Rural Poverty Identification and Comprehensive Poverty Assessment Based on Quality-of-Life: The Case of Gansu Province (China)

Rural poverty has received extensive attention worldwide. Eliminating poverty and achieving common prosperity are the major tasks for China to build a well-off society in an all-round way. Based on the evaluation results of quality of rural life (QRL) and relative poverty index (RPI), this paper identifies and classifies the poor objects using importance–Performance analysis (IPA) method and poverty degree model. The results were as following: (1) QRL has obvious regional differences, and its value gradually decreases from west to east, which is opposite to the spatial distribution pattern of RPI. In areas with high QRL value, the RPI is lower. (2) Fifty counties and districts are clustered in the second quadrant of IPA quadrant map, i.e., Low QRL-High RPI, and the lower quality-of-life corresponds to the higher degree of relative poverty. (3) The coincidence between the poverty-stricken counties and the poverty-stricken counties of the country identified as 84.48% by IPA method, which indicates that the accuracy of poverty delineation based on income is high. (4) Gansu Province is dominated by highly impoverished areas, accounting for 60% of the total number of impoverished counties. The results of comprehensive poverty classification are in line with the actual situation of impoverished counties. In counties with higher CPL, the poverty level is deeper. It is more difficult to get rid of poverty. This study can provide theoretical basis and decision-making reference for the formulation and implementation of Poverty Alleviation Policies in the late stage of underdeveloped areas in western China.