The connection between urbanization and carbon emissions: a panel evidence from West Africa
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The connection between urbanization and carbon emissions: a panel evidence from West Africa Mohammed Musah1 · Yusheng Kong1 · Isaac Adjei Mensah2 · Stephen Kwadwo Antwi1 · Mary Donkor1 Received: 4 February 2020 / Accepted: 25 November 2020 © The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2020
Abstract This study examined the nexus between urbanization and carbon emissions in West Africa. Second-generation econometric techniques that are robust to cross-sectional dependence and slope heterogeneity were used for the study. From the Pesaran–Yamagata homogeneity test, the slope coefficients were heterogeneous in nature. Also, the Breusch–Pagan LM test, the Pesaran scaled LM test, bias-corrected LM test, Pesaran CD test and the Friedman’s test confirmed the studied panels to be cross-sectionally dependent. Further, the CADF and the CIPS unit root tests established the variables to be first-differenced stationary. Additionally, the Westerlund and Edgerton bootstrap cointegration test and the Pedroni residual cointegration test affirmed the series to be cointegrated in the long run. The Driscoll–Kraay standard errors regression estimator was employed to examine the long-run equilibrium relationship amid the series, and from the results, urbanization had a significantly positive influence on CO2 emissions in all the three panels. Also, economic growth had a materially positive effect on CO2 emissions, while renewable energy consumption had a substantially negative impact on C O2 emissions in all the panels. The causal connections amid the series were finally explored through the Dumitrescu–Hurlin panel causality test, and the discoveries were a bit varied across the various panels. Policy recommendations are further discussed. Keywords Urbanization · Carbon emissions · Renewable energy consumption · Economic growth · Driscoll–Kraay standard errors regression estimator · West African countries List of symbols RE Renewable energy REC Renewable energy consumption EC Energy consumption ED Environmental degradation POP Population * Mohammed Musah [email protected] 1
School of Finance and Economics, Jiangsu University, Zhenjiang, People’s Republic of China
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Institute of Applied Systems Analysis (IASA), School of Mathematics, Jiangsu University, Zhenjiang, People’s Republic of China
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URB Urbanization FDI Foreign direct investments FD Financial development LI Low-income countries LMI Low–middle-income countries GDP Economic growth CO2 Carbon emissions MENA Middle East and North Africa OECD Organisation for Economic Co-operation and Development EU European Union USA United States of America UAE United Arab Emirates OVB Omitted variable bias BRICS Brazil, Russia, India, China and South Africa VIF Variance inflation factor WDI World development indicators CLRM Classical linear regression model CD Cross-sectional dependence LM Lagrangian multiplier CADF Cross-sectionally augmented Dickey–Fuller CIPS Cross-sect
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