[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/vrs/jecman/v45y2023i1p216-236n7.html
   My bibliography  Save this article

Applying Benford’s law to detect earnings management

Author

Listed:
  • Sylwestrzak Marek

    (Department of Finance and Accounting Faculty of Economic Sciences University of Warsaw, Poland)

Abstract
Aim/purpose – This paper analyzes the role of Benford’s law in the detection of earnings management in Poland. Previous research that uses Benford’s law does not split the sample into a fraud and a control group; however, this method is used in logistic regression and data mining analysis. Design/methodology/approach – The sample comprises 126 observations of Polish non-financial companies listed on the Warsaw Stock Exchange for the years 2010-2021. The author uses first, second, and first-two digits analysis as a proxy for earnings management detection. Findings – The results indicate that fraudulent companies have different deviations in the digits than control firms. Accordingly, the statistical test results indicate that control companies have weaker conformity with the Benford distribution than fraudulent companies. Research implications/limitations – The study sample is limited to 126 observations, which is due to the small number of listed firms that received a monetary fine from the Polish Financial Supervision Authority (UKNF Board) for violation of IAS/IFRS principles related to their financial statements during the study period. Originality/value/contribution – The author offers a significant contribution to the accounting literature by proposing the separation of fraudulent and control observations in Benford analysis due to differences in the deviations of digits. Also, analyzing the full sample may lead to the identification of inappropriate areas for further auditor analysis.

Suggested Citation

  • Sylwestrzak Marek, 2023. "Applying Benford’s law to detect earnings management," Journal of Economics and Management, Sciendo, vol. 45(1), pages 216-236, January.
    • Handle: RePEc:vrs:jecman:v:45:y:2023:i:1:p:216-236:n:7
    DOI: 10.22367/jem.2023.45.10
    as

    Download full text from publisher

    File URL: https://doi.org/10.22367/jem.2023.45.10
    Download Restriction: no
    File URL: https://libkey.io/10.22367/jem.2023.45.10?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
    ---><---

    References listed on IDEAS

    as
    1. Alex Ely Kossovsky, 2021. "On the Mistaken Use of the Chi-Square Test in Benford’s Law," Stats, MDPI, vol. 4(2), pages 1-35, May.
    2. Sitsofe Tsagbey & Miguel de Carvalho & Garritt L. Page, 2017. "All Data are Wrong, but Some are Useful? Advocating the Need for Data Auditing," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 231-235, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roy Cerqueti & Claudio Lupi, 2023. "Severe testing of Benford’s law," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 677-694, June.
    2. Arezzo, Maria Felice & Cerqueti, Roy, 2023. "A Benford’s Law view of inspections’ reasonability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    3. Junho Lee & Miguel de Carvalho, 2019. "Technological improvements or climate change? Bayesian modeling of time-varying conformance to Benford’s Law," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-11, April.
    4. Eutsler, Jared & Kathleen Harris, M. & Tyler Williams, L. & Cornejo, Omar E., 2023. "Accounting for partisanship and politicization: Employing Benford's Law to examine misreporting of COVID-19 infection cases and deaths in the United States," Accounting, Organizations and Society, Elsevier, vol. 108(C).

    More about this item

    Keywords

    earnings management; digital analysis; Polish companies.;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

    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:vrs:jecman:v:45:y:2023:i:1:p:216-236:n:7. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.