The role of model complexity and the performance of the selection criteria in asymmetric price transmission models

Abstract

The role of model complexity in asymmetric price transmission model selection is not well understood. In order to appreciate the role of model complexity in model selection performance, this study fits alternative asymmetric price transmission models that differ in complexity to simulated data and evaluates the ability of the model selection method to recover the true model. The results of Monte Carlo experimentation suggest that in general BIC, CAIC and DIC were superior to AIC when the true data generating process was the Manning Error Correction model (MECM). However, AIC was more successful when the true model was the Complex Error Correction Model (CECM). The tendency of the complex model (CECM) to over fit the relatively simpler true asymmetric data generating process (MECM) is minimized in larger samples. The research findings demonstrate the role of model complexity in asymmetric price transmission model comparison and selection