Covid economy

 

The economics of a pandemic: the case of Covid-19

Paolo Surico and Andrea Galeotti Professors of Economics at London Business School

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Financial support from the European Research Council and the Wheeler Institute is gratefully acknowledged.

This Lecture 1. Science

2. Health policies

3. Economics

4. Macroeconomic policies

london.edu The economics of a pandemic: The case of Covid-19 2

Source: The Economist, 14th March 2020

The enemy

london.edu The economics of a pandemic: The case of Covid-19 3

The basics about Covid-19: what it is

• The cause: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

• The disease: Coronavirus disease 2019 (COVID-19)

• Possible origin in wet animal market in Wuhan, China, early Dec 2019

• A strain of the same virus as SARS-CoV-1, which affected 8,000 people in 2002/03

• 96% DNA match between bat coronavirus and human found in a study from February; suggests link to humans is not direct but through intermediate host

• Initially pangolins were suspected, but now seems to not be so; still unclear

• Made of 4 proteins and a strand of RNA (molecule which can store genetic information)

• One protein is the spike, which gives the crown-like appearance

• Two proteins sit in the membrane between the spikes to provide structural integrity

• In the membrane, the fourth protein is a scaffold around the genetic material
Source: The Economist, 23rd January 2020; Nature: “Mystery deepens over animal source of coronavirus” https://www.nature.com/articles/d41586-020-00548-w

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The basics about Covid-19: how it works

• Enters through nose, mouth, or eyes. Attaches to cells in the respiratory tract producing a protein called ACE2

• It fuses with the cell and releases the RNA; the hijacked infected cell will produce proteins based on the “instructions” from the virus’ RNA

• Each infected cell can release millions of copies of the virus before dying

• Affects upper respiratory tract (airways from nose to vocal chords), can spread to lungs

• In serious cases, immune system can overreact and attack lung cells; in some cases, the infection leads to acute respiratory distress syndrome and possibly death

• The virus can also end up in droplets that escape the lungs through coughing or sneezing; this leads to contagion directly to other humans, or indirectly through contaminated surfaces

• Soap destroys the virus because its molecules can wedge themselves into the membrane and break it down
Source: The Economist, 23rd January 2020; https://www.bbc.co.uk/news/av/health-51883255/coronavirus-explained-in-60-seconds; https://www.nytimes.com/interactive/2020/03/11/science/how-coronavirus-hijacks-your-cells.html

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The basics about Covid-19: characteristics

Virus appears highly transmissible
• Average patient infects 1.6 to 2.4 other people

Disproportionally affects older patients

• Fatality rate in the 70s is 3-4 times larger than the average

• Under 40 seems to be around 0.2%

• Men are twice more likely to get infected than women
Many factors unclear:

• What is the extent of undetected cases, due to mild or no symptoms, or lack of testing

• Whether asymptomatic individuals can transmit the virus and how long is the incubation period

• Whether recovery implies immunity, and for how long

• Whether the virus is seasonal and will decrease during spring and summer
Source: McKinsey & Company: Coronavirus COVID-19: Facts and Insight, updated 9th March 2020.

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Current drug efforts

 Focus on already existing drugs  Many approaches, e.g.:

  targetingreplicationabilityofvirus

  stimulatingimmunesystemtoshutdown
protein production

  decreasingtheoverstimulationofotherparts of the immune system

  Lower number of cases in China means trials are now being set in other places

  Scientistsplanningtrialsinplacesthatwill face more cases soon

  WHOworkingonprotocoltopoolpatients from many countries in standardised trials

  Fast ramping-up of production can be challenging
Source: The Economist, 14th March 2020

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The theoretical contagion curve

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The empirical contagion curve(s)

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Patterns of contagion in different countries

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Patterns of contagion in different countries

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The current situation worldwide

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Europe is now the epicentre of the crisis

Source: Johns Hopkins University CSSE (https://coronavirus.jhu.edu/map.html). Click the image to open the page

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Developing economies face higher risks

In Africa, South Asia and to a lesser extent Latin America:

• Much lower health system capacity (e.g. fewer intensive care units and ventilators).

• People have less possibility to wash their hands with soap frequently.

• More exposed to the world trade cycle because their goods (and services) are highly dependent on advanced economies demand and thus more vulnerable to the crisis.

• Far less access to the internet and therefore working from home will have far more disruptions and unprecedented economic costs than the already very large and heterogeneous costs that it will have in advanced economies (more later).

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The economics of a pandemic: The case of Covid-19 14

Pandemic

World Health Organization declared a pandemic on 11 March

• WHO definition: “A pandemic is the worldwide spread of a new disease. An influenza pandemic occurs when a new influenza virus emerges and spreads around the world, and most people do not have immunity.”

• US CDC definition: “Pandemic refers to an epidemic that has spread over several countries or continents, usually affecting a large number of people.”
Declaration about geographic spread, not about the severity of the disease
Source: WHO; Washington Post “WHO declares a pandemic of coronavirus disease covid-19”

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A historical perspective on contagious diseases

• 14th century Europe: bubonic plague. 25 million (pop. 100 million)

• 1918-1920 Worldwide Influenza epidemic. 50 million or higher

• 1981-currently AIDS: >25 million lives + 33 million living with HIV

• Recent smaller outbreaks:

• 2002-04 SARS: 8k cases, 774 death

• 2009 Avian flu: 151k-575k deaths

• 2014-16 Ebola: >11k deaths
Source: Notes by Flavio Toxvaraed; Baldwin and Weder di Mauro (2020), “Economics in the Time of COVID-19”

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Comparison with other contagious diseases

 Mortality rate = (Death / Population)  Fatality rate = (Death / Cases)*

  Measuring fatality rate is much more difficult and imprecise because the majority of tests are done on sick patients.

  This implies that the measured fatality rates are likely to overstate grossly the actual fatality rate, especially in the light of the large number of suspected asymptomatic.

 Covid-19 appears both more deadly and contagious than other well known influenzas: a main cause though is the lack of a vaccine.

Source: McKinsey & Company: Coronavirus COVID-19: Facts and Insight, updated 16th March 2020.

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Covid-19 infects more the young!

KEY DIFFERENCE

Korea has tested large share of the population ‘at random’ BUT
Italy has tested only (worst) symptomatic cases.

Comparison suggests that most carriers are actually in younger groups!

A quasi-natural experiment:

the case of the Italian town of

Vo in Veneto (FT, March 17th). london.edu

Source: https://medium.com/@andreasbackhausab/coronavirus-why-its-so-deadly-in-italy-c4200a15a7bf The economics of a pandemic: The case of Covid-19 18

  

…but kills more the old

Source: McKinsey & Company: Coronavirus COVID-19: Facts and Insight, updated 16th March 2020.

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Italians are older CHINA

Share of population

Source: https://www.populationpyramid.net/, based on United Nations Data
london.edu The economics of a pandemic: The case of Covid-19

ITALY

   

Share of population

20

Age groups

Age groups

Old Italians are more connected to the young

Average daily contacts with those 70+ by age group

    

0-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69

Germany

Italy

                

70+
0 0.5 1 1.5 2

Number of daily contacts with those 70+

The economics of a pandemic: The case of Covid-19 21 Source: Mossong et al. (2008, PLoS Med), “Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases”

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Summary of part 1 (science)

• Covid-19 is the worst health crisis of our times

• Young far more likely to be infected (the carrier) but old more likely to die

• Many countries are facing strong excess demand for health care: too many critical patients (not only Covid-19 cases) for too few ICU beds and ventilators

• Expanding health care supply requires turning hotels, barracks and possibly schools into ICU and converting selected manufacturers into ventilator makers

• Not enough medical personnel. Recall retired nurses and doctors. Train police officer and volunteers while the army carries out police duties
Full set of slides available at https://sites.google.com/site/paolosurico/covid-19 Next video: A user guide to Covid-19. Part ii – epidemiology for dummies

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This Lecture

1. Science

2. Health policies

3. Economics

4. Macroeconomic policies

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The consensus: flattening the curve

How to flatten the curve?

A. Expand intensive care capacity (expand supply of health care)

B. Slowdown the speed of contagion (contract demand for health care)

Goal: avoid excess of demand
How to achieve this more effectively?

 

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Health system capacity constraints

  Danger in the lack of capacity of health systems

  Number of ICU beds in most countries cannot cope with the spread of disease if peak is high

  Lack of ventilators:

  Italy asked its only domestic manufacturer to quadruple supply from 125 a month to 500 (each costs €17k)

  Germany has ordered 10,000

  Matt Hancock, UK health secretary: “We’re saying that if you produce a ventilator, then we will buy it. No number is too high”
Source: https://www.ft.com/content/5a2ffc78-6550-11ea-b3f3-fe4680ea68b5

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99%
94%

80%

60%

40%

20%

0%

100%

Health system capacity constraints across Italian regions

Share of Intensive Care Units used for Covid-19 patients

35%

20%
16% 16% 16%

13% 13%

12% 12%

90%
84%

67%

62% 60%
50% 48%

Average spare capacity

54%

51%

43%

40%

                     

Dati: Protezione Civile e Ministero della Salute.

Source: Matteo Villa (Istituto per gli studi di politica internazionale)
The economics of a pandemic: The case of Covid-19 26

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Whenever possible, use hotels, class rooms and barracks as Intensive Care Units (ICU).

Turn to manufacturing industry to produce or convert intensive care equipment (e.g. ventilators).

Pay for independent sector facilities: UK NHS deal added 8,000 beds, 1,200 ventilators, and 20,000 staff.

Even if the elasticity of supply for beds and equipment is high, how quickly can we train new medical personnel? Recall retired workers.

If cases regionally concentrated, spread non-contagious intensive care cases to other regions.

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Number of Intensive Care Units in Lombardy

The short-run elasticity of health care supply

 

Health system

capacity

Source: Matteo Villa (Istituto per gli studi di politica internazionale)
The economics of a pandemic: The case of Covid-19 27

A typical epidemiology model S(usceptible)I(nfected)R(ecovered)

Susceptible
Key parameter
: R0 value (Replication number)

Average number of infected people per one contagious person

Infected

 

R0 <1 : the speed of recovery is higher than the speed of contagion. Therefore, the virus dies out

Very important channel. Very simplistic for the moment. More later

R0 >1 : first phase, virus spread fast and rate of infection grows exponentially; second phase, as people recover the population becomes

immune, thereby pushing R0 <1 and the virus dies out

Recovered

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The economics of a pandemic: The case of Covid-19

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– still unknown The economics of a pandemic: The case of Covid-19

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Susceptible

What are the determinants of R0? Infected

 

1. Viruscharacteristics
a. infectious period
b. easiness of transmission

sign Covid-19 + high

Very important channel. Very simplistic for the moment. More later

+ high 2. Socialinteraction/meetingrates +

3. Fractionofimmunepopulation a. vaccination
b. recovered with immunity

– not yet available

Recovered

Susceptible

What policies can influence R0? Infected

 

A. Containment
lowering R0 but keeping it above 1 (attempted quarantine)

B. Suppression lowering R0 below 1 (social distancing)

Very important channel. Very simplistic for the moment. More later

 

Recovered

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Contagion under laissez-faire

Source: Harry Stevens, Washington Post (https://www.washingtonpost.com/graphics/2020/world/corona-simulator/)
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Containment vs suppression in theory…

 

U.K. style of approach (until mid-march)

Source: Harry Stevens, Washington Post (https://www.washingtonpost.com/graphics/2020/world/corona-simulator/) london.edu The economics of a pandemic: The case of Covid-19

China/Italy style of approach

  

32

…and in practice!

