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空间视角下财政分权的碳排放效应研究--基于半参数空间面板滞后模型
引用本文:郑万吉,叶阿忠.空间视角下财政分权的碳排放效应研究--基于半参数空间面板滞后模型[J].软科学,2017(1).
作者姓名:郑万吉  叶阿忠
作者单位:福州大学 经济与管理学院,福州,350108
基金项目:国家自然科学基金项目(71171057);教育部人文社会科学基金项目(10YJA790227);教育部高等学校博士点基金项目(20103514110009)
摘    要:基于2000~2013年中国省份面板数据,通过构建半参数空间面板滞后模型( S-PSLM)结合工具变量法分析我国地方政府财政分权度对于碳排放的影响。研究表明:财政分权度对于碳排放增长率的影响呈现倒“U型”,该作用随财政分权度的增大而先增后减,由抑制到促进再到抑制;重工业发展会促进本地区碳排放的增加,而周边省份的重工业发展则会降低本地区的碳排放上升压力;自身对外贸易发展虽然对碳排放影响不显著,不过区域间的外贸合作却是降低碳排放增长的有效途径;R&D研发强度增加有助于减缓碳排放增长,而区域技术创新能力不平衡阻碍了空间溢出效应。

关 键 词:财政分权  碳排放  半参数面板空间模型  工具变量

Research on the Carbon Emission Perspective of Environmental Benefits of Fiscal Decentralization---Based on Semi-parametric Panel of Spatial Lag Model
ZHENG Wan-ji,YE A-zhong.Research on the Carbon Emission Perspective of Environmental Benefits of Fiscal Decentralization---Based on Semi-parametric Panel of Spatial Lag Model[J].Soft Science,2017(1).
Authors:ZHENG Wan-ji  YE A-zhong
Abstract:Combined with the method of instrumental variables , this paper analyzes the relationship between fiscal decentral-ization and carbon emission by building the semi-parametric panel ( S-PSLM) of spatial lag model and using Chinese prov-ince data from 2000 to 2013.Results show that, firstly, there is a nolinear impact between fiscal decentralization and carbon emission, which demonstrates an invertd “U-type”.It means that, with the development of fiscal decentralization , fiscal decentralization firstly rose the growth of carbon emission , and then slow it.Secondly, development of heavy industry in lo-cal region will promote the increase of carbon emissions , but the development of surrounding provinces'will reduce it.Al-though foreign trade's impact on carbon emissions is not significant , inter-regional trade cooperation is an effective way to re-duce the increasing emissions .Research and development strength is helpful to slow emissions growth , and regional techno-logical innovation capability imbalance hinders its spatial spillover effects .
Keywords:fiscal decentralization  carbon emission  semi-parametric panel of spatial model  instrumental variables
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