| Publications [#238362] of Shakeeb Khan
Journal Articles
- Khan, S; Powell, JL, Two-step estimation of semiparametric censored regression models,
Journal of Econometrics, vol. 103 no. 1-2
(2001),
pp. 73-110 [repository], [doi]
(last updated on 2017/07/05)
Abstract: Root-n-consistent estimators of the regression coefficients in the linear censored regression model under conditional quantile restrictions on the error terms were proposed by Powell (Journal of Econometrics 25 (1984) 303-325, 32 (1986a) 143-155). While those estimators have desirable asymptotic properties under weak regularity conditions, simulation studies have shown these estimators to exhibit a small sample bias in the opposite direction of the least squares bias for censored data. This paper introduces two-step estimators for these models which minimize convex objective functions, and are designed to overcome this finite-sample bias. The paper gives regularity conditions under which the proposed two-step estimators are consistent and asymptotically normal; a Monte Carlo study compares the finite sample behavior of the proposed methods with their one-step counterparts. © 2001 Elsevier Science S.A. All rights reserved.
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