Analyzing the Impact of Digital Finance on Farm Household Income in the Agricultural Sector: Mechanisms and Challenges

Abstract

This paper explores the dynamic interplay between digital finance and farm household income within the agricultural sector, utilizing the income elasticity of demand theory from bioeconomics to understand shifts in human needs and market models. We construct a theoretical framework to assess how digital finance tools are applied in bio-agriculture, focusing on their mechanisms in expanding market access, altering financing modes, and broadening coverage for agricultural households. Our analysis delves into the correlation between digital finance and farm incomes, exploring the threshold effects that delineate significant changes. We employ a comprehensive panel regression analysis using a mixed OLS model, along with random and fixed effects models, to quantify the impacts of digital finance on both agricultural and non-agricultural income among farmers. Our findings reveal substantial disparities: the mean non-agricultural income of farmers stands at 7,682.97 with a standard deviation of 5,054.09, whereas their agricultural income averages at 4,358.77 with a standard deviation of 1,667. Additionally, we document a pronounced growth in non-agricultural income, which has increased by approximately 9,000 yuan per capita over nine years, correlating with improvements in the total digital finance index. This growth suggests a homogenous promotion effect between digital finance and non-agricultural income. The insights garnered from this study offer valuable implications for policies aimed at fostering rural revitalization in conjunction with the expansion of digital finance, underscoring the critical role of digital technologies in enhancing the economic well-being of the agricultural sector.