The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods - INTERNATIONAL TRADE WORKING PAPER

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                                                 2021/08

INTERNATIONAL TRADE WORKING PAPER

The Impact of COVID-19
on the Global and Intra-
Commonwealth Trade in
Goods
Sangeeta Khorana, Inmaculada Martínez-­
Zarzoso and Salamat Ali
International Trade Working Paper 2021/08
ISSN 2413-3175
© Commonwealth Secretariat 2021
By Sangeeta Khorana (Bournemouth University); Inmaculada Martínez-Zarzoso (University of
Goettingen and University Jaume) and Salamat Ali (Commonwealth Secretariat).
Please cite this paper as: Khorana, S, I Martínez-Zarzoso and S Ali (2021), ‘The Impact of COVID-19
on the Global and Intra-Commonwealth Trade in Goods’, International Trade Working Paper
2021/08, Commonwealth Secretariat, London.

  The International Trade Working Paper series promptly documents and disseminates reviews,
  analytical work and think-pieces to facilitate the exchange of ideas and to stimulate debates and
  discussions on issues that are of interest to developing countries in general and Commonwealth
  members in particular. The issues considered in the papers may be evolving in nature, leading
  to further work and refinement at a later stage. The views expressed here are those of the
  author(s) and do not necessarily represent those of the Commonwealth Secretariat.
  For more information contact the Series Editor: Dr Brendan Vickers, b.vickers@common­
  wealth.int.

                                               Abstract
This paper employs the gravity model of international trade to examine the effect of the COVID-
19 pandemic on global and intra-Commonwealth trade flows. It uses bilateral monthly exports
data at the HS6 level and the number of COVID-19 cases and deaths, as well as the stringency of
measures taken to contain the virus, to estimate the effect of the pandemic on Commonwealth
countries’ trade. The study finds that the incidence of COVID-19 in both exporting and importing
countries has impacted on Commonwealth trade flows and that the extent of the effect varies with
the development level of trading partners. High numbers of COVID-19 cases, including deaths, in
low-income importing countries led to a reduction in Commonwealth exports, while a high inci-
dence of COVID-19 in high-income importing countries led to with an increase in their exports.
The incidence of COVID-19 in an exporting country was also found to impact on trade among a
global sample of countries. Restrictions aiming to contain COVID-19 in high-income countries
were associated with an increase in Commonwealth countries’ trade. Short-term projections of
trade trends point towards a negative change in both exports and imports of Commonwealth
countries. The study also proposes a set of policy options and recommendations targeting sustain-
able recovery and building resilience in Commonwealth economies.

JEL Classifications: E00, F10, F62
Keywords: COVID-19, goods, international trade, Commonwealth, trade flows
International Trade Working Paper 2021/08                                    3

                                            Contents

1. Introduction                                                              5
2. Correlations between the COVID-19 pandemic and Commonwealth countries’
   trade flows                                                               6
3. Literature review                                                         9
4. Methodology                                                              11
5. Conclusions and policy implications                                      19

Notes                                                                       20
References                                                                  20
Annex                                                                       22
4                       The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

                  Abbreviations and Acronyms

ACFTA   African Continental Free Trade Area
CEPII   Centre d’Etudes Prospectives et d’Informations Internationales
CES     constant elasticity substitution
CGE     computable general equilibrium
DD      difference-in-difference
FDI     foreign direct investment
FE      fixed effects
FTAs    free trade agreements
GDP     gross domestic product
GVCs    global value chains
IMF     International Monetary Fund
LDCs    least developed countries
MRT     multilateral resistance terms
NLS     non-linear least squares
OLS     ordinary least squares
PPML    Poisson pseudo maximum likelihood
WTO     World Trade Organization
International Trade Working Paper 2021/08                                                               5

                                      1. Introduction

The COVID-19 pandemic generated a global              largely rely on exporting fuels, agricultural
shock of unprecedented magnitude, with a              commodities and minerals.
devastating effect on international trade flows          Given that around 70 per cent of Common­
(WTO, 2020a). This followed from disruption of        wealth countries’ exports comprise merchan-
economic activity as a consequence of lockdowns,      dise, this study examines how the COVID-19
travel restrictions, international border and port    shock has impacted bilateral merchandise trade
closures, and other virus-containment measures        in those countries. It employs recent advance-
resulted in a macroeconomic shock. Several            ments in empirical modelling to estimate the
accounts indicate that 2020’s global recession        aggregate effect of the COVID-19 pandemic on
has been the worst since 1930 (Blake and              the global and intra-Commonwealth trade in
Wadhwa, 2020; Hevia and Neumeyer, 2020).              member countries’ goods and to explore the het-
The pandemic affected trade flows along both          erogeneity (or otherwise) of that impact across
supply and demand channels (Lakatos, 2020).           various groups, including the least developed
In 2020, global trade flows collapsed on average      countries (LDCs) and small states. It also devel-
by around 8 per cent (WTO, 2020b); that               ops a set of policy options and recommendations
impact, however, has varied across countries          aiming to revive merchandise trade flows in the
and regions, largely depending upon the level         Commonwealth and ensure a sustainable recov-
of development, trade structure, stringency           ery from the economic impact of the COVID-19
of containment measures, and governments’             pandemic, as well as to build resilience against
capacity to implement policies supporting             future shocks.
business and households.                                 Few studies have examined the relationship
   The pandemic had a disproportionately              between trade and COVID-19. To our
severe economic and trade effect on 54                knowledge, only Hayakawa and Mukunoki
Commonwealth countries. It induced a deep             (2020), Espitia et al. (2021), and Friedt and Zhang
recession in 45 Commonwealth economies,               (2021) have used an econometric approach to
the gross domestic product (GDP) of which             examine the impact of COVID-19 on trade.
collapsed by US $1.45 trillion in a single            None of these, however, focuses on how the
year. This translated to $345 billion forgone         pandemic has impacted Commonwealth trade.
in member countries’ global exports and $60           Thus this paper aims to fill a gap in the literature
billion in intra-Commonwealth trade flows.            and inform discussions of the potential impact
Among other things, their large populations,          of COVID-19 on Commonwealth merchandise
heavy reliance on commodities exports, and            trade flows, as well as to offer recommendations
similar deep recessions in major export markets,      for policy to revive Commonwealth countries’
made these countries particularly susceptible to      economies.
financial contagion (see section 2). Moreover,           The paper uses bilateral monthly exports
because of pre-existing structural vulnerabilities,   data from January 2019 to November 2020
COVID-19 proved to be a particular problem            to examine the short-term effects of the
for low-income countries, including several of        COVID-19 pandemic on global and intra-
the Commonwealth’s small states.                      Commonwealth trade in member countries’
   Against this backdrop, there has as yet been       goods, including among these countries
no detailed contextualisation of the linkage          the LDCs and small states. We examine the
between the incidence of COVID-19 and the             exporting Commonwealth countries and their
trade flows within the diverse group of countries     trading partners to investigate how shocks
that comprise the Commonwealth. The                   related to COVID-19 and sector characteristics
International Monetary Fund (IMF) estimated a         may have impacted on trade relationships.
fall in commodity prices with an adverse impact       The study uses three different measures of
on trade and the macroeconomic situation of           the incidence of COVID-19 in a country: the
those countries affected (IMF, 2020). Thus, the       number of COVID-19 infections, the number
effect of COVID-19 on trade may be particularly       of deaths and the stringency of measures aiming
acute for Commonwealth countries, which               to contain the virus.
6                                            The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

