The Impact of Income Inequality on Carbon Emissions in China: A Household-Level Analysis

Income inequality, economic growth, renewable energy usage, and environmental degradation in the Belt and Road initiative countries: dynamic panel estimation

This study investigates the effect of income inequality, carbon dioxide emissions, renewable energy consumption, and economic growth on each other's in the Belt and Road initiative countries from 2002 to 2019. By using OLS, fixed effect, difference GMM, system GMM, and seemingly unrelated regression (SUR) models, the results show that income inequality and renewable energy consumption are reduced while economic growth, foreign direct investment, and financial development have an increasing effect on carbon emissions. The effect of carbon emissions and renewable energy consumption is negative, while economic growth is positive and negative for income inequality across different models. Income inequality, carbon dioxide emissions, economic growth, and foreign direct investment are negatives for renewable energy consumption. Income inequality is positive, while carbon dioxide and financial development negatively affect economic growth. The findings have considerable policy implications for the sample countries regarding income distribution, energy use, environmental quality, and enhancing economic growth. The countries should focus on acquiring renewable energy sources to increase economic growth and reduce environmental pollution.

The nexus between natural resources, renewable energy consumption, economic growth, and carbon dioxide emission in BRI countries

This study investigates the nexus between natural resources, renewable energy consumption, economic growth, and carbon emission in 35 belt and road initiative (BRI) countries from 1985 to 2019. By employing OLS, fixed effect, generalized method of moments, and seemingly unrelated regression models, the results show that carbon dioxide and renewable energy are the driver factors of economic growth while natural resources reduce economic growth. The effect of economic growth and natural resources on carbon dioxide is positive; however, renewable energy consumption significantly reduces carbon emission. Economic growth rise renewable energy consumption while carbon dioxide and natural resources reduce it. The findings of this study have considerable policy implications for the belt and road countries that how natural resources and income inequality influence the interlinkage of renewable energy consumption, economic growth, and carbon dioxide emission.

The Impact of the Income Gap on Carbon Emissions: Evidence from China

The income gap and global warming have always been topics of common concern to scholars worldwide. Internationally, there is no consensus yet about the impact of the income gap on carbon emissions, and there are few studies about that in China. To explore the effect of the income gap on carbon emissions at the provincial level in China, this paper first theoretically and qualitatively analyzes the non-linear impact of the income gap on carbon emissions. Then, the Gini coefficient of the resident income of different regions in China from 2010 to 2019 is calculated. Finally, a threshold regression model is used to quantitatively test the existence of a threshold effect between the income gap and carbon emission intensity in China. The threshold value is the per capita disposable income of residents. The results show that the income gap is positively related to carbon emission intensity in poor regions. In high-income areas, the widening income gap inhibits the increase in carbon emission intensity. Based on this, this paper proposes policy recommendations to narrow the income gap and reduce the intensity of carbon emissions.

Income inequality, ecological footprint, and carbon dioxide emissions in Asian developing economies: what effects what and how?

The reduction of income inequality and environmental vulnerability is the most important factor, through which we can achieve the target of Sustainable Development Goals (SDGs). The past papers have investigated the nexus between income inequality and carbon emissions; however, the relationship between income inequality and carbon emissions along with ecological footprint has not been studied in the case of developing countries. To this end, this study analyzed the impact of income inequality on both carbon emissions and ecological footprint as well as the impact of carbon emission and ecological footprint on income inequality by using the dataset from 2006 to 2017 for the 18 Asian developing economies. This study confirmed the positive relationship between carbon emissions, ecological footprint, and income inequality under the methodology of Driscoll and Kraay (D&K) standard error approach. Specifically, a higher-income gap is destructive for environmental degradation, whereas increasing level of carbon emissions and ecological footprint also leads to rising income inequality in the investigated region. Furthermore, foreign direct investment (FDI), easy access to electricity, and population growth control income inequality, but they have a detrimental effect on both ecological footprint and carbon emissions. The empirical findings also provide some important policy implications.