 1918 Influenza Pandemic:  Philadelphia:

  First cases reported in 17 September

  Authorities downplayed significance; city-wide parade on 28 September

  Social distancing measures implemented in 3 October
 St. Louis:

  First cases in October 5

  Social distancing measures in October 7
Source: Hatchett, Mecher and Lipsitch. Proceedings of the National Academy of Sciences May 2007, 104 (18) 7582-7587; DOI: 10.1073/pnas.0610941104

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But the trade-off is draconian!

▪ Policies to contain the virus (i.e. lowering replication number BUT NOT below 1) much less effective in flattening the curve,

possible strong repercussion in the short-run because of limited health system capacity, immunity builds up faster and so population becomes less vulnerable in the medium term.

▪ Policies to suppress the virus (i.e. lowering replication number below 1) effective in delay the spread of the virus in the short-run,
but slow-down the build-up of herd immunity,
population is vulnerable to new outbreaks in the medium term,

not a problem if vaccination is soon available; if not, buys time to expand health system capacity.

 

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The role of critical complications S(usceptible)I(nfected)R(ecovered)

Susceptible

NOTE: All these transitions are highly heterogeneous across groups of demographics and health conditions

Infected

  

Critical complications

Asymptomatic

  

Deaths

Recovered/Immune

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We focus on such cases as testing is most complete for the most severely ill patients. When examining mitigation strategies, we assume policies are in force for 3 months, other than social distancing of

Health care policies

those over the age of 70 which is assumed to remain in place for one month longer. Suppression strategies are assumed to be in place for 5 months or longer.

Table 2: Summary of NPI interventions considered.

Label

Policy

Description

CI

Case isolation in the home

Symptomatic cases stay at home for 7 days, reducing non- household contacts by 75% for this period. Household contacts remain unchanged. Assume 70% of household comply with the policy.

HQ

Voluntary home quarantine

Following identification of a symptomatic case in the household, all household members remain at home for 14 days. Household contact rates double during this quarantine period, contacts in the community reduce by 75%. Assume 50% of household comply with the policy.

SDO

Social distancing of those over 70 years of age

Reduce contacts by 50% in workplaces, increase household contacts by 25% and reduce other contacts by 75%. Assume 75% compliance with policy.

SD

Social distancing of entire population

All households reduce contact outside household, school or workplace by 75%. School contact rates unchanged, workplace contact rates reduced by 25%. Household contact rates assumed to increase by 25%.

PC

Closure of schools and universities

Closure of all schools, 25% of universities remain open. Household contact rates for student families increase by 50% during closure. Contacts in the community increase by 25% during closure.

Source: Ferguson et al. (2020), Impact of non-pharmaceutical interventions (NPIs) to reduce COVID- 19 mortality and healthcare demand. Imperial College COVID-19 Response Team. Results

london.edu The economics of a pandemic: The case of Covid-19 36 In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we

would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In

years, social distancing of the entire population, stopping mass gatherings and closure of schools and

of disruption imposed and the likely period over which the interventions can be maintained. In this

between 100 and 3000 critical care cases. Conditional on that duration, the most effective

universities) are decisions made at the government level. For these interventions we therefore
consider surveillance triggers based on testing of patients in critical care (intensive care units, ICUs). scenario, interventions can limit transmission to the extent that little herd immunity is acquired –

We focus on such cases as testing is most complete for the most severely ill patients. When examining

mitigation strategies, we assume policies are in force for 3 months, other than social distancing of those over the age of 70 which is assumed to remain in place for one month longer. Suppression strategies are assumed to be in place for 5 months or longer.

Table 2: Summary of NPI interventions considered.

ve

of

A. Policies

t

o

c

n

h

lea

di

ng to

th

ep

infection is seen once interventions are lifted

o

300

250

200

150

100

50 0

Surge critical care bed capacity

Do nothing Case isolation

Case isolation and household quarantine

Closing schools and universities

Case isolation, home quarantine, social distancing of >70s

n

oss

ib

ilit

y

that

a

se

cond

w

a

t

a

i

t

e

v

i

r

u

s

Label

Policy

Description

CI

Case isolation in the home

Symptomatic cases stay at home for 7 days, reducing non- household contacts by 75% for this period. Household contacts remain unchanged. Assume 70% of household comply with the policy.

HQ

Voluntary home quarantine

Following identification of a symptomatic case in the household, all household members remain at home for 14 days. Household contact rates double during this quarantine period, contacts in the community reduce by 75%. Assume 50% of household comply with the policy.

SDO

Social distancing of those over 70 years of age

Reduce contacts by 50% in workplaces, increase household contacts by 25% and reduce other contacts by 75%. Assume 75% compliance with policy.

SD

Social distancing of entire population

All households reduce contact outside household, school or workplace by 75%. School contact rates unchanged, workplace contact rates reduced by 25%. Household contact rates assumed to increase by 25%.

PC

Closure of schools and universities

Closure of all schools, 25% of universities remain open. Household contact rates for student families increase by 50% during closure. Contacts in the community increase by 25% during closure.

