metadata: authors: 0: author: Maliszewska,Maryla
1: author: Mattoo,Aaditya
2: author: Van Der Mensbrugghe,Dominique
count: World
docna: 0: docna: The Potential Impact of COVID-19 on GDP and
            Trade : A Preliminary Assessment
docty: Policy Research Working Paper
subtopic: International Trade and Trade Rules,Transport Services,Public Health Promotion,Business Cycles and Stabilization Policies,Pulp & Paper Industry,Textiles, Apparel & Leather Industry,General Manufacturing,Food & Beverage Industry,Common Carriers Industry,Construction Industry,Plastics & Rubber Industry
teratopic: International Economics and Trade,Transport,Health, Nutrition and Population,Macroeconomics and Economic Growth,Industry
abstracts: cdata!: The virus that triggered a localized
            shock in China is now delivering a significant global shock.
            This study simulates the potential impact of COVID-19 on
            gross domestic product and trade, using a standard global
            computable general equilibrium model. It models the shock as
            underutilization of labor and capital, an increase in
            international trade costs, a drop in travel services, and a
            redirection of demand away from activities that require
            proximity between people. A baseline global pandemic
            scenario sees gross domestic product fall by 2 percent below
            the benchmark for the world, 2.5 percent for developing
            countries, and 1.8 percent for industrial countries. The
            declines are nearly 4 percent below the benchmark for the
            world, in an amplified pandemic scenario in which
            containment is assumed to take longer and which now seems
            more likely. The biggest negative shock is recorded in the
            output of domestic services affected by the pandemic, as
            well as in traded tourist services. Since the model does not
            capture fully the social isolation induced independent
            contraction in demand and the decline in investor
            confidence, the eventual economic impact may be different.
            This exercise is illustrative, because it is still too early
            to make an informed assessment of the full impact of the
            pandemic. But it does convey the likely extent of impending
            global economic pain, especially for developing countries
            and their potential need for assistance.
repnme: repnme: The Potential Impact of COVID-19 on GDP and
            Trade : A Preliminary Assessment
display_title: The Potential Impact of COVID-19 on
            GDP and Trade : A Preliminary Assessment
listing_relative_url: /research/2020/04/31944777/potential-impact-covid-19-gdp-trade-preliminary-assessment
topicv3: Tourism m1326299 825,Manufacturing Sectors m1326521 1281,Transport m1326661 135,Trade m1326924 698,Pandemics m1327520 2167
publishtoextweb_dt: 2020-04-10T00:00:00Z
historic_topic: International Economics and Trade,Transport,Health, Nutrition and Population,Macroeconomics and Economic Growth,Industry
origu: EFI-MTI-TIC-Trade and RI (ETIRI)
no_of_pages: 26
author_keys: 0: author_key: 545393
1: author_key: 429183
2: author_key: 428604
model_extractions: Policy Research Working Paper 9211 The Potential Impact of COVID-19 on GDP and Trade A Preliminary Assessment _Maryla Maliszewska Aaditya Mattoo Dominique van der Mensbrugghe_ East Asia and the Pacific Region Office of the Chief Economist & Macroeconomics, Trade and Investment Global Practice April 2020
Policy Research Working Paper 9211

# **Abstract**

The virus that triggered a localized shock in China is now delivering a significant global shock. This study simulates the potential impact of COVID-19 on gross domestic product and trade, using a standard global computable general equilibrium model. It models the shock as underutilization of labor and capital, an increase in international trade costs, a drop in travel services, and a redirection of demand away from activities that require proximity between people. A baseline global pandemic scenario sees gross domestic product fall by 2 percent below the benchmark for the world, 2.5 percent for developing countries, and 1.8 percent for industrial countries. The declines are nearly 4 percent below the benchmark for the world, in an amplified pandemic scenario in which containment is assumed to take longer and which now seems more likely. The biggest negative shock is recorded in the output of domestic services affected by the pandemic, as well as in traded tourist services. Since the model does not capture fully the social isolation induced independent contraction in demand and the decline in investor confidence, the eventual economic impact may be different. This exercise is illustrative, because it is still too early to make an informed assessment of the full impact of the pandemic. But it does convey the likely extent of impending global economic pain, especially for developing countries and their potential need for assistance.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific Region and the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mmaliszewska@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# The Potential Impact of COVID-19 on GDP and Trade: A Preliminary Assessment

Maryla Maliszewska, Aaditya Mattoo and Dominique van der Mensbrugghe<sup>**1**</sup> _JEL Codes: F17, I15, C68_ _Keywords: COVID-19, Infectious Disease, International Trade, Economic Growth, CGE Modeling_

> 1 A joint product of the Chief Economist Office of East Asia and Pacific and the Trade and Regional Integration Global Unit. Maria Pereira provided excellent research assistance. We are grateful to Caroline Freund, Ergys Islamaj, Antonio Nucifora and Ekaterine Vashakmadze for helpful suggestions and discussions. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
# **1. Introduction**

As the coronavirus emerged in China and spread globally, authorities have acted to limit its spread. Experience with similar diseases reveals that while the human costs are significant, the bulk of the economic costs are due to the preventive behavior of individuals and the transmission control policies of governments (Brahmbhatt and Dutta, 2008). Current experience is no different. As the virus spread internationally, many countries have already taken or will eventually take action to limit the spread, through social isolation policies, such as shutting educational institutions, limiting work and restricting the mobility of people. The preventive actions have had an immediate and significant impact on all economies, and through trade and tourism, on partner economies.

Economic models can be used to model the consequences of pandemics (Burns et. al. (2006), Bloom et. al. (2005), Lee and McKibbin (2004), McKibbin et. al. (2006), Evans et. al. (2014)). Building on previous studies, this paper focuses on four channels—i) the direct impact of a reduction in employment; ii) the increase in costs of international transactions; iii) the sharp drop in travel; and iv) the decline in demand for services that require proximity between people.

We consider two scenarios: a global pandemic and an amplified global pandemic. In the case of the global pandemic, it is assumed that countries bear only one-half of the impact of the full China shock. In the case of the amplified global pandemic, the shocks are uniform across all countries. A baseline global pandemic scenario sees GDP of the world fall by 2 percent below the baseline, of developing countries by 2.5 percent, and of industrial countries by 1.8 percent. The declines are nearly twice as large in an amplified pandemic scenario in which containment is assumed to take longer.

