Comparing the values of economic, ecological and population indicators in Highand Low-Income Economies
DOI:
https://doi.org/10.17059/ekon.reg.2021-1-6Keywords:
population, gross domestic product, renewable energy, CO2 emission, high-income economies, low-income economies, Granger causality, random-effects regressions, fixed-effects regressionsAbstract
The quest to achieve economic development worldwide has increased carbon dioxide (COJ 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-in-come 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.References
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