Bivariate phase-type distributions for experience rating in disability insurance
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<title>Bivariate phase-type distributions for experience rating in disability insurance</title>
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<namePart>Sørensen, Jacob Juhl</namePart>
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<namePart>Yslas, Jorge</namePart>
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<abstract displayLabel="Summary">The article develops advanced mixed Poisson regression models applied to experience rating in disability insurance. It introduces hierarchical gamma distributions and multivariate phase-type distributions to model heterogeneity and dependence between disability and recovery rates. Estimation algorithms based on EM and ECM are presented, together with a simulation study comparing the predictive performance of the different approaches. The results show that phase-type models offer greater flexibility and improved predictive performance, especially when complex dependencies exist between latent group effects</abstract>
<note type="statement of responsibility">Christian Furrer, Jacob Juhl Sørensen and Jorge Yslas</note>
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<topic>Seguro de incapacidad</topic>
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<topic>Tarificación</topic>
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<topic>Modelos actuariales</topic>
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<topic>Riesgo aleatorio</topic>
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<topic>Rendimiento</topic>
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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>13/04/2026 Número 16 issue 1 - abril 2026 , 37 p.</text>
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