Results

In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic. Epidemic timings are approximate given the limitations of surveillance data in both countries: The epidemic is predicted to be broader in the US than in GB and to peak slightly later. This is due to the larger geographic scale of the US, resulting in more distinct localised epidemics across states (Figure 1B) than seen across GB. The higher peak in mortality in GB

Figure 2: Mitigation strategy scenarios for GB showing critical care (ICU) bed requirements. The black line shows the unmitigated epidemic. The green line shows a mitigation strategy incorporating closure of schools and universities; orange line shows case isolation; yellow line shows case isolation and household quarantine; and the blue line shows case isolation, home quarantine and social distancing of those aged over 70. The blue shading shows the 3-month period in which these interventions are assumed to remain in place.

DOI:

Page 6 of 20
Source: Ferguson et al. (2020), Impact of non-pharmaceutical interventions (NPIs) to reduce COVID- 19 mortality and healthcare demand. Imperial College COVID-19 Response Team.

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Table 3 shows the predicted relative impact on both deaths and ICU capacity of a range of s nd

The economics of a pandemic: The case of Covid-19

combined NPIs interventions applied nationally in GB for a 3-month period based on triggers of

ingle a

37

Critical care beds occupied per 100,000 of population

years, social distancing of the entire population, stopping mass gatherings and closure of schools and universities) are decisions made at the government level. For these interventions we therefore consider surveillance triggers based on testing of patients in critical care (intensive care units, ICUs).

mitigation strategies, we assume policies are in force for 3 months, other than social distancing of
those over the age of 70 which is assumed to remain in place for one month longer. Suppression
strategies are assumed to be in place for 5 months or longer. 300

Table 2: Summary of NPI interventions considered.

Surge critical care bed capacity

general social distancing

School and university closure, case isolation and general social distancing

Label Policy
CI Case isolation in the home

HQ Voluntary home quarantine

SDO Social distancing of those over 70 years of age

SD Social distancing of entire population

PC Closure of schools and universities

Results

Description

Symptomatic cases stay at home for 7 days, reducing non- household contacts by 75% for this period. Household contacts remain unchanged. Assume 70% of household comply with the policy.

Following identification of a symptomatic case in the household, all household members remain at home for 14 days. Household contact rates double during this quarantine period, contacts in the community reduce by 75%. Assume 50% of household comply with the policy. Reduce contacts by 50% in workplaces, increase household contacts by 25% and reduce other contacts by 75%. Assume 75% compliance with policy.

All households reduce contact outside household, school or workplace by 75%. School contact rates unchanged, workplace contact rates reduced by 25%. Household contact rates assumed to increase by 25%.

Closure of all schools, 25% of universities remain open. Household contact rates for student families increase by 50% during closure. Contacts in the community increase by 25% during closure.

(B)

150 100 50 0

20 18 16 14 12 10

8 6 4 2 0

In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic. Epidemic timings are approximate given the limitations of surveillance data in both countries: The epidemic is predicted to be broader in the US than in GB and to peak slightly later. This is due to the larger geographic scale of the US, resulting in more distinct localised epidemics across states (Figure 1B) than seen across GB. The higher peak in mortality in GB

Figure 3: Suppression strategy scenarios for GB showing ICU bed requirements. The black line shows the unmitigated epidemic. Green shows a suppression strategy incorporating closure of schools and universities, case isolation and population-wide social distancing beginning in late March 2020. The orange line shows a containment strategy incorporating case isolation, household quarantine and population-wide social distancing. The red line is the estimated surge ICU bed capacity in GB. The blue shading shows the 5-month period in which these interventions are assumed to remain in place. (B) shows the same data as in panel (A) but zoomed in on the lower levels of the graph. An equivalent figure for the US is shown in the Appendix.

DOI:

Page 6 of 20

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intervention policies remain in place. While there are many uncertainties in policy effectiveness, such

a combined strategy is the most likely one to ensure that critical care bed requirements would remain

We focus on such cases as testing is most complete for the most severely ill patients. When examining

within surge capacity.

B. Policies to suppress the virus

(A)

350

250
200 Case isolation, household quarantine and

Critical care beds occupied per 100,000 of population

Critical care beds occupied per 100,000 of population

The economics of a pandemic: The case of Covid-19 38
Source: Ferguson et al. (2020), Impact of non-pharmaceutical interventions (DNOPI:s) to reduce COVID- 19 mortality and healthcare demand. Imperial College COVID-19 Response Team. Page 10 of 20

Do nothing

The mortality curve during the 1918 influenza

Three weekly combined influenza and pneumonia mortality, United Kingdom, 1918–1919

Source: Taubengerger and Morens (2006), 1918 Influenza: the Mother of All Pandemics. Emerging Infectious Diseases, vol. 12, issue 1.
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A critique to Ferguson et al. (2020)

Imperial College report predicts that, under no policy measures or behavioural changes, 510k deaths in the UK, 2.2m in the US

• Suppression would still lead to >40k ICU beds needed at peak (vs actual capacity at ~5k); Expect second wave in the Fall when toughest restrictions are lifted.

• Summary: no great choices, but some worse than others
Shen, Taleb and Bar-Yam criticize some of the modelling assumptions in the previous simulations:

• Lack of additional transmission mechanisms or policy options:

• Contact tracing and door-to-door monitoring (potentially useful for the second wave)

• Geographical barriers and travel restrictions (helps contain localized outbreaks)

• Super-spreader events (fat tail of infections per person; could lead to banning of large events)

• Summary: these aspects could lead to worse outcomes in case of no policy, but also a role for more effective policy.
Source: Ferguson et al. (2020), On behalf of the Imperial College COVID-19 Response Team.
Shen, Taleb and Bar-Yam (2020), “Review of Ferguson et al (…)”. https://www.ft.com/content/16764a22-69ca-11ea-a3c9-1fe6fedcca75

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The key role of the asymptomatic

“We estimate 86% of all infections were undocumented prior to 23 January 2020 travel restrictions. Per person, the transmission rate of undocumented infections was 55% of documented infections, yet, due to their greater numbers, undocumented infections were the infection source for 79% of documented cases.”

