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Estimation of nonseparable models with censored dependent variables and endogenous regressors

Taylor, Luke and Otsu, Taisuke (2016) Estimation of nonseparable models with censored dependent variables and endogenous regressors. Econometric Reviews. pp. 1-21. ISSN 0747-4938

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Identification Number: 10.1080/07474938.2016.1235310

Abstract

In this article 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 formalize the identification argument put forward in Altonji, Ichimura, and Otsu (2012 Altonji, J. G., Ichimura, H., Otsu, T. (2012). Estimating derivatives in nonseparable models with limited dependent variables. Econometrica 80:1701–1719. [CrossRef], [Web of Science ®] ), construct a nonparametric estimator, characterize its asymptotic property, and conduct a Monte Carlo investigation to study its 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.

Item Type: Article
Official URL: http://www.tandfonline.com/toc/lecr20/current
Additional Information: © 2016 Taylor & Francis Group
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Date Deposited: 20 Dec 2016 11:50
Last Modified: 20 Oct 2021 02:25
URI: http://eprints.lse.ac.uk/id/eprint/68678

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