Deeper Effects of fiscal multidimensional poverty reduction: household characteristics, financial lags and elite capture.

Abstract

The governance of multidimensional relative poverty is a key challenge in rural poverty alleviation in the new era, as well as an important practice of the implementation of the United Nations Sustainable Development Goals in China. Based on provincial fiscal and financial data as well as data from the China Family Panel Studies (CFPS), this article employs multilevel linear regression and structural equation modeling to empirically examine the impact and mechanisms of fiscal investment in agriculture on multidimensional relative poverty among farmers. The research results indicate that fiscal investment in agriculture can effectively alleviate multidimensional relative poverty among rural households, and this conclusion still holds after the robustness and endogeneity tests of traditional measurement and Double Machine Learning. However, differences in household characteristics affect the performance of fiscal poverty alleviation. Households in the central and western regions, with larger family sizes, younger members, and lower levels of education, exhibit higher policy responsiveness. In terms of mechanisms, digital inclusive finance and social capital serve as important channels for fiscal multidimensional poverty reduction. However, attention should be paid to the positive lag effect of digital inclusive finance and the risk of "elite capture" in households with low levels of social capital. Accordingly, the article recommends that fiscal spending should be increased and made more efficient, with precise policy measures, strengthened institutional coordination, and efforts to cultivate optimal levels of social capital. While the article is limited by data availability to allow for a more in-depth and complex discussion, it still provides insights for fiscal strategies aimed at building high-quality shared prosperity.