Regional Workshop on Integrating a Gender Perspective in the Production of Statistics 1-4 December 2014, Amman, Jordan United Nations Statistics Division

Regional Workshop on Integrating a Gender Perspective in the Production of Statistics1-4 December 2014, Amman, Jordan United Nations Statistics Division

Use of census data for gender statistics and analysis

Margaret MbogoniDemographic and Social Statistics Branch

Statistics Division, DESAUnited Nations, New York


Outline of the Methodological Guidelines for the Gender Analysis of National Population and Housing Census Data

Strengths and weaknesses of census data for gender analysis Examples of questions for gender analysis that have been asked in

national censuses Select topics for gender analysis based on census data

– Relative numbers of females/males by age– Households and families– Marital status– Education and literacy– Fertility– Special population groups

Outline


Methodological Guidelines for the Gender Analysis of National Population and Housing Census Data


Contents: Part 1Introduction

PART ONE - Background and Conceptual Clarifications for Gender Analysis of Census Data

1. Gender in Population and Housing Censuses2. Conceptual Clarifications on Gender Equality and Gender-Responsive Data

Analysis


Contents: Part 2PART TWO – 10 Key Gender Issues Analysed with Census Data3. Fertility4. Mortality5. Sex Ratio at Birth and During the Life Course6. Marital Status, Polygamy, Widowhood, Child Marriage7. Households and Families8. Income, Poverty and Living Conditions9. Education and Literacy10.Work, Economic Activities and Social Protection11.Migration12.Disability


Conclusions and AppendicesConclusionsReferences

APPENDICES1. Gender-Relevant Issues in 2005-2014 Census Forms2. Glossary of Important Gender Terms3. Mapping of Resources on Gender Statistics4. Brief Overview of the Evolution of Gender Statistics5. From Understanding the Gender Data Gap to Improving the Production

and Analysis of Gender Statistics


Structure of each chapter1. What is it?2. Why is it important?3. Data issues4. Tabulations5. Indicators6. Multivariate and further gender analyses7. Interpretation, policy and advocacy


Tables, indicators and analysis The basic premise of the manual is that the census offers

many opportunities for in-depth studies, but that this requires going beyond the standard tabulations and constructing more complex indicators and analyses

Some of these techniques go beyond what NSOs normally consider to be their mandate, namely the preparation of standard general-purpose tables and simple indicators. In order to implement some of the proposals contained in the manual (e.g. multivariate analyses), it may be necessary to build strong research ties with academic and research institutions outside the NSOs


Tables, indicators and analysis

To make the best possible use of the advantages offered by census data

− DISAGGREGATE, DISAGGREGATE, DISAGGREGATE

− Or at least, STANDARDIZE

But have a plan for why you are disaggregating

Control as many intervening factors as you can, if necessary by using multivariate techniques


Strengths of census data for gender analysis Censuses provide universal information on the demographic

and social characteristics and living arrangements of every individual within the scope of the enumeration up to the lowest geographical level– Sex-disaggregated characteristics of the entire population can be

presented in detail down to the lowest geographic level– Locality-specific differentials can be derived– Good for identifying vulnerable groups for targeted interventions

Censuses provide insights into the private and community spheres and (indirectly) into time-use of women and girls, men and boys


Strengths of census data for gender analysis Census data for advocacy: A local-level “early warning

system” on gender inequalities Censuses provide essential background information allowing

for further research on women and men, girls and boys− Identify data gaps on gender issues− Sampling frame


Weaknesses of census data for gender analysis Census data may not have been produced in a gender-

responsive way Census data are of very limited scope and depth (basic

characteristics) Gender-related discrimination is not explicitly measured by

censuses (e.g. why lower schooling rates for females than for males)

The level of analysis for census data is sex, not gender The census data may be outdated or of low quality (e.g. due to

underreporting on women) Data access and the capacity to analyze census data in the

appropriate ways may be problematic


Some interesting questions in censuses

Time spent caring for children: own or of other people (Australia) Looking after, or give any help or support to family members, friends,

neighbours or others because of either: (i)long-term physical or mental ill-health/disability, or (ii) problems related to old age (UK)

Time spent for sick or disabled household members (Aruba, Australia, Iran, Ireland)

Unpaid domestic work carried out in the household (Australia) Matrix of family relationships between household members (Ireland) Children ever born, not only for women, but also for men (Bermuda,

Croatia, Hungary) Reasons to migrate (Cambodia, Nepal, Iran) Previous marriages (Ireland, Nepal, Mauritius, Maldives)



Income data detailed by household members or by source (several)

Trans-gender identity (India, Thailand) Question about homosexual unions (Germany, Brazil, Croatia, UK) Any kind of activity which generated income (several) Fertility preferences (Kazakhstan, Korea) Ownership of land and/or property (Nepal) Assistance received in the delivery (Cambodia) Sex of person sending remittances (El Salvador)



