A Predictive Approach to Model Selection and Multicollinearity
AbstractWe 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. For several special cases these measures are shown to be related to widely used tools for studying model specification. Results for a set of simulated data and for two economic applications are presented as examples.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9308001.
Length: 30 pages
Date of creation: 05 Aug 1993
Date of revision:
Note: Latex document, 30 pages (22 without figures)
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Web page: http://126.96.36.199
Other versions of this item:
- Greenberg, Edward & Parks, Robert P, 1997. "A Predictive Approach to Model Selection and Multicollinearity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 67-75, Jan.-Feb..
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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- Panaretos, John & Psarakis, Stelios & Xekalaki, Evdokia & Karlis, Dimitris, 2005. "The Correlated Gamma-Ratio Distribution in Model Evaluation and Selection," MPRA Paper 6355, University Library of Munich, Germany.
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