Has Digital Financial Inclusion Narrowed the Urban–Rural Income Gap? A Study of the Spatial Influence Mechanism Based on Data from China

Abstract

Although extant literature has extensively discussed the poverty reduction effect of digital financial inclusion, few papers have explored the association from a spatial perspective. Based on the Peking University Digital Financial Inclusive Index, this study empirically tests the impact of digital financial inclusion on the urban–rural income gap in China. To perform the analysis, this paper employs the spatial Durbin model (SDM) with double fixed effects and a mediating effect model. We find that (1) there is a significant positive spatial correlation between digital financial inclusion and the urban–rural income gap, and both variables have certain spatial agglomeration characteristics; (2) digital financial inclusion has a significant promotion effect and a positive spatial spillover effect on reducing the urban–rural income gap; and (3) the test of the spatial influence mechanism shows that the above effect is achieved by promoting industrial structure upgrading. This paper combines the above results to propose corresponding policy recommendations, which are valuable for other developing countries and emerging economies with similar backgrounds to China.

Analysis of Income Effects of Agricultural Technology Services on Farm Households

“…The positive regression coefficients indicate that the two factors have a higher promoting effect on income increase for high-income farmers than low-income farmers, further widening the income gap between farmers. In model (6), the regression coefficients of the two variables are positive at the 10%-90% quantiles of the dependent variable, further supporting that they are averse to reducing the income gap between farmers.…”

“…It indicates that the effect of receiving agricultural technical services on promoting income of low-income farmers is greater than that of high-income farmers. Model (6) indicates that at the 1% significance level, the regression coefficient of accepting agricultural technical guidance is negatively significant, with an impact effect of -0.564, further supporting the fact that farmers' acceptance of agricultural technical guidance can narrow the income gap between high-income farmers and low-income farmers.…”

“…Farmers' cooperatives can effectively increase incomes, alleviate poverty in developing countries, and reduce the burden on poor farmers [3][4][5] . Some scholars suggest that digital technology has a greater impact on high-income farm households, widening the income gap 6 . Green agricultural policies can help narrow the gap 7,8 , and democratically governed groups are more cooperative 9 .…”

Driving rural industry revitalization in the digital economy era: Exploring strategies and pathways in China

“…In contrast to the levels of digitization witnessed in secondary and tertiary sectors, the application of digital technologies in agriculture remains relatively limited in terms of quality and depth [ 2 ]. Certain areas with lower levels of development experience slower progress in digital rural development, while remote regions face challenges in establishing a conducive environment for digital infrastructure and Digital financial environment(DFE) [ 3 ]. Additionally, government financial support is inadequate [ 4 ], and there is a scarcity of skilled professionals specializing in basic digital rural expertise [ 5 ].…”

Impact of the Urban-Rural Income Disparity on Carbon Emission Efficiency Based on a Dual Perspective of Consumption Level and Structure

“…Second, scholars do not consider spatial spillover effects as much when studying URID and carbon emissions. Liu et al (2023) confirmed the existence of significant spatial agglomeration characteristics between URID in China [25]. The study by Zhang and Hao (2022) reflects that it is necessary to consider the spatial spillover effect when analyzing the effects of income disparity and economic agglomeration on carbon emissions [22].…”