It is still too early to make an assessment of the impact of the virus based on full statistical evidence. High frequency data are providing some indicators, but it is hard to assess the depth and the breadth of the pandemic as it spreads, and to precisely estimate how long it will take countries to return to normal activity levels. This paper seeks to illustrate the transmission channels and heterogenous impact of COVID19 on output and trade in different scenarios. The results presented here should be regarded as scenario analyses, not as projections. The implemented shocks are illustrative and based on previous episodes of global epidemics or on preliminary data.

The assumptions on the spread of the disease are not grounded in epidemiological projections, they do not take into consideration the quality of the health systems in the affected countries, transport connections to affected countries, and health policy responses to the outbreak. The model incorporates the decline in demand due to reduced production and incomes but does not fully capture the independent contraction in demand, except for the reductions in tourism and other services that require close human contact. It also does not include the decline in investor confidence and any financial repercussions. We capture some aspects of global value chains trade, but a fuller analysis will require a richer data set. This analysis will evolve as we fine tune assumptions in line with early impacts and evaluate potential scenarios of the spread of the virus.

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# **2. Methodology, transmission channels, and scenarios**

# **2.1 Global computable general equilibrium model Envisage**

The quantitative findings in this paper are based on simulations using a version of the Envisage model calibrated to GTAP Version 10A (Aguiar et al. (2019); see Annex 1 for aggregation mappings). The latter has a 2014 reference year and the model is being used in its comparative static specification. Envisage is a relatively standard computable general equilibrium (CGE) model.<sup>2</sup> The model has been configured for a short-term closure with the following assumptions:

- Production elasticities have been reduced to near zero, so there is little substitution possibility across inputs in production.

- In order to capture the typically durable relationship within global value chains, trade elasticities for goods have been reduced from their standard values to represent the short-run inability to replace imported components and final goods with products from other countries. The elasticity between domestic and imported goods has been set to 0.4. The elasticity of substitution across import sources has been set to 0.8.

- Labor supply is exogenous, while wages adjust to equate demand and supply of labor. The return to capital is fixed, while supply of capital is endogenous.

# **2.2 Transmission channels**

The shocks have been divided into four sets, but all are assumed to occur simultaneously, i.e. the final shock encompasses all shocks.<sup>3</sup> The duration of the shocks is currently unknown, though, based on prior events, it is likely to last from 8-12 weeks and most likely unsynchronized across countries.

1. The first shock is a drop in employment by 3 percent below the baseline. With lower availability of labor, we would expect wages, ceteris paribus, to rise, while return to capital is unchanged under our assumptions. Lower labor also means lower demand for capital, as firms need a combination of labor and capital to produce goods and services.

Underutilization of capacity takes place due to factory closures (workers stay home, leaving capital and natural resources idle) as well as social distancing forcing workers to stay at home. Due to higher rates of contagion, immediate unemployment consequences of COVID-related business closures and negative demand shock, we conservatively assume the underutilization of the labor force to be 3% on average over the whole year across all sectors of the economy.<sup>4</sup> There is a lot of uncertainty surrounding these assumptions, and the country-specific employment effects will depend on the duration and intensity of the pandemic and containment measures, the sectoral composition of employment, and the flexibility of the labor market.

> 2 A full description of the Envisage model is available at

> https://mygeohub.org/groups/gtap/File:/uploads/ENVISAGE10.01_Documentation.pdf.

> 3 The shocks are scaled down as compared with the shocks derived for Liberia under the Ebola epidemic, as in Evans et al. (2014).

> 4 This is a conservative estimate. Some estimates put potential reduction of employment at the annual level at 10%, assuming unemployment of over 30% in Q2 and returning to pre-crisis level in Q3 and Q4. <u>https://www.stlouisfed.org/on-the-economy/2020/march/back-envelope-estimates-next-quartersunemployment-rate</u>

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2. The second shock (cumulative with the supply shock) raises the international trade costs of imports and exports by 25%. The shock is applied across all goods and services. Trade costs arise when goods cross borders.

The assumed increase in transport and transactions costs in foreign trade is driven by additional inspections, reduced hours of operation, road closures, border closures, increases in transport costs, etc. Evans et al. (2015) estimate that the outbreak of Ebola could lead to an increase in trade costs of 10%. Since COVID-19 is affecting more countries and the containment measures seem more severe due to the efforts to contain the virus, we amplified the shock increasing international trade costs of imports and exports to 25%.

3. The third shock entails a sharp drop in international tourism. This is captured via a 50% consumption tax on international tourism-related services, such as transport, accommodation, etc. This generates a typically small revenue for the relevant countries that is rebated back to households with a lump sum.<sup>5</sup> The export tax is applied to both outbound and inbound (tourist) services that include: accommodation, food and service activities; water, air and other transport; and recreational and other services.

The effects of COVID-19 in the tourism, hospitality and recreation sectors have been unprecedented. In the accommodation and lodging sectors, quarterly revenues are down 75%. Travel agents saw a slowdown in bookings of 50% in March of 2020. Airlines worldwide are expected to lose $113 billion in revenues for 2020. In the peak of the outbreak, 70% of scheduled flights in China have been canceled. As of mid-March 2020, international travel has ground to a halt, with the World Travel and Tourism Council (WTTC) estimating that global travel would decline at least 25 percent in 2020. To capture the effects of the drop in tourism, hospitality and recreation services, we implemented a 50% tax on the export of trade-related services, resulting in a drop in exports of tourism services at a global level of 20-32%.

4. The fourth shock represents a demand switch by households who purchase fewer services requiring close human interaction, such as mass transport, domestic tourism, restaurants, and recreational activities, while redirecting demand towards consumption of goods and other services. Demand for the targeted services is assumed to drop by 15%. This results in a reallocation of household demand across sectors, while total expenditures are still driven by previous shocks and relative prices of goods in the consumption basket.

It is difficult to estimate the impact of social distancing and overall decline of economic activity on those selected sectors, but anecdotal evidence suggests that it is likely to be significant. With social distancing measures and closures of nonessential businesses, the bookings through Opentable network declined by 100% in the second half of March (data form the United States, the United Kingdom, and Germany). Depending on the length of the business closures, the annual impact could vary drastically. The decline of 15% at an annual level seems like a middle of the road estimate.

5 There are a number of ways to affect demand choices by increasing the cost of purchasing the relevant good. The solution in this case has been to impose export taxes that directly affect the price of the targeted services. The revenues generated by this tax are rebated back to households.

