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干旱区地理 ›› 2020, Vol. 43 ›› Issue (5): 1358-1370.doi: 10.12118/j.issn.1000-6060.2020.05.21

• • 上一篇    下一篇

“一带一路”沿线国家开放度时空格局及其影响因素

马 卫 1,2,3,4, 黄晓燕 2,3,4, 曹小曙 2,3,4   

  1. 1 陕西师范大学地理科学与旅游学院,陕西 西安 710119;2 陕西师范大学自然资源与国土空间研究院, 陕西 西安 710119;3 陕西师范大学西北城镇化与国土环境空间模拟重点实验室,陕西 西安 710119; 4 陕西师范大学全球区域与城市研究院,陕西 西安 710119
  • 收稿日期:2019-10-12 修回日期:2020-04-22 出版日期:2020-09-25 发布日期:2020-09-25
  • 通讯作者: 曹小曙(1970-),男,甘肃灵台人,博士,教授,博士生导师,研究方向为地理与规划.
  • 作者简介:马卫(1988-),男,江苏泰州人,博士研究生,研究方向为交通地理与区域发展.E-mail:mawei15194@163.com
  • 基金资助:
    国家自然科学基金重点项目(41831284)

Spatio-temporal pattern of openness of countries along the Belt and Road Initiative and its influencing factors

MA Wei1, 2, 3, 4, HUANG Xiao-yan2, 3, 4, CAO Xiao-shu2, 3, 4   

  1. 1 School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, Shaanxi, China; 2 Academy of Natural Resources and Territorial Space, Shaanxi Normal University, Xi’an 710119, Shaanxi, China; 3 Key Laboratory for Urbanization and Land Environment Geosimulation in Northwest China, Shaanxi Normal University, Xi’an 710119, Shaanxi, China; 4 Institute of Global Regional and Urban Studies, Shaanxi Normal University, Xi’an 710119, Shaanxi, China
  • Received:2019-10-12 Revised:2020-04-22 Online:2020-09-25 Published:2020-09-25

摘要: “一带一路”开启了中国对外开放新格局,并对沿线国家及全世界的共同发展和繁荣会产 生重大影响。基于 2000—2015 年“一带一路”沿线 66 个国家的面板数据,构建开放度综合评价指 标体系,采用核密度估计、标准差椭圆、探索性空间数据分析及动态空间杜宾模型,分析了“一带一 路”沿线国家开放度时空格局及其影响因素。结果发现:(1)2000—2015 年“一带一路”沿线开放度 水平总体呈上升趋势,且差异逐渐缩小。(2)开放度的重心在移动方位上分为两个阶段:2000— 2008 年重心向西北方向移动,而 2008 年之后重心逐渐向偏东方向移动。(3)开放度存在明显的空间 差异,西北部开放度较高,而中部和南部开放度相对较低。(4)开放度在全局上存在显著的空间自 相关性。热点区集中于新加坡和塞浦路斯 2 国,冷点区主要集中在中国、中亚和南亚。(5)动态空间 杜宾模型(DSDM)分析表明,经济发展水平、人力资本、陆路交通和港口对开放度均存在长短期效 应以及直接、间接效应。

关键词: 开放度, 时空格局, 动态空间杜宾模型, “一带一路”

Abstract: The Belt and Road Initiative (BRI) has marked a new pattern for China’s all-round opening-up, and it will have significant impacts on the common development and prosperity of countries along the BRI. Based on the panel data of 66 countries from 2000 to 2015, this paper develops a comprehensive evaluation index system of openness in order to examine its spatio-temporal pattern of openness and influencing factors, which integrated the approaches of Kernel Density Estimation (KDE), Standard Deviation Ellipse (SDE), Exploratory Spatial Data Analysis (ESDA) and Dynamic Spatial Durbin Model (DSDM). The empirical results show: (1) Openness presents a rising trend year by year, and the difference gradually narrows. (2) The center of gravity of openness is divided into two stages in moving direction: from 2000 to 2008, the center of gravity moves to the northwest, while after 2008, the center of gravity gradually moves to the east. (3) There were obvious spatial differences in openness, with the northwest regions having a high degree of openness than the central and southern regions relatively. (4) In global agglomeration, openness had a positive spatial autocorrelation. In local agglomeration, hot spots were concentrated in Singapore and Cyprus, while cold spots were mainly in China, Central Asia and South Asia. (5) DSDM analysis shows that level of economic development, human capital, land transport and port had strong positive direct effects and indirect effects on openness, both in short-term and long-term.

Key words: openness, spatio-temporal pattern, DSDM, the Belt and Road Initiative (BRI)