A Comparative Analysis of Residential Energy Consumption in Urban and Rural China: Determinants and Regional Disparities

Abstract

Residential energy consumption (REC) has become increasingly important in constructing an energy-saving and environment-friendly society in China. The main purpose of this study is to provide a more in-depth analysis of the determinants of REC from an urban-rural segregation perspective, and quantify the contributions of individual determinants to the regional disparities of REC. Based on the extended STIRPAT (the stochastic impacts by regression on population, affluence, and technology) model, seemingly unrelated regression (SUR) estimation is employed to examine the impacts of various determinants of urban REC per capita (URECP) and rural REC per capita (RRECP) in a sample of China’s 30 provinces over the period 2007–2016. Then, following the results of SUR, this paper tries to explore the reasons for interprovincial disparities of URECP and RRECP by using the Shapley value decomposition. The empirical results show that income level and heating lead to an increase in URECP, while other factors, including the share of natural gas, average temperature, child dependency ratio and gross dependency ratio, significantly decrease URECP. In terms of RRECP, it is shown that old-age dependency ratio, income level and the share of coal consumption positively influence RRECP, while average temperature has a negative effect on RRECP. Specially, the effect of gross dependency ratio on RRECP is positive, indicating the non-working-age population causes more energy use than the working-age population in rural areas. According to the Shapley decomposition, rather than social-economic variables, climate and heating factors contribute the most to the interprovincial differences in URECP. Furthermore, it is found that income level is the most important factor accounting for inter-provincial differences in RRECP. The findings of this research are of great interest, not only to scholars in REC-related fields, but also to decision makers.

Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China

“…From 2007 to 2018, the Kernel density curve moves to the right, which shows the URE per capita is gradually increasing during the study period. There is evidence that income increase contributes to residential energy consumption [1]. The improvement of living standards promotes each person to consume more residential energy.…”

“…China, as the largest developing country globally, has become the largest energy consumer [1] and energy producer [2]. Energy has been a key factor in evaluating the sustainable development of an economy [3][4][5].…”

“…In existing research, lots of scholars employ econometric analysis methods to study the influencing factors of residential energy consumption. Many studies focus on the relationship between income and residential energy consumption [1,12,13]. For example, Dong et al [1] use seemingly unrelated regression to study the driving factors of urban and rural residential energy use in China.…”

“…Many studies focus on the relationship between income and residential energy consumption [1,12,13]. For example, Dong et al [1] use seemingly unrelated regression to study the driving factors of urban and rural residential energy use in China. The results show income is the main factor increasing residential energy consumption.…”

Empirical Study on Households’ Energy-Conservation Behavior of Jiangsu Province in China: The Role of Policies and Behavior Results

“…An individual resident is the most basic energy consumer, and households are the terminal link of energy consumption. Their behaviors not only directly affect the scale and growth of energy consumption and carbon emissions but also drive the emissions of industry, construction, transportation, and the service industries [8,9]. Therefore, the household potential for reduction is of great significance for environmental conservation.…”