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This study addresses the problem of model selection in asymmetric price  transmission models by combining the use of bootstrap methods with  information theoretic selection criteria. Subsequently, parametric bootstrap  technique is used to select the best model according to Akaike’s Information  Criteria (AIC) and Bayesian Information Criteria (BIC). Bootstrap simulation  results indicated that the performances of AIC and BIC are affected by the  size of the data, the level of asymmetry and the amount of noise in the model  used in the application. This study further establishes that the BIC is  consistent and outperforms AIC in selecting the correct asymmetric price  relationship when the bootstrap sample size is large

journal of agricultural sciences

A bootstrap approach to evaluating the performance of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in selection of an asymmetric price relationship