In this paper we propose an algorithm to carry out the monitoring and retrospective intervention process in Dynamic Linear Models, both selectively and automatically. The algorithm is illustrated by analysing several series taken from the literature, in which the proposed procedure is shown to...

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...

This paper is devoted to an analysis of financial ratio adjustment in European financial statements. To that end, we use an hierarchical model based on the partial adjustment model. This model allows us to distinguish between adjustments that are due to external shocks and which affect all...

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...

In this paper, we propose a Bayesian hierarchical model based on the partial adjustment model described by Wu and Ho (Rev. Quant. Finance Acc. 9 (1997) 71). The proposed model allows us to estimate the average adjustment coefficients associated with the error correction component and with the...

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...