THE RELATIONSHIP BETWEEN ENERGY SECURITY AND MILITARY EXPENDITURES: A BOOTSTRAP PANEL GRANGER CAUSALITY ANALYSIS FOR ENERGY EXPORTER COUNTRIES

Abstract

Purpose: The aim of this study is to analyze the causality relationship between military expenditures and energy security risk levels. In this context, the main purpose of the study is to investigate whether military expenditures have a role in ensuring energy security and to perform a pioneering study examining the relationship between energy security and military expenditures. In addition, the variables of economic growth and energy export revenues are also included in empirical analysis.
Methodology: The Kónya (2006) bootstrap panel Granger causality approach is used in empirical analysis. The analysis covers 16 major energy exporter countries and the years 1990 and 2018.
Results: It was found that there is one-directional causality from military expenditures to energy security risk levels for three countries, and from energy security risk levels to military expenditures for two countries. On the other hand, it was determined that there is one-directional causality from energy security risk levels to economic growth for four countries, from economic growth to energy security risk levels for two countries, from energy security risk level to energy export revenues for four countries, and from energy export revenues to energy security risk levels for one country. Moreover, it was determined that there is bidirectional causality between energy security risk levels and economic growth for four countries, and between energy security risk levels and energy export revenues for two countries.
Conclusion: The results obtained in this study demonstrate that the causality relationship between energy security and other variables (military expenditures, GDP, and energy export income) cannot be generalized across countries. However, it may be argued that energy security is an important policy tool that has important economic consequences for energy-exporting countries through its effects on different variables.