Ekonomik Büyüme, Karbon Salımı ve Enerji Tüketimi Arasındaki İlişkinin Belirlenmesi: G20 Ülkelerinde Panel Eşbütünleşme ve Nedensellik Yaklaşımı

Yıl 2025, Cilt: 11 Sayı: 1, 1 - 11, 30.06.2025

Ziya Gökalp Göktolga

https://doi.org/10.51803/yssr.1544004

Cited By: 1

Öz

Bilindiği gibi CO2 bir sera gazıdır. Fosil yakıtların içerdiği sera gazları atmosfere karışarak yeryüzünde küresel ısınmaya neden olmaktadır. Küresel ısınma, düzensiz yağışlar, kuraklık, tatlı suya erişimde zorluklar, canlı biyolojisinde değişiklikler gibi birçok olumsuz duruma neden olmaktadır. Bu yüzden yeryüzündeki yaşam giderek daha fazla tehdit altına girmektedir. Bu çalışmada ekonomik büyümeyi etkileyen faktörler arasında yer alan CO2 emisyonları ile yenilenebilir ve fosil bazlı enerji kullanımı arasındaki ilişki G-20 ülkelerinde panel veri analizi ile incelenmiştir. Araştırmanın verileri Dünya Bankası'ndan toplanmıştır. 19 ülkede ve 31 zaman boyutunda toplam 589 veri incelenmiştir. Yatay kesit bağımlılığı, birim kök testleri ve homojenlik testleri yapılarak verilerin uzun vadeli tahmininde AMG yöntemi kullanıldı. Değişkenler arasında Granger nedensellik testi yapıldı. GSYİH büyümesi ile CO2 arasında pozitif bir ilişki bulunmuş ve CO2 kullanımındaki bir birimlik artışın GSYİH büyümesinde 0,88 birimlik bir artışa neden olacağı bulunmuştur. Ayrıca çalışma, yenilenebilir enerji, fosil enerji tüketimi ve CO2 kullanımından GSYİH büyümesine doğru tek yönlü bir nedensellik olduğunu ortaya çıkarmıştır.

Anahtar Kelimeler

Panel Veri , Küresel Isınma , G-20 , AMG , Granger Nedensellik.

Determining the Relationship Between Economic Growth, Carbon Emission and Energy Consumption: Panel Cointegration and Causality Approach in G20 Countries

Öz

As it is known, CO2 is a greenhouse gas. Greenhouse gases contained in fossil fuels mix with the atmosphere and cause global warming on earth. Global warming causes many negative situations such as irregular rainfall, drought, difficulties in accessing fresh water, and changes in living biology. Thus, life on earth is becoming increasingly threatened. In this study, the relationship between CO2 emissions and renewable and fossil-based energy use, which are among the factors affecting economic growth, was applied in G-20 countries with panel data analysis. The data of the study were collected from the World Bank. A total of 589 data were studied in 19 countries and 31 time dimensions. AMG method was used for long-term estimation of the data by performing cross-section dependence, unit root tests and homogeneity tests. Granger causality test was performed between the variables. A positive relationship was found between GDP growth and CO2, and it was found that a one-unit increase in CO2 use would cause a 0.88-unit increase in GDP growth. Additionally, the study found that there is a unidirectional causality from renewable energy, fossil energy consumption and CO2 usage to GDP growth.

Anahtar Kelimeler

Panel Data , Global Warming , G-20 , AMG , Granger Causality.

