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Benford's Law and Fraud Detection. Facts and Legends

  • Andreas Diekmann


  • Ben Jann


Is Benford's law a good instrument to detect fraud in reports of statistical and scientific data? For a valid test the probability of "false positives" and "false negatives" has to be low. However, it is very doubtful whether the Benford distribution is an appropriate tool to discriminate between manipulated and non-manipulated estimates. Further research should focus more on the validity of the test and test results should be interpreted more carefully.

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Paper provided by ETH Zurich, Chair of Sociology in its series ETH Zurich Sociology Working Papers with number 8.

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Length: 8 pages
Date of creation: 06 Feb 2010
Date of revision:
Handle: RePEc:ets:wpaper:8
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  1. 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.
  2. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
  3. Andreas Diekmann, 2002. "Diagnose von Fehlerquellen und methodische Qualität in der sozialwissenschaftlichen Forschung [Sources of Bias and Quality of Data in Social Science Research]," ITA manu:scripts 02_04, Institute of Technology Assessment (ITA).
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