Author: Chisato Tagami
My research is aimed to reveal the specific role and the quantitative impact of Military Industrial Complex (MIC) on the income inequality in accordance with the defense economy. MIC has been considered as a complicated and polemical concept. In general, MIC is consisted of the four players: The defense department, the pressure group of the congress, the arm-producing company, and the academic institutions. For decades, there were numerous assertions and discussions about MIC. However, there appear to be no existing researches on the numerical aspect of MIC. This study fills the gap by employing the dynamic panel data analysis for 24 countries for the period from 2001 to 2014 with difference and system GMM. According to the literature, control variables such as indicators of major arms trade and terrorism incidents are selected. In order to see the impact on income inequality fairly, the dependent variables are chosen from the set of Theilfs T index based on the household final consumption, Gini coefficient and Human Development Index (HDI). Based on the empirical analysis, a negative relationship between MIC and income inequality is concluded, suggesting that an increase in MIC activity could reduce the income inequality. In addition, the number of terrorism incidents and the trade openness affects negatively while the amount of major arms trade has a positive relationship.
My research is aimed to reveal the specific role and the quantitative impact of Military Industrial Complex (MIC) on the income inequality in accordance with the defense economy. MIC has been considered as a complicated and polemical concept. In general, MIC is consisted of the four players: The defense department, the pressure group of the congress, the arm-producing company, and the academic institutions. For decades, there were numerous assertions and discussions about MIC. However, there appear to be no existing researches on the numerical aspect of MIC. This study fills the gap by employing the dynamic panel data analysis for 24 countries for the period from 2001 to 2014 with difference and system GMM. According to the literature, control variables such as indicators of major arms trade and terrorism incidents are selected. In order to see the impact on income inequality fairly, the dependent variables are chosen from the set of Theilfs T index based on the household final consumption, Gini coefficient and Human Development Index (HDI). Based on the empirical analysis, a negative relationship between MIC and income inequality is concluded, suggesting that an increase in MIC activity could reduce the income inequality. In addition, the number of terrorism incidents and the trade openness affects negatively while the amount of major arms trade has a positive relationship.
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