Diao, Xinshen; Randriamamonjy, Josee; Thurlow, James; Ellis, Mia; and Ulimwengu, John M. 2023.

1. Democratic Republic of Congo’s Agrifood System
Structure and Drivers of Transformation
Xinshen Diao, Mia Ellis, Karl Pauw, Josee Randriamamonjy, James Thurlow, and John Ulimwengu
International Food Policy Research Institute
This diagnostic analysis was conducted by IFPRI with financial support from USAID.
July 2023

2. Four Parts to the Diagnostics
• Current structure
What does DRC’s food system look like today?
• Decomposing value chains
How are different products contributing to the broader agrifood system?
• Growth and market structure
How is DRC’s agrifood system growing and transforming?
• Future drivers of inclusive agricultural transformation
Which value chains could be most effective?
2019
2009-2019
2019+

3. Summary
DRC’s agrifood system (AFS) diagnostic results
DRC’s AFS lacked transformation during 2009–2019
• Share of off-farm components in AFS GDP did not change over time
AFS growth has been mainly driven by importable value chains for meeting domestic demand
• Domestic consumption patterns (and changing diets) are therefore important drivers of agricultural transformation
The country will continue to face food security challenges
• Total AFS and primary agriculture have grown slowly; their growth rates were just slightly higher than population growth
• Many food crops had growth rates below population growth, e.g., maize and cassava
Looking forward, the structure of AFS growth will be crucial in driving development outcomes…
… but no single value chain is the most effective at driving all these development outcomes
• Livestock and horticulture are most effective at reducing poverty and improving diet quality; cassava and maize have strong
employment effects; and rice has large growth multiplier effects
• Rising wheat prices in the world market caused by the recent Russia-Ukraine war has led the country to explore possibly
substituting cassava flour for making bread. If successful, this will boost the demand for cassava and create more non-farm value
addition and jobs along the cassava value chain, which can also save foreign exchange reserves
Promoting these value chains would offer an effective way to achieve broad-based outcomes
Note: See a new initiative for cassava: https://www.iita.org/news-item/ata-drc-commences-with-huge-anticipation/

4. Framework | Agrifood Systems (AFS)
Primary agriculture
Agroprocessing
Trade and transport
Food services
Trade and transport
Input supply Demand
Consumption of own-
produced goods
Purchase of primary
agricultural goods
Purchase of processed
agrifood goods
Purchase of ready-made
foods outside of home
Imports
A
C
B
D
E
Includes agriculture, plus all upstream/downstream sectors
• Five major components (A to E)
• Same format as standard economywide datasets (e.g., national accounts)
• Allows us to measure AFS structure and performance using actual data
Agrifood System GDP (AgGDP+)
Total value added generated by all agricultural
value chains (in constant dollars)
Agrifood System Employment (AgEMP+)
Total number of workers who are primarily
employed in an agricultural value chain

5. Structure2019 | DRC’s Agrifood System Today
GDP
($ billions)
Employment
(millions of workers)
Total economy 49.3 100% 28.6 100%
Agrifood system 17.1 34.6% 21.3 74.7%
Primary agric. (A) 6.1 12.3% 18.4 63.4%
Off-farm AFS 11.0 22.3% 3.0 10.3%
Processing (B) 4.7 9.5% 0.8 2.8%
Trade & transport (C) 3.7 7.5% 1.9 6.6%
Food services (D) 2.2 4.5% 0.2 0.8%
Input supply (E) 0.4 0.9% 0.0 0.1%
Rest of economy 32.2 65.4% 7.2 25.3%
GDP and employment in DRC’s agrifood system (2019)
• Part 1 focuses on the current size and
structure of the national agrifood system
• Latest AgGDP+ and AgEMP+ estimates
• Decomposed into five AFS components
• Situates AFS within the broader economy
• Uses official data sources
• GDP from national accounts
• Employment from various sources (i.e., population
census, labor force surveys, ILO, etc.)
• DRC estimates indicate that
• AFS makes up one-third of GDP
($17.1 billion AgGDP+) …
• … and three-quarters of total employment
(21.3 million AgEMP+)
• Primary agriculture (A) is still large, while off-farm
components (B–E) are more important in AgGDP+
(60% of AgGDP+, 14% of AgEMP+)

