Abstract
Alternative formulations of the Bayesian Information Criteria provide a basis for choosing between competing methods for detecting price asymmetry. However, very little is understood about their performance in the asymmetric price transmission modelling framework. In addressing this issue, this paper introduces and applies parametric bootstrap techniques to evaluate the ability of Bayesian Information Criteria (BIC) and Draper's Information Criteria (DIC) in discriminating between alternative asymmetric price transmission models under various error and sample size conditions. The results of the bootstrap simulations indicate that model selection performance depends on bootstrap sample size and the amount of noise in the data generating process. The Bayesian criterion clearly identifies the true asymmetric model out of different competing models in the presence of bootstrap samples. Draper's Information Criteria (DIC; Draper, 1995) outperforms BIC at either larger bootstrap sample size or lower noise level.
Highlights
Numerous studies have examined the performance of information criteria in choosing the ‘best’ model from a set of competing models or theories of asymmetric price transmission with the aid of relevant empirical data
This study examined the ability of Bayesian Information Criteria (BIC) and its extension Draper’s Information Criteria (DIC) to clearly identify the true asymmetric model out of different competing models in the presence of bootstrap samples
Both BIC and DIC clearly identify the true model in bootstrap samples
Summary
Numerous studies have examined the performance of information criteria in choosing the ‘best’ model from a set of competing models or theories of asymmetric price transmission with the aid of relevant empirical data. In the presence of bootstrap samples, will BIC and DIC point to the true model as noted in previous Monte Carlo studies? In effect this study compares the relative performance of the well known Bayesian Information Criteria with a lesser-known criterion, DIC (Draper, 1995) in terms of their ability to recover the true data generating process (DGP) in the presence of bootstrap samples. An introduction of the model selection criteria is presented This is followed by an introduction of bootstrap methods and a brief description of asymmetric price transmission models.
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