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KAMU BORCU VE KURUMSAL KALİTE GÖSTERGELERİNİN CEE ÜLKELERİNDE YENİLENEBİLİR ENERJİ ARZI ÜZERİNDEKİ UZUN DÖNEMLİ ETKİLERİ

Year 2025, Issue: 49, 369 - 386
https://doi.org/10.18092/ulikidince.1723099

Abstract

Bu çalışma, Orta ve Doğu Avrupa (ODA) ülkelerinde kamu borcu ve yolsuzluk kontrolü ile ifade özgürlüğü ve hesap verebilirlik ölçütleriyle değerlendirilen kurumsal kalitenin yenilenebilir enerji arzı üzerindeki uzun vadeli etkilerini araştırmayı amaçlamaktadır. Zaman aralığı 1996–2019 dönemini kapsamaktadır. Ampirik süreçte heterojen panel otoregresif dağıtılmış gecikmeler (ARDL) metodolojisi benimsenmiştir. Panel ARDL analizinden elde edilen uzun dönem bulguları, kamu borcunun yenilenebilir enerji üretimini teşvik ettiğini ortaya koymaktadır. Ayrıca, uzun dönem katsayıları ifade özgürlüğü ve hesap verebilirlikteki iyileşmelerin temiz enerji arzını artırdığını, buna karşın yüksek yolsuzluk seviyelerinin yenilenebilir enerji gelişimi üzerinde olumsuz etkiler yarattığını göstermektedir. Buna ek olarak, panel Granger nedensellik analizi kişi başına düşen gelirden, yolsuzluğun kontrolünde ve şeffaflık ve hesap verebilirlikten, yenilenebilir enerji arzına doğru bir nedensel ilişkinin varlığını ortaya koymuştur. Bu bulgular, ODA ülkelerindeki politika yapıcılar için kamu maliyesi ve kurumsal kalitenin yeşil enerji üretiminin geliştirilmesindeki kritik rolünü vurgulayan yeni ve değerli içgörüler sunmaktadır.

References

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THE LONG-RUN IMPACTS OF PUBLIC DEBT AND INSTITUTIONAL QUALITY INDICATORS ON RENEWABLE ENERGY SUPPLY IN CEE COUNTRIES

Year 2025, Issue: 49, 369 - 386
https://doi.org/10.18092/ulikidince.1723099

Abstract

This study aims to investigate the long-term affects of public debt and institutional quality—measured by control of corruption and voice and accountability—on the renewable energy supply in Central and Eastern European (CEE) countries. Time span covers the period from 1996–2019. Heterogeneous panel autoregressive distributed lag (ARDL) methodology adopted in the empirical process. The long-run findings from the panel ARDL analysis indicate that public debt stimulates renewable energy production. Additionally, the long-run coefficients suggest that improvements in voice and accountability enhance clean energy supply, while higher levels of corruption have a detrimental effect on renewable energy development. Furthermore, the panel Granger causality analysis provides evidence of a causal relationship from income per capita, control of corruption, and voice and accountability to renewable energy supply. These findings offer novel and valuable insights for policymakers in CEE countries, highlighting the critical role of public finance and institutional quality in advancing green energy production.

Ethical Statement

Çalışmada etik beyanı gerektirecek veriler ve analiz yöntemleri kullanılmamıştır.

