中国产业结构调整与节能减排的计量分析
|
摘要
2006年以来，节能减排成为中国可持续发展战略的重要组成部分。从中国现实看，产业结构是经济能耗的重要来源，而产业结构调整和升级是实现节能减排的重要措施和政策手段。从文献资料看，有关中国产业结构与节能减排关系的研究主要采用线性回归（协整）模型或指数分解模型。然而，中国经济的周期波动和政府宏观调控使产业结构反复波动，具有典型的非线性特征，这导致已有的研究结论常与现实不一致，其政策建议也存在局限性。本文针对中国能源变量的数据特征和能源经济相关理论，应用前沿且适用的能源经济和计量经济的理论和方法，展开对上述问题的研究，以期产生具有明显的现实与政策意义的结论。全文的研究工作和结论及其创新意义概况如下：
（1）应用不同的理论和方法的研究结果均表明，中国不同时期的产业结构（以工业增加值占GDP的比重来度量）对能源强度产生的效应不尽相同。以中国产业结构与能源强度的数据演变特征为依据，构建了一个非线性阈值协整模型，研究结果表明，在产业结构处于40.435%处，产业结构对能源强度的长期效应发生非线性转移，并可由逻辑函数刻画其转移特征。具体而言，在工业增加值占GDP的比重向下调整的1983-1994年、1998-2002年和2009年间，产业结构对能源强度具有微弱间断的
结构红利；而在1980-1982、1995-1997和2003-2008年间，产业结构体现了明显耗能的特征。这一结论表明，始终不渝的调整结构、加快经济增长方式的转变，是实现结构具有持续节能效应的长期战略；而在短期内，建议将工业占GDP比重调整到40%以下。与已有研究文献相比，本文的研究结论明确了产业结构调整的方向与幅度。
（2）基于Kaya恒等式所反映的理论内涵和变量关系，尤其是针对中国经济增长和结构调整的非线性波动特征，应用非线性模型揭示了结构调整对碳强度的影响受制于经济增速。具体来说，当经济增速高于9.053%时，产业结构和能源消费结构的调整均不利于碳强度的下降。在此基础上，基于估计的模型而应用依赖于蒙特卡洛模拟的情景分析，结论表明，中国碳强度年均下降速度的可能值是4.34%（2011-2015年）和3.51%（2016-2020年），这意味着碳强度2020年同比2005年预期将下降41.19%；而将经济增长速度调控到适度区间（约为7%~8.4%），有助于碳减排的可持续性。显然，非线性模型的设定及其实证分析充分体现了中国的经济背景和现实特征，而基于仿真的情景分析，消除了以往文献中简单的三种情景分析中的主观性因素，其分析结论具有稳健性和合理性，因此，上述研究结论对中国未来实施碳减排具有重要的应用价值和实际意义。
（3）中国不同省份的资源配置方式具有显著差异，已有文献在分析各省的能效水平时常忽略了这一差异。本文充分考虑各省资源配置方式的异质性，以产业结构合理化水平为阈值变量，运用阈值效应随机前沿模型分析了各省的全要素能源效率。检验和估计结果表明，各省的经济增长存在三个技术俱乐部，且产业结构逾合理，全要素能源效率值逾高。不同技术俱乐部下产出增长率的分解结果显示，产业结构逾不合理，要素投入，尤其是资本投入对经济产出的贡献度逾高，而技术进步对经济产出的贡献度逾低。上述结论表明，改变依赖要素投入的粗放型经济增长方式，依靠技术进步而提高产业结构合理化水平，是提高能源利用效率的有效途径。
（4）考虑能耗产生的碳排放污染，本文采用超效率DEA模型而估计环境方向距离函数以改善效率前沿面省份的节能减排效率值；基于估计结果运用面板数据模型考察投资驱动的经济增长方式、产业结构调整对节能减排效率的影响。结果表明，投资驱动的经济增长不利于节能减排效率的提高；劳动力要素的产业间流动有助于提高节能减排效率，而资本的产业间转移则相反；制造业结构变动和升级无助于提高能源效率，但有助于提高节能减排效率。这些结论表明，转变经济增长方式、破除产业间壁垒而促进要素流动和转移、坚持引进技术的消化吸收和自主创新而提高制造业结构的高度化水平是可持续性节能减排的长期途径。与已有文献不同，本文从产业结构合理化和制造业结构高度化为实施节能减排的结构调整政策提供了新视角和新证据。
Since2006,―energy conservation and emission reduction‖has become an essentialpart of China's sustainable development strategy. From historical data, the heavierindustrial structure is a significant source of energy consumption, and industrialadjustment and upgrading is an important entry point and main measure for governmentsto implement―energy conservation and emission reduction‖. From the previousdocuments about the relationship between industrial structure and energy/carbon intensityof China, the main methods are linear regression model and index decomposition methods.However, because of economic cycle and macro-control, China's industrial structure has atypical non-linear characteristics, which led to the existing research conclusions are ofteninconsistent with the reality, and its policy recommendations have limitations. Based onthe data characteristics and the theory of energy economy, this thesis applied latest andproper econometrical models to analysis the relationship between industrial structure and―energy conservation and emission reduction‖of China. This research is expected toproduce some conclusions in line with the actual situation of China, and give someinspiring policy recommendations. The main research contents and conclusions and itsinnovative profile are as following:
(1) Based on the results of different theories and methods, the effects of industrialstructure (measured by the ratio of industry added value to GDP) on energy intensity(measured by energy consumption per unit of GDP) are variously in different periods ofChina. According to data features between industrial structure and energy intensity during1980-2009, this paper applied a threshold cointegration model to analysis the nonlinearrelationship between them. The results exposes that industrial structure has nonlineareffects on energy intensity when industrial structure is around40.435%: during the periodsof1983-1994,1998-2002and2009, the industry/GDP was declined, and industrialstructure produced negative effects on energy intensity weakly and discontinuously; during the periods of1980-1982,1995-1997and2003-2008, the adjustment ofindustry/GDP was not conducive to the reduction of energy intensity. This conclusionsuggests that readjusting the industrial structure and transforming the pattern of economicgrowth are long-term strategies for sustainably pushing the decline of energy intensity. Inshort-term, it suggests readjust the industry/GDP to below than40%. Compared with theexisting research literatures, the conclusions of this study clearly shows the direction andmagnitude of structural adjustment in China.
(2) Based on the Kaya identity and the data characteristics of China's economicgrowth and structural adjustment, a nonlinear model was tested and estimated in order toreflect whether the effects of structural adjustment on carbon intensity were subject toeconomic growth or not. The results show that if the rate of economic growth is higherthan9.053%, industrial structure and energy mix were not conducive to decline in carbonintensity. Furthermore, the scenario analysis which depends on the Monte Carlosimulation show that the expected values of the average annual decrease rate of China'scarbon intensity are4.34%(2011-2015) and3.51%(2016-2020). It means the carbonintensity in2020is expected to decline by41.19%compare to2005. It also suggests thatthe rate of economic growth in the interval of7%to8.4%can contribute to carbonemission reduction. Obviously, the positive analysis of the nonlinear model is fully reflectsChina's economic background and carbon emission‘s characteristics, and simulation-basedscenario analysis eliminate subjective factors in similar studies, so the conclusion is robustand rationality. Therefore, the conclusion of the study has an important application valueand practical significance for China‘s carbon emission reduction in the future.
(3) There is a significant difference of resource allocation in different provinces ofChina, but past papers about energy efficiency often ignore it. Take account of theheterogeneity of resource allocation in provinces, this paper takes rationalization ofindustrial structure as a threshold variable, and uses a threshold effects stochastic frontiermodel to analysis the total factor energy efficiency. The test and estimate results show thatthe economic growth of the different provinces has three technological clubs, and the more reasonable of industrial structure, the higher total factor energy efficiency. Furthermore,the decomposition results show that the less rational industrial structure, the highercontribution of factor inputs, especially the capital investment, on economic output, andthe lower contribution of technological progress on economic output. The aboveconclusions mean that change the economic growth pattern, and enhance the level ofrationalization of the industrial structure by technological progress are effective ways toimprove energy efficiency.
(4) Because carbon emission generates by energy consumption, this paper usesenvironmental directional distance functions, which is estimated by super-DEA model toimprove the efficiency frontier provinces‘estimators, to calculate the total-factor energyefficiency (TFCE). Then, it uses some panel data models to examine the relationshipbetween economic growth pattern, which is characteristic by investment driven, theindustrial structure adjustment and the total-factor energy efficiency. The results indicateChina‘s economic growth pattern is not benefit to improving TFCE; labor flow betweenindustries produces "structure bonus" on TFCE, and capital flow between industriesproduces "structure burden" on TFCE; the change and upgrade of manufacturing industrystructure doesn‘t benefit to improve energy efficiency, but it is help to enhance TFCE.These conclusions indicate that it is long-term ways to improve energy/carbon efficiencyby transforming economic growth pattern, and getting rid of the barriers betweenindustries, and enhancing the optimization of manufacturing structure by digestion andabsorption of new international technology and self-innovation. Compared with theexisting literatures, this article provides a new perspective and a new evidence forimplement―energy conservation and emission reduction‖through industrial structure fromthe rationalization of industrial structure and the optimization of manufacturing structure.
