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我国环保企业生产效率及不确定性——基于面板数据的DEA与神经网络分析
引用本文:陶迎平,胡俊,宋马林.我国环保企业生产效率及不确定性——基于面板数据的DEA与神经网络分析[J].安徽理工大学学报(社会科学版),2012(1):24-29.
作者姓名:陶迎平  胡俊  宋马林
作者单位:安徽财经大学统计与应用数学学院
基金项目:国家自然科学基金项目(71171001);教育部人文社会科学研究青年基金项目(10YJC630208);安徽省高等学校省级自然科学研究重点项目(KJ2011A001)
摘    要:环境保护产业作为中国战略性新兴产业之一,为新一轮中国经济增长增添动力。同时,它也是中国促进可持续发展与技术发展、抓住新机遇,建设一个创新型国家的重要措施。然而,由于工业化的反作用,同时作为环保科技产业自身的特点,环保企业的生产效率从总体来说普遍不高。为了反映生产效率,建立一个考虑固定资产、管理费用、财务费用、与职工有关现金支出、总税费支出、利润等与企业环保有关的财务支出指标体系。利用DEA方法对2004-2010年各企业面板数据分析企业的生产效率,同时利用神经网络模拟预测其2011年到2015年发展前景。

关 键 词:数据包络分析  规模效率  技术效率  Malmquist指数  BP神经网络

The productivity and its uncertainties of entrepreneurs related to environmental protection in China
TAO Ying-ping,HU Jun,Song Ma-lin.The productivity and its uncertainties of entrepreneurs related to environmental protection in China[J].Journal of Anhui University of Science and Technology:Social Science,2012(1):24-29.
Authors:TAO Ying-ping  HU Jun  Song Ma-lin
Institution:(School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Bengbu,Anhui 233030,China)
Abstract:As one of China’s strategic emerging industries,environmental protection industry facilitates a new round of economic growth in China.Meanwhile,it is also an important measure for China’s seizure of new opportunities for scientific and technological development as well as her construction of an innovative country.Nevertheless,due to the counter-effect of industrialization and its features of tech-industries of environmental protection,the productivity of environmental protection industries is not high in general.To reflect the productivity,an indicator system will be developed that takes financial data of the environmental protection industries into account such as fixed assets,management expenses,finance charges,cash payments on staff,the total amount of taxes and profits.In this paper,the method of DEA is used in the analysis of the entrepreneurs’ productivity between 2004 and 2010,and a neural network simulation adopted for forecasting its prospect from 2011 to 2015.
Keywords:data envelopment analysis  scale efficiency  technology efficiency  Malmquist index  BP neural network
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