我国粮食生产力的空间差距分解及影响因素分析 —基于单要素生产力视角
作者:
作者单位:

贵州大学 管理学院/中国西部发展能力研究中心;浙江大学 管理学院/中国农村发展研究院,贵州大学 管理学院/中国西部发展能力研究中心,贵州大学 管理学院/ 中国西部发展能力研究中心,浙江大学 管理学院/中国农村发展研究院

中图分类号:

F323.2

基金项目:

国家自然科学基金项目(71673065);贵州省2014年重大应用基础研究项目(黔科合JZ字[2014]200205);贵州大学文科重点特色学科重大项目(GDZT201504)。


Analysis on the decomposition of the spatial disparities and the influencing factors of China’s grain productivity: From the perspective of single factor productivity
Author:
Affiliation:

School of Management/China Center for Western Capacity Development Research,Guizhou University; School of Management/China Academy of Rural Development,Zhejiang University,School of Management/China Center for Western Capacity Development Research,Guizhou University,School of Management/China Center for Western Capacity Development Research,Guizhou University,School of Management/China Academy of Rural Development,Zhejiang University

Fund Project:

National Natural Science Foundation of China (71673065); Major Applied Basic Research Program of Guizhou Province in 2014 (JZ[2014]200205); Major Program of Key Specialty Majors in Social Science of Guizhou University (GDZT201504).

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    摘要:

    能否有效提升单要素生产力是保障我国粮食安全以及提升全要素生产力的基础所在。本文以我国30个省区2003-2015年间粮食单要素生产力为研究对象,通过构建“描述性统计-泰尔指数(Theil Index)分解-空间回归模型”这一实证分析框架,较为全面地比较了粮食单产水平( )和劳动生产率( )两指标之间的关联与差异。结果表明:1)国内研究大都选择 ,而国际学界则更多采用 作为测度指标。研究范式的差异是造成指标选取差异的根源所在,不同测度指标的选取也会深刻影响粮食政策制定与实施的一般性倾向;2)两指标均呈现由东北向西南逐渐降低的空间分布特征,但彼此间并不存在均匀的线性相关关系。两指标经整体与局部空间层面的泰尔指数分解后均呈现较为明显的相异趋势;3)空间回归分析中,农地流转和中间投入品等变量对两指标的影响机制在回归系数的方向、大小和显著性等方面具有较高一致性,但以 为因变量的模型拟合效果显著优于 。精准化与差异化的施策方式为本文的政策启示所在。

    Abstract:

    Improving the single factor productivity efficiently is the basis for China’s grain security and the improvement of the total factor productivity. Based on the data of 30 provincial areas in China from 2000 to 2015, this paper built an empirical framework, “descriptive statistics- decomposition of Theil Index-spatial regression models”, and examined the relationship and differences between the two different indicators, including the grain yield per unit area ( ) and the labor productivity ( ). Results show that: 1) Domestic researchers usually prefer , while foreign researchers often select , as the measuring indicator of agricultural productivity. The difference in selecting indicators originates from different research paradigms. The indicator selection will affect the general tendency profoundly when making and enforcing grain policies; 2) The spatial distribution of the two indicators displays a gradual declining trend from the northeast to the southwest and there is no obvious linear relationship between them. Opposite trends have been shown obvious difference after decomposing the Theil Index of the two indicators; and 3) Spatial regression analysis shows that farmland transfer and intermediate inputs have consistent influences on these two indicators in terms of the direction, magnitude and significance level of the estimated coefficients. However, the models’ goodness of fit performs better when is treated as the dependent variable than when .is treated as the dependent variable. Policy implications of this paper include enforcing and optimizing the current polices in a more targeted and heterogeneous way.

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引用本文

洪名勇,吴昭洋,何玉凤,王珊. 我国粮食生产力的空间差距分解及影响因素分析 —基于单要素生产力视角[J]. 农业现代化研究, 2017, 38(4): 561-570
HONG-Ming-yong, WU Zhao-yang, HE-Yu-feng, WANG Shan. Analysis on the decomposition of the spatial disparities and the influencing factors of China’s grain productivity: From the perspective of single factor productivity[J]. Research of Agricultural Modernization, 2017, 38(4): 561-570

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  • 收稿日期:2017-04-30
  • 最后修改日期:2017-06-18
  • 录用日期:2017-06-19
  • 在线发布日期: 2017-07-31
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