报告题目：Energy efficiency in the Chinese provinces: A fixed effects stochastic frontier spatial Durbin error panel analysis

报告人：36365线路检测中心 姜磊 博士

报告时间：2016年12月1日 下午15点10分

报告地点：36365线路检测中心6号楼210室

组织发起：36365线路检测中心前沿文献与经典著作读书会

主办单位：36365线路检测中心

协办单位：科研处

内容摘要：

Energy efficiency improvement has been a key objective of China’s long-term energy policy. In this paper, we derive single-factor technical energy efficiency (abbreviated as energy efficiency) in China from multi-factor efficiency estimated by means of a translog production function and a stochastic frontier model on the basis of panel data on 29 Chinese provinces over the period 2003-2011. We find that average energy efficiency has been increasing over the research period and that the provinces with the highest energy efficiency are at the east coast and the ones with the lowest in the west, with an intermediate corridor in between. In the analysis of the determinants of energy efficiency by means of a spatial Durbin error model both factors in the own province and in first-order neighboring provinces are considered. Per capita income in the own province has a positive effect. Furthermore, foreign direct investment and population density in the own province and in neighboring provinces have positive effects whereas the share of state-owned enterprises in Gross Provincial Product in the own province and in neighboring provinces have negative effects. From the analysis it follows that inflow of foreign direct investment, and reform of state-owned enterprises are important policy handles.

参考文献：

1. Elhorst, JP (2014) Spatial econometrics: From cross-sectional data to spatial panels. Springer, Berlin Heidelberg.

2. Filippini M, Hunt LC (2011) Energy demand and energy efficiency in the OECD countries: A stochastic demand frontier approach. Energy J 32: 59-80.

3. Filippini M, Hunt LC (2012) US residential energy demand and energy efficiency: A stochastic demand frontier approach. Energy Econ 34: 1484-1491.

4. Reinhard S, Lovell CK, Thijssen G (1999) Econometric estimation of technical and environmental efficiency: An application to Dutch dairy farms. Am J Agric Econ 81: 44-60.

5. Song F, Zheng X (2012) What drives the change in China’s energy intensity: Combining decomposition analysis and econometric analysis at the provincial level. Energy Policy 51: 445-453.

6. Song M, Wang S, Yu H, Yang L, Wu J (2011) To reduce energy consumption and to maintain rapid economic growth: Analysis of the condition in China based on expended IPAT model. Renew Sustain Energy Rev 15: 5129-5134.

7. Tang J, Folmer H, van der Vlist A, Xue J (2013) The impacts of management reform on irrigation water use efficiency in the Guanzhong plain, China. Pap Reg Sci 93: 455-475.

8. Wang HJ, Ho CW (2010) Estimating fixed effect panel stochastic frontier models by model transformation. J Econom 157: 286-296.