1. Ismael FOFANA
Director for Capacity and Deployment
Akademiya2063

2. Impact of COVID-19 Induced
Global Trade Disruptions on
African Food Systems
Ismael FOFANA, Akademiya2063
Alhassane CAMARA, University of Sherbrooke
Mariam A. DIALLO, Akademiya2063
Leysa M. SALL, Akademiya2063

3. The COVID-19 pandemic has resulted in major disruptions in
global trade and markets of primary commodities
Changes in primary commodity prices between 2019 and 2020, percentage point difference between estimated and predicted prices for 2020
-40
-30
-20
-10
0
10
20
30
40
Coal,
Australia
Crude
oil,
avg
Natural
gas,
Europe
Natural
gas,
US
Natural
gas
LNG,
Japan
Cocoa
Coffee,
Arabica
Coffee,
Robusta
Tea,
auctions
(3),
average
Coconut
oil
Groundnut
oil
Palm
oil
Soybean
meal
Soybean
oil
Soybeans
Barley
Maize
Rice,
Thailand,
5%
Wheat,
US,
HRW
Bananas,
US
Meat,
beef
Meat,
chicken
Oranges
Shrimp,
Mexico
Sugar,
World
Logs,
Cameroon
Logs,
Malaysia
Sawnwood,
Malaysia
Cotton
A
Index
Rubber,
Malaysian
Tobacco
DAP
Phosphate
rock
Potassium
chloride
TSP
Urea,
E.
Europe,
bulk
Aluminum
Copper
Iron
ore
Lead
Nickel
Tin
Zinc
Gold
Silver
Platinum
Introduction

4. The COVID-19 pandemic has resulted in major disruptions in global
trade and markets of primary commodities (cont.)
Sector-specific percentage changes in global trade of commodities between 2019 and 2020
-11.8
-9.5
-9.0
-8.8
-8.3
-7.4
-7.3
-6.3
-6.0
-5.8
-4.1
Transport equipment
Fishing
Mining and quarrying
Electrical and machinery
Metal products
Petroleum, chemical an non-metallic mineral…
Agriculture
Wood and paper
Other manufacturing
Food and beverages
Textiles and wearing apparel
Introduction (Cont.)

5. Export baskets of most African countries are highly dependent on primary
commodities.
0 10 20 30 40 50 60 70 80 90 100
Lesotho
Tunisia
Morocco
Madagascar
Eswatini
Liberia
Ethiopia
Kenya
Sierra Leone
Guinea Bissau
Egypt
Seychelles
Togo
Niger
South Africa
Sudan
Gambia
Tanzania
Senegal
DRC
Rwanda
Benin
Gabon
Cabo Verde
Cote d'Ivoire
Malawi
Guinea
Uganda
CAR
Namibia
Zambia
Ghana
Mauritania
Burkina Faso
Zimbabwe
Mozambique
Botswana
Congo
Chad
Nigeria
Mali
Angola
Cameroon
South Sudan
0 10 20 30 40 50 60 70 80 90 100
South Sudan
Liberia
Ethiopia
Chad
Uganda
DRC
Sudan
Gabon
Seychelles
Ghana
Cameroon
Niger
Sierra Leone
Congo
Morocco
Malawi
Tanzania
South Africa
CAR
Madagascar
Tunisia
Mali
CaboVerde
Eswatini
Kenya
Burkina Faso
Zambia
Angola
Guinea
Mauritania
Nigeria
Egypt
Guinea Bissau
Rwanda
Cote d'Ivoire
Togo
Gambia
Namibia
Senegal
Mozambique
Zimbabwe
Lesotho
Benin
Botswana
Percentage share of primary commodities in total imports in 2019
Percentage share of primary commodities in total exports, 2019
Introduction (Cont.)

