2010Journal of Development and Agricultural EconomicsOpen access

Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of an asymmetric price relationship

Henry De-Graft Acquah

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Abstract

Information criteria provide an attractive basis for model selection. However, little is understood about their relative performance in asymmetric price transmission modelling framework. To explore this issue, this research evaluated the performance of the two commonly used model selection criteria, Akaike information criteria (AIC) and Bayesian information criteria (BIC) in discriminating between asymmetric price transmission models under various conditions. Monte Carlo experimentation indicated that the performance of the different model selection criteria are affected by the size of the data, the level of asymmetry and the amount of noise in the model used in the application. The Bayesian information criterion is consistent and outperforms AIC in selecting the suitable asymmetric price relationship in large samples.    Key words: Model selection, Akaike’s information criteria (AIC), Bayesian information criteria (BIC), asymmetry, Monte Carlo.

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What this paper is about

Information criteria provide an attractive basis for model selection. However, little is understood about their relative performance in asymmetric price transmission modelling framework. To explore this issue, this research evaluated the performance of the two commonly used model selection criteria, Akaike information criteria (AIC) and Bayesian information criteria (BIC) in discriminating between asymmetric price transmission models under various conditions. Monte Carlo experimentation indicated that the performance of the different model selection criteria are affected by the size of the data, the level of asymmetry and the amount of noise in the model used in the application. The Bayesian information criterion is consistent and outperforms AIC in selecting the suitable asymmetric price relationship in large samples.    Key words: Model selection, Akaike’s information criteria (AIC), Bayesian information criteria (BIC), asymmetry, Monte Carlo.

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Available abstract

Information criteria provide an attractive basis for model selection. However, little is understood about their relative performance in asymmetric price transmission modelling framework. To explore this issue, this research evaluated the performance of the two commonly used model selection criteria, Akaike information criteria (AIC) and Bayesian information criteria (BIC) in discriminating between asymmetric price transmission models under various conditions. Monte Carlo experimentation indicated that the performance of the different model selection criteria are affected by the size of the data, the level of asymmetry and the amount of noise in the model used in the application. The Bayesian information criterion is consistent and outperforms AIC in selecting the suitable asymmetric price relationship in large samples.    Key words: Model selection, Akaike’s information criteria (AIC), Bayesian information criteria (BIC), asymmetry, Monte Carlo.

Key concepts: Akaike information criterion, Bayesian information criterion, Deviance information criterion, Information Criteria, Model selection, Bayesian probability, Selection (genetic algorithm), Monte Carlo method

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