This paper extends the Markov-switching vector autoregressive models to accommodate both the typical lack of synchronicity that characterizes the real-time daily flow of macroeconomic information and economic indicators sampled at different frequencies. The results of the empirical application...

Practitioners do not always use research findings, sometimes because 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 on short-term forecasting in real time. Towards this end, we review the most...

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 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...

This paper estimates a firm-specific capital DSGE model. Firm-specific capital improves the fit of DSGE models to the data (as shown by a large increase in the value of the log marginal likelihood). This results from a lower implied estimate of the NKPC slope for a given degree of price...

The paper addresses the question on what is the typical time horizon over which a full transmission of movements in the real exchange rate into real economy takes place. To this end, we base our analysis on the mixed-frequency small-scale dynamic factor model of Siliverstovs (2012) fitted to the...

We present a medium-scale dynamic factor model to estimate and forecast the rate of growth of the Spanish economy in the very short term. The intermediate size of the model overcomes the serious specification problems associated with large scale-models and the implicit loss of information of...