During the COVID-19 pandemic, economists have struggled to obtain reliable economic predictions, with standard models becoming outdated and their forecasting performance deteriorating rapidly. This paper presents two novelties that could be adopted by forecasting institutions in unconventional...

In response to the two waves of Covid-19 in 2020, the Italian government implemented a general lockdown in March, but geographically targeted policies during fall. We exploit this natural experiment to compare the effects of the two policies in a difference-in-differences design, leveraging a...

This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates the linkages between them in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in...

This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates the linkages between them in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in...

For years the economics profession has been puzzled by one of the most perplexing economic problems - the overall slowdown in the growth rate of labour productivity since 1973. Not only was the deceleration a worldwide trend, the growth of productivity also turned out to be markedly slower in...

This paper documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The paper is the result of a collaborative effort between the two institutions, allowing us to study the time-stamped...

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable...

We perform a robust estimation of the Phillips curve in the euro area using a battery of 630 theory-driven models. We extend the existing literature by adding model specifications, taking into account the uncertainty in the measurement of variables and testing for potential non-linearities and...

This paper proposes a large-scale Bayesian vector autoregression with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks in G7 countries. The curse of dimensionality is addressed by means of a global-local shrinkage prior that mimics...

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable...