We compare sparse and dense representations of predictive models in macroeconomics, microeconomics, and finance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate...

Summary This paper develops a factor model for forecasting inflation in the euro area. The model can handle variables with different timeliness, sample size and frequency. We show that the forecasts based on the factor model outperform naïve random walk forecasts, a hard to beat benchmark for...

Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables....

Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables....

This paper uses a data-set including time series data on macroeconomic variables, loans, deposits and interest rates for the euro area in order to study the features of financial intermediation over the business cycle. We find that stylized facts for aggregate monetary and real variables are...

This study evaluates the macroeconomic effects of Outright Monetary Transaction (OMT) announcements by the European Central Bank (ECB). Using high-frequency data, we find that OMT announcements decreased the Italian and Spanish 2-year government bond yields by about 2 percentage points, while...

This paper analyses the impact on the macroeconomy of the ECB’s non-standard monetary policy implemented in the aftermath of the collapse of Lehman Brothers in the Fall of 2008. We study in particular the effect of the expansion of the intermediation of transactions across central bank balance...

This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...