Cilt 13 Sayı 4 (2025): Business & Management Studies: An International Journal
Makaleler

Yenilenebilir enerji ve fosil yakıtların karbon emisyonlarına etkisi: En çok yenilenebilir enerji tüketen 10 ülke üzerine CS-ARDL analizi

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  • Yasin Büyükkör
Yasin Büyükkör
Dr. Öğretim Üyesi, Karamanoğlu Mehmetbey Üniversitesi, Karaman, Türkiye

Yayınlanmış 25.12.2025

Anahtar Kelimeler

  • Emissions, Renewable Energy, Fossil Fuel Consumption, Sustainable Growth, CS-ARDL Model
  • Karbon Emisyonları, Yenilenebilir Enerji, Fosil Yakıt Tüketimi, Sürdürülebilir Büyüme, CS-ARDL Modeli

Nasıl Atıf Yapılır

Yenilenebilir enerji ve fosil yakıtların karbon emisyonlarına etkisi: En çok yenilenebilir enerji tüketen 10 ülke üzerine CS-ARDL analizi. (2025). Business & Management Studies: An International Journal, 13(4), 2019-2036. https://doi.org/10.15295/bmij.v13i4.2664

Telif Hakkı (c) 2025 Yasin Büyükkör

Creative Commons License

Bu çalışma Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License ile lisanslanmıştır.

Nasıl Atıf Yapılır

Yenilenebilir enerji ve fosil yakıtların karbon emisyonlarına etkisi: En çok yenilenebilir enerji tüketen 10 ülke üzerine CS-ARDL analizi. (2025). Business & Management Studies: An International Journal, 13(4), 2019-2036. https://doi.org/10.15295/bmij.v13i4.2664

Öz

Küresel ölçekte artan fosil yakıt tüketimi, iklim değişikliği ve çevresel bozulmaların başlıca nedenlerinden biridir. Bu çerçevede, yenilenebilir enerji kaynaklarının kullanımının yaygınlaştırılması, sürdürülebilir kalkınma politikalarının temel bir bileşeni olarak değerlendirilmektedir. Bu çalışma, 1990–2021 dönemi için yenilenebilir enerjiyi en çok tüketen 10 ülke örnekleminde, karbon dioksit (CO₂) emisyonlarının temel belirleyicilerini incelemeyi amaçlamaktadır. Çalışmada bağımlı değişken olarak CO₂ emisyonları kullanılmış; ekonomik büyüme (GDP), yenilenebilir enerji tüketimi (RE), fosil yakıt tüketimi (FOS), sabit sermaye yatırımları (GFC) ve nüfus artış oranı (POPGR) bağımsız değişkenler olarak modele dâhil edilmiştir. Panel veri setiyle yürütülen analizde öncelikle yatay kesit bağımlılığı, durağanlık ve eğim homojenliği testleri uygulanmıştır. Değişkenler arasındaki uzun dönem ilişkiler Westerlund eşbütünleşme testi ile sınanmış; kısa ve uzun dönemli etkiler Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) modeliyle tahmin edilmiştir. Bulgular, fosil yakıtların CO₂ emisyonlarını artırdığını, yenilenebilir enerjinin ise emisyonları azalttığını göstermektedir. Ayrıca ekonomik büyüme ve nüfus artışı emisyonlar üzerinde pozitif yönde, sabit sermaye yatırımlarının uzun dönemde negatif etkisi olduğu belirlenmiştir. Sonuçlar, enerji dönüşümünün hızlandırılmasının ve yenilenebilir enerji yatırımlarının artırılmasının çevresel sürdürülebilirlik açısından kritik olduğunu ortaya koymaktadır.

