,20% - 9M482 10 2 2 28 5 155 41 14 5 Czech

Republic (CZ) 1276 512M 64,80% 1,30% 0,30% 0,30% 3,80% 0,70% 20,80% 5,50% 1,90% 0,70% - 20M574 39 15 6 24 36 165 22 35 6

Denmark (DK) 1322 355M 62,30% 4,20% 1,60% 0,70% 2,60% 3,90% 17,90% 2,40% 3,80% 0,70% - 45M495 56 10 9 35 36 200 10 21

Finland (FI) 1379 478M 56,80% 6,40% 1,10% 1,00% 4,00% 4,10% 22,90% 1,10% - 2,40% - 29M520 63 18 1 41 19 298 124 10 19

France (FR) 1669 444M 46,70% 5,70% 1,60% 0,10% 3,70% 1,70% 26,80% 11,10% 0,90% 1,70% - 112M266 56 21 18 138 109 19 Germany-

West (DE-W) 850 223M 42,40% 8,90% - - 3,30% 2,90% 22,00% 17,40% - 3,00% - 153 21 27 9 85 5 10 Germany-

East (DE-E) 437 126M 49,40% 6,80% - - 8,70% 2,90% 27,40% 1,60% - 3,20% - 1M166 44 87 9 6 104 48 18 4 Great Britain

(GB) 873 386M 34,20% 9,10% 17,90% - 1,90% 1,20% 21,40% 9,90% 3,70% 0,80% - 1M269 11 2 1 30 1 185 41 34 9

Hungary (HU) 1021 393M 46,10% 1,90% 0,30% 0,20% 5,10% 0,20% 31,70% 7,00% 5,80% 1,50% - 45M356 62 4 3 13 3 91 120 13 3

Ireland (IE) 1065 397M 53,30% 9,30% 0,60% 0,40% 1,90% 0,40% 13,60% 18,00% 1,90% 0,40% - 287 67 7 1 25 13 81 66 9 17 2 Israel Jews

(IL-J) 1066 298M 49,90% 11,70% 1,20% 0,20% 4,30% 2,30% 14,10% 11,50% 1,60% 3,00% 0,30% 193M29 7 1 1 1 31 1Israel Arabs

(IL-A) 152 73M 40,80% 9,90% - - 1,40% 1,40% 1,40% 43,70% 1,40% - - 8M320 54 13 51 4 101 212 15 2

Japan (JP) 1102 317M 41,50% 7,00% 1,70% 6,60% 0,50% - 13,10% 27,50% 1,90% 0,30% - 13M373 29 14 2 29 6 85 49 8 3

Latvia (LV) 1000 400M 62,40% 4,80% 2,30% 0,30% 4,80% 1,00% 14,20% 8,20% 1,30% 0,50% - 2M 341 95 49 4 8 7 134 71 2New Zealand

(NZ) 1036 292M 48,00% 13,40% 6,90% 0,60% 1,10% 1,00% 18,80% 10,00% 0,30% - - 33M

Norway (NO) 1469 1469M - - - - - - - - - - - 366 25 23 92 2 247 45 1

Poland (PL) 1277 476M 45,70% 3,10% 2,90% - 11,50% 0,20% 30,80% 5,60% - 0,10% - 594 14 1 46 198 163 13 15

Portugal (PT) 1602 545M 56,90% 1,30% - 0,10% 4,40% - 19,00% 15,60% 1,20% 1,40% - 13M446 124 6 2 15 5 24 235 8 15 Philippines

(PH) 1200 314M 50,70% 14,10% 0,70% 0,20% 1,70% 0,60% 2,70% 26,70% 0,90% 1,70% - 6M734 48 10 1 58 13 264 72 51 19

Russia (RU) 2383 1113M 57,80% 3,80% 0,80% 0,10% 4,60% 1,00% 20,80% 5,70% 4,00% 1,50% - 475 17 5 4 57 8 115 11 1 12 Slovak

Republic (SK) 1152 385M 67,40% 2,40% 0,70% 0,60% 8,10% 1,10% 16,30% 1,60% 0,10% 1,70% - 62M368 11 2 1 50 13 247 27 5 5

Slovenia (SI) 1093 353M 50,50% 1,50% 0,30% 0,10% 6,90% 1,80% 33,90% 3,70% 0,70% 0,70% - 11M622 111 313 25 128 72 7 264 South Africa

(ZA) 2483 941M 40,30% 7,20% - - 20,30% 1,60% 8,30% 4,70% 0,50% 17,10% - 503 59 47 19 2 53 179 3 14 South Korea

(KR) 1315 435M 57,20% 6,70% - 5,30% 2,20% 0,20% 6,00% 20,40% 0,30% 1,60% - 1M350 15 5 3 11 8 141 237 3 7

Spain (ES) 1212 420M 44,90% 1,90% 0,60% 0,40% 1,40% 1,00% 18,10% 30,40% 0,40% 0,90% - 12M426 107 3 4 20 43 119 5 41 13

Sweden (SE) 1186 405M 54,50% 13,70% 0,40% 0,50% 2,60% 5,50% 15,20% 0,60% 5,20% 1,70% - 287 154 9 2 4 7 107 86 8 5 Switzerland

(CH) 1037 354M 42,90% 23,00% 1,30% 0,30% 0,60% 1,00% 16,00% 12,90% 1,20% 0,70% - 14M680 48 39 90 74 1 134 314 41 6 7

Taiwan (TW) 2016 581M 47,40% 3,30% 2,70% 6,30% 5,20% 0,10% 9,30% 21,90% 2,90% 0,40% 0,50% 1M 382 60 16 8 86 73 11 United States

(US) 1216 572M 60,10% 9,40% - - 2,50% 1,30% 13,50% 11,50% - 1,70% - 8M323 46 41 4 32 101 83 4 1 2

Uruguay (UY) 1108 471M 50,70% 7,20% 6,40% 0,60% 5,00% 15,90% 13,00% 0,60% 0,20% - 0,30% Venezuela (VE) 1199 1199M - - - - - - - - - - - Sum 44170 16918M 13421 1864 497 254 1304 431 4715 3104 402 554 39 5M 662M


WRKHRS: R's hours worked weekly Missing Values: 00;97;98;99 Wrkhrs. Working hours - number of hours (usually) worked weekly. . xx. Number of hours 00. Not applicable, not available. 97. Refused. 98. DK,cant say,varies too much. 99. No answer. Notes: (1) Not asked in South Africa

WRKHRS Count Minimum Maximum Mean Std Deviation Valid N

Australia (AU) 2183 1 96 38,7 14,87 N=1284 Austria (AT) 1006 4 95 41,2 13,57 N=862 Bulgaria (BG) 1069 7 96 42,4 12,96 N=448 Canada (CA) 1211 2 96 37,9 12,4 N=701 Chile (CL) 1505 4 96 46,7 14,56 N=699 Czech Republic (CZ) 1276 8 96 45,5 10,81 N=491 Denmark (DK) 1322 4 96 38,1 9,63 N=1167 Finland (FI) 1379 1 84 37,8 10,59 N=763 France (FR) 1669 6 90 38,8 10,65 N=816 Germany-East (DE-E) 437 9 96 42,3 10,49 N=204 Germany-West (DE-W) 850 7 96 39,7 12,51 N=430 Great Britain (GB) 873 10 84 37,7 13,02 N=436 Hungary (HU) 1021 10 95 45 10,43 N=380 Ireland (IE) 1065 2 95 39 13,23 N=855 Israel Arabs (IL-A) 152 14 96 37,7 12,64 N=81 Israel Jews (IL-J) 1066 4 96 39,6 16,9 N=560 Japan (JP) 1102 2 96 43,3 15,06 N=599 Latvia (LV) 1000 10 86 42,4 10,27 N=544 New Zealand (NZ) 1036 2 96 39,2 14,58 N=635 Norway (NO) 1469 1 90 37,8 11,94 N=1340 Philippines (PH) 1200 2 96 45,2 21,06 N=641 Poland (PL) 1277 4 96 45,7 13,1 N=1084 Portugal (PT) 1602 5 95 41,8 11,03 N=1285 Russia (RU) 2383 2 96 40,5 11,86 N=1235 Slovak Republic (SK) 1152 15 80 42 7,76 N=644 Slovenia (SI) 1093 1 96 41,9 12,23 N=571 South Africa (ZA) 2483 , , N=0 South Korea (KR) 1315 5 96 46 12,25 N=697 Spain (ES) 1212 2 72 39 10,23 N=528 Sweden (SE) 1186 5 80 38 9,55 N=811 Switzerland (CH) 1037 1 90 39,3 14,24 N=968 Taiwan (TW) 2016 5 96 49,1 16,53 N=1543 United States (US) 1216 1 89 42,2 15,32 N=798 Uruguay (UY) 1108 3 96 41,8 18,13 N=612 Venezuela (VE) 1199 3 96 42,9 17,68 N=503


ISCO88: R: Occupation ILO,ISCO 1988 4-digit Missing Values: 0;9997;9998;9999 ISCO88. Respondent occupation, using ISCO 1998 4-digit notation 1 xxxx ISCO code 110. Armed Forces 1000. Legislators, Senior Officials and Managers 2000. Professionals 3000. Technicians and Associate Professionals 4000. Clerks 5000. Service Workers and Shop Market Sales workers 6000. Skilled Agricultural and Fishery workers 7000. Craft and Related Trades workers 8000. Plant and Machine Operators and Assemblers 9000. Elementary Occupations 9996. Not otherwise specified 0. NAP, NAV, Not asked; Never had a job 9997. Refused. 9998. Dont know. 9999. NA. Notes: (1) Venezuela used a different notation. France used 3-digit ISCO. South-Africa used 1-digit ISCO. Table shows 1 digit ISCO distribution for simplicity


0 110 1000 2000 3000 4000 5000 6000 7000 8000 9000 9996 9997 9998 9999ISCO88B (N) % % % % % % % % % % % % % % %

8 264 383 261 312 243 33 199 103 148 31Australia (AU) 2183 198M 0,40% 13,30% 19,30% 13,10% 15,70% 12,20% 1,70% 10,00% 5,20% 7,50% 1,60%

1 65 68 146 131 155 43 134 61 79 Austria (AT) 1006 105M 0,10% 7,40% 7,70% 16,50% 14,80% 17,60% 4,90% 15,20% 6,90% 8,90% - 18M

26 118 114 47 94 28 211 109 158 Bulgaria (BG) 1069 61M - 2,90% 13,00% 12,60% 5,20% 10,40% 3,10% 23,30% 12,00% 17,50% - 5M 44M 54M

90 207 182 86 85 16 49 33 38 Canada (CA) 1211 389M - 11,50% 26,30% 23,20% 10,90% 10,80% 2,00% 6,20% 4,20% 4,80% - 36M

24 117 87 71 127 23 86 60 164 Chile (CL) 1505 741M - 3,20% 15,40% 11,50% 9,40% 16,70% 3,00% 11,30% 7,90% 21,60% - 1M 4M

72 113 189 139 154 23 214 132 78 Czech Republic (CZ) 1276 81M - 6,50% 10,10% 17,00% 12,50% 13,80% 2,10% 19,20% 11,80% 7,00% - 10M 71M

12 134 188 258 140 177 29 127 68 81 Denmark (DK) 1322 108M 1,00% 11,00% 15,50% 21,30% 11,50% 14,60% 2,40% 10,50% 5,60% 6,70% -

6 120 231 178 99 152 68 107 58 84 102Finland (FI) 1379 174M 0,50% 10,00% 19,20% 14,80% 8,20% 12,60% 5,60% 8,90% 4,80% 7,00% 8,50%

14 105 164 224 137 82 22 52 45 20 France (FR) 1669 804M 1,60% 12,10% 19,00% 25,90% 15,80% 9,50% 2,50% 6,00% 5,20% 2,30% -

3 54 85 139 92 106 25 136 50 57 27Germany-West (DE-W) 850 65M 0,40% 7,00% 11,00% 18,00% 11,90% 13,70% 3,20% 17,60% 6,50% 7,40% 3,50% 11M

1 24 40 77 48 43 13 92 31 28 8Germany-East (DE-E) 437 30M 0,20% 5,90% 9,90% 19,00% 11,90% 10,60% 3,20% 22,70% 7,70% 6,90% 2,00% 2M

2 74 115 96 153 147 10 74 78 106 Great Britain (GB) 873 12M 0,20% 8,70% 13,50% 11,20% 17,90% 17,20% 1,20% 8,70% 9,10% 12,40% - 6M

57 82 98 60 93 40 257 68 106 Hungary (HU) 1021 51M - 6,60% 9,50% 11,40% 7,00% 10,80% 4,60% 29,80% 7,90% 12,30% - 109M

3 86 151 47 139 173 57 86 104 65 Ireland (IE) 1065 143M 0,30% 9,40% 16,60% 5,20% 15,30% 19,00% 6,30% 9,40% 11,40% 7,10% - 11M

9 66 246 170 104 105 7 70 36 61 Israel Jews (IL-J) 1066 185M 1,00% 7,60% 28,10% 19,50% 11,90% 12,00% 0,80% 8,00% 4,10% 7,00% - 7M

2 22 7 17 11 1 19 6 9 Israel Arabs (IL-A) 152 58M - 2,10% 23,40% 7,40% 18,10% 11,70% 1,10% 20,20% 6,40% 9,60% -

3 57 25 65 114 113 42 89 34 46 31Japan (JP) 1102 470M 0,50% 9,20% 4,00% 10,50% 18,40% 18,30% 6,80% 14,40% 5,50% 7,40% 5,00% 6M 7M

1 35 100 135 42 119 28 106 53 76 Latvia (LV) 1000 270M 0,10% 5,00% 14,40% 19,40% 6,00% 17,10% 4,00% 15,30% 7,60% 10,90% - 32M 2M 1M

1 109 158 99 79 45 62 60 41 47 New Zealand (NZ) 1036 292M 0,10% 15,50% 22,50% 14,10% 11,30% 6,40% 8,80% 8,60% 5,80% 6,70% - 43M

4 161 181 285 137 244 45 155 80 70 Norway (NO) 1469 34M 0,30% 11,80% 13,30% 20,90% 10,10% 17,90% 3,30% 11,40% 5,90% 5,10% - 73M

11 64 108 96 80 135 101 220 99 172 Poland (PL) 1277 188M 1,00% 5,90% 9,90% 8,80% 7,40% 12,40% 9,30% 20,30% 9,10% 15,80% - 3M

12 91 121 121 177 187 47 294 138 220 Portugal (PT) 1602 185M 0,90% 6,50% 8,60% 8,60% 12,60% 13,30% 3,30% 20,90% 9,80% 15,60% - 3M 6M

5 129 50 62 66 103 141 112 47 236 Philippines (PH) 1200 231M 0,50% 13,60% 5,30% 6,50% 6,90% 10,80% 14,80% 11,80% 4,90% 24,80% - 15M 3M

14 85 462 265 137 258 41 380 239 279 Russia (RU) 2383 190M 0,60% 3,90% 21,40% 12,30% 6,30% 11,90% 1,90% 17,60% 11,10% 12,90% - 33M

80 109 253 62 67 6 80 45 59 Slovak Republic (SK) 1152 91M - 10,50% 14,30% 33,20% 8,10% 8,80% 0,80% 10,50% 5,90% 7,80% - 126M 16M 158M

41 125 134 97 125 29 181 93 75 Slovenia (SI) 1093 151M - 4,60% 13,90% 14,90% 10,80% 13,90% 3,20% 20,10% 10,30% 8,30% - 25M 17M

39 82 91 82 89 6 92 42 424 117South Africa (ZA) 2483 1416M - 3,70% 7,70% 8,60% 7,70% 8,40% 0,60% 8,60% 3,90% 39,80% 11,00% 3M

5 94 100 121 155 215 94 101 75 78 South Korea (KR) 1315 253M 0,50% 9,10% 9,60% 11,70% 14,90% 20,70% 9,10% 9,70% 7,20% 7,50% - 24M

8 67 59 80 106 122 36 156 92 163 Spain (ES) 1212 321M 0,90% 7,50% 6,60% 9,00% 11,90% 13,70% 4,00% 17,50% 10,30% 18,30% - 2M

2 108 169 194 90 171 12 81 97 47 Sweden (SE) 1186 215M 0,20% 11,10% 17,40% 20,00% 9,30% 17,60% 1,20% 8,30% 10,00% 4,80% -

2 91 183 245 114 130 36 107 28 57 Switzerland (CH) 1037 33M 0,20% 9,20% 18,40% 24,70% 11,50% 13,10% 3,60% 10,80% 2,80% 5,70% - 2M 9M

45 41 136 277 208 208 129 171 233 139 Taiwan (TW) 2016 416M 2,80% 2,60% 8,60% 17,50% 13,10% 13,10% 8,10% 10,80% 14,70% 8,80% - 13M

6 195 243 134 162 142 9 99 93 78 United States (US) 1216 55M 0,50% 16,80% 20,90% 11,50% 14,00% 12,20% 0,80% 8,50% 8,00% 6,70% -

10 64 94 63 115 184 21 162 78 237 2Uruguay (UY) 1108 78M 1,00% 6,20% 9,10% 6,10% 11,20% 17,90% 2,00% 15,70% 7,60% 23,00% 0,20%

18 78 95 316 4Venezuela (VE) 1199 688M - 3,50% 15,30% 18,60% - - - - - 61,80% 0,80% Sum 44170 8782M 188 2832 4913 5088 3798 4604 1323 4559 2649 4101 322 271M 114M 626M


SPISCO88: SP: Occupation ILO,ISCO 1988 4-digit Missing Values: 0;9997;9998;9999 SPISCO88. Spouse/partner occupation, using ISCO 1998 4-digit notation 1,2 xxxx ISCO code 110. Armed Forces 1000. Legislators, Senior Officials and Managers 2000. Professionals 3000. Technicians and Associate Professionals 4000. Clerks 5000. Service Workers and Shop Market Sales workers 6000. Skilled Agricultural and Fishery workers 7000. Craft and Related Trades workers 8000. Plant and Machine Operators and Assemblers 9000. Elementary Occupations 9996. Not otherwise specified 0. NAP, NAV, Not asked; Never had a job; No spouse 9997. Refused. 9998. Dont know. 9999. NA. Notes: (1) Venezuela used a different notation. France used 3-digit ISCO. South-Africa used 1-digit ISCO. (2) Not asked in Japan Table shows 1 digit ISCO distribution for simplicity


0 110 1000 2000 3000 4000 5000 6000 7000 8000 9000 9996 9997 9998 9999SPISCO8B (N) % % % % % % % % % % % % % % %

4 194 248 118 210 161 33 161 90 111 42Australia (AU) 2183 811M 0,30% 14,10% 18,10% 8,60% 15,30% 11,70% 2,40% 11,70% 6,60% 8,10% 3,10%

1 56 52 91 76 79 29 101 27 34 Austria (AT) 1006 415M 0,20% 10,30% 9,50% 16,70% 13,90% 14,50% 5,30% 18,50% 4,90% 6,20% - 28M 17M

19 86 81 42 66 28 144 72 103 9Bulgaria (BG) 1069 332M - 2,90% 13,20% 12,50% 6,50% 10,20% 4,30% 22,20% 11,10% 15,80% 1,40% 30M 57M

2 76 210 139 75 112 15 44 36 35 Canada (CA) 1211 410M 0,30% 10,20% 28,20% 18,70% 10,10% 15,10% 2,00% 5,90% 4,80% 4,70% - 57M

18 52 64 45 68 34 96 66 101 Chile (CL) 1505 931M - 3,30% 9,60% 11,80% 8,30% 12,50% 6,20% 17,60% 12,10% 18,60% - 30M

1 37 64 95 91 96 9 151 103 30 Czech Republic (CZ) 1276 11M 0,10% 5,50% 9,50% 14,00% 13,40% 14,20% 1,30% 22,30% 15,20% 4,40% - 519M 69M

111 141 174 89 115 25 97 61 59 Denmark (DK) 1322 450M - 12,70% 16,20% 20,00% 10,20% 13,20% 2,90% 11,10% 7,00% 6,80% -

8 100 161 101 43 95 56 87 58 36 74Finland (FI) 1379 478M 1,00% 12,20% 19,70% 12,30% 5,30% 11,60% 6,80% 10,60% 7,10% 4,40% 9,00% 82M

16 83 147 205 160 92 38 78 63 241 France (FR) 1669 546M 1,40% 7,40% 13,10% 18,30% 14,20% 8,20% 3,40% 6,90% 5,60% 21,50% -

27 39 51 37 32 5 58 25 21 18Germany-West (DE-W) 850 525M - 8,60% 12,50% 16,30% 11,80% 10,20% 1,60% 18,50% 8,00% 6,70% 5,80% 12M

1 13 14 43 17 17 4 40 15 5 4Germany-East (DE-E) 437 262M 0,60% 7,50% 8,10% 24,90% 9,80% 9,80% 2,30% 23,10% 8,70% 2,90% 2,30% 2M

1 15 8 5 8 6 1 17 10 9 Great Britain (GB) 873 791M 1,20% 18,80% 10,00% 6,20% 10,00% 7,50% 1,20% 21,20% 12,50% 11,20% - 2M

34 53 39 40 56 23 140 50 72 Hungary (HU) 1021 393M - 6,70% 10,50% 7,70% 7,90% 11,00% 4,50% 27,60% 9,90% 14,20% - 121M

1 50 83 52 76 73 60 81 78 40 Ireland (IE) 1065 456M 0,20% 8,40% 14,00% 8,80% 12,80% 12,30% 10,10% 13,60% 13,10% 6,70% - 15M

10 54 151 92 84 67 4 47 33 26 Israel Jews (IL-J) 1066 488M 1,80% 9,50% 26,60% 16,20% 14,80% 11,80% 0,70% 8,30% 5,80% 4,60% - 10M

3 12 3 2 2 2 6 5 4 Israel Arabs (IL-A) 152 113M - 7,70% 30,80% 7,70% 5,10% 5,10% 5,10% 15,40% 12,80% 10,30% -

Japan (JP) 1102 1102M - - - - - - - - - - - 24 61 89 24 65 17 83 57 46

Latvia (LV) 1000 502M - 5,20% 13,10% 19,10% 5,20% 13,90% 3,60% 17,80% 12,20% 9,90% - 25M 7M 77 124 64 51 35 46 53 29 31

New Zealand (NZ) 1036 465M - 15,10% 24,30% 12,50% 10,00% 6,90% 9,00% 10,40% 5,70% 6,10% - 61M4 141 126 208 71 163 35 87 47 47 10

Norway (NO) 1469 405M 0,40% 15,00% 13,40% 22,20% 7,60% 17,40% 3,70% 9,30% 5,00% 5,00% 1,10% 125M6 47 56 117 54 77 94 139 82 82

Poland (PL) 1277 520M 0,80% 6,20% 7,40% 15,50% 7,20% 10,20% 12,50% 18,40% 10,90% 10,90% - 3M8 53 75 73 87 90 28 211 115 124

Portugal (PT) 1602 735M 0,90% 6,10% 8,70% 8,40% 10,10% 10,40% 3,20% 24,40% 13,30% 14,40% - 1M 2M8 80 32 41 39 55 84 96 55 196

Philippines (PH) 1200 495M 1,20% 11,70% 4,70% 6,00% 5,70% 8,00% 12,20% 14,00% 8,00% 28,60% - 11M 5M 3M20 35 210 145 35 121 19 244 199 112

Russia (RU) 2383 1163M 1,80% 3,10% 18,40% 12,70% 3,10% 10,60% 1,70% 21,40% 17,50% 9,80% - 80M 57 62 119 25 49 4 97 55 20

Slovak Republic (SK) 1152 377M - 11,70% 12,70% 24,40% 5,10% 10,00% 0,80% 19,90% 11,30% 4,10% - 99M 27M 161M21 88 111 78 80 18 119 74 45

Slovenia (SI) 1093 384M - 3,30% 13,90% 17,50% 12,30% 12,60% 2,80% 18,80% 11,70% 7,10% - 16M 5M 54M37 30 65 59 82 6 102 68 221 74

South Africa (ZA) 2483 1730M - 5,00% 4,00% 8,70% 7,90% 11,00% 0,80% 13,70% 9,10% 29,70% 9,90% 9M 9 104 65 87 98 125 59 86 73 45

South Korea (KR) 1315 539M 1,20% 13,80% 8,70% 11,60% 13,00% 16,60% 7,90% 11,50% 9,70% 6,00% - 25M 3 45 34 36 59 65 29 121 87 66

Spain (ES) 1212 649M 0,60% 8,30% 6,20% 6,60% 10,80% 11,90% 5,30% 22,20% 16,00% 12,10% - 18M5 87 124 127 72 117 8 59 67 31

Sweden (SE) 1186 489M 0,70% 12,50% 17,80% 18,20% 10,30% 16,80% 1,10% 8,50% 9,60% 4,40% - 1 27 103 107 43 55 16 52 16 30

Switzerland (CH) 1037 585M 0,20% 6,00% 22,90% 23,80% 9,60% 12,20% 3,60% 11,60% 3,60% 6,70% - 2M24 33 77 149 111 156 147 133 131 116

Taiwan (TW) 2016 905M 2,20% 3,10% 7,10% 13,80% 10,30% 14,50% 13,60% 12,30% 12,20% 10,80% - 22M 9M 3M2 88 150 69 65 74 4 60 43 36

United States (US) 1216 622M 0,30% 14,90% 25,40% 11,70% 11,00% 12,50% 0,70% 10,20% 7,30% 6,10% - 3M8 29 64 34 67 89 13 108 38 138 3

Uruguay (UY) 1108 517M 1,40% 4,90% 10,80% 5,80% 11,30% 15,10% 2,20% 18,30% 6,40% 23,40% 0,50% 16 46 69 272 7

Venezuela (VE) 1199 776M - 3,90% 11,20% 16,80% - - - - - 66,30% 1,70% 13MSum 44170 20372M 143 1891 3048 3063 2133 2635 993 3198 2028 2585 241 236M 709M 895M


WRKTYPE: R: Working for private,public sector, selfemployed Missing Values: 0;9 Wrktype. Private vs. public - Working for private versus public sector 1 1. Work for government. 2. Public owned firm,national industry 3. Private. 4. Self employed. 5. BG: Cooperative firm. 6. GB: Other. 0. Not applicable, not available; Not asked 9. No answer, don't know. Notes: (1) Not asked in South Africa


0 1 2 3 4 5 6 9

WRKTYPE (N) % % % % % % % % 403 139 1066 380

Australia (AU) 2183 195M 20,30% 7,00% 53,60% 19,10% - - 212 592 91

Austria (AT) 1006 105M 23,70% - 66,10% 10,20% - - 6M166 8 276 9 16

Bulgaria (BG) 1069 579M 34,90% 1,70% 58,10% 1,90% 3,40% - 15M191 147 355 99

Canada (CA) 1211 389M 24,10% 18,60% 44,80% 12,50% - - 30M89 20 450 194

Chile (CL) 1505 725M 11,80% 2,70% 59,80% 25,80% - - 27M50 392 531 128Czech Republic

(CZ) 1276 175M 4,50% 35,60% 48,20% 11,60% - - 434 68 585 111

Denmark (DK) 1322 56M 36,20% 5,70% 48,80% 9,30% - - 68M397 165 467 156

Finland (FI) 1379 154M 33,50% 13,90% 39,40% 13,20% - - 40M287 58 432 78

France (FR) 1669 804M 33,60% 6,80% 50,50% 9,10% - - 10M108 569 85Germany-West

(DE-W) 850 65M - 14,20% 74,70% 11,20% - - 23M49 301 48Germany-East

(DE-E) 437 30M - 12,30% 75,60% 12,10% - - 9M226 23 497 87 22

Great Britain (GB) 873 12M 26,40% 2,70% 58,10% 10,20% - 2,60% 6M64 456 347 78

Hungary (HU) 1021 51M 6,80% 48,30% 36,70% 8,30% - - 25M197 55 532 122

Ireland (IE) 1065 143M 21,70% 6,10% 58,70% 13,50% - - 16M106 140 269 85

Israel Jews (IL-J) 1066 427M 17,70% 23,30% 44,80% 14,20% - - 39M24 10 34 17Israel Arabs (IL-

A) 152 66M 28,20% 11,80% 40,00% 20,00% - - 1M43 406 179

Japan (JP) 1102 470M 6,80% - 64,60% 28,50% - - 4M181 139 348 56

Latvia (LV) 1000 276M 25,00% 19,20% 48,10% 7,70% - - 147 87 365 186New Zealand

(NZ) 1036 251M 18,70% 11,10% 46,50% 23,70% - - 460 61 711 149

Norway (NO) 1469 34M 33,30% 4,40% 51,50% 10,80% - - 54M488 75 273 218

Poland (PL) 1277 188M 46,30% 7,10% 25,90% 20,70% - - 35M198 78 924 202

Portugal (PT) 1602 185M 14,10% 5,60% 65,90% 14,40% - - 15M98 7 463 389

Philippines (PH) 1200 235M 10,20% 0,70% 48,40% 40,60% - - 8M1330 41 733 18

Russia (RU) 2383 190M 62,70% 1,90% 34,50% 0,80% - - 71M178 284 352 79Slovak Republic

(SK) 1152 114M 19,90% 31,80% 39,40% 8,80% - - 145M57 516 287 52

Slovenia (SI) 1093 129M 6,20% 56,60% 31,50% 5,70% - - 52M

South Africa (ZA) 2483 2483M - - - - - - 46 26 617 231

South Korea (KR) 1315 378M 5,00% 2,80% 67,10% 25,10% - - 17M99 49 602 133

Spain (ES) 1212 319M 11,20% 5,50% 68,20% 15,10% - - 10M412 94 482 101

Sweden (SE) 1186 97M 37,80% 8,60% 44,30% 9,30% - - 299 539 144

Switzerland (CH) 1037 43M 30,40% - 54,90% 14,70% - - 12M207 66 983 337

Taiwan (TW) 2016 423M 13,00% 4,10% 61,70% 21,20% - - 222 811 128United States

(US) 1216 54M 19,10% - 69,90% 11,00% - - 1M119 52 486 373

Uruguay (UY) 1108 78M 11,60% 5,00% 47,20% 36,20% - - 97 36 165 204

Venezuela (VE) 1199 689M 19,30% 7,20% 32,90% 40,60% - - 8MSum 44170 10612M 7527 3449 16850 4947 16 22 747M


SPWRKTYP: Rs Spouse-Partner working for private,public sector, selfemployed Missing Values: 0;9 Spwrktyp. Spouse-Partner: Private vs. public - Working for private versus public sector1. 1. Work for government. 2. Public owned firm,national industry 3. Private. 4. Self employed. 5. BG: Cooperative firm. 6. GB: Other. 0. NAV;Not married;no spouse/partner, Not asked 9. No answer, don't know. Notes: (1) Not asked in Bulgaria, Canada, Israel, Norway, South Africa and United States


