This paper studies the cyclical properties of real GDP, house prices, credit, and nominal liquid financial assets in 17 EU countries, by applying several methods to extract cycles. The estimates confirm earlier findings of large medium-term cycles in credit volumes and house prices. GDP appears...

We show that an extension of the Markov-switching dynamic factor models that accounts for the specificities of the day to day monitoring of economic developments such as ragged edges, mixed frequencies and data revisions is a good tool to forecast the Euro area recessions in real time. We...

We examine the short-term performance of two alternative approaches to forecasting using dynamic factor models. The first approach extracts the seasonal component of the individual indicators before estimating the dynamic factor model, while the alternative uses the non-seasonally adjusted data...

We extend the Markov-switching dynamic factor model to account for some of the specifi cities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as ragged edges and mixed frequencies. We examine the theoretical benefi ts of this extension and corroborate...

We examine the finite-sample performance of small versus large scale dynamic factor models. Our Monte Carlo analysis reveals that small scale factor models out-perform large scale models in factor estimation and forecasting for high levels of cross-correlation across the idiosyncratic errors of...

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov-switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully non-linear multivariate specification (one-step approach)...