COWLES FOUNDATION FOR RESEARCH IN ECONOMICS
AT YALE UNIVERSITY

Box 208281
New Haven, CT 06520-8281

COWLES FOUNDATION DISCUSSION PAPER NO. 906

"Asymptotic Optimality of Generalized C_L, Cross-Validation,
and Generalized Cross-Validation in Regression with Heteroskedastic Errors"

Donald W.K. Andrews

May 1989

The problem considered here is that of using a data-driven procedure to select a good estimate from a class of linear estimates indexed by a discrete parameter. In contrast to other papers on this subject, we consider models with heteroskedastic errors. The results apply to model selection problems in linear regression and to nonparametric regression estimation via series estimators, nearest neighbor estimators, and local regression estimators, among others. Generalized C_L, cross-validation, and generalized cross-validation procedures are analyzed.

JE Classification: 211

Keywords: Heteroskedasticity, linear regression, nonparametric regression, model selection, asymptotic theory, cross validation