The Dynamic Impact of Agricultural Fiscal Expenditures and Gross Agricultural Output on Poverty Reduction: A VAR Model Analysis

China was the first developing country to achieve the poverty eradication target of the 2030 Agenda for Sustainable Development Goals (SDG) 10 years ahead of schedule. Its past approach has been, mainly, to allocate more fiscal spending to rural areas, while strengthening accountability for poverty alleviation. However, some literature suggests that poor rural areas still lack the endogenous dynamics for sustainable growth. Using a vector autoregression (VAR) model, based on data from 1990 to 2019, we find that fiscal spending plays a much more significant role in reducing the poverty ratio than agricultural development. When poverty alleviation is treated as an administrative task, each poor village must complete the spending of top-down poverty alleviation funds within a time frame that is usually shorter than that required for successful specialty agriculture. As a result, the greater the pressure of poverty eradication and the more funds allocated, the more poverty alleviation projects become an anchor for accountability, and the more local governments’ consideration of industry cycles and input–output analysis give way to formalism, homogeneity, and even complicity. We suggest using the leverage of fiscal funds to direct more resources to productive uses, thus guiding future rural revitalization in a more sustainable direction.