COVID-19: the economic and business impact

The new and fast evolving COVID-19 global pandemic has already caused, according to the IMF, 'the worst downturn since the great depression'. This post considers what the history and scientific analysis of previous large scale economic and disease shocks can tell us about the likely scale and location of the challenge to the global corporate sector, which are likely to play out in due course through legal restructuring, bankruptcy and litigation channels.

In particular we look at historical comparators, the three key factors impacting on the economic outcome (SIR modelling, introduction of non-pharmaceutical interventions (NPIs) and length of NPIs), leading to the likely economic impacts and identification of the industries most at risk of restructuring.

The immediate impact on companies occurs both through the direct effect of COVID-19 on employers, suppliers, consumers and networks and through the indirect impacts of government and public responses around the world.

Previous scenario modelling has suggested that only 10 to 20 per cent of the economic impact may be attributable to the direct effects of the disease and the remaining 80 to 90 per cent attributable to public and government policy responses. 

So it is important to consider how extensively and for how long governments are likely to intervene.

Previous economic and disease-driven crises

Government policy responses to the COVID-19 crisis have been made so far at amazing speed and scale, and are evolving rapidly. 

These are driven by the experience and theoretical knowledge derived from responses to previous large-scale economic crises including:

• the 2007-08 financial crisis and its aftermath; 
• the first world war (1914-18) and second world war (1939-45);
• the Wall Street Crash (1929) and Great Depression (1930-36);
• the collapse of the former Soviet Union and its aftermath (1990-97); and
• the 9/11 terrorist attacks and their aftermath.

They are also driven by medical responses to previous disease epidemics and pandemics, including Ebola, SARS, MERS, HIV/AIDS, malaria, Asian flu (1957), Spanish flu (1918-19) and, more distantly, the Black Death (14th century).    

The global pandemic risk scenario

A new pandemic flu strain had in fact been a leading fear of government and institutional planners over many years and the COVID-19 pandemic has many similar characteristics to a new flu pandemic except that it involves a novel coronovirus (SARS-Cov-2) rather than a novel influenza strain.

COVID-19 also shares many characteristics with recent SARS, MERS and Ebola epidemics and these have also provided valuable lessons to governments on potential treatment and response strategies.

Some key lessons from previous crises

The key lesson from the previous major economic crises is that government need to intervene at scale with a huge coordinated counter-cyclical Keynesian economic boost to offset the large scale global economic shocks. 

Arguably this was done successfully after the 2007-08 financial crisis, also for Europe after the second world war with the Marshall Plan, but generally omitted with terrible consequences for affected countries after the breakup of the former Soviet Union, and in the early years of the Great Depression.

There are a number of key lessons that can be drawn from responses to historic epidemics and pandemics.

• A general lesson is that each infectious disease has its own special characteristics, so the best policy responses depend on the characteristics of the specific disease and level of available knowledge and technology. The problem with COVID-19 is that key parameters of the disease are still unknown and being determined and may indeed evolve over time. Diagnosis and treatment technology is still evolving and there is currently no vaccine or standard anti-viral therapy.
• SARS, MERS, Ebola and the Chinese and South Korean responses to COVID-19 have shown that strict quarantine, isolation, contract tracing and barrier nursing can cause an epidemic to die out locally.
• Malaria and HIV/AIDS have shown that a pandemic can become endemic and drain economic activity indefinitely until good treatment options become available.
• Spanish flu showed us that pandemics can sweep across the world in a succession of waves just months apart with dramatically different effects in different waves and in different places.
• Normal flu shows that mutating viral diseases can become annual or seasonal, causing a long repeating sequence of economic shocks.
• A lesson from Spanish flu, SARS, Ebola, AIDS, malaria is that some of these infectious diseases can have very high lethality and morbidity rates.

Together, what this means is that optimal government responses to COVID-19 are driven in part by and have to respond to the particular characteristics of the disease as they become clear.

The new use of SIR modelling data

Against this broad experience background a key driver of government responses has been mathematical modelling of the pandemic using so-called 'SIR models' (i.e. with individuals in the population moving between Susceptible, Infectious and Recovered groups) under different policy interventions. 

One key parameter in these models is the so-called R or 'reproductive number'. This determines how many people on average an infected person will infect. If R is:

• greater than 1 then the epidemic tends to grow exponentially;
• around 1 then the epidemic tends to be stable and persist endemically in the population; and 
• less than 1, then the epidemic tends to evaporate over time and disappear. 

Unfortunately, the R number for COVID-19 without policy interventions appears to be much greater than 1, leading to a doubling of cases in less than a week. So total global cases on COVID-19 are estimated to have risen from one for patient zero at the end of 2019 to around 5 million in May 2020.

Another key parameter is the case fatality ratio. For seasonal flu that we are familiar with, this is typically about 0.1 per cent. For Spanish flu, the case fatality rate was much higher at around 3 per cent. 

