Knowledge that Transforms

The traditional literature applying statistical sampling to auditing has recognized neither the special structure of auditing populations nor the unique environment in which this sampling occurs. Much of the literature is based on techniques developed for sample surveys. But the auditor typically has a great deal more information about his population than is available to the social scientist in sample surveys. Counterbalancing this, the auditor operates under much tighter precision requirements than the sample survey investigator. In this paper, we explore these issues in greater detail and show how the auditor must use statistical estimators which explicitly use all the auxiliary information available to him. We investigate a class of such estimators and show that, for typical auditing populations, the standard distribution theory is not always appropriate for statistical inference. Therefore, we conclude that entirely new approaches may be required for statistical sampling in auditing.

A. Rashad Abdel-Khalik, [Discussion of The Effect of Aggregating Accounting Reports on the Quality of the Lending Decision: An Empirical Investigation]: A Reply, Journal of Accounting Research, Vol. 11, Empirical Research in Accounting: Selected Studies 1973 (1973), pp. 151-162

Accounting choices, Investment decisions, Investors

External reporting, Semantics, Terminology, Antecedent-consequent method

Edward J. Lusk, [Discussion of Cognitive Aspects of Annual Reports: Field Independence/ Dependence]: A Reply, Journal of Accounting Research, Vol. 11, Empirical Research in Accounting: Selected Studies 1973 (1973), pp. 215-224

The annual report is a communication instrument which may be used to differentiate among the various organizations in the business community. Both the results of economic activity (content), and the manner in which those results are presented (form),' constitute the message of the annual report (Li [1]). Owing to the potential impact of the annual report on decision makers, the Securities and Exchange Commission and the American Institute of Certified Public Accountants,2 through their institutional pronouncements, act to develop user confidence in the information contained in the annual report. These pronouncements have in large measure been addressed to monitoring content, leaving the presentation format of the annual report a discretionary variable.' Any attempts to influence annual report user (stockholders, security

Auditing, Stochastic model, Sampling

Business failure, Bankruptcy, Prediction model, Adjusted Cash

MUCH APPLIED ECONOMETRIC work is based on the correlation and regression of ratio variables which have the same denominator. The denominator generally deflates the various sets of measurements in order to make them comparable. In certain cases deflation is a way of obtaining efficient estimators. Briggs [1] has studied the effect of errors in the deflating variable on the correlation between ratios. The effect of errors in the deflating variable on a scatter diagram of measurements on ratio variables is to displace each representative point along a ray from the origin passing through the representative point of the error-free measurement. This suggests that with error in the deflating variable the ordinary least squares (OLS) estimators of a bivariate regression are biased toward indicating a relationship of proportionality between the ratio variables. It can be demonstrated that this conjecture is generally valid for multiple linear regression with error in the deflator. In most cases in which deflation is used, it is reasonable to suppose that the deflator is a random variable distributed independently of the ratio variables; in this case the conditional expectation of the undeflated independent variables is proportional to the value of the deflator. Under this assumption it can be established that when there is error in the deflator the estimators of the slopes of the regression are inconsistent unless (i) the ratio regression has zero intercept, or (ii) the mean of each of the independent variables is zero, or (iii) the error in the deflator is systematic (i.e., the error term has zero variance). The estimator of the intercept may be inconsistent even when the estimators of the slopes are consistent; for the intercept estimator to be consistent it is necessary that either (i) the intercept