Recession Forecasting with Dynamic Probit Models under Real Time Conditions

In this paper a dynamic probit model for recession forecasing under pseudo-real time is set up using a large set of macroeconomic and financial monthly indicators for Germany. Using different initial sets of explanatory variables, alternative dynamic probit specifications are obtained through an automatized general-to-specific lag selection procedure, which are then pooled in order to decrease the volatility of the estimated recession probabilities and increase their forecasting accuracy. As it is shown in the paper, this procedure does not only feature good in-sample forecast statistics, but has also good out-of-sample performance, as pseudo-real time evaluation exercises show.