一种嵌入空间计量分析的全要素生产率核算改进方法
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摘要
研究目标:在空间计量分析框架下对全要素生产率核算的索洛余值法做出改进,从而使核算结果更为精准。研究方法:将索洛余值法中的生产函数由非空间模型拓展为通用嵌套空间模型及其退化模型,并考察时空权重矩阵内生或外生设定和投入要素二元或多元假设下全要素生产率的核算方法,还将之应用于省级层面全要素生产率核算的算例中。研究发现:嵌入空间计量分析的索洛余值改进方法相比传统方法更为精准,其关键在于通用嵌套空间模型及其退化模型的优选过程,且不同最优模型对应不同的要素投入份额计算公式。研究创新:在空间计量分析框架下实现了对全要素生产率核算的索洛余值法的改进。研究价值:有利于实现空间计量分析和索洛余值法的有机结合。
Research Objectives:Improve the Solow residual method for total factor productivity(TFP)calculating under the framework of spatial econometrical analysis.Research Methods:Extend the production function of the Solow residual method from non-spatial model to general nesting spatial model(GNSM)and its degradation models,and analyze the principles of calculating TFP under the Solow residual method with the extended models,which might have different spatial temporal weight matrices(endogenous or exogenous)and input factors(two or more).Moreover,this paper applies the principles into the TFP calculating of Chinese 31 provinces during 1990～2016.Research Findings:The improved Solow residual method is essentially different in that GNSM and its degradation models have different calculating formulas of share of input factors,which decided TFP and its growth rate;TFP should be calculated by the optimal model and its corresponding share of input factors,which can be chose by hypothesis test;exogenous spatial weight matrix should be employed in the improved method.Research Innovations:Promote an improved Solow residual method under the framework of spatial econometric analysis so that TFP can be calculated more accurately.Research Value:Realize the organic combination of spatial econometric analysis and the Solow residual method for TFP calculating.
Research Objectives:Improve the Solow residual method for total factor productivity(TFP)calculating under the framework of spatial econometrical analysis.Research Methods:Extend the production function of the Solow residual method from non-spatial model to general nesting spatial model(GNSM)and its degradation models,and analyze the principles of calculating TFP under the Solow residual method with the extended models,which might have different spatial temporal weight matrices(endogenous or exogenous)and input factors(two or more).Moreover,this paper applies the principles into the TFP calculating of Chinese 31 provinces during 1990～2016.Research Findings:The improved Solow residual method is essentially different in that GNSM and its degradation models have different calculating formulas of share of input factors,which decided TFP and its growth rate;TFP should be calculated by the optimal model and its corresponding share of input factors,which can be chose by hypothesis test;exogenous spatial weight matrix should be employed in the improved method.Research Innovations:Promote an improved Solow residual method under the framework of spatial econometric analysis so that TFP can be calculated more accurately.Research Value:Realize the organic combination of spatial econometric analysis and the Solow residual method for TFP calculating.
引文
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[2]Ackerberg D.,Benkard L.,Steven B.,Ariel P.,2007,Econometric Tools for Analyzing Market Outcomes[A],in Heckman J.J.,Leamer E.E.(eds.),Handbook of Econometrics[C],Chapter 63Elsevier.
[3]Blundell R.,Bond S.,1998,Initial Conditions and Moment Restrictions in Dynamic Panel Data Models[J],Journal of Econometrics,87(1),115~143.
[4]Caves D.W.,Christensen L.R.,Diewert W.E.,1982,The Economic Theory of Index Numbers and the Measurement of Input,Output,and Productivity[J],Econometrica,50(6),1393~1414.
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[6]Chang T.,Hu J.,Chou R.Y.,Sun L.,2012,The Sources of Bank Productivity Growth in China During 2002~2009:A Disaggregation View[J],Journal of Banking&Finance,36(7),1997~2006.
[7]Charnes A.,Cooper W.W.,Rhodes E.,1978,Measuring the Efficiency of Decision Making U-nits[J],European Journal of Operational Research,2(6),429~444.
[8]DubéJ.,Legros D.,Thériault M.,Rosiers F.,2014,A Spatial Difference-in-Differences Estimator to Evaluate the Effect of Change in Public Mass Transit Systems on House Prices[J],Transportation Research Part B:Methodological,64,24~40.
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[10]Farrell M.J.,1957,The Measurement of Productive Efficiency[J],Journal of the Royal Statistical Society.Series A(General),120(3),253~290.
