LAPSE:2023.12404
Published Article

LAPSE:2023.12404
Exploring Increasing Urban Resident Electricity Consumption: The Spatial Spillover Effect of Resident Income
February 28, 2023
Abstract
The impact of average wages on electricity consumption among urban residents in China has generated many fascinating debates for scholarly research, but only a few studies have considered the spatial spillover effect of average wages on residential electricity consumption. With the use of city-level panel data from 278 Chinese cities spanning 2005 to 2016, this preliminary study explores the impacts of the average wage on residential electricity consumption. Specifically, based on the spatial Durbin model with fixed effects, three different spatial weight matrices (the economic distance, the inverse distance, and the four nearest neighbours) are utilised to check the robustness of the results under different standards. The results show that the residential electricity consumption of each city increased during the observation period, presenting obvious spatial correlations. Secondly, the average wage of residents had a positive spatial spillover effect, which promoted the residential electricity consumption of both local and surrounding cities. Thirdly, the population density, electricity intensity, educational level of urban residents, and per capita household liquefied petroleum gas consumption in urban areas are key factors influencing residential electricity consumption. Therefore, improving the educational level of urban residents and reducing the electricity intensity can help reduce electricity consumption by residents in China. This paper also presents policy recommendations.
The impact of average wages on electricity consumption among urban residents in China has generated many fascinating debates for scholarly research, but only a few studies have considered the spatial spillover effect of average wages on residential electricity consumption. With the use of city-level panel data from 278 Chinese cities spanning 2005 to 2016, this preliminary study explores the impacts of the average wage on residential electricity consumption. Specifically, based on the spatial Durbin model with fixed effects, three different spatial weight matrices (the economic distance, the inverse distance, and the four nearest neighbours) are utilised to check the robustness of the results under different standards. The results show that the residential electricity consumption of each city increased during the observation period, presenting obvious spatial correlations. Secondly, the average wage of residents had a positive spatial spillover effect, which promoted the residential electricity consumption of both local and surrounding cities. Thirdly, the population density, electricity intensity, educational level of urban residents, and per capita household liquefied petroleum gas consumption in urban areas are key factors influencing residential electricity consumption. Therefore, improving the educational level of urban residents and reducing the electricity intensity can help reduce electricity consumption by residents in China. This paper also presents policy recommendations.
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Keywords
average wage, China, residential electricity consumption, spatial Durbin model, spatial spillover effect
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Suggested Citation
Liu S, Zhang Z, Yang J, Hu W. Exploring Increasing Urban Resident Electricity Consumption: The Spatial Spillover Effect of Resident Income. (2023). LAPSE:2023.12404
Author Affiliations
Liu S: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Zhang Z: State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China; School of Geomatics, Anhui University of Science and Technology, Huainan 232001, China [ORCID]
Yang J: State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China
Hu W: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Zhang Z: State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China; School of Geomatics, Anhui University of Science and Technology, Huainan 232001, China [ORCID]
Yang J: State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China
Hu W: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Journal Name
Energies
Volume
15
Issue
12
First Page
4249
Year
2022
Publication Date
2022-06-09
ISSN
1996-1073
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PII: en15124249, Publication Type: Journal Article
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LAPSE:2023.12404
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https://doi.org/10.3390/en15124249
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