Benford's Law as an Indicator of Survey Reliability: Can We Trust Our Data?

Micha Kaiser*

*Corresponding author for this work

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Abstract

This paper analyzes how closely different income measures conform to Benford's law, a mathematical predictor of probable first digit distribution across many sets of numbers. Because Benford's law can be used to test data set reliability, we use a Benford analysis to assess the quality of six widely used survey data sets. Our findings indicate that although income generally obeys Benford's law, almost all the data sets show substantial discrepancies from it, which we interpret as a strong indicator of reliability issues in the survey data. This result is confirmed by a simulation, which demonstrates that household level income data do not manifest the same poor performance as individual level data. This finding implies that researchers should focus on household level characteristics whenever possible to reduce observation errors.

Original languageEnglish
JournalJournal of Economic Surveys
Volume33
Issue number5
Pages (from-to)1602-1618
Number of pages17
ISSN0950-0804
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes

Keywords

  • Benford's law
  • Data quality
  • Fraud detection
  • Measurement error
  • Survey quality

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