本文基于2011~2021年全国337个城市的面板数据及北京大学数字普惠金融指数,运用Dagum基尼系数及其分解法研究全国及各重大战略区域数字普惠金融水平的差异情况,同时通过变异系数和空间计量模型开展σ收敛和β收敛分析,为我国及各重大战...本文基于2011~2021年全国337个城市的面板数据及北京大学数字普惠金融指数,运用Dagum基尼系数及其分解法研究全国及各重大战略区域数字普惠金融水平的差异情况,同时通过变异系数和空间计量模型开展σ收敛和β收敛分析,为我国及各重大战略区域数字普惠金融的发展提供量化支撑,对促进我国数字普惠金融水平整体提升和区域经济协调发展具有政策启示。研究发现:全国数字普惠金融水平显著上升,总体上表现为“东强西弱,北高南低”的空间格局;各重大战略区域数字普惠金融发展差异较为明显,南北方区域间差异是总体区域差异的主要来源;全国及各区域数字普惠金融发展均存在σ收敛、绝对β收敛和条件β收敛,在条件β收敛分析中,区域内经济水平、传统金融发展水平、人口密度、产业结构对各区域数字普惠金融水平增长率有显著的异质性影响。Based on the panel data of 337 cities in China from 2011~2021 and the digital inclusive finance index of Peking University, this paper uses Dagum Gini coefficient and its decomposition method to study the differences in the level of digital inclusive finance across the country and in major strategic regions. At the same time, it carries out σ convergence and β convergence analysis through variation coefficient and spatial econometric model, providing quantitative support for the development of digital inclusive finance in China and in major strategic regions, and has policy implications for promoting the overall improvement of digital inclusive finance in China and the coordinated development of regional economy. Research has found that the level of digital inclusive finance in China has significantly increased, generally manifested as a spatial pattern of “strong in the east and weak in the west, high in the north and low in the south”;there are significant differences in the development of digital inclusive finance among major strategic r展开更多
文摘本文基于2011~2021年全国337个城市的面板数据及北京大学数字普惠金融指数,运用Dagum基尼系数及其分解法研究全国及各重大战略区域数字普惠金融水平的差异情况,同时通过变异系数和空间计量模型开展σ收敛和β收敛分析,为我国及各重大战略区域数字普惠金融的发展提供量化支撑,对促进我国数字普惠金融水平整体提升和区域经济协调发展具有政策启示。研究发现:全国数字普惠金融水平显著上升,总体上表现为“东强西弱,北高南低”的空间格局;各重大战略区域数字普惠金融发展差异较为明显,南北方区域间差异是总体区域差异的主要来源;全国及各区域数字普惠金融发展均存在σ收敛、绝对β收敛和条件β收敛,在条件β收敛分析中,区域内经济水平、传统金融发展水平、人口密度、产业结构对各区域数字普惠金融水平增长率有显著的异质性影响。Based on the panel data of 337 cities in China from 2011~2021 and the digital inclusive finance index of Peking University, this paper uses Dagum Gini coefficient and its decomposition method to study the differences in the level of digital inclusive finance across the country and in major strategic regions. At the same time, it carries out σ convergence and β convergence analysis through variation coefficient and spatial econometric model, providing quantitative support for the development of digital inclusive finance in China and in major strategic regions, and has policy implications for promoting the overall improvement of digital inclusive finance in China and the coordinated development of regional economy. Research has found that the level of digital inclusive finance in China has significantly increased, generally manifested as a spatial pattern of “strong in the east and weak in the west, high in the north and low in the south”;there are significant differences in the development of digital inclusive finance among major strategic r
