Modeling Country Economic Security: a Machine Learning Approach
This study employs a machine learning approach to forecast a country’s level of economic security and investigate the complex relationships between economic factors, security indicators, and the nation’s economic security. An innovative methodology is proposed that accounts for determinants of national security alongside traditional economic indicators. This allowed an assessment of the reverse impact of national security on economic security. The analysis shows that foreign direct investment and the net migration rate are critical factors for economic security. The Global Peace Index, which evaluates the peacefulness and safety of nations, demonstrates a more substantial impact on economic security than oil consumption and wattage consumption. The obtained results underscore nations’ dependence on foreign sources of capital, the importance of balanced migration policies, and the bidirectional interplay between economic and national security.
Authors
- Roman Ivanytskyy (ORCID: https://orcid.org/0009-0004-1687-9539)
- Ludmila Babala (ORCID: https://orcid.org/0000-0002-2388-270X)
- Kateryna Berezka (ORCID: https://orcid.org/0000-0002-9632-4004)
- Olha Ya. Kovalchuk (ORCID: https://orcid.org/0000-0001-6490-9633)
- Nataliia Karpyshyn (ORCID: https://orcid.org/0000-0002-5264-1200)
- Natalіa Zhuk (ORCID: https://orcid.org/0000-0003-3860-5489)
Institutions
- West Ukrainian National University (UA)
- Security Service of Ukraine (UA)
- Ternopil Volodymyr Hnatiuk National Pedagogical University (UA)
Publication Details
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1109/acit62333.2024.10712462
- Citations
- 3
- Primary Topic
- Economic Development and Digital Transformation
- Type
- article
- Field-Weighted Citation Impact
- 2.49