Research On The Evolution Trend And Dynamic Convergence Of Urban Digital Inclusive Finance In China

In recent years,the Chinese government has attached great importance to digital construction and vigorously developed digital inclusive finance.However,most regions in China are still plagued by financial exclusion,leading to severe limitations in the development of digital inclusion.Therefore,studying the evolutionary trend of digital inclusive finance development in Chinese cities and its quantile dynamic convergence characteristics can not only provide a basis for the construction of a new development pattern of regional synergistic development and dual cycle of digital inclusive finance in Chinese cities,but also provide a reference for policy makers to timely adjust the development strategy of digital inclusive finance that effectively serves the real economy.This article is generally divided into five parts.In the first part,the theme and significance of the article are introduced by analyzing the current development background of digital inclusive finance.In the second part,the research results of scholars on digital inclusive finance are systematically sorted out to lay the foundation for this research.In the third part,based on the identification of the connotation of digital inclusive finance,the digital inclusive finance development indicators used in this paper are determined and fitted using the nonparametric kernel density estimation method to reveal the evolutionary trend of digital inclusive finance in China’s cities by analyzing the distribution dynamics of the development of digital inclusive finance and its sub-dimensions in each region.In the fourth part,by summarizing and generalizing the theoretical basis of convergence research,the idea of quantile is incorporated in the convergence theory to determine the corresponding dynamic q-σ convergence and dynamic q-β convergence models.Further,based on the panel data of 327 prefecture-level cities from 2011-2019,the dynamic q-σ convergence and dynamic q-β convergence characteristics of the urban digital financial inclusion index at different quartiles are analyzed.In the fifth section,the empirical findings of this paper are summarized and relevant policy recommendations are proposed.The findings of this paper are as follows.First,the development of urban digital inclusive finance and its sub-dimensions tends to rise significantly,and the absolute difference decreases,but there is a trend of slight expansion in the later stages.Second,the development of urban digital inclusive finance and its sub-dimensions show significant dynamic q-σ convergence,where the q-σ convergence coefficients show a “U” curve pattern from the low to the high quantile in the same year,i.e.,the dynamic q-σconvergence trend is significantly stronger in the middle quantile than in the low and high quantile.Third,the development of urban digital inclusive finance and its sub-dimensions show significant dynamic absolute q-β convergence and dynamic conditional q-βconvergence,and dynamic conditional q-β convergence has a stronger convergence effect compared to dynamic absolute q-β convergence.Fourth,the digital financial inclusion index,digital financial coverage breadth index and digital financial usage depth index have convergence heterogeneity at different quantile levels,and the dynamic absolute q-βconvergence and dynamic conditional q-β convergence characteristics are significantly stronger at the high quantile than at the low quantile.The main innovations of this paper include the first study of the dynamic convergence of total and sub-indicators of digital inclusive finance,and the incorporation of the idea of quantile in the econometric model to explore the heterogeneity of this convergence trend at different levels of development,rather than the homogeneity of previous studies.Second,the mean-based σ convergence model is extended,and a new class of q-σ convergence models is constructed to test the dynamic q-σ convergence characteristics of the digital financial inclusion index at different quartiles,taking into account the distribution differences and time-varying nature of convergence comprehensively.Third,a newly proposed panel time-varying quantile regression model with a factor structure is applied as a way to test the dynamic q-β convergence characteristics of urban digital financial inclusion at different quantile levels.The model describes the differences in shocks of common factors to different individuals by including a high-dimensional interaction term in the form of the product of time and individual effects,which effectively reduces the model setting misbias and omitted variable errors.