Tightening CAV (DUS) bounds by using a parametric model

Article Abstract:

An innovative way to set upper bounds for aggregate error sampling related to accounting and auditing populations is presented that uses dollar unit sampling (DUS). This new method of setting bounds is compared to the Stringer bound-setting method, which makes use of certain combined attributes and variables (CAV) when establishing sampling bounds. The new method could minimize overauditing caused by bound setting that leads accountants to believe the probability for error is greater than it is in actuality. The DUS bound-setting method developed is dependent upon power function density models for taintings within the samples and parametric bootstrap methods, both of which are described. One simulation running of the bound setting method developed suggests that modeling of the distribution of taintings could result in more economical and more efficient audit planning.

Planning, Statistical sampling, Sampling (Statistics), Analysis of variance, Mathematical research, Statistics (Mathematics), Mathematical statistics

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A within-subjects test of expectancy theory in a public accounting environment

Article Abstract:

Expectancy models developed by Jiambalvo (1979) and Ferris (1977) are used to analyze employee motivation and performance among certified public accountants, emphasizing a 'within-subjects' approach, although a 'between-subjects' approach is also used for comparative purposes. The research confirms findings by Kopelman (1977) and suggests the validity of expectancy theory to explain certified public accountants' motivation and performance. The results of the expectancy model's application upholds the validity of the expectancy theory as well, although the variance among results suggests that the model used did not predict motivation and performance as well as other expectancy models might.

Models, Management, Human resource management, Accounting firms, Accounting services, Accountants, Employee motivation, Motivation (Psychology), Expectation (Psychology), Expectations, Performance standards, Job performance standards, Distribution (Probability theory)

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Accuracy of auxiliary information interval estimation in statistical auditing

Article Abstract:

Auxiliary information estimators, used extensively in statistical auditing, are reviewed. The reasons that the confidence levels of these estimators do not conform to a normal distribution are examined. It is demonstrated that the distribution of these estimators is skewed because so few audited accounts have errors.

Methods, Analysis, Statistics, Statistics (Data)

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