能源消费对中国雾霾污染的空间溢出效应——基于静态与动态空间面板数据模型的实证研究

唐登莉, 李力, 洪雪飞

系统工程理论与实践 ›› 2017, Vol. 37 ›› Issue (7) : 1697-1708.

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系统工程理论与实践 ›› 2017, Vol. 37 ›› Issue (7) : 1697-1708. DOI: 10.12011/1000-6788(2017)07-1697-12
论文

能源消费对中国雾霾污染的空间溢出效应——基于静态与动态空间面板数据模型的实证研究

    唐登莉, 李力, 洪雪飞
作者信息 +

The spatial spillover effect of energy consumption on haze pollution in China——An empirical research based on the static and dynamic spatial panel data model

    TANG Dengli, LI Li, HONG Xuefei
Author information +
文章历史 +

摘要

基于2004——2013年中国30个省、市及自治区的空间面板数据,运用探索性空间数据分析方法研究中国雾霾污染的空间相关性,再结合静态和动态空间面板数据模型实证分析能源消费对中国雾霾污染的影响.研究结果表明:中国雾霾污染存在显著的空间相关性,其中高高集聚区主要集中在北京、山东、河北、河南、陕西等地区,低低集聚区主要集中在广东、贵州、广西、云南等地区;静态和动态空间面板数据模型均显示能源消费对雾霾污染具有显著的正向影响,但不同地区能源消费对雾霾污染的影响程度存在差异,其中东部和中部地区能源消费对雾霾污染的影响显著,西部地区能源消费对雾霾污染的影响不显著.

Abstract

Based on provincial spatial panel data from 2004 to 2013, this paper studies the spatial correlation of haze pollution in China using exploratory spatial data analysis method, and the impact of energy consumption on haze pollution in China using static and dynamic spatial panel data models. The results show that haze pollution in China exists significant spatial correlation, and High-High cluster region is mainly distributed in Beijing, Shandong, Hebei, Henan and Shaanxi, Low-Low cluster region is mainly distributed in Guangdong, Guizhou, Guangxi and Yunnan. Otherwise, static and dynamic spatial panel data models show that energy consumption has a positive effect on haze pollution, but the effects of eastern and central regions are significant, and the effect of western region is not significant.

关键词

能源消费 / 雾霾污染 / 空间相关性 / 空间面板数据模型

Key words

energy consumption / haze pollution / spatial correlation / spatial panel data model

引用本文

导出引用
唐登莉 , 李力 , 洪雪飞. 能源消费对中国雾霾污染的空间溢出效应——基于静态与动态空间面板数据模型的实证研究. 系统工程理论与实践, 2017, 37(7): 1697-1708 https://doi.org/10.12011/1000-6788(2017)07-1697-12
TANG Dengli , LI Li , HONG Xuefei. The spatial spillover effect of energy consumption on haze pollution in China——An empirical research based on the static and dynamic spatial panel data model. Systems Engineering - Theory & Practice, 2017, 37(7): 1697-1708 https://doi.org/10.12011/1000-6788(2017)07-1697-12
中图分类号: F062.2   

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基金

国家自然科学基金(71371060,71361004);教育部人文社会科学研究规划基金项目(13YJAZH044);广东省软科学研究计划重点项目(2013B070206002)
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