东北三省创新全要素生产率增长的时空特征及其发展趋势预测

doi:10.13249/j.cnki.sgs.2017.02.001

地理科学 ›› 2017, Vol. 37 ›› Issue (2): 161-171.doi: 10.13249/j.cnki.sgs.2017.02.001

• • 下一篇

东北三省创新全要素生产率增长的时空特征及其发展趋势预测

韩增林^1,²(), 孙嘉泽¹(), 刘天宝², 彭飞¹, 钟敬秋^1,²

1.辽宁师范大学海洋经济与可持续发展研究中心,辽宁大连 116029
2.辽宁师范大学城市与环境学院,辽宁大连 116029

收稿日期:2016-03-14 修回日期:2016-09-20 出版日期:2017-02-25 发布日期:2017-02-25
作者简介:
作者简介:韩增林（1956-）,男,教授,博士,博士生导师,主要从事区域发展规划、交通运输地理及海洋经济地理等研究。E-mail:hzl@lnnu.edu.cn
基金资助:
国家自然基金项目(41571122,41601114);辽宁省社科联项目(2016lSLJDWT-28);大连市社科联重点课题(2015DLSKZD078)项目资助

The Spatiotemporal Characteristics and Development Trend Forecast of Innovative TFP Growth in China’s Three Northeastern Provinces

Zenglin Han^1,²(), Jiaze Sun¹(), Tianbao Liu², Fei Peng¹, Jingqiu Zhong^1,²

1.Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029,Liaoning,China
2.College of Urban and Environment, Liaoning Normal University, Dalian 116029, Liaoning, China

Received:2016-03-14 Revised:2016-09-20 Online:2017-02-25 Published:2017-02-25
Supported by:
National Natural Science Foundation of China (41571122, 41601114);Liaoning Provincial Federation Social Science Circles Foundation (20161LSLJDWT-28);Dalian Federation Social Science Circles Major Foundation (2015DLSKZD078)

摘要/Abstract

摘要：

使用DEA-Malmquist方法在对比1994~2013年间中国东北三省、东部、中部和西部地区之间创新全要素生产率（TFP）时空差异的基础上,分析了东北三省内部创新TFP的时空演变特征,并运用PVAR模型对东北三省创新TFP的发展趋势进行了预测。研究表明：① 从空间格局上看东北三省创新TFP增速略高于西部地区,但低于中部和东部地区;② 东北三省创新TFP增长的主要动力来源于技术进步,在东北三省内部吉林省创新TFP的增长最快,其增长动力主要源于纯效率变化,其次为技术进步;而辽宁省和黑龙江省创新TFP的动力主要是技术进步;③ 预测显示东北三省创新TFP增长幅度未来会逐渐放缓,其增长的主要动力将会由技术进步转变为规模效率的改进。

关键词: 创新全要素生产率（TFP）, Malmquist指数, PVAR模型, 东北三省

Abstract:

Among various different measures which can be used to make the promotion of regional economic development, the role of innovation cannot be ignored. Over the past 20 years, the proportion of the total number of researchers in the three northeastern provinces (including Heilongjiang, Jilin and Liaoning) of China has dropped 6.6 percent. Besides, the R & D / GDP of the three northeastern provinces increased by only 0.09%, which is far below the national average (1.51%). According to the current researches, it can be found that the economic growth achieved through the innovation capacity in the northeastern provinces accounts for 49.3%, which indicates that innovation plays an important role during the process of promoting the economic development.Innovation has turned into more and more important for regional development in China. On the basis of the panel data of China ranging from 1995 to 2013, Malmquist index model was used to make the analysis on the spatial and temporal differences of innovation TFP in the three provinces of Northeastearn China. The PVAR model was constructed on decomposed data. The change trend of TFP and its decomposition inthese three provinces of Northeast Chinaareforecasted. In accordance with the above process, three conclusions can be made as follows:1) The innovation TFP growth speed of Northeast China is slightly higher than that of Western China while is lower than Central China and Eastern China. 2) From the inside of the three northeastern provinces, the innovation TFP of Jilin Province, which is driven by the improvement of the management level and the adjustment of the system (PEC), grew fastest from 1995 to 2013. Secondly, the major driving force of innovation TFP of Liaoning Province came from technology. However, its technological progress has been limited by the scale of innovation. The growth rate of innovation TFP in Heilongjiang Province is the slowest, which is mainly due to the limited growth rate of endogenous power (SEC, PTC, STC, PEC). At the same time, the result shows that the promotion of the system and management level in these three northeastern provinces is far greater than the technological progress and the enlargement of the scale. 3) Based on the forecast results, the three provinces in the Northeast innovation TFP growth rate may continue to slow down in the near future. From the perspective of unit changes, STC and SEC unit changes play the dominant roles in improving TFP of the three northeastern provinces. In terms of the degree of influence, the innovation of TFP in Northeast China is mainly affected by the change of PEC and STC.

