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Evaluation of simple methods for regional mortality forecasts

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 an...

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Autor principal: Wilson, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6182339/
https://www.ncbi.nlm.nih.gov/pubmed/30363781
http://dx.doi.org/10.1186/s41118-018-0040-z
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author Wilson, Tom
author_facet Wilson, Tom
author_sort Wilson, Tom
collection PubMed
description 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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spelling pubmed-61823392018-10-22 Evaluation of simple methods for regional mortality forecasts Wilson, Tom Genus Original Article 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. Springer International Publishing 2018-09-27 2018 /pmc/articles/PMC6182339/ /pubmed/30363781 http://dx.doi.org/10.1186/s41118-018-0040-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Wilson, Tom
Evaluation of simple methods for regional mortality forecasts
title Evaluation of simple methods for regional mortality forecasts
title_full Evaluation of simple methods for regional mortality forecasts
title_fullStr Evaluation of simple methods for regional mortality forecasts
title_full_unstemmed Evaluation of simple methods for regional mortality forecasts
title_short Evaluation of simple methods for regional mortality forecasts
title_sort evaluation of simple methods for regional mortality forecasts
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6182339/
https://www.ncbi.nlm.nih.gov/pubmed/30363781
http://dx.doi.org/10.1186/s41118-018-0040-z
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