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...

The effect of successive periods of unemployment according to household type has not been analysed in any depth with respect to the Spanish labour market. In this article, we propose a nonparametric methodology based on a data-driven likelihood ratio function to describe the dependence between...

A semi-parametric Bayesian methodology based on Cox's proportional hazards model is proposed in order to evaluate the efficacy of training programmes offered by the University of Zaragoza (Spain) in the labour market insertion process. To this end, a matched comparison group has been designed in...

A methodology is proposed to select the information set in ARMA-GARCH models in order to forecast the future evolution of an univariate heteroscedastic time series when it is suspected that the DGP is time changing. Using this methodology the stability of the DGP in the Spanish Stock Market is...

Many researchers have used parametric ARCH models to specify the conditional variance of financial series. However, the usual tests do not provide any information on the form of the conditional variance. The objective of this paper is to present a test for heteroscedasticity, i.e. to decide...

This article proposes a new methodology to estimate the Value at Risk (VaR) in a time varying heteroscedastic dynamic regression context. The methodology assumes that the form of the model and its information set may also change over time and takes into account the uncertainty associated with...