中国区域技术创新绩效计量研究
|
摘要
研究区域技术创新体系的现象与规律是促进区域技术创新的重要组成部分，是实现我国区域可持续协调发展的重要举措，也是实现国家区域发展战略的重要步骤。要建立有效的区域技术创新体系就离不开区域技术创新投入。目前，我国各区域以研发（R&D）投入为主要标志的区域技术创新投入有了较大提高，政界、业界和学界对区域技术创新直接绩效（区域技术创新投入与直接产出的关系）评价问题的研究也较为深入，出现了大量研究成果，也得到了一些有益结论。但是，区域技术创新投入会对我国宏观经济产生多大影响等区域技术创新投入的间接绩效及其评价问题却至今还没有引进足够重视。
本文研究正是从这一点出发，主要应用空间统计、空间计量经济学、空间过滤、带异质性的随机前沿模型、分位数回归、面板单位根、面板协整等现代计量方法，完成对区域技术创新直接绩效的研究之后，在理论分析的基础上，建立区域技术创新投入到国家宏观经济发展的传导模型以及中国小型宏观计量经济协整模型，并且通过两个模型联接，分析评价我国区域技术创新投入对我国主要宏观经济变量的影响，即中国区域技术创新的间接绩效问题。论文把区域技术创新绩效放在国家宏观经济发展的背景下来考察，相对于已有的技术创新绩效评价文献来说，在技术创新绩效评价内容方面，无疑具有创新意义。论文研究主要得出如下结论：
第一，研究发现中国区域技术创新活动的空间相关性非常明显，存在着向东部地区聚集的趋势。区域专利申请量的基尼系数分析表明，中国区域技术创新的空间集中性呈现增强趋势。总体上大约有40%的省域创新活动显现出相似的高高的空间关联形式。研究也说明在区域行政中心300公里的范围内，区域技术创新活动呈现出强烈的正自空间相关性；从离行政中心大约1400公里开始，区域技术创新活动开始出现负自相关性；在大约2800公里的时，区域技术创新活动呈现出明显的负空间自相关性。中国区域技术创新存在条件收敛和条件门槛收敛效应，从而存在着三大收敛俱乐部特征。人力资本低强度区域存在绝对收敛现象，而人力资本中高强度区域存在条件收敛现象。面板门槛回归模型解决了收敛理论中的俱乐部效应内生性问题。
第二，研究发现中国区域技术创新投入产出代理变量具有较强空间相关性，空间过滤方法可以有效地消除了变量空间相关性，进而可以应用传统回归模型对其进行回归分析。在本文所考虑的模型中，区域技术创新投入与产出代理变量之间存在着协整关系。对中国区域知识生产函数的研究发现，研发经费支出、科技活动人数、外商投资总额、区域进口、区域自身知识存量及邻近区域知识存量等六大因素对区域技术创新产出在统计上有显著影响，研发经费支出、科技活动人数对技术创新产出的弹性分别为0.2397和0.5133，区域内部知识存量弹性要比相邻区域知识存量弹性大20%左右。分位回归分析表明，上述六大因素的区域技术创新产出弹性各自具有一定的内在波动性。进一步分析知识溢出对区域技术创新产出的弹性时可以发现，中国区域知识溢出存在着双向溢出现象。知识正向溢出大致发生在以区域行政中心为圆心，以（100，600）公里及（900，1200）公里为半径的圆环区域内，知识溢出对区域技术创新产出弹性分别为0.2214和0.9618；知识负向溢出大致发生在以区域行政中心为圆心，以（600，900）公里及（1200，1500）公里为半径的圆环区域内，其弹性分别为-0.1561和-0.5561。
第三，研究发现影响中国区域技术创新效率的环境因素都是平稳变量，区域技术创新投入与产出代理变量之间存在协整关系。中国区域技术创新效率显东部高、中部中、西部低的空间分布特征。西部地区技术创新效率低，但增长率较高，西部地区技术创新的追赶迹象已经出现。影响区域技术创新效率的因素在全国及三大区域之间略有差异。创新主体参与强度和区域市场开放度是影响全国及三大区域技术创新效率的主要的显著因素。政府资助、金融机构支持等其他因素对全国及三大区域技术创新效率的影响方向和显著性程度各不相同。
第四，研究中国区域技术创新宏观绩效的中国区域─宏观计量经济协整模型有三个特征，即模型根据SNA体系建立并且是一个供需双导向的年度宏观经济计量模型、行为方程设计依靠经济理论和数据特征的双重驱动、是一个协整计量经济模型。对东中西部三大区域研发投入增加的宏观经济效应分析表明：三大区域研发投入同等幅度的增加对八大主要宏观经济变量的影响关系都是相同的；三大区域研发投入的增加，对八大主要宏观经济变量影响程度的排序也几乎是相同的；三大区域研发投入增加，对主要宏观经济变量影响程度的大小按东中西的顺序排列。对八大区域研发投入增加的宏观经济效应分析也得出类似结论。情景分析特别发现，中国区域研发投入增加有利于中国城市化发展，有利于中国居民收入增加。
The study of the phenomenon and the rule of regional innovation system is theimportant component of promoting regional innovation and is the important measures forrealizing the regional sustainable development and is also the immportant steps s torealize national regional development strategy. It is necessary to establish regionalinnovation system that can not leave the regional innovation investment. Now, eachregion in China with r&d investment as the main sign of regional innovative investmenthas a improved greatly. Regional innovation direct performance, namely the regionalinnovation input and output relationship, has been studied deeply for the politics, theindustry and the academic circle. There appear a large number of research results, andsome useful conclusions are obtained. But, some questions,for examlpe which kinds ofinfluence will be produce for regional innovation investment to Chinese macroeconomicand regional innovation investment indirect performance and its evaluation, have yet tointroduce paid enough attention.
In this paper, study is from that point. The methods in this paper include spacestatistical, space econometrics, space filtering, stochastic frontier model withheterogeneous effects, percentile regression, non-parametric regression, panel unit root,panel cointegration, macro cointegration econometric model and other modern measuringmethod. After completion of the direct performance of regional innovation, transmissionmodel from regional innovation to national macro economy development has been made,and the China's macro cointegration econometrics model has also been established.Through the two model connection, the influence of regional innovation investment toour country main macroeconomic variables has been analysed. The paper investigatesthe regional innovation indirect performance under the background of national macroeconomic development, which is the innovative points of this paper. The mainconclusions are as follows:
Firstly, the study finds that the spatial correlation of Chinese regional innovationactivities is very apparent and that the aggregation trend of innovation in eastern regionexists. Gini coefficient analysis shows that the space concentration trend of China'sregional innovation has been increased. Overall, about forty percent of the provincialinnovation activities appear similar high space correlation form. Research also shows thatin the regional administrative center of300kilometers, inventive activities present a strong positive space correlation from. At the same time, when the distance expands toabout2800kilometers, regional innovation activities present a significant degree ofnegative correlation. China's regional innovation exists conditions threshold convergenceor conditions convergence effect. Panel threshold regression model solves the problem ofendogenous convergence club in the convergence theory.
Secondly, the study finds that there exists strong spatial correlation in proxiedvariables of Chinese regional innovation. With spatial filtering method, the spatialcorrelation can be effectively eliminated and the variables can be applied to traditionalregression model. In the model of this paper, there exists co-integration relationshipamong proxied variables of input and output of Chinese regional innovation.Through theChinese regional knowledge production function, the study finds that research anddevelopment expenditure, science and technology activities, the total amount of foreigninvestment, regional import, regional itself and neighbor area knowledge stock are thesix main factors that affect the regional innovation output significantly. We also findthat the regional knowledge spillovers lie in two-way effects by further analysis ofChinese regional knowledge spillover.
Thirdly, the study finds that proxied variables of the environment factors that affectChinese regional technological innovation efficiency are stable variables, which canguarantee the co-integration relationship in the regression model. Chinese regionaltechnology innovation efficiency shows the space distribution characteristics which theeastern China has high efficiency, China's central has middle efficience and westernChina has low efficiency. The western China with low efficiency of technologicalinnovation has a higher growth rate, and there exists sign of catching-up in western areaof technology innovation. Factors affecting regional technological innovation efficiencyin the national and the China's three big areas vary slightly. Innovation agencyparticipation in strength and regional market openness are the main factors that affecttechnological innovation efficiency in the national and the China's three big areas. Otherfactors that affect technological innovation efficiency in the national and the China's threebig areas are not identical.
Fourthly, the China regional─macro econometric model for the study of Chineseregional innovation macro performance has three characteristics, which include thatmodel according to SNA system is set up and is a supply and demand of the dual pilotannual macroeconometric model, behavior equation design depends on dual drive of theeconomic theory and data characteristics, the model is a co-integration econometric model. Analysis of macro economic effect of the r&d investment in the Chinese threeregions shows that: the effect of the three regions r&d input to the same extent increase onthe eight main macroeconomic variables are the same. The sort of the influence of thethree regions r&d input increase on the eight main macro economic variables is almostthe same also. Analysis of macro economic effect of the8regional r&d investment showsalso a similar conclusion. Scene analysis finds that increasing the Chinese regional r&dinvestment is beneficial to Chinese urbanization development, to increase income inChina.
本文研究正是从这一点出发，主要应用空间统计、空间计量经济学、空间过滤、带异质性的随机前沿模型、分位数回归、面板单位根、面板协整等现代计量方法，完成对区域技术创新直接绩效的研究之后，在理论分析的基础上，建立区域技术创新投入到国家宏观经济发展的传导模型以及中国小型宏观计量经济协整模型，并且通过两个模型联接，分析评价我国区域技术创新投入对我国主要宏观经济变量的影响，即中国区域技术创新的间接绩效问题。论文把区域技术创新绩效放在国家宏观经济发展的背景下来考察，相对于已有的技术创新绩效评价文献来说，在技术创新绩效评价内容方面，无疑具有创新意义。论文研究主要得出如下结论：
第一，研究发现中国区域技术创新活动的空间相关性非常明显，存在着向东部地区聚集的趋势。区域专利申请量的基尼系数分析表明，中国区域技术创新的空间集中性呈现增强趋势。总体上大约有40%的省域创新活动显现出相似的高高的空间关联形式。研究也说明在区域行政中心300公里的范围内，区域技术创新活动呈现出强烈的正自空间相关性；从离行政中心大约1400公里开始，区域技术创新活动开始出现负自相关性；在大约2800公里的时，区域技术创新活动呈现出明显的负空间自相关性。中国区域技术创新存在条件收敛和条件门槛收敛效应，从而存在着三大收敛俱乐部特征。人力资本低强度区域存在绝对收敛现象，而人力资本中高强度区域存在条件收敛现象。面板门槛回归模型解决了收敛理论中的俱乐部效应内生性问题。
第二，研究发现中国区域技术创新投入产出代理变量具有较强空间相关性，空间过滤方法可以有效地消除了变量空间相关性，进而可以应用传统回归模型对其进行回归分析。在本文所考虑的模型中，区域技术创新投入与产出代理变量之间存在着协整关系。对中国区域知识生产函数的研究发现，研发经费支出、科技活动人数、外商投资总额、区域进口、区域自身知识存量及邻近区域知识存量等六大因素对区域技术创新产出在统计上有显著影响，研发经费支出、科技活动人数对技术创新产出的弹性分别为0.2397和0.5133，区域内部知识存量弹性要比相邻区域知识存量弹性大20%左右。分位回归分析表明，上述六大因素的区域技术创新产出弹性各自具有一定的内在波动性。进一步分析知识溢出对区域技术创新产出的弹性时可以发现，中国区域知识溢出存在着双向溢出现象。知识正向溢出大致发生在以区域行政中心为圆心，以（100，600）公里及（900，1200）公里为半径的圆环区域内，知识溢出对区域技术创新产出弹性分别为0.2214和0.9618；知识负向溢出大致发生在以区域行政中心为圆心，以（600，900）公里及（1200，1500）公里为半径的圆环区域内，其弹性分别为-0.1561和-0.5561。
第三，研究发现影响中国区域技术创新效率的环境因素都是平稳变量，区域技术创新投入与产出代理变量之间存在协整关系。中国区域技术创新效率显东部高、中部中、西部低的空间分布特征。西部地区技术创新效率低，但增长率较高，西部地区技术创新的追赶迹象已经出现。影响区域技术创新效率的因素在全国及三大区域之间略有差异。创新主体参与强度和区域市场开放度是影响全国及三大区域技术创新效率的主要的显著因素。政府资助、金融机构支持等其他因素对全国及三大区域技术创新效率的影响方向和显著性程度各不相同。
第四，研究中国区域技术创新宏观绩效的中国区域─宏观计量经济协整模型有三个特征，即模型根据SNA体系建立并且是一个供需双导向的年度宏观经济计量模型、行为方程设计依靠经济理论和数据特征的双重驱动、是一个协整计量经济模型。对东中西部三大区域研发投入增加的宏观经济效应分析表明：三大区域研发投入同等幅度的增加对八大主要宏观经济变量的影响关系都是相同的；三大区域研发投入的增加，对八大主要宏观经济变量影响程度的排序也几乎是相同的；三大区域研发投入增加，对主要宏观经济变量影响程度的大小按东中西的顺序排列。对八大区域研发投入增加的宏观经济效应分析也得出类似结论。情景分析特别发现，中国区域研发投入增加有利于中国城市化发展，有利于中国居民收入增加。
The study of the phenomenon and the rule of regional innovation system is theimportant component of promoting regional innovation and is the important measures forrealizing the regional sustainable development and is also the immportant steps s torealize national regional development strategy. It is necessary to establish regionalinnovation system that can not leave the regional innovation investment. Now, eachregion in China with r&d investment as the main sign of regional innovative investmenthas a improved greatly. Regional innovation direct performance, namely the regionalinnovation input and output relationship, has been studied deeply for the politics, theindustry and the academic circle. There appear a large number of research results, andsome useful conclusions are obtained. But, some questions,for examlpe which kinds ofinfluence will be produce for regional innovation investment to Chinese macroeconomicand regional innovation investment indirect performance and its evaluation, have yet tointroduce paid enough attention.