Key words: innovation total factor productivity, Malmquist index, PVAR model, Northeast China

中图分类号:

F129.9

韩增林, 孙嘉泽, 刘天宝, 彭飞, 钟敬秋. 东北三省创新全要素生产率增长的时空特征及其发展趋势预测[J]. 地理科学, 2017, 37(2): 161-171.

Zenglin Han, Jiaze Sun, Tianbao Liu, Fei Peng, Jingqiu Zhong. The Spatiotemporal Characteristics and Development Trend Forecast of Innovative TFP Growth in China’s Three Northeastern Provinces[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(2): 161-171.

图/表 9

表1

图1

表2

图2

表3

表4

图3

表5

表6

参考文献 32

[1]	国家统计局,科学技术部.中国科技统计鉴[M].北京:中国统计出版社,1994-2014.
	[National Bureau of the People’s Republic of China,The People's Republic of China ministry of science and technology.China statistical yearbook on science and technology.Beijing:China Statistics Press,1994-2014.]
[2]	庞瑞芝, 范玉, 李扬. 中国科技创新支撑经济发展了吗?[J]. 数量经济技术经济研究, 2014, (10): 37-52.
	[Pang Ruizhi, Fan Yu, Li Yang.Has technical innovation Supported Economic development in China?The Journal of Quantitative&Technical Economics. 2014,(10): 37-52.]
[3]	师萍,韩先锋,周凡磬,宋文飞. 全国研发创新全要素生产率增长特征及空间差异分析[J]. 科学学与科学技术管理,2011,32(1):35-39,72.
	[Shi Ping, Han Xianfeng, Zhou Fanqing, Song Wenfei.The analysis of total factor productivity growth features and spatial differences of China＇s R＆D innovation.Science of Science and Management of S.& T,2011,32(1):35-39,72.]
[4]	戴彬, 金刚, 韩明芳, 等. 中国沿海地区海洋科技全要素生产率时空格局演变及影响因素[J]. 地理研究, 2015, 34(2): 328-340. doi: 10.11821/dlyj201502012
	[Dai Bin, Jin Gang, Han Mingfang et al. Analysis on temporal and spatial evolution of Marine science and technology total factor productivity and its influencing factors in Chinese coastal areas. Geographical Research, 2015, 34(2): 328-340.] doi: 10.11821/dlyj201502012
[5]	白俊红,江可申,李婧. 全国地区研发创新的相对效率与全要素生产率增长分解[J]. 数量经济技术经济研究,2009,(3):139-151.
	[Bai Junhong,Shen Kejiang,Li Jing.On the efficiency and total factor productivity growth of China’s R&D innovation. The Journal of Quantitative & Technical Economics, ,2009,(3):139-151.]
[6]	樊华,周德群. 全国省域科技创新效率演化及其影响因素研究[J]. 科研管理,2012,33(1):10-18,26.
	[Fan Hua, Zhou Dequn .Regional science and technology innovation efficiency evolution and its affect factors in Chinese provinces. Science Research Management, 2012,33(1):10-18,26.]
[7]	桂黄宝. 我国高技术产业创新效率及其影响因素空间计量分析[J]. 经济地理, 2014, 34(6): 100-107.
	[Gui Huangbao.Innovation efficiency and its influencing factors of China's High-Tech industry based on the spatial econometric model. Economic Geography, 2014, 34(6): 100-107.]
[8]	方创琳, 马海涛, 王振波, 等. 中国创新型城市建设的综合评估与空间格局分异[J]. 地理学报, 2014, 69(4): 459-473. doi: 10.11821/dlxb201404003
	[Fang Chuanglin, Ma Haitao, Wang Zhenbo et al. Comprehensive assessment and spatial heterogeneity of the construction of innovative cities in China. Acta Geographica Sinica, 2014, 69(4): 459-473.] doi: 10.11821/dlxb201404003
[9]	刘建国, 张文忠. 中国区域全要素生产率的空间溢出关联效应研究[J]. 地理科学, 2014, 34(5): 522-530.
	[Liu Jianguo, Zhang Wenzhong.The spatial spillover effects of regional total factor productivity in China. Scientia Geographica Sinica, 2014, 34(5): 522-530.]
[10]	黄亮, 杜德斌. 创新型城市研究的理论演进与反思[J]. 地理科学, 2014, 34(7): 773-779.
