A regression model for the copula graphic estimator

Simon M.S. LO, Ralf A. WILKE

Research output: Journal PublicationsJournal Article (refereed)peer-review

6 Citations (Scopus)


We suggest a pragmatic extension of the non-parametric copula-graphic estimator to a depending competing risks model with covariates. Our model is an attractive empirical approach for practitioners in many disciplines as it does not require knowledge of the marginal distributions. Although non-observable and only set-identifiable in most applications, classical duration models typically impose ad-hoc assumptions on their functional forms. Instead of directly estimating these distributions, we suggest a plug-in regression framework which utilises an estimator for the observable cumulative incidence curves which specification can be visually inspected. We perform simulations and estimate an unemployment duration model to demonstrate the advantages of our model compared to classical duration models such as the Cox proportional hazard model.
Original languageEnglish
Pages (from-to)21 - 46
Number of pages26
JournalJournal of Econometric Methods
Issue number1
Early online date5 Sept 2013
Publication statusPublished - Jan 2014

Bibliographical note

We thank Jason Abrevaya and two reviewers for their helpful comments. Wilke is supported by the Economic and Social Research Council through the Bounds for Competing Risks Duration Models using Administrative Unemployment Duration Data (RES-061-25-0059) grant.


  • Archimedean copula
  • dependent censoring
  • partial identification


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