Estimating Derivatives in Nonseparable Models with Limited Dependent Variables

Joseph Altonji, Hidehiko Ichimura and Taisuke Otsu
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Taisuke Otsu: Cowles Foundation, Yale University, https://cowles.yale.edu/

No 1668R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

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.

Keywords: Censored regression; Nonseparable models; Endogenous regressors; Tobit; Extreme quantiles (search for similar items in EconPapers)
JEL-codes: C1 C14 C23 C24 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2008-07, Revised 2011-05
Note: CFP 1369.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Econometrica (July 2012), 80(4): 1701-1719

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Related works:
Journal Article: Estimating Derivatives in Nonseparable Models With Limited Dependent Variables (2012)
Working Paper: Estimating Derivatives in Nonseparable Models with Limited Dependent Variables (2008)
Working Paper: Estimating derivatives in nonseparable models with limited dependent variables (2008)
Working Paper: Estimating Derivatives in Nonseparable Models with Limited Dependent Variables (2008)
Working Paper: Estimating Derivatives in Nonseparable Models with Limited Dependent Variables (2008)
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