EconPapers    
Economics at your fingertips  
 

Semiparametric estimation of single-index hazard functions without proportional hazards

Tue Gørgens

Econometrics Journal, 2006, vol. 9, issue 1, 1-22

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. Copyright Royal Economic Society 2006

Date: 2006
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:9:y:2006:i:1:p:1-22

Ordering information: This journal article can be ordered from
http://www.ectj.org

Access Statistics for this article

Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().

 
Page updated 2025-03-19
Handle: RePEc:ect:emjrnl:v:9:y:2006:i:1:p:1-22