Imputation rules for the implementation of the pre-unification education variable in the BASiD Data Set

Using combined data from the German Pension Insurance and the Federal Employment Agency (BASiD), this study proposes different procedures for imputing the pre-unification education variable in the BASiD data. To do so, we exploit information on education-related periods that are creditable for the Pension Insurance. Combining these periods with information on the educational system in the former GDR, we propose three different imputation procedures, which we validate using external GDR census data for selected age groups. A common result from all procedures is that they tend to underpredict (overpredict) the share of high-skilled (low-skilled) for the oldest age groups. Comparing our imputed education variable with information on educational attainment from the Integrated Employment Biographies (IEB) reveals that the best match is obtained for the vocational training degree. Although regressions show that misclassification with respect to IEB information is clearly related to observables, we do not find any systematic pattern across skill groups.