In this paper, study is from that point. The methods in this paper include spacestatistical, space econometrics, space filtering, stochastic frontier model withheterogeneous effects, percentile regression, non-parametric regression, panel unit root,panel cointegration, macro cointegration econometric model and other modern measuringmethod. After completion of the direct performance of regional innovation, transmissionmodel from regional innovation to national macro economy development has been made,and the China's macro cointegration econometrics model has also been established.Through the two model connection, the influence of regional innovation investment toour country main macroeconomic variables has been analysed. The paper investigatesthe regional innovation indirect performance under the background of national macroeconomic development, which is the innovative points of this paper. The mainconclusions are as follows:
Firstly, the study finds that the spatial correlation of Chinese regional innovationactivities is very apparent and that the aggregation trend of innovation in eastern regionexists. Gini coefficient analysis shows that the space concentration trend of China'sregional innovation has been increased. Overall, about forty percent of the provincialinnovation activities appear similar high space correlation form. Research also shows thatin the regional administrative center of300kilometers, inventive activities present a strong positive space correlation from. At the same time, when the distance expands toabout2800kilometers, regional innovation activities present a significant degree ofnegative correlation. China's regional innovation exists conditions threshold convergenceor conditions convergence effect. Panel threshold regression model solves the problem ofendogenous convergence club in the convergence theory.
Secondly, the study finds that there exists strong spatial correlation in proxiedvariables of Chinese regional innovation. With spatial filtering method, the spatialcorrelation can be effectively eliminated and the variables can be applied to traditionalregression model. In the model of this paper, there exists co-integration relationshipamong proxied variables of input and output of Chinese regional innovation.Through theChinese regional knowledge production function, the study finds that research anddevelopment expenditure, science and technology activities, the total amount of foreigninvestment, regional import, regional itself and neighbor area knowledge stock are thesix main factors that affect the regional innovation output significantly. We also findthat the regional knowledge spillovers lie in two-way effects by further analysis ofChinese regional knowledge spillover.
Thirdly, the study finds that proxied variables of the environment factors that affectChinese regional technological innovation efficiency are stable variables, which canguarantee the co-integration relationship in the regression model. Chinese regionaltechnology innovation efficiency shows the space distribution characteristics which theeastern China has high efficiency, China's central has middle efficience and westernChina has low efficiency. The western China with low efficiency of technologicalinnovation has a higher growth rate, and there exists sign of catching-up in western areaof technology innovation. Factors affecting regional technological innovation efficiencyin the national and the China's three big areas vary slightly. Innovation agencyparticipation in strength and regional market openness are the main factors that affecttechnological innovation efficiency in the national and the China's three big areas. Otherfactors that affect technological innovation efficiency in the national and the China's threebig areas are not identical.
Fourthly, the China regional─macro econometric model for the study of Chineseregional innovation macro performance has three characteristics, which include thatmodel according to SNA system is set up and is a supply and demand of the dual pilotannual macroeconometric model, behavior equation design depends on dual drive of theeconomic theory and data characteristics, the model is a co-integration econometric model. Analysis of macro economic effect of the r&d investment in the Chinese threeregions shows that: the effect of the three regions r&d input to the same extent increase onthe eight main macroeconomic variables are the same. The sort of the influence of thethree regions r&d input increase on the eight main macro economic variables is almostthe same also. Analysis of macro economic effect of the8regional r&d investment showsalso a similar conclusion. Scene analysis finds that increasing the Chinese regional r&dinvestment is beneficial to Chinese urbanization development, to increase income inChina.
引文
①转引自周芳.中小企业技术创新的需求诱致与对策研究[J].中外企业家,2006,(l):84-87.
①转引自胡宝清,严志强等.区域生态系统经济学理论、方法与实践[M].北京:中国环境科学出版社,2005:9-10,31-33
①转引自程雁,李平.创新基础设施对中国区域技术创新能力影响的实证分析[J].经济问题探索,2007(9):51-54
①钟惠波,雷家骕,连建辉.知识经济学范式:一个演进的视点[J].科学学与科学技术管理,2005(07):17-22.
白菊红.2002.省际间农民收入分配不均等及影响因素的S-Gini分析[J].河南农业大学学报,(04):401-404.
白俊红,江可申,李婧,李佳.2009.区域创新效率的环境影响因素分析——基于DEATobit两步法的实证检验[J].研究与发展管理,(02):96-102.
白俊红,江可申,李婧.2010.中国地区研发创新的技术效率与技术进步[J].科研管理,(06):7-18.
蔡虹,吴凯,孙顺成.2010.基于专利引用的国际性技术外溢实证研究[J].管理科学,(01):18-26.
蔡虹,张永林.2008.我国区域间外溢技术知识存量的测度及其经济效果研究[J].管理学报,(04):568-575+590.
陈傲,柳卸林,程鹏.2010.知识溢出空间扩散过程的实证检验——以追踪一类专利扩散为线索[J].科学学与科学技术管理,(12):96-101.
陈丹宇.2010.长三角区域创新系统中的协同效应研究[D].浙江大学,博士论文
陈斐.2008.区域空间经济关联模式分析[M].北京:中国社会科学出版社4.
陈继勇,雷欣.2010.我国区域间知识溢出的数量测度[J].科技进步与对策,(01):39-44.
陈劲,陈钰芬,王鹏飞.2009.国家创新能力的测度与比较研究[J].技术经济,(08):1-5+40.
陈向东,王磊.2007.基于专利指标的中国区域创新的俱乐部收敛特征研究[J].中国软科学,(10):76-85.
陈秀山,张可云.区域经济理论[M],商务印书馆2003版:第5页.
程华等.2009.政府科技投入与企业R&D:实证研究与政策选择[M].北京:科学出版社.
池仁勇,唐根年.2004.基于投入与绩效评价的区域技术创新效率研究[J].科研管理,(04):23-27.
邓明,钱争鸣.2009.我国省际知识存量、知识生产与知识的空间溢出[J].数量经济技术经济研究,(05):42-53.
刁丽琳,张蓓,马亚男.2011.基于SFA模型的科技环境对区域技术效率的影响研究[J].科研管理,(04):143-151.
窦雪霞,程开明,窦志强.2009.创新溢出的空间尺度与实证检验[J].科研管理,(04):51-56+88.
杜颖.2011.区域创新环境对创新绩效影响的实证分析[J].新疆财经大学学报,(01):29-33.
段会娟.2010.知识溢出的测度方法综述[J].科技进步与对策,(05):154-157.
樊华.2010.中国省际科技创新效率演化及影响因素实证研究[J].中国科技论坛,(12):36-42.
范红忠.2007.有效需求规模假说、研发投入与国家自主创新能力[J].经济研究,(03):33-44.
范凌钧,李南,陈燕儿.2011.中国高技术产业技术效率区域差异的实证分析[J].系统工程,(02):56-62.
方成.2002.技术创新系统理论在区域经济发展中的作用[J].新视野,(6):66-67.
方旋,刘春仁,邹珊刚.2000.对区域科技创新理论的探讨[J].华南理工大学学报(自然科学版),(09):1-7.
冯涛,杨达.2010.我国宏观经济政策效应的模拟分析——基于季度宏观经济联立方程模型[J].东北大学学报(社会科学版),(04):304-310.
冯之浚.1999.国家创新系统的理论与政策[M].北京:经济科学出版社.
符焱.2008.中国经济增长总量的计量分析---技术扩散、收入分配和可持续发展[M].广州:中山大学出版社.
傅家骥.1998.技术经济学[M].北京:清华大学出版社.
傅晓霞,吴利学.2007.前沿分析方法在中国经济增长核算中的适用性[J].世界经济,(07):56-66.
高建,汪剑飞,魏平.2004.企业技术创新绩效指标:现状、问题和新概念模型[J].科研管理,(S1):14-22.
龚荒,孙鸽.2008.江苏省区域自主创新能力的对比研究[J].科技管理研究,(07):21-25.
郭国峰,温军伟,孙保营.2007.技术创新能力的影响因素分析——基于中部六省面板数据的实证研究[J].数量经济技术经济研究,(09):134-143.
郭树东,关忠良,肖永青.2004.以企业为主体的国家创新系统的构建研究[J].中国软科学,(06):103-105+6.
郭晓川.2001.合作技术创新-大学与企业合作的理论和实证-第1版[M].北京:经济管理出版社.
郭艳秋.2010.基于随机前沿模型的区域技术效率研究[D].辽宁工程技术大学,博士论文
国务院研究中心课题组.1994.中国区域协调发展战略[M].北京:中国经济出版社:45.
韩伯棠,方伟,王栋,刘锦.2008.企业集群网络的知识溢出研究综述[J].科技进步与对策,(11):230-235.
韩剑.2009.知识溢出的空间有限性与企业R&D集聚——中国企业R&D数据的空间计量研究[J].研究与发展管理,(03):22-27.
何新华,吴海英,曹永福,刘睿.2005.中国宏观经济季度模型China_QEM[M].北京:社会科学出版社.6.
侯强,王晓莉,叶丽绮.2008.基于SFA的辽宁省城市技术效率差异分析[J].沈阳工业大学学报(社会科学版),(03):230-234.
贾蔚文.1999.技术创新一科技与经济一体化发展与道路[M].北京:中国经济出版.
李京文.1999.迎接知识经济新时代[M].上海:上海远东出版社.
李婧,白俊红,谭清美.2011.考虑空间效应的区域创新效率测评[J].研究与发展管理,(01):17-22.
李婧,谭清美,白俊红,岳良运.2009.中国区域创新效率的随机前沿模型分析[J].系统工程,(08):44-50.
李婧,谭清美,白俊红.2009.中国区域创新效率及其影响因素[J].中国人口.资源与环境,(06):142-147.
李平,崔喜君,刘建.2007.中国自主创新中研发资本投入产出绩效分析——兼论人力资本和知识产权保护的影响[J].中国社会科学,(02):32-42+204-205.
李习保.2007.区域创新环境对创新活动效率影响的实证研究[J].数量经济技术经济研究,(08):13-24.
李习保.2007.中国区域创新能力变迁的实证分析:基于创新系统的观点[J].管理世界,(12):18-30+171.
李晓钟,张小蒂.2005.江浙区域技术创新效率比较分析[J].中国工业经济,(07):57-64.
李志刚,汤书昆,梁晓艳,吴灵光.2006.我国创新产出的空间分布特征研究——基于省际专利统计数据的空间计量分析[J].科学学与科学技术管理,(8):64-71.
李子奈,潘文卿.2010.计量经济学-3版[M].北京:高等教育出版社.3.
林佳显,龙志和,林光平.2010.空间面板随机前沿模型及技术效率估计[J].商业经济与管理,(05):71-78.
林学明.2006.区域创新系统的动态模型设计及实证研究[D].厦门大学,硕士论文
林云.2008.技术创新效率的经验分析[D].浙江大学,博士论文
刘和东.2011.中国区域研发效率及其影响因素研究——基于随机前沿函数的实证分析[J].科学学研究,(04):548-556.
