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Does BIC Estimate and Forecast Better Than AIC?

  • Carlos A. Medel
  • Sergio C. Salgado

We test two questions: (i) Is the Bayesian information criterion (BIC) more parsimonious than the Akaike information criterion (AIC)?, and (ii) Can the BIC forecast better than the AIC? 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.

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Paper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 679.

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Date of creation: Nov 2012
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Handle: RePEc:chb:bcchwp:679
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