Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/35795 
Year of Publication: 
2009
Series/Report no.: 
IZA Discussion Papers No. 3971
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant exponential model, which leads to convenient estimation based on a Poisson regression model fit to person-period, or split-episode data. This specification allows for a flexible representation of the baseline hazard and provides a straightforward way to introduce time-varying covariates and time-varying effects. We provide computational details underlying the method and apply the technique to the decomposition of the black-white difference in first premarital birth rates into components reflecting characteristics and effect contributions of several predictors, as well as the effect contribution attributable to race differences in the baseline hazard.
Subjects: 
Decomposition
hazard rates
piecewise constant exponential model
Poisson regression
JEL: 
C20
C41
J13
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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