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Referanslar

  1. Abbas, Q., Nurunnabi, M., Alfakhri, Y., Khan, W., Hussain, A., & Iqbal, W. (2020). The role of fixed capital formation, renewable and non-renewable energy in economic growth and carbon emission: a case study of Belt and Road Initiative project. Environmental Science and Pollution Research, 27, 45476–45486. https://doi.org/10.1007/s11356-020-10413-y
  2. Abbasi, K. R., Shahbaz, M., Zhang, J., Irfan, M., & Alvarado, R. (2022). Analyse the environmental sustainability factors of China: The role of fossil fuel energy and renewable energy. Renewable Energy, 187, 390–402. https://doi.org/10.1016/j.renene.2022.01.066
  3. Adebayo, T. S., Ullah, S., Kartal, M. T., Ali, K., Pata, U. K., & Ağa, M. (2023). Endorsing sustainable development in BRICS: The role of technological innovation, renewable energy consumption, and natural resources in limiting carbon emission. Science of the Total Environment, 859, 160181. https://doi.org/10.1016/j.scitotenv.2022.160181
  4. Akın, F. (2025). Karbon Emisyonlarını Azaltmada Yenilenebilir Enerjinin Rolü: Çevresel Performans Endeksinde Başarılı Olan 10 Ülkeden Kanıtlar. Üçüncü Sektör Sosyal Ekonomi Dergisi, 60(2), 1525–1542. https://doi.org/10.63556/tisej.2025.1492
  5. Ali, M., & Seraj, M. (2022). Nexus between energy consumption and carbon dioxide emission: evidence from 10 highest fossil fuel and 10 highest renewable energy-using economies. Environmental Science and Pollution Research, 29, 87901–87922. https://doi.org/10.1007/s11356-022-21900-9
  6. Ali, S., Yusop, Z., Kaliappan, S. R., & Chin, L. (2020). Dynamic common correlated effects of trade openness, FDI, and institutional performance on environmental quality: evidence from OIC countries. Environmental Science and Pollution Research, 27(11), 11671-11682. https://doi.org/10.1007/s11356-020-07768-7
  7. Asongu, S. A., Agboola, M. O., Alola, A. A., & Bekun, F. V. (2020). The criticality of growth, urbanisation, electricity and fossil fuel consumption to environment sustainability in Africa. Science of the Total Environment, 712, 136376. https://doi.org/10.1016/j.scitotenv.2019.136376
  8. Azam, M., Uddin, I., Khan, S., & Tariq, M. (2022). Are globalisation, urbanisation, and energy consumption cause carbon emissions in SAARC region? New evidence from CS ARDL approach. Environmental Science and Pollution Research, 29, 87746–87763. https://doi.org/10.1007/s11356-022-21835-1
  9. 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.
  10. Chudik, A., & Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393–420. https://doi.org/10.1016/j.jeconom.2015.03.007
  11. Çobanoğulları, G. (2024). Exploring the link between CO2 emissions, health expenditure, and economic growth in Türkiye: evidence from the ARDL model. Environment, Development and Sustainability, 26, 29605–29619. https://doi.org/10.1007/s10668-024-04835-8
  12. Deka, A., Yakubu Bako, S., Özdeşer, H., & Seraj, M. (2023). The impact of energy efficiency in reducing environmental degradation: does renewable energy and forest resources matter? Environmental Science and Pollution Research, 30, 86957–86972. https://doi.org/10.1007/s11356-023-28434-8
  13. Dumitrescu, E. I. ve Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. https://doi.org/10.1016/j.econmod.2012.02.014
  14. Dünya Bankası (2025). World Development Indicators. Dünya Bankası Veri Bankası. https://databank.worldbank.org (Erişim tarihi: 20.08.2025).
  15. Dünya Sağlık Örgütü / World Health Organization. (2023, 12 Ekim). Climate change and health. Retrieved 20 August 2025, from https://www.who.int/news-room/fact-sheets/detail/climate-change-and-health
  16. Ebaidalla, M. E. (2024). The impact of taxation, technological innovation and trade openness on renewable energy investment: Evidence from the top renewable energy producing countries. Energy, 306, 132539. https://doi.org/10.1016/j.energy.2024.132539
  17. Eid, A. G., Mrabet, Z., & Alsamara, M. (2024). Assessing the impact of energy R&D on green growth in OECD countries: a CS-ARDL analysis. Environmental Economics and Policy Studies. https://doi.org/10.1007/s10018-024-00413-4
