云南省农业科技创新资源配置效率及影响因素研究
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摘要
[目的]为及时了解云南省农业科技创新的最新动态,充分合理地开发云南省农业科技资源,文章对2002—2016年云南省的农业科技创新资源配置进行研究。[方法]首先分析各个单项指标15年内的变化趋势,分析其对资源配置的影响和作用。再运用DEA模型分析法,将2002—2016年的每个年份作为一个决策单元进行处理,对云南省农业科技创新资源配置效率进行分析。[结果] 2002—2016年云南省农业科技创新资源配置的综合效率为0. 984,并且呈现出不稳定的波动,在2004和2009—2012年出现了配置效率降低的情况。总体来看,资源配置的综合效率大体上是接近于1的水平。处于DEA有效的年份为2002—2003年,2005—2008及2013—2016,属于规模报酬不变的阶段; 2004年属于弱DEA有效阶段,规模报酬则处于上升阶段;处于非DEA有效的有2004年、2009—2012年。[结论]云南省农业科技创新资源的配置效率整体水平处于较高的状态,综合效率值总体上接近于1。有个别年份出现了较小范围的波动,可能与总播种面积的变化有关。综合来看,云南省农业科技创新资源在技术投入、人力资源和农业资金投入逐年的增加,使资源配置效率能够保持在较高的水平,并在出现下降后迅速恢复。
In order to keep abreast of the latest trends of agricultural science and technology innovation in Yunnan province and fully and rationally develop agricultural science and technology resources in Yunnan province,this paper makes a study on the allocation of agricultural science and technology innovation resources in Yunnan province from 2002 to 2016. Firstly,the trend of each single index within 15 years was analyzed,and its influence and effect on resource allocation were analyzed. Then DEA model analysis was used to treat each year from 2002 to2016 as a decision unit to analyze the allocation efficiency of agricultural scientific and technological innovation resources. The results showed that the average comprehensive efficiency of agricultural scientific and technological innovation resources in Yunnan province from 2002 to 2016 was 0. 984,and showed unstable fluctuations. The allocation efficiency decreased in 2004 and from 2009 to 2012. The overall efficiency of resource allocation was almost 1. The DEA effective years were 2002-2003,2005-2008 and 2013-2016,which belonged to the stage of constant return on scale. The year 2004 belonged to the effective stage of weak DEA,while the return to scale was in the rising stage. The DEA ineffective years were 2004 and from 2009 to 2012. The overall allocation efficiency of agricultural scientific and technological innovation resources in Yunnan province is in a high state,and the overall comprehensive efficiency value is close to 1. A small range of fluctuations occurred in a few years,which may be related to the change of the total sown area. To sum up,Yunnan' s agricultural scientific and technological innovation resources have been increasing year by year in terms of technology input,human resources and agricultural capital input,so that the efficiency of resource allocation can be maintained at a high level and quickly recover after a decline.
In order to keep abreast of the latest trends of agricultural science and technology innovation in Yunnan province and fully and rationally develop agricultural science and technology resources in Yunnan province,this paper makes a study on the allocation of agricultural science and technology innovation resources in Yunnan province from 2002 to 2016. Firstly,the trend of each single index within 15 years was analyzed,and its influence and effect on resource allocation were analyzed. Then DEA model analysis was used to treat each year from 2002 to2016 as a decision unit to analyze the allocation efficiency of agricultural scientific and technological innovation resources. The results showed that the average comprehensive efficiency of agricultural scientific and technological innovation resources in Yunnan province from 2002 to 2016 was 0. 984,and showed unstable fluctuations. The allocation efficiency decreased in 2004 and from 2009 to 2012. The overall efficiency of resource allocation was almost 1. The DEA effective years were 2002-2003,2005-2008 and 2013-2016,which belonged to the stage of constant return on scale. The year 2004 belonged to the effective stage of weak DEA,while the return to scale was in the rising stage. The DEA ineffective years were 2004 and from 2009 to 2012. The overall allocation efficiency of agricultural scientific and technological innovation resources in Yunnan province is in a high state,and the overall comprehensive efficiency value is close to 1. A small range of fluctuations occurred in a few years,which may be related to the change of the total sown area. To sum up,Yunnan' s agricultural scientific and technological innovation resources have been increasing year by year in terms of technology input,human resources and agricultural capital input,so that the efficiency of resource allocation can be maintained at a high level and quickly recover after a decline.
