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A Simple Solution to the Identification Problem in Detailed Wage Decompositions

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  • Yun, Myeong-Su

    ()
    (Tulane University)

Abstract

Oaxaca and Ransom (1999) show that a detailed decomposition of the coefficients effect is destined to suffer from an identification problem since the detailed coefficients effect attributed to a dummy variable is not invariant to the choice of reference groups. It turns out that the identification problem in the decomposition equation is a disguised identification problem of constant and dummy variables in a regression equation. This paper proposes a simple and natural remedy for this problem by utilizing “normalized” regressions which enable us to identify the constant and estimates of each dummy variable. The identification problem is automatically resolved once we obtain “normalized” regression equations for two comparison groups.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 836.

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Length: 16 pages
Date of creation: Jul 2003
Date of revision:
Publication status: published in: Economic Inquiry, 2005, 43 (4), 766-772
Handle: RePEc:iza:izadps:dp836

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Keywords: coefficients effect; characteristics effect; identification; invariance; detailed decomposition; normalized regression;

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References

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  1. John P. Haisken-DeNew & Christoph M. Schmidt, . "Inter-Industry and Inter-Region Differentials: Mechanics and Interpretation," Working Papers, SELAPO Center for Human Resources 9504, SELAPO Center for Human Resources.
  2. John Ham & Jan Svejnar & Katherine Terrell, 1998. "Unemployment and the Social Safety Net During Transitions to a Market Economy: Evidence from the Czech and Slovak Republic," William Davidson Institute Working Papers Series 169, William Davidson Institute at the University of Michigan.
  3. Radchenko, Stanislav I. & Yun, Myeong-Su, 2003. "A Bayesian approach to decomposing wage differentials," Economics Letters, Elsevier, Elsevier, vol. 78(3), pages 431-436, March.
  4. Edin, Per-Anders & Zetterberg, Johnny, 1992. "Interindustry Wage Differentials: Evidence from Sweden and a Comparison with the United States," American Economic Review, American Economic Association, American Economic Association, vol. 82(5), pages 1341-49, December.
  5. William C. Horrace & Ronald L. Oaxaca, 2001. "Inter-industry wage differentials and the gender wage gap: An identification problem," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 54(3), pages 611-618, April.
  6. Greene, William H & Seaks, Terry G, 1991. "The Restricted Least Squares Estimator: A Pedagogical Note," The Review of Economics and Statistics, MIT Press, vol. 73(3), pages 563-67, August.
  7. Krueger, Alan B & Summers, Lawrence H, 1988. "Efficiency Wages and the Inter-industry Wage Structure," Econometrica, Econometric Society, Econometric Society, vol. 56(2), pages 259-93, March.
  8. 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.
  9. 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, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
  10. F. L. Jones, 1983. "On Decomposing the Wage Gap: A Critical Comment on Blinder's Method," Journal of Human Resources, University of Wisconsin Press, vol. 18(1), pages 126-130.
  11. Ronald L. Oaxaca & Michael R. Ransom, 1999. "Identification in Detailed Wage Decompositions," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 154-157, February.
  12. Kennedy, Peter, 1986. "Interpreting Dummy Variables," The Review of Economics and Statistics, MIT Press, vol. 68(1), pages 174-75, February.
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