Source: Ruiyun Li et al. (2020), Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2), Science, 16 March 2020, DOI: 10.1126/science.abb3221

A few consequences:

1. Good news: existing estimates of case-fatality rates and alike might be over-estimated
2. Goodnews:someimmunityalreadyinthesystem(consistentwiththetrendinChinawherethe

virus did not pick up after restrictions have been relaxed)
3. Bad news: it is likely that when interventions started in Europe and USA the virus was widely

spread. The estimates from simulation on how measures of suppression will flatten the curve in the short run may be over-optimistic

Bottom line: we are designing policies based on highly incomplete evidence/information

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A simple policy proposal
Random testing, statistical analysis and surveillance

1. Test a representative sample of the population (independently of symptoms), recording socio, economical, demographic and locational characteristics at the household level

2. Use standard statistical methods to infer the household characteristics most likely to predict whether someone is infected or not in the whole population

3. Develop surveillance strategies based on the information revealed in (2): nation-wide contact tracing, targeted social distancing.

Collecting the right data and conducting extensive statistical analysis can save MANY lives!!! Goal: prevent a 2nd peak and flatten the contagion curve that may spike again in the Fall 2020.

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An early success: the case of South Korea

• South Korea had a sharp increase in cases during February but has managed to slow the spread in March

• In addition the death rate as of March 22nd has been particularly low: 1.2% (vs 9.5% in Italy)

• Additional measures in South Korea:

• Rapid scaling of testing, (e.g., 5,500 test for every one million people; U.K.: 750 for every one million people)

• Readily available tests (e.g., free with doctor prescription, available privately, but reimbursed by the government is positive)

• Contact tracing, targeted testing and monitoring infected (e.g., government app to locate people)
Source: https://www.nytimes.com/2020/03/13/opinion/coronavirus-best-response.html

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Different strategies and associated policies have been devised across nations, with varying effects. It can be argued that there is some flexibility in the policies put in place, but there is a consistent call for more policies, more measures, and more severe suppression tactics

Everybody needs to do more, “Not testing alone. Not contact tracing alone. Not quarantine alone. Not social distancing alone. Do it all.” says WHO Director General Tedros Adhanom Ghebreyesus

“At this point 100% of nations that got it under control did so based on testing and tracing, isolation, quarantining” Marcel Slaathe, epidemiologist at the Federal Institute of Technology of Lausanne

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Slow response to barring large gatherings (UK, US)

Shutting theatres, restaurants, cinemas, and gyms

Closing schools

Lockdown except essential trips with police enforcement (China, Italy)

What tactics have been used across countries

Mitigation: More relaxed measures. May allow for the less vulnerable to get sick to build up immunity

Suppression: Deploying all available tactics. May allow for relaxing and re- strengthening measures over time

  

SOCIAL DISTANCING

Flexible policies such as:

• Keeping schools open for students of vital workers (Austria, Netherlands)

• Halving capacities in schools and increasing cleaning procedures (Singapore)

• Closing non-essential stores, extending market hours to reduce congestion (Germany)

  

Dispersed responsibility creating a variable response 74 tests / million (US)

Scaled up testing

Drive-through testing, separated sick and well centres

Testing program, isolation of infected, contact tracing and quarantining 5200 tests / million (SK)

 

TESTING & ISOLATION

Flexible policies such as:
Engaging and activating the public to report cases, self-isolate, and inform

contacts to get tested

  

Source: https://science.sciencemag.org/content/367/6484/1287.full The economics of a pandemic: The case of Covid-19 44

Managing a heterogeneous population

• Goal: to avoid binding health system capacity and thus flatten the curve for high risk individuals

• Homogenous interventions are likely to be sub-optimal. If supply of tests is limited: who should we
target these tests to in order to implement most efficiently the suppression/containment policy?

• At the moment, tests are primarily be given to:
all patients in critical care for pneumonia, acute respiratory distress syndrome (ARDS) or flu like illness
all other patients requiring admission to hospital for pneumonia, ARDS or flu like illness
where an outbreak has occurred in a residential or care setting, for example long-term care facility or prisons

• The value to distribute some of those tests to asymptomatic population is very large. In Korea, testing the asymptomatic proved key to limit very significantly the death toll.

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Externalities

Each individual choice affects the whole system: contagious diseases are rife with “negative externalities”

Low-risk category individuals have low incentives to self-isolate or take precautionary measures

Is it enough to tell people to self-isolate?
Taiwan strict fines up to 33k USD for non-compliants of home-quarantine

16th of March, 8 thousand Italian people reported by police for non-compliants of social-distance law See Rowthorn and Toxvaerd (2018) for theoretical analysis

Social distance for high-risk individuals requires providing services to them: food, medicine, and alike. Will the market provide these services efficiently? Congestion problem for online food delivery services

Similar problems for any services related to bandwidth. Most sectors will suffer (see later), but for services like digital services and home-delivery, this phase will spike demand and make it very inelastic. Are those services provided competitively? If not, market power will destroy surplus. Should companies offering those services (and benefitting by the virus) subsidize who will suffer most from the incoming recession? Goal is to avoid social unrest!

Non-Covid-19 patients will be crowded out in intensive care unit

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Source: The Economist, 14th March 2020

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WARNING ON INTERPRETATIONS
If a vaccine can be found in the next six months (and the scientific community seems to agree

this looks very unlikely), then suppression (i.e. countries lock down) is a dominant strategy If six months are NOT enough, there will be a very significant death toll, either way:

• Containment fronts load causalities: the curve does not flatten but people develop immunity (big unknown: will recovered cases be actually immune from being infected again?)