刘加林,严立冬.2011.环境规制对我国区域技术创新差异性的影响——基于省级面板数据的分析[J].科技进步与对策,(01):32-36.
刘满凤,唐厚兴.2010.基于空间Durbin模型的区域知识溢出效应实证研究[J].科技进步与对策,(18):28-33.
刘润芳,杨建飞.2010.陕西省区域技术创新能力影响因素分析[J].统计与信息论坛,(11):62-66.
刘晓越.2004.中国年度宏观经济计量模型与模拟研究[M].北京:中国统计出版社.
刘亚军,张娥.2010.新经济地理学基本模型及其扩展综述[J].统计与决策,(23):160-162.
刘莹莹.2008.我国区域创新能力影响因素的实证研究[D].湖南大学,硕士论文
柳卸林.1993.技术创新经济学[M].北京:中国经济出版社:16-30.
柳卸林.2002.中国区域创新能力的分布及其成因分析[J].重庆商学院学报,(3).
卢时雨.2009.区域创新能力与区域创新效率关联性分析及测度研究[D].吉林大学,博士论文
陆懋祖.1999.高等时间序列经济计量学[M].上海:上海人民出版社.
罗守贵,甄峰.2000.区域创新能力评价研究[J].南京经济学院学报,(03):31-35.
罗亚非.2010.区域技术创新生态系统绩效评价研究[M].北京:经济科学出版社.3.
罗彦如,冉茂盛,黄凌云.2010.中国区域技术创新效率实证研究——三阶段DEA模型的应用[J].科技进步与对策,(14):20-24.
罗震世,杨正沛,衣凤鹏.2011.技术创新资源对技术创新绩效影响的实证研究[J].北京行政学院学报,(03):82-85.
孟玉明.2005.区域科技创新与评价指标体系研究[J].市场周刊(研究版),(03):91-92+95.
宁军明.2008.知识溢出与区域经济增长[M].北京:经济科学出版社.
牛莲芳,费良杰,庞娟.2006.有关技术创新的文献综述[J].甘肃科技,(09):16-18.
戚汤,李千目.2009.科学研究绩效评价的理论与方法[M].北京:科学出版社:10一43.
钱晓烨,迟巍,黎波.2010.人力资本对我国区域创新及经济增长的影响——基于空间计量的实证研究[J].数量经济技术经济研究,(04):107-121.
乔彬,李国平.2008.在联立框架中的产业集聚与知识溢出[J].当代经济科学,(06):45-49+123.
乔治.泰奇著.苏竣，柏杰译.2002.研究与开发政策的经济学[M].北京:清华大学出版社.
任海云,师萍.2010.企业R&D投入与绩效关系研究综述——从直接关系到调节变量的引入[J].科学学与科学技术管理,(02):143-151.
沈能.2010.基于知识溢出的我国政府R&D支出空间布局特征[J].科学学研究,(06):858-864.
师萍,韩先锋,宋文飞,周凡磬.2011.我国R&D技术效率的空间差异及变动趋势检验[J].统计与决策,(01):77-79.
师萍,许治,张炳南.2007.政府公共R&D对企业R&D的效应分析[J].中国科技论坛,(04):24-28.
师萍,张蔚虹.2008.中国R&D投入的绩效分析与缺席支持研究[M].北京:科学出版社.
石风光,周明.2011.中国地区技术效率的测算及随机收敛性检验——基于超效率DEA的方法[J].研究与发展管理,(01):23-30.
时鹏将,许晓雯,蔡虹.2004.R&D投入产出效率的DEA分析[J].科学学与科学技术管理,(01):28-30.
史修松,赵曙东,吴福象.2009.中国区域创新效率及其空间差异研究[J].数量经济技术经济研究,(03):45-55.
苏方林.2006.中国省域R&D溢出的空间模式研究[J].科学学研究,(05):696-701.
苏方林.2007.省域R&D知识溢出的GWR实证分析[J].数量经济技术经济研究,(02):145-153.
苏方林.2009.中国研发与经济增长的空间统计分析[M].北京:经济科学出版社:58.
孙建,吴利萍,齐建国.2009.技术引进与自主创新:替代或互补[J].科学学研究(01):133-138.
孙建,齐建国.2009.人力资本门槛与中国区域创新收敛性研究[J].科研管理,(06):31-38.
孙建,吴利萍.2010.区域研发、知识溢出与中国经济增长——区域研发宏观效应评价[J].西部论坛,(01):41-49.
孙建,周兵.2009.工业技术发展战略选择与中国宏观经济增长——基于宏观协整计量经济模型的实证[J].华东经济管理,(02):36-40.
孙建.2005.重庆出口贸易与经济增长的相关性分析[J].重庆工商大学学报.西部论坛,(02):43-46.
孙建.2008.中国工业技术发展战略与经济增长——基于宏观计量经济模型的研究[J].河北经贸大学学报,(04):22-26.
孙建.2011.中国区域创新内生俱乐部收敛研究——空间过滤与门槛面板分析[J].科学学与科学技术管理,(7):74-80.
唐德祥,李京文,孟卫东.2008.R&D对技术效率影响的区域差异及其路径依赖——基于我国东、中、西部地区面板数据随机前沿方法(SFA)的经验分析[J].科研管理,(02):115-121+127.
涂俊,吴贵生.2006.基于DEATobit两步法的区域农业创新系统评价及分析[J].数量经济技术经济研究,(04):136-145.
王达政.2009.自主创新还是技术引进——基于我国专利投入产出的实证研究[J].科技进步与对策,(24):30-34.
王家庭,单晓燕.2010.我国区域技术创新的效率测度及动态比较[J].中国科技论坛,(11):73-78.
王劲峰.2006.空间分析[M].北京:科学出版社.
王立平.2008.知识溢出及其对我国区域经济增长作用的实证研究[M].合肥:合肥工业大学出版社.5.
王锐淇,彭良涛,蒋宁.2010.基于SFA与Malmquist方法的区域技术创新效率测度与影响因素分析[J].科学学与科学技术管理,(09):121-128.
王善礼.2008.区域创新环境对区域技术创新效率影响的实证研究[D].重庆大学,硕士论文
王元.2006.自主创新是建设创新型国家的必然[J].前线,(06):19-20.
王争,史晋川.2007.转型时期中国工业生产绩效的地区差异及波动性的解释——基于随机前沿生产函数的分析[J].世界经济文汇,(04):29-45.
王铮,马翠芳,王莹,翁桂兰.2003.区域间知识溢出的空间认识[J].地理学报,(05):773-780.
王志刚.2008.面板数据模型及其在经济分析中的应用[M].北京:经济科学出版社.9.
魏守华,吴贵生,吕新雷.2010.区域创新能力的影响因素——兼评我国创新能力的地区差距[J].中国软科学,(09):76-85.
邬滋.2010.集聚结构、知识溢出与区域创新绩效——基于空间计量的分析[J].山西财经大学学报,(03):15-22.
毋红军,刘章.2003.统计数据的异常值检验[J].华北水利水电学院学报,(01):69-72.
吴和成.2008.专利产出对科技投入要素的弹性研究[J].科技进步与对策,(02):142-144.
吴玉鸣.2004.中国经济增长与收入分配差异的空间统计分析[D].华东师范大学,博士论文
吴玉鸣.2006.空间计量经济模型在省域研发与创新中的应用研究[J].数量经济技术经济研究,(05):74-85+130.
吴玉鸣.2007.中国区域研发、知识溢出与创新的空间计量经济研究[M].北京:人民出版社.
向坚,刘洪伟.2011.技术创新绩效评价研究综述[J].科技进步与对策,(06):155-160.
向希尧,蔡虹.2008.试论地理距离与社会距离对知识溢出的影响——基于专利引用研究视角[J].外国经济与管理,(11):18-26+42.
萧鸣政.2007.中国政府人力资源开发及其战略[J].上海行政学院学报(03):73-79.
肖敏,谢富纪.2009.我国区域R&D资源配置效率差异及其影响因素分析[J].软科学,(10):1-5.
谢丽娟,杨文鹏,周杭.2009.基于DEA模型的区域创新环境对创新绩效影响的评价[J].西安工程大学学报,(06):124-128+146.
许庆瑞.1990.技术创新管理[M].杭州:浙江大学出版社.
许庆瑞.2002.研究与开发绩效评价在中国：实践与趋势明[J].科研管理,23(1):46-53.
姚伟峰,何枫,冯宗宪.2004.CEPA下珠江三角洲与长江三角洲技术效率比较研究[J].开放导报,(02):104-107.
姚先国,薛强军,黄先海.2007.效率增进、技术创新与GDP增长——基于长三角15城市的实证研究[J].中国工业经济,(02):60-66.
叶阿忠.2003.非参数计量经济学[M].天津:南开大学出版社.7.
于明超,申俊喜.2010.区域异质性与创新效率——基于随机前沿模型的分析[J].中国软科学,(11):182-192.
于瑛英.2006.我国区域R&D效率评价研究[J].经济论坛,(24):21-24.
余泳泽,周茂华.2010.制度环境、政府支持与高技术产业研发效率差异分析[J].财经论丛,(05):1-5.
虞晓芬,李正卫,池仁勇,施鸣炜.2005.我国区域技术创新效率:现状与原因[J].科学学研究,(02):258-264.
袁立科.2007.邻近对技术创新的影响研究[D].重庆大学,博士论文
袁鹏.2009.基于空间过滤的制造业劳动生产率地区收敛性估计[J].数理统计与管理,3:502-510.
岳书敬.2008.中国区域研发效率差异及其影响因素——基于省级区域面板数据的经验研究[J].科研管理,(05):173-179.
张龙.2010.我国财政政策与货币政策及其配合效应分析[D].西北大学,博士论文
张五六.2009.基于分位数回归模型的我国“费雪效应”检验[J].统计教育,(12):7-11.
张晓峒.2001.计量经济学基础[M].天津:南开大学出版社.
张莹,张宗益.2009.区域创新环境对创新绩效影响的实证研究——以重庆市为例[J].科技管理研究,(02):104-106.
张宗和,彭昌奇.2009.区域技术创新能力影响因素的实证分析——基于全国30个省市区的面板数据[J].中国工业经济,(11):35-44.
张宗益,周勇,钱灿,赖德林.2006.基于SFA模型的我国区域技术创新效率的实证研究[J].软科学(02):125-128.
赵国庆,杨健.2003.经济数学模型的理论与方法[M].北京:中国金融出版社.8.
赵立雨,师萍,张炳南.2009.我国基础研究投入的多元效应及度量模型分析[J].科学学与科学技术管理,(10):10-14.
赵立雨.2010.基于SFA的区域R&D效率的空间相关性研究[C].第六届中国科技政策与管理学术年会论文集
赵勇,白永秀.2009.知识溢出测度方法研究综述[J].统计与决策,(08):132-135.
中国科技发展战略研究小组.1999.中国科技发展研究报告（1999）[M].北京,经济管理出版社.
周凌瑶.2010.中国宏观经济年度模型的研制及应用[M].北京:中国农业出版社.6.
周晓艳,葛健,马丽仪.2009.基于动态面板数据模型的中国区域创新体系效率实证[J].经济管理,(03):28-32.
周勇.2006.我国区域技术创新效率的实证研究[D].重庆大学,硕士论文
朱平芳,徐伟民.2003.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——上海市的实证研究[J].经济研究,(06):45-53.
朱有为,徐康宁.2006.中国高技术产业研发效率的实证研究[J].中国工业经济,(11):38-45.
邹新月,罗发友,李汉通.2001.技术创新内涵的科学理解及其结论[J].技术经济,(5):13-14.
Acemoglu.1994.Search in the labour market, incomplete contracts and growth[J].CEPR DiscussionPaper Working Paper,NO.1026.
Acs, Anselin,Varga.2002.Patents and innovation counts as measures of regional production of newknowledge[J].Research Policy,31(7):1069-1085.
Aigner, Lovell,Schmidt.1977.Formulation and estimation of stochastic frontier production functionmodels[J].Journal of Econometrics,6(1):21-37.
Andersson,Karlsson.2006.Regional innovation systems in small and medium-sized regions[J].TheEmerging Digital Economy:55-81.
Anselin, Varga,Acs.1997.Local Geographic Spillovers between University Research and HighTechnology Innovations[J].Journal of urban economics,42(3):422-448.
Anselin, Varga,Acs.2000.Geographic and sectoral characteristics of academic knowledgeexternalities[J]. Regional Science,79(4):435-443.