	[Huang Liang, Du Debin.The evolution and Introspection for the theory of innovative city. Scientia Geographica Sinica, 2014, 34(7): 773-779.]
[11]	程叶青, 王哲野, 马靖. 中国区域创新的时空动态分析[J]. 地理学报, 2014, 69(12): 1779-1789. doi: 10.11821/dlxb201412004
	[Cheng Sheqing, Wang Zheye, Ma Jing.Analyzing the space-time dynamics of innovation in China. Acta Geographica Sinica, 2014, 69(12): 1779-1789.] doi: 10.11821/dlxb201412004
[12]	王春杨, 张超. 中国地级区域创新产出的时空模式研究——基于ESDA的实证[J]. 地理科学, 2014, 34(12): 1438-1444.
	[Wang Chunyang, Zhang Chao.Spatial-temporal pattern of prefecture-level innovation outputs in China:An investigation Using the ESDA. Scientia Geographica Sinica, 2014, 34(12): 1438-1444.]
[13]	吕拉昌, 梁政骥, 黄茹. 中国主要城市间的创新联系研究[J]. 地理科学, 2015, 35(1): 30-37.
	[Lv Lachang, Liang Zhengji, Huang Ru.The innovation linkage among Chinese major cities. Scientia Geographica Sinica, 2015, 35(1): 30-37.]
[14]	范斐, 杜德斌, 李恒, 等. 中国地级以上城市科技资源配置效率的时空格局[J]. 地理学报, 2013, 68(10): 1331-1343. doi: 10.11821/dlxb201310003
	[Fan Fei, Du Debin, Li Heng et al. Spatial-temporal characteristics of scientific and technological resources allocation efficiency in prefecture-level cities of China. Acta Geographica Sinica, 2013, 68(10): 1331-1343.] doi: 10.11821/dlxb201310003
[15]	韩增林, 徐丹, 郭建科. 东北三省装备制造业区域专业化水平分析[J]. 地理学报, 2010, 65(8): 899-906.
	[Han Zenglin, Xu Dan, Guo Jianke.Industrial specialization of equipment manufacturing industry in the three provinces of Northeast China. Acta Geographica Sinica, 2010, 65(8): 899-906.]
[16]	王福君, 沈颂东. 东北装备制造业区域合作的重点,模式与对策研究[J]. 东北师大学报:哲学社会科学版, 2011, (3): 54-58.
	[Wang Fujun, Shen Songdong.The main point,model and countermeasures of regional cooperation of Northeast equipment manufacturing industry. Journal of Northeast Normal University (Philosophy and Social Sciences), 2011,(3): 54-58.]
[17]	陈晓刚. 科技创新与东北老工业基地振兴[J]. 辽宁大学学报:哲学社会科学版, 2013, 41(1): 89-94.
	[Chen Xiaogang.Science and technology innovation and the rejuvenation of the old industrial base in Northeast China. Journal of Liaoning University (Philosophy and Social Sciences Edition), 2013, 41(1): 89-94.]
[18]	张利群. 东北三省区域创新体系建设问题与对策研究[J]. 特区经济, 2010, (5): 225-226.
	[Zhang Liqun.Northeast regional innovation system problems and solutions. Special Zone Economy, 2010,(5): 225-226.]
[19]	郑文范,孙家成.论创新驱动与东北老工业基地再振兴[J].科技进步与对策,2014,31(24):41-44. doi: 10.6049/kjjbydc.2014100286
	[Zheng Wenfan, SunJiacheng. Innovation driven and revival of the old industrial base in Northeast China.Science & Technology Progress and Policy, 2014,31(24):41-44.] doi: 10.6049/kjjbydc.2014100286
[20]	王珍珍, 黄茂兴. 我国科技创新效率的实证研究--基于DEA-Malmquist模型和全国省际面板数据[J]. 技术经济, 2013, 32(10): 55-61. doi: 10.3969/j.issn.1002-980X.2013.10.009
	[Wang Zhenzhen, Huang Maoxing.Empirical study on scientific and technological innovation efficiency:based on DEA-Malmquist model and provincial panel data of China. Technolgy Economics, 2013, 32(10): 55-61.] doi: 10.3969/j.issn.1002-980X.2013.10.009
[21]	于波涛, 刘亚杰. 基于DEA的大中型工业企业技术创新效率研究——以东北三省为例[J]. 技术经济与管理研究, 2013, (6): 53-57.
	[Yu Botao, Liu Yajie.Research on technological innovation efficiency of large and medium-sized industrial enterprises based on DEA——taking three provinces in the Northeast of China as examples. Fudan International Studies Review, 2013,(6): 53-57.]
