Developing an economic and social security index for Euro-Atlantic area countries: a panel data analysis
Abstract
The concepts of economic and social security are very complex and dynamic, closely related to many new challenges that characterize today’s societies. Our research aims at investigating the economic and social security considering the current vulnerabilities, using an integrated multicriteria approach to this issue, taking into account five pillars (dimensions): demographic, climate, globalization, and ITC adaptation, social, and economic. Based on these dimensions, we developed an Economic and Social Security Index across the Euro-Atlantic countries and we found that the European Union (EU) is better positioned compared to the other country-groups analysed. Furthermore, we estimated the effects of duration of schooling and climate degradation on economic growth, by using the Panel EGLS method over the period 2010–2019, and we compared the results obtained for EU countries to the ones obtained for the other groups of countries in EuroAtlantic space: EU neighbours and candidate/potential candidate countries and other Eastern EU neighbourhood countries. We found a positive impact of the duration of schooling on the economic growth, which is greater in countries registering high levels of socio-economic security, the effect of the duration of schooling varying depending on the quality of education. In terms of the effects of CO2 emissions on economic growth, we found a negative impact, considering the one year lag.
Keyword : economic security, social security, economic growth, schooling, environment, demographic
How to Cite
Șerban, A. C., & Jianu, I. (2023). Developing an economic and social security index for Euro-Atlantic area countries: a panel data analysis. Journal of Business Economics and Management, 24(1), 112–135. https://doi.org/10.3846/jbem.2023.18610
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Leit, N. C. (2014). Economic growth, carbon dioxide emissions, renewable energy and globalization. International Journal of Energy Economics and Policy, 4(3), 391–399.
Maity, S., & Sinha, A. (2021). Linkages between economic growth and population ageing with a knowledge spillover effect. Journal of the Knowledge Economy, 12(4), 1905–1924. https://doi.org/10.1007/s13132-020-00696-4
Moen, P., Pedtke, J. H., & Flood, S. (2020). Disparate disruptions: Intersectional COVID-19 employment effects by age, gender, education, and race / ethnicity. Work Aging and Retirement, 6(4), 207–228. https://doi.org/10.1093/workar/waaa013
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Serban, A. C., & Lytras, M. D. (2020). Artificial intelligence for smart renewable energy sector in Europe – Smart energy infrastructures for next generation smart cities. IEEE Access, 8(1), 77364–77377. https://doi.org/10.1109/ACCESS.2020.2990123
Serban, A. C., Pelinescu, E., & Dospinescu, A. S. (2022). Beta convergence analysis of gross value added in the high-technology manufacturing industries. Technological and Economic Development of Economy, 28(2), 290–312. https://doi.org/10.3846/tede.2021.15918
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