科研管理

科研管理 ›› 2016, Vol. 37 ›› Issue (7): 145-153.

• 论文 • 上一篇    下一篇

中国生物农业全要素生产率增长特征及行业差异

季凯文1,2   

  1. 1 江西财经大学产业经济研究院，江西 南昌330013；
    2 江西省发展改革研究院经济研究所，江西 南昌330046
  • 收稿日期:2014-01-22 修回日期:2015-12-04 出版日期:2016-07-20 发布日期:2016-07-12
  • 通讯作者: 季凯文
  • 基金资助:

    国家自然科学基金项目“基于损失厌恶的的供应链决策行为与管理策略研究”（编号：71261006，起止时间：2013-2016）；江西省社会科学“十二五”规划项目“中国生物农业技术效率测度及其提升路径研究”（编号：15GL35，起止时间：2015-2017）；
    中国博士后科学基金第59批面上资助项目“技术效率、技术进步与中国生物农业发展”（编号：2016M592102，起止时间：2016-2018）

Growth features and industry differences of total factor productivity in China’s bio-agriculture

Ji Kaiwen1,2   

  1. 1. Research Institute of Industrial Economics, Jiangxi Finance and Economics University, Nanchang 330013,Jiangxi, China;
    2. Economics Research Institute, Jiangxi Development and Reform Research Academy, Nanchang 330046,Jiangxi, China
  • Received:2014-01-22 Revised:2015-12-04 Online:2016-07-20 Published:2016-07-12

摘要： 本文以上市公司为样本，采用考虑环境因素的三阶段DEA-Malmquist指数模型，实证分析了中国生物农业全要素生产率的真实增长特征及行业差异。研究发现，宏观经济的快速扩张、政府补贴的增加及过于集中的股权结构，不利于全要素生产率的提升；剔除环境变量和随机误差的影响后，全要素生产率增长更为显著且主要由技术效率推动，技术水平呈现退步趋势；全要素生产率增长的样本差异分化明显，各子行业发展相对均衡，而子行业内部良莠不齐。为此，政府应优化外部环境、促进技术创新、强化分类指导，以便更为有效地提升生物农业全要素生产率。

关键词: 生物农业, 全要素生产率, 三阶段DEA模型, Malmquist指数

Abstract: Taking listed companies as sample and using three stage DEA-Malmquist index model which considers environmental factors, this paper makes empirical analysis on the real growth features and industry differences of total factor productivity in China’s bio-agriculture. The results show that rapid expansion of macro economy, increase of government subsidies and excessive concentration of ownership structure, are not conducive to improve total factor productivity; growth of total factor productivity is more significant which driven mainly by technical efficiency and technical level is backward after eliminating influence of environmental variables and random errors; sample differences of total factor productivity growth is obvious, development of various sub-sectors is relatively balanced, but development of internal sub-sector is uneven. Therefore, government should optimize external environment, promote technological innovation, and strengthen classification guidance in order to improve total factor productivity of bio-agriculture more effectively.

Key words: bio-agriculture, total factor productivity, three stage DEA model, Malmquist index