This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the … likelihood and two different Bayesian approaches, and traditional benchmark models, e.g. the random walk. The accuracy of point … present. We also critically examine the role of Bayesian model probabilities and other frequently used low …

on the short run dynamics with a resulting prior which only depends on a few hyperparameters and is therefore easily …

modelled as functions of the covariates. Inference is Bayesian and the computation is carried out using Markov chain Monte …

prevents overfitting and makes it feasible to fit high-dimensional nonparametric surfaces. We use Bayesian inference and Markov …

We consider a Bayesian Model Averaging approach for the purpose of forecasting Swedish consumer price index inflation … these indicators in combination can give rise to. The results, in terms of out-of-sample-performance, suggest that Bayesian …

estimated using a Bayesian approach via a highly efficient Markov Chain Monte Carlo (MCMC) algorithm with tailored proposals and …

challenge from a methodological perspective, especially within the common value framework. We develop a Bayesian analysis of the … valuations using a hierarchical Gamma model. We use a Bayesian variable selection algorithm that simultaneously samples the … demonstrated that the Bayesian algorithm is very efficient and that the approximation error in the bid function has virtually no …