基于非参数前沿方法的中国省际全要素能源效率研究
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摘要
在全球面临化石能源枯竭和气候变暖严重威胁的现实背景下,作为仅次于美国的世界第二大能源消费国和二氧化碳排放最多的发展中国家,中国必须肩负节能减排的艰巨历史责任和使命。为了适应自身发展和国际社会要求,最大程度的缓解能源与环境危机,实行提高能源效率的能源战略势在必行。为此,科学、系统研究中国省际能源效率及其相关问题,并在此基础上制定行之有效的能源与环境政策,对于深入贯彻落实科学发展观、全面建设社会主义和谐社会和实现中国经济、社会全面、协调可持续发展都具有重大现实意义。
本文基于非参数前沿分析方法,在全要素能源效率框架下比较了中国各省份、三大地区能源利用效率及能源技术水平的高低,在此基础上探讨了中国省际全要素能源效率的时空演变规律及其影响因素,并引入能源利用的环境效应,在经济、资源与环境多目标约束下更系统、科学的研究中国能源效率问题,以期为中国各省份制定节能减排政策提供有效决策支持。论文的主要研究成果和创新如下:
1.基于DEA方法和方向性距离函数(DDF),提出了基于节能增产联合目标的全要素能源效率模型并就中国省际数据进行了实证研究。该模型将节能目标和经济增长目标有效结合在一起,共同融入到全要素能源效率指标之中,在理论上丰富了全要素能源效率的内涵,也更符合我国宏观经济发展实际。
2.提出了“能源强度效率”的概念,以反映中国各省份“现实能源强度”与相对“最优能源强度”的差距,为“单要素能源效率”和“全要素能源效率”两种方法提供了联系的纽带,并为中国各省份制定切实可行的节能降耗目标提供了理论依据。
3.充分考虑到中国三大地区(东部、中部和西部)之间存在的能源技术发展差距,基于非参数共同前沿(metafrontier)理论,分析了中国全要素能源效率及能源技术的区域差异,为制定地区针对性的节能减排政策提供了理论与实践依据。
4.在基于节能增产联合目标的全要素能源效率测度方法的基础上,引入非参数Luenberger指数考察了中国全要素能源效率的时空动态演变规律,将全要素能源效率变动分解为技术效率变动和技术进步,寻找出推动生产前沿面向外移动的能源技术“创新者”省份并采用面板数据模型检验了影响中国省际全要素能源效率变动的主要影响因素。
5.从系统论的角度出发,考虑到能源利用的负外部性,将环境污染引入全要素能源效率框架,利用DEA方法测度了考虑环境效应下中国各省份、三大地区的全要素能源效率并将其分解为纯技术效率和规模效率;提出了中国省际能源利用效率的四类模式并利用Tobit模型分析了中国全要素能源效率地区差异的形成原因。
6.利用环境DEA技术和方向性距离函数(DDF)构建中国省际能源利用的环境效率测度模型并进行了实证研究,将“环境规制”思想引入到研究体系之中,测算了中国各省份环境规制导致的效率损失以及规制成本。
With the background of the overall world facing energy depletion and climate change, China, the world’s second-largest energy-consumed country after the Unite States and the Number one carbon dioxide-emitting developing country in the world, should undertake arduous mission and responsibility for energy conservation and emission reduction. In order to relieve the energy and environmental crises to the greatest degree and adapt to the requests from own development and international community, it is necessary to carry out the energy strategy of improving energy efficiency for China’s government. As a result, to study China’s provincial energy efficiency and related problems scientifically, on the basis of which draw up some effective energy and environmental policies, is to have great realistic meaning for thoroughly applying the Scientific Outlook on Development, building socialist harmonious society and the realization of overall, harmonious and sustainable development of economics and the society of China.
Based on non-parametric frontier method, this dissertation compares energy utilization efficiency and energy technology level under the framework of total-factor energy efficiency, on basis of which this dissertation probes the temproal and spatial evolution and impact factors of China’s provincial total-factor energy efficiency. Then, we study China’s energy efficiency problem under the restrains of economy, resource and evironment more systematically by introducing the environmental impacts of energy utlization in order to provide decision supports for China’s each province drawing up energy conservation and emission reduction polices. The main work and innovations of this dissertation include:
1. Total-factor energy efficiency model based on the joint goals of energy conservation and output growth is put forward by using DEA method and Directional Distance Fucntion (DDF). This model combines energy conservation goal and output growth goal effectively, and integrates into total-factor energy efficiency index, which makes the connotation of total-factor energy efficiency more plentiful and better conforms to our country’s macroeconomic developments acutal.
2. To reflect China’s each province’s gap between“actual energy intensity”and relative“optmal energy intensity”, the conception of“enegy intensity efficiency”is put forward, which establish a bond beween“partial-factor energy efficiency”and“total-factor energy efficiency”and provides the theory basis for China’s each province to draw up practical targets for enegy conservation.
3. Giving plenty of consideration to the technology development gap among China’s three major areas (Eastern area, Central area and Western area), this dissertation analyzes the regional differences of China’s total-factor energy efficiency based on non-parametric metafrontier theory, and provides theory and practice basis for each province to draw up appropriate energy conservation and emission reduction policies.
4. On the basis of total-factor energy efficiency model based on the joint goals of energy conservation and emission reduction, this dissertation uses non-parametric Luenberger indicator to investigate the temporal and spatial evolution of China’s total-factor energy efficiency and decomposes the indicator into technical efficiency index and technical progress index. Then, the energy technology“innovators”which shift the frontier among China’s 29 provinces are determined. Additionally, a panel data model is used to test the major impact factors of the change of China’s provincial total-factor energy efficiency.
5. From the standpoint of system theory, considering the negative externalities from energy utilization, this dissertation puts environmental pollution into the study framework of toal-factor energy efficiency. DEA method is used for measure China’s total-factor energy efficiency of 29 provinces and three major areas including environmental effects. In order to study China’s each province’s technical efficiency and scale efficiency, we decompose total-factor energy efficiency into two indexes of pure techncial efficiency and scale efficiency. Consequently, four kinds of models of China’s provincial energy efficiency were put forward and Tobit model was used to investigate the formulation reasons for the regional difference of China’s total-factor energy efficiency.
6. Environmental DEA technology and Directional Distance Function are used to build up the model of China’s provincial environmental efficiency of energy utilization. In the course of empricial study,“environmental regulation”is introduced to the dissertation’s study system, on the basis of which China’s all provinces’losses of efficiency and regulation costs from environmental regulation are measured.
本文基于非参数前沿分析方法,在全要素能源效率框架下比较了中国各省份、三大地区能源利用效率及能源技术水平的高低,在此基础上探讨了中国省际全要素能源效率的时空演变规律及其影响因素,并引入能源利用的环境效应,在经济、资源与环境多目标约束下更系统、科学的研究中国能源效率问题,以期为中国各省份制定节能减排政策提供有效决策支持。论文的主要研究成果和创新如下:
1.基于DEA方法和方向性距离函数(DDF),提出了基于节能增产联合目标的全要素能源效率模型并就中国省际数据进行了实证研究。该模型将节能目标和经济增长目标有效结合在一起,共同融入到全要素能源效率指标之中,在理论上丰富了全要素能源效率的内涵,也更符合我国宏观经济发展实际。
2.提出了“能源强度效率”的概念,以反映中国各省份“现实能源强度”与相对“最优能源强度”的差距,为“单要素能源效率”和“全要素能源效率”两种方法提供了联系的纽带,并为中国各省份制定切实可行的节能降耗目标提供了理论依据。
3.充分考虑到中国三大地区(东部、中部和西部)之间存在的能源技术发展差距,基于非参数共同前沿(metafrontier)理论,分析了中国全要素能源效率及能源技术的区域差异,为制定地区针对性的节能减排政策提供了理论与实践依据。
4.在基于节能增产联合目标的全要素能源效率测度方法的基础上,引入非参数Luenberger指数考察了中国全要素能源效率的时空动态演变规律,将全要素能源效率变动分解为技术效率变动和技术进步,寻找出推动生产前沿面向外移动的能源技术“创新者”省份并采用面板数据模型检验了影响中国省际全要素能源效率变动的主要影响因素。
5.从系统论的角度出发,考虑到能源利用的负外部性,将环境污染引入全要素能源效率框架,利用DEA方法测度了考虑环境效应下中国各省份、三大地区的全要素能源效率并将其分解为纯技术效率和规模效率;提出了中国省际能源利用效率的四类模式并利用Tobit模型分析了中国全要素能源效率地区差异的形成原因。
6.利用环境DEA技术和方向性距离函数(DDF)构建中国省际能源利用的环境效率测度模型并进行了实证研究,将“环境规制”思想引入到研究体系之中,测算了中国各省份环境规制导致的效率损失以及规制成本。
With the background of the overall world facing energy depletion and climate change, China, the world’s second-largest energy-consumed country after the Unite States and the Number one carbon dioxide-emitting developing country in the world, should undertake arduous mission and responsibility for energy conservation and emission reduction. In order to relieve the energy and environmental crises to the greatest degree and adapt to the requests from own development and international community, it is necessary to carry out the energy strategy of improving energy efficiency for China’s government. As a result, to study China’s provincial energy efficiency and related problems scientifically, on the basis of which draw up some effective energy and environmental policies, is to have great realistic meaning for thoroughly applying the Scientific Outlook on Development, building socialist harmonious society and the realization of overall, harmonious and sustainable development of economics and the society of China.
Based on non-parametric frontier method, this dissertation compares energy utilization efficiency and energy technology level under the framework of total-factor energy efficiency, on basis of which this dissertation probes the temproal and spatial evolution and impact factors of China’s provincial total-factor energy efficiency. Then, we study China’s energy efficiency problem under the restrains of economy, resource and evironment more systematically by introducing the environmental impacts of energy utlization in order to provide decision supports for China’s each province drawing up energy conservation and emission reduction polices. The main work and innovations of this dissertation include:
1. Total-factor energy efficiency model based on the joint goals of energy conservation and output growth is put forward by using DEA method and Directional Distance Fucntion (DDF). This model combines energy conservation goal and output growth goal effectively, and integrates into total-factor energy efficiency index, which makes the connotation of total-factor energy efficiency more plentiful and better conforms to our country’s macroeconomic developments acutal.
2. To reflect China’s each province’s gap between“actual energy intensity”and relative“optmal energy intensity”, the conception of“enegy intensity efficiency”is put forward, which establish a bond beween“partial-factor energy efficiency”and“total-factor energy efficiency”and provides the theory basis for China’s each province to draw up practical targets for enegy conservation.
