SEMIPARAMETRIC LEAST-SQUARES (SLS) AND WEIGHTED SLS ESTIMATION OF SINGLE-INDEX MODELS

被引：709

作者：

ICHIMURA, H

机构：

[1] University of Minnesota, Minneapolis

来源：

JOURNAL OF ECONOMETRICS | 1993年 / 58卷 / 1-2期

关键词：

D O I：

10.1016/0304-4076(93)90114-K

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

For the class of single-index models, I construct a semiparametric estimator of coefficients up to a multiplicative constant that exhibits 1/square-root n-consistency and asymptotic normality. This class of models includes censored and truncated Tobit models, binary choice models, and duration models with unobserved individual heterogeneity and random censoring. I also investigate a weighting scheme that achieves the semiparametric efficiency bound.

引用

页码：71 / 120

页数：50

共 22 条

[1] CONSISTENCY IN NONLINEAR ECONOMETRIC-MODELS - A GENERIC UNIFORM LAW OF LARGE NUMBERS [J].