Anselin,Bera.1998.Spatial dependence in linear regression models with an introduction to spatialeconometrics[A].In Handbook of applied economic statistics[C].New York,Marcel Dekker
Anselin,Florax.1995.New directions in spatial econometrics.Springer.
Anselin,Rey.1991.Properties of tests for spatial dependence in linear regression models[J].Geographical Analysis,23(2):112-131.
Anselin.1992.Spatial data analysis with GIS: an introduction to application in the socialsciences[J].National Center for Geographic Information Analysis Working Paper.
Anselin.1996.The Moran scatterplot as an ESDA tool to assess local instability in spatialassociation[A].In M, H,Urwin.Spatial analytical perspectives on GIS[C]. London,Taylor andFrancis:121
Anselin.2007.Spatial econometrics[A].In Baltagi.A companion to theoretical econometrics[C].Malden,MA, USA,Blackwell Publishing Ltd,:310-330
Arrow.1962.Economic welfare and the allocation of resources for invention[J].UMI Working Paper.
Arundel,Kabla.1998.What percentage of innovations are patented? Empirical estimates for Europeanfirms[J].Research Policy,27(2):127-141.
Azariadis,Drazen.1990.Threshold externalities in economic development[J].The quarterly journal ofeconomics,105(2):501.
Azariadis.1996.The economics of poverty traps part one: complete markets[J].Journal of EconomicGrowth,1(4):449-486.
Bagnai,Ospina.2007.Structural changes and the transition process: a macroeconometric model ofChina[J].Luiss Lab on European Economics Working Documents Series.
Battese,Corra.1977.Estimation of a production frontier model: with application to the pastoral zone ofEastern Australia[J].Australian Journal of Agricultural Economics,21(3):169-179.
Bernardin, et al.1995.Performance appraisal design, development, and implementation[J].Handbook ofhuman resource management,462:493.
Bode.2004.The spatial pattern of localized R&D spillovers: an empirical investigation forGermany[J].Journal of Economic Geography,4(1):43-64.
Bottazzi,Peri.2000.INNOVATION AND SPILLOVERS:EVIDENCE FROM EUROPEANREGIONS[J].CESifo Working Paper,NO.340.
Bottazzi,Peri.2003.Innovation and spillovers in regions: Evidence from European patentdata[J].European Economic Review,47(4):687-710.
Bradley, Morgenroth,Untiedt.2003.Macro-regional evaluation of the Structural Funds using theHERMIN modelling framework[J].Italian Journal of Regional Science,3(3):5-28.
Branstetter.1998.Looking for international knowledge spillovers a review of the literature withsuggestions for new approaches[J].Annales d'Economie et de Statistique:517-540.
Buchinsky.1998.Recent advances in quantile regression models: a practical guideline for empiricalresearch[J].The Journal of Human Resources,33(1):88-126.
Buesa, Heijs, Mart¨nez Pellitero,Baumert.2006.Regional systems of innovation and the knowledgeproduction function: the Spanish case[J].Technovation,26(4):463-472.
Buesa, Heijs, Martnez Pellitero,Baumert.2006.Regional systems of innovation and the knowledgeproduction function: the Spanish case[J].Technovation,26(4):463-472.
Buesa, Heijs,Baumert.2010.The determinants of regional innovation in Europe: A combined factorialand regression knowledge production function approach[J].Research Policy,39(6):722-735.
Cabrer-Borras,Serrano-Domingo.2007.Innovation and R&D spillover effects in Spanish regions: aspatial approach[J].Research Policy,36(9):1357-1371.
Cambell, Mccoloy, Oppler,Sager.1993.personal selection in organization.San Francisco Josey-Bass:35-70.
Cani ls,Verspagen.2001.Barriers to knowledge spillovers and regional convergence in an evolutionarymodel[J].Journal of Evolutionary Economics,11(3):307-329.
Cassar,Nicolini.2008.Spillovers and growth in a local interaction model[J].the Annals of RegionalScience,42(2):291-306.
Coe,Helpman.1995.International r&d spillovers[J].European Economic Review,39(5):859-887.
Conway.1999.Distinguishing contextual performance from task performance for managerialjobs[J].Journal of Applied Psychology,84(1):3.
Cooke.1996.Regional Innovation System: An Evolutionary Approach, Regional InnovationSystem[A].In H., P.,Heidenreieh.RegionalInnovationSystem[C].London, University of LondonPress
Crosby.2000.Patents, innovation and growth[J].Economic Record,76(234):255-262.
Cullmann, Schmidt-Ehmcke,Zloczysti.2011.R&D Efficiency and Barriers to Entry: a Two-stageSemi-parametric DEA Approach[J].Oxf. Econ. Pap.,63(2).
Czarnitzki,Hussinger.2004.The link between R&D subsidies, R&D spending and technologicalperformance[J].ZEW-Centre for European Economic Research Working Paper.
Czarnitzki,Licht.2006.Additionality of public R&D grants in a transition economy[J].Economics ofTransition,14(1):101.
De Dominicis, Florax,De Groot.2011.Regional Clusters of Innovative Activity in Europe: Are SocialCapital and Geographical Proximity the Key Determinants?[J].Tinbergen Institute DiscussionPapers.
De Graeve, Kick,Koetter.2008.Monetary policy and financial (in) stability: An integrated micro-macroapproach[J].Journal of Financial Stability,4(3):205-231.
Dixit,Stiglitz.1977.Monopolistic competition and optimum product diversity[J].The AmericanEconomic Review,67(3):297-308.
Eaton,Kortum.1996.Trade in ideas Patenting and productivity in the OECD[J].Journal of InternationalEconomics,40(3-4):251-278.
Edquist, Eriksson,Sjogren.2002.Characteristics of collaboration in product innovation in the regionalsystem of innovation of East Gothia[J].European Planning Studies,10(5):563-581.
Elhorst.2003.Specification and estimation of spatial panel data models[J].International RegionalScience Review,26(3):244.
Elhorst.2010.Spatial panel data models[A].In Fischer,Getis.Handbook of applied spatial analysis[C].Berlin Heidelberg New York,Springer:377-407
Engle,Granger.1987.Cointegration and error correction: representation, estimation and testing[J].Econometrica,55(2):251-76.
Enos.1962.Invention and innovation in the petroleum refining industry[A].In Nelson.The rate anddirection of inventive activity:Economic and social factors[C].Princeton,NJ,Princeton UniversityPress:299-321
Fare,Grosskopf.1997.Efficiency and productivity in rich and poor countries[A].In Wong.Dynamics,economic growth, and international trade[C].Ann Arbor,University of Michigan Press, Studies inInternational Economics:243-63
Farrell.1957.The measurement of productive efficiency[J].Journal of the Royal Statistical Society.Series A (General),120(3):253-290.
Ferstl.2007.Spatial Filtering with EViews and MATLAB[J].Austrian Journal of Statistics,36(1):17-26.
Fischer, Scherngell,Jansenberger.2006.The Geography of Knowledge Spillovers BetweenHigh-Technology Firms in Europe: Evidence from a Spatial Interaction Modeling Perspective[J].Geographical Analysis,38(3):288-309.
Fischer,Varga.2003.Spatial knowledge spillovers and university research: evidence from Austria[J].theAnnals of Regional Science,37(2):303-322.
Fitjar,Rodrguez-Pose.2011.Innovating in the Periphery: Firms, Values and Innovation in SouthwestNorway[J].European Planning Studies,19(4):555-574.
Freeman.1982.The economics of industrial innovation. MIT press:110-114.
Fritsch,Franke.2004.Innovation, regional knowledge spillovers and R&D cooperation[J].ResearchPolicy,33(2):245-255.
Fritsch,Slavtchev.2007.Universities and innovation in space[J].Industry&Innovation,14(2):201-218.
Fritsch.2002.Measuring the Quality of Regional Innovation Systems: A Knowledge ProductionFunction Approach[J]. International Regional Science Review,25(1):86-101.
Funke,Niebuhr.2000.Spatial R&D spillovers and economic growth: evidence from West Germany.Hamburgisches Welt-Wirtschafts-Archiv.
Funke,Niebuhr.2005.Regional geographic research and development spillovers and economic growth:evidence from West Germany[J].Regional Studies,39(1):143-153.
Furman, Porter,Stern.2002.The determinants of national innovative capacity[J].Research Policy,31(6):899-933.
Getis,Griffith.2002.Comparative spatial filtering in regression analysis[J].Geographical Analysis,34(2):130-140.
Getis,Ord.1992. The analysis of spatial association in use of distance statistics[J].GeographicalAnalysis(24):189-206.
Getis,Ord.1996.Local spatial statistics: an overview[J].Spatial analysis: Modelling in a GISenvironment,374.
Goodchild, RP,Wise.1992.Integrating GIS and Spatial Data Analysis: problems and possibilities[J].J.Geographical Information Systems,6(5):407-23.
Greene.2005.Fixed and random effects in stochastic frontier models[J].Journal of ProductivityAnalysis,23(1):7-32.
Gregory,Hansen.1996.Residual-based tests for cointegration in models with regime shifts[J].Journal ofEconometrics,70(1):99-126.
Griffith.2000.A linear regression solution to the spatial autocorrelation problem[J].Journal ofGeographical Systems,2(2):141-156.
Griliches.1979.Issues in Assessing the Contribution of Research and Development to ProductivityGrowth[J].The Bell Journal of Economics,10(1):92-116.
Griliches.1980.R&D and the Productivity Slowdown[J].The American Economic Review,70(2):343-348.
Griliches.1990.Patent statistics as economic indicators: a survey[J].Journal of economic literature,28(4):1661-1707.
Griliches.1992.The search for R&D spillovers[J].The Scandinavian Journal of Economics,94:29-47.
Griliches.1998.R&D and Productivity[M].Chicago:University of Chicago Press.
Grossman,Helpman.1991.Trade, knowledge spillovers, and growth[J].NBER Working Paper.
Grossman,Helpman.1994.Endogenous innovation in the theory of growth[J].The Journal of EconomicPerspectives,8(1):23-44.
Guan,Chen.2010.Modeling macro-R&D production frontier performance: an application to Chineseprovince-level R&D[J].Scientometrics,82(1):165-173.
Guellec,De La Potterie.2003.The impact of public R&D expenditure on business R&D[J].Economicsof innovation and new technology,12(3):225-243.
Gutierrez.2003.On the power of panel cointegration tests: a Monte Carlo comparison[J].EconomicsLetters,80(1):105-111.
Hagedoorn,Cloodt.2003.Measuring innovative performance: is there an advantage in using multipleindicators?[J].Research Policy,32(8):1365-1379.
Hansen.1992.Tests for parameter instability in regressions with I (1) processes[J].Journal of Business&Economic Statistics,10(3):321-335.
Hansen.1999.Threshold effects in non-dynamic panels: Estimation, testing, and inference[J].Journal ofEconometrics,93(2):345-368.
HO.2006.INCOME THRESHOLDS AND GROWTH CONVERGENCE: A PANEL DATAAPPROACH[J].The Manchester School,74(2):170-189.
Hoover.1970.The vascular plants of San Luis Obispo County, CaliforniaUniversity of California Press,Berkeley.
Hsiao.2003.Analysis of panel data.Cambridge Univ Press.
Hu,Mathews.2005.National innovative capacity in East Asia[J].Research Policy,34(9):1322-1349.
Hu,Mathews.2008.China's national innovative capacity[J].Research Policy,37(9):1465-1479.
Ilgen,Schneider.1991.Performance measurement: A multi-discipline view[J].International review ofindustrial and organizational psychology,6:71.
Im, Pesaran,Shin.2003.Testing for unit roots in heterogeneous panels[J].Journal of Econometrics,115(1):53-74.
Isard.1960.Methods of regional analysis: an introduction to regional science[M].New York:Publishedjointly by the Technology Press of the Massachusetts Institute of Technology and Wiley.
Jaffe, Trajtenberg,Henderson.1993.Geographic Localization of Knowledge Spillovers as Evidenced byPatent Citations[J].Quarterly Journal of Economics,108(3):577-598.
Jaffe,Trajtenberg.1996.Flows of knowledge from universities and federal labs: modeling the flow ofpatent citations over time and across institutional and geographic boundaries[J].NBER workingpaper.
Jaffe.1986.Technological opportunity and spillovers of R&D: evidence from firms' patents, profits,and market value[J].The American Economic Review,76(5):984-1001.
Jaffe.1989.Real Effects of Academic Research[J].American Economic Review,79(5):957-970.
