Abstract
Using spatial econometric analysis technique, the spatial weight matrix constructed according to the geographical features of the sample cities, and the spatial lag model (SLM) and spatial error model (SEM) based on the environmental Kuznets curve (EKC), this paper empirically investigates the spatial autocorrelation and the socioeconomic influential factors of urban carbon emissions in China through data of 280 cities in 2013. The research shows that urban carbon emissions in China is significant positive spatial autocorrelation; and the relationship between GDP and urban carbon emission is N type curve, which shows the environmental Kuznets (EKC) curve of the inverted U is not existence at the present stage of urban carbon emission; In addition, the secondary on urban carbon emissions is not significant and negative correlation. While the amount of motor vehicles, the foreign investment and the urban population have significant and positive influences on urban carbon emission. As a result, a series of comprehensive measures in both social and economic aspects as well as the regional coordination of environmental policies are needed to reduce urban carbon emission.
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