Partial rank estimation of duration models with general forms of censoring
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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.
Published Version (Please cite this version)10.1016/j.jeconom.2006.03.003
Publication InfoKhan, 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.
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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