中国农业科技创新绩效的地区差异研究——对农业科研机构创新绩效的实证分析
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摘要
文章基于VRS模型测度了中国31个省(市、区) 2007—2016年农业科研机构科技创新绩效,按照华东、西北、华北、中南、西南、东北六大区域进行地区差异分析,并对农业科研机构科技创新绩效差异进行σ收敛和β收敛检验分析。研究表明:从地域差异看,六大区域农业科技创新绩效存在显著差异,按绩效值由高到低依次为:华东区﹥西北区﹥华北区﹥中南区﹥西南区﹥东北区;六大区域农业科研机构科技创新绩效的总体差异并未呈现出显著的σ收敛,但绝对β收敛和条件β收敛模型研究表明,六大区域的农业科研机构科技创新绩效差异正在逐渐缩小,且存在落后者对先进者的"追赶效应";华北区以最快速度缩小省际差距达到内部稳态水平,东北区次之,华东区最为缓慢。正确认识中国农业科研机构科技创新绩效的地区差异,可以促使合理配置农业科技资源,强化农业科技创新驱动力,完善农业科技创新体系,加快现代农业实现的步伐,助力乡村振兴战略。
Based on panel data of China' s 31 provinces from 2007 to 2016, this study uses VRS model to assess provincial agricultural science and technology innovation performance. Then it analyzes spatial and temporal disparity of technology innovation performance in six regions, namely, the Eastern, the Northwest,the Northern, the South Central, the Southwest and the Northeast, and conducts σ convergence and βconvergence analysis of technology innovation performance differences in research institutions. The empirical results are as follows: In terms of spatial differences, there are significant differences between provincial performances. According to its performance value from high to low, six regions can be sorted as follows, the Eastern > the Northwest > the Northern > the South Central > the South West > the Northeast. It didn' t show significant σ convergence in overall disparity of science and technology innovation performance among regional agricultural research institutions. But absolute β convergence and conditional β convergence model suggest that difference of science and technology innovation performance of agricultural research institutions is gradually narrowing down between six regions. And there exists "chase effect" of backward areas on advanced regions. Provinces in North China will narrow the gap between each other at the fastest speed to achieve internal homeostasis level, followed by the Northeastern. And that of the Eastern region is the slowest. A proper understanding of spatial and temporal differences of science and technology innovation performance in China agricultural scientific research institutions is an important prerequisite for rationally allocating agricultural science and technology resources, strengthening the driving force of agricultural science and technology innovation, improving the innovation system of agricultural science and technology, speeding up the pace of modern agriculture, and promoting the strategy of Rural Revitalization.
Based on panel data of China' s 31 provinces from 2007 to 2016, this study uses VRS model to assess provincial agricultural science and technology innovation performance. Then it analyzes spatial and temporal disparity of technology innovation performance in six regions, namely, the Eastern, the Northwest,the Northern, the South Central, the Southwest and the Northeast, and conducts σ convergence and βconvergence analysis of technology innovation performance differences in research institutions. The empirical results are as follows: In terms of spatial differences, there are significant differences between provincial performances. According to its performance value from high to low, six regions can be sorted as follows, the Eastern > the Northwest > the Northern > the South Central > the South West > the Northeast. It didn' t show significant σ convergence in overall disparity of science and technology innovation performance among regional agricultural research institutions. But absolute β convergence and conditional β convergence model suggest that difference of science and technology innovation performance of agricultural research institutions is gradually narrowing down between six regions. And there exists "chase effect" of backward areas on advanced regions. Provinces in North China will narrow the gap between each other at the fastest speed to achieve internal homeostasis level, followed by the Northeastern. And that of the Eastern region is the slowest. A proper understanding of spatial and temporal differences of science and technology innovation performance in China agricultural scientific research institutions is an important prerequisite for rationally allocating agricultural science and technology resources, strengthening the driving force of agricultural science and technology innovation, improving the innovation system of agricultural science and technology, speeding up the pace of modern agriculture, and promoting the strategy of Rural Revitalization.
引文
[1]林毅夫.制度、技术与中国农业发展[M].上海:上海三联书店,上海人民出版社,2008:84-85.
[2]白俊红,蒋伏心.协调创新、空间关联与区域创新绩效[J].经济研究,2015(7):174-187.
[3]张占仓.中国农业供给侧结构性改革的若干战略思考[J].中国农村经济,2017(10):26-37.
[4]刘学,郑军卫.世界著名科学院思想库咨询项目的组织管理机制与启示[J].科学管理研究,2015,33(5):112-115.
[5]COCCIA M. A scientometric model for the assessment of scientific research performance within public institutes[J].Scientometrics,2005,65(3):307-321.
