Francis P. McCamley

Evaluating Environmental Risks Using Safety-First Constraints

This article incorporates an upper partial moment concept into a linear programming model to impose safety-first environmental constraints. The model is linear and deterministic, treats a discrete sample as an empirical distribution, and optimizes over the column space. It allows a decision maker to specify the objectives and the compliance probabilities with the objectives when making decisions, and endogenously determines the risk levels. Even though it is presented in the context of environmental management, the model is general enough to be extended to other situations where the probability of a variable exceeding some target or standard is restricted. Copyright 2001, Oxford University Press.

Describing and Identifying the Complete Set of Target MOTAD Solutions

For some Target MOTAD applications, only enterprise mixtures associated with a single target level are of interest. However, in most cases knowledge of other Target MOTAD enterprise mixtures provides useful information. The complete set of Target MOTAD enterprise mixtures is the union of a finite number of closed convex subsets. It can be identified by parametric programming. For well-behaved problems, only two parameters, target income level (T) and expected deviations (λ), need to be varied to identify the set of Target MOTAD mixtures. Data from a problem by Hazell are used to illustrate this technique.

Energy-Related Input Demand by Crop Producers

This study uses expected income variance (E-V) analysis to examine the effect of alternative energy and crop prices on the energy consumed (directly and indirectly) by risk-averse Missouri crop producers. Expressing fuels, chemicals, and fertilizers in terms of their BTU equivalents allows aggregating these energy-related inputs. Energy demand functions are estimated from the solutions associated with many price and risk-aversion coefficient combinations. Quadratic approximations of the energy demand functions are presented. For input and output price levels close to those prevailing in Missouri in the recent past, energy demand by crop producers is moderately responsive to changes in energy price levels. Energy consumption elasticities with respect to crop prices are generally larger than those with respect to energy price. Increases in maize and sorghum prices increase energy demand, but increases in soyabeans and wheat prices decrease it. As degree of risk aversion decreases, energy demand increases

A method for estimating the sampling variances of multipliers derived from a from-to model

Interindustry models provide a) a simple, logical, and internally consistent way of portraying the interdependent structure of a region and b) an analytic framework which can be used to provide answers to a wide variety of questions. Many of these answers can be expressed as easily understood multipliers, but because the persons for whom these multipliers are most useful possess only limited understanding of the underlying model, they are often forced to accept (or reject) them on faith. In many cases it should be possible to supply these users with some indication of the reliability of estimated multipliers. Many factors affect reliability and these factors are not equally measurable. This paper has the limited objective of estimating that component of multiplier variance induced by the use of sample data to construct the basic model. The procedure adopted exploits a first order approximation technique. It is applied to the data used to construct a from-to model of Oklahoma Planning Region 9. Selected limitations and implications of the resulting estimates are examined.

Incorporating Risk Considerations into the Estimation of Demand for Diesel Fuel by Crop Producers

A quadratic programming model was formulated to estimate diesel fuel demand by a representative risk averse crop producer. Data to estimate the demand function were obtained by varying energy prices, crop prices, and degree of risk aversion. Diesel fuel demand was not very responsive to energy price changes. Wheat and soybean prices as well as producers attitude toward risk had greater impacts on fuel use than did energy prices. Increases in soybean and sorghum prices tended to increase diesel fuel use while increases in wheat prices and degree of risk aversion decreased diesel fuel use.