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A Regression Model for the Copula Graphic Estimator


Simon Lo


Lingnan University, Hong Kong Institute of Business Studies

Ralf A. Wilke


University of York (UK); Center for European Economic Research (ZEW); Policy Studies Institute (PSI)

April 30, 2011

Nottingham School of Economics Discussion Paper No. 11-04

Abstract:     
We consider a dependent competing risks model with many risks and many covariates. We show identifiability of the marginal distributions of latent variables for a given dependence structure. Instead of directly estimating these distributions, we suggest a plug-in regression framework for the Copula-Graphic estimator which utilizes a consistent estimator for the cumulative incidence curves. Our model is an attractive empirical approach as it does not require knowledge of the marginal distributions which are typically unknown in applications. We illustrate the applicability of our approach with the help of a parametric unemployment duration model with an unknown dependence structure. We construct identification bounds for the marginal distributions and partial effects in response to covariate changes. The bounds for the partial effects are surprisingly tight and often reveal the direction of the covariate effect.

Number of Pages in PDF File: 24

Keywords: archimedean copula, dependent censoring

JEL Classification: C14, C24, C41

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Date posted: June 6, 2011  

Suggested Citation

Lo, Simon and Wilke, Ralf A., A Regression Model for the Copula Graphic Estimator (April 30, 2011). Nottingham School of Economics Discussion Paper No. 11-04. Available at SSRN: http://ssrn.com/abstract=1858645 or http://dx.doi.org/10.2139/ssrn.1858645

Contact Information

Simon Lo
Lingnan University, Hong Kong Institute of Business Studies ( email )
Hong Kong
Ralf A. Wilke (Contact Author)
University of York (UK) ( email )
Department of Economics and Related Studies
Heslington, York YO10 5DD
United Kingdom
Center for European Economic Research (ZEW) ( email )
P.O. Box 10 34 43
L 7,1 D-68161 Mannheim
Germany
Policy Studies Institute (PSI) ( email )
London NW1 3SR
United Kingdom
Feedback to SSRN (Beta)


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