[6]胡慧英,申红芳,廖西元,等.农业科研机构科技创新能力的影响因素分析[J].科研管理,2010,31(3):78-88.
[7]曹博,赵芝俊.技术进步类型选择和我国农业技术创新路径[J].农业技术经济,2017(9):80-87.
[8]李容.我国公共农业科研机构科研激励制度调查分析——以1338名科学家为例[J].科学学研究,2012,30(1):72-80.
[9]万宝瑞.实现农业科技创新的关键要抓好五大转变[J].农业经济问题,2012(10):4-7.
[10]缴旭,魏琦,陈秧分,等.优秀青年农业科技人才离职意愿及其影响因素研究——以中国农业科学院为例[J].农业经济问题,2017(8):45-51,111.
[11]毛世平,曹志伟,刘瀛弢,等.中国农业科研机构科技投入问题研究——兼论国家级农业科研机构科技投入[J].农业经济问题,2013(1):49-56,111.
[12]彭国华.中国地区收入差距、全要素生产率及其收敛分析[J].经济研究,2005(9):19-29.
[13]申红芳,廖西元,胡慧英.农业科研机构科技产出绩效评价及其影响因素分析[J].科研管理,2010,31(6):126-136,150.
[14]MILLER S M,UPADHYAY M P. Total factor productivity and the convergence hypothesis[J]. Journal of Macroeconomics.2002,24(2):267-286.
[15]吴雪莲,张俊飚,丰军辉.农业科研机构科技创新、空间外溢与农业经济增长[J].科技管理研究,2016(17):79-86.
(1)六大农业生态区,即华北区(北京、天津、河北、山西、内蒙)、东北区(辽宁、吉林、黑龙江)、华东区(上海、江苏、浙江、安徽、福建、江西、山东)、中南区(河南、湖北、湖南、广东、广西、海南)、西南区(重庆、四川、贵州、云南、西藏)和西北区(陕西、甘肃、青海、宁夏和新疆)。
(2)2006年国务院发布了《国家中长期科学和技术发展规划纲要(2006—2020)》,本文以纲要发布后至最近一期的数据为数据来源。
[2]白俊红,蒋伏心.协调创新、空间关联与区域创新绩效[J].经济研究,2015(7):174-187.
[3]张占仓.中国农业供给侧结构性改革的若干战略思考[J].中国农村经济,2017(10):26-37.
[4]刘学,郑军卫.世界著名科学院思想库咨询项目的组织管理机制与启示[J].科学管理研究,2015,33(5):112-115.
[5]COCCIA M. A scientometric model for the assessment of scientific research performance within public institutes[J].Scientometrics,2005,65(3):307-321.
[6]胡慧英,申红芳,廖西元,等.农业科研机构科技创新能力的影响因素分析[J].科研管理,2010,31(3):78-88.
[7]曹博,赵芝俊.技术进步类型选择和我国农业技术创新路径[J].农业技术经济,2017(9):80-87.
[8]李容.我国公共农业科研机构科研激励制度调查分析——以1338名科学家为例[J].科学学研究,2012,30(1):72-80.
[9]万宝瑞.实现农业科技创新的关键要抓好五大转变[J].农业经济问题,2012(10):4-7.
[10]缴旭,魏琦,陈秧分,等.优秀青年农业科技人才离职意愿及其影响因素研究——以中国农业科学院为例[J].农业经济问题,2017(8):45-51,111.
[11]毛世平,曹志伟,刘瀛弢,等.中国农业科研机构科技投入问题研究——兼论国家级农业科研机构科技投入[J].农业经济问题,2013(1):49-56,111.
[12]彭国华.中国地区收入差距、全要素生产率及其收敛分析[J].经济研究,2005(9):19-29.
[13]申红芳,廖西元,胡慧英.农业科研机构科技产出绩效评价及其影响因素分析[J].科研管理,2010,31(6):126-136,150.
[14]MILLER S M,UPADHYAY M P. Total factor productivity and the convergence hypothesis[J]. Journal of Macroeconomics.2002,24(2):267-286.
[15]吴雪莲,张俊飚,丰军辉.农业科研机构科技创新、空间外溢与农业经济增长[J].科技管理研究,2016(17):79-86.
(1)六大农业生态区,即华北区(北京、天津、河北、山西、内蒙)、东北区(辽宁、吉林、黑龙江)、华东区(上海、江苏、浙江、安徽、福建、江西、山东)、中南区(河南、湖北、湖南、广东、广西、海南)、西南区(重庆、四川、贵州、云南、西藏)和西北区(陕西、甘肃、青海、宁夏和新疆)。
(2)2006年国务院发布了《国家中长期科学和技术发展规划纲要(2006—2020)》,本文以纲要发布后至最近一期的数据为数据来源。
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