Semiparametric Estimation of Single-Index Transition Intensities

Tue Gørgens
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Tue Gørgens: University of New South Wales

No 99-25, Discussion Papers from University of Copenhagen. Department of Economics

Abstract: This research develops semiparametric kernel-based estimators of state-specific conditional transition intensitiesm, hs (y|x), for duration models with right-censoring and/or multiple destinations (competing risks). Both discrete and continous duration data are considered. The maintained assumptions are that hs(y|x) depends on x only through an index x'Bs. In contrast to existing semiparametric estimators, proportional intensities is not assumed. The new estimators are asymptotically normally distributed. The estimator of Bs is root-n consistent. The estimator of hs (y|x) achieves the one-dimensional rate of convergence. Thus the single-index assumption eliminates the "curse of dimensionality". The estimators perform well in Monte Carlo experiments.

Keywords: semiparametric estimation; kernel regression; duration analysis; competing risks; censoring (search for similar items in EconPapers)
JEL-codes: C14 C24 C41 (search for similar items in EconPapers)
Pages: 41 pages
Date: 1999-12
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http://www.econ.ku.dk/english/research/publications/wp/1999/9925.pdf/ (application/pdf)

Related works:
Working Paper: Semiparametric Estimation of Single-Index Transition Intensities (2000)
Working Paper: Semiparametric Estimation of Single-Index Transition Intensities (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:kud:kuiedp:9925

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