Sample Sizes for Reliably Estimating Lower and Upper Income Shares in Income Distribution Analysis

Charles Beach ()

No 1505, Working Paper from Economics Department, Queen's University

Abstract: 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: Income share standard errors; sample size; statistical inference (search for similar items in EconPapers)
JEL-codes: C12 C46 D31 D63 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2023-04
New Economics Papers: this item is included in nep-ecm
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