3. Giving plenty of consideration to the technology development gap among China’s three major areas (Eastern area, Central area and Western area), this dissertation analyzes the regional differences of China’s total-factor energy efficiency based on non-parametric metafrontier theory, and provides theory and practice basis for each province to draw up appropriate energy conservation and emission reduction policies.
4. On the basis of total-factor energy efficiency model based on the joint goals of energy conservation and emission reduction, this dissertation uses non-parametric Luenberger indicator to investigate the temporal and spatial evolution of China’s total-factor energy efficiency and decomposes the indicator into technical efficiency index and technical progress index. Then, the energy technology“innovators”which shift the frontier among China’s 29 provinces are determined. Additionally, a panel data model is used to test the major impact factors of the change of China’s provincial total-factor energy efficiency.
5. From the standpoint of system theory, considering the negative externalities from energy utilization, this dissertation puts environmental pollution into the study framework of toal-factor energy efficiency. DEA method is used for measure China’s total-factor energy efficiency of 29 provinces and three major areas including environmental effects. In order to study China’s each province’s technical efficiency and scale efficiency, we decompose total-factor energy efficiency into two indexes of pure techncial efficiency and scale efficiency. Consequently, four kinds of models of China’s provincial energy efficiency were put forward and Tobit model was used to investigate the formulation reasons for the regional difference of China’s total-factor energy efficiency.
6. Environmental DEA technology and Directional Distance Function are used to build up the model of China’s provincial environmental efficiency of energy utilization. In the course of empricial study,“environmental regulation”is introduced to the dissertation’s study system, on the basis of which China’s all provinces’losses of efficiency and regulation costs from environmental regulation are measured.
引文
[1] Magda S, Diego P. Measuring productivity quality changes using envelopment analysis: An application to Catalan hospitals[J]. Finanical Accountability and Mangement, 2001, 17(3): 219-245.
[2] Farrell M J. The measurement of productive efficiency[J]. Journal of Royal Statisitc Society, 1957, Series A, 120 (Ⅲ): 253-281.
[3] Koopmans T C. Analysis of production as an efficient combination of activities[J]. Activity Analysis of Production and Allocation, 1951: 33-97.
[4] Debreu G. The coefficient of resource utilization[J]. Econometrica, 1951, (19): 273-292.
[5] F?re R, Grosskopf S. Measuring output efficiency[J]. European Journal of Operational Research, 1983, (13): 173-179.
[6] F?re R, Grosskopf S, Lovell C A K. The measurement of efficiency of production[M]. Boston: Kluwer Nijhoff Publishing Co, 1985.
[7] F?re R, Grosskopf S, Norris M, Zhong-yang Z. Productivity growth, technical progress, and efficiency change in industrialized countries[J]. American economic review, 1994, 84(1): 66-83.
[8] F?re R, Primont D. Multi-output production and duality: Theory and applications[M]. Kluwer Academic Publishers, Boston, 1995.
[9] Malmquist S. Index numbers and indifference surfaces[J]. Trabajos de Estatistica, 1953, (4): 209-242.
[10] Shephard R W. Cost and Production Functions[M]. Princeton University Press, Princeton, New Jersey, 1953.
[11] Aigner D J, Lovell C A K, Schmidt P. Formulation and estimation of stochastic frontier production models[J]. Journal of Econometrics, 1977, (6): 21-37.
[12] Meeusen W, Van Den Broeck. Efficiency estimation from Cobb-Douglas production function with composed error[J]. International Economic Review, 1977, (18): 435-444.
[13] Battese G E, Coelli T J. Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India[J]. Journal of Productivity Analysis, 1992, (3): 153-169.
[14] Battese G E, Coelli T J. A model for techncial inefficiency effects in a stochastic frontier production function for panel data[J]. Empirical Economics, 1995, 20(2): 325-332.
[15] Battese G E, Corra G S. Estimation of a production frontier model: with application to the pastoral zone of eastern Australia[J]. Australian Journal of Agricultural Economics, 1977, 21(3): 169-179.
[16] Mark M P, Lung F L. The measurement and sources of technical inefficiency in the Indonesian weaving industry[J]. Journals of Development Economics, 1981, 9(1): 43-64.
[17] Kalirajan. An econometric analysis of yield variability in paddy production[J]. Canadian Journal of Agricultural Economics, 1981, (29): 283-294.
[18] Wang E C. R&D efficiency and economic performance: A cross-country analysis using the stochastic frontier approach[J]. Journal of Policy Modeling, 2007, 29(2): 345-360.
[19] Paul F, Vencappa D, Diacon S, Klumpes P, O’Brien C. Market structure and the efficiency of European insurance companies: A stochastic frontier analysis[J]. Journal of Banking and Finance, 2008, 32(1): 86-100.
[20]闫冰,冯根福.基于随机前沿函数的中国工业R&D效率分析[J].当代经济科学,2005, 27(6): 14-19.
[21]黄薇.基于SFA方法对中国保险机构效率的实证研究[J].南开经济研究,2006, (5): 104-115.
[22]干春晖,郑若谷.中国工业生产绩效:1998-1007—基于细分行业的推广随机前沿函数的分析[J].财经研究,2009, 35(6): 97-108.
[23]史丹,吴利学,傅晓霞等.中国能源效率地区差异及其成因研究—基于随机前沿生产函数的方差分解[J].管理世界,2008, (2): 35-43.
[24] Coelli T, Perelman S. A comparison of parametric and non-parametric distance function: with application to European railways[J]. European Journal of Operational Reasearch, 1999, (117): 326-339.
[25] Fecher F, Kessler D, Perelman S, Pestieau P. Productive performance of the French insurance industry[J]. Journal of Productivity Analysis, 1993, (14): 77-93.
[26] Sharma K R, Leung P, Zaleski H M. Productive efficiency of the Swine industry in Hawaii: Stochastic frontier vs. Data envelopment analysis[J]. Journal of Productivity Analysis, 1997, (18): 447-459.
[27] Granderson G, Linvill C. Parametric and non-parametric approches to benchmarking the regulated firm[J]. Journal of Productivity Analysis, 1999, (12): 211-231.
[28] Luis R M, Juan A V. The use of parametric and non-parametric frontier methods to measure the production efficiency in the industry sector: A comparative study[J]. International Journal of Production Economics, 2001, (69): 265-275.
[29] Bauer P W, Berger A N, Ferrier G D, Humphrey D B. Consistency condition for regulatory analysis of financial institution: A comparison of frontier efficiency methods[J]. Journal of Economics and Business, 1998, (50): 85-114.
[30] Giuffrida A, Hugh G. Measuring performance in primary care: Econometric analysis and DEA[J]. Applied Economics, 2001, (33): 163-175.
[31] Lawrence W L, Erwin T L. Measuring techncialand scale efficiency in rail industry: A comparison of 85 railways using DEA and SFA[J]. Asia Conference on Efficiency and Productivity, 2002: 30-45.
[32] Boles J N. Efficiency squared-efficiency computation of efficiency indexes[J]. Proceedings of the 39thAnnual Meeting of the Western Farm Economics Association, 1966: 137-142.
[33] Afriat S N. Efficiency estimation of production functions[J]. International Economic Review, 1972, 13(3): 568-598.
[34] Charnes A, Cooper W W, Rhode E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, (2): 429-444.
[35] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science, 1984, (30): 1078-1092.
[36] Charnes A, Cooper W W, Wei Q L and Huang Z M. Cone ratio data envelopment analysis and multi-objective program ming[J]. Interantional Journal of System Science, 1989, (20): 1099-1118.
[37] Yu G, Wei Q L, Brockett P. A generalized data envelopment analysis model: A unification and extension methods for efficiency analysis of decision making units[J]. Annals of Operational Research, 1996, (66): 47-89.
[38] F?re R, Grosskopf S. A nonparmetric cost approach to scale efficiency[J]. The Scandinavian Journal of Economics, 1985, (87): 594-604.
[39] F?re R, Grosskopf S, Logan J. The relative performance of publicly-owned and privately-owned electric utilities[J]. Journal of Public Economics, 1985, (26):89-106.
[40] Seiford L M, Thrall R M. Recent developments in DEA: The mathematical approach to frontier analysis[J]. Journal of Econometrics, 1990, (46): 7-38.
[41] Lovell C A K, Pastor J T. Units invariant and translation invariant DEA models[J]. Operational Research Letters, 1995, (18): 147-151.
[42] Ali A I, Seiford L M. The mathematical programming approach to efficiency analysis, The measurement of Productive Efficiency: Techniques and Applications[M], Oxford university press, New York, 1993.
[43] Lovell C A K. Production frontiers and productive efficiency, in Fried H O, Lovell C A K and Schmidt S S (Eds.), The Measurement of Productive Efficiency: Techniques and Applications[M]. Oxford University Press, New York, 1993.
[44] Charnes A, Cooper W W, Lewin A Y and Seiford L M. Data Envelopment Analysis: Theory, methodology and applications[M]. Kluwer Academic Publishers, Boston, 1995.
[45] Seiford L M. Data Envelopment Analysis: The evolution of the state of the art (1978-1995)[J]. Journal of Productivity Analysis, 1996, (7): 99-138.
[46] Cooper W W, Seiford L M, Tone K. Data Envelopment Analysis: A comprehensive text with models, applications, reference and DEA-solver software[M]. Kluwer Academic Publishers, Boston, 2000.
[47] Thanassoulis E. Introduction to the theory and application of data envelopment analysis: A foundation text with integrated software[M]. Kluwer Academic Publishers, Boston, 2001.
[48] Gleason J M, Barnum D T. Toward valid measures of public sector productivity: performance measures in urban transit[J]. Management Science, 1982, 28(4): 279-386.
[49] Diewert W E. Exact and superlative index numbers[J]. Journal of Econometrics, 1976, (4): 115-146.
[50] Caves D W, Christensen L R, Diewert W E. Multilateral comparisons of output, input, and productivity using superlative index numbers[J]. Economic Journal, 1982, (92): 73-86.
[51] Coelli T J, Prasada R D S, Battese G E. An introduction to efficiency and productivity analysis[M]. Kluwer Academic Publishers, Boston, 1998.
[52] F?re R, Grosskopf S, Lovell C A K. Production frontiers[M]. CambridgeUniversity Press, Cambridge, 1994.
[53] F?re R, Grosskopf S, Ross P. Malmquist productivity indexes: A survey of theory and practice[M]. Kluwer Academic Publishers, Boston, 1998.
[54] Meadow D L. Limits to growth-report to the Club of Rome[M]. University Books, New York, 1972.
[55] Dasgupta P, Heal G M. The optimal depletion of exhaustible resources[J]. Reviews of Economic Studies, Symposium, 1974, 3-28.