Estimates vary for the case fatality ratio of COVID-19. For the general population of the UK it appears to be around one per cent,  but figures from Italy and Spain suggest that it could be as high as 10 per cent and even higher for population subgroups such as the elderly or those with co-morbidities. For hospitalised COVID-19 patients in England, the death rate has been around 33 per cent and so comparable with Ebola.

The importance of non-pharmaceutical interventions (NPIs)

For the proportion of patients that become seriously ill particularly with viral pneumonia following COVID-19 infection, hospital treatment often involving intensive care, oxygen treatment, intubated ventilation and round-the-clock full barrier nursing care is essential to minimise mortality and risk. 

However these medical resources tend to be in limited supply in OECD countries and often unavailable in developing ones. So in the absence of effective drug-based treatment or vaccines, OECD governments have typically chosen to implement NPIs, including:

• introducing lockdowns and social-distancing measures specifically to reduce the effective R number and growth of the COVID-19 pandemic; and 
• expanding emergency care provision with the construction of field hospitals to prevent their emergency health services being overwhelmed.  

The same argument applies more strongly in less developed countries, because there is proportionally much less availability of emergency medical care, although NPIs may be structurally harder to implement there due, for example, to cramped living conditions. 

This unfortunately means that there is likely to be an explosion of cases and mortality in the developing world and a persistent human reservoir of COVID-19 infection from now on.

How long could the lockdown last?

These are the factors behind the global lockdown approach to the COVID-19 pandemic and huge government economic policy responses to try to compensate. Given that the typical timeframe to develop new drugs is 12 to 18 months and in fact as HIV/AIDs shows may take decades, there is a possibility that a combination of lockdown measures and other NPIs will take at least a year.  

So the economic shock could be both extreme and persistent leading both to the development and uptake of new technology, e.g. related to 5G and remote working, and to a huge shakeout in the traditional industry and rise in the restructuring and bankruptcy cycle with attendant litigation.

Some likely economic impacts

The likely economic impacts of the COVID-19 pandemic and policy responses are currently expected to be huge and unprecedented in recent times, including potential annual GDP falls in 2020 alone (depending on the particular scenario applied) in G7, OECD and world economies of 10 per cent or much more.         

Government economic responses are likely to attenuate some of the immediate shocks to traditional industry to some degree, but also to store up future problems by affecting future interest rates, global borrowing  and taxes.

If we look back to the 2007-08 financial crisis, there were contractions in the financial markets sector where shocks had originated, and annual US corporate bankruptcies rose around 200 per cent between 2006 and 2009.

Given the unusual nature, huge size and potential but uncertain long duration of the COVID-19 pandemic shock and responses, it is difficult to read across from history directly about where bankruptcies and related litigation are likely to fall, and what the extent will be. 

However we can see which industries have been most affected by the business cycle and technology changes in recent years, and by the start of the COVID-19 pandemic, and on the basis that if it continues for any time, then this is where the pressure will likely become unbearable and restructuring and bankruptcies will occur.

Which industries have the greatest risk of restructuring, bankruptcy and related litigation

The International Labour Organization and other commentators flag up the following industries currently under greatest pressure:

• accommodation;
• agriculture, forestry and fishing;
• arts, entertainment, leisure and recreation;
• business and administrative activities;
• communication;
• construction;
• employment services;
• financial services and insurance;
• food services;
• information media and telecoms;
• manufacturing;
• mining and quarrying;
• motor vehicles and motorcycles;
• petrochemicals, oil and gas;
• postal services;
• real estate and business activities;
• sports;
• storage and warehousing;
• transport and travel; and
• wholesale trade.

And corresponding regions, cities and states with the greatest exposure to these industries and greatest supply chain bottlenecks as at greatest risk. Low short-term business cash reserves are also identified as a key bankruptcy risk factor.

The time-frame for consequent bankruptcies, consolidation and litigation in this area is also unclear, but if the illiquid or stalled companies and their creditors perceive that markets will remain untenable in the medium term, then they may have an incentive to undertake bankruptcy, consolidation and restructuring as quickly as possible before conditions deteriorate further, which could set off an immediate self-fulfilling tsunami of bankruptcies and contagious market shocks later in 2020 and 2021.

The difficult timing problem left for politicians

Arguably it is for this reason, combined with the political business cycle, that political leaders around the world are desperate to restart their economies as soon as possible. 

However, time to do so to avoid economic collapse is short, whereas removing the NPIs too early will be just as damaging if this launches new waves of COVID-19 infections.

Rupert Macey-Dare is a commercial barrister and PhD economist. Rupert gratefully acknowledges helpful comments from Christopher Stothers , Timothy Harkness , Elaine Graham and Richard Saldanha. These are discussion points of the author and do not constitute legal or economic advice.