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<!-- Start of picture text --> , _nCov19 Shock<br>Envisage Model<br>_. International trade costs<br>a increase<br>Lower demand for services af a<br>requiring human interaction af a Tourism inbound and<br>‘. af af crncnt AF 1) cmon ~ outbound declines<br>nn<br>at | interme diate<br>_¢©_ GoodsDemand and CG o nsumptionwerament ee GoodsProduceand<br># Pid Services Services<br>“e<br>== Travde:<br>Savings < __ ——— Natural Resources<br>A‘ rs ee al Manufacturing<br>! Tra nsfers, Services Transport<br>Mh ce se Services Services<br>Supply Demand<br>Inputs Inputs<br>KY (KU)<br>Labor Underutilization (L)<br>Decline of Investment (K)<br><!-- End of picture text -->
# **“Amplified global pandemic” scenario**

In the amplified global pandemic scenario, we capture a bigger reduction in annual output due to a deeper and more prolonged pandemic. The same shocks are assumed in all countries, effectively doubling the shocks for all countries and keeping the China shock unchanged.

# **3. Impacts of COVID-19**

# **3.1 Macroeconomic impacts**

The global pandemic scenario assumes that the pandemic hits China the hardest, but also hurts other countries, so we use it as an example to explain the impacts on other countries. The global pandemic is expected to reduce Chinese GDP by 3.7% (all percentage changes are reported in relation to the baseline). The impact on China becomes progressively more negative as impacts of the shocks accumulate. First, the supply shock reduces GDP through reduction in employment (and capital) leading to lower production and exports, as well as lower imports due to lower income of households and shrinking production.

Second, with higher trade costs, the price of a unit of imports and exports increases and the competitiveness of Chinese production declines due to higher costs of exporting and higher costs of inputs; final goods’ prices also increase. The rising trade costs represent a productivity loss, since additional inputs are needed to bring goods to their consumers, instead of being available for consumption and investment. Further, inbound and outbound tourism decreases significantly, resulting in further decline of Chinese GDP and exports. Finally, with the composition of expenditures changing with lower demand for sectors hit by social distancing (transport, hospitality) and relatively higher demand for goods, the composition of output tilts towards manufacturing. Loss of competitiveness and lower income result in a decline of total exports by 3.5%, while imports decline by 3.2 %. China’s exports of tourist-related activities decline by 29%, while imports of tourist-related activities decline by 37%. Real consumption by households declines by 7.2%.

Global GDP is expected to decline by 2.1%, while developing countries’ GDP is expected to decline by 2.5% and high-income countries by 1.9%. The biggest GDP losses under the global pandemic scenario are expected in East Asia and Pacific (EAP) countries due to their relatively deep integration through trade and direct impact on tourism, e.g. Cambodia (3.2 %), Singapore (2.1 %), Hong Kong SAR, China (2.3 %), Thailand (3 %), Vietnam (2.7 %), and Malaysia (2.1 %).

Exports at the global level are expected to decrease by 2.5%. China, considered to be the “world’s factory”, suffers a decline in production across all sectors and goods, due to an underutilization of labor and capital, and, together with an increase of its trade costs, increases the import costs for the rest of the world, which translates into a decline in global exports. China sees a contraction in exports of 3.7%. Vietnam sees a decline in its total exports by only 1%, because it benefits to an extent from the gap left by the decrease in Chinese exports. Some countries in the East Asia and Pacific region are the most affected in terms of export declines, with Hong Kong SAR, China, suffering the biggest losses (5.2 %), followed by the Lao People’s Democratic Republic (3.6%), Cambodia (3.9%) and Singapore (4.4%). Selected countries see an increased demand for their tourism exports due to diversion of tourism from the EAP region, with some flows increasing by 2%-3% between countries outside the EAP region, but in all countries total tourism flows decline across the board, with exports from the EAP region declining by about 30%. These small bilateral tourism export gains disappear, as the shock spreads from China and East Asia to other parts of the world.

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Global Pandemic <!-- Start of picture text --> Hi cop<br>Restof ator curopee atin Middle gy Other Hi Exports<br>China; Japan Korea IncomeHigh Developingestor. UnitedStates UnionEuropean. +UK Central“UrOPE: America.atin & EastNorth& Saharanube. South Asia_ Developingcountries5 IncomeHigh- WorldTotal<br>East Asia., East Asia Asia Caribbean Africa. Africa countries.<br>0.0%<br>-0.5%<br>-1.0%<br>-1.5%<br>-2.0%<br>-2.5%<br>-3.0%<br>-3.5%<br><!-- End of picture text --> Global Pandemic <!-- Start of picture text --> Wi cop<br>BB Exports<br>China Cambodia Indonesia Laos Malaysia Philippines Thailand Vietnam<br>0.0%<br>-0.5%<br>-1.0%<br>-1.5%<br>-2.0%<br>-2.5%<br>-3.0%<br>-3.5%<br>-4.0%<br><!-- End of picture text -->
Union over 3.4%, Japan – 4.6%, the United States – 3.4% and Canada – 3.2%. Countries in Sub-Saharan Africa (SSA) and the Middle East and North Africa (MENA) are the least affected, and under the global and amplified global pandemic scenarios, the estimated loss of GDP is estimated to be around 3%.

Under the amplified global pandemic scenario, global exports decline 4.6 %. Several countries that experience larger than global average losses of exports are in the EAP region such as Hong Kong SAR, China (9.8%), Cambodia (7.4%), Singapore (8.5%), Lao PDR (7.3%), Thailand (6.8%), but also the Russian Federation and the Philippines see losses up of 6.4%, while Canada, Europe, and the United States see declines of around 4.5%. With the amplified global spread of the virus, all countries see their total exports decline, but the least integrated regions through trade and tourism, such as MENA, SSA, and Latin America and the Caribbean, are the least affected. Some EAP countries tend to be relatively less affected in this scenario than others, but all countries’ exports decline the most under the amplified global pandemic scenario, e.g., Vietnam, Japan, and Korea.

Our estimates are broadly in line with previous studies. Annex 2 reviews several analyses by OECD, Brookings and S&P quantifying the potential impacts of the COVID-19 outbreak. The studies use a variety of tools, with OECD relying on a macroeconomic model and Brookings applying a hybrid CGE/DSGE model with rational expectations. Most estimates on the impacts on China range from 0.5% to 2% of GDP. World GDP is expected to decline between 0.1% and 1.5 %, while global trade is expected to decline between 0.2% and 3.75 %. The biggest impacts are reported in the extreme scenarios by McKibbin and Fernando (2020), with Chinese GDP declining by up to 6%, with GDP declines in the United States and Japan reaching, respectively, 8% and 10%.

