Forecasting multiple functional time series in a group structure : an application to mortality

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      <subfield code="a">Lin Shang, Han</subfield>
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      <subfield code="a">Forecasting multiple functional time series in a group structure</subfield>
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      <subfield code="a">When modelling subnational mortality rates, we should consider three features: How to incorporate any possible correlation among subpopulations to potentially improve forecast accuracy through multi-population joint modelling; How to reconcile subnational mortality forecasts so that they aggregate adequately across various levels of a group structure; Among the forecast reconciliation methods, how to combine their forecasts to achieve improved forecast accuracy. To address these issues, we introduce an extension of grouped univariate functional time-series method. We first consider a multivariate functional time-series method to jointly forecast multiple related series. We then evaluate the impact and benefit of using forecast combinations among the forecast reconciliation methods. Using the Japanese regional age-specific mortality rates, we investigate 115-step-ahead point and interval forecast accuracies of our proposed extension and make recommendations.</subfield>
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      <subfield code="g">01/05/2020 Volumen 50 Número 2 - mayo 2020 , p. 357-379</subfield>
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