Comparative Performance of Two Multinomial-Based Methods for Obtaining Lower Bounds on the Total Overstatement Error in Accounting Populations

Matsumura, Ella Mae, et al

Journal of Business & Economic Statistics, 1991, vol. 9, issue 4, 423-29

Abstract: Accurately estimating a lower bound on the total overstatement error in an accounting population is important in many audit decision situations. This article reports the results of a simulation study of three lower-bound estimation procedures based on a multinomial model with a dollar-unit sampling scheme. The ability of each procedure to attain a specified confidence level is assessed with respect to changes in error rate and random sampling method. The simulation study shows that the tested procedures perform well in achieving specified lower-bound coverages on the total overstatement error in the chosen accounting populations. Coauthors are Robert Plante, Kam-Wah Tsui, and P. Kannan.

Date: 1991
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:9:y:1991:i:4:p:423-29

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().