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Testing the Newcomb-Benford Law: experimental evidence

Author

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  • Uwe Hassler
  • Mehdi Hosseinkouchack

Abstract

The (Newcomb-)Benford Law has been widely used to detect fraud in data from accounting and finance, or in economic, survey and scientific data. Many empirical studies rely on the outcomes of two particular statistical tests. Our power investigation shows that these tests are weak in terms of power under specific fraudulent pattern. Much more powerful criteria are identified, and in particular, a simple, one-sided mean test is recommended.

Suggested Citation

  • Uwe Hassler & Mehdi Hosseinkouchack, 2019. "Testing the Newcomb-Benford Law: experimental evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 26(21), pages 1762-1769, December.
    • Handle: RePEc:taf:apeclt:v:26:y:2019:i:21:p:1762-1769
    DOI: 10.1080/13504851.2019.1597248
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    Cited by:

    1. Roy Cerqueti & Claudio Lupi, 2021. "Some New Tests of Conformity with Benford’s Law," Stats, MDPI, vol. 4(3), pages 1-17, September.
    2. Ausloos, Marcel & Ficcadenti, Valerio & Dhesi, Gurjeet & Shakeel, Muhammad, 2021. "Benford’s laws tests on S&P500 daily closing values and the corresponding daily log-returns both point to huge non-conformity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    3. Roeland de Kok & Giulia Rotundo, 2022. "Benford Networks," Stats, MDPI, vol. 5(4), pages 1-14, September.

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