Politická ekonomie 2025, 73(2) Special Issue I:157-178 | DOI: 10.18267/j.polek.1431

Political Economy of Environmental Poverty: The Role of Political Risk and Income Level

Xiaohan Gu ORCID...1, Fanrong Li ORCID...2, Weizheng Wang ORCID...3, Xiao Gu ORCID...4
1 Faculty of Law, University of Salamanca, Salamanca, Spain
2 School of Marxism, Harbin Institute of Technology, Harbin, China
3 Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, Beijing, China
4 Research Centre for the Modernisation of Governance in Urban Rural Community, Hangzhou, China

Environmental poverty is a global concern for developed and developing economies, particularly in light of sustainable development goals. Unlike previous research, this study evaluates the role of political risk index and income level on environmental poverty in developed regions, namely, OECD economies in the period 2004-2022. We also examine the role of renewable energy consumption. We initially developed a multidimensional index for assessing weighted average environmental poverty alongside a novel index to gauge political risk within OECD economies. We employ several panel econometric procedures, including cross-sectional dependence and slope heterogeneity, CIPS unit root circle for identifying unit roots and Westerlund cointegration for long-run connection among variables. Besides, the study employed cross-sectional autoregressive distributive lags (CS-ARDL) to identify the short-run and long-run impact of explanatory variables on environmental poverty. The results show that variables are heterogenous and cross-sectionally dependent. Moreover, the unit roots are found within the unit root circle, implying that variables are static at the first difference and long-run equilibrium exists among variables. The empirical results confirm that the political risk index reduces environmental poverty. A one-percent increase in the betterment of the political risk index lowers environmental poverty by -0.022% and -0.034%, respectively. However, the results for PRI in the short run are inconclusive while effective in the long run. Since the OECD countries have lower political risk and effective PRI, economic and financial activities spur, which leads to the positive influence of income on environmental poverty. A one-percent increase in income level (GDP) increases environmental poverty in OECD countries by 1.21% and 1.34% in the short and long run. Conversely, the results for renewable energy consumption (REC) are negative in both the short and long run and we conclude that REC significantly reduces environmental poverty in the region. Besides, the robustness analysis employed through an augmented mean group (AMG) estimator is reported to have similar and robust results. The Dumitrescu-Hurlin panel causality test reports that REC and environmental poverty (ENVP) have bidirectional causal linkage and provide feedback to each other, while GDP and PRI have a unidirectional connection and no feedback effect is found. Relevant policies are inferred from the conclusions.

Keywords: Political risk index, GDP, renewable energy consumption, environmental poverty, OECD economies
JEL classification: E01, P00, Q40, Q50

Received: October 11, 2023; Revised: December 5, 2023; Accepted: January 3, 2024; Prepublished online: November 20, 2024; Published: April 29, 2025  Show citation

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Gu, X., Li, F., Wang, W., & Gu, X. (2025). Political Economy of Environmental Poverty: The Role of Political Risk and Income Level. Politická ekonomie, 73(Spec.issue I.), 157-178. doi: 10.18267/j.polek.1431
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    References

