Search

Forecasting mortality for small populations by mixing mortality data

<?xml version="1.0" encoding="UTF-8"?><modsCollection xmlns="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-8.xsd">
<mods version="3.8">
<titleInfo>
<title>Forecasting mortality for small populations by mixing mortality data</title>
</titleInfo>
<name type="personal" usage="primary" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20140002542">
<namePart>Ahcan, Ales</namePart>
<nameIdentifier>MAPA20140002542</nameIdentifier>
</name>
<typeOfResource>text</typeOfResource>
<genre authority="marcgt">periodical</genre>
<originInfo>
<place>
<placeTerm type="code" authority="marccountry">esp</placeTerm>
</place>
<dateIssued encoding="marc">2014</dateIssued>
<issuance>serial</issuance>
</originInfo>
<language>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</language>
<physicalDescription>
<form authority="marcform">print</form>
</physicalDescription>
<abstract displayLabel="Summary">In this paper we address the problem of projecting mortality when data are severely affected by random fluctuations, due in particular to a small sample size, or when data are scanty. Such situations may emerge when dealing with small populations, such as small countries (possibly previously part of a larger country), a specific geographic area of a (large) country, a life annuity portfolio or a pension fund, or when the investigation is restricted to the oldest ages. The critical issues arising from the volatility of data due to the small sample size (especially at the highest ages) may be made worse by missing records; this is the case, for example, of a small country previously part of a larger country, or a specific geographic area of a country, given that in some periods mortality data could have been collected just at an aggregate level.</abstract>
<note type="statement of responsibility">Ales Ahcan, Annamaria Olivieri, Ermanno Pitacco</note>
<classification authority="">6</classification>
<location>
<url displayLabel="MÁS INFORMACIÓN" usage="primary display">mailto:centrodocumentacion@fundacionmapfre.org?subject=Consulta%20de%20una%20publicaci%C3%B3n%20&body=Necesito%20m%C3%A1s%20informaci%C3%B3n%20sobre%20este%20documento%3A%20%0A%0A%5Banote%20aqu%C3%AD%20el%20titulo%20completo%20del%20documento%20del%20que%20desea%20informaci%C3%B3n%20y%20nos%20pondremos%20en%20contacto%20con%20usted%5D%20%0A%0AGracias%20%0A</url>
</location>
<relatedItem type="host">
<titleInfo>
<title>Insurance : mathematics and economics</title>
</titleInfo>
<originInfo>
<publisher>Oxford : Elsevier, 1990-</publisher>
</originInfo>
<identifier type="issn">0167-6687</identifier>
<identifier type="local">MAP20077100574</identifier>
<part>
<text>13/01/2014 Volumen 54 Número 1 - enero 2014 </text>
</part>
</relatedItem>
<recordInfo>
<recordContentSource authority="marcorg">MAP</recordContentSource>
<recordCreationDate encoding="marc">140220</recordCreationDate>
<recordChangeDate encoding="iso8601">20140227133442.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20140006687</recordIdentifier>
<languageOfCataloging>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</languageOfCataloging>
</recordInfo>
</mods>
</modsCollection>