Does the Bic Estimate and Forecast Better than the Aic?*

  • Carlos A. Medel Central Bank of Chile
  • Sergio C. Salgado University of Minnesota
Keywords: AIC, BIC, information criteria, time-series models, overfitting, forecast comparison, joint hypothesis testing

Abstract

We test two questions: (i) Is the Bayesian Information Criterion (BIC) more parsimonious than Akaike Information Criterion (AIC)? and (ii) Is BIC better than AIC for forecasting purposes? By using simulated data, we provide statistical inference of both hypotheses individually and then jointly with a multiple hypotheses testing procedure to control better for type-I error. Both testing procedures deliver the same result: The BIC shows an in- and out-of-sample superiority over AIC only in a long-sample context.
How to Cite
Medel, C. A., & Salgado, S. C. (1). Does the Bic Estimate and Forecast Better than the Aic?*. Economic Analysis Review, 28(1), 47-64. Retrieved from https://www.rae-ear.org/index.php/rae/article/view/rae-28-3
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Articles