外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数（AQI）为例

doi:10.13249/j.cnki.sgs.2018.03.004

地理科学 ›› 2018, Vol. 38 ›› Issue (3): 351-360.doi: 10.13249/j.cnki.sgs.2018.03.004

外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数（AQI）为例

姜磊^1,²(), 周海峰¹, 柏玲³

1.浙江财经大学经济学院,浙江杭州310018
2.南京航空航天大学经济与管理学院,江苏南京210016
3.南昌大学经济管理学院,江西南昌330031

收稿日期:2017-02-18 修回日期:2017-05-27 出版日期:2018-03-21 发布日期:2018-03-21
作者简介:
作者简介：姜磊（1983-）,男,山东烟台人,博士,助理教授,主要从事应用空间计量经济学、空间数据分析和区域经济学研究。E-mail: lei_jiang@zufe.edu.cn
基金资助:
国家自然科学基金项目（41761021,71742001）、教育部人文社会科学青年基金项目（17YJC790061）、江西省主要学科学术和技术带头人培养计划项目（2014BCB22002）、中国博士后科学基金面上项目(2017M621740)资助

Spatial Heterogeneity Analysis of Impacts of Foreign Direct Investment on Air Pollution：Empirical Evidence from 150 Cities in China Based on AQI

Lei Jiang^1,²(), Haifeng Zhou¹, Ling Bai³

1. School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, Zhejiang, China;
2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
3. School of Economics & Management, Nanchang University, Nanchang 330031, Jiangxi, China;

Received:2017-02-18 Revised:2017-05-27 Online:2018-03-21 Published:2018-03-21
Supported by:
National Natural Sciences Foundation of China (41761021,71742001),The Project of Humanities and Social Science Youth Fund of Ministry of Education (17YJC790061), Major Disciplines Academic and Technical Leaders Project Plan of Jiangxi Province (2014BCB22002),China Postdoctoral Science Foundation（2017M621740）

摘要/Abstract

摘要：

空气污染问题引起了人们极大的关注。以中国2014年150个地级市作为样本数据,采用空气质量指数（AQI）作为全面衡量空气污染的指标,运用地理加权回归模型从空间异质性视角出发,分析了不同城市外商直接投资与空气污染之间的关系。研究结果表明：总体上,外商直接投资由于带来了先进的技术,有利于空气质量的改善。此外,人均地区生产总值的增加、二氧化硫和PM_2.5浓度的提高均是导致空气污染加剧的重要因素;而环保意识的提升则有利于空气质量的改善。民用汽车保有量变量在统计上不显著。从地理加权回归模型估计结果来看,不同城市的外商直接投资对环境的改善作用存在显著的空间异质性。其中,东北城市群、关中城市群和长江中游城市群外商直接投资对空气质量的改善作用最大,山东半岛城市群和川渝城市群外商直接投资对空气质量的改善作用不明显。

关键词: 外商直接投资, “污染避难所”假说;, 空气质量指数, 地理加权回归模型

Abstract:

The issue of air pollution in China has already surged in recent years, attracting public concerns, even great anxiety. This paper employs a unique cross-sectional data set of 150 Chinese cities in 2014 and adopts air quality index (AQI), an indicator newly-developed by the ministry of environmental protection of China, to measure air quality. Then, from a spatial heterogeneity perspective it applies ordinary least square (OLS) technique and geographically weighted regression (GWR) model to analyze the impact of foreign direct investment (FDI) on air pollution controlling for other five explanatory variables, namely, per capita GDP, population density, sulfur dioxide emissions, PM_2.5 concentration, and the number of vehicles. Meanwhile, it also investigates if there is an inverted U-shaped curve between per capita GDP and air quality index, specifically environmental Kuznets curve (EKC). The findings are the following. Firstly, there is no evidence of EKC, but an increasing linear relationship between income and air pollution. Secondly, the variable of FDI is found to be significant and negative, indicating that an increase of foreign capital may reduce air quality index, in other words, improve air quality. This is because foreign capital brings advanced technologies, improving air quality effectively. Besides, sulfur dioxide emissions and PM_2.5 concentration are found to have significant and positive impacts on AQI while population density, as an indicator of environmental awareness, is found to have a negative impact on AQI. However, from the results of the OLS model, the variable of private cars is not statistically significant, even found to be positive. It hence was deleted from the model. Thirdly, the GWR model results suggest that the impacts of FDI of 150 cities on air pollution greatly vary from city to city. Specifically speaking, foreign capitals of the northeastern cities, Guangzhong plain urban cities and cities of the middle reaches of the Yangtze River play a more important role in reducing air pollution than those of other cities. On the contrary, the contribution of foreign capitals of Shandong peninsula cities and Sichuan-Chongqing urban cluster is found to be insignificant. Finally, from the above analysis, a series of policy handles and suggestions are given.

Key words: foreign direct investment, ‘pollution haven hypothesis’, air quality index, geographically weighted regression model

中图分类号:

F205

姜磊, 周海峰, 柏玲. 外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数（AQI）为例[J]. 地理科学, 2018, 38(3): 351-360.

Lei Jiang, Haifeng Zhou, Ling Bai. Spatial Heterogeneity Analysis of Impacts of Foreign Direct Investment on Air Pollution：Empirical Evidence from 150 Cities in China Based on AQI[J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(3): 351-360.

图/表 5

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变量	OLS模型1	OLS模型2	OLS模型3	OLS模型4
lnFDI	-0.0129***(-3.2030)	-0.0128***(-3.2540)
lnGDP	0.0450***(3.0158)	0.0459***(3.6422)
lnFDI_t-1			-0.0115***(-2.8557)	-0.0114***(-2.8677)
lnGDP _t-1			0.0286**(2.3574)	0.0299***(3.0351)
lnDensity	-0.0109*(-1.5951)	-0.0112*(-1.8038)	-0.0107(-1.4966)	-0.0113*(-1.7683)
lnSO₂	0.0078*(1.6964)	0.0078*(1.6987)	0.0074(1.5596)	0.0073(1.5546)
lnPM_2.5	0.7839***(52.3631)	0.7841***(52.8270)	0.7921***(49.8536)	0.7928***(51.2384)
lnCars	0.0011(0.1120)		0.0019(0.1842)
常数项	0.9268***(5.6546)	0.9154***(7.1439)	1.0657***(7.4329)	1.0485***(9.6700)
R²	0.9626	0.9626	0.9615	0.9615
调整后的R²	0.9610	0.9613	0.9599	0.9602
F统计量	613.5905***	741.3901***	595.8910***	719.8921***

变量	最小值	第一分位	中位数	第三分位	最大值	全域
lnFDI	-0.0243	-0.0163	-0.0098	-0.0051	0.0056	-0.0128
lnGDP	-0.0573	0.0089	0.0171	0.0407	0.1718	0.0459
lnDensity	-0.0506	-0.0107	0.0017	0.0095	0.0660	-0.0112
lnSO₂	-0.0098	0.0030	0.0118	0.0185	0.0367	0.0078
lnPM_2.5	0.6702	0.7339	0.7705	0.7824	0.8769	0.7841
常数项	-0.6278	0.9143	1.1600	1.2470	1.9220	0.9154

外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数（AQI）为例

Spatial Heterogeneity Analysis of Impacts of Foreign Direct Investment on Air Pollution：Empirical Evidence from 150 Cities in China Based on AQI

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