Abstract
The present paper addresses the selection-of-regressors issue into a general discrimination framework. We show how this framework is useful in unifying various procedures for selecting regressors and helpful in understanding the different strategies underlying these procedures. We review selection of regressors in linear, nonlinear and nonparametric regression models. In each case we successively consider model selection criteria and hypothesis testing procedures.
Keywords
Selection of regressor; Discrimination;
JEL codes
- C52: Model Evaluation, Validation, and Selection
- C20: General
Reference
Pascal Lavergne, “Selection of Regressors in Econometrics: Parametric and Nonparametric Methods”, Econometric Reviews, vol. 17, n. 3, 1998, pp. 227–273.
Published in
Econometric Reviews, vol. 17, n. 3, 1998, pp. 227–273