Simple adjustments of observed distributions for missing income and missing people

François Bourguignon

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)171-188
Number of pages18
JournalJournal of Economic Inequality
Issue number2
StatePublished - Jun 1 2018


  • Gini coefficient
  • Inequality
  • Lorenz curve
  • Missing income

ASJC Scopus subject areas

  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)
  • Organizational Behavior and Human Resource Management


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