Abstract:
This study evaluates the performance of the recently developed model
selection criteria (WIC) against commonly used alternatives (AIC and BIC)
in terms of their ability to recover the true asymmetric data generating
process. Monte Carlo simulation results indicate that the performance of the
model selection methods depends on the sample size, the difference in
asymmetric adjustment parameters and the amount of noise in the model
used in the application. WIC outperforms AIC and BIC under stable
conditions such as a large sample and small noise levels. Additionally, WIC
outperforms AIC and BIC as the difference between asymmetric adjustment
speeds increases. These results suggest that WIC is a very reliable and
useful criterion in asymmetric price transmission model selection
