Unconditional Quantile Regressions

53 Pages Posted: 13 Jul 2007

See all articles by Sergio Firpo

Sergio Firpo

Insper

Nicole M. Fortin

University of British Columbia (UBC) - Department of Economics

Thomas Lemieux

University of British Columbia (UBC) - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: July 2007

Abstract

We propose a new regression method to estimate the impact of 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 is a widely used tool in robust estimation that can easily be computed for each quantile of interest. We show how standard partial effects, as well as policy effects, can be estimated using our regression approach. We propose three different regression estimators based on a standard OLS regression (RIF-OLS), a logit regression (RIF-Logit), and a nonparametric logit regression (RIF-OLS). We also discuss how our approach can be generalized to other distributional statistics besides quantiles.

Suggested Citation

Firpo, Sergio and Fortin, Nicole M. and Lemieux, Thomas, Unconditional Quantile Regressions (July 2007). NBER Working Paper No. t0339. Available at SSRN: https://ssrn.com/abstract=1000349

Sergio Firpo (Contact Author)

Insper ( email )

R Quata 300
Sao Paulo, 04542-030
Brazil

HOME PAGE: http://https://sites.google.com/site/sergiopfirpo/

Nicole M. Fortin

University of British Columbia (UBC) - Department of Economics ( email )

997-1873 East Mall
Department of Economics
Vancouver, BC V6T1Z1
Canada
604-822-3222 (Phone)
604-822-5915 (Fax)

Thomas Lemieux

University of British Columbia (UBC) - Department of Economics ( email )

997-1873 East Mall
Vancouver, BC V6T 1Z1
Canada

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States
514-343-2395 (Phone)
514-343-5831 (Fax)

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