Gelir Eşitsizliğinin CO₂ Emisyonu Üzerindeki Etkisi: Düşük ve Orta Gelirli Ülkelerden Kanıtlar

Abstract

Gelir eşitsizliği ile CO₂ emisyonu arasındaki ilişki, çevre ekonomisi literatüründe hem pozitif hem de negatif etkilerin rapor edilmesi nedeniyle uzun süredir tartışılmaktadır. Bu farklı bulgular, gelir eşitsizliği ile çevresel bozulma arasındaki ilişkinin güncelliğini koruduğunu ve dinamik bir araştırma alanı olarak önemini sürdürdüğünü göstermektedir. Bu çalışmada, düşük ve orta gelirli ülkelerde, 2000–2021 dönemine ait yıllık veriler kullanılarak gelir eşitsizliğinin CO₂ emisyonu üzerindeki etkisi incelenmiştir. Analizlerde, olası içsellik ve gözlenemeyen farklılıkları kontrol edebilmek amacıyla Sistem GMM kullanılmıştır. Ampirik bulgular, gelir eşitsizliğini temsilen kullanılan Gini katsayısındaki artışın CO₂ emisyonunu azalttığını göstermektedir. Bulgular aynı zamanda Çevresel Kuznets Eğrisi ile Kirlilik Cenneti hipotezlerinin geçerli olduğunu, ticari açıklık düzeyi ve ekonomik büyüme ile gini katsayısının etkileşimi arttıkça CO₂ emisyonunun artacağını, buna karşın yenilenebilir enerji tüketimi arttıkça CO₂ emisyonunun azalacağını göstermiştir.

Keywords

• Gelir Eşitsizliği
• Gini Katsayısı
• CO₂ Emisyonu
• Panel Veri Analizi

The Effect of Income Inequality on CO₂ Emissions: Findings from Low and Middle Income Countries

Abstract

The relationship between income inequality and CO₂ emissions has long been debated in the environmental economics literature due to the reporting of both positive and negative effects. These mixed findings indicate that the link between income inequality and environmental degradation remains a relevant and dynamic area of research. In this study, the effect of income inequality on CO₂ emissions is examined for low- and middle-income countries using annual data for the period 2000–2021. To address potential endogeneity and unobserved heterogeneity, the System GMM is employed. The empirical results reveal that an increase in the Gini coefficient, representing income inequality, reduces CO₂ emissions. Moreover, the findings confirm the validity of both the Environmental Kuznets Curve and the Pollution Haven Hypothesis. The results further indicate that as the interaction between trade openness, economic growth, and income inequality increases, CO₂ emissions tend to rise, while higher levels of renewable energy consumption contribute to lower emissions.

Keywords

• Income Inequality
• Gini Coefficient
• CO₂ Emissions
• Panel Data Analysis

References

1. Alataş, S., & Akın, T. (2022). The impact of income inequality on environmental quality: a sectoral-level analysis. Journal of Environmental Planning and Management, 65(10), 1949-1974.
2. Ali, H. S., Hassan, S. & Kofarmata, Y. I. (2016). Dynamic impact of income inequality on carbon dioxide emissions in Africa: New evidence from heterogeneous panel data analysis. International Journal of Energy Economics and Policy, 6(4), 760-766.
3. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and application to employment equations, Review of Economic Studies, vol. 58, pp. 277–297.
4. Arellano, M., & Bover O. (1995). Another look at the instrumental variable estimation of error components models, Journal of Econometrics, vol. 68, pp. 29-52.
5. Blundell, R. & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel models. Journal of Econometrics, Vol. 87, pp. 115-143.
6. Borghesi, S. (2000). Income inequality and the environmental Kuznets curve. Environment, inequality and collective action, 33.
7. Boyce, J. K. (1994). Inequality as a cause of environmental degradation. Ecol. Econ. 11, 169–178.
8. Che, C., Li, S., Yin, Q., Li, Q., Geng, X., & Zheng, H. (2023). Does income inequality have a heterogeneous effect on carbon emissions between developed and developing countries? Evidence from simultaneous quantile regression. Frontiers in Environmental Science, 11, 1271457.