              The paper is structured as follows.                         • Section 4 offers insight into the data and the
                                                                            empirical specification of the gravity model,
• In section 2, we provide descriptive evi-                                 as well as delivers our main findings.
  dence of the impact of COVID-19 on                                      • In section 5, we draw some conclusions and
  Commonwealth countries’ economies.                                        make recommendations for Commonwealth
• Section 3 presents an overview of the cur-                                countries seeking to build resilience and
  rent literature on the economic impact of                                 protect their economies against future
  COVID-19.                                                                 shocks.

  2. Correlations between the COVID-19 pandemic and
         Commonwealth countries’ trade flows

The Commonwealth is diverse group of 54                                   (Roser et al., 2020). This crisis was accompa-
countries stretching from the east coast of New                           nied by a severe drop in the Commonwealth’s
Zealand to the western parts of the Caribbean                             global and intra-Commonwealth trade flows
and South America. Six Commonwealth mem-                                  (see Figure 1). Relative to pre-pandemic
ber countries are developed, while 48 are at                              growth trends, Commonwealth economies
various levels of economic development. This                              contracted by around 10 per cent in 2020, mak-
is not a formal trade bloc, but myriad drivers                            ing this group of countries an interesting case
of international trade, such as a common lan-                             in which to study the implications of the pan-
guage (English being a first or second lang­                              demic. While some of them have been able to
uage in most Commonwealth countries), a                                   contain the pandemic and resume production
shared colonial history, some cultural common                             and trading activities, at time of writing most
ground and similar legal systems, underpin the                            Commonwealth countries are still struggling to
trade and economic relationships within this                              tame the pandemic.
heterogeneous association.                                                   Several factors likely contributed to the seis-
   The COVID-19 pandemic wreaked havoc on                                 mic trade meltdown in these economies. First,
most of the Commonwealth countries’ econo-                                the Commonwealth is home to 32 per cent of
mies. As of 20 March 2021, Commonwealth                                   the world’s people and its membership includes
populations had succumbed to 20 million                                   four of the ten most populated countries (India,
infections and witnessed 1 million deaths                                 Pakistan, Bangladesh and Nigeria). Aside from

Figure 1. Commonwealth’s global and intra-Commonwealth exports compared, 2019 and 2020
                                Global exports                                                Intra-commonwealth exports

              3.9                                                               710                     701.2
              3.9                   3.83                                        700
              3.8                                                               690
              3.8     3.73                                                      680   672.6
              3.7
US$ trilion

                                                                  US$ billion

                                                                                670
              3.7
                                                                                660
              3.6
              3.6                                      3.54                     650
                                                                                                                            641.0
              3.5                                                               640
              3.5                                                               630
              3.4                                                               620
              3.4                                                               610
                                  Pre-COVID          In-COVID                                        Pre-COVID             In-COVID
                                   forecast           estimate                                        forecast              estimate
                      2019                    2020                                    2019                     2020

Note: Calculated using the IMF’s pre-pandemic forecasts (October 2019) and in-pandemic estimates (April
2021), and trade-to-GDP ratios taken from the World Development Indicators.
Source: Commonwealth Trade Review (2021).
International Trade Working Paper 2021/08                                                                                                                                7

these demographic reasons, several underlying                                             by mineral ores (36 per cent) and agri-food
structural factors made these countries particu-                                          products (22 per cent). Around 55 per cent of
larly vulnerable to the trade contagion.                                                  these exports are destined for only five mar-
   Second, two-thirds of the Commonwealth’s                                               kets: China, the USA, the European Union, the
global and intra-Commonwealth trade is in                                                 United Kingdom and Australia. The COVID-
manufactured goods and commodities. For                                                   19 pandemic negatively affected demand for
many member countries, especially developing                                              commodities in these countries, leading to a
countries, the proportion of commodities in                                               collapse in commodity prices, particularly of
gross national exports ranges from 40 per cent                                            fuels. The prices of other key commodities,
to more than 95 per cent, which is extremely                                              such as agricultural products and mineral ores,
high compared with the world average of 29 per                                            were relatively less affected. Nevertheless, a
cent (see Figure 2). These economies were con-                                            reduction in demand, along with challenges
sequently hit particularly hard when commodi-                                             associated with production and exporting, led
ties prices dropped.                                                                      to an aggregate export loss of around US $125
   Commonwealth countries’ main commod-                                                   billion for Commonwealth countries in 2020—
ity exports are food products, mineral ores,                                              even though the prices of most commodities
metals and fuels. Among these, fuels are the                                              had surged in the second half of 2020, offset-
most exported, constituting around 42 per cent                                            ting some of the earlier trade losses in com-
of all commodities exports. This is followed                                              modity-dependent economies (see Figure 3).

Figure 2. Excessive reliance of Commonwealth countries on commodities exports
                                             Commonwealth Country Groups                                              Developing Commonwealth Countries
                                                     Percent                                                                       Percent
                                     –     10 20 30 40 50 60 70 80               90                     –   10   20      30    40    50    60   70      80    90   100

  Commonwealth CDCWCs (35)                                                      84
                                                                                          Pacific (9)                                                               97

  Commonwealth developed (6)                                        51
                                                                                           Africa (9)                                                    79

        All commonwealth (54)                                  45

                                                                                      Caribbean (12)                                         58
 Commonwealth developing (48)                             40

                     World average                                                           Asia (8)                      29
                                                     29

Source: Ali et al. (2020).

