A. N. Halter

The Value of Frost Forecasting: A Bayesian Appraisal

The economic value of frost forecasts is estimated under various assumptions concerning prior information, accuracy of forecasts, and the shape of the orchard operators utility functions. The frost protection decision process is simulated in the context of Bayesian decision making under uncertainty. The averaged seasonal values estimated per day per acre were

Use of Simulation in Evaluating Management Policies under Uncertainty: Application to a Large Scale Ranch

5.39 for frost forecasts provided by the U.S. Weather Service,

A Macro-Economic Model for Agricultural Sector Analysis

8.57 for perfect frost forecasts,

Simulation of Nigerian Development: Northern Region Model

4.73 for profit maximizers, and

Simulating a Developing Agricultural Economy: Methodology and Planning Capability

191.39 for completely ignorant decision makers. The methodology used has general application to determination of economic value of information under conditions of uncertainty.

Systems-Simulation in a Practical Policy-Making Setting: The Venezuelan Cattle Industry

Price and weather environment and decision-making processes are simulated for a large California range-feedlot operation; then DYNAMO programming is used to write the equations and to obtain the equivalent of 400 years of data by simulations on an electronic computer. Formulation of expectations of prices are the main managerial policies tested in the article, but the technique has broader applications to policies and decision making under uncertainty. A comparison among simulated net incomes is made over the period 1954–1963. It is concluded that relatively naive price forecasting methods are sufficiently accurate for the feeder buying decision considered here.

Computer Simulation as a Planning Tool in Developing Economies

Agricultural sector analyses for purposes of agricultural policy evaluation and planning in developing countries are generally conducted in a partial equilibrium framework without regard to agricultural-nonagricultural interactions. A relatively simple simulation model built on an input-output framework is developed which, in combination with an agricultural sector analysis, enables interactions in the product markets and labor market to be considered. The model is illustrated through linkage with an agricultural simulation model to evaluate alternative agricultural policies in Nigeria. The model also has potential for use with other formal and informal sector analysis techniques.

Grade Utility: A New Noncognitive Factor in Academic Prediction

A multidisciplinary team is currently studying the applicability of computer simulation to problems of agricultural sector development in Nigeria. The program has as one of its major objectives the exploration of simulation as a tool for aiding policy makers of that country concerned with meeting the nutritional needs of the population, generation of foreign exchange earnings and raw material inputs for industrialization, and other important questions relating to long-run development of the agricultural sector and its interaction with nonagricultural development. While the project is localized in a particular country, models are being developed with adaptability to other developing areas of the world as a major objective. To date, a model of the northern region of the country has been developed which will be linked to a southern model currently under construction. The structure of the northern model is described in some detail as an example of the application of simulation to a macroeconomic system. Preliminary tests of this model are discussed and an assessment of the capabilities and limitations of this approach to planning development in emerging countries is given.

Refinements in energy economic modeling for policy purposes

SIMULATION-a systems analysis approachcan provide a comprehensive view of a complex system [3, 5, 7, 9, 10, 11, 16, 17, 24, 29 ]. In development planning we are interested in studying and approximating, via a mathematical model, those relationships within the economy that are important in the development process. By translating this model into a computer language, the likely end results of alternative development schemes can be evaluated through manipulation of the specified computer simulation model. We are interested in exploring this approach to development planning because it might provide a more informed basis for planning development [ 12, 13 ]. The design of development, or planning, is especially important in less developed countries because they usually have comparatively few funds available relative to their apparent needs. Consequently, allocation mistakes appear to have a somewhat greater opportunity cost in terms of human well-being in the underdeveloped setting. Planning in any country is a process fraught with uncertainty. Frequently, there is uncertainty about likely immediate and longer range effects of development strategies. Further, the degree to which policies aimed at one set of economic phenomena may have unintended side effects on other aspects of the society is often uncertain. The paucity of information available for decision making is often cited in developed countries, with even more frequent mention in less developed countries. Poor communication facilities, especially prevalent in LDCs, often impede the accumulation of potentially available relevent information which might otherwise provide a reasonably well-informed basis for decision making. Given these difficulties and uncertainties, let us consider the utility of a systems analysis ap-

Mutual Entropy Interactions Between Growth Patterns of Oregon Counties

Shifting the Venezuelan cattle industry from traditional to modern production is the problem of formulating policy at the federal government level. A systems-simulation model shows the consequences, through time, of the current set of policies and hypothesizes the consequences of other policy alternatives. Validity of the model was established, on the basis of the decision-makers criterion, through a game of hide-and-go-seek. Interaction between the researchers and decision-makers brought together the relevant positive and normative information before a policy was established.