中国工业部门碳生产率研究
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摘要
随着气候变化问题谈判进程的加快，发展中国家面临的承担减限排的潜在压力与日俱增。中国政府对于应对全球气候变化、控制温室气体排放等国际事务历来高度重视，已经把应对气候变化、控制温室气体排放作为经济社会发展的一项重大战略。基于这一背景，对碳生产率的研究成为当前低碳经济领域关注的热点问题之一。
碳生产率概念的提出时间较晚，尚没有完整的理论体系和测算方法。为了使研究具有较好的理论传承性，本文在全要素生产率的分析框架下对碳生产率进行了系统研究。同时，充分考虑到工业部门在低碳经济研究领域中的重要性，本文的研究范围限定在了中国工业部门。
全文共分为7章。第1章主要对研究背景、研究意义、研究方法等进行了说明。第2章对生产率相关研究进行了回顾，主要从不同发展阶段稀缺性对象会不断改变的角度，对劳动生产率、资本生产率、资源生产率和碳生产率的相关研究进行了系统的回顾和评述，以期为后续研究提供坚实的理论基础。第3章在全要素生产率的分析框架下，对中国工业部门的碳生产率进行了测算，并对其收敛性进行了检验，为后续实证研究提供数据支持的同时，引出了中国工业部门碳生产率变化过程中存在的问题。第4章将碳生产率纳入经济增长的分析框架，推导出资源配置对碳生产率影响的理论模型，在此基础上，对劳动力、资本和二氧化碳排放空间等投入要素的配置与碳生产率之间的关系进行了实证研究，依此来考察资源配置对碳生产率的影响。第5章对中国工业部门的规模经济性进行了测度，并对规模经济与碳生产率之间的关系进行了实证研究，深层次挖掘了规模经济效应对碳生产率的影响机理。第6章首先对技术进步的内涵及技术进步的分类进行了回顾，然后分析了中国工业部门技术进步的特点，在此基础上对中国工业部门技术进步与碳生产率的关系进行了实证研究，依此来判断技术进步对碳生产率的影响。第7章根据研究结论提出了一系列提高中国工业部门碳生产率的政策建议。
本文研究结论表明：（1）在全要素生产率的研究框架下，基于方向性距离函数和数据包络分析方法所测度的碳生产率指数值相比传统意义下的单要素的碳生产率指数值要低，这意味着单要素的碳生产率指数确实高估了二氧化碳排放空间投入要素的效率，全要素生产率框架下的碳生产率指数更能真实反映中国工业部门的碳生产率的增长情况。经过进一步的分析发现，中国工业部门各两位数行业的碳生产率指数同时呈现出δ-收敛和绝对β=收敛。（2）二氧化碳排放空间要素配置比例的变化对全要素生产率框架下碳生产率的变化具有显著的负向影响；煤炭资源配置比例的变动对全要素生产率框架下的碳生产率的变动具有显著的负向影响。这意味着中国工业部门二氧化碳排放空间要素向碳生产率相对较高行业的再配置是形成中国工业部门碳生产率指数收敛和绝对
β收敛的重要原因；降低煤炭资源消费比例是提高中国工业部门各两位数行业碳生产率的一条重要途径。（3）中国工业部门整体上表现出规模不经济性，行政垄断造成的外部规模不经济对全要素生产率框架下碳生产率具有负向影响，而行业内规模效益的提高所反映的内部规模经济对全要素生产率框架下的碳生产率具有正向影响。（4）中国工业部门整体上存在技术进步，且技术进步是非体现的中性技术进步和资本体现型技术进步共同作用的结果，并且资本体现型技术进步对中国工业部门碳生产率具有正向的显著影响。
针对上述结论，本文提出了优化能源消费结构，优化部门产权结构，加大技术引进力度、提高装备制造水平等提高中国工业部门碳生产率的相应政策建议。
本文继承已有的国内外研究，紧密结合中国工业部门的特点，充分汲取了前人的研究成果，主要在以下方面做了一些创新性的探讨：（1）从一个新的视角出发，将碳生产率看做要素生产率的一种（即将二氧化碳排放空间作为一种投入要素），以经济增长因素分解理论为基础，对中国工业部门碳生产率进行了比较系统的分析；（2）在全要素生产率的分析框架下，对中国工业部门碳生产率进行了测度，与传统的单要素的碳生产率相比，本文的测度结果更能真实反映中国工业部门碳生产率的增长情况；（3）在碳生产率测度过程中，基于方向性距离函数的数据包络分析方法的应用，更能突出碳生产率的特点；（4）分别从资源配置、规模经济、技术进步三个方面，系统地研究了中国工业部门碳生产率的影响机制。（5）提出了一系列具有针对性和可操作性的提高中国工业部门碳生产率的相应政策建议。
With the acceleration of the negotiation process on climate change, developing countriesare facing potential pressure to reduce greenhouse gas emissions. China has always attachedgreat importance to the issues of global climate change and greenhouse gas emissions.Controlling greenhouse gas emissions have been a major strategy for economic and socialdevelopment. Against this background, the study on carbon-productivity has become a hotspot in the field of low-carbon economy.
The rise of the concept of carbon productivity was late, therefore, there was no completetheoretical system and calculation method on it. In order to enable the study have a goodtheoretical succession, the paper carried out a systematic study on the carbon productivityunder the framework of the total factor productivity. At the same time, taking into account theimportance of the industrial sector in the field of low-carbon economy, the scope of this paperwas limited to the China’s industrial sector.
There were seven chapters in this thesis. In chapter one, background, research methodswere described. In chapter two, the productivity-related research review and comments wereshowed mainly from the perspective that the scarcity of object would continue to change inthe different stages of development, this provided theoretical support for the followingresearch. In chapter three, the carbon productivity of Chinese industrial sector was calculatedunder the analytical framework of total factor productivity. The results provided data tosupport the subsequent empirical research. At the same time its convergence analysis wasconducted, which draw forth the problems in the change of China's carbon-productivity.Taking carbon-productivity into the analytical framework of economic growth, chapter fourderived a theoretical model of resource allocation effects to carbon-productivity. On this basis,the paper discussed the relationship among the configuration of the input factors of labor,capital and space of carbon dioxide emissions and carbon-productivity. In chapter five, thepaper measured the effect of economics of scale in China's industrial sector, and had anempirical research on the relationship between economics of scale and carbon-productivity;deep-level mined the mechanism of economies of scale on carbon-productivity. In chapter six,the author first made a review of the classification of technological progress and theconnotation of technical progress, and then analyzed the characteristics of the technologicalprogress of China's industrial sector, finally the paper determined the impact of technologicalprogress on carbon-productivity based on the empirical study result of the relationship between technological progress and the carbon-productivity of Chinese industrial sectors. Inchapter seven, the author put forward a series of policy recommendations to improve thecarbon-productivity of Chinese industrial sector according to the conclusions from chapterthree to chapter six.
This study concluded that:(1) the carbon-productivity index in the framework of totalfactor productivity based on directional distance function and data envelopment analysismethod was lower than the single elements carbon-productivity index based on the traditionalsense. This meant that the carbon-productivity index in the framework of total factorproductivity was a more true reflection of the carbon-productivity growth in China’s industrialsector. Based on the further analysis, the author found that the carbon productivity index ofthe Chinese industrial sector showed both δ-convergence and absolute β-convergence.(2)The changes of the proportion in carbon dioxide emissions space and coal resource hadsignificant negative impacts on the carbon-productivity growth. This meant that thereallocation of carbon dioxide emissions space was the important reason of the-convergence and absolute β-convergence of Chinese industrial sector carbon-productivity,reducing the consumption ratio of coal resources was an important way to increasecarbon-productivity of China's industrial sector.(3) China's industrial sector as a wholeshowed the diseconomies of scale. The external diseconomies of scale reflected byadministrative monopoly had the negative impact on carbon-productivity. The internaleconomics of scale reflected by the increased benefit of scale had a positive impact oncarbon-productivity.(4) China's industrial sector as a whole had technological progress;meanwhile the technological progress resulted from both the non-embodied neutraltechnological progress and capital-embodied technological progress. Capital-embodiedtechnological progress had a significant positive effect on the carbon-productivity of China'sindustrial sector.
Based on above mentioned conclusions, this paper proposed some corresponding policyrecommendations to improve the carbon-productivity of China's industrial sector, such asoptimizing energy consumption structure, optimizing the structure of property rights,increasing the introduction of technology, improving the technical level of the equipmentmanufacturing industry, et al.
The innovative explorations of this paper were mainly on the following aspects:
(1) Provided a new research perspective. The author regarded the carbon-productivity asfactor productivity, and made a systematic analysis of the carbon productivity on the basis of decomposition theory of economic growth factor;(2) Had a study under the framework oftotal factor productivity. The carbon-productivity index in the framework of total factorproductivity was lower than the single elements carbon-productivity index based on thetraditional sense, so it was a more true reflection of the carbon-productivity growth of theChinese industrial sector.(3) Applied the directional distance function and data envelopmentanalysis method to measure the carbon-productivity. Because they could highlight thecharacteristics of the carbon-productivity;(4) Conducted a systematic study on the impactmechanism of carbon-productivity of China’s industrial sector in three aspects: allocation ofresources, economies of scale, technological progress,(5) Proposed a series of targeted andoperable appropriate policy recommendations to improve carbon-productivity of China'sindustrial sector.
碳生产率概念的提出时间较晚，尚没有完整的理论体系和测算方法。为了使研究具有较好的理论传承性，本文在全要素生产率的分析框架下对碳生产率进行了系统研究。同时，充分考虑到工业部门在低碳经济研究领域中的重要性，本文的研究范围限定在了中国工业部门。
全文共分为7章。第1章主要对研究背景、研究意义、研究方法等进行了说明。第2章对生产率相关研究进行了回顾，主要从不同发展阶段稀缺性对象会不断改变的角度，对劳动生产率、资本生产率、资源生产率和碳生产率的相关研究进行了系统的回顾和评述，以期为后续研究提供坚实的理论基础。第3章在全要素生产率的分析框架下，对中国工业部门的碳生产率进行了测算，并对其收敛性进行了检验，为后续实证研究提供数据支持的同时，引出了中国工业部门碳生产率变化过程中存在的问题。第4章将碳生产率纳入经济增长的分析框架，推导出资源配置对碳生产率影响的理论模型，在此基础上，对劳动力、资本和二氧化碳排放空间等投入要素的配置与碳生产率之间的关系进行了实证研究，依此来考察资源配置对碳生产率的影响。第5章对中国工业部门的规模经济性进行了测度，并对规模经济与碳生产率之间的关系进行了实证研究，深层次挖掘了规模经济效应对碳生产率的影响机理。第6章首先对技术进步的内涵及技术进步的分类进行了回顾，然后分析了中国工业部门技术进步的特点，在此基础上对中国工业部门技术进步与碳生产率的关系进行了实证研究，依此来判断技术进步对碳生产率的影响。第7章根据研究结论提出了一系列提高中国工业部门碳生产率的政策建议。
本文研究结论表明：（1）在全要素生产率的研究框架下，基于方向性距离函数和数据包络分析方法所测度的碳生产率指数值相比传统意义下的单要素的碳生产率指数值要低，这意味着单要素的碳生产率指数确实高估了二氧化碳排放空间投入要素的效率，全要素生产率框架下的碳生产率指数更能真实反映中国工业部门的碳生产率的增长情况。经过进一步的分析发现，中国工业部门各两位数行业的碳生产率指数同时呈现出δ-收敛和绝对β=收敛。（2）二氧化碳排放空间要素配置比例的变化对全要素生产率框架下碳生产率的变化具有显著的负向影响；煤炭资源配置比例的变动对全要素生产率框架下的碳生产率的变动具有显著的负向影响。这意味着中国工业部门二氧化碳排放空间要素向碳生产率相对较高行业的再配置是形成中国工业部门碳生产率指数收敛和绝对
β收敛的重要原因；降低煤炭资源消费比例是提高中国工业部门各两位数行业碳生产率的一条重要途径。（3）中国工业部门整体上表现出规模不经济性，行政垄断造成的外部规模不经济对全要素生产率框架下碳生产率具有负向影响，而行业内规模效益的提高所反映的内部规模经济对全要素生产率框架下的碳生产率具有正向影响。（4）中国工业部门整体上存在技术进步，且技术进步是非体现的中性技术进步和资本体现型技术进步共同作用的结果，并且资本体现型技术进步对中国工业部门碳生产率具有正向的显著影响。
针对上述结论，本文提出了优化能源消费结构，优化部门产权结构，加大技术引进力度、提高装备制造水平等提高中国工业部门碳生产率的相应政策建议。
本文继承已有的国内外研究，紧密结合中国工业部门的特点，充分汲取了前人的研究成果，主要在以下方面做了一些创新性的探讨：（1）从一个新的视角出发，将碳生产率看做要素生产率的一种（即将二氧化碳排放空间作为一种投入要素），以经济增长因素分解理论为基础，对中国工业部门碳生产率进行了比较系统的分析；（2）在全要素生产率的分析框架下，对中国工业部门碳生产率进行了测度，与传统的单要素的碳生产率相比，本文的测度结果更能真实反映中国工业部门碳生产率的增长情况；（3）在碳生产率测度过程中，基于方向性距离函数的数据包络分析方法的应用，更能突出碳生产率的特点；（4）分别从资源配置、规模经济、技术进步三个方面，系统地研究了中国工业部门碳生产率的影响机制。（5）提出了一系列具有针对性和可操作性的提高中国工业部门碳生产率的相应政策建议。
With the acceleration of the negotiation process on climate change, developing countriesare facing potential pressure to reduce greenhouse gas emissions. China has always attachedgreat importance to the issues of global climate change and greenhouse gas emissions.Controlling greenhouse gas emissions have been a major strategy for economic and socialdevelopment. Against this background, the study on carbon-productivity has become a hotspot in the field of low-carbon economy.
The rise of the concept of carbon productivity was late, therefore, there was no completetheoretical system and calculation method on it. In order to enable the study have a goodtheoretical succession, the paper carried out a systematic study on the carbon productivityunder the framework of the total factor productivity. At the same time, taking into account theimportance of the industrial sector in the field of low-carbon economy, the scope of this paperwas limited to the China’s industrial sector.
There were seven chapters in this thesis. In chapter one, background, research methodswere described. In chapter two, the productivity-related research review and comments wereshowed mainly from the perspective that the scarcity of object would continue to change inthe different stages of development, this provided theoretical support for the followingresearch. In chapter three, the carbon productivity of Chinese industrial sector was calculatedunder the analytical framework of total factor productivity. The results provided data tosupport the subsequent empirical research. At the same time its convergence analysis wasconducted, which draw forth the problems in the change of China's carbon-productivity.Taking carbon-productivity into the analytical framework of economic growth, chapter fourderived a theoretical model of resource allocation effects to carbon-productivity. On this basis,the paper discussed the relationship among the configuration of the input factors of labor,capital and space of carbon dioxide emissions and carbon-productivity. In chapter five, thepaper measured the effect of economics of scale in China's industrial sector, and had anempirical research on the relationship between economics of scale and carbon-productivity;deep-level mined the mechanism of economies of scale on carbon-productivity. In chapter six,the author first made a review of the classification of technological progress and theconnotation of technical progress, and then analyzed the characteristics of the technologicalprogress of China's industrial sector, finally the paper determined the impact of technologicalprogress on carbon-productivity based on the empirical study result of the relationship between technological progress and the carbon-productivity of Chinese industrial sectors. Inchapter seven, the author put forward a series of policy recommendations to improve thecarbon-productivity of Chinese industrial sector according to the conclusions from chapterthree to chapter six.
This study concluded that:(1) the carbon-productivity index in the framework of totalfactor productivity based on directional distance function and data envelopment analysismethod was lower than the single elements carbon-productivity index based on the traditionalsense. This meant that the carbon-productivity index in the framework of total factorproductivity was a more true reflection of the carbon-productivity growth in China’s industrialsector. Based on the further analysis, the author found that the carbon productivity index ofthe Chinese industrial sector showed both δ-convergence and absolute β-convergence.(2)The changes of the proportion in carbon dioxide emissions space and coal resource hadsignificant negative impacts on the carbon-productivity growth. This meant that thereallocation of carbon dioxide emissions space was the important reason of the-convergence and absolute β-convergence of Chinese industrial sector carbon-productivity,reducing the consumption ratio of coal resources was an important way to increasecarbon-productivity of China's industrial sector.(3) China's industrial sector as a wholeshowed the diseconomies of scale. The external diseconomies of scale reflected byadministrative monopoly had the negative impact on carbon-productivity. The internaleconomics of scale reflected by the increased benefit of scale had a positive impact oncarbon-productivity.(4) China's industrial sector as a whole had technological progress;meanwhile the technological progress resulted from both the non-embodied neutraltechnological progress and capital-embodied technological progress. Capital-embodiedtechnological progress had a significant positive effect on the carbon-productivity of China'sindustrial sector.
