1. USAGE OF ADMINISTRATIVE DATA IN EU-SILC SURVEY Signe Bāliņa University of Latvia

2. EU-SILC  EU-SILC - European Union Statistics on Income and Living Conditions  EU-SILC is expected to become the EU reference source for comparative statistics on income distribution and social exclusion at European level

3. The Main Purpose and Main Tasks  The main purpose  To analyse the possibility of the usage of Latvian administrative registers for collecting income data necessary for EU-SILC survey  Main tasks  Gathering of information on existing administrative income registers and the analysis of them  The analysis of possible links and integration between data from EU-SILC survey and administrative registers

4. EU-SILC  EU-SILC   The reference population - all private households and their current members (16+)   Annual data:   Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions   Longitudinal data pertaining to individual-level changes over time, observed periodically over a four year period  Sample size in Latvia:  3750 households per year  7650 persons (16+)

5. EU-SILC Pilot  Population – all private households and their members (16+)  The method of sampling – a two-stage stratified random sample of households  Sample size  500 households  The financial resources of the pilot survey allowed to survey 200 responding households (from 328, response level 61%)  In 200 responding households there were 505 persons from whom 408 persons (16+)

6. EU-SILC Pilot  The income data reference period in Latvian pilot survey was the preceding calendar year (year 2003), which for the respondents is a clear and unambiguous category  The information gathering method – direct interview  Household questioner  Person questioner

7. Identification of Persons and Related Problems  All permanent residents of Latvia have a unique person identification code  The person ID code can be effectively used as a key variable for merging different data bases  During the interviews of the 1st wave of the EU-SILC pilot survey the person ID code was not registered: it was suspected that registration of the person ID code may significantly decrease the survey response rate  After the 1st wave the person ID code was identified for 311 persons or 60% of respondents  In the 2nd wave respondents were asked also about their person ID code:  485 person ID codes were identified  For 20 persons identification of their person ID codes was impossible

8. Income Information of Administrative Registers  The main information sources:  State Revenue Service (SRS):  Monthly employers statutory declaration of income and tax about their employees  Statutory annual income declarations for self-employed persons (till April of the next calendar year)  The annual tax declaration of any tax payer (on voluntary base)  Specifying all income from different sources  Calculated and withhold taxes  Expenses redeemed from taxes (including contributions to the private pension funds)  State Social Insurance Agency information (SSIA)  Different type of pensions  Social benefits and allowances paid to Latvian residents

9. Information from SRS  Information requested about 485 person  Received income and tax information about 201 persons, from who were 178 respondents Income sourceFrequenc y Wages and salaries 189 Income declaration 13 Dividends 28 Income from partnership 1 Income from intellectual property 1 Pensions 8 Sickness benefits 1 Other incomes 1 TOTAL242

10. Persons' Status at the Time of EU-SILC Pilot Study, no Information from SRS Darba un ikdienas aktivitātes Frequency Working full time8 Working part-time6 Unemployed15 Pupil, student, further training, unpaid work experience18 In retirement or in early retirement97 Permanently disabled or/and unfit to work4 Fulfilling domestic tasks12 Other inactive person45 Persons under 16 years79 TOTAL284

11. Possible Information from SSIA  The SSIA register contains income information of several respondent groups of the EU-SILC survey:  pensioners – 30.5% of respondents  unemployed persons – 7.5% of respondents  persons receiving sickness benefits – 4.0% of respondents  persons receiving disability benefits – 3.3% of respondents  persons receiving maternity benefit – 2.5% of respondents  In the SSIA register it is possible to find some income information of more than 40% of all respondents of the EU-SILC pilot survey

12. Information about Wages and Salaries EU-SILCTotal AvailableNot Available Information about wages and salaries from SRS 12859187 Information about other type of income from SRS 11314 TOTAL12972201

13. Gross Wages and Salaries (Annual Data) Frequency%Cumulative % Gross income in EU-SILC > Gross income in SRS 1318.8   10% 2942.060.9 Gross income in SRS > Gross income in EU-SILC 2739.1100.0 TOTAL69100.0

14. Gross Wages and Salaries, Annual Data (n=69)  Coefficient of correlation 0.983, p-value < 0.01  SRS:  Average wage Ls 2956.71  Median Ls 1824.86  EU-SILC  Average wage Ls 2663.91  Median Ls 1509.00

15. Gross Wages and Salaries, Monthly Data Frequency%Cumulative % Gross income in EU-SILC > Gross income in SRS 430.8   10% 538.569.2 Gross income in SRS > Gross income in EU-SILC 430.8100.0 TOTAL13100.0

16. Gross Wages and Salaries, Monthly Data (n=13)  Coefficient of correlation 0.139, = p-value = 0.651 > 0.05

17. Net Wages and Salaries, Annual Data Frequency%Cumulative % Gross income in EU-SILC > Gross income in SRS 38   10% 28 66 Gross income in SRS > Gross income in EU-SILC 34 100 TOTAL100

18. Net Wages and Salaries, Annual Data (n=100)  Coefficient of correlation 0.884, p-value < 0.01  SRS:  Average wage Ls 1944.98  Median Ls 1211.21  EU-SILC  Average wage Ls 2115.94  Median Ls 1480.00

19. Net Wages and Salaries, Monthly Data (n=23)  Coefficient of correlation 0.864, p-value < 0.01

20. Conclusions  Inclusion of a person identification code in the EU-SILC questionnaire is necessary  It is no significant difference in annual gross/net wages and salaries from SRS and EU-SILC data  It is a significant difference in annual gross/net wages and salaries from SRS and EU-SILC data  It is necessary to solve the existing legislation problems in usage of the person level income data from SSIA register

21. Conclusions  The usage of register data:  Allows significant reduction of the response burden for persons participating in the EU-SILC survey  Allows obtaining detailed and more complete income data on wages and salaries  Promotes the survey response rate  Improves the total quality of the survey