[56] Stiglitz J E. Growth with exhaustible natural resources: The competitive economy[J]. Review of Economies Studies, 1974, (41): 139-152.
[57] Garg P C, Sweenney J L. Optimal growth with depletable resources[J]. Resources and Energy, 1978, (1): 43-56.
[58] Rasche R H, Tatom J A. Energy resources and potential GNP[J]. Federal Reserve Bank of St. Louis Review, 1977: 10-24.
[59] Renshaw E F. Energy efficiency and the slump in labour productivity in the USA[J]. Energy Economics, 1981, 3(1): 36-42.
[60] Suzuki K, Takenaka H. The role of investment for energy conservation: Future Japanese economic growth[J]. Energy Economics, 1981, (3): 233-243.
[61] Uri N D, Hassanein S A. Energy prices, labor productivity and causality: An empirical examination[J]. Energy Economics, 1982, (4): 98-104.
[62] Nordhaus W D. To slow or not to slow: The economics of the greenhouse effect[J]. The Economic Journal, 1991, 101(407): 920-937.
[63] Bovenberg A L, Smulders S A. Transitional of impacts of environmental policy in an endogenous growth model[J]. International Economic Review, 1996, (37): 861-893.
[64] Grimaud A, Rouge L. Non-renewable resources and growth with vertical innovations: Optimum, equilibrium and economic policies[J]. Journal of Environmental Economics and Management, 2003, (45): 433-453.
[65] Grimaud A, Rouge L. Polluting not-renewable resourece, innovation and growth: Welfare and environmental policy[J]. Resources and Energy Economics, 2005, (27): 109-129.
[66] Granger C W J, Newbald P. Forecasting economic time series[M]. Academic Press, New York, 1977.
[67] Philips P C B. Understanding spurious regression in econometrics[J]. Journal of Econometric, 1986, (33): 311-340.
[68] Engle R F, Granger C W J. Cointegration and error correction: representation, estimation and testing[J]. Econometrica, 1987, (55): 251-276.
[69] Engle R F, Yoo B S. Forecasting and testing in cointegrated systems[J]. Journal of Econometrics, 1987, (35): 143-159.
[70] Kraft J, Kraft A. On the relationship between energy and GNP[J]. Journal of Energy and Development, 1978, (3): 401-403.
[71] Yu E S H, Hwang B K. The relationship between energy and GDP: further results[J]. Energy Economics, 1984, (6): 186-190.
[72] Yu E S H, Choi J Y. The causal relationship between energy and GNP: an international comparison[J]. Journal of Energy and Development, 1985, (10): 249-272.
[73] Cheng B S. Energy consumption and economic growth in Brazil, Mexico and Venezuela: a time series analysis[J]. Applied Economics Letters, 1997, (4): 671-674.
[74] Yu S H, Jin J C. Cointegration test of energy consumption, income and employment[J]. Resources and Energy, 1992, (14): 259-266.
[75] Masih A M M, Masih R. Energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modeling techniques[J]. Energy Economics, 1996, (18): 165-183.
[76] Glasure Y U. Energy and national income in Korea: further evidence on the role of omitted variables[J]. Energy Economics, 2002, (24): 355-365.
[77] Soytas U, Sari R. Energy consumption and GDP: causality relationship in G-7 countries and emerging markets[J]. Energy Economics, 2003, (25): 33-37.
[78] Oh W, Lee K. Causal relationship between energy consumption and GDP revisited: the case of Korea 1970-1999[J]. Energy Economics, 2005, (26): 51-59.
[79] Lee C C. Energy consumption and GDP in developing countries: a cointegrated panel analysis[J]. Energy Economics, 2005, (27): 415-427.
[80] Wolde-Rufael Y. Electricity consumption and economic growth: a time series experience for 17 African countries[J]. Energy Policy, 2006, (34): 1106-1114.
[81]赵丽霞,魏巍贤.能源与经济增长模型研究[J].预测,1998, (6): 33-35.
[82] Shiu A, Lam P L. Electricity consumption and economic growth in China[J]. Energy Policy, 2004, (32): 47-54.
[83] Wolde-Rufael Y. Disaggregated industrial energy consumption and GDP: the case of Shanghai, 1952-1999[J]. Energy Economics, 2004, (26): 69-75.
[84] Hwang D B K, Gum B. The causal relationship between energy and GDP: the case of Taiwan[J]. Journal of Energy and Development, 1992, (16): 219-226.
[85] Cheng B S, Lai T W. An investigation of cointegration and causality between energy consumption and economic activity in Taiwan[J]. Enery Economics, 1997, (19): 435-444.
[86]林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003, (11): 18-27.
[87]林伯强.结构变化、效率改进与能源需求预测——以中国电力行业为例[J].经济研究,2003, (5): 57-66.
[88]韩智勇,魏一鸣,范英.中国能源强度与经济结构变化特征研究[J].数理统计与管理,2004, (11): 1-7.
[89]马超群,储慧斌,李科等.中国能源消费与经济增长的协整与误差校正模型研究[J].系统工程,2004, 22(10): 47-50.
[90]贲兴振,杨宝臣.中国能源消费与经济增长的协整关系分析[J].哈尔滨理工大学学报,2005, 10(8): 117-120.
[91]刘凤朝,刘源远,潘雄锋.中国经济增长与能源消费的动态特征[J].资源科学,2007, 29(5): 63-68.
[92]赵进文,范继涛.经济增长与能源消费内在依从关系的实证研究[J].经济研究,2007, (8): 31-42.
[93]牟敦国.中国能源消费与经济的因果关系研究[J].厦门大学学报(哲学社会科学版),2008, (2): 100-107.
[94]刘长生,郭小东,简玉峰.能源消费对中国经济增长的影响研究——基于线性与非线性回归方法的比较分析[J].产业经济研究,2009, (1): 1-9.
[95] Meadous D H, Meadows D L, Randers J. Beyond the limits[M]. Post Mills, VT: Chelsea Green Publishing Co., 1992.
[96] Daly H E. Beyond growth: the economics of sustainable development[M]. Beacon Press, 1996.
[97] Hirst E. Improving energy efficiency in the USA: The federal role[J]. Energy Policy, 1991, (19): 567-577.
[98] Porter M E. vander Linde C. Green and Competitive: Ending the statemate[J]. Harvard Business Review, 1995, 73(5): 120-134.
[99] Patterson M G. What is energy efficiency? Concepts, indicators and methodological issues[J]. Energy Policy, 1996, 24(5): 377-390.
[100]中国能源发展战略与政策研究课题组.中国能源发展战略与政策研究[M].北京:经济科学出版社,2004.
[101]魏楚,沈满洪.能源效率及其影响因素:基于DEA的实证分析[J].管理世界,2007, (8): 66-76.
[102]何祚庥,王亦楠.我国与美国、日本能源利用效率的差距到底有多大?[J].中国科学院院士建议,2004, (4).
[103]戴彦德,朱跃中.应慎重看待能源效率水平评价的国际比较[J].石油与化工节能,2005, (4).
[104]韩晓平.从全球资源配置角度分析我国的能源利用效率[J].红旗文稿,2007, (15).
[105] Hu J L, Wang S C. Total-factor energy efficiency of regions in China[J]. Energy Policy, 2006, (34): 3206-3217.
[106] Zhou P, Ang B W, Poh K L. A survey of data envelopment analysis in energy and environmental studies[J]. European Journals of Operational Research, 2008, (189): 1-18.
[107] Hu J L, Kao C H. Efficient energy-saving targets for APEC economies[J]. Energy Policy, 2007, (35): 373-382.
[108] Zhang J L, Wang G S. Energy saving technologies and productive efficiency in the Chinese iron and steel sector[J]. Energy Policy, 2008, (33): 525-537.
[109] Mukherjee K. Energy use efficiency in U.S. manufacturing: A nonparametirc analysis[J]. Energy Economics, 2008, (30): 76-96.
[110] Mukherjee K. Energy use efficiency in the Indian manufacturing sector: An interstate analysis[J]. Energy Policy, 2008, (36): 662-672.
[111] Honma S., Hu J.L.Total-factor energy productivity growth of regions in Japan[J]. Energy Policy, 2009, (37): 3941-3950.
[112] Yeh T L, Chen T Y, Lai P Y. A comparative study of energy utilzation efficiency between Taiwan and China[J]. Energy Policy, 2010, 38(5):2386-2394.
[113] Onut S, Soner S. Analysis of enery use and efficiency in Turkish manufacturing sector SEMs[J]. Energy Conversion and Management, 2007, 48(2): 384-394.
[114] Zhou P, Ang B W. Linear Programming models for measuring economy-wide energy efficiency performance[J]. Energy Policy, 2008, 36(8): 2911-2916.
[115] Nassiri S M, Singh S. Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique[J]. Applied Energy, 2009, 86(7-8): 1320-1325.
[116] Mukherjee K. Measuring energy efficiency in the context of an emergingeconomy: the case of Indian manufacturing[J]. European Journal of Operational Research, 2010, (201): 933-941.
[117] Vaclav S. China’s Energy[R]. in Report Prepared for the U.S. Congress, Washington D. C: Office of Technology Assessment, 1990.
[118] Kambara T. The energy sistuation in China[J]. China Quarterly, 1992, (131): 508-636.
[119] Garbaccio R F, Ho M S, Jorgenson D W. Why has the energy-output ratio fallen in China?[J]. Energy Journal, 1999, 20(3): 63-92.
[120] Lin X, Polenske K R. Input-output anatomy of China’s energy use change in the 1980s[J]. Economic System Research, 1995, 7(1): 67-84.
[121]史丹.我国经济增长过程中能源利用效率的改进[J].经济研究,2002, (9): 49-57.
[122]王庆一.中国的能源效率及国际比较[J].节能与环保,2003, (8): 5-7.
[123]蒋金荷.提高能源效率与经济结构调整的策略分析[J]. 2003, (10): 16-23.
[124]丁建勋.最优能源强度与我国经济增长[J].财经科学,2007, (4): 29-35.
[125]何建坤,张希良.我国十一五期间能源强度下降趋势分析——如何实现能源强度下降20%的目标[J].中国软科学,2006, (4): 33-38.
[126]齐志新,陈文颖,吴宗鑫.中国的能源强度究竟有多高[J].数量经济技术经济研究,2007, (8): 51-58.
[127]贺灿飞,王俊松.经济转型与中国省区能源强度研究[J].地理科学,2009, 29(4): 461-469.
[128] Huang J P. Industry energy use and structural change: A case study of the People’s Republic of China[J]. Energy Economics, 1993, 15(2): 131-136.
[129] Zhang Z X. Why did energy intensity fall in China’s industrial sector in the 1990s? the relative importance of structural change and intensity change[J]. Energy Economics, 2003, 25(6): 625-638.
