摘要
在资源日趋紧张、环境压力加大的国际大背景下,建设资源节约型和环境友好型社会,已成为世界各国共同追求的目标。工业企业作为"两型社会"建设的主体,责任重大。企业两型化发展既是企业可持续发展的本质要求也是承担社会责任的必然选择。本文首先采用超效率DEA对样本企业两型化发展效率进行度量,在此基础上运用动态广义矩法(GMM)对影响企业两型化发展效率的因素进行分析,并从企业异质性的不同角度分析了企业内部因素影响两型化发展效率的差异。最后,采用Heckman两步法进行稳健性检验。研究结果表明:(1)资源使用价格、政府奖励、技术进步以及两型文化对企业两型化发展效率有显著正向影响;(2)环境规制对企业两型化发展效率的作用在经济学意义上不显著;(3)企业所在区域、企业规模、行业特征等方面的不同使得各企业两型化发展效率存在差异。本文据此提出相关政策建议。
With an international background of increasingly tense resources and environmental pressures,to construct a resource-saving and environment-friendly society has become the common goal of all countries.As the main body of＂Two-oriented Society＂ construction,industrial enterprises shoulder heavy responsibility.Therefore,the construction of ＂Two-oriented Enterprise＂ becomes the essence of sustainable development of enterprises as well as an inevitable choice for social responsibility.In this case,this essay firstly evaluates the two-oriented development efficiency of the sample enterprise.On this basis,dynamic Generalized method of moments is used to analyze the factors that affect the efficiency.Then,internal factors that affect the difference of the efficiency is analyzed from different angles due to enterprise heterogeneity.Finally,Heckman Two-step Estimation is adopted to conduct robustness test.The results show that：（1）The price of resources use,government incentives,technological advances,two-oriented culture has a significant positive effect on the development efficiency;（2）Environmental regulation play a nonsignificant role on development efficiency in the economic sense;（3）Factors as business region,firm size,industry characteristics and ownership structure,make differences in efficiency of two-oriented development between enterprises.Some suggestions according to the results above are also put forward.
出处
《中国软科学》
CSSCI
北大核心
2013年第4期128-139,共12页
China Soft Science
基金
教育部哲学社会科学研究重大课题攻关项目(10JZD0020)
国家自然科学基金委创新研究群体科学基金项目(70921001)
985工程哲学社会科学创新研究基地--中南大学资源节约型及环境友好型社会研究中心资助
关键词
企业两型化
超效率DEA
影响因素
Heckman两步法
Two-goal Enterprise
super——efficiency data envelopment analysis
Influencing Factors
Heckman Two-step Estimation
