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Decomposing the Gender Wage Gap in the Netherlands with Sample Selection Adjustments

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Author Info

  • James Albrecht

    ()
    (Georgetown University, Washington, USA)

  • Aico van Vuuren

    ()
    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

  • Susan Vroman

    ()
    (Georgetown University, Washington, USA)

Abstract

In this paper, we use quantile regression decomposition methods to analyzethe gender gap between men and women who work full time in the Nether-lands. Because the fraction of women working full time in the Netherlands isquite low, sample selection is a serious issue. In addition to shedding light onthe sources of the gender gap in the Netherlands, we make two methodolog-ical contributions. First, we prove that the Machado-Mata quantile regres-sion decomposition procedure yields consistent and asymptotically normalestimates of the quantiles of the counterfactual distribution that it is de-signed to simulate. Second, we show how the technique can be extended toaccount for selection.We find that there is a positive selection of women into full-time workin the Netherlands, i.e., women who get the greatest return to working fulltime do work full time. We find that about two-thirds of this selection isdue to observables such as education and experience with the remainder dueto unobservables. Our decompositions show that the majority of the genderlog wage gap is due to differences between men and women in returns tolabor market characteristics rather than to differences in the characteristics.This is true across the wage distribution, particularly in the top half of thedistribution.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 04-123/3.

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Date of creation: 18 Nov 2004
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Handle: RePEc:dgr:uvatin:20040123

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Keywords: Gender; quantile regression; selection;

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  1. Albrecht, James & Björklund, Anders & Vroman, Susan, 2001. "Is There a Glass Ceiling in Sweden?," IZA Discussion Papers 282, Institute for the Study of Labor (IZA).
  2. Dorothe Bonjour & Michael Gerfin, 1997. "The Unequal Distribution of Unequal Pay - An Empirical Analysis of the Gender Wage Gap in Switzerland," Diskussionsschriften dp9702, Universitaet Bern, Departement Volkswirtschaft.
  3. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2004. "Changes in the distribution of male and female wages accounting for employment composition using bounds," IFS Working Papers W04/25, Institute for Fiscal Studies.
  4. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 33-58, January.
  5. Gubta, Nabanita Datta & Oaxaca, Ronald L. & Smith, Nina, 2002. "Swimming Upstream, Floating Downstream: Trends in the U.S. and Danish Gender Wage Gaps," CLS Working Papers 01-6, University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research.
  6. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
  7. Fitzenberger, Bernd & Wunderlich, Gaby, 2001. "The changing gender gap across the wage distribution in the UK," ZEW Discussion Papers 01-56, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  8. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
  9. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  10. Ichimura, H., 1991. "Semiparametric Least Squares (sls) and Weighted SLS Estimation of Single- Index Models," Papers 264, Minnesota - Center for Economic Research.
  11. Gerard J. van den Berg & Geert Ridder, 1998. "An Empirical Equilibrium Search Model of the Labor Market," Econometrica, Econometric Society, vol. 66(5), pages 1183-1222, September.
  12. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
  13. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  14. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
  15. Bernd Fitzenberger & Gaby Wunderlich, 2002. "Gender Wage Differences in West Germany: A Cohort Analysis," German Economic Review, Verein für Socialpolitik, vol. 3(4), pages 379-414, November.
  16. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  17. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
  18. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier.
  19. Dolado, Juan J. & Llorens, Vanesa, 2004. "Gender Wage Gaps by Education in Spain: Glass Floors versus Glass Ceilings," CEPR Discussion Papers 4203, C.E.P.R. Discussion Papers.
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