ASSESSING THE SIMULATION PERFORMANCES OF MULTIPLE MODEL SELECTION ALGORITHM

The Autometrics is an algorithm for single equation model selection. It is a hybrid method which combines expanding and contracting search techniques. In this study, the algorithm is extended for multiple equations modelling known as SURE-Autometrics. The aim of this paper is to assess the performance of the extended algorithm using various simulation experiment conditions. The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes. Overall results show that the algorithm has performed well for a model with two equations. The findings also indicated that the number of variables in the true models affect the algorithm performances. Hence, this study suggests improvement on the algorithm development for future research.