  18. Feng, M. Q., Morake, O., Sampene, A. K., & Agyeman, F. O. (2024). Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies. Environmental Science and Pollution Research, 31, 31424–31442. https://doi.org/10.1007/s11356-024-33059-6
  19. Hao, L.-N., Umar, M., Khan, Z., & Ali, W. (2021). Green growth and low carbon emission in G7 countries: How critical the network of environmental taxes, renewable energy and human capital is? Science of the Total Environment, 752, 141853. https://doi.org/10.1016/j.scitotenv.2020.141853
  20. Ibrahim, R. L. (2022). Post-COP26: can energy consumption, resource dependence, and trade openness promote carbon neutrality? Homogeneous and heterogeneous analyses for G20 countries. Environmental Science and Pollution Research, 29(57), 86759-86770. https://doi.org/10.1007/s11356-022-21855-x
  21. Ibrahim, R. L., Ajide, K. B., Usman, M., & Kousar, R. (2022). Heterogeneous effects of renewable energy and structural change on environmental pollution in Africa: Do natural resources and environmental technologies reduce pressure on the environment? Renewable Energy, 200, 244–256. https://doi.org/10.1016/j.renene.2022.09.134
  22. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74.
  23. Im, K. S., Pesaran, M. H., & Shin, Y. (1997). Testing for unit roots in heterogeneous panels (Working Paper). University of Cambridge.
  24. Ito, K. (2017). CO2 emissions, renewable and non-renewable energy consumption, and economic growth: Evidence from panel data for developing countries. International Economics, 151, 1-6. https://doi.org/10.1016/j.inteco.2017.02.001
  25. Khan, M. A., Abdul, D., Wang, W., Tanveer, A., Faheem, M., & Hassan, T. (2025). The dynamic role of income inequality, renewable energy and risk components towards environmental sustainability: fresh insights through CS-ARDL approach. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-025-06024-7
  26. Kumari, D., Shashwat, S., Verma, P. K., & Giri, A. K. (2025). Examining the nexus between carbon dioxide emissions, economic growth, fossil fuel energy use, urbanisation and renewable energy towards achieving environmental sustainability in India. International Journal of Energy Sector Management, 19(3), 731–746. https://doi.org/10.1108/IJESM-05-2024-0007
  27. Kuo, M.-H., Lin, T.-C., & Ho, C.-C. (2022). Fresh evidence on environmental quality measures using natural resources, renewable energy, non renewable energy and economic growth for 10 Asian nations from CS ARDL technique. Fuel, 320, 123914. https://doi.org/10.1016/j.fuel.2022.123914
  28. Li, S., Samour, A., Irfan, M., & Ali, M. (2023). Role of renewable energy and fiscal policy on trade adjusted carbon emissions: Evaluating the role of environmental policy stringency. Renewable Energy, 205, 156–165. https://doi.org/10.1016/j.renene.2023.01.047
  29. Li, Y., Alharthi, M., Ahmad, I., Hanif, I., & Hassan, M. U. (2022). Nexus between renewable energy, natural resources and carbon emissions under the shadow of transboundary trade relationship from South East Asian economies. Energy Strategy Reviews, 41, 100855. https://doi.org/10.1016/j.esr.2022.100855
  30. Li, Z., Hu, S., Mehmood, U., & Agyekum, E. B. (2022). Assessing the linkages of economic freedom and environmental quality in South Asian Countries: application of CS-ARDL. Environmental Science and Pollution Research, 29, 66405–66412. https://doi.org/10.1007/s11356-022-20351-6
  31. Lu, Y., Tian, T., & Ge, C. (2023). Asymmetric effects of renewable energy, fintech development, natural resources, and environmental regulations on the climate change in the post-covid era. Resources Policy, 85, 103902. https://doi.org/10.1016/j.resourpol.2023.103902
  32. Mebrek, N., & Louail, B. (2024). The impact of economic growth on CO2 emissions in East Asian and North African Countries during the period 1990-2020 using the CS-ARDL model. International Journal of Economic Perspectives, 18(4), 790–804. https://ijeponline.org/index.php/journal/article/view/594
