Study on Energy Efficiency of China's Manufacturing Industry Based on Stochastic Frontier Analysis

Tong-Tong Jiang ； Xiu-Guo Wu

《管理科學與統計決策》 10卷3期 (2013/09) Pp. 77-87

https://doi.org/10.6704/JMSSD.2013.10.3.77

並列摘要

Using the stochastic frontier analysis method, this paper calculates and analyses the energy efficiency and its influencing factors of China's 30 manufacturing sub-sectors from 2003 to 2010. The following conclusions are found. The overall total factor energy efficiency of China's manufacturing industry is low, only average of 0.3504. There are many energy conservation and emission reduction pressures in manufacturing industry. In the same year, the energy efficiency of different manufacturing sub-sectors is at the relatively fixed level. But the energy efficiency has been rising with the passage of time. The average size of company, total profits and industry concentration would promote the energy efficiency in a certain extent. While property system has brought negative impact on energy efficiency in some degrees.

並列關鍵字

Stochastic Frontier Analysis ； Manufacturing Industry ； Total Factor Energy Efficiency ； Energy Conservation and Emission Reduction

參考文獻

Aigner, D.,Lovell, C.A.K.,Schmidt, P.(1977).Formulation and Estimation of Stochastic Frontier Production Function Models.Journal of Econometrics.6(1),21-37.

Battese, G. E.,Coelli, T. J.(1992).Frontier Production Functions, Technical Efficiency and Panel Data: with Application to Paddy Farmers in India.The Journal of Productivity Analysis.3(1-2),153-169.

Battese, G. E.,Coelli, T. J.(1995).A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data.Empirical Economics.20(2),325-332.

Jondrow, J.(1982).On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model.Journal of Econometrics.19(2-3),233-238.

Hu, J-L.,Lee, Y-C(2008).Efficient Three Industrial Waste Abatement for Regions in China.International Journal of Sustainable Development & World Ecology.15(2),132-144.