Point and interval forecasts of age-specific life expectancies: A model averaging approach

Han Lin Shang

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: Any improvement in the forecast accuracy of life expectancy would be beneficial for policy decision regarding the allocation of current and future resources. In this paper, I revisit some methods for forecasting age-specific life expectancies. Objective: This paper proposes a model averaging approach to produce accurate point forecasts of age-specific life expectancies. Methods: Illustrated by data from fourteen developed countries, we compare point and interval forecasts among ten principal component methods, two random walk methods, and two univariate time-series methods. Results: Based on averaged one-step-ahead and ten-step-ahead forecast errors, random walk with drift and Lee-Miller methods are the two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, the Hyndman-Ullah methods generally provide more accurate interval forecasts than the Lee-Carter methods. However, the Hyndman-Ullah methods produce wider half-widths of prediction interval than the Lee-Carter methods. Conclusions: Model averaging approach should be considered to produce more accurate point forecasts. Comments: This study is a sequel to another Demographic Research paper by Shang, Booth and Hyndman (2011), in which the authors compared the principal component methods for forecasting age-specific mortality rates and life expectancy at birth.
Original languageEnglish
Pages (from-to)593 - 644
Number of pages52
JournalDemographic Research
Volume27
DOIs
Publication statusPublished - 2012

Cite this

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title = "Point and interval forecasts of age-specific life expectancies: A model averaging approach",
abstract = "Background: Any improvement in the forecast accuracy of life expectancy would be beneficial for policy decision regarding the allocation of current and future resources. In this paper, I revisit some methods for forecasting age-specific life expectancies. Objective: This paper proposes a model averaging approach to produce accurate point forecasts of age-specific life expectancies. Methods: Illustrated by data from fourteen developed countries, we compare point and interval forecasts among ten principal component methods, two random walk methods, and two univariate time-series methods. Results: Based on averaged one-step-ahead and ten-step-ahead forecast errors, random walk with drift and Lee-Miller methods are the two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, the Hyndman-Ullah methods generally provide more accurate interval forecasts than the Lee-Carter methods. However, the Hyndman-Ullah methods produce wider half-widths of prediction interval than the Lee-Carter methods. Conclusions: Model averaging approach should be considered to produce more accurate point forecasts. Comments: This study is a sequel to another Demographic Research paper by Shang, Booth and Hyndman (2011), in which the authors compared the principal component methods for forecasting age-specific mortality rates and life expectancy at birth.",
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Point and interval forecasts of age-specific life expectancies: A model averaging approach. / Shang, Han Lin.

In: Demographic Research, Vol. 27, 2012, p. 593 - 644.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Point and interval forecasts of age-specific life expectancies: A model averaging approach

AU - Shang, Han Lin

PY - 2012

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N2 - Background: Any improvement in the forecast accuracy of life expectancy would be beneficial for policy decision regarding the allocation of current and future resources. In this paper, I revisit some methods for forecasting age-specific life expectancies. Objective: This paper proposes a model averaging approach to produce accurate point forecasts of age-specific life expectancies. Methods: Illustrated by data from fourteen developed countries, we compare point and interval forecasts among ten principal component methods, two random walk methods, and two univariate time-series methods. Results: Based on averaged one-step-ahead and ten-step-ahead forecast errors, random walk with drift and Lee-Miller methods are the two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, the Hyndman-Ullah methods generally provide more accurate interval forecasts than the Lee-Carter methods. However, the Hyndman-Ullah methods produce wider half-widths of prediction interval than the Lee-Carter methods. Conclusions: Model averaging approach should be considered to produce more accurate point forecasts. Comments: This study is a sequel to another Demographic Research paper by Shang, Booth and Hyndman (2011), in which the authors compared the principal component methods for forecasting age-specific mortality rates and life expectancy at birth.

AB - Background: Any improvement in the forecast accuracy of life expectancy would be beneficial for policy decision regarding the allocation of current and future resources. In this paper, I revisit some methods for forecasting age-specific life expectancies. Objective: This paper proposes a model averaging approach to produce accurate point forecasts of age-specific life expectancies. Methods: Illustrated by data from fourteen developed countries, we compare point and interval forecasts among ten principal component methods, two random walk methods, and two univariate time-series methods. Results: Based on averaged one-step-ahead and ten-step-ahead forecast errors, random walk with drift and Lee-Miller methods are the two most accurate methods for producing point forecasts. By combining their forecasts, point forecast accuracy is improved. As measured by averaged coverage probability deviance, the Hyndman-Ullah methods generally provide more accurate interval forecasts than the Lee-Carter methods. However, the Hyndman-Ullah methods produce wider half-widths of prediction interval than the Lee-Carter methods. Conclusions: Model averaging approach should be considered to produce more accurate point forecasts. Comments: This study is a sequel to another Demographic Research paper by Shang, Booth and Hyndman (2011), in which the authors compared the principal component methods for forecasting age-specific mortality rates and life expectancy at birth.

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