Factors Influencing the Spatial Difference in Household Energy Consumption in China

Yongxia Ding, Wei Qu, Shuwen Niu, Man Liang, Wenli Qiang and Zhenguo Hong
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Yongxia Ding: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China
Wei Qu: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China
Shuwen Niu: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China
Man Liang: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China
Wenli Qiang: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China
Zhenguo Hong: College of Earth and Environmental Sciences, Lanzhou University, No. 222, Tianshui South Road, Lanzhou 730000, China

Sustainability, 2016, vol. 8, issue 12, 1-20

Abstract: What factors determine the spatial heterogeneity of household energy consumption (HEC) in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model and panel dataset for 30 provinces in China over the period 1997–2013, this paper investigated influences of the income per capita, urbanization level and annual average temperature on HEC, and revealed the spatial effects of these influencing factors. The results show that the income level is the main influencing factor, followed by the annual average temperature. There exists a diminishing marginal contribution with increasing income. The influence of urbanization level varies according to income level. In addition, from the eastern region to western region of China, variances largely depend upon economic level at the provincial level. From the northern region to southern region, change is mainly caused by temperature. The urbanization level has more significant impact on the structure and efficiency of household energy consumption than on its quantity. These results could provide reference for policy making and energy planning.

Keywords: household energy consumption; spatial difference; geographical factors; urbanization level; panel data model; STIRPAT model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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