Forecasting Demand and Supply of Doctoral Scientists and Engineers Report of a Workshop on Methodology (2000) / Chapter Skim
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5 Presentation of Uncertainty and Use of Forecasts with Explicit Uncertainty
5 Presentation of Uncertainty and Use of Forecasts with Explicit Uncertainty
Pages 37-48
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From page 37... ...
Increasing the span the level of aggregation over occupations typically increases forecast accuracy because random errors and movements between the occupations in the aggregate are averaged out. However, this may not be the case if increasing span Increases heterogeneity, and the forecasting model is not successful in representing the effects of this heterogeneity.
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From page 38... ...
For short-term models, the uncertainty of point estimates can be measured by the mean squared error, in which forecasted values are compared with actual observations. Other measures of uncertainty include the confidence interval and mean absolute percentage error.
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From page 39... ...
Figure 5-1 shows the historical trend in natural gas wellhead prices and forecasts future prices with a reference case and two additional scenarios. The scenarios reflect changes that might happen in the forecast depending on the assumptions made on how rapidly new technology penetrates the 39
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From page 40... ...
Sometimes scenarios are constructed from statistical confidence bounds on model inputs or parameters, such as confidence limits on the future economic growth rate. Users can be misled, however, if they interpret the resulting scenarios as confidence bounds, as neither future paths nor forecasts at particular dates need be contained between "high" and "low" scenarios with any degree of confidence.
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From page 41... ...
The Annual Energy Outlook 1997 addressed electricity restructuring by incorporating the Federal Energy Regulatory Commission actions on open access, lower costs for natural gas-fired generation plants, and early retirements of higher-cost fossil plants. The Annual Every Outlook 1998 makes additional assumptions about competitive pricing and restructuring, including: · Lower operation and maintenance costs.
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From page 42... ...
These include economic growth both in the United States and elsewhere in the world, technology growth, defense needs, wars, and the demographics of scientists and engineers. We are reasonably good at describing the overall 5.5 demographics of the population, but scientists and engineers are a special group that is affected by things that we are not good at predicting, such as labor force participation and immigration.
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From page 43... ...
These areas of uncertainty include attitudes of college students toward science, plans of the scientists or engineers for shifting from scientific work to other tasks such as administration, and attitudes toward retirement. The fourth source of uncertainty is the most serious and the hardest to convey to forecast users what economists call parameter uncertainty (also called systematic errors)
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From page 44... ...
We recognize that the labor market for scientists and engineers is not a classic spot market in which workers offer their labor in response to a wage offer by employers and higher wage offers immediately bring forth a supply of additional workers. Were it so, the demand for labor by government and industry would be quickly met by a supply of scientists and engineers and the market would clear easily.
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From page 45... ...
Usually this final measure is destabilizing, since institutions have difficulty expanding or contracting faculty size in the short term. A distinction should be made between the instruments of policy control (e.g., enrollment quotas)
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From page 46... ...
This helps agencies to fine-tune the questions and tailor the responses to address agency goals. Perhaps the forecasting community could conduct cognitive studies on how best to present a forecast's usefulness and accuracy.
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From page 47... ...
A forecast of college enrollment for 18-21 year olds, however, is likely to be conditional, since it depends on rates of high school completion and college participation that are uncertain and may depend on variables outside the pure demographic model, e.g., job prospects for high school graduates and availability of financial aid.
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From page 48... ...
· Finally, forecasters need to conduct research into methods of displaying uncertainty of forecasts. The goal is to discover the most convincing ways to display forecast results so the audience understands that forecasting models are a useful tool in the policy formation process, but have limitations in accuracy that affect how they should be interpreted and used.
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