• Suppression backs load causalities: the curve flattens but people exposed when policy ends (big unknown: will be a vaccine developed sufficiently fast? Strategy buys time to expand health system capacity)
Alternative is Conditional Suppression, until a vaccine for mass production is ready. Not a free lunch, though, as likely to generate pervasive social unrest if the policy lasts over prolonged period
DISCLAIMER: we take no view on which policy is (second)-best. Our analysis is meant to highlight the social and economic trade-offs inherently involved with any policy option

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Summary of part 2 (health policies)

• Covid-19 health policies have all one objective: decreasing the replication number of the disease

• Given existing capacity of health care systems, suppression policies are the only one that can help us in the short-run

• Please do follow government guidelines

• Let’s use the time bought by suppression policies effectively:

• Test a representative sample of the population to gather reliable and unbiased information about the prevalence of Covid-19

• Extensive statistical analysis within and across countries (that are in different phases)

• Develop surveillance strategies based on this reliable information
Full set of slides available at https://sites.google.com/site/paolosurico/covid-19 Next video: A user guide to Covid-19. Part iii – economics for dummies

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This Lecture

1. Science
2. Health policies 3. Economics

4. Macroeconomic policies

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A major recession coming

IGM poll of top economists:

  Majority of European and US economists predict major recession

  Europeans have a stronger view than US

  Less clear in emerging markets

Source: https://voxeu.org/article/economic-impact-pandemic-igm-forum-survey (12th March)
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CHINA – NOWCAST AND FORECAST – in real-time, everyday!

Quarterly GDP growth, year-on-year, %

Q1 2020 Q2 2020

10 10 88 66 44 22 00

-2 -2 -4 -4

Source: live Now-Casting model, Reichlin (19th March 2020)

                  

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EURO AREA – NOWCAST AND FORECAST – in real time, everyday

Quarterly GDP growth, quarter-on-quarter, %

Q1 2020

0.5 0.4 0.3 0.2 0.1

Q2 2020

0.5 0.4 0.3 0.2 0.1

 

00

. -0.1  -0.1

. -0.2  -0.2

. -0.3  -0.3

. -0.4  -0.4

Source: new, international nowcasting model , Reichlin (19th March 2020)

                                       

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The economics of a pandemic: The case of Covid-19 53

Impact on stock markets

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Impact on travel services

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Source: https://www.opentable.com/state-of-industry

Impact on restaurants

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Impact on durables expenditure

In face of negative income shocks, one of the first and strongest response of households with high marginal propensity to consume is to postpone vehicle purchases. Increase in uncertainty is likely to have a similar effect that works via a precautionary motive.

Evidence (from projects funded by ERC grants): U.S. – Misra-Surico (2014, AEJM),
Italy – Surico-Trezzi (2019, JEEA),
U.K. – Cloyne-Ferreira-Surico (2020, ReStud)

Data on China suggests overall impact will be extraordinary large! Unfortunately, this is only the direct effect. More on this later.

 

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Impact on the supply chain

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Impact on the supply chain cont’ed

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McKinsey Global report (9th march 2020)

The most affected sectors

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The search for a safe haven

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Meanwhile in Russia and Saudi Arabia

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Short-run effects: pollution levels decline

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Social isolation will increase

• Increase in social isolation during social distancing/quarantine phase

• Costly across demographics..

• .. And particularly so for elderly, whose families are more likely to distance from to minimize chances of contagion

• Older population is both:

• vulnerable to the disease

• AND vulnerable to the side effect of the disease
Source: New York Times (https://www.nytimes.com/2020/03/13/opinion/coronavirus-social-distancing.html)

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High-skilled more likely to work form home

• Firms may reconsider and increase acceptance of remote work going forward

• More flexibility for workers

• Lower congestion in cities

• Unequal opportunity:

• More high-skilled individuals can work from home (education, financial services, corporate jobs; not health professionals) than low-skilled workers (drivers and deliverers, cleaners, distribution supply chain, retail workers, etc.)

• Skills may correlate with liquidity to sustain brief unemployment spell during the health crisis
Source: The Guardian (https://www.theguardian.com/business/2020/mar/13/us-companies-work-from-home-policy-ford-general-motors)

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High earners more likely to work from home

• 29% of American workers could work from home according to a BLS survey in 2017-18

• Proportions varies widely across occupation (see chart) and industry

• Income is also a crucial factor:

• 0-25th percentile: 9.2%

• 25-50th percentile: 20.1%

• 50-75th percentile: 37.3%

• 75-100th percentile: 61.5%

Source: BLS (https://www.bls.gov/news.release/flex2.t01.htm)

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The economics of a pandemic: The case of Covid-19 66

Most workers in manufacturing, retail, leisure, construction and transportation and utilities can hardly work from home.

Source: BLS (https://www.bls.gov/news.release/flex2.t01.htm)

Strong heterogeneity across sectors

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The economics of a pandemic: The case of Covid-19 67

Potential long-term changes

• Universities and business worldwide have quickly moved towards remote working and learning for the remainder of the school year

• Despite the disruption, this event has been seen as a critical opportunity for digital learning

• Companies hope this can become a persistent change

• Zoom, a popular remote conferencing software, has seen a sharp increase in its stock price during the first few months of 2020

Source: https://www.nytimes.com/2020/03/17/style/zoom-parties-coronavirus-memes.html; https://www.marketwatch.com/story/this-is-online-educations-moment-as-colleges-close-during-coronavirus-

pandemic-2020-03-17

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Home schooling, internet access and education

More than 770 million learners are now being affected by school and university closures (United Nations).

