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A simple linear model is constructed for production, use and recycling of various paper and related products. This model is used to estimate the maximum feasible recycling rate given the current state of pulp and paper technology. Parametric linear programming is used to investigate the effect of the efficiency of collecting, sorting and transporting waste paper on the fraction recycled. [ABSTRACT FROM AUTHOR]

Several behavioral scientists have contributed to special issues of the "Decision Science" journal. K. MacCrimmon and J. Siu tackled the significant problem of modeling and measuring and individual decision maker's inevitable trade-offs. The authors find that the choice mode consistently exceeds the equivalence mode in its predictive accuracy. R. Duncan's paper examined possible determinants of the structure of decision units within organization. A. Delbecq studied contextual variables affecting decision making in program planning. Lastly, V. Vroom and A. Jago wrote a paper about decision making as a social process.

The article provides an explanation of sociologist Leo Goodman's paper hierarchical models for significance tests in multivariate contingency tables. In several papers Goodman presents and elaborates a system for the analysis of contingency tables that promises to be extremely useful to sociologists. The papers are however, extremely compressed, heavily complex with the cumbersome notation of contingency analysis and are not easily accessible to the student and average research worker. The aim of this article is to explain the logic and procedures of the system in terms the reader may find more comfortable. The Goodman system consists of two parts: a scheme for making significance tests by means of hierarchical models and an extensive discussion of a set of techniques known as log linear models. The two parts are logically and practically distinct. Among the important uses of hierarchical models are the following: tests for the significance of partial correlations, tests for interactions, where the control variable has as many categories as one pleases, tests for higher-order interactions, succinct statements of what is and what is not going on in a contingency table. Since none of these tools have been easily available to the average sociologist, the Goodman system is well worth learning especially because it provides considerable insight into the properties of cross-classifications and the logic of significance tests.

On the basis of a variety of evidence, including the paper with Professor Harold Watts and a paper by the author, the case for seeking and frequently using disaggregated data seemed strong, but one nagging concern remained. Suppose, as seems likely, the microcomponents exhibit different behaviors. In this case it might not be sensible to pool the data and treat it as a single sample from a single universe. This paper copes directly with this issue, and demonstrates the importance of using disaggregated data even when microcomponents. Instead of using a simulation to study aggregation across components with different behaviors, one could have attempted a mathematical deduction of the effects. In order to do this certain simplifying assumptions would need to be introduced in order to make the problem tractable. Another approach to the problem of aggregation is to use data from the real world to fit models at different levels of aggregation, and then to evaluate the relative worth of these models by means of some quantitative measure.

This paper discusses the theories of and the relationships between the direct and indirect methods of standardizing death rates for males, females, and persons. The author notes that the standardization procedures have two objectives, to eliminate the disturbing influences of varying age and sex distributions, and to provide reliable indications of the overall comparative mortalities of different groups. The author also points out that the Registrar General's methods and publications have always fulfilled the objectives in a thorough and practical manner.

The article presents comments on the management science paper "On Sequencing n Jobs on One Machine to Minimize the Number of Late Jobs," by William L. Maxwell. The paper focused on an integer programming formulation of a one-machine job shop problem. The author contends that Maxwell made in error in proving the validity of an optimal algorithm by applying cutting plane constraints to the problem. The author explains that the problem cannot be solved through traditional cutting plane procedures. The author provides a mathematical model in an attempt to correct the proof.

In a paper in this Journal, Watson (1961) has discussed the use of group screening methods for detecting effective factors. The methods are analogous to those suggested by Doff man (1943) for the medical problem of detecting a rare defect among members of a large population by using pooled blood samples. One step in Watson's derivation of the probability that an effective factor is declared significant is invalid. The purpose of this note is to derive the correct expression for this probability and show how the correction affects the subsequent theory. None of Watson's qualitative statements about the efficiency of group screening methods nor his numerical example are seriously affected. [ABSTRACT FROM AUTHOR]

Econometric model building of the type represented in the Duesenberry-Bosworth paper was at best an attempt to see whether systems of, say more than 25 equations, add much to our knowledge of the economy and the response to policy changes. They have not, I believe, at least to this point, and I am not optimistic about a change in the next few years, instead of commenting on the details of the particular models presented at this session, I will explain some of the reasoning that brings me to that conclusion. Before doing so, let me make clear that my comments are not directed at either "theory" or empirical science. There is very little of either in current econometric practice. I view my comments as a criticism of large models, models of twenty-five or more equations, not as a criticism of modelling or testing economic hypotheses. [ABSTRACT FROM AUTHOR]