Figure 3. Monthly variation in commodity price indices in 2020
                    180

                    160

                    140

                    120
         2015=100

                    100

                     80

                     60

                     40
                                         Agricultural products            Agricultural raw materials             Minerals, ores and metals            Fuels
                     20

                      0
                           Dec.           Jan.     Feb.     Mar.         Apr.    May       Jun. Jul.             Aug.     Sep.     Oct.      Nov.    Dec.
                           2019           2020     2020     2020         2020    2020      2020 2020             2020     2020     2020      2020    2020

Source: Calculated using data from UNCTADstat.
8                                The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

Figure 4. Impact of the pandemic on Commonwealth merchandise exports, December 2019 to December 2020
      1.1

      1.0

      0.9

      0.8

      0.7

      0.6
      0.5

      0.4

      0.3

                                                                                   .
             9

                  n

                         b

                               ar

                                        r

                                              ay

                                                         n

                                                               l

                                                                      g

                                                                              t

                                                                                         v.

                                                                                                     0
                                                             Ju

                                                                                   ct
                                      Ap

                                                                             p
           01

                 Ja

                                                       Ju

                                                                                                   02
                       Fe

                                                                    Au

                                                                                        No
                              M

                                                                          Se
                                             M

                                                                                  O
         .2

                                                                                                 .2
      ec

                                                                                             ec
     D

                                                                                             D
                                              Global               Intra-CW

Note: Exports are indexed to 1 in December 2019.
Source: Commonwealth Trade Review (2021).

    The adverse effect of the pandemic on                containment measures in place are those that
global and intra-Commonwealth merchan-                   have experienced a large decline in trade flows.
dise exports was first felt in early January                Finally, the period of the pandemic
2020, immediately after the outbreak of the              saw constrained economic growth in the
novel coronavirus in China in December                   Commonwealth’s major export markets,
2019. The most marked effect occurred dur-               adversely affecting demand for goods and ser-
ing April and May 2020, when the USA and                 vices (see Figure 5). Other than China, where
many large export markets in Europe imposed              GDP expanded by 2.3 per cent, the major des-
national lockdowns. In these two months,                 tinations for Commonwealth exports recorded
Commonwealth members’ exports dropped to                 significant contractions in GDP in 2020. In India
almost half their baseline (see Figure 4). The           and Singapore, GDP declined by more than 5
impact was higher for intra-Commonwealth                 per cent. In the USA, which absorbs 31 per cent
exports compared with global exports because             of developed Commonwealth members’ goods
many of the large intra-Commonwealth trad-               and services exports and 12 per cent of those
ers—including India, Singapore, South Africa             from developing members, GDP contracted by
and the United Kingdom—experienced an                    3.5 per cent. The European Union, which col-
economic contraction, affecting supply and               lectively represents the second-largest market
demand. Exports plateaued in May 2020, but               for Commonwealth exports, contracted by 6.6
they rebounded in June 2020 as firms sought              per cent. Within the EU-27, growth in the three
to adapt to pandemic containment measures.               top destinations for Commonwealth exports—
At time of writing, merchandise exports                  Germany, France and the Netherlands—fell
are gradually recovering as lockdowns and                by 4.9 per cent, 8.2 per cent and 3.7 per cent,
other restrictions on economic activities are            respectively. Similarly, the GDP of the United
lifted in many countries. In December 2020,              Kingdom, a key destination for intra-Com-
however, the Commonwealth’s exports were                 monwealth exports, dropped by around 9.9 per
still well below their pre-pandemic levels in            cent. These markets collectively absorb around
December 2019.                                           75 per cent of Commonwealth developed
    The drop in Commonwealth countries’                  members’ exports and around half those of
exports correlates strongly with incidence of            developing countries. At time of writing, most
the virus. Those countries with high num-                of these economies are still subject to various
bers of infections (and deaths) and with strict          virus-containment measures.
International Trade Working Paper 2021/08                                                                                           9

Figure 5. Commonwealth market share and GDP drop for large export markets (%)
                                         Commonwealth countries pre-COVID-19 export share, by market (%)

       All commonwealth
                                                                                Japan, 4
                                 USA, 22             EU-28, 20         China, 13                            ROW, 39
                                                                                  Singapore, 3

                          0        10         20       30         40        50        60         70           80      90     100
                                                                         Share (%)

                                                           GDP impact for large export markets

                               USA

                                UK

                          Singapore

                              Japan

                               India

    Hong Kong, China

                          Euro area

                              China

                                 –12.0     –10.0    –8.0      –6.0     –4.0     –2.0       0.0        2.0      4.0     6.0    8.0
                                                                     GDP growth rate (%)
                                                        2020 actual     2020 pre-COVID forecast

Source: Commonwealth Trade Review (2021).

                                                    3. Literature review

The COVID-19 pandemic resulted in an eco-                                    investment. McKibbin and Fernando (2020)
nomic shock across countries that, in turn,                                  offer a supply-side analysis of the pandemic and
impacted GDP and generated an economic                                       suggest that reduced labour supply increased
downturn, with a negative effect on international                            the cost of production. Similarly, social distanc-
trade. Studies highlighting pandemic-related                                 ing measures introduced to reduce the spread
shocks to demand and supply attribute transmis-                              of the disease affected production, consump-
sion of these shocks to the disruption of global                             tion and trade patterns, both directly and indi-
value chains (GVCs) (Baldwin and Freeman,                                    rectly (Espitia et al., 2021). Those examining
2020; Baldwin and Tomiura, 2020). These studies                              the impact of measures imposed to prevent
suggest that the pandemic disrupted manufac-                                 the spread of COVID-19 unanimously agree
turing sectors when containment efforts stifled                              that the restrictions led to a sharp economic
direct supply, with impact on the international                              downturn.
flow of intermediate inputs, and when global                                    Studies examining the relationship between
demand dropped as consumer spending slowed                                   trade and COVID-19 focus mainly on GVCs
and investment was delayed.                                                  and whether these absorbed or transmit-
   On the demand side, Correia and colleagues                                ted COVID-19 shocks. Baldwin and Tomiura
(2020) examine the economic contagion as                                     (2020), Javorcik (2020a, 2020b) and Miroudot
COVID-19 impacted the aggregate demand                                       (2020), for example, report that GVC disrup-
channel and depressed household spending,                                    tions magnified pandemic-induced produc-
leading to business uncertainty about future                                 tion shock and impacted adversely on all of
demand and an adverse effect on business                                     output, employment and trade. Others, such as
10                            The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

