We study the crash of bank stock prices during the COVID-19 pandemic. We find evidence consistent with a “credit line drawdown channel”. Stock prices of banks with large ex-ante exposures to undrawn credit lines as well as large ex-post gross drawdowns decline more. The effect is attenuated for banks with higher capital buffers. These banks reduce term loan lending, even after policy measures were implemented. We conclude that bank provision of credit lines appears akin to writing deep out-of-the-money put options on aggregate risk; we show how the resulting contingent leverage and stock return exposure can be incorporated tractably into bank capital stress tests.
The policy response to the COVID-19 shock included regulatory easing across jurisdictions to loosen financial conditions by facilitating the flow of credit to the economy. Using an intraday event study, this paper examines how equity returns—a key driver in financial conditions—reacted to the announcement of these measures in a sample of 18 advanced economies and 8 emerging markets. The paper finds that the announcement of looser regulation overall contributed to easing financial conditions, but effects varied across sectors and tools. Financial regulatory easing led to lower valuations for financial sector stocks, and higher valuations for non-financial sector stocks, particularly for industries that are more dependent on bank financing. Furthermore, valuations declined and financial conditions tightened following announcements related to easier bank capital regulation while equity valuation rose and financial conditions loosened after those about liquidity regulation. Effects from non-regulatory financial measures appear to be generally more muted.
Early evidence on the pandemic’s effects pointed to women’s employment falling disproportionately, leading observers to call a “she-cession.” This paper documents the extent and persistence of this phenomenon in a quarterly sample of 38 advanced and emerging market economies. We show that there is a large degree of heterogeneity across countries, with over half to two-thirds exhibiting larger declines in women’s than men’s employment rates. These gender differences in COVID-19’s effects are typically short-lived, lasting only a quarter or two on average. We also show that she-cessions are strongly related to COVID-19’s impacts on gender shares in employment within sectors.
This paper estimates the dynamic effect of Stay-At-Home (SAH) orders on the transmission of COVID-19 in the United States. Identification in this setting is challenging due to differences between real and reported case data given the imperfect testing environment, as well as the clearly non-random adoption of treatment. We extend a Susceptible-Infected-Recovered (SIR) model from Epidemiology to account for endogenous testing at the county level, and exploit this additional structure to recover identification. With the inclusion of model-derived sufficient statistics and fixed effects, SAH orders have a large and sustained negative effect on the growth of cases under plausible assumptions about the progression of testing. Point estimates range from a 44% to 54% reduction in the growth rate of cases one month after a SAH order. We conclude with a discussion on extending the methodology to later phases of the pandemic.