The effect of income inequality and energy consumption on environmental degradation: the role of institutions and financial development in 180 countries of the world

This study investigates the effect of income inequality and institutional quality on carbon emission in 180 countries of the world from 2002 to 2019. The study employed OLS, fixed effect, and system generalized method of moments (SGMM), and the results show that income inequality, institutional quality, financial development, and economic growth have a direct significant and positive effect on carbon emission while trade openness and renewable energy significantly reduce carbon emission. VOA, ROL from the legal system, and GOV from the political system negatively affect carbon emission while the interaction term between GDP and GINI is found negative for carbon emission while the interaction of FD and GINI, INST and GINI, FD, and GDP are positively linked with carbon emission. The EKC hypothesis has been evidenced in the analysis with all INST indices. Our findings have considerable policy implications for the sample countries regarding the income inequality and institutions' development toward environmental quality enrichment.

Income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from Ethiopia

The relationship between income inequality, economic growth, and CO₂ emissions is ambiguous both theoretically and empirically. Hence, this study examines the link between income inequality, economic growth and CO₂ emissions in Ethiopia for time span covering 1979-2014 using ARDL bounds test and DOLS approach to cointegration. The Zivot-Andrews unit root test and Clemente-Montanes-Reyes unit root test reveal that some of the variables under consideration are stationary at level while others become stationary after first differencing. Both ARDL and DOLS approaches confirm that there is a long-run relationship among the series during the study period. The long-run empirical results show that a 1% increase in economic growth accounts for a 1.05% increase in CO₂ emissions while a 1% increase in economic growth squared reduces CO2 emissions by 0.11%. The U-test result reveals that the relationship between CO₂ emissions and economic growth confirms existence of the Environmental Kuznets Curve hypothesis. The effect of income inequality on CO₂ is not robust to alternative estimation techniques; it is statistically insignificant under the ARDL estimation, but DOLS estimates show that a 1% increase in income inequality increases CO₂ emissions by 0.21% in the long-run during the study period. In the long-run, a 1% rise in urbanization, population size, energy intensity, and industrialization each positively contribute to environmental degradation in Ethiopia by 0.38%, 0.22%, 0.07%, and 0.11% respectively. Results from the Toda-Yamamoto Granger causality show a bidirectional causal relationship between CO₂ emissions and all other variables except economic growth. CO₂ emissions Granger causes economic growth with no feedback effect. Results suggested important policy implications in the light of achieving its 2030 targets of low-carbon economy for Ethiopia.

A Regression Analysis of the Carbon Footprint of Megacities

Urbanization and climate change are two major issues that humanity faces in the 21st century. Megacities are large urban agglomerations with more than 10 million inhabitants that emerged in the 20th century. The world’s top 100 economies include many North and South American megacities, such as New York, Los Angeles, Mexico City, Sao Paulo and Buenos Aires; European cities such as London and Paris; and Asian cities such as Tokyo, Osaka, Seoul, Beijing and Mumbai. This paper addresses a dearth of megacity energy metabolism models in the literature. Cross-sectional data for 36 global megacities were collected from many literature and Internet sources. Variables included megacity name, country and region; population; area; population density; (per capita) GDP; income inequality measures; (per capita) energy consumption; household electricity prices; (per capita) carbon and ecological footprint; degree days; average urban heat island intensity; and temperature and precipitation. A descriptive comparison of the characteristics of megacities was followed by ordinary least squares with heteroskedasticity-robust standard errors that were used to estimate four alternative multiple regression models. The per-capita carbon footprint of megacities was positively associated with the megacity GDP per capita, and the megacity ecological footprint; and negatively associated with country income inequality, a low-income country dummy, the country household electricity price, and the megacity annual precipitation. Targeted policies are needed, but more policy autonomy should be left to megacities. Collecting longitudinal data for megacities is very challenging but should be a next step to overcome misspecification and bias issues that plague cross-sectional approaches.