基于环境学习曲线的工业大气污染物排放强度下降潜力测算  

Measurement of the Reduction Potential of Industrial Air Pollutants Intensity Based on Environmental Learning Curves

作　　者：王文熹 于渤[1] WANG Wen-xi;YU Bo(School of Management,Harbin Institute of Technology,Harbin 150001,China)

机构地区：[1]哈尔滨工业大学管理学院,黑龙江哈尔滨150001

出　　处：《经济问题》2018年第12期68-76,共9页On Economic Problems

基　　金：国家自然科学基金项目"省域装备制造业绿色创新效率评价;空间关联与提升路径研究"(41401655)

摘　　要：工业大气污染物排放强度下降潜力是大气污染物减排规划制定的基础。在环境学习曲线的基础上,借助于异质性随机前沿分析的方法,构建了包含干中学、研发中学和引进中学等因素的大气污染物排放强度下降潜力模型及测算指标。研究结果表明:我国工业大气污染物排放强度存在26. 5%至33. 5%的下降空间;东北地区和东部的工业大气污染物排放强度下降潜力最大,其次是西部地区和中部地区;海南、吉林、江西等是我国工业大气污染物排放强度下降潜力最大的地区;干中学、研发中学及引进中学均对工业大气污染物减排起到了积极的作用。The reduction potential of industrial air pollutants intensity is the basis for iormulating air pollutant emission reduction plan.This paper build a model to measure the reduction potential of industrial air pollutants intensity based on heterogeneous stochastic frontier analysis method and thetheory of environmental learning curves that include factors such as learning-by-doing,learning-by -researching andlearning-by-importing.The resulks show thatChina's industrial air pollutants intensity has a reduction potential of 26.5%to 33.5%.The rank of different regions for reduction potential of industrial air pollutants intensity from large to small is the northeast region,the eastern region,the western regionand the central region.In addition,learning-by-doing,learning-by-researching andlearning-by-importing play a positive role in reducing the industrial air pollutants intensity.

关 键 词：环境学习曲线 大气污染物排放强度 随机前沿分析模型 

分 类 号：F402.4[经济管理—产业经济]