References

  • Akintande, O.J., Olubusoye, O.E., Adenikinju, A.F. & Olanrewaju, B.T. (2020). Modeling the Determinants of Renewable Energy Consumption: Evidence from the Five Most Populous Nations in Africa. Energy, 206, 117992.
  • Alsaleh, M. & Abdul-Rahim, A.S. (2021). The Nexus Between Worldwide Governance Indicators and Hydropower Sustainable Growth in EU 28 Region. International Journal of Environmental Reserach, 15, 1001–1015.
  • Annual Macro-Economic Database (AMECO). (2023). Economy and Finance. Accessed from https://economy-finance.ec.europa.eu/economic-research-and-databases/economic-databases/ameco-database_en
  • Baltagi, B.H. & Kao, C. (2000). Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey. Center for Policy Research Working Papers 16. Syracuse University, Maxwell School, Center for Policy Research.
  • Baltagi, B.H. & Pesaran, M.H. (2007). Heterogeneity and Cross Section Dependence in Panel Data Models: Theory and Applications Introduction. Journal of Applied Econometrics, 22(2), 229-232.
  • Belaid, F., Elsayed, A.H. & Omri, A. (2021). Key Drivers of Renewable Energy Deployment in the MENA Region: Empirical Evidence Using Panel Quantile Regression. Structural Change and Economic Dynamics, 57, 225-238.
  • Bellakhal, R., Kheder, S.B. & Haffoudhi, H. (2019). Governance and Renewable Energy Investment in MENA Countries: How Does Trade Matter? Energy Economics, 84, 104541.
  • Blackburne, III E.F. & Frank, M.W. (2007). Estimation of Nonstationary Heterogeneous Panels. Stata Journal, 7(2), 197-208.
  • Botha, I., Gherghina, C.Ş., Simionescu, L.N., Botezatu, M.A. & Coculescu, C. (2022). Investigating the Drivers of Renewable Energy Production: Panel Data Evidence for Central and Eastern European Countries. Economic Computation and Economic Cybernetics Studies and Research, 56(1), 5-22.
  • British Petrol (BP). (2022). BP Statistical Review of World Energy 2022. Accessed from https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html
  • Brunnschweiler, C.N. (2008). Cursing the Blessings? Natural Resource Abundance, Institutions, and Economic Growth. World Development, 36(3), 399-419.
  • Buchanan, B.G., Le, Q.V. & Rishi, M. (2012). Foreign Direct Investment and Institutional Quality: Some Empirical Evidence. International Review of Financial Analysis, 21, 81-89.
  • CAN Europe. (2022). Climate Laws in Europe: Essential for Achieving Climate Neutrality. Accessed from https://caneurope.org/climate-laws-2023/
  • Cetkovic, S. & Buzogany, A. (2019). The Political Economy of EU Climate and Energy Policies in Central and Eastern Europe Revisited: Shifting Coalitions and Prospects for Clean Energy Transitions. Politics and Governance, 7(1), 124-138.
  • Chen, C., Pınar, M. & Stengos, T. (2021). Determinants of Renewable Energy Consumption: Importance of Democratic Institutions. Renewable Energy, 179, 75-83.
  • Choi, I. (2001). Unit Root Tests for Panel Data. Journal of International Money and Finance, 20(2), 249–272.
  • Cipriani, G. (2021). Improving the Accountability of the EU Budget’s Multi-Level Implementation: Strengthening the Contribution of the European Court of Auditors. German Law Journal, 22(3), 466-489.
  • Damette, O. & Marques, A.C. (2019). Renewable Energy Drivers: A Panel Cointegration Approach. Applied Economics, 51(26), 2793-2806.
  • Danish, Baloch, M.A. & Wang, B. (2019). Analyzing the Role of Governance in CO2 Emissions Mitigation: The BRICS Experience. Structural Change and Economic Dynamics, 51:119-125.
  • Dumitrescu, E-I. & Hurlin, C. (2012). Testing for Granger Non-causality in Heterogeneous Panels. Economic Modelling, 29, 1450-1460.
  • European Commision (2023b). AMECO database. Accessed from https://economy-finance.ec.europa.eu/economic-research-and-databases/economic-databases/ameco-database_en
  • European Commission (2021). 'Fit for 55': Delivering the EU's 2030 Climate Target on the way to Climate Neutrality. Accessed from https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/ ?uri=CELEX:52021DC0550
  • European Commission (2022). REPowerEU Plan. Accessed from https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52022DC0230&from=EN
  • European Commission (2023a). National Energy and Climate Plans: EU countries’ 10-year National Energy and Climate Plans for 2021-2030. Accessed from https://commission .europa.eu/energy-climate-change-environment/implementation-eu-countries/energy-and-climate-governance-and-reporting/national-energy-and-climate-plans_en
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  • Florea, N.M., Badîrcea, R.M., Meghisan-Toma, G-M., Puiu, S., Manta, A.G. & Berceanu, D. (2021). Linking Public Finances’ Performance to Renewable-Energy Consumption in Emerging Economies of the European Union. Sustainability, 13, 6344.
  • Gan, J. & Smith, C.T. (2011). Drivers for Renewable Energy: A Comparison among OECD Countries. Biomass and Bioenergy, 35(11), 4497-4503.
  • Gua, W., Fan, W. & Yu, S. (2024). Rule of Law, Corruption and Transparency Impacts on Green Growth of East Asian Economies. Humanities & Social Sciences Communications, 11, 1169.
