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Conditional Moment Tests for Parametric Duration Models

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  • James E. Prieger

    (Department of Economics, University of California Davis)

Abstract

This paper develops and compares specification tests for parametric duration models estimated with censored data. The tests are based on generalized residuals (the integrated hazard), which is exponentially distributed if the model is correctly specified. I present several conditional moment tests based on the generalized residuals: a raw moments test, a test based on Laguerre polynomials, and a Lagrange multiplier (LM) test. The LM test extends Lancasterâ??s (1985) test by allowing an arbitrarily precise approximation of the likelihood under the alternative. The raw moments test implemented via an auxiliary regression is examined using both asymptotic and bootstrap critical values. Monte Carlo evidence indicates that no one test dominates the others in all situations in terms of size, power, and ease of use. When the data are not censored, the Laguerre test appears to be the best choice. When there is censoring in the data, the Laguerre test is still at least as powerful as the other tests, but the raw moment test may be more convenient to perform. For the convenience of the practitioner the explicit forms of the tests for exponential and Weibull duration models are presented.

Suggested Citation

  • James E. Prieger, 2003. "Conditional Moment Tests for Parametric Duration Models," Working Papers 246, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:246
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    Cited by:

    1. Cho, Jin Seo & White, Halbert, 2010. "Testing for unobserved heterogeneity in exponential and Weibull duration models," Journal of Econometrics, Elsevier, vol. 157(2), pages 458-480, August.
    2. James Prieger, 2003. "Bootstrapping the conditional moment test for parametric duration models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 597-600.
    3. James Prieger, 2003. "Bootstrapping the conditional moment test for parametric duration models," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 597-600.

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