Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts
This paper shows entropic tilting to be a flexible and powerful tool for combining medium-term forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting systematically improves the accuracy of both point and density forecasts, and tilting the BVAR forecasts based on nowcast means and variances yields slightly greater gains in density accuracy than does just tilting based on the nowcast means. Hence entropic tilting can offer—more so for persistent variables than not-persistent variables—some benefits for accurately estimating the uncertainty of multi-step forecasts that incorporate nowcast information.
Keywords: Forecasting, Prediction, Bayesian Analysis.
JEL classification code: E17, C11, C53
Suggested citation: Krueger, Fabian, Todd E. Clark, and Francesco Ravazzolo, 2014. “Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts,” Federal Reserve Bank of Cleveland, working paper no. 14-39.