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

Alfredo Romero ()
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Alfredo Romero: Department of Economics, College of William and Mary

No 62, Working Papers from Department of Economics, College of William and Mary

Abstract: 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.

Keywords: Adjusted R squared; Schwarz Information Criterion BIC; Neyman-Pearson Testing; Nonsense Correlations (search for similar items in EconPapers)
JEL-codes: C12 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2007-10-21

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