scholarly journals Dependence modeling of multivariate longitudinal hybrid insurance data with dropout

2021 ◽  
pp. 115552
Author(s):  
Edward W. Frees ◽  
Catalina Bolancé ◽  
Montserrat Guillen ◽  
Emiliano A. Valdez
Crisis ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 217-223 ◽  
Author(s):  
Paul Yip ◽  
David Pitt ◽  
Yan Wang ◽  
Xueyuan Wu ◽  
Ray Watson ◽  
...  

Background: We study the impact of suicide-exclusion periods, common in life insurance policies in Australia, on suicide and accidental death rates for life-insured individuals. If a life-insured individual dies by suicide during the period of suicide exclusion, commonly 13 months, the sum insured is not paid. Aims: We examine whether a suicide-exclusion period affects the timing of suicides. We also analyze whether accidental deaths are more prevalent during the suicide-exclusion period as life-insured individuals disguise their death by suicide. We assess the relationship between the insured sum and suicidal death rates. Methods: Crude and age-standardized rates of suicide, accidental death, and overall death, split by duration since the insured first bought their insurance policy, were computed. Results: There were significantly fewer suicides and no significant spike in the number of accidental deaths in the exclusion period for Australian life insurance data. More suicides, however, were detected for the first 2 years after the exclusion period. Higher insured sums are associated with higher rates of suicide. Conclusions: Adverse selection in Australian life insurance is exacerbated by including a suicide-exclusion period. Extension of the suicide-exclusion period to 3 years may prevent some “insurance-induced” suicides – a rationale for this conclusion is given.


2020 ◽  
Vol 19 (3) ◽  
pp. 268-277
Author(s):  
YoonDeok Han ◽  
◽  
Sunghyeon Jung ◽  
Kwang-tae Ha ◽  
Seung-Mi Kwon ◽  
...  

2011 ◽  
Vol 14 (1) ◽  
pp. 3-40
Author(s):  
Sandra Gaisser ◽  
Christoph Memmel ◽  
Rafael Schmidt ◽  
Carsten Wehn

2016 ◽  
Author(s):  
César L. C. Mattos ◽  
Amauri H. Souza Júnior ◽  
Ajalmar R. Rocha Neto ◽  
Guilherme A. Barreto ◽  
Ronaldo F. Ramos ◽  
...  

2017 ◽  
Vol 6 (3) ◽  
pp. 43
Author(s):  
Nikolai Kolev ◽  
Jayme Pinto

The dependence structure between 756 prices for futures on crude oil and natural gas traded on NYMEX is analyzed  using  a combination of novel time-series and copula tools.  We model the log-returns on each commodity individually by Generalized Autoregressive Score models and account for dependence between them by fitting various copulas to corresponding  error terms. Our basic assumption is that the dependence structure may vary over time, but the ratio between the joint distribution of error terms and the product of marginal distributions (e.g., Sibuya's dependence function) remains the same, being time-invariant.  By performing conventional goodness-of-fit tests, we select the best copula, being member of the currently  introduced class of  Sibuya-type copulas.


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