自然资源学报 ›› 2021, Vol. 36 ›› Issue (8): 2095-2112.doi: 10.31497/zrzyxb.20210814

• 其他研究论文 • 上一篇    下一篇

中国水禽产业时空演进及影响因素——基于全要素生产率增长视角

李刚(), 刘灵芝()   

  1. 华中农业大学经济管理学院,武汉 430070
  • 收稿日期:2020-01-10 修回日期:2020-03-06 出版日期:2021-08-28 发布日期:2021-10-28
  • 通讯作者: 刘灵芝(1971- ),女,湖北宜昌人,博士,教授,研究方向为农业经济理论与政策。E-mail: liulingzhi@mail.hzau.edu.cn
  • 作者简介:李刚(1990- ),男,贵州盘州人,博士研究生,研究方向为农业经济、环境科学与资源利用。E-mail: ligang520202@163.com
  • 基金资助:
    国家现代农业产业技术体系专项资金项目(CARS-42-28)

Spatio-temporal evolution of waterfowl industry in China and its influencing factors:From the perspective of total factor productivity growth

LI Gang(), LIU Ling-zhi()   

  1. College of Economic and Management, Huazhong Agricultural University, Wuhan 430070, China
  • Received:2020-01-10 Revised:2020-03-06 Online:2021-08-28 Published:2021-10-28

摘要:

水禽产业快速发展离不开技术进步的贡献。准确审视水禽产业全要素生产率的时空演进规律,探讨不同阶段水禽全要素生产率(TFP)的提升策略十分重要。基于中国水禽体系产业经济团队的调研数据和固定观测点数据,结合有关年鉴整理出水禽的投入和产出数据,运用GIS技术分析后得出结论:2010—2018年水禽产业时空演进特征为“东退西进,北向南移”。结合永续盘存法和索洛余值,运用数据包络分析法(DEA-Malmquist)估算全国29个省份水禽TFP指数,比较各地区的TFP增长率和贡献率,进而分析此期间的时空演进规律,结果显示:2014年TFP增长率大幅下跌,2015年又逐渐上升,2016年以后才趋于平稳增长,概括水禽TFP增长率的时空变化规律为先降后升的“U”型走势。运用Tobit模型分析其变动的影响因素,结果表明:受H7N9突发事件影响,水禽产业劳动力投入和资本投入发生了改变,主要影响因素为水电及燃料动力投入、基础设施维护及新增投入、疫苗防疫及医疗投入等,这些因素对水禽TFP增长的时空变动影响显著,进一步说明水禽技术效率有待提升,风险规避机制有待完善。

关键词: 水禽产业, 时空演进, GIS, 全要素生产率, 数据包络分析法, Tobit模型

Abstract:

The rapid development of waterfowl industry is inseparable from technological progress. It is very important to examine the evolution law of total factor productivity (TFP) in waterfowl industry and to explore the promotion strategies of TFP in different stages. Based on the survey data and fixed observation point data of the industrial economic team of China waterfowl system, combined with the input and output data of waterfowl industry sorted out in the relevant yearbooks, the paper uses GIS technology to analyze and draws the conclusion that the spatio-temporal evolution characteristics of waterfowl industry in 2010-2018 are "shift from east to west and from north to south". Combined with the perpetual inventory method and Solow residual value, data envelopment analysis DEA-Malmquist is used to estimate TFP of waterfowl industry in 29 provincial-level areas of China. The growth rate and contribution rate of TFP in each of six regions are compared, and then the spatio-temporal evolution law of this period is analyzed. The results show that the growth rate of TFP fell sharply in 2014, rose gradually in 2015, and then grew steadily after 2016. The spatio-temporal growth rate of TFP of waterfowl indutry is summarized. The curve of change presents a "U"-shaped pattern of first falling and then rising. Tobit model is used to examine the influencing factors of the changes. The results show that, affected by H7N9 emergencies, the labor and capital investment in waterfowl industry has changed. The main influencing factors are hydropower and fuel power investment, infrastructure maintenance and new investment, vaccine and epidemic prevention and medical investment. These factors have significant impact on the spatio-temporal changes in waterfowl TFP growth, which further shows that the technical efficiency of waterfowl industry needs to be enhanced, and the risk aversion mechanism should be improved.

Key words: waterfowl industry, spatio-temporal evolution, GIS, total factor productivity, data envelopment analysis, Tobit model