This paper has introduced L(W[sub 0], k, A) and R(W[sub 0], k, A) as three-parameter risk measures embodying decisions about a reference level about which deviations are to be measured, the relative importance of small versus large deviations, and the range of deviations that will be included in the risk measure. The popular risk measures of variance, semi-variance, mean absolute deviation, and probability of an outcome worse than some prespecified level are special cases of L(W[sub 0], k, A) and standard deviation is a special case of R(W[sub 0], k, A). These risk measures were shown to differ in their choice of one or more of the parameters W[sub 0], k, and A. It was shown that both L and R are monotone increasing functions of A; however, neither L nor R are necessarily monotone increasing functions of k. Clearly L(W[sub 0], k, A) and R(W[sub 0], k, A), are not the only potentially useful functions of the three decision parameters that have been implicit in the selection of the popular risk measures; they are, however, a rich and fairly general family. Further study of their properties should lead to advances in the theory of risk and specification of criteria for the selection of risk measures. This paper has attempted to establish a foundation for these advances. [ABSTRACT FROM AUTHOR]

The article analyzes economist James Ohlson's paper "Analysis of the Usefulness of Accounting Data for the Portfolio Decision: A Decision-Theory Approach," in order to determine if he's making a model comparison or a model choice. Ohlson's thesis is that he used methods of comparing models, but the author demonstrates the inaccuracies in that thesis. The author tests Ohlson's findings and also considers the portfolio-choice problem and whether the findings are conditional upon the comparison of the forecasting models used.

The purpose of this paper is to make a detailed comparison of three macroeconometric models of the U.S. economy with regard to their predictive ability and policy multiplier properties. Three models are the St. Louis Model, the Wharton Model and the M.P.S. Model. These models are constructed with different emphasis on the treatment of the monetary phenomena, depending upon the philosophy of the model builder. They may respectively be called a monetarist model, a Keynesian-type income-expenditure model, and a structural model which emphasizes the monetary structure for the stabilization policy analysis. The structure of each model is not discussed in this paper but only a brief sketch of their special features is given in the next section. The predictive performance and the policy multiplier analysis are discussed in the 3rd and 4th sections, followed by some concluding remarks. [ABSTRACT FROM AUTHOR]

Many methods have been developed to determine the proper reorder points and order quantities in an inventory system. These methods are based on a wide range of inventory models—from elementary deterministic models to sophisticated probabilistic models with time-varying parameters. This paper deals with two topics related to these calculations which were encountered during the design of an inventory control system for a firm in the heavy goods industry. A mathematical model is developed to describe the average annual variable cost of maintaining the inventory. Based on this model, the paper evaluates the savings obtained by using a simultaneous solution for reorder point and order quantity rather than a simpler separate solution. Then, this model is extended to describe the effect of batch withdrawals as a renewal process. The paper presents an adjustment which can be applied to the original reorder points based on unit withdrawals. Both of these topics are described in the context of a practical application. [ABSTRACT FROM AUTHOR]

The article reports on interest rate risk and discusses the paper "Systematic Interest-Rate Risk in a Two-Index Model of Returns," by Bernell K. Stone. Stone extends the single-factor market model into a two-index model so that he can improve the explanation of the stochastic process which creates security returns. The creation of the two-factor market model is so that the components of systematic or covariance risk not explained by the single model can be examined. The factors of Stone's model are the return on an equity index and the return on a bond index.

The article discusses the abstracts of several papers on economics published in the May 1965 issue of the journal "International Economic Review." The first article "Two Models of the British Economy: A Fragment of a Critical Survey," by Marc Nerlove, represents a portion of survey covering macroeconometric models of the Klein-Tinbergen Variety; that is, model based on time series and fundamentally of a Keynesian nature. The second article of the journal "Innovational Intensity and Factor Bias in the Theory of Growth," by Gustav Ranis and John C.H. Fei, makes a rigorous presentation of some well-known concepts of innovational intensity and bias and demonstrates the existence of a linear relationship between them. The third article is "Some Properties of the Closed Linear Model of Production," by Sidney G. Winter. Four assumptions are typically used to characterize the most general type of closed linear production model: convexity and closedness of the production cone, costless disposal, impossibility of something from nothing, every commodity is producible.

The article discusses problems associated with economic growth at maximal rate. The main purpose of the present article is expository. Drawing where needed on the studies cited, the authors utilize a diagrammatic device that makes it possible to exhibit, in terms of a two-commodity world, the essentials of the model by economist John von Neumann and its maximal growth properties. It is reported that in 1936 von Neumann presented orally, for subsequent publication in an Austrian mathematical periodical little known to economists, a paper that has greatly influenced economic theory up to the present time, and of which all the ramifications have perhaps not yet become fully apparent. Paradoxically, von Neumann's paper shows that for a piece of work to spark several new developments in economic theory, it is not necessary that it have any particular claim to realism in its portrayal of economic life. Subsequent developments have fully vindicated the intuitions that led von Neumann to make these drastic and arbitrary-looking simplifications.