（1）应用不同的理论和方法的研究结果均表明，中国不同时期的产业结构（以工业增加值占GDP的比重来度量）对能源强度产生的效应不尽相同。以中国产业结构与能源强度的数据演变特征为依据，构建了一个非线性阈值协整模型，研究结果表明，在产业结构处于40.435%处，产业结构对能源强度的长期效应发生非线性转移，并可由逻辑函数刻画其转移特征。具体而言，在工业增加值占GDP的比重向下调整的1983-1994年、1998-2002年和2009年间，产业结构对能源强度具有微弱间断的
结构红利；而在1980-1982、1995-1997和2003-2008年间，产业结构体现了明显耗能的特征。这一结论表明，始终不渝的调整结构、加快经济增长方式的转变，是实现结构具有持续节能效应的长期战略；而在短期内，建议将工业占GDP比重调整到40%以下。与已有研究文献相比，本文的研究结论明确了产业结构调整的方向与幅度。
（2）基于Kaya恒等式所反映的理论内涵和变量关系，尤其是针对中国经济增长和结构调整的非线性波动特征，应用非线性模型揭示了结构调整对碳强度的影响受制于经济增速。具体来说，当经济增速高于9.053%时，产业结构和能源消费结构的调整均不利于碳强度的下降。在此基础上，基于估计的模型而应用依赖于蒙特卡洛模拟的情景分析，结论表明，中国碳强度年均下降速度的可能值是4.34%（2011-2015年）和3.51%（2016-2020年），这意味着碳强度2020年同比2005年预期将下降41.19%；而将经济增长速度调控到适度区间（约为7%~8.4%），有助于碳减排的可持续性。显然，非线性模型的设定及其实证分析充分体现了中国的经济背景和现实特征，而基于仿真的情景分析，消除了以往文献中简单的三种情景分析中的主观性因素，其分析结论具有稳健性和合理性，因此，上述研究结论对中国未来实施碳减排具有重要的应用价值和实际意义。
（3）中国不同省份的资源配置方式具有显著差异，已有文献在分析各省的能效水平时常忽略了这一差异。本文充分考虑各省资源配置方式的异质性，以产业结构合理化水平为阈值变量，运用阈值效应随机前沿模型分析了各省的全要素能源效率。检验和估计结果表明，各省的经济增长存在三个技术俱乐部，且产业结构逾合理，全要素能源效率值逾高。不同技术俱乐部下产出增长率的分解结果显示，产业结构逾不合理，要素投入，尤其是资本投入对经济产出的贡献度逾高，而技术进步对经济产出的贡献度逾低。上述结论表明，改变依赖要素投入的粗放型经济增长方式，依靠技术进步而提高产业结构合理化水平，是提高能源利用效率的有效途径。
（4）考虑能耗产生的碳排放污染，本文采用超效率DEA模型而估计环境方向距离函数以改善效率前沿面省份的节能减排效率值；基于估计结果运用面板数据模型考察投资驱动的经济增长方式、产业结构调整对节能减排效率的影响。结果表明，投资驱动的经济增长不利于节能减排效率的提高；劳动力要素的产业间流动有助于提高节能减排效率，而资本的产业间转移则相反；制造业结构变动和升级无助于提高能源效率，但有助于提高节能减排效率。这些结论表明，转变经济增长方式、破除产业间壁垒而促进要素流动和转移、坚持引进技术的消化吸收和自主创新而提高制造业结构的高度化水平是可持续性节能减排的长期途径。与已有文献不同，本文从产业结构合理化和制造业结构高度化为实施节能减排的结构调整政策提供了新视角和新证据。
Since2006,―energy conservation and emission reduction‖has become an essentialpart of China's sustainable development strategy. From historical data, the heavierindustrial structure is a significant source of energy consumption, and industrialadjustment and upgrading is an important entry point and main measure for governmentsto implement―energy conservation and emission reduction‖. From the previousdocuments about the relationship between industrial structure and energy/carbon intensityof China, the main methods are linear regression model and index decomposition methods.However, because of economic cycle and macro-control, China's industrial structure has atypical non-linear characteristics, which led to the existing research conclusions are ofteninconsistent with the reality, and its policy recommendations have limitations. Based onthe data characteristics and the theory of energy economy, this thesis applied latest andproper econometrical models to analysis the relationship between industrial structure and―energy conservation and emission reduction‖of China. This research is expected toproduce some conclusions in line with the actual situation of China, and give someinspiring policy recommendations. The main research contents and conclusions and itsinnovative profile are as following:
(1) Based on the results of different theories and methods, the effects of industrialstructure (measured by the ratio of industry added value to GDP) on energy intensity(measured by energy consumption per unit of GDP) are variously in different periods ofChina. According to data features between industrial structure and energy intensity during1980-2009, this paper applied a threshold cointegration model to analysis the nonlinearrelationship between them. The results exposes that industrial structure has nonlineareffects on energy intensity when industrial structure is around40.435%: during the periodsof1983-1994,1998-2002and2009, the industry/GDP was declined, and industrialstructure produced negative effects on energy intensity weakly and discontinuously; during the periods of1980-1982,1995-1997and2003-2008, the adjustment ofindustry/GDP was not conducive to the reduction of energy intensity. This conclusionsuggests that readjusting the industrial structure and transforming the pattern of economicgrowth are long-term strategies for sustainably pushing the decline of energy intensity. Inshort-term, it suggests readjust the industry/GDP to below than40%. Compared with theexisting research literatures, the conclusions of this study clearly shows the direction andmagnitude of structural adjustment in China.
(2) Based on the Kaya identity and the data characteristics of China's economicgrowth and structural adjustment, a nonlinear model was tested and estimated in order toreflect whether the effects of structural adjustment on carbon intensity were subject toeconomic growth or not. The results show that if the rate of economic growth is higherthan9.053%, industrial structure and energy mix were not conducive to decline in carbonintensity. Furthermore, the scenario analysis which depends on the Monte Carlosimulation show that the expected values of the average annual decrease rate of China'scarbon intensity are4.34%(2011-2015) and3.51%(2016-2020). It means the carbonintensity in2020is expected to decline by41.19%compare to2005. It also suggests thatthe rate of economic growth in the interval of7%to8.4%can contribute to carbonemission reduction. Obviously, the positive analysis of the nonlinear model is fully reflectsChina's economic background and carbon emission‘s characteristics, and simulation-basedscenario analysis eliminate subjective factors in similar studies, so the conclusion is robustand rationality. Therefore, the conclusion of the study has an important application valueand practical significance for China‘s carbon emission reduction in the future.
(3) There is a significant difference of resource allocation in different provinces ofChina, but past papers about energy efficiency often ignore it. Take account of theheterogeneity of resource allocation in provinces, this paper takes rationalization ofindustrial structure as a threshold variable, and uses a threshold effects stochastic frontiermodel to analysis the total factor energy efficiency. The test and estimate results show thatthe economic growth of the different provinces has three technological clubs, and the more reasonable of industrial structure, the higher total factor energy efficiency. Furthermore,the decomposition results show that the less rational industrial structure, the highercontribution of factor inputs, especially the capital investment, on economic output, andthe lower contribution of technological progress on economic output. The aboveconclusions mean that change the economic growth pattern, and enhance the level ofrationalization of the industrial structure by technological progress are effective ways toimprove energy efficiency.
(4) Because carbon emission generates by energy consumption, this paper usesenvironmental directional distance functions, which is estimated by super-DEA model toimprove the efficiency frontier provinces‘estimators, to calculate the total-factor energyefficiency (TFCE). Then, it uses some panel data models to examine the relationshipbetween economic growth pattern, which is characteristic by investment driven, theindustrial structure adjustment and the total-factor energy efficiency. The results indicateChina‘s economic growth pattern is not benefit to improving TFCE; labor flow betweenindustries produces "structure bonus" on TFCE, and capital flow between industriesproduces "structure burden" on TFCE; the change and upgrade of manufacturing industrystructure doesn‘t benefit to improve energy efficiency, but it is help to enhance TFCE.These conclusions indicate that it is long-term ways to improve energy/carbon efficiencyby transforming economic growth pattern, and getting rid of the barriers betweenindustries, and enhancing the optimization of manufacturing structure by digestion andabsorption of new international technology and self-innovation. Compared with theexisting literatures, this article provides a new perspective and a new evidence forimplement―energy conservation and emission reduction‖through industrial structure fromthe rationalization of industrial structure and the optimization of manufacturing structure.
引文
[1] Aghion Philippe and Howitt Peter., Endogenous Growth Theory. Cambridge: MITPress,1998.
[2] Aigner D., C. A. K. Lovell and Schmidt P., Formulation and Estimation of StochasticFrontier Production Function Models. Journal of Econometrics,1977,(6):21-37.
[3] Almanidis P., Accounting for Heterogeneous Technologies in Banking Industry: ATime-Varying Stochastic Frontier Model with Threshold Effects, Working paper,Rice University,2011.
[4] Anastasios Xepapadeas, Economic Growth and the Environment, Intended as Chapter23in: Handbook of Environmental Economics, Volume3, K.-G. M ler and J.R.Vincent (eds), Elsevier B.V.,2005,1219-1271.
[5] Andersen P., Petersen N.C. A Procedure for Ranking Efficient Units in DataEnvelopment Analysis. Management Science,1993,39:1261-1264.
[6] Arellano M., Bond S., Some Tests of Specification for Panel Data: Monte CarloEvidence and an Application to Employment Equations, The Review of EconomicStudies,1991,58:277-297.
[7] Art B.v., Timmer M., Asia‘s Productivity Performance and Potential: TheContribution of Sectors and Structural Change, University of Groningen&Conference Board, The Netherlands, working paper,2003.
[8] Asafu-Adjaye, J. The Relationship between Energy Consumption, Energy Prices andEconomic Growth: Time Series Evidence from Asian Developing Countries. EnergyEconomics,2000,22:615-625.
[9] Aslanidis N., Iranzo S., Environment and development: is there a Kuznets curve forCO2emissions?, Applied Economics,2009,41:803-810.
[10]Bai J., Perron P., Estimating and Testing Linear Models with Multiple StructuralChanges. Econometrica,1998,66:47-78.
