Binary Autoregressive Moving Average (BARMA) models provide a modeling technology for binary time series analogous to the classic Gaussian ARMA models used for continuous data. BARMA models mitigate the curse of dimensionality found in long lag Markov models and allow for non-Markovian...

We offer improved dating of U.S. business cycle turning points both retrospectively and in real time. This improvement is made possible by augmenting existing Markov-switching dynamic factor models with additional information on stock return volatility. The model significantly improves...

Recessions and subsequent recoveries are frequently classified as “L-shaped” or “U-shaped,” with output losses in the former being permanent and losses in the latter at least partially made up by higher than average growth during the recovery. We estimate the probability of a U-shaped...