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Accounting Information, Aggregation, and Discriminant Analysis

Author

Listed:
  • Anil Arya

    (Fisher College of Business, The Ohio State University, 2100 Neil Avenue, Columbus, Ohio 43210)

  • John Fellingham

    (Fisher College of Business, The Ohio State University, 2100 Neil Avenue, Columbus, Ohio 43210)

  • Doug Schroeder

    (Fisher College of Business, The Ohio State University, 2100 Neil Avenue, Columbus, Ohio 43210)

Abstract

Aggregation is a pervasive theme in accounting. The preparation of financial statements involves extensive aggregation---information regarding several transactions is summarized using a few account balances. In this article, we study linear, double-entry aggregation rules. The level of aggregation (transactions versus account balance information) affects a decision maker's ability to discriminate between two entities. We show that the orientation of the discriminant function relative to the row space and the nullspace (two fundamental subspaces) of the double-entry matrix determines the information loss due to aggregation. In addition, we observe that an interdependency in account balances is introduced by the double-entry process. The cause and effect property (debit and credit) translates into a negative covariance being introduced among account balances; this, in turn, affects the decision maker's optimal use of information. Finally, in discussing benefits to aggregation, we present an example in which adopting a double-entry aggregation rule serves as a commitment device for the owner.

Suggested Citation

  • Anil Arya & John Fellingham & Doug Schroeder, 2000. "Accounting Information, Aggregation, and Discriminant Analysis," Management Science, INFORMS, vol. 46(6), pages 790-806, June.
    • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:6:p:790-806
    DOI: 10.1287/mnsc.46.6.790.11935
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    References listed on IDEAS

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    1. Lim, S.S. & Sunder, S., 1990. "Econometric Efficiency Of Asset Valuation Rules Under Price Movement And Measurement Errors," GSIA Working Papers 89-90-40, Carnegie Mellon University, Tepper School of Business.
    2. Anil Arya & Jonathan Glover & K. Sivaramakrishnan., "undated". "The Interaction between Decision and Control Problems and the Value of Information," Corporate Finance & Organizations _016, Ohio State University.
    3. Sappington, David E. M., 1986. "Commitment to regulatory bureaucracy," Information Economics and Policy, Elsevier, vol. 2(4), pages 243-258, December.
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    Cited by:

    1. Debreceny, Roger S. & Gray, Glen L., 2010. "Data mining journal entries for fraud detection: An exploratory study," International Journal of Accounting Information Systems, Elsevier, vol. 11(3), pages 157-181.
    2. Anil Arya & John Fellingham & Doug Schroeder & Jonathan Glover, 2002. "Depreciation in a model of probabilistic investment," European Accounting Review, Taylor & Francis Journals, vol. 11(4), pages 681-697.
    3. Plot-Vicard, Emmanuelle, 2010. "L’information diffusée par l’exploitant sur le risque nucléaire : quelle réponse aux attentes des parties prenantes ?," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/5592 edited by Richard, Jacques.
    4. Anil Arya & John C. Fellingham & Jonathan C. Glover & Douglas A. Schroeder & Gilbert Strang, 2000. "Inferring Transactions from Financial Statements," Contemporary Accounting Research, John Wiley & Sons, vol. 17(3), pages 366-385, September.
    5. Ray, Sangeeta & Ray, Pradeep Kanta, 2021. "Innovation strategy of latecomer firms under tight appropriability regimes: The Indian pharmaceuticals industry," Journal of International Management, Elsevier, vol. 27(1).

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