19 countries ask for the date or the age of the woman at the time of her first marriage

11 countries ask for the date (year) or the age of the mother at the time of birth of the first live-born child

24 countries allow the identification of domestic servants in the household

Some countries ask men about polygamous unions Several censuses address causes of disability (Zambia 2010

has spousal violence) 30 countries are asking the questions allowing the

estimation of maternal mortality from the census


Gender analysis based on census data Are there any gender issues (problems, questions related to

women/girls and men/boys in society) regarding:

Their relative numbers?− Age/sex distribution

Where they live?− Spatial distribution (urban/rural)− Migration − Housing conditions

Whom they live with?− Households and families − Marital status


Gender analysis based on census data

Are there any gender issues (problems, questions related to women/girls and men/boys in society) regarding:

Their socio-economic and demographic characteristics?−Education and literacy−Fertility−Mortality−Labour force participation

Vulnerabilities−Special population groups (children, youth, elderly, persons with disabilities)


Population size by age and sex

Numbers of males and females at different ages depends on their numbers at birth, migration patterns and mortality conditions throughout the life cycle

Relative proportions of males to females by age group follow an expected pattern with extreme departures (imbalances) requiring investigation of underlying demographic processes (births, deaths, and migration)


Male and female population size by age Policy relevance:Statistics and indicators on age/sex composition are important to assess the needs of the different age groups (care for pre-school aged children, education for the young, employment for adolescents and working age adults, care for the elderly, etc.)

In terms of distribution by age and sex:− Is there a balanced ratio of females to males or is there significantly

more of one sex?− At what ages are deficits of females or males substantial and what

are the likely causes as well as consequences?


Male and female population size by age (total, rural/urban) Tabulation

- Population by single years of age(age groups)and sex

Indicators− Proportional age distribution by sex− Proportion by sex for each age group − Sex ratios

Data issues− Errors in age reporting− Selective under-reporting− Distinguishing errors from other issues


Relative sizes (males/females)Proportion of population by age and sex, total, Malawi (2008)


Relative sizes (males/females)Proportion of population by age and sex, urban, Malawi (2008)


Relative sizes (males/females)

Proportion of population by age and sex, rural, Malawi (2008)


Proportion of population by sex, by age, total, Malawi (2008)





Relative size (males/females)


Sex ratios at birth, selected age groupsRegions At birth 0-4 years 5-14

years15-24 years

Sub-Saharan Africa 104 103 102 101

Middle East and North Africa 105 105 105 105

South Asia 107 108 108 108

South Asia excl. India 105 105 105 104

East Asia and Pacific 113 114 114 109

East Asia and Pacific excl. China 105 105 105 104

Latin America and the Caribbean 105 104 104 103

CEE/CIS 106 106 105 103

Developing countries 107 107 108 106

World 107 107 107 106


Sex ratio by age, total, urban, rural – Malawi (2008)


Sex ratio by age, total – Qatar (2010)


Households and familiesPolicy relevance: Statistics on household size, composition and headship are

useful indicators for gender analysis with regard to living arrangements of families, likely number of wage earners and overall economic needs that have to be provided for within the household− Families with children present a higher likelihood of vulnerability and

poverty than families without children− Families of lone mothers (e.g., teenagers) versus those of lone fathers in

terms of poverty rates− Care-giving roles of females in home and likely impact on their schooling

and participation in formal employment− Living arrangements of elderly persons


Households and families

Policy relevance:

Important for identifying the prevalence of one-person households, single-parent and multi-generational families

Statistics on household/family characteristics can be linked to data on housing characteristics (living conditions)


Households and families Tabulations (total, urban, rural): − Population in households by age and sex and relationship to head or other

reference member of household, and institutional population by age and sex

− Households by household size and age and sex of head of household or other reference

− Households by type of household, age and sex of head of household or other reference member

− Population in households by age and sex and marital status of head of household or other reference member

− Children under 15 years by age and sex and whether living with: (i) both parents, (ii) mother only, (iii) father only, (iv) parents and grandparents, and (v) grandparents only


Households and families Indicators:

− Percentage distribution of the population by age and sex and living arrangements (with family, alone, institutional, etc)

− Percentage distribution of households by sex and age of head or other reference member of household

− Percentage distribution of households by size (population by household size), by age and sex of head or other reference member of household

− Percentage distribution population by age, sex and marital status of head or other reference member of household

− Percentage distribution of households with children under 15 years of age by age, by presence of both parent, presence of mother only, presence of father only


Households and families Indicators:

− Percentage distribution of households with children under 15 years by number of children, sex and marital status of head

− Percentage distribution of elderly persons by age and sex and living arrangements (couple, living alone, with children, grandchildren, other relatives, non-relatives)


