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Why population forecasts should be probabilistic - illustrated by the case of Norway

Author

Listed:
  • Nico Keilman

    (Universitetet i Oslo)

  • Dinh Quang Pham

    (Statistisk sentralbyrå (Statistics Norway))

  • Arve Hetland

    (Statistisk sentralbyrå (Statistics Norway))

Abstract

Deterministic population forecasts do not give an appropriate indication of forecast uncertainty. Forecasts should be probabilistic, rather than deterministic, so that their expected accuracy can be assessed. We review three main methods to compute probabilistic forecasts, namely time series extrapolation, analysis of historical forecast errors, and expert judgement. We illustrate, by the case of Norway up to 2050, how elements of these three methods can be combined when computing prediction intervals for a population’s future size and age-sex composition. We show the relative importance for prediction intervals of various sources of variance, and compare our results with those of the official population forecast computed by Statistics Norway.

Suggested Citation

  • Nico Keilman & Dinh Quang Pham & Arve Hetland, 2002. "Why population forecasts should be probabilistic - illustrated by the case of Norway," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(15), pages 409-454.
    • Handle: RePEc:dem:demres:v:6:y:2002:i:15
    DOI: 10.4054/DemRes.2002.6.15
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    forecasting; uncertainty; cohort-component method; forecast errors; simulation; stochastic population forecast; time series;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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