In this paper we extend the Stock and Watson's (Leading economic indicators, new approaches and forecasting records, 1991) single-index dynamic factor model in an econometric framework that has the advantage of combining information from real and financial indicators published at different...

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 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 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,...

In this paper, we propose a small-scale dynamic factor model for monitoring Argentine GDP in real time using economic data at mixed frequencies (monthly and quarterly). Our model not only produces a coincident index of the Argentine business cycle in striking accordance with professional...

This paper proposes two refinements to the single-index dynamic factor model developed by Aruoba and Diebold (AD, 2010) to monitor US economic activity in real time. First, we adapt the model to include survey data and financial indicators. Second, we examine the predictive performance of 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...