Sforza and Steininger (2020), Meier and Pinto        machinery products in the importing countries
(2020), and Eppinger et al. (2020), have inves-      but negatively affected final machinery exports
tigated interconnectedness and the channels          in supplier countries; as a result, supply-side
through which economic shock is transmitted,         shocks were more significant in the early stages
finding that the economic effect of COVID-19         of the pandemic. A substitution effect was wit-
was spread through supply chain linkages, with       nessed, results showing that a country’s exports
particularly severe consequences for highly          are positively associated with the pandemic
integrated economies compared to those less          burden borne by its neighbours.
integrated in GVCs.                                     Espitia et al. (2021) use the gravity model
   Eppinger and colleagues (2020) and Gerschel       to examine how bilateral trade growth may
et al. (2020) also examine the global intercon-      have been impacted by supply and demand
nectedness of international trade and GVCs,          shocks during the COVID-19 crisis among
showing that slowing productivity in China’s         exporting, partner and third countries. This
Hubei province impacted on the global econ-          study, examining 28 exporting countries and
omy. Friedt and Zhang (2021) employ gravity          multiple trading partners over a period from
modelling to specifically examine the impact         the beginning of the pandemic to June 2020,
of the pandemic on Chinese exports and to            employs DD techniques and relates COVID-
explore the heterogeneity of trade effects across    19 shocks to sector characteristics. The shocks
Chinese provinces, international trade partners      across sectors are assumed to be heterogeneous
and commodities. Their results show that GVC         and that sector characteristics can address the
contagion reduced Chinese exports by 40–45           decline in bilateral export growth induced by
per cent during the first half of 2020—that is,      the shocks. The regression results, based on a
that Chinese exports were highly sensitive to        sector-level gravity model, show that negative
rising rates of infection both nationally and        trade effects induced by the shocks varied widely
globally. Fernandes (2020) uses difference-in-       across sectors and that sectors within which
difference (DD) techniques to focus on trade         remote working was possible contracted less
resilience measures such as a sector’s depen-        than those within which it was not. Espitia et al.
dence on China for inputs, the labour intensity      (2021) also find that while GVC participation
of its production and its technological proxim-      increased traders’ vulnerability to shocks, it
ity to other sectors.                                also reduced their exposure to domestic shocks.
   Bonadio et al. (2020) have examined the              Other studies have focused on the
impact of GVC disruption on GDP. Their study         implications of COVID-19 for trade in services,
differentiates between foreign and domestic          foreign direct investment (FDI), tourism and
shocks, and it calibrates the likely impact of       food security. For example, Maliszewska et al.
lockdown measures in 64 countries by simu-           (2020) employ a standard global computable
lating what would happen if countries were to        general equilibrium (CGE) model to examine
be reliant on domestic inputs. Guan and col-         the impact on trade in services by simulating
leagues (2020) use the economic disaster model       the potential impact of COVID-19 on GDP and
to assess the supply chain effects of different      trade. Their results show that domestic services
COVID-19 control measures and they empha-            and traded tourist services suffer the biggest
sise the indirect impacts on other countries         negative shock. With an open-economy model,
through supply chain linkages.                       Ozge et al. (2020) examine the macroeconomic
   Hayakawa and Mukunoki (2020) assess the           effects of pandemic-induced shocks on capital
correlation between the number of COVID-19           flows to emerging market economies. Their
cases and deaths and rates of bilateral exports      study shows output losses in emerging markets
and imports of machinery goods (finished and         and attributes these losses to local currency
intermediates) between January and June 2020         depreciation, which has a knock-on effect
for 26 reporting and 185 partner countries.          within the developed world.
Their results indicate that registered COVID-           International organisations have analysed the
19 cases and deaths in the exporting countries       impact of COVID-19 on developing countries,
were likely to be a key factor suppressing inter-    focusing in particular on how trade in the com-
national trade. Their findings also suggest that     modity sectors has been affected (OECD, 2020a,
COVID-19 did not impact demand for finished          2020b; UNECLAC, 2020; Escaith et al., 2020).
International Trade Working Paper 2021/08                                                               11

Within the context of the Commonwealth               commodity exports to the destination markets
countries, Ali and colleagues (2020) estimated       would decline by US $98–123 billion in 2020—
the impact of pandemic-induced trade dis-            in percentage terms, an export loss of 19–24 per
ruptions on exports of commodities to China,         cent compared to pre-pandemic benchmark
the USA, the European Union, the United              estimates.
Kingdom and Australia. They predicted that

                                     4. Methodology

We use the gravity model of international            Xijt = exp(β1 ln GDPit + β2 ln GDPjt
trade to assess the impact of the COVID-                   + β3 ln COVIDit + β4 ln COVID jt
19 pandemic on bilateral trade flows. In a                                                             (1)
                                                           + β5 Dij + β6 FTAij + β7COLij
basic gravity model, trade between country
i and country j is proportional to the size of             + β7 BORDij + β5 LANGij + θi
the economies and inversely relates to the                 + π j + γt )µijt
distance—a proxy for transportation costs—
between them. Thus it can generally be               where
described as:                                          GDPit and GDPjt are the GDPs of countries
                           YiY j                                 i and j, respectively, in period t
                 Xij = A                                COVIDit and COVIDjt are the number of
                           Dij
                                                                 COVID-19 cases or deaths (or the strin-
where                                                            gency of containment measures) in the
                                                                 respective countries at time t
  Xij is trade flows or exports from country            Dij denotes the great circle distance between
       i to country j                                            countries i and j
   Yi is the GDP of country i                             FTAij denotes an FTA dummy variable
   Yj is the GDP of country j                             COLij denotes colonial relationship (either past
   Dij denotes geographical distance between                    or present) between the trading countries
       the two countries (which could be replaced          BORDij denotes a shared border (i.e. neigh-
       by trade costs proxies).                                  bouring countries)
                                                            LANGij denotes that countries have at least
   A commonly used analytical framework, the                     one (first or second) language in common
gravity model has been applied in many empir-                γt indicates time-specific effects (by month)
ical studies to estimate the effects of trade pol-               that are common to all trading countries.
icy changes by introducing dummy variables.
Among the policies analysed are the effects of          Since GDP variables are available for the
free trade agreements (FTAs).                        whole of 2019, we use the origin and destina-
   The model in this study introduces the            tion fixed effects θi and πj, which are a proxy for
following:                                           multilateral resistance factors in equation (1).
• the number of COVID-19 cases by country               The second empirical specification, equation
  and time;                                          (2), replaces the typical bilateral gravity variables
• the number of deaths resulting from the            by time-invariant fixed effects, denoted by Φij:
  virus; and                                         Xijt = exp(β1 ln GDPit + β2 ln GDPjt
• an index that is a proxy for the stringency of
                                                           + β3 ln COVIDit + β4 ln COVID jt            (2)
  virus-containment measures implemented
  during the pandemic in each country.                     + φij + γt )µijt