0 1 2 3 4 6 9

SPWRKTYP (N) % % % % % % % 253 67 745 312

Australia (AU) 2183 652M 18,40% 4,90% 54,10% 22,70% - 154M95 372 91

Austria (AT) 1006 368M 17,00% - 66,70% 16,30% - 80M

Bulgaria (BG) 1069 1069M - - - - -

Canada (CA) 1211 1211M - - - - - 50 16 356 135

Chile (CL) 1505 931M 9,00% 2,90% 63,90% 24,20% - 17M40 244 380 63

Czech Republic (CZ) 1276 455M 5,50% 33,60% 52,30% 8,70% - 94M288 47 435 117

Denmark (DK) 1322 393M 32,50% 5,30% 49,00% 13,20% - 42M254 100 420

Finland (FI) 1379 585M 32,80% 12,90% 54,30% - - 20M308 486 113

France (FR) 1669 505M 34,00% - 53,60% 12,50% - 257M20 262 30

Germany-West (DE-W) 850 528M - 6,40% 84,00% 9,60% - 10M5 143 23

Germany-East (DE-E) 437 263M - 2,90% 83,60% 13,50% - 3M11 53 16 1

Great Britain (GB) 873 791M 13,60% - 65,40% 19,80% 1,20% 1M43 278 220 25

Hungary (HU) 1021 393M 7,60% 49,10% 38,90% 4,40% - 62M108 40 328 124

Ireland (IE) 1065 446M 18,00% 6,70% 54,70% 20,70% - 19M

Israel Jews (IL-J) 1066 1066M - - - - -

Israel Arabs (IL-A) 152 152M - - - - - 37 268 141

Japan (JP) 1102 656M 8,30% - 60,10% 31,60% - 102 112 232 41

Latvia (LV) 1000 512M 20,90% 23,00% 47,60% 8,40% - 1M139 88 382 177

New Zealand (NZ) 1036 250M 17,70% 11,20% 48,60% 22,50% -

Norway (NO) 1469 1469M - - - - - 342 47 168 157

Poland (PL) 1277 520M 47,90% 6,60% 23,50% 22,00% - 43M134 56 544 119

Portugal (PT) 1602 736M 15,70% 6,60% 63,80% 14,00% - 13M82 12 361 228

Philippines (PH) 1200 499M 12,00% 1,80% 52,90% 33,40% - 18M834 44 248 46

Russia (RU) 2383 1163M 71,20% 3,80% 21,20% 3,90% - 48M139 114 270 90

Slovak Republic (SK) 1152 372M 22,70% 18,60% 44,00% 14,70% - 167M41 375 211 50

Slovenia (SI) 1093 391M 6,10% 55,40% 31,20% 7,40% - 25M

South Africa (ZA) 2483 2483M - - - - - 40 29 423 218

South Korea (KR) 1315 584M 5,60% 4,10% 59,60% 30,70% - 21M36 15 386 107

Spain (ES) 1212 650M 6,60% 2,80% 71,00% 19,70% - 18M282 89 311 78

Sweden (SE) 1186 426M 37,10% 11,70% 40,90% 10,30% - 133 244 71

Switzerland (CH) 1037 585M 29,70% - 54,50% 15,80% - 4M139 56 654 246

Taiwan (TW) 2016 921M 12,70% 5,10% 59,70% 22,50% -

United States (US) 1216 1216M - - - - - 83 26 301 178

Uruguay (UY) 1108 517M 14,10% 4,40% 51,20% 30,30% - 3M58 29 201

Venezuela (VE) 1199 887M 20,10% 10,10% - 69,80% - 24MSum 44170 24645M 4071 1909 9203 3197 1 1144M


NEMPLOY: Self-employment II - how many employees Missing Values: 0;9997;9998;9999 Nemploy. (If self employed) Do you have any employees, If so, how many? (exact number of employees). 1 . xxxx number of employees. 0. NAP, NAV, Not asked 9995. No employee. 9997. Refused. 9998. Dont know. 9999. NA. Notes: (1) Not asked in Austria, South Africa NEMPLOY Count Minimum Maximum Mean Std Deviation Valid N Australia (AU) 2183 1 1000 19,7 96,58 N=135 Austria (AT) 1006 , , , , N=0 Bulgaria (BG) 1069 1 20 3,7 3,87 N=31 Canada (CA) 1211 1 425 19,5 60,46 N=83 Czech Republic (CZ) 1276 1 30 5,6 6,59 N=24 Chile (CL) 1505 1 300 15,0 41,11 N=109 Denmark (DK) 1322 1 120 9,3 16,89 N=73 Finland (FI) 1379 1 50 5,6 8,42 N=58 France (FR) 1669 1 60 5,6 10,04 N=34 Germany-East (DE-E) 437 9 50 16,2 15,51 N=23 Germany-West (DE-W) 850 9 49 12,3 9,78 N=47 Great Britain (GB) 873 1 100 11,4 22,32 N=28 Hungary (HU) 1021 1 160 19,8 33,61 N=86 Ireland (IE) 1065 1 30 2,8 4,67 N=109 Israel Arabs (IL-A) 152 1 4 2,3 1,04 N=8 Israel Jews (IL-J) 1066 1 30 4,8 5,67 N=38 Japan (JP) 1102 1 449 11,9 53,26 N=136 Latvia (LV) 1000 1 40 5,9 9,46 N=50 New Zealand (NZ) 1036 1 170 6,4 18,45 N=87 Norway (NO) 1469 1 250 13,0 34,18 N=59 Philippines (PH) 1200 1 20 4,3 5,01 N=32 Poland (PL) 1277 1 85 5,5 11,74 N=106 Portugal (PT) 1602 1 400 13,0 52,54 N=61 Russia (RU) 2383 2 300 38,0 98,31 N=9 Slovak Republic (SK) 1152 1 120 11,5 23,89 N=35 Slovenia (SI) 1093 1 988 41,7 161,41 N=61 South Africa (ZA) 2483 , , , , N=0 South Korea (KR) 1315 1 20 5,2 5,02 N=58 Spain (ES) 1212 1 50 6,3 9,41 N=35 Sweden (SE) 1186 1 22 3,4 4,95 N=31 Switzerland (CH) 1037 1 60 3,8 7,76 N=126 Taiwan (TW) 2016 1 300 10,4 34,10 N=165 United States (US) 1216 1 30 7,7 8,10 N=55 Uruguay (UY) 1108 1 50 7,0 11,07 N=47 Venezuela (VE) 1199 1 658 14,2 49,43 N=219


WRKSUP: R Supervises Missing Values: 0;7;8;9 Wrksup. R Supervises – Do you supervise others at work?1. . 1. Yes. 2. No. 0. Not applicable, unemployed, not in labour force; Not asked 7. Refused. 8. Don't know. 9. No answer. Notes: (1) Not asked in South Africa


0 1 2 7 8 9

WRKSUP (N) % % % % % % 882 978

Australia (AU) 2183 47,40% 52,60% - 323M315 586

Austria (AT) 1006 105M 35,00% 65,00% - 99 409

Bulgaria (BG) 1069 545M 19,50% 80,50% - 16M384 420 7

Canada (CA) 1211 389M 47,30% 51,80% 0,90% 11M218 550 2

Chile (CL) 1505 725M 28,30% 71,40% 0,30% 1M 9M163 510

Czech Republic (CZ) 1276 593M 24,20% 75,80% - 1M 9M466 752

Denmark (DK) 1322 56M 38,30% 61,70% - 12M 36M228 954

Finland (FI) 1379 19,30% 80,70% - 33M 164M402 443

France (FR) 1669 808M 47,60% 52,40% - 16M184 247 Germany-West (DE-

W) 850 414M 42,70% 57,30% - 5M78 128 Germany-East (DE-

E) 437 231M 37,90% 62,10% - 319 537

Great Britain (GB) 873 12M 37,30% 62,70% - 5M86 884

Hungary (HU) 1021 51M 8,90% 91,10% - 284 602

Ireland (IE) 1065 143M 32,10% 67,90% - 36M 246 344 1

Israel Jews (IL-J) 1066 436M 41,60% 58,20% 0,20% 1M 38M11 76

Israel Arabs (IL-A) 152 64M 12,60% 87,40% - 1M177 432

Japan (JP) 1102 470M 29,10% 70,90% - 23M153 525 5

Latvia (LV) 1000 316M 22,40% 76,90% 0,70% 1M 312 625

New Zealand (NZ) 1036 99M 33,30% 66,70% - 478 877

Norway (NO) 1469 34M 35,30% 64,70% - 80M239 845

Poland (PL) 1277 188M 22,00% 78,00% - 5M275 1128

Portugal (PT) 1602 185M 19,60% 80,40% - 14M140 833 4

Philippines (PH) 1200 204M 14,30% 85,30% 0,40% 19M452 1741

Russia (RU) 2383 190M 20,60% 79,40% - 308 620 13

Slovak Republic (SK) 1152 114M 32,70% 65,90% 1,40% 4M 93M292 608

Slovenia (SI) 1093 133M 32,40% 67,60% - 4M 56M

South Africa (ZA) 2483 2483M - - - 214 489

South Korea (KR) 1315 606M 30,40% 69,60% - 6M93 448

Spain (ES) 1212 655M 17,20% 82,80% - 16M371 708

Sweden (SE) 1186 107M 34,40% 65,60% - 454 537

Switzerland (CH) 1037 43M 45,80% 54,20% - 2M 1M399 1193 8

Taiwan (TW) 2016 416M 24,90% 74,60% 0,50% 197 334

United States (US) 1216 677M 37,10% 62,90% - 8M251 778

Uruguay (UY) 1108 78M 24,40% 75,60% - 1M163 338

Venezuela (VE) 1199 689M 32,50% 67,50% - 9MSum 44170 12259M 9333 21479 40 95M 964M


UNION: R's syndical affiliation Missing Values: 0;8;9 Union. Is respondent member of a trade union? 1. 1. Currently member. 2. Once member, not now. 3. Never member. 0. NAP;Unemployed, etc; Not asked 8. Don't know. 9. No answer, refused. Notes: (1) Not asked in South Africa


0 1 2 3 8 9

UNION (N) % % % % % % 382 769 855

Australia (AU) 2183 19,00% 38,30% 42,60% 177M366 143 478

Austria (AT) 1006 37,10% 14,50% 48,40% 19M 93 472 486

Bulgaria (BG) 1069 8,80% 44,90% 46,20% 18M244 89 452

Canada (CA) 1211 389M 31,10% 11,30% 57,60% 2M 35M66 628

Chile (CL) 1505 725M 9,50% - 90,50% 86M116 495 556Czech Republic

(CZ) 1276 9,90% 42,40% 47,60% 109M913 237 153

Denmark (DK) 1322 70,10% 18,20% 11,70% 19M753 275 287

Finland (FI) 1379 57,30% 20,90% 21,80% 64M191 662

France (FR) 1669 808M 22,40% 77,60% - 8M115 128 605Germany-West (DE-

W) 850 13,60% 15,10% 71,30% 2M56 212 167Germany-East (DE-

E) 437 12,90% 48,70% 38,40% 2M175 270 409

Great Britain (GB) 873 12M 20,50% 31,60% 47,90% 1M 6M82 870

Hungary (HU) 1021 51M 8,60% 91,40% - 1M 17M200 245 377

Ireland (IE) 1065 143M 24,30% 29,80% 45,90% 100M 172 74 378

Israel Jews (IL-J) 1066 426M 27,60% 11,90% 60,60% 1M 15M34 6 47

Israel Arabs (IL-A) 152 63M 39,10% 6,90% 54,00% 2M102 83 241

Japan (JP) 1102 658M 23,90% 19,50% 56,60% 18M106 456 357

Latvia (LV) 1000 67M 11,50% 49,60% 38,80% 12M 2M124 410 444

New Zealand (NZ) 1036 58M 12,70% 41,90% 45,40% 710 332 409

Norway (NO) 1469 48,90% 22,90% 28,20% 18M90 400 787

Poland (PL) 1277 7,00% 31,30% 61,60% 190 261 952

Portugal (PT) 1602 185M 13,50% 18,60% 67,90% 14M11 42 1032

Philippines (PH) 1200 1,00% 3,90% 95,10% 115M468 1270 645

Russia (RU) 2383 19,60% 53,30% 27,10% 196 500 352Slovak Republic

(SK) 1152 18,70% 47,70% 33,60% 104M305 707

Slovenia (SI) 1093 30,10% - 69,90% 81M

South Africa (ZA) 2483 2483M - - - 79 387

South Korea (KR) 1315 842M 17,00% - 83,00% 7M105 99 915

Spain (ES) 1212 9,40% 8,80% 81,80% 93M738 225 202

Sweden (SE) 1186 63,30% 19,30% 17,30% 21M173 110 750

Switzerland (CH) 1037 16,70% 10,60% 72,60% 3M 1M386 167 1038

Taiwan (TW) 2016 24,30% 10,50% 65,20% 1M 424M72 740

United States (US) 1216 402M 8,90% - 91,10% 2M 204 820

Uruguay (UY) 1108 78M 19,90% - 80,10% 6M52 110 1034

Venezuela (VE) 1199 4,30% 9,20% 86,50% 2M 1MSum 44170 7390M 8069 9412 17690 144M 1465M


HOMPOP: R's size of household Missing Values: 00;98;99 Hompop. Number of people in household1. xx. xx persons2. 00. Not applicable, not available; Not asked 98. Don't know. 99. No answer, refused. Notes: (1) Not asked in South Africa (2) Venezuela: 2= 2 or more persons Spain: 9= 9 or more persons Sweden: 8= 8 or more persons


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

HOMPOP (N) % % % % % % % % % % % % % % % 287 847 347 403 196 50 11 1 2 2 1

Australia (AU) 2183 13,40% 39,40% 16,10% 18,80% 9,10% 2,30% 0,50% % 0,10% 0,10% - % - -243 288 197 194 58 17 7 1 1

Austria (AT) 1006 24,20% 28,60% 19,60% 19,30% 5,80% 1,70% 0,70% 0,10% 0,10% - - - - -113 299 252 236 77 41 14 4 6 4 1 3

Bulgaria (BG) 1069 10,80% 28,40% 24,00% 22,50% 7,30% 3,90% 1,30% 0,40% 0,60% 0,40% 0,10% - 0,30% -153 508 196 180 67 19 5 5

Canada (CA) 1211 13,50% 44,80% 17,30% 15,90% 5,90% 1,70% 0,40% 0,40% - - - - - -130 229 293 336 245 137 66 34 18 8 3 1 2 1

Chile (CL) 1505 8,60% 15,20% 19,50% 22,30% 16,30% 9,10% 4,40% 2,30% 1,20% 0,50% 0,20% 0,10% 0,10% 0,10%206 394 279 285 69 7 4 4 2

Czech Republic (CZ) 1276 16,50% 31,50% 22,30% 22,80% 5,50% 0,60% 0,30% 0,30% - 0,20% - - - -218 573 203 209 94 14 5 1 1

Denmark (DK) 1322 16,50% 43,50% 15,40% 15,90% 7,10% 1,10% 0,40% 0,10% - 0,10% - - - -260 539 238 180 92 30 8 1 1 1 1 2

Finland (FI) 1379 19,20% 39,80% 17,60% 13,30% 6,80% 2,20% 0,60% 0,10% - 0,10% 0,10% - 0,10% 0,10%621 430 227 245 108 21 11 3 3

France (FR) 1669 37,20% 25,80% 13,60% 14,70% 6,50% 1,30% 0,70% 0,20% 0,20% - - - - -157 318 146 157 43 20 6 2

Germany-West (DE-W) 850 18,50% 37,50% 17,20% 18,50% 5,10% 2,40% 0,70% 0,20% - - - - - -76 161 111 71 12 2 2 1 1

Germany-East (DE-E) 437 17,40% 36,80% 25,40% 16,20% 2,70% 0,50% 0,50% 0,20% 0,20% - - - - -235 334 130 122 41 7 3 1

Great Britain (GB) 873 26,90% 38,30% 14,90% 14,00% 4,70% 0,80% 0,30% - - - - 0,10% - -176 301 220 196 80 29 11 5 2 1

Hungary (HU) 1021 17,20% 29,50% 21,50% 19,20% 7,80% 2,80% 1,10% 0,50% 0,20% - 0,10% - - -117 278 197 223 144 63 28 9 3 2 1

Ireland (IE) 1065 11,00% 26,10% 18,50% 20,90% 13,50% 5,90% 2,60% 0,80% 0,30% 0,20% - 0,10% - -113 255 175 177 152 91 38 15 12 8 5 2 1 1

Israel Jews (IL-J) 1066 10,80% 24,40% 16,70% 16,90% 14,50% 8,70% 3,60% 1,40% 1,10% 0,80% 0,50% 0,20% 0,10% 0,10%1 11 24 20 30 29 27 7 2 1

Israel Arabs (IL-A) 152 0,70% 7,20% 15,80% 13,20% 19,70% 19,10% 17,80% 4,60% 1,30% 0,70% - - - -74 237 200 280 150 85 47 10 5 2

Japan (JP) 1102 6,80% 21,70% 18,30% 25,70% 13,80% 7,80% 4,30% 0,90% 0,50% 0,20% - - - -140 257 242 229 84 31 11 3 3

Latvia (LV) 1000 14,00% 25,70% 24,20% 22,90% 8,40% 3,10% 1,10% 0,30% 0,30% - - - - -129 401 163 184 95 30 15 6 2 1

New Zealand (NZ) 1036 12,60% 39,10% 15,90% 17,90% 9,30% 2,90% 1,50% 0,60% 0,20% - 0,10% - - -206 543 242 285 130 23 8 2 2

Norway (NO) 1469 14,30% 37,70% 16,80% 19,80% 9,00% 1,60% 0,60% 0,10% - 0,10% - - - -119 243 280 296 190 88 39 13 5 1 2 1

Poland (PL) 1277 9,30% 19,00% 21,90% 23,20% 14,90% 6,90% 3,10% 1,00% 0,40% 0,10% 0,20% - 0,10% -253 514 408 299 83 30 10 3 1 1

Portugal (PT) 1602 15,80% 32,10% 25,50% 18,70% 5,20% 1,90% 0,60% 0,20% 0,10% - - - 0,10% -14 95 196 234 233 163 111 64 36 22 10 9 6 2

Philippines (PH) 1200 1,20% 7,90% 16,30% 19,50% 19,40% 13,60% 9,20% 5,30% 3,00% 1,80% 0,80% 0,80% 0,50% 0,20%413 635 658 472 135 51 7 4 6 2

Russia (RU) 2383 17,30% 26,60% 27,60% 19,80% 5,70% 2,10% 0,30% 0,20% 0,30% - - 0,10% - -125 250 256 346 115 38 9 4 1

Slovak Republic (SK) 1152 10,90% 21,90% 22,40% 30,20% 10,10% 3,30% 0,80% 0,30% - - 0,10% - - -87 230 257 304 131 59 15 7 2

Slovenia (SI) 1093 8,00% 21,10% 23,50% 27,80% 12,00% 5,40% 1,40% 0,60% 0,20% - - - - -

South Africa (ZA) 2483 2483M - - - - - - - - - - - - - -135 237 325 466 109 36 5 2

South Korea (KR) 1315 10,30% 18,00% 24,70% 35,40% 8,30% 2,70% 0,40% 0,20% - - - - - -107 349 279 326 97 38 10 2 2

Spain (ES) 1212 8,80% 28,80% 23,10% 26,90% 8,00% 3,10% 0,80% 0,20% 0,20% - - - - -248 482 163 165 78 15 4 1

Sweden (SE) 1186 21,50% 41,70% 14,10% 14,30% 6,70% 1,30% 0,30% 0,10% - - - - - -262 376 151 152 68 19 5 1 1

Switzerland (CH) 1037 25,30% 36,30% 14,60% 14,70% 6,60% 1,80% 0,50% 0,10% 0,10% - - - - -55 203 239 472 443 253 157 73 37 33 10 18 10 2

Taiwan (TW) 2016 2,70% 10,10% 11,90% 23,40% 22,00% 12,50% 7,80% 3,60% 1,80% 1,60% 0,50% 0,90% 0,50% 0,10%293 446 205 169 68 30 3 1 1

United States (US) 1216 24,10% 36,70% 16,90% 13,90% 5,60% 2,50% 0,20% 0,10% 0,10% - - - - -151 296 231 192 129 57 25 10 6 5 2 2

Uruguay (UY) 1108 13,60% 26,70% 20,80% 17,30% 11,60% 5,10% 2,30% 0,90% 0,50% 0,50% 0,20% 0,20% - -26 1171

Venezuela (VE) 1199 2,20% 97,80% - - - - - - - - - - - -

Sum 44170 2483M 5943 12730 7730 8105 3846 1623 727 299 157 94 37 37 25 8


15 16 17 18 19 22 24 26 27 50 98 99

HOMPOP (N) % % % % % % % % % % % % 1 1

Australia (AU) 2183 - - - - - - % - - % - 34M

Austria (AT) 1006 - - - - - - - - - - - 1

Bulgaria (BG) 1069 0,10% - - - - - - - - - - 18M

Canada (CA) 1211 - - - - - - - - - - - 78M 1 1

Chile (CL) 1505 - - - - - 0,10% - 0,10% - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - 26M

Denmark (DK) 1322 - - - - - - - - - - - 4M

Finland (FI) 1379 - - - - - - - - - - - 26M

France (FR) 1669 - - - - - - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - 1M

Germany-East (DE-E) 437 - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - 1

Israel Jews (IL-J) 1066 0,10% - - - - - - - - - - 20M

Israel Arabs (IL-A) 152 - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - 12M

Latvia (LV) 1000 - - - - - - - - - - -

New Zealand (NZ) 1036 - - - - - - - - - - - 10M 1

Norway (NO) 1469 - - - - - - 0,10% - - - - 27M

Poland (PL) 1277 - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - 1 1 1 1 1

Philippines (PH) 1200 0,10% 0,10% 0,10% - 0,10% - - - 0,10% - -

Russia (RU) 2383 - - - - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - - 8M

Slovenia (SI) 1093 - - - - - - - - - - - 1M

South Africa (ZA) 2483 - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - 2M

Sweden (SE) 1186 - - - - - - - - - - - 30M

Switzerland (CH) 1037 - - - - - - - - - - - 2M 5 1 1 1 3

Taiwan (TW) 2016 0,20% - % % % - - - - - 0,10%

United States (US) 1216 - - - - - - - - - - - 1 1

Uruguay (UY) 1108 0,10% - - 0,10% - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - 2M Sum 44170 9 1 2 2 2 1 2 1 1 1 3 301M


INCOME: Family income Missing values 0;999997;999998;999999 INCOME. Family income in [Country] currency 1..999996 Income 0. Not available; No income; Not asked 999997. Refused 999998. Don’t know 999999. No answer Notes: This variable is country specific, even it if is integrated in the same variable. Some countries have coded the income as mid points of intervals that were asked to respondents. Unless specified otherwise, values are monthly incomes. Each country provided values in their own currency. An approximate exchange rate to the Euro at the field time is given for conversion purposes only (no conversion is provided within data itself). AUSTRALIA Respondent was asked for the Annual Income Mid points (Amounts in Australian $; 1 Australian Dollar = 0.62033 Euro) 1040 3120 5200 7280 9360 13000 18200 23400 25600 33800 39000 46800 65000 91000 104000 AUSTRIA Mid points (Amounts in Euros) 160 385 552 675 825 975 1125 1275 1425 1575 1725 1875 2025 2175 2325 2550 2850 3150 3450 3750 5000 BULGARIA Absolute values (Amounts in Bulgarian Levs; 1 Bulgarian Lev = 0.50826 Euro) 0: No income or No answer


CANADA Respondent was asked for the Annual Income before taxes Mid-points (Amounts in Canadian $; 1 Canadian Dollar = 0.68516 Euro) Under $15.000 7500 $15.000-$24.999 20000 $25.000-$34.999 30000 $35.000-$44.999 40000 $45.000-$54.999 50000 $55.000-$64.999 60000 $65.000-$74.999 70000 $75.000+ 80000 CZECH REPUBLIC Mid-points (Amounts in Czech Crowns; 1 Czech Koruna = 0.03319 Euro) 4000,00 9000,00 11000,00 13000,00 15000,00 17000,00 19000,00 21500,00 24500,00 28000,00 32500,00 37500,00 45000,00 55000,00 67500,00 82500,00 97500,00 CHILE Mid points (Amounts in Chilean Pesos; 1 Chilean Peso = 0.001428 Euro) 17500 Less than $35.000 45000 $35.001 to $56.000 58000 $56.001 to $78.000 89500 $78.001 to $101.000 127500 $101.001 to $134.000 156500 $134.001 to $179.000 201500 $179.001 to $224.000 257500 $224.001 to $291.000 324500 $291.001 to $358.000 403000 $358.001 to $448.000 724000 $448.001 to $1.000.000 1500000 $1.000.001 to $2.000.000 2500000 $2.000.001 to $3.000.000 3500000 More than $3.000.000 DENMARK Respondent were asked total annual income Mid points (Amounts in Danish Crowns; 1 Danish Krone = 0.13412 Euro) 50000 'below dkr 100.000 125000 'dkr 100.000 to 149.999 175000 'dkr 150.000 to 199.999 225000 'dkr 200.000 to 249.999 275000 'dkr 250.000 to 299.999 350000 'dkr 300.000 to 399.999 450000 'dkr 400.000 to 499.999 550000 'dkr 500.000 to 599.999 650000 'dkr 600.000 to 699.999 750000 'dkr 700.000 to 799.999


850000 'dkr 800.000 to 899.999 950000 'dkr 900.000 to 999.999 1050000 'dkr 1 million or more FINLAND Continuous values (Amounts in Finnish Markka; 1 Finnish Markka = 0.16819 Euro) FRANCE Mid points (Amounts in Euros) 305 euros 610 euros 915 euros 1296 euros 1906 euros 2668 euros 3430 euros 4192 euros 5335 euros 6860 euros 9909 euros GERMANY Continuous values (Amounts in Euros) GREAT BRITAIN Respondent were asked total annual income Mid points (Amounts in English Pounds; 1 British Pound = 1.45298 Euro) 2000 < 3 999 5000 4 000 - 5 999 7000 6 000 - 7 999 9000 8 000 - 9 999 11000 10 000 - 11 999 13500 12 000 - 14 999 16500 15 000 - 17 999 19000 18 000 - 19 999 21500 20 000 - 22 999 24500 23 000 - 25 999 27500 26 000 - 28 999 30500 29 000 - 31 999 35000 32 000 - 37 999 41000 38 000 - 43 999 47000 44 000 - 49 999 53000 50 000 - 55 999 59000 56 000 or more HUNGARY Continuous values (Amounts in Hungarian Forints; 1 Hungarian Forint = 0.004051 Euro) IRELAND Respondent were asked total annual income Mid points (Amounts in Euros) 6900 9025 13575 18700 24450 31000 38325 47500 61175 75000


ISRAEL Mid points (Amounts in Israeli Shekel; 1 Israeli New Shekel = 0.18203 Euro) 2250,00 5000,00 6000,00 7000,00 8000,00 9500,00 12000,00 14500,00 17750,00 22000,00 JAPAN Mid points (Amounts in Yens; 1 Japanese Yen = 0.007445 Euro) 1000 2500 3500 4500 5500 6500 7500 8500 9500 11000 13500 20000 LATVIA Continuous values (Amounts in Lats; 1 Latvian Lats = 1.43748 Euro) NEW ZEALAND Respondent were asked total annual income Mid points (Amounts in 1 New Zealand Dollar = 0.56331 Euro) 7500 17500 25000 35000 45000 55000 65000 75000 90000 120000 NORWAY Continuous values (Amounts in thousands Norwegian Kroner; 1 Norwegian Kroner = 0.12702 Euro) PHILIPPINES Continuous values (Amounts in Philippines Pesos ; 1 Philippine Peso = 0.01491 Euro) POLAND Continuous values (Amounts in Polish Zlotys; 1 Polish Zloty = 0.24569 Euro) PORTUGAL Mid points (Amounts in Euros) 175 < or=350 425 351-500 euros 650 501-800 euros 1150 801-1500 euros 2000 1501-2500 euros 5000 >2500 euros


RUSSIA Continuous values (Amounts in Russian Roubles; 1 Russian Rouble = 0.02902 Euro) SLOVAKIA Continuous values (Amounts in Slovak Koruna; 1 Slovak Koruna = 0.02581 Euro) SLOVENIA Continuous values (Amounts in Slovenian Tolars; 1 Slovenian Tolar = 0.004179 Euro) SOUTH AFRICA Mid points (Amounts in Rands; 1 South African Rand = 0.12217 Euro) 250 R1 – R500 625 R501 –R750 875 R751 – R1 000 1250 R1 001-R1 500 1750 R1 501 – R2 000 2500 R2 001 – R3 000 4000 R3 001 – R5 000 6250 R5 001 – R7 500 8750 R7 501 – R10 000 12500 R10 001 – R15 000 17500 R15 001 – R20 000 25000 R20 001 – R30 000 45000 R30 000 + SOUTH KOREA Mid Points (Amounts in thousands South Korean Won; 1 South-Korean Won = 0.0007919 Euro) 250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 5750 6250 6750 7250 7750 8250 8750 9250 9750 10500 11500 15500 17500 23500 25500 32500 42500 99998 SPAIN Mid points (Amounts in Euros) 150 Up to 300 euros 375 301 - 450 euros 525 451 - 600 euros 750 601 - 900 euros


1050 901 - 1.200 euros 1425 1.201 - 1.650 euros 1875 1.651 - 2.100 euros 2550 2.101 - 3.000 euros 4500 3.001 euros and more SWEDEN Continuous values per Month, pre-tax (Amount in Swedish Krones; 1 Swedish Krona = 0.10597 Euro) SWITZERLAND Continuous values (Amounts in Swiss Francs, 1 Swiss Franc = 0.64305 Euro) TAIWAN Mid points (values in Taiwan Dollars; 1 Taiwan Dollar = 0.02599 Euro) 5000 TWN:< than 9999 15000 TWN:10000-19999 25000 TWN:20000-29999 35000 TWN:30000-39999 45000 TWN:40000-49999 55000 TWN:50000-59999 65000 TWN:60000-69999 75000 TWN:70000-79999 85000 TWN:80000-89999 95000 TWN:90000-99999 105000 TWN:100000-109999 115000 TWN:110000-119999 125000 TWN:120000-129999 135000 TWN:130000-149999 145000 TWN:140000-149999 155000 TWN:150000-159999 195000 TWN:190000-199999 250000 TWN:200000-299999 350000 TWN:300000-399999 450000 TWN:400000-499999 750000 TWN:500000-999999 1500000 TWN: More than 1000000 URUGUAY Mid points (Amounts in Uruguayan Pesos; 1 Uruguayan Peso = 0.03377 Euro) 1500 Less than $3.000 4500 $3.000 to $5.999 6750 $6.000 to $7.499 8500 $7.500 to $9.499 10500 $9.500 to $11.499 12500 $11.500 to $13.499 15000 $13.500 to $16.499 18500 $16.500 to $20.499 23500 $20.500 to $26.499 32750 $26.500 to $38.999 58500 More than $39.000


