Effectiveness of a Cluster of Determinants to Increase Economic Growth Rate: A Combined Statistical Criteria Approach

Abstract

This paper attempts to estimate the effectiveness of a cluster of determinants to increase GDP growth rate by using a combined statistical criteria approach. First, combining three ranking measures i.e. partial regression coefficients, adjusted R-square and Bayesian information criterion (BIC) into one single ranking procedure for finding and ranking the impact of each determinant - Y-Procedure. Second, ranking the effectiveness of a cluster of determinants, each of which has been Y-Procedure ranked using F statistics, adjusted R-square and Bayesian information criterion (BIC) in increasing GDP growth rate - Y-Average. The results show that sets of top five or more variables should be considered as one entity with respect to increasing GDP growth rate, and the degree of effectiveness increases if their Y-Average of relative measures increases. On application of this Y-Procedure and Y-Average to Australian GDP growth rate, it is found that Investment, Current Account Balance, Gross Foreign Liability, Export and Import have the highest impact and thus, these five variables should be given priority when constructing the relevant economic policies and allocation of funds towards increasing GDP growth rate specifically for the case of Australia.

Keywords

• Prioritize, Allocation, Ranking measures, Y-Procedure, Y-Average