Abstract
We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables, and X is independent of the unobservables. We treat models in which Y is censored from above, below, or both. The basic idea is to first estimate the derivative of the conditional mean of Y given X at x with respect to x on the uncensored sample without correcting for the effect of x on the censored population. We then correct the derivative for the effects of the selection bias. We discuss nonparametric and semiparametric estimators for the derivative. We also discuss the cases of discrete regressors and of endogenous regressors in both cross section and panel data contexts.
Original language  English (US) 

Pages (fromto)  17011719 
Number of pages  19 
Journal  Econometrica 
Volume  80 
Issue number  4 
DOIs 

State  Published  Jul 2012 
Keywords
 Average derivatives
 Censored dependent variables
 Extreme quantiles
 Nonparametric
 Nonseparable models
 Semiparametric
ASJC Scopus subject areas
 Economics and Econometrics