   After adding the dimension of time and               Theoretically, the model is based on a con-
other variables, the first empirical specification   stant elasticity substitution (CES) system.
of the model is:                                     Anderson and van Wincoop (2003) used a
12                              The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

non-linear least squares (NLS) model that con-         The data on the number of COVID-19 cases,
siders the endogeneity of trade costs to refine        number of deaths and the stringency index is
the theoretical foundations of the gravity model       retrieved from Roser and colleagues (2020).
and provide evidence of border effects in trade.       Data on GDP in nominal values and popula-
They indicated that the costs of bilateral trade       tion in number of inhabitants is obtained from
between two countries are affected not only by         the World Bank Development Indicators data
bilateral trade costs, such as distance, whether       series. The data on geographical and cultural
or not they are landlocked, a shared border and        proximity, such as distance, shared border and
a common language, but also by the relative            common language, is from the Centre d’Etudes
weight of trade costs in comparison to those of        Prospectives et d’Informations Internationales
their trading partners in the rest of the world        (CEPII) database.
(the so-called multilateral resistance terms, or          Table 1 presents some summary statistics.
MRT).1 Anderson and van Wincoop (2003)
pointed out that these multilateral resistance         4.2 Empirical specification and main results
factors should be taken into account in empiri-        To examine how COVID-19 may have
cal research to avoid a biased estimation of           impacted international trade, we analysed
the model’s parameters. Baier and Bergstrand           monthly trade data for 186 countries over a
(2007) used country-pair fixed effects in addi-        period spanning January 2019 to November
tion to time-varying trade costs to obtain unbi-       2020.
ased estimates. According to the most recent              Table 2 presents the main results for the
developments, a Poisson pseudo maximum                 whole sample.
likelihood (PPML) approach can be applied if              The gravity model has been estimated using
the model is to retain zero trade flows (Head          PPML: first, with exporter and importer fixed
and Mayer, 2014; Yotov et al., 2016).                  effects (FE) as proxies for the MRT (equation
                                                       (1)) and with time FE; and, secondly, with
4.1 Data sources and variables                         bilateral and time FE (equation (2)). The first
The main source for bilateral trade flows is           three columns of Table 2 report the results
monthly data from the UN Comtrade database             of equation (1) using PPML and show the
for January 2019 to November 2020. See Table           estimated coefficient of COVID-19-related and
A.1 for a list of Commonwealth countries.              gravity variables. All of the variables are taken
   Health authorities worldwide have collected         with one lag—that is, the previous month—to
primary data on COVID-19 on a daily basis.             account for lagged effects.

Table 1. Summary statistics

 Variable                                 Obs          Mean            SD           Min           Max

 Trade value (US$)                      213380      1.025e+08       7.982e+08             0    4.713e+10
 Partner GDP 2019, constant 2010        206439      6.568e+11       2.070e+12      12581       1.830e+13
 Reporter GDP 2019, constant 2010       213349      9.698e+11       2.602e+12      18008       1.830e+13
 Partner population 2019                207605       55230309       1.784e+08      11646       1.398e+09
 Reporter population 2019               206805       59541509       1.838e+08      18008       1.366e+09
 Partner new monthly cases              213380      10331.793       93175.493             0      4496410
 Partner monthly deaths                 213380         291.381       2290.678             0        60750
 Partner monthly average stringency     213380          16.473         29.057             0             100
 Reporter total monthly cases           213380      19659.207       152796.27             0      2621418
 Reporter total monthly deaths          213380         523.002       3368.124             0        60750
 Reporter monthly average stringency    213380          15.647         27.556             0             100
 Contiguity dummy                       213380             .024           .154            0               1
 Common language dummy                  213380             .134           .341            0               1
 Former colony dummy                    213380             .022           .148            0               1
 Distance between countries             213380        6983.341       4354.057      19.127      19812.043
International Trade Working Paper 2021/08                                                                                 13

Table 2. Main results: gravity model estimations with PPML for the whole sample

 Dep. var.: export value           (1)             (2)               (3)             (4)            (5)            (6)

 Explanatory var.
 Lag-lncovcai                   −0.033***                                         −0.028***
                                   (0.005)                                          (0.005)
 Lag-lncovcaj                      −0.002                                           −0.003
                                   (0.003)                                          (0.003)
 Lag-lncovdei                                   −0.028***                                        −0.023***
                                                  (0.005)                                          (0.005)
 Lag-lncovdej                                     −0.003                                           −0.003
                                                  (0.004)                                          (0.005)
 Lag-lnstrini                                                    −0.039***                                      −0.050***
                                                                    (0.014)                                        (0.013)
 Lag-lnstrinj                                                       −0.008                                         −0.009
                                                                    (0.009)                                        (0.008)
 lndij                          −0.621***       −0.620***        −0.619***
                                   (0.034)        (0.034)           (0.034)
 Regional trade agreement        0.349***        0.349***         0.350***
   dummy
                                   (0.072)        (0.072)           (0.072)
 Former colony dummy             0.262***        0.262***         0.261***
                                   (0.096)        (0.096)           (0.097)
 Contiguity dummy                0.366***        0.367***         0.367***
                                   (0.102)        (0.102)           (0.102)
 Common language dummy              0.111           0.111             0.110
                                   (0.089)        (0.089)           (0.089)
 Observations                     178,120        178,120           178,120         177,137        177,137        177,137
 Month FE                                Yes             Yes               Yes             Yes            Yes            Yes
 i                                       j FE            j FE              j FE
 Pseudo-R2                          0.923           0.923             0.923           0.991          0.991          0.991
 ij FE                                                                                     Yes            Yes            Yes

