In this paper we estimate a Bayesian vector autoregressive model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area. This allows us to treat macroeconomic uncertainty as a latent quantity during estimation. Only a limited number of...

Empirical work described in this paper explains the daily evolution of the reproduction rate, R, and mobility for a large sample of countries, in terms of containment and public health policies. This is with a view to providing insight into the appropriate policy stance as countries prepare for...

We define tail interdependence as a situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multiinformation to quantify tail interdependence, decompose it into systemic and residual interdependence and measure the...

We investigate how often replication studies are published in empirical economics and what types of journal articles are eventually replicated. We find that from 1974 to 2014 0.10% of publications in the Top 50 economics journals were replications. We take into account the results of replication...

Computational methods to gauge investor sentiment from commonly used online data sources that rely on machine learning classifiers and lexicons have shown considerable promise, but suffer from measurement and classification errors. In our work, we develop a simple, direct and unambiguous...

The forecasting uncertainty around point macroeconomic forecasts is usually measured by the historical performance of the forecasting model, using measures such as root mean squared forecasting errors (RMSE). This measure, however, has the major drawback that it is constant over time and hence...