"This paper considers the ability of simulated data from linear and nonlinear time-series models to reproduce features in U.S. real GDP data related to business cycle phases. We focus our analysis on a number of linear ARIMA models and nonlinear Markov-switching models. To determine the timing...

We consider the extent to which different time-series models can generate simulated data with the same business cycle features that are evident in U.S. real GDP. We focus our analysis on whether multivariate linear models can improve on the previously documented failure of univariate linear...

We consider which labor market variables are the most informative for estimating and nowcasting the US output gap using a multivariate trend-cycle decomposition. Although the unemployment rate clearly contains important cyclical information, it also appears to reflect more persistent movements...

An updated version of our Markov-switching model of U.S. real GDP clearly suggests the COVID-19 recession was more U shaped than L shaped. As with linear time series models, it is important to account for extreme outliers during the pandemic, but a simple decay function for volatility from...