The present paper has two main objectives: first, to accurately estimate commodity price uncertainty; and second to analyze the uncertainty connectedness among commodity markets and the macroeconomic uncertainty, using the time-varying vector-autoregressive (TVP-VAR) model. We use eight main...

This paper proposes an econometric framework for nowcasting the monetary policy stance and decisions of the European Central Bank (ECB) exploiting the ow of conventional and textual data that become available between two consecutive press conferences. Decompositions of the updated nowcasts into...

The present paper has two main objectives: first, to accurately estimate commodity price uncertainty; and second to analyze the uncertainty connectedness among commodity markets and the macroeconomic uncertainty, using the time-varying vector-autoregressive (TVP-VAR) model. We use eight main...

Although the unemployment rate is traditionally used to diagnose the current state of the labor market, this indicator does not reflect the existence of asymmetries, mobility costs, and rigidities which impede labor to freely flow over the business cycle. Thus, to get a better portrait of the...

We propose a modelling approach involving a series of small-scale factor models. They are connected to each other within a cluster, whose linkages are derived from Granger-causality tests. GDP forecasts are established across the production, income and expenditure accounts within a disaggregated...

A factor augmented dynamic model for analysing tail behaviour of high dimensional time series is proposed. As a first step, the tail event driven latent factors are extracted. In the second step, a VAR (Vectorautoregression model) is carried out to analyse the interaction between these factors...