Robert E. Markland

Modeling demographic-employment interactions in an urban economy

This paper describes a simulation model of the economy of the St. Louis Standard Metropolitan Statistical Area. The model focuses on the opera tion of the areas labor market. It uses (a) an age-specific regimen for predicting changes in population and (b) the concept that the areas unemployment level is inversely related to the areas exports. The validity of the model is tested by setting its initial conditions to the 1960 values of the vari ables in the model and running it forward to 1970. The resultant errors are then analyzed and, with two exceptions, found to be small. The exceptions are analyzed and hypotheses to explain them are outlined. The authors conclude that the model should be useful in finding the key areas in the local economy and in experimenting with economic policies to assess the long-term impact of alternate policies on the local economy. A systematic simulation study is then designed, and approximately 100 runs are made. Analysis of these runs indicates (a) that the transportation-equipment industry is the key industry in the area and (b) that increasing its growth rate by 2 percent annually over the USA national average for that industry, combined with a 0.1 decrease in the relative cost ratio (compared to the national average) of labor in the durable-fabrication area, would have a very marked effect in reducing unem ployment in the St. Louis area.

Computerized regional planning for land disposal of wastewater

Abstract This paper describes the development and utilization of a large scale mixed integer programming model for regional planning of land disposal of wastewater within the St. Louis Metropolitan Statistical area. This model is derived, and used to determine which land disposal sites should serve which treatment plants, when initial construction should be initiated and completed, and when capacity expansion should occur. Consideration is given to relevant construction and operating costs for land sites and transmission arteries, land acquisition costs, tangible benefits from land use, controls on pollution of aquifers, and various other engineering and technical constraints. The computational aspects of the models use are emphasized in the paper, and extensive test results are presented and discussed.

An application of mathematical programming to soybean processing

In this paper, a mathematical programming methodology is applied to a production planning problem involving a soybean processing plant which can purchase its raw materials from multiple origins and must ship its finished products to multiple destinations. A time horizon production planning model is developed, with the objective of maximizing the net income produced by this plant. This model is tested for a five origin, three destination, processing network, over a thirteen month time horizon. Test results, in terms of a production plan and associated purchasing-allocation decisions, are presented and discussed.

Analyzing commodity market trading strategies within a corporate environment

Abstract Improvement of the planning of commodity purchases remains a formidable problem in many agri-business firms. This paper addresses this problem within the corn purchasing environment of a large American food company. A time-horizon simulation model is developed for testing various commodity purchasing plans. The model is used to analyze interactions between various hedging strategies, profit-taking rules, and stop-loss rules, over an extended time period, under simulated market conditions. Extensive test results are presented and discussed.

A risk-return simulation model of commodity market hedging strategies

The American food processing industry is characterized by a vast array of products, which are produced in large quantities at relatively low unit costs. The principal component of the unit cost for these food products is their raw material (usually a basic grain commodity) constituent. Consequently, most food processing companies are greatly concerned with the prices they pay for their raw materials, and as the prices of these raw materials change, the typical food processing companys profits may be greatly affected. Since most companies prefer a steady growth rate, these raw material price fluctuations must be counter-balanced by other strategic or operating decisions. One basic set of decisions which is utilized to overcome raw materials price fluctuations involves the established commodity trading markets. The operation of the commodity futures markets allows food processors to determine what prices they will pay for their raw materials over the production horizon. However, since a number of futures options may exist for each commodity, the inherent risk of price fluctuation remains with the processor, as some manufacturers may buy their supply of the commodity at significantly lower prices than others and reflect this difference in the price of the finished product. The research described in this paper was conducted within the commodity market trading environment of a major American agri-business firm. The objective of the study was the development of a risk-return simulation model which could be used for testing commodity market hedging strategies in both cash and futures markets. The model was developed under general assumptions for the basic commodity, corn, and included a market price change simulation subsystem, a hedging strategy testing subsystem, and a risk return measurement subsystem. The simulation model was tested over a multi-period time horizon for a series of commodity market hedging strategies, and extensive test results are presented.

Regional economic analysis: A systems dynamics approach

Abstract This paper describes the development, validation, testing, and utilization of a systems dynamics model of the stagnating economy of the St. Louis Metropolitan Area. The model focuses on the operation of the areas labor market and uses an age-specific regimen for predicting changes in population, and the concept that the areas unemployment level is inversely related to its exports. The validity of the model is tested by setting its initial conditions to the 1960 values of its variables and running the model forward to 1970. Testing and utilization has involved a series of policy action simulations designed to determine what set of conditions might lead to improvement in the regional economy during the period 1975–2000. Extensive test results from application of the model are presented, and the implications of the various policy actions are discussed.