National Academies Press: OpenBook
Suggested Citation:"CONCLUSIONS." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers. Washington, DC: The National Academies Press. doi: 10.17226/1853.
Page 325

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EVALUATING THE ACCURACY OF U.S. POPULATION PROJECTION MODELS 325 It would be useful to have a more explicit definition of “reasonable” so that users can determine the degree of confidence to place in the range of estimates. CONCLUSIONS In Chapter 3 of Volume I, several recommendations were advanced for policy agencies that supply projections about future events. How do official U.S. population projections measure up in light of these recommendations? The first recommendation (3–9) relates to the need to prepare information about the levels and sources of uncertainty in the projections. Those who make population projections do a good job of reporting on the sources of error (baseline population, fertility, mortality, and migration), but they fail to make explicit the level of uncertainty surrounding each input component. Recommendation 3–11 concerns the need for ongoing error analysis and validation tests. The Census Bureau routinely reports on the accuracy of past projections as a guide to users of its published figures. The bureau has also carried out more comprehensive analyses (see Long [1987], for example). The SSA, to our knowledge, has not conducted any external validations of its projections. A third recommendation (3–14) suggests that in presenting results to decision makers, agencies should report estimates of uncertainty regarding model output. Providing high, middle, and low alternatives is helpful in this regard, but as already noted there is a need to inform users of the level of uncertainty regarding the alternatives. In two other recommendations (3–12 and 3–13), Volume I argues for the need to document the model's analytical structure and make the models comprehensible and reproducible. The Census Bureau and the SSA do a good job of describing the techniques used to make the projections. The projections can easily be reestimated with different assumptions at some later time. However, there is a subjective component to the choice of inputs that cannot be reproduced in future analyses. This chapter describes the basic methodology for making cohort component population projections. This methodology, which is used by the Census Bureau and the SSA, requires four inputs: a baseline population and assumptions regarding future fertility, mortality, and migration. We illustrate how several aspects of the future population depend on these assumptions and conclude that projections of the population under age 5 are affected most by the fertility assumptions, whereas the population over age 75 is affected most by the mortality assumptions, at least for the first 75 years beyond the base year. Using the median projections made by the Census Bureau and the SSA, we compared projections of total population size with actual population outcomes. The success of past performance has been determined largely by the time at which the projections were made. Projections prior to the mid-1950s tended to be too low; projections from the mid-1950s to around 1970 were too high; and projections since 1970 have come quite close to actual outcomes, albeit

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This volume, second in the series, provides essential background material for policy analysts, researchers, statisticians, and others interested in the application of microsimulation techniques to develop estimates of the costs and population impacts of proposed changes in government policies ranging from welfare to retirement income to health care to taxes.

The material spans data inputs to models, design and computer implementation of models, validation of model outputs, and model documentation.

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