Based on above mentioned conclusions, this paper proposed some corresponding policyrecommendations to improve the carbon-productivity of China's industrial sector, such asoptimizing energy consumption structure, optimizing the structure of property rights,increasing the introduction of technology, improving the technical level of the equipmentmanufacturing industry, et al.
The innovative explorations of this paper were mainly on the following aspects:
(1) Provided a new research perspective. The author regarded the carbon-productivity asfactor productivity, and made a systematic analysis of the carbon productivity on the basis of decomposition theory of economic growth factor;(2) Had a study under the framework oftotal factor productivity. The carbon-productivity index in the framework of total factorproductivity was lower than the single elements carbon-productivity index based on thetraditional sense, so it was a more true reflection of the carbon-productivity growth of theChinese industrial sector.(3) Applied the directional distance function and data envelopmentanalysis method to measure the carbon-productivity. Because they could highlight thecharacteristics of the carbon-productivity;(4) Conducted a systematic study on the impactmechanism of carbon-productivity of China’s industrial sector in three aspects: allocation ofresources, economies of scale, technological progress,(5) Proposed a series of targeted andoperable appropriate policy recommendations to improve carbon-productivity of China'sindustrial sector.
引文
①参见赵国浩，裴卫东，张东明，《中国煤炭工业与可持续发展》，中国物价出版社，2000。
[1] Eric Beinhocker, et al, The carbon productivity challenge:Curbing climate change andsustaining economic growth[R].2008, McKinsey Climate Change Special Initiative.
[2]何建坤，苏明山.应对全球气候变化下的碳生产率分析[J].中国软科学，2009(10):p.42-47,147.
[3] Lynn Price, E.W., Nathan Martin, et al, China’s industrial sector in an internationalcontext[R].2000, Lawrence Berkeley National Laboratory.
[4]白仲林，张晓峒.面板数据的计量经济分析[M].天津:南开大学出版社，2009.
[5] Yokobori.K., K.Y., Environment, Energy and Economy: Strategies forSustainability[M].1999: Delhi Bookwell Publications.
[6]谌伟，诸大建，白竹岚.上海市工业碳排放总量和碳生产率关系[J].中国人口资源与环境，2010.20(9): p.24-29.
[7]唐.埃思里奇（美）著，朱钢译.应用经济学研究方法论[M].北京:经济科学出版社，1998.
[8]约翰·伊特维尔，莫里·米尔盖特，彼得·纽曼主编.新帕尔格雷夫经济学大辞典（中译本）[M].北京:经济科学出版社，1996，p.84.
[9]马歇尔.《经济学原理》（上册）[M].商务印书馆，1981.
[10]张雄辉.技术进步、技术效率对经济增长贡献的研究[D].山东大学博士学位论文，2010.4.10: p.20.
[11]吴斐丹，张草纫.魁奈经济著作选[M].北京:商务印书馆，1979.
[12] Kaplan, R.c.R., Cost and Effect–Using Integrated cost system to Drive Profitabilityand Performance[M].1998, Boston: Harvard business School Press.
[13] Moseng.B, a.R.A. Success Factor in the Productivity Process[C]. in10th worldProductivity congress.2001.
[14] Sharpe, A., Productivity Concepts, Trends and Prospects: An Overview[Z]. AndrewSharpe text,2002.11.
[15] Denison, E.F., The Sources of economic growth in the United States and thealternatives before us[M].1962, New York: Committee for Economic Development.
[16] Grillches, J.D.W.a.Z., The explanation of productivity change[J]. Review of EconomicStudies,1967(34).
[17] Aigner, D., C. A. K. Lovell, and P. Schmidt, Formulation and estimation of stochasticfrontier production function models[J]. Journal of Econometrics,1977(6): p.21-37.
[18] Meeusen, W., and J. van den Broeck, Efficiency estimation from Cobb–Douglasproduction functions with composed error[J]. International Economic Review,1977(18): p.435-444.
[19] Battese, G.E., and T. J. Coelli, Frontier production functions, technical efficiency andpanel data: With application to paddy farmers in India[J]. Journal of ProductivityAnalysis,1992(3): p.153-169.
[20] F re R., S.Grosskopf and C.A.Lovell, Production Frontiers[M].1994, CambridgeUniversity Press: Cambridge.
[21] Timothy J. Coelli等著，王忠玉译.效率与生产率分析引论（第二版）[M].中国人民大学出版社，2008.
[22] Charnes A, C.W.W., Phodes E, Measuring the Efficiency of DMU[J]. EuropeanJournal of Operational Researeh,1978.2(6): p.429-444.
[23] Banker.R.D, Estimating Most Productive Scale Size Using Data EnvelopmentAnalysis[J]. European Journal of Operational Research,1984.17(1): p.35-44.
[24] Charnes.A, C.W.W., Phodes.E, Invariant multiplicative efficiency and piecewiseCobb-Douglas envelopment[J]. Ops Res Lett,1985.2(3): p.101-103.
[25] Charnes.A, C.W., Huang.Z.M,Sun.D.B, Polyhedral cone-ratio DEA models with anillustrative application to large commercial banks[J]. Journal of Econometrics1990(46): p.73-91.
[26] Chames.A, C.W.W., Huang.Z.M, SunD.B., Polyhedral cone-ratio DEA models with anillustrative application to large commercial banks[J]. Journal of Econometrics,1990(46): p.73-91.
[27] Chames.A, C.W.W., Wei.Q.L, Huang.Z.M, Cone ratio data envelopment analysis andmulti-objective programming[J]. Intenational Journal of Systems Science,1989(20): p.1099-1118.
[28] Charnes A, C.W.W., Wei QL, A Semi-infinite Multicriteria Progamming Approach toData Envelopment Analysis with Infinitely Many Decision Making Units[R].1986,The University of Texas at Austin, Center for Cybernetic studies Report CCS551:Austin.
[29] Yun.Y.B，Nakayama.H, T.T., A generalized model for data envelopment analysis[J].European Journal of operational Research,2004(157): p.87-105.
[30] Douglas W.Caves, L.R.C.a.W.E.D., The economic theory of index numbers and themeasurement of input, output and productivity [J]. Econometricia,1982.50(6): p.1393-1414.
[31] F re R., S. Grosskopf, Malmquist Indexes and Fisher Ideal Indexes[J]. The EconomicJournal,1992.102(410): p.158-60.
[32] F re R., S. Grosskopf, Intertemporal Production Frontiers: With Dynamic DEA[M].1996, Kluwer. Academic Publishers: Boston.
[33] F re R., S. Grosskopf, Norris M., Productivity growth, technical progress, andefficiency change in industrialized countries[J]. American Economic Review,1997a.87(5): p.1040-1043.
[34] Kendrick, J.W., ProduetivityTrends in the United State[M].1961, Princeton: PrincetonUniversity Press.
[35] Stephen L.Parente, E.C.P., Barriers to Technology Adoption and Development[J]. theJournal of Political Economy,1994.102(2): p.298-321.
[36] Taylor, M.P.a.L.S., The behavior of real exchange rates during the post-Bretton Woodsperiod[J]. Journal of International Economics,1998.48: p.281-312.
[37] Daron Acemoglu, J.A., How Large Are Human-Capital Externalities? Evidence fromCompulsory Schooling Laws[R]. NBER Macroeconomics Annual,2000.15: p.9-59.
[38] Robert J. Barro, R.M.M., Religion and Economic Growth[R].2003, NBER WorkingPapers.
[39] Laura Alfaroa, A.C., Sebnem Kalemli-Ozcanc,Selin Sayekd, FDI and economicgrowth: the role of local financial markets[J]. Journal of International Economics,2004.64: p.89-112.
[40] Romer, P.M., Endogenous Technological Change[J]. The Journal of Political Economy,1990.98(5): p.71-102.
[41] Grossman, G.a.E.H., Innovation and Growth in the Global Economy[M].1991,Cambridge: MIT Press.
