Rank estimation of a generalized fixed-effects regression model

Abstract

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 n rate. Smoothed versions of these estimators, however, converge at rates approaching the 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.