Who Are Identified as Poor in Rural China’s Targeted Poverty Alleviation Strategy? Applying the Multidimensional Capability Approach

This article examines how poverty identification is operationalized in the Targeted Poverty Alleviation (TPA) strategy in rural China. Using the 2016 “Thousand-Person Hundred-Village” national survey data and multilevel regression analyses, we found that the TPA strategy used a multidimensional approach to identify poor households and register them into the national poverty database. In addition to experiencing income poverty, rural households that suffered deprivations in education, health, employment, living conditions had greater odds of being registered as poor. Households from non-eastern regions as well as those from less urbanized counties were also more likely to be identified as poor. This article uses the Alkire and Foster method to construct a multidimensional poverty measure. We found that using the multidimensional poverty measure achieved better targeting performance of poverty identification than using the income poverty measure only. Households that were registered into the national poverty database—regardless of whether they were income poor, multidimensionally poor, or non-poor—received more public assistance from the government than those who were non-registered poor. These findings provide new insights into rural China’s multidimensional poverty identification practice and suggest implications for China’s future poverty monitoring and alleviation efforts.