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
This paper applies a stochastic translog production function to examine the underlying causes of technical inefficiency for 28 provinces in the Chinese mainland over the period 1970-2011.We find that inefficiency was ...This paper applies a stochastic translog production function to examine the underlying causes of technical inefficiency for 28 provinces in the Chinese mainland over the period 1970-2011.We find that inefficiency was present in production and several relevant explanatory variables contributed to it.Specifically,we find that the provinces with higher level of human capital,higher engagement in international trade,a further relaxation of the household registration(hukou)system and a smaller government size tended to lie closer to the national frontier.In addition,public infrastructure was not productive and we find no evidence to support the general view that state-owned enterprises(SOEs)were operating relatively inefficiently when compared to non-SOEs.展开更多
Does pollution drive up public spending on health care?This paper aims to answer such a crucial question empirically using a panel data set of 31 Chinese provinces during the period 1997–2014.In particular,this paper...Does pollution drive up public spending on health care?This paper aims to answer such a crucial question empirically using a panel data set of 31 Chinese provinces during the period 1997–2014.In particular,this paper explores the non-stationarity and cointegration properties between health care expenditure and environmental indicators in a panel cointegration framework;in doing so,it examines both the long-run and the short-run impacts of the per capita provincial GDP,waste gas emissions,dust and smog emissions,and waste water emissions on the per capita public health expenditure.We apply panel unit root tests,heterogeneous panel cointegration tests,FMOLS techniques,and a panel-based error-correction model.The conclusion is that,both in the long run and in the short run,public health care expenditure is positively affected not only by the provincial economy but also by the environmental quality.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.
基金supported by the Fundamental Research Funds for the Central Universitiesthe Research Funds of Renmin University of China(Project No.:13XNJ017)
文摘This paper applies a stochastic translog production function to examine the underlying causes of technical inefficiency for 28 provinces in the Chinese mainland over the period 1970-2011.We find that inefficiency was present in production and several relevant explanatory variables contributed to it.Specifically,we find that the provinces with higher level of human capital,higher engagement in international trade,a further relaxation of the household registration(hukou)system and a smaller government size tended to lie closer to the national frontier.In addition,public infrastructure was not productive and we find no evidence to support the general view that state-owned enterprises(SOEs)were operating relatively inefficiently when compared to non-SOEs.
基金supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China[grant number.13XNJ017]Institute of China's Economic Reform&Development at Renmin University of China as the Key Research Base of Humanities and Social Sciences of Ministry of Education:Social Security System in China[grant number 14JJD790033].
文摘Does pollution drive up public spending on health care?This paper aims to answer such a crucial question empirically using a panel data set of 31 Chinese provinces during the period 1997–2014.In particular,this paper explores the non-stationarity and cointegration properties between health care expenditure and environmental indicators in a panel cointegration framework;in doing so,it examines both the long-run and the short-run impacts of the per capita provincial GDP,waste gas emissions,dust and smog emissions,and waste water emissions on the per capita public health expenditure.We apply panel unit root tests,heterogeneous panel cointegration tests,FMOLS techniques,and a panel-based error-correction model.The conclusion is that,both in the long run and in the short run,public health care expenditure is positively affected not only by the provincial economy but also by the environmental quality.
