A comparative analysis of the outliers influence using GMM estimation based on dynamic panel data model

Abstract

This study proposes a novel approach by combining the first differenced generalized method of moments method (DIF-GMM) to remove the estimates bias in the dynamic panel data model and the least trimmed squares (LTS) to control outlier influence. The combination of these two methods is referred to as DIF-GMM+LTS. We apply this approach to examine the influence of outliers on the effect of financial development on economic growth. Our results show a counter-intuitive evidence that the bank development negatively affects economic growth when the outlier influence is ignored. However, the bank development exhibits a positive influence on economic growth once the proposed approach DIF-GMM+LTS is adopted. Also, stock market development shows a positive effect on economic growth regardless of the outliers.