Purpose: This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.Design/methodology/approach: This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.Findings: (i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.Research limitations/implications: Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.Originality/value: This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

This study presents nonlinear evidence of the effects of a microcredit program implemented in poverty-stricken villages in China on rural public health using multivariate-ordered Probit and IV-ordered Probit models. The results, which were based on a unique set of data gathered from two rounds of official tracking statistics obtained through investigation (2015 and 2018) at a household level, suggest that rural residents’ health levels and health insurance demands are related to the formal credit amount that they receive from the microcredit program. Further, the amount of debt that remains to be paid is a negative mediator and the poverty reduction degree is a positive mediator for the health impact of credit. After dividing the sample into subgroups according to income, credit rating and social network, the results show heterogeneity: the health outcomes of groups with a low income, a high credit rating and a strong social network are more significantly improved by loans. The estimations are still robust after using network and village clan numbers as instrumental variables to address endogeneity. Although most of the existing literature demonstrates that credit and indebtedness have negative impacts on health, our results supplement previous findings of the positive causality between access to formal credit and rural public health by showing that the former can exert positive effects by relaxing individuals’ external constraints and increasing health spending.

After eliminating absolute poverty, China’s anti-poverty efforts have shifted towards multidimensional relative poverty. This study uses microdata from the Chinese Academy of Agricultural Sciences (CAAS) from 2012 to 2021, applies the Kakwani index to construct a multidimensional relative poverty indicator, and uses an endogenous transformation model to analyze the impact of land transfer on multidimensional relative poverty in rural areas. The study found that (1) land transfer can effectively reduce the multidimensional relative poverty of farm households. (2) Land transfer has a better mitigating effect on young farmers, farmers with higher literacy levels, and farmers who have not acute poverty. (3) Land transfer alleviates multidimensional relative poverty by increasing agricultural mechanization, business income, off-farm employment, and wage income. (4) The effects of land transfer out and land transfer in on the dimensions of multidimensional relative poverty are heterogeneous.

The deep integration of digital technologies with agricultural production is reshaping how rural land is used and offers new opportunities for narrowing the urban–rural gap in land use efficiency. Building on theoretical analysis, this study uses panel data for 700 Chinese counties from 2010 to 2024, treats the Digital Agriculture Innovation and Application Base pilot program as a quasi-natural experiment, and applies a double machine learning model to examine the effect of smart agriculture construction on the urban–rural gap in land use efficiency. The results show the following: (1) Smart agriculture construction significantly narrows the urban–rural gap in land use efficiency, with channel evidence pointing to agricultural technological progress, improved capital allocation, and agricultural industrial upgrading. (2) The policy effect is statistically significant only in formerly poverty-stricken counties, counties with higher land-transfer rates, and counties with stronger digital foundations, while Fisher permutation tests do not establish statistically significant cross-group differences. (3) Decomposition results show that the program raises rural land use efficiency and the rural marginal returns to capital and labor while leaving the corresponding urban indicators statistically unchanged, so the observed convergence is driven primarily by rural catch-up rather than urban decline. From a factor allocation perspective, this study clarifies how smart agriculture construction can rebalance urban–rural land resource use while identifying the statistical limits of the heterogeneity and channel evidence.