Rank estimation of a generalized fixed-effects regression model

This paper considers estimation of a fixed-effects version of the generalized regression model of Han (1987, Journal of Econometrics 35, 303-316). The model allows for censoring, places no parametric assumptions on the error disturbances, and allows the fixed effects to be correlated with the covariates. We introduce a class of rank estimators that consistently estimate the coefficients in the generalized! fixed-effects regression model. The maximum score estimator for the binary choice fixed-effects model is part of this class. Like the maximum score estimator, the class of rank estimators converge at less than the root n rate. Smoothed versions of these estimators, however, converge at rates approaching the root n rate. In a version of the model that allows for truncated data, a sufficient condition for consistency of the estimators is that the error disturbances have an increasing hazard function. (C) 2000 Elsevier Science S.A. All rights reserved. JEL classification: C23; C14.