USA Respondent were asked total annual income Mid points (Amounts in US Dollars; 1 US Dollar = 0.83507 Euro) 500,00 2000,00 3500,00 4500,00 5500,00 6500,00 7500,00 9000,00 11250,00 13750,00 16250,00 18750,00 21250,00 23750,00 27500,00 32500,00 37500,00 45000,00 55000,00 67500,00 82500,00 100000,00 999996,00 USA:> $110000 VENEZUELA Continuous values (Amounts in Venezuelan Bolivar; 1 Venezuelan Bolivar = 0.0003894 Euro)


INCOME Count Minimum Maximum Mean Std Deviation Valid N

Australia (AU) 2183 1040 182000 58496 43731 1932Austria (AT) 1006 160 5000 1955 1040 712Bulgaria (BG) 1069 36 2100 334 262 841Canada (CA) 1211 7500 80000 53610 23847 1083Czech Republic (CZ) 1276 4000 97500 19791 13000 874Chile (CL) 1505 17500 3500000 325228 446638 1261Denmark (DK) 1322 50000 1050000 435472 245756 1282Finland (FI) 1379 16 350000 3854 11317 1127France (FR) 1669 305 9909 3101 2053 1037Germany-East (DE-E) 437 200 7500 1980 1074 373Germany-West (DE-W) 850 100 10000 2325 1417 711Great Britain (GB) 873 2000 59000 23800 16465 773Hungary (HU) 1021 907 1250000 115017 96473 843Ireland (IE) 1065 6900 75000 34474 21682 919Israel Arabs (IL-A) 152 2250 17750 6297 2789 149Israel Jews (IL-J) 1066 2250 22000 7546 4867 851Japan (JP) 1102 1000 20000 5809 4154 703Latvia (LV) 1000 12 1200 203 125 722New Zealand (NZ) 1036 7500 120000 57201 35532 895Norway (NO) 1469 9 7000 498 425 1311Philippines (PH) 1200 300 200000 8958 13317 1076Poland (PL) 1277 40 40000 2044 2085 1146Portugal (PT) 1602 175 5000 1208 1200 1176Russia (RU) 2383 100 90000 6989 6941 2184Slovak Republic (SK) 1152 1450 100000 21044 12401 996Slovenia (SI) 1093 3000 996000 135584 116926 702South Africa (ZA) 2483 250 45000 2968 5413 1660South Korea (KR) 1315 250 42500 2989 2546 1259Spain (ES) 1212 150 4500 1124 711 778Sweden (SE) 1186 1000 150000 32511 16892 1010Switzerland (CH) 1037 87 150000 7283 6618 781Taiwan (TW) 2016 5000 1500000 73772 98521 1857United States (US) 1216 500 165000 58534 47275 1108Uruguay (UY) 1108 1500 58500 9958 10763 1051Venezuela (VE) 1199 4000 10000000 632007 662399 1157


RINCOME: Respondent’s earnings RINCOME. Respondent earnings in [Country] currency 1..999996 R’s Income 0. Not available; No income; Not asked 999997. Refused 999998. Don’t know 999999. No answer Notes: This variable is country specific, even it if is integrated in the same variable. Some countries have coded the income as mid points of intervals that were asked to respondents. Unless specified otherwise, values are monthly incomes. Each country provided values in their own currency. An approximate exchange rate to the Euro at the field time is given for conversion purposes only (no conversion is provided within data itself). AUSTRALIA Respondent was asked for the Annual Income Mid points (Amounts in Australian $; 1 Australian Dollar = 0.62033 Euro) 1040 3120 5200 7280 9360 13000 18200 23400 25600 33800 39000 46800 65000 91000 104000 AUSTRIA Mid points (Amounts in Euros) 160 385 552 675 825 975 1125 1275 1425 1575 1725 1875 2025 2175 2325 2550 2850 3150 3450 3750 5000


BULGARIA Absolute values (Amounts in Bulgarian Levs; 1 Bulgarian Lev = 0.50826 Euro) 0: No income or No answer CANADA Respondent was asked for the Annual Income before taxes Mid-points (Amounts in Canadian $; 1 Canadian Dollar = 0.68516 Euro) Under $15.000 7500 $15.000-$24.999 20000 $25.000-$34.999 30000 $35.000-$44.999 40000 $45.000-$54.999 50000 $55.000-$64.999 60000 $65.000-$74.999 70000 $75.000+ 80000 CZECH REPUBLIC Mid-points (Amounts in Czech Crowns; 1 Czech Koruna = 0.03319 Euro) 3000,00 6750,00 8250,00 9500,00 10500,00 11500,00 12750,00 14250,00 16000,00 18500,00 22500,00 27500,00 32500,00 37500,00 45000,00 55000,00 CHILE Mid points (Amounts in Chilean Pesos; 1 Chilean Peso = 0.001428 Euro) 17500 Less than $35.000 45000 $35.001 to $56.000 58000 $56.001 to $78.000 89500 $78.001 to $101.000 127500 $101.001 to $134.000 156500 $134.001 to $179.000 201500 $179.001 to $224.000 257500 $224.001 to $291.000 324500 $291.001 to $358.000 403000 $358.001 to $448.000 724000 $448.001 to $1.000.000 1500000 $1.000.001 to $2.000.000 2500000 $2.000.001 to $3.000.000 3500000 More than $3.000.000


DENMARK Respondent were asked total annual income Mid points (Amounts in Danish Crowns; 1 Danish Krone = 0.13412 Euro) 50000 'below dkr 100.000 125000 'dkr 100.000 to 149.999 175000 'dkr 150.000 to 199.999 225000 'dkr 200.000 to 249.999 275000 'dkr 250.000 to 299.999 350000 'dkr 300.000 to 399.999 450000 'dkr 400.000 to 499.999 550000 'dkr 500.000 to 599.999 650000 'dkr 600.000 or more FINLAND Continuous values (Amounts in Finnish Markka; 1 Finnish Markka = 0.16819 Euro) FRANCE Mid points (Amounts in Euros) 305 euros 610 euros 915 euros 1296 euros 1906 euros 2668 euros 3430 euros 4192 euros 5335 euros 6860 euros 9909 euros GERMANY Continuous values (Amounts in Euros) GREAT BRITAIN Respondent were asked total annual income Mid points (Amounts in English Pounds; 1 British Pound = 1.45298 Euro) 2000 < 3 999 5000 4 000 - 5 999 7000 6 000 - 7 999 9000 8 000 - 9 999 11000 10 000 - 11 999 13500 12 000 - 14 999 16500 15 000 - 17 999 19000 18 000 - 19 999 21500 20 000 - 22 999 24500 23 000 - 25 999 27500 26 000 - 28 999 30500 29 000 - 31 999 35000 32 000 - 37 999 41000 38 000 - 43 999 47000 44 000 - 49 999 53000 50 000 - 55 999 59000 56 000 or more HUNGARY Continuous values (Amounts in Hungarian Forints; 1 Hungarian Forint = 0.004051 Euro)


IRELAND Respondent were asked total annual income Mid points (Amounts in Euros) 6900 9025 13575 18700 24450 31000 38325 47500 61175 75000 ISRAEL Mid points (Amounts in Israeli Shekel; 1 Israeli New Shekel = 0.18203 Euro) 1000,00 3000,00 5000,00 7000,00 9000,00 13000,00 15500,00 JAPAN Mid points (Amounts in Yens; 1 Japanese Yen = 0.007445 Euro) 500 1500 2500 3500 4500 5500 6500 7500 8500 9500 11000 13500 20000 LATVIA Continuous values (Amounts in Lats; 1 Latvian Lats = 1.43748 Euro) NEW ZEALAND Respondent were asked total annual income Mid points (Amounts in 1 New Zealand Dollar = 0.56331 Euro) 5000 12500 17500 22500 27500 35000 45000 60000 85000 120000 NORWAY Continuous values (Amounts in thousands Norwegian Kroner; 1 Norwegian Kroner = 0.12702 Euro) PHILIPPINES Continuous values (Amounts in Philippines Pesos ; 1 Philippine Peso = 0.01491 Euro)


POLAND Continuous values (Amounts in Polish Zlotys; 1 Polish Zloty = 0.24569 Euro) PORTUGAL Mid points (Amounts in Euros) 175 < or=350 425 351-500 euros 650 501-800 euros 1150 801-1500 euros 2000 1501-2500 euros 5000 >2500 euros RUSSIA Continuous values (Amounts in Russian Roubles; 1 Russian Rouble = 0.02902 Euro) SLOVAKIA Continuous values (Amounts in Slovak Koruna; 1 Slovak Koruna = 0.02581 Euro) SLOVENIA Continuous values (Amounts in Slovenian Tolars; 1 Slovenian Tolar = 0.004179 Euro) SOUTH AFRICA Mid points (Amounts in Rands; 1 South African Rand = 0.12217 Euro) 250 R1 – R500 625 R501 –R750 875 R751 – R1 000 1250 R1 001-R1 500 1750 R1 501 – R2 000 2500 R2 001 – R3 000 4000 R3 001 – R5 000 6250 R5 001 – R7 500 8750 R7 501 – R10 000 12500 R10 001 – R15 000 17500 R15 001 – R20 000 25000 R20 001 – R30 000 45000 R30 000 + SOUTH KOREA Mid Points (Amounts in thousands South Korean Won; 1 South-Korean Won = 0.0007919 Euro) 250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 5750 6250 7250 8250 10500 15500 20500 42500


SPAIN Mid points (Amounts in Euros) 150 Up to 300 euros 375 301 - 450 euros 525 451 - 600 euros 750 601 - 900 euros 1050 901 - 1.200 euros 1425 1.201 - 1.650 euros 1875 1.651 - 2.100 euros 2550 2.101 - 3.000 euros 4500 3.001 euros and more SWEDEN Continuous values per Month, pre-tax (Amounts in Swedish Krones; 1 Swedish Krona = 0.10597 Euro) SWITZERLAND Continuous values (Amounts in Swiss Francs, 1 Swiss Franc = 0.64305 Euro) TAIWAN Mid points (values in Taiwan Dollars; 1 Taiwan Dollar = 0.02599 Euro) 5000 TWN:< than 9999 15000 TWN:10000-19999 25000 TWN:20000-29999 35000 TWN:30000-39999 45000 TWN:40000-49999 55000 TWN:50000-59999 65000 TWN:60000-69999 75000 TWN:70000-79999 85000 TWN:80000-89999 95000 TWN:90000-99999 105000 TWN:100000-109999 115000 TWN:110000-119999 125000 TWN:120000-129999 135000 TWN:130000-149999 145000 TWN:140000-149999 155000 TWN:150000-159999 195000 TWN:190000-199999 250000 TWN:200000-299999 450000 TWN:> than 300000 URUGUAY Mid points (Amounts in Uruguayan Pesos; 1 Uruguayan Peso = 0.03377 Euro) 1500 Less than $3.000 4500 $3.000 to $5.999 6750 $6.000 to $7.499 8500 $7.500 to $9.499 10500 $9.500 to $11.499 12500 $11.500 to $13.499 15000 $13.500 to $16.499 18500 $16.500 to $20.499 23500 $20.500 to $26.499 32750 $26.500 to $38.999 58500 More than $39.000 USA Respondent were asked total annual income Mid points (Amounts in US Dollars; 1 US Dollar = 0.83507 Euro) 500,00 2000,00 3500,00 4500,00 5500,00


6500,00 7500,00 9000,00 11250,00 13750,00 16250,00 18750,00 21250,00 23750,00 27500,00 32500,00 37500,00 45000,00 55000,00 67500,00 82500,00 100000,00 999996,00 USA:> $110000 VENEZUELA Continuous values (Amounts in Venezuelan Bolivar; 1 Venezuelan Bolivar = 0.0003894 Euro)


RINCOME Count Minimum Maximum Mean Std Deviation Valid N Australia (AU) 2183 1040 104000 34320 26437 1969 Austria (AT) 1006 160 5000 1183 636 735 Bulgaria (BG) 1069 1 1050 171 136 783 Canada (CA) 1211 7500 80000 37538 23405 1064 Czech Republic (CZ) 1276 3000 55000 10331 6384 912 Chile (CL) 1505 17500 3500000 203200 349484 1272 Denmark (DK) 1322 50000 650000 240388 144396 1290 Finland (FI) 1379 4 20000 1860 1657 1160 France (FR) 1669 305 9909 1772 1448 1186 Germany-East (DE-E) 437 70 7500 1071 747 374 Germany-West (DE-W) 850 98 10000 1394 994 675 Great Britain (GB) 873 2000 59000 19818 12393 415 Hungary (HU) 1021 8000 250000 56417 31595 833 Ireland (IE) 1065 6900 75000 20499 15026 817 Israel Arabs (IL-A) 152 1000 9000 3854 1806 96 Israel Jews (IL-J) 1066 1000 15500 4932 3445 646 Japan (JP) 1102 500 20000 3153 3256 763 Latvia (LV) 1000 6 900 112 83 775 New Zealand (NZ) 1036 5000 120000 33268 26967 938 Norway (NO) 1469 2 7300 295 335 1319 Philippines (PH) 1200 150 50000 4956 5305 599 Poland (PL) 1277 50 8000 1248 911 498 Portugal (PT) 1602 175 5000 644 747 1228 Russia (RU) 2383 150 60000 5025 5195 1065 Slovak Republic (SK) 1152 200 80000 10236 7492 921 Slovenia (SI) 1093 1000 996000 274727 178347 663 South Africa (ZA) 2483 250 45000 2009 4049 1183 South Korea (KR) 1315 250 42500 2027 2194 692 Spain (ES) 1212 150 4500 761 470 649 Sweden (SE) 1186 1000 130000 18777 11161 1042 Switzerland (CH) 1037 9 150000 4930 6034 799 Taiwan (TW) 2016 5000 450000 35170 39899 1442 United States (US) 1216 500 165000 39965 36599 768 Uruguay (UY) 1108 1500 58500 6510 8396 947 Venezuela (VE) 1199 4000 6000000 394395 484139 658


HHCYCLE: Household composition Missing Values: 00;99 Hhcycle. Household composition: number of adults and of children under 18 years) 1. 00. Not applicable, not available. 01. Single household. 02. 1A,1CH. 03. 1A,2CH. 04. 1A,3or>CH. 05. 2A. 06. 2A,1CH. 07. 2A,2CH. 08. 2A,3or>CH. 09. 3A. 10. 3A+CH. 11. 4A. 12. 4A+CH. 13. 5A. 14. 5A+CH. 15. 6A. 16. 6A+CH. 17. 7A. 18. 7A+CH. 19. 8A. 20. 8A+CH. 21. 9A. 22. 9A+CH. 23. 10A. 24. 10A+CH. 25. 11A. 26. 11 adults+children. 27. 12A. 28. 12A+CH. 95. Otherwise. 99. No answer, refused. Notes: (1) Not asked in Slovenia and South Africa


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

HHCYCLE (N) % % % % % % % % % % % % % % % 504 20 20 5 807 287 327 90 44 41 13

Australia (AU) 2183 23,30% 0,90% 0,90% 0,20% - - - 37,30% 13,30% 15,10% 4,20% 2,00% 1,90% 0,60%245 16 11 4 269 117 119 33 72 51 35 10 14 6

Austria (AT) 1006 24,40% 1,60% 1,10% 0,40% 26,70% 11,60% 11,80% 3,30% 7,20% 5,10% 3,50% 1,00% 1,40% 0,60%113 7 2 1 292 109 102 12 214 146 53

Bulgaria (BG) 1069 10,80% 0,70% 0,20% 0,10% 27,80% 10,40% 9,70% 1,10% - 20,40% - 13,90% 5,00% -142 19 8 4 484 101 130 56 87 24 43 15

Canada (CA) 1211 12,50% 1,70% 0,70% 0,40% 42,50% 8,90% 11,40% 4,90% 7,60% 2,10% 3,80% 1,30% - -130 24 21 17 203 165 182 101 109 203 58 144 27 69

Chile (CL) 1505 8,60% 1,60% 1,40% 1,10% 13,50% 11,00% 12,10% 6,70% 7,20% 13,50% 3,90% 9,60% 1,80% 4,60%206 30 15 3 241 107 137 23 67 23 1

Czech Republic (CZ) 1276 24,00% 3,50% 1,70% 0,30% 28,10% 12,50% 16,00% 2,70% - 7,80% - 2,70% - 0,10%217 15 19 4 557 127 152 76 56 61 15 11 2

Denmark (DK) 1322 16,50% 1,10% 1,40% 0,30% 42,40% 9,70% 11,60% 5,80% 4,30% 4,60% 1,10% 0,80% 0,20% -258 37 32 5 503 127 124 92 78 51 20 18 4 1

Finland (FI) 1379 19,00% 2,70% 2,40% 0,40% 37,00% 9,40% 9,10% 6,80% 5,70% 3,80% 1,50% 1,30% 0,30% 0,10%620 49 43 18 381 100 146 56 85 49 54 23 24 5

France (FR) 1669 37,50% 3,00% 2,60% 1,10% 23,00% 6,00% 8,80% 3,40% 5,10% 3,00% 3,30% 1,40% 1,50% 0,30%157 10 1 2 306 65 98 25 77 48 22 12 8 6

Germany-West (DE-W) 850 18,70% 1,20% 0,10% 0,20% 36,50% 7,70% 11,70% 3,00% 9,20% 5,70% 2,60% 1,40% 1,00% 0,70%76 8 4 152 46 39 4 59 19 15 7 2 1

Germany-East (DE-E) 437 17,60% 1,80% 0,90% - 35,10% 10,60% 9,00% 0,90% 13,60% 4,40% 3,50% 1,60% 0,50% 0,20%235 28 17 12 306 63 76 34 49 21 20 5 3 1

Great Britain (GB) 873 26,90% 3,20% 1,90% 1,40% 35,10% 7,20% 8,70% 3,90% 5,60% 2,40% 2,30% 0,60% 0,30% 0,10%177 13 10 3 288 69 78 29 140 69 80 35 10 10

Hungary (HU) 1021 17,30% 1,30% 1,00% 0,30% 28,20% 6,80% 7,60% 2,80% 13,70% 6,80% 7,80% 3,40% 1,00% 1,00%117 7 7 8 271 59 85 77 131 76 87 62 34 19

Ireland (IE) 1065 11,00% 0,70% 0,70% 0,80% 25,40% 5,50% 8,00% 7,20% 12,30% 7,10% 8,20% 5,80% 3,20% 1,80%111 11 4 3 210 59 80 109 22 104 13 77 7 26

Israel Jews (IL-J) 1066 13,00% 1,30% 0,50% 0,40% 24,60% 6,90% 9,40% 12,80% 2,60% 12,20% 1,50% 9,00% 0,80% 3,00%1 2 11 14 7 25 21 17 9

Israel Arabs (IL-A) 152 0,90% - 1,80% - 9,70% 12,40% 6,20% 22,10% - 18,60% - 15,00% - 8,00%74 3 1 229 54 78 29 144 81 160 75 58 45

Japan (JP) 1102 6,90% 0,30% 0,10% - 21,20% 5,00% 7,20% 2,70% 13,40% 7,50% 14,80% 7,00% 5,40% 4,20%140 237 20 112 130 37 192 7 77

Latvia (LV) 1000 14,00% - - - 23,70% 2,00% - - 11,20% 13,00% 3,70% 19,20% 0,70% 7,70%129 13 9 387 96 114 64 67 57 35 27 13 9

New Zealand (NZ) 1036 12,60% - 1,30% 0,90% 37,70% 9,40% 11,10% 6,20% 6,50% 5,60% 3,40% 2,60% 1,30% 0,90%203 23 16 6 517 130 180 97 91 81 44 19 7 3

Norway (NO) 1469 14,30% 1,60% 1,10% 0,40% 36,40% 9,10% 12,70% 6,80% 6,40% 5,70% 3,10% 1,30% 0,50% 0,20%119 3 1 1 240 104 102 34 175 140 111 112 47 43

Poland (PL) 1277 9,30% 0,20% 0,10% 0,10% 18,80% 8,10% 8,00% 2,70% 13,70% 11,00% 8,70% 8,80% 3,70% 3,40%255 22 11 3 493 187 123 25 213 101 101 35 17 7

Portugal (PT) 1602 15,90% 1,40% 0,70% 0,20% 30,80% 11,70% 7,70% 1,60% 13,30% 6,30% 6,30% 2,20% 1,10% 0,40%15 13 12 17 85 123 132 204 65 189 46 111 30 69

Philippines (PH) 1200 1,30% 1,10% 1,00% 1,40% 7,10% 10,30% 11,00% 17,00% 5,40% 15,80% 3,80% 9,30% 2,50% 5,80%413 71 20 3 564 347 148 23 291 236 130 77 24 27

Russia (RU) 2383 17,30% 3,00% 0,80% 0,10% 23,70% 14,60% 6,20% 1,00% 12,20% 9,90% 5,50% 3,20% 1,00% 1,10%124 33 6 7 221 120 186 30 134 77 100 56 25 14

Slovak Republic (SK) 1152 10,80% 2,90% 0,50% 0,60% 19,30% 10,50% 16,30% 2,60% 11,70% 6,70% 8,70% 4,90% 2,20% 1,20%

Slovenia (SI) 1093 1093M - - - - - - - - - - - - - -

South Africa (ZA) 2483 2483M - - - - - - - - - - - - - -135 5 12 2 229 136 243 34 174 111 138 41 29 9

South Korea (KR) 1315 10,40% 0,40% 0,90% 0,20% 17,60% 10,40% 18,60% 2,60% 13,40% 8,50% 10,60% 3,10% 2,20% 0,70%107 22 17 5 327 134 172 43 128 56 116 24 28 11

Spain (ES) 1212 8,80% 1,80% 1,40% 0,40% 27,00% 11,10% 14,20% 3,50% 10,60% 4,60% 9,60% 2,00% 2,30% 0,90%248 34 23 5 448 80 119 58 60 54 12 11 3

Sweden (SE) 1186 21,50% 2,90% 2,00% 0,40% 38,80% 6,90% 10,30% 5,00% 5,20% 4,70% 1,00% 1,00% 0,30% -262 16 10 2 359 75 97 60 66 29 33 16 6 2

Switzerland (CH) 1037 25,30% 1,50% 1,00% 0,20% 34,70% 7,30% 9,40% 5,80% 6,40% 2,80% 3,20% 1,50% 0,60% 0,20%55 8 3 2 195 59 133 69 177 236 242 236 181 147

Taiwan (TW) 2016 2,70% 0,40% 0,10% 0,10% 9,70% 2,90% 6,60% 3,40% 8,80% 11,70% 12,00% 11,70% 9,00% 7,30%293 43 23 16 403 102 110 50 80 47 25 14 6 3

United States (US) 1216 24,10% 3,50% 1,90% 1,30% 33,10% 8,40% 9,00% 4,10% 6,60% 3,90% 2,10% 1,20% 0,50% 0,20%151 32 19 6 264 121 85 72 91 125 45 52 14 18

Uruguay (UY) 1108 13,60% 2,90% 1,70% 0,50% 23,80% 10,90% 7,70% 6,50% 8,20% 11,30% 4,10% 4,70% 1,30% 1,60%36 12 7 12 78 89 88 127 70 204 49 168 26 103

Venezuela (VE) 1199 3,00% 1,00% 0,60% 1,00% 6,50% 7,40% 7,40% 10,60% 5,80% 17,00% 4,10% 14,00% 2,20% 8,60%

Sum 44170 3576M 6068 634 410 185 9750 3305 3665 2578 3390 3359 1976 1915 750 754


15 16 17 18 19 20 21 22 23 24 25 26 27 28 95 99

HHCYCLE (N) % % % % % % % % % % % % % % % % 3 1 1

Australia (AU) 2183 0,10% % % - - - - - - - - - - - - 20M3 1

Austria (AT) 1006 0,30% - - - - - - - - - - - - - 0,10%

Bulgaria (BG) 1069 - - - - - - - - - - - - - - - 18M25

Canada (CA) 1211 - - - - - - - - - - - - - - 2,20% 73M11 25 1 10 2 2 1

Chile (CL) 1505 0,70% 1,70% 0,10% 0,70% - 0,10% - 0,10% - 0,10% - - - - - 4 1

Czech Republic (CZ) 1276 - 0,50% - 0,10% - - - - - - - - - - - 418M1

Denmark (DK) 1322 - - 0,10% - - - - - - - - - - - - 9M8

Finland (FI) 1379 - - - - - - - - - - - - - - 0,60% 21M

France (FR) 1669 - - - - - - - - - - - - - - - 16M2

Germany-West (DE-W) 850 0,20% - - - - - - - - - - - - - - 11M1

Germany-East (DE-E) 437 - - - 0,20% - - - - - - - - - - - 4M1 1

Great Britain (GB) 873 0,10% 0,10% - - - - - - - - - - - - - 1M5 4 1

Hungary (HU) 1021 0,50% 0,40% - - - 0,10% - - - - - - - - - 11 7 3 1 1 1 1

Ireland (IE) 1065 1,00% 0,70% 0,30% 0,10% 0,10% 0,10% - - - 0,10% - - - - - 9 1 6 1

Israel Jews (IL-J) 1066 - 1,10% 0,10% 0,70% - 0,10% - - - - - - - - - 213M5 1

Israel Arabs (IL-A) 152 - 4,40% - - - 0,90% - - - - - - - - - 39M25 12 6 1 1 1 1

Japan (JP) 1102 2,30% 1,10% 0,60% 0,10% 0,10% 0,10% 0,10% - - - - - - - - 24M31 11 3 3

Latvia (LV) 1000 - 3,10% - 1,10% - 0,30% - 0,30% - - - - - - - 1 4 1

New Zealand (NZ) 1036 0,10% 0,40% - 0,10% - - - - - - - - - - - 10M1 1 1 1

Norway (NO) 1469 0,10% 0,10% - 0,10% 0,10% - - - - - - - - - - 48M9 17 4 1 1 1 12

Poland (PL) 1277 0,70% 1,30% 0,30% 0,10% 0,10% 0,10% - - - - - - - - 0,90% 3 1 3 2

Portugal (PT) 1602 0,20% 0,10% 0,20% 0,10% - - - - - - - - - - - 12 34 7 15 2 8 1 4 1 2 1

Philippines (PH) 1200 1,00% 2,80% 0,60% 1,30% 0,20% 0,70% 0,10% 0,30% 0,10% 0,20% - - - 0,10% - 2M4 2 3

Russia (RU) 2383 0,20% 0,10% 0,10% - - - - - - - - - - - - 3 4 1 1 1 1

Slovak Republic (SK) 1152 0,30% 0,30% 0,10% 0,10% 0,10% - - - - - - - - - 0,10% 8M

Slovenia (SI) 1093 - - - - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - - - - - 4 1

South Korea (KR) 1315 0,30% - - 0,10% - - - - - - - - - - - 12M12 1 3 1 1 1 1 2

Spain (ES) 1212 1,00% 0,10% 0,20% 0,10% - 0,10% - - - 0,10% 0,10% - - - 0,20% 1

Sweden (SE) 1186 0,10% - - - - - - - - - - - - - - 30M1

Switzerland (CH) 1037 0,10% - - - - - - - - - - - - - - 3M79 72 33 36 6 27 6 4 1 3 2 1

Taiwan (TW) 2016 3,90% 3,60% 1,60% 1,80% 0,30% 1,30% - 0,30% - 0,20% % 0,10% 0,10% - % 3M1

United States (US) 1216 0,10% - - - - - - - - - - - - - - 1 7 1 2 1 1

Uruguay (UY) 1108 0,10% 0,60% - 0,10% - 0,20% - - - 0,10% - - - 0,10% - 13 62 2 24 3 12 1 7 3 1

Venezuela (VE) 1199 1,10% 5,20% 0,20% 2,00% 0,30% 1,00% 0,10% 0,60% - 0,30% - 0,10% - - - 2MSum 44170 206 304 69 115 16 61 3 22 1 13 2 4 2 2 50 985M


PARTY_LR: R's scale of political ideology Missing Values: 0;8;9 Party_LR. Party preference or vote intention, coded to left-right position 1. 1. Far left. 2. Left,center left. 3. Center,liberal. 4. Right,conservative. 5. Far right. 6. Other. 0. Not applicable, not available; variable from which is derived not asked 7. No party. 8. Don't know, DK: Don't remember. 9. No answer, refused. Notes: (1) Not asked in Chile, Israel, South Africa and Taiwan


0 1 2 3 4 5 6 7 8 9

PARTY_LR (N) % % % % % % % % % % 2 857 53 752 41 434

Australia (AU) 2183 0,10% 40,10% 2,50% 35,20% 1,90% - 20,30% 1M 43M 80 238 216 62 5

Austria (AT) 1006 158M 13,30% 39,60% - 35,90% 10,30% 0,80% - 29M 218M 50 118 46 89 34 1 545

Bulgaria (BG) 1069 5,70% 13,40% 5,20% 10,10% 3,90% 0,10% 61,70% 126M 60M 172 446 202 2 103 225

Canada (CA) 1211 - 15,00% 38,80% 17,60% 0,20% 9,00% 19,60% 61M

Chile (CL) 1505 1505M - - - - - - - 107 125 69 280 6 65

Czech Republic (CZ) 1276 16,40% 19,20% 10,60% 42,90% 0,90% 10,00% - 265M 359M 120 328 114 475 89 3 9

Denmark (DK) 1322 84M 10,50% 28,80% 10,00% 41,70% 7,80% 0,30% 0,80% 77M 23M 298 269 212 139 80

Finland (FI) 1379 - 29,90% 27,00% 21,20% - 13,90% 8,00% 252M 129M 125 347 370 277 115

France (FR) 1669 10,10% 28,10% 30,00% 22,40% 9,30% - - 435M 5 191 47 260 10 10 109

Germany-West (DE-W) 850 65M 0,80% 30,20% 7,40% 41,10% 1,60% 1,60% 17,20% 120M 33M 53 80 21 87 3 1 88

Germany-East (DE-E) 437 5M 15,90% 24,00% 6,30% 26,10% 0,90% 0,30% 26,40% 84M 15M 16 321 104 227 28 133