Kaynakça

• REFERENCES
• Acaravci, A., Bozkurt, C., & Erdoğan, S. (2015). Democracy-economic growth nexus in MENA countries. Journal of Business and Economic Studies, 3(4), 119–129.
• Adewuyi, A. O. (2016). Determinants of import demand for non-renewable energy (petroleum) products: Empirical evidence from Nigeria. Energy Policy, 95, 73–93.
• Ajmi, A. N., Hammoudeh, S., Nguyen, D. K., & Sato, J. R. (2015). On the relationships between CO₂ emissions, energy consumption and income: The importance of time variation. Energy Economics, 49, 629–638.
• Akinlo, A. E. (2008). Energy consumption and economic growth: Evidence from 11 sub-Sahara African countries. Energy Economics, 30(5), 2391–2400.
• Ang, J. B. (2008). Economic development, pollutant emissions and energy consumption in Malaysia. Journal of Policy Modeling, 30, 271–278.
• Asafu-Adjaye, J. (2000). The relationship between energy consumption, energy prices and economic growth: Time series evidence from Asian developing countries. Energy Economics, 22(6), 615–625.
• Bastola, U., & Sapkota, P. (2015). Relationships among energy consumption, pollution emission, and economic growth in Nepal. Energy, 80, 254–262.
• Blomquist, J., & Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121, 374–378.
• Bozoklu, S., & Yilanci, V. (2013). Energy consumption and economic growth for selected OECD countries: Further evidence from the Granger causality test in the frequency domain. Energy Policy, 63, 877–881.
• Breusch, T., & Pagan, A. (1980). The Lagrange multiplier test and its application to model specification in econometrics. Review of Economic Studies, 47(1), 239–253.
• Cengiz, O., & Manga, M. (2023). Does economic globalization trigger deindustrialization in Western Balkan countries? Empirical evidence based on augmented mean group estimator. Regional Science Policy & Practice, 1–21.
• Chang, C.-C., & Carballo, C. F. S. (2011). Energy conservation and sustainable economic growth: The case of Latin America and the Caribbean. Energy Policy, 39(7), 4215–4221.
• Chen, S.-T., Kuo, H.-I., & Chen, C.-C. (2007). The relationship between GDP and electricity consumption in 10 Asian countries. Energy Policy, 35(4), 2611–2621.
• Chien, T., & Hu, J. L. (2008). Renewable energy: An efficient mechanism to improve GDP. Energy Policy, 36(8), 3045–3052.
• Chu, H. P., & Chang, T. (2012). Nuclear energy consumption, oil consumption and economic growth in G-6 countries: Bootstrap panel causality test. Energy Policy, 48, 762–769.
• Coondoo, D., & Dinda, S. (2008). The carbon dioxide emission and income: A temporal analysis of cross-country distributional patterns. Ecological Economics, 65, 375–385.
• Demir, Y., & Görür, Ç. (2020). Investigation of the relationship between various energy consumption and economic growth belonging to OECD countries by panel cointegration analysis. Ekoist: Journal of Econometrics and Statistics, 32, 15–33.
• Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460.
• Eberhardt, M., & Teal, F. (2010). Productivity analysis in global manufacturing production. Discussion Paper 515, Department of Economics, University of Oxford.
• Eberhardt, M., & Bond, S. (2009). Cross-section dependence in nonstationary panel models: A novel estimator. MPRA Paper 17692, 1–26.
• El-Erian, M. A. (2008). A crisis to remember. Finance and Development, 45(4).
• Esso, L. J., & Keho, Y. (2016). Energy consumption, economic growth and carbon emissions: Cointegration and causality evidence from selected African countries. Energy, 114, 492–497.
• Friedl, B., & Getzner, M. (2003). Determinants of CO₂ emissions in a small open economy. Ecological Economics, 45(1), 133–148.
• Halicioglu, F. (2009). An econometric study of CO₂ emissions, energy consumption, income and foreign trade in Turkey. Energy Policy, 37, 1156–1164.
• Heil, M. T., & Selden, T. M. (1999). Panel stationarity with structural breaks: Carbon emissions and GDP. Applied Economics Letters, 6, 223–225.
• Huang, B. N., Hwang, M. J., & Yang, C. W. (2008). Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach. Ecological Economics, 67(1), 41–54.
• Jalil, A. (2014). Energy-growth conundrum in energy exporting and importing countries: Evidence from heterogeneous panel methods robust to cross-sectional dependence. Energy Economics, 44, 314–324.
