This document summarizes the key findings from a diagnostic analysis of Sudan's agrifood system conducted by IFPRI. It finds that: 1) Sudan's agrifood system lacked transformation from 2011-2019, with agricultural GDP share barely changing and off-farm GDP growing modestly. The system remains dominated by primary agriculture. 2) Growth has been driven by less-traded value chains oriented toward the domestic market, like livestock and fruits. Domestic consumption patterns are important drivers of agricultural transformation. 3) Moving forward, jointly promoting value chains like fruits, root crops, rice and wheat could effectively achieve multiple development outcomes like reducing poverty and improving diets.

1. Transformation of Sudan’s Agrifood System
Structure and Drivers
Xinshen Diao, Mia Ellis, Karl Pauw, Mariam Raouf, Khalid Siddig, and James Thurlow
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 Sudan’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 Sudan’s agrifood system growing and transforming?
• Future drivers of inclusive agricultural transformation
Which value chains could be most effective?
2019
2011-2019
2019+

3. Summary
Sudan’s agrifood system (AFS) diagnostic results
Sudan’s AFS lacked transformation during 2011–2019
• Agricultural share of total GDP barely changed over time
• Off-farm AFS GDP grew more rapidly, while its share of total AFS GDP rose only modestly
• AFS continues to be dominated by primary agriculture both in GDP and employment
AFS growth has been driven by value chains oriented toward the domestic market
• Less-traded value chains dominated AFS growth with their large size and above-average growth
• Domestic consumption patterns (and changing diets) are therefore important drivers of agricultural transformation
Although Sudan’s AFS growth and transformation has stalled following the recent military conflict, looking forward,
the structure of AFS growth will be crucial in driving development outcomes…
(e.g., poverty, dietary improvements, employment creation, and growth)
… but no single value chain is the most effective at driving all these development outcomes
• Cereal value chains are most effective at reducing poverty; fruits and vegetables are best for improving diet quality; cotton and
livestock have strong employment effects; and root crops have large growth multiplier effects
Jointly promoting fruits, root crops, rice and wheat would offer an effective way to achieve multiple
development outcomes

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 | Sudan’s Agrifood System Today
GDP and employment in Sudan’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 (CBoS)
• Employment from various sources (i.e., labor force
surveys, ILO, etc.)
• Sudan estimates indicate that
• AFS makes up one-third of GDP
($11.1 billion AgGDP+) …
• … and more than half of total employment
(7.0 million AgEMP+)
• Primary agriculture (A) is large, but off-farm
components (B–E) are also important
(40% of AgGDP+, 15% of AgEMP+)
GDP
($ billions)
Employment
(millions of workers)
Total economy 32.3 100% 12.4 100%
Agri-food system 11.1 34.4% 7.0 56.8%
Primary agric. (A) 6.5 20.2% 6.2 49.9%
Off-farm AFS 4.6 14.2% 1.0 7.9%
Processing (B) 1.4 4.2% 0.2 1.8%
Trade & transport (C) 1.9 5.9% 0.6 5.0%
Food services (D) 1.0 3.2% 0.1 0.9%
Input supply (E) 0.3 0.9% 0.04 0.3%
Rest of the economy 21.2 65.6% 5.4 43.2%

6. Structure2019 | Comparing to Other Countries
• Importance and structure of the AFS varies at different stages of development
Sudan was a lower-middle-income country (LMIC) in most years of 2010s, but its income fell to a low-income country (LIC) level in 2019
• A: Sudan’s AgGDP+ share of total GDP lies between LICs and LMICs averages
• B: Sudan’s primary agriculture component in AFS is similar to the LMIC average
• C: Sudan’s agro-processing is smaller than expected, while food services are larger
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
20.2
8.2
13.4
11.9
10.6
6.6
14.2
All LIC LMIC UMIC HIC Sudan
Primary agriculture Off-farm AFS
34.0
66.2
58.6
40.2
15.6
58.7
66.0
33.8
41.4
59.8
84.4
41.3
All LIC LMIC UMIC HIC Sudan
Primary agriculture Off-farm AFS
33.7 37.8 38.4
46.9
26.1 29.8
31.7
42.8 38.6 21.4
35.9
41.4
23.1
13.7
11.2
18.2 27.8
22.5
11.4 5.8 11.8 13.5 10.3 6.3
All LIC LMIC UMIC HIC Sudan
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 ($0.26 bil.) Imports ($0.94 bil.)
58.7%
12.3%
29.0%
$0.24 bil.
90.4%
$0.03 bil.
9.6%
Primary agriculture
Agrifood processing
$0.79 bil.
84.5%
$0.15 bil.
15.5%
57.1%
27.3%
15.6%
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 (> 1.8%)
• Importable value chains have above-average import-demand
ratios (> 6.3%)
• Less-traded value chains make up the rest
• Domestic market dominates AgGDP+ (78%) – seven less-
traded value chains; relatively smaller off-farm share (72.2%)
and larger on-farm (primary) share (82.2% of total), with fruits
value chain an exception
• Only two exportable value chain groups; relatively small share
of AgGDP+ (8.9%)
• Oilseed value chain also has above-average import-demand
ratio; exports are seeds, while imports are cooking oil
• Three importable value chains account for a disproportionate
share of off-farm AFS (14.2%); these value chains compete
with processed agrifood imports
 Promoting some importable value chains and fruits (less
traded) could be effective in driving agricultural
transformation by boosting value added and employment in
off-farm AFS
Breakdown of Sudan’s agrifood system (2019)
Share of total GDP (%) Exports /
output
(%)
Imports /
demand
(%)
Total
AFS
Primary
agric.
Off-farm
AFS
Total 100 100 100 1.8 6.3
Exportable 8.9 10.2 7.1 13.8 6.8
Oilseeds 8.7 9.9 7.1 12.2 6.8
Cotton 0.2 0.3 0.1 64.3
Importable 10.4 7.7 14.2 1.6 31.3
Other cereals 2.4 0.9 4.5 2.3 21.7
Other crops 5.7 4.4 7.5 42.5
Forestry 2.3 2.3 2.2 3.7 11.3
Less traded 78.0 82.2 72.2 0.5 1.3
Sorghum 13.8 13.7 14.0
Root crops 0.9 1.3
Pulses 4.1 5.4 2.4 1.0 5.7
Vegetables 6.5 9.2 2.6 0.4 0.8
Fruits 7.4 6.5 8.6 0.1 2.4
Livestock 44.1 44.9 42.9 0.7 1.1
Fish 1.3 1.2 1.4 0.5 1.3

