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))
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Bibliographic InfoPaper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series FDZ Methodenreport with number 200503_en.
Length: 50 pages
Date of creation: 23 Sep 2005
Date of revision:
Publication status: published in: Schmollers Jahrbuch. Zeitschrift für Wirtschafts- und Sozialwissenschaften, Jg. 126, H. 3 (2006), p. 405-436
IAB-Beschäftigtenstichprobe; Bildungsabschluss; Bildungsverlauf; Datengewinnung; Validität; Stichprobenfehler; Datenaufbereitung; Arbeitsmarktforschung; Reliabilität; Datenqualität; Imputationsverfahren;
Other versions of this item:
- Bernd Fitzenberger & Aderonke Osikominu & Robert Völter, 2006. "Imputation Rules to Improve the Education Variable in the IAB Employment Subsample," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 126(3), pages 405-436.
- Fitzenberger, Bernd & Osikominu, Aderonke & Völter, Robert, 2005. "Imputation Rules to Improve the Education Variable in the IAB Employment Subsample," ZEW Discussion Papers 05-10, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
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