  Economic shocks due to Covid-19 were exceptional in their severity,
suddenness and heterogeneity across industries. To study the upstream and
downstream propagation of these industry-specific demand and supply shocks, we
build a dynamic input-output model inspired by previous work on the economic
response to natural disasters. We argue that standard production functions, at
least in their most parsimonious parametrizations, are not adequate to model
input substitutability in the context of Covid-19 shocks. We use a survey of
industry analysts to evaluate, for each industry, which inputs were absolutely
necessary for production over a short time period. We calibrate our model on
the UK economy and study the economic effects of the lockdown that was imposed
at the end of March and gradually released in May. Looking back at predictions
that we released in May, we show that the model predicted aggregate dynamics
very well, and sectoral dynamics to a large extent. We discuss the relative
extent to which the model's dynamics and performance was due to the choice of
the production function or the choice of an exogenous shock scenario. To
further explore the behavior of the model, we use simpler scenarios with only
demand or supply shocks, and find that popular metrics used to predict a priori
the impact of shocks, such as output multipliers, are only mildly useful.