[42] Anusua Datta, H.M., Endogenous Imitation and Technology Absorption in a Model ofNorth-South Trade[J]. International Economic Journal,2006.20: p.431-459.
[43] Keller, W., International Technology Diffusion[R].2001, NBER Working Papers.
[44] Jess Benhabib, M.M.S., The Role of Human Capital in Economic Development:Evidence from Aggregate Cross-Country Data[J]. Journal of Monetary Economics,1994.34: p.143-173.
[45] Jess Benhabib, M.M.S., Human Capital and Technology Diffusion[C], in.Aghionand Durlanf Handbook of Eeonomic Growth，4ed.2005:.Amsterdam: NorthHolland.
[46] E. Borensztein, J.D.G., J-W. Lee, How does foreign direct investment affect economicgrowth?[J]. Journal of International Economics,1998.45: p.115-135.
[47] Miller, S.M., Upadhyay，P.Mukti, The Effects of Openness, Trade Orientation andHuman Capital on Total Factor Productivity[J]. Journal of Development Economics,2000.63: p.399-423.
[48] Guifang Yang, K.E.M., Intellectual Property Rights, Licensing, and Innovation[R],World Bank Policy Research Working Paper.
[49]李京文，钟学义.中国生产率分析前沿[M].北京:社会科学文献出版社，1998.
[50]张军，施少华.中国经济全要素生产率变动：1952-1998[J].世界经济文汇，2003(2):p.17-24.
[51]彭国华.中国地区收入差距、全要素生产率及其收敛分析[J].经济研究，2005(9):p.19-29.
[52]郭庆旺，贾俊雪.中国全要素生产率的估算：1979—2004[J].经济研究，2005(6):p.51-60.
[53]田银华，贺胜兵，胡石其.环境约束下地区全要素生产率增长的再估算：1998—2008[J].中国工业经济，2011(1): p.47-57.
[54]颜鹏飞，王兵.技术效率、技术进步与生产率增长:基于DEA的实证分析[J].经济研究，2004(12): p.55-65.
[55]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): p.19-32.
[56]周燕，蔡宏波.中国工业行业全要素生产率增长的决定因素：1996-2007[J].北京师范大学学报(社会科学版)，2011(1): p.133-141.
[57]曹泽，李东，朱达荣.中国区域全要素生产率增长的R&D贡献分析[J].系统工程，2011.29(1): p.57-62.
[58]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): p.55-66.
[59]陶长琪，齐亚伟.中国全要素生产率的空间差异及其成因分析[J].数量经济技术经济研究，2010(1): p.19-32.
[60]陈涛涛.影响中国外商直接投资溢出效应的行业特征[J].中国社会科学，2003(4):p.33-43.
[61]赖明勇，包群，彭水军，张新.外商直接投资与技术外溢：基于吸收能力的研究[J].经济研究，2005(8): p.95-105.
[62]易先忠，张亚斌.技术差距、知识产权保护与后发国技术进步[J].数量经济技术经济研究，2006(10): p.111-121.
[63]路江涌.外商直接投资对内资企业效率的影响和渠道[J].经济研究，2008(6): p.95-106.
[64]蒋殿春，张宇.经济转型与外商直接投资技术溢出效应[J].经济研究，2008(7): p.26-38.
[65]沈坤荣，李剑.企业间技术外溢的测度[J].经济研究，2009(4): p.77-89.
[66]舒元，才国伟.我国省际技术进步及其空间扩散分析[J].经济研究，2007(6): p.106-118.
[67]邹薇，代谦.技术模仿、人力资本积累与经济赶超[J].中国社会科学，2003(5): p.26-38.
[68]许和连，亓朋，祝树金.贸易开放度、人力资本与全要素生产率[J].世界经济，2006(12): p.3-10.
[69]魏梅.区域全要素生产率影响因素及效率收敛分析[J].统计与决策，2008(12): p.77-79.
[70]魏下海.贸易开放、人力资本与中国全要素生产率——基于分位数回归方法的经验研究[J].数量经济技术经济研究，2009(7): p.61-72.
[71]高凌云，王洛林.进口贸易与工业行业全要素生产率[J].经济学（季刊），2010.9(2):p.391-414.
[72]李玉红，王皓，郑玉歆.企业演化：中国工业生产率增长的重要途径[J].经济研究，2008(6): p.12-24.
[73]李国璋，刘津汝.产权制度、金融发展和对外开放对全要素生产率增长贡献的经验研究[J].经济问题，2011(2): p.4-9.
[74]关兵.出口地理方向与我国全要素生产率增长[J].国际贸易问题，2010(11): p.13-21.
[75]关兵.出口商品结构与我国全要素生产率增长[J].山西财经大学学报，2010.32(7):p.1-9.
[76]邹明.我国对外直接投资对国内全要素生产率的影响[J].北京工业大学学报（社会科学版），2008.8(6): p.30-35.
[77]姚洋.非国有经济成分对我国工业企业技术效率的影响[J].经济研究，1998(12): p.29-35.
[78]涂正革，肖耿.转轨时期大中型工业企业全要素生产率增长的行业特征[J].统计与决策，2005(12): p.64-65.
[79]谢千里，罗斯基，张轶凡.中国工业生产率的增长与收敛[J].经济学（季刊），2008.7(3): p.209-826.
[80]郑兵云，陈圻.转型期中国工业全要素生产率与效率[J].数理统计与管理，2010.29(3): p.480-489.
[81]诸大建，周建亮.循环经济理论与全面小康社会[J].同济大学学报（社会科学版），2003.14(3): p.107-112.
[82] Pearce, D., Resource Productivity: Outsider view of the state of play and what mightneed to be done[R].2001, University of London.
[83] Green Alliance, Building a bright green economy an agenda fou action on resourceproductivity[R].2002: Green Alliance.
[84] Hendrik A. Verfaillie, R.B., Measuring eco-efficiency[Z].2000.06. p.7.
[85] Annik Magerholm Fet, O.M., Industrial Ecology and Eco-Efficiency——Anintroduction to the concepts[R].2002: Vilnius, Lithuania. p.3.
[86] Micheal Porter, E., Class van der Linde, Green and Competitiveness Ending theStalemate[J]. Harvard Business Review,1995.9-10.
[87]迈克尔．波特[美]著，高登第，李明轩译.竞争论[M].北京:中信出版社，2003.
[88] DETR, Achieving a borer quality of life-Review of progress towards a sustainabledevelopment[R]. Government Annual Report,2000.
[89] Hoh.H, Scoer.K, Seibel.S, Eco-Efficiency Indicators in German EnvironmentalEconomic Accounting[Z]. Federal Statistical Office,Germany,2001.
[90]诸大建，朱远.生态效率与循环经济[J].复旦大学学报（社科版），2005(2): p.60-66.
[91]邱寿丰，诸大建.我国生态效率指标设计和应用[J].科学管理研究，2007(1): p.20-24.
[92]杨永华，钱斌华，王明兰.经济增长中的资源生产率分析[J].青岛行政学院学报，2005(3): p.16-18.
[93]杨永华,诸大建,胡冬洁.资源生产率视角的经济增长模型分析[J].广东行政学院学报，2007.19(2): p.59-62.
[94] Won-kyu, K., Current Issues and Implications of Korea’s Carbon Productivity[N].http://kiet.re.kr/UpFile/newsbrief/1266304157908.pdf,Jan,2010.,2010.
[95]刘国平，曹莉萍.基于福利绩效的碳生产率研究[J].中国软科学，2011.25(1): p.71-74.
[96]魏梅，曹明福，江金荣.生产中碳排放效率长期决定及其收敛性分析[J].数量经济技术经济研究，2010(9): p.43-52.
[97]潘家华，张丽峰.我国碳生产率区域差异性研究[J].中国工业经济，2011(5): p.47-57.
[98]袁富华.低碳经济约束下的中国潜在经济增长[J].经济研究，2010(8): p.79-89,154.
[99]顾乾屏，张棋，彭淑华等.商业银行分支机构效率评价的参数与非参数方法比较研究[J].数理统计与管理，2007.26(4): p.676-684.
[100] Chambers R. G, C.Y., Fare R, Benefitand Distance Functions [J]. Journal of EconomicTheory,1996.70(2): p.407-419.
[101] Baumol, W., Productivity growth, convergence and welfare: the long-run data show[J].American Economic Reviews,1986: p.1072-1085.
[102] Barro, R.J., Sala-i-Martin, X, Convergence across states and regions[J]. BrookingsPapers on Economic Activity,1991.22(1): p.107-182.
[103]刘强.中国经济增长的收敛性分析[J].经济研究，2001(6).
[104] Anderson, T.W.a.C.H., Estimation of dynamic models with error components[J].Journal of the American Statistical Association,1981(76): p.598-606.
[105] Ahn, S.C.a.P.S., Efficient estimation of models for dynamic panel data[J]. Journal ofEconometrics,1995(68): p.5-27.
[106] Arellano M., S.B., Some Tests of Specification for Panel Data:Monte Carlo Evidenceand an Application to Employment Equations[J]. Review of Economic Studies,1991.58: p.277-297.
[107] Blundell R., S.B., Initial Conditions and Moment Restrictions in Dynamic Panel DataModels[J]. Journal of Econometrics,1998.87: p.115-143.
[108]王亮.经济增长收敛假说的存在性检验与形成机制研究[D].吉林大学博士学位论文，2010.6.
[109] Pesaran, H., A simple panel unit root test in the presence of cross-sectiondependence[J]. Journal of Applied Econometrics,2007.22(2): p.265-312.
[110] Im K.S., M.H.P., Y. Shin, Testing for Unit Roots in Heterogeneous Panels[J]. Journalof Econometrics,2003.115: p.53-74.
[111] Maddala, G.S.a.W., Shaowen, A Comparative Study of Unit Root Tests With PanelData and A New Simple Test[J]. Oxford Bulletin of Economics and Statistics,1999.61:p.631-652.
[112] Levin, A., Lin, Chien-Fu and Chia-Shang James Chu, Unit Root Tests in Panel Data:Asymptotic and Finite Sample Properties[J]. Journal of Econometrics,2002.108(1): p.1-24.
[113]傅永东.我国农村新型合作经济组织发展模式研究[D].国防科技大学博士学位论文，2006.
[114]施蔚.江苏木材加工产业的规模经济问题研究[D].南京林业大学博士学位论文，2007.
[115]楚序平.中国钢铁产业规模经济研究[D].南开大学博士学位论文，2009.
[116]罗四维.基于DEA模型的商业银行规模经济研究[D].湖南大学硕士学位论文，2003.
[117]刘明.基于新竞争(力)视角的企业规模经济性研究[D].天津大学博士学位论文，2007.
[118]乔治.J.施蒂格勒.产业组织和政府管制[M].上海:上海三联书店，1989.
[119]张如海.规模经济：理论辨析和现实思考[J].经济问题，2001(1): p.8-11.
[120] Solow, R.M., Technical change and the Aggregate production function[J]. Review ofEconomics and Statistics,1957.39(8): p.312-320.
[121] Hicks, J., The Theory of Wages[M].1932,2nd ed.,1963, London: Macmillan.
[122] Solow, R.M., Investment and Technical Progress[M], ed. S.K. Kenneth J. Arrow, andPatrick Suppes.1960, Stanford: Stanford University.
[123] Phelps, E., The New View of Investment[J]. Quarterly Journal of Economics,1962.76(4): p.548-567.
[124]黄先海，刘毅群.物化性技术进步与我国工业生产率增长[J].数量经济技术经济研究，2006(4): p.52-60.
[125] Szirmai, M.P.T.R.v.d.K., Measuring Embodied Technological Change in IndonesianTextiles: The Core Machinery Approach[J] Journal of Development Studies,2002.39(2): p.155-177.
[126] R.Boucekkine, F.d.R.a.O.L., Obsolescence and Modernization in the GrowthProcess[J]. Journal of Development Economics,2005.77: p.153-17.
[127]宋冬林，王林辉，董直庆.资本体现式技术进步及其对经济增长的贡献率[J].中国社会科，2011(2): p.91-106.
[128]赵玉林.创新经济学[M].中国经济出版社，2006.
[129]傅东平.中国生产率的变化及其影响因素研究[D].华中科技大学博士学位论文，2009.
[130] MacDougall, G.D.A., The Benefits and Costs of Private Investment from Abroad:ATheoretical Approach[J]. Economic Record,1962.36(73): p.13-15.
[131] Kokko, A., Foreign direct investment, host country characteristics, and Spillovers[M].1992, The Economics Research Institute: Stockholm.
[132]沈坤荣，耿强.外国直接投资、技术外溢与内生经济增长[J].中国社会科学，2001(5): p.82-93.
[133]何洁.外商直接投资对中国工业部门外溢效应的进一步精确量化[J].世界经济，2000(12): p.29-36.
[134]易行健，李良生.市场是否可以换来技术进步?——来自广东省工业部门面板数据的实证分析[J].南方经济，2007(7): p.71-82.
[135]李小平，朱钟棣.国际贸易、R&D溢出和生产力增长[J].经济研究，2006(2): p.31-43.
[136]李小平，卢现祥，朱钟棣.国际贸易、技术进步和中国工业行业的生产率增长[J].经济学（季刊），2008.7(2): p.549-564.
[137]许培源，高伟生.国际贸易对中国技术创新能力的溢出效应[J].财经研究，2009.35(9): p.70-79.
[138]易纲，樊纲，李岩.关于中国经济增长与全要素生产率的理论思考[J].经济研究，2003(8).
[139]黄先海，刘毅群.设备投资、体现型技术进步与生产率增长:跨国经验分析[J].世界经济，2008(4): p.47-61.
[140]林毅夫，任若恩.东亚经济增长模式相关争论的再探讨[J].经济研究，2007(8): p.4-11.
[141]赵志耘，吕冰洋，郭庆旺，贾俊雪.资本积累与技术进步的动态融合:中国经济增长的一个典型事实[J].经济研究，2007(11): p.18-31.
[142]王玺，张勇.关于中国技术进步水平的估算———从中性技术进步到体现式技术进步[J].中国软科学，2010(4): p.155-163.
[143] Griliches, Z., R&D and productivity Slowdown[J]. American Economic Review,1980a.70(1): p.343-348.
[144] Griliches, Z., Productivity R&D and Basic Research at the Firm Level in the1970[J].American Eeonomic Review,1986.76(6): p.141-154.
[145] Griliches, Z., R&D and Productivity[M].1998, Chicago: University of Chicago Press.
[146] Suzuki, G.A.a.K., R&D Capital, Rate of Return on R&D Investment and Spillover ofR&D in Japanese Manufacturing Industries[J]. Review of Eeonomics and Statistics,1989.71: p.555-564.
[147] Coe, D.S.a.E.H., International R&D Spillover[J]. European Economic Review,1995.39(5): p.859-887.
[148]朱平芳，徐伟民.政府的科技激励政策对大中型工业企业R&D投入及其专利产出的影响[J].经济研究，2003(6): p.45-53.
[149]陈师，赵磊.中国经济周期特征与技术变迁——中性、偏向性抑或投资专有技术变迁[J].数量经济技术经济研究，2009(4): p.19-32.
[150]董直庆，王林辉.资本体现式技术进步与经济增长周期波动关联效应[J].求是学刊，2011.38(2): p.63-68.
[151]田立新，孙梅.能源供需系统分析[M].北京:科学出版社，2011.
[152]张国宝.中国能源发展报告2010[M].北京:经济科学出版社，2010.
[153]赵国浩，高文静.山西省煤炭工业和装备制造业转型发展将迎来新机遇[J].现代工业经济和信息化，2011(1): p.43-45.
[154]翟燕妮，赵国浩.基于循环经济的煤炭工业发展模式研究[C].和谐发展与系统工程——中国系统工程学会第十五届年会论文集.2008:江西，南昌. p.57-61.
[155]赵国浩，裴卫东，张东明.中国煤炭工业与可持续发展[M].北京:中国物价出版社，2000.
[156]陈文颖，高鹏飞，何建坤.用MARKAL-MACRO模型研究碳减排对中国能源系统的影响[J].清华大学学报(自然科学版)，2004(2):342-346.
[157]赵国浩，阎世春.煤炭工业可持续发展研究[M].北京:经济管理出版社，2008.
[158]魏一鸣，刘翠兰，范英，等.中国能源报告2008：碳排放研究[M].北京:科学出版社，2008.
[159]张金锁，邹绍辉.基于实物期权的煤炭资源投资决策方法研究[J].中国矿业，2009(9):21-26.
[160]闫新华，赵国浩.经济增长与环境污染的VAR模型分析[J].经济问题，2009(6):59-62
[161]范英，张晓兵，朱磊.基于多目标规划的中国二氧化碳减排的宏观经济成本估计[J].气候变化研究进展，2010(2):130-135.
[162]王群伟，周德群，沈璇，张力菠.我国全要素能源效率的测度与分析[J].管理评论，2010(3):37-43.
[163]廖华，魏一鸣.世界能源消费的差异性与不平衡性及其变化研究[J].中国软科学，2010(10):6-14
[164]李玮，赵国浩.基于环境约束的工业行业结构优化研究[J].中国人口资源环境，2010.20(12):129-133
[165]张鹏伟，李嫣怡主编. Stata统计分析与应用[M].北京：电子工业出版社，2011.
[1] Eric Beinhocker, et al, The carbon productivity challenge:Curbing climate change andsustaining economic growth[R].2008, McKinsey Climate Change Special Initiative.
[2]何建坤，苏明山.应对全球气候变化下的碳生产率分析[J].中国软科学，2009(10):p.42-47,147.
[3] Lynn Price, E.W., Nathan Martin, et al, China’s industrial sector in an internationalcontext[R].2000, Lawrence Berkeley National Laboratory.
[4]白仲林，张晓峒.面板数据的计量经济分析[M].天津:南开大学出版社，2009.
[5] Yokobori.K., K.Y., Environment, Energy and Economy: Strategies forSustainability[M].1999: Delhi Bookwell Publications.
[6]谌伟，诸大建，白竹岚.上海市工业碳排放总量和碳生产率关系[J].中国人口资源与环境，2010.20(9): p.24-29.
[7]唐.埃思里奇（美）著，朱钢译.应用经济学研究方法论[M].北京:经济科学出版社，1998.
[8]约翰·伊特维尔，莫里·米尔盖特，彼得·纽曼主编.新帕尔格雷夫经济学大辞典（中译本）[M].北京:经济科学出版社，1996，p.84.
[9]马歇尔.《经济学原理》（上册）[M].商务印书馆，1981.
[10]张雄辉.技术进步、技术效率对经济增长贡献的研究[D].山东大学博士学位论文，2010.4.10: p.20.
[11]吴斐丹，张草纫.魁奈经济著作选[M].北京:商务印书馆，1979.
[12] Kaplan, R.c.R., Cost and Effect–Using Integrated cost system to Drive Profitabilityand Performance[M].1998, Boston: Harvard business School Press.
[13] Moseng.B, a.R.A. Success Factor in the Productivity Process[C]. in10th worldProductivity congress.2001.
[14] Sharpe, A., Productivity Concepts, Trends and Prospects: An Overview[Z]. AndrewSharpe text,2002.11.
[15] Denison, E.F., The Sources of economic growth in the United States and thealternatives before us[M].1962, New York: Committee for Economic Development.
[16] Grillches, J.D.W.a.Z., The explanation of productivity change[J]. Review of EconomicStudies,1967(34).
[17] Aigner, D., C. A. K. Lovell, and P. Schmidt, Formulation and estimation of stochasticfrontier production function models[J]. Journal of Econometrics,1977(6): p.21-37.
[18] Meeusen, W., and J. van den Broeck, Efficiency estimation from Cobb–Douglasproduction functions with composed error[J]. International Economic Review,1977(18): p.435-444.
[19] Battese, G.E., and T. J. Coelli, Frontier production functions, technical efficiency andpanel data: With application to paddy farmers in India[J]. Journal of ProductivityAnalysis,1992(3): p.153-169.
[20] F re R., S.Grosskopf and C.A.Lovell, Production Frontiers[M].1994, CambridgeUniversity Press: Cambridge.
[21] Timothy J. Coelli等著，王忠玉译.效率与生产率分析引论（第二版）[M].中国人民大学出版社，2008.
[22] Charnes A, C.W.W., Phodes E, Measuring the Efficiency of DMU[J]. EuropeanJournal of Operational Researeh,1978.2(6): p.429-444.
[23] Banker.R.D, Estimating Most Productive Scale Size Using Data EnvelopmentAnalysis[J]. European Journal of Operational Research,1984.17(1): p.35-44.
[24] Charnes.A, C.W.W., Phodes.E, Invariant multiplicative efficiency and piecewiseCobb-Douglas envelopment[J]. Ops Res Lett,1985.2(3): p.101-103.
[25] Charnes.A, C.W., Huang.Z.M,Sun.D.B, Polyhedral cone-ratio DEA models with anillustrative application to large commercial banks[J]. Journal of Econometrics1990(46): p.73-91.
[26] Chames.A, C.W.W., Huang.Z.M, SunD.B., Polyhedral cone-ratio DEA models with anillustrative application to large commercial banks[J]. Journal of Econometrics,1990(46): p.73-91.
[27] Chames.A, C.W.W., Wei.Q.L, Huang.Z.M, Cone ratio data envelopment analysis andmulti-objective programming[J]. Intenational Journal of Systems Science,1989(20): p.1099-1118.
[28] Charnes A, C.W.W., Wei QL, A Semi-infinite Multicriteria Progamming Approach toData Envelopment Analysis with Infinitely Many Decision Making Units[R].1986,The University of Texas at Austin, Center for Cybernetic studies Report CCS551:Austin.
[29] Yun.Y.B，Nakayama.H, T.T., A generalized model for data envelopment analysis[J].European Journal of operational Research,2004(157): p.87-105.
[30] Douglas W.Caves, L.R.C.a.W.E.D., The economic theory of index numbers and themeasurement of input, output and productivity [J]. Econometricia,1982.50(6): p.1393-1414.
[31] F re R., S. Grosskopf, Malmquist Indexes and Fisher Ideal Indexes[J]. The EconomicJournal,1992.102(410): p.158-60.
[32] F re R., S. Grosskopf, Intertemporal Production Frontiers: With Dynamic DEA[M].1996, Kluwer. Academic Publishers: Boston.
[33] F re R., S. Grosskopf, Norris M., Productivity growth, technical progress, andefficiency change in industrialized countries[J]. American Economic Review,1997a.87(5): p.1040-1043.
[34] Kendrick, J.W., ProduetivityTrends in the United State[M].1961, Princeton: PrincetonUniversity Press.
[35] Stephen L.Parente, E.C.P., Barriers to Technology Adoption and Development[J]. theJournal of Political Economy,1994.102(2): p.298-321.
[36] Taylor, M.P.a.L.S., The behavior of real exchange rates during the post-Bretton Woodsperiod[J]. Journal of International Economics,1998.48: p.281-312.
[37] Daron Acemoglu, J.A., How Large Are Human-Capital Externalities? Evidence fromCompulsory Schooling Laws[R]. NBER Macroeconomics Annual,2000.15: p.9-59.
[38] Robert J. Barro, R.M.M., Religion and Economic Growth[R].2003, NBER WorkingPapers.
[39] Laura Alfaroa, A.C., Sebnem Kalemli-Ozcanc,Selin Sayekd, FDI and economicgrowth: the role of local financial markets[J]. Journal of International Economics,2004.64: p.89-112.
[40] Romer, P.M., Endogenous Technological Change[J]. The Journal of Political Economy,1990.98(5): p.71-102.
[41] Grossman, G.a.E.H., Innovation and Growth in the Global Economy[M].1991,Cambridge: MIT Press.
[42] Anusua Datta, H.M., Endogenous Imitation and Technology Absorption in a Model ofNorth-South Trade[J]. International Economic Journal,2006.20: p.431-459.
[43] Keller, W., International Technology Diffusion[R].2001, NBER Working Papers.
[44] Jess Benhabib, M.M.S., The Role of Human Capital in Economic Development:Evidence from Aggregate Cross-Country Data[J]. Journal of Monetary Economics,1994.34: p.143-173.
[45] Jess Benhabib, M.M.S., Human Capital and Technology Diffusion[C], in.Aghionand Durlanf Handbook of Eeonomic Growth，4ed.2005:.Amsterdam: NorthHolland.
[46] E. Borensztein, J.D.G., J-W. Lee, How does foreign direct investment affect economicgrowth?[J]. Journal of International Economics,1998.45: p.115-135.
[47] Miller, S.M., Upadhyay，P.Mukti, The Effects of Openness, Trade Orientation andHuman Capital on Total Factor Productivity[J]. Journal of Development Economics,2000.63: p.399-423.
[48] Guifang Yang, K.E.M., Intellectual Property Rights, Licensing, and Innovation[R],World Bank Policy Research Working Paper.
[49]李京文，钟学义.中国生产率分析前沿[M].北京:社会科学文献出版社，1998.
[50]张军，施少华.中国经济全要素生产率变动：1952-1998[J].世界经济文汇，2003(2):p.17-24.
[51]彭国华.中国地区收入差距、全要素生产率及其收敛分析[J].经济研究，2005(9):p.19-29.
[52]郭庆旺，贾俊雪.中国全要素生产率的估算：1979—2004[J].经济研究，2005(6):p.51-60.
[53]田银华，贺胜兵，胡石其.环境约束下地区全要素生产率增长的再估算：1998—2008[J].中国工业经济，2011(1): p.47-57.
[54]颜鹏飞，王兵.技术效率、技术进步与生产率增长:基于DEA的实证分析[J].经济研究，2004(12): p.55-65.
[55]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): p.19-32.
[56]周燕，蔡宏波.中国工业行业全要素生产率增长的决定因素：1996-2007[J].北京师范大学学报(社会科学版)，2011(1): p.133-141.
[57]曹泽，李东，朱达荣.中国区域全要素生产率增长的R&D贡献分析[J].系统工程，2011.29(1): p.57-62.
[58]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): p.55-66.
[59]陶长琪，齐亚伟.中国全要素生产率的空间差异及其成因分析[J].数量经济技术经济研究，2010(1): p.19-32.
[60]陈涛涛.影响中国外商直接投资溢出效应的行业特征[J].中国社会科学，2003(4):p.33-43.
[61]赖明勇，包群，彭水军，张新.外商直接投资与技术外溢：基于吸收能力的研究[J].经济研究，2005(8): p.95-105.
[62]易先忠，张亚斌.技术差距、知识产权保护与后发国技术进步[J].数量经济技术经济研究，2006(10): p.111-121.
[63]路江涌.外商直接投资对内资企业效率的影响和渠道[J].经济研究，2008(6): p.95-106.
[64]蒋殿春，张宇.经济转型与外商直接投资技术溢出效应[J].经济研究，2008(7): p.26-38.
[65]沈坤荣，李剑.企业间技术外溢的测度[J].经济研究，2009(4): p.77-89.
[66]舒元，才国伟.我国省际技术进步及其空间扩散分析[J].经济研究，2007(6): p.106-118.
[67]邹薇，代谦.技术模仿、人力资本积累与经济赶超[J].中国社会科学，2003(5): p.26-38.
[68]许和连，亓朋，祝树金.贸易开放度、人力资本与全要素生产率[J].世界经济，2006(12): p.3-10.
[69]魏梅.区域全要素生产率影响因素及效率收敛分析[J].统计与决策，2008(12): p.77-79.
[70]魏下海.贸易开放、人力资本与中国全要素生产率——基于分位数回归方法的经验研究[J].数量经济技术经济研究，2009(7): p.61-72.
[71]高凌云，王洛林.进口贸易与工业行业全要素生产率[J].经济学（季刊），2010.9(2):p.391-414.
[72]李玉红，王皓，郑玉歆.企业演化：中国工业生产率增长的重要途径[J].经济研究，2008(6): p.12-24.
[73]李国璋，刘津汝.产权制度、金融发展和对外开放对全要素生产率增长贡献的经验研究[J].经济问题，2011(2): p.4-9.
[74]关兵.出口地理方向与我国全要素生产率增长[J].国际贸易问题，2010(11): p.13-21.
[75]关兵.出口商品结构与我国全要素生产率增长[J].山西财经大学学报，2010.32(7):p.1-9.
[76]邹明.我国对外直接投资对国内全要素生产率的影响[J].北京工业大学学报（社会科学版），2008.8(6): p.30-35.
[77]姚洋.非国有经济成分对我国工业企业技术效率的影响[J].经济研究，1998(12): p.29-35.
[78]涂正革，肖耿.转轨时期大中型工业企业全要素生产率增长的行业特征[J].统计与决策，2005(12): p.64-65.
[79]谢千里，罗斯基，张轶凡.中国工业生产率的增长与收敛[J].经济学（季刊），2008.7(3): p.209-826.
[80]郑兵云，陈圻.转型期中国工业全要素生产率与效率[J].数理统计与管理，2010.29(3): p.480-489.
[81]诸大建，周建亮.循环经济理论与全面小康社会[J].同济大学学报（社会科学版），2003.14(3): p.107-112.
[82] Pearce, D., Resource Productivity: Outsider view of the state of play and what mightneed to be done[R].2001, University of London.
[83] Green Alliance, Building a bright green economy an agenda fou action on resourceproductivity[R].2002: Green Alliance.
[84] Hendrik A. Verfaillie, R.B., Measuring eco-efficiency[Z].2000.06. p.7.
[85] Annik Magerholm Fet, O.M., Industrial Ecology and Eco-Efficiency——Anintroduction to the concepts[R].2002: Vilnius, Lithuania. p.3.
[86] Micheal Porter, E., Class van der Linde, Green and Competitiveness Ending theStalemate[J]. Harvard Business Review,1995.9-10.
[87]迈克尔．波特[美]著，高登第，李明轩译.竞争论[M].北京:中信出版社，2003.
[88] DETR, Achieving a borer quality of life-Review of progress towards a sustainabledevelopment[R]. Government Annual Report,2000.
[89] Hoh.H, Scoer.K, Seibel.S, Eco-Efficiency Indicators in German EnvironmentalEconomic Accounting[Z]. Federal Statistical Office,Germany,2001.
[90]诸大建，朱远.生态效率与循环经济[J].复旦大学学报（社科版），2005(2): p.60-66.
[91]邱寿丰，诸大建.我国生态效率指标设计和应用[J].科学管理研究，2007(1): p.20-24.
[92]杨永华，钱斌华，王明兰.经济增长中的资源生产率分析[J].青岛行政学院学报，2005(3): p.16-18.
[93]杨永华,诸大建,胡冬洁.资源生产率视角的经济增长模型分析[J].广东行政学院学报，2007.19(2): p.59-62.
[94] Won-kyu, K., Current Issues and Implications of Korea’s Carbon Productivity[N].http://kiet.re.kr/UpFile/newsbrief/1266304157908.pdf,Jan,2010.,2010.
[95]刘国平，曹莉萍.基于福利绩效的碳生产率研究[J].中国软科学，2011.25(1): p.71-74.
[96]魏梅，曹明福，江金荣.生产中碳排放效率长期决定及其收敛性分析[J].数量经济技术经济研究，2010(9): p.43-52.
[97]潘家华，张丽峰.我国碳生产率区域差异性研究[J].中国工业经济，2011(5): p.47-57.
[98]袁富华.低碳经济约束下的中国潜在经济增长[J].经济研究，2010(8): p.79-89,154.
[99]顾乾屏，张棋，彭淑华等.商业银行分支机构效率评价的参数与非参数方法比较研究[J].数理统计与管理，2007.26(4): p.676-684.
[100] Chambers R. G, C.Y., Fare R, Benefitand Distance Functions [J]. Journal of EconomicTheory,1996.70(2): p.407-419.
[101] Baumol, W., Productivity growth, convergence and welfare: the long-run data show[J].American Economic Reviews,1986: p.1072-1085.
[102] Barro, R.J., Sala-i-Martin, X, Convergence across states and regions[J]. BrookingsPapers on Economic Activity,1991.22(1): p.107-182.
[103]刘强.中国经济增长的收敛性分析[J].经济研究，2001(6).
[104] Anderson, T.W.a.C.H., Estimation of dynamic models with error components[J].Journal of the American Statistical Association,1981(76): p.598-606.
[105] Ahn, S.C.a.P.S., Efficient estimation of models for dynamic panel data[J]. Journal ofEconometrics,1995(68): p.5-27.
[106] Arellano M., S.B., Some Tests of Specification for Panel Data:Monte Carlo Evidenceand an Application to Employment Equations[J]. Review of Economic Studies,1991.58: p.277-297.
