Semiparametric estimation of single-index hazard functions without proportional hazards

Tue Gørgens*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    This research develops a semiparametric kernel-based estimator of hazard functions which does not assume proportional hazards. The maintained assumption is that the hazard functions depend on regressors only through a linear index. The estimator permits both discrete and continuous regressors, both discrete and continuous failure times, and can be applied to right-censored data and to multiple-risks data, in which case the hazard functions are risk-specific. The estimator is root- n consistent and asymptotically normally distributed. The estimator performs well in Monte Carlo experiments.

    Original languageEnglish
    Pages (from-to)1-22
    Number of pages22
    JournalEconometrics Journal
    Volume9
    Issue number1
    DOIs
    Publication statusPublished - Mar 2006

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