The impact of income inequality on consumption-based greenhouse gas emissions at the global level: A partially linear approach

Baležentis, Tomas; Liobikienė, Genovaitė; Štreimikienė, Dalia; Sun, Kai

doi:10.1016/j.jenvman.2020.110635

Cited by 45 publications

(35 citation statements)

References 69 publications

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“…In particular, Baležentis et al. (2020) explored the impact of income inequality on consumption‐based emissions and found a U‐shape relationship between GDP per capita and carbon emissions per capita.…”

Section: Literature Reviewmentioning

confidence: 99%

The relationship between China's income inequality and transport infrastructure, economic growth, and carbon emissions

Zhang

Zhang²

2021

Growth and Change

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Since the beginning of the 21st century, accompanied by the tremendous achievements of China's economic growth is an increasingly severe income gap between the rich and the poor. Based on panel data from 2000 to 2018, this study systematically examined the relationship among transport infrastructure, economic growth, carbon emissions, and income inequality in China, using the panel vector autoregressive model estimated by the generalized method of moments. We further divided China into three regions to investigate the regional heterogeneity of these relationships. The results show a long‐run equilibrium relationship between transport infrastructure, economic growth, carbon emissions, and income inequality. Income inequality in the previous year significantly affects that in the current year positively. Whether at the national or regional level, economic growth affects income inequality negatively. For the national sample, the highway reduces income inequality, while the railway increases income inequality. For both the subsamples and the national sample, carbon emissions significantly increase income inequality and are the Granger test cause for income inequality. Furthermore, we discuss some of the possible mechanisms of these results. Our findings generate policy implications for reducing income inequality in regard to economic growth, transport infrastructure, and carbon emissions.

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Section: Literature Reviewmentioning

confidence: 99%

The relationship between China's income inequality and transport infrastructure, economic growth, and carbon emissions

Zhang

Zhang²

2021

Growth and Change

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“…Inequality analysis has been widely used in environmental studies (e.g., Baležentis, Liobikienė, Štreimikienė, & Sun, 2020; Chen et al., 2019) and thus an inequality analysis is introduced to capture the differences in CI due to regional heterogeneities in this study. The Gini coefficient and the Theil index are the two commonly used inequality analysis tools.…”

Section: Methodology and Data Sourcesmentioning

confidence: 99%

Net primary productivity‐based factors of China's carbon intensity: A regional perspective

Chen

Xie

et al. 2020

Growth and Change

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Reducing carbon intensity (CI) is one of the core steps of climate change mitigation. This study emphasized the roles of ecological services and regional heterogeneity in determining CI. We considered heterogeneities based on geography and income and explored the roles of net primary productivity (NPP)-based carbon footprint and CI in the changes in China's CI over 2001−2015 using an extended production-theoretical decomposition analysis and matching the socioeconomic data sets with NPP data from a remote sensing satellite. We found that group technological change, reflecting the effect of shrinkage or expansion of the group best practice frontier, and the potential NPP-based carbon footprint, reflecting the impact of energy-related CO 2 emissions on ecological carbon absorption, are the most significant factors accounting for the increase and decrease in CI, respectively, while NPP-based CI generally accounts for the decline in CI. We further showed that the technology gap change exhibited by an invert U-shaped curve contributed to the increase in CI under geography-based heterogeneity. We advise that China's policies should be more focused on ecological factors and regional heterogeneity in regions with abundant NPP (e.g., Yunnan and Sichuan) to further reduce CI. 1728 | CHEN Et al. 1 | INTRODUCTION Global warming is one of the most challenging problems of the 21st century (Akorede, Hizam, Ab Kadir, Aris, & Buba, 2012). It is caused by greenhouse gases, with CO 2 emissions contributing up to 77% of the total anthropogenic emissions (Intergovernmental Panel on Climate Change, 2007). Tackling climate change requires responses from the economic system because of the policy implications on climate change mitigation (Mendelsohn, Nordhaus, & Shaw, 1994; Nordhaus, 1982). Carbon intensity (CI), or carbon emissions per unit of Gross Domestic Product (GDP), is an indicator for emission mitigation policy targets. A decline in CI indicates better low carbon development in economic terms. Compared to aggregate and per capita carbon emissions, CI reflects both emissions and economic performance (Dong et al., 2018). Therefore, CI is widely used as an indicator of emission mitigation by governments and researchers. For example, India plans to reduce its CI by 20%-25% between 2005 and 2020 (Stern & Jotzo, 2010), while Malaysia aims to reduce its CI by 40% in 2020 based on its 2005 levels (Mustapa & Bekhet, 2016). This is also particularly true for other developing countries, including China. China is the world's largest developing country. It has the world's largest population and is the second largest economy. The country has experienced high economic growth since the opening up reforms were instituted, with average annual growth exceeding 9% (Chen, Xu, Li, & Song, 2018). This rapid economic growth consumed a large amount of energy and resulted in massive CO 2 emissions. To address global warming and achieve low carbon development, the Chinese government has set a series of top-down policies. For example, China set targets to ...

