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Econometrica Vol. 80 No. 4 2012

Estimating Derivatives in Nonseparable Models With Limited Dependent Variables

Joseph G. Altonji1; Hidehiko Ichimura2; Taisuke Otsu3,1,4

1 Yale University · 2 The University of Tokyo · 3 U.S. National Science Foundation · 4 APT Foundation

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.

DOI
10.3982/ecta8004
Volume
80
Issue
4
Pages
1701-1719
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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