The quality of poverty alleviation statistics guarantees the quality of the national poverty alleviation work.This paper uses Benfords law to test the authenticity of the first two digits of the data, and builds a principal component panel regression model to logically match the indicators with the statistics of four important poverty alleviation indicators across the country and povertystricken areas from 2013 to 2018. It then uses the residuals obtained by regression analysis to further detect the time and area of the problem data and give some suggestions. We find that: the results of Benfords law chi square test show that the poverty incidence rate, rural per capita disposable income, and rural per capita consumption expenditure in the countryside and povertystricken areas failed the test. Except the disposable income of rural per capita residents, the second digits of other indicators have passed the statistical distribution test at the 0.05 significance level. There is a good logical match between the poverty incidence data and the other three indicators in poor areas from 2013 to 2018. The data quality of other regions is good, except the data of individual regions such as Hebei, Shaanxi, Hainan, and Tibet, which have not passed the residual test.