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Unconditional Quantile Regressions

  • Sergio Firpo
  • Nicole M. Fortin
  • Thomas Lemieux

We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics. Copyright 2009 The Econometric Society.

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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 77 (2009)
Issue (Month): 3 (05)
Pages: 953-973

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Handle: RePEc:ecm:emetrp:v:77:y:2009:i:3:p:953-973
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  1. Florens, Jean-Pierre & Heckman, James & Meghir, Costas & Vytlacil, Edward, 2003. "Instrumental Variables, Local Instrumental Variables and Control Functions," IDEI Working Papers 249, Institut d'Économie Industrielle (IDEI), Toulouse.
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  8. Fortin, N.M. & Lemieux, T., 1996. "Rank Regressions, Wage Distributions and the Gender Gap," Cahiers de recherche 9607, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  14. repec:cup:cbooks:9780521608275 is not listed on IDEAS
  15. Thomas Lemieux, 2007. "The Changing Nature of Wage Inequality," NBER Working Papers 13523, National Bureau of Economic Research, Inc.
  16. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, 09.
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  18. Rosa L. Matzkin, 1999. "Nonparametric Estimation of Nonadditive Random Functions," Working Papers 38, Universidad de San Andres, Departamento de Economia, revised Sep 2001.
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