9. Growth2011-2019 | Agrifood System Performance
• Sudan’s AFS lacked transformation during 2011–2019
• Agricultural share of total GDP barely changed over time
• Off-farm share of AFS GDP rose modestly
• Share of agricultural employment fell (56% to 50%), indicating a modest improvement in agricultural productivity
Agricultural GDP, agrifood system GDP, and employment shares (2011–2019)
• Part 3 analyzes structural change in the AFS and the contribution of different value chains to AFS growth
19.9
32.4
38.5
56.3
20.2
34.4
41.3
49.9
Agricultural GDP share AgGDP+ share Off-farm share of AgGDP+ Agricultural employment
share
Share
(%)
2011 2019

10. Growth2011-2019 | Value Chain Performance
• Modest AgGDP+ growth (4% p.a.) during
2011–2019
• Less-traded value chains dominated AFS
growth with their large size and above-
average growth (4.2%), contributing 85%
of AFS growth
• Four value chains with above-average
growth (*)
• Cotton – exportable value chain
• Other cereals – importable value chain
• Livestock, fish – less-traded value chains
• Off-farm growth was faster for fast-
growing value chains except for cotton
• Some large less-traded value chains had
stagnant or negative growth (sorghum,
root crops, vegetables, and fruits)
Value chain growth in Sudan (2011-2019)
Average annual GDP growth rate (%)
Total
AFS
Primary
agric.
Off-farm
AFS
Process-
ing
Total AFS 4.0 3.4 4.9 7.9
Exportable 3.1 2.3 4.9 8.4
Oilseeds 3.0 2.2 5.0 8.5
Cotton* 6.8 7.6 2.6 -7.0
Importable 2.0 -1.7 5.8 10.0
Other cereals* 6.7 6.5 6.7 9.2
Other crops 1.0 -4.5 9.2 11.7
Forestry 0.6 3.1 -2.3 9.8
Less traded 4.2 4.1 4.3 7.4
Sorghum 0.6 -2.3 6.2 8.0
Roots -0.8 -0.1 -4.1
Pulses 2.4 3.0 0.6 9.7
Vegetables -0.3 0.4 -3.4 10.1
Fruits 0.6 -2.4 4.9 8.5
Livestock* 7.8 10.6 4.6 6.8
Fish* 6.5 7.4 5.6 8.4

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 outcome)
1.09
1.65
2.10
0.90
0.23
1.27
1.34
1.14
1.03
1.01
-0.02
-0.19
-0.30
0.00
0.40
-0.07
-0.08
-0.06
0.12
0.01
0.04
0.09
0.05
1.32
0.08
0.15
0.19
0.07
0.16
0.08
-1.03
-0.68
-0.03
-0.17
-0.13
-0.12
0.05
-0.01
0.01
0.03
-0.44
-0.36
-0.29
-0.26
-0.15
-0.10
-0.07
-0.07
-0.07
-0.04
Sorghum
Rice & wheat
Root crops
Fruits
Cotton
Oilseeds
Vegetables
Pulses
Livestock
Other crops
0.50
0.41
0.40
0.36
0.33
0.30
0.22
0.20
0.20
0.15
Fruits
Root crops
Rice & wheat
Sorghum
Cotton
Livestock
Other crops
Oilseeds
Vegetables
Pulses
Total
Fruits
Root crops
Rice & wheat
Sorghum
Cotton
Livestock
Other crops
Oilseeds
Vegetables
Pulses
Poverty Growth Jobs Diets

13. Future Drivers2019+ | Key Messages from the Model
AFS growth is pro-poor
• Growth led by all value chains reduces poverty, but two cereal value chains – sorghum and rice & wheat are most effective
AFS growth is effective in improving food security (hunger) and diet quality
• Most value chains reduce hunger; the two cereal value chains are most effective
• Most value chains improve diet quality; fruits value chain is most effective
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
• Cotton is the most effective value chain in creating jobs in the overall economy and within the AFS
Agricultural growth has strong growth multiplier effects that generate income beyond agriculture
• Root crops and rice & wheat have strongest multiplier effects for both AFS income and total GDP growth
In conclusion, promoting multiple value chains can achieve broad-based impact
• No single value chain group is the most effective in achieving all the development outcomes we consider
• Fruits, root crops, and rice & wheat rank highly in the combined outcome scores for poverty, diet, jobs, and growth
• Promoting these value chains would offer an effective way to achieve 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
Sorghum (13.8%) Sorghum 100%
Other cereals (2.7%) Maize 2.4% | Rice 11.9% | Wheat & barley 6.5% | Other cereals 79.2%
Oilseeds (8.7%) Groundnuts 60.6% | