Journal of Economic Modeling Research

This study examines the long run relationship between the efficiency component (good market efficiency and labor market efficiency) in the global competitiveness index and the variables of economic success (economic growth and unemployment) by using new econometric methods in selected countries of Asia with the average upward Global Competitiveness Index. This study, in the framework of the Panel Vector Error Correction Model (PVECM), examines the long run relationship between variables over the period 2008-2016. Estimation of long run coefficients by using Dynamic Ordinary Least Squares (DOLS) and estimating error correction temr coefficients by using the Pool Mean Group Method (PMG) and Panel Vector Error Correction Model has been done. Estimations of the coefficients of the variables of the good market efficiency and labor market efficiency by using DOLS method show that the effects of good market efficiency and labor markets efficiency on the economic growth in the long run are positive and significant. The impacts of good market efficiency and labor market efficiency on unemployment in the long run are negative and significant. Also, the results of estimating logarithmic coefficients in the DOLS method show that the most effective variable on economic success variables (economic growth and unemployment) is related to good market efficiency. The estimation of the coefficients of error correction term by using the PMG and PVECM method show that when the economic growth rate is dependent variable, since the coefficient of error correction term for this variable is negative and significant, therefore, There is a long run relationship between the rate of economic growth, good market efficiency and labor market efficiency. When the unemployment rate is dependent variable, since the coefficient of error correction term is negative and significant for this variable, there is a long run relationship between the unemployment rate, good market efficiency and labor market efficiency.

Insurance as a central risk-taking institution as well as one of the investment institutions increases economic participation, investment development and stimulating economic growth. Therefore, identification of the effective factors on the insurance penetration in developing countries seems necessary. In this regard, the present study attempted to investigate the impact of national competitiveness on insurance penetration coefficient in 20 developing countries during the period 2007-2017. The research model was estimated using panel data and generalized moment’s method in two case. In the first case, the sub-indicators of national competitiveness including basic requirements, efficiency enhancer’s factors and innovation and sophistication factors were used as key variables in the research, and in the second case, the overall competitiveness index is used as a key variable in the research model. The results showed that the effect of overall competitiveness index and its sub-indicators on insurance penetration was positive and significant. Also, the effect of control variables, including per capita income and urbanization rate on insurance penetration is positive and significant, and the effect of dependency ratio on insurance penetration is negative and significant.