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

We propose a Markov-switching dynamic factor model to construct an index of global business cycle conditions, for performing short-term forecasts of quarterly world GDP growth in real time and computing real-time business cycle probabilities. To overcome the real-time forecasting challenges, the...

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...

In this paper we propose a new real-time forecasting model for euro area GDP growth, D€STINY, which attempts to bridge the existing gap in the literature between large- and small-scale dynamic factor models. By adopting a disaggregated modelling approach, D€STINY uses most of the information...

We show that the single-index dynamic factor model developed by Aruoba and Diebold (Am Econ Rev, 100:20-24, 2010) to construct an index of US business cycle conditions is also very useful for forecasting US GDP growth in real time. In addition, we adapt the model to include survey data and...

We develop a dynamic factor model to compute short term forecasts of the Spanish GDP growth in real time. With this model, we compute a business cycle index which works well as an indicator of the business cycle conditions in Spain. To examine its real time forecasting accuracy, we use real-time...

We propose a model to compute short-term forecasts of the Euro area GDP growth in real-time. To allow for forecast evaluation, we construct a real-time data set that changes for each vintage date and includes the exact information that was available at the time of each forecast. In this context,...