[11]Baltagi B.H., Econometric Analysis of Panel Data(Third Edition), Chichester, WestSussex, England: John Wiley&Sons Ltd.,2005.
[12]Battese G.E., Coelli T.J., Frontier Production Functions, Technical Efficiency andPanel Data: With Application to Paddy Farmers in India. The Journal of ProductivityAnalysis,1992,(3):153-169.
[13]Baumol W. J., Innovations and Growth: Two Common Misapprehensions. Journal ofPolicy Modeling,2003,25:435-444.
[14]Blundell R., Bond S., Initial conditions and moment restrictions in dynamic panel datamodels, Journal of Econometrics,1998,87:115-143.
[15]Bovenberg A. L. and Smulders S. A., Environmental Quality andPollution-augmenting Technological Change in a Two Sector Endogenous Growthmodel. Journal of Public Economics,1995,57(2):369-391.
[16]Bovenberg A. L. and Smulders S. A., Transitional Impacts of Environmental Policy inan Endogenous Growth Model. International Economic Review,1996,37:861-893.
[17]Caner M., Hansen B.E., Threshold Autoregression with a Unit Root, Econometrica,2001,69(6):1555-1596.
[18]Carson,Richard T.and Yongil Jeon, et al, The Relationship between Air PollutionEmissions and Income: U.S.Data. Environment and Development Economics,1997,2(4):433-450.
[19]Chambers R., Chung Y.H. and F re R., Benefit and Distance Function, Journal ofEconomic Theory,1996,70:407-419.
[20]Choi I., Saikkonen P., Testing linearity in cointegrating smooth transition regressions,Econometrics Journal,2004,(7):341–365.
[21]Choi I., Saikkonen P., Tests for Nonlinear Cointegration, Working paper, Departmentof Economics, Hong Kong University of Science and Technology,2008.
[22]Chua S., Economic Growth, Liberalization and the Environment: A Review of theEconomic Evidence. Annual Review of Environment.1999,24:391-430.
[23]Chung Y. H., F re R., Grosskopf S., Productivity and Undesirable Outputs: ADirectional Distance Function Approach, Journal of Environmental Management,1997,51:229-240.
[24]Coelli T., Estimators and Hypothesis Tests for a Stochastic Frontier Function: AMonte Carlo Analysis. Journal of Productivity Analysis,1995,(6):247-268
[25]Coelli T.J., Rao D.S. P., O'Donnell C.J., Battese G.E., An Introduction To EfficiencyAnd Productivity Analysis(Second Edition), Springer,2005.
[26]Common M. and Perrings C., Towards an Ecological Economics of Sustainability.Ecology Economic,1992,(6):7-34.
[27]Cornwell, C., Schmidt, P., and Sickles, R.C., Production frontiers with cross-sectionaland time series variation in effciency levels. Journal of Econometrics,1990,46:185-200.
[28]D.-H. Oh, J.-D. Lee, A metafrontier approach for measuring Malmquist productivityindex. Empirical Economics,2010,38(1):47-64.
[29]Daly Herman E., Steady-State Economics(2nd edition). Washington D.C.: IslandPress,1991.
[30]Daniel L. Millimet, John A. List, Thanasis Stengos, The Environmental KuznetsCurve: Real Progress or Misspecified Models? The Review of Economics andStatistics,2003,85(4):1038-1047.
[31]Dasgupta, P. and G. Heal., Economic Theory and Exhaustible Resources. Cambridge:Cambridge University Press,1979.
[32]Dijk D.v., Ter svirta T., Franses P.H., Smooth Transition Autoregressive Models—ASurvey of Recent Developments, Econometric Reviews,2002,21:1-47.
[33]Engle, R.F. and C.W.J. Granger, Co-integration and Error-correction: Representation,Estimation and Testing, Econometrica,1987,55:251-276.
[34]F re R., Grosskopf S., Noh D.W., Weber W., Characteristics of a pollutingtechnology: theory and practice, Journal of Econometrics,2005,126:469-492.
[35]F re R., Grosskopf S., Carl A., Jr. Pasurka, Environmental production functions andenvironmental directional distance functions, Energy,2007,32:1055-1066.
[36]Fagerberg J., Technological progress, structural change and productivity growth: acomparative study, Structural Change and Economic Dynamics,2000,(11):393-411.
[37]Fan S G, Zhang X B, Robinson S., Structural Change and Economic Growth in China,Review of Development Economics,2003,7(3):360-377.
[38]Feng T.W., Sun L.Y., Zhang Y., The relationship between energy consumptionstructure, economic structure and energy intensity in China, Energy Policy,2009,37:5475-5483.
[39]Fisher-Vanden K., The effects of market reforms on structural change: implicationsfor energy use and carbon emissions in China, The energy Journal,2003,24(3):27-62.
[40]Fisher-Vanden K., Gary H. J., Liu H. M., Tao Q., What is driving China‘s decline inenergy intensity?, Resource and Energy Economics,2004,26:77-97.
[41]Fried H. O., Lovell C. A. K. and Schmidt S. S., The Measurement of ProductiveEfficiency and Productivity Growth. New York: Oxford University Press,2008.
[42]Ghali, K.H., El-Sakka, M.I.T., Energy Use and Output Growth in Canada: AMultivariate Cointegration Analysis. Energy Economics,2004,26:225-238.
[43]González A., T. Ter svirta, and D. van Dijk.,2005, Panel smooth transition models,SSE/EFI Working Paper Series in Economics and Finance, No.604, StockholmSchool of Economics.
[44]Gordon R. J., Does the New Economy‘Measure up to the Great Inventions of thePast? Journal of Economic Perspectives,2000,14(4):49-74
[45]Gradus R. and Smulders S., The Trade-off between Environmental Care andLong-term Growth—Pollution in Three Prototype Growth Models. Journal ofEconomics,1993,58(1):25-51.
[46]Greening L.A., William B. D., Schipper L., Khrushch M., Comparison of sixdecomposition methods: application to aggregate energy intensity for manufacturingin10OECD countries, Energy Economics,1997,19:375-390.
[47]Greenwood, Hercowitz, and Krusell, Long-run Implications of Investment-SpecificTechnological change, American economic review,1997,87(3):363-382.
[48]Green W., Distinguishing between heterogeneity and ine ciency: stochastic frontieranalysis of theWorld Health Organization‘s panel data on national health care systems.Health Economics,2004,13:1-22.
[49]Green W., Reconsidering heterogeneity in panel data estimators of the stochasticfrontier model. Journal of Econometrics,2005,126:269-303.
[50]Grossman G.M. and Krueger A. B., Environmental impacts of a North American freetrade agreement. NBER working paper No3914,1991.
[51]Grossman G.M. and Krueger A. B., Economic Growth and Environment. TheQuarterly Journal of Economics.1995,110(2):353-377.
[52]Guan D., Hubacek K., Weber C.L., Peters G.P., Reiner D.M., The drivers of ChineseCO2emissions from1980to2030, Global Environmental Change,2008,18:626-634.
[53]Hamilton J.D., What is an Oil Shock? Journal of Econometrics,2003,113:363-398.
[54]Hansen B.E., Inference when a Nuisance Parameter is not identified under the NullHypothesis. Econometrica,1996,64:413-430.
[55]Hansen B.E., Threshold effects in non-dynamic panels: Estimation, testing, andinference. Journal of Econometrics,1999,93:345-368.
[56]Harberger A.C., A Vision of the Growth Process, American Economic Review,1998,88(1):1-32.
[57]Hofman B., Labar K., Structural Change and Energy Use: Evidence from China‘sProvinces, World Bank and University of Clermont-Ferrand, China Working PaperSeries No.6, working paper,2007.
[58]Homer-Dixon Tomans., The Ingenuity Gap: Can Poor Countries Adapt to ResourceScarcity? Population and Development Review,1995,21(3):1-26.
[59]Hu J.L., Lin C.H., Disaggregated Energy Consumption and GDP in Taiwan: AThreshold Co-integration Analysis. Energy Economics,2008,30:2342-2358.
[60]Hu Jin-Li, Wang Shih-Chuan, Total-factor Energy Efficiency of Regions in China,Energy Policy,2006,34:3206-3217.
[61]Hu J, Wang S., Total factor Energy Efficiency of Regions in China, Energy Policy,2006,34:3206-3217.
[62]Huffman W.E., Evenson R.E., Structural and productivity change in US agriculture,1950–1982, Agricultural Economics,2001,24:127-147.
[63]Isaksson A., Structural Change and Productivity Growth: A Review with Implicationsfor Developing Countries, Research and Statistics Branch, UNIDO, Working paper,08/2009.
[64]Jalil A., Mahmud S.F., Environment Kuznets curve for CO2emissions: Acointegration analysis for China, Energy Policy,2009,37:5167-5172.
[65]Kaufmann R.K., Davidsdottir B. and Garnham S., et al. The Determinants ofAtmospheric SO2Concentrations: Reconsidering the Environmental Kuznets Curve.Ecological Economics,1998,25(2):209-220.
[66]Kraft J. and Kraft A., On the Relationship between Energy and GNP. EnergyDevelopment,1978(3):401-403.
[67]Krüger J.J., Productivity and Structural Change: A Review of the Literature, Journalof Economic Surveys,2008,22(2):330-363
[68]Kumbhakar, S.C., Production frontiers, panel data, and time-varying technicalefficiency. Journal of Econometrics,1990,46:201-212.
[69]Kumbhakar S. C., Lovell C. A. K., Stochastic Frontier Analysis（随机边界分析）.刘晓宏，杨倩译，上海：复旦大学出版社，2007.
[70]Lantz, Feng. Assessing Income, Population and Technology Impacts on CO2Emissions in Canada: Where‘s the EKC? Ecological Economics,2006,57:229-238.
[71]Lee C.C., Chang C.P., Structural Breaks, Energy Consumption, and EconomicGrowth Revisited Evidence from Taiwan. Energy Economics,2005,27:857-872.
[72]Lee C.C., Chang C.P., Energy consumption and GDP revisited: A Panel Analysis ofDeveloped and Developing Countries. Energy Economics,2007,29:1206-1223.
[73]Liao Hua, Fan Y., Wei Y.M., What induced China‘s energy intensity to fluctuate:1997-2006?, Energy Policy,2007,35:4640-4649.
[74]Limam Y.R., and Miller S.M., Explaining Economic Growth: Factor Accumulation,Total Factor Productivity Growth, and Production Efficiency Improvement, workingpaper, March,2004.
[75]Lise, W., Montfort, K.E., Energy Consumption and GDP in Turkey: Is there aCo-integration Relationship? Energy Economics,2007,29:1166-1178.
[76]Liu N., Ang B.W., Factors shaping aggregate energy intensity trend for industry:Energy intensity versus product mix, Energy Economics,2007,29:609-635.
[77]Ma Chunbo, Stern D. I., China's changing energy intensity trend: A decompositionanalysis, Energy Economics,2008,30:1037-1053.
[78]Ma H.Y., Oxley L., Gibson J., China's energy economy: A survey of the literature,Economic Systems,2010,34:105-132.
[79]Medlock K.B., Soligo R., Economic Development and End-Use Energy Demand,Energy Journal,2001,22(2):77-105.
[80]Moon Y. S. and Soon Y. H., Productive Energy Consumption and Economic Growth:an Endogenous Growth Model and its Empirical Application. Resource and EnergyEconomics,1996,18:189-200.
[81]Moore, J. H., A Measure of Structural Change in Output, The Review of Income andWealth,1978,(3):105-117.
[82]Murillo-Zamorano L. R., Economic Efficiency and Frontier Techniques, Journal ofEconomic Surveys,2004,18(1):33-77.
[83]Orea L., Kumbhakar S.C., Efficiency measurement using a latent class stochasticfrontier model. Empirical Economics,2004,29:169-183.
[84]Oulton N., Srinivasan S., Productivity growth in UK industries,1970-2000: structuralchange and the role of ICT, Paper to be presented at the―Information Technology,Productivity and Growth‖conference, National Institute of Economic and SocialResearch, London,28-29October,2004.
[85]Panayotou T., Empirical Tests and Policy Analysis of Environmental Degradation atDifferent Stages of Economic Development. ILO Technology and EmploymentProgramme Working Paper WP238,1993.
[86]Panayotou T., Demystifying the Environmental Kuznets Curve: Turning a Black Boxinto a Policy Tool. Environment and Development Economics,1997,2(4):465-484.
[87]Philip Andrews-Speed, China‘s ongoing energy efficiency drive: Origins, progressand prospects, Energy Policy,2009,37:1331-1344.
[88]Ramakrishnan Ramanathan, An Analysis of Energy Consumption and CarbonDioxide Emissions in Countries of the Middle East and North Africa. Energy,2005,30:2831-2842.
[89]Rambaldi A. N., Rao D.S.P., Dolan，D．, Measuring Productivity Growth PerformanceUsing Metafrontiers with Applications to Regional Productivity Growth Analysis in aGlobal Context, In: O‘Donnell C.J., Australian Meeting of the Econometric SocietyESAM07,2007, Brisbane,1-33.
[90]Romer David, Advanced Macroeconomics(2ndedition). Shanghai: ShanghaiUniversity of Finance&Economics Press,2001,35-42.
[91]Sch fer A. Structural change in energy use, Energy Policy,2005,33:429-437.
[92]Scholz C. M. and Georg Ziemes, Exhaustible Resources, Monopolistic Competitionand Endogenous Growth. Environmental&Resource Economics,1999,13(2):169-185.
[93]Schmidt P., Sickles R.C., Production frontiers and panel data. Journal of Business andEconomic Statistics,1984,(2):367-374.
[94]Selden T.M., Song D., Environmental quality and Development: Is there a KuznetsCurve for Air Pollution Emissions? Journal of Environmental Economics andManagement,1994,27:147-162.
[95]Sheehan P., Sun F., Energy Use and CO2Emissions in China: Retrospect andProspect. Climate Change Project Working Paper Series No.4, Centre for StrategicEconomic Studies, Victoria University,2006.
[96]Smulders S., Entropy, Environment and Endogenous Economic Growth. InternationalTax and Public Finance,1995(2):319-338.
[97]Smulders S., Economic Growth and Environmental Quality. Intended as Chapter21in:Principles of Environmental Economics, Henk Folmer and Landis Gabel (eds),Edward Elgar,2000.
[98]Solow R. M., Intergenerational Equity and Exhaustible Resources. Review ofEconomic Studies,1974,41:29-45.
[99]Stern, D.I., A Multivariate Cointegration Analysis of the Role of Energy in the USMacroeconomy. Energy Economics,2000,22:267-283.
[100] Stern, D.I., The Rise and Fall of the Environmental Kuznets Curve. WorldEconomics,2004,32(8):1419-1439.
[101] Stiglitz J. E., Growth with Exhaustible Natural Resources: Efficient and OptimalGrowth Paths. Review of Economic Studies,1974,41:123-138.
[102] Stokey N L., Are there Limits to Growth? International Economic Review,1998,39(1):1-31.
[103] Syrquin M., Patterns of Structural Change, in H. Chenery and T.N. Srinivasan, eds.,Handbook of Development Economics, Volume1. Elsevier,1995:203-273.
[104] Ter svirta, T.; Tj stheim, D.&Granger, C. W., Modeling nonlinear economic timeseries, Unpublished Book,2008.
[105] Thomas Mike., Climate Change and the Stern Review: An Overview and Commentfrom Future in Our Hands Network, http://www.climatecooperation.org/Pindex.php?title=Stern–Review PMI ke-Thomas-2.2007.
[106] Timmer M.P., Szirmai A., Productivity growth in Asian manufacturing: thestructural bonus hypothesis examined, Structural Change and Economic Dynamics,2000,(11):371–392.
[107] Tol R. S. J., Stephen W. Pacala and Robert Socolow. Understanding Long-TermEnergy Use and Carbon Dioxide Emissions in the USA. Working Paper No.107,2006.
[108] Tsionas E.G., Tran K.C., Bayesian Inference in Threshold Stochastic FrontierModels, working paper,2007.
[109] Unander F., Decomposition of manufacturing energy-use in IEA countries: How dorecent developments compare with historical long-term trends?, Applied Energy,2007,84:771-780.
[110] Unruh, G.C. and W.R. Moomaw, An Alternative Analysis of Apparent EKC-typeTransitions. Ecological Economics,1998,25:221-229.
[111] Wang C., Chen Jining, Zou J., Decomposition of energy-related CO2emission inChina:1957-2000, Energy,2005,30:73-83.
[112] Wang H-J., Schmidt P., One-Step and Two-Step Estimation of the Effects ofExogenous Variables on Technical Efficiency Levels, Journal of ProductivityAnalysis,2002,18:129-144.
[113] Wang J. S.&He C.F., Technological Progress, Structural Change and China‘sEnergy Efficiency, Chinese Journal of Population, Resources and Environment,2009,7(2):44-49.
[114] Weber C.L., Measuring structural change and energy use: Decomposition of the USeconomy from1997to2002, Energy Policy,2009,37:1561-1570.
[115] Wei S.Z.C., Chen C.F., Zhu Z., Economic growth and Energy ConsumptionRevisited—Evidence from Linear and Nonlinear Granger Causality. EnergyEconomics,2008,30:3063-3076.
[116] Wen G., Cao Z., An Empirical Study on the Relationship between China‘s EconomicDevelopment and Environmental Quality——Testing China‘s EnvironmentalKuznets Curve, Journal of Sustainable Development,2009,2(2):65-72.
[117] William T. Harbaugh, Arik Levinson, David Molloy Wilson, Reexamining theEmpirical Evidence for an Environmental Kuznets Curve. The Review ofEconomics and Statistics,2002,84(3):541-551.
[118] Wing I.S., Explaining the declining energy intensity of the U.S. economy, Resourceand Energy Economics,2008,30:21-49.
[119] Wooldridge J.M., Econometric Analysis of Cross Section and Panel Data,Cambridge, MA: The MIT Press,2002.
[120] Wu Libo, Kaneko Shinji, Matsuoka Shunji, Driving forces behind the stagnancy ofChina‘s energy-related CO2emissions from1996to1999: the relative importance ofstructural change, intensity change and scale change, Energy Policy,2005,33:319-335.
[121] Wu N., Energy Intensity, Renewable Energy, and Economic Development:Examining Three Provinces in China, Working paper, Department of Urban Studiesand Planning, MIT.2008.
[122] Yélou C., Larue B., Tran K.C., Threshold effects in panel data stochastic frontiermodels of dairy production in Canada, Economic Modelling,2010,27:641-647
[123] Yuan C. Q., Liu S. F., Fang Z. G., Xie N. M., The relation between Chineseeconomic development and energy consumption in the different periods, EnergyPolicy,2010,38:5189-5198.
[124] Zhang H.B., Qi Y., A Structure Decomposition Analysis of China‘sProduction-Source CO2Emission:1992-2002, Environment and ResourceEconomics,2011,49:65-77.
[125] Zhang Z.X., Cheng X.M., Energy consumption, carbon emissions, and economicgrowth in China, Ecological Economics,2009,68:2706-2712.
[126] Zhang Z.X., Assessing China‘s carbon intensity pledge for2020: stringency andcredibility issues and their implications, Environment Economic Policy Study, DOI10.1007/s10018-011-0012-4, Published online:2011,30March.
