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Does the Bic Estimate and Forecast Better than the Aic?

Carlos A. Medel () and Sergio Salgado Ibáñez ()

Revista de Analisis Economico – Economic Analysis Review, 2013, vol. 28, issue 1, 47-64

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; information criteria; time-series models; overfitting; forecast comparison; joint hypothesis testing (search for similar items in EconPapers)
JEL-codes: L16 L25 L52 L60 (search for similar items in EconPapers)
Date: 2013
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Working Paper: Does BIC Estimate and Forecast Better Than AIC? (2012) Downloads
Working Paper: Does BIC Estimate and Forecast Better than AIC? (2012) Downloads
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