The article presents the author's comments on the paper "On Place Utility and the Normative Allocation of Intraurban Migrants," by L.A. Brown, F.E. Horton and R.L. Wittick, previously published in a 1970 issue of the journal "Demography." He says that throughout the paper the authors have maintained that normative models of migration, which have an identifiable place utility component, may operationalize the concept of place utility. The paper also reiterates, using slightly different formulations, a statement and a model that involves a cost minimizing linear programming allocation of intraurban migrants to vacancies. The dual variables of the problem are interpreted as measures of place utility. However, the interpretation of the dual variables on which the paper is based is contradictory and untenable. The paper assumes origins and destinations containing, respectively, migrants and vacancies. Migrants are allocated to vacancies so as to minimize migration costs subject to the following conditions: one, no more migrants be shipped out of any origin than are available there and two, all vacancies be filled at all destinations.

The article discusses the effects of accounting variations on decision making and the paper "An Experimental Design for Study of Effects of Accounting Variations in Decision Making" by R.E. Jensen. The statistical methodology and design used by Jensen in his research of the effects of alternative accounting reporting techniques in the selection of portfolios and their security evaluation is examined as is the data collection. The limitation of whether or not there was adequate control over the research environment and the probability level of the statistical tests is not known in Jensen's paper because he does not mention these issues.

A conference paper on the impact of monetary policy by testing a structural model with a simultaneous-equation estimation method to evaluate what influence monetary authorities can have through policy. Mathematical models are used that have three different structural equations for the supply function and demand function of balances and a reduced-form income equation. Exogeneity can be used by authorities to meet goals such as changes in the money supply or to adjust interest rates.

This paper presents the Matrix model of organizational analysis and a partial empirical test of its descriptive validity. The model, concerned with the impact of technology and personal discretion on organization structure, offers a series of propositions about task-unit differentiation and integration. Two major propositions provide the focus of the empirical section of this paper: (1) task units become increasingly autonomous from the administrative system as the structural design moves from the Routine to Heuristic organizational strategy; and (2) task unit members become increasingly autonomous from supervision as the structural design moves from Routine to Heuristic. Data from 828 task units generated from 18 attitude survey items are used to test the first proposition; the data support the proposition, and modifications of the model are suggested. [ABSTRACT FROM AUTHOR]

Recent theoretical and empirical work in portfolio theory has exhibited a natural evolution from the two-moment EV model popularized by Markowitz through the higher moment models to selection on the basis of the entire probability function. This latter approach, referred to as the Stochastic Dominance (SD) approach to portfolio selection, has been shown to be theoretically superior to all of the "moment methods" and has been the focus of an increasing volume of empirical work. In comparison with the EV model, however, the SD approach has one potentially significant deficiency from the standpoint of empirical testing. With a given set of portfolios to evaluate, the computer processor time required for the determination of the EV efficient set is quite short. One can calculate and sort means and variances on several hundred portfolios in a matter of seconds. In contrast, the processor time required for the determination of the SD efficient set for the same number of portfolios can be prohibitive. The purpose of this paper is to examine the factors responsible for the relatively time-consuming nature of empirical tests of SD efficiency and to present the major results of our search for efficient algorithms for conducting SD tests. Section I briefly examines the time-consuming nature of the tests for SD efficiency. Section II presents and evaluates; our most efficient algorithms for obtaining true SD efficiency results. Section lit examines an approach that yields approximate SD efficiency results with further reductions in required processor time. [ABSTRACT FROM AUTHOR]

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This paper describes the application of a linear programming model to the process of resource allocation at Illinois State University. The model developed is a general model designed to assist academic administrators in allocating the scarce resources at their disposal. The model, and the assumptions upon which it is based, may be altered to suit the particular decision criteria of any particular academic institution. The linear programming model developed here maximizes an objective function which reflects the total net social profit realized by the university on its outputs to society. This objective function was maximized subject to a myriad of constraints which reflected the limitations of budget, space, and other scarce inputs. Further, the constraints reflect the joint interdependency of many parts of the university and the particular educational delivery system employed by a given department. The outputs of the model include the optimal mixture of academic outputs by the university, the optimal distribution and usage of inputs inside the university, and the shadow price of each input. While the linear programming model developed here is general and may be applied to any university, it was applied to Illinois State University in this paper. In the case of Illinois State University, the model recommended a substantial reduction in emphasis upon teacher education. [ABSTRACT FROM AUTHOR]

This paper studies the linear programming problem in which all coefficients (even those of the stipulations matrix) are rational functions of a single parameter t called ‘time,’ and provides an algorithm that can serve problems of the following two types: (1) Steady-state behavior [the algorithm can be used to determine the functional form x(t) of the optimal solution as a function of t, this form being valid for all ‘sufficiently large’ values of t], and (2) sensitivity analysis [if a value t0 of ‘time’ is given, the algorithm can be used to determine the two possible functional forms of the optimal solution for all values of t ‘sufficiently dose’ to t0 (the first functional form valid for t«t0, the second for t»t0)]. In addition, the paper gives certain qualitative information regarding steady-state behavior, including the following result: If for some one of the properties of consistency, boundedness, or bounded constraint set, there exists a sequence tn↗+∞ such that the linear program at tn has this property for all n, then the program has this property for all ‘sufficiently large’ values of t. [ABSTRACT FROM AUTHOR]