Using Forecast Evaluation to Improve the Accuracy of the Greenbook Forecast

Abstract

Much research has been concerned with forecast efficiency regressions. Recently, Patton and Timmermann (2012) proposed a more powerful kind of forecast efficiency regression at multiple horizons, which provides evidence against the efficiency of the Fed's Greenbook forecasts. I use their forecast efficiency evaluation to propose a method for adjusting the Greenbook forecasts. Using this method in a real-time out-of-sample forecasting exercise, I find that it gives modest but consistent improvements in forecast accuracy, the magnitude of which is from one to eighteen percent. These improvements are statistically significant in some cases.