[127]蔡昉、都阳、王美艳，经济发展方式转变与节能减排内在动力，经济研究，2008（6）：4-11.
[128]陈诗一，能源消耗、二氧化碳排放与中国工业的可持续发展，经济研究，2009（4）：41-55.
[129]陈诗一，中国的绿色工业革命:基于环境全要素生产率视角的解释（1980-2008），经济研究，2010（11）：21-34.
[130]陈诗一，节能减排、结构调整与工业发展方式转变研究，北京：北京大学出版社，2011.
[131]程永宏，改革以来全国总体基尼系数的演变及其城乡分解，中国社会科学，2007（4）：45-60.
[132]干春晖、郑若谷、余典范，中国产业结构变迁对经济增长和波动的影响，经济研究，2011（5）：4-16.
[133]高凌云、王洛林，进口贸易与工业行业全要素生产率，经济学（季刊），2010（1）：391-414.
[134]胡鞍钢、郑京海、高宇宁、张宁、许海萍，考虑环境因素的省级技术效率排名（1999-2005），经济学（季刊），2008，7（3）：933-960.
[135]胡鞍钢，中国的绿色低碳发展，载于薛进军主编《中国低碳经济发展报告》.北京：社会科学文献出版社，2011，257-267.
[136]胡初枝，黄贤金，钟太洋，谭丹，中国碳排放特征及其动态演进分析，中国人口·资源与环境，2008，18（3）：38-42.
[137]金碚、吕铁、邓洲，中国工业结构转型升级：进展、问题与趋势，中国工业经济，2011（2）：5-15.
[138]赖永剑、朱卫平，异质性的技术俱乐部与中国地区工业增长——基于潜类别随机前沿模型的研究，数量经济技术经济研究，2011（6）：107-119.
[139]李国志、李宗植，中国二氧化碳排放的区域差异和影响因素研究，中国人口、资源与环境，2010，（5）：22-27.
[140]李科、王少平，中国产业结构高端化和碳减排——基于动态面板平滑转换模型的经验分析，中国数量经济年会2011年年会论文.
[141]李世祥、成金华，中国主要工业省区能源效率分析：1990～2006年，数量经济技术经济研究，2008（10）：32-43.
[142]李小平、卢现祥，中国制造业的结构变动和生产率增长，世界经济，2007（5）：52-64.
[143]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，经济学（季刊），2008（1）：549-564.
[144]李艳梅、张雷，中国能源消费增长原因分析与节能途径探讨，中国人口.资源与环境，2008，18（3）：83-87.
[145]林伯强、蒋竺均，中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析，管理世界，2009，（4）：27-36.
[146]林伯强、刘希颖，中国城市化阶段的碳排放:影响因素和减排策略，经济研究，2010（8）：66-78.
[147]林伯强、孙传旺，如何在保障中国经济增长前提下完成碳减排目标，中国社会科学，2011（1）：64-76.
[148]林毅夫、苏剑，论我国经济增长方式的转换，管理世界，2007（11）：5-13.
[149]刘畅、孔宪丽、高铁梅，中国能源消耗强度变动机制与价格非对称效应研究——基于结构VEC模型的计量分析，中国工业经济，2009（3）：59-70.
[150]吕铁、周叔莲，中国的产业结构升级与经济增长方式转变，管理世界，1999（1）：113-125.
[151]吕铁，制造业结构变化对生产率增长的影响研究，管理世界，2002（2）：87-94.
[152]罗洁，自然资源与经济增长：资源瓶颈及其解决途径，经济研究，2007（6）：142-152.
[153]欧阳峣、易先忠、生延超，技术差距、资源分配与后发大国经济增长方式转换，中国工业经济，2012（6）：18-30.
[154]齐志新、陈文颖、吴宗鑫，工业轻重结构变化对能源消费的影响，中国工业经济，2007（2）：35-42.
[155]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，数量经济技术经济研究，2009（8）：29-43.
[156]单豪杰，中国资本存量K的再估算：1952～2006年，数量经济技术经济研究，2008（10）：17-31.
[157]史丹、吴利学、傅晓霞、吴滨，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，管理世界，2008（2）：35-43.
[158]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，世界经济，2008（9）：49-59.
[159]沈坤荣等，经济发展方式转变的机理与路径，人民出版社，2011.
[160]沈利生、王恒，增加值率下降意味着什么，经济研究，2006（3）：59-66.
[161]宋德勇，卢忠宝，中国碳排放影响因素分解及其周期性波动研究.中国人口·资源与环境，2009，19（3）：18-24.
[162]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（1981-2007），中国社会科学，2011（2）：91-106.
[163]孙传旺、刘希颖、林静，碳强度约束下中国全要素生产率测算和收敛性研究，金融研究，2010（6）：17-33.
[164]孙成浩，耿强，要素投入变化与经济增长的环境效应——基于中国省级面板数据的动态效应分析，南开经济研究，2009（1）：22-34.
[165]涂正革，环境、资源与工业的协调性，经济研究，2008（2）：93-105.
[166]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，经济研究，2008（5）：19-32.
[167]王兵、吴延瑞、颜鹏飞，中国区域环境效率与环境全要素生产率增长，经济研究，2010（5）：95-109.
[168]王海建，耗竭性资源管理与人力资本积累内生经济增长，管理工程学报，2000（3）：11-14.
[169]汪克亮、杨宝臣、杨力，环境约束下的中国全要素能源效率测度及其收敛性，管理学报，2012，9（7）：1071-1077.
[170]王少平、欧阳志刚，中国城乡收入差距对实际经济增长的阈值效应，中国社会科学，2008（2）：54-66.
[171]王少平、杨继生，中国工业能源调整的长期战略和短期措施——基于12个主要工业行业能源需求的综列协整分析，中国社会科学，2006（4）：88-96.
[172]王小鲁、樊纲、刘鹏，中国经济增长方式转换和增长可持续性，经济研究，2009（1）：4-16.
[173]王志平，生产效率的区域特征与生产率增长的分解——基于主成分分析与随机前沿超越对数生产函数的方法，数量经济技术经济研究，2010（1）：33-43.
[174]魏楚、沈满洪，能源效率与能源生产率——基于DEA方法的省际数据比较，数量经济技术经济研究，2007（9）：110-121.
[175]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，世界经济，2008（11）：77-85.
[176]魏楚、沈满洪，能源效率研究发展及趋势：一个综述，浙江大学学报（人文社会科学版），2009（3）：55-63.
[177]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，数量经济技术经济研究，2010，（9）：43-52.
[178]吴利学，中国能源效率波动：理论解释、数值模拟及政策含义，经济研究，2009（5）：130-142.
[179]吴延瑞，生产率对中国经济增长的贡献：新的估计，经济学（季刊），2008，7（3）：827-842.
[180]吴玉鸣、李建霞，中国省域能源消费的空间计量经济分析，中国人口资源与环境，2008，18（3）：93-98.
[181]许广月，碳排放收敛性：理论假说和中国的经验研究，数量经济技术经济研究，2010，（9）：31-42.
[182]杨红亮、史丹，能效研究方法和中国各地区能源效率的比较，经济理论与经济管理，2008（3）：12-20.
[183]杨继生，国内外能源相对价格对中国的能源效率，经济学家，2009（4）：90-97.
[184]余江，资源约束、结构变动与经济增长——理论与中国能源消费的经验，北京：人民出版社，2008.
[185]姚洋、张晔，中国出口品国内技术含量升级的动态研究——来自全国及江苏省、广东省的证据，中国社会科学，2008（2）：67-82.
[186]姚愉芳、陈杰、李花菊，结构变化的节能潜力计算的方法论研究，数量经济技术经济研究，2007（4）：115-123.
[187]俞毅，GDP增长与能源消耗的非线性门限，中国工业经济，2010（12）：57-65.
[188]袁富华，低碳经济约束下的中国潜在经济增长，经济研究，2010（8）：79-89.
[189]张军、陈诗一、Gary H. Jefferson，结构改革与中国工业增长，经济研究，2009（7）：4-20.
[190]张军、吴桂英、张吉鹏，中国省际物质资本存量估算：1952-2000，经济研究，2004（10）：35-44.
[191]张伟、吴文元，基于环境绩效的长三角都市圈全要素能源效率研究，经济研究，2011（10）：95-109.
[192]张友国，经济发展方式变化对中国碳排放强度的影响，经济研究，2010（4）：120-133.
[193]赵春雨、朱承亮，安树伟，生产率增长、要素重置与中国经济增长——基于分行业的经验研究，中国工业经济，2011（8）：79-88.
[194]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，经济研究，2007（8）：31-42.
[195]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，经济研究，2007（11）：18-31.
[196]张红凤、周峰、杨慧、郭庆，环境保护与经济发展双赢的规制绩效实证分析，经济研究，2009（3）：14-26.
[197]郑若谷、干春晖、余典范，转型期中国经济增长的产业结构和制度效应——基于一个随机前沿模型的研究，中国工业经济，2010（2）：58-67.
[2] Aigner D., C. A. K. Lovell and Schmidt P., Formulation and Estimation of StochasticFrontier Production Function Models. Journal of Econometrics,1977,(6):21-37.
[3] Almanidis P., Accounting for Heterogeneous Technologies in Banking Industry: ATime-Varying Stochastic Frontier Model with Threshold Effects, Working paper,Rice University,2011.
[4] Anastasios Xepapadeas, Economic Growth and the Environment, Intended as Chapter23in: Handbook of Environmental Economics, Volume3, K.-G. M ler and J.R.Vincent (eds), Elsevier B.V.,2005,1219-1271.
[5] Andersen P., Petersen N.C. A Procedure for Ranking Efficient Units in DataEnvelopment Analysis. Management Science,1993,39:1261-1264.
