B�hmelt, T and Bove, V (2014) Forecasting military expenditure. Research & Politics, 1 (1). p. 205316801453590. DOI https://doi.org/10.1177/2053168014535909
B�hmelt, T and Bove, V (2014) Forecasting military expenditure. Research & Politics, 1 (1). p. 205316801453590. DOI https://doi.org/10.1177/2053168014535909
B�hmelt, T and Bove, V (2014) Forecasting military expenditure. Research & Politics, 1 (1). p. 205316801453590. DOI https://doi.org/10.1177/2053168014535909
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.
Item Type: | Article |
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Uncontrolled Keywords: | Bayesian model averaging forecasting in-sample prediction military spending out-of-sample prediction |
Subjects: | J Political Science > JA Political science (General) |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Government, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 16 Oct 2014 11:12 |
Last Modified: | 04 Dec 2024 06:43 |
URI: | http://repository.essex.ac.uk/id/eprint/10885 |
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Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0