Analysis of the German linked employer-employee database IAB

1. Analysis of the German linked employer-employee database IAB 2nd WORKS workshop on Measuring changes in work by organisation surveys Stefan Bender 19 March 2007, Leuven

2. Contents • the LIAB • individual level: process-generated (adminstrative) data • firm level: IAB Establishment Panel • LIAB data models • data access via FDZ

3. Data Sources and Paths Data Sources FDZ Data IAB Establishment Panel Surveys Social security notifications Establishment History Panel Employment statistics BA Employment Panel Employment history Employee and benefit recipient history IAB Employment Samples Process-generated data Linked Employer Employee Data Benefit recipient history Integrated Employment Biographies Sample Participants in measures Applicants pool

4. Two data sources for the LIAB Individuals: Employee and benefit recipient history of IAB (BLH) Process-generated data Establishments: IAB-Establishment Panel Survey data

5. Personal information for the LIAB based on two different administrative processes • process data generated by internal procedures in the BA (benefit recipient history) • notification process of the social security system (employees covered by social security)

6. Advantages • no selective non-response, no panel attrition • to some extent, very accurate information • high number of observations (entire population in some cases) • to some extent, large sample periods • Disadvantages • main purpose of surveys is the supply of appropriate information for administrative usage • research constitutes only secondary usage • no research related variables • type and size of survey vary

7. Notification process of employment statistics • Data generation due to contribution assessment and benefit calculation for the federal health, pension, and unemployment insurance as well as the insurance for long-term care for the elderly • at least one notification per year (on Dec 31 if employment is continued) • exit notice (for example due to change of company or health insurance)

8. Particularities • every employment covered by social security is reported (therefore, simultaneous employment is captured as well) • 80% of the German labour force is in the data; not included self-employed, civil servants • employment history (since 1975 for West Germany, since 1992 for East Germany as well) on a daily basis

9. Structural breaks: • different industrial classifications (German code, NACE) • new variables and values after 1999: contribution group, person group, marginal part-time employment • Data quality: • contribution and benefit related variables are more reliable than variables exclusively generated for statistics • examples of reliable variables: wage, start date, end date, sex, age, place of work • examples of less reliable variables: education, profession, occupational status, nationality

10. Benefit recipient history • Data on receipt of unemployment benefits, unemployment assistance and maintenance allowance drawn from data of the Federal Employment Agency • nearly 70% of all unemployed are covered by the data (stock and duration) • data since 1975 available

11. IAB Establishment Panel Establishment information for the LIAB • annual interview on voluntary basis (waves 1993-1996; East Germany since 1996); around 16,000 businesses at the moment • stratified random sample by industries firm size classes and region (target population: all businesses with at least one employee covered by social security on June 30 of previous year) • since 2001: representativeness on federal state level

12. IAB Establishment Panel II • Topics: development of employment, business policy and development, investments, in-house innovations, government subsidies, personnel structure, vocational training and apprenticeship places, recruitments and dismissals, personnel search, wages, working hours, training programmes, general company information • main focus varies over years

13. Linked Employer Employee Data of IAB (LIAB) • the IAB Establishment Panel data are matched with individual data from the employment history and the benefit recipient history • connection of the IAB Estabishment Panel with individual data from the employee and benefit recipient history (BLH) (around 1% of all businesses and 8% to 10% of all employees covered by social security) • enormous amount of data • consistency problems between both datasets

14. LIAB for the users • enormous amount of data (storage problems) • Solution: different data models and data versions account for • different evaluation requests • LIAB cross-sectional model • LIAB longitudinal model

15. LIAB cross-sectional model • contains employments reported on June 30 of every year in which the survey was conducted • the cross-sectional data can be combined to construct a panel • if employees leave a company, no further information will be available for those employees

16. LIAB longitudinal model • contains all employment and benefit reports of individuals in a certain period • of time • time-consuming data preparation and calculation • if employees leave a company, further information will be available for those employees

