A single risk approach to the semiparametric competing risks model with parametric Archimedean risk dependence

Simon M.S. Lo; Ralf A. Wilke

doi:10.1016/j.jmva.2023.105276

A single risk approach to the semiparametric competing risks model with parametric Archimedean risk dependence

Simon M.S. Lo, Ralf A. Wilke

Economics and Finance - (CBE)

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This paper considers a dependent competing risks model with the distribution of one risk being a semiparametric proportional hazards model, whereas the model for the other risks and the degree of risk dependence of an Archimedean copula are unknown. Identifiability is shown when there is at least one covariate with at least two values. Estimation is done by means of a n-consistent semiparametric two-step procedure. Applicability and attractive finite sample performance are demonstrated with the help of simulations. An application to unemployment duration confirms the importance of estimating rather than assuming risk dependence.

Original language	English
Article number	105276
Journal	Journal of Multivariate Analysis
Volume	201
DOIs	https://doi.org/10.1016/j.jmva.2023.105276
Publication status	Published - May 2024

Keywords

Archimedean copula
Depending censoring
Identifiability

ASJC Scopus subject areas

Statistics and Probability
Numerical Analysis
Statistics, Probability and Uncertainty

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jmva.2023.105276

Cite this

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N2 - This paper considers a dependent competing risks model with the distribution of one risk being a semiparametric proportional hazards model, whereas the model for the other risks and the degree of risk dependence of an Archimedean copula are unknown. Identifiability is shown when there is at least one covariate with at least two values. Estimation is done by means of a n-consistent semiparametric two-step procedure. Applicability and attractive finite sample performance are demonstrated with the help of simulations. An application to unemployment duration confirms the importance of estimating rather than assuming risk dependence.

AB - This paper considers a dependent competing risks model with the distribution of one risk being a semiparametric proportional hazards model, whereas the model for the other risks and the degree of risk dependence of an Archimedean copula are unknown. Identifiability is shown when there is at least one covariate with at least two values. Estimation is done by means of a n-consistent semiparametric two-step procedure. Applicability and attractive finite sample performance are demonstrated with the help of simulations. An application to unemployment duration confirms the importance of estimating rather than assuming risk dependence.

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KW - Depending censoring

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A single risk approach to the semiparametric competing risks model with parametric Archimedean risk dependence

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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