Covid-19 caused an abrupt disruption in the world economy and posed big challenges to macroeconomic and time-series analysis. The deep trough in the business cycle was unprecedented in momentum and magnitude, was not approached smoothly, and the pandemic shock was not heralded by any warning...

The Covid-19 epidemic affected the ability of traditional forecasting models to produce reliable scenarios for the evolution of economic activity. We combine macroeconomic variables with epidemiological indicators to account for the Covid-19 shock and predict the short-term evolution of Italian...

This paper provides an overview of how information on payments has been recently exploited by Banca d’Italia staff for the purposes of tracking economic activity and forecasting. In particular, the payment data used for this work are drawn from the payment systems managed by Banca d’Italia...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

We study how FDI affects the financial structure of targeted firms, by looking at a sample of foreign acquisitions that occurred in Italy between 1998 and 2016. We show that the entry of foreign investors promotes the diversification of financing sources. Moreover, foreign acquisitions lower...