[130]王玉潜.能源消耗强度变动的因素分解方法及其应用[J].数量经济技术经济研究,2003, (8): 151-154.
[131] Fisher-Vanden K, Jefferson G H, Liu H M, et al. What is driving China’s decline in energy intensity?[J]. Resource and Energy Economics, 2004, 26(1): 77-97.
[132] Ma C, Stern D I. China’s energy intensity trend: a decomposition analysis[J]. Working papers, Rensselaer Polytechnic Insititute, 2006.
[133]齐志新,陈文颖.结构调整还是技术进步?——改革开放后我国能源效率提高的因素分析[J].上海经济研究,2006, (6): 8-16.
[134]吴巧生,成金华.中国工业化进程中的能源消耗强度变动及因素分析——基于分解模型的实证分析[J].财经研究,2006, 32(6): 75-85.
[135]周勇,李廉水.中国能源强度变化的结构与效率因素贡献[J].产业经济研究,2006, (4): 68-74.
[136]吴巧生,成金华.中国能源消耗强度变动及因素分解:1980-2004[J].经济理论与经济管理,2006, (10): 34-40.
[137]李国璋,王双.区域能源强度变动:基于GFI的因素分解分析[J].中国人口资源与环境,2008, 18(4): 62-66.
[138]刘叶,王磊.我国工业能源强度变动的影响因素分解分析——基于LMDI分解法[J].中国矿业大学学报(社会科学版),2009, (4): 66-70.
[139]吴巧生.中国工业化进程中的能源消耗强度变动及影响因素——基于Fisher指数分解方法的实证分析[J].经济理论与经济管理,2010, (5): 44-50.
[140]张晓平,孙磊.中国工业能源消费强度变化的分解分析[J].资源科学,2010, 32(9): 1685-1892.
[141] Ang B W, Zhang F Q. A survey of index decomposition analysis in energy and environmental studies[J]. Energy, 2000, 25(12): 1149-1176.
[142]王少平,杨继生.中国工业能源调整的长期战略与短期措施——基于12个主要工业行业能源需求的综列协整分析[J].中国社会科学,2006, (4):88-97.
[143]史丹.中国能源效率的地区差异与节能减排潜力分析[J].中国工业经济,2007, (10): 49-58.
[144]张贤,周勇.外商直接投资对我国能源强度的空间效应分析[J].数量经济技术经济研究,2007, (1): 101-108.
[145]刘畅,崔艳红.中国能源消耗强度区域差异的动态关系比较研究——基于省市面板数据模型的实证分析[J].中国工业经济,2008, (4): 34-43.
[146]徐刚,潘祺志.中国能源消费与经济增长及能源效率关系的实证分析——基于6大产业部门的综列协整和PVECM模型[J].中央财经大学学报,2009, (5): 63-68.
[147]王军,仲伟周.中国地区能源强度差异研究——要素禀赋的分析视角[J].产业经济研究,2009, (6): 44-51.
[148]吴利学.中国能源效率波动:理论解释、数值模拟及政策含义[J].经济研究,2009, (5): 130-143.
[149]张宗益,呙小明,汪锋.能源价格上升对中国第三产业能源效率的冲击——基于VAR模型的实证分析[J].管理评论,2010, (6): 61-70.
[150]谭忠富,张金良.中国能源效率与其影响因素的动态关系研究[J].中国人口资源与环境,2010, 20(4): 43-49.
[151]徐国泉,刘则渊. 1998-2005年中国八大经济区域全要素能源效率——基于省际面板数据的分析[J].中国科技论坛,2007, (7): 68-72.
[152]李世祥,成金华.中国主要工业省区能源效率分析:1990-2006[J].数量经济技术经济研究,2008, (10): 32-43.
[153]师博,沈坤荣.市场分割下的中国全要素能源效率:基于超效率DEA方法的经验分析[J].世界经济,2008, (9): 49-59.
[154]魏楚,沈满洪.结构调整能否改善能源效率:基于中国省级数据的研究[J].世界经济,2008, (11): 77-85.
[155]邵军,管驰明.中国工业部门能源使用效率及其影响因素研究[J].经济学家,2009, (1): 58-65.
[156]李世祥,成金华.中国工业行业的能源效率特征及其影响因素——基于非参数前沿的实证分析[J].财经研究,2009, 35(7): 134-143.
[157]庞瑞芝,王卢羡,张泉.转型期间中国工业部门全要素能源效率的要素效应、结构效应与技术效应分析[J].当代经济科学,2009, 31(5): 21-29.
[158]武春友,吴琦.基于超效率DEA的能源效率评价模型研究[J].管理学报,2009, 6(11): 1460-1465.
[159]杨红亮,史丹,肖洁.自然环境能够因素对能源效率的影响——中国各地区的理论节能潜力与实际节能潜力分析[J].中国工业经济,2009, (4): 73-84.
[160]李廉水,周勇.技术进步能提高能源效率吗?——基于中国工业部门的实证检验[J].管理世界,2006, (10): 82-89.
[161] Wei Y.M., Liao H., Fan Y.An empricial analysis of energy efficiency in China’s iron and steel sector[J]. Energy, 2007, (32): 2262-2270.
[162]王群伟,周德群.中国全要素能源效率变动的实证研究[J].系统工程,2008, 26(7): 74-80.
[163]屈小娥.中国省际全要素能源效率变动分解——基于Malmquist指数的实证研究[J].数量经济技术经济研究,2009, (8): 29-43.
[164]袁晓玲,张宝山,杨万平.基于环境污染的中国全要素能源效率研究[J].中国工业经济,2009, (2): 76-86.
[165]吴琦,武春友.基于DEA的能源效率评价模型研究[J].管理科学,2009, 22(1): 103-112.
[166]汪克亮,杨宝臣,杨力.中国能源利用的经济效率、环境绩效与节能减排潜力[J].经济管理, 2010, (10): 1-9.
[167] Glodsmith R W. A perpetual inventory of national wealth[J]. Studies in income and wealth, 1951, 14(1): 5-61.
[168]张军,吴桂荣,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004, (10): 35-44.
[169] Chambers R G, Chung Y, F?re R. Benefit and distance function[J]. Journal of Economic Theory, 1996, (70): 407-419.
[170] Battese G E, Rao D S P. Technology gap, efficiency, and a stochastic metafrontier function[J]. International Journal of Business and Economics, 2002, 1(2): 87-93.
[171] O’Donnell C J, Rao D S P, Battese G. E. Metafrontier frameworks for the study of firm-level efficiency and technology ratios[J]. Empirical Economics, 2007, (34): 231-255.
[172] Battese G E, Rao D S P, O’Donnell C J. A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies[J]. Journal of Productivity Analysis, 2004, (21): 91-103.
[173] Hayami Y. Source of agricultural productivity gap among selected countries[J]. American Journal of Agricultural Economics, 1969, (51): 564-575.
[174] Hayami Y, Ruttan V W. Agricultural development: An international perspective[M]. Baltimore and London: John Hopkins Unviersity Press, 1971.
[175] Chen K H, Huang Y J, Yang C H. Analysis of regional productivity growth in China: A generalized metafrontier MPI approach[J]. China Economic Review, 2009, (20): 777-792.
[176] Oh D H. A metafrontier approach for measuring an envionmentally sensitive productivity growth index[J]. Energy Economics, 2010, (32): 146-157.
[177] Huang Y J, Chen K H, Yang C H. Cost efficiency and optimal scale of electricity distribution firms in Taiwan: An application of metafriontier analysis[J]. Energy Economics, 2010, (32): 15-23.
[178]徐国祥,刘汉良,孙允午等.统计学[M].上海:上海财经大学出版社,2005.
[179] Tulkens H, Vanden Eeckaut, P. Non-parametric efficiency, progress, and regress measure for panel data: Methodological aspects. European Journal of Operational Research, 1995, (80): 472-479.
[180] Chung Y H, F?re R, Grosskopf S. Productivity and Undesirable Outputs: A Directional Distance Function Approach [J]. Journal of EnvironmentalManagement, 1997, (51): 229-240.
[181] Yu M M, Hsu S H, Ching-Cheng, Duu-Hwa Lee. Productivity growth of Taiwan’s Major Domestic Airports in the Presence of Aircraft Noise [J]. Transportation Research Paper Part E, 2008, (44): 543-554.
[182] F?re R, Grosskopf S, Pasurka C. Accounting for Air Pollution Emissions in Measuring State Manufacturing Productivity Growth [J]. Journal of Regional Science, 2001, (41): 381-409.
[183] Yoruk B, Zaim O. Productivity Growth in OECD Countries: A Comparision with Malmquist Indices [J]. Journal of Comparative Economies, 2005, (33): 401-420.
[184] Kumar S. Environmentally Sensitive Productivity Growth: A Global Analysis Using Malmquist-Luenberger Index [J]. Ecological Economics, 2006, (56): 280-293.
[185]王兵,吴延瑞,颜鹏飞.环境管制与全要素生产率增长:APEC的实证研究[J].经济研究, 2008, (5): 19-32.
[186] Hu J L, Chang T P Total-factor Energy Productivity Growth of Regions in China [J]. National Chiao Tung Unviersity, Taipei, 2009, Working Paper.
[187]杨俊,邵汉华.环境约束下中国工业增长状况研究—基于Malmquist-Luenb -erger指数的实证研究》[J]数量经济技术经济研究, 2009, (9): 64-77.
[188]吴军.环境约束下中国地区工业全要素生产力在增长及收敛分析[J].数量经济技术经济研究, 2009, (11): 17-27.
[189] Chambers, R.G., Fare, R., Grosskopf, S. Productivity Growth in APEC countries [J]. Pacific Economic Review, 1996, 1 (3): 181-190.
[190] F?re R, Grosskopf S, Pasurka C. Accounting for air pollution emissions in measuring state manufacturing productivity growth[J]. Journal of Regional Science, 2001, (41): 381-409.
[191] Nghiem H, Coelli T. The effect of incentive reforms upon productivity: evidence from the vietnamese rice industry[J]. Journal of Development Studies, 2002, 39(1): 74-93.
[192]王亚华,吴凡,王争.交通行业生产率变动的Bootstrap-Malmquist指数分析(1980-2005)[J].经济学季刊,2008, 7(3): 891-912.
[193]王群伟,周鹏,周德群.我国二氧化碳排放绩效的动态变化、区域差异及影响因素[J].中国工业经济,2010, (1): 45-54.
[194] Charnes A, Clark C T, Cooper W W., et al. A Development Study of DataEnvelopement Analysis in Measuring the Efficiency of Maintaince Units in the US Air Force [J]. Annals of Operational Research, 1985, 2 (1): 95-112.
