Forecasting Italian GDP growth with epidemiological data

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 GDP growth. In particular, we use a mixed-frequency dynamic factor model together with a sophisticated susceptible-infectious-recovered epidemic model featuring endogenous policy responses. First, we simulate different scenarios of economic growth depending on the course of the pandemic in Italy. Second, we evaluate the forecast performance of the model for the period August 2020-March 2021. We find that taking epidemiological indicators into consideration is important for obtaining reliable projections.