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Table 1: GDP implications of various scenarios - cumulative impacts (% deviations from the benchmark)

||**Global**<br>**pandemic**|**Amplified**<br>**global**<br>**pandemic**|
|---|---|---|
|China|-3.69|-4.31|
|DevelopingEAP excludingChina|-2.38|-4.76|
|Cambodia|-3.21|-6.57|
|Lao PDR|-2.15|-4.05|
|Malaysia|-2.09|-4.23|
|Thailand|-3.03|-6.21|
|Vietnam|-2.65|-4.49|
|Philippines|-2.46|-4.80|
|Indonesia|-1.74|-3.51|
|HongKongSAR,China|-2.31|-4.82|
|Korea,Rep.|-2.44|-4.89|
|Singapore|-2.08|-4.45|
|Taiwan,China|-2.81|-5.67|
|Canada|-1.57|-3.18|
|Europe|-1.85|-3.85|
|Japan|-2.23|-4.57|
|United States|-1.67|-3.40|
|Middle East & North Africa|-1.38|-2.95|
|Sub-Saharan Africa|-1.44|-2.95|
|Brazil|-1.71|-3.42|
|Rest of Latin America & Caribbean|-1.85|-3.73|
|Russian Federation|-1.94|-3.99|
|Rest of Europe & Central Asia|-2.21|-4.60|
|India|-2.41|-4.93|
|Rest of South Asia|-2.31|-4.68|
|Oceania|-1.70|-3.37|
|Developingcountries|-2.49|-4.00|
|High-income countries|-1.84|-3.77|
|World Total|-2.09|-3.86|

_Source:_ Envisage simulations

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Table 2: Real exports implications of various scenarios - cumulative impacts (% deviations from the benchmark)

||**Global**<br>**pandemic**|**Amplified**<br>**global**<br>**pandemic**|
|---|---|---|
|China|-3.73|-3.08|
|DevelopingEAP excludingChina|-1.75|-4.07|
|Cambodia|-3.89|-7.40|
|Lao PDR|-3.57|-7.29|
|Malaysia|-2.45|-5.28|
|Thailand|-3.40|-6.81|
|Vietnam|-1.00|-2.82|
|Philippines|-2.94|-6.35|
|Indonesia|-1.38|-3.21|
|HongKongSAR,China|-5.18|-9.80|
|Korea,Rep.|-1.90|-3.95|
|Singapore|-4.39|-8.48|
|Taiwan,China|1.14|1.07|
|Canada|-2.30|-4.73|
|Europe|-2.48|-4.86|
|Japan|-1.04|-2.33|
|United States|-2.37|-4.60|
|Middle East & North Africa|-2.22|-4.87|
|Sub-Saharan Africa|-1.87|-4.29|
|Brazil|-2.03|-4.27|
|Rest of Latin America & Caribbean|-2.21|-4.76|
|Russian Federation|-3.49|-7.44|
|Rest of Europe & Central Asia|-2.89|-5.72|
|India|-1.68|-3.45|
|Rest of South Asia|-1.99|-4.12|
|Oceania|-2.32|-4.98|
|Developingcountries|-2.80|-4.54|
|High-income countries|-2.30|-4.59|
|World Total|-2.50|-4.57|

_Source:_ Envisage simulations

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<!-- Start of picture text --> Amplified Global Pandemic<br>Hi cop<br>Restof pestof Europes atin Mitte gu Other Boers<br>China Japan Korea High Developing United European Central America & East & Saharan South Asia Developing High- World<br>Income . States Union +UK : . North . countries Income Total<br>East Asia.. East Asia Asia Caribbean Africa. Africa countries.<br>0.0%<br>-1.0%<br>-2.0%<br>-3.0%<br>-4.0%<br>-5.0%<br>-6.0%<br><!-- End of picture text --> Amplified Global Pandemic <!-- Start of picture text --> Wi cop<br>BB Exports<br>China Cambodia Indonesia Laos Malaysia Philippines Thailand Vietnam<br>0.0%<br>-1.0%<br>-2.0%<br>-3.0%<br>-4.0%<br>-5.0%<br>-6.0%<br>-7.0%<br><!-- End of picture text -->
<!-- Start of picture text --> USA<br>NaturalAgricultureresources ae|]| |<br>Manufacturing AOe<br>Domestic Services ooBUEE<br> services affected by pandemic — BE 9834 oo<br>Traded tourist services — ff Ee os<br>Total ee|ie<br>-90 -85 -80 -75 -70 -65 -60 -$5 -50 -45 -40 -35 -30 -25 -20 -15 -10 ) ie) 5<br>Billion (2014 US$)<br>Oi china I Europe & Central Asia Bh Latin America & Caribbean<br>OB canada I East Asia and Pacific High Income BB Middle East & North Africa<br>Bl oceania Il Rest of East Asia and Pacific I sub-Saharan Africa<br>M8) European Union + UK IB south Asia<br><!-- End of picture text -->
<!-- Start of picture text --> China<br>Agriculture al<br>Natural resources I<br>Manufacturing GEEEEOBO<br>Services ee|<br>Domestic services affected by pandemic Hi On!<br>Traded tourist services | |i oon | il<br>Total EEE AM lO ——— Ee<br>-75 -70 -65 -60 “55 -50 -45 -40 -35 -30 -25 -20 15 -10 5 0 5<br>Billion (2014 US$)<br>Husa Bl Europe & Central Asia BB Latin America & Caribbean<br>canada Il East Asia and Pacific High Income BB Middle East & North Africa<br>I oceania IB Rest of East Asia and Pacific I sub-Saharan Africa<br>1 European Union + UK BB South Asia<br><!-- End of picture text -->

<!-- Start of picture text --> Thailand<br>Agriculture |<br>Natural resources |<br>ManufacturingServices I Ea—=E€EE OE 2<br>Domestic services affected by pandemic — ooo—=$E=— ——EO———EI EE<br>Traded tourist services ee ee ke<br>Total Cte<br>22. -21 20 4-19 -18 -17 -16 -15 -14 13 -12 -11 10 9 8 7 6 5 4 3 2 2 0 1<br>Billion (2014 US$)<br>Wi china 1B European Union + UK BB South Asia<br>usa Hi Europe & Central Asia Hl Latin America & Caribbean<br>Mi canada i East Asia and Pacific High Income I Middle East & North Africa<br>BB Oceania i Rest of East Asia and Pacific Il Sub-Saharan Africa<br><!-- End of picture text -->
# **3.3 Sectoral output impacts**

Each transmission channel results in a somewhat different sectoral reallocation of output due to changes in demand and supply. The first shock affects all sectors in a similar fashion, by limiting the availability of labor and capital, though labor-intensive sectors are likely to be hit harder. The trade costs impact tradeable sectors, as well as goods and services that rely heavily on imported inputs. The increase in the tourism tax results in a decline of tourism, but all other industries that supply inputs needed to generate tourism services will be impacted by a negative demand shock as well. Finally, social distancing results in lower demand for selected sectors, but some substitution towards goods and remaining services sectors. Overall, the sectoral impact of the amplified global pandemic scenario (Table 3) leads to a steeper decline in services as compared to agriculture and manufacturing. The biggest negative shock is recorded in the output of domestic services affected by the pandemic, as well as in traded tourist services. At the global level, output of services affected by the pandemic could decline by 9.3%, tourism services could decline by 8.8%, with a decline in agricultural and manufacturing output of about 3%.

Under the amplified global pandemic scenario, Thailand, for example, is expected to record an aggregate output loss of 5.3%, the largest drop among the developing countries covered by our analysis (Figure 5). All sectors would see a decline of output, but the biggest percentage drops are recorded in transport services, recreational activities, and accommodation (between 10% and 20%). However, the sectors that suffer the most in absolute terms include trade and selected agricultural (crops) and manufacturing goods (chemicals, electronics, refined oil). These are the real impacts on the volume of output. The declining commodity prices and changing relative prices would result in a somewhat different ranking of the most impacted sectors. These are only illustrative impacts that rely on the type and the size of the assumed shocks. However, they serve as a useful representation of distributional impacts across sectors, with likely diverse impacts on employment and wages of skilled and unskilled workers, as well as female and male workers. Further analysis will be conducted to understand the potential distributional impacts of the pandemic.

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<!-- Start of picture text --> Thailand<br>Crops ©<br>Livestock I<br>Natural resource products I<br>Fossil fuel extraction I<br>Meat products (inc. fisheries) int<br>Other food isi}<br>Textiles I<br>Wearing apparel I<br>Leather products<br>Wood and paper products 1<br>Refined oil S<br>Chemical products (incl. rubber and plastics) |<br>Non-metallic minerals I<br>Metals i<br>Computer, electronic and optical products S<br>Machinery and equipment nec =<br>Motor vehicles and parts a<br>Transport equipment nec I<br>Other manufacturing | |<br>Electricity I<br>Construction B<br>Trade incl. warehousing a<br>Accommodation, food and service activities i<br>Water transport |<br>Air transport fa<br>Other transport Si<br>Communications I<br>Recreational and other services iil<br>Other services |<br>AGRICULTURE B<br>NATURAL RESOURCES I<br>MANUFACTURING ||<br>SERVICES I<br>DOMEST SERVICES AFFECTED BY PANDEMIC a<br>TRADED TOURIST SERVICES —EE=<br>TOA Bs<br>-50 -40 -30 -20 -10 0 -15.0% -10.0% -5.0% 0.0%<br>Billion (2014 dollars) %<br><!-- End of picture text -->
Table 3. Output implications of amplified global pandemic – cumulative impacts (% deviations from the benchmark)

||**Agriculture**|**Natural**<br>**resources**|**Manufacturing**|**Services**|**Domestic**<br>**services**<br>**affected by**<br>**pandemic**|**Traded**<br>**tourist**<br>**services**|**Total**|
|---|---|---|---|---|---|---|---|
|China|-3.12|-1.08|-3.61|-3.67|-4.85|-4.64|-3.54|
|Developing EAP excluding<br>China|-2.70|-1.04|-3.21|-5.40|-9.45|-11.28|-4.12|
|Cambodia|-2.87|-3.98|-2.69|-9.66|-14.96|-19.00|-5.11|
|Lao PDR|-2.41|-3.89|-2.60|-5.85|-12.18|-15.02|-3.57|
|Malaysia|-4.19|-0.79|-4.11|-4.34|-7.30|-9.73|-4.03|
|Thailand|-3.06|-2.91|-4.43|-6.84|-11.53|-14.64|-5.29|
|Vietnam|-3.06|-0.72|-3.34|-3.93|-8.52|-8.99|-3.37|
|Philippines|-2.51|-2.65|-3.93|-5.16|-11.10|-13.30|-4.44|
|Indonesia|-2.70|-0.61|-3.03|-3.67|-7.65|-8.84|-3.15|
|HongKongSAR,China|-1.29|-3.24|-1.33|-6.06|-8.46|-9.23|-5.35|
|Korea,Rep.|-3.91|-4.25|-3.68|-4.53|-6.87|-6.15|-4.10|
|Singapore|-2.61|-3.47|-4.32|-4.01|-7.18|-6.28|-4.11|
|Taiwan,China|-1.04|-7.75|-1.80|-6.84|-7.82|-7.17|-4.15|
|Canada|-4.30|-1.10|-3.25|-3.02|-8.95|-9.16|-2.96|
|Europe|-3.00|-1.02|-2.89|-4.02|-9.04|-9.06|-3.65|
|Japan|-4.71|-2.85|-2.77|-4.62|-8.75|-8.35|-3.98|
|United States|-3.60|-0.21|-2.45|-3.80|-9.99|-11.27|-3.38|
|Middle East & North Africa|-2.76|-1.65|-2.67|-3.02|-9.11|-10.03|-2.65|
|Sub-Saharan Africa|-2.51|-1.72|-2.95|-3.02|-6.35|-8.13|-2.79|
|Brazil|-3.40|-1.20|-2.86|-3.14|-8.55|-9.28|-2.99|
|Rest of Latin America &<br>Caribbean|-2.64|-1.21|-2.94|-4.05|-10.51|-11.87|-3.49|
|Russian Federation|-3.00|-2.19|-3.73|-3.86|-8.72|-9.62|-3.58|
|Rest of Europe & Central<br>Asia|-2.20|-0.59|-3.53|-5.07|-10.20|-11.36|-4.20|
|India|-3.36|-0.84|-3.98|-4.35|-8.23|-8.76|-4.03|
|Rest of South Asia|-2.62|-2.64|-3.25|-5.23|-8.04|-9.28|-4.14|
|Oceania|-3.93|-1.89|-3.10|-3.20|-8.21|-8.07|-3.11|
|Developingcountries|-2.90|-1.42|-3.47|-3.87|-7.98|-8.63|-3.51|
|High-income countries|-3.49|-0.95|-2.78|-4.00|-9.20|-9.60|-3.59|
|World Total|-3.04|-1.29|-3.13|-3.95|-8.77|-9.26|-3.56|

Note: Agriculture – Crops, Livestock; Manufacturing - Meat products (incl. fisheries), Other food, Textiles, Wearing apparel, Leather products, Wood and paper products, Refined oil, Chemical products (incl. rubber and plastics), Non-metallic minerals, Metals, Computer, electronic and optical products, Machinery and equipment nec, Motor vehicles and parts, Transport equipment nec, Other manufacturing; Services – Electricity, Construction, Trade incl. warehousing, Accommodation, food and service activities, Water transport, Air transport, Other transport, Communications, Recreational and other services, Other services; Natural resources - Natural resource products, Fossil fuel extraction; Domestic services affected by pandemic - Trade, Accommodation, food and service activities, Water transport, Air transport, Other transport, Recreational and other services; Traded tourist services - Accommodation, food and service activities, Water transport, Air transport, Other transport, Recreational and other services.

_Source:_ Envisage simulations

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# **4. Conclusion**

COVID-19 is spreading fast across the globe. At the time of writing,<sup>6</sup> the WHO reported cases of COVID19 in 206 countries with the tragic deaths of more than 40,000 people. The primary focus is necessarily on containment, treating the ill and helping communities cope with the epidemic. Our illustrative scenarios indicate that the potential loss of income in affected countries could be significant, with global GDP declining by up to 3.9%, and developing countries hit the hardest (4% on average, but some over 6.5%). Governments will need to offer significant support to affected businesses and households.

Our analysis is likely to underestimate the potential economic costs of the epidemic. We do not fully capture several important channels, such as the uncertainty-driven contraction in demand and FDI, and other real effects of a financial shock. We capture some aspects of global value chains trade through inputoutput linkages and assumptions that mimic the durability of relationships between firms in value chains but plan to extend the analysis using a richer data set. We have examined, but not yet finalized, the effects of raising domestic trade costs as well as demand switching away from activities requiring direct contact with other people. Our analysis will evolve as we bring assumptions and scenarios in line with more recent health and economic indicators.

Early indications of the economic costs and the magnitude of estimated impacts demonstrate the need for a coordinated international response to the crisis. A global crisis requires a global response and there is a need for global collaboration not just on health, but also on trade, finance and macroeconomic policies. Fortunately, global institutions are beginning to catalyze and coordinate global efforts, as well as to provide technical and financial support to countries coping with the health and economic consequences of the outbreak.

6 March 31, 2020.

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# **Annex 1** Regional and sectoral aggregations

# **Regional concordance**

||**Region/Country**|**GTAP concordance**|
|---|---|---|
|1|Oceania (ANZ)|Australia (AUS), New Zealand (NZL)|
|2|Rest of Oceania (XOC)|Rest of Oceania (XOC)|
|3|China (CHN)|China (CHN)|
|4|Hong Kong SAR, China (HKG)|Hong Kong (HKG)|
|5|Japan (JPN)|Japan (JPN)|
|6|Korea, Rep. (KOR)|Korea (KOR)|
|7|Taiwan, China (TWN)|Taiwan (TWN)|
|8|Cambodia (KHM)|Cambodia (KHM)|
|9|Indonesia (IDN)|Indonesia (IDN)|
|10|Lao PDR (LAO)|Laos (LAO)|
|11|Malaysia (MYS)|Malaysia (MYS)|
|12|Philippines (PHL)|Philippines (PHL)|
|13|Singapore (SGP)|Singapore (SGP)|
|14|Thailand (THA)|Thailand (THA)|
|15|Vietnam (VNM)|Viet Nam (VNM)|
|16|Rest of East Asia (XEA)|Mongolia (MNG), Rest of East Asia (XEA), Brunei Darussalam<br>(BRN),Rest of Southeast Asia(XSE)|
|17|India (IND)|India (IND)|
|18|Rest of South Asia (XSA)|Bangladesh (BGD), Nepal (NPL), Pakistan (PAK), Sri Lanka (LKA),<br>Rest of South Asia(XSA)|
|19|Canada (CAN)|Canada (CAN)|
|20|United States (USA)|United States of America (USA)|
|21|Brazil (BRA)|Brazil (BRA)|
|22|Rest of Latin America & Caribbean<br>(XLC)|Mexico (MEX), Rest of North America (XNA), Argentina (ARG),<br>Bolivia (BOL), Chile (CHL), Colombia (COL), Ecuador (ECU),<br>Paraguay (PRY), Peru (PER), Uruguay (URY), Venezuela (VEN), Rest<br>of South America (XSM), Costa Rica (CRI), Guatemala (GTM),<br>Honduras (HND), Nicaragua (NIC), Panama (PAN), El Salvador<br>(SLV), Rest of Central America (XCA), Dominican Republic (DOM),<br>Jamaica (JAM), Puerto Rico (PRI), Trinidad and Tobago (TTO), Rest<br>of Caribbean(XCB)|
|23|Europe (EUR)|Austria (AUT), Belgium (BEL), Cyprus (CYP), Czech Republic (CZE),<br>Denmark (DNK), Estonia (EST), Finland (FIN), France (FRA),<br>Germany (DEU), Greece (GRC), Hungary (HUN), Ireland (IRL), Italy<br>(ITA), Latvia (LVA), Lithuania (LTU), Luxembourg (LUX), Malta<br>(MLT), Netherlands (NLD), Poland (POL), Portugal (PRT), Slovakia<br>(SVK), Slovenia (SVN), Spain (ESP), Sweden (SWE), United<br>Kingdom (GBR), Switzerland (CHE), Norway (NOR), Rest of EFTA<br>(XEF),Rest of Europe(XER),Rest of the World(XTW)|
|24|Russian Federation (RUS)|Russian Federation (RUS)|
|25|Rest of Europe & Central Asia<br>(XEC)|Albania (ALB), Bulgaria (BGR), Belarus (BLR), Croatia (HRV),<br>Romania (ROU), Ukraine (UKR), Rest of Eastern Europe (XEE),<br>Kazakhstan (KAZ), Kyrgyzstan (KGZ), Tajikistan (TJK), Rest of<br>Former Soviet Union (XSU), Armenia (ARM), Azerbaijan (AZE),<br>Georgia(GEO),Turkey (TUR)|

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|26|Middle East & North Africa (MNA)|Bahrain (BHR), Iran (IRN), Israel (ISR), Jordan (JOR), Kuwait (KWT),<br>Oman (OMN), Qatar (QAT), Saudi Arabia (SAU), United Arab<br>Emirates (ARE), Rest of Western Asia (XWS), Egypt (EGY),<br>Morocco(MAR),Tunisia(TUN),Rest of North Africa(XNF)|
|---|---|---|
|27|Sub-Saharan Africa (SSA)|Benin (BEN), Burkina Faso (BFA), Cameroon (CMR), Côte d'Ivoire<br>(CIV), Ghana (GHA), Guinea (GIN), Nigeria (NGA), Senegal (SEN),<br>Togo (TGO), Rest of Western Africa (XWF), Central Africa (XCF),<br>Rest of South-Central Africa (XAC), Ethiopia (ETH), Kenya (KEN),<br>Madagascar (MDG), Malawi (MWI), Mauritius (MUS),<br>Mozambique (MOZ), Rwanda (RWA), Tanzania (TZA), Uganda<br>(UGA), Zambia (ZMB), Zimbabwe (ZWE), Rest of Eastern Africa<br>(XEC), Botswana (BWA), Namibia (NAM), South Africa (ZAF), Rest<br>of South African Customs Union(XSC)|

# **Sector concordance**

|1|Crops (crp)|Paddy rice (PDR), Wheat (WHT), Cereal grains nec (GRO),<br>Vegetables, fruit, nuts (V_F), Oil seeds (OSD), Sugar cane, sugar<br>beet (C_B), Plant-based fibers (PFB), Crops nec (OCR), Processed<br>rice(PCR),Sugar(SGR)|
|---|---|---|
|2|Livestock (lvs)|Bovine cattle, sheep and goats, horses (CTL), Animal products nec<br>(OAP),Raw milk(RMK),Wool,silk-worm cocoons(WOL)|
|3|Natural resource products (NRS)|Forestry (FRS), Other Extraction (formerly omn Minerals nec)<br>(OXT)|
|4|Fossil fuel extraction (FFL)|Coal (COA), Oil (OIL), Gas (GAS), Gas manufacture, distribution<br>(GDT)|
|5|Meat products (inc. fisheries)<br>(PMT)|Fishing (FSH), Bovine meat products (CMT), Meat products nec<br>(OMT), Dairy products (MIL)|
|6|Other food (OFD)|Vegetable oils and fats (VOL), Food products nec (OFD),<br>Beverages and tobaccoproducts(B_T)|
|7|Textiles (TEX)|Textiles (TEX)|
|8|Wearing apparel (WAP)|Wearing apparel (WAP)|
|9|Leather products (LEA)|Leather products (LEA)|
|10|Wood and paper products (WDP)|Wood products (LUM), Paper products, publishing (PPP)|
|11|Refined oil (P_C)|Petroleum, coal products (P_C)|
|12|Chemical products (incl. rubber<br>andplastics) (CHM)|Chemical products (CHM), Basic pharmaceutical products (BPH),<br>Rubber and plastic products (RPP)|
|13|Non-metallic minerals (NMM)|Mineral products nec (NMM)|
|14|Metals (MET)|Ferrous metals (I_S), Metals nec (NFM)|
|15|Computer, electronic and optical<br>products(ELE)|Computer, electronic and optical products (ELE)|
|16|Machinery and equipment nec<br>(OME)|Electrical equipment (EEQ), Machinery and equipment nec (OME)|
|17|Motor vehicles and parts (MVH)|Motor vehicles and parts (MVH)|
|18|Transport equipment nec (OTN)|Transport equipment nec (OTN)|
|19|Other manufacturing (XMN)|Metal products (FMP), Manufactures nec (OMF)|
|20|Electricity (ELY)|Electricity (ELY)|
|21|Construction (CNS)|Construction (CNS)|
|22|Trade incl. warehousing (TRD)|Trade (TRD), warehousing and support activities (WHS)|

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|23|Accommodation, food and service<br>activities(AFS)|Accommodation, food and service activities (AFS)|
|---|---|---|
|24|Water transport (WTP)|Water transport (WTP)|
|25|Air transport (ATP)|Air transport (ATP)|
|26|Other transport (XTP)|Transport nec (OTP)|
|27|Communications (CMN)|Communication (CMN)|
|28|Recreational and other services<br>(ROS)|Recreational and other services (ROS)|
|29|Other services (XSV)|Water (WTR), Financial services nec (OFI), Insurance (formerly isr)<br>(INS), Real estate activities (RSA), Business services nec (OBS),<br>Public Administration and defense (OSG), Education (EDU),<br>Human health and social work activities(HHT),Dwellings(DWE)|

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**Annex 2 Literature review on the impacts of Covid-19**

|Title & Authors|Model|Assumptions|Scenarios||Results|
|---|---|---|---|---|---|
|“Coronavirus:<br>The world<br>economy at<br>risk” (OECD<br>2020)|NiGEM<br>macro<br>model|Monetary<br>policy is<br>allowed to be<br>endogenous.;<br>The automatic<br>fiscal<br>stabilisers are<br>allowed to<br>operate fully in<br>all<br>countries,<br>implying that<br>governments<br>do not react to<br>the shock by<br>attempting to<br>maintain a<br>previously<br>announced|Contained<br>Outbreak<br>(short lived<br>but severe<br>downturn in<br>China)|-Domestic demand in<br>China and Hong Kong,<br>China is reduced by 4% in<br>the first quarter of 2020,<br>and 2% in the second<br>quarter of 2020.<br>-Global equity prices and<br>non-food commodity<br>prices are lowered by 10%<br>in the first half of 2020.<br>- Higher uncertainty is<br>modelled via a small rise<br>of 10 basis points in<br>investment risk premia in<br>all<br>countries in the first half<br>of 2020. This raises the<br>cost of capital and<br>reduces investment.|China GDP loss = -0.2<br>percentage point in 2020H1;<br>Reduction of China import<br>demand = -6%;<br>World GDP is reduced by to<br>0.5 percentage point in 2020;<br>Global trade declines 0.9% in<br>2020 (and 1.4% in first half of<br>2020)|
|||budget path.|A “domino”<br>scenario:<br>broader<br>contagion|-Domestic demand in<br>most other Asia-Pacific<br>economies, including<br>Japan and Korea, and<br>private<br>consumption in the<br>advanced northern<br>hemisphere economies is<br>reduced by 2% (relative to<br>baseline) in the second<br>and third quarters of<br>2020.<br>- Global equity prices and<br>non-food commodity<br>prices are lowered by 20%<br>in the first nine months of<br>2020.<br>- Heighted uncertainty is<br>modelled via an increase<br>of 50 basis points in<br>investment risk premia in<br>all countries in 2020.|World GDP is reduced by up to<br>1 1⁄2 per cent; World trade is<br>declining by around 3 3⁄4 per<br>cent in 2020|
|“Coronavirus<br>Casts Shadow||Assumption<br>that the supply<br>side of the<br>economy–|Only one<br>scenario|Top Asia-Pacific: Risk<br>Coronavirus restrictions<br>set back China’s growth<br>(risk level: High);|China GDP growth loss of 0.7<br>percentage point in 2020. Full<br>recover in 2021; Global GDP|