6. Structure2019 | Comparing to Other Countries
• Importance and structure of the AFS varies at different stages of development
DRC is a low-income country (LIC)
• A: DRC’s AgGDP+ share of total GDP lies between LICs and lower-middle-income countries (LMICs)
• B: DRC’s primary agriculture component in AFS is even lower than the upper-middle-income country (UMIC) average (possibly due to
extremely low labor productivity in agriculture)
• C: DRC’s off-farm structure of AFS is close to the LIC average
Share of total GDP (%) Share of AFS GDP (%) Share of off-farm AFS GDP (%)
LIC = low-income countries | LMIC = lower-middle income | UMIC = upper-middle-income | HIC = high-income Source: IFPRI Agri-Food System Database
A B C
4.2
26.4
16.9
7.1
1.2
12.3
8.2
13.4
11.9
10.6
6.6
22.3
All LIC LMIC UMIC HIC DRC
Primary agriculture Off-farm AFS
34.0
66.2
58.6
40.2
15.6
35.6
66.0
33.8
41.4
59.8
84.4
64.4
All LIC LMIC UMIC HIC DRC
Primary agriculture Off-farm AFS
33.7 37.8 38.4
46.9
26.1
42.4
31.7
42.8 38.6 21.4
35.9
33.6
23.1
13.7
11.2
18.2 27.8
20.0
11.4 5.8 11.8 13.5 10.3
3.9
All LIC LMIC UMIC HIC DRC
Processing Trade and transport
Food services Input supply

7. Structure2019 | Supply vs. Demand Sides of the Agrifood System
Agrifood GDP vs. consumption
Primary, processed, and other product shares (%)
• AgGDP+ defines the AFS on the supply side
• Household demand and trade (imports) capture AFS structure on the demand side
• Agrifood processing is more important on the demand side than the supply side in the AFS
AgGDP+ Household demand
Agrifood exports vs. imports
Primary and processed product shares (%)
Exports ($0.11 bil.) Imports ($2.37 bil.)
35.6%
27.3%
37.1%
$0.09 bil.
77.6%
$0.02 bil.
22.4%
Primary agriculture
Agrifood processing
$1.44 bil.
60.8%
$0.93 bil.
39.2%
27.3%
62.8%
9.9%
Primary agriculture
Agroprocessing
Other off-farm

8. Value Chains2019 | Contributions & Trade Orientation
• Part 2 decomposes the AFS across broad value
chain groupings
• Classify value chains based on trade orientation
• Exportable value chains have above-average export-
output ratios (> 0.4%)
• Importable value chains have above-average import-
demand ratios (> 8.8%)
• Less traded value chains make up the rest
• Exportable is small and cocoa & coffee account for less
than 1% of AFS GDP
• Importable dominates AgGDP+ (60.7%) – six value chain
groups account for a disproportionally large share of off-
farm GDP (77%) but a much small share of primary
agriculture (27%) – importable value chains compete with
imports of processed products
• Less-traded value chains dominate primary agriculture
(64% of total) and have very small off-farm components
(15% in total)
Promoting importable value chain could be effective in
driving agricultural transformation by boosting value
added and employment in off-farm AFS
Share of GDP (%) Exports /
output
(%)
Imports /
demand
(%)
Total
AFS
Primary
agric.
Off-farm
AFS
Total 100 100 100 0.4 8.8
Exportable 5.3 9.6 3.0 8.5 3.5
Cocoa and coffee 0.3 0.5 0.1 100.0
Forestry 5.1 9.0 2.9 4.5 3.6
Importable 60.7 26.7 76.9 11.5
Maize 15.7 10.7 18.5 13.0
Rice 7.1 8.7 6.2 10.0
Other crops 7.5 0.5 11.3 12.0
Livestock 25.8 3.0 38.3 8.2
Fish 4.7 3.8 5.2 18.0
Less traded 32.2 63.8 14.8 0.1 2.1
Oilseeds 8.0 6.2 9.0 0.2 5.2
Pulses 1.5 3.8 0.3 2.2
Cassava 9.4 23.1 2.0 0.1
Other roots 9.9 45.9 2.7 0.0
Horticulture 3.4 7.9 1.0 3.1
Breakdown of DRC’s agrifood system (2019)