Great Britain (GB) 873 1,90% 38,70% 12,50% 27,40% - 3,40% 16,00% 31M 13M 6 456 9 273 13

Hungary (HU) 1021 0,80% 60,20% 1,20% 36,10% 1,70% - - 174M 90M 15 30 93 409 172 68 32

Ireland (IE) 1065 1,80% 3,70% 11,40% 49,90% 21,00% 8,30% 3,90% 234M 12M

Israel Jews (IL-J) 1066 1066M - - - - - - -

Israel Arabs (IL-A) 152 152M - - - - - - - 19 19 182 349 472

Japan (JP) 1102 1,80% 1,80% 17,50% 33,50% - - 45,30% 61M 63 43 157 63

Latvia (LV) 1000 19,30% 13,20% 48,20% 19,30% - - - 674M 11 118 193 212 14 18 217

New Zealand (NZ) 1036 1,40% 15,10% 24,60% 27,10% 1,80% 2,30% 27,70% 179M 74M 21 530 173 456 15 65

Norway (NO) 1469 1,70% 42,10% 13,70% 36,20% - 1,20% 5,20% 186M 23M 182 108 142 112 45 17

Poland (PL) 1277 459M 30,00% 17,80% 23,40% 18,50% 7,40% 2,80% - 210M 2M 156 419 290 18 4 518

Portugal (PT) 1602 11,10% 29,80% 20,60% 1,30% - 0,30% 36,90% 197M 27 49 445 167 66 326

Philippines (PH) 1200 2,50% 4,50% 41,20% 15,50% 6,10% - 30,20% 83M 37M 256 53 129 193 18 17 933

Russia (RU) 2383 16,00% 3,30% 8,10% 12,10% 1,10% 1,10% 58,30% 784M 13 102 246 90 14 16 357

Slovak Republic (SK) 1152 1,60% 12,20% 29,40% 10,70% 1,70% 1,90% 42,60% 180M 134M 122 355 213 26 31 99

Slovenia (SI) 1093 - 14,40% 42,00% 25,20% 3,10% 3,70% 11,70% 202M 45M

South Africa (ZA) 2483 2483M - - - - - - - 54 324 334 423 78

South Korea (KR) 1315 4,50% 26,70% 27,50% 34,90% 6,40% - - 102M 8 444 299 221

Spain (ES) 1212 0,80% 45,70% 30,80% 22,70% - - - 240M 106 431 362 158 64

Sweden (SE) 1186 9,50% 38,40% 32,30% 14,10% - 5,70% - 65M 5 209 3 216 7 14 552

Switzerland (CH) 1037 0,50% 20,80% 0,30% 21,50% 0,70% 1,40% 54,90% 11M 20M

Taiwan (TW) 2016 2016M - - - - - - - 415 427 360 9

United States (US) 1216 - 34,30% 35,30% 29,70% - 0,70% - 5M 12 432 141 282 10 169

Uruguay (UY) 1108 1,10% 41,30% 13,50% 27,00% 1,00% - 16,20% 58M 4M 52 88 352 258 24 25 247

Venezuela (VE) 1199 5,00% 8,40% 33,70% 24,70% 2,30% 2,40% 23,60% 138M 15M

Sum 44170 7993M 1564 7467 5871 7550 849 653 5610 3526M 3087M


XX_PRTY: Country Specific Vote Intention Missing Values: 00;97;98;99 R's voting intention in national elections (Country specific) xx. Party 00. Not applicable, not available.; Not asked 95. Other Party 96. Would not vote 97. Refuse. 98. Don't know. 99. No answer. Notes: (1) Not asked in Bulgaria and South Africa Australia AU_PRTY n % 1. Liberal Party 691 31,7 2. Labour Party 750 34,4 3. National Party 60 2,7 4. Democrats 53 2,4 5. Greens 107 4,9 6. One nation 41 1,9 95. Other Party 4 0,2 96. None 434 19,9 99. NA, refused 43 2,0 (N) 2183 100% Austria AT_PRTY n % 1. SPOE (Soc-Democr) 238 25,3 2. OEVP (Cons) 216 23,0 3. FPOE (Liberal) 62 6,6 4. GRUENE (Green) 80 8,5 95. Other party 5 0,5 96. Would not vote 93 9,9 97. Refused 29 3,1 99. NA 218 23,2 (N) 941 100% Bulgaria BG_PRTY n % (N) 0 100%


Canada CA_PRTY n % 1. New Democratic Party 101 8,3 2. Liberal 446 36,8 3. Conservative 202 16,7 4. Bloc Quebecois 71 5,9 95. Other Party 105 8,7 96. Would not vote;no party preference 225 18,6 99. NA 61 5,0 (N) 1211 100% Chile CL_PRTY n % 1. Independent National Alliance 35 2,3 2. Communist Party of Chile 37 2,5 3. Christian Democratic Party 166 11,0 4. Humanist Party 29 1,9 5. Democracy Party PPD 135 9,0 6. Radical Social Democratic 12 0,8 7. Chilean Socialist Party 122 8,1 8. National Renewal Party 100 6,6 9. Independent Democratic Union 141 9,4 95. Other Party 3 0,2 96. No party, no preference 625 41,5 98. Dont know 47 3,1 99. NA 53 3,5 (N) 1505 100% Czech Republic CZ_PRTY n % 1. CSSD Social Democrats 125 9,8 2. ODA Civil Democratic Alliance 8 0,6 3. Nadeje Hope 5 0,4 4. RMS Republicans of Miroslav Sladek 6 0,5 5. CSNS Czech National Social Praty 2 0,2 6. SV-SOS party of the Countryside-United Civil Powers 3 0,2 7. Association of Independens 25 2,0 8. ODS Civic Democratic 251 19,7 9. KSCM Communist Party 107 8,4 10. KDU-CSL Chirtian Dem Party-Czechoslovak Peoples P 67 5,3 11. US-DEU Freedom Union - Democartic Union 13 1,0 12. SZJ Party for Life Securities 11 0,9 13. PB Right Block 8 0,6 14. SZ Party of Greens 13 1,0 95. Other Party 8 0,6 97. Refused 214 16,8 98. Dont know 265 20,8 99. NA 145 11,4 (N) 1276 100%

ZA - No. 3910 I S S P 2003 - National Identity II Page II -236

Denmark DK_PRTY n % 1. Social Democratic P 328 26,5 2. Radical Liberal P 83 6,7 3. Conservative P 88 7,1 4. Centre Democratic 13 1,1 5. Socialist Peoples P 91 7,4 6. Danish Peoples Prty 85 6,9 7. Christian Peoples P 18 1,5 9. Liberal 387 31,3 10. Progressive 4 0,3 11. Leftwing Alliance 29 2,3 95. Other Party 3 0,2 96. No preference,no vote 9 0,7 98. Dont know 77 6,2 99. NA 23 1,9 (N) 1238 100%

ZA - No. 3910 I S S P 2003 - National Identity II Page II -237

Finland FI_PRTY n % 1. Social Democratic Party of Finland 245 17,8 2. Center Party of Finland 174 12,6 3. National Coalition Party 196 14,2 4. Left Alliance 53 3,8 5. Swedish People´s Party in Finland 46 3,3 6. Green League 127 9,2 7. Christian Democrats 49 3,6 8. True Finns 16 1,2 9. Reform Group 3 0,2 95. Other party 9 0,7 96. Would not vote 80 5,8 97. Refused 114 8,3 98. Dont know 252 18,3 99. No answer 15 1,1 (N) 1379 100% France FR_PRTY n % 1. Far left 38 2,3 2. Communist party 49 2,9 3. Socialist party 332 19,9 4. Green 150 9,0 5. UDF-Center Right 125 7,5 6. UMP-Conservative 356 21,3 7. National Front 68 4,1 95. Other Party 17 1,0 96. No preference 367 22,0 97. Refused 73 4,4 99. NA 94 5,6 (N) 1669 100% Germany DE_PRTY n % 1. CDU/ CSU 347 28,5 2. SPD 188 15,4 3. FDP 68 5,6 4. Buendnis 90/Gruene 83 6,8 7. Republikaner 13 1,1 8. PDS/Linke Liste 58 4,8 95. Other Party 11 0,9 96. Would not vote;not eligible 197 16,2 97. Refused 48 3,9 98. Dont know 204 16,8 (N) 1217 100%


Great Britain GB_PRTY n % 1. Conservative 227 26,0 2. Labour 321 36,8 3. Liberal Democrats,SLD 104 11,9 6. SNP (Scot National) 12 1,4 7. Plaid Cymru 1 0,1 93. Other answer 7 0,8 95. Other Party 24 2,7 96. Would not vote;No party preference 133 15,2 98. Dont know 31 3,6 99. NA 13 1,5 (N) 873 100% Hungary HU_PRTY n % 1. HDF-Hungarian Democratic Forum 16 1,6 2. FFD-Free Democrats 33 3,2 3. ISHP-Independent Small Holders 2 0,2 4. HSP-Hungarian Socialist Party 423 41,4 5. FYD-Federation of Young Democrats 255 25,0 7. HSPW-Socialist workers 6 0,6 8. HIJP-Hungarina Truth 13 1,3 95. Other Party 9 0,9 96. Would not vote;no party preference 174 17,0 97. Refused 77 7,5 99. NA 13 1,3 (N) 1021 100% Ireland IE_PRTY n % 1. Fianna Fail 218 55,3 2. Fine Gael 83 21,1 3. Labour 39 9,9 4. Progressive Democrats 9 2,3 5. Green Party 10 2,5 6. Socialist Party 7 1,8 7. Sinn Fein 20 5,1 95. Other Party 4 1,0 99. NA 4 1,0 (N) 394 100%


Israel IL_PRTY n % 1. Israel ahat 123 10,1 2. Likud 321 26,4 3. Shase 51 4,2 4. Meretz 71 5,8 5. Mafdal 50 4,1 6. Yahadut-hatora, Agudat-Isarel, Degel-hatora 56 4,6 7. Am ehad 6 0,5 8. Shinuy 97 8,0 9. Haehud haleumi 17 1,4 10. The center party 3 0,2 11. Israel baliya 4 0,3 12. Israel byteno 21 1,7 15. Tzomet 2 0,2 16. Gimlaim 3 0,2 21. Hadash 41 3,4 22. Balad 34 2,8 23. Tnua Haravit Leshinui 8 0,7 24. Hatnua Harabit Hameauhedet 22 1,8 26. ale yarok 4 0,3 97. Refusal 74 6,1 98. Don´t know 89 7,3 99. No answer 121 9,9 (N) 1218 100% Japan JP_PRTY n % 1. Liberal Democratic Party 348 31,6 2. The Democratic Party 140 12,7 4. New Komeito 42 3,8 5. Japanese Communist Party 19 1,7 6. Social Democratic Party 19 1,7 95. Other Party 1 0,1 96. No party preference 472 42,8 99. NA 61 5,5 (N) 1102 100%


Latvia LV_PRTY n % 1. Alliance "Tçvzemei un Brîvîbai"/LNNK 18 1,8 2. The political organisation -For Human Rights in United Latvi 63 6,3 3. Social-democratic wellfare party 2 0,2 5. Latvian Social Democratic Workers’ Party (LSDSP) 11 1,1 7. Jaunais laiks 123 12,3 8. The People´s party 45 4,5 9. Latvia´s First Party 17 1,7 13. Social Democratic Union + SDS 2 0,2 15. Union -Latvia´s Way 17 1,7 18. Latgales Gaisma 1 0,1 20. Political organisation "Green and Farmer union" 27 2,7 96. No vote 445 44,5 97. Refused 46 4,6 98. DK 183 18,3 (N) 1000 100% New Zealand NZ_PRTY n % 1. ACT 40 3,9 2. Alliance 9 0,9 3. Green 45 4,3 4. Labour 283 27,3 5. National 147 14,2 6. New Zealand First 67 6,5 7. Progressive Coalition 2 0,2 8. United Future 41 4,0 9. Undocumented 17 1,6 96. Didnt vote/not eligible 65 6,3 98. Dont know/Cant remember 47 4,5 99. NA 273 26,4 (N) 1036 100% Norway NO_PRTY n % 1. Red Electoral All 21 1,4 2. Labour Party 317 21,6 3. Progress Party 258 17,6 4. Conserv Party 198 13,5 5. Christ Democr Party 60 4,1 6. Centre party 78 5,3 7. Socialist Left 213 14,5 8. Liberal 35 2,4 95. Other Party 15 1,0 96. No party preference;wouldnt vote 65 4,4 98. Dont know 186 12,7 99. NA 23 1,6 (N) 1469 100%


Poland PL_PRTY n % 1. SLD-UP: Democratic left alliance/labour union 182 22,2 2. AWS: Solidarity election action 44 5,4 3. UW: Freedom union 57 7,0 4. Lepper´s self-defense trade union 62 7,6 5. PiS: Law and justice party 63 7,7 6. PSL: Polish peasants party 46 5,6 7. PO: Civic platform of the rep of Poland 85 10,4 9. PWN: Polish national fellowship 1 0,1 10. LPR: League of polish families 49 6,0 11. German minority 3 0,4 13. PUG: Polish economic union 3 0,4 95. Other list 11 1,3 98. Don´t know 210 25,7 99. No answer 2 0,2 (N) 818 100% Portugal PT_PRTY n % 1. Bloco de Esquerda 62 3,9 2. CDS/PP 18 1,1 3. CDU-PCP 91 5,7 5. PPD/PSD 290 18,1 6. PS 419 26,2 7. PSR 2 0,1 8. UDP 1 0,1 95. Other 4 0,2 96. None, no preference 518 32,3 99. NA 197 12,3 (N) 1602 100%


Philippines PH_PRTY n %

1. Lakas NUCD-UMDP(Lakas ng tao-National Union of Christian de) 33 2,8 2. LDP(Laban ng Demokratikong Pilipino) 7 0,6 3. NPC(Nationalists Peoples Coalition) 7 0,6 5. LP(Liberal Party) 17 1,4 6. NP(Nacionalista Party) 4 0,3 8. PDSP(Partido Demokratiko sosyalista ng pilipinas) 1 0,1 10. PMP(Partido ng Masang Pilipino) 8 0,7 16. Reforma 3 0,2 18. Estrada Party 14 1,2 19. Raul Roco Party 1 0,1 21. Miriam defensor party 1 0,1 22. Arroyo Party 9 0,8 25. OSME¥A PARTY 5 0,4 26. Mayor romanate in tubod Party 1 0,1 33. Ted Failon Party 1 0,1 34. Ibanez Party 1 0,1 35. Promdi 1 0,1 36. FPJ(Colonia Brigade) 1 0,1 38. BOPK(Bando Osme¥a Pondok Kaliswagan) 2 0,2 41. Robert Barbers Party 1 0,1 42. PPC 3 0,2 43. Balani 2 0,2 44. Mayor Parohinog Party 1 0,1 56. Lammp 1 0,1 57. Mayor of placer party 1 0,1 60. Professional Criminilogist Association Phil. 1 0,1 61. Drilon Party 1 0,1 62. Danding Party 1 0,1 63. Cory Party 1 0,1 64. Enrile Party 1 0,1 96. None 1069 89,1 (N) 1200 100% Russia RU_PRTY n % 1. Agrarian Party 11 0,5 2. Women of Russia 71 3,0 3. Yabloko 84 3,5 4. Unated Russia 305 12,8 5. LDPR 86 3,6 6. KPRF 219 9,2 7. Union of right forces 64 2,7 95. Other Party 119 5,0 96. Would not vote;no party preference 186 7,8 98. Dont know 1238 52,0 (N) 2383 100%


Slovakia SK_PRTY n % 1. S. Bernat (KSS) 7 0,6 2. M. Butora (Civic org.) 66 5,7 3. I. Gasparovic (HZD) 244 21,2 4. J. Kalman (Ind.) 5 0,4 5. J. Kralik (SDL) 9 0,8 6. J. Kubik (Ind.) 3 0,3 7. E. Kukan (SDKU) 175 15,2 8. V. Meciar (HZDS-LS) 183 15,9 9. F. Miklosko (KDH) 49 4,3 10. R. Schuster (Former President) 43 3,7 11. J. Sestak (Ind.) 3 0,3 96. Abstain, no party preference 338 29,3 99. NA 27 2,3 (N) 1152 100% Slovenia SI_PRTY n % 1. Democratic ret DESUS 35 3,2 2. Liberal Democrat LDS 319 29,2 3. Peoples party SLS 64 5,9 4. Slovenian Nation SNS 26 2,4 5. Social Democratic SDS 94 8,6 6. NSI - New Slovenia 55 5,0 7. Combined list ZLSD 87 8,0 8. Youth party SMS 36 3,3 95. Other Party 31 2,8 96. Would not vote;No party preference 45 4,1 97. Refused 202 18,5 98. Dont know 99 9,1 (N) 1093 100% South Africa ZA_PRTY n % (N) 0 100% South Korea KR_PRTY n % 1. United Liberal Democrats 12 0,9 2. Grand National Party 226 17,2 3. National Alliance 21 22 1,7 4. Millennium Democratic Party 249 18,9 5. People´s party for reform 18 1,4 6. Democratic Labor Party 65 4,9 7. No party affiliation 635 48,3 8. The Uri Party 5 0,4 95. Other party 6 0,5 98. DK 77 5,9 (N) 1315 100%


Spain ES_PRTY n % 1. Popular Party (Partido Popular - PP) 332 27,4 2. Socialist Party (Partido Socialista Obrero Español - PSOE) 369 30,4 3. Communist Party (Izquierda Unida - IU) 65 5,4 4. Regional Party of Center (Part Nac de Centro y Derecha) 52 4,3 5. Regional Party of Left (Partidos Nacionalistas de Izquierda) 33 2,7 6. Ecologist Party (Ecologistas - Verdes) 19 1,6 94. White (En Blanco) 27 2,2 95. Other Party (Otros) 2 0,2 96. No vote (No votará) 133 11,0 98. Don´t Know (NS) 105 8,7 99. No answer (NC) 75 6,2 (N) 1212 100% Sweden SE_PRTY n % 1. C (Centre Party) 71 6,0 2. FP (Liberals) 144 12,1 3. KD (Christ Democr) 91 7,7 4. MP (Ecologists) 56 4,7 5. M (Liberal Conserv) 158 13,3 6. S (Social Democrats) 431 36,3 7. V (Socialists) 106 8,9 95. Other Party 64 5,4 99. NA 65 5,5 (N) 1186 100% Switzerland CH_PRTY n % 1. Christian Democratic Party 46 4,4 2. Evangelical Peoples Party 6 0,6 3. Radical Party 93 9,0 4. Social Democratic Party 147 14,2 5. Swiss Peoples Party 69 6,7 6. Independent Party 2 0,2 7. Liberal Party 9 0,9 8. Labour Party 5 0,5 9. Swiss Democrats 7 0,7 10. Green Party 62 6,0 95. Other Party 8 0,8 96. No party preference 552 53,2 98. Not interested so much in politics 11 1,1 99. NA 20 1,9 (N) 1037 100%


Taiwan TW_PRTY n % 1. KuoMinTang 170 8,4 2. Democratic Progressive Party 38 1,9 3. People Frist Party 12 0,6 95. Other Party 6 0,3 96. None 1775 88,0 97. Refuse to answer which party 13 0,6 98. Refused 2 0,1 (N) 2016 100% United States US_PRTY n % 1. Strong democrat 212 17,4 2. N very strong democrat 203 16,7 3. Indep,close democrat 108 8,9 4. Independent 204 16,8 5. Indep,close republic 115 9,5 6. N very strong republic 178 14,6 7. Strong republican 182 15,0 95. Other party 9 0,7 99. No answer 5 0,4 (N) 1216 100% Uruguay UY_PRTY n % 1. Red Party 129 11,6 2. National Party 230 20,8 3. Wide front Party 454 41,0 4. Independent Party 6 0,5 5. Liberal Party 1 0,1 95. Other Party 2 0,2 96. No party preference 275 24,8 99. NA 11 1,0 (N) 1108 100% Venezuela VE_PRTY n % 1. AD (Soc-Democr) 126 10,5 2. Copei (Cons) 42 3,5 3. MAS (Center left) 17 1,4 4. MVR (Left) 350 29,2 5. Proyecto Venezuela (Liberal) 69 5,8 6. Primero Justicia (Liberal) 69 5,8 7. PPT (Center left) 13 1,1 8. Causa R (Left) 5 0,4 9. Convergencia (Cons) 8 0,7 10. Chavista (Left) 18 1,5 95. Others 8 0,7 96. None 456 38,0 98. Dont know 13 1,1 99. Na 5 0,4 (N) 1199 100%


VOTE_LE: R: Vote last election: yes, no Missing Values: 0;8;9 Vote_LE. Did you vote in last election? 1. 1. Yes. 2. No. 0. Not applicable, not available. 8. Don't know. 9. No answer. NOTES: (1) Not asked in South Africa


0 1 2 8 9

VOTE_LE (N) % % % % % 2101 41

Australia (AU) 2183 98,10% 1,90% 41M601 158

Austria (AT) 1006 79,20% 20,80% 247M766 250

Bulgaria (BG) 1069 75,40% 24,60% 53M1066 109

Canada (CA) 1211 90,70% 9,30% 36M1116 368

Chile (CL) 1505 75,20% 24,80% 21M717 464

Czech Republic (CZ) 1276 60,70% 39,30% 95M1231 84

Denmark (DK) 1322 93,60% 6,40% 7M1037 240

Finland (FI) 1379 71M 81,20% 18,80% 31M1348 206

France (FR) 1669 86,70% 13,30% 115M647 102

Germany-West (DE-W) 850 85M 86,40% 13,60% 16M342 65

Germany-East (DE-E) 437 25M 84,00% 16,00% 5M598 250

Great Britain (GB) 873 25M 70,50% 29,50% 864 148

Hungary (HU) 1021 85,40% 14,60% 9M875 189

Ireland (IE) 1065 82,20% 17,80% 1M920 141

Israel Jews (IL-J) 1066 86,70% 13,30% 5M133 18

Israel Arabs (IL-A) 152 88,10% 11,90% 1M817 222

Japan (JP) 1102 59M 78,60% 21,40% 4M637 209

Latvia (LV) 1000 138M 75,30% 24,70% 16M935 48

New Zealand (NZ) 1036 95,10% 4,90% 53M1164 220

Norway (NO) 1469 68M 84,10% 15,90% 17M819 401

Poland (PL) 1277 67,10% 32,90% 57M1154 411

Portugal (PT) 1602 73,70% 26,30% 16M 21M951 243

Philippines (PH) 1200 79,60% 20,40% 6M1401 967

Russia (RU) 2383 59,20% 40,80% 15M807 345

Slovak Republic (SK) 1152 70,10% 29,90% 843 178

Slovenia (SI) 1093 82,60% 17,40% 72M

South Africa (ZA) 2483 2483M - - 1059 196

South Korea (KR) 1315 50M 84,40% 15,60% 10M817 239

Spain (ES) 1212 77,40% 22,60% 33M 123M1018 159

Sweden (SE) 1186 86,50% 13,50% 9M539 295


Taiwan (TW) 2016 77,70% 22,30% 12M771 438

United States (US) 1216 63,80% 36,20% 7M954 152

Uruguay (UY) 1108 86,30% 13,70% 2M607 587

Venezuela (VE) 1199 50,80% 49,20% 1M 4MSum 44170 3004M 31212 8590 222M 1142M


RELIG: Religious denomination Missing Values: 000;997;998;999 Relig. Religious denomination. 000. No religion. 423. Filipinista. 100. Roman Catholic. 424. Iglesia ng Dios. 110. Greek Catholic. 429. Kristohanon. 200. Protestant (evangelische) free church. 430. Apostle Twelve. 210. Anglican,Ch Engl,Episcopal. 431. African Evangelical. 220. Baptists. 432. Duthc Reform. 230. Congregationalists. 433. Full Gospel Church of God. 240. Mennonite. 434. Faith Mission. 250. Lutheran, evangelical church. 435. St Johns Apostolic. 260. Methodist. 436. Nazareth. 270. Pentecostal, ZA: Pentecostal Holiness Church. 437. Zionist Christian Church. 280. Presbyterian,Ch of Scot. 444. Wesleyan. 289. Universal Church of God. 448. Camacop Alliance. 290. Other Protestants (no spec.rel). 457. Faith Tabernacle. 291. Brethren. 490. Unspecified Christian Groups. 292. Mormon. 491. Jehova´s Witness. 293. Salvation Army. 500. Jewish. 294. Assemblies of God. 530. Reform. 295. Seventh Day Adventists. 590. Jewish Religion general. 296. Hussites. 600. Islam. 297. Unitarians,AUS:Uniting church. 670. Druse. 298. United Church CDN. 690. Muslim,Mohammedan,Islam. 299. Church of God and Saint of Christ. 700. Buddhists. 300. Orthodox; Eastern Orthodox. 790. Buddhism general. 310. Greek Orthodox. 800. Hinduism. 320. Russian Orthodox. 820. Sikhism. 390. Orthodox (no spec. mentioned). 890. Hinduism general. 400. Other Christian Groups. 900. Other Asian Religion. 401. Aglipayan. 901. Shintoism. 402. Born Again. 902. Taoism. 405. United Church of Christ in the Phils. 950. Other East Asian Religion. 407. Dating Daan. 960. Other Religions. 412. Christians. 961. Ratana/Ringatu. 413. Espiritista. 997. Refused. 414. Iglesia ni Cristo. 998. Don't know. 415. Church of Christ. 999. No answer. 418. Evangelical Christian.


0 100 110 200 210 220 230 240 250 260 270 280

RELIG (N) % % % % % % % % % % % % 547 501 31 24 24 68

Australia (AU) 2183 549M 36,30% - - 33,30% 2,10% - - 1,60% - 1,60% 4,50%724 54

Austria (AT) 1006 149M 87,00% - 6,50% - - - - - - - -8 3

Bulgaria (BG) 1069 75M 0,80% - 0,30% - - - - - - - -471 4 14 76 21 9 17 8 27

Canada (CA) 1211 147M 56,50% 0,50% 1,70% 9,10% 2,50% - 1,10% 2,00% - 1,00% 3,20%1095 3 8 1 38 73 2

Chile (CL) 1505 95M 78,90% - - 0,20% 0,60% 0,10% - - 2,70% 5,30% 0,10%368 19

Czech Republic (CZ) 1276 696M 86,20% - - - - - - 4,40% - - -7 1146

Denmark (DK) 1322 129M 0,60% - - - - - - 97,50% - - -1134

Finland (FI) 1379 191M - - - - - - - 95,90% - - -911 31

France (FR) 1669 580M 91,70% - 3,10% - - - - - - - -345 305

Germany-West (DE-W) 850 129M 48,10% - - - - - - 42,50% - - -15 102

Germany-East (DE-E) 437 313M 12,20% - - - - - - 82,90% - - -84 236 10 3 15 36

Great Britain (GB) 873 385M 17,30% - - 48,60% 2,10% 0,60% - - 3,10% - 7,40%688 19 169 47

Hungary (HU) 1021 73,60% 2,00% 18,10% - - - - 5,00% - - -930 1 26 2 6

Ireland (IE) 1065 50M 95,00% - 0,10% 2,70% - - - - 0,20% - 0,60%12

Israel Jews (IL-J) 1066 1,10% - - - - - - - - - -6

Israel Arabs (IL-A) 152 3,90% - - - - - - - - - -

Japan (JP) 1102 648M - - - - - - - - - - -197 3 232

Latvia (LV) 1000 329M 29,60% - - - 0,50% - - 34,90% - - -133 9 221 19 1 36 9 137

New Zealand (NZ) 1036 258M 17,90% - 1,20% 29,70% 2,60% - - 0,10% 4,80% 1,20% 18,40%12 1216 16

Norway (NO) 1469 139M 0,90% - - - - - - 93,10% - 1,20% -1155 6

Poland (PL) 1277 104M 98,50% - 0,50% - - - - - - - -1395 6

Portugal (PT) 1602 132M 95,60% - 0,40% - - - - - - - -986 23 11 2 10

Philippines (PH) 1200 1M 82,20% - 1,90% - 0,90% - - - 0,20% 0,80% -7 3

Russia (RU) 2383 448M 0,40% - 0,20% - - - - - - - -734 44 27 103

Slovak Republic (SK) 1152 146M 79,60% 4,80% 2,90% - - - - 11,20% - - -770 8

Slovenia (SI) 1093 226M 93,60% - - - - - - 1,00% - - -148 90 23 32 55 140 21

South Africa (ZA) 2483 233M 6,80% - - 4,10% 1,10% 1,50% - 2,50% 6,40% 1,00% -147 267

South Korea (KR) 1315 564M 19,60% - 35,60% - - - - - - - -1090 1 3

Spain (ES) 1212 109M 99,30% - 0,10% - - - - 0,30% - - -9 793

Sweden (SE) 1186 335M 1,10% - 95,70% - - - - - - - -378 456 1 1

Switzerland (CH) 1037 125M 41,50% - 50,10% 0,10% - - - - 0,10% - -27 87

Taiwan (TW) 2016 401M 1,70% - 5,40% - - - - - - - -288 162 29 209 5 51 89 22 24

United States (US) 1216 170M 27,60% - 15,50% 2,80% 20,00% 0,50% - 4,90% 8,50% 2,10% 2,30%558 63 1 1 1 3

Uruguay (UY) 1108 372M 75,90% - 8,60% - 0,10% - - 0,10% 0,10% 0,40% -902 8

Venezuela (VE) 1199 92M 81,50% - 0,70% - - - - - - - -Sum 44170 8320M 15147 67 2183 1183 336 41 9 4464 324 186 300


289 290 291 292 293 294 295 296 297 298 299 300

RELIG (N) % % % % % % % % % % % % 1 2 2 5 1 6 155

Australia (AU) 2183 - 0,10% 0,10% 0,10% 0,30% 0,10% 0,40% - 10,30% - - -

Austria (AT) 1006 - - - - - - - - - - - -858

Bulgaria (BG) 1069 - - - - - - - - - - - 87,20%25 5 1 1 1 3 86

Canada (CA) 1211 - 3,00% - 0,60% 0,10% 0,10% 0,10% - 0,40% 10,30% - -83

Chile (CL) 1505 - 6,00% - - - - - - - - - -32

Czech Republic (CZ) 1276 - - - - - - - 7,50% - - - -

Denmark (DK) 1322 - - - - - - - - - - - -11

Finland (FI) 1379 - - - - - - - - - - - 0,90%5

France (FR) 1669 - - - - - - - - - - - 0,50%12

Germany-West (DE-W) 850 - 1,70% - - - - - - - - - -4

Germany-East (DE-E) 437 - 3,30% - - - - - - - - - -10

Great Britain (GB) 873 - 2,10% - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -2

Ireland (IE) 1065 - 0,20% - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -5 2

