- Research Handbooks in Law and Economics series
Edited by Alon Harel and Keith N. Hylton
Chapter 8: Stumbling into Crime: Stochastic Process Models of Accounting Fraud
8 Stumbling into crime: stochastic process models of accounting fraud 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...
You are not authenticated to view the full text of this chapter or article.
Elgaronline requires a subscription or purchase to access the full text of books or journals. Please login through your library system or with your personal username and password on the homepage.
Non-subscribers can freely search the site, view abstracts/ extracts and download selected front matter and introductory chapters for personal use.
Your library may not have purchased all subject areas. If you are authenticated and think you should have access to this title, please contact your librarian.