Jondrow.1982.On the estimation of technical inefficiency in the stochastic frontier production functionmodel[J].Journal of Econometrics,19(2-3):233-238.
Josty.1990.A tentative model of the innovation process[J].R&D Management,20(1):35-45.
Jungmittag.2006.Innovation dynamics in the EU: convergence or divergence? A cross-country paneldata analysis[J].Empirical Economics,31(2):313-331.
Kao.1999.Spurious regression and residual-based tests for cointegration in panel data[J].Journal ofEconometrics,90(1):1-44.
Keilbach.2000.Spatial knowledge spillovers and the dynamics of agglomeration and regionalgrowth.Springer.
Keller.2002.Trade and the Transmission of Technology[J].Journal of Economic Growth,7(1):5-24.
Keller.2004.International technology diffusion[J].Journal of economic literature,42(3):752-782.
Kim,Han.2001.A decomposition of total factor productivity growth in Korean manufacturingindustries: A stochastic frontier approach[J].Journal of Productivity Analysis,16(3):269-281.
Koenker,Bassett Jr.1978.Regression quantiles[J].Econometrica: journal of the EconometricSociety,46(1):33-50.
Koop, Osiewalski,Steel.1999.The components of output growth: A stochastic frontier analysis[J].Oxford Bulletin of Economics and statistics,61(4):455-487.
Kortum.1998.a Model of Research, Patenting, and Technological Change[J].National Bureau ofEconomic Research Cambridge, Mass., USA Working Paper.
Krammer.2009.Drivers of national innovation in transition: Evidence from a panel of EasternEuropean countries[J].Research Policy,38(5):845-860.
Krugman.1991.Geography and trade.the MIT Press.
Kumbhakar,Lovell.2000.Stochastic frontier analysis.Cambridge Univ Pr.
Levin, Lin,James Chu.2002.Unit root tests in panel data: asymptotic and finite-sampleproperties[J].Journal of Econometrics,108(1):1-24.
Li,Racine.2004.Cross-validated local linear nonparametric regression[J].Statistica Sinica,14(2):485-512.
Li,Racine.2007.Nonparametric econometrics: Theory and practice[M].N.J.:Princeton University PressPrinceton.
Li.2009.China's regional innovation capacity in transition: An empirical approach[J].ResearchPolicy,38(2):338-357.
Lichtenberg.1988.The private R and D investment response to federal design and technicalcompetitions[J].The American Economic Review,78(3):550-559.
Lucas.1988.On the mechanics of economic development[J].Journal of Monetary Economics,22(1):3-42.
Lundvall.1988.Innovation as an interactive process: from user-producer interaction to the nationalsystem of innovation[J].Technical change and economic theory:349-369.
Mansfield.1971.The economics of technological change[M].New York:W.W.Norton and Company.
Maudos, Pastor,Serrano.1999.Total factor productivity measurement and human capital in OECDcountries[J].Economics Letters,63(1):39-44.
McCoskey,Kao.1998.A residual-based test of the null of cointegration in panel data[J].Econometricreviews,17(1):57-84.
Meeusen,van Den Broeck.1977.Efficiency estimation from Cobb-Douglas production functions withcomposed error[J].International Economic Review,18(2):435-444.
Moreno, Paci,Usai.2005.Spatial spillovers and innovation activity in European regions[J].Environmentand Planning A,37(10):1793-1812.
Mueser.1985.Identifying technical innovations[J].IEEE Transactions on Engineering Management,32:158-176.
Myers,Marquis.1969.Successful industrial innovations: A study of factors underlying innovation inselected firms[M].Washington:National Science Foundation.
Narayanan.2001.Managing Technology and Innovation for Competitive Advantage.New Jersey:Prentice Hall.
Nasierowski,Arcelus.2003.On the efficiency of national innovation systems[J].Socio-EconomicPlanning Sciences,37(3):215-234.
Nelson.1959.The simple economics of basic scientific research[J].The Journal of PoliticalEconomy,67(3):297-306.
Nelson.1993.National innovation systems: a comparative analysis.Oxford University Press, USA.
Pakes,Griliches.1980.Patents and R&D at the firm level: A first report[J].Economics Letters,5(4):377-381.
Pakes,Griliches.1984.Estimating Distributed Lags in Short Panels with an Application to theSpecification of Depreciation Patterns and Capital Stock Constructs[J].The Review of EconomicStudies,51(2):243.
Patuelli, Griffith, Tiefelsdorf,Nijkamp.2011.Spatial Filtering and Eigenvector Stability: Space-TimeModels for German Unemployment Data[J].International Regional Science Review,34(2):253.
Pedroni.1999.Critical values for cointegration tests in heterogeneous panels with multipleregressors[J].Oxford Bulletin of Economics and statistics,61(S1):653-670.
Perelman.1995.R&D, technological progress and efficiency change in industrial activities[J].Review ofIncome and Wealth,41(3):349-366.
Pires,Garcia.2004.Productivity of Nations: a stochastic frontier approach to TFP decomposition[C].Econometric Society,Latin AmericanMeetings(292)
Ponds, Oort,Frenken.2010.Innovation, spillovers and university¨Cindustry collaboration: an extendedknowledge production function approach[J].Journal of Economic Geography,10(2):231.
Racine,Li.2004.Nonparametric estimation of regression functions with both categorical and continuousdata[J].Journal of Econometrics,119(1):99-130.
Rangel, Diniz-Filho,Bini.2010.SAM: a comprehensive application for Spatial Analysis inMacroecology[J].Ecography,33(1):46-50.
Ray,Desli.1997.Productivity growth, technical progress, and efficiency change in industrializedcountries: Comment[J].The American Economic Review,87(5):1033-1039.
Rodrguez-Pose,Crescenzi.2008.Research and development, spillovers, innovation systems, and thegenesis of regional growth in Europe[J].Regional Studies,42(1):51-67.
Romer.1986.Increasing returns and long-run growth[J].The Journal of Political Economy,94(5):1002-1037.
Romer.1990.Endogenous technological change[J].Journal of Political Economy,98(5):71-102.
Rondé,Hussler.2005.Innovation in regions: what does really matter?[J].Research Policy,34(8):1150-1172.
Scherer.1965.Firm size, market structure, opportunity, and the output of patented inventions[J].TheAmerican Economic Review,55(5):1097-1125.
Schmidt,Sickles.1984.Production frontiers and panel data[J].Journal of Business&EconomicStatistics,2(4):367-374.
Schulze.2004.Applied quantile regression: microeconometric, financial, and environmental analyses[J].Inaugural-Dissertation, Tubingen.
Sharma,Thomas.2008.Inter-country R&D efficiency analysis: An application of data envelopmentanalysis[J].Scientometrics,76(3):483-501.
Stoneman.1983.The economic analysis of technological change[M].Oxford:Oxford University Press.
Tadesse.2002.Financial architecture and economic performance: international evidence[J].Journal offinancial intermediation,11(4):429-454.
Thomas, Sharma,Jain.2010.Using patents and publications to assess R&D efficiency in the states of theUSA[J].World Patent Information.
Tobler.1979.Lattice tuning[J].Geographical Analysis,11(1):36-44.
Todtling,Trippl.2005.One size fits all?Towards a differentiated regional innovation policyapproach[J].Research Policy,34(8):1203-1219.
Utterback.1974.Innovation in Industry and the Diffusion of Technology[J].Science,183(4125):620.
Varga,Schalk.2004.Knowledge spillovers, agglomeration and macroeconomic growth: An empiricalapproach[J].Regional Studies,38(8):977-989.
Varga,Schalk.2006.Macroeconomic effects of the geography of technological change[J]. DIMEworkshop on Dynamics of Knowledge Accumulation, Competitiveness, Regional Cohesion andEconomic Policies Working Paper,WIIW, Vienna.
Wallsten.2000.The effects of government-industry R&D programs on private R&D: the case of theSmall Business Innovation Research program[J].The Rand Journal of Economics:82-100.
Wang,Ho.2010.Estimating fixed-effect panel stochastic frontier models by model transformation[J].Journal of Econometrics,157(2):286-296.
Wang,Huang.2007.Relative efficiency of R&D activities: A cross-country study accounting forenvironmental factors in the DEA approach[J].Research Policy,36(2):260-273.
Woodward, Figueiredo,Guimaraes.2006.Beyond the Silicon Valley: University R&D andhigh-technology location[J]. Journal of urban economics,60(1):15-32.
Yu, Lu,Stander.2003.Quantile regression: applications and current research areas[J].Journal of theRoyal Statistical Society: Series D (The Statistician),52(3):331-350.
Zhong, Yuan, Li,Huang.2011.The performance evaluation of regional R&D investments in China: Anapplication of DEA based on the first official China economic census data[J]. Omega,39(4):447-455.
Zitikis,Gastwirth.2002.The Asymptotic distribution of the S¨CGini Index[J].Australian&NewZealand Journal of Statistics,44(4):439-446.
①转引自胡宝清,严志强等.区域生态系统经济学理论、方法与实践[M].北京:中国环境科学出版社,2005:9-10,31-33
①转引自程雁,李平.创新基础设施对中国区域技术创新能力影响的实证分析[J].经济问题探索,2007(9):51-54
①钟惠波,雷家骕,连建辉.知识经济学范式:一个演进的视点[J].科学学与科学技术管理,2005(07):17-22.
白菊红.2002.省际间农民收入分配不均等及影响因素的S-Gini分析[J].河南农业大学学报,(04):401-404.
白俊红,江可申,李婧,李佳.2009.区域创新效率的环境影响因素分析——基于DEATobit两步法的实证检验[J].研究与发展管理,(02):96-102.
白俊红,江可申,李婧.2010.中国地区研发创新的技术效率与技术进步[J].科研管理,(06):7-18.
蔡虹,吴凯,孙顺成.2010.基于专利引用的国际性技术外溢实证研究[J].管理科学,(01):18-26.
蔡虹,张永林.2008.我国区域间外溢技术知识存量的测度及其经济效果研究[J].管理学报,(04):568-575+590.
陈傲,柳卸林,程鹏.2010.知识溢出空间扩散过程的实证检验——以追踪一类专利扩散为线索[J].科学学与科学技术管理,(12):96-101.
陈丹宇.2010.长三角区域创新系统中的协同效应研究[D].浙江大学,博士论文
陈斐.2008.区域空间经济关联模式分析[M].北京:中国社会科学出版社4.
陈继勇,雷欣.2010.我国区域间知识溢出的数量测度[J].科技进步与对策,(01):39-44.
陈劲,陈钰芬,王鹏飞.2009.国家创新能力的测度与比较研究[J].技术经济,(08):1-5+40.
陈向东,王磊.2007.基于专利指标的中国区域创新的俱乐部收敛特征研究[J].中国软科学,(10):76-85.
陈秀山,张可云.区域经济理论[M],商务印书馆2003版:第5页.
程华等.2009.政府科技投入与企业R&D:实证研究与政策选择[M].北京:科学出版社.
池仁勇,唐根年.2004.基于投入与绩效评价的区域技术创新效率研究[J].科研管理,(04):23-27.
邓明,钱争鸣.2009.我国省际知识存量、知识生产与知识的空间溢出[J].数量经济技术经济研究,(05):42-53.
刁丽琳,张蓓,马亚男.2011.基于SFA模型的科技环境对区域技术效率的影响研究[J].科研管理,(04):143-151.
窦雪霞,程开明,窦志强.2009.创新溢出的空间尺度与实证检验[J].科研管理,(04):51-56+88.
杜颖.2011.区域创新环境对创新绩效影响的实证分析[J].新疆财经大学学报,(01):29-33.
段会娟.2010.知识溢出的测度方法综述[J].科技进步与对策,(05):154-157.
樊华.2010.中国省际科技创新效率演化及影响因素实证研究[J].中国科技论坛,(12):36-42.
范红忠.2007.有效需求规模假说、研发投入与国家自主创新能力[J].经济研究,(03):33-44.
范凌钧,李南,陈燕儿.2011.中国高技术产业技术效率区域差异的实证分析[J].系统工程,(02):56-62.
方成.2002.技术创新系统理论在区域经济发展中的作用[J].新视野,(6):66-67.
方旋,刘春仁,邹珊刚.2000.对区域科技创新理论的探讨[J].华南理工大学学报(自然科学版),(09):1-7.
冯涛,杨达.2010.我国宏观经济政策效应的模拟分析——基于季度宏观经济联立方程模型[J].东北大学学报(社会科学版),(04):304-310.
冯之浚.1999.国家创新系统的理论与政策[M].北京:经济科学出版社.
