Analysis of the Spatial Correlation and Influencing Factors for Inclusive Financeof Chinese Countryside——Based on 2015 “Investigation of Thousands of Villages” by SUFE

Abstract

Abstract:

Base on the micro data of 2015 “Investigation of Thousands of Villages” conducted by Shanghai University of Finance and Economics, this paper uses the information comentropy method to measure the development of inclusive finance in Chinese countryside and applies the spatial econometric models to examines the spatial correlations among villages and the influencing factors. The results indicate that the development of the inclusive finance in the countryside of China is far from satisfacory. Comparatively speaking, the development of the inclusive fincance is better in eastern area s than in western areas, and it's the worst in central areas. There are obvious spatial correlations in the development of inclusive finance in the countryside, which are most conspicuous in the geographical matrix. There are more HH villages in eastern areas, and more LL villages in central areas. The spatial lag model is the best model to analyze the influencing factors of inclusive finance. Economical development level, democracy at the grassroots level, science & technology,and express shops all have an effect on the development of inclusive finance in Chinese countryside.

Key words: inclusive finance, spatial correlation, influencing factors

摘要：

基于上海财经大学2015年“千村调查”的微观数据,运用信息熵法衡量我国农村地区普惠金融发展程度,并运用空间计量模型验证普惠金融在村庄之间的空间传染效应,以空间的视角分析影响普惠金融发展的因素。研究发现:我国农村普惠金融的发展普遍偏低,东部相对较好,中部最差;农村普惠金融发展存在明显的空间传染效应,地理矩阵下的空间传染效应尤其突出;东部地区显著的HH型村庄较多,中部地区显著的LL型村庄较多;空间滞后模型是分析地理矩阵空间特征下普惠金融影响因素的最佳模型,经济发展水平、基层民主、科学技术和快递点均影响我国农村地区的普惠金融发展。

关键词: 普惠金融, 空间相关性, 影响因素

CLC Number:

F830

FANG Lei, SU Fang. Analysis of the Spatial Correlation and Influencing Factors for Inclusive Financeof Chinese Countryside——Based on 2015 “Investigation of Thousands of Villages” by SUFE[J]. , 2017, 33(1): 39-48.

方蕾, 粟芳. 我国农村普惠金融的空间相关特征和影响因素分析——基于上海财经大学2015“千村调查”[J]. 财经论丛, 2017, 33(1): 39-48.

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