Forecasting Australian subnational age-specific mortality rates.

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Authors: Han Lin Shang and Yang Yang
Date: Mar. 2021
From: Journal of Population Research(Vol. 38, Issue 1)
Publisher: Springer
Document Type: Report; Brief article
Length: 171 words

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Abstract :

Keywords: Multivariate functional principal component analysis; Hierarchical/grouped time series; Forecast reconciliation; Australian regional mortality rates Abstract When modeling sub-national mortality rates, it is important to incorporate any possible correlation among sub-populations to improve forecast accuracy. Moreover, forecasts at the sub-national level should aggregate consistently across the forecasts at the national level. In this study, we apply a grouped multivariate functional time series to forecast Australian regional and remote age-specific mortality rates and reconcile forecasts in a group structure using various methods. Our proposed method compares favorably to a grouped univariate functional time series forecasting method by comparing one-step-ahead to five-step-ahead point forecast accuracy. Thus, we demonstrate that joint modeling of sub-populations with similar mortality patterns can improve point forecast accuracy. Author Affiliation: (1) Department of Actuarial Studies and Business Analytics, Macquarie University, Level 7, 4 Eastern Rd, 2109, Sydney, NSW, Australia (2) Research School of Finance, Actuarial Studies and Statistics, Australian National University, 2601, Canberra, ACT, Australia (a) hanlin.shang@mq.edu.au Article History: Registration Date: 10/22/2020 Accepted Date: 10/22/2020 Online Date: 11/09/2020 Byline:

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Gale Document Number: GALE|A655010455