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A Regression Model for the Copula-Graphic Estimator

Author

Listed:
  • Lo Simon M.S.

    (Lingnan University, SEK 208, Simon and Eleanor Kwok Building, Lingnan University, Hong Kong)

  • Wilke Ralf A.

    (Department of Economics, University of York, Hesslingtom, York YO10 5DD, UK)

Abstract

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.

Suggested Citation

  • Lo Simon M.S. & Wilke Ralf A., 2014. "A Regression Model for the Copula-Graphic Estimator," Journal of Econometric Methods, De Gruyter, vol. 3(1), pages 21-46, January.
    • Handle: RePEc:bpj:jecome:v:3:y:2014:i:1:p:21-46:n:1
    DOI: 10.1515/jem-2012-0016
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    References listed on IDEAS

    as
    1. McCall, Brian P, 1996. "Unemployment Insurance Rules, Joblessness, and Part-Time Work," Econometrica, Econometric Society, vol. 64(3), pages 647-682, May.
    2. Simon M. S. Lo & Ralf A. Wilke, 2010. "A copula model for dependent competing risks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 359-376, March.
    3. Yi‐Hau Chen, 2010. "Semiparametric marginal regression analysis for dependent competing risks under an assumed copula," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 235-251, March.
    4. Simon M.S. Lo & Ralf A. Wilke, 2011. "Identifiability and estimation of the sign of a covariate effect in the competing risks model," Discussion Papers 11/03, University of Nottingham, School of Economics.
    5. Rivest, Louis-Paul & Wells, Martin T., 2001. "A Martingale Approach to the Copula-Graphic Estimator for the Survival Function under Dependent Censoring," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 138-155, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Lo, Simon M.S. & Stephan, Gesine & Wilke, Ralf, 2012. "Estimating the Latent Effect of Unemployment Benefits on Unemployment Duration," IZA Discussion Papers 6650, Institute of Labor Economics (IZA).
    2. Melanie Arntz & Simon Lo & Ralf Wilke, 2014. "Bounds analysis of competing risks: a non-parametric evaluation of the effect of unemployment benefits on migration," Empirical Economics, Springer, vol. 46(1), pages 199-228, February.
    3. Lo, Simon M.S. & Wilke, Ralf A. & Emura, Takeshi, 2024. "A semiparametric model for the cause-specific hazard under risk proportionality," Computational Statistics & Data Analysis, Elsevier, vol. 195(C).

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    More about this item

    Keywords

    Archimedean copula; dependent censoring; partial identification; JEL Code: C24; C41;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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