Improving the Accuracy and Precision of Analytical Procedures Using Multilocation Data
Robert D. Allen
University of Utah - School of Accounting and Information Systems
Mark S. Beasley
North Carolina State University
Bruce C. Branson
North Carolina State University - College of Management
According to SAS No. 56, Analytical Procedures, the use of disaggregate, individual location data can improve the effectiveness of analytical procedures used in multilocation audits. Using disaggregate data obtained from a multilocation company, we examine two issues: 1) whether the accuracy and precision of analytical procedures is enhanced by including contemporaneous observations of the account balance in the prediction model, and 2) whether expectations developed using disaggregate data are more accurate and precise than expectations based on aggregate data only. We find that the contemporaneous models are consistently more accurate and precise and that the summation of individual location account balance forecasts based on disaggregate, contemporaneous models are superior to expectations developed using aggregate, company-wide data only. The results indicate that when auditors are generating expectations of company-wide balances, that disaggregate, contemporaneous models will provide predictions that are both more accurate and more precise than company-wide, aggregate models.
Number of Pages in PDF File: 45
JEL Classification: M49, C43working papers series
Date posted: January 14, 1998
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