大气污染治理效率与环境政策工具选择——基于29个省市的经验证据  

Air Pollution Abatement Efficiency and Selection of Environmental Policy Tools:Empirical Evidence of 29 Provinces or Municipalities

作　　者：郑石明[1] 罗凯方 

机构地区：[1]华南理工大学公共管理学院,广东广州510641 [2]中南大学公共管理学院,湖南长沙410083

出　　处：《中国软科学》2017年第9期184-192,共9页China Soft Science

基　　金：国家自然科学基金面上项目"绿色创新政策对环境治理绩效的影响:机制;路径及其效应"(71673308);教育部重大攻关项目"我国社会治理体系构建及其运行机制研究"(16JZD026);湖南省社科基金项目"地方政府环境政策对城市空气质量的影响研究"(15YBA387)

摘　　要：基于我国29个省市2005-2014年大气污染治理面板数据,运用超效率DEA模型测算出大气污染治理效率,并运用面板校正标准误(PCSE)模型评估三类政策工具对大气污染治理效率的影响。研究显示:对比2005年与2014年的聚类结果显示,十年前后,海南、宁夏和内蒙古均居高效率组,湖南、广东、四川和天津则一直处于低效率组,上海从高效率组跌至低效率组。政策工具的滞后回归表明,我国管制型和市场型政策工具对大气污染治理均有成效,与治理效率呈正相关,自愿型政策工具则对大气污染治理效率暂无正向影响。该结果通过了稳健性检验。Abstract： Based on the panel data of 29 provinces and municipalities in 2005 -2014, super-efficiency DEA model is employed to measure the air pollution abatement efficiency. Subsequently we employ panel-corrected standard error model to evaluate the impacts of policy tools on air pollution abatement efficiency. The results suggest that Hainan, Ningxia and Inner Mongolia were clustered in high efficiency group in 2005 and 2014, while Hunan, Guangdong, Siehuan and Tianjin in low efficiency group. Shanghai dropped from the high efficiency group in 2005 to the low in 2014. The lag regression results of policy tools＇ impacts reveal that regulatory and market-oriented policy tools are effective and positively correlated with air pollution abatement efficiency, while voluntary policy tools has been witnessed no positive correlation. The results above have passed the robustness test. Key words：air pollution abatement efficiency; environmental policy tools; super-efficiency DEA

关 键 词：大气污染治理效率 环境政策工具 超效率DEA模型 

分 类 号：D035.5[政治法律—政治学]