英文文献：Estimating China’s Energy and Environmental Productivity Efficiency: A Parametric Hyperbolic Distance Function Approach-估计中国能源和环境生产力效率:参数双曲距离函数方法
英文文献作者：Zhang, Zibin,Jin, Xiangrong,Dong, Xuebing,Wetzstein, Michael E.
英文文献摘要：
Since the beginning of this century, China’s annual GDP growth is over 9%. This growth is fueled by large increases in energy consumption, led by a coal-dominated energy structure, and associated with higher sulfur dioxide emissions and industry dust. In 2008, China accounted for over 17% of the world’s total primary energy consumption and accounts for nearly three-quarters of global energy growth. At an average annual energy growth rate over 12% since 2000, China’s future share of primary energy consumption will continue to increase. A consequence of this growth is China becoming the global leader in sulfur and carbon dioxide emissions. To deal with these energy and environmental challenges, the government set energy saving and pollution reduction target objectives in the 11th Five Year Plan (2006-2010): relative to 2005 by 2010, saving national energy use per unit of GDP by 20% and reducing the country’s primary pollution emissions by 10%. These targets were then disaggregated into energy saving targets for each province. With this disaggregated scheme, similar to country’s target, 20 provinces were assigned a 20% energy saving target, seven provinces were assigned targets below 20%, varying from 12% to 17%, and four provinces were given targets above 20%. These allocation were generally not guided by technical or economic efficiency, and thus may not be optimal from the perspectives of equity and efficiency. Historically less energy efficiency provinces may have more potential to reduce their energy consumption and pollution emissions, while higher efficiency provinces may have less potential. The major objective is to determine the optimal targets for each province required to comply with the national Five Year Plan target. A comparison of the estimated optimal with the current government targets will then reveal the value of incorporating economic theory into the decision calculation of setting disaggregate targets. Determining optimal targets requires consideration of both desirable and undesirable comes from alternative feasible targets. An objective is then to delineate these comes as criterion for selection. The procedure employed is a parametric hyperbolic distance function approach with a translog specification. This procedure provides the flexibility of using energy, labor, and capital stock as inputs to produce the desirable output (GDP) and the undesirable output (sulfur dioxide emissions). The procedure will address the objectives by simultaneously estimating both the desirable and undesirable comes. Specifically, the production frontier and environmental productivity efficiency are estimated for each province. The hyperbolic distance function enables the estimation of efficiency scores by incorporating all types of inputs and outputs, and only requires information on input and outputs quantities but not on prices, making it possible to model the emissions in the production process, given nonmarket characteristics of emissions. Based on these parametric estimations, the optimal targets are determined. The trajectory of obtaining these optimal targets for each province is determined by estimating how each province can improve its productive performance through increasing its desirable output and reducing its undesirable output, while simultaneously saving energy inputs. The results provide an empirical measurement of energy efficiency with maximum potential of energy saving for each province at a given technology considering the diverse economic, industry, and energy consumption patterns in the provinces. With a panel data of 29 provinces in China from 2000-2007, the hyperbolic distance function allows us to measure environmental productivity change over time, and then decompose this environmental productivity change into efficiency change, which is the movement toward the frontier, and technical change, which is the shift of the frontier. These further analyses help us identify potential different contributions of productivity growth for each province in China, and examine how the energy saving program will affect the environmental productivity growth for each province.

估计中国能源和环境生产力效率:参数双曲距离函数方法。本世纪以来，中国国内生产总值年均增长超过9%。煤炭占主导地位的能源结构导致能源消费大幅增长，二氧化硫和工业粉尘的排放也随之增加。2008年，中国占世界一次能源消费总量的17%以上，占全球能源增长的近四分之三。自2000年以来，中国能源年均增长率超过12%，未来中国在一次能源消费中所占的份额将继续增加。这种增长的结果是中国成为全球硫和二氧化碳排放的领导者。为了应对这些能源和环境挑战，政府在“十一五”(2006-2010)规划中提出了节能减排目标:到2010年，单位国内生产总值能耗比2005年降低20%，一级污染排放降低10%。然后将这些目标分解为各省的节能目标。在这个分类方案中，类似于国家的目标，20个省份制定了20%的节能目标，7个省份制定了低于20%的目标(在12% - 17%之间)，4个省份制定了20%以上的目标。这些分配一般不以技术或经济效率为指导，因此从公平和效率的角度来看可能不是最佳的。从历史上看，能源效率低的省份在减少能源消耗和污染排放方面可能更有潜力，而效率高的省份可能潜力更小。主要目标是为每个省份确定符合国家五年计划目标的最佳目标。将估计的最优目标与当前的政府目标进行比较，将揭示将经济理论纳入非总目标的决策计算的价值。确定最优目标需要同时考虑理想目标和不理想目标，即可选择的可行目标。目标是描述这些来作为选择的标准。所采用的程序是一种参数双曲距离函数方法与跨对数规范。这一程序提供了使用能源、劳动力和资本存量作为输入来产生理想的产出(GDP)和不希望的产出(二氧化硫排放)的灵活性。该程序将通过同时估计期望的和不期望的来达到目标。具体地，估计了每个省的生产前沿和环境生产力效率。双曲线距离函数可以通过纳入所有类型的投入和产出来估计效率分数，并且只需要投入和产出数量的信息，而不需要价格信息，这使得在生产过程中根据排放的非市场特征建立排放模型成为可能。基于这些参数估计，确定了最优目标。通过估计每个省份如何通过增加其期望产出和减少其不期望产出来提高其生产绩效，同时节约能源投入，来确定每个省份获得这些最优目标的轨迹。考虑到各省不同的经济、工业和能源消费模式，结果提供了在给定技术条件下各省最大节能潜力下的能源效率的经验度量。利用2000-2007年中国29个省份的面板数据，双曲线距离函数可以测量环境生产率随时间的变化，然后将这种环境生产率变化分解为效率变化(即向前沿的移动)和techni