Testing Environmental Kuznets Curve Hypothesis for Sub-Saharan African Countries: The Role of Income Inequality and Economic Freedom

Abstract

The rise in atmospheric carbon dioxide (CO2) concentrations has become one of the world’s major environmental concerns nowadays. It has prompted many scholars to investigate the factors that influence CO2 emissions. Many researchers, but overlook the role of economic freedom and income inequality in analyzing the EKC in Sub-Saharan African (SSA) countries. Taking 16 countries based on data availability, this study examines the effect of economic freedom and income disparity on CO2 emissions under the environmental Kuznets curve hypothesis, using balanced quarterly data straddling from 2000 to 2015. To undertake pre-estimation tests, we applied the second-generation panel cross-sectional dependence, slope homogeneity, and unit root tests. By applying cointegration and Granger tests that take heterogeneity into account, the study examined the cointegration status and direction of causality between the variables under scrutiny. PMG/ARDL estimation technique was applied to estimate the long-run coefficients. Results from the PMG/ARDL reveal that economic freedom has no statistically significant effect on CO2 emissions. The result supports the EKC hypothesis. Income inequality, industrialization, and non-renewable energy consumption have statistically significant positive effects on CO2 emissions in the long run. Economic freedom does not affect the environmental quality in the panel of countries studied. The results from the Granger causality analysis indicate that economic freedom, income inequality, renewable energy consumption, non-renewable energy consumption, industrialization, urbanization, and economic growth Granger cause CO2 emissions with a feedback effect except for economic freedom and industrialization. Policies intended to lessen income inequality can enhance environmental quality.

New insight into decoupling carbon emissions from economic growth: Do financialization, human capital, and energy security risk matter?

“…To support the findings of the study for policy, we implement the recently developed JKS (2021) Granger non-causality test for robustness (Table 8). The test is superior to previously developed approaches like that of Dumitrescu and Hurlin (2012) in the following ways: first, the JKS test uses the half-panel jackknife (HPJ) method to overcome the "nickel bias" and aids in comprehending the estimates' stability and dependability in the presence of potentially significant outliers (Hundie et al, 2022). Second, the JKS approach is equally applicable for both heterogeneous and homogeneous panels.…”