TY  - JOUR
AU  - Firpo,Sergio
AU  - Fortin,Nicole M.
AU  - Lemieux,Thomas
TI  - Unconditional Quantile Regressions
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 339
PY  - 2007
Y2  - July 2007
UR  - http://www.nber.org/papers/t0339
L1  - http://www.nber.org/papers/t0339.pdf
N1  - Author contact info:
Sergio Firpo
São Paulo School of Economics
E-Mail: sergio.firpo@fgv.br

Nicole Fortin
Department of Economics
University of British Columbia
#997-1873 East Mall
Vancouver, BC V6T 1Z1
Canada
Tel: (604) 822-3222
Fax: (604) 822-5915
E-Mail: nifortin@interchange.ubc.ca

Thomas Lemieux
Department of Economics
University of British Columbia
#997-1873 East Mall
Vancouver, BC V6T 1Z1
CANADA
Tel: 604/822-2092
Fax: 604/822-5915
E-Mail: thomas.lemieux@ubc.ca
AB  - 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.
ER  -