城市规模、空间集聚与电力强度

City Size,Spatial Agglomeration and Electricity Intensity in China

中国仍处在快速城市化的过程中,城市人口、工业及其他因素共同决定着不同的城市规模和产业结构,进而影响着一个城市的电力强度水平。本文选取了2003—2013年我国31个省级行政区267个地级市相关数据,通过建立动态面板模型进行回归分析。研究结果表明,城市规模与电力强度之间存在倒U型的非线性关系,即随着城市规模的扩大电力强度出现先上升后下降的现象。为了进一步探索城市规模对电力强度的影响机制,本文引入空间集聚的概念,同时构建了一个用来反映省级行政区内部空间集聚水平的重要指标——空间基尼系数。本文利用相关数据对空间基尼系数进行计算,并将其纳入模型进行回归分析。研究结果发现,空间集聚对电力强度确实具有一定程度的负向影响。本文研究结论从优化电力强度的视角,探讨了城市电力强度最优条件下的合理城市规模,并为我国城市化过程中建设现代化的大型城市提供了实践参考与决策支持。

Summary： With outstanding quality and clean features, electricity is a secondary energy which is accessible most conveniently in cities. Due to the impact of the fog and haze, China has promoted the transition of urban energy consumption toward electricity in recent years. Some proposals, such as replacing coal with electricity and replacing oil with electricity, are provided to make electricity the core of the end-use energy system. China has made great progress in renewable energy power generation recently. However, based on the current conditions of resource endowment and technology development, the renewable energy sourcing supply is still mainly generated by coal in the present and is expected to continue in the future. China is still in the process of fast urbanization. In this stage, urban electricity intensity is jointly influenced by changes of population structure, industry structure, land use structure, and spatial region structure. This paper analyzes their impacts from the perspectives of city size and spatial agglomeration. The literature mainly includes study of variation trends and influence factors of electricity intensity. Lin et al. （2010）, Zha et al. （2012）, Herrerias ＆ Liu （2013）, Ouyang ＆ Lin （2014）, and Xie et al. （2015） found that the variation of China＇s electricity intensity fluctuates, with a declining tendency based on industry structure, technology improvement, and energy price. No research has analyzed the impacts of city size and spatial agglomeration on urban electricity intensity. This study attempted to research this field and determine the effect of city size on electricity intensity. Most of the literature has been based on province-level data sets, with few studies addressing the energy efficiency of electricity using prefecture city or smaller-scale data. The study is in two sections. First, using the data of 267 prefecture cities from China＇s 31 provincial administrative regions during 2003 to 2013, we built a dynamic panel data model. The estimation methodology was based on the GMM approach of Arellano ＆ Bover （1995） and Blundell ＆ Bond （1998）. Discussions on the relationship between city size and electricity intensity were based on analyses of prefecture-level data. Second, we introduced the important indicator the spatial Gini coefficient, which illustrated the value of spatial agglomeration in the provincial administrative regions. Using the data of China＇s provincial administrative regions from 2003 to 2013, we established another GMM-based dynamic panel data model. The results revealed the relationship between spatial agglomeration and electricity intensity. The relationship between city size and electricity intensity appeared in our results as an inverted U shape. With the growth in city size, urban electricity intensity has increased. But with city size expansion over the population threshold of 746.84 million urban electricity intensity decreases. Furthermore, spatial agglomeration has had inhibiting effect on electricity intensity. When the spatial Gini coefficient increases by one standard deviation, electricity intensity decreases by 1.08% , indicating that the clustering of population and economic activities in large cities helps to reduce electricity intensity. According to the results, we suggest that during the process of urbanization, the government should promote population and industry clustering, the development of which is specialized and industrialized, into big cities. A series of policies referring to population, land, and fiscal taxation should be properly introduced. These policies could help energy conservation and emissions reduction and support the sustainable development of the economy, society, and environment.