Predicting cycles in economic activity is one of the more challenging but important aspects of economic forecasting. This paper reports the results from estimation of binary probit models that predict the probability of an economy being in a recession using a variety of financial and real...

We use Bayesian time-varying parameters VARs with stochastic volatility to investigate changes in the marginal predictive content of the yield spread for output growth in the United States and the United Kingdom, since the Gold Standard era, and in the Eurozone, Canada, and Australia over the...

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...