Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/230051
Authors: 
Kaiser, Micha
Year of Publication: 
2019
Citation: 
[Journal:] Journal of Economic Surveys [ISSN:] 1467-6419 [Volume:] 33 [Issue:] 5 [Pages:] 1602-1618
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.
Subjects: 
Benford´s law
Data quality
Fraud detection
Measurement error
Survey quality
C18
C15
C46
C55
C81
I100
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by-nc-nd/4.0/
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.