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A PREDICTIVE APPROACH TO MODEL SELECTION AND MULTICOLLINEARITY
Author(s) -
GREENBERG EDWARD,
PARKS ROBERT P.
Publication year - 1997
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/(sici)1099-1255(199701)12:1<67::aid-jae427>3.0.co;2-w
Subject(s) - multicollinearity , econometrics , model selection , covariance , regression , selection (genetic algorithm) , regression analysis , variance inflation factor , economics , statistics , computer science , mathematics , machine learning
We argue for the adoption of a predictive approach to model specification. Specifically, we derive the difference between means and the ratio of determinants of covariance matrices when a subset of explanatory variables is included or excluded from a regression. Results for an economic application are presented as an example. © 1997 by John Wiley & Sons, Ltd.