Using the Consensus Economics dataset with individual expert forecasts from G7 countries we investigate determinants of disagreement (crosssectional dispersion of forecasts) about six key economic indicators. Disagreement about real variables (GDP, consumption, investment and unemployment) has a...

There is a broad consensus in the literature that costs of information processing and acquisition may generate costly disagreements in expectations among economic agents, and that central banks may play a central role in reducing such dispersion in expectations. This paper analyses empirically...

This paper addresses the estimation of Phillips curve equations for the euro area while employing less stringent assumptions on the functional correspondence between price inflation, inflation expectations and marginal costs. Expectations are not assumed to be an unbiased predictor of actual...

Recent models of monetary policy have analyzed the desirability of different optimal and ad hoc interest rules under the restrictive assumption that forecasts of the private sector and the central bank are homogenous. In this paper, we study the implications of heterogeneity in forecasts of the...

We evaluate how the euro area economy would have performed since mid-2021 under alternative monetary policy strategies. We use the ECB's workhorse estimated DSGE model and contrast actual policy conduct against alternative strategies which differ in their "lower-for-longer" commitment as well as...

We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy levels of inflation: individual products, product groups, and headline inflation. At...

In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

We find that it does, but choosing the right specification is not trivial. We unveil notable model instability, with breaks in the performance of most simple Phillips curves. Euro area inflation was particularly hard to forecast in the run-up to the EMU and after the sovereign debt crisis, when...

We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area in ation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting in ation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting in ation with the ability of quantile regression to...