We study the forecasting performance of three alternative large scale approaches using a dataset for Germany that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating information, yet on different...

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...

We propose a simple modification of the time series filter by Hamilton (2018b) that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8-quarter ahead forecasts errors of an autoregression. While this approach yields a cyclical component of...

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...

We analyze cyclical co-movement in credit, house prices, equity prices, and long-term interest rates across 17 advanced economies. Using a time-varying multi-level dynamic factor model and more than 130 years of data, we analyze the dynamics of co-movement at different levels of aggregation and...

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...