Too poor to be clean? A quantile ARDL assessment of the environmental Kuznets curve in SADC countries

Andrew Phiri, Simbarashe Mhaka and Lovemore Taonezvi ()
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Lovemore Taonezvi: BA ISAGO University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 11, No 9, 27323 pages

Abstract: Abstract The purpose of this study is to investigate whether there is a fit of the environmental Kuznets curve for Southern African development community (SADC) countries. To this end, we estimate a quadratic regression between greenhouse gas emissions (CO2, N20, CH4), per capita income and other controls, using the pooled mean group (PMG) and quantile autoregressive distributive lag (QARDL) models applied to annual data spanning from 1990 to 2021. On one hand, the PMG (Pooled mean group) estimators reveal an EKC fit for CO2 emissions (turning point = $4675), an inverse EKC for CH4 emissions (turning point = $6310) and no fit for the N20 emissions. On the other hand, the QARDL estimators further reveal more significant effects existing at the tail end distributions of the curve for all classes of emissions with turning points in the upper (lower) quantiles being higher (lower) than those from the PMG estimators. Further analysis informs us that only Seychelles have crossed the EKC ‘turning point’ at the upper quantile while the remaining countries are ‘too poor to go green.’ Overall, these findings have implications for the debate on climate justice in Africa.

Keywords: Environmental Kuznets curve (EKC); South African development community (SADC); Pooled mean group (PMG) estimators; Quantile autoregressive distributive lag (QARDL) model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03760-6

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