In the recent years several commentators hinted at an increase of the correlation between equity and commodity prices, and blamed investment in commodity-related products for this. First, this paper investigates such claims by looking at various measures of correlation. Next, we assess to what...

A number of recent studies in the economics literature have focused on the usefulness of factor models in the context of prediction using big data. In this paper, our over-arching question is whether such big data are useful for modelling low frequency macroeconomic variables such as...

Path forecasts, defined as sequences of individual forecasts, generated by vector autoregressions are widely used in applied work. It has been recognized that a profound econometric analysis often requires, besides the path forecast, a joint prediction region that contains the whole future path...

We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key di erence from traditional Bayesian variable selection is that we also allow for uncertainty...

Path forecasts, defined as sequences of individual forecasts, generated by vector autoregressions are widely used in applied work. It has been recognized that a profound econometric analysis requires, besides the path forecast, a joint prediction region that contains the whole future path with a...

This paper investigates if the impact of uncertainty shocks on the US economy has changed over time. To this end, we develop an extended Factor Augmented VAR model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on a range of variables. We find...

We use a factor model with stochastic volatility to decompose the time-varying variance of Macro economic and Financial variables into contributions from country-specific uncertainty and uncertainty common to all countries. We find that the common component plays an important role in driving the...

This paper evaluates the performance of a variety of structural VAR models in estimating the impact of credit supply shocks. Using a Monte-Carlo experiment, we show that identification based on sign and quantity restrictions and via external instruments is effective in recovering the underlying...

A growing empirical literature has considered the impact of uncertainty using SVAR models that include proxies for uncertainty shocks as endogenous variables. In this paper we consider the possible impact of measurement error in the uncertainty shock proxies on the estimated impulse responses...

This paper evaluates the performance of structural VAR models in estimating the impact of credit supply shocks. In a simple Monte-Carlo experiment, we generate data from a DSGE model that features bank lending and credit supply shocks and use SVARs to try and recover the impulse responses to...