符焱.2008.中国经济增长总量的计量分析---技术扩散、收入分配和可持续发展[M].广州:中山大学出版社.
傅家骥.1998.技术经济学[M].北京:清华大学出版社.
傅晓霞,吴利学.2007.前沿分析方法在中国经济增长核算中的适用性[J].世界经济,(07):56-66.
高建,汪剑飞,魏平.2004.企业技术创新绩效指标:现状、问题和新概念模型[J].科研管理,(S1):14-22.
龚荒,孙鸽.2008.江苏省区域自主创新能力的对比研究[J].科技管理研究,(07):21-25.
郭国峰,温军伟,孙保营.2007.技术创新能力的影响因素分析——基于中部六省面板数据的实证研究[J].数量经济技术经济研究,(09):134-143.
郭树东,关忠良,肖永青.2004.以企业为主体的国家创新系统的构建研究[J].中国软科学,(06):103-105+6.
郭晓川.2001.合作技术创新-大学与企业合作的理论和实证-第1版[M].北京:经济管理出版社.
郭艳秋.2010.基于随机前沿模型的区域技术效率研究[D].辽宁工程技术大学,博士论文
国务院研究中心课题组.1994.中国区域协调发展战略[M].北京:中国经济出版社:45.
韩伯棠,方伟,王栋,刘锦.2008.企业集群网络的知识溢出研究综述[J].科技进步与对策,(11):230-235.
韩剑.2009.知识溢出的空间有限性与企业R&D集聚——中国企业R&D数据的空间计量研究[J].研究与发展管理,(03):22-27.
何新华,吴海英,曹永福,刘睿.2005.中国宏观经济季度模型China_QEM[M].北京:社会科学出版社.6.
侯强,王晓莉,叶丽绮.2008.基于SFA的辽宁省城市技术效率差异分析[J].沈阳工业大学学报(社会科学版),(03):230-234.
贾蔚文.1999.技术创新一科技与经济一体化发展与道路[M].北京:中国经济出版.
李京文.1999.迎接知识经济新时代[M].上海:上海远东出版社.
李婧,白俊红,谭清美.2011.考虑空间效应的区域创新效率测评[J].研究与发展管理,(01):17-22.
李婧,谭清美,白俊红,岳良运.2009.中国区域创新效率的随机前沿模型分析[J].系统工程,(08):44-50.
李婧,谭清美,白俊红.2009.中国区域创新效率及其影响因素[J].中国人口.资源与环境,(06):142-147.
李平,崔喜君,刘建.2007.中国自主创新中研发资本投入产出绩效分析——兼论人力资本和知识产权保护的影响[J].中国社会科学,(02):32-42+204-205.
李习保.2007.区域创新环境对创新活动效率影响的实证研究[J].数量经济技术经济研究,(08):13-24.
李习保.2007.中国区域创新能力变迁的实证分析:基于创新系统的观点[J].管理世界,(12):18-30+171.
李晓钟,张小蒂.2005.江浙区域技术创新效率比较分析[J].中国工业经济,(07):57-64.
李志刚,汤书昆,梁晓艳,吴灵光.2006.我国创新产出的空间分布特征研究——基于省际专利统计数据的空间计量分析[J].科学学与科学技术管理,(8):64-71.
李子奈,潘文卿.2010.计量经济学-3版[M].北京:高等教育出版社.3.
林佳显,龙志和,林光平.2010.空间面板随机前沿模型及技术效率估计[J].商业经济与管理,(05):71-78.
林学明.2006.区域创新系统的动态模型设计及实证研究[D].厦门大学,硕士论文
林云.2008.技术创新效率的经验分析[D].浙江大学,博士论文
刘和东.2011.中国区域研发效率及其影响因素研究——基于随机前沿函数的实证分析[J].科学学研究,(04):548-556.
刘加林,严立冬.2011.环境规制对我国区域技术创新差异性的影响——基于省级面板数据的分析[J].科技进步与对策,(01):32-36.
刘满凤,唐厚兴.2010.基于空间Durbin模型的区域知识溢出效应实证研究[J].科技进步与对策,(18):28-33.
刘润芳,杨建飞.2010.陕西省区域技术创新能力影响因素分析[J].统计与信息论坛,(11):62-66.
刘晓越.2004.中国年度宏观经济计量模型与模拟研究[M].北京:中国统计出版社.
刘亚军,张娥.2010.新经济地理学基本模型及其扩展综述[J].统计与决策,(23):160-162.
刘莹莹.2008.我国区域创新能力影响因素的实证研究[D].湖南大学,硕士论文
柳卸林.1993.技术创新经济学[M].北京:中国经济出版社:16-30.
柳卸林.2002.中国区域创新能力的分布及其成因分析[J].重庆商学院学报,(3).
卢时雨.2009.区域创新能力与区域创新效率关联性分析及测度研究[D].吉林大学,博士论文
陆懋祖.1999.高等时间序列经济计量学[M].上海:上海人民出版社.
罗守贵,甄峰.2000.区域创新能力评价研究[J].南京经济学院学报,(03):31-35.
罗亚非.2010.区域技术创新生态系统绩效评价研究[M].北京:经济科学出版社.3.
罗彦如,冉茂盛,黄凌云.2010.中国区域技术创新效率实证研究——三阶段DEA模型的应用[J].科技进步与对策,(14):20-24.
罗震世,杨正沛,衣凤鹏.2011.技术创新资源对技术创新绩效影响的实证研究[J].北京行政学院学报,(03):82-85.
孟玉明.2005.区域科技创新与评价指标体系研究[J].市场周刊(研究版),(03):91-92+95.
宁军明.2008.知识溢出与区域经济增长[M].北京:经济科学出版社.
牛莲芳,费良杰,庞娟.2006.有关技术创新的文献综述[J].甘肃科技,(09):16-18.
戚汤,李千目.2009.科学研究绩效评价的理论与方法[M].北京:科学出版社:10一43.
钱晓烨,迟巍,黎波.2010.人力资本对我国区域创新及经济增长的影响——基于空间计量的实证研究[J].数量经济技术经济研究,(04):107-121.
乔彬,李国平.2008.在联立框架中的产业集聚与知识溢出[J].当代经济科学,(06):45-49+123.
乔治.泰奇著.苏竣，柏杰译.2002.研究与开发政策的经济学[M].北京:清华大学出版社.
任海云,师萍.2010.企业R&D投入与绩效关系研究综述——从直接关系到调节变量的引入[J].科学学与科学技术管理,(02):143-151.
沈能.2010.基于知识溢出的我国政府R&D支出空间布局特征[J].科学学研究,(06):858-864.
师萍,韩先锋,宋文飞,周凡磬.2011.我国R&D技术效率的空间差异及变动趋势检验[J].统计与决策,(01):77-79.
师萍,许治,张炳南.2007.政府公共R&D对企业R&D的效应分析[J].中国科技论坛,(04):24-28.
师萍,张蔚虹.2008.中国R&D投入的绩效分析与缺席支持研究[M].北京:科学出版社.
石风光,周明.2011.中国地区技术效率的测算及随机收敛性检验——基于超效率DEA的方法[J].研究与发展管理,(01):23-30.
时鹏将,许晓雯,蔡虹.2004.R&D投入产出效率的DEA分析[J].科学学与科学技术管理,(01):28-30.
史修松,赵曙东,吴福象.2009.中国区域创新效率及其空间差异研究[J].数量经济技术经济研究,(03):45-55.
苏方林.2006.中国省域R&D溢出的空间模式研究[J].科学学研究,(05):696-701.
苏方林.2007.省域R&D知识溢出的GWR实证分析[J].数量经济技术经济研究,(02):145-153.
苏方林.2009.中国研发与经济增长的空间统计分析[M].北京:经济科学出版社:58.
孙建,吴利萍,齐建国.2009.技术引进与自主创新:替代或互补[J].科学学研究(01):133-138.
孙建,齐建国.2009.人力资本门槛与中国区域创新收敛性研究[J].科研管理,(06):31-38.
孙建,吴利萍.2010.区域研发、知识溢出与中国经济增长——区域研发宏观效应评价[J].西部论坛,(01):41-49.
孙建,周兵.2009.工业技术发展战略选择与中国宏观经济增长——基于宏观协整计量经济模型的实证[J].华东经济管理,(02):36-40.
孙建.2005.重庆出口贸易与经济增长的相关性分析[J].重庆工商大学学报.西部论坛,(02):43-46.
孙建.2008.中国工业技术发展战略与经济增长——基于宏观计量经济模型的研究[J].河北经贸大学学报,(04):22-26.
孙建.2011.中国区域创新内生俱乐部收敛研究——空间过滤与门槛面板分析[J].科学学与科学技术管理,(7):74-80.
唐德祥,李京文,孟卫东.2008.R&D对技术效率影响的区域差异及其路径依赖——基于我国东、中、西部地区面板数据随机前沿方法(SFA)的经验分析[J].科研管理,(02):115-121+127.
涂俊,吴贵生.2006.基于DEATobit两步法的区域农业创新系统评价及分析[J].数量经济技术经济研究,(04):136-145.
王达政.2009.自主创新还是技术引进——基于我国专利投入产出的实证研究[J].科技进步与对策,(24):30-34.
王家庭,单晓燕.2010.我国区域技术创新的效率测度及动态比较[J].中国科技论坛,(11):73-78.
王劲峰.2006.空间分析[M].北京:科学出版社.
王立平.2008.知识溢出及其对我国区域经济增长作用的实证研究[M].合肥:合肥工业大学出版社.5.
王锐淇,彭良涛,蒋宁.2010.基于SFA与Malmquist方法的区域技术创新效率测度与影响因素分析[J].科学学与科学技术管理,(09):121-128.
王善礼.2008.区域创新环境对区域技术创新效率影响的实证研究[D].重庆大学,硕士论文
王元.2006.自主创新是建设创新型国家的必然[J].前线,(06):19-20.
王争,史晋川.2007.转型时期中国工业生产绩效的地区差异及波动性的解释——基于随机前沿生产函数的分析[J].世界经济文汇,(04):29-45.
王铮,马翠芳,王莹,翁桂兰.2003.区域间知识溢出的空间认识[J].地理学报,(05):773-780.
王志刚.2008.面板数据模型及其在经济分析中的应用[M].北京:经济科学出版社.9.
魏守华,吴贵生,吕新雷.2010.区域创新能力的影响因素——兼评我国创新能力的地区差距[J].中国软科学,(09):76-85.
邬滋.2010.集聚结构、知识溢出与区域创新绩效——基于空间计量的分析[J].山西财经大学学报,(03):15-22.
毋红军,刘章.2003.统计数据的异常值检验[J].华北水利水电学院学报,(01):69-72.
吴和成.2008.专利产出对科技投入要素的弹性研究[J].科技进步与对策,(02):142-144.
吴玉鸣.2004.中国经济增长与收入分配差异的空间统计分析[D].华东师范大学,博士论文
吴玉鸣.2006.空间计量经济模型在省域研发与创新中的应用研究[J].数量经济技术经济研究,(05):74-85+130.
吴玉鸣.2007.中国区域研发、知识溢出与创新的空间计量经济研究[M].北京:人民出版社.
向坚,刘洪伟.2011.技术创新绩效评价研究综述[J].科技进步与对策,(06):155-160.
向希尧,蔡虹.2008.试论地理距离与社会距离对知识溢出的影响——基于专利引用研究视角[J].外国经济与管理,(11):18-26+42.
萧鸣政.2007.中国政府人力资源开发及其战略[J].上海行政学院学报(03):73-79.
肖敏,谢富纪.2009.我国区域R&D资源配置效率差异及其影响因素分析[J].软科学,(10):1-5.
谢丽娟,杨文鹏,周杭.2009.基于DEA模型的区域创新环境对创新绩效影响的评价[J].西安工程大学学报,(06):124-128+146.
许庆瑞.1990.技术创新管理[M].杭州:浙江大学出版社.
许庆瑞.2002.研究与开发绩效评价在中国：实践与趋势明[J].科研管理,23(1):46-53.
姚伟峰,何枫,冯宗宪.2004.CEPA下珠江三角洲与长江三角洲技术效率比较研究[J].开放导报,(02):104-107.
姚先国,薛强军,黄先海.2007.效率增进、技术创新与GDP增长——基于长三角15城市的实证研究[J].中国工业经济,(02):60-66.
叶阿忠.2003.非参数计量经济学[M].天津:南开大学出版社.7.
