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Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis

机译:中国环境污染的社会经济驱动因素:空间计量经济学分析

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摘要

This paper studies the environmental pollution and its impacts in China using prefecture-level cities and municipalities data. Moran's I, the widely used spatial autocorrelation index, provides a fairly strong pattern of spatial clustering of environmental pollution and suggests a fairly high stability of the positive spatial correlation. To investigate the driving forces of environmental pollution and explore the relationship between fiscal decentralization, economic growth, and environmental pollution, spatial Durbin model is used for this analysis.The result shows that fiscal decentralization of local unit plays a significant role in promoting the environmental pollution and the feedback effect of fiscal decentralization on environmental pollution is also positive, though it is not significant. The relationship of GDP per capita and environmental pollution shows inverted U-shaped curve. Due to the scale effect of secondary industry, the higher the level of secondary industry development in a unit is, the easier it is to attract the secondary industry in adjacent units, which mitigates the environmental pollution in adjacent units. Densely populated areas tend to deteriorate local environment, but environmental regulation in densely populated areas is often tighter than other areas, which reduces environmental pollution to a certain extent.
机译:本文使用县级城市和市政数据研究环境污染及其对中国的影响。莫兰的I,广泛使用的空间自相关指数,提供了环境污染的相当强烈的空间聚类模式,并表明了积极空间相关的相当高的稳定性。为了调查环境污染的驱动力,探索财政分散,经济增长和环境污染之间的关系,空间德国模型用于该分析。结果表明,地方单位的财政分权在促进环境污染方面发挥着重要作用财政权力下放对环境污染的反馈效果也是积极的,尽管它并不重要。人均GDP和环境污染的关系显示倒U形曲线。由于二级行业的规模效应,单位中的二级行业发展水平越高,越突出的是吸引邻近单位的二级行业,这减轻了相邻单位的环境污染。浓密的人口稠密的区域往往会恶化当地环境,但浓密人口稠密地区的环境监管往往比其他地区更紧密,这在一定程度上降低了环境污染。

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