Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model
AbstractRenewable energy can help to tackle energy poverty issues of the availability of modern energy services and the sustainability of energy supply. Based on the concept of the Energy Development Index, published by International Energy Agency, this paper builds the clean energy development index and applies the Grey incidence decision method to analyze regional energy poverty issues in China. A model using panel data investigates the influencing factors that are governing energy poverty alleviation and the relationship between energy poverty and social development. The improved index system not only considers the access to modern energy services, but also addresses the cleanliness of energy supply and the transition to clean energy consumption for cooking. The results indicate that due to insufficient clean energy development, China’s Northeast and West regions have experienced increasing energy poverty problems, while energy poverty in the Southwest region has improved considerably because of its renewable energy development. Urbanization, affordability, and renewable energy development can increase access to modern energy services, contributing to energy poverty alleviation. However, the role of rural household consumption levels in energy poverty alleviation should be considered in rural energy policy. View Full-Text
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Wang, B.; Li, H.-N.; Yuan, X.-C.; Sun, Z.-M. Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model. Energies 2017, 10, 1942.
Wang B, Li H-N, Yuan X-C, Sun Z-M. Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model. Energies. 2017; 10(12):1942.Chicago/Turabian Style
Wang, Bing; Li, Hua-Nan; Yuan, Xiao-Chen; Sun, Zhen-Ming. 2017. "Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model." Energies 10, no. 12: 1942.
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