于明超,申俊喜.2010.区域异质性与创新效率——基于随机前沿模型的分析[J].中国软科学,(11):182-192.
于瑛英.2006.我国区域R&D效率评价研究[J].经济论坛,(24):21-24.
余泳泽,周茂华.2010.制度环境、政府支持与高技术产业研发效率差异分析[J].财经论丛,(05):1-5.
虞晓芬,李正卫,池仁勇,施鸣炜.2005.我国区域技术创新效率:现状与原因[J].科学学研究,(02):258-264.
袁立科.2007.邻近对技术创新的影响研究[D].重庆大学,博士论文
袁鹏.2009.基于空间过滤的制造业劳动生产率地区收敛性估计[J].数理统计与管理,3:502-510.
岳书敬.2008.中国区域研发效率差异及其影响因素——基于省级区域面板数据的经验研究[J].科研管理,(05):173-179.
张龙.2010.我国财政政策与货币政策及其配合效应分析[D].西北大学,博士论文
张五六.2009.基于分位数回归模型的我国“费雪效应”检验[J].统计教育,(12):7-11.
张晓峒.2001.计量经济学基础[M].天津:南开大学出版社.
张莹,张宗益.2009.区域创新环境对创新绩效影响的实证研究——以重庆市为例[J].科技管理研究,(02):104-106.
张宗和,彭昌奇.2009.区域技术创新能力影响因素的实证分析——基于全国30个省市区的面板数据[J].中国工业经济,(11):35-44.
张宗益,周勇,钱灿,赖德林.2006.基于SFA模型的我国区域技术创新效率的实证研究[J].软科学(02):125-128.
赵国庆,杨健.2003.经济数学模型的理论与方法[M].北京:中国金融出版社.8.
赵立雨,师萍,张炳南.2009.我国基础研究投入的多元效应及度量模型分析[J].科学学与科学技术管理,(10):10-14.
赵立雨.2010.基于SFA的区域R&D效率的空间相关性研究[C].第六届中国科技政策与管理学术年会论文集
赵勇,白永秀.2009.知识溢出测度方法研究综述[J].统计与决策,(08):132-135.
中国科技发展战略研究小组.1999.中国科技发展研究报告（1999）[M].北京,经济管理出版社.
周凌瑶.2010.中国宏观经济年度模型的研制及应用[M].北京:中国农业出版社.6.
周晓艳,葛健,马丽仪.2009.基于动态面板数据模型的中国区域创新体系效率实证[J].经济管理,(03):28-32.
周勇.2006.我国区域技术创新效率的实证研究[D].重庆大学,硕士论文
朱平芳,徐伟民.2003.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——上海市的实证研究[J].经济研究,(06):45-53.
朱有为,徐康宁.2006.中国高技术产业研发效率的实证研究[J].中国工业经济,(11):38-45.
邹新月,罗发友,李汉通.2001.技术创新内涵的科学理解及其结论[J].技术经济,(5):13-14.
Acemoglu.1994.Search in the labour market, incomplete contracts and growth[J].CEPR DiscussionPaper Working Paper,NO.1026.
Acs, Anselin,Varga.2002.Patents and innovation counts as measures of regional production of newknowledge[J].Research Policy,31(7):1069-1085.
Aigner, Lovell,Schmidt.1977.Formulation and estimation of stochastic frontier production functionmodels[J].Journal of Econometrics,6(1):21-37.
Andersson,Karlsson.2006.Regional innovation systems in small and medium-sized regions[J].TheEmerging Digital Economy:55-81.
Anselin, Varga,Acs.1997.Local Geographic Spillovers between University Research and HighTechnology Innovations[J].Journal of urban economics,42(3):422-448.
Anselin, Varga,Acs.2000.Geographic and sectoral characteristics of academic knowledgeexternalities[J]. Regional Science,79(4):435-443.
Anselin,Bera.1998.Spatial dependence in linear regression models with an introduction to spatialeconometrics[A].In Handbook of applied economic statistics[C].New York,Marcel Dekker
Anselin,Florax.1995.New directions in spatial econometrics.Springer.
Anselin,Rey.1991.Properties of tests for spatial dependence in linear regression models[J].Geographical Analysis,23(2):112-131.
Anselin.1992.Spatial data analysis with GIS: an introduction to application in the socialsciences[J].National Center for Geographic Information Analysis Working Paper.
Anselin.1996.The Moran scatterplot as an ESDA tool to assess local instability in spatialassociation[A].In M, H,Urwin.Spatial analytical perspectives on GIS[C]. London,Taylor andFrancis:121
Anselin.2007.Spatial econometrics[A].In Baltagi.A companion to theoretical econometrics[C].Malden,MA, USA,Blackwell Publishing Ltd,:310-330
Arrow.1962.Economic welfare and the allocation of resources for invention[J].UMI Working Paper.
Arundel,Kabla.1998.What percentage of innovations are patented? Empirical estimates for Europeanfirms[J].Research Policy,27(2):127-141.
Azariadis,Drazen.1990.Threshold externalities in economic development[J].The quarterly journal ofeconomics,105(2):501.
Azariadis.1996.The economics of poverty traps part one: complete markets[J].Journal of EconomicGrowth,1(4):449-486.
Bagnai,Ospina.2007.Structural changes and the transition process: a macroeconometric model ofChina[J].Luiss Lab on European Economics Working Documents Series.
Battese,Corra.1977.Estimation of a production frontier model: with application to the pastoral zone ofEastern Australia[J].Australian Journal of Agricultural Economics,21(3):169-179.
Bernardin, et al.1995.Performance appraisal design, development, and implementation[J].Handbook ofhuman resource management,462:493.
Bode.2004.The spatial pattern of localized R&D spillovers: an empirical investigation forGermany[J].Journal of Economic Geography,4(1):43-64.
Bottazzi,Peri.2000.INNOVATION AND SPILLOVERS:EVIDENCE FROM EUROPEANREGIONS[J].CESifo Working Paper,NO.340.
Bottazzi,Peri.2003.Innovation and spillovers in regions: Evidence from European patentdata[J].European Economic Review,47(4):687-710.
Bradley, Morgenroth,Untiedt.2003.Macro-regional evaluation of the Structural Funds using theHERMIN modelling framework[J].Italian Journal of Regional Science,3(3):5-28.
Branstetter.1998.Looking for international knowledge spillovers a review of the literature withsuggestions for new approaches[J].Annales d'Economie et de Statistique:517-540.
Buchinsky.1998.Recent advances in quantile regression models: a practical guideline for empiricalresearch[J].The Journal of Human Resources,33(1):88-126.
Buesa, Heijs, Mart¨nez Pellitero,Baumert.2006.Regional systems of innovation and the knowledgeproduction function: the Spanish case[J].Technovation,26(4):463-472.
Buesa, Heijs, Martnez Pellitero,Baumert.2006.Regional systems of innovation and the knowledgeproduction function: the Spanish case[J].Technovation,26(4):463-472.
Buesa, Heijs,Baumert.2010.The determinants of regional innovation in Europe: A combined factorialand regression knowledge production function approach[J].Research Policy,39(6):722-735.
Cabrer-Borras,Serrano-Domingo.2007.Innovation and R&D spillover effects in Spanish regions: aspatial approach[J].Research Policy,36(9):1357-1371.
Cambell, Mccoloy, Oppler,Sager.1993.personal selection in organization.San Francisco Josey-Bass:35-70.
Cani ls,Verspagen.2001.Barriers to knowledge spillovers and regional convergence in an evolutionarymodel[J].Journal of Evolutionary Economics,11(3):307-329.
Cassar,Nicolini.2008.Spillovers and growth in a local interaction model[J].the Annals of RegionalScience,42(2):291-306.
Coe,Helpman.1995.International r&d spillovers[J].European Economic Review,39(5):859-887.
Conway.1999.Distinguishing contextual performance from task performance for managerialjobs[J].Journal of Applied Psychology,84(1):3.
Cooke.1996.Regional Innovation System: An Evolutionary Approach, Regional InnovationSystem[A].In H., P.,Heidenreieh.RegionalInnovationSystem[C].London, University of LondonPress
Crosby.2000.Patents, innovation and growth[J].Economic Record,76(234):255-262.
Cullmann, Schmidt-Ehmcke,Zloczysti.2011.R&D Efficiency and Barriers to Entry: a Two-stageSemi-parametric DEA Approach[J].Oxf. Econ. Pap.,63(2).
Czarnitzki,Hussinger.2004.The link between R&D subsidies, R&D spending and technologicalperformance[J].ZEW-Centre for European Economic Research Working Paper.
Czarnitzki,Licht.2006.Additionality of public R&D grants in a transition economy[J].Economics ofTransition,14(1):101.
De Dominicis, Florax,De Groot.2011.Regional Clusters of Innovative Activity in Europe: Are SocialCapital and Geographical Proximity the Key Determinants?[J].Tinbergen Institute DiscussionPapers.
De Graeve, Kick,Koetter.2008.Monetary policy and financial (in) stability: An integrated micro-macroapproach[J].Journal of Financial Stability,4(3):205-231.
Dixit,Stiglitz.1977.Monopolistic competition and optimum product diversity[J].The AmericanEconomic Review,67(3):297-308.
Eaton,Kortum.1996.Trade in ideas Patenting and productivity in the OECD[J].Journal of InternationalEconomics,40(3-4):251-278.
Edquist, Eriksson,Sjogren.2002.Characteristics of collaboration in product innovation in the regionalsystem of innovation of East Gothia[J].European Planning Studies,10(5):563-581.
Elhorst.2003.Specification and estimation of spatial panel data models[J].International RegionalScience Review,26(3):244.
Elhorst.2010.Spatial panel data models[A].In Fischer,Getis.Handbook of applied spatial analysis[C].Berlin Heidelberg New York,Springer:377-407
Engle,Granger.1987.Cointegration and error correction: representation, estimation and testing[J].Econometrica,55(2):251-76.
Enos.1962.Invention and innovation in the petroleum refining industry[A].In Nelson.The rate anddirection of inventive activity:Economic and social factors[C].Princeton,NJ,Princeton UniversityPress:299-321
Fare,Grosskopf.1997.Efficiency and productivity in rich and poor countries[A].In Wong.Dynamics,economic growth, and international trade[C].Ann Arbor,University of Michigan Press, Studies inInternational Economics:243-63
Farrell.1957.The measurement of productive efficiency[J].Journal of the Royal Statistical Society.Series A (General),120(3):253-290.
Ferstl.2007.Spatial Filtering with EViews and MATLAB[J].Austrian Journal of Statistics,36(1):17-26.
Fischer, Scherngell,Jansenberger.2006.The Geography of Knowledge Spillovers BetweenHigh-Technology Firms in Europe: Evidence from a Spatial Interaction Modeling Perspective[J].Geographical Analysis,38(3):288-309.
Fischer,Varga.2003.Spatial knowledge spillovers and university research: evidence from Austria[J].theAnnals of Regional Science,37(2):303-322.
Fitjar,Rodrguez-Pose.2011.Innovating in the Periphery: Firms, Values and Innovation in SouthwestNorway[J].European Planning Studies,19(4):555-574.
Freeman.1982.The economics of industrial innovation. MIT press:110-114.
Fritsch,Franke.2004.Innovation, regional knowledge spillovers and R&D cooperation[J].ResearchPolicy,33(2):245-255.
Fritsch,Slavtchev.2007.Universities and innovation in space[J].Industry&Innovation,14(2):201-218.
Fritsch.2002.Measuring the Quality of Regional Innovation Systems: A Knowledge ProductionFunction Approach[J]. International Regional Science Review,25(1):86-101.
Funke,Niebuhr.2000.Spatial R&D spillovers and economic growth: evidence from West Germany.Hamburgisches Welt-Wirtschafts-Archiv.
Funke,Niebuhr.2005.Regional geographic research and development spillovers and economic growth:evidence from West Germany[J].Regional Studies,39(1):143-153.
Furman, Porter,Stern.2002.The determinants of national innovative capacity[J].Research Policy,31(6):899-933.
Getis,Griffith.2002.Comparative spatial filtering in regression analysis[J].Geographical Analysis,34(2):130-140.
Getis,Ord.1992. The analysis of spatial association in use of distance statistics[J].GeographicalAnalysis(24):189-206.
Getis,Ord.1996.Local spatial statistics: an overview[J].Spatial analysis: Modelling in a GISenvironment,374.
Goodchild, RP,Wise.1992.Integrating GIS and Spatial Data Analysis: problems and possibilities[J].J.Geographical Information Systems,6(5):407-23.
