  The COVID-19 pandemic has caused a massive economic shock across the world
due to business interruptions and shutdowns from social-distancing measures. To
evaluate the socio-economic impact of COVID-19 on individuals, a micro-economic
model is developed to estimate the direct impact of distancing on household
income, savings, consumption, and poverty. The model assumes two periods: a
crisis period during which some individuals experience a drop in income and can
use their precautionary savings to maintain consumption; and a recovery period,
when households save to replenish their depleted savings to pre-crisis level.
The San Francisco Bay Area is used as a case study, and the impacts of a
lockdown are quantified, accounting for the effects of unemployment insurance
(UI) and the CARES Act federal stimulus. Assuming a shelter-in-place period of
three months, the poverty rate would temporarily increase from 17.1% to 25.9%
in the Bay Area in the absence of social protection, and the lowest income
earners would suffer the most in relative terms. If fully implemented, the
combination of UI and CARES could keep the increase in poverty close to zero,
and reduce the average recovery time, for individuals who suffer an income
loss, from 11.8 to 6.7 months. However, the severity of the economic impact is
spatially heterogeneous, and certain communities are more affected than the
average and could take more than a year to recover. Overall, this model is a
first step in quantifying the household-level impacts of COVID-19 at a regional
scale. This study can be extended to explore the impact of indirect
macroeconomic effects, the role of uncertainty in households' decision-making
and the potential effect of simultaneous exogenous shocks (e.g., natural
disasters).
