As a bridge and link connecting urban and rural economies, advancing the economic development of counties has an important impact on promoting the construction and economic transformation and upgrading of China’s new countryside. However, constrained by a variety of factors such as infrastructure, capital, and technology, the foundation of industrial development in counties is weak, the overall economic capacity is low, and there is still a large space for development. As an important integration form of digital information technology and finance, digital inclusive finance(DIF) provides a new idea for promoting county economic development (CED). Nevertheless, current studies on the relationship between digital inclusive finance and county economic development are relatively few in number, the theoretical analysis is not comprehensive enough, and there is a lack of mechanism research from the perspective of labor mobility, which is yet to be combined with the actual development of counties to carry out a more in-depth analysis. Based on the panel data of Chinese counties from 2014 to 2020, this paper constructs a multiple linear regression model and a mediation effect model for empirical testing. The results show that DIF can significantly promote CED in China, and the regression results are still robust after considering the night lighting data as a substitute for the development level of the county economy and endogenous problems. Furthermore, we also find that there are structural differences and regional differences in the impact of DIF on CED. Specifically, compared with the coverage and depth of use, the degree of digitalization of DIF has a more obvious role in promoting county economic development; in the central and western regions as well as in poor counties, digital inclusive finance has a stronger role in promoting CED, reflecting the inclusive characteristics of DIF. The mechanism analysis shows that labor mobility plays a partial intermediary role between DIF and CED. Compared with previous literature, this paper expands on the following two aspects. On one hand, unlike existing studies that mostly take the provincial area as the research object, this paper starts from the county level, theoretically and empirically analyzes the influence of DIF and its sub-dimensions on CED, and further discusses the differential influence based on the heterogeneity of geographical regions. On the other hand, based on the perspective of labor mobility, this paper explores the mechanism of DIF’s effect on CED and expands the previous path research from a brand-new perspective. To a certain extent, our research reveals the important role of the labor force as the most active and dynamic factor in all kinds of production factors in the influence of DFI on CED, which is helpful for government departments to formulate digital inclusive finance development policies and labor mobility guidance measures in combination with the characteristics of county development and implement differentiated policy support for regions with different economic development levels, so as to promote common prosperity and coordinated regional development.