COMPARING THE VALUES OF ECONOMIC, ECOLOGICAL AND POPULATION INDICATORS IN HIGH- AND LOW-INCOME ECONOMIES
Ali, E. B.& Amfo, B.
COMPARING THE VALUES OF ECONOMIC, ECOLOGICAL AND POPULATION INDICATORS
IN HIGH- AND LOW-INCOME ECONOMIES
The quest to achieve economic development worldwide has increased carbon dioxide (CO2) emissions, which could vary in high- and low-income economies due to differences in economic activities. Using empirical evidence from the panel data for the period 1960–2018 obtained from the World Bank, we investigate differences in the impact of population, gross domestic product (GDP), and renewable energy on CO2 emissions in high- and low-income economies. For that purpose, we applied the Pesaran cross-sectional dependence test (for cross-sectional dependence), Levin-Lin-Chu unit root test (for Unit roots), Granger causality Wald test (for the possibility of Granger causality among the variables), fixed-effects and random-effects regressions. We established that population, GDP and energy consumption considerably influence CO2 emissions. Results of the Granger causality Wald test, fixed-effects and random-effects regressions clearly demonstrated that growth in population and GDP directly correlates with CO2 emissions in high- and low-income economies, while renewable energy consumption has an indirect correlation. While there are no differences in terms of directions, we revealed differences in the magnitude in high- and low-income economies. The impact of population and renewable energy consumption on CO2 emissions in low-income economies is greater than that of high-income economies. The impact of GDP on CO2 emissions is greater in high-income economies than in low-income economies. Thus, to reduce CO2 emissions, policy makers should promote low carbon emission economic activities and implement population control measures.
Keywords: population, gross domestic product, renewable energy, CO2 emission, high-income economies, low-income economies, Granger causality, random-effects regressions, fixed-effects regressions