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 propose a fundamentals-based econometric model for the weekly changes in the euro-dollar rate with the distinctive feature of mixing economic variables quoted at different frequencies. The model obtains good in-sample fit and, more importantly, encouraging out-of-sample forecasting results at...

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)...