Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2017, Vol. 53 ›› Issue (1): 101-110.DOI: 10.13209/j.0479-8023.2017.001

• Orginal Article • Previous Articles     Next Articles

Spatial-Temporal Pattern and Causes for Agricultural Labor Productivity in Beijing-Tianjin-Hebei Region

Yu LIU1, Yandong ZHENG2, Yangfen CHEN3,()   

  1. 1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097
    2. Consolidation and Rehabilitation Center of Hebei Province, Shijiazhuang 050051
    3. Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2015-08-24 Revised:2015-11-23 Online:2017-01-09 Published:2017-01-20
  • Contact: Yangfen CHEN


刘玉1, 郑艳东2, 陈秧分3,()   

  1. 1. 北京农业信息技术研究中心, 北京 100097
    2. 河北省土地整理服务中心, 石家庄 050051
    3. 中国农业科学院农业经济与发展研究所, 北京 100081
  • 通讯作者: 陈秧分
  • 基金资助:
    国家自然科学基金(41201173, 41471115, 41401193)资助


Taking 171 counties of Beijing-Tianjin-Hebei region as research units, adopting GIS spatial analysis methods, it is revealed that spatial difference of agricultural labor productivity in 1994, 2000, 2006 and 2012. With geographically weighted regression model, the causes for the spatial difference of labor productivity in 2000 and 2012 are revealed. The results indicate that the agricultural labor productivity at county level shows unbalanced development with remarkable special differentiation. The counties in Beijing-Tianjin-Tangshan region possess higher agricultural labor productivity, however, there is a slow increase in labor productivity for the counties in Beijing, obvious decrease in number of agglomeration unit. The agricultural labor productivity of the counties in Shijiazhuang surrounding area sees high-level agglomeration; Agricultural labor productivity of the counties in Zhangjiakou, Chengde, Baoding and Xingtai is situated at a relatively low level. During the research period, agricultural labor productivity has a rapid increase, with no obvious polarization trend. In four research years, agricultural labor productivity at county level shows positive correlation but with weakened agglomerating level, so agricultural labor productivity at county level shows a decentralized sign. Simulation result of geographically weighted regression model is significantly better than ordinary least squares. Parameter estimation results for regression coefficients of controlled variables of 171 countries are different. Driving factors of labor productivity of agricultural work are featured as localization other than unbalanced linkage, and effects of agricultural labor productivity in previous stage are most obvious. Therefore, current status of agricultural labor productivity and driving factor should be combined to optimize agricultural labor productivity in Beijing-Tianjin-Hebei region.

Key words: agricultural labor productivity, spatial-temporal pattern, impact factor, geographically weighted regression, Beijing-Tiajin-Hebei region


以京津冀地区 171 个县域为研究单元, 利用GIS空间分析等方法, 分析1994, 2000, 2006 和 2012 年农业劳动生产率的空间分异特征, 并借助地理加权回归模型揭示2000和2012年县域农业劳动生产率空间分异的影响因素, 得到以下结果。1) 县域农业劳动生产率发展不均衡, 空间分异显著。京津唐地区的农业劳动生产率较高, 但近年来北京所辖区县的农业劳动生产率提升较慢, 高高集聚单元数明显减少; 石家庄市周边出现新的高高集聚类型区; 张家口、承德、保定和邢台所辖多数县域的农业劳动生产率处于较低水平。2) 县域农业劳动生产率快速提升, 并且两极分化趋势不明显; 4 个年份中, 县域农业劳动生产率存在显著的正向相关性, 但空间集聚程度减弱。3) 地理加权回归模型的拟合结果明显优于普通最小二乘法。171个县域各控制变量的参数估计结果和回归系数均不相同, 县域农业劳动生产率的驱动因素呈现非均衡联动的局域性特征, 其中, 上期农业劳动生产率的影响最显著。因此, 应结合县域农业劳动生产率的现状和影响因子的效应, 因地制宜地采取相应措施, 优化和提升区域农业劳动生产率。

关键词: 农业劳动生产率, 时空格局, 影响因素, 地理加权回归, 京津冀地区

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