This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample...

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the...

In this paper we describe the use of Gibbs sampling methods for making posterior inferences.in stochastic frontier models with composed error. We show how Gibbs sampling methods can greatly reduce the computational difficulties involved in analyzing such models. Our findings are illustrated in...