Assessing the distributional effects of financial development on consumption-based carbon emissions in Sub-Saharan Africa: a quantile-based analysis
This study assessed the role of financial development (FD) and its distributional effects in explaining consumption-based carbon (ConCO2) emissions, in a framework that also examined the environmental Kuznets curve (EKC) hypothesis, in the context of 19 Sub-Saharan African countries. A composite ind...
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| Veröffentlicht in: | Environmental science and pollution research international 2022-07, Vol.29 (33), p.49870-49883 |
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| creator | Anochiwa, Lasbrey I. Agbanike, Tobechi F. Ikpe, Marius Ojike, Richard O. Obidike, Paul C. |
| description | This study assessed the role of financial development (FD) and its distributional effects in explaining consumption-based carbon (ConCO2) emissions, in a framework that also examined the environmental Kuznets curve (EKC) hypothesis, in the context of 19 Sub-Saharan African countries. A composite index was used as measure of FD in a set of data spanning over the period 1995–2017, while controlling for population size (PS), energy intensity (EI) and natural resource rents (Nrr). Given that the variables deviate from expected normal distribution as adjudged by results of pre-estimation tests, the method of moments quantile regression (MM-QR) estimation technique was used to account for distributional effects of FD on ConCO2. Results of the fixed-effect regression based on Driscoll-Kray standard errors (FE-DK) which was validated by three other estimators (fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR)) statistically provided support for FD, PS and EI as drivers of ConCO2. Distributional effects of this show that FD exerts significant positive effect on ConCO2 among countries in the higher quantiles, but insignificant positive effect among those at the lower quantiles. The model provided no support for the EKC hypothesis for SSA; policy implications of these results were presented. |
| doi_str_mv | 10.1007/s11356-022-18671-8 |
| format | Article |
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A composite index was used as measure of FD in a set of data spanning over the period 1995–2017, while controlling for population size (PS), energy intensity (EI) and natural resource rents (Nrr). Given that the variables deviate from expected normal distribution as adjudged by results of pre-estimation tests, the method of moments quantile regression (MM-QR) estimation technique was used to account for distributional effects of FD on ConCO2. Results of the fixed-effect regression based on Driscoll-Kray standard errors (FE-DK) which was validated by three other estimators (fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR)) statistically provided support for FD, PS and EI as drivers of ConCO2. Distributional effects of this show that FD exerts significant positive effect on ConCO2 among countries in the higher quantiles, but insignificant positive effect among those at the lower quantiles. The model provided no support for the EKC hypothesis for SSA; policy implications of these results were presented.</description><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-022-18671-8</identifier><identifier>PMID: 35220518</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Carbon ; Consumption ; Earth and Environmental Science ; Ecotoxicology ; Emissions ; Energy consumption ; Energy utilization ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental Kuznets curve ; Environmental science ; Hypotheses ; Least squares ; Method of moments ; Natural resources ; Normal distribution ; Population number ; Quantiles ; Regression ; Research Article ; Statistical analysis ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Environmental science and pollution research international, 2022-07, Vol.29 (33), p.49870-49883</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022</rights><rights>2022. 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The model provided no support for the EKC hypothesis for SSA; policy implications of these results were presented.</description><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Carbon</subject><subject>Consumption</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Emissions</subject><subject>Energy consumption</subject><subject>Energy utilization</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental Kuznets curve</subject><subject>Environmental science</subject><subject>Hypotheses</subject><subject>Least squares</subject><subject>Method of moments</subject><subject>Natural resources</subject><subject>Normal distribution</subject><subject>Population number</subject><subject>Quantiles</subject><subject>Regression</subject><subject>Research Article</subject><subject>Statistical 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assessed the role of financial development (FD) and its distributional effects in explaining consumption-based carbon (ConCO2) emissions, in a framework that also examined the environmental Kuznets curve (EKC) hypothesis, in the context of 19 Sub-Saharan African countries. A composite index was used as measure of FD in a set of data spanning over the period 1995–2017, while controlling for population size (PS), energy intensity (EI) and natural resource rents (Nrr). Given that the variables deviate from expected normal distribution as adjudged by results of pre-estimation tests, the method of moments quantile regression (MM-QR) estimation technique was used to account for distributional effects of FD on ConCO2. Results of the fixed-effect regression based on Driscoll-Kray standard errors (FE-DK) which was validated by three other estimators (fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR)) statistically provided support for FD, PS and EI as drivers of ConCO2. Distributional effects of this show that FD exerts significant positive effect on ConCO2 among countries in the higher quantiles, but insignificant positive effect among those at the lower quantiles. The model provided no support for the EKC hypothesis for SSA; policy implications of these results were presented.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35220518</pmid><doi>10.1007/s11356-022-18671-8</doi><tpages>14</tpages></addata></record> |
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| subjects | Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Carbon Consumption Earth and Environmental Science Ecotoxicology Emissions Energy consumption Energy utilization Environment Environmental Chemistry Environmental Health Environmental Kuznets curve Environmental science Hypotheses Least squares Method of moments Natural resources Normal distribution Population number Quantiles Regression Research Article Statistical analysis Waste Water Technology Water Management Water Pollution Control |
| title | Assessing the distributional effects of financial development on consumption-based carbon emissions in Sub-Saharan Africa: a quantile-based analysis |
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