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A Principled Approach to Assessing Missing-Wage Induced Selection Bias

Author

Listed:
  • Duo Qin

    (Department of Economics, SOAS University of London, UK)

  • Sophie van Huellen

    (Department of Economics, SOAS University of London, UK)

  • Raghda Elshafie

    (The Center for Victims of Torture, Egypt)

  • Yimeng Liu

    (School of Economics and Resource Management, Beijing Normal University, China)

  • Thanos Moraitis

    (Department of Economics, SOAS University of London, UK)

Abstract

Multiple imputation (MI) techniques are applied to simulate missing wage rates of non-working wives under the missing-at-random (MAR) condition. The assumed selection effect of the labour force participation decision is framed as deviations of the imputed wage rates from MAR. By varying the deviations, we assess the severity of subsequent selection bias in standard human capital models through sensitivity analyses (SA). Our experiments show that the bias remains largely insignificant. While similar findings are possibly attainable through the Heckman procedure, SA under the MI approach provides a more structured and principled approach to assessing selection bias.

Suggested Citation

  • Duo Qin & Sophie van Huellen & Raghda Elshafie & Yimeng Liu & Thanos Moraitis, 2019. "A Principled Approach to Assessing Missing-Wage Induced Selection Bias," Working Papers 216, Department of Economics, SOAS University of London, UK.
    • Handle: RePEc:soa:wpaper:216
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    File URL: https://www.soas.ac.uk/sites/default/files/2022-10/economics-wp216.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Sophie van Huellen & Duo Qin, 2019. "Compulsory Schooling and Returns to Education: A Re-Examination," Econometrics, MDPI, vol. 7(3), pages 1-20, September.

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    More about this item

    Keywords

    wage; labour supply; selection; missing at random; multiple imputation;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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