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Are Auditors' Judgments Sufficiently Regressive?

Edward J. Joyce; Gary C. Biddle
Journal of Accounting Research 1981 19(2), 323 open access
The primary purpose of this paper is to test for the use of the representativeness heuristic by auditors in situations in which its use will lead to judgments that systematically depart from the Bayesian optimal responses. No explicit representation of payoffs was made, nor were subjects typically asked to choose a course of action. Thus it cannot be concluded that use of the representativeness heuristic in the experimental situations tested is not cost effective. To the extent, however, that one is willing to assume that action choices are sensitive to judgments of outcome probabilities, and these action choices have differential expected payoffs, a finding of extensive heuristic use by auditors would suggest further research to assess the economic consequences of such use.

Anchoring and Adjustment in Probabilistic Inference in Auditing

Edward J. Joyce; Gary C. Biddle
Journal of Accounting Research 1981 19(1), 120 open access
Auditors are faced with the task of formulating opinions about the fairness of their clients' financial statements. In doing so, they use their professional judgment to determine the type and amount of information to collect, the timing and manner of collecting it, and the implications of the information collected. This information is rarely, if ever, perfectly reliable or perfectly predictive of the "true" state of a client's financial statements. Nevertheless, auditors may be held liable at common law or under the federal securities laws should the audited financial statements prove to be unrepresentative of this true state. Thus, it is important for auditors to have the ability to formulate appropriately judgments based on probabilistic data. In this paper, we describe the results of experiments designed to assess whether auditors formulate judgments in accordance' with normative principles of decision making or whether a particular alternative to the normative model of decision making under uncertainty 's employed. In the next section, we discuss several alternatives to normative decision models, focusing on the anchoring and adjustment heuristic which forms the basis for our experiments.