Subjective Prior Probability Distributions and Audit Risk

Abstract

Bayesian models of the auditor's decision process (e.g., Bailey and Jensen [1977], Kinney [1975], and Scott [1973; 1975]) incorporate subjective beliefs formalized as prior probability distributions (PPDs). Recent studies by Solomon [1982] and Tomassini et al. [1982] investigated two conformance properties of auditors' account balance PPDs: extremeness and calibration. PPD extremeness is measured over a sequence of elicitation trials by computing the average subjective probability assigned to intervals containing the auditees' actual account values and, as such, can be viewed as a measure of predictive ability (see Seaver, von Winterfeldt, and Edwards [1978]). Calibration, in turn, is a measure of the ability to express an appropriate degree of confidence in such subjective estimates.1 Both the Solomon [1982] and Tomassini et al. [1982] studies reported that auditors' PPDs were miscalibrated and that there was