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机构地区:[1]江西财经大学协同创新中心,中国江西南昌330013 [2]江西财经大学信息管理学院,中国江西南昌330013
出 处:《经济地理》2014年第4期25-32,共8页Economic Geography
基 金:国家自然科学基金项目(71263020);江西财经大学重大招标项目"鄱阳湖生态经济区资源;环境与社会经济发展跟踪评价研究";江西省落地计划项目"数字鄱阳湖生态经济区建设研究"
摘 要:首先分别用Herfindahl指数、Gini指数、地理集中度指数测度了我国省级区域的经济集聚度水平与污染集聚度水平,通过空间相关性检验,证明了经济集聚度与污染集聚度存在很强的正相关关系,即经济的集聚加速了污染的集聚,并且污染的集聚态势趋同于经济的集聚态势。其次,应用空间误差模型分析了影响污染集聚的因素。经济集聚是引起污染集聚的首要决定因素,能源消费、城镇化进程、外商直接投资都会显著促进污染的集聚;技术创新则会显著降低污染的集聚;产业结构对污染集聚的作用不显著;人口的集聚性高则未必会引起污染的集聚性高,如我国的上海和北京等发达城市,尽管人口密度很大,但是由于污染处理及时得力,并没有引起污染的迅速集聚。At first, this paper respectively uses Herfindahl index, Gini index and geographic concentration index to measure the economy aggregation degree and the pollution aggregation degree, uses spatial correlation test to prove the strong positive correlation between economy aggregation degree and pollution aggregation degree, and then proves that economy aggregation accelerates the pollution aggregation, and finds that the trend of pollution aggregation is similar to the trend of economy aggregation. Secondly, the spatial error model is used to analyze the factors affecting pollution aggregation.Economy aggregation is the first determinant factor of pollution aggregation, energy consumption, the urbanization process and foreign direct investment will significantly promote the pollution aggregation. Technology innovation can significantly reduce the pollution aggregation. The role of industrial structure promoting pollution aggregation is not significant. High population aggregation does not necessarily lead to high pollution aggregation, for example developed city like Shanghai and Beijing, due to timely and effective treatment of pollution, it doesn't cause pollution quickly gathered though the population density is very large.
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