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


  • 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.

Suggested Citation

  • Alfredo A. Romero, 2007. "A Note on the Use of R-squared in Model Selection," Working Papers 62, Department of Economics, College of William and Mary.
  • Handle: RePEc:cwm:wpaper:62

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

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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