Latvia (LV) 1000 - 0,80% - - - - 0,30% - - - - -9 9 4 1 2

New Zealand (NZ) 1036 - - 1,20% 1,20% 0,50% 0,10% 0,30% - - - - -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -4 10

Philippines (PH) 1200 - - - 0,30% - - 0,80% - - - - -

Russia (RU) 2383 - - - - - - - - - - - -7

Slovak Republic (SK) 1152 - - - - - - - - - - - 0,80%

Slovenia (SI) 1093 - - - - - - - - - - - -9 4 37 18 18

South Africa (ZA) 2483 0,40% - - - 0,20% 1,70% 0,80% - - - 0,80% -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -8

Sweden (SE) 1186 - - - - - - - - - - - 1,00%7

Switzerland (CH) 1037 - - - - - - - - - - - 0,80%

Taiwan (TW) 2016 - - - - - - - - - - - -22 8 2 6

United States (US) 1216 - - - 2,10% - 0,80% 0,20% - 0,60% - - -1 13

Uruguay (UY) 1108 - - 0,10% 1,80% - - - - - - - -55

Venezuela (VE) 1199 - - - - - - - - - - - 5,00%Sum 44170 9 142 12 55 14 48 41 32 164 86 18 951


310 320 390 400 401 402 405 407 412 413 414 415

RELIG (N) % % % % % % % % % % % % 1 40 11

Australia (AU) 2183 0,10% - 2,70% 0,70% - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -3

Canada (CA) 1211 - - - - - 0,40% - - - - - -36

Chile (CL) 1505 - - - 2,60% - - - - - - - -7

Czech Republic (CZ) 1276 - - - 1,60% - - - - - - - -

Denmark (DK) 1322 - - - - - - - - - - - -29

Finland (FI) 1379 - - - 2,50% - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -3

Great Britain (GB) 873 - - - 0,60% - - - - - - - -1

Hungary (HU) 1021 0,10% - - - - - - - - - - -2

Ireland (IE) 1065 - - - 0,20% - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -190 2

Latvia (LV) 1000 - 28,60% - 0,30% - - - - - - - -3 72

New Zealand (NZ) 1036 - - 0,40% - - - - - 9,70% - - -42

Norway (NO) 1469 - - - 3,20% - - - - - - - -3 4

Poland (PL) 1277 - 0,30% - 0,30% - - - - - - - -52

Portugal (PT) 1602 - - - 3,60% - - - - - - - -4 10 23 1 1 3 2 34 3

Philippines (PH) 1200 - - - 0,30% 0,80% 1,90% 0,10% 0,10% 0,30% 0,20% 2,80% 0,30%1731

Russia (RU) 2383 - 92,20% - - - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - - -25 5

Slovenia (SI) 1093 - - 3,00% 0,60% - - - - - - - -38 263

South Africa (ZA) 2483 - - - 1,70% - - - - 12,10% - - -

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -7

Sweden (SE) 1186 - - - 0,80% - - - - - - - -32

Switzerland (CH) 1037 - - - 3,50% - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -8 29

United States (US) 1216 - - 0,80% 2,80% - - - - - - - -1

Uruguay (UY) 1108 - - 0,10% - - - - - - - - -122

Venezuela (VE) 1199 - - - 11,00% - - - - - - - -Sum 44170 2 1924 77 425 10 26 1 1 338 2 34 3


418 423 424 429 430 431 432 433 434 435 436 437

RELIG (N) % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - -

Canada (CA) 1211 - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - -

Denmark (DK) 1322 - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - -

Germany-West (DE-W) 850 - - - - - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - -

Ireland (IE) 1065 - - - - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - -

Latvia (LV) 1000 - - - - - - - - - - - -

New Zealand (NZ) 1036 - - - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - -2 2 2 3 1

Philippines (PH) 1200 0,20% 0,20% 0,20% 0,30% - - - 0,10% - - - -

Russia (RU) 2383 - - - - - - - - - - - -


Slovenia (SI) 1093 - - - - - - - - - - - -109 30 221 32 37 32 33 240

South Africa (ZA) 2483 - - - - 5,00% 1,40% 10,20% 1,50% 1,70% 1,50% 1,50% 11,00%

South Korea (KR) 1315 - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - -

United States (US) 1216 - - - - - - - - - - - -

Uruguay (UY) 1108 - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - -Sum 44170 2 2 2 3 109 30 221 33 37 32 33 240


444 448 457 490 491 500 530 590 600 670 690 700

RELIG (N) % % % % % % % % % % % % 20 7 11

Australia (AU) 2183 - - - 1,30% - 0,50% - - 0,70% - - -22

Austria (AT) 1006 - - - - - - - - 2,60% - - -109

Bulgaria (BG) 1069 - - - - - - - - - - 11,10% -4 4 2 3

Canada (CA) 1211 - - - - - 0,50% 0,50% - - - 0,20% 0,40%30 1 1

Chile (CL) 1505 - - - 2,20% - - - 0,10% - - - 0,10%


Denmark (DK) 1322 - - - - - - - - 0,40% - - -

Finland (FI) 1379 - - - - - - - - - - - -9 25

France (FR) 1669 - - - - - 0,90% - - 2,50% - - -19 1 28

Germany-West (DE-W) 850 - - - 2,60% - - - 0,10% - - 3,90% -1

Germany-East (DE-E) 437 - - - - - - - - - - 0,80% -57 8 12 1

Great Britain (GB) 873 - - - 11,70% - 1,60% - - 2,50% - - 0,20%2

Hungary (HU) 1021 - - - - - 0,20% - - - - - -10

Ireland (IE) 1065 - - - 1,00% - - - - - - - -1028 1

Israel Jews (IL-J) 1066 - - - - - 96,40% - - 0,10% - - -128 18

Israel Arabs (IL-A) 152 - - - - - - - - 84,20% 11,80% - -13

Japan (JP) 1102 - - - 3,10% - - - - - - - -4 2

Latvia (LV) 1000 - - - - - - - 0,60% 0,30% - - -3 1 6 11

New Zealand (NZ) 1036 - - - - 0,40% 0,10% - - - - 0,80% 1,50%15

Norway (NO) 1469 - - - - - - - - 1,10% - - -2 1 1

Poland (PL) 1277 - - - 0,20% - - - - 0,10% - - 0,10%1 2

Portugal (PT) 1602 - - - - - 0,10% - - 0,10% - - -1 2 1 2 51

Philippines (PH) 1200 0,10% 0,20% 0,10% - 0,20% - - - 4,30% - - -4 112

Russia (RU) 2383 - - - - - 0,20% - - 6,00% - - -6 1

Slovak Republic (SK) 1152 - - - 0,70% - 0,10% - - - - - -15

Slovenia (SI) 1093 - - - - - - - - - - 1,80% -17 1 80 1

South Africa (ZA) 2483 - - - - 0,80% % - - - - 3,70% %313

South Korea (KR) 1315 - - - - - - - - - - - 41,70%1 2 1

Spain (ES) 1212 - - - 0,10% 0,20% - - - - - 0,10% -1 5

Sweden (SE) 1186 - - - - - 0,10% - - 0,60% - - -4 18 5

Switzerland (CH) 1037 - - - - - 0,40% - - 2,00% - - 0,50%

Taiwan (TW) 2016 - - - - - - - - - - - -32 8 5

United States (US) 1216 - - - - - 3,10% - - 0,80% - - 0,50%20 5

Uruguay (UY) 1108 - - - 2,70% - - - 0,70% - - - -1 1 1

Venezuela (VE) 1199 - - - - - 0,10% - - 0,10% - - 0,10%Sum 44170 1 2 1 178 24 1104 4 11 419 18 242 342


790 800 820 890 900 901 902 950 960 961 962

RELIG (N) % % % % % % % % % % % 27 14 7

Australia (AU) 2183 1,80% 0,90% - - - - - - 0,50% - - 32

Austria (AT) 1006 - - - - - - - - 3,80% - - 6

Bulgaria (BG) 1069 - - - - - - - - 0,60% - - 1 48

Canada (CA) 1211 - 0,10% - - - - - - 5,80% - - 1 16

Chile (CL) 1505 - - - - - 0,10% - - 1,20% - - 1

Czech Republic (CZ) 1276 - - - - - - - - 0,20% - - 17

Denmark (DK) 1322 - - - - - - - - 1,40% - - 8

Finland (FI) 1379 - - - - - - - - 0,70% - - 12

France (FR) 1669 - - - - - - - - 1,20% - - 3 1 3

Germany-West (DE-W) 850 0,40% - - 0,10% - - - - 0,40% - - 1

Germany-East (DE-E) 437 - - - - - - - - 0,80% - - 7 2 2

Great Britain (GB) 873 - 1,40% 0,40% - - - - - 0,40% - - 9

Hungary (HU) 1021 - - - - - - - - 1,00% - -

Ireland (IE) 1065 - - - - - - - - - - - 25

Israel Jews (IL-J) 1066 - - - - - - - - 2,30% - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - 376 21 15

Japan (JP) 1102 88,50% - - - - 4,90% - - 3,50% - - 28

Latvia (LV) 1000 - - - - - - - - 4,20% - - 8 24 27

New Zealand (NZ) 1036 - 1,10% - - - - - - 3,20% 3,60% - 5

Norway (NO) 1469 - - - - - - - - 0,40% - -

Poland (PL) 1277 - - - - - - - - - - - 3

Portugal (PT) 1602 - - - - - - - - 0,20% - - 1

Philippines (PH) 1200 0,10% - - - - - - - - - - 4 17

Russia (RU) 2383 0,20% - - - - - - - 0,90% - -


Slovenia (SI) 1093 - - - - - - - - - - - 113 329

South Africa (ZA) 2483 - 5,20% - - - - - - 15,10% - - 23

South Korea (KR) 1315 - - - - - - - - 3,10% - -

Spain (ES) 1212 - - - - - - - - - - - 1 5

Sweden (SE) 1186 - 0,10% - - - - - - 0,60% - - 4 4

Switzerland (CH) 1037 - 0,40% - - - - - - 0,40% - - 418 159 918 6

Taiwan (TW) 2016 25,90% - - - - - 9,80% 56,80% 0,40% - - 7 5 33 1

United States (US) 1216 - 0,70% - - 0,50% - - - 3,20% - 0,10% 1 1 66

Uruguay (UY) 1108 0,10% - - - 0,10% - - - 9,00% - - 2 15

Venezuela (VE) 1199 - 0,20% - - - - - - 1,40% - - Sum 44170 830 157 2 1 6 22 159 918 760 27 1


997 998 999

RELIG (N) % % %

Australia (AU) 2183 - 129M

Austria (AT) 1006 - 3M 22M

Bulgaria (BG) 1069 - 10M

Canada (CA) 1211 - 230M

Chile (CL) 1505 - 5M 17M

Czech Republic (CZ) 1276 - 17M 136M

Denmark (DK) 1322 - 9M 9M

Finland (FI) 1379 - 6M

France (FR) 1669 - 3M 93M

Germany-West (DE-W) 850 - 4M

Germany-East (DE-E) 437 - 1M

Great Britain (GB) 873 - 1M 1M

Hungary (HU) 1021 - 4M 82M

Ireland (IE) 1065 - 1M 35M

Israel Jews (IL-J) 1066 -

Israel Arabs (IL-A) 152 -

Japan (JP) 1102 - 8M 21M

Latvia (LV) 1000 - 6M

New Zealand (NZ) 1036 - 33M

Norway (NO) 1469 - 24M

Poland (PL) 1277 - 1M

Portugal (PT) 1602 - 1M 10M 4

Philippines (PH) 1200 0,30%

Russia (RU) 2383 - 57M

Slovak Republic (SK) 1152 - 16M 68M

Slovenia (SI) 1093 - 4M 40M 5

South Africa (ZA) 2483 0,20% 5M 69M

South Korea (KR) 1315 - 1M

Spain (ES) 1212 - 5M

Sweden (SE) 1186 - 3M 19M

Switzerland (CH) 1037 - 1M 1M

Taiwan (TW) 2016 -

United States (US) 1216 - 1M

Uruguay (UY) 1108 - 1M

Venezuela (VE) 1199 - Sum 44170 9 138M 1075M


RELIGGRP: R: Religious main groups (derived) Missing Values: 97;98;99 Religgrp. Religious denomination. 01. No religion. 02. Roman Catholic. 03. Protestant. 04. Christian Orthodox. 05. Jewish. 06. Islam. 07. Buddhism. 08. Hinduism. 09. Other Christian Religions. 10. Other Eastern Religions. 11. Other Religions. 97. Refused. 98. Don't know. 99. No answer.


1 2 3 4 5 6 7 8 9 10 11 97 98 99

RELIGGRP (N) % % % % % % % % % % % % % % 549 547 820 41 7 11 27 14 31 7

Australia (AU) 2183 26,70% 26,60% 39,90% 2,00% 0,30% 0,50% 1,30% 0,70% 1,50% - 0,30% - 129M149 724 54 22 32

Austria (AT) 1006 15,20% 73,80% 5,50% - - 2,20% - - - - 3,30% - 3M 22M75 8 3 858 109 6

Bulgaria (BG) 1069 7,10% 0,80% 0,30% 81,00% - 10,30% - - - - 0,60% - 10M147 475 288 4 2 3 1 8 53

Canada (CA) 1211 15,00% 48,40% 29,40% - 0,40% 0,20% 0,30% 0,10% 0,80% - 5,40% - 230M95 1095 208 66 1 1 1 16

Chile (CL) 1505 6,40% 73,80% 14,00% - 4,50% 0,10% - 0,10% - 0,10% 1,10% - 5M 17M696 368 51 7 1

Czech Republic (CZ) 1276 62,00% 32,80% 4,50% - - - - - 0,60% - 0,10% - 17M 136M129 7 1146 5 17

Denmark (DK) 1322 9,90% 0,50% 87,90% - - 0,40% - - - - 1,30% - 9M 9M191 1134 11 29 8

Finland (FI) 1379 13,90% - 82,60% 0,80% - - - - 2,10% - 0,60% - 6M580 911 31 5 9 25 12

France (FR) 1669 36,90% 57,90% 2,00% 0,30% 0,60% 1,60% - - - - 0,80% - 3M 93M129 345 317 1 28 3 1 19 3

Germany-West (DE-W) 850 15,20% 40,80% 37,50% - 0,10% 3,30% 0,40% 0,10% 2,20% - 0,40% - 4M313 15 106 1 1

Germany-East (DE-E) 437 71,80% 3,40% 24,30% - - 0,20% - - - - 0,20% - 1M385 84 310 8 12 1 9 60 2

Great Britain (GB) 873 44,20% 9,60% 35,60% - 0,90% 1,40% 0,10% 1,00% 6,90% - 0,20% - 1M 1M688 216 20 2 9

Hungary (HU) 1021 - 73,60% 23,10% 2,10% 0,20% - - - - - 1,00% - 4M 82M50 930 37 12

Ireland (IE) 1065 4,90% 90,40% 3,60% - - - - - 1,20% - - - 1M 35M12 1028 1 25

Israel Jews (IL-J) 1066 - 1,10% - - 96,40% 0,10% - - - - 2,30% - 6 146

Israel Arabs (IL-A) 152 - 3,90% - - - 96,10% - - - - - - 648 376 13 21 15

Japan (JP) 1102 60,40% - - - - - 35,00% - 1,20% 2,00% 1,40% - 8M 21M329 197 231 217 2 4 10 4

Latvia (LV) 1000 33,10% 19,80% 23,20% 21,80% - 0,20% 0,40% - 1,00% - 0,40% - 6M258 133 457 3 1 6 11 8 75 51

New Zealand (NZ) 1036 25,70% 13,30% 45,60% 0,30% 0,10% 0,60% 1,10% 0,80% 7,50% - 5,10% - 33M139 12 1232 15 42 5

Norway (NO) 1469 9,60% 0,80% 85,30% - - 1,00% - - 2,90% - 0,30% - 24M104 1155 6 3 1 1 6

Poland (PL) 1277 8,20% 90,50% 0,50% 0,20% - 0,10% 0,10% - 0,50% - - - 1M132 1395 6 1 2 52 3

Portugal (PT) 1602 8,30% 87,70% 0,40% - 0,10% 0,10% - - 3,30% - 0,20% - 1M 10M1 986 46 51 1 111 4

Philippines (PH) 1200 0,10% 82,20% 3,80% - - 4,20% 0,10% - 9,20% - - 0,30% 448 7 3 1731 4 112 4 17

Russia (RU) 2383 19,30% 0,30% 0,10% 74,40% 0,20% 4,80% 0,20% - - - 0,70% - 57M 146 778 130 7 1 6

Slovak Republic (SK) 1152 13,70% 72,80% 12,20% 0,70% 0,10% - - - 0,60% - - - 16M 68M226 770 8 25 15 5

Slovenia (SI) 1093 21,50% 73,40% 0,80% 2,40% - 1,40% - - - - 0,50% - 4M 40M233 148 447 1 80 1 113 1052 329 5

South Africa (ZA) 2483 9,70% 6,10% 18,60% - % 3,30% % 4,70% 43,70% - 13,70% 0,20% 5M 69M564 147 267 313 23

South Korea (KR) 1315 42,90% 11,20% 20,30% - - - 23,80% - - - 1,80% - 1M109 1090 6 1 1

Spain (ES) 1212 9,00% 90,30% 0,50% - - 0,10% - - 0,10% - - - 5M335 9 793 8 1 5 1 7 5

Sweden (SE) 1186 28,80% 0,80% 68,10% 0,70% 0,10% 0,40% - 0,10% 0,60% - 0,40% - 3M 19M125 378 456 7 4 18 5 4 34 4

Switzerland (CH) 1037 12,10% 36,50% 44,10% 0,70% 0,40% 1,70% 0,50% 0,40% 3,30% - 0,40% - 1M 1M401 27 87 418 1077 6

Taiwan (TW) 2016 19,90% 1,30% 4,30% - - - 20,70% - - 53,40% 0,30% - 170 288 625 8 32 8 5 7 33 5 34

United States (US) 1216 14,00% 23,70% 51,40% 0,70% 2,60% 0,70% 0,40% 0,60% 2,70% 0,40% 2,80% - 1M372 558 83 1 5 1 20 1 66

Uruguay (UY) 1108 33,60% 50,40% 7,50% 0,10% 0,50% - 0,10% - 1,80% 0,10% 6,00% - 1M92 902 8 55 1 1 1 2 122 15

Venezuela (VE) 1199 7,70% 75,20% 0,70% 4,60% 0,10% 0,10% 0,10% 0,20% 10,20% - 1,30% - Sum 44170 8320 15195 9612 3000 1176 680 1175 161 1750 1105 774 9 138M 1075M


ATTEND: Religious services - how often Missing Values: 00;97;98;99 Attend. Attendance of religious services. 01. Several times a week. 02. Once a week. 03. 2 or 3 times a month. 04. Once a month. 05. Sev times a year. 06. Once a year. 07. Less frequently. 08. Never. 00. NAP; No religion; Not asked 97. Refused. 98. DK, varies too much. 99. No answer.


0 1 2 3 4 5 6 7 8 97 98 99ATTEND (N) % % % % % % % % % % % %

89 228 62 48 307 218 421 373Australia (AU) 2183 363M 5,10% 13,10% 3,60% 2,70% 17,60% 12,50% 24,10% 21,40% - 74M

16 105 62 95 233 64 201 101 22 Austria (AT) 1006 97M 1,80% 11,70% 6,90% 10,60% 25,90% 7,10% 22,40% 11,20% 2,40% 10M

15 33 27 61 375 111 165 203Bulgaria (BG) 1069 61M 1,50% 3,30% 2,70% 6,20% 37,90% 11,20% 16,70% 20,50% - 18M

293 98 49 159 272 123Canada (CA) 1211 217M 29,50% - 9,90% 4,90% 16,00% - 27,40% 12,40% -

121 212 127 128 339 118 181 181 3 Chile (CL) 1505 75M 8,60% 15,00% 9,00% 9,10% 24,00% 8,40% 12,80% 12,80% 0,20% 20M

18 58 28 34 124 110 168 104Czech Republic (CZ) 1276 563M 2,80% 9,00% 4,30% 5,30% 19,30% 17,10% 26,10% 16,10% - 27M 42M

7 10 25 37 328 287 330 169Denmark (DK) 1322 77M 0,60% 0,80% 2,10% 3,10% 27,50% 24,10% 27,70% 14,20% - 40M 12M

24 33 32 21 302 327 460 56 27 Finland (FI) 1379 69M 1,90% 2,60% 2,50% 1,60% 23,60% 25,50% 35,90% 4,40% 2,10% 17M 11M

126 48 30 223 291 268France (FR) 1669 439M 12,80% - 4,90% 3,00% 22,60% - 29,50% 27,20% - 145M 99M

18 97 106 145 277 114Germany-West (DE-W) 850 90M 2,40% 12,80% 14,00% - 19,20% - 36,60% 15,10% - 3M

2 6 12 29 99 23Germany-East (DE-E) 437 265M 1,20% 3,50% 7,00% - 17,00% - 57,90% 13,50% - 1M

98 20 40 98 26 456Great Britain (GB) 873 125M - 13,30% 2,70% 5,40% 13,30% 3,50% 61,80% - - 7M 3M

21 83 36 38 163 110 215 346 9 Hungary (HU) 1021 2,10% 8,10% 3,50% 3,70% 16,00% 10,80% 21,10% 33,90% 0,90%

107 518 91 58 159 39 26 17 1 Ireland (IE) 1065 12M 10,50% 51,00% 9,00% 5,70% 15,60% 3,80% 2,60% 1,70% 0,10% 7M 30M

148 78 32 21 255 152 81 291Israel Jews (IL-J) 1066 14,00% 7,40% 3,00% 2,00% 24,10% 14,40% 7,70% 27,50% - 8M

13 16 4 3 23 16 9 68Israel Arabs (IL-A) 152 8,60% 10,50% 2,60% 2,00% 15,10% 10,50% 5,90% 44,70% -

15 8 36 67 510 213 43 40 4 Japan (JP) 1102 137M 1,60% 0,90% 3,80% 7,20% 54,50% 22,80% 4,60% 4,30% 0,40% 5M 24M

4 21 42 62 284 158 135 32 15 Latvia (LV) 1000 223M 0,50% 2,80% 5,60% 8,20% 37,70% 21,00% 17,90% 4,20% 2,00% 23M 1M

37 111 41 31 187 106 199 108New Zealand (NZ) 1036 162M 4,50% 13,50% 5,00% 3,80% 22,80% 12,90% 24,30% 13,20% - 36M 18M

17 34 41 33 135 407 391 294Norway (NO) 1469 94M 1,30% 2,50% 3,00% 2,40% 10,00% 30,10% 28,90% 21,70% - 23M

50 492 260 102 187 67 52 24Poland (PL) 1277 36M 4,10% 39,90% 21,10% 8,30% 15,20% 5,40% 4,20% 1,90% - 7M

75 333 109 128 239 139 229 206Portugal (PT) 1602 132M 5,10% 22,80% 7,50% 8,80% 16,40% 9,50% 15,70% 14,10% - 1M 11M

154 508 229 152 99 23 30 3 1 Philippines (PH) 1200 1M 12,80% 42,40% 19,10% 12,70% 8,30% 1,90% 2,50% 0,30% 0,10%

17 37 56 86 522 262 446 558Russia (RU) 2383 399M 0,90% 1,90% 2,80% 4,30% 26,30% 13,20% 22,50% 28,10% -

93 259 74 41 162 55 132 99 20 Slovak Republic (SK) 1152 123M 9,90% 27,70% 7,90% 4,40% 17,30% 5,90% 14,10% 10,60% 2,10% 26M 68M

24 162 78 58 363 82 53 91 1 Slovenia (SI) 1093 158M 2,60% 17,80% 8,60% 6,40% 39,80% 9,00% 5,80% 10,00% 0,10% 23M

1148 299 317 81 42 121 103 10 South Africa (ZA) 2483 268M - 54,10% 14,10% 14,90% 3,80% 2,00% 5,70% 4,90% 0,50% 74M 20M

126 171 72 81 184 47 21 34South Korea (KR) 1315 565M 17,10% 23,20% 9,80% 11,00% 25,00% 6,40% 2,90% 4,60% - 14M

36 146 95 89 244 92 224 164 5 Spain (ES) 1212 68M 3,30% 13,30% 8,70% 8,10% 22,30% 8,40% 20,50% 15,00% 0,50% 6M 43M

20 24 25 25 164 188 375 163Sweden (SE) 1186 158M 2,00% 2,40% 2,50% 2,50% 16,70% 19,10% 38,10% 16,60% - 18M 26M

19 64 71 64 281 104 236 131Switzerland (CH) 1037 61M 2,00% 6,60% 7,30% 6,60% 29,00% 10,70% 24,30% 13,50% - 6M

45 76 81 55 249 243 511 530Taiwan (TW) 2016 226M 2,50% 4,20% 4,50% 3,10% 13,90% 13,60% 28,50% 29,60% -

105 271 117 87 174 180 80 102United States (US) 1216 96M 9,40% 24,30% 10,50% 7,80% 15,60% 16,10% 7,20% 9,10% - 4M

56 109 57 65 121 71 68 210Uruguay (UY) 1108 351M 7,40% 14,40% 7,50% 8,60% 16,00% 9,40% 9,00% 27,70% -

112 256 90 153 186 162 91 53Venezuela (VE) 1199 92M 10,20% 23,20% 8,20% 13,90% 16,90% 14,70% 8,30% 4,80% - 2M 2MSum 44170 5803M 2023 5805 2683 2359 7634 4219 7089 5382 118 465M 590M


TOPBOT: R:Top Bottom self-placement 10 point scale Missing Values: 00;97;98;99 Topbot. Top Bottom self-placement of respondent in a 10 point scale 1,2. 01. Lowest. 02. 03. 04. 05. 06. 07. 08. 09. 10. Highest. 0. Not applicable, Not available; Not asked 97. Refused. 98. DK, varies too much. 99. No answer. NOTES: (1) Not asked in Great Britain and South Africa (2) In Canada, the variable was derived from CLASS, with these categories:

1 The lower class 2 The working class 3 Upper working class/lower middle class 4 Middle class 5 Upper middle class 6 Upper class


0 1 2 3 4 5 6 7 8 9 10 97 98 99TOPBOT (N) % % % % % % % % % % % % % %

42 37 106 157 506 385 392 192 40 41 Australia (AU) 2183 - 2,20% 1,90% 5,60% 8,30% 26,70% 20,30% 20,70% 10,10% 2,10% 2,20% 285M

8 18 121 225 272 187 77 42 12 4 Austria (AT) 1006 - 0,80% 1,90% 12,50% 23,30% 28,20% 19,40% 8,00% 4,30% 1,20% 0,40% 40M

105 178 230 195 141 147 26 11 2 Bulgaria (BG) 1069 - 10,10% 17,20% 22,20% 18,80% 13,60% 14,20% 2,50% 1,10% 0,20% - 25M 9M

21 253 95 496 169 7 Canada (CA) 1211 - 2,00% - 24,30% - 9,10% 47,60% 16,20% - 0,70% - 1M 44M 125M

47 109 208 261 526 185 81 43 4 5 Chile (CL) 1505 - 3,20% 7,40% 14,20% 17,80% 35,80% 12,60% 5,50% 2,90% 0,30% 0,30% 18M 18M

50 104 174 243 279 170 100 41 15 3 Czech Republic (CZ) 1276 - 4,20% 8,80% 14,80% 20,60% 23,70% 14,40% 8,50% 3,50% 1,30% 0,30% 97M

9 10 30 52 264 365 314 192 31 17 Denmark (DK) 1322 - 0,70% 0,80% 2,30% 4,00% 20,60% 28,40% 24,50% 15,00% 2,40% 1,30% 38M

25 48 117 151 289 225 235 154 34 11 Finland (FI) 1379 - 1,90% 3,70% 9,10% 11,70% 22,40% 17,50% 18,20% 11,90% 2,60% 0,90% 90M

45 55 134 210 270 455 210 112 23 13 France (FR) 1669 - 2,90% 3,60% 8,80% 13,80% 17,70% 29,80% 13,80% 7,30% 1,50% 0,90% 142M

4 17 59 74 129 299 171 74 9 2 Germany-West (DE-W) 850 - 0,50% 2,00% 7,00% 8,80% 15,40% 35,70% 20,40% 8,80% 1,10% 0,20% 12M

5 17 47 62 91 125 52 25 2 2 Germany-East (DE-E) 437 - 1,20% 4,00% 11,00% 14,50% 21,30% 29,20% 12,10% 5,80% 0,50% 0,50% 9M

873 Great Britain (GB) 873 100,00% - - - - - - - - - -

25 72 160 193 313 149 56 28 4 4 Hungary (HU) 1021 - 2,50% 7,20% 15,90% 19,20% 31,20% 14,80% 5,60% 2,80% 0,40% 0,40% 17M

5 5 24 71 201 288 211 145 47 52 Ireland (IE) 1065 - 0,50% 0,50% 2,30% 6,80% 19,20% 27,50% 20,10% 13,80% 4,50% 5,00% 16M

34 18 49 71 272 168 157 150 24 63 Israel Jews (IL-J) 1066 - 3,40% 1,80% 4,90% 7,10% 27,00% 16,70% 15,60% 14,90% 2,40% 6,30% 15M 26M 19M

1 6 7 15 32 49 29 7 6 Israel Arabs (IL-A) 152 - - 0,70% 3,90% 4,60% 9,90% 21,10% 32,20% 19,10% 4,60% 3,90%

15 19 82 116 350 243 133 65 7 12 Japan (JP) 1102 - 1,40% 1,80% 7,90% 11,10% 33,60% 23,30% 12,80% 6,20% 0,70% 1,20% 60M

22 52 133 185 238 160 99 50 8 1 Latvia (LV) 1000 - 2,30% 5,50% 14,00% 19,50% 25,10% 16,90% 10,40% 5,30% 0,80% 0,10% 52M

30 14 29 48 245 271 189 108 21 19 New Zealand (NZ) 1036 - 3,10% 1,40% 3,00% 4,90% 25,20% 27,80% 19,40% 11,10% 2,20% 2,00% 62M

10 18 50 76 150 480 358 223 40 21 Norway (NO) 1469 - 0,70% 1,30% 3,50% 5,30% 10,50% 33,70% 25,10% 15,60% 2,80% 1,50% 43M

48 79 168 196 253 339 110 61 10 6 Poland (PL) 1277 - 3,80% 6,20% 13,20% 15,40% 19,90% 26,70% 8,70% 4,80% 0,80% 0,50% 1M 6M

71 132 277 336 320 171 112 45 9 3 Portugal (PT) 1602 - 4,80% 8,90% 18,80% 22,80% 21,70% 11,60% 7,60% 3,00% 0,60% 0,20% 104M 22M