Greene.2005.Fixed and random effects in stochastic frontier models[J].Journal of ProductivityAnalysis,23(1):7-32.
Gregory,Hansen.1996.Residual-based tests for cointegration in models with regime shifts[J].Journal ofEconometrics,70(1):99-126.
Griffith.2000.A linear regression solution to the spatial autocorrelation problem[J].Journal ofGeographical Systems,2(2):141-156.
Griliches.1979.Issues in Assessing the Contribution of Research and Development to ProductivityGrowth[J].The Bell Journal of Economics,10(1):92-116.
Griliches.1980.R&D and the Productivity Slowdown[J].The American Economic Review,70(2):343-348.
Griliches.1990.Patent statistics as economic indicators: a survey[J].Journal of economic literature,28(4):1661-1707.
Griliches.1992.The search for R&D spillovers[J].The Scandinavian Journal of Economics,94:29-47.
Griliches.1998.R&D and Productivity[M].Chicago:University of Chicago Press.
Grossman,Helpman.1991.Trade, knowledge spillovers, and growth[J].NBER Working Paper.
Grossman,Helpman.1994.Endogenous innovation in the theory of growth[J].The Journal of EconomicPerspectives,8(1):23-44.
Guan,Chen.2010.Modeling macro-R&D production frontier performance: an application to Chineseprovince-level R&D[J].Scientometrics,82(1):165-173.
Guellec,De La Potterie.2003.The impact of public R&D expenditure on business R&D[J].Economicsof innovation and new technology,12(3):225-243.
Gutierrez.2003.On the power of panel cointegration tests: a Monte Carlo comparison[J].EconomicsLetters,80(1):105-111.
Hagedoorn,Cloodt.2003.Measuring innovative performance: is there an advantage in using multipleindicators?[J].Research Policy,32(8):1365-1379.
Hansen.1992.Tests for parameter instability in regressions with I (1) processes[J].Journal of Business&Economic Statistics,10(3):321-335.
Hansen.1999.Threshold effects in non-dynamic panels: Estimation, testing, and inference[J].Journal ofEconometrics,93(2):345-368.
HO.2006.INCOME THRESHOLDS AND GROWTH CONVERGENCE: A PANEL DATAAPPROACH[J].The Manchester School,74(2):170-189.
Hoover.1970.The vascular plants of San Luis Obispo County, CaliforniaUniversity of California Press,Berkeley.
Hsiao.2003.Analysis of panel data.Cambridge Univ Press.
Hu,Mathews.2005.National innovative capacity in East Asia[J].Research Policy,34(9):1322-1349.
Hu,Mathews.2008.China's national innovative capacity[J].Research Policy,37(9):1465-1479.
Ilgen,Schneider.1991.Performance measurement: A multi-discipline view[J].International review ofindustrial and organizational psychology,6:71.
Im, Pesaran,Shin.2003.Testing for unit roots in heterogeneous panels[J].Journal of Econometrics,115(1):53-74.
Isard.1960.Methods of regional analysis: an introduction to regional science[M].New York:Publishedjointly by the Technology Press of the Massachusetts Institute of Technology and Wiley.
Jaffe, Trajtenberg,Henderson.1993.Geographic Localization of Knowledge Spillovers as Evidenced byPatent Citations[J].Quarterly Journal of Economics,108(3):577-598.
Jaffe,Trajtenberg.1996.Flows of knowledge from universities and federal labs: modeling the flow ofpatent citations over time and across institutional and geographic boundaries[J].NBER workingpaper.
Jaffe.1986.Technological opportunity and spillovers of R&D: evidence from firms' patents, profits,and market value[J].The American Economic Review,76(5):984-1001.
Jaffe.1989.Real Effects of Academic Research[J].American Economic Review,79(5):957-970.
Jondrow.1982.On the estimation of technical inefficiency in the stochastic frontier production functionmodel[J].Journal of Econometrics,19(2-3):233-238.
Josty.1990.A tentative model of the innovation process[J].R&D Management,20(1):35-45.
Jungmittag.2006.Innovation dynamics in the EU: convergence or divergence? A cross-country paneldata analysis[J].Empirical Economics,31(2):313-331.
Kao.1999.Spurious regression and residual-based tests for cointegration in panel data[J].Journal ofEconometrics,90(1):1-44.
Keilbach.2000.Spatial knowledge spillovers and the dynamics of agglomeration and regionalgrowth.Springer.
Keller.2002.Trade and the Transmission of Technology[J].Journal of Economic Growth,7(1):5-24.
Keller.2004.International technology diffusion[J].Journal of economic literature,42(3):752-782.
Kim,Han.2001.A decomposition of total factor productivity growth in Korean manufacturingindustries: A stochastic frontier approach[J].Journal of Productivity Analysis,16(3):269-281.
Koenker,Bassett Jr.1978.Regression quantiles[J].Econometrica: journal of the EconometricSociety,46(1):33-50.
Koop, Osiewalski,Steel.1999.The components of output growth: A stochastic frontier analysis[J].Oxford Bulletin of Economics and statistics,61(4):455-487.
Kortum.1998.a Model of Research, Patenting, and Technological Change[J].National Bureau ofEconomic Research Cambridge, Mass., USA Working Paper.
Krammer.2009.Drivers of national innovation in transition: Evidence from a panel of EasternEuropean countries[J].Research Policy,38(5):845-860.
Krugman.1991.Geography and trade.the MIT Press.
Kumbhakar,Lovell.2000.Stochastic frontier analysis.Cambridge Univ Pr.
Levin, Lin,James Chu.2002.Unit root tests in panel data: asymptotic and finite-sampleproperties[J].Journal of Econometrics,108(1):1-24.
Li,Racine.2004.Cross-validated local linear nonparametric regression[J].Statistica Sinica,14(2):485-512.
Li,Racine.2007.Nonparametric econometrics: Theory and practice[M].N.J.:Princeton University PressPrinceton.
Li.2009.China's regional innovation capacity in transition: An empirical approach[J].ResearchPolicy,38(2):338-357.
Lichtenberg.1988.The private R and D investment response to federal design and technicalcompetitions[J].The American Economic Review,78(3):550-559.
Lucas.1988.On the mechanics of economic development[J].Journal of Monetary Economics,22(1):3-42.
Lundvall.1988.Innovation as an interactive process: from user-producer interaction to the nationalsystem of innovation[J].Technical change and economic theory:349-369.
Mansfield.1971.The economics of technological change[M].New York:W.W.Norton and Company.
Maudos, Pastor,Serrano.1999.Total factor productivity measurement and human capital in OECDcountries[J].Economics Letters,63(1):39-44.
McCoskey,Kao.1998.A residual-based test of the null of cointegration in panel data[J].Econometricreviews,17(1):57-84.
Meeusen,van Den Broeck.1977.Efficiency estimation from Cobb-Douglas production functions withcomposed error[J].International Economic Review,18(2):435-444.
Moreno, Paci,Usai.2005.Spatial spillovers and innovation activity in European regions[J].Environmentand Planning A,37(10):1793-1812.
Mueser.1985.Identifying technical innovations[J].IEEE Transactions on Engineering Management,32:158-176.
Myers,Marquis.1969.Successful industrial innovations: A study of factors underlying innovation inselected firms[M].Washington:National Science Foundation.
Narayanan.2001.Managing Technology and Innovation for Competitive Advantage.New Jersey:Prentice Hall.
Nasierowski,Arcelus.2003.On the efficiency of national innovation systems[J].Socio-EconomicPlanning Sciences,37(3):215-234.
Nelson.1959.The simple economics of basic scientific research[J].The Journal of PoliticalEconomy,67(3):297-306.
Nelson.1993.National innovation systems: a comparative analysis.Oxford University Press, USA.
Pakes,Griliches.1980.Patents and R&D at the firm level: A first report[J].Economics Letters,5(4):377-381.
Pakes,Griliches.1984.Estimating Distributed Lags in Short Panels with an Application to theSpecification of Depreciation Patterns and Capital Stock Constructs[J].The Review of EconomicStudies,51(2):243.
Patuelli, Griffith, Tiefelsdorf,Nijkamp.2011.Spatial Filtering and Eigenvector Stability: Space-TimeModels for German Unemployment Data[J].International Regional Science Review,34(2):253.
Pedroni.1999.Critical values for cointegration tests in heterogeneous panels with multipleregressors[J].Oxford Bulletin of Economics and statistics,61(S1):653-670.
Perelman.1995.R&D, technological progress and efficiency change in industrial activities[J].Review ofIncome and Wealth,41(3):349-366.
Pires,Garcia.2004.Productivity of Nations: a stochastic frontier approach to TFP decomposition[C].Econometric Society,Latin AmericanMeetings(292)
Ponds, Oort,Frenken.2010.Innovation, spillovers and university¨Cindustry collaboration: an extendedknowledge production function approach[J].Journal of Economic Geography,10(2):231.
Racine,Li.2004.Nonparametric estimation of regression functions with both categorical and continuousdata[J].Journal of Econometrics,119(1):99-130.
Rangel, Diniz-Filho,Bini.2010.SAM: a comprehensive application for Spatial Analysis inMacroecology[J].Ecography,33(1):46-50.
Ray,Desli.1997.Productivity growth, technical progress, and efficiency change in industrializedcountries: Comment[J].The American Economic Review,87(5):1033-1039.
Rodrguez-Pose,Crescenzi.2008.Research and development, spillovers, innovation systems, and thegenesis of regional growth in Europe[J].Regional Studies,42(1):51-67.
Romer.1986.Increasing returns and long-run growth[J].The Journal of Political Economy,94(5):1002-1037.
Romer.1990.Endogenous technological change[J].Journal of Political Economy,98(5):71-102.
Rondé,Hussler.2005.Innovation in regions: what does really matter?[J].Research Policy,34(8):1150-1172.
Scherer.1965.Firm size, market structure, opportunity, and the output of patented inventions[J].TheAmerican Economic Review,55(5):1097-1125.
Schmidt,Sickles.1984.Production frontiers and panel data[J].Journal of Business&EconomicStatistics,2(4):367-374.
Schulze.2004.Applied quantile regression: microeconometric, financial, and environmental analyses[J].Inaugural-Dissertation, Tubingen.
Sharma,Thomas.2008.Inter-country R&D efficiency analysis: An application of data envelopmentanalysis[J].Scientometrics,76(3):483-501.
Stoneman.1983.The economic analysis of technological change[M].Oxford:Oxford University Press.
Tadesse.2002.Financial architecture and economic performance: international evidence[J].Journal offinancial intermediation,11(4):429-454.
Thomas, Sharma,Jain.2010.Using patents and publications to assess R&D efficiency in the states of theUSA[J].World Patent Information.
Tobler.1979.Lattice tuning[J].Geographical Analysis,11(1):36-44.
Todtling,Trippl.2005.One size fits all?Towards a differentiated regional innovation policyapproach[J].Research Policy,34(8):1203-1219.
Utterback.1974.Innovation in Industry and the Diffusion of Technology[J].Science,183(4125):620.
Varga,Schalk.2004.Knowledge spillovers, agglomeration and macroeconomic growth: An empiricalapproach[J].Regional Studies,38(8):977-989.
Varga,Schalk.2006.Macroeconomic effects of the geography of technological change[J]. DIMEworkshop on Dynamics of Knowledge Accumulation, Competitiveness, Regional Cohesion andEconomic Policies Working Paper,WIIW, Vienna.
Wallsten.2000.The effects of government-industry R&D programs on private R&D: the case of theSmall Business Innovation Research program[J].The Rand Journal of Economics:82-100.
Wang,Ho.2010.Estimating fixed-effect panel stochastic frontier models by model transformation[J].Journal of Econometrics,157(2):286-296.
Wang,Huang.2007.Relative efficiency of R&D activities: A cross-country study accounting forenvironmental factors in the DEA approach[J].Research Policy,36(2):260-273.
Woodward, Figueiredo,Guimaraes.2006.Beyond the Silicon Valley: University R&D andhigh-technology location[J]. Journal of urban economics,60(1):15-32.
Yu, Lu,Stander.2003.Quantile regression: applications and current research areas[J].Journal of theRoyal Statistical Society: Series D (The Statistician),52(3):331-350.
Zhong, Yuan, Li,Huang.2011.The performance evaluation of regional R&D investments in China: Anapplication of DEA based on the first official China economic census data[J]. Omega,39(4):447-455.
Zitikis,Gastwirth.2002.The Asymptotic distribution of the S¨CGini Index[J].Australian&NewZealand Journal of Statistics,44(4):439-446.