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We estimate the impact of COVID-19 for bilateral trade
relations of all monthly reporting states present in the IHS Markit
GTA Forecasting database over the period 2019M1 - 2020M8 using a
semi-mixed effects panel data model in the trade gravity
framework
The impact of COVID-19 on bilateral trade is
statistically significant and adverse, ceteris paribus, on both the
exporter's and importer's side
The result holds for both monthly-reported new COVID-19
cases as well as new COVID-19 related deaths as a proxy for the
severity of pandemic
The impact is found to be asymmetric at the level of
individual states as could have been expected taking into account
the time-path and gravity of the pandemic
The models re-estimated on a monthly basis show that
the impact globally becomes adverse and statistically significant
in March 2020 and endures. This coincides with the escalation of
COVID-19 from Asia to Western Europe and then
globally
The stringency of governments response to the COVID-19
pandemic as measured by Oxford COVID-19 Government Response Tracker
index it has a statistically significant and negative impact on the
importer's side only in a global sample model which could be
indicative of the creation of significant hindrance to trade and
weaker consumer demand
Introduction
2020 proves to be the most challenging year on record for global
trade and the global economy in a century. The COVID-19 pandemic
has destroyed hopes for a strong global upturn.
As of 1 November, 46 million cases and 1.2 million deaths have
been reported globally by the WHO. The further acceleration in the
incidence of new cases was most notable in the European Region,
which reported half of the global new cases (over 1.7 million cases
- a 22% increase from the previous week). Moreover, the European
region also reported a substantial rise in the number of new deaths
(a 46% increase compared with the previous week), with Europe and
the Americas now each reporting over 17,000 new deaths in the last
week. Europe seems to be experiencing a second wave of the
pandemic.
The COVID-19 pandemic is the worst health crisis in more than a
century and potentially without precedent if we take the globalized
nature of the current economy. It's a simultaneous supply and
demand shock that led to a global recession and unprecedented
contraction in global trade (affecting both the export potential of
nations and their demand for imports). The contraction is by now
far larger than the effects of the global financial crisis in
2008-09 (referred to as the Great Trade Collapse) or any other
recent health crisis (e.g. SARS, Ebola, or MERS).
The effects of COVID-19 form a theoretical
perspective
The direct trade effects of COVID-19 (Baldwin & Toimura,
2020) are related to direct supply disruptions hindering production
(local/ regional lockdowns & forced production stoppages),
increased transport cost due to implementation of stricter rules,
supply-chains contagion effect which amplified the direct supply
shocks (manufacturing sectors in less-affected nations found it
harder and more expensive to acquire the necessary imported inputs
from hard-hit nations) and finally to demand disruptions due to a
decrease in the aggregate demand (recession), and precautionary or
wait-and-see purchase delays (delayed purchases &
investments).
Reporters most adversely affected are the ones struck by the
pandemic itself as well as economies most dependent on the trade
with these nations through export/import linkages (forward/backward
linkages in global value chains, GVCs). Increased defragmentation
of production chains and certain management principles
(just-in-time and lean production with low stockpiles of inputs)
increased the susceptibility of the global economy to the shock.
The impact is, however, asymmetric due to the nature of the
individual (sector-level) value-added chains. Some GVCs dependent
on adversely affected regional or global hubs such as China, Italy,
Spain, or Germany were more affected (e.g. automotive industry,
electronics). Some industries or sectors gained on the crisis (e.g.
pharmaceuticals, IT services).
Global uncertainty levels skyrocketed with an adverse impact on
financial markets. Increased uncertainty and falling demand
decrease the level of investments by firms which could have dire
dynamic consequences (lower accumulation, lower growth rates).
Individual economies and groups of economies once again took
unprecedented steps to mitigate the crisis, which could have
similarly to 2007-08 negative consequences for public finances and
global debt levels. This increases the probability of the W-shape
scenario (the initially assumed V-shape with a strong recession
followed by sharp recovery is already highly unlikely).
The pattern of trade collapse reflects the spread of the
pandemic and the steps taken by individual governments. The overall
impact will depend critically on the duration, severity, and
spatial pattern of the pandemic. The remedy would be the
introduction of a successful vaccine or global herd immunity.
