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The Blinder–Oaxaca decomposition for nonlinear regression models

Author

Listed:
  • Mathia Sinning

    (Australian National University)

  • Markus Hahn

    (University of Melbourne)

  • Thomas K. Bauer

    (RWI Essen)

Abstract

In this article, a general Blinder–Oaxaca decomposition for nonlinear models is derived, which allows the difference in an outcome variable between two groups to be decomposed into several components. We show how, using nldecompose, this general decomposition can be applied to different models with discrete and limited dependent variables. We further demonstrate how the standard errors of the estimated components can be calculated by using Stata’s bootstrap command as a prefix. Copyright 2008 by StataCorp LP.

Suggested Citation

  • Mathia Sinning & Markus Hahn & Thomas K. Bauer, 2008. "The Blinder–Oaxaca decomposition for nonlinear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 480-492, December.
    • Handle: RePEc:tsj:stataj:v:8:y:2008:i:4:p:480-492
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    References listed on IDEAS

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    6. Ben Jann, 2008. "The Blinder–Oaxaca decomposition for linear regression models," Stata Journal, StataCorp LP, vol. 8(4), pages 453-479, December.
    7. Thomas Bauer & Mathias Sinning, 2008. "An extension of the Blinder–Oaxaca decomposition to nonlinear models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(2), pages 197-206, May.
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