Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2017, Vol. 53 ›› Issue (6): 1089-1098.DOI: 10.13209/j.0479-8023.2017.128

• Orginal Article • Previous Articles     Next Articles

Spatial-temporal Pattern and Causes for GDP per Capita at County Level in Beijing-Tianjin-Hebei Region

Xiumei TANG1,2,3,4, Yunbing GAO1,2,3,4, Yu LIU1,2,3,4(), Chao SUN1,2,3,4   

  1. 1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097
    2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097
    3. Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097
    4. Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097
  • Received:2016-05-29 Revised:2016-11-10 Online:2017-08-06 Published:2017-11-20

京津冀地区县域人均GDP的空间差异演化及其影响因素

唐秀美1,2,3,4, 郜允兵1,2,3,4, 刘玉1,2,3,4(), 孙超1,2,3,4   

  1. 1. 北京农业信息技术研究中心, 北京 100097
    2. 国家农业信息化工程技术研究中心, 北京 100097
    3. 农业部农业信息技术重点实验室, 北京 100097
    4. 北京市农业物联网工程技术研究中心, 北京 100097
  • 基金资助:
    国家自然科学基金(41201173, 41301093)资助

Abstract:

Taking 171 counties of Beijing-Tiajin-Hebei Region as research units, based on spatial analysis model of GIS and geographic weighted regression model, the spatial-temporal characteristics of GDP per capita and its cause in 1993- 2013 were revealed. Results were as follows. GDP per capita in the Beijing-Tianjin-Hebei Region at county level showed rapid growth trend with expanding difference; GDP per capita at county level showed a significant positive correlation, that is to say, the pattern of high-high concentration and low-low concentration was enhanced. Beijing-Tianjin-Tangshan Region was always the hot economic development zone in Beijing-Tianjin-Hebei Region, the GDP per capita of most counties in Hebei Province was at low level, and cold economic development belt of “Laiyuan County-Gaoyang County-Wuyi County-Zaoqiang Qiu County” was gradually formed. GDP per capita at county level showed spatial pattern of “northeast-southwest”, and the overall trend was enhanced. Wen’an County was the core of GDP per capita gravity, and the centre of economic gravity moved southwest firstly and then northeast, indicating that the economic development function in the northeast of Beijing-Tianjin-Hebei Region further strengthen. Compared with OLS model, the fitting effect of GWR model was improved obviously. The development of GDP per capita in 2013 was mainly promoted by the gross industrial output value per capita, the proportion of value-added of the tertiary industry, the contracted investment actually utilized per capita and urbanization level.

Key words: GDP per capita, standard deviation ellipse, geographic weighted regression, Beijing-Tianjin-Hebei region

摘要:

基于GIS空间分析和地理加权回归模型等方法, 研究1993—2013年京津冀地区县域人均GDP的空间分异特征及其影响因素, 以期为促进县域经济发展的政策制定和路径设计提供依据。得到以下结论。1) 京津冀地区县域人均GDP快速增长, 县域间的差异扩大; 县域人均GDP呈现显著的正向相关性, “高高集聚”和“低低集聚”的趋同性在增强。2) 京津唐地区一直是京津冀地区经济发展的热点区域, 河北省大部分县域的人均GDP处于较低水平, “涞源县-高阳县-武邑县-枣强县-邱县”经济冷点带逐渐形成; 县域人均GDP呈现“东北-西南”的走向分布, 并且整体上呈现强化趋势; 经济发展重心以文安县为核心, 呈现“先西南、后东北”的“V”形变动, 东北方向的经济功能进一步强化。3) 与OLS模型相比, 地理加权回归模型的拟合效果明显改善。人均规模以上工业增加值、第三产业增加值比重、人均实际使用外资金额以及城镇化水平等显著促进了2013年京津冀地区的县域经济发展。

关键词: 人均GDP, 标准差椭圆, 地理加权回归, 京津冀地区