9. Growth2009-2019 | Agrifood System Performance
DRC’s AFS lacked transformation during 2009–2019
• Agricultural share of total GDP fell modestly
• Share of off-farm components in AFS GDP did not change
Share of agricultural employment fell modestly
• An indication of lack of structural change in the economy with a less improved labor productivity in agriculture
Agricultural GDP, Agrifood system GDP, and employment shares (2009–2019)
• Part 3 analyzes structural change in the AFS and the contribution of different value chains to AFS growth
46.0
16.2
64.6
68.0
34.6
12.3
64.4
56.3
Agricultural GDP share AgGDP+ share Off-farm share of AgGDP+ Agricultural employment share
Share
(%)
2009 2019

10. Growth2009-2019 | Value Chain Performance
• AgGDP+ grew slowly during 2009–2019
(3.2% p.a.)
• Importable value chains dominate AFS growth
with their large size and above average growth
(3.4%), contributing two-thirds of AFS growth in
2009–2019
• Exportable value chains had worst performance
and value added of cocoa & coffee fell
• Only two value chains have above-average
growth (*)
• Livestock – an importable value chain, its rapid
growth is driven by its off-farm components
• Other root crops – a less-traded value chain
with growth rate three times the AFS average
Value chain growth in DRC (2009-2019)
Average annual GDP growth rate (%)
Total
AFS
Primary
agric.
Off-farm
AFS
Process-
ing
Total AFS 3.2 3.2 3.1 3.2
Exportable 1.1 3.3 -1.9 5.0
Cocoa and coffee -7.6 -3.7 -13.7
Forestry 1.9 3.9 -0.8 5.0
Importable 3.4 2.8 3.5 3.0
Maize 2.0 2.2 1.9 2.5
Rice 2.6 6.0 0.6 0.3
Other crops 0.4 2.3 0.4 1.5
Livestock* 5.7 2.0 5.9 3.5
Fish 0.5 0.0 0.7 6.8
Less traded 2.9 3.4 1.8 4.1
Pulses 0.3 1.3 -4.8
Oilseeds 2.2 0.8 2.8 4.1
Cassava 0.9 2.0 -3.9
Other roots* 10.5 10.9 9.1
Horticulture -1.7 -1.8 -1.6

11. Future Drivers2019+ | Modeling Faster Growth
• IFPRI’s RIAPA model is used to analyze different sources of agricultural growth
• Expand production in different value chains
• Increase on-farm productivity growth rates in targeted value chains
• Achieve same overall growth in agriculture GDP (e.g., 1.0%)
• Track linkage effect within value chain and spillover effects to other value chains
• Assess outcomes
• Poverty – Poverty-growth elasticity in percentage points based on $2.15-a-day
• Hunger – Hunger-growth elasticity in percentage points based on prevalence of undernourishment
• Diet – Diet quality to growth elasticity in % derived from Reference Diet Deprivation index (REDD)
• Jobs – Employment multiplier in thousand employed persons associated with US$1 million growth in targeted value chain
• GDP – GDP growth multiplier in US$ millions associated with US$1 million growth in targeted value chain
• Average across outcomes
• The value of outcome indicators (elasticity or multiplier) is expected to differ across value chain growth; not all value chains are
equally effective at achieving all outcomes
• Normalizing the individual outcome scores
• The values of each outcome indicator are scaled so that the most effective value chain is given a score of one and the leasteffective is given a
score of zero. A value chain with adverse impact is also given a score of zero.
• An average score with equal weights is used to measure the total impacts across all value chains

