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
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.rae-ear.org/index.php/rae/article/view/371 (application/pdf)

Related works:
Working Paper: Does BIC Estimate and Forecast Better Than AIC? (2012)
Working Paper: Does BIC Estimate and Forecast Better than AIC? (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ila:anaeco:v:28:y:2013:i:1:p:47-64

Ordering information: This journal article can be ordered from

Access Statistics for this article

Revista de Analisis Economico – Economic Analysis Review is currently edited by Carlos Ponce

More articles in Revista de Analisis Economico – Economic Analysis Review from Universidad Alberto Hurtado/School of Economics and Business Contact information at EDIRC.
Bibliographic data for series maintained by Mauricio Tejada ().