The dependence structure in mortality data cannot be ignored in projecting future trends, in particular for a group of similar populations characterized by common long-run relationships. We propose a new multifactor model for capturing common and specific features of the trend over time. We implement the model and investigate its impact on actuarial valuations, through the introduction of the concept of the dependency premium.

The dependency premium based on a Multifactor Model for dependent mortality data / D'Amato, Valeria; Haberman, Steven; Piscopo, Gabriella. - In: COMMUNICATIONS IN STATISTICS. THEORY AND METHODS. - ISSN 0361-0926. - 48:1(2019), pp. 50-61. [10.1080/03610926.2017.1366523]

The dependency premium based on a Multifactor Model for dependent mortality data

D'amato, Valeria;Piscopo, Gabriella
2019

Abstract

The dependence structure in mortality data cannot be ignored in projecting future trends, in particular for a group of similar populations characterized by common long-run relationships. We propose a new multifactor model for capturing common and specific features of the trend over time. We implement the model and investigate its impact on actuarial valuations, through the introduction of the concept of the dependency premium.
2019
The dependency premium based on a Multifactor Model for dependent mortality data / D'Amato, Valeria; Haberman, Steven; Piscopo, Gabriella. - In: COMMUNICATIONS IN STATISTICS. THEORY AND METHODS. - ISSN 0361-0926. - 48:1(2019), pp. 50-61. [10.1080/03610926.2017.1366523]
File in questo prodotto:
File Dimensione Formato  
CIS2017.pdf

non disponibili

Tipologia: Versione Editoriale (PDF)
Licenza: Accesso privato/ristretto
Dimensione 1.19 MB
Formato Adobe PDF
1.19 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/695110
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact