Income Heterogeneity and the Environmental Kuznets Curve Turning Points: Evidence from Africa

Abstract

The concept of environmental sustainability aims to achieve economic development while achieving a sustainable environment. The inverted U-shape relationship between economic growth and environmental quality, also called Environmental Kuznets Curve (EKC), describes the correlation between economic growth and carbon emissions. This study assesses the role of agriculture and energy-related variables while evaluating the EKC threshold in 54 African economies, and income groups, according to World Bank categorization, including low income, lower-middle, upper-middle, and high-income in Africa. With 1990–2015 panel data, the results are estimated using panel cointegration, Fully Modified Ordinary Least Square (FMOLS), and granger causality tests. The results are: (1) The study validated the EKC hypothesis in the low-income, lower-, and upper-middle-income economies. However, there is no evidence of EKC in the full African and high-income panels. Furthermore, the turning points of EKC in the income group are meagerly low, showing that Africa could be turning on EKC at lower income levels. (2) The correlation between agriculture with CO2 is found positive in the high-income economy. However, agriculture has a mitigation effect on emissions in the lower-middle-income and low-income economies, and the full sample. Also, renewable energy is negatively correlated with emissions in Africa and the high-income economy. In contrast, non-renewable energy exerts a positive effect on emissions in all income groups except the low-income economies.

Decoupling Effect of County Carbon Emissions and Economic Growth in China: Empirical Evidence from Jiangsu Province

“…The reason may be that the differences in the regional economic development levels were not considered when examining the EKC effect of county carbon emissions. However, related studies showed that income heterogeneity was also an important factor affecting the establishment of the EKC [ 70 , 71 , 72 , 73 , 74 ].…”

“…Similarly, empirical analyses of the applicability of the carbon emission EKC in different income countries produced mixed conclusions. For example, Ogundipe et al supported the establishment of the EKC hypothesis only in a low-income group in Africa [ 72 ], Azam et al recognized the existence of the EKC effect only in low-income and low-middle-income countries [ 73 ], and Tachega et al found that the EKC hypothesis was effective only in the samples of low-income, middle-income and upper-middle income economies in Africa [ 74 ]. There is also empirical evidence from different industries.…”

“…Second, the existing studies believe that the reasons for the inconsistent EKC test results lie in the research samples, selection of variables and measurement methods, and few literatures mention income differences. However, empirical evidence shows that the heterogeneity of income should be an important factor that cannot be ignored [ 70 , 71 , 72 , 73 , 74 ]. In addition, the 2008, the global economic crisis changed the evolution pattern of carbon emissions in many countries, including China [ 76 ].…”

“…The EKC shows that there is an inverted U-shaped relationship between economic growth and environmental pollution. When testing the validity of the carbon dioxide emissions EKC hypothesis, there are three cases for the measurement of variables: carbon dioxide emissions and GDP [ 50 , 51 , 64 ], carbon dioxide emissions and GDP per capita [ 46 , 60 , 72 ], and carbon dioxide emissions per capita and GDP per capita [ 13 , 30 , 42 , 43 , 44 , 47 , 52 , 53 , 55 , 56 , 61 , 62 , 65 , 66 , 68 , 70 , 73 , 74 ]. Referring to the practice of most scholars, this paper selected per capita indicators to test the EKC effect of county-level carbon emissions in Jiangsu province.…”

Influence of Population Income on Energy Consumption and CO2 Emissions in Buildings of Cities

“…However, the most common is once again the analysis of the influence that certain variables, including GDP, have on emissions. The relationship between emissions, GDP, and energy consumption has also been studied in different scenarios [39] and in different countries: in 54 African countries [40], in 17 countries in Europe and Asia [41], and in 30 Chinese provinces [42]. The results show that non-renewable energies have a positive causality on CO 2 emissions.…”