This paper combines energy demand modelling with stochastic frontier analysis to investigate the changing trends,variations and determinants of energy efficiency for 27 Chinese provinces over the period 1995 to 2014.A...This paper combines energy demand modelling with stochastic frontier analysis to investigate the changing trends,variations and determinants of energy efficiency for 27 Chinese provinces over the period 1995 to 2014.An aggregate‘frontier’energy demand function and an efficiency function are estimated simultaneously.We obtained several findings.First,the energy intensity is not a particularly good indicator of energy efficiency.Second,the energy efficiency levels for all the provinces improved during the sample period,but the current efficiency levels are still low,implying great potential for energy saving.In addition,the energy efficiency gap among the provinces seems to have widened over the past 20 years,as the variance has increased by almost three times.Finally,technological progress driven by new investment and the development of market mechanisms are two important drivers of energy efficiency improvement.展开更多
生产效率一般会受到空间相关性和时间滞后效应的影响,不易准确测算。本文考虑时空双重滞后特征,提出一种动态面板数据空间随机前沿模型,针对模型的内生性问题,借鉴已有的估计方法,本文提出一种广义矩估计方法(Generalized Method of Mom...生产效率一般会受到空间相关性和时间滞后效应的影响,不易准确测算。本文考虑时空双重滞后特征,提出一种动态面板数据空间随机前沿模型,针对模型的内生性问题,借鉴已有的估计方法,本文提出一种广义矩估计方法(Generalized Method of Moments,GMM),并证明了参数估计的一致性。在应用分析中,利用本文所提出的理论模型实证分析了我国战略性新兴产业发展的效率,该理论模型能够客观、科学地测算技术效率,实证结论验证了理论模型的应用效果。展开更多
基金The authors appreciate the financial support from the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China[13XNJ017].
文摘This paper combines energy demand modelling with stochastic frontier analysis to investigate the changing trends,variations and determinants of energy efficiency for 27 Chinese provinces over the period 1995 to 2014.An aggregate‘frontier’energy demand function and an efficiency function are estimated simultaneously.We obtained several findings.First,the energy intensity is not a particularly good indicator of energy efficiency.Second,the energy efficiency levels for all the provinces improved during the sample period,but the current efficiency levels are still low,implying great potential for energy saving.In addition,the energy efficiency gap among the provinces seems to have widened over the past 20 years,as the variance has increased by almost three times.Finally,technological progress driven by new investment and the development of market mechanisms are two important drivers of energy efficiency improvement.
文摘生产效率一般会受到空间相关性和时间滞后效应的影响,不易准确测算。本文考虑时空双重滞后特征,提出一种动态面板数据空间随机前沿模型,针对模型的内生性问题,借鉴已有的估计方法,本文提出一种广义矩估计方法(Generalized Method of Moments,GMM),并证明了参数估计的一致性。在应用分析中,利用本文所提出的理论模型实证分析了我国战略性新兴产业发展的效率,该理论模型能够客观、科学地测算技术效率,实证结论验证了理论模型的应用效果。