Measurement of the Energy Intensity of Human Well-Being and Spatial Econometric Analysis of Its Influencing Factors

Ruyin Long, Qin Zhang, Hong Chen, Meifen Wu and Qianwen Li
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Ruyin Long: School of Management, China University of Mining and Technology, Xuzhou 221116, China
Qin Zhang: School of Management, China University of Mining and Technology, Xuzhou 221116, China
Hong Chen: School of Management, China University of Mining and Technology, Xuzhou 221116, China
Meifen Wu: School of Management, China University of Mining and Technology, Xuzhou 221116, China
Qianwen Li: School of Management, China University of Mining and Technology, Xuzhou 221116, China

IJERPH, 2020, vol. 17, issue 1, 1-21

Abstract: Current energy efficiency indicators (such as energy intensity) do not properly reflect the inherent relationship between “energy-environment-health”. Therefore, this study introduces the indicator of energy intensity of human well-being (EIWB) to depict the efficiency problem between energy consumption and residents’ health. In this paper, panel data of 30 provinces in mainland China from 2005 to 2016 is used to calculate the EIWB of each province and analyze its spatial distribution. Moreover, the effect of influencing factors on EIWB is investigated by using the spatial Durbin model. The results show that: (1) The EIWB presents a spatial agglomeration. The provinces with high EIWB mostly cluster in the northern China. (2) Industrial structure and energy structure have positive effects on EIWB in local area through increasing energy consumption and damaging residents’ health. (3) The effect of urbanization and income on local EIWB is significantly positive because it will promote energy consumption. (4) Industrial structure, health expenditure, foreign direct investment and technological progress have spatial spillover effects due to its significant impact on residents’ health in neighboring areas. Based on conclusions, the corresponding policy recommendations are proposed.

Keywords: energy intensity of human well-being; influencing factors; spatial econometric analysis; China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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