Ryuzo Sato, Tetsunori Koizumi; Substitutability, Complementarity and the Theory of Derived Demand1, The Review of Economic Studies, Volume 37, Issue 1, 1 Januar

Markowitz's [2] portfolio selection model was originally concerned with financial investments, but the model's implications for capital budgeting are now well recognized. Markowitz's basic idea is that the optimal portfolio for an investor is not simply any collection of good securities, but a balanced whole, providing the investor with the best combination of “return” and “risk.” Return and risk are to be measured by the expected value and variance of the probability distribution of portfolio return. Although financial writers have generally accepted Markowitz's measure of return, they have not been completely satisfied with his suggested measure of risk [1]. In fact, Markowitz himself had reservations about choosing variance as a measure of risk.1 Besides variance, he considered five other alternative measures of risk:(1) The expected value of loss;(2) The probability of loss;(3) The expected absolute deviation;(4) The maximum expected loss; and(5) The semivariance.

Variables and their scores, 648. — Validation procedures, 649. — Conclusions, 650.

The exact sampling distributions of estimators of structural parameters of econometric models are unknown except for a few simple cases. In this situation two alternative approaches towards evaluating finite sample properties of various estimators have been adopted in the literature: (i) Monte Carlo experiments, and (ii) the approach pioneered by Nagar and his students in which the sampling error of an estimator is expressed as the sum of an infinite series of random variables, successive terms of which are of decreasing order of sample size in probability. It is claimed that the small sample properties of the estimator under consideration can be approximated by those of the first few terms of such an infinite series. This paper shows through examples that the Nagar approach can be misleading in the sense that it can yield an estimate for finite sample bias that differs from the true finite sample bias to the same order of sample size. And it can yield estimates of bias which are finite (infinite) while the true bias is infinite (finite). The paper also draws attention to some of the pitfalls to be avoided in studying the properties of an infinite sequence of random variables.

Journal Article The Effect of Demand on Prices in British Manufacturing: Another View Get access B. T. McCallum B. T. McCallum University of Virginia Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 37, Issue 1, January 1970, Pages 147–156, https://doi.org/10.2307/2296504 Published: 01 January 1970 Article history Received: 01 October 1968 Accepted: 01 May 1969 Published: 01 January 1970

The various aspects of cost provide the conceptual core of management accounting. Incremental cost and opportunity cost are particularly important concepts, since they provide the foundations for the accountant's contribution to decision-making. The article sets out to test the validity of the two concepts. It says that there seem to be some confusion as to the precise meaning of the terms incremental and opportunity cost. The confusion exists in the literature of management accounting, managerial economics, and pure economics. The article suggests that a definition, using systems terminology, can help to clarify the meaning of the two terms. It defines incremental cost as the sum of the opportunity costs of the inputs to a system, each input being used independently of other inputs. Opportunity cost is defined as the revenue sacrificed by not implementing the next best alternative output from the resources making up a system. It is seen that incremental cost provides a floor to opportunity cost. The task of measuring opportunity cost is synonymous with the task of maximizing the profit from the use of the resources under a firm's control. The accountant cannot be expected to tackle this problem alone.

Since its inception, accounting has had a dependency relationship with other disciplines. Accounting education has developed, as a part of business administration and therefore, this has been the intellectual environment within which accounting thought has been incubated. The importance of this environmental setting can be seen by looking at the contributions to accounting theory of Australian academicians who are usually much more a part of economics departments than of schools of business as compared to the United States. This environmental factor is important in looking ahead to future developments in accounting theory. Four developments in business administration promise significant changes for the environment within which accounting theory will be developed and research will be carried on. Business administration has changed from an emphasis on description of business practice to a more analytical discipline where great attention is given to the underlying concepts and real attempts are being made to construct the practical models. The underlying basic discipline of Economics, which has been the primary base for theoretical models in the past, has been partially supplanted by the behavioral sciences, and it has been supplemented by greater attention to mathematical models. The economic goals, which were implicitly, or explicitly the almost exclusive objectives of business administration have been expanded to include broad society goals. The study of business administration is being expanded to a general study of administration for all types of organizations.