Knowledge that Transforms

Analyst following, Institutional investors, Information costs

Auditing, Auditor expertise, Auditor experience, Information processing

Decision making, Decision aids, Financial incentives, Performance Feedback

In this study, we explore a view of expertise in which specific experiences and training create knowledge, and knowledge is combined with innate ability to perform specific audit tasks. Specifically, we test the extent to which we can explain cross-sectional variation in auditors' performance in several audit tasks using various types of knowledge and ability measures that have been identified in the psychology literature as important determinants of auditor expertise. We compare these results to the explanatory power of a simple measure of general audit experience. Our results indicate that, although more experienced auditors outperform less experienced auditors on average (and given our performance criteria), knowledge and innate ability provide a better explanation of variation in performance. Part of the motivation for this paper is to distinguish between general and expertise in the performance of information-processing tasks. Early studies of human information processing in accounting examined the effect of on performance in audit tasks (see, for example, Ashton and Brown [1980], Hamilton and Wright [1982], and Messier [1983]). Implicit in this research is the notion that . . a primary determinant of improved expertise ... is experience (Hamilton and Wright [1982, p. 757]). The reasoning behind this notion is that knowledge can be gained through and many audit tasks are knowl-

Peter Brownell, Kenneth A. Merchant, The Budgetary and Performance Influences of Product Standardization and Manufacturing Process Automation, Journal of Accounting Research, Vol. 28, No. 2 (Autumn, 1990), pp. 388-397

Auditing, Audit quality, Audit performance, Time pressure

In this study I propose and test a model that predicts individual analyst forecasts of corporate earnings per share (EPS) using the change in the mean consensus forecast of other analysts since the date of the analyst's current outstanding forecast; the deviation of the analyst's current forecast from the consensus forecast; and cumulative stock returns since the date of the analyst's current forecast. I find that these three variables explain about 38% of the variability in analyst forecast revisions. While there is evidence of a relation between changes in earnings expectations and price changes, virtually all of the explanatory power of my model arises from other analyst forecasts. Section 2 describes the data bases used and the sample selection process. Section 3 presents the model and method for predicting individual analyst forecasts. Section 4 reports the bias and accuracy of the predicted forecasts. Conclusions are in section 5.

The purpose of this paper is to investigate whether financial analysts with superior earnings forecasting ability can be distinguished on the basis of ex post forecast accuracy. I explore the question by estimating and comparing average accuracy across individuals, and by considering whether the observed distribution of analyst forecast accuracies differs from the distribution expected if their relative performances each year were purely random. Overall, I do not find systematic differences in forecast accuracy across individuals. Financial press coverage suggests there are superior financial analysts. For example, Institutional Investor's annual All American Research Team includes analysts rated by money managers as superior on a variety of criteria, including earnings forecasting, ability to pick stocks, and the quality of written reports. Clearly, financial analyst services other than forecast accuracy are valued by their clients. I focus on only one activity, earnings forecasting, for two reasons. First, forecast data are available, quantitative, and can be evaluated against observable earnings outcomes. Services such as insightful, well-written research reports are harder to evaluate quantitatively. Second, academic use of analyst forecasts as earnings expectations data in capital markets empir-

Auditing, Audit risk, Accounting errors, Strategic audit risk

Taxation, Tax complexity, Tax-reporting positions