The effects of income imputation on microanalyses: evidence from the European Community Household Panel

Cheti Nicoletti, Franco Peracchi

Research output: Contribution to journalArticlepeer-review


Social surveys are usually affected by item and unit non-response. Since it is unlikely that a sample of respondents is a random sample, social scientists should take the missing data problem into account in their empirical analyses. Typically, survey methodologists try to simplify the work of data users by ‘completing’ the data, filling the missing variables through imputation. The aim of the paper is to give data users some guidelines on how to assess the effects of imputation on their microlevel analyses. We focus attention on the potential bias that is caused by imputation in the analysis of income variables, using the European Community Household Panel as an illustration.
Original languageEnglish
Pages (from-to)625
Number of pages1271
JournalJournal of the Royal Statistical Society: Series A (Statistics in Society)
Issue number3
Early online date16 May 2006
Publication statusPublished - 1 Jun 2006


  • Imputation
  • Missing data
  • Income
  • Missing at random

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