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Multicollinearity in regression: Review and examples
Author(s) -
Askin Ronald G.
Publication year - 1982
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980010307
Subject(s) - multicollinearity , variance inflation factor , econometrics , regression , estimation , regression analysis , computer science , selection (genetic algorithm) , statistics , mathematics , machine learning , economics , management
When building regression models for forecasting, analysts often encounter the problem of multicollinearity or illconditioning in their data sets. In such cases, large variances and covariances can make subset selection and parameter estimation difficult to impossible. In this paper, we suggest several approaches for extending estimation results to forecasting and review theoretical results useful for forecasting with multicollinearity. Several examples are provided.