Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors

Taisuke Otsu and Luke Taylor

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: In this paper we develop a nonparametric estimator for the local average response of a censored dependent variable to endogenous regressors in a nonseparable model where the unobservable error term is not restricted to be scalar and where the nonseparable function need not be monotone in the unobservables. We formalise the identification argument put forward in Altonji, Ichimura and Otsu (2012), construct the nonparametric estimator, characterise its asymptotic property, and conduct a Monte Carlo investigation to study the small sample properties. Identification is constructive and is achieved through a control function approach. We show that the estimator is consistent and asymptotically normally distributed. The Monte Carlo results are encouraging.

JEL-codes: C14 C24 C34 (search for similar items in EconPapers)
Date: 2014-08
New Economics Papers: this item is included in nep-ecm and nep-ore
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https://sticerd.lse.ac.uk/dps/em/em575.pdf (application/pdf)

Related works:
Journal Article: Estimation of nonseparable models with censored dependent variables and endogenous regressors (2019)
Working Paper: Estimation of nonseparable models with censored dependent variables and endogenous regressors (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:575

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