This paper discusses how the forecast accuracy of a Bayesian vector autoregression (BVAR) is affected by introducing … the zero lower bound on the federal funds rate. As a benchmark I adopt a common BVAR specification, including 18 variables …

area, the United States and Japan. In particular, incorporating survey forecast information helps to reduce the uncertainty …

entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey … of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model …, including those that are not directly tilted but are affected through spillover effects from tilted variables. The forecast …

, (ii) aggregate demand and (iii) oil-specific demand shock, by proposing the Information Criterion model averaging as a … demand shock, and more persistent following an oil specific demand shock …

In this paper, I examine the forecasting performance of a Bayesian Vector Autoregression (BVAR) model with steady … period 2016q1-2020q1. My findings suggest that inflation forecasts produced by the BVAR model are more accurate than those of … the QPM model two quarters ahead and are competitive for the longer horizon. For GDP growth, the forecasts of the BVAR …