[22]	王晓岭, 武春友, 于文嵩. 绿色增长驱动因素的国际比较研究-基于“20国集团(G20)”面板数据的实证检验[J]. 北京理工大学学报:社会科学版, 2015, 17(6): 12-20. doi: 10.15918/j.jbitss1009-3370.2015.0602
	[Wang Xiaoling, Wu Chunyou, Yu Wensong.International comparison on determinants of green Growth-Empirical analysis on panel data of G20. Journal of Beijing Institute of Technology (Social Sciences Edition), 2015, 17(6): 12-20.] doi: 10.15918/j.jbitss1009-3370.2015.0602
[23]	张瑞, 苏方林, 李臣. 基于PVAR模型的R＆D投入与产出关系的实证研究[J]. 科学学与科学技术管理, 2011, 32(12): 18-25.
	[Zhang Rui, Su Fanglin, Li Chen.An empirical research on the relationships of R&D input and output based on PVAR model. Science of Science and Management of S.& T., 2011, 32(12): 18-25.]
[24]	张诚,张瑜. 跨国企业在华研发活动对我国高科技行业创新的影响——基于面板VAR的分析[J]. 世界经济研究,2012,(2):57-63,88-89.
	[Zhang Cheng,Zhang Yu. The effect of R＆D investment of transnational corporation in China on domestic High-Tech industries' innovation: An analysis based on panel VAR. World Economy Study, 2012,(2):57-63,88-89.]
[25]	王冬, 韩伯棠, 高丽娜. 两化融合和技术创新能力的关系基于PVAR模型的实证研究[J]. 工业经济论坛, 2015, (5): 22-33. doi: 10.11970/j.issn.2095-7866.2015.09.003
	[Wang Dong, Han Baitang, Gao Lina.The relationship analysis between industry and information technology integration and innovation ability --Empirical research based on PVAR model. Industrial Economy Review, 2015,(5): 22-33.] doi: 10.11970/j.issn.2095-7866.2015.09.003
[26]	Zofio J L.Malmquist productivity index decompositions:a unifying framework[J]. Applied Economics, 2007, 39(16/18): 2371-2387. doi: 10.1080/00036840600606260
[27]	Jiménez-Sáez F.Zabala-Iturriagagoitia J M,zofío J L.who leads research productivity growth?guidelines for R&D policy-makers[J]. Scientometrics, 2013, 94(1): 273-303. doi: 10.1007/s11192-012-0763-0
[28]	连玉君, 程建. 投资-现金流敏感性:融资约束还是代理成本?[J]. 财经研究, 2007, 33(2): 37-46. doi: 10.3969/j.issn.1001-9952.2007.02.004
	[Lian Yujun, Cheng Jian.Investment-Cash flow sensitivity: financial constraints or agency costs?. Journal of Finance and Economics, 2007, 33(2): 37-46.] doi: 10.3969/j.issn.1001-9952.2007.02.004
[29]	柳卸林. 技术创新经济学[M].北京:清华大学出版社,2014.1-2
	[Liu Xielin.Economics of technological innovation. Beijing: Tsinghua University Press, 2014:1-2.]
[30]	余泳泽,刘大勇. 我国区域创新效率的空间外溢效应与价值链外溢效应——创新价值链视角下的多维空间面板模型研究[J]. 管理世界,2013,(7):6-20,70,187.
	[Yu Yongze,Liu Dayong. The effect of the space outflow of China's regional innovation and the effect of the outflow of value chanins: A study,from the PersPECtive of the innovative value Chain,on the model of the panel of multidimentsional space.Management World, 2013,(7):6-20,70,187.]
[31]	牛泽东, 张倩肖. 中国装备制造业的技术创新效率[J]. 数量经济技术经济研究, 2012, (11): 51-67.
	[Niu Zedong, Zhang Qianxiao.An analysis of technological innovation eficiency of manufacturing equipment industries in China. The Journal of Quantitative & Technical Economics, 2012,(11): 51-67.]
[32]	李政. 当前东北三省经济增长问题成因与创新转型对策[J]. 经济纵横, 2015, (7): 14-17.
	[Li Zheng.The causes of the problems of economic growth in the Northeast region and the countermeasures of innovation and transformation. Economic Review, 2015,(7): 14-17.]

