We have studied the comparative performance of a number of interest rate spreads as predictors of the German inflation and business cycle in the post Bretton Woods era. The two-regime Markov switch model that we used as a nonlinear filter allows the dynamic behavior of the economy to vary...

We estimate a Bayesian learning model with heterogeneity aimed at explaining the evolution of expert disagreement in forecasting real GDP growth and inflation over 24 monthly horizons for G7 countries during 1990-2007. Professional forecasters are found to begin and have relatively more success...

We have argued that from the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. With a standard factor decomposition of a panel of forecasts, we...

This paper focuses on a number of newly proposed on-line forecast combination algorithms in Sancetta (2010), Yang (2004), and Wei and Yang (2012). We first establish certain asymptotic properties of these algorithms and compare them with the Bates and Granger (1969) method. We then show that...

We combine the probability forecasts of a real GDP decline from the U.S. Survey of Professional Forecasters, after trimming the forecasts that do not have “value” as measured by the Kuiper Skill Score and in the sense of Merton (1981). For this purpose, we use a simple test to evaluate the...