SEMIPARAMETRIC EFFICIENCY FOR CENSORED LINEAR REGRESSION MODELS WITH HETEROSKEDASTIC ERRORS

Tao Chen

Econometric Theory, 2018, vol. 34, issue 1, 228-245

Abstract: Using a simplified approach developed by Severini and Tripathi (2001), we calculate the semiparametric efficiency bound for the finite-dimensional parameters of censored linear regression models with heteroskedastic errors. Under an additional identification at infinity type assumption, we propose an efficient estimator based on a novel result from Lewbel and Linton (2002). An extension to censored partially linear single-index models is also presented.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:cup:etheor:v:34:y:2018:i:01:p:228-245_00

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