指数	Malmquist	PEC	PTC	SEC	STC
东北三省	1.091	1.003	1.108	1.041	1.005
东部	1.097	1.007	1.129	1.028	1.024
中部	1.123	1.016	1.084	1.048	1.040
西部	1.080	1.019	1.083	1.056	1.009

指数	Malmquist	PEC	PTC	SEC	STC
1995~1996	1.300	1.048	1.254	1.044	0.947
1996~1997	0.910	0.933	0.979	1.135	0.877
1997~1998	1.158	1.061	1.084	0.683	1.475
1998~1999	1.059	1.073	1.001	1.197	0.824
1999~2000	1.527	1.095	1.409	0.982	1.008
2000~2001	0.728	0.966	1.011	0.857	0.871
2001~2002	1.087	0.951	1.227	1.443	0.645
2002~2003	0.808	0.522	1.775	0.658	1.327
2003~2004	1.204	1.558	0.698	1.224	0.905
2004~2005	1.342	0.994	1.297	1.272	0.819
2005~2006	0.914	0.923	0.882	1.100	1.019
2006~2007	1.532	0.920	1.382	0.975	1.237
2007~2008	0.697	0.887	0.980	1.095	0.732
2008~2009	1.563	1.443	1.025	0.737	1.434
2009~2010	0.819	0.622	0.998	1.300	1.013
2010~2011	1.260	1.043	1.234	0.992	0.987
2011~2012	0.874	1.089	0.800	1.016	0.987
2012~2013	0.850	0.932	0.911	1.025	0.976
1995~2013	1.091	1.003	1.108	1.041	1.004

时期	地区	Malmquist	PEC	PTC	SEC	STC
	黑龙江	1.075	1.011	1.072	1.065	0.991
1995~2002年	吉林	1.244	1.103	1.111	1.019	1.016
	辽宁	1.120	1.017	1.139	1.062	0.972
	黑龙江	1.104	1.097	1.200	1.003	1.043
2002~2008年	吉林	1.654	1.547	1.351	1.025	1.055
	辽宁	1.051	0.950	1.203	1.039	0.999
	黑龙江	1.018	1.008	0.978	0.952	1.105
2008~2013年	吉林	1.156	1.248	0.940	0.947	1.093
	辽宁	1.111	1.036	1.054	1.001	1.027
	黑龙江	1.069	1.039	1.088	1.013	1.040
1995~2013年	吉林	1.356	1.291	1.144	1.001	1.050
	辽宁	1.094	1.000	1.136	1.037	0.996

变量	LLC	Breitung	IPS
Malmquist	-6.0505^***	-4.0174^***	-3.6022^***
PEC	-7.8016^***	-4.1239^***	-4.0515^***
SEC	13.7514	-5.2212^***	-4.7774^***
PTC	-5.6219^***	-4.3472^***	-3.4753^***
STC	-1.7345^**	-2.6164^***	-4.2480^***

