Boosting recessions

This paper explores the effectiveness of boosting, often regarded as the state of the art classification tool, in giving warning signals of recessions three, six and twelve months ahead. Boosting is used to screen as many as 1500 potentially relevant predictors consisting of 132 real and financial time series and their lags. Estimation over the full sample 1961:1-2011:12 finds that there are fewer than ten important predictors and the identity of these variables change with the forecast horizon. There is a distinct difference in the size and composition of the relevant predictor set before and after mid-1980. Rolling window estimation reveals that the importance of the term and default spreads are recession specific. The Aaa spread is the most robust predictor of recessions three and six months ahead, while the risky bond and 5yr spreads are important for twelve months ahead predictions. Certain employment variables have predictive power for the two most recent recessions when the interest rate spreads were uninformative. Warning signals for the post 1990 recessions have been sporadic and easy to miss. The results underscore the challenge that changing characteristics of business cycles pose for predicting recessions