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基于31个省份事件史分析的河长制创新与扩散的影响因素
引用本文:梅正午,刘文璋,孙玉栋.基于31个省份事件史分析的河长制创新与扩散的影响因素[J].中国环境科学,2021,41(6):2956-2963.
作者姓名:梅正午  刘文璋  孙玉栋
作者单位:中国人民大学公共管理学院, 北京 100872
基金项目:教育部哲学社会科学研究重大课题攻关项目(17JZD014);北京市社会科学基金重大项目(18ZDA10);中国人民大学科学研究基金(中央高校基本科研业务费专项资金资助)项目(21XNH032);中央高校建设世界一流大学(学科)和特色发展引导专项资金
摘    要:利用事件史分析(EHA)模型对河长制政策2010~2016年在省级层面的扩散进行实证研究,结果表明:水污染越是严重的地区,越倾向于采纳河长制,平均而言,人均水污染排放量每增加一个单位,一个省份河长制政策得到采纳的优势会增加30.2%;财政自给率在水污染严重程度与河长制采纳之间具有负向调节效应,即面临严重的环境污染,财政自给率高的省份不太倾向于采纳河长制,而财政自给率低的省份则更加倾向于采纳河长制;河长制政策采纳具有明显的政治周期性,在党代会召开的当年,省政府更加倾向于采纳河长制;邻近省份的政策采纳并不会对河长制的横向扩散产生显著影响.

关 键 词:河长制  创新扩散  事件史分析  
收稿时间:2020-11-17

Influencing factors of policy diffusion of river chief system based on event history analysis of 31 provinces
MEI Zheng-wu,LIU Wen-zhang,SUN Yu-dong.Influencing factors of policy diffusion of river chief system based on event history analysis of 31 provinces[J].China Environmental Science,2021,41(6):2956-2963.
Authors:MEI Zheng-wu  LIU Wen-zhang  SUN Yu-dong
Institution:School of Public Administration and Policy, Renmin University of China, Beijing 100872, China
Abstract:Using the event history analysis (EHA) model, we conducted an empirical study on the diffusion of river chief system (RCS) policy at the provincial level from 2010 to 2016. The RCS policy was more likely to be adopted by provinces with more serious water pollution. Specifically, on average, a one-unit increase in per capita water pollution emission increased the odds of RCS policy adoption by 30.2%; but the effect of water pollution on the adoption of RCS policy was negatively moderated by the fiscal self-financing rate. Under same water pollution level, provinces with low fiscal self-financing rate were more likely to adopt the RCS policy. Provincial governments were more likely to adopt the RCS policy in the years when the party congresses were held. The adoption of the RCS policy in a certain province did not have a significant impact on the horizontal policy diffusion across its neighboring provinces.
Keywords:river chief system  policy diffusion  event history analysis  
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