Which type of substantive analytical procedure uses statistical models to quantify our expectation

journal article

The Accounting Review

Vol. 65, No. 3 (Jul., 1990)

, pp. 557-577 (21 pages)

Published By: American Accounting Association

https://www.jstor.org/stable/247950

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Abstract

This study extends the existing research on the audit effectiveness of analytical procedures in a setting that used actual accounting data seeded with "material" simulated accounting errors. Five sample companies, whose revenues represented a wide range of time-series behavior, were selected to analyze the effects of eight commonly encountered accounting errors on 15 often-used analytical procedures (eight ratios and seven accounts). A "best case" scenario was induced by using, among other factors, single-industry companies, quarterly data, and more sophisticated expectation models than had been used in prior studies. The best predicting of six candidate models (four naive, a regression, and the Census X-11 time-series model) was used to generate quarterly predictions for comparison with actual data seeded with the largest of four empirically based materiality measures. Five investigation rules, including two simple percentage change rules and a statistical rule using three different alpha levels, were applied to prediction errors to determine whether error investigations were correctly signaled. The results of prediction model selection were dominated by X-11, followed by regression. Also, X-11 emerged as the "best" model more often for ratios than for accounts, while the reverse was true for the regression models. Overall, the analytical procedures examined did not signal (Type I and Type II error rates) very well when applied in isolation to quarterly data. However, when the quarterly signaling resulting were "annualized," and when an annual material error was seeded into an individual quarter's data, the results were much more encouraging. The lowest error rates were observed for instances where the primary substantive test would have been direct recomputation (i.e., interest and depreciation errors). The assertion of SAS No. 56 that income statement accounts should be more predictable than balance sheet accounts was contradicted, but the evidence is limited. The seeded quarterly material errors were generally swamped by prediction errors of the best-predicting expectation models. A significant correlation was observed between the ratio (prediction error/materiality) and the incidence of Type II signaling errors, indicating that this relationship might be used as a filter to determine when analytical procedures are likely to be effective audit tests.

Journal Information

The Accounting Review is the premier journal for publishing articles reporting the results of accounting research and explaining and illustrating related research methodology. The scope of acceptable articles embraces any research methodology and any accounting-related subject. The primary criterion for publication in The Accounting Review is the significance of the contribution an article makes to the literature.

Publisher Information

The American Accounting Association is the world's largest association of accounting and business educators, researchers, and interested practitioners. A worldwide organization, the AAA promotes education, research, service, and interaction between education and practice. Formed in 1916 as the American Association of University Instructors in Accounting, the association began publishing the first of its ten journals, The Accounting Review, in 1925. Ten years later, in 1935, the association changed its name to become the American Accounting Association. The AAA now extends far beyond accounting, with 14 Sections addressing such issues as Information Systems, Artificial Intelligence/Expert Systems, Public Interest, Auditing, taxation (the American Taxation Association is a Section of the AAA), International Accounting, and Teaching and Curriculum. About 30% of AAA members live and work outside the United States.

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