Many popular estimators for duration models require independent competing risks or independent censoring. In contrast, copula-based estimators are also consistent in the presence of dependent competing risks. We suggest a computationally convenient extension of the copula graphic estimator to a model with more than two dependent competing risks. We analyse the applicability of this estimator by means of simulations and unemployment duration data from Germany. We obtain evidence that our estimator yields nice results if the dependence structure is known and that it is a powerful tool for the assessment of the relevance of (in-)dependence assumptions in applied duration research.
|Number of pages||18|
|Journal||Journal of the Royal Statistical Society. Series C: Applied Statistics|
|Publication status||Published - 1 Jan 2010|
- Archimedean copula
- Dependent censoring
- Duration of unemployment