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

  • Albrecht, James

    ()

    (Georgetown University)

  • van Vuuren, Aico

    ()

    (VU University Amsterdam)

  • Vroman, Susan

    ()

    (Georgetown University)

In this paper, we use quantile regression decomposition methods to analyze the gender gap between men and women who work full time in the Netherlands. Because the fraction of women working full time in the Netherlands is quite low, sample selection is a serious issue. In addition to shedding light on the sources of the gender gap in the Netherlands, we make two methodological contributions. First, we prove that the Machado-Mata quantile regression decomposition procedure yields consistent and asymptotically normal estimates of the quantiles of the counterfactual distribution that it is designed to simulate. Second, we show how the technique can be extended to account for selection. We find that there is a positive selection of women into full-time work in the Netherlands; i.e., women who get the greatest return to working full time do work full time. We find that about two thirds of this selection is due to observables such as education and experience with the remainder due to unobservables. Our decompositions show that the majority of the gender log wage gap is due to differences between men and women in returns to labor market characteristics rather than to differences in the characteristics. This is true across the wage distribution, particularly in the top half of the distribution.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1400.

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Length: 53 pages
Date of creation: Nov 2004
Date of revision:
Publication status: published in: Labour Economics, 2009, 16 (4), 383-396
Handle: RePEc:iza:izadps:dp1400
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  1. Fitzenberger, Bernd & Wunderlich, Gaby, 2000. "Gender wage differences in West Germany: a cohort analysis," ZEW Discussion Papers 00-48, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  2. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
  3. 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.
  4. 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.
  5. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  6. James Albrecht & Anders Bjorklund & Susan Vroman, 2003. "Is There a Glass Ceiling in Sweden?," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 145-177, January.
  7. 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.
  8. 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.
  9. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  10. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-44, September.
  11. Dorothe Bonjour & Michael Gerfin, 2001. "The unequal distribution of unequal pay - An empirical analysis of the gender wage gap in Switzerland," Empirical Economics, Springer, vol. 26(2), pages 407-427.
  12. 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.
  13. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2006. "Changes in the Distribution of Male and Female Wages Accounting for Employment Composition Using Bounds," CIRJE F-Series CIRJE-F-420, CIRJE, Faculty of Economics, University of Tokyo.
  14. Gerard J. van den Berg, 1998. "Empirical Inference with Equilibrium Search Models of the Labor Market," Tinbergen Institute Discussion Papers 98-089/3, Tinbergen Institute.
  15. repec:dgr:uvatin:2098089 is not listed on IDEAS
  16. 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.
  17. 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.
  18. 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.
  19. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  20. repec:dgr:uvatin:1998089 is not listed on IDEAS
  21. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," Review of Economic Studies, Oxford University Press, vol. 70(1), pages 33-58.
  22. Ichimura, H., 1991. "Semiparametric Least Squares (sls) and Weighted SLS Estimation of Single- Index Models," Papers 264, Minnesota - Center for Economic Research.
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