Forecasting military expenditure

Author:

Böhmelt Tobias1,Bove Vincenzo1

Affiliation:

1. University of Essex, UK

Abstract

To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

Publisher

SAGE Publications

Subject

Political Science and International Relations,Public Administration,Sociology and Political Science

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A double-edged sword into a plowshare: Analyzing geopolitical implications of alternative socioeconomic development pathways;One Earth;2024-01

2. Militarization and Income Inequality in European Countries (2000–2017);Peace Economics, Peace Science and Public Policy;2022-09-01

3. The Impact of Reducing Military Expenditures in South Korea Using a CGE Model;Journal of Quantitative Economics;2022-06-16

4. Deconstructing the ‘Yoshida Doctrine’;Japanese Journal of Political Science;2022-02-08

5. Market Movements at High Frequencies and Latency in Response Times;Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1;2021-10-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3