| Abstract: | This paper provides a one-month-ahead, macroeconomic, Bayesian Vector Autoregressive (BVAR) forecasting approach that offers several advantages over conventional short-term forecasting procedures. In particular, it produces more accurate forecasts than the Bloomberg consensus forecasts, on average, for 20 major macroeconomic variables. In addition to a quantitative comparison of BVAR and Bloomberg consensus forecast, the paper focuses on five important areas of macroeconomic forecasting: the role of short-term macroeconomic forecasting, the importance of a robust forecasting approach, the importance of timing of data releases, forecast evaluation criteria, and the importance of changing model specifications as conditions warrant. |
