文章利用2003—2017年中国29个省（自治区、直辖市）的面板数据,分析各省域环境税及产业结构的空间相关性与局域集聚特征,基于4种空间权重矩阵构建空间误差模型,考察环境税对产业结构的调整效应。结果表明：①通过全局莫兰指数和局部莫兰指数证实环境税及产业结构存在显著的空间依赖性,具有“高—高”集聚和“低—低”集聚的特点;②从全国样本回归结果来看,环境总税费显著抑制了产业结构优化,其中排污费效应不显著,资源税、车船税、城市维护建设税、耕地占用税存在显著负效应,而城镇土地使用税则具有显著正效应;③从分区域样本回归结果来看,环境税对产业结构的调整效应存在明显的区域异质性,中部地区最强、西部地区次之,东部地区最弱。因此,文章从“制定差异化环境税政策”“加强地方政府间的合作与协调”“规范地方政府间的横向竞争”三方面提出相应的政策建议。
Based on the panel data of 29 provinces and municipalities in China from 2003 to 2017,this article analyzes the spatial correlation between environmental taxes and industrial structure in various provinces and municipalities and their regional agglomeration characteristics,and constructs the spatial error model based on four weight matrices to study the adjustment effect of environmental taxes on industrial structure. The results are as follows: 1) It confirms that it has significant spatial dependence between environmental taxes and industrial structure on the basis of global Moran's I and local Moran's I,and shows the characteristics of "high-high" regional agglomeration and "low-low" regional agglomeration. 2) According to the regression results of the national samples,the total environmental taxes have significantly inhibited the optimization of industrial structure,among which the effect of sewage charges is not significant,resource tax,vehicle and vessel tax,urban maintenance and construction tax,and farmland occupation tax have significant negative effects,while the urban land use tax has a significant positive effect. 3) According to the regression results of the regional samples,the adjustment effect of environmental taxes on the industrial structure has obvious regional heterogeneity,with the central region being the strongest followed by the western region and the eastern region. Therefore,it puts forward corresponding policy suggestions from three aspects: formulating differentiated environmental tax policies,strengthening cooperation and coordination among local governments,standardizing horizontal competition among local governments and so on.
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