[195]高铁梅.计量经济分析方法与建模——Eviews应用及实例(第二版)[M].北京:清华大学出版社,2009.
[196]王志刚.面板数据模型及其在经济分析中的应用[M].北京:经济科学出版社,2008.
[197] Arellano M.著,朱平芳译.面板数据计量经济学[M].上海:上海财经大学出版社,2008.
[198]王群伟,周德群,沈璇等.我国全要素能源效率的测度与分析[J].管理评论, 2010, (3): 37-43.
[199]王志刚,龚六堂,陈玉宇.地区间生产效率与全要素生产率增长率分解(1978-2003)[J].中国社会科学, 2006, (2): 55-67.
[200]张宇. FDI技术外溢的地区差异与吸收能力的门限特征[J].数量经济技术经济研究,2008, (1): 28-39.
[201]邵军,徐康宁.外商直接投资、人力资本与中国工业技术进步——基于吸收能力的FDI技术外溢研究[J].东南大学学报(哲学社会科学版), 2008, (5): 24-30.
[202] Miketa A, Mulder P. Energy Producivity across Developed and Developing Countries in 10 Manufacturing Sectors: Patterns of Growth and Convergence [J]. Energy Economics, 2005, (27): 429-453.
[203] F?re R, Grosskopf S, Lovell C A K, Pasurka C. Multilateral Productivity Comparisons When Some Output are Undesirable: A Nonparametric Approach[J]. The Review of Economics and Statistics, 1989, 71(1): 90-98.
[204] Zofio J L, Prieto A M. Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries[J]. Resource and Energy Economics, 2001, (23): 63-83.
[205]王波,张群.环境约束下不同生产效率模型研究[J].系统工程理论与实践,2002, (1): 1-8.
[206] Yaisawarng S, Klein J. The effects of sulfur dioxide controls on productivity change in the U.S. electric power industry[J]. Review of Economics and Statisitics, 1994, (76): 447-460.
[207] Hu J L, Lee Y C. Efficient Three Industrial Waste Abatement for Regions in China [J]. International Journal of Sustainable development & World Ecology, 2008, 15(3): 132-144.
[208] Honma S, Hu J L. Efficient Waste and Pollution Abatement for Regions in Japan[J]. International Journal of Sustainable Development & World Ecology, 2009, 16(4): 270-285.
[209] Zhu J, Chen Y. Asessing texitle factory performance[J]. Journal of System Science and System Engineering, 1993, (2): 119-133.
[210] Golany B, Roll Y. An application procedure for DEA[J]. Omega: The International Journal of Management Science, 1989, (17): 237-250.
[211] Athanassopoulos A D, Thanassoulis E. Separating market efficiency from profitability and its implications for planning[J]. Journal of the Operational Research Society, 1995, (46): 20-34.
[212] Scheel H. Undesirable outputs in efficiency valuations[J]. European Journal of Operational Research, 2001, (132): 400-410.
[213] Seiford L M, Zhu J. Modeling undesirable factors in efficiency evaluation[J]. European Journal of Operational Research, 2002, (142): 16-20.
[214] Jahanshahloo G R, Venchen A H, Foroughi A A, Matin R K. Inputs/outputs estimation in DEA when some factors are undesirable[J]. Applied Mathematics and Computation, 2004, (156): 19-32.
[215] Venchen A H, Matin R K, Kajani M T. Undesirable factors in efficiency measurement[J]. Applied Mathematics and Computation, 2005, (163): 547-552.
[216] Liang L, Li Y J, Li S B. Increasing the discriminatory power of DEA in the presence of the undesirable outputs and large dimensionality of data sets with PCA[J]. Expert System with Applications, 2009,36(3): 5895-5899.
[217]卞亦文.基于DEA理论的环境效率评价方法研究[D].合肥:中国科学技术大学博士学位论文,2006.
[218] F?re R, Grosskopf S. Modeling undesirable factors in efficiency evaluation: Comment[J]. European Journal of Operational Research, 2004, (157): 242-245.
[219] Lee J D, Park J B, Kim T Y. Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach[J]. Journal of Environmental Management, 2002, (64): 365-375.
[220] Zaim O. Measuring environmental performance of state manufacturing through changes in pollution intensitites: a DEA framework[J]. Ecological Economics, 2004, (48): 37-47.
[221] Dyckhoff H, Allen K. Measuring ecological efficiency with data envelopmentanalysis (DEA)[J]. European Journal of Operational Research, 2001, (132): 312-325.
[222] F?re R, Grosskopf S, Jr C A. Environmental Production Fucntions and Environmental Directional Distance Functions [J].Energy, 2007,32 (7): 1055-1066.
[223] Watanabe M, Tanaka K. Efficiency Analysis of Chinese Industry: A Directional Distance Function Approach[J]. Energy Policy, 2007,35 (12): 6323-6331.
[224] Coelli T J, Rao D S, Battese G E. An Introduction to Efficiency and Productivity Analysis[M]. Kluwer Academic Publishers, Boston, 1998.
[225]胡鞍钢,郑京海,高宇宁等.考虑环境因素的省际技术效率排名:1999-2005[J].经济学季刊,2008, 4(3): 933-960.
[226]徐士元.技术进步对能源效率影响的实证分析[J].科研管理,2009, 30(6): 16-24.
[227] Chambers R G, F?re R, Grosskopf, S. Productivity Growth in APEC countries[J]. Pacific Economic Review, 1996, 1(3): 181-190.
[228] Dervaux, B, Leleu, H., Minvielle, E., et al. Performance of French intensive care units: A directional distance function approach at the patient level[J]. Int. J. Production Economics, 2009, (120): 585-594.
[229] F?re R, Grosskopf, S, Jr A. Environmental production functions and environme- -ntal directional distance function[J]. Energy, 2007, (32): 1055-1066.
[230] Picazo-Tadeo, Andres J, et al. Directional distance function and environmental regulation[J]. Resource and Energy Economics, 2005, (27): 131-142.
[231]王群伟,周德群,葛世龙等.环境规制下的投入产出效率及规制成本研究[J].管理科学,2009, 22(6): 111-119.
[232]魏楚.中国能源效率问题研究[D].杭州:浙江大学博士学位论文,2009.
[2] Farrell M J. The measurement of productive efficiency[J]. Journal of Royal Statisitc Society, 1957, Series A, 120 (Ⅲ): 253-281.
[3] Koopmans T C. Analysis of production as an efficient combination of activities[J]. Activity Analysis of Production and Allocation, 1951: 33-97.
[4] Debreu G. The coefficient of resource utilization[J]. Econometrica, 1951, (19): 273-292.
[5] F?re R, Grosskopf S. Measuring output efficiency[J]. European Journal of Operational Research, 1983, (13): 173-179.
[6] F?re R, Grosskopf S, Lovell C A K. The measurement of efficiency of production[M]. Boston: Kluwer Nijhoff Publishing Co, 1985.
[7] F?re R, Grosskopf S, Norris M, Zhong-yang Z. Productivity growth, technical progress, and efficiency change in industrialized countries[J]. American economic review, 1994, 84(1): 66-83.
[8] F?re R, Primont D. Multi-output production and duality: Theory and applications[M]. Kluwer Academic Publishers, Boston, 1995.
[9] Malmquist S. Index numbers and indifference surfaces[J]. Trabajos de Estatistica, 1953, (4): 209-242.
[10] Shephard R W. Cost and Production Functions[M]. Princeton University Press, Princeton, New Jersey, 1953.
[11] Aigner D J, Lovell C A K, Schmidt P. Formulation and estimation of stochastic frontier production models[J]. Journal of Econometrics, 1977, (6): 21-37.
[12] Meeusen W, Van Den Broeck. Efficiency estimation from Cobb-Douglas production function with composed error[J]. International Economic Review, 1977, (18): 435-444.
[13] Battese G E, Coelli T J. Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India[J]. Journal of Productivity Analysis, 1992, (3): 153-169.
[14] Battese G E, Coelli T J. A model for techncial inefficiency effects in a stochastic frontier production function for panel data[J]. Empirical Economics, 1995, 20(2): 325-332.
[15] Battese G E, Corra G S. Estimation of a production frontier model: with application to the pastoral zone of eastern Australia[J]. Australian Journal of Agricultural Economics, 1977, 21(3): 169-179.
[16] Mark M P, Lung F L. The measurement and sources of technical inefficiency in the Indonesian weaving industry[J]. Journals of Development Economics, 1981, 9(1): 43-64.
[17] Kalirajan. An econometric analysis of yield variability in paddy production[J]. Canadian Journal of Agricultural Economics, 1981, (29): 283-294.
[18] Wang E C. R&D efficiency and economic performance: A cross-country analysis using the stochastic frontier approach[J]. Journal of Policy Modeling, 2007, 29(2): 345-360.
[19] Paul F, Vencappa D, Diacon S, Klumpes P, O’Brien C. Market structure and the efficiency of European insurance companies: A stochastic frontier analysis[J]. Journal of Banking and Finance, 2008, 32(1): 86-100.
[20]闫冰,冯根福.基于随机前沿函数的中国工业R&D效率分析[J].当代经济科学,2005, 27(6): 14-19.
[21]黄薇.基于SFA方法对中国保险机构效率的实证研究[J].南开经济研究,2006, (5): 104-115.
[22]干春晖,郑若谷.中国工业生产绩效:1998-1007—基于细分行业的推广随机前沿函数的分析[J].财经研究,2009, 35(6): 97-108.
[23]史丹,吴利学,傅晓霞等.中国能源效率地区差异及其成因研究—基于随机前沿生产函数的方差分解[J].管理世界,2008, (2): 35-43.
[24] Coelli T, Perelman S. A comparison of parametric and non-parametric distance function: with application to European railways[J]. European Journal of Operational Reasearch, 1999, (117): 326-339.
[25] Fecher F, Kessler D, Perelman S, Pestieau P. Productive performance of the French insurance industry[J]. Journal of Productivity Analysis, 1993, (14): 77-93.
[26] Sharma K R, Leung P, Zaleski H M. Productive efficiency of the Swine industry in Hawaii: Stochastic frontier vs. Data envelopment analysis[J]. Journal of Productivity Analysis, 1997, (18): 447-459.
[27] Granderson G, Linvill C. Parametric and non-parametric approches to benchmarking the regulated firm[J]. Journal of Productivity Analysis, 1999, (12): 211-231.
[28] Luis R M, Juan A V. The use of parametric and non-parametric frontier methods to measure the production efficiency in the industry sector: A comparative study[J]. International Journal of Production Economics, 2001, (69): 265-275.
