A long-term care multi-state Markov model revisited : a Markov chain Monte Carlo approach

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      <subfield code="a">Fleischmann, Anselm</subfield>
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      <subfield code="a">A long-term care multi-state Markov model revisited</subfield>
      <subfield code="b">: a Markov chain Monte Carlo approach</subfield>
      <subfield code="c">Anselm Fleischmann, Jonas Hirz, Daniel Sirianni</subfield>
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      <subfield code="a">A multi-state Markov model is calibrated to Austrian data on recipients of long-term care payments the amount of which depends on defined frailty state levels. In contrast to a predecessor paper by one of the authors (see Fleischmann in Eur Actuar J 5(2):327354, 2015), we are able to allow for different mortality intensities for different frailty states. A correction term is introduced in the mortality intensities' functional representation to deal with observed mortality humps around the retirement age for certain frailty levels. Parameter calibration is done using MCMC methods (adaptive MetropolisHastings-within-Gibbs). The results reveal a considerably better fit of refined to raw prevalence units than the original model of Fleischmann (Eur Actuar J 5(2):327354, 2015). Finally, the results are used to estimate the remaining healthy lifetime for certain ages, indicating slight but significant increases over the last 4 years.

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      <subfield code="a">Simulación Monte Carlo</subfield>
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      <subfield code="a">Modelo de Markov</subfield>
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      <subfield code="a">Hirz, Jonas</subfield>
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      <subfield code="g">06/06/2022 Volúmen 12 - Número 1 - junio 2022 , p. 215-247</subfield>
      <subfield code="t">European Actuarial Journal</subfield>
      <subfield code="d">Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</subfield>
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