Title

Estimating accounting errors in audit sampling : extensions and empirical tests of a decomposition approach

Document Type

Journal article

Source Publication

Journal of Accounting, Auditing and Finance

Publication Date

4-1-1996

Volume

11

Issue

2

First Page

153

Last Page

161

Abstract

A decomposition approach was presented by Chan (1988) to estimate accounting errors based on a ratio estimator in audit sampling. That approach decomposed the tainting distribution into several distinct components according to the characteristics of typical accounting populations, and modeled each component separately. A simulation procedure was then used to combine the probabilistic components to determine the error bounds. A deficiency with this approach is its reliance on the central limit theorem (CLT) to model an important component of the tainting distribution when the error rate is low. This paper proposes two alternatives, the chi-square and the exponential distributions to replace the use of the central limit theorem in the model. Empirical tests confirm that the proposed alternatives improve on the overall reliability of the original CLT method for low-error-rate populations. For populations with high error rates of 10 percent or more, however, the performance of all three methods is similar.

Print ISSN

0148558X

E-ISSN

21604061

Publisher Statement

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Full-text Version

Publisher’s Version

Recommended Citation

Chan, K. H. (1996). Estimating accounting errors in audit sampling: Extensions and empirical tests of a decomposition approach. Journal of Accounting, Auditing & Finance, 11(2), 153-161. Retrieved from http://jaf.sagepub.com/content/11/2/153.abstract