[29] Bauer P W, Berger A N, Ferrier G D, Humphrey D B. Consistency condition for regulatory analysis of financial institution: A comparison of frontier efficiency methods[J]. Journal of Economics and Business, 1998, (50): 85-114.
[30] Giuffrida A, Hugh G. Measuring performance in primary care: Econometric analysis and DEA[J]. Applied Economics, 2001, (33): 163-175.
[31] Lawrence W L, Erwin T L. Measuring techncialand scale efficiency in rail industry: A comparison of 85 railways using DEA and SFA[J]. Asia Conference on Efficiency and Productivity, 2002: 30-45.
[32] Boles J N. Efficiency squared-efficiency computation of efficiency indexes[J]. Proceedings of the 39thAnnual Meeting of the Western Farm Economics Association, 1966: 137-142.
[33] Afriat S N. Efficiency estimation of production functions[J]. International Economic Review, 1972, 13(3): 568-598.
[34] Charnes A, Cooper W W, Rhode E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, (2): 429-444.
[35] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science, 1984, (30): 1078-1092.
[36] Charnes A, Cooper W W, Wei Q L and Huang Z M. Cone ratio data envelopment analysis and multi-objective program ming[J]. Interantional Journal of System Science, 1989, (20): 1099-1118.
[37] Yu G, Wei Q L, Brockett P. A generalized data envelopment analysis model: A unification and extension methods for efficiency analysis of decision making units[J]. Annals of Operational Research, 1996, (66): 47-89.
[38] F?re R, Grosskopf S. A nonparmetric cost approach to scale efficiency[J]. The Scandinavian Journal of Economics, 1985, (87): 594-604.
[39] F?re R, Grosskopf S, Logan J. The relative performance of publicly-owned and privately-owned electric utilities[J]. Journal of Public Economics, 1985, (26):89-106.
[40] Seiford L M, Thrall R M. Recent developments in DEA: The mathematical approach to frontier analysis[J]. Journal of Econometrics, 1990, (46): 7-38.
[41] Lovell C A K, Pastor J T. Units invariant and translation invariant DEA models[J]. Operational Research Letters, 1995, (18): 147-151.
[42] Ali A I, Seiford L M. The mathematical programming approach to efficiency analysis, The measurement of Productive Efficiency: Techniques and Applications[M], Oxford university press, New York, 1993.
[43] Lovell C A K. Production frontiers and productive efficiency, in Fried H O, Lovell C A K and Schmidt S S (Eds.), The Measurement of Productive Efficiency: Techniques and Applications[M]. Oxford University Press, New York, 1993.
[44] Charnes A, Cooper W W, Lewin A Y and Seiford L M. Data Envelopment Analysis: Theory, methodology and applications[M]. Kluwer Academic Publishers, Boston, 1995.
[45] Seiford L M. Data Envelopment Analysis: The evolution of the state of the art (1978-1995)[J]. Journal of Productivity Analysis, 1996, (7): 99-138.
[46] Cooper W W, Seiford L M, Tone K. Data Envelopment Analysis: A comprehensive text with models, applications, reference and DEA-solver software[M]. Kluwer Academic Publishers, Boston, 2000.
[47] Thanassoulis E. Introduction to the theory and application of data envelopment analysis: A foundation text with integrated software[M]. Kluwer Academic Publishers, Boston, 2001.
[48] Gleason J M, Barnum D T. Toward valid measures of public sector productivity: performance measures in urban transit[J]. Management Science, 1982, 28(4): 279-386.
[49] Diewert W E. Exact and superlative index numbers[J]. Journal of Econometrics, 1976, (4): 115-146.
[50] Caves D W, Christensen L R, Diewert W E. Multilateral comparisons of output, input, and productivity using superlative index numbers[J]. Economic Journal, 1982, (92): 73-86.
[51] Coelli T J, Prasada R D S, Battese G E. An introduction to efficiency and productivity analysis[M]. Kluwer Academic Publishers, Boston, 1998.
[52] F?re R, Grosskopf S, Lovell C A K. Production frontiers[M]. CambridgeUniversity Press, Cambridge, 1994.
[53] F?re R, Grosskopf S, Ross P. Malmquist productivity indexes: A survey of theory and practice[M]. Kluwer Academic Publishers, Boston, 1998.
[54] Meadow D L. Limits to growth-report to the Club of Rome[M]. University Books, New York, 1972.
[55] Dasgupta P, Heal G M. The optimal depletion of exhaustible resources[J]. Reviews of Economic Studies, Symposium, 1974, 3-28.
[56] Stiglitz J E. Growth with exhaustible natural resources: The competitive economy[J]. Review of Economies Studies, 1974, (41): 139-152.
[57] Garg P C, Sweenney J L. Optimal growth with depletable resources[J]. Resources and Energy, 1978, (1): 43-56.
[58] Rasche R H, Tatom J A. Energy resources and potential GNP[J]. Federal Reserve Bank of St. Louis Review, 1977: 10-24.
[59] Renshaw E F. Energy efficiency and the slump in labour productivity in the USA[J]. Energy Economics, 1981, 3(1): 36-42.
[60] Suzuki K, Takenaka H. The role of investment for energy conservation: Future Japanese economic growth[J]. Energy Economics, 1981, (3): 233-243.
[61] Uri N D, Hassanein S A. Energy prices, labor productivity and causality: An empirical examination[J]. Energy Economics, 1982, (4): 98-104.
[62] Nordhaus W D. To slow or not to slow: The economics of the greenhouse effect[J]. The Economic Journal, 1991, 101(407): 920-937.
[63] Bovenberg A L, Smulders S A. Transitional of impacts of environmental policy in an endogenous growth model[J]. International Economic Review, 1996, (37): 861-893.
[64] Grimaud A, Rouge L. Non-renewable resources and growth with vertical innovations: Optimum, equilibrium and economic policies[J]. Journal of Environmental Economics and Management, 2003, (45): 433-453.
[65] Grimaud A, Rouge L. Polluting not-renewable resourece, innovation and growth: Welfare and environmental policy[J]. Resources and Energy Economics, 2005, (27): 109-129.
[66] Granger C W J, Newbald P. Forecasting economic time series[M]. Academic Press, New York, 1977.
[67] Philips P C B. Understanding spurious regression in econometrics[J]. Journal of Econometric, 1986, (33): 311-340.
[68] Engle R F, Granger C W J. Cointegration and error correction: representation, estimation and testing[J]. Econometrica, 1987, (55): 251-276.
[69] Engle R F, Yoo B S. Forecasting and testing in cointegrated systems[J]. Journal of Econometrics, 1987, (35): 143-159.
[70] Kraft J, Kraft A. On the relationship between energy and GNP[J]. Journal of Energy and Development, 1978, (3): 401-403.
[71] Yu E S H, Hwang B K. The relationship between energy and GDP: further results[J]. Energy Economics, 1984, (6): 186-190.
[72] Yu E S H, Choi J Y. The causal relationship between energy and GNP: an international comparison[J]. Journal of Energy and Development, 1985, (10): 249-272.
[73] Cheng B S. Energy consumption and economic growth in Brazil, Mexico and Venezuela: a time series analysis[J]. Applied Economics Letters, 1997, (4): 671-674.
[74] Yu S H, Jin J C. Cointegration test of energy consumption, income and employment[J]. Resources and Energy, 1992, (14): 259-266.
[75] Masih A M M, Masih R. Energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modeling techniques[J]. Energy Economics, 1996, (18): 165-183.
[76] Glasure Y U. Energy and national income in Korea: further evidence on the role of omitted variables[J]. Energy Economics, 2002, (24): 355-365.
[77] Soytas U, Sari R. Energy consumption and GDP: causality relationship in G-7 countries and emerging markets[J]. Energy Economics, 2003, (25): 33-37.
[78] Oh W, Lee K. Causal relationship between energy consumption and GDP revisited: the case of Korea 1970-1999[J]. Energy Economics, 2005, (26): 51-59.
[79] Lee C C. Energy consumption and GDP in developing countries: a cointegrated panel analysis[J]. Energy Economics, 2005, (27): 415-427.
[80] Wolde-Rufael Y. Electricity consumption and economic growth: a time series experience for 17 African countries[J]. Energy Policy, 2006, (34): 1106-1114.
[81]赵丽霞,魏巍贤.能源与经济增长模型研究[J].预测,1998, (6): 33-35.
[82] Shiu A, Lam P L. Electricity consumption and economic growth in China[J]. Energy Policy, 2004, (32): 47-54.
[83] Wolde-Rufael Y. Disaggregated industrial energy consumption and GDP: the case of Shanghai, 1952-1999[J]. Energy Economics, 2004, (26): 69-75.
[84] Hwang D B K, Gum B. The causal relationship between energy and GDP: the case of Taiwan[J]. Journal of Energy and Development, 1992, (16): 219-226.
[85] Cheng B S, Lai T W. An investigation of cointegration and causality between energy consumption and economic activity in Taiwan[J]. Enery Economics, 1997, (19): 435-444.
[86]林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003, (11): 18-27.
[87]林伯强.结构变化、效率改进与能源需求预测——以中国电力行业为例[J].经济研究,2003, (5): 57-66.
[88]韩智勇,魏一鸣,范英.中国能源强度与经济结构变化特征研究[J].数理统计与管理,2004, (11): 1-7.
[89]马超群,储慧斌,李科等.中国能源消费与经济增长的协整与误差校正模型研究[J].系统工程,2004, 22(10): 47-50.
[90]贲兴振,杨宝臣.中国能源消费与经济增长的协整关系分析[J].哈尔滨理工大学学报,2005, 10(8): 117-120.
[91]刘凤朝,刘源远,潘雄锋.中国经济增长与能源消费的动态特征[J].资源科学,2007, 29(5): 63-68.
[92]赵进文,范继涛.经济增长与能源消费内在依从关系的实证研究[J].经济研究,2007, (8): 31-42.
[93]牟敦国.中国能源消费与经济的因果关系研究[J].厦门大学学报(哲学社会科学版),2008, (2): 100-107.
[94]刘长生,郭小东,简玉峰.能源消费对中国经济增长的影响研究——基于线性与非线性回归方法的比较分析[J].产业经济研究,2009, (1): 1-9.
[95] Meadous D H, Meadows D L, Randers J. Beyond the limits[M]. Post Mills, VT: Chelsea Green Publishing Co., 1992.
[96] Daly H E. Beyond growth: the economics of sustainable development[M]. Beacon Press, 1996.
[97] Hirst E. Improving energy efficiency in the USA: The federal role[J]. Energy Policy, 1991, (19): 567-577.
[98] Porter M E. vander Linde C. Green and Competitive: Ending the statemate[J]. Harvard Business Review, 1995, 73(5): 120-134.