6. Assess the effects of changes in international prices and traded
volumes of primary commodities on the food systems in selected
African countries.
• 23 African countries: Cabo Verde, Cameroon, Central African Republic, Chad,
Congo, Côte d’Ivoire, Democratic Republic of the Congo, Egypt, Ethiopia, Gabon,
Ghana, Guinea, Kenya, Lesotho, Malawi, Mozambique, Namibia, Rwanda,
Senegal, Sudan, South Africa, Zambia, and Zimbabwe.
Objectives

7. Methodology
• Simulation models (Akademiya2063 / ReSAKSS)
 Single-CountryCGE Models
• World Development Indicators database (World Bank)
 Macroeconomic data (2019/2018)
• Statistics on international trade (United Nations)
 Import and export data (2019/2018)
• Primary commodity price database (World Bank)
 Monthly price estimates for 46 primary commodities
 Annual price predictions (Commodity market outlook)
• Koks and Hall (2021)
 Global Economic Impacts of COVID-19 Lockdown Measures Stand Out in High-
Frequency Shipping Data.
Update the
Simulation
Tools
Build the
Scenarios
Simulation
Tools

8.  Changes in the international price of primary commodities (Price Shock)
• Commodities prices estimate for 2019 and 2020 (COVID Scenario)
• Commodity prices outlook for 2020 released in October 2019 (BaU Scenario)
 Disruption of global trade conditions and market access (Volume Shock)
• Sector specific changes in global trade between 2020 and 2019 using high-
frequency shipping data (COVID Scenario)
• Changes in import and export volumes (aggregate) in 2020 from the IMF’s outlook
in October 2019 (BaU Scenario)
Methodology (Cont.)

9. • Several segments of
the food supply chain
captured: production,
processing, trade, and
consumption.
Component Indicator
Agricultural production Production, in constant value
Input cost
Output price
Value added, in constant value
Employment
Food processing Production, in constant value
Input cost
Output price
Value added, in constant value
Employment
Food services Production, in constant value
Input cost
Output price
Value added, in constant value
Employment
Aggregate supply of agricultural Production, in constant value
and food products Input cost
Output price
Value added, in constant value
Employment
Trade Export aggregate, in constant value
Export agriculture, in constant value
Export processed food, in constant value
Export food services, in constant value
Import aggregate, in constant value
Import agriculture, in constant value
Import processed food, in constant value
Import food services, in constant value
Consumption Household consumption, national
Household consumption, rural
Household consumption, urban
Household expenditures, national
Household expenditures, rural
Household expenditures, urban
Consumption price, national
Consumption price, rural
Consumption price, urban
Employment, national
Employment, rural
Employment, urban
Methodology (Cont.)

10. Methodology (Cont.)
A score is computed to appreciate the impact of the COVID-19-related global
trade shock on African food systems.
Score =
Number of indicators adverselyimpacted by the COVID−19 shock
Total number of indicators considered
x 100

11. Moderate impact of the COVID-19-related global trade shock on
the food systems in the selected African countries
Sensitivity of food systems to COVID-19-related global trade shock, score in percentage, computed for selected African countries
80
69 67 66
45 44 43
39 37 35 33 30 30 28 28 28 27 27 25 25 25 23
18
13
KEN
ZMB
DRC
GHA
CMR
ZAF
ETH
CAR
ALL
MOZ
NAM
CGO
EGY
GAB
ZWE
SEN
CHD
MWI
SDN
LSO
CIV
CPV
RWA
GIN
Findings

12. The Group of countries with a diversified export basket are less
adversely impacted by the global trade shock.
40% 38%
29%
37%
Agricultural Exporters Mineral Exporters Other Exporters All Exporters
Impact of COVID-19-related global trade shock on African food systems, average score in percentage, countries grouped by exports
Findings (Cont.)

13. Food processing and food service industries are the most vulnerable
component of the system to the global trade shock caused by the COVID-
19 pandemic
Sensitivity to COVID-19-related global trade shock, average score in percentage, by country groups and along the food system chain
37%
26%
54%
28%
19%
43%
All
Production
Processing
Trade
Consumption
Macro
Findings (Cont.)

14. Conclusion and Key Recommendations
Well-diversified export basket is key to strengthening the
resilience of Africa’s food systems to external shocks.
Embracing digital technologies across the food value
chain to mitigate the adverse impact of external shocks.