 Simple adjustments of observed distributions for missing income and missing peoplePSE-Ecole d'économie de Paris (Postprint) from HAL Abstract: Correcting household survey distribution data for missing income or for undersampling may give an idea of the extent of possible biases in measuring inequality, especially when there are reasons to expect the missing income and people to belong to the top of the distribution. There are simple ways to do so when only an aggregate estimate of how much is missing is available. Atkinson had provided a formula to correct the Gini coefficient for the missing income, which was later generalized by Alvaredo (Econ. Lett. 110(3), 274–277 2011). This paper concentrates on the whole distribution and explores various alternative adjustment methods based on three key parameters: how much income, how many people are missing and on what range of income the correction should bear. Keywords: Inequality; Missing income; Gini coefficient; Lorenz curve (search for similar items in EconPapers) Published in Journal of Economic Inequality, 2018, 16 (2), pp.171 - 188. ⟨10.1007/s10888-018-9388-8⟩ There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hal:pseptp:halshs-01883896 DOI: 10.1007/s10888-018-9388-8 Access Statistics for this paper More papers in PSE-Ecole d'économie de Paris (Postprint) from HAL |
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