9. Chen, J., Xian, Q., Zhou, J., & Li, D. (2020). Impact of income inequality on CO2 emissions in G20 countries. Journal of environmental management, 271, 110987.
10. Chen, X., Niu, Z., Xu, Y. (2025). Impact of Income Inequality on Carbon Emission Efficiency: Evidence from China. Sustainability, 17, 3930.
11. Chowdhury, R. A. & Russell, B. (2017). The difference, system and ‘Double-D’ GMM panel estimators in the presence of structural breaks. Scottish Journal of Political Economy, 65(3), 271-292. Advance online publication.
12. Dauda, L., Long, X., Mensah, C. N., Salman, M., Boamah, K. B., Ampon-Wireko, S., & Dogbe, C. S. K. (2021). Innovation, trade openness and CO2 emissions in selected countries in Africa. Journal of Cleaner Production, 281, 125143.
13. Demir, C., Cergibozan, R., & Gök, A. (2019). Income inequality and CO2 emissions: Empirical evidence from Turkey. Energy & Environment, 30(3), 444-461.
14. Dinda, S. (2004). Environmental Kuznets curve hypothesis: a survey. Ecological economics, 49(4), 431-455.
15. Fukase, E. (2010). Revisiting linkages between openness, education and economic growth: System GMM approach. Journal of Economic Integration, 193-222.
16. Grunewald, N., Klasen, S., Martinez-Zarzoso, I., Muris, C. (2017). The trade-off between income inequality and carbon dioxide emissions. Ecol. Econ. 142, 240–256.
17. Hailemariam, A., Dzhumashev, R., Shahbaz, M. (2019). Carbon emissions, income inequality and economic development. Empirical Economics.
18. Hou, N. & Chen, B. (2013). Military expenditure and economic growth in developing countries: evidence from system GMM estimates, Defence and Peace Economics, 24:3, 183-193.
19. Kang, H. (2022). Impacts of income inequality and economic growth on CO2 emissions: Comparing the Gini coefficient and the top income share in OECD Countries. Energies, 15, 6954.
20. Khan, M., Rana, A. T., & Ghardallou, W. (2023). FDI and CO2 emissions in developing countries: the role of human capital. Natural Hazards, 117(1), 1125-1155.
21. Kusumawardani, D., & Dewi, A. K. (2020). The effect of income inequality on carbon dioxide emissions: a case study of Indonesia. Heliyon, 6(8).
22. Li, Z., Yang, R., & Zhong, Z. (2022). The Impacts of Income Inequality on China’s Carbon Emissions: A Longitudinal Analysis. In 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022) (pp. 995-1004). Atlantis Press.
23. Mittmann, Z., & De Mattos, E. J. (2020). Income inequality and carbon dioxide emissions: Evidence from Latin America. Journal of International Development, 32(3), 389-407.
24. Ridzuan, S. (2019). Inequality and the environmental Kuznets curve. Journal of cleaner production, 228, 1472-1481.
25. Ritchie, H., & Roser, M. (2020). CO₂ emissions” Published online at OurWorldinData.org. Retrieved from: 'https://ourworldindata.org/co2-emissions'
26. Solt, F. (2020). Measuring income inequality across countries and over time: the standardized world income inequality database. Social Science Quarterly 101(3): 1183-1199.
27. Torras, M., & Boyce, J. (1998). Income, inequality, and pollution: a reassessment of the environmental Kuznets curve. Ecol. Econ. 25, 147–160.
28. Wang, F., & Qu, M. (2024). The interaction of income inequality and energy poverty on global carbon emissions: A dynamic panel data approach. Energy Economics, 140, 108027.
29. World Bank, World Development Indicators, https://databank.worldbank.org/source/world-development-indicators Erişim Tarihi: 10.09.2025.
30. Wu, R, & Z. Xie. (2020). Identifying the impacts of income inequality on CO2 emissions: Empirical evidences from OECD countries and Non-OECD countries. Journal of Cleaner Production 277: 123858.
31. Yağış, O. (2024). Gelir eşitsizliği ve CO2 emisyonu ilişkisi: Panel veri analizi. Dicle Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (36), 412-435.
32. Yang, Z., Ren, J., Ma, S., Chen, X., Cui, S., & Xiang, L. (2022). The emission-inequality nexus: empirical evidence from a wavelet-based quantile-on-quantile regression approach. Frontiers in Environmental Science, 10, 871846.
33. Zhang, C., & Zhao, W. (2014). Panel estimation for income inequality and CO2 emissions: A regional analysis in China. Applied energy, 136, 382-392.