A copula duration model with dependent states and spells

A nested Archimedean copula model for dependent states and spells is introduced and the link to a classical survival model with frailties is established. The model relaxes an important restriction of classical survival models as unobservable heterogeneities are permitted to be correlated with the observable covariates. Its modular structure has practical advantages as the different components can be separately specified and estimation can be done sequentially or separately. This makes the model versatile and adaptable in empirical work. An application to labour market transitions with linked administrative data supports the need for a flexible specification of the dependence structure and the model for the marginal survivals. The conventional Markov Chain Model is shown to give sizeably biased results in the application.

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Publication Details

Journal
Computational Statistics & Data Analysis
Published
2024-11-28
DOI
https://doi.org/10.1016/j.csda.2024.108104
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
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article

A copula duration model with dependent states and spells

Simon Lo, Shuolin Shi, Ralf A. Wilke
Computational Statistics & Data Analysis
Financial Risk and Volatility Modeling
article

A copula duration model with dependent states and spells

Simon Lo, Shuolin Shi, Ralf A. Wilke
article en

Abstract

A nested Archimedean copula model for dependent states and spells is introduced and the link to a classical survival model with frailties is established. The model relaxes an important restriction of classical survival models as unobservable heterogeneities are permitted to be correlated with the observable covariates. Its modular structure has practical advantages as the different components can be separately specified and estimation can be done sequentially or separately. This makes the model versatile and adaptable in empirical work. An application to labour market transitions with linked administrative data supports the need for a flexible specification of the dependence structure and the model for the marginal survivals. The conventional Markov Chain Model is shown to give sizeably biased results in the application.

Computational Statistics & Data AnalysisVol. 204
Copenhagen Business School (DK)
Openalex Percentile: Top 71%
Financial Risk and Volatility Modeling
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A copula duration model with dependent states and spells — Simon Lo, Shuolin Shi, et al. · Computational Statistics & Data Analysis (2024) | TGRS Research Map | TGRS