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A Predictive Approach to Model Selection and Multicollinearity

  • Edward Greenberg

    (Washington University)

  • Robert P. Parks

    (Washington University)

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. 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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Paper provided by EconWPA in its series Econometrics with number 9308001.

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Length: 30 pages
Date of creation: 05 Aug 1993
Date of revision:
Handle: RePEc:wpa:wuwpem:9308001
Note: Latex document, 30 pages (22 without figures)
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Steven M. Fazzari & R. Glenn Hubbard & BRUCE C. PETERSEN, 1988. "Financing Constraints and Corporate Investment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 141-206.
  2. Steven Fazzari & Bruce Petersen, 1990. "Investment smoothing with working capital: new evidence on the impact of financial constraints," Working Paper Series, Macroeconomic Issues 90-18, Federal Reserve Bank of Chicago.
  3. Cooley, Thomas F & LeRoy, Stephen F, 1981. "Identification and Estimation of Money Demand," American Economic Review, American Economic Association, vol. 71(5), pages 825-44, December.
  4. Zellner, Arnold, 1981. "Posterior odds ratios for regression hypotheses : General considerations and some specific results," Journal of Econometrics, Elsevier, vol. 16(1), pages 151-152, May.
  5. Zellner, Arnold, 1978. "Jeffreys-Bayes posterior odds ratio and the Akaike information criterion for discriminating between models," Economics Letters, Elsevier, vol. 1(4), pages 337-342.
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