Professional Forecasters and the Real-time Forecasting Performance of an Estimated New Keynesian Model for the Euro Area

Abstract

This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets, and Wouters (2012) estimated on euro area data. It investigates to what extent forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the "noise" approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the "news" approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated over the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model and a random walk.

Keywords: Bayesian methods, DSGE model, real-time database, Survey of Professional Forecasters, macroeconomic forecasting, estimated New Keynesian model, euro area

JEL Classification: E24, E31, E32