Document Type
Discussion Paper
Publication Date
6-1-1989
CFDP Number
918
CFDP Pages
23
Abstract
This paper presents a nonparametric and distribution-free estimator for the function h*, of observable exogenous variables, x, in the generalized regression model, y - G(h*(x), mu). The method does not require a parametric specification for either the function h* or for the distribution of the random term mu. The estimation proceeds by maximizing a rank correlation criterion (Han (1987)) over a set of functions that are monotone increasing, concave, and homogeneous degree one; the function h* is assumed to belong to this set of functions. The estimator is shown to be strongly consistent.
Recommended Citation
Matzkin, Rosa L., "A Nonparametric Maximum Rank Correlation Estimator" (1989). Cowles Foundation Discussion Papers. 1162.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1162