我国农业科技创新能力与效率研究
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摘要
创新是国家经济增长的源泉和动力,创新已成为民族进步的灵魂。农业科技创新则必然成为农业增长的主导动力。目前,我国农业科技创新存在自主创新能力不强,科技水平不高、农业科技推广滞后,农业科技成果转化率低等问题。尽管国家已出台系列支农和惠农政策,逐年加大对农业科技创新平台建设的投入力度,但我国农业科技创新能力水平及各区域间差异程度如何、农业科技创新效率水平及各区域间差异程度如何、我国农业科技创新的能力和效率协调性程度,是我国农业由传统农业向现代农业转轨过程中必须要解决的关键问题,也是我国各级政府决策时面临的重大现实问题。且这些方面都是目前理论探讨的薄弱点或空白点。基于此,本文从农业科技创新创新能力、效率、能力与效率协调性等方面对我国农业科技创新进行研究,从理论上以弥补相关研究方面的欠缺,同时为各级政策提供决策依据。
本文在梳理相关理论和国内外文献的基础上,首先从农业科技创新潜在能力、农业科技创新发展能力、农业科技创新产出能力及农业科技创新贡献能力方面构建农业科技创新能力指标体系,运用因子分析法,利用2006-2008年的统计数据对我国农业科技创新的整体水平及各区域的农业科技创新能力进行评价。其次,运用DEA模型和投入产出模型,利用2006-2008年的统计数据对我国农业科技创新的整体效率及各区域的农业科技创新效率进行评价,并对影响农业科技创新效率的因素进行实证分析。再次,基于能力分析和效率分析的基础上,运用空间计量经济的投影变换原理,构建农业科技创新水平指数,利用2006-2008年的统计数据对我国农业科技创新的整体水平及各区域的农业科技创新水平进行评价,并对我国农业科技创新能力与效率协调性进行实证分析。第四、在全面总结美国、德国、荷兰、以色列等国农业科技创新实践经验的基础上,有针对性、分区域地提出提高我国农业科技创新水平的对策。论文主要研究结论如下:
(1)根据因子分析法的评价结果,我国各省农业科技创新能力差异较大。东部地区农业科技创新能力最强,以北京和上海两地尤其突出,广东、浙江、山东、江苏也显著的高于全国平均水平;西部省市区域农业科技创新能力得分均低于全国平均水平;中部地区的河南,东北地区的黑龙江,华南地区的福建、华北地区的天津的农业科技创新能力略高于全国平均水平;
(2)通过投入产出法分析得出,2006-2008年,大多数位于中东部省(市)农业科技创新效率处于第一类和第二类水平,效率较高,西部地区的农业科技创新效率处于第三类和第四类水平(青海和宁夏除外),效率较低。农业科技创新Malmquist生产率指数的分解结果得出,中国农业科技创新效率的增长主要是由技术进步所引起的,而不是得益于技术效率的改善。
(3)1990-2008年,中国农业科技创新效率处于适度增长的态势,年平均增长率为3%,向中国农业总产值的增长率贡献了29.7%。从不同时期来看,中国农业科技创新效率TFP增长呈现出明显的波动性特征,整体呈现“U”型演进轨迹;从区域层面来看,2006-2008年,东、中、西部三大地区的农业科技创新的TFP增长率均实现了正增长,但是存在着显著的区域差异,其中西部地区的增长速度最快,东部地区次之,中部地区最慢。
(4)通过构造农业科技创新水平指数得出,2006-2008年我国农业科技创新整体创新水平较低(0.3999),呈现波动状态。通过构造农业科技创新协调系数指数得出,2006-2008年我国农业科技创新整体协调性较高(0.9348),呈现波动状态,但变化幅度不大,协调性基本趋于一致。通过对农业科技创新水平与协调性进行聚类分析得出,农业科技创新类型呈现高水平高协调型、高水平低协调型、低水平高协调型和低水平低协调型四种类型。大部分省(市)的农业科技创新水平和农业科技创新协调性基本保持一致,农业科技创新水平与协调性两因素呈弱正相关性(Pearson相关系数为0.387)。
Innovation is the resources of essential and motivation of state economy’s increasing, and it is core of national development. Therefore, innovation of agricultural science and technology will become the main motivation of agricultural growth. At present, there are such problems in innovation of agricultural science and technology as independent innovation capability is limited, sci-tech level is not high and agricultural extension is delay. Although the central government has adopted a series of policies to assist agriculture, and increased input to construct the platform for innovation of agricultural science and technology annually, there are still key problems need to be solved during transferring from traditional agriculture to modern agriculture, such as the difference of different regions on innovation level and efficiency of agricultural science and technology, the ability and efficiency coordinating degree of agricultural science and technology. These are also important questions of reality the government at all levels facing to when they make decision. At present, the theory research is blank or weak in these fields.
