TY  - BOOK
AU  - Firpo,Sergio
AU  - Fortin,Nicole M.
AU  - Lemieux,Thomas
ED  - National Bureau of Economic Research.
TI  - Unconditional Quantile Regressions
T2  - NBER technical working paper series
PY  - 2007///
CY  - Cambridge, Mass.
PB  - National Bureau of Economic Research
N1  - July 2007; Hardcopy version available to institutional subscribers
N2  - 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
UR  - https://www.nber.org/papers/t0339
UR  - http://dx.doi.org/10.3386/t0339
ER  -