东北大学学报(社会科学版) ›› 2015, Vol. 17 ›› Issue (6): 573-579.DOI: 10.15936/j.cnki.1008-3758.2015.06.005

• 经济与管理研究 • 上一篇    下一篇

中国省域碳排放的空间溢出与影响因素研究基于空间面板数据模型

曹洪刚,陈凯,佟昕   

  1. (东北大学工商管理学院,辽宁沈阳110819)
  • 收稿日期:2015-04-10 修回日期:2015-04-10 出版日期:2015-11-25 发布日期:2015-11-25
  • 通讯作者: 曹洪刚
  • 作者简介:曹洪刚(1975-),男,黑龙江七台河人,东北大学博士研究生,主要从事区域经济、低碳经济研究;陈凯(1961-),男,山西浑源人,东北大学教授,博士生导师,主要从事能源经济、理论经济等研究;佟昕(1975-),女,辽宁沈阳人,东北大学讲师,主要从事区域经济、低碳经济、控制与决策等研究。
  • 基金资助:

    教育部人文社会科学研究规划基金资助项目(12YJA790010);东北大学人文社会科学基金重点资助项目(XNR201307)。

Study on the Spatial Spillover and Influencing Factors of Chinas Provincial Carbon EmissionBased on the Spatial Panel Data Model

CAO Hong-gang, CHEN Kai, TONG Xin   

  1. (School of Business Administration, Northeastern University, Shenyang 110819, China)
  • Received:2015-04-10 Revised:2015-04-10 Online:2015-11-25 Published:2015-11-25
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摘要:

以空间地理视角,验证了我国省域碳排放空间依赖性;基于空间面板数据模型,估计了不同视域影响因素对碳排放增长的贡献。研究发现:2000—2012年间,中国省域能源碳排放空间上具有依赖性,邻近省域的碳排放及影响因素的空间溢出效应明显;经济增长、金融发展、城镇化率、产业结构和出口依存度系数均为正值,人口、技术进步对降低碳排放增长作用效果显著,能源价格对碳排放增长作用效果没有通过显著性检验。政府部门在制定碳排放相关政策和发展规划时,必须考虑邻近区域碳排放影响因素的作用,结合碳排放及相关影响因素的空间溢出效应,实现中国在时间维度和空间维度的碳排放量整体降低。

关键词: 碳排放, 空间溢出, 空间面板数据模型

Abstract:

From the spatial geographical perspective the spatial dependence of Chinas provincial carbon emission was examined, and based on the spatial panel data model, the contribution of different influencing factors to carbon emission growth was estimated. It was found that there exists spatial dependence in Chinas provincial energy carbon emission from 2000 to 2012, and the spatial spillover effects of neighboring provincial carbon emission and influencing factors are remarkable—the coefficients of economic growth, financial development, urbanization rate, industrial structure and export dependence are positive, the effect of population and technological progress on reducing carbon emission growth is remarkable, but the effect of energy price on carbon emission growth fails to pass the test of significance. In policy making and development planning, the government should take into account the effect of neighboring regions carbon emission, and integrate carbon emission and the spatial spillover effect of related influencing factors so as to reduce Chinas carbon emission in both temporal and spatial dimensions as a whole.

Key words: carbon emission, spatial spillover, spatial panel data model

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