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Asymptotics for Sieve Estimators of Hazard Rates: Estimating Hazard Functionals

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  • James Wolter

Abstract

This paper derives asymptotics for functionals of a hazard model with an exposure-time effect and time-varying covariates. A semi-nonparametric sieve maximum likelihood estimator of a competing risks model based on the Cox proportional hazard is considered. Consistency of the estimator and its rate of convergence in the Fisher norm are derived. These results are prerequisites for asymptotic normality of plug-in estimators of hazard functionals. This provides an inference procedure for a large class of functionals including the conditional probability of events and various asset pricing formulas for defaultable securities. Asset pricing formulas in this class include the value of mortgages, insurance contracts, bonds, swaps and other options.

Suggested Citation

  • James Wolter, 2015. "Asymptotics for Sieve Estimators of Hazard Rates: Estimating Hazard Functionals," Economics Series Working Papers 760, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:760
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    References listed on IDEAS

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    More about this item

    Keywords

    Conditional probabilities; Sieve estimation; Hazard models;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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