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On the sensitivity of wage gap decompositions

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  • Huber, Martin
  • Solovyeva, Anna

Abstract

This paper investigates the sensitivity of average wage gap decompositions to methods resting on different assumptions regarding endogeneity of observed characteristics, sample selection into employment, and estimators’functional form. Applying five distinct decomposition techniques to estimate the gender wage gap in the U.S. using data from the National Longitudinal Survey of Youth 1979, we find that the magnitudes of the wage gap components are generally not stable across methods. Furthermore, the definition of the observed characteristics matters: merely including their levels (as frequently seen in wage decompositions) entails smaller explained and larger unexplained components than when including both their levels and histories in the analysis. Given the sensitivity of our results, we advise caution when using wage decompositions for policy recommendations.

Suggested Citation

  • Huber, Martin & Solovyeva, Anna, 2018. "On the sensitivity of wage gap decompositions," FSES Working Papers 497, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    • Handle: RePEc:fri:fribow:fribow00497
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    Cited by:

    1. Hanewald, Katja & Jia, Ruo & Liu, Zining, 2021. "Why is inequality higher among the old? Evidence from China," China Economic Review, Elsevier, vol. 66(C).
    2. Yamamoto, Yuki & Matsumoto, Ken’ichi & Kawata, Keisuke & Kaneko, Shinji, 2019. "Gender-based differences in employment opportunities and wage distribution in Nepal," Journal of Asian Economics, Elsevier, vol. 64(C), pages 1-1.
    3. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
    4. Jeremiah Richey & Nikolas Tromp, 2021. "The Black–White wage gap among young men in 1990 versus 2011: With sample selection adjustments," Bulletin of Economic Research, Wiley Blackwell, vol. 73(4), pages 780-805, October.
    5. Ana Fernandes & Martin Huber & Giannina Vaccaro, 2021. "Gender differences in wage expectations," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-24, June.
    6. Bonaccolto-Töpfer, Marina & Satlukal, Sascha, 2024. "Gender differences in reservation wages: New evidence for Germany," Labour Economics, Elsevier, vol. 91(C).
    7. Valentina S. Consiglio & Denisa M. Sologon, 2022. "The Myth of Equal Opportunity in Germany? Wage Inequality and the Role of (Non-)academic Family Background for Differences in Capital Endowments and Returns on the Labour Market," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 455-493, January.

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    Keywords

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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