This paper examines the role of financial variables for nowcasting the Italian GDP growth rate, with a focus on the pandemic period. The analysis combines factor models and regression models with data at different frequencies (MIxed DAta Sampling, MIDAS) and uses weekly financial variables, along with real variables and qualitative survey variables, both at monthly frequency.
Financial variables improve the nowcasting accuracy of the Italian GDP growth rate; the accuracy increases especially in the first month of the reference quarter, when the availability of macroeconomic data for the entire period is limited. The improvement is more pronounced in periods of severe economic shocks, such as during the COVID-19 pandemic.
