Imputation rules to improve the education variable in the IAB employment subsample

Abstract

"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." (Author's abstract, IAB-Doku) ((en))IAB-Beschäftigtenstichprobe, Bildungsabschluss, Bildungsverlauf, Datengewinnung, Validität, Stichprobenfehler, Datenaufbereitung, Arbeitsmarktforschung, Reliabilität, Datenqualität, Imputationsverfahren