17. cross-sectional data 1998 working histories persons version 2 working histories persons version 2 persons version 2 persons version 2 plants version 2 plants version 1 plants version 2 1991 1993 1996 2000 2002 2003 • Overview over LIAB versions working histories persons version 1 persons version 1 t

18. First version of the LIAB longitudinal model • # of firms: 2,131 (West); 2,116 (East) • # of employees: 1 Mio. (West); 0.7 Mio. (East) • # of notifications: 14 Mio. (West); 11 Mio. (East)

19. Data access via the FDZ

20. Data access • For reasons of data protection, LIAB data can be analyzed through on-site use only. • You have to visit Nuremberg at least once. • There are possibilities for co-financing your stay. • After building up “your” LIAB, remote data access is possible.

21. How to get to Nuremberg • You have to complete a request form, which is on our web-site and submit it to the RDC. • The request documents submitted are verified by the RDC in cooperation with the Federal Ministry of Labour and Social Affairs. • A use agreement is concluded between the researcher and the RDC. Finding a date for the research visit. The maximum duration of a research visit is two weeks.  • Prior to the research visit, the user can submit workable and documented programs in SPSS, Stata or SAS created on the basis of our test data. • On-site use of data at the FDZ is subject to adherence to the guidelines for on-site use. Analysis results are verified for compliance with the given data protection legislation and transmitted to the user no later than five days after the research visit.

22. Working tools • data reports • user guides • test data (outlook: labels in english) • code plans • exemplary syntax • meta data (near future)

23. More information regarding • content of available datasets • data access possibilities • publications • working tools http://fdz.iab.de/en THANK YOU for your attention!!!

24. BACKUP

25. Current FDZ projects with regard to the generation of new linked data or data access improvements to linked data • „Factual Anonymisation/Disclosure of Official Business Survey Data“ (IAW, Destatis, Stat. Landesämter): SUF of IAB Establishment Panel and, possibly, of a LIAB • Linking establishment data of IAB with establishment data of the statistical offices (KombiFiD)

26. Inconsistencies of establishment and individual data a) the number of employees covered by social security in the IAB Establishment Panel differs from the aggregate numbers of the employment statistics b) no information on employees are found for an interviewed establishment a) information can be inaccurate due to rapid labor turnover or incorrect recollection  tolerances should be permitted when comparing, here: 1 to 5 employees : 40 percent variation 5 to 19 employees: 30 percent variation 20 to 100 employees : 20 percent variation 100 and more employees: 10 percent variation b) can be examined directly

27. Deficiencies and inconsistencies of establishment and individual data Result for currently available LIAB data (in percent of establishments; reference date June 30, 1993 through 2001) :

28. PanelWhiz • Collection of Stata add-ons for dealing with large scale panel data sets (SOEP, Mikrozensus, . . . ) • PanelWhiz now supports the IAB Establishment Panel (coming soon) • People behind PanelWhiz IAB-BP • Author: John Haisken-DeNew • Contributers: Markus Hahn and Matthias Vorell • Forschungsdatenzentrum (FDZ) at the IAB • Further information: www.panelwhiz.eu

29. Main topics of Panelwhiz Main idea: item correspondence • Item = vector of variables • variable names can change over the years Output data set - Long format • idnum-year observations • Allows immediate use with Stata’s panel analysis commands Plugins • Ensure time consistency over time • Cure data errors • Create new variables (real values, etc.)

30. Working with PanelWhiz User-friendly interface: easy access to all variables • Internet-like browsing through the data set • Categories • Keywords Projects: Composing data sets as easy as "internet shopping" • Adding, removing, opening, appending, saving, . . . • Projects can be shared because they contain no actual data • Web library Retrieval do-files: • Can directly be used with the original data • Original data files of the Betriebspanel ) Long format • Serve as documentation

31. How can I get PanelWhiz IAB-BP? • Wait until it’s ready • Fill out the PanelWhiz user contract • Make a direct donation to UNICEF (€20) • Send the filled-out contract with an evidence of your donation to John Haisken-DeNew at RWI-Essen • Wait again • You receive an email with the installation program and a password • Then install PanelWhiz Installation will take 2minThe Betriebspanel test data are already included