Sample sizes for reliably estimating lower and upper income shares in income distribution analysis - Charles M. Beach (Queen's University, Department of Economics, 2023)
This paper uses distribution-free formulas for the asymptotic variances of sample quantile income shares - as typically published by statistical agencies as measures of the distribution of income inequality - to calculate how large a survey sample must be in order to estimate a more refined quantile breakdown for a given level of confidence. The approach is applied to decile and quintile earnings data to calculate required increases in sample size to obtain tail 5 percent quantal share estimates and to test changes in income shares. Simple rules of thumb are offered for such a required increase.
Keywords: C12; C46; D31; D63; 330; Income share standard errors; sample size; statistical inference