Semi-parametric Bayesian Analysis of the Proportional Hazard Rate Model An Application to the Effect of Training Programs on Graduate Unemployment

Abstract

In this paper, we introduce a semi-parametric Bayesian methodology based on the proportional hazard model that assumes that the baseline hazard function is constant over segments but, by contrast to what is usually assumed in the literature, with the periods at which the function changes not being specified in advance. The methodology is applied to explore the impact of Vocational Training courses offered by the University of Zaragoza (Spain) on the duration of the initial periods of unemployment experienced by graduate leavers. The framework is very flexible and allows us, in particular, to capture the presence of seasonality in the job insertion of graduates.

Keywords:

• Bayesian survival analysis
• semi-parametric models
• proportional hazard
• training programs
• labor market

Acknowledgements

This work was partially supported by the Modelos Estadísticos No Paramétricos en el Mercado Laboral and Decisión Multicriterio Zaragoza (http://gdmz.unizar.es) Consolidated Research Groups of the Government of Aragon.

Notes

¹The University of Aragon vocational training bureau, Universa, requires candidates for its courses to register with the INEM.