Simple time trend variables in factor demand models can be statistically powerful variables, but may tell the researcher very little. Even more complex specification of technical change, e.g. factor biased, are still the economentrician's measure of ignorance'' about the shifts that occur in the...

The effectiveness of SO{sub 2} emission allowance trading under Title 4 of the 1990 Amendments to the Clean Air Act (CAA) is of great interest due to the innovative nature of this market incentive approach. However, it may be a mistake to frame the compliance problem for a utility as a decision...

The objectives of this project are to support the DOE direct coal liquefaction process development program and to improve the useful application of analytical chemistry to direct coal liquefaction process development. Independent analyses by well-established methods will be obtained of samples...

The development of an approximate-reasoning (AR)-based model to analyze pretreatment options for high-level waste is presented. AR methods are used to emulate the processes used by experts in arriving at a judgment. In this paper, the authors first consider two specific issues in applying AR to...

Environmental radiological assessments rely heavily on the use of mathematical models. The predictions of these models are inherently uncertain because these models are inexact representations of real systems. The major sources of this uncertainty are related to biases in model formulation and...

To compensate for the potential for overly conservative estimates of risk using standard US Environmental Protection Agency methods, an uncertainty analysis should be performed as an integral part of each risk assessment. Uncertainty analyses allow one to obtain quantitative results in the form...

This paper addresses problems of calibration and estimation of a parameter, p{sub o}, in high level neutron coincidence counting (HLNC) measurement. The presentation begins with a deductive approach, based on the generally accepted physical equations which are satisfied by the total and...

Measurement error modeling is a statistical approach to the estimation of unknown model parameters which takes into account the measurement errors in all of the data. Approaches which ignore the measurement errors in so-called independent variables may yield inferior estimates of unknown model...

The DSD method for modeling propagating detonation is based on three elements: (1) a subscale theory of multi-dimensional detonation that treats the detonation as a front whose dynamics depends only on metrics of the front (such as curvature, etc.), (2) high-resolution, direct numerical...

A comparison of ten models for computing the cost of hydrothermal energy is presented. This comparison involved a detailed examination of a number of technical and economic parameters of the various quantitative models with the objective of identifying the most important parameters in the...