[99] Patterson M G. What is energy efficiency? Concepts, indicators and methodological issues[J]. Energy Policy, 1996, 24(5): 377-390.
[100]中国能源发展战略与政策研究课题组.中国能源发展战略与政策研究[M].北京:经济科学出版社,2004.
[101]魏楚,沈满洪.能源效率及其影响因素:基于DEA的实证分析[J].管理世界,2007, (8): 66-76.
[102]何祚庥,王亦楠.我国与美国、日本能源利用效率的差距到底有多大?[J].中国科学院院士建议,2004, (4).
[103]戴彦德,朱跃中.应慎重看待能源效率水平评价的国际比较[J].石油与化工节能,2005, (4).
[104]韩晓平.从全球资源配置角度分析我国的能源利用效率[J].红旗文稿,2007, (15).
[105] Hu J L, Wang S C. Total-factor energy efficiency of regions in China[J]. Energy Policy, 2006, (34): 3206-3217.
[106] Zhou P, Ang B W, Poh K L. A survey of data envelopment analysis in energy and environmental studies[J]. European Journals of Operational Research, 2008, (189): 1-18.
[107] Hu J L, Kao C H. Efficient energy-saving targets for APEC economies[J]. Energy Policy, 2007, (35): 373-382.
[108] Zhang J L, Wang G S. Energy saving technologies and productive efficiency in the Chinese iron and steel sector[J]. Energy Policy, 2008, (33): 525-537.
[109] Mukherjee K. Energy use efficiency in U.S. manufacturing: A nonparametirc analysis[J]. Energy Economics, 2008, (30): 76-96.
[110] Mukherjee K. Energy use efficiency in the Indian manufacturing sector: An interstate analysis[J]. Energy Policy, 2008, (36): 662-672.
[111] Honma S., Hu J.L.Total-factor energy productivity growth of regions in Japan[J]. Energy Policy, 2009, (37): 3941-3950.
[112] Yeh T L, Chen T Y, Lai P Y. A comparative study of energy utilzation efficiency between Taiwan and China[J]. Energy Policy, 2010, 38(5):2386-2394.
[113] Onut S, Soner S. Analysis of enery use and efficiency in Turkish manufacturing sector SEMs[J]. Energy Conversion and Management, 2007, 48(2): 384-394.
[114] Zhou P, Ang B W. Linear Programming models for measuring economy-wide energy efficiency performance[J]. Energy Policy, 2008, 36(8): 2911-2916.
[115] Nassiri S M, Singh S. Study on energy use efficiency for paddy crop using data envelopment analysis (DEA) technique[J]. Applied Energy, 2009, 86(7-8): 1320-1325.
[116] Mukherjee K. Measuring energy efficiency in the context of an emergingeconomy: the case of Indian manufacturing[J]. European Journal of Operational Research, 2010, (201): 933-941.
[117] Vaclav S. China’s Energy[R]. in Report Prepared for the U.S. Congress, Washington D. C: Office of Technology Assessment, 1990.
[118] Kambara T. The energy sistuation in China[J]. China Quarterly, 1992, (131): 508-636.
[119] Garbaccio R F, Ho M S, Jorgenson D W. Why has the energy-output ratio fallen in China?[J]. Energy Journal, 1999, 20(3): 63-92.
[120] Lin X, Polenske K R. Input-output anatomy of China’s energy use change in the 1980s[J]. Economic System Research, 1995, 7(1): 67-84.
[121]史丹.我国经济增长过程中能源利用效率的改进[J].经济研究,2002, (9): 49-57.
[122]王庆一.中国的能源效率及国际比较[J].节能与环保,2003, (8): 5-7.
[123]蒋金荷.提高能源效率与经济结构调整的策略分析[J]. 2003, (10): 16-23.
[124]丁建勋.最优能源强度与我国经济增长[J].财经科学,2007, (4): 29-35.
[125]何建坤,张希良.我国十一五期间能源强度下降趋势分析——如何实现能源强度下降20%的目标[J].中国软科学,2006, (4): 33-38.
[126]齐志新,陈文颖,吴宗鑫.中国的能源强度究竟有多高[J].数量经济技术经济研究,2007, (8): 51-58.
[127]贺灿飞,王俊松.经济转型与中国省区能源强度研究[J].地理科学,2009, 29(4): 461-469.
[128] Huang J P. Industry energy use and structural change: A case study of the People’s Republic of China[J]. Energy Economics, 1993, 15(2): 131-136.
[129] Zhang Z X. Why did energy intensity fall in China’s industrial sector in the 1990s? the relative importance of structural change and intensity change[J]. Energy Economics, 2003, 25(6): 625-638.
[130]王玉潜.能源消耗强度变动的因素分解方法及其应用[J].数量经济技术经济研究,2003, (8): 151-154.
[131] Fisher-Vanden K, Jefferson G H, Liu H M, et al. What is driving China’s decline in energy intensity?[J]. Resource and Energy Economics, 2004, 26(1): 77-97.
[132] Ma C, Stern D I. China’s energy intensity trend: a decomposition analysis[J]. Working papers, Rensselaer Polytechnic Insititute, 2006.
[133]齐志新,陈文颖.结构调整还是技术进步?——改革开放后我国能源效率提高的因素分析[J].上海经济研究,2006, (6): 8-16.
[134]吴巧生,成金华.中国工业化进程中的能源消耗强度变动及因素分析——基于分解模型的实证分析[J].财经研究,2006, 32(6): 75-85.
[135]周勇,李廉水.中国能源强度变化的结构与效率因素贡献[J].产业经济研究,2006, (4): 68-74.
[136]吴巧生,成金华.中国能源消耗强度变动及因素分解:1980-2004[J].经济理论与经济管理,2006, (10): 34-40.
[137]李国璋,王双.区域能源强度变动:基于GFI的因素分解分析[J].中国人口资源与环境,2008, 18(4): 62-66.
[138]刘叶,王磊.我国工业能源强度变动的影响因素分解分析——基于LMDI分解法[J].中国矿业大学学报(社会科学版),2009, (4): 66-70.
[139]吴巧生.中国工业化进程中的能源消耗强度变动及影响因素——基于Fisher指数分解方法的实证分析[J].经济理论与经济管理,2010, (5): 44-50.
[140]张晓平,孙磊.中国工业能源消费强度变化的分解分析[J].资源科学,2010, 32(9): 1685-1892.
[141] Ang B W, Zhang F Q. A survey of index decomposition analysis in energy and environmental studies[J]. Energy, 2000, 25(12): 1149-1176.
[142]王少平,杨继生.中国工业能源调整的长期战略与短期措施——基于12个主要工业行业能源需求的综列协整分析[J].中国社会科学,2006, (4):88-97.
[143]史丹.中国能源效率的地区差异与节能减排潜力分析[J].中国工业经济,2007, (10): 49-58.
[144]张贤,周勇.外商直接投资对我国能源强度的空间效应分析[J].数量经济技术经济研究,2007, (1): 101-108.
[145]刘畅,崔艳红.中国能源消耗强度区域差异的动态关系比较研究——基于省市面板数据模型的实证分析[J].中国工业经济,2008, (4): 34-43.
[146]徐刚,潘祺志.中国能源消费与经济增长及能源效率关系的实证分析——基于6大产业部门的综列协整和PVECM模型[J].中央财经大学学报,2009, (5): 63-68.
[147]王军,仲伟周.中国地区能源强度差异研究——要素禀赋的分析视角[J].产业经济研究,2009, (6): 44-51.
[148]吴利学.中国能源效率波动:理论解释、数值模拟及政策含义[J].经济研究,2009, (5): 130-143.
[149]张宗益,呙小明,汪锋.能源价格上升对中国第三产业能源效率的冲击——基于VAR模型的实证分析[J].管理评论,2010, (6): 61-70.
[150]谭忠富,张金良.中国能源效率与其影响因素的动态关系研究[J].中国人口资源与环境,2010, 20(4): 43-49.
[151]徐国泉,刘则渊. 1998-2005年中国八大经济区域全要素能源效率——基于省际面板数据的分析[J].中国科技论坛,2007, (7): 68-72.
[152]李世祥,成金华.中国主要工业省区能源效率分析:1990-2006[J].数量经济技术经济研究,2008, (10): 32-43.
[153]师博,沈坤荣.市场分割下的中国全要素能源效率:基于超效率DEA方法的经验分析[J].世界经济,2008, (9): 49-59.
[154]魏楚,沈满洪.结构调整能否改善能源效率:基于中国省级数据的研究[J].世界经济,2008, (11): 77-85.
[155]邵军,管驰明.中国工业部门能源使用效率及其影响因素研究[J].经济学家,2009, (1): 58-65.
[156]李世祥,成金华.中国工业行业的能源效率特征及其影响因素——基于非参数前沿的实证分析[J].财经研究,2009, 35(7): 134-143.
[157]庞瑞芝,王卢羡,张泉.转型期间中国工业部门全要素能源效率的要素效应、结构效应与技术效应分析[J].当代经济科学,2009, 31(5): 21-29.
[158]武春友,吴琦.基于超效率DEA的能源效率评价模型研究[J].管理学报,2009, 6(11): 1460-1465.
[159]杨红亮,史丹,肖洁.自然环境能够因素对能源效率的影响——中国各地区的理论节能潜力与实际节能潜力分析[J].中国工业经济,2009, (4): 73-84.
[160]李廉水,周勇.技术进步能提高能源效率吗?——基于中国工业部门的实证检验[J].管理世界,2006, (10): 82-89.
[161] Wei Y.M., Liao H., Fan Y.An empricial analysis of energy efficiency in China’s iron and steel sector[J]. Energy, 2007, (32): 2262-2270.
[162]王群伟,周德群.中国全要素能源效率变动的实证研究[J].系统工程,2008, 26(7): 74-80.
[163]屈小娥.中国省际全要素能源效率变动分解——基于Malmquist指数的实证研究[J].数量经济技术经济研究,2009, (8): 29-43.
[164]袁晓玲,张宝山,杨万平.基于环境污染的中国全要素能源效率研究[J].中国工业经济,2009, (2): 76-86.
[165]吴琦,武春友.基于DEA的能源效率评价模型研究[J].管理科学,2009, 22(1): 103-112.
[166]汪克亮,杨宝臣,杨力.中国能源利用的经济效率、环境绩效与节能减排潜力[J].经济管理, 2010, (10): 1-9.
[167] Glodsmith R W. A perpetual inventory of national wealth[J]. Studies in income and wealth, 1951, 14(1): 5-61.
[168]张军,吴桂荣,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004, (10): 35-44.
[169] Chambers R G, Chung Y, F?re R. Benefit and distance function[J]. Journal of Economic Theory, 1996, (70): 407-419.
