Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/101859
Authors: 
van den Berg, Gerard J.
Janys, Lena
Mammen, Enno
Nielsen, Jens P.
Year of Publication: 
2014
Series/Report no.: 
IZA Discussion Papers 8339
Abstract: 
We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker or covariate effects. A number of well-known models are special cases. In a counting process framework, a general profile likelihood estimator is developed and the parametric component of the model is shown to be asymptotically normal and efficient. The analysis improves on earlier results for special cases. Finite sample properties are investigated in simulations. The estimator is shown to work well under realistic empirical conditions. The estimator is applied to investigate the long-run relationship between birth weight and later-life mortality using data from the Uppsala Birth Cohort Study of individuals born in 1915-1929. The results suggest a relationship that is difficult to capture with simple parametric specifications. Moreover, its shape at higher birth weights differs across gender.
Subjects: 
asymptotic distribution
local linear estimation
survival analysis
covariate effects
birth weight
mortality
social class
JEL: 
C41
C14
I12
J13
Document Type: 
Working Paper

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