vector can be recovered from the BVAR posterior estimates: a new 'quasi-Bayesian' DSGE estimation. An empirical application …

Autoregressive (BVAR) models. The moments of the assumed Normal-Inverse Wishart (no conjugate) prior distribution of the VAR … the results from previous studies, BVAR models with theoretical priors seem to achieve forecasting performance that is … comparable - if not better - to the one obtained using theory free "Minnesota" priors (Doan et al., 1984). Additionally, the …

Estimating demand for wide assortments of differentiated goods requires the specification of a demand system that is … parameters within a log-linear demand system where the number of price elasticity parameters grows quadratically in the number of … elasticities and demand predictions can be improved by imposing shrinkage to higher-level group effects rather than zero …

forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the … compare the density forecast performance of a DSGE model to DSGE-VARs and reduced-form linear Gaussian models. …

indicates that a BVAR performs better than the benchmark in all forecast horizons. Statistical differences between the two BVAR … desired policy goals. This paper develops a group of models to forecast inflation for Argentina, which includes autoregressive … models and different scale Bayesian VARs (BVAR), and compares their relative accuracy. The results show that the BVAR model …

show that the BVAR model can improve the forecast ability of the univariate autoregressive benchmark's model of inflation …. The Giacomini-White test indicates that a BVAR performs better than the benchmark in all forecast horizons. Statistical … corrections to reach the desired policy goals. This paper develops a group of models to forecast inflation for Argentina, which …