It has to be stressed here that the impact of the pandemic on
the global economy is extremely complex and takes place through a
large number of potential direct & indirect channels. Formal
economic models have been utilized to analyze past pandemics (e.g.
Bloom et al. 2005). In order to account for the complexity of the
phenomenon usually complex computable general equilibrium
frameworks are applied. The CGE model of Maliszewska, Mattoo, &
Van Der Mensbrugghe (2020) for instance took into account the
direct impact of a reduction in employment, the increase in costs
of international transactions, the sharp drop in trade and the
decline in demand for services. It shows clearly that the effect on
the global economy will depend on the severity of the pandemic and
the duration of containment efforts with particularly adverse
effects for developing states.
Unfortunately, the spread of COVID-19 resembles the infamous
Spanish Flu pandemic of 1918-20 that lasted two years and had three
major waves with the second one particularly sinister (Johnson
& Mueller, 2002). The incoming data provides the first signs of
the second wave in a growing number of reporters. The economic
impact will now depend on actions taken - judging from the
overreaction in spring they are unlikely to introduce tough and
economically harmful measures unless the situation significantly
deteriorates (e.g. Israel recently has reintroduced a three-week
long national lockdown).
We already understand that the impact of a pandemic won't be
limited to the short run. It is likely to have long-term
consequences as well. We are likely to observe more pronounced
adjustments to GVC/trade patterns (trade diversion effects) the
larger, the longer the pandemic lasts. COVID-19 has already led to
an acceleration in digital transformation, adjustments in work
patterns, and an increase in the role of RPA/AI in numerous
sectors. Health security issues are going to be taken more
seriously are likely to modify decision making of MNEs and, this
could affect their location choices and thus lead to the
reconfiguration of GVC/logistic chains. We are likely to see a
trend towards onshoring or backshoring, more nearshoring, and thus
the transformation of GVC towards more regionalized value chains.
Reversal from globalization is however unlikely.
An empirical investigation of the impact of COVID-19 on
global trade
To empirically identify the impact of COVID-19 on the trade we
have built an econometric model in the gravity tradition explaining
the intensity of bilateral trade relations between all monthly
reporting states present in the Global Trade Atlas Forecasting
database.
The period analyzed covers monthly observations from January
2019 to August 2020. We utilize data from IHS Markit on bilateral
exports from the GTA Forecasting database (cleaned and after the
application of country ranking scheme) available for all monthly
reporting economies and data on GDP from IHS Markit Comparative
World Overview. This gives us approximately 360,000 observations.
We intentionally take the whole 2019 into account in order to
account for the pre-COVID-19 period and detect the impact of the
pandemic itself.
In addition, we utilize standard trade gravity variable from the
CEPII gravity database
supplementing it with data on daily reported new cases of COVID-19
and COVID-19 related deaths aggregated to months. The data on
COVID-19 has been adopted from the Coronavirus Source Data provided
by Our World in Data. The variables
were transformed separately for an exporter and an importer and
were zero-adjusted to take zero observations into account (the
variables are coded as x_l_newc, m_l_newc for the log of new cases,
as well as x_l_newd & m_l_newd for new COVID-19 related
deaths).
Furthermore, as the impact on trade critically depends on the
stringency of actions of individual governments taken in response
to the escalating pandemic, we take into account monthly averages
of the Oxford COVID-19 Government Response
Tracker (OxCGRT) - for both exporters and importers (asi_x,
asi_m). The OxCGRT (Hale, Petherick, Phillips, & Webster 2020)
collects information on different common policy responses that
governments have taken to respond to the pandemic on 18 different
indicators such as school closures and travel restrictions. The
value of the index varies between 0 (no measures) to 100 (complete
lockdown). The global average of the stringency of response is
presented in the following graph with a clear peak in April 2020.
We also plot the maximum level of stringency globally with a
similar peak in April-May 2020.
As is clearly visible, the monthly average of the OxCGRT is
correlated with IHS Markit's ECR Division COVID-19 Government
Containment index available for selected countries since March 2020
and forecasted forward till June 2021. The containment index takes
values from 0 - no measures in place to 100 - extreme measures.
We estimate the model using a semi mixed-effects panel model
(Lombardía and Sperlich, 2012; Proença, Sperlich, and Savaşcı 2015)
estimated with the use of PPML or Pseudo Poisson maximum likelihood
method as suggested by the Silva & Tenreyro (2011). All
floating variables utilized in the model apart from the explained
variable enter the model in logs. All binary variables are
introduced as dummies.
The data on new COVID-19 cases represents the severity of the
pandemic in each economy. The data on COVID-19 related deaths to us
takes into account the burden of the pandemic on a given reporter's
health system and thus takes into account the efficiency of a given
health system and could be considered an even better approximation
of the pandemic. Naturally, the number of cases and deaths is
related to the size of the population of a given economy.
The list of explanatory variables includes the standard
variables utilizing the gravity equations approach that is the log
of real GDP of the exporter (l_x_gdp), the log of real GDP of an
importer (l_m_gdp) as well as the log of distance in kilometers
between the capital cities of both trade partners (l_distance_cap).
The distance is measured using the "as the crow flies" approach.
The standard variables have been supplemented with other
traditional variables from CEPII gravity dataset (Head, Mayer &
Ries 2010) such as contingency of trade partners or common border
(contig), common official language (comlang_off), a binary variable
depicting a former colony status for a given country pair (colony)
as well as the presence of RTA or regional trade agreement notified
to WTO between a given pair of countries (rta).
In order to account for a common business cycle we have
introduced time fixed effects and in line with the suggestions of
Silva & Tenreyro (2011).
The obtained results prove the viability of the gravity approach
in explaining the intensity of bilateral trade. The coefficient of
determination is high in many cases exceeds 0.9 thus 90% or more of
the variation in the explained variable, namely the value of
exports, is explained by the factors included in the model.
The coefficients on key variables are in line with economic
theory and prove the robustness of the gravity approach. The
coefficients on exporter's and importer's size are positive and
statistically significant. The impact of distance, in line with
theory, is adverse and statistically significant. The impact of
contingency is positive as expected. In many specifications of the
model, the impact of, the commonality of language is positive. The
former colony status isn't statically significant in the general
specifications; however, its impact is significant in
exporter-specific specifications of the model. Last but not least,
the impact of RTA between a pair of countries is significant and
positive as could have been expected.
In the following empirical analysis of the impact of COVID-19 on
trade, we follow the succeeding empirical strategy. We first
estimate the model for the global sample introducing our two
proxies, new COVID-19 cases and deaths, in separate specifications.
Secondly, we show the results for models estimated for separate
months from January to August 2020 to depict the changing
elasticity of the reaction to COVID-19. Thirdly we estimate the
models for selected top global exporters to show the asymmetry of
the reaction at the level of states. Fourthly, we account for the
impact of stringency of government reaction to COVID-19.
At first, in accordance with the above strategy, we estimate the
general model for the global sample introducing simultaneously the
COVID-19 specific variables for both exporter and importer. In the
first specification, we account for the new COVID-19 cases while in
the second one we introduce the COVID-19 related deaths. As can be
seen (please refer to Table 1), the impact of the COVID-19 pandemic
on bilateral exports is statistically significant and adverse. The
impact does not seem to depend on the proxy utilized - both new
COVID-19 cases, as well as COVID-19 deaths, harm bilateral exports,
however, the magnitude of the effect is higher for new COVID-19
related deaths. It could be related to the nature of the variable
which accounts, at least partially in our understanding, for the
efficiency of a particular national health system to the COVID-19
pandemic. The magnitude of the reaction to COVID-19 new cases in
the exporter is weaker than on the importer's side. The magnitude
of the effects for new COVID-19 related deaths is on the other hand
similar on the exporter's and importer's side. Please take into
account that the method utilized allows us to interpret the
coefficients as elasticities. Thus, an increase in monthly COVID-19
related deaths by 100% for both exporter and importer decreases the
trade between them by approx. 5.3%, ceteris paribus.