    1. Acheampong, A. O., Opoku, E. E. O. (2023). Environmental degradation and economic growth: Investigating linkages and potential pathways. Energy Economics, 123, 106734. https://doi.org/10.1016/j.eneco.2023.106734 Go to original source...
    2. Adebayo, T. S., Akadiri, S. S., Akanni, E. O., et al. (2022). Does political risk drive environmental degradation in BRICS countries? Evidence from the method of moments quantile regression. Environmental Science and Pollution Research, 29(21), 32287-32297. https://doi.org/10.1007/s11356-022-20002-w Go to original source...
    3. Amin, A., Wang, Z., Shah, A. H., et al. (2023). Exploring the dynamic nexus between renewable energy, poverty alleviation, and environmental pollution: fresh evidence from E-9 countries. Environmental Science and Pollution Research, 30(10), 25773-25791. https://doi.org/10.1007/s11356-022-23870-4 Go to original source...
    4. Awad, A., Warsame, M. H. (2022). The poverty-environment nexus in developing countries: Evidence from heterogeneous panel causality methods, robust to cross-sectional dependence. Journal of Cleaner Production, 331, 129839. https://doi.org/10.1016/j.jclepro.2021.129839 Go to original source...
    5. Ceglia, F., Marrasso, E., Samanta, S., et al. (2022). Addressing Energy Poverty in the Energy Community: Assessment of Energy, Environmental, Economic, and Social Benefits for an Italian Residential Case Study. Sustainability, 14(22), 15077. https://doi.org/10.3390/su142215077 Go to original source...
    6. 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 Go to original source...
    7. Dickey, D. A., Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057. https://doi.org/10.2307/1912517 Go to original source...
    8. Ehigiamusoe, K. U., Majeed, M. T., Dogan, E. (2022). The nexus between poverty, inequality, and environmental pollution: Evidence across different income groups of countries. Journal of Cleaner Production, 341, 130863. https://doi.org/10.1016/j.jclepro.2022.130863 Go to original source...
    9. Essel-Gaisey, F., Chiang, T. F. (2022). Turning the tide on environmental poverty in Ghana: Does financial inclusion matter? Sustainable Production and Consumption, 33, 88-100. https://doi.org/10.1016/j.spc.2022.06.018 Go to original source...
    10. Grossman, G., Krueger, A. (1991). Environmental Impacts of a North American Free Trade Agreement. NBER Working Paper No. 3914. Go to original source...
    11. Hashem Pesaran, M., 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 Go to original source...
    12. IEA (2023). IEA. [Retrieved 2023-06-28] Available at: https://www.iea.org/
    13. IPCC (2021). Climate Change 2021: The Physical Science Basis. [Retrieved 2023-06-28] Available at: https://www.ipcc.ch/report/ar6/wg1/
    14. Khan, Z., Badeeb, R. A., Zhang, C., et al. (2023). Financial inclusion and energy efficiency: role of green innovation and human capital for Malaysia. https://doi.org/10.1080/00036846.2023.2206109 Go to original source...
    15. Khan, Z., Haouas, I., Trinh, H. H., et al. (2023). Financial inclusion and energy poverty nexus in the era of globalization: Role of composite risk index and energy investment in emerging economies. Renewable Energy, 204, 382-399. https://doi.org/10.1016/j.renene.2022.12.122 Go to original source...
    16. Kirikkaleli, D., Adebayo, T. S. (2022). Political risk and environmental quality in Brazil: Role of green finance and green innovation. International Journal of Finance & Economics, 29(2), 1205-1218. https://doi.org/10.1002/ijfe.2732 Go to original source...
    17. Kirikkaleli, D., Shah, M. I., Adebayo, T. S., et al. (2022). Does political risk spur environmental issues in China? Environmental Science and Pollution Research, 29(41), 62637-62647. https://doi.org/10.1007/s11356-022-19951-z Go to original source...
    18. Lee, C. C., Yuan, Z., Lee, C.-Chu., et al. (2022). The impact of renewable energy technology innovation on energy poverty: Does climate risk matter? Energy Economics, 116, 106427. https://doi.org/10.1016/j.eneco.2022.106427 Go to original source...
    19. Li, M., Zhang, K., Alamri, A. M., et al. (2023). Resource curse hypothesis and sustainable development: Evaluating the role of renewable energy and R&D. Resources Policy, 81, 103283. https://doi.org/10.1016/j.resourpol.2022.103283 Go to original source...
    20. Mukhtarov, S., Mikayilov, J. I. (2023). Could financial development eliminate energy poverty through renewable energy in Poland? Energy Policy, 182, 113747. https://doi.org/10.1016/j.enpol.2023.113747 Go to original source...
    21. Nawaz, S., Iqbal, N. (2021). How cash transfer program affect environmental poverty among the ultra-poor? Insights from the BISP in Pakistan. Energy Policy, 148, 111978. https://doi.org/10.1016/j.enpol.2020.111978 Go to original source...
    22. 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. https://doi.org/10.1002/jae.951 Go to original source...
    23. PRS Group (2023). The International Country Risk Guide (ICRG). [Retrieved 2023-05-28] Available at: https://www.prsgroup.com/explore-our-products/icrg/
    24. Qin, L., Kirikkaleli, D., Hou, Y., et al. (2021). Carbon neutrality target for G7 economies: Examining the role of environmental policy, green innovation, and composite risk index. Journal of Environmental Management, 295. https://doi.org/10.1016/j.jenvman.2021.113119 Go to original source...
    25. Tundys, B., Bretyn, A., Urbaniak, M. (2021). Energy Poverty and Sustainable Economic Development: An Exploration of Correlations and Interdependencies in European Countries. Energies, 14(22), 7640. https://doi.org/10.3390/en14227640 Go to original source...
    26. Wang, W., Xiao, W., Bai, C. (2022). Can renewable energy technology innovation alleviate energy poverty? Perspective from the marketization level. Technology in Society, 68, 101933. https://doi.org/10.1016/j.techsoc.2022.101933 Go to original source...
    27. Wang, Z., Y, C., Zhang, B., et al. (2023). Environmental degradation, renewable energy, and economic growth nexus: Assessing the role of financial and political risks? Journal of Environmental Management, 325(B), 116678. https://doi.org/10.1016/j.jenvman.2022.116678 Go to original source...
    28. 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 Go to original source...
    29. WHO (2022). Progress on drinking-water, sanitation and hygiene in schools: 2000-2021 Data update. Geneva: World Health Organization. ISBN 978-92-4-005494-3.
    30. WB Group (2023). World Bank Group - International Development, Poverty, & Sustainability. [Retrieved 2023-02-17] Available at: https://www.worldbank.org/en/home
    31. Xia, W., Murshed, M., Khan, Z., et al. (2022). Exploring the nexus between fiscal decentralization and energy poverty for China: Does country risk matter for energy poverty reduction? Energy, 255, 124541. https://doi.org/10.1016/j.energy.2022.124541 Go to original source...
    32. Zhao, J., Dong, K., Dong, X., et al. (2022). How does renewable energy alleviate energy poverty? A global analysis. Renewable Energy, 186, 299-311. https://doi.org/10.1016/j.renene.2022.01.005 Go to original source...

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