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Counterfactual decomposition of changes in wage distributions using quantile regression

  • José Mata
  • José A. F. Machado

    (Faculdade de Economia, Universidade Nova de Lisboa, Portugal)

We propose a method to decompose the changes in the wage distribution over a period of time in several factors contributing to those changes. The method is based on the estimation of marginal wage distributions consistent with a conditional distribution estimated by quantile regression as well as with any hypothesized distribution for the covariates. Comparing the marginal distributions implied by different distributions for the covariates, one is then able to perform counterfactual exercises. The proposed methodology enables the identification of the sources of the increased wage inequality observed in most countries. Specifically, it decomposes the changes in the wage distribution over a period of time into several factors contributing to those changes, namely by discriminating between changes in the characteristics of the working population and changes in the returns to these characteristics. We apply this methodology to Portuguese data for the period 1986-1995, and find that the observed increase in educational levels contributed decisively towards greater wage inequality. Copyright © 2005 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 20 (2005)
Issue (Month): 4 ()
Pages: 445-465

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Handle: RePEc:jae:japmet:v:20:y:2005:i:4:p:445-465
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  1. Jeffrey A. Mills & Sourushe Zandvakili, 1999. "Statistical Inference via Bootstrapping for Measures of Inequality," Macroeconomics 9902003, EconWPA.
  2. Ronald Oaxaca, 1971. "Male-Female Wage Differentials in Urban Labor Markets," Working Papers 396, Princeton University, Department of Economics, Industrial Relations Section..
  3. Gosling, Amanda & Machin, Stephen & Meghir, Costas, 2000. "The Changing Distribution of Male Wages in the U.K," Review of Economic Studies, Wiley Blackwell, vol. 67(4), pages 635-66, October.
  4. 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.
  5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  6. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
  7. Mata, Jose & Machado, Jose A. F., 1996. "Firm start-up size: A conditional quantile approach," European Economic Review, Elsevier, vol. 40(6), pages 1305-1323, June.
  8. Francine D. Blau & Lawrence M. Kahn, 1994. "International Differences in Male Wage Inequality: Institutions versus Market Forces," NBER Working Papers 4678, National Bureau of Economic Research, Inc.
  9. José Ferreira Machado & José Mata, 1998. "Earning Functions in Portugal 1982-1994: Evidence From Quantile Regressions," Working Papers w199802, Banco de Portugal, Economics and Research Department.
  10. Fitzenberger, Bernd & Kurz, Claudia, 1997. "New insights on earnings trends across skill groups and industries in West Germany," Discussion Papers 38, University of Konstanz, Center for International Labor Economics (CILE).
  11. Jaume Garcia & Pedro J. Hernández & Ángel López Nicolás, 1998. "How wide is the gap? An investigation of gender wage differences using quantile regression," Economics Working Papers 287, Department of Economics and Business, Universitat Pompeu Fabra.
  12. George E. Johnson, 1997. "Changes in Earnings Inequality: The Role of Demand Shifts," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 41-54, Spring.
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