The Probability of the Military Potential Increase: Financial and Economic Factors
Abstract
Purpose: To model financial and economic indicators and determine their real impact on Ukraine’s military power (military potential).
Method: Non-linear modelling.
Findings: The results of the preliminary exploratory data analysis indicate that it is advisable to use the following variables for modelling: business environment and credit. Thus, an increase in the business environment indicator (improvement in the following parameters: stability of economic policy for doing business; economic policy and entrepreneurship culture) adds 3.64% to the probability of improving the military potential rating; an increase in the credit indicator (financing start-ups and scaling up; domestic loans to the private sector, as a percentage of GDP; loans to microfinance institutions, as a percentage of GDP) adds 2.04% to the probability of improving the military potential rating.
Theoretical implications: The understanding of Ukraine’s economic capabilities has been expanded to include the following factors: investment; credit; business environment; general infrastructure; intangible assets; trade, diversification and market scale. Ukraine’s military potential has good chances for growth if defence production, i.e. military entrepreneurship, is properly supported, which in turn requires improvement of business tools and the business climate. Meanwhile, business activities related to the production of weapons and military equipment require proper crediting—financial support from the state and local budgets.
Value: Classical and neoclassical theories have become a sufficient basis for an empirical study, which indicates that, given the positive dynamics of the financial and economic sector of Ukraine, the process of military building takes place in the plane of a favourable business climate and lending to entrepreneurial activities, in particular, the production of weapons and military equipment.
Future research: The prospect of further research is to expand the range of time series, countries, and methods of nonlinear modelling.
Future research: The prospect for further research lies in expanding the range of time series, countries, and nonlinear modeling methods.
Paper type: емпірична.
Downloads
References
Abramovitz, M. (1986). Catching Up, Forging Ahead, and Falling Behind. The Journal of Economic History, 46(2), 385–406. https://doi.org/10.1017/S0022050700046209
Ai, C. R., & Norton, E. C. (2003). Interaction terms in logit and probit models. ECONOMICS LETTERS, 80(1), 123–129.https://doi.org/10.1016/S0165–1765(03)00032–6
Bollen, K. A. (1989). Structural Equations with Latent Variables. John Wiley & Sons
Durango-Gutiérrez, M. P., Lara-Rubio, J., & Navarro-Galera, A. (2023). Analysis of default risk in microfinance institutions under the Basel III framework. International Journal of Finance and Economics, 28(2), 1261–1278. Scopus. https://doi.org/10.1002/ijfe.2475
Global Firepower—2025 World Military Strength Rankings. (n.d.). Retrieved 7 February 2025, from https://www.globalfirepower.com/
Global Innovation Index 2024. (n.d.). Retrieved 6 February 2025, from https://www.wipo.int/web-publications/global-innovation-index-2024/index.html
Gupta S., et. al. (2004). Fiscal consequences of armed conflict and terrorism in low and middle income countries. European journal of political economy. 2 (20), 403–421. https://doi.org/10.5089/9781451856262.001
Ismawati, I. Y., & Faturohma, T. (2023). CREDIT RISK SCORING MODEL FOR CONSUMER FINANCING: LOGISTIC REGRESSION METHOD. International Symposia in Economic Theory and Econometrics, 31, 167–189. Scopus. https://doi.org/10.1108/S1571-038620230000031023
Malerba, F., & Nelson, R. (2011). Learning and catching up in different sectoral systems: Evidence from six industries. Industrial and Corporate Change, 20(6), 1645–1675. https://doi.org/10.1093/icc/dtr062
Porter, M. E. (1990, March 1). The Competitive Advantage of Nations. Harvard Business Review. https://hbr.org/1990/03/the-competitive-advantage-of-nations
Abstract views: 98 PDF Downloads: 76
Copyright (c) 2025 Oleksandr Ostapenko, Oles Koval
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors agree with the following conditions:
1. Authors retain copyright and grant the journal right of first publication (Download agreement) with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
2. Authors have the right to complete individual additional agreements for the non-exclusive spreading of the journal’s published version of the work (for example, to post work in the electronic repository of the institution or to publish it as part of a monograph), with the reference to the first publication of the work in this journal.
3. Journal’s politics allows and encourages the placement on the Internet (for example, in the repositories of institutions, personal websites, SSRN, ResearchGate, MPRA, SSOAR, etc.) manuscript of the work by the authors, before and during the process of viewing it by this journal, because it can lead to a productive research discussion and positively affect the efficiency and dynamics of citing the published work (see The Effect of Open Access).
