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Nonparametric analysis of a duration model with stochastic unobserved heterogeneity

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  • Botosaru, Irene

Abstract

This paper develops nonparametric identification and estimation results for a single-spell hazard model, where the unobserved heterogeneity is specified as a Lévy subordinator. The identification approach solves a nonlinear Volterra integral equation of the first kind with an unknown kernel function. Both the kernel of the integral operator, which models the distribution of the unobserved heterogeneity, and the functions that enter it are identified given regularity conditions and minimal variation in the observed covariates. The paper proposes a shape-constrained nonparametric two-step sieve minimum distance estimator. Rates of convergence are derived and Monte Carlo experiments show the finite sample performance of the estimator.

Suggested Citation

  • Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    • Handle: RePEc:eee:econom:v:217:y:2020:i:1:p:112-139
    DOI: 10.1016/j.jeconom.2019.06.006
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    Cited by:

    1. Gimenes, Nathalie & Guerre, Emmanuel, 2020. "Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids," Journal of Econometrics, Elsevier, vol. 219(1), pages 1-18.
    2. Nathalie Gimenes & Emmanuel Guerre, 2019. "Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids," Papers 1910.10646, arXiv.org.

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    More about this item

    Keywords

    Duration model; Lévy process; Nonlinear Volterra integral equation of the first kind; Shape restricted estimation;
    All these keywords.

    JEL classification:

    • 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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