Pairwise Comparison Estimation of Censored Transformation Models

Shakeeb Khan and Elie Tamer

No 495, RCER Working Papers from University of Rochester - Center for Economic Research (RCER)

Abstract: In this paper a pairwise comparison estimation procedure is proposed for the regression coefficients in a censored transformation model. The main advantage of the new estimator is that it can accommodate covariate dependent censoring without the requirement of smoothing parameters, trimming procedures, or stringent tail behavior restrictions. We also modify the pairwise estimator for other variations of the transformation model and propose estimators for the transformation function itself, as well as regression coefficients in heteroskedastic and panel data models. The estimators are shown to converge at the parametric (root-$n$) rate, and the results of a small scale simulation study indicate they perform well in finite samples. We illustrate our estimator using the Stanford Heart Transplant data and marriage length data from the CPS fertility supplement.

Keywords: Transformation Models; Pairwise Comparison; Maximum Rank Correlation; Duration Analysis (search for similar items in EconPapers)
JEL-codes: C13 C14 C24 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2002-10
New Economics Papers: this item is included in nep-ecm
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