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Validating Allocation Functions in Energy Models: An Experimental Methodology

V. Kerry Smith and Lawrence J. Hill

Year: 1985
Volume: Volume 6
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol6-No4-4
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Abstract:
In the late 1970s, the Energy Information Administration initiated a program calling for review and evaluation of its data and validation of energy models used in support of the policymaking process. One of the more controversial aspects of this program was the effort to validate the large-scale energy models developed under DOE auspices and, in some cases, still under development. As all participants in this process (i.e., modelers and evaluators) acknowledge, there is no absolute standard by which a model can be validated. By definition, a model is an approximation to some real-world process. It abstracts from the complexities of the process but is intended to capture essential dimensions of the forces governing outcomes of that process. Consequently, all evaluations of a model involve judgment. To illustrate the prospects for divergent yet individually sensible judgments of an energy model, consider a recent appraisal of the Regional Demand Forecasting Model (RDFOR).



Validating Allocation Functions in Energy Models: A Comment

David B. Reister

Year: 1987
Volume: Volume 8
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol8-No1-11
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Abstract:
In their recent paper, Smith and Hill (1985) perform a numerical experiment to compare three allocation functions: translog, logistic, and probabilistic. They found that the logistic function was generally better than the other two alternatives and that the probabilistic function was distinctly inferior to other methods in nearly all experiments. They observe that the probabilistic function has wide application in energy models and hope that their paper may dampen the enthusiasm for the probabilistic function.





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