12. Future Drivers2019+ | Prioritizing Agricultural Growth
Poverty
(change in %-point)
Hunger
(change in %-point)
Jobs
(change in 1,000)
Diet quality
(change in %)
Average across outcomes
(averaged normalized scores, reordered)
GDP
(change in bil. $)
Individual outcomes
(per unit change in agricultural GDP, ordered by poverty)
0.63
2.27
2.46
1.79
3.76
1.21
1.53
1.22
0.63
Horticulture
Livestock
Pulses
Oilseeds
Rice
Fish
Maize
Cassava
Other roots
0.13
-0.34
0.04
0.16
-0.08
-0.12
0.31
0.72
0.15
3.34
0.62
0.55
0.60
0.14
0.14
0.12
-0.03
-0.04
Horticulture
Livestock
Pulses
Oilseeds
Rice
Fish
Maize
Cassava
Other roots
-0.19
0.07
-0.73
-0.82
-0.50
-0.01
-0.39
-0.23
-0.14
-0.65
-0.55
-0.50
-0.44
-0.36
-0.21
-0.14
-0.07
-0.06
Horticulture
Livestock
Pulses
Oilseeds
Rice
Fish
Maize
Cassava
Other roots
0.61
0.47
0.42
0.39
0.39
0.30
0.27
0.12
0.12
Horticulture
Pulses
Oilseeds
Rice
Livestock
Cassava
Maize
Fish
Other roots
Total
Horticulture
Pulses
Oilseeds
Rice
Livestock
Cassava
Maize
Fish
Other roots
Poverty Growth Jobs Diets

13. Future Drivers2019+ | Key Messages
AFS growth is pro-poor
• Growth led by all value chains reduces poverty, but horticulture and livestock are most effective
AFS growth is effective in improving food security (hunger) and diet quality
• Most value chains reduce hunger; oilseeds are most effective
• Most value chains improve diet quality; horticulture is most effective
• Improvement in diet quality is measured by narrowing the gaps between actual consumption across six food groups and their recommended
healthy consumption levels
• At least 50% of DRC population is currently deficient in vitamin B12 and other micronutrients, and there is no a single food item that can translate
into significant change in diet quality
Agricultural growth creates jobs but not necessarily on-farm
• Most value chains are associated with an increase in total employment, but AFS jobs are mainly created off-farm
• Cassava and maize value chains are more effective in creating jobs in the overall economy
Agricultural growth has strong growth multiplier effects that generate income beyond agriculture
• Rice has the strongest growth multiplier effect for both AFS income and total GDP growth
In conclusion, promoting multiple value chains can achieve broad impact
• No single value chain group is the most effective in achieving all the outcomes we consider
• Horticulture, pulses & oilseeds rank highly in the combined outcome scores for poverty, diet, jobs, and growth
• Rising wheat prices in the world market caused by recent Russia-Ukraine war has led the country to explore possibly substituting cassava flour
for making bread. If successful, this will boost the demand for cassava and create more non-farm value-addition and jobs along cassava value
chain, which can also save foreign exchange reserves
• Together with horticulture, pulse, and oilseeds, promoting these value chains would offer an effective way at achieving broad-based
outcomes

14. Note: Value Chain Groups and Agricultural Sectors in Individual
VC Groups
Value chain group and their
share of AgGDP+
Individual products and their share of group’s agriculture GDP
Maize (15.7%) Maize 100%
Rice (7.1%) Rice 100%
Oilseeds (8.0%) Groundnuts 42.6% | Other oilseeds 57.6%
Pulses (1.5%) Pulses 100%
Cassava (9.4%) Cassava 100%
Other roots (9.9%) Sweet potatoes 11.0% | Irish potatoes 10.7% | Other roots 5.4% | Plantains 72.8%
Horticulture (3.4%) Vegetables 22.3% | Fruit bananas 30.1% | Other fruits 47.6%
Cocoa and coffee (0.3%) Cocoa 66.0% | Coffee 34.0%
Other crops (7.5%) Sorghum & millet 59.1% | Sugarcane 40.9%
Livestock (25.8%) Cattle & milk 33.1% | Poultry & eggs 16.0% | Small ruminants 15.5% | Other livestock 35.5%
Fish (4.7%) Capture fisheries 100%
Forestry (5.1%) Forestry 100%