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The interaction of income inequality and energy poverty on global carbon emissions: A dynamic panel data approach

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  • Wang, Feng
  • Qu, Mengdie

Abstract

Income inequality and energy poverty are critical obstacles to the worldwide low-carbon transformation and deeply affect human behavior. Applying a dynamic panel data model, this study investigates the effect of income inequality and energy poverty on global carbon emissions. We determine the effect of the interaction between income inequality and energy poverty on the global low-carbon transformation based on a panel data set of 193 countries from 1990 to 2019. A one standard deviation decrease in the Gini coefficient causes a 2.98 % decrease in carbon emissions per capita, with the median value of energy poverty. However, in poor countries where the proportion of population with access to electricity is less than 86.0 %, reducing income inequality will increase carbon emissions. The role of energy poverty on carbon emissions per capita is also affected by income inequality. When the Gini coefficient is lower than 0.461, increasing access to electricity will reduce carbon emissions. In contrast, when the Gini coefficient is higher than the critical value of 0.461, increased access to electricity will raise carbon emissions. These findings indicate a new strategy for advancing low-carbon transformation based on the interrelationship between income equality and energy poverty eradication.

Suggested Citation

  • Wang, Feng & Qu, Mengdie, 2024. "The interaction of income inequality and energy poverty on global carbon emissions: A dynamic panel data approach," Energy Economics, Elsevier, vol. 140(C).
  • Handle: RePEc:eee:eneeco:v:140:y:2024:i:c:s0140988324007369
    DOI: 10.1016/j.eneco.2024.108027
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    References listed on IDEAS

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    1. Zhang, Chuanguo & Zhao, Wei, 2014. "Panel estimation for income inequality and CO2 emissions: A regional analysis in China," Applied Energy, Elsevier, vol. 136(C), pages 382-392.
    2. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
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    More about this item

    Keywords

    Carbon emissions; Income inequality; Energy poverty; Dynamic panel data model;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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