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Population Forecasting

  • Dennis A. Ahlburg
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 30)

Abstract

Population forecasters have paid too little attention to forecast accuracy, uncertainty, and approaches other than the cohort-component method. They should track forecast errors and use them to adjust forecasts. They have chosen measures of forecast accuracy arbitrarily, with the result that flawed error measures are widely used in population forecasting. An examination of past forecasts would help establish what approaches are most accurate in particular applications and under what circumstances. Researchers have found that alternative approaches to population forecasting, including econometric models and extrapolation, provide more accurate forecasts than the cohort-component method in at least some situations. If they can determine the conditions under which these approaches are best, they can use them instead of the established method or in combination with it.

Methodological advances have made it possible to produce population forecasts with a greater degree of disaggregation and decomposition than before. If this decomposition allows a better understanding of the causal forces underlying population change, then decomposition may improve forecast accuracy. Even if disaggregation and decomposition do not improve overall forecast accuracy, they may lead to improved understanding or accurate forecasts of important components of the population, such as the elderly widowed population. Uncertainty has not been well-integrated into population forecasts. Researchers are pushing ahead in three main areas: population forecasts that include probability distributions; combining expert judgment and statistical methods; and the specification of situations that provide an internally consistent forecast of the population under particular circumstances. Evidence suggests that relying on experts to choose the fertility and mortality assumptions of the forecast has done little to improve forecast accuracy, but this is probably because expert opinion has been obtained in an unstructured way. Experience in other areas of forecasting has shown how to use experts to improve forecast accuracy.

Keywords

Accuracy combining disaggregation experts population projection uncertainty 

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Dennis A. Ahlburg
    • 1
    • 2
  1. 1.Carlson School of ManagementUniversity of MinnesotaUSA
  2. 2.Department of Social StatisticsUniversity of SouthamptonUK

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