Headship rates


Variety of household compositions – Cambodia 2008Cambodia (2008) Without other

adultsWith other adults

Male head

Female head

Male head

Female head

Head without spouse or children 30,274

68,377 52,970

174,078

Couple without children 121,031 10,135

256,785 19,225

Couple with 1-2 children under 15 485,038 38,463 568,448 45,617Couple with 3+ children under 15 246,319 18,834 288,206 22,632Lone parent with 1-2 children under 15

12,286 81,563 32,561 173,868

Lone parent with 3+ children under 15

2,835 25,275 9,601 49,643


Living arrangements of older persons – Australia (2011)

65-74 years 75–84 years 85 years and over

Total 65 yearsand over

MaleLiving with spouse or partner 73.8 67.6 46.1 69Living with children or other relatives 3.6 4.4 7.3 4.2Group household 2.3 1.7 1.2 2Lone person 15.3 18.5 25.2 17.4Total in private dwellings 98.3 95.1 82.3 95.7In non-private dwelling 1.7 4.9 17.7 4.3Grand total (no.) 740.9 417 132.2 1290.1 FemaleLiving with spouse or partner 59.6 37.4 11.5 44.4Living with children or other relatives 9.5 13.4 14.8 11.6Group household 1.9 1.2 0.7 1.5Lone person 25 38.8 40.5 32.2Total in private dwellings 98.6 92.9 69.3 91.9In non-private dwelling 1.4 7.1 30.7 8.1Grand total (no.) 775 514.5 250.9 1 540.4


Headship problems The definition of ‘head of household’ is vague and in no way

uniform across countries thereby putting into question how the results should be interpreted. At least five different concepts of head of household can be found in censuses:− Main breadwinner− Householder− Main authority− Reference person− Questionnaire respondent

Gender inequality may take place at the intra-household level (e.g. unequal distribution of earnings and consumption among members of the household). Therefore, focusing on female-headed households may not capture these inequalities and be misleading.


Marital statusPolicy relevance:Related to living arrangements, educational attainment, fertility…Early marriage interferes with the educational and career development of women much more than for men, especially when early marriage is associated with early pregnancy and childbirthMarital status is related to property rights in some societiesWomen are more vulnerable to dependency and poverty with early marriage and in likelihood of marital dissolution, e.g., widowhoodPolygamy has many potential negative impacts on women


Marital status Tabulations (total, urban, rural):− Population aged 15 (??) years and older by marital status, age group and

sex− Population aged 15 (??) years and older by age at first marriage, age group

and sex− Total population 15 years and older, by disability status, marital status, age

and sex

Data problems:− Definition of marriage and implications for entry into a union− Age mis-reporting


Marital status Indicators (total, urban, rural)− Percentage distribution of population by age, sex and marital status

o Widowhood and divorce related to vulnerability particularly for women

− Sex distribution within marital status categories by age group− Age at first marriage by sex

o Singulate mean age at marriage by sexo Singulate mean age at marriage by sex and educational attainmento Percentage of women aged 20-24 years old who were married or in a

union before age 18 Early marriage (relates to termination of education and lack of career development

leading to economic dependency and poverty) Adolescent fertility

− Age difference between spouses


Marital status Population 15 years and older by Population 15 years and older bymarital status and sex – Egypt (2006)


Tabulation of Census Data – Australia (2011)


Educational characteristicsPolicy relevance:− School attendance provides information on access by gender

especially for boys and girls− Educational attainment levels of the population give an overview

of the distribution of skills and the extent of preparedness for the labour force and is linked to age at marriage, fertility, socio-economic status, health and survival of women and children

− Literacy is crucial in contemporary society as it ensures access to knowledge and information


Educational characteristicsTabulations (total, urban, rural):− Population 5 years of age and over by school attendance,

educational attainment, age and sex− Population 10 years of age and over by literacy, age and sex− Population 5-29 years of age, by disability status, school

attendance, age and sex− Population 15 years of age and over by disability status,

educational attainment, age and sexData problems:− Literacy is self-declared with likelihood of reluctance of some

persons to admit not being literate and difficulty of administering test to ascertain literacy


Educational characteristicsIndicators (total, urban, rural):− Percentage distribution of population 5 years of age and over by

school attendance, educational attainment, age and sex− Percentage distribution of population 10 years of age and over

by literacy, age and sex− Proportionate distribution of population 5 years of age and over

by school attendance, educational attainment, age and sex− Proportionate distribution of population 10 years of age and

over by literacy, age and sex


School attendance by age and sex, Lesotho (2006) Total Males Females Age Number Percent Number Percent Number Percent Total 497,110 100.0 239,617 48.2 257,493 51.8

6-12 267,021 53.7 130,414 48.8 136,607 51.2 13-17 172,569 34.7 81,064 47.0 91,505 53.0 18-24 57,520 11.6 28,139 48.9 29,381 51.1