引文
[1]常文涛.农业科技创新资金与科技人力资本支农绩效实证分析.统计与决策,2018(21):113-116.
[2]黄红星,刘晓珂,万忠.科技引领广东农业供给侧结构性改革的思路和方向.江西农业学报,2018(11):147-150.
[3]陈建伟.我国农业科技创新效率研究.河北农业大学,2010.
[4]赵连明.重庆市农业科技创新资源配置效率及影响因素研究.中国农业资源与区划,2018,39(7):92-98.
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[6]何鸿辉.基于阶段DEA模型的甘肃农业生产效率研究.兰州财经大学,2018.
[7]董明涛.我国农业科技创新资源的配置效率及影响因素研究.华东经济管理,2014,28(2):53-58.
[8]张德刚,刘艳红,王丹,等.云南绿春哈尼梯田不同土地利用方式下土壤养分特征.广东农业科学,2010,37(7):81-83.
[9]陈文华,甘淑.云南山地坝区土地利用变化及其驱动分析——以保山坝子为例.云南地理环境研究,2009,21(6):34-39.
[10]童绍玉,鲁永新,杨新平,等.云南省耕地垂直变化规律及其驱动力分析.云南财经大学学报(社会科学版),2010,25(6):87-92.
[11]周跃,丁文荣,曾和平,等.云南纵向岭谷区土地利用对土壤侵蚀的影响——以黑惠江、龙川江、盘龙河流域为例.昆明理工大学学报(理工版),2009,34(04):68-72.
[12]段梦,黄德林.基于CGE模型的农业转移人口市民化对农业经济的影响研究.中国农业资源与区划,2018(9):224-230.
[13]孙悦.乡村振兴战略下的农村土地闲置问题研究.南方农机,2018(21):77-82.
[2]黄红星,刘晓珂,万忠.科技引领广东农业供给侧结构性改革的思路和方向.江西农业学报,2018(11):147-150.
[3]陈建伟.我国农业科技创新效率研究.河北农业大学,2010.
[4]赵连明.重庆市农业科技创新资源配置效率及影响因素研究.中国农业资源与区划,2018,39(7):92-98.
[5]肖碧云.基于DEA模型的我国农业科技创新资源配置效率研究.吉林农业科技学院学报,2016,25(4):62-65.
[6]何鸿辉.基于阶段DEA模型的甘肃农业生产效率研究.兰州财经大学,2018.
[7]董明涛.我国农业科技创新资源的配置效率及影响因素研究.华东经济管理,2014,28(2):53-58.
[8]张德刚,刘艳红,王丹,等.云南绿春哈尼梯田不同土地利用方式下土壤养分特征.广东农业科学,2010,37(7):81-83.
[9]陈文华,甘淑.云南山地坝区土地利用变化及其驱动分析——以保山坝子为例.云南地理环境研究,2009,21(6):34-39.
[10]童绍玉,鲁永新,杨新平,等.云南省耕地垂直变化规律及其驱动力分析.云南财经大学学报(社会科学版),2010,25(6):87-92.
[11]周跃,丁文荣,曾和平,等.云南纵向岭谷区土地利用对土壤侵蚀的影响——以黑惠江、龙川江、盘龙河流域为例.昆明理工大学学报(理工版),2009,34(04):68-72.
[12]段梦,黄德林.基于CGE模型的农业转移人口市民化对农业经济的影响研究.中国农业资源与区划,2018(9):224-230.
[13]孙悦.乡村振兴战略下的农村土地闲置问题研究.南方农机,2018(21):77-82.