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A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa

The aim of this study is to test the environment Kuznets curve (EKC) and pollution haven (PH) hypotheses in Sub-Saharan Africa (SSA). An important methodological point that has been over-looked by many studies is that environmental quality is not only correlated in time but also in space. For this p...

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Autores principales: Jeetoo, Jamiil, Chinyanga, Earnest Rungano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163136/
https://www.ncbi.nlm.nih.gov/pubmed/36973630
http://dx.doi.org/10.1007/s11356-023-26306-9
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author Jeetoo, Jamiil
Chinyanga, Earnest Rungano
author_facet Jeetoo, Jamiil
Chinyanga, Earnest Rungano
author_sort Jeetoo, Jamiil
collection PubMed
description The aim of this study is to test the environment Kuznets curve (EKC) and pollution haven (PH) hypotheses in Sub-Saharan Africa (SSA). An important methodological point that has been over-looked by many studies is that environmental quality is not only correlated in time but also in space. For this purpose, the study applies spatial panel econometric analysis using a balanced panel of 35 SSA nations from 2002 to 2015 to examine the EKC and PH hypotheses. Both spatial interdependence and individual heterogeneity are accounted for through the application of the spatial Durbin model (SDM) so as to avoid potential bias and inefficiencies in parameter estimates. As proxies for environmental quality, panel data aggregates on carbon dioxide (CO(2)) emissions and the depletion of natural resources are utilised. The findings offer proof for the EKC theory about the depletion of natural resources in SSA. The EKC theory, however, does not apply to CO(2) emissions. Moreover, the study finds that the positive scale effect of trade outweighs the negative technique effect of trade, which indicates that trade liberalisation has a negative effect on both environmental quality indices. This discovery supports the PH theory. The study also demonstrates positive spatial spill-over for natural resource depletion between neighbouring countries and negative spatial spill-over for carbon dioxide emission between close countries.
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spelling pubmed-101631362023-05-07 A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa Jeetoo, Jamiil Chinyanga, Earnest Rungano Environ Sci Pollut Res Int Research Article The aim of this study is to test the environment Kuznets curve (EKC) and pollution haven (PH) hypotheses in Sub-Saharan Africa (SSA). An important methodological point that has been over-looked by many studies is that environmental quality is not only correlated in time but also in space. For this purpose, the study applies spatial panel econometric analysis using a balanced panel of 35 SSA nations from 2002 to 2015 to examine the EKC and PH hypotheses. Both spatial interdependence and individual heterogeneity are accounted for through the application of the spatial Durbin model (SDM) so as to avoid potential bias and inefficiencies in parameter estimates. As proxies for environmental quality, panel data aggregates on carbon dioxide (CO(2)) emissions and the depletion of natural resources are utilised. The findings offer proof for the EKC theory about the depletion of natural resources in SSA. The EKC theory, however, does not apply to CO(2) emissions. Moreover, the study finds that the positive scale effect of trade outweighs the negative technique effect of trade, which indicates that trade liberalisation has a negative effect on both environmental quality indices. This discovery supports the PH theory. The study also demonstrates positive spatial spill-over for natural resource depletion between neighbouring countries and negative spatial spill-over for carbon dioxide emission between close countries. Springer Berlin Heidelberg 2023-03-28 2023 /pmc/articles/PMC10163136/ /pubmed/36973630 http://dx.doi.org/10.1007/s11356-023-26306-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Jeetoo, Jamiil
Chinyanga, Earnest Rungano
A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title_full A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title_fullStr A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title_full_unstemmed A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title_short A spatial econometric analysis of the environment Kuznets curve and pollution haven hypothesis in Sub-Saharan Africa
title_sort spatial econometric analysis of the environment kuznets curve and pollution haven hypothesis in sub-saharan africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163136/
https://www.ncbi.nlm.nih.gov/pubmed/36973630
http://dx.doi.org/10.1007/s11356-023-26306-9
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