between models as well as over time. It introduces an information reduction step by using a clustering mechanism that …

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets …

multivariate time series forecasting. This extends the foundational BPS framework to the multivariate setting, with detailed … evaluates – sequentially and adaptively over time – varying forecast biases and facets of miscalibration of individual forecast … densities for multiple time series, and – critically – their time-varying interdependencies. We define BPS methodology for a new …

logistic auto-regressive processes, change over time and their dynamics are possible driven by the past forecasting …

dynamic model averaging. These methods not only allow for coefficients to change over time, but also allow for the entire … forecasting model to change over time. We find that dynamic model averaging leads to substantial forecasting improvements over … simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. We also …

This paper studies how to combine real-time forecasts from a broad range of Bayesian vector autoregression (BVAR …