Asymmetric causality between military expenditures and economic growth in top six defense spenders

Abstract

This study applies asymmetric Granger causality test, proposed by Hatemi-J (2011; 2012) to revisit military expenditures-growth nexus for the world top 6 defense spenders over 1988-2013. Empirical results indicate that the military expenditure-led hypothesis is supported in China and Japan. However, the growth-led hypothesis is supported in four countries, i.e. France, Russia, Saudi Arabia and US. Except for Saudi Arabia, strong economic growth by no means implies automatic expansion of military expenditures. Defense planning in these countries is a matter of matching their limited resources to attain the suitable priorities. The more threats they perceived, the more military spends. This evidence provides useful insight into the behavior of other potential defense suppliers.

Stock prices and economic activity nexus in OECD countries: new evidence from an asymmetric panel Granger causality test in the frequency domain

“…For instance, Hatemi-J (2011) suggested an asymmetric panel causality test, while Hatemi-J (2014) introduced asymmetric generalized impulse responses by decomposing the variables into positive and negative shocks. Yilanci and Aydin (2016) suggested the asymmetric bootstrap panel causality test by using this idea, while Hatemi-J et al (2018) proposed a panel hidden-cointegration test. Bahmani-Oskooee et al (2016) extended the causality test in the frequency-domain with negative and positive shocks and tested the causality link between the variables using the new asymmetric causality test in the frequency domain.…”

The military expenditures and economic growth nexus: Panel bootstrap granger causality evidence from NATO countries

“…Aside from these nonlinear tests, some empirical research on the relationship between military expenditures and economic growth have applied second-generation estimation methods, such as bootstrap Granger causality (Hsien-Hung Kung and Jeniffer C. H. Min 2013; Mehmet Destek and Ilyas Okumuş 2016), bootstrap cointegration (Destek and Okumuş 2016), and spatial data analysis (Yildirim and Öcal, 2016). Nevertheless, to our knowledge, most works have not applied the asymmetric causality method as a second-generation estimation method in their models, except for Hatemi-J et al (2018), Hüseyin Alperen Özer, Özge Filiz Yağcıbaşı, and Sadık Karaoğlan (2017), and Ekrem Gül and Mustafa Torusdağ (2019).…”

“…In this sense, although many studies have aimed to examine the symmetric causality between these two variables, fewer works have explored the asymmetric causality between them. For example, previous analyses of this relationship have focused particularly on the symmetric causality (see, for example, Alper Ozun and Erman Erbaykal 2014; Jakub Odehnal and Jiri Neubauer, 2016); in contrast Abdulnasser Hatemi-J et al (2018) investigated the asymmetric causality in six countries. The existing empirical literature, which includes intensive investigations of the relationship between military expenditures and economic growth, does not provide a consensus on the direction and characteristic of this relationship, especially in NATO member countries.…”

Energy Consumption and Health Insurance Premiums in China's Provinces: Evidence From Asymmetric Panel Causality Test

“…Besides, it also allows us to take possible instabilities into the causal link, which may arise out of structural breaks. The mentioned advantages make the method widely used in many fields, including innovation expenditure ( 49 ), economic growth ( 50 ), stock market ( 51 ), and exchange rate ( 52 ). The extensive utilization proves the reliability of the method, and it can be employed in our study.…”