[11]Glass A.J.,Kenjegalieva K.,2019,A Spatial Productivity Index in the Presence of Efficiency Spillovers:Evidence for U.S.Banks,1992~2015[J],European Journal of Operational Research,273(3),1165~1179.
[12]Jorgenson D.W.,Gollop F.M.,Fraumeni B.M.,1987,Productivity and U.S.Economic Growth[M],Harvard University Press.
[13]Kumbhakar S.C.,Lovell C.A.K.,2000,Stochastic Frontier Analysis[M],Cambridge University Press.
[14]LeSage J.P.,Pace R.K.,2009,Introduction to Spatial Econometrics[M],CRC Press Taylor&Francis Group.
[15]Levinsohn J.,Petrin,A.,2003,Estimating Production Functions Using Inputs to Control for Unobservables[J],Review of Economic Studies,70(2),317~341.
[16]Malmquist S.,1953,Index Numbers and Indifference Surfaces[J],Trabajos de Estadistica,4(2),209~242.
[17]Olley G.S.,Pakes A.,1996,The Dynamics of Productivity in the Telecommunications Equipment Industry[J],Econometrica,64(6),1263~1297.
[18]Solow R.M.,1957,Technical Change and the Aggregate Production Function[J],Review of E-conomics and Statistics,39(3),312~320.
[19]Theil H.,1965,The Information Approach to Demand Analysis[J],Econometrica,33(1),67~87.
[20]Tientao A.,Legros D.,Pichery M.C.,2016,Technology Spillover and TFP Growth:A Spatial Durbin Model[J],International Economics,145,21~31.
[21]Tone K.,2001,A Slacks-Based Measure of Efficiency in Data Envelopment Analysis[J],European Journal of Operational Research,130(3),498~509.
[22]陈红蕾、覃伟芳:《中国经济的包容性增长:基于包容性全要素生产率视角的解释》[J],《中国工业经济》2014年第1期。
[23]谌莹、张捷:《碳排放、绿色全要素生产率和经济增长》[J],《数量经济技术经济研究》2016年第8期。
[24]程惠芳、陈超:《开放经济下知识资本与全要素生产率---国际经验与中国启示》[J],《经济研究》2017年第10期。
[25]范巧、Hudson Darren:《一种新的包含可变时间效应的内生时空权重矩阵构建方法》[J],《数量经济技术经济研究》2018年第1期。
[26]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年第6期。
[27]王兵、刘光天:《节能减排与中国绿色经济增长---基于全要素生产率的视角》[J],《中国工业经济》2015年第5期。
[28]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年第2期。
[29]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年第8期。
[30]余泳泽:《异质性视角下中国省际全要素生产率再估算:1978~2012》[J],《经济学(季刊)》2017年第3期。
[31]袁礼、欧阳峣:《发展中大国提升全要素生产率的关键》[J],《中国工业经济》2018年第6期。
[32]张志强:《微观企业全要素生产率测度方法的比较与应用》[J],《数量经济技术经济研究》2015年第12期。
[33]郑玉歆:《全要素生产率的再认识---用TFP分析经济增长质量存在的若干局限》[J],《数量经济技术经济研究》2007年第9期。
[34]周黎安:《中国地方官员的晋升锦标赛模式研究》[J],《经济研究》2007年第7期。
[35]朱英明:《区域制造业规模经济、技术变化与全要素生产率---产业集聚的影响分析》[J],《数量经济技术经济研究》2009年第10期。
[2]Ackerberg D.,Benkard L.,Steven B.,Ariel P.,2007,Econometric Tools for Analyzing Market Outcomes[A],in Heckman J.J.,Leamer E.E.(eds.),Handbook of Econometrics[C],Chapter 63Elsevier.
[3]Blundell R.,Bond S.,1998,Initial Conditions and Moment Restrictions in Dynamic Panel Data Models[J],Journal of Econometrics,87(1),115~143.
[4]Caves D.W.,Christensen L.R.,Diewert W.E.,1982,The Economic Theory of Index Numbers and the Measurement of Input,Output,and Productivity[J],Econometrica,50(6),1393~1414.
[5]Chambers R.,Fre R.,Grosskopf S.,1996,Productivity Growth in APEC Country[J],Pacific Economic Review,1(3),181~190.
[6]Chang T.,Hu J.,Chou R.Y.,Sun L.,2012,The Sources of Bank Productivity Growth in China During 2002~2009:A Disaggregation View[J],Journal of Banking&Finance,36(7),1997~2006.
[7]Charnes A.,Cooper W.W.,Rhodes E.,1978,Measuring the Efficiency of Decision Making U-nits[J],European Journal of Operational Research,2(6),429~444.
[8]DubéJ.,Legros D.,Thériault M.,Rosiers F.,2014,A Spatial Difference-in-Differences Estimator to Evaluate the Effect of Change in Public Mass Transit Systems on House Prices[J],Transportation Research Part B:Methodological,64,24~40.
[9]Elhorst J.P.,2014,Spatial Econometrics:From Cross-Sectional Data to Spatial Panels[M],Heidelberg,Dordrecht,Springer.
[10]Farrell M.J.,1957,The Measurement of Productive Efficiency[J],Journal of the Royal Statistical Society.Series A(General),120(3),253~290.
[11]Glass A.J.,Kenjegalieva K.,2019,A Spatial Productivity Index in the Presence of Efficiency Spillovers:Evidence for U.S.Banks,1992~2015[J],European Journal of Operational Research,273(3),1165~1179.
[12]Jorgenson D.W.,Gollop F.M.,Fraumeni B.M.,1987,Productivity and U.S.Economic Growth[M],Harvard University Press.
[13]Kumbhakar S.C.,Lovell C.A.K.,2000,Stochastic Frontier Analysis[M],Cambridge University Press.
[14]LeSage J.P.,Pace R.K.,2009,Introduction to Spatial Econometrics[M],CRC Press Taylor&Francis Group.
[15]Levinsohn J.,Petrin,A.,2003,Estimating Production Functions Using Inputs to Control for Unobservables[J],Review of Economic Studies,70(2),317~341.
[16]Malmquist S.,1953,Index Numbers and Indifference Surfaces[J],Trabajos de Estadistica,4(2),209~242.
[17]Olley G.S.,Pakes A.,1996,The Dynamics of Productivity in the Telecommunications Equipment Industry[J],Econometrica,64(6),1263~1297.
[18]Solow R.M.,1957,Technical Change and the Aggregate Production Function[J],Review of E-conomics and Statistics,39(3),312~320.
[19]Theil H.,1965,The Information Approach to Demand Analysis[J],Econometrica,33(1),67~87.
[20]Tientao A.,Legros D.,Pichery M.C.,2016,Technology Spillover and TFP Growth:A Spatial Durbin Model[J],International Economics,145,21~31.
[21]Tone K.,2001,A Slacks-Based Measure of Efficiency in Data Envelopment Analysis[J],European Journal of Operational Research,130(3),498~509.
[22]陈红蕾、覃伟芳:《中国经济的包容性增长:基于包容性全要素生产率视角的解释》[J],《中国工业经济》2014年第1期。
[23]谌莹、张捷:《碳排放、绿色全要素生产率和经济增长》[J],《数量经济技术经济研究》2016年第8期。
[24]程惠芳、陈超:《开放经济下知识资本与全要素生产率---国际经验与中国启示》[J],《经济研究》2017年第10期。
[25]范巧、Hudson Darren:《一种新的包含可变时间效应的内生时空权重矩阵构建方法》[J],《数量经济技术经济研究》2018年第1期。
[26]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年第6期。
[27]王兵、刘光天:《节能减排与中国绿色经济增长---基于全要素生产率的视角》[J],《中国工业经济》2015年第5期。
[28]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年第2期。
[29]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年第8期。
[30]余泳泽:《异质性视角下中国省际全要素生产率再估算:1978~2012》[J],《经济学(季刊)》2017年第3期。
[31]袁礼、欧阳峣:《发展中大国提升全要素生产率的关键》[J],《中国工业经济》2018年第6期。
[32]张志强:《微观企业全要素生产率测度方法的比较与应用》[J],《数量经济技术经济研究》2015年第12期。
[33]郑玉歆:《全要素生产率的再认识---用TFP分析经济增长质量存在的若干局限》[J],《数量经济技术经济研究》2007年第9期。
[34]周黎安:《中国地方官员的晋升锦标赛模式研究》[J],《经济研究》2007年第7期。
[35]朱英明:《区域制造业规模经济、技术变化与全要素生产率---产业集聚的影响分析》[J],《数量经济技术经济研究》2009年第10期。