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<br />2-1 <br /> <br /> <br />~ #. '.,4') 41;' ~l <br /> <br />'~", ",,:,~ ". <br /> <br />SECTION 2.0 <br />PRICE PROJECTION METHODOLOGIES <br /> <br />Numerous methodologies have. been used in recent years to project <br />prices of energy commodities. Often price projections have been linked to <br />energy production/consumption projections, usually as inputs to drive the <br />energy demand calculations. Generally, the various methodologies fall <br />into three broad categories--judgment, mathematical models, and historical <br />trend analysis. Within each category, the methodologies can have a wide <br />range of complexity as is briefly discussed in the following paragraphs. <br /> <br />2.1 JUDGMENT <br />Professional judgment is the informed opinion of experts in the area <br />of interest. This method lacks the sophistication and apparent precision <br />of mathematical and modeling or trend projections; however, it has the <br />virtue of simplicity and is frequently a good short-range forecasting <br />method. <br />A recent development which utilizes the judgement of a group of <br />informed individuals is the "Delphi" technique. This method, in its full- <br />est development, in\iolves surveying the individuals together with provid- <br />ing them survey feedback and educational materials. In this way, a <br />concensus is produced through controlled iterations of the survey/feedback <br />process. <br />All judgmental FlPproaches are, however, more appropriate for near- <br />term projections, since it is difficult for the experts to stand back from <br />the present. 1 That' is, such forecasts tend to be highly subjective. <br /> <br />2.2 MATHEMATICAl- MODELS <br />Mathematical mqdels are algebraic descriptions of economic systems <br />and include several basic types: econometric, input-output (I/O), engi- <br />neering economic, or game theoretic models.2 Although each of these can <br />be used separately ro some extent, recently developed models such as the <br />SRI energy/technology/price forecasting model and the Energy Information <br />