The Luxembourg Income Study at Age 25

1. The Luxembourg Income Study at Age 25 Providing Protected Microdata for the Analysis of Income, Employment and Wealth Prepared for 56th Session of the International Statistical Institute 24 Aug 2007

2. Outline • Background • Microdata Access • LIS Data Security • Data Comparability

3. LIS Background • Research center and microdata archive • Founded founded in 1983 • International board of advisers • Financed by the participating countries • supplemental funding from the Luxembourg government and outside grants

4. LIS Background • Staff • Janet Gornick, Director • Professor of Political Science and Sociology • Baruch College, CUNY, U.S.A. • Markus Jantti, Research Director • Professor of Economics • Åbo Akademi University, Finland • Two offices • Luxembourg & U.S. • 7 researchers and statisticians

5. Goal • Promote comparative social science and policy research • Provide secure method for microdata access • LIS handles contact with data providers • Administration • Confidentiality agreements • Translation • Allows access not available to individual researchers • Country-specific privacy restrictions • Harmonise social and economic microdata • Standardised variable names promote ease of use • Content selection improves comparability

6. LIS Data Base • Socio-economic micro-data • private households • representative of the country population • Availability • 6 waves • every 5 years starting in 1980 • every 4 years starting with Wave VI (2004) • historical data base pre-1980 • 32 countries • expanding in Wave VI and beyond • 150 current data sets • 19 Wave VI data sets ready to be lissified

7. LIS Data Base

8. LIS Research • Used by over 1,500 researchers in 35 countries to analyze economic and social policy effects • poverty • income inequality • employment status • wage patterns • gender inequality • family formation • child-wellbeing • health status • immigration • political behavior and public opinion • women’s economic status • economic gender inequality

9. LIS Research • Articles in major academic journals • Economics • Political science • Sociology • Well-known for use in measuring comparative poverty and income inequality • Used to inform OECD, UN, World Bank • Instrumental in changes in child policy in Great Britain • Bradshaw and Chen (1997)

10. Microdata Access • Public Access • Key Figures • Working Paper Series • User Support • Restricted Access • Microdata Programming Access (“LISsy”) • Web Tabulator • Visiting Scholar Program • Workshops

11. LISsy System • Purpose • Allow for user-programmed analysis • Programs run directly on microdata • Use any of 3 popular statistical packages • Stata, SAS, SPSS • Fully automated system running 24/7 • Results • Output from user programs • Extent of analysis limited only by software functionality and user ability • Not confined to pre-packaged tables or analyses

12. Web Tabulator • Purpose • Provide user-friendly access to microdata • design and create tables derived from LIS datasets • no need for knowledge of statistical packages • secure internet interface • Results • User-created cross-national cross-tabulations • view on-line • export results to text file

13. Visiting Scholar Program • Purpose • Provide direct access to subset of LIS microdata • Individual software need • Analysis requires viewing individual records • Direct access to LIS experts • Application process • LIS pays all expenses • Results • Individually-tailored analysis • Knowledge and guidance of LIS staff

14. Workshops • Purpose • Provide intensive training for new users • Results • Annual summer workshop • 25-30 researchers • Week-long training course • Taught by entire staff • Outside experts and researchers • Country workshops • Individually-tailored workshops • LIS staff travels to researchers

15. LIS Data Security • Users must meet specific criteria • Available for social science research purposes only • No private or commercial use is permitted • Researchers must be: • Working for or attending an academic organization • Member of government or non-profit organization research departments

16. LIS Data Security • Users must register to analyze data • Describe research objectives and projected length of project • Sign a confidentiality pledge • Not to attempt to identify individuals • Not to attempt to copy or list individual records • Re-register annually • update contact information • renew confidentiality pledge

17. LIS Data Security • Accessed by users through e-mail • E-mail system is not in direct contact with the microdata • Database cannot be downloaded

18. LIS Data Security • Users submit requests by e-mail • Clearly identifies sender • LISsy : • Accepts requests from e-mail server • Checks e-mail request • Identity • Registration • Security & confidentiality issues • Sends requests to batch processing • Checks output for confidentiality issues • Returns completed listings by e-mail • Only to the address given during the registration process • Listings only returned with aggregated information

19. Balancing Access and Data Security • Provides user-friendly microdata access • Remote access • 3 popular statistical packages • Individual-specific analysis • Speed • Maintains confidentiality and security • Country-specific requirements • General issues • Registration and identification of user • User output

20. Comparability Challenges • Country : Different institutions/societal norms across countries • Surveys • Different types of original collection instrument • Level of detail of information collected differs • Time : Changes in institutions and surveys • Technical differences • Weighting procedures • Treatment of missing values, imputation methods • Topcoding • Differences in confidentiality requirements

21. LIS Golden Rules Maximise comparability • Set clear definitions for each variable • Follow the definitions as much as possible • Preserve cross-sectional comparability first and comparability over waves after • Ease of use • Create standardised codes within variables • Allow flexibility • Keep country-specific detail to allow users to redefine to suit their specific needs • Preserve as much detail as possible • Document • Warn users of all deviations from the ideal definition

22. On-line Documentation • Survey information • Technical information on the original survey • Data collection methods, reference period, sample, sampling errors etc • Lissification tables • Precise definition and contents of each LIS variable • Explains deviations from ideal variable definitions • Basic descriptives • Unweighted descriptive statistics of each variable • Institutional information • exhaustive information on the tax and transfer programs corresponding to microdata variables

23. Additional Help • Additional comparative databases • country-level policy indicators • welfare states database • family policy database

24. Future Challenges • Expansion • New countries • Less likely to conform to existing definitions • Need to add more country-specific information in addition to core LIS variables? • What is the right mix of data expansion and comparability?