Department of Economics and Business Economics

Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors

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Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors. / Taylor, Luke Nicholas; Otsu, Taisuke.

In: Econometric Reviews, Vol. 38, No. 1, 2019, p. 4-24.

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Taylor, Luke Nicholas ; Otsu, Taisuke. / Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors. In: Econometric Reviews. 2019 ; Vol. 38, No. 1. pp. 4-24.

Bibtex

@article{07fe933b03bc41b3ab5b96166012b435,
title = "Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors",
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), 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.",
keywords = "Average derivatives, censored dependent variables, endogeneity, nonparametric estimation, nonseparable models, NONPARAMETRIC IDENTIFICATION, TRANSFERS",
author = "Taylor, {Luke Nicholas} and Taisuke Otsu",
year = "2019",
doi = "10.1080/07474938.2016.1235310",
language = "English",
volume = "38",
pages = "4--24",
journal = "Econometric Reviews",
issn = "0747-4938",
publisher = "Taylor & Francis Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors

AU - Taylor, Luke Nicholas

AU - Otsu, Taisuke

PY - 2019

Y1 - 2019

N2 - 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), 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.

AB - 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), 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.

KW - Average derivatives

KW - censored dependent variables

KW - endogeneity

KW - nonparametric estimation

KW - nonseparable models

KW - NONPARAMETRIC IDENTIFICATION

KW - TRANSFERS

U2 - 10.1080/07474938.2016.1235310

DO - 10.1080/07474938.2016.1235310

M3 - Journal article

VL - 38

SP - 4

EP - 24

JO - Econometric Reviews

JF - Econometric Reviews

SN - 0747-4938

IS - 1

ER -