Possibilities of exploiting administrative data in short term statistics in Poland

Possibilities of exploiting

administrative data in short

term statistics in Poland

Jacek Kowalewski

STATISTICAL OFFICE IN POZNAŃ

Possibilities of exploiting administrative data in short term statistics in Poland

• possibilities of using existing administrative registers in short term statistics

• assessment of potential usefulness of administrative sources

• analysis of ways to decrease response burden for some companies

• improvement in data completeness and quality• assessment of the possibilities of exploiting register data

for purposes of calibration in the case of incomplete data

Research program

DG1 survey


• business activity report • the basic source of short-term information about

economic activity of businesses• covers only enterprises with over 9 employees • timeliness – 5th day after the end of each month• sales, taxes and subsidies, turnover, employees,

working time• 30 questions in the survey form converted into 460

variables• current prices, constant prices

DG1 survey

SURVEY SCOPE

BY THEMES

SALES

of manufacturing output:-total-domestic-exported (of which goods exported to the Eurozone countries)

of construction output:-total-by type of work-by buidling type

of goods and materials:-In retail trade-online-In wholesale trade

TAXES & SUBSIDIES

Excise duty:-on goods produced for sale-on goods and materials

Specific subsidies

EMPLOYEES

working personsaverage number of employees

SALARIES

Wages and salaries

Dividend

Social insurance premiums

PRICES

of goods and services:-total-domestic-exported

construction work-

price indexes

NEW ORDERS

New orders received:-total-domestic-exportedof which orders exported to the Eurozone countries)

T RANSPORT

Load capacity of road transport

Transport of goods

Transport of passengers-total- city transport- bus intercity transport.

ZP

WORKING TIME

time worked

TURNOVER

Turnover:-total-domestic-exported(of which goods exported to the Eurozone countries)

SURVEYSCOPE

18 594 78 443

18 594(100%)

13 353(about 17%)

Sample31 947

10% refusals

14% reminders

25% explanations

Analysis of the processing of the DG-1 survey

URZĄD STATYSTYCZNY W POZNANIU

sample

aggregation

sections, divisions, classes

generalization

URZĄD STATYSTYCZNY W POZNANIU

Analysis of the processing of the DG-1 survey

18 594(100%)

13 353(about 17%)

Sprawozdanie DG-1

Kontrola i tworzenie

bazy B1

Baza B1

Naliczanie bazy BB

Baza BB

Naliczanie na działy

i sektory w bazie B3(suma sprawozdań)

Baza B3

Uogólnianie działów i

sektorów w bazie B3

Kartoteka

Baza B3

Sumowanie bazy B3na wyższe agregaty

Baza B3

Korekta wskaźników uogólnienia

Baza B3

Czy poprawne?

TAK

NIE

Sumowanie bazy B1na bazy specjalizacji

BP; BR; BH

Bazy Bx

Uogólnianie baz specjalizacjiBP; BR; BH

Uogólnione

bazy Bx

Kartoteka

Korekta wskaźników uogólnienia w bazach

Bx

Bazy Bx

Czy poprawne?

TAK

NIE

Sprawozdanie DG-1

Kontrola i tworzenie

bazy B1

Baza B1

Naliczanie bazy BB

Baza BB

Naliczanie na działy

i sektory w bazie B3(suma sprawozdań)

Baza B3

Uogólnianie działów i

sektorów w bazie B3

Kartoteka

Baza B3

Sumowanie bazy B3na wyższe agregaty

Baza B3

Korekta wskaźników uogólnienia

Baza B3

Czy poprawne?

TAK

NIE

Sumowanie bazy B1na bazy specjalizacji

BP; BR; BH

Bazy Bx

Uogólnianie baz specjalizacjiBP; BR; BH

Uogólnione

bazy Bx

Kartoteka

Korekta wskaźników uogólnienia w bazach

Bx

Bazy Bx

Czy poprawne?