VARIABLES	Malmquist	PTC	PEC	STC	SEC
L.Malmquist	-1.833^***	-0.0998	-2.327^***	-0.182^***	0.150^***
	(0.181)	(0.106)	(0.355)	(0.0291)	(0.0354)
L.PTC	1.682^***	-0.305	2.820^***	0.319^***	-0.222^***
	(0.235)	(0.191)	(0.483)	(0.0494)	(0.0566)
L.PEC	1.453^***	0.409^***	1.268^***	0.162^***	-0.103^***
	(0.114)	(0.0852)	(0.196)	(0.0215)	(0.0298)
L.STC	4.903^***	1.532^***	5.388^***	-0.371^***	0.318^**
	(0.584)	(0.315)	(0.732)	(0.120)	(0.146)
L.SEC	5.832^***	2.479^***	5.730^***	0.307^**	-0.287^*
	(0.631)	(0.300)	(0.805)	(0.120)	(0.163)
Observations	48	48	48	48	48

东北三省创新全要素生产率增长的时空特征及其发展趋势预测

The Spatiotemporal Characteristics and Development Trend Forecast of Innovative TFP Growth in China’s Three Northeastern Provinces

RichHTML

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 32

相关文章 15

Metrics

本文评价

推荐阅读 10

时期	模型变量	PTC	PEC	STC	SEC	Malmquist
2	Malmquist	0.0005	0.2737	0.0347	0.2800	0.4111
5	Malmquist	0.0974	0.2326	0.0476	0.2581	0.3643
10	Malmquist	0.1011	0.2257	0.0641	0.2502	0.3589
15	Malmquist	0.1017	0.2254	0.0644	0.2499	0.3586

[1]	李宁,李铁滨,房艳刚,周丽君,王昱,赵伟. 吉林省县域经济效率时空格局演化研究[J]. 地理科学, 2019, 39(8): 1293-1301.
[2]	黄禹铭. 东北三省城乡协调发展格局及影响因素[J]. 地理科学, 2019, 39(8): 1302-1311.
[3]	马丽亚,修春亮,冯兴华. 基于母子企业联系的东北三省城市网络特征[J]. 地理科学, 2019, 39(7): 1129-1138.
[4]	陈卓,金凤君,王姣娥. 基于高速公路流的东北大都市区边界识别与结构特征研究[J]. 地理科学, 2019, 39(6): 929-937.
[5]	田俊峰, 王彬燕, 王士君. 东北三省城市土地利用效益评价及耦合协调关系研究[J]. 地理科学, 2019, 39(2): 305-315.
[6]	李成宇, 张士强, 张伟. 中国省际工业生态效率空间分布及影响因素研究[J]. 地理科学, 2018, 38(12): 1970-1978.
[7]	戚伟, 刘盛和, 金凤君. 东北三省人口流失的测算及演化格局研究[J]. 地理科学, 2017, 37(12): 1795-1804.
[8]	刘洋, 王雨飞, 刘勇, 王光辉. 基于生态位理论的东北三省政府干预强度与市场化水平格局演变研究[J]. 地理科学, 2016, 36(9): 1301-1309.
[9]	郑蕾, 刘毅, 刘卫东. 东北三省对外直接投资空间格局及影响因素[J]. 地理科学, 2016, 36(9): 1329-1337.
[10]	刘志高, 张薇, 刘卫东. 中国东北三省对外贸易空间格局研究[J]. 地理科学, 2016, 36(9): 1349-1358.
[11]	关伟, 曹佳宾, 许淑婷. 东北三省服务业发展空间极化的演变及驱动因子分析[J]. 地理科学, 2015, 35(6): 733-741.
[12]	陈雪婷, 宋涛, 蔡建明, 李玏, 邓羽. 基于DEA和Malmquist的中国城市代谢效率研究[J]. 地理科学, 2015, 35(4): 419-426.
[13]	蔡善柱, 陆林. 中国经济技术开发区效率测度及时空分异研究[J]. 地理科学, 2014, 34(7): 794-802.
[14]	孙景荣, 张捷, 章锦河, 马金海, 李莉, 张富生. 中国区域旅行社业效率的空间分异研究[J]. 地理科学, 2014, 34(4): 430-437.
[15]	王洪桥, 袁家冬, 孟祥君. 东北三省旅游经济差异的时空特征分析[J]. 地理科学, 2014, 34(2): 163-169.