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Evaluation of simple methods for regional mortality forecasts.

Tom Wilson1

  • 1Northern Institute, Charles Darwin University, Darwin, NT 0909 Australia.

Genus
|October 27, 2018
PubMed
Summary

Evaluating regional mortality forecasting methods is crucial for accurate population predictions. Simple methods like Broad Age SMR Scaling offer a good balance of ease and accuracy for demographers.

Keywords:
AustraliaEvaluationForecast errorMortality forecastRegionsSmoothness Index

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Area of Science:

  • Demography
  • Population Studies
  • Public Health

Background:

  • Existing mortality forecasting research primarily focuses on national populations.
  • Subnational (regional and local) mortality forecasting requires more dedicated attention for planning and service delivery.

Purpose of the Study:

  • To evaluate eight relatively simple regional mortality forecasting methods.
  • To assess methods based on criteria relevant to practicing demographers in government and business.

Main Methods:

  • Retrospective mortality rate forecasts generated for 88 Australian regions (2006-2016).
  • Evaluation based on data requirements, ease of calculation, assumption setting, plausibility, smoothness of age profiles, and accuracy.

Main Results:

  • Two methods (National Death Rates, SMR Scaling) showed higher forecast errors.
  • Five methods were similar in suitability; Broad Age SMR Scaling and Broad Age Rate Ratio Scaling were easiest to implement.
  • Brass Relational and Mortality Surface offered smooth age profiles and plausible rates but were more complex.

Conclusions:

  • Method choice significantly impacts regional population forecast accuracy.
  • Plausibility and ease of implementation are critical factors alongside accuracy in selecting forecasting methods.