Therefore, the thesis does research on innovation of agricultural science and technology from ability, efficiency, and the coordinating between ability and efficiency, in order to cover the shortage in relevant research and offer reference for policies’decision making.
On the basis of the review on related theories and documents home and abroad, from the perspective of potential ability,development ability, output ability and contribution ability on innovation of agricultural science and technology, the thesis is firstly to analyze how construct the index system for the ability and evaluate the integrated ability of China as a whole and ability in different regions on innovation of agricultural science and technology by using Factor anlytic method and statistical data. Secondly, it stresses on the evaluation of the efficiency on innovation of agricultural science and technology nationally and regionally, and the analysis on the factors that affect the efficiency. Thirdly, it focuses on the evaluation of the national and regional level on innovation of agricultural science and technology through the statistical data collected from 2006 to 2008 by using special data analysis and constructing the index on the level of innovation of agricultural science and technology. Lastly, it proposes the suggestions on raising the level of innovation of agricultural science and technology in China, according to the summary of the experiences and practices about innovation of agricultural science and technology from America, Israel and Japan.
The thesis has such conclusion as follows:
1. According to the Evaluate Results of Factor Analysis Method, the innovative capacity of agricultural science and technology of every province in China is quite different. The eastern region has the strongest capacity , especially in Beijing and Shanghai, and the capacity of Guangdong, Zhejiang, Shandong, Jiangsu is also significantly higher than the national average level. The capacity in the western regional provinces is lower than the national average level. The innovation capacity of Henan Province in the western region, Heilongjiang Province in the northeastern region, Fujian Province in the south China region and Tianjin in the north China region is slightly higher than the national average level.
2. The conclusion is gotten through Input Output Analysis Method as that from 2006 to 2008, the efficiency of agricultural science and technology innovation of most provinces (cities) located in east central China is at the first-class and second-class level, which is quite high. The correspondence of west China is at the third-class and fourth-class level, which is quite low. After analyzing the Malmquist index of agricultural science and technology innovation, we could get the conclusion that the increasing of the efficiency of agricultural science and technology innovation in China is caused by technology improving, instead of the amelioration of technological efficiency.
3. 1990—2008, the efficiency of agricultural science and technology innovation is in the moderate growing situation in annual growth of 3%, and the growth rate has made a contribution of 29.7% to the growth rate of China’s agricultural output. During the different periods, the growth of China’s agricultural TFP has displayed obvious volatility features, which shows like“U”type track overall. From the aspect of region, the growth of agricultural TFP in the all three regions has achieved positive growth from 2006 to 2008, however, there are significant regional differences, which the growth of western region is the fastest, the eastern region takes second place, followed by the slowest central region.