  33. Mehboob, M. Y., Ma, B., Sadiq, M., & Zhang, Y. (2024). Does nuclear energy reduce consumption-based carbon emissions: The role of environmental taxes and trade globalisation in highest carbon emitting countries. Nuclear Engineering and Technology, 56, 180–188. https://doi.org/10.1016/j.net.2023.09.022
  34. Mehmood, U. (2021). Renewable energy and foreign direct investment: Does the governance matter for CO₂ emissions? Application of CS ARDL. Environmental Science and Pollution Research, 29(13), 19816–19822. https://doi.org/10.1007/s11356-021-17222-x
  35. Mehmood, U. (2022). Investigating the linkages of female employer, education expenditures, renewable energy, and CO₂ emissions: Application of CS ARDL. Environmental Science and Pollution Research, 29(40), 61277–61282. https://doi.org/10.1007/s11356-022-20275-1
  36. Mehmood, U., Agyekum, E. B., Uhunamure, S. E., Shale, K., & Mariam, A. (2022). Evaluating the influences of natural resources and ageing people on CO2 emissions in G-11 nations: Application of CS-ARDL approach. International Journal of Environmental Research and Public Health, 19(3), 1449. https://doi.org/10.3390/ijerph19031449
  37. Meng, Y., Wu, H., Wang, Y., & Duan, Y. (2022). International trade diversification, green innovation, and consumption-based carbon emissions: The role of renewable energy for sustainable development in BRICST countries. Renewable Energy, 198, 1243–1253. https://doi.org/10.1016/j.renene.2022.08.045
  38. Musa, M., Gao, Y., Rahman, P., Albattat, A., Ali, M. A. S., & Saha, S. K. (2024). Sustainable development challenges in Bangladesh: an empirical study of economic growth, industrialisation, energy consumption, foreign investment, and carbon emissions—using dynamic ARDL model and frequency domain causality approach. Clean Technologies and Environmental Policy. https://doi.org/10.1007/s10098-023-02680-3
  39. Ouni, M., & Ben Abdallah, K. (2024). Environmental sustainability and green logistics: Evidence from BRICS and Gulf countries by cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach. Sustainable Development, 32(4), 3753–3770. https://doi.org/10.1002/sd.2856
  40. Öztürk, S., Han, V., & Özsolak, B. (2023). How do renewable energy, gross capital formation, and natural resource rent affect economic growth in G7 countries? Evidence from the novel GMM-PVAR approach. Environmental Science and Pollution Research, 30, 78438–78448. https://doi.org/10.1007/s11356-023-27958-3
  41. Pan, B., Adebayo, T. S., Ibrahim, R. L., & Al-Faryan, M. A. S. (2023). Does nuclear energy consumption mitigate carbon emissions in leading countries by nuclear power consumption? Evidence from quantile causality approach. Energy & Environment, 34(7), 2521-2543. https://doi.org/10.1177/0958305X221112
  42. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers. Economics, 1240(1), 1.
  43. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of applied econometrics, 22(2), 265-312.
  44. Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50–93. https://doi.org/10.1016/j.jeconom.2007.05.010
  45. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The Econometrics Journal, 11(1), 105-127.
  46. Rahman, A., Murad, S. M. W., Mohsin, A. K. M., & Wang, X. (2024). Does renewable energy proactively contribute to mitigating carbon emissions in major fossil fuels consuming countries? Journal of Cleaner Production, 452, 142113. https://doi.org/10.1016/j.jclepro.2024.142113
  47. Sadiq, M., Chau, K. Y., Ha, N. T. T., Phan, T. T. H., Ngo, T. Q., & Huy, P. Q. (2024). The impact of green finance, eco-innovation, renewable energy and carbon taxes on CO₂ emissions in BRICS countries: Evidence from CS ARDL estimation. Geoscience Frontiers, 15(4), 101689. https://doi.org/10.1016/j.gsf.2023.101689
  48. Sadiq, M., Hassan, S. T., Khan, I., & Rahman, M. M. (2024). Policy uncertainty, renewable energy, corruption and CO₂ emissions nexus in BRICS 1 countries: A panel CS ARDL approach. Environment, Development and Sustainability, 26(8), 21595–21621. https://doi.org/10.1007/s10668-023-03546-w
