Estimating the Impact of COVID-19 on
Corporate Default Risk
Jonathan William Welburn, Aaron Strong
RAND Social and Economic Well-Being
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Estimating the Impact of COVID-19 on Corporate Default Risk
Jonathan W. Welburn, Aaron Strong
The COVID-19 global pandemic has resulted in a fast-moving health crisis with
significant uncertainty. Policy makers have responded by imposing social
distancing policies (non-pharmaceutical interventions) which close schools, bars,
and restaurants, close non-essential business, restrict movement, and impose
quarantines. Under the weight of significant business interruptions, reductions in
both supply and demand, and supply chain disruptions the health crisis has given
way to deep economic contraction. The confluence of sharp economic losses and
historic levels of corporate debt risk producing a financial crisis on top of the health
crisis. We build on the work of Vardavas et al. (2020) and Strong and Welburn
(2020), who estimate the health and economic impacts of COVID-19 under a set
of social distancing scenarios, to estimate the potential for firm exits. We use a
structural model of financial distress based on Merton's distance to default to
estimate the likelihood of firm defaults conditional on losses in aggregate income.
Using the Vardavas et al. (2020) set of scenarios and estimations of reduced income,
we estimate average firm default probabilities over a large set of US listed firms.
We find that the crisis coincides with exceptional risk of corporate default. Under
modest levels of social distancing and economic losses, we estimate high levels of
average corporate default risk. As social distancing measures and economic
contractions persist, levels of corporate default risk exceed those of the 2008
financial crisis. Under the harshest scenarios of prolonged strict interventions, we
estimate exceptional levels of corporate default risk ranging from to double to triple
those witness during the 2008 financial crisis. While unmodeled, recent credit
market interventions may thwart the worst of the default risk scenarios that we
estimate by extending credit access to firms on the brink of insolvency.
Acknowledgments: We would like to thank Tyna Eloundou, Jeanne Ringel, Krishna
Kumar, and Howard Shatz for their useful support, comments, and feedback. We would
also like to than Anita Chandra and Peter Hussey for their support of this work through
RAND 's Social Economic and Well-Being and Health Care research divisions.
1987 1992 1997 2002 2007 2012 2017
Total default rate (%) Investment-grade default rate Speculative-grade default rate
𝑑𝑉 = 𝜇𝑉𝑑𝑡 + 𝜎 𝑉𝑑𝑊
𝐸 𝐹 𝑟
𝐸 = 𝑉𝒩(𝑑 ) − 𝑒( )𝐹𝒩(𝑑 )
ln 𝑉 𝐹⁄ + (𝑟 + 0.5𝜎 )𝑇
, 𝑑 = 𝑑 − 𝜎 √𝑇
𝑇 𝑇 = 1
𝜎 = 𝜎
𝐸 + 𝐹
+ (0.05 + 0.25 ∗ 𝜎 )
𝐸 + 𝐹
𝜎 𝐸 𝐹
ln(𝑉 𝐹⁄ ) + (𝜇 + 0.5𝜎 )𝑇
𝜋 ≡ 𝑃(def | 𝐸, 𝐹, 𝜎 ) = 𝒩(−𝐷𝐷 ) = 𝒩 −
ln[(𝐸 + 𝐹) 𝐹⁄ ] + (𝑟 + 0.5𝜎 )𝑇
𝜓 = 𝐿 𝑌 =
, 𝜓 ∈ [0,1]
𝑁 = 𝑁 − 𝜓 ∗ Δ ∗ 𝐺
𝐹 = 𝐹 + 𝜓 ∗ Δ ∗ 𝐺.
𝑉′ = 𝑁𝐼 + 𝛿 (1 + 𝑔)𝑁𝐼 = 𝑉 − (𝑁𝐼 − 𝑁𝐼 )
𝐸 = 𝑉 − 𝐿 + 𝑇𝐴 = 𝐸 − (𝑁𝐼 − 𝑁𝐼 ).
𝜎 = 𝜎
𝐸 + 𝐹
+ (0.05 + 0.25 ∗ 𝜎 )
𝐸 + 𝐹
𝜋 = 𝒩 −
ln[(𝐸′ + 𝐹′) 𝐹⁄ ] + 𝑟 + 0.5𝜎 𝑇
𝑇 = 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
0.0%-2.0% 2.0%-4.0% 4.0%-6.0% 6.0%-8.0% 8.0%-10.0%
public health and the economy, we find that resulting large losses in output may further
exacerbate economic shocks through significant risk of corporate default and firm exit.
The COVID-19 pandemic hits corporate debt markets which would otherwise be facing
large headwinds from historic levels of corporate debt. Significant income losses and high
preexisting debt levels result in high risk levels where even the most modest of social
distancing scenarios result in high risk levels. However, as the economic consequences
become more burdensome, either as a result of severe social distancing or long crisis
durations, our estimated average likelihood of default correspond to default rates which
exceed the spike in corporate default seen during the 2008 crisis.
This analysis, of course, comes with limitations. First, we estimate default risk for
listed firms and thereby do not capture risks to many small businesses which may be
higher. Second, we take the approach of using a structural model to estimate default
likelihoods conditional on estimated losses. As estimations compound, uncertainty grows.
This effort aims to bound default risk, all things equal, and in the absence of policy.
However, the extraordinary measures - both monetary and fiscal - will likely lessen the
impact of the COVID-19 crisis in the near term making our estimates more of an upper
bound in reality.
Policy interventions alter the landscape of default risk. Following the emergency
reduction in its benchmark interest rate on March 1, 2020, the U.S. Federal Reserve has
provided trillions of dollars in stimulus to support credit markets across assets classes.
While the Fed began purchasing commercial paper and investment grade commercial debt,
providing support to fund daily corporate expenses, on March 17th , they extended their
support to midsize corporations on March 23rd , expanded support on March 23rd , and
expanded commercial paper purchases to sub-investment grade debt on April 9th (Julia
Ambra and Wyatt, 2020). This, in combination with large stimulus efforts of the CARES
Act and the coronavirus relief program of the Small Business Administration, pr