To Örebro University

The Bayesian VAR model provides a convenient tool for generating predictive densities and making probability statements regarding the future development of economic variables. This paper investigates the usefulness of standard macroeconomic Bayesian VAR models to estimate the probability of a US recession. Defining a recession as two quarters in a row of negative GDP growth, the probability is estimated for two quarters of the most recent US recession, namely 2008Q3–2008Q4. In contrast to judgemental probabilities from this point in time, it is found that the BVAR assigns a very low probability to such an event. This is true also when survey data, which generally are considered as good leading indicators, are included in the models. We conclude that while Bayesian VAR models are good forecasting tools in many cases, the results in this paper raise question marks regarding their usefulness for predicting recessions.