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Difficulties Detecting Fraud? The Use of Benford’s Law on Regression Tables

Author

Listed:
  • Bauer Johannes

    (Ludwig-Maximilians-Universität München, Institut für Soziologie Konradstr. 6, 80539 München, Germany)

  • Groß Jochen

    (Senior Quantitative Consultant, Roland Berger Strategy Consultants Holding GmbH, Mies-van-der-Rohe-Str. 6, 80807 München, Germany)

Abstract

The occurrence of scientific fraud damages the credibility of science. An instrument to discover deceit was proposed with Benford’s law, a distribution which describes the probability of significant digits in many empirical observations. If Benford-distributed digits are expected and empirical observations deviate from this law, the difference yields evidence for fraud.

Suggested Citation

  • Bauer Johannes & Groß Jochen, 2011. "Difficulties Detecting Fraud? The Use of Benford’s Law on Regression Tables," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 733-748, October.
  • Handle: RePEc:jns:jbstat:v:231:y:2011:i:5-6:p:733-748
    DOI: 10.1515/jbnst-2011-5-611
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    References listed on IDEAS

    as
    1. Karl-Heinz Tödter, 2009. "Benford's Law as an Indicator of Fraud in Economics," German Economic Review, Verein für Socialpolitik, vol. 10, pages 339-351, August.
    2. David Giles, 2007. "Benford's law and naturally occurring prices in certain ebaY auctions," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 157-161.
    3. Andreas Diekmann, 2005. "Not the First Digit! Using Benford’s Law to Detect Fraudulent Scientific Data," Others 0507001, University Library of Munich, Germany.
    4. Andreas Diekmann, 2007. "Not the First Digit! Using Benford's Law to Detect Fraudulent Scientif ic Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(3), pages 321-329.
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    1. Florian El Mouaaouy & Jan Riepe, 2018. "Benford and the Internal Capital Market: A Useful Indicator of Managerial Engagement," German Economic Review, Verein für Socialpolitik, vol. 19(3), pages 309-329, August.
    2. Walter R. Schumm & Duane W. Crawford & Lorenza Lockett & Asma bin Ateeq & Abdullah AlRashed, 2023. "Can Retracted Social Science Articles Be Distinguished from Non-Retracted Articles by Some of the Same Authors, Using Benford’s Law or Other Statistical Methods?," Publications, MDPI, vol. 11(1), pages 1-13, March.
    3. Teddy Lazebnik & Dan Gorlitsky, 2023. "Can We Mathematically Spot the Possible Manipulation of Results in Research Manuscripts Using Benford’s Law?," Data, MDPI, vol. 8(11), pages 1-11, October.
    4. Horton, Joanne & Krishna Kumar, Dhanya & Wood, Anthony, 2020. "Detecting academic fraud using Benford law: The case of Professor James Hunton," Research Policy, Elsevier, vol. 49(8).

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