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On the Ranking Uncertainty of Labor Market Wage Gaps

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  • William C. Horrace

    (University of Arizona)

Abstract

This paper uses multiple comparison methods to perform inference on labor market wage gap estimates from a regression model of wage determination. The regression decomposes a sample of workers' wages into a human capital component and a gender specific component; the gender component is called the gender differential or wage gap and is sometimes interpreted as a measure of sexual discrimination. Using data on fourteen industry classifications (e.g. retail sales, agriculture), a new relative estimator of the wage gap is calculated for each industry. The industries are then ranked based on the magnitude of these estimators, and inference experiments are performed using "multiple comparisons with the best" and "multiple comparisons with a control". The inference indicates that differences in gender discrimination across industry classifications is statistically insignificant at the 95% confidence level and that previous studies which have failed to perform inference on gender wage gap order statistics may be misleading.

Suggested Citation

  • William C. Horrace, 2002. "On the Ranking Uncertainty of Labor Market Wage Gaps," Econometrics 0206003, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0206003
    Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP; pages: 17; figures: included. Multiple comparison inference techniques applied to labor amrket wage gap estimation
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0206/0206003.pdf
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    Citations

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    Cited by:

    1. Yun, Myeong-Su, 2006. "Revisiting Inter-Industry Wage Differentials and the Gender Wage Gap: An Identification Problem," IZA Discussion Papers 2427, Institute of Labor Economics (IZA).
    2. Beyza Ural & William Horrace & Jin Hwa Jung, 2009. "Inter-industry gender wage gaps by knowledge intensity: discrimination and technology in Korea," Applied Economics, Taylor & Francis Journals, vol. 41(11), pages 1437-1452.
    3. William C. Horrace & Christopher F. Parmeter, 2017. "Accounting for Multiplicity in Inference on Economics Journal Rankings," Southern Economic Journal, John Wiley & Sons, vol. 84(1), pages 337-347, July.
    4. William Horrace & Joseph Marchand & Timothy Smeeding, 2008. "Ranking inequality: Applications of multivariate subset selection," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 5-32, March.
    5. Lin, Eric S., 2010. "Gender wage gaps by college major in Taiwan: Empirical evidence from the 1997-2003 Manpower Utilization Survey," Economics of Education Review, Elsevier, vol. 29(1), pages 156-164, February.
    6. Chuang, Hwei-Lin & Lin, Eric S. & Chiu, Shih-Yung, 2018. "The gender wage gap in the financial industry: Evidence from the interindustry ranking," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 246-258.
    7. Myeong-Su Yun & Eric S. Lin, 2015. "Alternative Estimator for Industrial Gender Wage Gaps: A Normalized Regression Approach," Pacific Economic Review, Wiley Blackwell, vol. 20(4), pages 569-587, October.
    8. William C. Horrace, 2002. "Selection Procedures for Order Statistics in Empirical Economic Studies," Econometrics 0206005, University Library of Munich, Germany.

    More about this item

    Keywords

    Labor economics; discrimination; wage differentials; multiple comparisons with the best;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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