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DISTRIBUTION-FREE ESTIMATION OF THE BOX–COXREGRESSION MODEL WITH CENSORING

Published online by Cambridge University Press:  25 November 2011

Songnian Chen
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Abstract

The Box–Cox regression model has been widely used inapplied economics. However, there has been verylimited discussion when data are censored. The focushas been on parametric estimation in thecross-sectional case, and there has been nodiscussion at all for the panel data model withfixed effects. This paper fills these important gapsby proposing distribution-free estimators for theBox–Cox model with censoring in both thecross-sectional and panel data settings. Theproposed methods are easy to implement by combininga convex minimization problem with a one-dimensionalsearch. The procedures are applicable to othertransformation models.

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Type
Brief Report
Information
Econometric Theory , Volume 28 , Issue 3 , June 2012 , pp. 680 - 695
Copyright
Copyright © Cambridge University Press 2011

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Footnotes

I thank the co-editor and two referees for theirinsightful comments, which have greatly improvedthe presentation of the paper. I also thank KenChay, Jerry Hausman, James Heckman, Bo Honoré,Cheng Hsiao, Lung-fei Lee, Jim Powell, Paul Ruud,Jeff Wooldridge, Zhiliang Ying, and workshopparticipants at the University of California atBerkeley, University of Chicago, Duke University,Johns Hopkins University, University of Michigan,Michigan State University, NorthwesternUniversity, Ohio State University, and VanderbiltUniversity for their helpful comments. Part of thework was carried out while I was at the NationalUniversity of Singapore.

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