Bayesian techniques. While asymptotic identification tests show that some of the parameters are weakly identified in the model … with the Bayesian posterior median parameters, but at the expense of some the ML estimates being implausible from a … problems with model misspecification, and not primarily weak identification, is the main challenge ahead in developing …

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 …

We extend the standard approach to Bayesian forecast combination by forming the weights for the model averaged forecast … standard Bayesian model averaging using the marginal likelihood. …

, based on microeconomic deposit market data. We impose identification restrictions both in the cross-section (across insured …

compared with two less structural approaches for identification of monetary policy shocks. The first assumes that shocks can be …

We introduce a Bayesian approach to model assessment in the class of graphical vector autoregressive (VAR) processes …

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