[107] Blundell R., S.B., Initial Conditions and Moment Restrictions in Dynamic Panel DataModels[J]. Journal of Econometrics,1998.87: p.115-143.
[108]王亮.经济增长收敛假说的存在性检验与形成机制研究[D].吉林大学博士学位论文，2010.6.
[109] Pesaran, H., A simple panel unit root test in the presence of cross-sectiondependence[J]. Journal of Applied Econometrics,2007.22(2): p.265-312.
[110] Im K.S., M.H.P., Y. Shin, Testing for Unit Roots in Heterogeneous Panels[J]. Journalof Econometrics,2003.115: p.53-74.
[111] Maddala, G.S.a.W., Shaowen, A Comparative Study of Unit Root Tests With PanelData and A New Simple Test[J]. Oxford Bulletin of Economics and Statistics,1999.61:p.631-652.
[112] Levin, A., Lin, Chien-Fu and Chia-Shang James Chu, Unit Root Tests in Panel Data:Asymptotic and Finite Sample Properties[J]. Journal of Econometrics,2002.108(1): p.1-24.
[113]傅永东.我国农村新型合作经济组织发展模式研究[D].国防科技大学博士学位论文，2006.
[114]施蔚.江苏木材加工产业的规模经济问题研究[D].南京林业大学博士学位论文，2007.
[115]楚序平.中国钢铁产业规模经济研究[D].南开大学博士学位论文，2009.
[116]罗四维.基于DEA模型的商业银行规模经济研究[D].湖南大学硕士学位论文，2003.
[117]刘明.基于新竞争(力)视角的企业规模经济性研究[D].天津大学博士学位论文，2007.
[118]乔治.J.施蒂格勒.产业组织和政府管制[M].上海:上海三联书店，1989.
[119]张如海.规模经济：理论辨析和现实思考[J].经济问题，2001(1): p.8-11.
[120] Solow, R.M., Technical change and the Aggregate production function[J]. Review ofEconomics and Statistics,1957.39(8): p.312-320.
[121] Hicks, J., The Theory of Wages[M].1932,2nd ed.,1963, London: Macmillan.
[122] Solow, R.M., Investment and Technical Progress[M], ed. S.K. Kenneth J. Arrow, andPatrick Suppes.1960, Stanford: Stanford University.
[123] Phelps, E., The New View of Investment[J]. Quarterly Journal of Economics,1962.76(4): p.548-567.
[124]黄先海，刘毅群.物化性技术进步与我国工业生产率增长[J].数量经济技术经济研究，2006(4): p.52-60.
[125] Szirmai, M.P.T.R.v.d.K., Measuring Embodied Technological Change in IndonesianTextiles: The Core Machinery Approach[J] Journal of Development Studies,2002.39(2): p.155-177.
[126] R.Boucekkine, F.d.R.a.O.L., Obsolescence and Modernization in the GrowthProcess[J]. Journal of Development Economics,2005.77: p.153-17.
[127]宋冬林，王林辉，董直庆.资本体现式技术进步及其对经济增长的贡献率[J].中国社会科，2011(2): p.91-106.
[128]赵玉林.创新经济学[M].中国经济出版社，2006.
[129]傅东平.中国生产率的变化及其影响因素研究[D].华中科技大学博士学位论文，2009.
[130] MacDougall, G.D.A., The Benefits and Costs of Private Investment from Abroad:ATheoretical Approach[J]. Economic Record,1962.36(73): p.13-15.
[131] Kokko, A., Foreign direct investment, host country characteristics, and Spillovers[M].1992, The Economics Research Institute: Stockholm.
[132]沈坤荣，耿强.外国直接投资、技术外溢与内生经济增长[J].中国社会科学，2001(5): p.82-93.
[133]何洁.外商直接投资对中国工业部门外溢效应的进一步精确量化[J].世界经济，2000(12): p.29-36.
[134]易行健，李良生.市场是否可以换来技术进步?——来自广东省工业部门面板数据的实证分析[J].南方经济，2007(7): p.71-82.
[135]李小平，朱钟棣.国际贸易、R&D溢出和生产力增长[J].经济研究，2006(2): p.31-43.
[136]李小平，卢现祥，朱钟棣.国际贸易、技术进步和中国工业行业的生产率增长[J].经济学（季刊），2008.7(2): p.549-564.
[137]许培源，高伟生.国际贸易对中国技术创新能力的溢出效应[J].财经研究，2009.35(9): p.70-79.
[138]易纲，樊纲，李岩.关于中国经济增长与全要素生产率的理论思考[J].经济研究，2003(8).
[139]黄先海，刘毅群.设备投资、体现型技术进步与生产率增长:跨国经验分析[J].世界经济，2008(4): p.47-61.
[140]林毅夫，任若恩.东亚经济增长模式相关争论的再探讨[J].经济研究，2007(8): p.4-11.
[141]赵志耘，吕冰洋，郭庆旺，贾俊雪.资本积累与技术进步的动态融合:中国经济增长的一个典型事实[J].经济研究，2007(11): p.18-31.
[142]王玺，张勇.关于中国技术进步水平的估算———从中性技术进步到体现式技术进步[J].中国软科学，2010(4): p.155-163.
[143] Griliches, Z., R&D and productivity Slowdown[J]. American Economic Review,1980a.70(1): p.343-348.
[144] Griliches, Z., Productivity R&D and Basic Research at the Firm Level in the1970[J].American Eeonomic Review,1986.76(6): p.141-154.
[145] Griliches, Z., R&D and Productivity[M].1998, Chicago: University of Chicago Press.
[146] Suzuki, G.A.a.K., R&D Capital, Rate of Return on R&D Investment and Spillover ofR&D in Japanese Manufacturing Industries[J]. Review of Eeonomics and Statistics,1989.71: p.555-564.
[147] Coe, D.S.a.E.H., International R&D Spillover[J]. European Economic Review,1995.39(5): p.859-887.
[148]朱平芳，徐伟民.政府的科技激励政策对大中型工业企业R&D投入及其专利产出的影响[J].经济研究，2003(6): p.45-53.
[149]陈师，赵磊.中国经济周期特征与技术变迁——中性、偏向性抑或投资专有技术变迁[J].数量经济技术经济研究，2009(4): p.19-32.
[150]董直庆，王林辉.资本体现式技术进步与经济增长周期波动关联效应[J].求是学刊，2011.38(2): p.63-68.
[151]田立新，孙梅.能源供需系统分析[M].北京:科学出版社，2011.
[152]张国宝.中国能源发展报告2010[M].北京:经济科学出版社，2010.
[153]赵国浩，高文静.山西省煤炭工业和装备制造业转型发展将迎来新机遇[J].现代工业经济和信息化，2011(1): p.43-45.
[154]翟燕妮，赵国浩.基于循环经济的煤炭工业发展模式研究[C].和谐发展与系统工程——中国系统工程学会第十五届年会论文集.2008:江西，南昌. p.57-61.
[155]赵国浩，裴卫东，张东明.中国煤炭工业与可持续发展[M].北京:中国物价出版社，2000.
[156]陈文颖，高鹏飞，何建坤.用MARKAL-MACRO模型研究碳减排对中国能源系统的影响[J].清华大学学报(自然科学版)，2004(2):342-346.
[157]赵国浩，阎世春.煤炭工业可持续发展研究[M].北京:经济管理出版社，2008.
[158]魏一鸣，刘翠兰，范英，等.中国能源报告2008：碳排放研究[M].北京:科学出版社，2008.
[159]张金锁，邹绍辉.基于实物期权的煤炭资源投资决策方法研究[J].中国矿业，2009(9):21-26.
[160]闫新华，赵国浩.经济增长与环境污染的VAR模型分析[J].经济问题，2009(6):59-62
[161]范英，张晓兵，朱磊.基于多目标规划的中国二氧化碳减排的宏观经济成本估计[J].气候变化研究进展，2010(2):130-135.
[162]王群伟，周德群，沈璇，张力菠.我国全要素能源效率的测度与分析[J].管理评论，2010(3):37-43.
[163]廖华，魏一鸣.世界能源消费的差异性与不平衡性及其变化研究[J].中国软科学，2010(10):6-14
[164]李玮，赵国浩.基于环境约束的工业行业结构优化研究[J].中国人口资源环境，2010.20(12):129-133
[165]张鹏伟，李嫣怡主编. Stata统计分析与应用[M].北京：电子工业出版社，2011.
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