Partial rank estimation of duration models with general forms of censoring
Abstract
In this paper we propose estimators for the regression coefficients in censored duration
models which are distribution free, impose no parametric specification on the baseline
hazard function, and can accommodate general forms of censoring. The estimators are
shown to have desirable asymptotic properties and Monte Carlo simulations demonstrate
good finite sample performance. Among the data features the new estimators can accommodate
are covariate-dependent censoring, double censoring, and fixed (individual or group
specific) effects. We also examine the behavior of the estimator in an empirical illustration.
© 2006 Elsevier B.V. All rights reserved.
Type
Journal articlePublished Version (Please cite this version)
10.1016/j.jeconom.2006.03.003Publication Info
Khan, S; & Tamer, E (2007). Partial rank estimation of duration models with general forms of censoring. Journal of Econometrics, 136(1). pp. 251-280. 10.1016/j.jeconom.2006.03.003. Retrieved from https://hdl.handle.net/10161/1906.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Shakeeb Khan
Professor of Economics
Professor Khan is on leave at Boston College for the 2016-17 academic year.Professor
Khan specializes in the fields of mathematical economics, statistics, and applied
econometrics. His studies have explored a variety of subjects from covariate dependent
censoring and non-stationary panel data, to causal effects of education on wage inequality
and the variables affecting infant mortality rates in Brazil. He was awarded funding
by National Science Foundation grants for his projects ent

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