Semiparametric Estimation of Single-Index Transition Intensities

T. Gorgens

Working Papers from Carleton - School of Public Administration

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 MODELS; EVALUATION (search for similar items in EconPapers)
JEL-codes: C14 C24 C41 (search for similar items in EconPapers)
Pages: 42 pages
Date: 1999
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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:fth:carlad:99-25

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