A nested copula duration model for competing risks with multiple spells

Simon M.S. Lo; Ennon Mammen; Ralf Wilke

doi:10.1016/j.csda.2020.106986

A nested copula duration model for competing risks with multiple spells

Simon M.S. Lo, Ennon Mammen, Ralf Wilke^*

^*Corresponding author for this work

Department of Economics and Finance

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

14 Citations (Scopus)

Abstract

A copula graphic estimator for the competing risks duration model with multiple spells is presented. By adopting a nested copula structure the dependencies between risks and spells are modelled separately. This breaks up an implicit restriction of popular duration models such as multivariate mixed proportional hazards. It is shown that the dependence structure between spells is identiable and can be estimated, in contrast to the dependence structure between competing risks. Thus, by allowing these two components to differ, the model is not identiable. This is an important nding related to the general identiability of competing risks models. Various features of the model are investigated by simulations and its practicality is illustrated by an application to unemployment duration data.

Original language	English
Article number	106986
Journal	Computational Statistics and Data Analysis
Volume	150
Online published	25 Apr 2020
DOIs	https://doi.org/10.1016/j.csda.2020.106986
Publication status	Published - Oct 2020

Research Keywords

Nested archimedean copula
Multiple occurrences
Frailty

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10.1016/j.csda.2020.106986

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title = "A nested copula duration model for competing risks with multiple spells",

abstract = "A copula graphic estimator for the competing risks duration model with multiple spells is presented. By adopting a nested copula structure the dependencies between risks and spells are modelled separately. This breaks up an implicit restriction of popular duration models such as multivariate mixed proportional hazards. It is shown that the dependence structure between spells is identiable and can be estimated, in contrast to the dependence structure between competing risks. Thus, by allowing these two components to differ, the model is not identiable. This is an important nding related to the general identiability of competing risks models. Various features of the model are investigated by simulations and its practicality is illustrated by an application to unemployment duration data.",

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AU - Lo, Simon M.S.

AU - Mammen, Ennon

AU - Wilke, Ralf

PY - 2020/10

Y1 - 2020/10

N2 - A copula graphic estimator for the competing risks duration model with multiple spells is presented. By adopting a nested copula structure the dependencies between risks and spells are modelled separately. This breaks up an implicit restriction of popular duration models such as multivariate mixed proportional hazards. It is shown that the dependence structure between spells is identiable and can be estimated, in contrast to the dependence structure between competing risks. Thus, by allowing these two components to differ, the model is not identiable. This is an important nding related to the general identiability of competing risks models. Various features of the model are investigated by simulations and its practicality is illustrated by an application to unemployment duration data.

AB - A copula graphic estimator for the competing risks duration model with multiple spells is presented. By adopting a nested copula structure the dependencies between risks and spells are modelled separately. This breaks up an implicit restriction of popular duration models such as multivariate mixed proportional hazards. It is shown that the dependence structure between spells is identiable and can be estimated, in contrast to the dependence structure between competing risks. Thus, by allowing these two components to differ, the model is not identiable. This is an important nding related to the general identiability of competing risks models. Various features of the model are investigated by simulations and its practicality is illustrated by an application to unemployment duration data.

KW - Nested archimedean copula

KW - Multiple occurrences

KW - Frailty

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DO - 10.1016/j.csda.2020.106986

M3 - RGC 21 - Publication in refereed journal

SN - 0167-9473

VL - 150

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

M1 - 106986

ER -

A nested copula duration model for competing risks with multiple spells

Abstract

Research Keywords

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