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...

Practitioners do not always use research findings, as the research is not always conducted in a manner relevant to real-world practice. This survey seeks to close the gap between research and practice in respect of short-term forecasting in real time. To this end, we review the most relevant...

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)...

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,...

This paper applies the programs TRAMO and SEATS to seasonal adjustment of the monthly Consumer Price Index Swiss series. It is shown how the results of the purely automatic procedure can be improved with two simple modifications: one that emerges from the TRAMO-SEATS diagnostics, and another...

The time aggregation properties of the Hodrick-Prescott (HP) filter to decompose a time series into trend and cycle are analized for the case of annual, quarterly, and monthly data. It is seen that aggregation of the disagreggate component estimators cannot be obtained as the exact result from...

Present practice in applied time series work, mostly at economic policy or data producing agencies, relies heavily on using moving average filters to estimate unobserved components in time series, such as the seasonally adjusted series, the trend, or the cycle. The purpose of the present paper...

One of the most extended empirical stylized facts about output dynamics in the United States is the positive autocorrelation of output growth. This paper shows that the positive autocorrelation can be better captured by shifts between business cycle states rather than by the standard view of...

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...