Imputation Rules to Improve the Education Variable in the IAB Employment Subsample

By Bernd Fitzenberger, A. Osikominu, Robert Voelter. Journal of Contextual Economics – Schmollers Jahrbuch, 2005

425 citations recorded by the source corpus.

The education variable in the IAB employment subsample has two shortcomings: missing values and inconsistencies with the reporting rule. We propose several deductive imputation procedures to improve the variable. They mainly use the multiple education information available in the data because the employees' education is reported at least once a year. We compare the improved data from the different procedures and the original data in typical applications in labor economics: educational composition of employment, wage inequality, and wage regression. We find, that correcting the education variable: (i) shows the educational attainment of the male labor force to be higher than measured with the original data, (ii) gives different values for some measures of wage inequality, and (iii) does not change the estimates in wage regressions much.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/44b10c9dedddf8623a15cd95219fba2b44be6223

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Citations in the corpus

Exporters and the rise in wage inequality: Evidence from German linked employer–employee data (2013, neutral): “To improve the quality of the education variable in the German social security data, Fitzenberger et al. (2006) propose an imputation procedure that relies on extrapolation of past and future information.”
Reallocation Effects of the Minimum Wage (2021, methodology): “D ow nloaded from https://academ ic.oup.com /qje/article/137/1/267/6355463 by guest on 26 D ecem ber 2021 are imputed using the imputation procedure suggested by Fitzenberger, Osikominu, and Völter (2005).”
Labor Supply Shocks, Native Wages, and the Adjustment of Local Employment (2017, methodology): “To improve the consistency of the education variable in our data set, we impute missing values using past and future values of the education variable (see Fitzenberger, Osikominu, and V¨olter 2006).”
Referral-Based Job Search Networks (2016, positive): “(12)To improve the consistency of the education variable in our data, we apply the imputation algorithm suggested by Fitzenberger et al. (2006). (13)Until 1 January 2000, citizenship in Germany was exclusively based on descent (ius sanguinis) and individuals born in Germany by non-German parents wer”
Rent-Sharing and Collective Bargaining Coverage: Evidence from Linked Employer–Employee Data (2009, methodology): “Missing and inconsistent data on education are corrected according to the imputation procedure described in Fitzenberger et al. (2005).”
Migration and Wage‐setting: Reassessing the Labor Market Effects of Migration* (2011, positive): “We therefore imputed the missing information on education by employing the procedure developed by Fitzenberger, Osikominu, and Völter (2005) for an earlier version of the IABS.”