Does Geopolitical Fragmentation Affect Clean Energy Generation? Panel Evidence from BRICS Countries

Abstract

The geopolitical fragmentation has been the center of much attention in the science of empirical economics for a few years. Especially after the 2008 financial crisis, the fragmentation in the world economy has risen significantly due to the various economic and political conflicts in the world. Therefore, the practitioners have started to investigate the impact of geopolitical fragmentation on economic variables. However, its effect on energy variables was surprisingly neglected by researchers. For this purpose, the current study aims to explore the impact of geopolitical fragmentation on clean energy generation for five emerging economies, namely, Brazil, Russia, India, China, and South Africa. This relationship is tested through novel panel data techniques. The empirical results proved that there is a cointegration relationship between clean energy generation, geopolitical fragmentation, per capita income, and financial development for the period 1989-2021. Our results suggest that geopolitical fragmentation leads to a rise in clean energy generation in China, while it has a negative impact on it in South Africa. These results may help policymakers to design better energy policies for the following periods.

Keywords

• BRICS countries
• clean energy generation
• financial development
• geopolitical fragmentation
• panel data analysis

Jeopolitik Parçalanma Temiz Enerji Üretimini Etkiliyor mu? BRICS Ülkelerinden Panel Veri Bulguları

Abstract

Bu çalışma, jeopolitik parçalanmanın BRICS ülkelerinde temiz enerji üretimi üzerindeki etkisini incelemektedir. Büyük Resesyon sonrasında uluslararası ekonomik düzenin parçalı bir yapıya yönelmesi, enerji dönüşümünün belirleyicilerini yeniden tartışmaya açmıştır. Kişi başına gelir ve finansal gelişmenin de modele dahil edildiği analizde, panel veri yöntemleri kullanılarak hem ortak hem de ülkeye özgü katsayılar tahmin edilmekte; yatay kesit bağımlılığı ve eğim heterojenliği dikkate alınmaktadır. Bulgular, kişi başına gelirin Brezilya, Rusya ve Çin’de temiz enerji üretimini artırdığını göstermektedir. Toplam finansal gelişme endeksinin temiz enerji üretimi üzerindeki etkisi Brezilya ve Güney Afrika’da pozitiftir. Jeopolitik parçalanma ise yalnızca Çin’de temiz enerji üretimini artırmaktadır. Bu sonuçlar, söz konusu değişkenlerin temiz enerji üretimi üzerindeki etkisinin BRICS ülkeleri arasında tördeş olmadığını ve politika tasarımında ülkelerin yapısal farklılıklarının dikkate alınması gerektiğini ortaya koymaktadır. Çalışma politika yapıcılar için üç temel çıkarım sunmaktadır: ekonomik büyümeye yönelik politikaların sürdürülmesi, gerekli kamu müdahalesiyle sağlıklı bir finansal sistemin kurulması ve jeopolitik risklerin enerji arz güvenliği açısından gözetilmesi.

Keywords

• BRICS ülekleri
• temiz enerji üretimi
• finansal gelişme
• jeopolitik parçalanma
• panel veri analizi

References

1. Asteriou, D., & Hall, S. G. (2011). Applied Econometrics (2nd ed.) Macmillan International Higher Education
2. Bai, J., & Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72(4), 1127-1177.
3. Baltagi, B. (2008). Econometrics (4th ed.). Springer.
4. Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
5. Bridgewater Insights (2025). Green Investments: Unleashing Africa’s Renewable Energy Potential Through FDI. https://bridgewatergh.com/blog/green-investments-unleashing-africas-renewable-energy-potential-through-fdi#:~:text=A%20prime%20example%20of%20FDI's,solar%20and%20wind%20power%20projects., [Accessed 8 September 2025].
6. Depraiter, L., & Goutte, S. (2025). Geopolitical risk and clean energy investments: Exploring the role of rare earths. International Review of Financial Analysis, 100, Article 103965.
7. Eberhardt, M., & Teal, F. (2010). Productivity analysis in global manufacturing production. Economics Series Working Papers 515. University of Oxford, Department of Economics.
8. Energy Institute (2025). Resources and data downloads. https://www.energyinst.org/statistical-review/resources-and-data-downloads, [Accessed 22 August 2025].

9. Engle, R. F. & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica, 55(2), 251-276.
10. Fernández-Villaverde, J., Mineyama, T., & Song, D. (2024). Are we fragmented yet? Measuring geopolitical fragmentation and its causal effect. No. w32638. National Bureau of Economic Research.
11. Ghazouani, T. (2022). Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence. Technological Forecasting and Social Change, 185, Article 122115.
12. Gozgor, G., Mahalik, M. K., Demir, E., & Padhan, H. (2020). The impact of economic globalization on renewable energy in the OECD countries. Energy Policy, 139, Article 111365.
13. IMF (2025). Financial Development Index. https://data.imf.org/en?sk=f8032e80-b36c-43b1-ac26-493c5b1cd33b, [Accessed 1 August 2025].
14. McCoskey, S., & Kao, C. (1998). A residual-based test of the null of cointegration in panel data. Econometric Reviews, 17(1), 57-84.
15. Nan, S., Huo, Y., & Lee, C. C. (2023). Assessing the role of globalization on renewable energy consumption: New evidence from a spatial econometric analysis. Renewable Energy, 215, Article 118974.
16. Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13-50.
17. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
18. Ren, X., Yang, W., & Jin, Y. (2024). Geopolitical risk and renewable energy consumption: Evidence from a spatial convergence perspective. Energy Economics, 131, Article 107384.
19. Westerlund, J., & Edgerton, D. L. (2007). A panel bootstrap cointegration test. Economics Letters, 97(3), 185-190.
20. World Bank (2025). GDP per capita (constant 2015 US$). https://data.worldbank.org/indicator/NY.GDP.PCAP.KD, [Accessed 22 August 2025].
21. Zhang, M., Zhang, S., Lee, C. C., & Zhou, D. (2021). Effects of trade openness on renewable energy consumption in OECD countries: New insights from panel smooth transition regression modelling. Energy Economics, 104, Article 105649.
22. Zhang, J. (2024). The politicization of Chinese stock markets. Geopolitical Intelligence Services. https://www.gisreportsonline.com/r/chinese-stock-markets/, [Accessed 8 September 2025].
23. Zhao, Z., Gozgor, G., Lau, M. C. K., Mahalik, M. K., Patel, G., & Khalfaoui, R. (2023). The impact of geopolitical risks on renewable energy demand in OECD countries. Energy Economics, 122, Article 106700.
24. Zuo, Q., & Majeed, M. T. (2024). Does trade policy uncertainty hurt renewable energy-related sustainable development goals in China?. Heliyon, 10(15), e35215.