I propose a new model, conditional quantile regression (CQR), that generates density forecasts consistent with a specific view of the future evolution of some variables. This addresses a shortcoming of existing quantile regression-based models, for example the at-risk framework popularised by...

We document how the distribution of exchange rate returns responds to changes in global financial conditions. We measure global financial conditions as the common component of country-specific financial condition indices, computed consistently across a large panel of developed and emerging...

We quantify the effects of wage bargaining shocks on macroeconomic aggregates using a structural vector auto-regression model for Germany. We identify exogenous variation in bargaining power from episodes of minimum wage introduction and industrial disputes. This narrative information...

Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...

We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with...

We characterise the probability distributions of various categories of gross capital flows conditional on information contained in financial asset prices in a panel of emerging market economies, with a focus on "tail" events. Our framework, based on the quantile regression methodology, allows...