School closing: “home-schooling” and on-line tutorial

• Empirical studies show strong impacts of quality of parental education on pupil educational attainment and long-term outcomes (Heckman, 2006) Science

Hence, School closing will reinforce this inequality

• Access to on-line resources not universal:

Between 56 million and 80 million people in China reported lacking either an internet connection or a web-enabled device in 2018 (NY Times, March 17)

10% of Households in UK have no internet connection.

• The closures could disproportionately affect children from poor and low-income families, many of whom

receive their weekday breakfast and lunch and, in some cases, dinner on campus (LA Times, March 13). Source: World Economic Forum (https://www.weforum.org/agenda/2020/03/3-ways-coronavirus-is-reshaping-education-and-what-changes-might-be-here-to-stay/)

   

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The race between supply and demand

At first, covid-19 may look like a supply shock:

• Disruption in global supply chains

• Quarantine and social distancing across the world decreasing labour supply
Aggregate Supply (AS) move from AS0 to AS1 Different from previous crises:

P

AS1 AS0

   

• •

Great recession of 2007-09: origin of supply shock was in the financial sector

War/natural disaster: origin of the supply shock is destruction of infrastructure or large-scale permanent loss in labour force.

AD0

Q’ Q Q

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70

The race between supply and demand

Then, demand effects materialize:

  Uncertainty about the progress of disease

  Uncertainty about economic policies that will alleviate

  Non-permanent workers will lose income, particularly in affected industries (e.g. hospitality, manufacturing)

  Households increase precautionary savings

  Firms wary of investing until situation
clears; also lack liquidity to do so

P

AS1 AS0

       

Q’’ Q’ Q

AD0 AD1

Q

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71

The race between supply and demand

Feedback loop into supply:

 Firms (especially those more dependent on cash flows) lack liquidity to fulfill commitments while facing lower demand and thus are forced to file for bankruptcies.

Demand and supply loop similarly to financial crisis, though uncertainty is about the disease.

Different from war/disaster: there, demand might increase as governments redirect war efforts towards fight/rebuild and so potentially inflationary.

P

AS2

AS1 AS0

        

london.edu The economics of a pandemic: The case of Covid-19

AD0 AD1

Q’’’ Q’’ Q’ Q Q 72

The race between supply and demand

Feedback loop into demand:

 Workers who lose jobs from closing businesses do not have an income anymore and therefore lower consumption, eventually depressing aggregate demand.

P

AS2

AS1 AS0

             

Q’’’’

Q’’’ Q’’

AD0 AD1

AD2

Q’Q Q

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73

The destruction of economic surplus

Covid-19 virus is not ‘just’ a (large) shock on real economic fundamentals; it is a shock on the frictionless of the market;

it introduces ‘a wall between demand and supply’ with strong complementary feedbacks in the real economy;

contraction in supply, leading to a contraction in demand, leading to contraction in supply…..leading to a large destruction of economic surplus

P

AS2

AS1 AS0

         

(red shaded area in the chart on the right)
london.edu The economics of a pandemic: The case of Covid-19

Q’’’’

Q’’’ Q’’

AD0 AD1

AD2

Q’Q Q

74

Supply vs demand

• IGM poll of top economists suggest that impact of demand shock will be larger than that of supply

Source: https://voxeu.org/article/economic-impact-pandemic-igm-forum-survey

london.edu The economics of a pandemic: The case of Covid-19 75

Many small businesses rely on cash flows

4.5 4 3.5 3 2.5 2

1 0.5 0

Cash Flows to Asset Ratio By Firm Size

 

Firms with cash flows to asset ratio above 0.5 account for about 10% of employment among private businesses

• All private businesses account
for more than 60% of total 1.5

employment. So (small) firms with cash flows to assets > 0.5 account for some 6% of total employment in the economy

            

Source: based on calculations from Bahaj, Foulis, Pinter and Surico (2019) on the universe of private non-financial firms in the U.K. The research in this paper has been funded by an ERC Consolidation Grant, whose support is gratefully acknowledged.

firm size

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Cash flows to asset ratio

Many mortgagors and renters have little cash-on-hands

Net Liquid wealth

                                                                                                                            

Net Housing wealth

                                                                                                                      

Figures in the table refer to £pounds value at 2005 prices

About 30-35% of the population (1/2 mortgagors + 1/2 renters) spend most of the cash flows they receive

Source: Cloyne, Ferreira and Surico (2020) on the U.K. household data
The research in this paper has been funded by an ERC Consolidation Grant, whose support is gratefully acknowledged.

                                   

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Summary of part 3 (economics)

• Global recession seems inevitable, possibly in emerging markets too.

• Overall, demand effects probably much larger than the initial supply shock.

• Uncertainty, panics and lock-down policies key to drive large drop in demand.

• The investment of many firms (esp. small and young) and spending of many households (esp. renters and mortgagors) depend largely on cash flows.

• Large drop in demand thus force these firms to close. This leads to a rise in lay-offs and a further drop in consumption. Economy enters a depressing loop!
Full set of slides available at https://sites.google.com/site/paolosurico/covid-19 Next video: A user guide to Covid-19. Part iv – policy options

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This Lecture

1. Science
2. Health policies 3. Economics

4. Macroeconomic policies

london.edu The economics of a pandemic: The case of Covid-19 79

A four stage strategy?

Link: https://www.youtube.com/watch?v=nSXIetP5iak
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Flattening the recession curve

  Short-run trade-off between flattening the epidemic curve and the size of the recession. Slowing down the peak of infections is likely to prolong the time that the economy is not at full capacity

  Economy is complex, made of interconnected agents (suppliers, customers, consumers, workers, banks)

  Individually rational decisions can cause a catastrophic chain reaction:
i. Consumers not spending because self-isolated
ii. Firms cut costs and reduce workers, default on loans and suppliers
iii. Banks with non-performing loans will cut lending

For health, isolation has positive externalities.
For the economy, isolation has negative externalities.

Source: Gourinchas: “Flattening the Pandemic and Recession Curves”, 13 March 2020

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Health policies and health expenditure

• At the FIRST sign of a highly contagious disease, isolate immediately the more vulnerables (e.g. the old) and test ‘at random’ representative samples of the population to identify the most contagious groups.

• Those who test positive need to self-isolate, independently of the symptoms.

• Trace the positive case and keep testing and isolating (more on next slide).

• Expand intensive care capacity (both beds and equipment) by building new units or convert available estates (e.g. hotel, barracks, etc)

• If the contagion is geographically concentrated, spread non-pandemic-related intensive care cases to other regions.

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Designing an efficient testing strategy

Once the curve is flatten out, how can social distancing be relaxed without a spike in infections?

• a. b. c.

Only available option: identify the infected fast, isolate them and trace the source.

But how? A three-step approach.
Scale up availability of tests for infection.
Develop simulation for optimal testing strategy.
Stratify tests across population to identify the key observable characteristics of diffusion.

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Direct and Indirect Effects on the economy

• Round 1: supply side disruptions and large death toll generates heightened uncertainty and panic for households and businesses

• Round 2: heightened uncertainty and panic leads to drop in consumption and investment.

• Round 3: large drop in demand dries up corporate cashflows, triggering firms’ bankruptcies

• Round 4: layoffs and exiting firms generate sharp rise in unemployment

• Round 5: Labour income fall significantly and non-performing loans spike up, which weakens demand and increases uncertainty further. Back to round 2 for another loop!
Indirect effects 2-to-5 potentially very large but not unprecedented by historical standards.
Major macroeconomic cost is associated with the suppression strategy to solve the health crisis.

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Economic costs of a suppression strategy

Assume only a temporary drop in economic activities: 50% for a month and 25% in the two following months. Then, GDP drop of almost 10% of annual output! (Gourinchas, 2020).

Make the countries lock down longer and add the supply/demand downward spiral, then the actual costs (without policy interventions) could exceed 15% of GDP!

Output loss associated with the Great Recession was about 4.5% and still unrecovered.

Output loss associated with the Covid-19 crisis likely to be permanent. A global recession in the advanced world is inevitable and a recession in China seems now likely already in 2020Q2!

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What macroeconomic objectives?

1. Ensure households delay mortgage/rental payments and have cash-on-hands.

2. Ensure workers receive paychecks even in quarantine or if temporarily laid off.

3. Ensure firms have enough cash flows (to pay workers and suppliers), especially small and young businesses, and can avoid bankruptcy.

4. Support financial system to avoid the health crisis becomes a financial crisis.

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The economics of a pandemic: The case of Covid-19 87

What macroeconomic policies?

A. Government spending on public health sector.

B. Tax relieves, tax cuts, tax holidays, tax incentives.

C. Tax rebates and temporary universal income to households; cash grants to firms.

D. Cut interest rates, launch QE programmes and lending schemes.

All would help but (C) most likely to stop immediate economic collapse.

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Whatever mix is chosen, policies need to:

i. be now and be massive, of the same order of magnitude of the output loss.
UK announced a package worth about 15% of GDP. Unprecedented!

ii. start from health expenditure: invest in testing and expansion of supply. Too late now for the first peak but still time to contain the second peak in the Fall of 2020.

iii. be about cash disbursements to households and businesses.
Tax incentives or cuts, emergency loans and borrowing on better terms, by their own, are unlikely to prevent a collapse in aggregate demand.

iv. use a coordination of fiscal and monetary interventions to maximize and multiply impact and provide financial backing to each other policy.

v. be global: interconnected society and economy requires global coordination.
The economics of a pandemic: The case of Covid-19 89

How to finance these macroeconomic policies?

Debt is attractive, especially given the ultra-low interest rates. But guaranteed by whom?

UK/US governments have sufficient credibility to afford it without too much sovereign risk but would still require coordination with the central bank (more on next slide)…

But Italy can’t! Lack both government credibility and independent national central bank.

An Italian problem? Not really. Just timing is different: “Europeans are all Italians”

Source: Ellison-Scott (2020, AEJM)

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A Governance Crisis in the EU. Again!

Common shocks require common policy.
von Der Leyen: “We will give Italy all it asks for”

Question is how? A few options:
A) Eurobonds via (an empowered) ESM
B) Coordinated sovereign debt issuance, ‘coronavirus bond’ C) Helicopter money

All require ECB backing by some form of public debt monetisation: the last economic taboo! ECB launched a €750bn Pandemic Emergency Purchase Programme to buy government and corporate debt until Covid-19 crisis is over. Fed launched a similar $700 bn programme.

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Summary of part 4 (macroeconomic policies)

• With little or no government interventions, economic costs will be immense!

• Government priority should be on health expenditure but need a strategy to flatten the contagion curve that may spike back in the Fall of 2020.

• Simple proposal: ‘random testing’ to identify individual treats that predict being infected and then targeted testing and surveillance on the ‘most likely’ infected.

• Government spending should be now and as large as the predicted economic costs, focusing directly on cash disbursement to firms and households.

• Central banks should provide financial backing to the government, not just through their own reserves but also by printing money if necessary.

• Global shock needs global response. No country has fiscal capacity to stand alone.
Full set of slides available at https://sites.google.com/site/paolosurico/covid-19
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