TY - JOUR
AU - Altonji,Joseph G.
AU - Ichimura,Hidehiko
AU - Otsu,Taisuke
TI - Estimating Derivatives in Nonseparable Models with Limited Dependent Variables
JF - National Bureau of Economic Research Working Paper Series
VL - No. 14161
PY - 2008
Y2 - July 2008
DO - 10.3386/w14161
UR - http://www.nber.org/papers/w14161
L1 - http://www.nber.org/papers/w14161.pdf
N1 - Author contact info:
Joseph G. Altonji
Department of Economics
Yale University
Box 208264
New Haven, CT 06520-8264
Tel: 203/432-6285
Fax: 203/432-5591
E-Mail: joseph.altonji@yale.edu
Hidehiko Ichimura
Graduate School of Economics
University of Tokyo
Hongo 7-3-1
Tokyo 113-0033
Japan
E-Mail: ichimura@e.u-tokyo.ac.jp
Taisuke Otsu
Department of Economics
Yale University
Box 208281
New Haven, CT 06520-8281
E-Mail: taisuke.otsu@yale.edu
AB - 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. We treat models in which Y is censored from above or below or potentially from 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 changes in x induced on the censored population. We then correct the derivative for the effects of the selection bias. We propose nonparametric and semiparametric estimators for the derivative. As extensions, we discuss the cases of discrete regressors, measurement error in dependent variables, and endogenous regressors in a cross section and panel data context.
ER -