[6] Arellano M., Bond S., Some Tests of Specification for Panel Data: Monte CarloEvidence and an Application to Employment Equations, The Review of EconomicStudies,1991,58:277-297.
[7] Art B.v., Timmer M., Asia‘s Productivity Performance and Potential: TheContribution of Sectors and Structural Change, University of Groningen&Conference Board, The Netherlands, working paper,2003.
[8] Asafu-Adjaye, J. The Relationship between Energy Consumption, Energy Prices andEconomic Growth: Time Series Evidence from Asian Developing Countries. EnergyEconomics,2000,22:615-625.
[9] Aslanidis N., Iranzo S., Environment and development: is there a Kuznets curve forCO2emissions?, Applied Economics,2009,41:803-810.
[10]Bai J., Perron P., Estimating and Testing Linear Models with Multiple StructuralChanges. Econometrica,1998,66:47-78.
[11]Baltagi B.H., Econometric Analysis of Panel Data(Third Edition), Chichester, WestSussex, England: John Wiley&Sons Ltd.,2005.
[12]Battese G.E., Coelli T.J., Frontier Production Functions, Technical Efficiency andPanel Data: With Application to Paddy Farmers in India. The Journal of ProductivityAnalysis,1992,(3):153-169.
[13]Baumol W. J., Innovations and Growth: Two Common Misapprehensions. Journal ofPolicy Modeling,2003,25:435-444.
[14]Blundell R., Bond S., Initial conditions and moment restrictions in dynamic panel datamodels, Journal of Econometrics,1998,87:115-143.
[15]Bovenberg A. L. and Smulders S. A., Environmental Quality andPollution-augmenting Technological Change in a Two Sector Endogenous Growthmodel. Journal of Public Economics,1995,57(2):369-391.
[16]Bovenberg A. L. and Smulders S. A., Transitional Impacts of Environmental Policy inan Endogenous Growth Model. International Economic Review,1996,37:861-893.
[17]Caner M., Hansen B.E., Threshold Autoregression with a Unit Root, Econometrica,2001,69(6):1555-1596.
[18]Carson,Richard T.and Yongil Jeon, et al, The Relationship between Air PollutionEmissions and Income: U.S.Data. Environment and Development Economics,1997,2(4):433-450.
[19]Chambers R., Chung Y.H. and F re R., Benefit and Distance Function, Journal ofEconomic Theory,1996,70:407-419.
[20]Choi I., Saikkonen P., Testing linearity in cointegrating smooth transition regressions,Econometrics Journal,2004,(7):341–365.
[21]Choi I., Saikkonen P., Tests for Nonlinear Cointegration, Working paper, Departmentof Economics, Hong Kong University of Science and Technology,2008.
[22]Chua S., Economic Growth, Liberalization and the Environment: A Review of theEconomic Evidence. Annual Review of Environment.1999,24:391-430.
[23]Chung Y. H., F re R., Grosskopf S., Productivity and Undesirable Outputs: ADirectional Distance Function Approach, Journal of Environmental Management,1997,51:229-240.
[24]Coelli T., Estimators and Hypothesis Tests for a Stochastic Frontier Function: AMonte Carlo Analysis. Journal of Productivity Analysis,1995,(6):247-268
[25]Coelli T.J., Rao D.S. P., O'Donnell C.J., Battese G.E., An Introduction To EfficiencyAnd Productivity Analysis(Second Edition), Springer,2005.
[26]Common M. and Perrings C., Towards an Ecological Economics of Sustainability.Ecology Economic,1992,(6):7-34.
[27]Cornwell, C., Schmidt, P., and Sickles, R.C., Production frontiers with cross-sectionaland time series variation in effciency levels. Journal of Econometrics,1990,46:185-200.
[28]D.-H. Oh, J.-D. Lee, A metafrontier approach for measuring Malmquist productivityindex. Empirical Economics,2010,38(1):47-64.
[29]Daly Herman E., Steady-State Economics(2nd edition). Washington D.C.: IslandPress,1991.
[30]Daniel L. Millimet, John A. List, Thanasis Stengos, The Environmental KuznetsCurve: Real Progress or Misspecified Models? The Review of Economics andStatistics,2003,85(4):1038-1047.
[31]Dasgupta, P. and G. Heal., Economic Theory and Exhaustible Resources. Cambridge:Cambridge University Press,1979.
[32]Dijk D.v., Ter svirta T., Franses P.H., Smooth Transition Autoregressive Models—ASurvey of Recent Developments, Econometric Reviews,2002,21:1-47.
[33]Engle, R.F. and C.W.J. Granger, Co-integration and Error-correction: Representation,Estimation and Testing, Econometrica,1987,55:251-276.
[34]F re R., Grosskopf S., Noh D.W., Weber W., Characteristics of a pollutingtechnology: theory and practice, Journal of Econometrics,2005,126:469-492.
[35]F re R., Grosskopf S., Carl A., Jr. Pasurka, Environmental production functions andenvironmental directional distance functions, Energy,2007,32:1055-1066.
[36]Fagerberg J., Technological progress, structural change and productivity growth: acomparative study, Structural Change and Economic Dynamics,2000,(11):393-411.
[37]Fan S G, Zhang X B, Robinson S., Structural Change and Economic Growth in China,Review of Development Economics,2003,7(3):360-377.
[38]Feng T.W., Sun L.Y., Zhang Y., The relationship between energy consumptionstructure, economic structure and energy intensity in China, Energy Policy,2009,37:5475-5483.
[39]Fisher-Vanden K., The effects of market reforms on structural change: implicationsfor energy use and carbon emissions in China, The energy Journal,2003,24(3):27-62.
[40]Fisher-Vanden K., Gary H. J., Liu H. M., Tao Q., What is driving China‘s decline inenergy intensity?, Resource and Energy Economics,2004,26:77-97.
[41]Fried H. O., Lovell C. A. K. and Schmidt S. S., The Measurement of ProductiveEfficiency and Productivity Growth. New York: Oxford University Press,2008.
[42]Ghali, K.H., El-Sakka, M.I.T., Energy Use and Output Growth in Canada: AMultivariate Cointegration Analysis. Energy Economics,2004,26:225-238.
[43]González A., T. Ter svirta, and D. van Dijk.,2005, Panel smooth transition models,SSE/EFI Working Paper Series in Economics and Finance, No.604, StockholmSchool of Economics.
[44]Gordon R. J., Does the New Economy‘Measure up to the Great Inventions of thePast? Journal of Economic Perspectives,2000,14(4):49-74
[45]Gradus R. and Smulders S., The Trade-off between Environmental Care andLong-term Growth—Pollution in Three Prototype Growth Models. Journal ofEconomics,1993,58(1):25-51.
[46]Greening L.A., William B. D., Schipper L., Khrushch M., Comparison of sixdecomposition methods: application to aggregate energy intensity for manufacturingin10OECD countries, Energy Economics,1997,19:375-390.
[47]Greenwood, Hercowitz, and Krusell, Long-run Implications of Investment-SpecificTechnological change, American economic review,1997,87(3):363-382.
[48]Green W., Distinguishing between heterogeneity and ine ciency: stochastic frontieranalysis of theWorld Health Organization‘s panel data on national health care systems.Health Economics,2004,13:1-22.
[49]Green W., Reconsidering heterogeneity in panel data estimators of the stochasticfrontier model. Journal of Econometrics,2005,126:269-303.
[50]Grossman G.M. and Krueger A. B., Environmental impacts of a North American freetrade agreement. NBER working paper No3914,1991.
[51]Grossman G.M. and Krueger A. B., Economic Growth and Environment. TheQuarterly Journal of Economics.1995,110(2):353-377.
[52]Guan D., Hubacek K., Weber C.L., Peters G.P., Reiner D.M., The drivers of ChineseCO2emissions from1980to2030, Global Environmental Change,2008,18:626-634.
[53]Hamilton J.D., What is an Oil Shock? Journal of Econometrics,2003,113:363-398.
[54]Hansen B.E., Inference when a Nuisance Parameter is not identified under the NullHypothesis. Econometrica,1996,64:413-430.
[55]Hansen B.E., Threshold effects in non-dynamic panels: Estimation, testing, andinference. Journal of Econometrics,1999,93:345-368.
[56]Harberger A.C., A Vision of the Growth Process, American Economic Review,1998,88(1):1-32.
[57]Hofman B., Labar K., Structural Change and Energy Use: Evidence from China‘sProvinces, World Bank and University of Clermont-Ferrand, China Working PaperSeries No.6, working paper,2007.
[58]Homer-Dixon Tomans., The Ingenuity Gap: Can Poor Countries Adapt to ResourceScarcity? Population and Development Review,1995,21(3):1-26.
[59]Hu J.L., Lin C.H., Disaggregated Energy Consumption and GDP in Taiwan: AThreshold Co-integration Analysis. Energy Economics,2008,30:2342-2358.
[60]Hu Jin-Li, Wang Shih-Chuan, Total-factor Energy Efficiency of Regions in China,Energy Policy,2006,34:3206-3217.
[61]Hu J, Wang S., Total factor Energy Efficiency of Regions in China, Energy Policy,2006,34:3206-3217.
[62]Huffman W.E., Evenson R.E., Structural and productivity change in US agriculture,1950–1982, Agricultural Economics,2001,24:127-147.
[63]Isaksson A., Structural Change and Productivity Growth: A Review with Implicationsfor Developing Countries, Research and Statistics Branch, UNIDO, Working paper,08/2009.
[64]Jalil A., Mahmud S.F., Environment Kuznets curve for CO2emissions: Acointegration analysis for China, Energy Policy,2009,37:5167-5172.
[65]Kaufmann R.K., Davidsdottir B. and Garnham S., et al. The Determinants ofAtmospheric SO2Concentrations: Reconsidering the Environmental Kuznets Curve.Ecological Economics,1998,25(2):209-220.