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“…If MPE increased with rising income, that is, the rich tended to have a higher MPE than the poor, declining income inequality would reduce environmental pollution [45]. Finally, some scholars used the "Veblen effect" to explain the effect of income inequality on environment [44,46,47]. Due to the "Veblen effect", work hours increased as income inequality rose [48].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Individuals in a given class preferred to compare themselves with the superior social class by emulating their consumption. Income inequality increased work hours and consumption, both of which would lead to environmental degradation [44,46,47,49].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some scholars found some cases in which income inequality measured by the Gini index deteriorated the environmental quality [50][51][52], improved the environmental quality [53], or had no impact on the environment [54] by using American data at the state level, Japanese data at the city level, or cross-country data. However, Chen et al, (2020), Baležentis et al, (2020), Grunewald et al, (2017), Jorgenson et al, (2017), and Uddin et al, (2020) [7,44,46,47,49] used data at the country level. They found that the income inequality measured by Gini index had a non-linear effect on carbon emission.…”

Section: Literature Reviewmentioning

confidence: 99%

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The Impact of Income Inequality on Subjective Environmental Pollution: Individual Evidence from China

2021

IJERPH

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Numerous studies have investigated the relationship between income inequality and objective environmental pollution, but few focus on the nexus between income inequality and subjective environmental pollution (SEP). Using micro data from the Chinese General Society Survey (CGSS) in 2013 and official statistical data at the provincial level, this paper tests the impact of individual-level income inequality on subjective environmental pollution in China. The results show that individual-level income inequality has an inverted U-shape relationship with subjective environmental pollution, which indicates that increasing the income inequality at the individual level will first rise and then reduce their perceived subjective environmental pollution after reaching the peak. For about 84% of respondents, their subjective environmental pollution decreases with the increase of individual-level income inequality. Furthermore, the heterogeneity analyses show that the income inequality of urban residents and of the locals have an inverted U-shape effect on SEP, and the SEP of females and of individuals with positive environmental attitude are more sensitive to the effect of income inequality. Additionally, we find that subjective well-being plays a mediating role in the relation between income inequality and SEP. Individual income inequality decreases their self-reported well-being, and an increase in well-being has a negative effect on their subjectively perceived environmental quality. We also find non-television media exposures, such as newspaper, magazine, broadcasting, Internet, and mobile custom messages, will amplify the effect of individual-level income inequality on subjective environmental pollution.

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The impact of income inequality on consumption-based greenhouse gas emissions at the global level: A partially linear approach

Cited by 45 publications

References 69 publications

The relationship between China's income inequality and transport infrastructure, economic growth, and carbon emissions

The relationship between China's income inequality and transport infrastructure, economic growth, and carbon emissions

Net primary productivity‐based factors of China's carbon intensity: A regional perspective

The Impact of Income Inequality on Subjective Environmental Pollution: Individual Evidence from China

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