Multi-population mortality modelling and forecasting : a hierarchical credibility regression approach

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<title>Multi-population mortality modelling and forecasting</title>
<subTitle>: a hierarchical credibility regression approach</subTitle>
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<name type="personal" usage="primary" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20220002219">
<namePart>Bozikas, Apostolos</namePart>
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<namePart>Pitselis, Georgios</namePart>
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<dateIssued encoding="marc">2021</dateIssued>
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<abstract displayLabel="Summary">This paper proposes a multi-level hierarchical credibility regression approach to model multi-population mortality data. Future mortality rates are derived using extrapolation techniques, while the forecasting performances between the proposed model, the original LeeCarter model and two LeeCarter extensions for multiple populations are compared for both genders of three northern European countries with small populations (Ireland, Norway, Finland). Empirical illustrations show that the proposed method produces more accurate forecasts than the LeeCarter model and its multi-population extensions.

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<note type="statement of responsibility">Apostolos Bozikas, Georgios Pitselis </note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555306">
<topic>Mortalidad</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20100065273">
<topic>Modelo Lee-Carter</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080608880">
<topic>Técnicas cuantitativas</topic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080637927">
<geographic>Irlanda</geographic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080637941">
<geographic>Noruega</geographic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080638177">
<geographic>Finlandia</geographic>
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<title>European Actuarial Journal</title>
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<publisher>Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</publisher>
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<identifier type="local">MAP20220007085</identifier>
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<text>07/06/2021 Volúmen 11 - Número 1 - junio 2021 , p. 231-267</text>
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