Research Handbook on the Economics of Criminal Law
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Research Handbook on the Economics of Criminal Law

Edited by Alon Harel and Keith N. Hylton

Jeremy Bentham and Gary Becker established the tradition of analyzing criminal law in utilitarian and economic terms. This seminal book continues that tradition with specially commissioned, original papers that span the philosophical foundations of the use of economics in criminal law, both traditional economic perspectives and behavioral and experimental approaches to the discipline.
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Chapter 8: Stumbling into Crime: Stochastic Process Models of Accounting Fraud

Michael D. Guttentag


Michael D. Guttentag* 1. INTRODUCTION Research on accounting fraud typically begins with the assumption that accounting fraud is a premeditated act. This assumption leads scholars to analyse accounting fraud in terms of the costs and benefits to the firm and the firm’s managers of committing such a fraud. Seminal work by Jennifer Arlen and William Carney, “Vicarious Liability for Fraud on Securities Markets: Theory and Evidence,” is an exemplar of this approach.1 These traditional economic models of the causes of accounting fraud can be further refined by drawing upon insights from behavioral economics, as work by Donald Langevoort has elegantly shown.2 However, even with these refinements, most research on accounting fraud still begins with the assumption that accounting fraud is premeditated. This chapter will explore the use of stochastic process models as a fundamentally different way to explain why managers commit accounting fraud. This chapter will show how to model the possibility that accounting fraud is the unforeseen consequence of a sequence of minor and seemingly innocuous transgressions, rather than a product of planning and forethought. While prior work has described accounting frauds as involving a “slippery slope” dynamic, this chapter will, for the first time, present models that formalize and suggest how to test the hypothesis that managers stumble into committing accounting fraud. There are at least four reasons to suspect that stochastic process models will be a useful tool to describe the dynamics within a firm that can lead to accounting fraud. Of these four reasons, one of...

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