[170] Battese G E, Rao D S P. Technology gap, efficiency, and a stochastic metafrontier function[J]. International Journal of Business and Economics, 2002, 1(2): 87-93.
[171] O’Donnell C J, Rao D S P, Battese G. E. Metafrontier frameworks for the study of firm-level efficiency and technology ratios[J]. Empirical Economics, 2007, (34): 231-255.
[172] Battese G E, Rao D S P, O’Donnell C J. A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies[J]. Journal of Productivity Analysis, 2004, (21): 91-103.
[173] Hayami Y. Source of agricultural productivity gap among selected countries[J]. American Journal of Agricultural Economics, 1969, (51): 564-575.
[174] Hayami Y, Ruttan V W. Agricultural development: An international perspective[M]. Baltimore and London: John Hopkins Unviersity Press, 1971.
[175] Chen K H, Huang Y J, Yang C H. Analysis of regional productivity growth in China: A generalized metafrontier MPI approach[J]. China Economic Review, 2009, (20): 777-792.
[176] Oh D H. A metafrontier approach for measuring an envionmentally sensitive productivity growth index[J]. Energy Economics, 2010, (32): 146-157.
[177] Huang Y J, Chen K H, Yang C H. Cost efficiency and optimal scale of electricity distribution firms in Taiwan: An application of metafriontier analysis[J]. Energy Economics, 2010, (32): 15-23.
[178]徐国祥,刘汉良,孙允午等.统计学[M].上海:上海财经大学出版社,2005.
[179] Tulkens H, Vanden Eeckaut, P. Non-parametric efficiency, progress, and regress measure for panel data: Methodological aspects. European Journal of Operational Research, 1995, (80): 472-479.
[180] Chung Y H, F?re R, Grosskopf S. Productivity and Undesirable Outputs: A Directional Distance Function Approach [J]. Journal of EnvironmentalManagement, 1997, (51): 229-240.
[181] Yu M M, Hsu S H, Ching-Cheng, Duu-Hwa Lee. Productivity growth of Taiwan’s Major Domestic Airports in the Presence of Aircraft Noise [J]. Transportation Research Paper Part E, 2008, (44): 543-554.
[182] F?re R, Grosskopf S, Pasurka C. Accounting for Air Pollution Emissions in Measuring State Manufacturing Productivity Growth [J]. Journal of Regional Science, 2001, (41): 381-409.
[183] Yoruk B, Zaim O. Productivity Growth in OECD Countries: A Comparision with Malmquist Indices [J]. Journal of Comparative Economies, 2005, (33): 401-420.
[184] Kumar S. Environmentally Sensitive Productivity Growth: A Global Analysis Using Malmquist-Luenberger Index [J]. Ecological Economics, 2006, (56): 280-293.
[185]王兵,吴延瑞,颜鹏飞.环境管制与全要素生产率增长:APEC的实证研究[J].经济研究, 2008, (5): 19-32.
[186] Hu J L, Chang T P Total-factor Energy Productivity Growth of Regions in China [J]. National Chiao Tung Unviersity, Taipei, 2009, Working Paper.
[187]杨俊,邵汉华.环境约束下中国工业增长状况研究—基于Malmquist-Luenb -erger指数的实证研究》[J]数量经济技术经济研究, 2009, (9): 64-77.
[188]吴军.环境约束下中国地区工业全要素生产力在增长及收敛分析[J].数量经济技术经济研究, 2009, (11): 17-27.
[189] Chambers, R.G., Fare, R., Grosskopf, S. Productivity Growth in APEC countries [J]. Pacific Economic Review, 1996, 1 (3): 181-190.
[190] F?re R, Grosskopf S, Pasurka C. Accounting for air pollution emissions in measuring state manufacturing productivity growth[J]. Journal of Regional Science, 2001, (41): 381-409.
[191] Nghiem H, Coelli T. The effect of incentive reforms upon productivity: evidence from the vietnamese rice industry[J]. Journal of Development Studies, 2002, 39(1): 74-93.
[192]王亚华,吴凡,王争.交通行业生产率变动的Bootstrap-Malmquist指数分析(1980-2005)[J].经济学季刊,2008, 7(3): 891-912.
[193]王群伟,周鹏,周德群.我国二氧化碳排放绩效的动态变化、区域差异及影响因素[J].中国工业经济,2010, (1): 45-54.
[194] Charnes A, Clark C T, Cooper W W., et al. A Development Study of DataEnvelopement Analysis in Measuring the Efficiency of Maintaince Units in the US Air Force [J]. Annals of Operational Research, 1985, 2 (1): 95-112.
[195]高铁梅.计量经济分析方法与建模——Eviews应用及实例(第二版)[M].北京:清华大学出版社,2009.
[196]王志刚.面板数据模型及其在经济分析中的应用[M].北京:经济科学出版社,2008.
[197] Arellano M.著,朱平芳译.面板数据计量经济学[M].上海:上海财经大学出版社,2008.
[198]王群伟,周德群,沈璇等.我国全要素能源效率的测度与分析[J].管理评论, 2010, (3): 37-43.
[199]王志刚,龚六堂,陈玉宇.地区间生产效率与全要素生产率增长率分解(1978-2003)[J].中国社会科学, 2006, (2): 55-67.
[200]张宇. FDI技术外溢的地区差异与吸收能力的门限特征[J].数量经济技术经济研究,2008, (1): 28-39.
[201]邵军,徐康宁.外商直接投资、人力资本与中国工业技术进步——基于吸收能力的FDI技术外溢研究[J].东南大学学报(哲学社会科学版), 2008, (5): 24-30.
[202] Miketa A, Mulder P. Energy Producivity across Developed and Developing Countries in 10 Manufacturing Sectors: Patterns of Growth and Convergence [J]. Energy Economics, 2005, (27): 429-453.
[203] F?re R, Grosskopf S, Lovell C A K, Pasurka C. Multilateral Productivity Comparisons When Some Output are Undesirable: A Nonparametric Approach[J]. The Review of Economics and Statistics, 1989, 71(1): 90-98.
[204] Zofio J L, Prieto A M. Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries[J]. Resource and Energy Economics, 2001, (23): 63-83.
[205]王波,张群.环境约束下不同生产效率模型研究[J].系统工程理论与实践,2002, (1): 1-8.
[206] Yaisawarng S, Klein J. The effects of sulfur dioxide controls on productivity change in the U.S. electric power industry[J]. Review of Economics and Statisitics, 1994, (76): 447-460.
[207] Hu J L, Lee Y C. Efficient Three Industrial Waste Abatement for Regions in China [J]. International Journal of Sustainable development & World Ecology, 2008, 15(3): 132-144.
[208] Honma S, Hu J L. Efficient Waste and Pollution Abatement for Regions in Japan[J]. International Journal of Sustainable Development & World Ecology, 2009, 16(4): 270-285.
[209] Zhu J, Chen Y. Asessing texitle factory performance[J]. Journal of System Science and System Engineering, 1993, (2): 119-133.
[210] Golany B, Roll Y. An application procedure for DEA[J]. Omega: The International Journal of Management Science, 1989, (17): 237-250.
[211] Athanassopoulos A D, Thanassoulis E. Separating market efficiency from profitability and its implications for planning[J]. Journal of the Operational Research Society, 1995, (46): 20-34.
[212] Scheel H. Undesirable outputs in efficiency valuations[J]. European Journal of Operational Research, 2001, (132): 400-410.
[213] Seiford L M, Zhu J. Modeling undesirable factors in efficiency evaluation[J]. European Journal of Operational Research, 2002, (142): 16-20.
[214] Jahanshahloo G R, Venchen A H, Foroughi A A, Matin R K. Inputs/outputs estimation in DEA when some factors are undesirable[J]. Applied Mathematics and Computation, 2004, (156): 19-32.
[215] Venchen A H, Matin R K, Kajani M T. Undesirable factors in efficiency measurement[J]. Applied Mathematics and Computation, 2005, (163): 547-552.
[216] Liang L, Li Y J, Li S B. Increasing the discriminatory power of DEA in the presence of the undesirable outputs and large dimensionality of data sets with PCA[J]. Expert System with Applications, 2009,36(3): 5895-5899.
[217]卞亦文.基于DEA理论的环境效率评价方法研究[D].合肥:中国科学技术大学博士学位论文,2006.
[218] F?re R, Grosskopf S. Modeling undesirable factors in efficiency evaluation: Comment[J]. European Journal of Operational Research, 2004, (157): 242-245.
[219] Lee J D, Park J B, Kim T Y. Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach[J]. Journal of Environmental Management, 2002, (64): 365-375.
[220] Zaim O. Measuring environmental performance of state manufacturing through changes in pollution intensitites: a DEA framework[J]. Ecological Economics, 2004, (48): 37-47.
[221] Dyckhoff H, Allen K. Measuring ecological efficiency with data envelopmentanalysis (DEA)[J]. European Journal of Operational Research, 2001, (132): 312-325.
[222] F?re R, Grosskopf S, Jr C A. Environmental Production Fucntions and Environmental Directional Distance Functions [J].Energy, 2007,32 (7): 1055-1066.
[223] Watanabe M, Tanaka K. Efficiency Analysis of Chinese Industry: A Directional Distance Function Approach[J]. Energy Policy, 2007,35 (12): 6323-6331.
[224] Coelli T J, Rao D S, Battese G E. An Introduction to Efficiency and Productivity Analysis[M]. Kluwer Academic Publishers, Boston, 1998.
[225]胡鞍钢,郑京海,高宇宁等.考虑环境因素的省际技术效率排名:1999-2005[J].经济学季刊,2008, 4(3): 933-960.
[226]徐士元.技术进步对能源效率影响的实证分析[J].科研管理,2009, 30(6): 16-24.
[227] Chambers R G, F?re R, Grosskopf, S. Productivity Growth in APEC countries[J]. Pacific Economic Review, 1996, 1(3): 181-190.
[228] Dervaux, B, Leleu, H., Minvielle, E., et al. Performance of French intensive care units: A directional distance function approach at the patient level[J]. Int. J. Production Economics, 2009, (120): 585-594.
[229] F?re R, Grosskopf, S, Jr A. Environmental production functions and environme- -ntal directional distance function[J]. Energy, 2007, (32): 1055-1066.
[230] Picazo-Tadeo, Andres J, et al. Directional distance function and environmental regulation[J]. Resource and Energy Economics, 2005, (27): 131-142.
[231]王群伟,周德群,葛世龙等.环境规制下的投入产出效率及规制成本研究[J].管理科学,2009, 22(6): 111-119.
[232]魏楚.中国能源效率问题研究[D].杭州:浙江大学博士学位论文,2009.