Urban 6-12 53,780 47.3 26,514 49.3 27,266 50.7

13-17 39,249 34.5 18,780 47.8 20,469 52.2 18-24 20,601 18.1 10,051 48.8 10,550 51.2

Rural 6-12 213,241 55.5 103,900 48.7 109,341 51.3 13-17 133,320 34.7 62,284 46.7 71,036 53.3 18-24 37,934 9.9 18,619 49.1 19,315 50.9


Educational attainment by sex, Lesotho (2006)


Fertility AnalysisPolicy relevance:Early and repeated child-bearing:−Poses risks for women’s health and often keeps them from obtaining sufficient education or training to ensure a secure future for themselves and their children−Interferes with employment

o When education is truncated, opportunities for employment are limitedo Women tend to withdraw from labour force to attend to family and take

care of young children with likely consequences for career development


Fertility AnalysisTabulations (total, urban, rural):1)Female population 15 years of age and over, by age and number of children ever born alive by sex2)Female population 15 years of age and over, by age and educational attainment and number of children ever born alive by sex3)Female population 15-49 years of age, number of live births, by sex, within the 12 months preceding the census

Data problems:1)Recall errors2)Reporting by a proxy


Basic fertility indicatorsIndicators: Total, urban, rural

Age specific fertility rates Total fertility rate (by education)Parity progression ratios (by education)Adolescent birth rate (15-19)Age at birth of first child born alive (by education)Percentage of childless women (Age 40-44 or 45-49)


Tabulation of Census Data – Fertility Analysis

The standard tables that NSOs prepare in their general-purpose census reports are geared towards the estimation of fertility levels and patterns (ASFRs/TFRs), for the general population or possibly some sub-groups

In practice, this means:− Even though the majority of censuses (except 10) allow disaggregating

births by sex, this is often not done

− In many cases only the total/average number of children by age category of the mother is tabulated, not a distribution by number of children ever born


Tabulation of Census Data – Fertility Analysis (contd.) Disaggregation by sex would allow the computation of Sex

Ratios at Birth (SRBs) which is an important indicator in some countries. Alternatively, one may compute the sex ratio among children under age 1, but this already contains a mortality component.

The distribution by numbers of children ever born would allow the analysis of childlessness by age category and preferably by marital status category. This is a major gender issue in many parts of the world.


Tabulation of Census DataExample 1.B. ChildlessnessProducing statistics on childlessness (preferably by marital status)

serves two purposes: To quantify this phenomenon, which in many countries

represents a significant social stigma, more so for women than for men. In many developed countries, on the other hand, childlessness is clearly on the rise, e.g. 21.0% of women aged 40, in the 2010 census of Finland, as opposed to 9.9% (Cambodia, 2008) and 7.0% (Ethiopia, 2007).

To relate childlessness to certain negative social repercussions, such as divorce/separation. The problem, however, is that this relation can go both ways (Nepal, 2001: 43.5% of divorced women were childless).


Special population groups Children (under 15 years) – school attendance, relationship to

head or reference member of household− Infant and child mortality by sex− Related to the girl child (school attendance, mortality, early marriage)

Youth (15-24 years) – school attendance, educational attainment, literacy, marital status, age at marriage, fertility, economic activity status

Elderly (60 years and over) – marital status, living arrangements Persons with disabilities – place of residence, living

arrangements, marital status, school attendance, educational attainment, economic activity status


Tabulation of Census DataExample 2 Disability and MarriageEl Salvador (2007) - Percentage of ever married 30-39 year olds by sex and

type of disability

Type of Disability Men WomenDifficulty Walking or Moving 57.0 49.9Difficulty in Use of Hands or Arms 53.4 48.0Sight Impairment, Even Using Glasses 68.8 67.0Hearing Impairment, Even Using Hearing Aids 39.3 42.5Speech Impairment 21.4 28.2Mental Retardation or Deficiency 6.9 16.0Difficulty Bathing, Clothing, Eating 31.8 38.7Other Type of Disability 51.9 51.7No Disability of Any Type 79.1 77.1


Conclusion Censuses have obvious limitations, especially with respect to the

subjects that can be investigated: No gender-based violence No female genital mutilation No male and female fertility preferences No distribution of resources within the household No time use information, etc. etc. etc.

However:− A lot of census information is relevant to gender analysis, if properly analyzed− Some censuses have special questions on gender-related topics− Census data can be disaggregated to much more specific levels than is

possible with surveys− Census data may be merged with surveys on specific topics, e.g. poverty

surveys


Thank you

شكرا

Documents

Regional Workshop on Integrating a Gender Perspective in the Production of Statistics 1-4 December 2014, Amman, Jordan United Nations Statistics Division