4. Through the establishment of agricultural science and technology index, we could know that China’s efficiency of agricultural science and technology innovation (2006-2008) was in fluctuation, at a lower level (0.3999). At the same time, the agriculture science and technology innovation coordinate coefficient index was at a higher level (0.9348), in fluctuation with little variation amplitude and keep in coordination. Clustering analysis the agriculture science and technology innovation level and coordination determined the four types of agriculture science and technology innovation i.e. high innovation level and high coordination type, high innovation level and low coordination type, low innovation level and high coordination type, low innovation level and low coordination type. Most of provinces’agriculture science and technology innovation level and agriculture science and technology innovation coordination were in consistent, the innovation level and coordination were in weak correlation (the index of Pearson is 0.387).
本文在梳理相关理论和国内外文献的基础上,首先从农业科技创新潜在能力、农业科技创新发展能力、农业科技创新产出能力及农业科技创新贡献能力方面构建农业科技创新能力指标体系,运用因子分析法,利用2006-2008年的统计数据对我国农业科技创新的整体水平及各区域的农业科技创新能力进行评价。其次,运用DEA模型和投入产出模型,利用2006-2008年的统计数据对我国农业科技创新的整体效率及各区域的农业科技创新效率进行评价,并对影响农业科技创新效率的因素进行实证分析。再次,基于能力分析和效率分析的基础上,运用空间计量经济的投影变换原理,构建农业科技创新水平指数,利用2006-2008年的统计数据对我国农业科技创新的整体水平及各区域的农业科技创新水平进行评价,并对我国农业科技创新能力与效率协调性进行实证分析。第四、在全面总结美国、德国、荷兰、以色列等国农业科技创新实践经验的基础上,有针对性、分区域地提出提高我国农业科技创新水平的对策。论文主要研究结论如下:
(1)根据因子分析法的评价结果,我国各省农业科技创新能力差异较大。东部地区农业科技创新能力最强,以北京和上海两地尤其突出,广东、浙江、山东、江苏也显著的高于全国平均水平;西部省市区域农业科技创新能力得分均低于全国平均水平;中部地区的河南,东北地区的黑龙江,华南地区的福建、华北地区的天津的农业科技创新能力略高于全国平均水平;
(2)通过投入产出法分析得出,2006-2008年,大多数位于中东部省(市)农业科技创新效率处于第一类和第二类水平,效率较高,西部地区的农业科技创新效率处于第三类和第四类水平(青海和宁夏除外),效率较低。农业科技创新Malmquist生产率指数的分解结果得出,中国农业科技创新效率的增长主要是由技术进步所引起的,而不是得益于技术效率的改善。
(3)1990-2008年,中国农业科技创新效率处于适度增长的态势,年平均增长率为3%,向中国农业总产值的增长率贡献了29.7%。从不同时期来看,中国农业科技创新效率TFP增长呈现出明显的波动性特征,整体呈现“U”型演进轨迹;从区域层面来看,2006-2008年,东、中、西部三大地区的农业科技创新的TFP增长率均实现了正增长,但是存在着显著的区域差异,其中西部地区的增长速度最快,东部地区次之,中部地区最慢。
(4)通过构造农业科技创新水平指数得出,2006-2008年我国农业科技创新整体创新水平较低(0.3999),呈现波动状态。通过构造农业科技创新协调系数指数得出,2006-2008年我国农业科技创新整体协调性较高(0.9348),呈现波动状态,但变化幅度不大,协调性基本趋于一致。通过对农业科技创新水平与协调性进行聚类分析得出,农业科技创新类型呈现高水平高协调型、高水平低协调型、低水平高协调型和低水平低协调型四种类型。大部分省(市)的农业科技创新水平和农业科技创新协调性基本保持一致,农业科技创新水平与协调性两因素呈弱正相关性(Pearson相关系数为0.387)。
Innovation is the resources of essential and motivation of state economy’s increasing, and it is core of national development. Therefore, innovation of agricultural science and technology will become the main motivation of agricultural growth. At present, there are such problems in innovation of agricultural science and technology as independent innovation capability is limited, sci-tech level is not high and agricultural extension is delay. Although the central government has adopted a series of policies to assist agriculture, and increased input to construct the platform for innovation of agricultural science and technology annually, there are still key problems need to be solved during transferring from traditional agriculture to modern agriculture, such as the difference of different regions on innovation level and efficiency of agricultural science and technology, the ability and efficiency coordinating degree of agricultural science and technology. These are also important questions of reality the government at all levels facing to when they make decision. At present, the theory research is blank or weak in these fields.
