Financial conditions and density forecasts for US output and inflation

When do ?nancial markets help in predicting economic activity? With incomplete markets, the link between ?nancial and real economy is state- dependent and ?nancial indicators may turn out to be useful particularly in forecasting "tail" macroeconomic events. We examine this conjecture by studying Bayesian predictive distributions for output growth and in?ation in the US between 1983 and 2012, comparing linear and nonlinear VAR models. We ?nd that ?nancial indicators signi?cantly improve the accuracy of the dis- tributions. Regime-switching models perform better than linear models thanks to their ability to capture changes in the transmission mechanism of ?nancial shocks between good and bad times. Such models could have sent a credible advance warning ahead of the Great Recession. Furthermore, the discrepan- cies between models are themselves predictable, which allows the forecaster to formulate reasonable real-time guesses on which model is likely to be more accurate in the next future.