In the next phase of our empirical analysis, the models on a
global sample are estimated separately for each month of the
pandemic that is starting from December 2019 till August 2020. For
obvious reasons, the model does not include fixed time-specific
effects. As can be seen, starting from March 2020 the elasticities
of reaction to COVID-19 cases both on the exporters and importer
side become statistically significant and negative. The effect
endures till the end of our sample which indicates the adverse
impact of COVID-19 on global trade starting from the global
escalation of the first wave, ceteris paribus. The effect is also
present and of similar magnitude if we control for new COVID-19
deaths. We visualize the elasticities of the reaction in the
following two graphs.
We expect the above effect to endure in the forthcoming months
if we consider the escalation of the pandemic in recent weeks
pointing to a clear second pandemic wave. Unfortunately, the effect
could last further with the expected third wave of the pandemic in
the next year unless the effective vaccine is found and globally
distributed and applied. It will be a very costly and arduous
process in itself requiring global coordination to bring the
desired effect.
Looking from that perspective, 2020 as well as 2021 can be
predicted to be the worst two years for global trade relations on
the record and in particular since the Second World War. The impact
of COVID-19, a major simultaneous supply and demand shock due to
the health crisis, proves to be adverse and significantly larger
than the prior outbreaks including HIV, Ebola, SARS, or MERS in
recent years.
In the next set of models (please refer to Table 2), we estimate
the models separately for selected top global exporters. The group
includes, in particular, the US, China (mainland), Japan, South
Korea, Canada, Brazil, India, Russia, Australia, and a selection of
European states including the United Kingdom and the largest of the
EU states, namely: Germany, France, Italy, Spain, and Poland. The
list thus includes several countries particularly adversely
affected by COVID-19. The aim is to identify a potential asymmetry
of reactions
The first set of models accounts for the new COVID-19 related
cases and the second set of models accounts for COVID-19 related
deaths. As can be seen, the elasticity of the reaction to COVID-19
cases or deaths differs between reporters. For several countries,
the impact of COVID-19 on the value of exports is statistically
insignificant on both sides. We observe it for Brazil, Spain, and
Germany. On the other hand, for India and Poland, the number of
cases in the exporter plays a negative role. For the US, China,
Japan, South Korea, Canada, and the UK the number of COVID-19 cases
on the importer side plays an adverse and statistically significant
role. The existence of a positive impact of the number of COVID-19
related cases for some of the reporters on the exporter side could
be due to the specific time sequence of the pandemic in individual
countries. It is worth stressing that in most of the cases, the
impact disappears when we utilize the new COVID-19 related
deaths.
In the last set of models (please refer to Table 3), we depict
the impact of COVID-19 by introducing the average Oxford COVID-19
Government Response Tracker (OxCGRT) for the exporter and importer
(shown here as asi_x & asi_m). The government response
stringency index has a negative and statistically significant
impact on the value of exports in the global sample only on the
importer's side. Thus, a more stringent response on the importer's
side seams to create significant trade barriers. It could be due as
well to the weakening demand for imports. On the supply side, the
exporter, the impact is insignificant. The individual governments
try to limit the harm caused by policy responses to their export
potential.
It is worth stressing that in a batch of models in which we
utilized the IHS Markit ECR's stringency of containment index for
exporter and importer (not shown here, available in the extended
version of the article) the impact was negative for the policy
response on both sides.
In the next set of specifications, we show once again the
asymmetry of the effect between countries. In seven countries, the
stringency of the importer's policy response has an adverse and
statistically significant impact on the value of trade. In India
and France, the impact is negative for the stringency of home
country reaction. Surprisingly, the impact of stringency of home
country measures is statistically significant and positive at the
usually applied level of 5% in the case of Japan and Australia. On
the other hand, for China, South Korea, Russia, Germany, and Spain
we identify no statistically significant effect of policy response
to COVID-19 on their exports. That could be related to the pattern
of their trade-in terms of most significant trade partners as well
as the product structure of their exports.
Summing up, the conducted analysis proves the existence of the
negative impact of COVID-19 on global trade relations. The effect
seems to endure from March 2020 onwards and now with the second
wave is likely to endure till the containment efforts and
potentially global vaccination will be effectively introduced.
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Johnson, N. P., & Mueller, J. (2002). Updating the accounts:
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Maliszewska, M., Mattoo, A., & Van Der Mensbrugghe, D.
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