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10 Account. Econ. Law 1 (2020)

handle is hein.journals/acteol10 and id is 1 raw text is: John Fellingham' / Haijin Lin' Is Accounting an Information Science? ' Ohio State University, Columbus, USA, E-mail: fellingham.i aosu.edu 2 University of Houston, Houston, USA Abstract: The central result is an equality connecting accounting numbers with information. In (1 + se ) rf +I(X; Y), rf is the risk free rate, In is the natural logarithm, Y is the outcome of interest, X is the information signal about Y, and I(X; Y) is a Shannon information measure. The equality is derived using economic income accounting; it is shown to hold, under appropriate conditions, for declining balance and straight line depreciation methods. Some social welfare implications are explored. Keywords: accounting, information, Shannon entropy, welfare DOI: 10.1515/ael-2016-0026 Table of Contents 1 Introduction 2 Information and rate of return 2.1 Entropy and mutual information 2.2 A decision problem 2.3 Kelly criterion 3 Accounting and rate of return 3.1 The law of large numbers 3.2 Maximum entropy probability assignment 3.3 A fundamental theorem of accounting 3.4 Illustration with continuous asset replacement 3.4.1 Analysis under economic income accounting 3.4.2 Analysis under declining balance accounting 3.4.3 Analysis under straight line accounting 4 Long run decisions and social welfare 5 Concluding remarks References 1 Introduction The paper is a modest attempt at a positive answer to the question about accounting being an information science. The main result is that accounting numbers are a statement about how much information the reporting entity has access to. We do not analyze the communication of the details of the information available to the reporting entity; the entity conveys a measure of the amount of information it holds, not the information itself. In a way, the accounting problem is changed from the question What is the value of the asset? to the question How much information does the asset possess? In order to confront the latter question, a metric is required which specifies the amount of information. That is, information is treated as something physical which can be manipulated and processed like other physical quantities such as mass or energy. The metric for amount of information is Shannon entropy--a function of probabilities (Shannon 1948). Shan- non's entropy concept has amplified the importance of information. Some other sciences are routinely referred John Fellingham is the corresponding author. © 2o8 Walter de Gruyter GmbH, Berlin/Boston. This content is free. 1 DE CRUYTER Accounting, Economics, and Law: AConvivium. 2018; 20160026 64 UCLA L. REV. 602

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