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作 者:段丁允 冯宗宪[1,2] DUAN Dingyun;FENG Zongxian(School of Economics and Finance,Xi’an Jiaotong University,Xi’an 710061,China;XJTU Institute of“The Belt and The Road”Pilot Free Trade Zone,Xi’an 710049,China)
机构地区:[1]西安交通大学经济与金融学院,陕西西安710061 [2]西安交通大学“一带一路”自由贸易试验区研究院,陕西西安710049
出 处:《西安交通大学学报(社会科学版)》2023年第3期44-60,共17页Journal of Xi'an Jiaotong University:Social Sciences
基 金:国家社会科学基金重点资助项目(19AJY001).
摘 要:从数字贸易的特征出发,通过构建数字贸易发展水平综合评价指标体系,采用面板数据熵值法测度中国十大城市群127座城市2011—2019年的数字贸易发展水平,运用Dagum基尼系数、核密度估计等方法分析其动态演进和区域差异。结果表明:(1)中国十大城市群2011—2019年数字贸易水平不断提升,数字贸易发展较好的城市群是京津冀、珠三角和长三角城市群,以北京市、深圳市、广州市、上海市、杭州市五座城市为引领。(2)十大城市群数字贸易发展差异较大,不同城市群之间的差异是中国数字贸易发展差异的主要来源。(3)十大城市群数字贸易发展水平存在一定的梯度效应和多极化现象;各城市群数字贸易发展水平稳定,改变类型的概率相对较低。(4)总体、成渝、海峡西岸、京津冀、辽中南、山东半岛、长三角、珠三角城市群存在收敛过程。基于此,对城市、城市群内部和城市群之间不同层面的数字贸易发展提出明确定位、优化布局等政策建议。In recent years,the development of digital technology has brought impact and changes to traditional production and trade methods.Digital trade has become a key force in changing the global competitive landscape.As the digital transformation continues,the digitization of cities has also begun,with far-reaching effects on the development of urban agglomerations.However,few studies analyze the current situation of digital trade development and its differences at the level of cities and city clusters,especially on the dynamic evolution of digital trade development differences and distribution in city clusters.This paper,from the characteristics of digital trade,takes cities and urban agglomerations as objects,constructs a city-level digital trade development indicator system based on panel data of 127 cities in ten major urban agglomerations from 2011-2019.We add quantitative data of digital trade policies to it,adopt the entropy value method to measure digital trade development.We also adopt the Dagum Gini coefficient,the Kernel density estimation,Markov chain method analysis as well asσconvergence andβconvergence methods to analyze and examine the dynamic evolution of regional disparities and distribution of the current status of digital trade development.We find that the level of digital trade in China’s ten major city clusters from 2011-2019 has been increasing,and the city clusters with better digital trade development are Beijing-Tianjin-Hebei,Pearl River Delta and Yangtze River Delta city clusters,led by the five cities of Beijing,Shenzhen,Guangzhou,Shanghai and Hangzhou.There are large differences in digital trade development among the ten major city clusters.There is a certain gradient effect and multipolarity in the level of digital trade development in the ten major urban agglomerations,with each urban agglomeration having a stable level of digital trade development and a relatively low probability of changing type.There are significant spatial absoluteβ-convergence and conditionalβ-convergence proce
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