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Semiparametric estimation of a censored regression model with endogeneity

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  • Chen, Songnian
  • Wang, Qian

Abstract

Censoring and endogeneity are common in empirical applications. However, the existing semiparametric estimation methods for the censored regression model with endogeneity under an independence restriction are associated with some drawbacks. In this paper we propose a new semiparametric estimator that overcomes these drawbacks. We derive conditional quantile moment conditions for all the conditional quantiles and propose a moment-based estimator. In particular, we construct two types of moment conditions and develop a computationally attractive estimator. We show that our estimator is consistent and asymptotic normal. A Monte Carlo study indicates that our estimator performs well in finite samples and compares favorably with existing methods.

Suggested Citation

  • Chen, Songnian & Wang, Qian, 2020. "Semiparametric estimation of a censored regression model with endogeneity," Journal of Econometrics, Elsevier, vol. 215(1), pages 239-256.
    • Handle: RePEc:eee:econom:v:215:y:2020:i:1:p:239-256
    DOI: 10.1016/j.jeconom.2019.08.006
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    1. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
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    Cited by:

    1. Jad Beyhum & Lorenzo Tedesco & Ingrid Van Keilegom, 2022. "Instrumental variable quantile regression under random right censoring," Papers 2209.01429, arXiv.org, revised Feb 2023.
    2. Chen, Songnian & Wang, Qian, 2023. "Quantile regression with censoring and sample selection," Journal of Econometrics, Elsevier, vol. 234(1), pages 205-226.
    3. Guo, Jing & Wang, Lei & Zhang, Zhengyu, 2022. "Identification and estimation of a heteroskedastic censored regression model with random coefficient dummy endogenous regressors," Economic Modelling, Elsevier, vol. 110(C).

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    More about this item

    Keywords

    Censored regression; Endogeneity; Semiparametric estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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