|
|
The findings suggest that banks are catching coronavirus, although the effect is not so obvious from bank balance sheets given the easing of regulatory requirements on loan classification and provisioning. Exposure to COVID has led to an increase in lending to support the economy, but driven by government support programmes, as well as a tightening in loan conditionality.
Across the globe, economies have been hit hard and fast by COVID-19 (IMF 2021). In the US, unemployment spiked in the first half of 2020 at an unprecedented speed. While such a shock is unlikely to leave banks unaffected, equity buffers have improved significantly since the 2007 financial crisis, and monetary and regulatory policy responses were swift and radical to strengthen the resilience of the financial system (Feyen et al. 2020). In addition, governments stepped in to support the real economy, which indirectly benefitted banks.
What has been the effect of the pandemic on banks’ health and their ability to support the economy with lending? In recent work, we explore if and how US banks’ health has been affected and if there have been changes in lending growth, including in reaction to government support programmes, and in loan conditionality (Beck and Keil 2021).
The US offers a unique laboratory to test the impact of the pandemic and policy reactions. COVID-19 outbreaks were initially concentrated in urban centres on both coasts before the pandemic moved Mid-West and ultimately into the South and Southwest. Similarly, state and county governments across the US have shown quite some variation in lockdown policies. Given the variation in regional exposure of banks, different banks were affected to a different degree by the pandemic as well as at different points in time. This allows us to not only document average trends across banks but also link geographic exposure of banks to pandemic and lockdown measures to banks’ performance.
We capture exposure to the pandemic by COVID-19 related deaths per 100,000, based on data from the New York Times, except for the five counties that form New York City, which the New York Times sums up into one metropolitan aggregate. For consistency we use CDC data for these counties. To capture lockdown policies, we use the non-pharmaceutical intervention (NPI) index from Olivier Lejeune.1 The NPI index is defined on the state level (there is little to no variation within states), ranging from 0 (no or few containment measures in place) to 6 (harsh lockdown where residents are not allowed to come out of their home) and is computed as the arithmetic average of all days in a quarter.
While there is a high correlation (0.67) between COVID deaths and the NPI index, we find independent effects of pandemic incidence and lockdown policies on unemployment rates across counties and over time.
We introduce a novel measure to gauge banks’ exposure to COVID-19 and
lockdown measures using data on bank branch deposit distributions.
Specifically, we use the 2019 bank branch deposit shares in total bank
deposits as weights for each county and then – using county-level
COVID-19 death rates per capita and a lockdown index – calculate
bank-quarter specific measures of COVID-19 and lockdown exposure. We
illustrate this idea visually with the examples of Citibank and Zions
Bancorp in Q2 2020 in Figure 1. Citi branches (solid red dots) are
concentrated in city centres, with a particularly heavy exposure to the
New York City metropolitan area – the early epicentre of the US
pandemic. Zions (hollow blue circles) is a counter example, operating a
relatively dispersed network of locations across the western US with a
presence in rural areas and cities less affected by COVID in the first
half of 2020. Computed on the bases of new Q2 deaths, this exposure
amounts to 67 for Citibank and 13 for Zions....
more at Vox