The paper presented in this seminar quantifies the finance uncertainty multiplier (i.e., the magnifying effect of the real impact of uncertainty shocks due to financial frictions) by relying on two historical events related to the US economy, i.e., the large jump in financial uncertainty occurred in October 1987 (which was not accompanied by a deterioration of the credit supply conditions), and the comparable jump in financial uncertainty in September 2008 (which went hand-in-hand with an increase in financial stress). Working with a VAR framework and a set-identification strategy which focuses on - but it is not limited to - these two dates, Giovanni estimates the finance uncertainty multiplier to be equal to 2, i.e., credit supply disruptions are found to double the negative output response to an uncertainty shock. The author then employs the model to estimate the overall economic cost of the COVID-19 uncertainty shock under different scenarios. The results point to the possibility of a cumulative yearly loss of industrial production as large as 31 per cent if credit supply gets disrupted. Liquidity interventions that keep credit conditions as healthy as they were before the COVID-19 uncertainty shock are found to substantially reduce such loss.