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A Note on the Use of R-squared in Model Selection


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  • Alfredo A. Romero

    (Department of Economics, College of William and Mary)


The use of R-squared in Model Selection is a common practice in econometrics. The rationale is that the statistic produces a consistent estimator of the true coefficient of determination for the underlying data while taking into consideration the number of variables involved in the model. This pursuit of parsimony comes with a cost: The researcher has no control over the error probabilities of the statistic. Alternative measures of goodness of fit, such as the Schwarz Information Criterion, provide only a marginal improvement to the problem. The F-Test under the Neyman-Pearson testing framework will provide the best alternative for model selection criteria.

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Bibliographic Info

Paper provided by Department of Economics, College of William and Mary in its series Working Papers with number 62.

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Length: 14 pages
Date of creation: 21 Oct 2007
Date of revision:
Handle: RePEc:cwm:wpaper:62

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Related research

Keywords: Adjusted R squared; Schwarz Information Criterion BIC; Neyman-Pearson Testing; Nonsense Correlations;

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