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|Over Credit<br>Outlook” (S&P<br>2020)||labor force,<br>productive<br>capital, and<br>productivity –<br>is unchanged,<br>meaning that<br>output after<br>the<br>coronavirus<br>shock returns<br>to its original<br>path.||Top Global Risk:<br>Coronavirus restrictions<br>less systemic globally,<br>with sector variations (risk<br>level: elevated)|growth loss of 0.3 percentage;<br>The U.S. and Europe may<br>experience minimal reductions<br>in growth, while the impact is<br>largest in East Asia.|
|---|---|---|---|---|---|
|“The Global<br>Macroeconomic|G-Cubed<br>Multi-|-6 sectors and<br>24 countries;|Scenario 1|China Shock, Low<br>Severity,|GDP loss (2020):<br>China = -0.4%;|
|Impacts of<br>COVID-19”|Country<br>Model –|Long-run stock<br>equilibrium||Temporary. Attack rate<br>for China = 1%; Case|USA = -0.1%;<br>Japan = -0.3%;|
|(McKibbin and|Global|obtains||fatalityrate China = 2%|Korea = -0.1%|
|Fernando 2020)|hybrid<br>DSGE/CGE|through the<br>adjustment of<br>asset prices;<br>Nominal wages<br>are sticky and<br>adjust over|Scenario 2|China Shock, Middle<br>severity, Temporary.<br>Attack rate for China =<br>10%; Case fatality rate<br>China = 2.5%|GDP loss (2020):<br>China = -1.9%;<br>USA = -0.1%;<br>Japan = -0.4%;<br>Korea = -0.2%|
|||time based on<br>country-<br>specific labor<br>contracting<br>assumptions.;|Scenario 3|China Shock, High<br>severity, Temporary;<br>Attack rate for China =<br>30%; Case fatality rate<br>China = 3%|GDP loss (2020):<br>China = -6%;<br>USA = -0.2%;<br>Japan = -0.5%;<br>Korea = -0.3%|
|||Short run<br>rigidities;<br>Heterogeneous<br>households<br>and firms|Scenario 4|Global Shock, Low<br>severity, Temporary;<br>Attack rate for China =<br>10%; Case fatality rate<br>China = 2%|GDP loss (2020):<br>China = -1.6%;<br>USA = -2%;<br>Japan = -2.5%;<br>Korea= -1.4%|
||||Scenario 5|Global Shock, Middle<br>severity, Temporary;<br>Attack rate for China =<br>20%; Case fatality rate<br>China = 2.5%|GDP loss (2020):<br>China = -3.6%;<br>USA = -4.8%;<br>Japan = -5.7%;<br>Korea = -3.3%|
||||Scenario 6|Global Shock, High<br>severity, Temporary;<br>Attack rate for China =<br>30%; Case fatality rate<br>China = 3%|GDP loss (2020):<br>China = -6.2%;<br>USA = -8.4%;<br>Japan = -9.9%<br>Korea = -5.8%|
||||Scenario 7|Global Shock, Low<br>severity, Permanent;<br>Attack rate for China =<br>10%; Case fatality rate<br>China = 2%|GDP loss (2020):<br>China = -2.2%;<br>USA = -1.5%;<br>Japan = -2%;<br>Korea = -1.3%|

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|“Coronavirus<br>could cost the<br>global economy<br>$2.7 trillion.”<br>(Orlik et al.<br>2020)|NiGEM —a<br>large scale<br>model of<br>the global<br>economy;<br>Static<br>assessment|Model allows:<br>-monetary<br>policy to<br>respond to<br>weaker<br>growth;<br>- a degree of<br>import<br>substitution|Scenario 1|Major blow to China, and<br>spillover to rest of world;<br>shock to China’s GDP in<br>1Q - China’s GDP growth<br>to slow 4.7 ppt below our<br>baseline forecast|GDP loss (2020):<br>World (1<sup>st</sup>Quarter) = -1.2%<br>China = -0.7%<br>Japan = -0.1%<br>Indonesia = -0.3<br>Canada = -0.1%<br>Germany = -0.1%<br> <br>|
|---|---|---|---|---|---|
|||Model does<br>not allow:<br>-supply chain<br>impacts to<br>propagate<br>beyond the<br>countries in<br>which they are|Scenario 2|Outbreaks cause localized<br>disruption, countries with<br>reported >100 cases in<br>early March suffer half of<br>the shock to China|GDP loss (2020):<br>World = -0.8%<br>China = -1.5%<br>Japan = 01%<br>US = -0.2%<br>France = -1.3%<br>Germany = -1.2%<br>Russia = -0.9%|
|||first felt|Scenario 3|Widespread contagion,<br>countries with current<br>reported cases >100<br>suffer the same shock as<br>China, and countries with<br>any reported cases suffer<br>half of the shock suffered<br>by China|GDP loss (2020):<br>World = -1.9%<br>China = -2%<br>Japan = -2.2%<br>Indonesia = -2.8<br>USA = -1.3%<br>Germany = -2.8%<br>Brazil = -1.7%|
||||Scenario 4|Global pandemic, all<br>countries suffer a severe<br>shock|<br>GDP loss (2020):<br>World = -3.1%|

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