Defense Budget Growth and Inflation: A Wavelet-Based Study of the U.S. and Britain

Despite the extensive theoretical connections between defense budget growth and inflation, empirical findings based on traditional time-domain methods have been inconclusive. This study reexamines the issue from a time–frequency perspective. Applying continuous wavelet analysis to the U.S. and Britain, it shows empirical evidence in support of positive bilateral effects in both cases. In the bivariate context, U.S. defense budget growth promoted inflation at 2- to 4-year cycles in the 1840s and at 8- to 24-year cycles between 1825 and 1940. Conversely, inflation accelerated defense spending growth at 5- to 7-year cycles in the 1830s and at 25- to 64-year cycles between 1825 and 1940. Similarly, British defense budget growth spurred inflation at 8- to 48-year cycles between 1890 and 1940 and at 50- to 65-year cycles between 1790 and 1860. Inflation fueled the growth of defense spending at 7- to 20-year cycles between 1840 and 1870, in the 1940s, and in the 1980s. Preliminary results from multivariate analyses are also supportive, though there is a need for further research that is contingent on advancements in the wavelet method in the direction of simulation-based significance tests.

Machine learning deployment for arms dynamics pattern recognition in Southeast Asia region

<p>Finding the most significant determinant variable of arms dynamic is highly required due to strategic policies formulations and power mapping for academics and policy makers. Machine learning is still new or underdiscussed among the study of politics and international relations. Existing literature have much focus on using advanced quantitative methods by applying various types of regression analysis. This study analyzed the arms dynamic in Southeast Asia countries along with its some strategic partners such as United States, China, Russia, South Korea, and Japan by using ‘Decision Tree’ of machine learning algorithm. This study conducted a machine learning analysis on 55 variable items which is classified into 8 classes of variables videlicet defense budget, arms trade exports, arms trade imports, political posture, economic posture, security posture and defense priority, national capability, and direct contact,. The results suggest three findings: (1) state who perceives maritime as strategic drivers and forces will seek more power for its maritime defense posture which is translated to defense budget, (2) big size countries tend to be an arms exporter country, and (3) state’s energy dependence often leads to a higher volume of arms transfers between countries.</p>

A Study on the Optimal Allocation of Maintenance Personnel in the Military Emergency Maintenance System Considering the Property of Impatience

Impatience characteristics are an important factor to be considered in the defense field, which is sensitive to time, but there are not many cases applied. In addition, due to the difficulty of analysis that must consider various probabilistic factors (breakdown/maintenance distribution, impatience characteristics, etc.), military decision makers consider only simple data (number of occurrences per year, maintenance time, etc.) Therefore, in this study, a model capable of analyzing the performance of the emergency maintenance system for determining the appropriate size and organization of military and civilian maintenance personnel was presented in consideration of impatience characteristics and probabilistic factors. And through numerical analysis, the appropriate size of the military and civilian emergency maintenance teams was analyzed. This study is significant in that it can improve readiness of operational power and prevent waste of defense budget through efficient operation of the military's emergency maintenance system.

Economics, Lobbying, and Geopolitics as Factors Shaping the Uncertainties and Risks of Defense Spending

Aim.The presented study aims to describe and analyze major opinions regarding the economic, lobbying, and geopolitical aspects of defense budget formation.Tasks.The authors qualitatively and quantitatively assess the impact of economic, geopolitical, and lobbying factors on the level of Russian military spending.Methods. This study uses general scientific methods of cognition to examine the effects of economic, geopolitical, and lobbying factors on the level of Russian military spending in various aspects.Results.Currently, there is uncertainty in assessing the impact of economic and geopolitical factors, as well as lobbying, on the level of military spending. However, it can be concluded that while the factor of lobbying for the interests of companies increases the level of military spending unilaterally, the interaction between the economy and military security is assessed by scientists as negative, positive, or neutral. A certain level of defense spending is established by balancing the influence of economic, geopolitical, and lobbying factors. At the same time, the capability to significantly “boost” defense spending is a distinctive feature of geopolitical factors.Conclusions.In today’s relatively calm geopolitical environment, the level of Russian defense spending stands at 65-75 billion US dollars (2.5–4.0% of GNI). However, geopolitical factors can raise the level of military spending to 300 billion dollars per year or even higher (20% of GNI and more). According to rough estimates based on data on the formation of US military spending, lobbying influences about 10% of defense spending.

Defense Budgeting and Resource Allocation

This chapter dissects the US defense budget, as well as various matters in the broader field of defense economics. It provides methodologies for understanding how different defense strategies and military force postures affect that budget. The chapter also explores various ways the defense budget can be categorized, broken down, and defined. It examines issues like military readiness — how the Department of Defense ensures that its forces are ready-to-go for crises that may emerge quickly. The chapter then looks into the economics of military bases, at home and abroad. It discusses military acquisition, modernization, and innovation. The chapter then shifts to the Congressional Budget Office (CBO) figures, and analyses how they provide the backbone of the cost estimates. It highlights the core of this section — understanding the costs of US Department of Defense's (DoD) force structure by type of unit. This is probably the core of defense budgeting methodology for those seeking to understand the fiscal implications of a given defense strategy and force structure. Ultimately, the chapter investigates how two different concepts of grand strategy and/or military policy might be translated into force structure, weapons acquisition, and budget plans.