IDEAS home Printed from
   My bibliography  Save this paper

Information theoretic approach for accounting classification


  • E. M. S. Ribeiro
  • G. A. Prataviera


In this paper we consider an information theoretic approach for the accounting classification process. We propose a matrix formalism and an algorithm for calculations of information theoretic measures associated to accounting classification. The formalism may be useful for further generalizations and computer-based implementation. Information theoretic measures, mutual information and symmetric uncertainty, were evaluated for daily transactions recorded in the chart of accounts of a small company during two years. Variation in the information measures due the aggregation of data in the process of accounting classification is observed. In particular, the symmetric uncertainty seems to be a useful parameter for comparing companies over time or in different sectors or different accounting choices and standards.

Suggested Citation

  • E. M. S. Ribeiro & G. A. Prataviera, 2014. "Information theoretic approach for accounting classification," Papers 1401.2954,, revised Sep 2014.
  • Handle: RePEc:arx:papers:1401.2954

    Download full text from publisher

    File URL:
    File Function: Latest version
    Download Restriction: no

    References listed on IDEAS

    1. Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2004. "Mutual information: a measure of dependency for nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 326-329.
    2. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2003. "Mutual information: a dependence measure for nonlinear time series," Econometrics 0311003, University Library of Munich, Germany.
    3. Henri Theil, 1969. "On the use of Information Theory Concepts in the Analysis of Financial Statements," Management Science, INFORMS, vol. 15(9), pages 459-480, May.
    4. Touchette, Hugo & Lloyd, Seth, 2004. "Information-theoretic approach to the study of control systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(1), pages 140-172.
    5. Navarra, F.S. & Utyuzh, O.V. & Wilk, G. & Włodarczyk, Z., 2004. "Information theory approach (extensive and nonextensive) to high-energy multiparticle production processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 467-476.
    6. Kowalski, A.M. & Plastino, A. & Proto, A.N., 2003. "Information theory and chaotic motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 327(1), pages 135-139.
    7. Wilhelm, Thomas & Hollunder, Jens, 2007. "Information theoretic description of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 385-396.
    8. Golan, Amos, 2008. "Information and Entropy Econometrics — A Review and Synthesis," Foundations and Trends(R) in Econometrics, now publishers, vol. 2(1–2), pages 1-145, February.
    9. de Oliveira, M. Elias & Menegaldo, L.L. & Lucarelli, P. & Andrade, B.L.B. & Büchler, P., 2011. "On the use of information theory for detecting upper limb motor dysfunction: An application to Parkinson’s disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4451-4458.
    10. Epstein, Barry J & King, William R, 1982. "An experimental study of the value of information," Omega, Elsevier, vol. 10(3), pages 249-258.
    11. Ribeiro, A.S. & Riera, R., 2013. "An information-based tool for inferring the nature of deterministic sources in real data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5053-5064.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:arx:papers:1401.2954. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.