  • Gökce, C. & Demirtaş, G. (2018). Cari Denge Açısından Yenilenebilir Enerjinin Rolü: Avrupa Birliği Ülkeleri ve Türkiye İçin Panel Veri Analizi. Yönetim ve Ekonomi, 25(3), 641-654.
  • Harris, R. & Sollis, R. (2003). Applied Time Series Modelling and Forecasting. Chichester: John Wiley and Sons.
  • Hashemizadeh, A., Bui, Q. & Kongbuamai, N. (2021). Unpacking the Role of Public Debt in Renewable Energy Consumption: New Insights from the Emerging Countries. Energy, 224, 120187.
  • Hurlin, C., & Mignon, V. (2007). Second Generation Panel Unit Root Tests. Working Paper No. halshs-00159842. HAL Archives. Accessed from https://shs.hal.science/halshs-00159842
  • Hosseini, S.E. (2020). An Outlook on the Global Development of Renewable and Sustainable Energy at the time of COVID-19. Energy Research & Social Sciences, 68, 101633.
  • Hysa, E., Akbar, M., Akbar, A., Banda, I., & Apostu, S. A. (2023). Renewable Energy through the Lenses of Financial Development and Technological Innovation: The Case of CEE Countries. LUMEN Proceedings, 19, 82-96.
  • Im, K., Pesaran, M.H. & Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74.
  • International Renewable Energy Agency (IRENA). (2019). Renewable Power Generation Costs in 2018. Accessed from https://www.irena.org/publications/2019/May/Renewable-power-generation-costs-in-2018
  • Jalil, A. & Mahmud, S.F. (2009). Environment Kuznets Curve for CO2 Emissions: A Cointegration Analysis for China. Energy Policy, 37(12), 5167-5172.
  • Kaufmann, D., Kraay, A., & Mastruzzi, M. (2008). Governance Matters VII: Aggregate and Individual Governance Indicators 1996–200. Policy Research Working Paper No. 4654. Washington, DC: World Bank.
  • Khan, H., Weili, L. & Khan, I. (2022). The Role of Financial Development and Institutional Quality in Environmental Sustainability: Panel Data Evidence from the BRI Countries. Environmental Science and Pollution Research, 29, 83624–83635.
  • Levin, A., & Lin, C. F. (1992). Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties. Discussion Paper No. 92 93. San Diego: University of California, Department of Economics.
  • Maddala, G.S. & Wu, S. (1999). A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test. Oxford Bulletin of Economics and Statistics, 61(S1), 631–652.
  • Marinaş, M-C., Dinu, M., Socol, A-G. & Socol, C. (2018). Renewable Energy Consumption and Economic Growth. Causality Relationship in Central and Eastern European Countries. PLOS ONE, 13(10), 1-29.
  • Marques, A.C., Fuinhas, J.A. & Manso, J.R.P. (2010). Motivations Driving Renewable Energy in European Countries: A Panel Data Approach. Energy Policy, 38(11), 6877-6885.
  • Mehmood, U., Agyekum, E.B., Tariq, S., Haq, Z.U., Uhunamure, S.E., Edokpayi, J.N. & Azhar, A. (2022). Socio-Economic Drivers of Renewable Energy: Empirical Evidence from BRICS. International Journal of Environmental Research and Public Health, 19(8), 4614.
  • Menegaki, A.N. (2019). The ARDL Method in the Energy-Growth Nexus Field; Best Implementation Strategies. Economies, 7(4), 105.
  • Muço, K., Valentini, E. & Lucarelli, S. (2021). The relationships between GDP Growth, Energy Consumption, Renewable Energy Production and CO2 Emissions in European Transition Economies. International Journal of Energy Economics and Policy, 11(4), 362-373.
  • Nguyen, C.P., Schinckus, C., Su, T.D. & Chong, F.H.L. (2022). The Energy Consumption: The Global Contributions from Financial Development and Institutions. Environmental Science and Pollution Research, 29, 18721–18740.
  • Oluoch, S., Lal, P. & Susaeta, A. (2021). Investigating Factors Affecting Renewable Energy Consumption: A Panel Data Analysis in Sub Saharan Africa. Environmental Challenges, 4, 100092.
  • Organisation for Economic Co-Operation and Development (OECD). (2023). Renewable energy. Accessed from https://data.oecd.org/energy/renewable-energy.htm.
  • Peltier-Rivest, D. (2018). A Model for Preventing Corruption. Journal of Financial Crime, 25(2), 545-561.
  • Pesaran, M. H., Shin, Y., & Smith, R.P. (1997). Pooled Estimation of Long‑Run Relationships in Dynamic Heterogeneous Panels. Cambridge Working Paper in Economics No. 9721. Cambridge: University of Cambridge, Faculty of Economics.
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There are 71 citations in total.

Details

Primary Language English
Subjects Panel Data Analysis, Development Economics - Macro, Policy of Treasury
Journal Section Articles
Authors

Mümin Atalay Çetin 0000-0002-0442-8720

Early Pub Date October 24, 2025
Publication Date October 28, 2025
Submission Date June 19, 2025
Acceptance Date August 4, 2025
Published in Issue Year 2025 Issue: 49

Cite

APA Çetin, M. A. (2025). THE LONG-RUN IMPACTS OF PUBLIC DEBT AND INSTITUTIONAL QUALITY INDICATORS ON RENEWABLE ENERGY SUPPLY IN CEE COUNTRIES. Uluslararası İktisadi Ve İdari İncelemeler Dergisi(49), 369-386. https://doi.org/10.18092/ulikidince.1723099

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