Note: Robust standard errors in parentheses; *** p
14                             The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

           Table 3. Gravity model estimations: heterogeneous effects by
           income level

            Dep. var.: export value             (1)                    (2)                 (3)

            Explanatory var.
            laglncovcai                     −0.026***
                                                (0.004)
            laglncovcaj                     −0.016***
                                                (0.003)
            laglncovcaiH                       −0.003*
                                                (0.002)
            laglncovcajH                      0.015***
                                                (0.002)
            laglncovdei                                             −0.020***
                                                                       (0.005)
            laglncovdej                                             −0.020***
                                                                       (0.004)
            laglncovdeiH                                              −0.005*
                                                                       (0.003)
            laglncovdejH                                             0.020***
                                                                       (0.004)
            laglnstrini                                                              −0.045***
                                                                                           (0.013)
            laglnstrinj                                                              −0.041***
                                                                                           (0.008)
            laglnstriniH                                                             −0.017***
                                                                                           (0.006)
            laglnstrinjH                                                              0.041***
                                                                                           (0.005)
            Observations                       177,137                177,137             177,137
            Month FE                                  Yes                    Yes                 Yes
            ij FE                                     Yes                    Yes                 Yes
            Pseudo-R2                            0.991                  0.991               0.991

           Note: Robust standard errors in parentheses; *** p
International Trade Working Paper 2021/08                                                                     15

   In Table 4, the gravity model is estimated for        (1)–(3)). The number of COVID-19 cases in
the Commonwealth exporting (columns (1)–                 the exporting countries plays only a minor role,
(3)) and importing (columns (4)–(6)) countries           however. When the focus is on Commonwealth
separately. As in Table 3, we add the interactions       imports (columns (4)–(6)), it is important to
for COVID-19 variables with a dummy variable             note that the incidence of COVID-19 in both the
for high-income Commonwealth countries to                exporting and importing countries plays a role.
acknowledge that the effects can be heteroge-               Table 5 presents similar estimates for intra-
neous. The estimates indicate that a high inci-          Commonwealth trade. The first part of the table
dence of COVID-19 in the low-income importing            present the results of gravity and COVID-19
countries (laglncovcaj) reduces Commonwealth             variables, whereas the second part replaces the
exports, whereas a high incidence in the high-           gravity variables with time-invariant bilateral FE,
income importing countries (laglncovcajH)                as in Table 2, for the whole sample. In general,
increases Commonwealth exports (see columns              similar to the results for all countries, the effect

Table 4. Model estimated for Commonwealth exporters and importers

                           Commonwealth exporters                         Commonwealth exporters

 Dep. var.: trade         (1)            (2)             (3)            (4)             (5)            (6)
 value

 Explanatory var.:
 Laglncovcai            −0.010*                                      −0.024***
                         (0.006)                                        (0.009)
 Laglncovcaj          −0.021***                                       −0.014**
                         (0.006)                                        (0.006)
 laglncovcaiH             −0.003                                      −0.013**
                         (0.004)                                        (0.005)
 laglncovcajH          0.017***                                       0.029***
                         (0.004)                                        (0.005)
 Laglncovdei                           −0.013**                                       −0.016*
                                         (0.006)                                       (0.008)
 Laglncovdej                          −0.026***                                     −0.028***
                                         (0.006)                                       (0.006)
 laglncovdeiH                            −0.007                                      −0.019**
                                         (0.005)                                       (0.008)
 laglncovdejH                          0.024***                                      0.038***
                                         (0.005)                                       (0.008)
 Laglnstrini                                           −0.025*                                      −0.045***
                                                        (0.013)                                        (0.014)
 Laglnstrinj                                         −0.033***                                      −0.050***
                                                        (0.011)                                        (0.019)
 laglnstriniH                                           −0.007                                      −0.041***
                                                        (0.011)                                        (0.012)
 laglnstrinjH                                         0.047***                                       0.062***
                                                        (0.010)                                        (0.010)
 Observations             41,649         41,649         41,649          38,279         38,279          38,279
 Month FE                       Yes            Yes             Yes            Yes             Yes            Yes
 ij FE                          Yes            Yes             Yes            Yes             Yes            Yes
 Pseudo-R2                 0.990            0.990         0.990          0.986           0.986          0.986

Note: Robust standard errors in parentheses; *** p
16                                  The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

Table 5. Results for intra-Commonwealth trade by developed and developing countries

                                     Developed CW countries                        Developing CW countries

 Dep. var.: trade value        (1)              (2)            (3)           (4)             (5)           (6)

 Explanatory var.
 laglncovcai                   –0.016                                      –0.023**
                               (0.014)                                      (0.010)
 laglncovcaj                –0.018**                                       –0.016**
                               (0.008)                                      (0.007)
 laglncovcaiH                  –0.006                                         0.006
                               (0.009)                                      (0.007)
 laglncovcajH               0.029***                                       0.033***
                               (0.006)                                      (0.006)
 laglncovdei                                    –0.008                                      –0.022*
                                                (0.016)                                     (0.013)
 laglncovdej                                –0.034***                                    –0.035***
                                                (0.010)                                     (0.010)
 laglncovdeiH                                   –0.012                                        0.006
                                                (0.015)                                     (0.010)
 laglncovdejH                                0.038***                                     0.044***
                                                (0.009)                                     (0.009)
 Laglnstrini                                                   –0.031                                      –0.046
                                                              (0.030)                                     (0.029)
 Laglnstrinj                                                   –0.035                                      –0.028
                                                              (0.025)                                     (0.024)
 laglnstriniH                                                  –0.008                                        0.017
                                                              (0.021)                                     (0.013)
 laglnstrinjH                                                0.069***                                    0.073***
                                                              (0.014)                                     (0.013)
 Lndij                     –0.624***        –0.624***       –0.621***
                               (0.106)          (0.106)       (0.107)
 Regional trade             0.699***         0.699***        0.699***
   agreement dummy
                               (0.136)          (0.136)       (0.136)
 Former colony dummy          0.612**          0.613**        0.606**
                               (0.295)          (0.295)       (0.295)
 Contiguity dummy             –0.866*          –0.866*         –0.861
                               (0.522)          (0.523)       (0.524)
 Common language            1.994***         1.996***        1.987***
   dummy
                               (0.385)          (0.386)       (0.386)
 Observations                   9,816            9,816          9,816         9,753           9,753          9,753
 Month FE                            Yes              Yes            Yes           Yes             Yes        Yes
 i,j FE                                                                            Yes             Yes        Yes
 Pseudo-R2                      0.886            0.886          0.886         0.977           0.977          0.977
 ij FE                                                                             Yes             Yes        Yes

