Multidimensional Poverty Measurement and Cause Analysis of Sichuan Qiang Ethnic Minority -Based on the Investigation of 245 Poor Households in Mao County

Since the central government made a decision to help the poor, China has achieved remarkable results in poverty alleviation, but ethnic minority areas are still the main battlefield for China to fight poverty. Mao County is the country's largest ethnic minority settlement. It uses the MPI analysis method to conduct multi-dimensional analysis of 245 households in four dimensions including education, health, income, and living conditions. It finds that household income structure and medical expenditure affect poverty. In the factor analysis, the individual factors and basic guarantees were added. SPSS 19.0 was used for logistics binary regression analysis. It was found that gender also had a significant impact on poverty. Through understanding the poverty status of the poverty-stricken households currently surveyed, the new understanding Poverty reduction factors, and the reconstruction of poverty alleviation policies, and further optimization of the poverty alleviation pathway, can play a positive role in the local poverty alleviation work.