Winsorized mean estimator for censored regression

Myoung Jae Lee

doi:10.1017/S0266466600012986

Winsorized mean estimator for censored regression

Myoung Jae Lee

Research output: Journal Publication › Article › peer-review

15 Citations (Scopus)

Abstract

We introduce a semiparametric estimator for the censored linear regression model. It is based on the regression version of Huber's [6] M-estimator. It includes Powell's [19] censored least absolute deviations estimator as a special case and is related to Powell's [20] symmetrically censored least-squares estimator. We prove strong consistency and derive its asymptotic distribution which is √n-consistent with an easily computable covariance matrix. A small-scale simulation study shows that it works quite well in various cases.

Original language	English
Pages (from-to)	368-382
Number of pages	15
Journal	Econometric Theory
Volume	8
Issue number	3
DOIs	https://doi.org/10.1017/S0266466600012986
Publication status	Published - Sept 1992
Externally published	Yes

ASJC Scopus subject areas

Social Sciences (miscellaneous)
Economics and Econometrics

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title = "Winsorized mean estimator for censored regression",

abstract = "We introduce a semiparametric estimator for the censored linear regression model. It is based on the regression version of Huber's [6] M-estimator. It includes Powell's [19] censored least absolute deviations estimator as a special case and is related to Powell's [20] symmetrically censored least-squares estimator. We prove strong consistency and derive its asymptotic distribution which is √n-consistent with an easily computable covariance matrix. A small-scale simulation study shows that it works quite well in various cases.",

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AB - We introduce a semiparametric estimator for the censored linear regression model. It is based on the regression version of Huber's [6] M-estimator. It includes Powell's [19] censored least absolute deviations estimator as a special case and is related to Powell's [20] symmetrically censored least-squares estimator. We prove strong consistency and derive its asymptotic distribution which is √n-consistent with an easily computable covariance matrix. A small-scale simulation study shows that it works quite well in various cases.

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U2 - 10.1017/S0266466600012986

DO - 10.1017/S0266466600012986

M3 - Article

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VL - 8

SP - 368

EP - 382

JO - Econometric Theory

JF - Econometric Theory

IS - 3

ER -

Winsorized mean estimator for censored regression

Abstract

ASJC Scopus subject areas

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