Note: Robust standard errors in parentheses; *** p
International Trade Working Paper 2021/08                                                                     17

of COVID-19 on intra-Commonwealth trade is               cases or deaths in the neighbouring countries,
higher in magnitude, in particular when consid-          calculated using a distance-weighted sum of
ering incidence in terms of the number of deaths         COVID-19 burden, is given by:
in the importing countries (cf. 0.02 in Table 3,
column (2), vs 0.044 in Table 5, column (5), for                                         COVID jt (it ) 
high-income countries). The stringency index
                                                         NeighCOVIDit ( jt ) =   ∑
                                                                                 j ≠i
                                                                                        
                                                                                          Distance 
                                                                                                   ij 
                                                                                                             (3)
also presents a different effect for Commonwealth
trade: in high-income Commonwealth countries,
                                                         where
a higher level of stringency measures increases
trade (cf. 0.073 in Table 5, column (6), vs 0.041 in       COVIDit(jt) represents the number of cases
Table 3, column (3)).                                       and number of deaths in country i(j).
   For robustness, we analyse the impact of
COVID-19 on neighbouring exporting and                      The empirical specification of the model,
importing countries in terms of bilateral                given by equation (1), is augmented with the
exports of a given trading pair. The number of           corresponding variables:

         Table 6. Gravity model for COVID-19 incidence in neighbouring countries

           Dep. var: trade value               (1)                    (2)                         (3)

           Explanatory var.
           lncovcai                         –0.025***
                                               (0.003)
           lncovcaj                          –0.008**
                                               (0.003)
           lnneigcovcait                      –0.042*
                                               (0.022)
           lnneigcovcajt                    –0.131***
                                               (0.034)
           lncovdei                                               –0.026***
                                                                     (0.004)
           lncovdej                                               –0.010***
                                                                     (0.003)
           lnneigcovdeit                                             –0.041
                                                                     (0.029)
           lnneigcovdejt                                          –0.116***
                                                                     (0.029)
           lnstrini                                                                          –0.033***
                                                                                                (0.008)
           lnstrinj                                                                          –0.026***
                                                                                                (0.008)
           lnneigcovsit                                                                         –0.101
                                                                                                (0.071)
           lnneigcovsjt                                                                         –0.020
                                                                                                (0.037)
           Constant                         21.911***             21.651***                  21.496***
                                               (0.146)               (0.097)                    (0.084)
           Observations                       212,112               212,112                    212,112
           Month FE                                Yes                   Yes                        Yes
           ij FE                                   Yes                   Yes                        Yes
           r2_p                                  0.991                 0.991                      0.991

         Note: Robust standard errors in parentheses; *** p
18                               The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

Xijt = exp(β1 ln GDPit + β2 ln GDPjt                      of the model with the number of COVID-19
                                                          cases and a counterfactual with zero COVID-
      + β3 ln COVIDit + β4 ln COVID jt
                                                          19 cases.
      + β3 ln NeighCOVIDit                          (4)      In Table A.3, the highest decreases in exports
      + β4 ln NeighCOVID jt                               over the period March–November 2020 are
      + β5 FTAijt + φij + γt )µijt                        observed for the USA (13 per cent), Canada
                                                          (12.4 per cent) and France (12 per cent); in the
where the definition of variables is that same as         case of imports, Namibia (19 per cent), Guyana
that provided under equation (2).                         (16 per cent) and Costa Rica (15 per cent) show
   Table 6 presents that an increase in the               the highest negative impact. It is worth men-
number of COVID-19 cases in neighbouring                  tioning that the time frame included a period
importing countries has a negative and signifi-           (summer 2020) during which some countries’
cant effect on exports that outweighs the effect          trade recovered slightly, which offset some of
on the average importing country (cf. –0.131              the negative impact experienced during the
vs –0.008) and this is also true for the number           first months of the pandemic.
of deaths. Lockdowns and other containment                   In addition, countries report bilateral
measures in neighbouring countries do not,                monthly data to the UN Comtrade data-
however, exert different impact on exports in             base only slowly, with the implication that, by
comparison to the average importer.                       January 2021, only 105 countries had reported
   The implications of COVID-19 on overall                their monthly trade statistics for January 2020;
trade—namely, exports and imports—for                     by the same date, only 50 countries had reported
specific countries are evaluated with the                 monthly data for November 2020.
coefficients obtained from estimates presented               The main consequence of this incomplete
in Table 2. Using the predictions of the gravity          matrix of monthly trade data is that we are not
model, we compared the expected trade with                able to present a forecast for 2021 using econo-
and without COVID-19 cases for the whole                  metric methods that require a balanced panel
period. Table 7 presents a summary of the                 data set. Nonetheless, we can use the coeffi-
results of those simulations, which shows                 cients obtained from the gravity models in a
negative changes in exports and imports for               partial equilibrium framework to infer what the
selected countries. All country-level results             effects of an increase or decrease in the number
can be found in the Appendix (Table A.3).                 of cases and deaths will be for the exports and
Table A.3 therefore compares the estimates                imports of the countries analysed.

