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我国城镇化发展与环境污染的关系研究—基于31个省市Panel Data变系数模型与VAR模型的实证分析
Analysis of the Relationship between Chinese Urbanization and Environmental Pollution —An Empirical Study Based on Panel Data Model with Variable Coefficients and VAR Model of 31 Provinces and Cities

DOI: 10.12677/SA.2014.33016, PP. 116-125

Keywords: 城镇化,环境污染,倒U型曲线,Panel Data变系数模型,VAR模型
Urbanization
, Environmental Pollution, Inverted U-Shaped Curve, Panel Data Models with Variable Coefficients, VAR Model

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Abstract:

“积极稳妥地推进城镇化”自纳入“十五”规划以来,已成为我国一项基本发展战略。而随着生活水平的日益提高,人们对环境问题也越来越关注。因此,研究城镇化发展与环境污染的关系有重要意义。本文首先利用环境类指标构造环境污染指数,并对历年城镇化率的统计口径进行了修正,然后用描述性统计方法对我国城镇化发展与环境污染的关系进行了特征研究,最后利用Panel Data变系数模型和VAR模型从静态和动态角度对城镇化发展与环境污染的关系进行了深入探讨。研究结果表明,我国大多数省市处于倒U型曲线的左半段,即城镇化的发展带来了一定的环境污染问题。然而对于少数省市(如北京、上海和天津等),城镇化发展会改善环境状况。针对这些结论,提出了相应的对策建议。
Since the 10th Five-Year Plan of China, “actively yet prudently moving forward with urbanization” has been a fundamental development strategy in our country. With rising living standards, people increasingly concern about environmental issues. Therefore, it is quite meaningful to study the relationship between urbanization and environmental pollution. First of all, we use environmental indicators to structure environmental pollution index and conduct a statistical correction on the urbanization rate over the years. Then, features of the relationship between Chinese urbanization and environmental pollution are studied by descriptive statistics. Finally, by using varied coefficients Panel Data model and VAR model, we deeply discuss the relationship between the de-velopment of urbanization and environmental pollution from the perspective of both static and dynamic. The result shows that, the majority of our provinces in the left sections of the inverted U shaped curve, namely the development of urbanization has brought some environmental problems. While for few provinces (such as Beijing, Shanghai and Tianjin etc.), urbanization will improve the environment. According to these conclusions, the paper puts forward the corresponding development suggestions.

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