58 36 92 131 446 190 96 66 26 59 Philippines (PH) 1200 - 4,80% 3,00% 7,70% 10,90% 37,20% 15,80% 8,00% 5,50% 2,20% 4,90%

292 264 442 381 350 432 116 55 13 20 Russia (RU) 2383 - 12,30% 11,20% 18,70% 16,10% 14,80% 18,30% 4,90% 2,30% 0,50% 0,80% 18M

19 39 133 168 378 218 119 55 14 4 Slovak Republic (SK) 1152 - 1,70% 3,40% 11,60% 14,60% 33,00% 19,00% 10,40% 4,80% 1,20% 0,30% 5M

24 30 81 124 421 179 116 66 8 10 Slovenia (SI) 1093 - 2,30% 2,80% 7,60% 11,70% 39,80% 16,90% 11,00% 6,20% 0,80% 0,90% 34M

2483 South Africa (ZA) 2483 100,00% - - - - - - - - - -

60 61 197 288 444 167 72 18 3 5 South Korea (KR) 1315 - 4,60% 4,60% 15,00% 21,90% 33,80% 12,70% 5,50% 1,40% 0,20% 0,40%

4 18 92 166 581 218 63 20 1 2 Spain (ES) 1212 - 0,30% 1,50% 7,90% 14,20% 49,90% 18,70% 5,40% 1,70% 0,10% 0,20% 47M

10 14 37 75 130 453 234 116 25 40 Sweden (SE) 1186 - 0,90% 1,20% 3,30% 6,60% 11,50% 39,90% 20,60% 10,20% 2,20% 3,50% 52M

10 16 66 118 242 280 178 74 20 5 Switzerland (CH) 1037 - 1,00% 1,60% 6,50% 11,70% 24,00% 27,80% 17,60% 7,30% 2,00% 0,50% 19M 9M

213 103 177 190 742 303 120 39 8 28 Taiwan (TW) 2016 - 11,10% 5,40% 9,20% 9,90% 38,60% 15,80% 6,20% 2,00% 0,40% 1,50% 93M

11 15 35 56 109 424 165 180 66 115 United States (US) 1216 - 0,90% 1,30% 3,00% 4,80% 9,30% 36,10% 14,00% 15,30% 5,60% 9,80% 22M 18M

55 77 171 192 358 144 54 27 6 7 Uruguay (UY) 1108 - 5,00% 7,10% 15,70% 17,60% 32,80% 13,20% 4,90% 2,50% 0,50% 0,60% 17M

155 59 143 124 160 426 63 36 1 7 Venezuela (VE) 1199 - 13,20% 5,00% 12,20% 10,60% 13,60% 36,30% 5,40% 3,10% 0,10% 0,60% 24M 1MSum 44170 3356 1532 1735 4123 4942 9580 8774 4697 2542 547 587 16M 335M 1404M


XX_REG: Country specific region Missing Values: 00;(98;99) or (8;9) depending on variable XX_REG. Country specific region 1 xx. Region code 00. Not available; Not asked 8/98. Don’t know 9/99. No answer NOTES: (1) Not asked in Taiwan and Venezuela Australia AU_REG n % 1. New South Wales 739 33,9 2. Victoria 569 26,1 3. Queensland 366 16,8 4. South Australia 189 8,7 5. Western Australia 186 8,5 6. Tasmania 62 2,8 7. Australian Capital Territory 42 1,9 8. Northern Territory 10 0,5 99. NA 20 0,9 (N) 2183 100% Austria AT_REG n % 1. Vorarlberg 40 4,0 2. Tirol 75 7,5 3. Salzburg 71 7,1 4. Oberoesterreich 169 16,8 5. Kaernten 76 7,6 6. Steiermark 152 15,1 7. Burgenland 37 3,7 8. Niederoesterreich 203 20,2 9. Wien 183 18,2 (N) 1006 100%


Bulgaria BG_REG n % 1. Blagoevgrad 48 4,5 2. Bourgas 56 5,2 3. Varna 61 5,7 4. Veliko Tarnovo 39 3,6 5. Vidin 16 1,5 6. Vratza 30 2,8 7. Gabrovo 23 2,2 8. Dobritch 29 2,7 9. Kardzali 39 3,6 10. Kustnedil 23 2,2 11. Lovetch 24 2,2 12. Montana 24 2,2 13. Pazardzik 45 4,2 14. Pernik 16 1,5 15. Pleven 51 4,8 16. Plovdiv 92 8,6 17. Razgrad 24 2,2 18. Rousse 33 3,1 19. Silistra 23 2,2 20. Sliven 32 3,0 21. Smolian 16 1,5 22. Sofia city 120 11,2 23. Sofia region 41 3,8 24. Stara Zagora 56 5,2 25. Targovishte 15 1,4 26. Haskovo 42 3,9 27. Shoumen 27 2,5 28. Yambol 24 2,2 (N) 1069 100% Canada CA_REG n % 1. Newfoundland 67 5,5 2. Nova Scotia 58 4,8 3. Prince Edward Island 88 7,3 4. New Brunswick 83 6,9 5. Quebec 311 25,7 6. Ontario 254 21,0 7. Manitoba 68 5,6 8. Saskatchewan 81 6,7 9. Alberta 77 6,4 10. British Colombia 102 8,4 99. NA 22 1,8 (N) 1211 100%


Chile CL_REG n % 1. Tarapaca 40 2,7 2. Antofagasta 50 3,3 3. Atacama 25 1,7 4. Coquimbo 60 4,0 5. Valparaiso 155 10,3 6. Libertador General 75 5,0 7. Maule 90 6,0 8. Biobio 185 12,3 9. La Araucania 85 5,6 10. Los Lagos 105 7,0 11. Aisen del General 10 0,7 12. Magallanes y Antari 15 1,0 13. Metropolitana de Santiago 610 40,5 (N) 1505 100% Czech Republic CZ_REG n % 1. Prague 103 8,1 2. Central Bohemia 138 10,8 3. South Bohemia 88 6,9 4. Pilsen 75 5,9 5. Carlsbad 29 2,3 6. Usti n/L 102 8,0 7. Liberec 47 3,7 8. Hradec Kralove 42 3,3 9. Pardubice 80 6,3 10. Vysocina 107 8,4 11. South Moravia 131 10,3 12. Olomouc 83 6,5 13. Moravia-Silesia 184 14,4 14. Zlin 67 5,3 (N) 1276 100%Denmark DK_REG n % 1. Copenhagen county 140 10,6 2. Frederiksborg county 103 7,8 3. Roskilde county 61 4,6 4. Westernzealand county 72 5,4 5. Storstroems county 65 4,9 7. Funen county 123 9,3 8. Southern Jutland county 66 5,0 9. Ribe county 54 4,1 10. Vejle county 99 7,5 11. Ringkoebing county 60 4,5 12. Aarhus county 171 12,9 13. Viborg county 69 5,2 14. Nothern Jutland county 116 8,8 15. Copenhagen municipality 88 6,7 16. Frederiksberg municipality 24 1,8 99. NA 11 0,8 (N) 1322 100%


Finland FI_REG n % 1. Uusimaa 363 26,3 2. Varsinais-Suomi 111 8,0 4. Satakunta 54 3,9 5. Kanta-Häme 45 3,3 6. Pirkanmaa 123 8,9 7. Päijät-Häme 56 4,1 8. Kymenlaakso 46 3,3 9. South Karelia 42 3,0 10. Etelä-Savo 44 3,2 11. Pohjois-Savo 61 4,4 12. North Karelia 46 3,3 13. Central Finland 77 5,6 14. South Ostrobothnia 42 3,0 15. Ostrobothnia 45 3,3 16. Central Ostrobothnia 17 1,2 17. North Ostrobothnia 93 6,7 18. Kainuu 27 2,0 19. Lapland 47 3,4 20. Itä-Uusimaa 25 1,8 21. Åland 7 0,5 99. Not known 8 0,6 (N) 1379 100%


France FR_REG n % n % n %

1. Ain 14 0,8 33. Gironde 59 3,5 65. Hautes-Pyrenees 5 0,3 2. Aisne 9 0,5 34. Herault 29 1,7 66. Pyrenees-Orientales 16 1,0 3. Allier 11 0,7 35. Ille-et-Vilaine 26 1,6 67. Bas-Rhin 24 1,4 4. Alpes-Hte-Provence 8 0,5 36. Indre 4 0,2 68. Haut-Rhin 21 1,3 5. Hautes-Alpes 3 0,2 37. Indre-et-Loire 17 1,0 69. Rhone 42 2,5 6. Alpes-Maritimes 27 1,6 38. Isere 35 2,1 70. Haute-Saone 9 0,5 7. Ardeche 10 0,6 39. Jura 7 0,4 71. Saone-et-Loire 13 0,8 8. Ardennes 5 0,3 40. Landes 8 0,5 72. Sarthe 8 0,5 9. Ariege 12 0,7 41. Loir-et-Cher 7 0,4 73. Savoie 9 0,5 10. Aube 9 0,5 42. Loire 16 1,0 74. Haute-Savoie 17 1,0 11. Aude 10 0,6 43. Haute-Loire 10 0,6 75. Ville de Paris 79 4,7 12. Aveyron 9 0,5 44. Loire-Atlantique 40 2,4 76. Seine-Maritime 29 1,7 13. Bouche-du-Rhone 55 3,3 45. Loiret 10 0,6 77. Seine-et-Marne 25 1,5 14. Calvados 17 1,0 46. Lot 4 0,2 78. Yvelines 44 2,6 15. Cantal 6 0,4 47. Lot-et-Garonne 11 0,7 79. Deux-Sevres 7 0,4 16. Charente 4 0,2 48. Lozere 4 0,2 80. Somme 19 1,1 17. Charente-Maritime 23 1,4 49. Maine-et-Loire 30 1,8 81. Tarn 6 0,4 18. Cher 4 0,2 50. Manche 16 1,0 82. Tarn-et-Garonne 3 0,2 19. Correze 8 0,5 51. Marne 11 0,7 83. Var 27 1,6 20. Haute-Corse 3 0,2 52. Haute-Marne 5 0,3 84. Vaucluse 19 1,1 21. Cote-d Or 12 0,7 53. Mayenne 3 0,2 85. Vendee 15 0,9 22. Cotes-d Armor 19 1,1 54. Meurthe-et-Moselle 28 1,7 86. Vienne 10 0,6 23. Creuse 9 0,5 55. Meuse 2 0,1 87. Haute-Vienne 7 0,4 24. Dordogne 12 0,7 56. Morbihan 24 1,4 88. Vosges 11 0,7 25. Doubs 19 1,1 57. Moselle 24 1,4 89. Yonne 12 0,7 26. Drome 11 0,7 58. Nievre 9 0,5 90. Belfort (Territoire) 1 0,1 27. Eure 12 0,7 59. Nord 52 3,1 91. Essone 29 1,7 28. Eure-et-Loir 8 0,5 60. Oise 9 0,5 92. Hauts-de-Seine 47 2,8 29. Finistere 29 1,7 61. Orne 5 0,3 93. Seine-Saint-Denis 21 1,3 30. Gard 22 1,3 62. Pas-de-Calais 39 2,3 94. Val-de-Marne 36 2,2 31. Haute-Garonne 38 2,3 63. Puy-de-Dome 15 0,9 95. Val-d Oise 20 1,2 32. Gers 5 0,3 64. Pyrenees-Atlantiques 18 1,1 96. Corse-Sud 2 0,1 99. NA 16 1,0 (N) 1669 100%


Germany DE_REG n % 1. Schleswig-Holstein 36 2,8 2. Hamburg 9 0,7 3. Niedersachsen 96 7,5 4. Bremen 5 0,4 5. Nordrhein-Westfalen 217 16,9 6. Hessen 104 8,1 7. Rheinland-Pfalz 59 4,6 8. Baden-Wuerttemberg 122 9,5 9. Bayern 168 13,1 10. Saarland 11 0,9 11. Berlin-Ost 31 2,4 12. Mecklbg-Vorpommern 52 4,0 13. Brandenburg 71 5,5 14. Sachsen-Anhalt 82 6,4 15. Thueringen 61 4,7 16. Sachsen 140 10,9 17. Berlin-West 23 1,8 (N) 1287 100% Great Britain GB_REG n % 1. Scotland 100 11,5 2. North,North West,Yorkshire Hbs 211 24,2 3. West, East Midlands 159 18,2 4. Wales 54 6,2 5. East Anglia,South West,S-E 274 31,4 6. London 75 8,6 (N) 873 100%


Hungary HU_REG n % 1. Budapest 179 17,5 2. Baranya 59 5,8 3. Bacs-Kiskun 48 4,7 4. Bekes 12 1,2 5. Borsod-Abauj 72 7,1 6. Csongrad 83 8,1 7. Fejer 46 4,5 8. Gyor-Sopron 60 5,9 9. Hajdu-Bihar 36 3,5 10. Heves 35 3,4 11. Komarom 12 1,2 12. Nograd 12 1,2 13. Pest 116 11,4 14. Somogy 36 3,5 15. Szabolcs-Szatmar 48 4,7 16. Szolnok 72 7,1 18. Vas 12 1,2 19. Veszprem 48 4,7 20. Zala 35 3,4 (N) 1021 100% Ireland IE_REG n % 1. Border 147 13,8 2. Dublin 239 22,4 3. Mid-East 131 12,3 4. Midland 51 4,8 5. Mid-West 121 11,4 6. South_east 81 7,6 7. South-West 187 17,6 8. West 108 10,1 (N) 1065 100% Israel IL_REG n % 1. North 261 21,4 2. South 174 14,3 3. Tel-Aviv 452 37,1 4. Jerusalem 169 13,9 5. Arab sector 152 12,5 99. NA 10 0,8 (N) 1218 100%


Japan JP_REG n % 1. Hokkaido, Tohoku 132 12,0 2. Kanto, Koshin-etsu 377 34,2 3. Chubu 177 16,1 4. Kinki 171 15,5 5. Chugoku, Shikoku 117 10,6 6. Kyushu 128 11,6 (N) 1102 100% Latvia LV_REG n % 1. Riga 331 33,1 2. Vidzeme 207 20,7 3. Kurzeme 132 13,2 4. Zemgale 169 16,9 5. Latgale 161 16,1 (N) 1000 100% New Zealand NZ_REG n % 1. Northland 43 4,2 2. Auckland 265 25,6 3. Thames Valley 11 1,1 4. Bay of Plenty 89 8,6 5. Waikato 72 6,9 6. Tongariro 3 0,3 7. East Cape 14 1,4 8. Hawkes Bay 50 4,8 9. Taranaki 33 3,2 10. Wanganui 16 1,5 11. Manawatu 39 3,8 12. Horowhenua 16 1,5 13. Wellington 99 9,6 14. Wairarapa 11 1,1 15. Nelson Bays 26 2,5 16. Marlborough 15 1,4 17. West Coast 9 0,9 18. Canterbury 115 11,1 19. Aorangi 12 1,2 20. Clutha-Centr Otago 22 2,1 21. Coastal-North Otago 28 2,7 22. Southland 36 3,5 99. NA 12 1,2 (N) 1036 100%


Norway NO_REG n % 1. Central East 317 21,6 2. East 420 28,6 3. South 78 5,3 4. West 382 26,0 5. Middle 139 9,5 6. North 133 9,1 (N) 1469 100% Poland PL_REG n % 1. Dolnoslaskie 98 7,7 2. Kujawsko-Pomorskie 64 5,0 3. Lubelskie 70 5,5 4. Lubuskie 38 3,0 5. Lodzkie 93 7,3 6. Maloposlkie 103 8,1 7. Mazowieckie 170 13,3 8. Opolskie 41 3,2 9. Podkarpackie 65 5,1 10. Podlaskie 38 3,0 11. Pomorskie 56 4,4 12. Slaskie 179 14,0 13. Swietokrzyskie 47 3,7 14. Warminsko-Mazurskie 47 3,7 15. Wielkopolskie 115 9,0 16. Zachodniopomorskie 53 4,2 (N) 1277 100% Portugal PT_REG n % 1. North 422 26,3 2. Centre 222 13,9 3. Lisbon a Tagus Val 808 50,4 4. Alentejo 99 6,2 5. Algarve 51 3,2 (N) 1602 100% Philippines PH_REG n % 1. National Capital Region (NCR) 300 25,0 2. Balance Luzon 300 25,0 3. Visayas 300 25,0 4. Mindanao 300 25,0 (N) 1200 100%


Russia RU_REG n % 1. North 139 5,8 2. North-West 82 3,4 3. Central 714 30,0 4. Volga-Vyatka 119 5,0 5. Black Earth 110 4,6 6. Volga Region 236 9,9 7. North Caucasus 237 9,9 8. Urals 289 12,1 9. West Siberia 212 8,9 10. East Siberia 131 5,5 11. Far East 114 4,8 (N) 2383 100% Slovakia SK_REG n % 1. Bratislava county 131 11,4 2. Trnava county 117 10,2 3. Trencin county 128 11,1 4. Nitra county 153 13,3 5. Zilina county 148 12,8 6. Ban. Bystrica county 141 12,2 7. Presov county 169 14,7 8. Kosice county 164 14,2 99. NA 1 0,1 (N) 1152 100% Slovenia SI_REG n % 1. Pomurska 80 7,3 2. Podravska 181 16,6 3. Koroska 51 4,7 4. Savinjska 158 14,5 5. Gorenjska 122 11,2 6. Zasavska 20 1,8 7. Osrednja 244 22,3 8. Spodnjeposavska 37 3,4 9. Dolenjska 62 5,7 10. Goriska 65 5,9 11. Obalnokraska 49 4,5 12. Kraska 24 2,2 (N) 1093 100%


South Africa ZA_REG n % 1. WC 270 10,9 2. EC 286 11,5 3. NC 243 9,8 4. FS 210 8,5 5. KZN 399 16,1 6. NW 203 8,2 7. GT 301 12,1 8. MP 276 11,1 9. LP 295 11,9 (N) 2483 100% South Korea KR_REG n % 1. Seoul Metropolitan City 291 22,1 2. Incheon Metropolitan city 74 5,6 3. Daejeon Metropolitan city 34 2,6 4. Busan Metropolitan city 107 8,1 5. Ulsan Metropolitan City 24 1,8 6. Deagu Metropolitan City 65 4,9 7. Gwangju Metropolitan city 43 3,3 8. Gyeonggi Province 249 18,9 9. Gangwon Province 44 3,3 10. Chungcheong Province 112 8,5 11. Gyeongsang Province 145 11,0 12. Jeolla Province 112 8,5 13. Jeju-do 15 1,1 (N) 1315 100% Spain ES_REG n % 1. Andalucia 210 17,3 2. Aragon 38 3,1 3. Asturias 34 2,8 4. Baleares 24 2,0 5. Cataluña 191 15,8 6. Canarias 49 4,0 7. Cantabria 17 1,4 8. Castilla-Leon 78 6,4 9. Castilla-La Mancha 52 4,3 10. Extremadura 31 2,6 11. Galicia 87 7,2 12. La Rioja 7 0,6 13. Madrid 152 12,5 14. Murcia 33 2,7 15. Navarra 17 1,4 16. Pais Vasco 68 5,6 17. Comunidad Valenciana 124 10,2 (N) 1212 100%


Sweden SE_REG n % 1. North 144 12,1 2. Mid North 126 10,6 3. Mid East 188 15,9 4. Stockholm 214 18,0 5. West 111 9,4 6. Goeteborg 124 10,5 7. Smaaland Gotland 102 8,6 8. South 103 8,7 9. Malmoe 70 5,9 99. NA 4 0,3 (N) 1186 100% Switzerland CH_REG n % 1. Zuerich 231 22,3 2. Bern 187 18,0 3. Luzern 41 4,0 8. Glarus 19 1,8 9. Zug 12 1,2 10. Fribourg 40 3,9 11. Solothurn 40 3,9 12. Baselstadt 7 0,7 17. St. Gallen 86 8,3 18. Graubuenden 27 2,6 19. Aargau 71 6,8 20. Thurgau 58 5,6 21. Ticino 42 4,1 22. Vaud 80 7,7 23. Wallis 41 4,0 25. Geneve 31 3,0 26. Jura 24 2,3 (N) 1037 100% Taiwan TW_REG n % 1. North 969 48,12. Central 323 16,03. South 624 31,04. East 100 5,0(N) 2016 100%


United States US_REG n % 1. New England 33 2,7 2. Middle Atlantic 152 12,5 3. East North Central 234 19,2 4. West North Central 90 7,4 5. South Atlantic 259 21,3 6. East South Central 67 5,5 7. West South Central 110 9,0 8. Mountain 94 7,7 9. Pacific 177 14,6 (N) 1216 100%

Uruguay UY_REG n % 1. Metropolitan statistical area of Montevideo 680 61,4 2. Rest of urban population 428 38,6 (N) 1108 100% Venezuela (Not asked) VE_REG n % (N) 0 100%


XX_SIZE: Country specific town size Missing Values: 00; (98;99) or (8;9) depending on variable XX_SIZE. Country specific town size 1 xx. Town size 00. Not available; Not asked 8/98. Don’t know 9/99. No answer NOTES: (1) Not asked in Chile, New Zealand and Venezuela (2) All except Finland and Philippines use categories that have been ordered so that 1 represents large cities and (nn) small cities. In Finland and Philippines, the town size in habitants has been used. Australia AU_SIZE n % 1. Inner metropolitan (over 100,000 people) 600 27,5 2. Outer metropolitan (over 100,000 people) 770 35,3 3. A large town (over 25,000 people) 269 12,3 4. A larger country town (over 10,000 people) 125 5,7 5. A small country town (under 10,000 people) 249 11,4 6. A rural area or on a farm 140 6,4 99. NA 30 1,4 (N) 2183 100% Austria AT_SIZE n % 1. >1 mill+Vienna 183 18,2 2. 50 001-1 million 142 14,1 3. 20 001-50 000 256 25,4 8. Less than 2 000 425 42,2 (N) 1006 100% Bulgaria BG_SIZE n % 1. Sofia (1.2Mill) 120 11,2 2. 100001-500000 183 17,1 3. 20001+100000 223 20,9 4. 2001-20000 293 27,4 5. up to 2000 250 23,4 (N) 1069 100%


Canada CA_SIZE n % 1. greater than 1 million 101 8,3 2. 750 000 - 999 999 91 7,5 3. 500 000 - 749 999 75 6,2 4. 250 000 - 499 999 94 7,8 5. 100 000 - 249 999 170 14,0 6. 50 000 - 99 999 143 11,8 7. 10 000 - 49 999 298 24,6 8. 1 000 - 9 999 150 12,4 9. less than 1 000 43 3,6 99. Na, refused 46 3,8 (N) 1211 100% Chile CL_SIZE n % (N) 0 100% Czech Republic CZ_SIZE n % 1. 1,2 Mill. (Prague) 103 8,1 2. 100 000+ 155 12,1 3. 50 000- 99 999 169 13,2 4. 10 000- 49 999 221 17,3 5. 5 000- 9 999 222 17,4 6. 2 000- 4 999 124 9,7 7. 1 000- 1 999 123 9,6 8. Less than 1 000 159 12,5 (N) 1276 100% Denmark DK_SIZE n % 1. Greater Copenhagen area 227 17,2 2. 50 000 to 500 000 201 15,2 3. 10 000-50 000 297 22,5 4. 5 000-10 000 141 10,7 5. Less than 5 000 345 26,1 8. Dont know 85 6,4 9. NA 26 2,0 (N) 1322 100%


Finland FI_SIZE n % 99. Not known 8 0,6 26257. Inhabitants (Åland region) 7 0,5 70674. Inhabitants (Central Ostrobothnia region) 17 1,2 87371. Inhabitants (Kainuu region) 27 2,0 90934. Inhabitants (Itä-Uusimaa region) 25 1,8 136694. Inhabitants (South Karelia region) 42 3,0 163276. Inhabitants (Etelä-Savo region) 44 3,2 165886. Inhabitants (Kanta-Häme region) 45 3,3 169722. Inhabitants (North Karelia region) 46 3,3 173006. Inhabitants (Ostrobothnia) 45 3,3 186111. Inhabitants (Kymenlaakso region) 46 3,3 187777. Inhabitants (Lapland region) 47 3,4 194105. Inhabitants (South Ostrobothnia region) 42 3,0 198088. Inhabitants (Päijät-Häme region) 56 4,1 235416. Inhabitants (Satakunta region) 54 3,9 251976. Inhabitants (Pohjois-Savo region) 61 4,4 265078. Inhabitants (Central Finland region) 77 5,6 369974. Inhabitants (North Ostrobothnia region) 93 6,7 450968. Inhabitants (Varsinais-Suomi region) 111 8,0 453978. Inhabitants (Pirkanmaa region) 123 8,9 1329004. Inhabitants (Uusimaa region) 363 26,3 (N) 1379 100% France FR_SIZE n % 1. Paris 133 8,0 2. > - 500 000 86 5,2 3. 100 001- 500 000 180 10,8 4. 50 001- 100 000 115 6,9 5. 20 001- 50 000 182 10,9 6. 10 001- 20 000 127 7,6 7. 2 001- 10 000 389 23,3 8. < 2 000 390 23,4 99. NA 67 4,0 (N) 1669 100% Germany DE_SIZE n % 1. > 500 000 156 12,3 2. 100 000-499 999 201 15,8 3. 50 000- 99 999 94 7,4 4. 20 000- 49 999 184 14,5 5. 5 000- 19 999 314 24,7 6. 2 000- 4 999 175 13,8 7. up to 1 999 146 11,5 (N) 1270 100%


Great Britain GB_SIZE n % 1. Highest population density 185 21,2 2. 2 225 25,8 3. 3 218 25,0 4. Lowest population density 245 28,1 (N) 873 100% Hungary HU_SIZE n % 1. 2 mill.inh.,Budapest 179 17,5 2. 100 000+ 72 7,1 3. 50 001-100 000 60 5,9 4. 20 001- 50 000 119 11,7 5. 10 001- 20 000 108 10,6 6. 5 001- 10 000 96 9,4 7. 2 001- 5 000 140 13,7 8. 1 001- 2 000 128 12,5 9. < 1 000 119 11,7 (N) 1021 100% Ireland IE_SIZE n % 1. Dublin 218 20,5 2. large city 70000 to 100000 85 8,0 3. medium city 50000 to 69999 11 1,0 4. large town 10000 to 49999 107 10,0 5. small town 3000 to 9999 92 8,6 6. Village up to 3000 159 14,9 7. Farm, rural property 370 34,7 99. 99 23 2,2 (N) 1065 100% Israel IL_SIZE n % 1. > than 100 000 586 48,1 2. 50 001-100 000 115 9,4 3. 20 001- 50 000 301 24,7 4. 10 001- 20 000 115 9,4 5. 5 001- 10 000 30 2,5 6. 2 501- 5 000 44 3,6 9. NA 27 2,2 (N) 1218 100% Japan JP_SIZE n % 1. 1.000.000 or more 198 18,0 2. 300.000-999.999 168 15,2 3. 100.000-299.999 237 21,5 4. less than 100.000 200 18,1 5. Town or village 299 27,1 (N) 1102 100%


Latvia LV_SIZE n % 1. > 500.000 331 33,1 2. 100.001-500.000 49 4,9 3. 50.001-100.000 89 8,9 4. 20.001- 50.000 71 7,1 5. 10.001- 20.000 76 7,6 6. 5.001- 10.000 64 6,4 7. 2.000- 5.000 168 16,8 8. < 2.000 152 15,2 (N) 1000 100% New Zealand NZ_SIZE n % (N) 0 100% Norway NO_SIZE n % 1. >100 000 367 25,0 2. 30 000- 99 999 283 19,3 3. 3 000- 29 999 727 49,5 4. < 3 000 92 6,3 (N) 1469 100% Poland PL_SIZE n % 1. > 500 000 26 2,0 2. 250 000-500 000 84 6,6 3. 100 000-249 999 253 19,8 4. 50 000- 99 999 150 11,7 5. 25 000- 49 999 104 8,1 6. 10 000- 24 999 92 7,2 7. < 10 000 108 8,5 8. Village 460 36,0 (N) 1277 100% Portugal PT_SIZE n % 1. greater than 100 000 206 12,9 2. 20 000-100 000 279 17,4 3. 5 000- 19 999 368 23,0 4. 1 000- 4 999 396 24,7 5. less than 1 000 353 22,0 (N) 1602 100%


Philippines PH_SIZE n % n % n % n %

0 NAV 67 5,6 1247 5 0,4 2886 5 0,4 9408 5 0,4192 5 0,4 1254 5 0,4 2895 5 0,4 9446 5 0,4209 5 0,4 1269 5 0,4 2925 5 0,4 11165 5 0,4234 5 0,4 1275 5 0,4 2950 5 0,4 11340 5 0,4308 5 0,4 1277 5 0,4 2996 5 0,4 11445 5 0,4357 5 0,4 1278 5 0,4 3044 5 0,4 11484 5 0,4368 5 0,4 1280 5 0,4 3144 5 0,4 11998 6 0,5381 5 0,4 1294 5 0,4 3174 5 0,4 12198 5 0,4403 5 0,4 1317 2 0,2 3201 5 0,4 13237 5 0,4408 5 0,4 1340 5 0,4 3214 5 0,4 13492 2 0,2423 5 0,4 1388 5 0,4 3293 1 0,1 14252 5 0,4457 5 0,4 1430 5 0,4 3295 5 0,4 14516 4 0,3506 5 0,4 1455 5 0,4 3318 5 0,4 15342 5 0,4516 5 0,4 1501 5 0,4 3344 5 0,4 16196 5 0,4521 5 0,4 1504 5 0,4 3416 5 0,4 17756 5 0,4537 5 0,4 1514 5 0,4 3592 5 0,4 17867 5 0,4566 5 0,4 1577 5 0,4 3871 5 0,4 18691 5 0,4567 5 0,4 1594 5 0,4 3904 5 0,4 18935 4 0,3595 5 0,4 1602 5 0,4 3960 5 0,4 19285 5 0,4598 5 0,4 1624 5 0,4 4020 5 0,4 19349 5 0,4626 5 0,4 1636 5 0,4 4080 5 0,4 19632 5 0,4633 5 0,4 1669 5 0,4 4087 5 0,4 20850 5 0,4636 5 0,4 1678 5 0,4 4195 5 0,4 22433 5 0,4640 5 0,4 1716 5 0,4 4238 5 0,4 24608 5 0,4656 5 0,4 1729 10 0,8 4313 5 0,4 24617 5 0,4711 5 0,4 1744 5 0,4 4526 5 0,4 24676 5 0,4714 5 0,4 1746 15 1,3 4592 5 0,4 26417 5 0,4715 5 0,4 1810 5 0,4 4633 5 0,4 26552 5 0,4740 5 0,4 1828 5 0,4 4635 5 0,4 29365 5 0,4741 5 0,4 1834 5 0,4 4685 5 0,4 30332 5 0,4743 5 0,4 1880 5 0,4 4775 5 0,4 31513 5 0,4747 7 0,6 1892 5 0,4 4856 4 0,3 32273 5 0,4808 5 0,4 1896 5 0,4 4996 5 0,4 32730 5 0,4810 5 0,4 1933 5 0,4 5048 5 0,4 34616 2 0,2834 5 0,4 1951 5 0,4 5062 5 0,4 35275 5 0,4839 5 0,4 1955 5 0,4 5109 5 0,4 36431 5 0,4860 5 0,4 2013 5 0,4 5138 5 0,4 37667 5 0,4863 5 0,4 2028 5 0,4 5296 5 0,4 38627 5 0,4899 5 0,4 2063 5 0,4 5508 5 0,4 42351 5 0,4931 5 0,4 2087 5 0,4 5664 5 0,4 42903 5 0,4958 5 0,4 2122 5 0,4 5758 5 0,4 43770 5 0,4963 5 0,4 2218 5 0,4 5790 5 0,4 45185 10 0,8965 5 0,4 2279 5 0,4 5840 5 0,4 46552 5 0,4969 5 0,4 2294 5 0,4 5853 5 0,4 48080 5 0,4980 5 0,4 2324 5 0,4 5870 5 0,4 50158 6 0,5981 5 0,4 2360 5 0,4 5915 5 0,4 63214 5 0,4