• Karkacier, O., Goktolga, Z. G., & Cicek, A. (2006). A regression analysis of the effect of energy use in agriculture. Energy Policy, 34, 3796–3800. Kraft, J., & Kraft, A. (1978). On the relationship between energy and GNP. Journal of Energy and Development, 3, 401–403.
• Lane, T. (1999). The Asian financial crisis: What have we learned? Finance and Development, 36(3).
• Lee, C. C. (2005). Energy consumption and GDP in developing countries: A cointegrated panel analysis. Energy Economics, 27(3), 415–427.
• Li, K., Cui, G., & Lu, L. (2020). Efficient estimation of heterogeneous coefficients in panel data models with common shocks. Journal of Econometrics, 216(2), 327–353.
• Mishra, V., Smyth, R., & Sharma, S. (2009). The energy–GDP nexus: Evidence from a panel of Pacific island countries. Resource and Energy Economics, 31(3), 210–220.
• Mozumder, P., & Marathe, A. (2007). Causality relationship between electricity consumption and GDP in Bangladesh. Energy Policy, 35(1), 395–402.
• Oh, W., & Lee, K. (2004). Causal relationship between energy consumption and GDP revisited: The case of Korea 1970–1999. Energy Economics, 26(1), 51–59.
• Omri, A., Mabrouk, N. B., & Sassi-Tmar, A. (2015). Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries. Renewable and Sustainable Energy Reviews, 42, 1012–1022. Paratama, D. P. (2023). Analysis of the determinants of economic growth in G20 countries 2012–2021. Indonesian Journal of Development Economics, 6(3), 290–311.
• Pedroni, P. (2007). Social capital, barriers to production and capital shares: Implications for the importance of parameter heterogeneity from a nonstationary panel approach. Journal of Applied Econometrics, 22(2), 429– 451.
• Pehlivan, C., Han, A., & Bingöl, N. (2020). The effect of CO₂ emission and energy consumption in G20 countries on social and economic variables. Journal of Beykoz Academy, 8(1), 334–348.
• Pesaran, M. H. (2021). General diagnostic tests for cross section dependence in panels. Empirical Economics, 60, 13–50. Pesaran, M. H. (2015). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6– 10), 1089–1117.
• 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.
• Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50–93.
• Rahman, M. M., & Velayutham, E. (2020). Renewable and non-renewable energy consumption-economic growth nexus: New evidence from South Asia. Renewable Energy, 147, 399–408.
• Rodríguez-Caballero, C. V., & Ventosa-Santaulària, D. (2016). Energy-growth long-term relationship under structural breaks: Evidence from Canada, 17 Latin American economies and the USA. Energy Economics, 61, 121– 134.
• Saqib, M., & Benhmad, F. (2021). Does ecological footprint matter for the shape of the environmental Kuznets curve? Evidence from European countries. Environmental Science and Pollution Research, 28, 13634–13648.
• Sikder, M., Wang, C., Yao, X., Huai, X., Wu, L., Yeboah, F. K., Wood, J., Zhao, Y., & Dou, X. (2022). The integrated impact of GDP growth, industrialization, energy use, and urbanization on CO₂ emissions in developing countries: Evidence from the panel ARDL approach. Science of The Total Environment, 837, 155795.
• Soytas, U., & Sari, R. (2009). Energy consumption, economic growth, and carbon emissions: Challenges faced by an EU candidate member. Ecological Economics, 68(6), 1667–1675.
• Soytas, U., Sari, R., & Ewing, B. T. (2007). Energy consumption, income, and carbon emissions in the United States. Ecological Economics, 62(3–4), 482–489.
• Turan, Z. (2011). Reasons for the emergence of crisis in the world and Turkey and its impact on economic development. Academic Review of Economics and Administrative Sciences, 4(1), 56–80.
• Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6), 709–748.
• Westerlund, J., & Edgerton, D. L. (2007). A panel bootstrap cointegration test. Economics Letters, 97(3), 185–190. World Bank. (2024). World Bank Data. https://data.worldbank.org/region/world
• Yadav, A., & Mahalik, K. (2024). Does renewable energy development reduce energy import dependency in emerging economies? Evidence from CS-ARDL and panel causality approach. Energy Economics, 131, 107356.
• Zhang, X.-P., & Cheng, X.-M. (2009). Energy consumption, carbon emissions, and economic growth in China. Ecological Economics, 68(10), 2706–2712.