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Does BIC Estimate and Forecast Better than AIC?

Carlos A. Medel () and Sergio Salgado Ibáñez

MPRA Paper from University Library of Munich, Germany

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.

Keywords: AIC; BIC; time-series models; overfitting; forecast comparison; joint hypothesis testing (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 C53 (search for similar items in EconPapers)
Date: 2012-10-25
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Related works:
Journal Article: Does the Bic Estimate and Forecast Better than the Aic? (2013) Downloads
Working Paper: Does BIC Estimate and Forecast Better Than AIC? (2012) Downloads
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