Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/166004
Authors: 
van den Berg, Gerard J.
Janys, Lena
Mammen, Enno
Nielsen, Jens P.
Year of Publication: 
2016
Series/Report no.: 
Working Paper, IFAU - Institute for Evaluation of Labour Market and Education Policy 2016:3
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 of 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-lite 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 sample parametric specifications. Moreover, its shape at higher birth weights differs across gender.
Subjects: 
survival analysis
semiparametric estimation
covariate effects
kernel estimation
local linear regression
birth weight
mortality
Barker hypothesis
social class
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.