Table 7. Decrease in exports due to COVID-19

 % decrease        Commonwealth countries                   Share of                 Share of intra-
 in exports        affected                                 Commonwealth trade       Commonwealth trade

 < 10%             Canada, India, Pakistan, South                  56.91                    40.83
                     Africa, UK
 7 – 10%           Australia, Bangladesh, Cameroon,                29.87                    38.44
                     Ghana, Jamaica, Kenya, Nigeria,
                     Singapore, Zambia
 5–7%              Bahamas, Belize, Botswana, Cyprus,              11.87                    18.37
                     Eswatini, Gambia, Guyana,
                     Malawi, Malaysia, Malta,
                     Mozambique, Namibia, Sri Lanka,
                     Trinidad & Tobago, Uganda
 Less than 5%      Antigua & Barbuda, Barbados,                     1.16                     2.12
                     Brunei Darussalem, Dominica,
                     Fiji, Lesotho, Mauritius, Nauru,
                     Papua New Guinea, Samoa,
                     Seychelles, Tanzania, Tonga,
                     Tuvalu, Vanuatu

Source: Model simulations
International Trade Working Paper 2021/08                                                           19

                5. Conclusions and policy implications

This paper uses gravity modelling to exam-             Short-term measures to overcome the chal-
ine the link between bilateral trade flows for      lenges of COVID-19 can be linked to eco-
Commonwealth exports and the impact of              nomic growth by investing in productivity and
COVID-19 on the global and intra-Common-            policies aiming to enhance the resilience of
wealth trade in goods. Analysis of data span-       Commonwealth countries. Appropriate plan-
ning January 2019 to November 2020 suggests         ning is required to minimise the impact on
that COVID-19 had an adverse impact on              sectors linked in GVCs. A roadmap will help
trade and that exports decreased as the num-        countries to achieve their short-, medium- and
ber of COVID-19 cases rose in an importing          long-term goals and to revitalise their econo-
country—that is, that high COVID-19 inci-           mies by taking into account the specific con-
dence in low-income importing countries             ditions and needs of those sectors adversely
reduces Commonwealth exports, whereas               affected. In the short term, governments should
high COVID-19 incidence in high-income              focus on the immediate health crisis, on ensur-
importing countries increases Commonwealth          ing food and nutritional security, on job cre-
exports. The incidence of COVID-19 in the           ation and on supporting the economy to ensure
exporting country, however, does not impact         that there is no long-term scarring from the
on trade. For Commonwealth imports, the             pandemic.
incidence of COVID-19 in both the exporting            In the medium term, Commonwealth coun-
and importing countries has an effect. In high-     tries’ focus should be on boosting bounce-back
income Commonwealth countries, more strin-          activities that will transform the recovering
gent measures aiming to contain the virus are       economy by promoting the long-term sustain-
associated with increased trade.                    able growth of international trade. For exam-
   The pandemic is ongoing at time of writing,      ple, regional co-operation might be one way of
and there is uncertainty about its likely dura-     achieving an inclusive structural transforma-
tion and severity across countries and regions.     tion. An important driver for co-operation in
The pandemic has also revealed the vulner-          Africa might be the African Continental Free
ability of Commonwealth countries linked in         Trade Area (ACFTA), which can add value and
GVCs, with supply and demand shocks having          support diversification, especially by means of
had a ripple effect. In this context, Friedt and    participation in regional value chains.
Zhang (2021) suggest that governments’ policy          Finally, in light of their growing participa-
response must aim at increasing the resilience      tion in world trade, Commonwealth countries
of GVCs—that policy-makers must devise              might find in the current situation a unique
measures that protect economies against sup-        opportunity to use new technologies to sup-
ply chain shocks and build their resilience. An     port policies targeting recovery. The use of new
important point to note is that, to design effec-   technologies, such as additive manufactur-
tive and co-operative policies as part of any       ing, will prompt a restructuring of GVCs and
recovery initiative within the Commonwealth,        may mitigate risks by means of a combination
co-operation is required at the regional and        of diversification strategies. It is also possible,
global levels.                                      however, that automation will fuel produc-
   To address the vulnerability of coun-            tion reshuffling that shifts nations’ incentives
tries linked in GVCs, commodity-dependent           and yields a redistribution of manufacturing
Common­wealth countries should consider a set       around the globe.
of policies and investments targeting inclusive        To conclude, while Commonwealth countries
structural transformation and aiming to diver-      will focus in the short term on remedying the
sify the economy. At the same time, commodity-      adverse impacts of the pandemic and restoring
dependent countries should consider adopting        jobs and employment, their long-term focus may
policy frameworks and measures that support a       be on improving productivity and boosting their
sustainable recovery post-COVID-19 and which        resilience by investing in a balanced portfolio
build resilience against future shocks.             of physical, human, social and natural capitals.
20                                     The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

For example, countries may choose to invest in                   providing sustainable returns for future genera-
health, education, skills development, innova-                   tions. In this way, Commonwealth countries may
tion, technological upgrading, and green infra-                  build capacity to deal with future challenges and
structure and natural capital, thereby increasing                mitigate the impact of future crises, including
the productive capacity of the population and                    pandemics, and other socio-economic shocks.

                                                           Notes

1 Anderson and van Wincoop (2003) derived the grav-                   yi and yj are the nominal income of countries i and j
  ity equation in a cross-sectional model as follows:                 yW≡∑jyj denotes world nominal income
                             1−σ                                      tij is the trade cost factor between countries i and j
           yi y j  t ij 
      xij = W                                                       σ is the elasticity of substitution between all goods
            y  Pi Pj                                                Pi and Pj measure the trade barriers of countries
                                                                            i and j in exports and imports, i.e. outward and
      where
                                                                            inward multilateral trade resistance.
       xij refers to exports from country i to country j

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22             The Impact of COVID-19 on the Global and Intra-Commonwealth Trade in Goods

                               Annex

      Table A.1 List of Commonwealth countries
      included in the analysis

       Partner countries                  Reporter countries

       Antigua and Barbuda                Antigua and Barbuda
       Australia                          Australia
       Bahamas                            Barbados
       Bangladesh                         Belize
       Barbados                           Botswana
       Belize                             Canada
       Botswana                           Cyprus
       Brunei Darussalam                  Eswatini
       Cameroon                           Ghana
       Canada                             Guyana
       Cyprus                             India
       Dominica                           Kenya
       Eswatini                           Malaysia
       Fiji                               Malta
       Ghana                              Mauritius
       Guyana                             Namibia
       India                              New Zealand
       Jamaica                            Pakistan
       Kenya                              Rwanda
       Kiribati                           Seychelles
       Lesotho                            Singapore
       Malawi                             South Africa
       Malaysia                           Uganda
       Malta                              United Kingdom
       Mauritius                          Zambia
       Mozambique
       Namibia
       Nauru
       New Zealand
       Nigeria
       Pakistan
       Papua New Guinea
       Rwanda
       Samoa
       Seychelles
       Sierra Leone
       Singapore
       South Africa
       Sri Lanka
       Tanzania, United Republic of
       Tonga
       Trinidad and Tobago
       Tuvalu
       Uganda
       United Kingdom
       Vanuatu
       Zambia

      Source: UN Comtrade.
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