Reviews the book "Accounting Education: An Innovative Approach," by Sunion Theodore Hong.

The article presents the author's reply to researcher L.S. Revsine's rejoinder on the article "Expectations and Achievements in Income Theory." The author feels that Revsine's comments on the article are based upon a series of misconceptions and unsupported assertions. The author's article was primarily concerned with relationships between ex ante and ex post measures of periodic income and asset values and why both sets of concepts are required. It concluded that the case for current cost accounting cannot be made to rest on the hypothesis that current market prices of assets are reliable indications of the present values of those assets, except under tight conditions; rather, the justification for current cost accounting depends upon a set of other factors. The rejoinder does not challenge successfully the validity of any of the author's analysis. In his rejoinder, Revsine first asserted that the author stated that previous authors have ignored the excess of present values over current market prices of assets for all nonmarginal asset purchases.

The article focuses on acceptance sampling plans for auditing. The interest in statistical sampling among accountants has become more pronounced and has broadened from problems of acceptance sampling to include techniques of statistical estimation. The paper contains a brief review of concepts, design and construction of both single sampling plans (SSP) and sequential sampling plans and presents a new cost optimization model with illustrative results for selection of the least-cost sampling plan. Throughout the paper, authors assume that the population is large relative to the sample size. Acceptance sampling consists of drawing samples or groups of samples from a population, examining these for properties of interest and finally, reaching some decision based upon the sample results. Elements of an acceptance-sampling plan are the method of sampling, the sample sizes and the appropriate decision rules for reaching some decision. The simplest acceptance sampling plan, an SSP, consists of the selection of a random sample of N items; the determination of the number of errors or defectives; and comparison of this quantity, with a previously determined acceptance number, or rejection number.

Reviews the book "Financial Accounting and Reporting: A Contemporary Emphasis," by John Dearden and John Shank.

The article focuses on some designs of multidimensional accounting system. An accounting system is viewed as a structured database capable of supporting a class of queries or requests for data. These queries could be specific requests for data, such as the current balance of an account or the value of an inventory item, or more complicated requests, such as a profit and loss statement or a balance sheet. The traditional accounting system is oriented toward financial reports and therefore, only financial data are stored. Information on an hourly wage earner, such as number of parts produced on a given day, the average number of defects or the value added to the part, normally is not stored with the accounting data. By storing the value added information, an employee can be evaluated on terms of wage times hours versus the value added to the product. Authors' contention is that an accounting system can be viewed as an information system that supports a specific class of queries. The paper presents a process for designing a common data structure, which will support the given set of queries.

The "Comment and Extension" of R. Picur and J. McKeown (hereafter, P and M) examines three aspects of "Alternative Income Concepts and Relative Performance Evaluations" (hereafter, KMT). The differences with P and M per their respective classifications is noted with respect to theoretical, methodological and statistical terms. The statistical extension of P and M, in particular, is completely invalid. The form of current value reporting used in KMT was shown to have theoretical support both in academia and in the profession. It does not agree with the proposal of P and M. However, the purpose was not at all to advocate a specific current value form, but to consider whether a typical current value form would indicate a performance difference among firms in an industry as compared to a typical historical cost form. The P and M proposed adjustment of liabilities to reflect changing market rates clearly would change the performance measures of the sample of KMT. However, there is no general agreement that liabilities should be so adjusted in current value financial statements, any more than there is general agreement that annuity depreciation should be used for historical cost reports.

In this study, the question of forecast accuracy by examining forecasts released by firms during 1970 and 1971 is considered. Since these forecast releases were voluntary on the part of the firms involved, there is some question about the validity of drawing inferences regarding overall accuracy of mandatory forecasts; thus, some results are included which are merely descriptive, in addition to certain statistical tests addressed more to the issue of inference. A second aim of the study was to examine the accuracy of forecasts made by outsiders (security analysts) relative to the forecasts of firms. Ideally, one would expect corporations to be able to forecast their earnings more accurately than outsiders, even when those outsiders are professional analysts. In short, based on the empirical results, forecast accuracy does not appear to be highly impressive for either group. Given the potential disruptive effects of poor forecasting on investment decisions and, as a result, on current stock market mechanisms, perhaps it would be wise to declare a moratorium on pressures for mandatory published forecasts by firms until forecasting techniques have been refined sufficiently to assure considerably better accuracy than apparently exists.

While the basic question that Professors S.H. Kratchman, R.E. Malcolm and R.D. Twark (hereafter referred to as K, M and T) sought to explore is of central importance to accounting research, it appears that the methodology employed to address this issue strongly impacts upon their findings. The limitations of an ill-defined and conceptually lacking method of "current" value leads to a meaningless hybrid. The failure to properly adjust liabilities to reflect changing market rates clearly distorts the balance sheets and, hence, the performance measures utilized, i.e., return on assets and return on equity. The statistical tests are inappropriate for the null hypothesis implied by the basic research question K, M and T pose. The net result of these compounding limitations has been depicted partially in revised sets of performance measure ratios-sets which vary dramatically from K, M and T's results. These conditions all point to one inescapable conclusion; i.e., the aggregation of these limitations is of such unknown magnitude that without a complete replication, any and all interpretations K, M and T offer must be held suspect.

In a recent article, Edward B. Deakin and Michael H. Granof " demonstrated how regression analysis, coupled with Bayesian statistical procedures, can be used to provide the auditor with assistance in selecting those accounts for investigation that are most likely to result in significant audit findings. The article encourages audit model development and experimentation by independent auditors with the application of these and other techniques which make use of additional information. The independent auditor's ultimate concern with respect to a reported account balance of a client, is whether it is "fairly presented." Suppose that the auditor has evaluated the design of an internal control subsystem and has conducted tests of compliance of system operation with system design. Substantive tests include analytical review of significant ratios and trends and resulting investigation of unusual fluctuations and questionable items and tests of details of transactions and balances. Without the refinement, the sample sizes required after using regression analysis to revise priors often will be substantially smaller than the 163 required under classical, unrestricted random sampling.

This paper provides a brief review of the salient economic, behavioral and quantitative literature in accounting and transfer pricing. Further, it relates this review to a relatively new programming formulation, suggesting the greater descriptive implications potential inherent in the new technique generalized goal decomposition programming. The paper does not develop new ideas, but attempts to relate existing material in a manner that will bring the reader's attention to the potential of the mathematical programming models in hierarchical organizations. The expanding literature in this area clearly is deserving of attention as it provides a means by which the behavioral and algorithmic approaches to resource transfer problems may be integrated. It is a step in the direction of models integration and thus, a step toward more realistic mathematical formulation of the decision-making environment. One rely on the scholar T. Ruefli model in this presentation as it provided a relatively easily explained formulation. Interested readers will find on pursuing this literature, that certain of the Ruefli limitations have been overcome in alternative algorithms.