Therefore, the thesis does research on innovation of agricultural science and technology from ability, efficiency, and the coordinating between ability and efficiency, in order to cover the shortage in relevant research and offer reference for policies’decision making.
On the basis of the review on related theories and documents home and abroad, from the perspective of potential ability,development ability, output ability and contribution ability on innovation of agricultural science and technology, the thesis is firstly to analyze how construct the index system for the ability and evaluate the integrated ability of China as a whole and ability in different regions on innovation of agricultural science and technology by using Factor anlytic method and statistical data. Secondly, it stresses on the evaluation of the efficiency on innovation of agricultural science and technology nationally and regionally, and the analysis on the factors that affect the efficiency. Thirdly, it focuses on the evaluation of the national and regional level on innovation of agricultural science and technology through the statistical data collected from 2006 to 2008 by using special data analysis and constructing the index on the level of innovation of agricultural science and technology. Lastly, it proposes the suggestions on raising the level of innovation of agricultural science and technology in China, according to the summary of the experiences and practices about innovation of agricultural science and technology from America, Israel and Japan.
The thesis has such conclusion as follows:
1. According to the Evaluate Results of Factor Analysis Method, the innovative capacity of agricultural science and technology of every province in China is quite different. The eastern region has the strongest capacity , especially in Beijing and Shanghai, and the capacity of Guangdong, Zhejiang, Shandong, Jiangsu is also significantly higher than the national average level. The capacity in the western regional provinces is lower than the national average level. The innovation capacity of Henan Province in the western region, Heilongjiang Province in the northeastern region, Fujian Province in the south China region and Tianjin in the north China region is slightly higher than the national average level.
2. The conclusion is gotten through Input Output Analysis Method as that from 2006 to 2008, the efficiency of agricultural science and technology innovation of most provinces (cities) located in east central China is at the first-class and second-class level, which is quite high. The correspondence of west China is at the third-class and fourth-class level, which is quite low. After analyzing the Malmquist index of agricultural science and technology innovation, we could get the conclusion that the increasing of the efficiency of agricultural science and technology innovation in China is caused by technology improving, instead of the amelioration of technological efficiency.
3. 1990—2008, the efficiency of agricultural science and technology innovation is in the moderate growing situation in annual growth of 3%, and the growth rate has made a contribution of 29.7% to the growth rate of China’s agricultural output. During the different periods, the growth of China’s agricultural TFP has displayed obvious volatility features, which shows like“U”type track overall. From the aspect of region, the growth of agricultural TFP in the all three regions has achieved positive growth from 2006 to 2008, however, there are significant regional differences, which the growth of western region is the fastest, the eastern region takes second place, followed by the slowest central region.
4. Through the establishment of agricultural science and technology index, we could know that China’s efficiency of agricultural science and technology innovation (2006-2008) was in fluctuation, at a lower level (0.3999). At the same time, the agriculture science and technology innovation coordinate coefficient index was at a higher level (0.9348), in fluctuation with little variation amplitude and keep in coordination. Clustering analysis the agriculture science and technology innovation level and coordination determined the four types of agriculture science and technology innovation i.e. high innovation level and high coordination type, high innovation level and low coordination type, low innovation level and high coordination type, low innovation level and low coordination type. Most of provinces’agriculture science and technology innovation level and agriculture science and technology innovation coordination were in consistent, the innovation level and coordination were in weak correlation (the index of Pearson is 0.387).
引文
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