The COVID−19 pandemic has significantly impacted the economy and livelihoods of people worldwide. To analyze the impact of the pandemic on material conditions, income levels, health conditions, industrial development and employment opportunities of farmers in China’s rural areas, especially poor areas and explore whether farmers can achieve stable poverty eradication during the COVID−19 pandemic, we interviewed 2662 farm households in poverty−stricken areas of China and used the multidimensional poverty measurement model, three−step feasible generalized least squares and propensity score matching to analyze data. We achieved the following results. First, the overall level of multidimensional poverty vulnerability index (MPVI) of the surveyed households was low and the MPVI of each dimension varied significantly. The MPVI of households in the treated group was higher than that of the control group. Second, COVID−19 increased farm households’ vulnerability to multidimensional poverty in poverty−stricken regions; MPVI increased by 27.9%. Third, COVID−19′s impact on various dimensions differed: the greatest impact was on the vulnerability to health deprivation, followed by industrial development, employment and income deprivation. However, the pandemic slightly reduced the vulnerability to material deprivation. Finally, we proposed various measures in response to the impact of the pandemic to assist farm households in poverty−stricken areas.
Industrial poverty alleviation is one of the most important aspects of targeted poverty alleviation. Identifying the mechanism influencing the spatial differentiation of the benefits of industrial poverty alleviation plays an essential role in optimising an industrial layout for poverty alleviation, consolidating poverty alleviation achievements, and revitalising rural industries. This study examined the spatial distribution characteristics and influencing factors of the benefits of industrial poverty alleviation at the village level using the household data collected from Jiangjin District, Chongqing, China. The results show that the benefits of industrial poverty alleviation presented obvious spatial differentiation in the villages with the overall performance being high in the north and low in the south and decreasing from the south of the county to the north and south. Spatially, there was a significant positively correlated agglomeration effect. High‐value agglomeration areas were concentrated in the north with the characteristics of ‘one centre and two subcentres’. However, low‐value and outlier agglomeration effects were not obvious, presenting sporadic distribution. Seven major factors affect industrial poverty alleviation in Jiangjin District, including average altitude and land transfer rate. The interaction between any two of the seven factors has a more significant impact than that of a single factor.
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