1060 10 0,8 2371 5 0,4 6259 5 0,4 64728 6 0,51066 5 0,4 2493 5 0,4 6416 5 0,4 76736 5 0,41067 5 0,4 2507 5 0,4 7051 5 0,4 82765 5 0,41089 5 0,4 2510 4 0,3 7077 5 0,4 89456 5 0,41097 5 0,4 2518 5 0,4 7341 5 0,4 91196 5 0,41111 5 0,4 2541 5 0,4 7419 5 0,4 1182 5 0,4 2639 5 0,4 7569 5 0,4 1185 5 0,4 2658 5 0,4 7589 5 0,4 1198 5 0,4 2679 5 0,4 7646 5 0,4 1222 5 0,4 2682 5 0,4 8190 5 0,4 1239 5 0,4 2694 5 0,4 8620 5 0,4 1241 5 0,4 2729 5 0,4 8758 5 0,4


Russia RU_SIZE n % 1. > 1 million 672 28,2 2. 500 001-1 000 000 209 8,8 3. 250 001- 500 000 229 9,6 4. 100 001- 250 000 199 8,4 5. 50 001- 100 000 205 8,6 6. 20 001- 50 000 169 7,1 7. Urban < 20 000 152 6,4 8. Rural 548 23,0 (N) 2383 100% Slovakia SK_SIZE n % 1. More than 100 000 144 12,5 2. 50 000 - 100 000 163 14,1 3. 10 000 - 50 000 315 27,3 4. 2 000 - 10 000 207 18,0 5. Up to 2 000 323 28,0 (N) 1152 100% Slovenia SI_SIZE n % 1. > 50 000 (Lblj,Mar) 168 15,4 2. 10 000-50 000 146 13,4 3. 4 000-10 000 65 5,9 4. 2 000-4 000 74 6,8 5. 500-2 000 285 26,1 6. < 500 347 31,7 99. NA 8 0,7 (N) 1093 100% South Africa ZA_SIZE n % 1. Tribal 490 19,7 2. Farms 287 11,6 3. Smallholdings 15 0,6 4. Urban formal 1377 55,5 5. Urban informal 296 11,9 9. Hostels 18 0,7 (N) 2483 100% South Korea KR_SIZE n % 1. 1 000 001 and more; metropolitan 638 48,5 2. 100 001-1 000 000; large city 510 38,8 3. 50 001- 100 000; middle city 129 9,8 4. Less than 50 000; rular county 38 2,9 (N) 1315 100%


Spain ES_SIZE n % 1. Madrid and Barcelona 143 11,8 2. > Than 250.000 179 14,8 3. 100.001 - 250.000 165 13,6 4. 50.001 - 100.000 129 10,6 5. 10.001 - 50.000 285 23,5 6. 5.001 - 10.000 132 10,9 7. 2.001 - 5.000 95 7,8 8. < Than 2.000 84 6,9 (N) 1212 100% Sweden SE_SIZE n % 1. More than 300 000 408 34,4 2. 90 000 - 300 000 415 35,0 3. 27 000 - 90 000 293 24,7 4. Less than 27 000 66 5,6 99. NA 4 0,3 (N) 1186 100% Switzerland CH_SIZE n % 7367900. Switzerland 1037 100,0 (N) 1037 100% Taiwan TW_SIZE n % 1. More than 9000 21 1,0 2. 8000-8999 25 1,2 3. 7000-7999 116 5,8 4. 6000-6999 143 7,1 5. 5000-5999 160 7,9 6. 4000-4999 290 14,4 7. 3000-3999 390 19,3 8. 2000-2999 328 16,3 9. 1000-1999 436 21,6 10. Less than 999 107 5,3 (N) 2016 100% United States US_SIZE n % 1. 1-9 millions 75 6,2 2. 500 000-999 999 48 3,9 3. 100 000-499 999 164 13,5 4. 50 000-99 999 137 11,3 5. 10 000-49 999 408 33,6 6. 1 000-9 999 360 29,6 7. - 999 24 2,0 (N) 1216 100%


Uruguay UY_SIZE n % 1. 1.597.943 urban population 680 61,4 2. 992.552 urban population 428 38,6 (N) 1108 100% Venezuela VE_SIZE n % (N) 0 100%


URBRURAL: Place of residence: urban-rural Missing Values: 0;9 Urbrural. Type of community: urban / rural 1,2. 0. Not available. 1. Urban,RP:total urban. 2. Suburb,city,town. 3. Town or small city. 4. Country village. 5. Farm or home in the country. 9. No answer. NOTES: (1) Not asked in Venezuela (2) Austria, Canada, France, Hungary, Israel, Poland, Portugal, Russia, Slovenia, Spain, US and Uruguay used the

old three categories classification Chile used a two category classification (total urban/total rural)


0 1 2 3 4 5 9URBRURAL (N) % % % % % % %

600 770 394 249 140 30Australia (AU) 2183 27,50% 35,30% 18,00% 11,40% 6,40% 1,40%

183 398 425Austria (AT) 1006 18,20% - 39,60% 42,20% - -

120 337 278 334Bulgaria (BG) 1069 11,20% 31,50% 26,00% 31,20% - -

312 739 138 22Canada (CA) 1211 25,80% 61,00% - 11,40% - 1,80%

1295 210Chile (CL) 1505 86,00% - - - 14,00% -

356 86 492 306 1 35Czech Republic (CZ) 1276 27,90% 6,70% 38,60% 24,00% 0,10% 2,70%

275 230 441 255 111 10Denmark (DK) 1322 20,80% 17,40% 33,40% 19,30% 8,40% 0,80%

156 461 311 270 169 12Finland (FI) 1379 11,30% 33,40% 22,60% 19,60% 12,30% 0,90%

684 470 494 21France (FR) 1669 41,00% 28,20% - 29,60% - 1,30%

172 108 238 289 26 17Germany-West (DE-W) 850 20,20% 12,70% 28,00% 34,00% 3,10% 2,00%

67 28 211 118 4 9Germany-East (DE-E) 437 15,30% 6,40% 48,30% 27,00% 0,90% 2,10%

64 197 458 130 15 9Great Britain (GB) 873 7,30% 22,60% 52,50% 14,90% 1,70% 1,00%

323 323 375Hungary (HU) 1021 31,60% - 31,60% 36,70% - -

89 242 203 172 356 3Ireland (IE) 1065 8,40% 22,70% 19,10% 16,20% 33,40% 0,30%

586 449 16 15Israel Jews (IL-J) 1066 55,00% - 42,10% 1,50% - 1,40%

112 28 12Israel Arabs (IL-A) 152 - - 73,70% 18,40% - 7,90%

112 165 436 308 78 3Japan (JP) 1102 10,20% 15,00% 39,60% 27,90% 7,10% 0,30%

479 31 180 160 150Latvia (LV) 1000 47,90% 3,10% 18,00% 16,00% 15,00% -

188 295 341 87 116 9New Zealand (NZ) 1036 18,10% 28,50% 32,90% 8,40% 11,20% 0,90%

376 195 331 299 248 20Norway (NO) 1469 25,60% 13,30% 22,50% 20,40% 16,90% 1,40%

363 454 460Poland (PL) 1277 28,40% - 35,60% 36,00% - -

1223 168 211Portugal (PT) 1602 76,30% 10,50% - 13,20% - -

457 67 173 463 40Philippines (PH) 1200 38,10% 5,60% 14,40% 38,60% 3,30% -

1309 526 548Russia (RU) 2383 54,90% - 22,10% 23,00% - -

208 36 471 432 4 1Slovak Republic (SK) 1152 18,10% 3,10% 40,90% 37,50% 0,30% 0,10%

396 168 521 8Slovenia (SI) 1093 36,20% 15,40% - 47,70% - 0,70%

1395 296 490 302South Africa (ZA) 2483 56,20% 11,90% 19,70% 12,20% - -

408 320 464 108 12 3South Korea (KR) 1315 31,00% 24,30% 35,30% 8,20% 0,90% 0,20%

487 414 311Spain (ES) 1212 40,20% - 34,20% 25,70% - -

271 228 307 270 106 4Sweden (SE) 1186 22,80% 19,20% 25,90% 22,80% 8,90% 0,30%

123 100 196 597 21Switzerland (CH) 1037 11,90% 9,60% 18,90% 57,60% 2,00% -

540 393 460 618 2 3Taiwan (TW) 2016 26,80% 19,50% 22,80% 30,70% 0,10% 0,10%

499 523 194United States (US) 1216 41,00% 43,00% 16,00% - - -

556 124 428Uruguay (UY) 1108 50,20% 11,20% 38,60% - - -

Venezuela (VE) 1199 1199M - - - - - -Sum 44170 1199M 14672 6777 10173 9294 1809 246


ETHNIC: R's Ethnicity or nationality (Country specific) Missing Values: 00;998;999 Ethnic. R's Ethnicity or nationality 1

1. Africa,Mandinka,Somalia,Sudan,Yoruba 49. German,Germany (CZ:Nemec) 96. Ozamisnon 2. Afrikaan 50. German+Danish 97. Pacific,Polynesian,Chamorro Guam 3. Aklanon,Romblon 51. Greek,Greece 98. Pakistan,Panjab/Punjabi,Pashto 4. Albanian 52. Hebrew/Ivrit 99. Panggalatok Pangasinan, Pangasinense 5. Alsacien, France 53. Hungarian,Hungary (CZ:Magyar) 100. Philippines,Tagalog,Filippino 6. American Indian,Navajo,Ind.Dialect 54. Ibanag 101. Pidgin, PNG Pidgin 7. American,American only,America,USA 55. Ifugao 102. Polish,Pole,Poland 8. Antiqueño 56. Igorot 103. Portuguese, Portugal 9. Arab,Arabic,Muslim 57. Ilocano 104. Provençal, France 10. Armenian,Transcaucasian 58. Ilonggo 105. Romani,Gipsy ,Tzyganes 11. Asian,Asia,other Asian 59. French+English 106. Romanian/Rumanian 12. Australian,Oceanian,Australia 60. Indian,Hindi,Urdu,Gujarati,Tamil 107. Romblonon 13. Austrian,Austria 61. Indonesian,Malay/Malaysian 108. Russian,Russia,USSR&Rep. 14. Bangladeshi,Bengali,Bangladesh 62. Inuit, Eskimo 109. Samic,Lapp 15. Basque/Vasco 63. Iranian,Persian/Farsi,Dari 110. Samoan,Tokelauan 16. Belgian,Belgium 64. Iraq 111. Scotland,Scots Gaelic,Scottish 17. Belorussian,Bialorussian 65. Irish/Irish Gaelic,Ireland 112. Sepedi 18. Bicolano/Bikol 66. Isindebele 113. Serbia,Serbian,Serb, Yugoslavian 19. Bilaan 67. Isixhosa 114. Sesotho 20. Black/African/Carribean,No-Spanish 68. Isizulu 115. Setswana 21. Bosnian, SLO:ethn.Muslim 69. Italian,Italy 116. Silesian 22. Breton, France 70. Itawis 117. Siswati 23. Bul-anon 71. Itneg 118. Slovakia,Slovak 24. Bulgarian 72. Japanese,Japan 119. Slovenia,Slovenian,Slovene 25. Cajun French 73. Jordan 120. Somalia 26. Catalan,Valencian,Balear/Mallorquin 74. Kapampangan' 121. Spanish,Castilian,Castellano 27. Coloured 75. Karay-a 122. Subanen 28. Cook Island Maori 76. Korean 123. Surigaonon 29. Corse, France 77. Kurdish,Assyrian,Lebanese 124. Swedish (both citizen) 30. Creole,Surinam/Sranan,Metis,Chavacano 78. Latin-American, South America,


31. Jewish/Yiddish 79. Latvian,Estonian,Lith.,Baltic 126. Tatar 32. Croatian 80. Lithuanian 127. Thai,Khmer,Vietnamese, Cont.Southeast 33. Czech-Czechia,Czech Republic 81. Luxemborger, Luxemburg 128. Tongan,Niuean 34. Chinese-Cantonese,Hakka,Mandarin 82. Philippine other (Maguindanao,


35. Danish,Denmark 83. Maori,NZ Maori 131. Turkey,Turkish 36. Danish+English 84. Maranaw/Maranao 132. Ukraine,Ukrainian 37. English + Persian 85. Masbateño 133. Visayan/Cebuano,Boholano,Leyteno 38. English + Tai 86. Metis 134. Waray 39. English,England&Wales,UK,England 87. Montenegro 135. Welsh 40. Esperanto,Latin,Slavonik,Celtic 88. Moravian 136. Whites (all) 41. Estonia 89. Netherlands,Dutch,Flemish 137. Xitsonga 42. Ethiopia 990. No languages at all 138. Zamboangeño 43. European,White/European,Europe 90. Nordic,Scandinavian other 980. Other African language 44. Europeans Mediterranean 91. North Africans 981. Other,East European 45. Finnish,Finland 92. Norwegian,Norway 982. Other,Middle East 46. French,France 93. Occitan, France 983. Other,Mixed origin 47. Gallego 94. One non-Swedish,both non-Swe 984. Other,Western European 48. Georgian 95. Oriental 0. Nap; Nav; Not asked

0. Not available (Not asked) 998. Don’t know. 999. No answer.

NOTES: (1) Not asked in Australia, Austria, Chile, Denmark, France, Great Britain, Hungary, Israel, Japan, New Zealand, Norway, Poland, Portugal, Spain, Switzerland, Taiwan and Uruguay.


0 1 3 6 7 10 11 12 13 17 18 20 21 24ETHNIC (N) % % % % % % % % % % % % % %

Australia (AU) 2183 2183M - - - - - - - - - - - - -

Austria (AT) 1006 1006M - - - - - - - - - - - - -1 921

Bulgaria (BG) 1069 - - - - 0,10% - - - - - - - 86,60%23 6 17

Canada (CA) 1211 1,90% - 0,50% - - - - - - - 1,40% - -

Chile (CL) 1505 1505M - - - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - - -

Denmark (DK) 1322 1322M - - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - - -

France (FR) 1669 1669M - - - - - - - - - - - - -2 2

Germany-West (DE-W) 850 2M - - - 0,20% - - - 0,20% - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - - -

Great Britain (GB) 873 873M - - - - - - - - - - - - -

Hungary (HU) 1021 1021M - - - - - - - - - - - - -2 2 2

Ireland (IE) 1065 0,20% - - 0,20% - - 0,20% - - - - - -

Israel Jews (IL-J) 1066 1066M - - - - - - - - - - - - -

Israel Arabs (IL-A) 152 152M - - - - - - - - - - - - -

Japan (JP) 1102 1102M - - - - - - - - - - - - -20

Latvia (LV) 1000 - - - - - - - - 2,00% - - - -

New Zealand (NZ) 1036 1036M - - - - - - - - - - - - -

Norway (NO) 1469 1469M - - - - - - - - - - - - -

Poland (PL) 1277 1277M - - - - - - - - - - - - -

Portugal (PT) 1602 1602M - - - - - - - - - - - - -5 60

Philippines (PH) 1200 - 0,40% - - - - - - - 5,00% - - -

Russia (RU) 2383 - - - - - - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - - - -4 15

Slovenia (SI) 1093 - - - - - - - 0,40% - - - 1,40% -1525

South Africa (ZA) 2483 61,40% - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - - -

Spain (ES) 1212 1212M - - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - - -

Switzerland (CH) 1037 1037M - - - - - - - - - - - - -

Taiwan (TW) 2016 2016M - - - - - - - - - - - - -164 12 3

United States (US) 1216 13,50% - 1,00% - - 0,20% - - - - - - -

Uruguay (UY) 1108 1108M - - - - - - - - - - - - -

Venezuela (VE) 1199 1199M - - - - - - - - - - - - -Sum 44170 20805M 1714 5 18 4 1 3 2 6 20 60 17 15 921


27 30 31 32 33 34 39 45 46 48 49 52 53 54ETHNIC (N) % % % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - - - -4 6 416 396 116

Canada (CA) 1211 - - 0,30% - - 0,50% 35,20% - 33,50% - 9,80% - - -

Chile (CL) 1505 - - - - - - - - - - - - - -1069 10 1

Czech Republic (CZ) 1276 - - - - 87,00% - - - - - 0,80% - 0,10% -

Denmark (DK) 1322 - - - - - - - - - - - - - -1379

Finland (FI) 1379 - - - - - - - #### - - - - - -

France (FR) 1669 - - - - - - - - - - - - - -2 776

Germany-West (DE-W) 850 - - - - - - - - 0,20% - 91,50% - - -430

Germany-East (DE-E) 437 - - - - - - - - - - 98,40% - - -

Great Britain (GB) 873 - - - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - - - -21 2

Ireland (IE) 1065 - - - - - - 2,00% - 0,20% - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - - - -1 1 9

Latvia (LV) 1000 - - - - - - - - - 0,10% 0,10% 0,90% - -

New Zealand (NZ) 1036 - - - - - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - - - -1 10

Philippines (PH) 1200 - 0,10% - - - - - - - - - - - 0,80%

Russia (RU) 2383 - - - - - - - - - - - - - -103

Slovak Republic (SK) 1152 - - - - - - - - - - - - 8,90% -30 2

Slovenia (SI) 1093 - - - 2,80% - - - - - - - - 0,20% -407

South Africa (ZA) 2483 16,40% - - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - - - -12

United States (US) 1216 - - - - - 1,00% - - - - - - - -

Uruguay (UY) 1108 - - - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - - - -Sum 44170 407 1 4 30 1069 18 437 1379 400 1 1333 9 106 10


57 58 60 62 65 69 72 74 76 78 79 80 82 84ETHNIC (N) % % % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - - - -

Bulgaria (BG) 1069 - - - - - - - - - - - - - -2 17 3

Canada (CA) 1211 - - 0,20% 1,40% - - - - - 0,30% - - - -

Chile (CL) 1505 - - - - - - - - - - - - - -

Czech Republic (CZ) 1276 - - - - - - - - - - - - - -

Denmark (DK) 1322 - - - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - - - -3

Germany-West (DE-W) 850 - - - - - 0,40% - - - - - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - - - -1025 1

Ireland (IE) 1065 - - - - 96,80% 0,10% - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - - - -587 13

Latvia (LV) 1000 - - - - - - - - - - 58,70% 1,30% - -

New Zealand (NZ) 1036 - - - - - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - - - -156 195 18 81 1

Philippines (PH) 1200 13,00% 16,30% - - - - - 1,50% - - - - 6,80% 0,10%

Russia (RU) 2383 - - - - - - - - - - - - - -

Slovak Republic (SK) 1152 - - - - - - - - - - - - - -3

Slovenia (SI) 1093 - - - - - 0,30% - - - - - - - -231

South Africa (ZA) 2483 - - 9,30% - - - - - - - - - - -1315

South Korea (KR) 1315 - - - - - - - - #### - - - - -

Spain (ES) 1212 - - - - - - - - - - - - - -

Sweden (SE) 1186 - - - - - - - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - - - -8 3 33

United States (US) 1216 - - 0,70% - - - 0,20% - - 2,70% - - - -

Uruguay (UY) 1108 - - - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - - - -Sum 44170 156 195 241 17 1025 7 3 18 1315 36 587 13 81 1


85 86 88 89 94 97 98 99 100 102 105 106 108 111ETHNIC (N) % % % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - - - -52

Bulgaria (BG) 1069 - - - - - - - - - - 4,90% - - -6 65

Canada (CA) 1211 - 0,50% - - - - - - - - - - - 5,50%

Chile (CL) 1505 - - - - - - - - - - - - - -111 4 7

Czech Republic (CZ) 1276 - - 9,00% - - - - - - 0,30% 0,60% - - -

Denmark (DK) 1322 - - - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - - - -1 25 3 1 1

Germany-West (DE-W) 850 - - - 0,10% - - 2,90% - - 0,40% - 0,10% 0,10% -3 1 3

Germany-East (DE-E) 437 - - - - - - 0,70% - - 0,20% - - 0,70% -

Great Britain (GB) 873 - - - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - - - -1 1

Ireland (IE) 1065 - - - - - - - - 0,10% - - 0,10% - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - - - -19 2 1 315

Latvia (LV) 1000 - - - - - - - - - 1,90% 0,20% 0,10% 31,50% -

New Zealand (NZ) 1036 - - - - - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - - - -13 10 288

Philippines (PH) 1200 1,10% - - - - - - 0,80% 24,00% - - - - -2383

Russia (RU) 2383 - - - - - - - - - - - - #### -

Slovak Republic (SK) 1152 - - - - - - - - - - - - - -

Slovenia (SI) 1093 - - - - - - - - - - - - - -

South Africa (ZA) 2483 - - - - - - - - - - - - - -

South Korea (KR) 1315 - - - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - - - -167

Sweden (SE) 1186 - - - - 14,10% - - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - - - -2 7

United States (US) 1216 - - - - - 0,20% - - 0,60% - - - - -

Uruguay (UY) 1108 - - - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - - - -Sum 44170 13 6 111 1 167 2 28 10 296 27 61 3 2702 65


113 116 118 119 121 124 125 126 127 131 132 133 134 136ETHNIC (N) % % % % % % % % % % % % % %

Australia (AU) 2183 - - - - - - - - - - - - - -

Austria (AT) 1006 - - - - - - - - - - - - - -78

Bulgaria (BG) 1069 - - - - - - - - - 7,30% - - - -

Canada (CA) 1211 - - - - - - - - - - - - - -

Chile (CL) 1505 - - - - - - - - - - - - - -9 16 1

Czech Republic (CZ) 1276 - 0,70% 1,30% - - - - - 0,10% - - - - -

Denmark (DK) 1322 - - - - - - - - - - - - - -

Finland (FI) 1379 - - - - - - - - - - - - - -

France (FR) 1669 - - - - - - - - - - - - - -8 3 1 1 1 18

Germany-West (DE-W) 850 0,90% - - - 0,40% 0,10% 0,10% - 0,10% 2,10% - - - -

Germany-East (DE-E) 437 - - - - - - - - - - - - - -

Great Britain (GB) 873 - - - - - - - - - - - - - -

Hungary (HU) 1021 - - - - - - - - - - - - - -2

Ireland (IE) 1065 - - - - 0,20% - - - - - - - - -

Israel Jews (IL-J) 1066 - - - - - - - - - - - - - -

Israel Arabs (IL-A) 152 - - - - - - - - - - - - - -

Japan (JP) 1102 - - - - - - - - - - - - - -1 19

Latvia (LV) 1000 - - - - - - - 0,10% - - 1,90% - - -

New Zealand (NZ) 1036 - - - - - - - - - - - - - -

Norway (NO) 1469 - - - - - - - - - - - - - -

Poland (PL) 1277 - - - - - - - - - - - - - -

Portugal (PT) 1602 - - - - - - - - - - - - - -313 47

Philippines (PH) 1200 - - - - - - - - - - - 26,10% 3,90% -

Russia (RU) 2383 - - - - - - - - - - - - - -1032

Slovak Republic (SK) 1152 - - 89,60% - - - - - - - - - - -25 1000

Slovenia (SI) 1093 2,30% - - 92,10% - - - - - - - - - -316

South Africa (ZA) 2483 - - - - - - - - - - - - - 12,70%

South Korea (KR) 1315 - - - - - - - - - - - - - -

Spain (ES) 1212 - - - - - - - - - - - - - -1017

Sweden (SE) 1186 - - - - - 85,90% - - - - - - - -

Switzerland (CH) 1037 - - - - - - - - - - - - - -

Taiwan (TW) 2016 - - - - - - - - - - - - - -966

United States (US) 1216 - - - - - - - - - - - - - 79,60%

Uruguay (UY) 1108 - - - - - - - - - - - - - -

Venezuela (VE) 1199 - - - - - - - - - - - - - -Sum 44170 33 9 1048 1000 5 1018 1 1 2 96 19 313 47 1282


981 982 983 984 999ETHNIC (N) % % % % %

Australia (AU) 2183 - - - -

Austria (AT) 1006 - - - - 11

Bulgaria (BG) 1069 - - 1,00% - 6M54 1 27 22

Canada (CA) 1211 4,60% 0,10% 2,30% 1,90% 30M

Chile (CL) 1505 - - - - 1

Czech Republic (CZ) 1276 - - 0,10% - 47M

Denmark (DK) 1322 - - - -

Finland (FI) 1379 - - - -

France (FR) 1669 - - - -

Germany-West (DE-W) 850 - - - -

Germany-East (DE-E) 437 - - - -

Great Britain (GB) 873 - - - -

Hungary (HU) 1021 - - - -

Ireland (IE) 1065 - - - - 6M

Israel Jews (IL-J) 1066 - - - -

Israel Arabs (IL-A) 152 - - - -

Japan (JP) 1102 - - - - 12

Latvia (LV) 1000 - - 1,20% -

New Zealand (NZ) 1036 - - - -

Norway (NO) 1469 - - - -

Poland (PL) 1277 - - - -

Portugal (PT) 1602 - - - -

Philippines (PH) 1200 - - - - 2M

Russia (RU) 2383 - - - - 17

Slovak Republic (SK) 1152 - - 1,50% - 7

Slovenia (SI) 1093 - - 0,60% - 7M4

South Africa (ZA) 2483 - - 0,20% -

South Korea (KR) 1315 - - - -

Spain (ES) 1212 - - - -

Sweden (SE) 1186 - - - - 2M

Switzerland (CH) 1037 - - - -

Taiwan (TW) 2016 - - - - 4

United States (US) 1216 - - 0,30% - 2M

Uruguay (UY) 1108 - - - -

Venezuela (VE) 1199 - - - - Sum 44170 54 1 83 22 102M


MODE: Administrative mode of data-collection Missing Values: 00;98;99 Mode. Interview method. 10. f2f,paper and pencil,no visuals. 11. Visuals. 12. R reading questionnaire. 13. Interpreter, no visuals. 14. Interpreter, visuals. 20. f2f,computer-assisted,no visuals. 21. Visuals. 22. R reading questionnaire. 23. Interpreter,no visuals. 24. Interpreter,visuals. 30. Self-completion,paper a pencil,interviewer attending. 31. Drop-off,pick up later. 32. Drop-off,mailed back by R. 33. Mailed to,hold for pick up. 34. Mailed back by R. 40. Self-completion, computer-assisted 50. Telephone, paper and pencil, no visuals 51. Telephone, paper and pencil, visuals

52. Telephone, paper and pencil, respondent reading questionnaire (DK: Telephone interview after mailing, where the interviewer read out the questionnaire and noted the respondents’ answers)

00. NAP/NAV.


0 10 11 12 14 20 21 30 31 34 40 52MODE (N) % % % % % % % % % % % % %

2183Australia (AU) 2183 - - - - - - - - 100,00% - -

1006Austria (AT) 1006 - - - - 100,00% - - - - - -

1069Bulgaria (BG) 1069 - 100,00% - - - - - - - - -

1211Canada (CA) 1211 - - - - - - - - 100,00% - -

1505Chile (CL) 1505 - 100,00% - - - - - - - - -

1276Czech Republic (CZ) 1276 - 100,00% - - - - - - - - -

1163 159Denmark (DK) 1322 - - - - - - - - 88,00% - 12,00%

1379Finland (FI) 1379 - - - - - - - - 100,00% - -

1669France (FR) 1669 - - - - - - - - 100,00% - -

850 Germany-West (DE-W) 850 - - - - - - 100,00% - - - -

437 Germany-East (DE-E) 437 - - - - - - 100,00% - - - -

873 Great Britain (GB) 873 - - - - - - - 100,00% - - -

1021Hungary (HU) 1021 - - - 100,00% - - - - - - -

1065Ireland (IE) 1065 - - - 100,00% - - - - - - -

1066 Israel Jews (IL-J) 1066 100,00% - - - - - - - - - -

152 Israel Arabs (IL-A) 152 100,00% - - - - - - - - - -

1102Japan (JP) 1102 - 100,00% - - - - - - - - -

1000Latvia (LV) 1000 - 100,00% - - - - - - - - -

1036New Zealand (NZ) 1036 - - - - - - - - 100,00% - -

1469Norway (NO) 1469 - - - - - - - - 100,00% - -

298 978 Poland (PL) 1277 23,40% - - - - - 76,60% - - - -

1602Portugal (PT) 1602 - 100,00% - - - - - - - - -

1200Philippines (PH) 1200 - - - 100,00% - - - - - - -

2383 Russia (RU) 2383 - - - - - - 100,00% - - - -

1152 Slovak Republic (SK) 1152 100,00% - - - - - - - - - -

1093Slovenia (SI) 1093 - - 100,00% - - - - - - - -

South Africa (ZA) 2483 2483M - - - - - - - - - - -1315

South Korea (KR) 1315 100,00% - - - - - - - - - -1212

Spain (ES) 1212 - 100,00% - - - - - - - - -1186

Sweden (SE) 1186 - - - - - - - - 100,00% - -1037

Switzerland (CH) 1037 - - - - - 100,00% - - - - -775 1103 116 22

Taiwan (TW) 2016 38,40% 54,70% 5,80% 1,10% - - - - - - -1216

United States (US) 1216 - - - - - - - - - 100,00% -1108

Uruguay (UY) 1108 - 100,00% - - - - - - - - -1199

Venezuela (VE) 1199 - 100,00% - - - - - - - - -Sum 44170 2483M 4758 12176 1209 3308 1006 1037 4648 873 11296 1216 159


