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A diagnostic test for specification of copulas under censorship

Author

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  • Juan Lin
  • Ximing Wu

Abstract

We propose a copula specification test for copula-based multivariate survival models under censorship. This flexible test is applicable to both Archimedean and non-Archimedean copulas and provides useful pointers for alternative copula construction when a null distribution is rejected. It is shown to be consistent and asymptotically distribution free. We demonstrate its good finite sample performance via Monte Carlo simulations. We apply this test to an insurance dataset on losses and expenses. Our test rejects the hypothesis of Gaussian copula. Furthermore, its diagnostic information suggests an alternative copula specification that captures the extreme-value dependence exhibited in the data.

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  • Juan Lin & Ximing Wu, 2020. "A diagnostic test for specification of copulas under censorship," Econometric Reviews, Taylor & Francis Journals, vol. 39(9), pages 930-946, October.
    • Handle: RePEc:taf:emetrv:v:39:y:2020:i:9:p:930-946
    DOI: 10.1080/07474938.2020.1721834
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    Cited by:

    1. Tao Sun & Yu Cheng & Ying Ding, 2023. "An information ratio‐based goodness‐of‐fit test for copula models on censored data," Biometrics, The International Biometric Society, vol. 79(3), pages 1713-1725, September.

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