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Systematic mortality improvement trends and mortality heterogeneity : insights from individual-level HRS data

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<titleInfo>
<title>Systematic mortality improvement trends and mortality heterogeneity</title>
<subTitle>: insights from individual-level HRS data</subTitle>
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<name type="personal" usage="primary" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20190009515">
<namePart>Xu, Mengyi</namePart>
<nameIdentifier>MAPA20190009515</nameIdentifier>
</name>
<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080179083">
<namePart>Sherris, Michael</namePart>
<nameIdentifier>MAPA20080179083</nameIdentifier>
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<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20130014067">
<namePart>Meyricke, Ramona</namePart>
<nameIdentifier>MAPA20130014067</nameIdentifier>
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<genre authority="marcgt">periodical</genre>
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<place>
<placeTerm type="code" authority="marccountry">usa</placeTerm>
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<dateIssued encoding="marc">2019</dateIssued>
<issuance>serial</issuance>
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<language>
<languageTerm type="code" authority="iso639-2b">eng</languageTerm>
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<extent>24 p. </extent>
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<abstract displayLabel="Summary">Providers of life annuities and pensions need to consider both systematic mortality improvement trends and mortality heterogeneity. Although how mortality improvement varies with age and gender at the population level is well studied, how trends vary with risk factors remains relatively unexplored. This article assesses how systematic mortality improvement trends vary with individual risk characteristics using individual-level longitudinal data from the U.S. Health and Retirement Study between 1994 and 2009. Initially a Lee-Carter model is used to assess mortality improvement trends by grouping individuals with similar risk characteristics of gender, education, and race. We then fit a longitudinal mortality model to individual-level data allowing for heterogeneity and time trends in individual-level risk factors. Our results show how survey data can provide valuable insights into both mortality heterogeneity and improvement trends more effectively than commonly used aggregate models. We show how mortality improvement differs across individuals with different risk factors. Significantly, at an individual level, mortality improvement trends have been driven by changes in health history such as high blood pressure, cancer, and heart problems rather than risk factors such as education, marital status, body mass index, and smoker status.</abstract>
<note type="statement of responsibility">Mengyi Xu, Michael Sherris, Ramona Meyricke</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20120019492">
<topic>Tendencias</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555306">
<topic>Mortalidad</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20100065273">
<topic>Modelo Lee-Carter</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080604394">
<topic>Valoración de riesgos</topic>
</subject>
<classification authority="">6</classification>
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<titleInfo>
<title>North American actuarial journal</title>
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<originInfo>
<publisher>Schaumburg : Society of Actuaries, 1997-</publisher>
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<identifier type="issn">1092-0277</identifier>
<identifier type="local">MAP20077000239</identifier>
<part>
<text>03/06/2019 Tomo 23 Número 2 - 2019 , p. 197-219</text>
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<recordCreationDate encoding="marc">190708</recordCreationDate>
<recordChangeDate encoding="iso8601">20190715150856.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20190021111</recordIdentifier>
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<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
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