On the Modeling and forecasting of socioeconomic mortality differentials : an application to deprivation and mortality in England

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      <subfield code="a">Villegas, Andres M.</subfield>
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      <subfield code="a">On the Modeling and forecasting of socioeconomic mortality differentials</subfield>
      <subfield code="b">: an application to deprivation and mortality in England</subfield>
      <subfield code="c">Andres M. Villegas, Steven Haberman</subfield>
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      <subfield code="a">In any country, mortality rates and indices such as life expectancy usually differ across subpopulations, for example, defined by gender, geographic area, or socioeconomic variables (e.g., occupation, level of education, or income). These differentials, and in particular those related to socioeconomic circumstances, pose important challenges for the design of public policies for tackling social inequalities, as well as for the design of pension systems and the management of longevity risk in pension funds and annuity portfolios. We discuss the suitability for the modeling and forecasting of socioeconomic differences in mortality of several multiple population extensions of the Lee-Carter model, including a newly introduced relative model based on the modeling of the mortality in socioeconomic subpopulations alongside the mortality of a reference population. Using England mortality data for socioeconomic subpopulations defined using a deprivation index, we show that this new relative model exhibits the best results in terms of goodness of fit and ex post forecasting performance. We then use this model to derive projections of deprivation specific mortality rates and life expectancies at pensioner ages and analyze the impact of socioeconomic differences in mortality on the valuation of annuities.</subfield>
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      <subfield code="t">North American actuarial journal</subfield>
      <subfield code="d">Schaumburg : Society of Actuaries, 1997-</subfield>
      <subfield code="x">1092-0277</subfield>
      <subfield code="g">03/02/2014 Tomo 18 Número 1 - 2014 </subfield>
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