DP7870 The Diversity of Forecasts from Macroeconomic Models of the U.S. Economy

Author(s): Volker Wieland, Maik H Wolters
Publication Date: June 2010
Keyword(s): Bayesian estimation, business cycles, forecast distribution, forecasting, heterogeneous beliefs, model uncertainty
JEL(s): C53, D84, E31, E32, E37
Programme Areas: International Macroeconomics
Link to this Page: www.cepr.org/active/publications/discussion_papers/dp.php?dpno=7870

This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated U.S. recessions. We generate forecasts from six different models of the U.S. economy and compare them to professional forecasts from the Federal Reserve's Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates.