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Information-rich expressions for model selection criteria

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  • Kevin Fox

Abstract

While many model selection criteria have been suggested over the last thirty years, applied researchers still rely on R2 and R -2 to a surprising degree. It is suggested that this is mainly due to the extra informational content of these criteria compared to other alternatives. Expressions for other (superior) criteria are derived which allow the same dimensions of information to be conveyed.

Suggested Citation

  • Kevin Fox, 2000. "Information-rich expressions for model selection criteria," Applied Economics Letters, Taylor & Francis Journals, vol. 7(1), pages 59-62.
    • Handle: RePEc:taf:apeclt:v:7:y:2000:i:1:p:59-62
    DOI: 10.1080/135048500352112
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    References listed on IDEAS

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    1. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
    2. Amemiya, Takeshi, 1980. "Selection of Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 331-354, June.
    3. Fox, K., 1995. "Model Selection Criteria: A reference Source," Papers 95/28, New South Wales - School of Economics.
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    Cited by:

    1. Miriam Steurer & Robert J. Hill & Markus Zahrnhofer & Christian Hartmann, 2012. "Modelling the Emergence of New Technologies using S-Curve Diffusion Models," Graz Economics Papers 2012-05, University of Graz, Department of Economics.

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