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Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis

Author

Listed:
  • Dauth, Wolfgang

    (Institute for Employment Research (IAB), Nuremberg, Germany ; Univ. Würzburg ; IZA)

  • Eppelsheimer, Johann

    (IAB)

Abstract

"Preparing the Sample of Integrated Labour Market Biographies (SIAB) for scientific analysis is a complicated and error-prone task. This paper elaborates on the steps necessary to prepare the SIAB and provides examples of how the preparation can be done. Among other topics covered, we show how to generate and merge additional variables, impute right-censored wages, deal with parallel employment episodes, and clean the dataset. Finally, we present a case study on the individual long-term effects of job loss from plant closure to demonstrate how our prepared version of the SIAB can be used to carry out an empirical analysis. The supplementary material of this paper contains extensively commented Stata do-files to replicate our data preparation and the subsequent analysis." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Dauth, Wolfgang & Eppelsheimer, Johann, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54, pages 1-010.
    • Handle: RePEc:iab:iabjlr:v:54:i::p:a010
    DOI: 10.1186/s12651-020-00275-9
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    References listed on IDEAS

    as
    1. Fackler, Daniel & Müller, Steffen & Stegmaier, Jens, 2017. "Explaining wage losses after job displacement: Employer size and lost firm rents," IWH Discussion Papers 32/2017, Halle Institute for Economic Research (IWH).
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    Citations

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    Cited by:

    1. Sona Badalyan, 2025. "Crowded Career Ladders? Intra-Firm Spillovers of Raised Retirement Age," CERGE-EI Working Papers wp810, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    2. Martin Lábaj & Tomáš Oleš & Gabriel Procházka, 2025. "Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(4), pages 953-1001, December.
    3. Egshiglen Batbayar & Christoph Breunig & Peter Haan & Boryana Ilieva, 2026. "Quantile Selection in the Gender Pay Gap," Rationality and Competition Discussion Paper Series 560, CRC TRR 190 Rationality and Competition.
    4. Beckmannshagen Mattis & König Johannes & Retter Isabella & Schluter Christian & Schröder Carsten & Tchokni Yogam, 2026. "Dealing with Censored Earnings in Register Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 246(1-2), pages 5-34.

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    Keywords

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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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