Partial rank estimation of duration models with general forms of censoring

By Shakeeb Khan, Elie Tamer. 2007

105 citations recorded by the source corpus.

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.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/cd31c497bee313051d2521130b3d8999afe2b2d6

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Citations in the corpus

Inference on endogenously censored regression models using conditional moment inequalities (2009, background): “The bounds approach, explained in Manski and Tamer (2002), emphasizes robustness of results and clarity of assumptions imposed at the cost of estimating sets of parameters that might be large.”