[66]Kraft J. and Kraft A., On the Relationship between Energy and GNP. EnergyDevelopment,1978(3):401-403.
[67]Krüger J.J., Productivity and Structural Change: A Review of the Literature, Journalof Economic Surveys,2008,22(2):330-363
[68]Kumbhakar, S.C., Production frontiers, panel data, and time-varying technicalefficiency. Journal of Econometrics,1990,46:201-212.
[69]Kumbhakar S. C., Lovell C. A. K., Stochastic Frontier Analysis（随机边界分析）.刘晓宏，杨倩译，上海：复旦大学出版社，2007.
[70]Lantz, Feng. Assessing Income, Population and Technology Impacts on CO2Emissions in Canada: Where‘s the EKC? Ecological Economics,2006,57:229-238.
[71]Lee C.C., Chang C.P., Structural Breaks, Energy Consumption, and EconomicGrowth Revisited Evidence from Taiwan. Energy Economics,2005,27:857-872.
[72]Lee C.C., Chang C.P., Energy consumption and GDP revisited: A Panel Analysis ofDeveloped and Developing Countries. Energy Economics,2007,29:1206-1223.
[73]Liao Hua, Fan Y., Wei Y.M., What induced China‘s energy intensity to fluctuate:1997-2006?, Energy Policy,2007,35:4640-4649.
[74]Limam Y.R., and Miller S.M., Explaining Economic Growth: Factor Accumulation,Total Factor Productivity Growth, and Production Efficiency Improvement, workingpaper, March,2004.
[75]Lise, W., Montfort, K.E., Energy Consumption and GDP in Turkey: Is there aCo-integration Relationship? Energy Economics,2007,29:1166-1178.
[76]Liu N., Ang B.W., Factors shaping aggregate energy intensity trend for industry:Energy intensity versus product mix, Energy Economics,2007,29:609-635.
[77]Ma Chunbo, Stern D. I., China's changing energy intensity trend: A decompositionanalysis, Energy Economics,2008,30:1037-1053.
[78]Ma H.Y., Oxley L., Gibson J., China's energy economy: A survey of the literature,Economic Systems,2010,34:105-132.
[79]Medlock K.B., Soligo R., Economic Development and End-Use Energy Demand,Energy Journal,2001,22(2):77-105.
[80]Moon Y. S. and Soon Y. H., Productive Energy Consumption and Economic Growth:an Endogenous Growth Model and its Empirical Application. Resource and EnergyEconomics,1996,18:189-200.
[81]Moore, J. H., A Measure of Structural Change in Output, The Review of Income andWealth,1978,(3):105-117.
[82]Murillo-Zamorano L. R., Economic Efficiency and Frontier Techniques, Journal ofEconomic Surveys,2004,18(1):33-77.
[83]Orea L., Kumbhakar S.C., Efficiency measurement using a latent class stochasticfrontier model. Empirical Economics,2004,29:169-183.
[84]Oulton N., Srinivasan S., Productivity growth in UK industries,1970-2000: structuralchange and the role of ICT, Paper to be presented at the―Information Technology,Productivity and Growth‖conference, National Institute of Economic and SocialResearch, London,28-29October,2004.
[85]Panayotou T., Empirical Tests and Policy Analysis of Environmental Degradation atDifferent Stages of Economic Development. ILO Technology and EmploymentProgramme Working Paper WP238,1993.
[86]Panayotou T., Demystifying the Environmental Kuznets Curve: Turning a Black Boxinto a Policy Tool. Environment and Development Economics,1997,2(4):465-484.
[87]Philip Andrews-Speed, China‘s ongoing energy efficiency drive: Origins, progressand prospects, Energy Policy,2009,37:1331-1344.
[88]Ramakrishnan Ramanathan, An Analysis of Energy Consumption and CarbonDioxide Emissions in Countries of the Middle East and North Africa. Energy,2005,30:2831-2842.
[89]Rambaldi A. N., Rao D.S.P., Dolan，D．, Measuring Productivity Growth PerformanceUsing Metafrontiers with Applications to Regional Productivity Growth Analysis in aGlobal Context, In: O‘Donnell C.J., Australian Meeting of the Econometric SocietyESAM07,2007, Brisbane,1-33.
[90]Romer David, Advanced Macroeconomics(2ndedition). Shanghai: ShanghaiUniversity of Finance&Economics Press,2001,35-42.
[91]Sch fer A. Structural change in energy use, Energy Policy,2005,33:429-437.
[92]Scholz C. M. and Georg Ziemes, Exhaustible Resources, Monopolistic Competitionand Endogenous Growth. Environmental&Resource Economics,1999,13(2):169-185.
[93]Schmidt P., Sickles R.C., Production frontiers and panel data. Journal of Business andEconomic Statistics,1984,(2):367-374.
[94]Selden T.M., Song D., Environmental quality and Development: Is there a KuznetsCurve for Air Pollution Emissions? Journal of Environmental Economics andManagement,1994,27:147-162.
[95]Sheehan P., Sun F., Energy Use and CO2Emissions in China: Retrospect andProspect. Climate Change Project Working Paper Series No.4, Centre for StrategicEconomic Studies, Victoria University,2006.
[96]Smulders S., Entropy, Environment and Endogenous Economic Growth. InternationalTax and Public Finance,1995(2):319-338.
[97]Smulders S., Economic Growth and Environmental Quality. Intended as Chapter21in:Principles of Environmental Economics, Henk Folmer and Landis Gabel (eds),Edward Elgar,2000.
[98]Solow R. M., Intergenerational Equity and Exhaustible Resources. Review ofEconomic Studies,1974,41:29-45.
[99]Stern, D.I., A Multivariate Cointegration Analysis of the Role of Energy in the USMacroeconomy. Energy Economics,2000,22:267-283.
[100] Stern, D.I., The Rise and Fall of the Environmental Kuznets Curve. WorldEconomics,2004,32(8):1419-1439.
[101] Stiglitz J. E., Growth with Exhaustible Natural Resources: Efficient and OptimalGrowth Paths. Review of Economic Studies,1974,41:123-138.
[102] Stokey N L., Are there Limits to Growth? International Economic Review,1998,39(1):1-31.
[103] Syrquin M., Patterns of Structural Change, in H. Chenery and T.N. Srinivasan, eds.,Handbook of Development Economics, Volume1. Elsevier,1995:203-273.
[104] Ter svirta, T.; Tj stheim, D.&Granger, C. W., Modeling nonlinear economic timeseries, Unpublished Book,2008.
[105] Thomas Mike., Climate Change and the Stern Review: An Overview and Commentfrom Future in Our Hands Network, http://www.climatecooperation.org/Pindex.php?title=Stern–Review PMI ke-Thomas-2.2007.
[106] Timmer M.P., Szirmai A., Productivity growth in Asian manufacturing: thestructural bonus hypothesis examined, Structural Change and Economic Dynamics,2000,(11):371–392.
[107] Tol R. S. J., Stephen W. Pacala and Robert Socolow. Understanding Long-TermEnergy Use and Carbon Dioxide Emissions in the USA. Working Paper No.107,2006.
[108] Tsionas E.G., Tran K.C., Bayesian Inference in Threshold Stochastic FrontierModels, working paper,2007.
[109] Unander F., Decomposition of manufacturing energy-use in IEA countries: How dorecent developments compare with historical long-term trends?, Applied Energy,2007,84:771-780.
[110] Unruh, G.C. and W.R. Moomaw, An Alternative Analysis of Apparent EKC-typeTransitions. Ecological Economics,1998,25:221-229.
[111] Wang C., Chen Jining, Zou J., Decomposition of energy-related CO2emission inChina:1957-2000, Energy,2005,30:73-83.
[112] Wang H-J., Schmidt P., One-Step and Two-Step Estimation of the Effects ofExogenous Variables on Technical Efficiency Levels, Journal of ProductivityAnalysis,2002,18:129-144.
[113] Wang J. S.&He C.F., Technological Progress, Structural Change and China‘sEnergy Efficiency, Chinese Journal of Population, Resources and Environment,2009,7(2):44-49.
[114] Weber C.L., Measuring structural change and energy use: Decomposition of the USeconomy from1997to2002, Energy Policy,2009,37:1561-1570.
[115] Wei S.Z.C., Chen C.F., Zhu Z., Economic growth and Energy ConsumptionRevisited—Evidence from Linear and Nonlinear Granger Causality. EnergyEconomics,2008,30:3063-3076.
[116] Wen G., Cao Z., An Empirical Study on the Relationship between China‘s EconomicDevelopment and Environmental Quality——Testing China‘s EnvironmentalKuznets Curve, Journal of Sustainable Development,2009,2(2):65-72.
[117] William T. Harbaugh, Arik Levinson, David Molloy Wilson, Reexamining theEmpirical Evidence for an Environmental Kuznets Curve. The Review ofEconomics and Statistics,2002,84(3):541-551.
[118] Wing I.S., Explaining the declining energy intensity of the U.S. economy, Resourceand Energy Economics,2008,30:21-49.
[119] Wooldridge J.M., Econometric Analysis of Cross Section and Panel Data,Cambridge, MA: The MIT Press,2002.
[120] Wu Libo, Kaneko Shinji, Matsuoka Shunji, Driving forces behind the stagnancy ofChina‘s energy-related CO2emissions from1996to1999: the relative importance ofstructural change, intensity change and scale change, Energy Policy,2005,33:319-335.
[121] Wu N., Energy Intensity, Renewable Energy, and Economic Development:Examining Three Provinces in China, Working paper, Department of Urban Studiesand Planning, MIT.2008.