International Occupation Codes: ILO/ISCO 1988 This Note refers to ISCO88 and SPISCO88 and contains the International Occupation Codes of 1988. 1, 2 and 3 digit ISCO codes are also included with trailing zeros to complete four digits. In this way, some countries providing 3-digit ISCO codes only could also be included. Country specific codes were recoded to the 3 digit category to which they belong or, if it didn’t exist, to the 2 or 1 digit category (for example country specific German code 7243 was recoded to 7240). Source: ILO/ ISCO 1988 International Standard Classification of Occupations: International Labour Office, Geneva 1991 Armed forces 110 'Armed forces' Legislators, senior officials and managers 1000 'Legislators, senior officials and managers' 1100 'Legislators and senior officials' 1110 'Legislators and senior government officials' 1120 'Senior government official' 1130 'Traditional chiefs+heads of villages' 1140 'Senior officials of special-interest organisations' 1141 'Senior officials of political party organisations' 1142 'Senior officials of employers´, workers´ and other economic-interest organisations' 1143 'Senior officials of humanitarian and other special-interest organisations' 1200 'Corporate managers' 1210 'Directors and chief executives' 1220 'Production and operations managers' 1221 'Production and operations managers in agriculture, hunting, forestry and fishing' 1222 'Production and operations managers in manufacturing' 1223 'Production and operations managers in construction' 1224 'Production and operations managers in wholesale and retail trade' 1225 'Production and operations managers in restaurants and hotels' 1226 'Production and operations managers in transport, storage and communications' 1227 'Production and operations managers in business services enterprises' 1228 'Production and operations managers in personal care, cleaning and related services' 1229 'Production and operations managers not elsewhere classified' 1230 'Other specialists managers' 1231 'Finance and administration managers' 1232 'Personnel and industrial relations managers' 1233 'Sales and marketing managers' 1234 'Advertising and public relations managers' 1235 'Supply and distribution managers' 1236 'Computing services managers' 1237 'Research and development managers' 1238 'Other department managers nec'


1239 'Other specialist managers not elsewhere classified' 1240 'USA:Miscelaneous office supervisors' 1250 'H:Miscelaneous officers' 1251 'H:High-grade military officer' 1252 'H:Low-grade commissioned officer' 1300 'Managers of small enterprises' 1310 'Managers of small enterprises' 1311 'Managers of small enterprises in agriculture, hunting, forestry and fishing' 1312 'Managers of small enterprises in manufacturing' 1313 'Managers of small enterprises in construction' 1314 'Managers of small enterprises in wholesale and retail trade' 1315 'Managers of small enterprises of restaurants and hotels' 1316 'Managers of small enterprises in transport, storage and communications' 1317 'Managers of small enterprises in business services enterprises' 1318 'Managers of small enterprises in personal care, cleaning and related services' 1319 'Managers of small enterprises not elsewhere classified' Professionals 2000 'Professionals' 2100 'Physical, mathematical and engineering science professionals' 2110 'Physicists, chemists and related professionals' 2111 'Physicists and astronomers' 2112 'Meteorologists' 2113 'Chemists' 2114 'Geologists and geophysicists' 2120 'Mathematicians, statisticians and related professionals' 2121 'Mathematicians and related professionals' 2122 'Statisticians' 2130 'Computing professionals' 2131 'Computer systems designers, analysts and programmers' 2139 'Computing professionals not elsewhere classified' 2140 'Architects, engineers and related professionals' 2141 'Architects, town and traffic planners' 2142 'Civil engineers' 2143 'Electrical engineers' 2144 'Electronics and telecommunications engineers' 2145 'Mechanical engineers' 2146 'Chemical engineers' 2147 'Mining engineers, metallurgists and related professionals' 2148 'Cartographers and surveyors' 2149 'Architects, engineers and related professionals not elsewhere classified' 2200 'Life science and health professionals' 2210 'Life science professionals' 2211 'Biologists, botanists, zoologists and related professionals' 2212 'Pharmacologists, pathologists and related professionals' 2213 'Agronomists and related professionals' 2220 'Health professionals (except nursing) ' 2221 'Medical doctors'


2222 'Dentists' 2223 'Veterinarians' 2224 'Pharmacists' 2229 'Health professionals (except nursing) not elsewhere classified' 2230 'Nursing and midwifery professionals' 2300 'Teaching professionals' 2310 'College, university and higher education teaching professionals' 2320 'Secondary education teaching professionals' 2330 'Primary and pre-primary education teaching professionals' 2331 'Primary education teaching professionals' 2332 'Pre-primary education teaching professionals' 2340 'Special education teaching professionals' 2350 'Other teaching professionals' 2351 'Education methods specialists' 2352 'School inspectors' 2359 'Other teaching professionals not elsewhere classified' 2400 'Other professionals' 2410 'Business professionals' 2411 'Accountants' 2412 'Personnel and careers professionals' 2419 'Business professionals not elsewhere classified' 2420 'Legal professionals' 2421 'Lawyers' 2422 'Judges' 2429 'Legal professionals not elswhere classified' 2430 'Archivists, librarians and related information professionals' 2431 'Archivists and curators' 2432 'Librarians and related information professionals' 2440 'Social science and related professionals' 2441 'Economists' 2442 'Sociologists, anthropologists and related professionals' 2443 'Philosophers, historians and political scientists' 2444 'Philologists, translators and interpreters' 2445 'Psychologists' 2446 'Social work professionals' 2450 'Writers and creative or performing artists' 2451 'Authors, journalists and other writers' 2452 'Sculptors, painters and related artists' 2453 'Composers, musicians and singers' 2454 'Choreographers and dancers' 2455 'Film, stage and related actors and directors' 2460 'Religious professionals' 2470 'Public service administrative professionals' Technicians and associate professionals 3000 'Technicians and associate professionals' 3100 'Physical and engineering science associate professionals' 3110 'Physical and engineering science technicians'


3111 'Chemical and physical science technicians' 3112 'Civil engineering technicians' 3113 'Electrical engineering technicians' 3114 'Electronics and telecommunications engineering technicians' 3115 'Mechanical engineering technicians' 3116 'Chemical engineering technicians' 3117 'Mining and metallurgical technicians' 3118 'Draughtspersons' 3119 'Physical and engineering science technicians not elsewhere classified' 3120 'Computer associate professionals' 3121 'Computer assistants' 3122 'Computer equipment operators' 3123 'Industrial robot controllers' 3130 'Optical and electronic equipment operators' 3131 'Photographers and image and sound recording equipment operators' 3132 'Broadcasting and telecommunications equipment operators' 3133 'Medical equipment operators' 3139 'Optical and electronic equipment operators not elsewhere classified' 3140 'Ship and aircraft controllers and technicians' 3141 'Ships´ engineers' 3142 'Ships´ deck officers and pilots' 3143 'Aircraft pilots and related associate professionals' 3144 'Air traffic controllers' 3145 'Air traffic safety technicians' 3150 'Safety and quality inspectors' 3151 'Building and fire inspectors' 3152 'Safety, health and quality inspectors' 3200 'Life science and health associate professionals' 3210 'Life science technicians and related associate professional' 3211 'Life science technicians' 3212 'Agronomy and forestry technicians' 3213 'Farming and forestry advisers' 3220 'Health associate professionals (except nursing)' 3221 'Medical assistants' 3222 'Hygienists, health and environmental officers' 3223 'Dieticians and nutritionists' 3224 'Optometrists and opticians' 3225 'Dental assistants' 3226 'Physiotherapists and related associate professionals' 3227 'Veterinary assistants' 3228 'Pharmaceutical assistants' 3229 'Health associate professionals (except nursing) not elsewhere classified' 3230 'Nursing and midwifery associate professionals' 3231 'Nursing associate professionals' 3232 'Midwifery associate professionals' 3300 'Teaching associate professionals' 3310 'Primary education teaching associate professionals' 3320 'Pre-primary education teaching associate professionals'


3330 'Special education teaching associate professionals' 3340 'Other teaching associate professionals' 3400 'Other associate professionals' 3410 'Finance and sales associate professionals' 3411 'Securities and finance dealers and brokers' 3412 'Insurance representatives' 3413 'Estate agents' 3414 'Travel consultants and organisers' 3415 'Technical and commercial sales representatives' 3416 'Buyers' 3417 'Appraisers, valuers and auctioneers' 3419 'Finance and sales associate professionals not elsewhere classified' 3420 'Business services agents and trade brokers' 3421 'Trade brokers' 3422 'Clearing and forwarding agents' 3423 'Employment agents and labour contractors' 3429 'Business services agents and trade brokers not elsewhere classified' 3430 'Administrative associate professionals' 3431 'Administrative secretaries and related associate professionals' 3432 'Legal and related business associate professionals' 3433 'Bookkeepers' 3434 'Statistical, mathematical and related associate professionals' 3440 'Customs, tax and related government associate professionals' 3441 'Customs and border inspectors' 3442 'Government tax and excise officials' 3443 'Government social benefits officials' 3444 'Government licensing officials' 3449 'Customs, tax and related government associate professionals not elsewhere classified' 3450 'Police inspectors and detectives' 3460 'Social work associate professionals' 3470 'Artistic, entertainment and sports associate professionals' 3471 'Decorators and commercial designers' 3472 'Radio, television and other announcers' 3473 'Street, night-club and related musicians, singers and dancers' 3474 'Clowns, magicians, acrobats and related associate professionals' 3475 'Athletes, sports persons and related associate professionals' 3480 'Religious associate professionals' Clerks 4000 'Clerks' 4100 'Office clerks' 4110 'Secretaries and keyboard-operating clerks' 4111 'Stenographers and typists' 4112 'Word-processor and related operators' 4113 'Data entry operators' 4114 'Calculating-machine operators' 4115 'Secretaries' 4120 'Numerical clerks'


4121 'Accounting and book-keeping clerks' 4122 'Statistical and finance clerks' 4130 'Material-recording and transport clerks' 4131 'Stock clerks' 4132 'Production clerks' 4133 'Transport clerks' 4140 'Library, mail and related clerks' 4141 'Library and filing clerks' 4142 'Mail carriers and sorting clerks' 4143 'Coding, proof-reading and related clerks' 4144 'Scribes and related workers' 4190 'Other office clerks' 4200 'Customer services clerks' 4210 'Cashiers, tellers and related clerks' 4211 'Cashiers and ticket clerks' 4212 'Tellers and other counter clerks' 4213 'Bookmakers and croupiers' 4214 'Pawnbrokers and money-lenders' 4215 'Debt-collectors and related workers' 4220 'Client information clerks' 4221 'Travel agency and related clerks' 4222 'Receptionists and information clerks' 4223 'Telephone switchboard operators' Service workers and shop and market sales workers 5000 'Service workers and shop and market sales workers' 5100 'Personal and protective services workers' 5110 'Travel attendants and related workers' 5111 'Travel attendants and travel stewards' 5112 'Transport conductors' 5113 'Travel guides' 5120 'Housekeeping and restaurant services workers' 5121 'Housekeepers and related workers' 5122 'Cooks' 5123 'Waiters, waitresses and bartenders' 5130 'Personal care and related workers' 5131 'Child-care workers' 5132 'Institution-based personal care workers' 5133 'Home-based personal care workers' 5139 'Personal care and related workers not elsewhere classified' 5140 'Other personal services workers' 5141 'Hairdressers, barbers, beauticians and related workers' 5142 'Companions and valets' 5143 'Undertakers and embalmers' 5149 'Other personal services workers not elsewhere classified' 5160 'Protective services workers' 5161 'Fire-fighters' 5162 'Police officers'


5163 'Prison guards' 5169 'Protective services workers not elsewhere classified' 5200 'Models, salespersons and demonstrators' 5210 'Fashion and other models' 5220 'Shop, stall and market salespersons and demonstrators' Skilled agricultural and fishery workers 6000 'Skilled agricultural and fishery workers' 6100 'Skilled agricultural and fishery workers' 6110 'Market gardeners and crop growers' 6111 'Field crop and vegetable growers' 6112 'Gardeners, horticultural and nursery growers' 6120 'Animal producers and related workers' 6121 'Dairy and livestock producers' 6122 'Poultry producers ' 6129 'Animal producers and related workers not elsewhere classified' 6130 'Crop and animal producers' 6140 'Forestry and related workers' 6141 'Forestry workers and loggers' 6142 'Charcoal burners and related workers' 6150 'Fishery workers, hunters and trappers' 6151 'Aquatic life cultivation workers' 6152 'Inland and coastal waters fishery workers' 6153 'Deep-sea fishery workers' 6154 'Hunters and trappers' Craft and related trades workers 7000 'Craft and related trades workers' 7100 'Extraction and building trades workers' 7110 'Miners, shotfirers, stone cutters and carvers' 7111 'Miners and quarry workers' 7112 'Shotfirers and blasters' 7113 'Stone splitters, cutters and carvers' 7120 'Building frame and related trades workers' 7121 'Builders' 7122 'Bricklayers and stonemasons' 7123 'Concrete placers, concrete finishers and related workers' 7124 'Carpenters and joiners' 7129 'Building frame and related trades workers not elsewhere classified' 7130 'Building finishers and related trades workers' 7131 'Roofers' 7132 'Floor layers and tile setters' 7133 'Plasterers' 7134 'Insulation workers' 7135 'Glaziers' 7136 'Plumbers and pipe fitters' 7137 'Building and related electricians' 7139 'Building finishers and related trade workers not elsewhere classified'


7140 'Painters, building structure cleaners and related trades workers' 7141 'Painters and related workers' 7143 'Building structure cleaners' 7200 'Metal, machinery and related trades workers' 7210 'Metal moulders, welders, sheet-metal workers, structural-metal preparers, and related trades workers' 7211 'Metal moulders and coremakers' 7212 'Welders and flame cutters' 7213 'Sheet-metal workers' 7214 'Structural-metal preparers and erectors' 7215 'Riggers and cable splicers' 7216 'Underwater workers' 7220 'Blacksmiths, tool-makers and related trades workers' 7221 'Blacksmiths, hammer-smiths and forging-press workers' 7222 'Tool-makers and related workers' 7223 'Machine-tool setters and setter-operators' 7224 'Metal wheel-grinders, polishers and tool sharpeners' 7230 'Machinery mechanics and fitters' 7231 'Motor vehicle mechanics and fitters' 7232 'Aircraft engine mechanics and fitters' 7233 'Agricultural- or industrial-machinery mechanics and fitters' 7240 'Electrical and electronic equipment mechanics and fitters' 7241 'Electrical mechanics fitters and services' 7242 'Electronics mechanics, fitters and servicers' 7244 'Telegraph and telephone installers and servicers' 7245 'Electrical line installers, repairers and cable jointers' 7300 'Precision, handicraft, craft printing and related trades workers' 7310 'Precision workers in metal and related materials' 7311 'Precision-instrument makers and repairers' 7312 'Musical-instrument makers and tuners' 7313 'Jewellery and precious-metal workers' 7320 'Potters, glass-makers and related trades workers' 7321 'Abrasive wheel formers, potters and related workers' 7322 'Glass-makers, cutters, grinders and finishers' 7323 'Glass engravers and etchers' 7324 'Glass, ceramics and related decorative painters' 7330 'Handicraft workers in wood, textile, leather and related materials' 7331 'Handicraft workers in wood and related materials' 7332 'Handicraft workers in textile, leather and related materials' 7340 'Craft printing and related trades workers' 7341 'Compositors, typesetters and related workers' 7342 'Stereotypers and electrotypers' 7343 'Printing engravers and etchers' 7344 'Photographic and related workers' 7345 'Bookbinders and related workers' 7346 'Silk-screen, block and craft textile printers' 7400 'Other craft and related trades workers' 7410 'Food processing and related trades workers'


7411 'Butchers, fishmongers and related food preparers' 7412 'Bakers, pastry-cooks and confectionery makers' 7413 'Dairy-products workers' 7414 'Fruit, vegetable and related preservers' 7415 'Food and beverage tasters and graders' 7416 'Tobacco preparers and tobacco products makers' 7420 'Wood treaters, cabinet-makers and related trades workers' 7421 'Wood treaters' 7422 'Cabinetmakers and related workers' 7423 'Woodworking machine setters and setter-operators' 7424 'Basketry weavers, brush makers and related workers' 7430 'Textile, garment and related trades workers' 7431 'Fibre preparers' 7432 'Weavers, knitters and related workers' 7433 'Tailors, dressmakers and hatters' 7434 'Furriers and related workers' 7435 'Textile, leather and related pattern-makers and cutters' 7436 'Sewers, embroiderers and related workers' 7437 'Upholsterers and related workers' 7440 'Pelt, leather and shoemaking trades workers' 7441 'Pelt dressers, tanners and fellmongers' 7442 'Shoe-makers and related workers' Plant and machine operators and assemblers 8000 'Plant and machine operators and assemblers' 8100 'Stationary plant and related operators' 8110 'Mining and mineral-processing-plant operators' 8111 'Mining plant operators' 8112 'Mineral-ore and stone-processing-plant operators' 8113 'Well drillers and borers and related workers' 8120 'Metal-processing plant operators' 8121 'Ore and metal furnace operators' 8122 'Metal melters, casters and rolling-mill operators' 8123 'Metal heat-treating-plant operators' 8124 'Metal drawers and extruders' 8130 'Glass, ceramics and related plant operators' 8131 'Glass and ceramics kiln and related machine operators' 8139 'Glass, ceramics and related plant operators not elsewhere classified' 8140 'Wood-processing- and papermaking-plant operators' 8141 'Wood-processing-plant operators' 8142 'Paper-pulp plant operators' 8143 'Papermaking-plant operators' 8150 'Chemical-processing-plant operators' 8151 'Crushing-, grinding- and chemical-mixing-machinery operators' 8152 'Chemical-heat-treating-plant operators' 8153 'Chemical-filtering- and separating-equipment operators' 8154 'Chemical-still and reactor operators (except petroleum and natural gas)' 8155 'Petroleum- and natural-gas-refining-plant operators'


8159 'Chemical-processing-plant operators not elsewhere classified' 8160 'Power-production and related plant operators' 8161 'Power-production plant operators' 8162 'Steam-engine and boiler operators' 8163 'Incinerator, water-treatment and related plant operators' 8170 'Industrial robot operators' 8200 'Machine operators and assemblers' 8210 'Metal- and mineral-products machine operators' 8211 'Machine-tool operators' 8212 'Cement and other mineral products machine operators' 8220 'Chemical-products machine operators' 8221 'Pharmaceutical-and toiletry-products machine operators' 8222 'Ammunition- and explosive-products machine operators' 8223 'Metal finishing-, plating- and coating-machine operators' 8224 'Photographic-products machine operators' 8229 'Chemical-products machine operators not elsewhere classified' 8230 'Rubber- and plastic-products machine operators' 8231 'Rubber-products machine operators' 8232 'Plastic-products machine operators' 8240 'Wood-products machine operators' 8250 'Printing-, binding- and paper-products machine operators' 8251 'Printing-machine operators' 8252 'Book-binding-machine operators' 8253 'Paper-products machine operators' 8260 'Textile-, fur- and leather-products machine operators' 8261 'Fibre-preparing-, spinning- and winding-machine operators' 8262 'Weaving- and knitting-machine operators' 8263 'Sewing-machine operators' 8264 'Bleaching-, dyeing- and cleaning-machine operators' 8265 'Fur- and leather-preparing-machine operators' 8266 'Shoemaking- and related machine operators' 8269 'Textile-, fur- and leather-products machine operators not elsewhere classified' 8270 'Food and related products machine operators' 8271 'Meat- and fish-processing-machine operators' 8272 'Dairy-products machine operators' 8273 'Grain- and spice-milling-machine operators' 8274 'Baked-goods, cereal- and chocolate-products machine operators' 8275 'Fruit-, vegetable- and nut-processing-machine operators' 8276 'Sugar production machine operators' 8277 'Tea-, coffee- and cocoa-processing-machine operators' 8278 'Brewers, wine and other beverage machine operators' 8279 'Tobacco production machine operators' 8280 'Assemblers' 8281 'Mechanical-machinery assemblers' 8282 'Electrical-equipment assemblers' 8283 'Electronic-equipment assemblers' 8284 'Metal-, rubber- and plastic-products assemblers' 8285 'Wood and related products assemblers'


8286 'Paperboard, textile and related products assemblers' 8287 'Composite products assemblers' 8290 'Other machine operators not elsewhere classified' 8300 'Drivers and mobile plant operators' 8310 'Locomotive engine drivers and related workers' 8311 'Locomotive engine drivers' 8312 'Railway brakers, signallers and shunters' 8320 'Motor vehicle drivers' 8321 'Motorcycle drivers' 8322 'Car, taxi and van drivers' 8323 'Bus and tram drivers' 8324 'Heavy truck and lorry drivers' 8330 'Agricultural and other mobile plant operators' 8331 'Motorised farm and forestry plant operators' 8332 'Earth-moving and related plant operators' 8333 'Crane, hoist and related plant operators' 8334 'Lifting-truck operators' 8340 'Ships´ deck crews and related workers' Elementary occupations 9000 'Elementary occupations' 9100 'Sales and services elementary occupations' 9110 'Street vendors and related workers' 9111 'Street vendors' 9113 'Door-to-door and telephone salespersons' 9120 'Shoe cleaning and other street services elementary occupations' 9130 'Domestic and related helpers, cleaners and launderers' 9131 'Domestic helpers and cleaners' 9132 'Helpers and cleaners in offices, hotels and other establishments' 9133 'Hand-launderers and pressers' 9140 'Building caretakers, window and related cleaners' 9141 'Building caretakers' 9142 'Vehicle, window and related cleaners' 9150 'Messengers, porters, doorkeepers and related workers' 9151 'Messengers, package and luggage porters and deliverers' 9152 'Doorkeepers, watchpersons and related workers' 9153 'Vending-machine money collectors, meter readers and related workers' 9160 'Garbage collectors and related labourers' 9161 'Garbage collectors' 9162 'Sweepers and related labourers' 9200 'Agricultural, fishery and related labourers' 9210 'Agricultural, fishery and related labourers' 9211 'Farm-hands and labourers' 9212 'Forestry labourers' 9213 'Fishery, hunting and trapping labourers' 9300 'Labourers in mining, construction, manufacturing and transport' 9310 'Mining and construction labourers' 9311 'Mining and quarrying labourers'


9312 'Construction and maintenance labourers: roads, dams and similar constructions' 9313 'Building construction labourers' 9320 'Manufacturing labourers' 9330 'Transport labourers and freight handlers' 9996 'Not classified;inadequately described' 9997 'Refused' 9998 'Dont know' 9999 'Na' 0 'NAP,NAV, No spouse, never had a job'.


Variable List V1 ISSP Study Number........................................................................................................................................................ 1 V2 Respondent ID Number.................................................................................................................................................. 1 V3 Country............................................................................................................................................................................ 2 V4 Most important group R identifies with........................................................................................................................ 3 V5 Second most important group R identifies with........................................................................................................... 5 V6 Third most important group R identifies with.............................................................................................................. 7 V7 How close do you feel to: Your town - city ................................................................................................................. 9 V8 How close do you feel to: Your [county] ..................................................................................................................... 11 V9 How close do you feel to: [country] ............................................................................................................................. 13 V10 How close do you feel to: continent ........................................................................................................................... 15 V11 Important: to have been born in [Country]................................................................................................................. 17 V12 Important: To have [Country nationality] citizenship................................................................................................ 19 V13 Important: To have lived in [Country] for most of one’s life.................................................................................... 21 V14 Important: To be able to speak [Country language] .................................................................................................. 23 V15 Important: To be a [religion]....................................................................................................................................... 25 V16 Important: To respect [Country nationality] political institutions and laws ............................................................. 27 V17 Important: To feel [Country nationality] .................................................................................................................... 29 V18 Important: To have [country nationality] ancestry..................................................................................................... 31 V19 I would rather be a citizen of [Country] than of any other country in the world...................................................... 33 V20 There are some things about [Country] today that make me feel ashamed of [Country] ....................................... 35 V21 The world would be a better place if people from other countries were more like the [Country nationality] ........ 37 V22 Generally speaking, [Country] is a better country than most other countries........................................................... 39 V23 People should support their country even if the country is in the wrong.................................................................. 41 V25 I am often less proud of [Country] than I would like to be......................................................................................... 45 V26 How proud: The way democracy works .................................................................................................................... 47 V27 How proud: Its political influence in the world ......................................................................................................... 49 V28 How proud: [Country’s] economic achievements ..................................................................................................... 51 V29 How proud: Its social security system........................................................................................................................ 53 V30 How proud: Its scientific and technological achievements ....................................................................................... 55 V31 How proud: Its achievements in sports....................................................................................................................... 57 V32 How proud: Its achievements in the arts and literature.............................................................................................. 59 V33 How proud: [Country’S] armed forces....................................................................................................................... 61 V34 How proud: Its history................................................................................................................................................. 63 V35 How proud: Its fair and equal treatment of all groups in society .............................................................................. 65 V36 [Country] should limit the import of foreign products in order to protect its national economy............................. 67 V37 For certain problems, like environment pollution, international bodies should have the right to enforce

solutions......................................................................................................................................................................... 69 V38 [Country] should follow its own interests, even if this leads to conflicts with other nations................................... 71 V39 Foreigners should not be allowed to buy land in [Country] ...................................................................................... 73 V40 [Country’s] television should give preference to [Country] films and programmes................................................ 75 V41 Large international companies are doing more and more damage to local businesses in [Country]. ..................... 77 V42 Free trade leads to better products becoming available in [Country]........................................................................ 79 V43 In general, [Country] should follow the decisions of international organizations to which it belongs, even if the government does not agree with them. ................................................................................................................................ 81 V44 International organizations are taking away too much power from the [Country nationality] government. .......... 83 V45 Increased exposure to foreign films, music, and books is damaging our national and local cultures. .................... 85 V46 A benefit of the Internet is that it makes information available to more and more people worldwide. .................. 87 V47 It is impossible for people who do not share [Country’s] customs and traditions to become fully [Country’s nationality] ............................................................................................................................................................................ 89 V48 Ethnic minorities should be given government assistance to preserve their customs and traditions....................... 91 V49 Help minorities to preserve traditions......................................................................................................................... 93 V50 Immigrants increase crime rates ................................................................................................................................. 95 V51 Immigrants are generally good for [Country’s] economy ......................................................................................... 97 V52 Immigrants take jobs away from people who were born in [Country] ..................................................................... 99 V53 Immigrants improve [Country nationality] society by bringing in new ideas and cultures..................................... 101 V54 Government spends too much money assisting immigrants. .................................................................................... 103


V55 Number of immigrants coming to country................................................................................................................. 105 V56 Are you a citizen of [Country] .................................................................................................................................... 107 V57 Parents citizen of [country] at birth............................................................................................................................. 109 V58 Racial-ethnic group of R ............................................................................................................................................. 111 V59 Children born in [Country] of parents who are not citizens should have the right to become [Country

Nationality] citizens. ..................................................................................................................................................... 122 V60 Children born abroad should have the right to become [Country Nationality] citizens if at least one of their

parents is a [Country Nationality] citizen. ................................................................................................................... 124 V61 Legal immigrants to [Country] who are not citizens should have the same rights as [Country Nationality]

citizens. .......................................................................................................................................................................... 126 V62 [Country] should take stronger measures to exclude illegal immigrants? ................................................................ 128 V63 How proud are you being country national ................................................................................................................ 130 V64 What language speak at home 1st mention ................................................................................................................ 132 V65 What language speak at home 2nd mention............................................................................................................... 140 V66 One nation - Separate nation....................................................................................................................................... 147 V67 How close do you feel to your ethnic group .............................................................................................................. 149 V68 R: More regional or national identity ......................................................................................................................... 151 V69 Heard-read about [the European Union] .................................................................................................................... 153 V70 Benefits from being member of [the European Union] ............................................................................................. 155 V70b Would benefit from being member of [the European Union]................................................................................. 157 V71 [Country] should follow decisions of EU................................................................................................................... 159 V72 EU should have more power than national government............................................................................................ 161 V73 Vote if referendum to become new member.............................................................................................................. 163 V74 EU members: Referendum to remain member .......................................................................................................... 165 SEX R: Sex .......................................................................................................................................................................... 167 AGE R's age......................................................................................................................................................................... 169 MARITAL R's marital status ............................................................................................................................................. 170 COHAB: R: Steady life-partner........................................................................................................................................... 172 EDUCYRS: R's Education I: years in school...................................................................................................................... 174 DEGREE: R's Education II: categories ............................................................................................................................... 180 XX_DEGR: Country Specific Education Degree............................................................................................................... 182 WRKST: R's current employment status............................................................................................................................. 193 SPWRKST: R's Spouse-Partner Current employment status............................................................................................. 195 WRKHRS: R's hours worked weekly.................................................................................................................................. 197 ISCO88: R: Occupation ILO,ISCO 1988 4-digit................................................................................................................ 198 SPISCO88: SP: Occupation ILO,ISCO 1988 4-digit ......................................................................................................... 200 WRKTYPE: R: Working for private,public sector, selfemployed..................................................................................... 202 SPWRKTYP: Rs Spouse-Partner working for private,public sector, selfemployed......................................................... 204 NEMPLOY: Self-employment II - how many employees ................................................................................................. 206 WRKSUP: R Supervises ...................................................................................................................................................... 207 UNION: R's syndical affiliation........................................................................................................................................... 209 HOMPOP: R's size of household......................................................................................................................................... 211 INCOME: Family income.................................................................................................................................................... 214 RINCOME: Respondent’s earnings .................................................................................................................................... 222 HHCYCLE: Household composition.................................................................................................................................. 230 PARTY_LR: R's scale of political ideology ....................................................................................................................... 233 XX_PRTY: Country Specific Vote Intention ..................................................................................................................... 235 VOTE_LE: R: Vote last election: yes, no ........................................................................................................................... 247 RELIG: Religious denomination ......................................................................................................................................... 249 RELIGGRP: R: Religious main groups (derived) .............................................................................................................. 257 ATTEND: Religious services - how often .......................................................................................................................... 259 TOPBOT: R:Top Bottom self-placement 10 point scale.................................................................................................... 261 XX_REG: Country specific region...................................................................................................................................... 263 XX_SIZE: Country specific town size ................................................................................................................................ 276 URBRURAL: Place of residence: urban-rural.................................................................................................................... 285 ETHNIC: R's Ethnicity or nationality (Country specific)................................................................................................... 287 MODE: Administrative mode of data-collection................................................................................................................ 294



Documents

Machine readable Codebook - Carleton University...The annual plenary meeting of the ISSP then adopts the final questionnaire. ISSP questions have to be relevant to all countries and