TAK

NIE

18 594 78 443

Digital reporting within the DG-1 survey national average from January 2008 to May 2010

2326

2629 29 30 31 32 34

3743

50

8288 88 88

8788 87

76

87 87 87 87 91 91 91 92 91

0

10

20

30

40

50

60

70

80

90

100

%

The use of data from

administrative registers


• recognition and description of the regulations• comparison of the scope of data used in the registers with

those used by public statistics• comparison of concept definitions and classifications • studies into methodological compatibility• evaluation of the quality of administrative systems to

determine their usefulness as data sources for business statistics

• specification of the scope of data to be used

Review of the systems

Table 1. Evaluation of the quality of administrative systems (max 49)

No. Database / Register Evaluation of system quality

Tax system

1. Database of taxpayers of the personal income tax PIT as a source of data in the field of labour market

41

2. Database of taxpayers of the personal income tax PIT as a source of data in the field of revenues and costs of activities as well as taxes

34

3. Database of taxpayers of the corporate income tax CIT as a source of data in the field of revenues and costs of activities as well as taxes

41

4. Database of taxpayers of the value added tax VAT as a source of data in the field of revenues and costs of activities as well as taxes

44

5. National Register of Taxpayers (KEP) as a source of data in the field of labour market and revenues and costs of activities

49

System of social insurance

1. Central Register of Contribution Payers as a source of data in the field of labour market

39

2. Central Register of the Insured as a source of data in the field of labour market

37

RevenuesDG1 survey vs administrative

registers

Distribution of enterprises by revenue, DG-1, 2008

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Num

ber

of e

nter

pris

es

Revenues

Relationship between the values of accumulated revenue - from DG-1, PIT or CIT register, all units together 2008

PIT

, C

IT r

egis

ter

DG1 survey

Relationship between the values of accumulated revenue - from DG-1, PIT or CIT register, all units together 2008

PIT

, C

IT r

egis

ter

DG1 survey

Usefulness of

calibration


• Transforming administrative data sources into statistical data sets

• General population (MEETS) consisting of companies in the DG-1 survey which were successfully matched with information from the the KEP, CIT, PIT and ZUS databases

• Mean revenue was estimated using a calibration estimator with a known vector of the population total of auxiliary variables (the Horvitz-Thompson estimator was used as a benchmark).

The study procedure

.==ˆ1=

ii

n

iii

sHT ydydY


• Simulation: 5%, 10% and 15% samples were drawn from the MEETS dataset

• After obtaining a sample, information about revenue (dependent variable Y) for some enterprises was replaced with missing data

• Different approaches were used to generate missing data: random fashion (option 1), missing data were attributed to enterprises with the lowest (option 2) and highest (option 3) revenue

• 500 iterations performed for each option, the expected value of revenue, the expected value of the bias

The study procedure - cntd

Table 2. The relative estimation error of estimators of the monthly enterprise revenue (in percent)

Horwitz-Thompson estimator

calibration estimator

sample size

% of missing data option 1 option 2 option 3 option 1 option 2 option 3

5%

5% 28.37 28.71 8.94 14.40 14.35 12.25

10% 29.78 26.61 7.51 14.89 14.06 9.79

15% 32.43 27.49 7.42 15.08 14.60 9.10

10%

5% 20.33 19.32 6.03 10.77 10.57 7.95

10% 19.65 18.94 5.45 9.73 10.04 6.19

15% 20.05 19.74 5.12 11.19 10.27 6.07

15%

5% 14.69 15.11 4.67 8.42 8.15 5.29

10% 16.40 14.15 4.24 8.67 7.87 4.75

15% 16.49 15.30 3.81 8.62 8.03 4.50

Conclusions


• It’s hard to obtain administrative registers (system barrier)• The direct use of administrative data in short-term statistics

is limited by the overly long time of data processing and a long period of waiting for data to be transferred by their administrators.

• Administrative databases can be used as direct data sources for

surveys, as a source of information to complete missing data, as a source of data for comparison with information collected in statistical surveys conducted by means of statistical reporting forms

• The databases are a rich source of potential auxiliary variables, which can improve the quality of estimations by reducing the negative effect of non-response in statistical reporting.

Conclusions


• The use of all available information about selected variables helps to

reduce the respondent burden and improve the efficiency of estimators

• Use of administrative data in producing business statistics may not completely solve all its problems (highly right-skewed distributions,

very high differentiation and high concentration) but it can significantly contribute to minimizing their negative effects.

• Calibration approach can improve the quality of short-term estimation

• Calibration combined with the methodology of small area statistics, can increase the range of estimation methods available in business surveys

Conclusions

To celebrate the 100th anniversary of the Polish Statistical Association

http://www.stat.gov.pl/pts/kongres2012

Documents

Possibilities of exploiting administrative data in short term statistics in Poland