  49. Schmalensee, R. (2012). From “Green Growth” to sound policies: An overview. Energy Economics, 34, S2-S6. https://doi.org/10.1016/j.eneco.2012.08.041
  50. Shao, X., Zhong, Y., Liu, W., & Li, R. Y. M. (2021). Modeling the effect of green technology innovation and renewable energy on carbon neutrality in N-11 countries? Evidence from advance panel estimations. Journal of Environmental Management, 296, 113189. https://doi.org/10.1016/j.jenvman.2021.113189
  51. Sharif, A., Kartal, M. T., Bekun, F. V., Pata, U. K., Foon, C. L., & Depren, S. K. (2023). Role of green technology, environmental taxes, and green energy towards sustainable environment: Insights from sovereign Nordic countries by CS-ARDL approach. Gondwana Research, 117, 194–206. https://doi.org/10.1016/j.gr.2023.01.009
  52. Shen, Y., Su, Z.-W., Malik, M. Y., Umar, M., Khan, Z., & Khan, M. (2021). Does green investment, financial development and natural resources rent limit carbon emissions? A provincial panel analysis of China. Science of The Total Environment, 755, 142538. https://doi.org/10.1016/j.scitotenv.2020.142538
  53. Sohail, A., Du, J., & Abbasi, B. N. (2023). Exploring the interrelationship among health status, CO2 emissions, and energy use in the top 20 highest emitting economies: based on the CS-DL and CS-ARDL approaches. Air Quality, Atmosphere & Health, 16, 1419–1442. https://doi.org/10.1007/s11869-023-01350-z
  54. Su, C. W., Umar, M., & Khan, Z. (2021). Does fiscal decentralisation and eco-innovation promote renewable energy consumption? Analysing the role of political risk. Science of the Total Environment, 751, 142220. https://doi.org/10.1016/j.scitotenv.2020.142220
  55. Swamy, P. A. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311–323.
  56. Tang, Q., Shahla, R., Aliyeva, L., & Huseynova, S. (2023). Moderating role of carbon emission and institutional stability on renewable energy across developing countries. Renewable Energy, 209, 413–419. https://doi.org/10.1016/j.renene.2023.03.113
  57. Vo, D. H., Ho, C. M., Le, Q. T. T., & Vo, A. T. (2022). Revisiting the energy-growth-environment nexus in the OECD countries: An application of the CS-ARDL approach. Energy, Sustainability and Society, 12, 47. https://doi.org/10.1186/s13705-022-00375-z
  58. Voumik, L. C., Mimi, M. B., & Raihan, A. (2023). Nexus between urbanisation, industrialisation, natural resources rent, and anthropogenic carbon emissions in South Asia: CS-ARDL approach. Anthropocene Science, 2, 48–61. https://doi.org/10.1007/s44177-023-00047-3
  59. Wang, H., & Zhang, D. (2023). Examining the interplay between fossil fuel mining, sustainable growth, and economic prosperity. Resources Policy, 87, 104324. https://doi.org/10.1016/j.resourpol.2023.104324
  60. Wang, K., Rehman, M. A., Fahad, S., & Linzhao, Z. (2023). Unleashing the influence of natural resources, sustainable energy and human capital on consumption-based carbon emissions in G-7 countries. Resources Policy, 81, 103384. https://doi.org/10.1016/j.resourpol.2023.103384
  61. Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709–748. https://doi.org/10.1111/j.1468-0084.2007.00477.x
  62. Wu, L., Adebayo, T. S., Yue, X.-G., & Umut, A. (2023). The role of renewable energy consumption and financial development in environmental sustainability: implications for the Nordic Countries. International Journal of Sustainable Development & World Ecology, 30(1), 21–36. https://doi.org/10.1080/13504509.2022.2115577
  63. Xu, R., & Chen, G. (2025). Does China’s outward direct investment decrease carbon intensity in ASEAN countries? Evidence from CS-ARDL model analysis. International Journal of Climate Change Strategies and Management, 17(1), 527–542. https://doi.org/10.1108/IJCCSM-07-2024-0120
  64. Yin, C., & Qamruzzaman, M. (2024). Empowering renewable energy consumption through public-private investment, urbanisation, and globalisation: Evidence from CS-ARDL and NARDL. Heliyon, 10, e26455. https://doi.org/10.1016/j.heliyon.2024.e26455