文章基本信息

标题：Does the Bic Estimate and Forecast Better than the Aic?*
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作者：Carlos A. Medel ; Sergio C. Salgado
期刊名称：Revista de Análisis Económico (RAE)
印刷版ISSN：0716-5927
电子版ISSN：0718-8870
出版年度：2013
卷号：28
期号：1
页码：47-64
语种：English
出版社：ILADES & Universidad Alberto Hurtado
摘要：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.
关键词：AIC, BIC, information criteria, time-series models, overfitting, forecast comparison, joint hypothesis testing