[122] Yélou C., Larue B., Tran K.C., Threshold effects in panel data stochastic frontiermodels of dairy production in Canada, Economic Modelling,2010,27:641-647
[123] Yuan C. Q., Liu S. F., Fang Z. G., Xie N. M., The relation between Chineseeconomic development and energy consumption in the different periods, EnergyPolicy,2010,38:5189-5198.
[124] Zhang H.B., Qi Y., A Structure Decomposition Analysis of China‘sProduction-Source CO2Emission:1992-2002, Environment and ResourceEconomics,2011,49:65-77.
[125] Zhang Z.X., Cheng X.M., Energy consumption, carbon emissions, and economicgrowth in China, Ecological Economics,2009,68:2706-2712.
[126] Zhang Z.X., Assessing China‘s carbon intensity pledge for2020: stringency andcredibility issues and their implications, Environment Economic Policy Study, DOI10.1007/s10018-011-0012-4, Published online:2011,30March.
[127]蔡昉、都阳、王美艳，经济发展方式转变与节能减排内在动力，经济研究，2008（6）：4-11.
[128]陈诗一，能源消耗、二氧化碳排放与中国工业的可持续发展，经济研究，2009（4）：41-55.
[129]陈诗一，中国的绿色工业革命:基于环境全要素生产率视角的解释（1980-2008），经济研究，2010（11）：21-34.
[130]陈诗一，节能减排、结构调整与工业发展方式转变研究，北京：北京大学出版社，2011.
[131]程永宏，改革以来全国总体基尼系数的演变及其城乡分解，中国社会科学，2007（4）：45-60.
[132]干春晖、郑若谷、余典范，中国产业结构变迁对经济增长和波动的影响，经济研究，2011（5）：4-16.
[133]高凌云、王洛林，进口贸易与工业行业全要素生产率，经济学（季刊），2010（1）：391-414.
[134]胡鞍钢、郑京海、高宇宁、张宁、许海萍，考虑环境因素的省级技术效率排名（1999-2005），经济学（季刊），2008，7（3）：933-960.
[135]胡鞍钢，中国的绿色低碳发展，载于薛进军主编《中国低碳经济发展报告》.北京：社会科学文献出版社，2011，257-267.
[136]胡初枝，黄贤金，钟太洋，谭丹，中国碳排放特征及其动态演进分析，中国人口·资源与环境，2008，18（3）：38-42.
[137]金碚、吕铁、邓洲，中国工业结构转型升级：进展、问题与趋势，中国工业经济，2011（2）：5-15.
[138]赖永剑、朱卫平，异质性的技术俱乐部与中国地区工业增长——基于潜类别随机前沿模型的研究，数量经济技术经济研究，2011（6）：107-119.
[139]李国志、李宗植，中国二氧化碳排放的区域差异和影响因素研究，中国人口、资源与环境，2010，（5）：22-27.
[140]李科、王少平，中国产业结构高端化和碳减排——基于动态面板平滑转换模型的经验分析，中国数量经济年会2011年年会论文.
[141]李世祥、成金华，中国主要工业省区能源效率分析：1990～2006年，数量经济技术经济研究，2008（10）：32-43.
[142]李小平、卢现祥，中国制造业的结构变动和生产率增长，世界经济，2007（5）：52-64.
[143]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，经济学（季刊），2008（1）：549-564.
[144]李艳梅、张雷，中国能源消费增长原因分析与节能途径探讨，中国人口.资源与环境，2008，18（3）：83-87.
[145]林伯强、蒋竺均，中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析，管理世界，2009，（4）：27-36.
[146]林伯强、刘希颖，中国城市化阶段的碳排放:影响因素和减排策略，经济研究，2010（8）：66-78.
[147]林伯强、孙传旺，如何在保障中国经济增长前提下完成碳减排目标，中国社会科学，2011（1）：64-76.
[148]林毅夫、苏剑，论我国经济增长方式的转换，管理世界，2007（11）：5-13.
[149]刘畅、孔宪丽、高铁梅，中国能源消耗强度变动机制与价格非对称效应研究——基于结构VEC模型的计量分析，中国工业经济，2009（3）：59-70.
[150]吕铁、周叔莲，中国的产业结构升级与经济增长方式转变，管理世界，1999（1）：113-125.
[151]吕铁，制造业结构变化对生产率增长的影响研究，管理世界，2002（2）：87-94.
[152]罗洁，自然资源与经济增长：资源瓶颈及其解决途径，经济研究，2007（6）：142-152.
[153]欧阳峣、易先忠、生延超，技术差距、资源分配与后发大国经济增长方式转换，中国工业经济，2012（6）：18-30.
[154]齐志新、陈文颖、吴宗鑫，工业轻重结构变化对能源消费的影响，中国工业经济，2007（2）：35-42.
[155]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，数量经济技术经济研究，2009（8）：29-43.
[156]单豪杰，中国资本存量K的再估算：1952～2006年，数量经济技术经济研究，2008（10）：17-31.
[157]史丹、吴利学、傅晓霞、吴滨，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，管理世界，2008（2）：35-43.
[158]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，世界经济，2008（9）：49-59.
[159]沈坤荣等，经济发展方式转变的机理与路径，人民出版社，2011.
[160]沈利生、王恒，增加值率下降意味着什么，经济研究，2006（3）：59-66.
[161]宋德勇，卢忠宝，中国碳排放影响因素分解及其周期性波动研究.中国人口·资源与环境，2009，19（3）：18-24.
[162]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（1981-2007），中国社会科学，2011（2）：91-106.
[163]孙传旺、刘希颖、林静，碳强度约束下中国全要素生产率测算和收敛性研究，金融研究，2010（6）：17-33.
[164]孙成浩，耿强，要素投入变化与经济增长的环境效应——基于中国省级面板数据的动态效应分析，南开经济研究，2009（1）：22-34.
[165]涂正革，环境、资源与工业的协调性，经济研究，2008（2）：93-105.
[166]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，经济研究，2008（5）：19-32.
[167]王兵、吴延瑞、颜鹏飞，中国区域环境效率与环境全要素生产率增长，经济研究，2010（5）：95-109.
[168]王海建，耗竭性资源管理与人力资本积累内生经济增长，管理工程学报，2000（3）：11-14.
[169]汪克亮、杨宝臣、杨力，环境约束下的中国全要素能源效率测度及其收敛性，管理学报，2012，9（7）：1071-1077.
[170]王少平、欧阳志刚，中国城乡收入差距对实际经济增长的阈值效应，中国社会科学，2008（2）：54-66.
[171]王少平、杨继生，中国工业能源调整的长期战略和短期措施——基于12个主要工业行业能源需求的综列协整分析，中国社会科学，2006（4）：88-96.
[172]王小鲁、樊纲、刘鹏，中国经济增长方式转换和增长可持续性，经济研究，2009（1）：4-16.
[173]王志平，生产效率的区域特征与生产率增长的分解——基于主成分分析与随机前沿超越对数生产函数的方法，数量经济技术经济研究，2010（1）：33-43.
[174]魏楚、沈满洪，能源效率与能源生产率——基于DEA方法的省际数据比较，数量经济技术经济研究，2007（9）：110-121.
[175]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，世界经济，2008（11）：77-85.
[176]魏楚、沈满洪，能源效率研究发展及趋势：一个综述，浙江大学学报（人文社会科学版），2009（3）：55-63.
[177]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，数量经济技术经济研究，2010，（9）：43-52.
[178]吴利学，中国能源效率波动：理论解释、数值模拟及政策含义，经济研究，2009（5）：130-142.
[179]吴延瑞，生产率对中国经济增长的贡献：新的估计，经济学（季刊），2008，7（3）：827-842.
[180]吴玉鸣、李建霞，中国省域能源消费的空间计量经济分析，中国人口资源与环境，2008，18（3）：93-98.
[181]许广月，碳排放收敛性：理论假说和中国的经验研究，数量经济技术经济研究，2010，（9）：31-42.
[182]杨红亮、史丹，能效研究方法和中国各地区能源效率的比较，经济理论与经济管理，2008（3）：12-20.
[183]杨继生，国内外能源相对价格对中国的能源效率，经济学家，2009（4）：90-97.
[184]余江，资源约束、结构变动与经济增长——理论与中国能源消费的经验，北京：人民出版社，2008.
[185]姚洋、张晔，中国出口品国内技术含量升级的动态研究——来自全国及江苏省、广东省的证据，中国社会科学，2008（2）：67-82.
[186]姚愉芳、陈杰、李花菊，结构变化的节能潜力计算的方法论研究，数量经济技术经济研究，2007（4）：115-123.
[187]俞毅，GDP增长与能源消耗的非线性门限，中国工业经济，2010（12）：57-65.
[188]袁富华，低碳经济约束下的中国潜在经济增长，经济研究，2010（8）：79-89.
[189]张军、陈诗一、Gary H. Jefferson，结构改革与中国工业增长，经济研究，2009（7）：4-20.
[190]张军、吴桂英、张吉鹏，中国省际物质资本存量估算：1952-2000，经济研究，2004（10）：35-44.
[191]张伟、吴文元，基于环境绩效的长三角都市圈全要素能源效率研究，经济研究，2011（10）：95-109.
[192]张友国，经济发展方式变化对中国碳排放强度的影响，经济研究，2010（4）：120-133.
[193]赵春雨、朱承亮，安树伟，生产率增长、要素重置与中国经济增长——基于分行业的经验研究，中国工业经济，2011（8）：79-88.
[194]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，经济研究，2007（8）：31-42.
[195]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，经济研究，2007（11）：18-31.
[196]张红凤、周峰、杨慧、郭庆，环境保护与经济发展双赢的规制绩效实证分析，经济研究，2009（3）：14-26.
[197]郑若谷、干春晖、余典范，转型期中国经济增长的产业结构和制度效应——基于一个随机前沿模型的研究，中国工业经济，2010（2）：58-67.