Evaluation of simple methods for regional mortality forecasts

Tom Wilson

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    Abstract

    Background: In recent decades, considerable research effort has been dedicated to improving mortality forecasting methods. While making valuable contributions to the literature, the bulk of this research has focused on national populations—yet much planning and service delivery occurs at regional and local scales. More attention needs to be paid to subnational mortality forecasting methods.

    Objective: The objective of this study was to evaluate eight fairly simple methods of regional mortality forecasting, focusing specifically on the requirements of practising demographers in government and business.

    Data and methods: Data were sourced primarily from the Australian Bureau of Statistics. Retrospective mortality rate forecasts were produced for 88 regions of Australia for 2006–2016. Regional mortality forecast methods were evaluated on the basis of (i) input data requirements, (ii) ease of calculation, (iii) ease of assumption setting and scenario creation, (iv) plausibility of forecast death rates, (v) smoothness of forecast mortality age profiles, and (vi) forecast accuracy.

    Results:
    Two of the methods produced noticeably higher forecast errors than the others (National Death Rates and SMR Scaling). Five of the methods were judged to be similar in their overall suitability. Two were particularly easy to implement (Broad Age SMR Scaling and Broad Age Rate Ratio Scaling) and provide a good return on the data and effort required. Two others (Brass Relational and Mortality Surface) produced very smooth mortality age profiles and highly plausible death rates, though were relatively more complex to implement.

    Conclusion: The choice of mortality forecasting method is important for the accuracy of regional population forecasts. But considerations additional to accuracy are important, including those relating to the plausibility of the forecasts and the ease of implementation.
    Original languageEnglish
    Article number14
    Pages (from-to)1-22
    Number of pages22
    JournalGenus: journal of population studies
    Volume74
    Issue number1
    DOIs
    Publication statusPublished - 27 Sep 2018

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    mortality
    evaluation
    death rate
    scaling
    statistics
    scenario
    planning

    Cite this

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    title = "Evaluation of simple methods for regional mortality forecasts",
    abstract = "Background: In recent decades, considerable research effort has been dedicated to improving mortality forecasting methods. While making valuable contributions to the literature, the bulk of this research has focused on national populations—yet much planning and service delivery occurs at regional and local scales. More attention needs to be paid to subnational mortality forecasting methods.Objective: The objective of this study was to evaluate eight fairly simple methods of regional mortality forecasting, focusing specifically on the requirements of practising demographers in government and business.Data and methods: Data were sourced primarily from the Australian Bureau of Statistics. Retrospective mortality rate forecasts were produced for 88 regions of Australia for 2006–2016. Regional mortality forecast methods were evaluated on the basis of (i) input data requirements, (ii) ease of calculation, (iii) ease of assumption setting and scenario creation, (iv) plausibility of forecast death rates, (v) smoothness of forecast mortality age profiles, and (vi) forecast accuracy.Results: Two of the methods produced noticeably higher forecast errors than the others (National Death Rates and SMR Scaling). Five of the methods were judged to be similar in their overall suitability. Two were particularly easy to implement (Broad Age SMR Scaling and Broad Age Rate Ratio Scaling) and provide a good return on the data and effort required. Two others (Brass Relational and Mortality Surface) produced very smooth mortality age profiles and highly plausible death rates, though were relatively more complex to implement.Conclusion: The choice of mortality forecasting method is important for the accuracy of regional population forecasts. But considerations additional to accuracy are important, including those relating to the plausibility of the forecasts and the ease of implementation.",
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    Evaluation of simple methods for regional mortality forecasts. / Wilson, Tom.

    In: Genus: journal of population studies, Vol. 74, No. 1, 14, 27.09.2018, p. 1-22.

    Research output: Contribution to journalArticleResearchpeer-review

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    N2 - Background: In recent decades, considerable research effort has been dedicated to improving mortality forecasting methods. While making valuable contributions to the literature, the bulk of this research has focused on national populations—yet much planning and service delivery occurs at regional and local scales. More attention needs to be paid to subnational mortality forecasting methods.Objective: The objective of this study was to evaluate eight fairly simple methods of regional mortality forecasting, focusing specifically on the requirements of practising demographers in government and business.Data and methods: Data were sourced primarily from the Australian Bureau of Statistics. Retrospective mortality rate forecasts were produced for 88 regions of Australia for 2006–2016. Regional mortality forecast methods were evaluated on the basis of (i) input data requirements, (ii) ease of calculation, (iii) ease of assumption setting and scenario creation, (iv) plausibility of forecast death rates, (v) smoothness of forecast mortality age profiles, and (vi) forecast accuracy.Results: Two of the methods produced noticeably higher forecast errors than the others (National Death Rates and SMR Scaling). Five of the methods were judged to be similar in their overall suitability. Two were particularly easy to implement (Broad Age SMR Scaling and Broad Age Rate Ratio Scaling) and provide a good return on the data and effort required. Two others (Brass Relational and Mortality Surface) produced very smooth mortality age profiles and highly plausible death rates, though were relatively more complex to implement.Conclusion: The choice of mortality forecasting method is important for the accuracy of regional population forecasts. But considerations additional to accuracy are important, including those relating to the plausibility of the forecasts and the ease of implementation.

    AB - Background: In recent decades, considerable research effort has been dedicated to improving mortality forecasting methods. While making valuable contributions to the literature, the bulk of this research has focused on national populations—yet much planning and service delivery occurs at regional and local scales. More attention needs to be paid to subnational mortality forecasting methods.Objective: The objective of this study was to evaluate eight fairly simple methods of regional mortality forecasting, focusing specifically on the requirements of practising demographers in government and business.Data and methods: Data were sourced primarily from the Australian Bureau of Statistics. Retrospective mortality rate forecasts were produced for 88 regions of Australia for 2006–2016. Regional mortality forecast methods were evaluated on the basis of (i) input data requirements, (ii) ease of calculation, (iii) ease of assumption setting and scenario creation, (iv) plausibility of forecast death rates, (v) smoothness of forecast mortality age profiles, and (vi) forecast accuracy.Results: Two of the methods produced noticeably higher forecast errors than the others (National Death Rates and SMR Scaling). Five of the methods were judged to be similar in their overall suitability. Two were particularly easy to implement (Broad Age SMR Scaling and Broad Age Rate Ratio Scaling) and provide a good return on the data and effort required. Two others (Brass Relational and Mortality Surface) produced very smooth mortality age profiles and highly plausible death rates, though were relatively more complex to implement.Conclusion: The choice of mortality forecasting method is important for the accuracy of regional population forecasts. But considerations additional to accuracy are important, including those relating to the plausibility of the forecasts and the ease of implementation.

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