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On the standard errors of Oaxaca-type decompositions for inter-industry gender wage differentials

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  • Eric S. Lin

    (National Tsing Hua University)

Abstract

Horrace and Oaxaca (2001) treat the regressors in gender wage gap by industry measures as non-stochastic when computing the corresponding standard errors. However, the non-stochastic regressors assumption is thought to be inappropriate in modern econometrics. In this paper, we derive the correct standard errors for the measures proposed by Horrace and Oaxaca (2001). We then empirically apply the derived correct standard errors in regard to the March 1998 Current Population Survey data adopted in Horrace and Oaxaca (2001), as well as the Manpower Utilization Survey in the Taiwan area conducted by the Census Bureau over the years from 1978 to 2003. The empirical results suggest that the researchers would be better to use the correct standard errors derived in this paper, accompanied by the White correction, to arrive at a more accurate statistical inference.

Suggested Citation

  • Eric S. Lin, 2007. "On the standard errors of Oaxaca-type decompositions for inter-industry gender wage differentials," Economics Bulletin, AccessEcon, vol. 10(6), pages 1-11.
    • Handle: RePEc:ebl:ecbull:eb-07j00001
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    References listed on IDEAS

    as
    1. Ben Jann, 2005. "Standard Errors for the Blinder-Oaxaca Decomposition," German Stata Users' Group Meetings 2005 03, Stata Users Group.
    2. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
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    Cited by:

    1. 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.
    2. Lin, Carl, 2012. "Less Myth, More Measurement: Decomposing Excess Returns from the 1989 Minimum Wage Hike," IZA Discussion Papers 6269, Institute of Labor Economics (IZA).
    3. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    4. 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.
    5. Ben Jann, 2008. "A Stata implementation of the Blinder-Oaxaca decomposition," ETH Zurich Sociology Working Papers 5, ETH Zurich, Chair of Sociology, revised 14 May 2008.
    6. 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.
    7. Lamprea-Barragan, T. C & García- Suaza, A. F., 2021. "Decomposing the Gender Pay Gap in Colombia: Do Industry and Occupation Matter?," Documentos de Trabajo 19437, Universidad del Rosario.
    8. Vogel, Matt & van Ham, Maarten, 2016. "Disentangling Neighborhood Effects in Person-Context Research: An Application of a Neighborhood-Based Group Decomposition," IZA Discussion Papers 9793, Institute of Labor Economics (IZA).

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    Keywords

    Gender wage gap;

    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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