IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v26y2019i21p1762-1769.html
   My bibliography  Save this article

Testing the Newcomb-Benford Law: experimental evidence

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2019.1597248
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13504851.2019.1597248?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:26:y:2019:i:21:p:1762-1769. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.