Show simple item record Chen, S Khan, S 2010-06-28T18:50:14Z 2001-12-01
dc.identifier.citation Econometric Theory, 2001, 17 (3), pp. 567 - 590
dc.identifier.issn 0266-4666
dc.description.abstract In this paper we propose an estimation procedure for a censored regression model where the latent regression function has a partially linear form. Based on a conditional quantile restriction, we estimate the model by a two stage procedure. The first stage nonparametrically estimates the conditional quantile function at in-sample and appropriate out-of-sample points, and the second stage involves a simple weighted least squares procedure. The proposed procedure is shown to have desirable asymptotic properties under regularity conditions that are standard in the literature. A small scale simulation study indicates that the estimator performs well in moderately sized samples.
dc.format.extent 567 - 590
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartof Econometric Theory
dc.title Semiparametric estimation of a partially linear censored regression model
dc.type Journal Article
dc.department Economics
pubs.issue 3
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Trinity College of Arts & Sciences
pubs.organisational-group /Duke/Trinity College of Arts & Sciences/Economics
pubs.publication-status Published
pubs.volume 17

Files in this item

This item appears in the following Collection(s)

Show simple item record