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
