The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Analyzing the relationship between poverty, income inequality, and CO2 emission in Sub-Saharan African countries
Abstract
Poverty and environmental degradation concerns are remained at top priority in achieving sustainable development targets. However, countries are still struggling in achieving poverty alleviation, reducing income inequality, and mitigating environmental pollution which requires immense attention. Hence, this study is an attempt to examine the linkage between, income inequality, poverty, and carbon dioxide (CO2) emissions for the 40 Sub-Saharan African countries over the period 2010 - 2016. Findings obtained from the Driscoll Kray regression estimator suggest that a rise in income inequality contributes to increasing CO2 emissions. Further, an increase in poverty has a detrimental effect on environmental pollution in Sub-Saharan African countries. Results suggested important policy implications in the light of Sustainable Development Goals (SDGs) for the study's sample countries.
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Cites
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571
Another look at the instrumental variable estimation of error-components models
Arellano, M., & Bover, O. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01642-d · Cited by 19,880
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1995) · Working Paper Series · doi:10.1920/wp.ifs.1995.9517 · Cited by 14,755
Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
Driscoll, J. C., & Kraay, A. C. (1998) · Review of Economics and Statistics · doi:10.1162/003465398557825 · Cited by 6,865
Inequality as a cause of environmental degradation
Boyce, J. K. (1994) · Ecological Economics · doi:10.1016/0921-8009(94)90198-8 · Cited by 708
Baloch, M. A., Zhang, J., Iqbal, K., & Iqbal, Z. (2019) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-3992-9 · Cited by 559
Self-citationWhat drives environmental degradation? Evidence from 14 Sub-Saharan African countries
Wang, J., & Dong, K. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2018.11.354 · Cited by 472
Carbon dioxide abatement in Africa: The role of renewable and non-renewable energy consumption
Nathaniel, S. P., & Iheonu, C. O. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.05.011 · Cited by 408
Income Inequality and Carbon Emissions in the United States: A State-level Analysis, 1997–2012
Jorgenson, A., Schor, J., & Huang, X. (2017) · Ecological Economics · doi:10.1016/j.ecolecon.2016.12.016 · Cited by 356
The Trade-off Between Income Inequality and Carbon Dioxide Emissions
Grunewald, N., Klasen, S., Martínez-Zarzoso, I., & Muris, C. (2017) · Ecological Economics · doi:10.1016/j.ecolecon.2017.06.034 · Cited by 356
Cited by
Khan, A., Chenggang, Y., Hussain, J., & Kui, Z. (2021) · Renewable Energy · doi:10.1016/j.renene.2021.02.075 · Cited by 394
Assessing energy poverty and its effect on CO2 emissions: The case of China
Zhao, J., Jiang, Q., Dong, X., & Dong, K. (2021) · Energy Economics · doi:10.1016/j.eneco.2021.105191 · Cited by 391
(2023) · Climate Change 2022 - Mitigation of Climate Change · doi:10.1017/9781009157926.004 · Cited by 253
Cao, X., Kannaiah, D., Ye, L., Khan, J., Shabbir, M. S., Bilal, K., & Tabash, M. I. (2022) · Environmental Science and Pollution Research · doi:10.1007/s11356-022-18772-4 · Cited by 78
Metadata
- Authors
- Baloch, M. A., Danish, Khan, S. U.-D., Ulucak, Z. Ş., & Ahmad, A.
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 740
- Pages
- 139867
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W3033668293
- Cited by
- 287
- References
- 36
- FWCI
- 33.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Baloch, M. A., Danish, Khan, S. U.-D., Ulucak, Z. Ş., & Ahmad, A. (2020). Analyzing the relationship between poverty, income inequality, and CO2 emission in Sub-Saharan African countries. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2020.139867
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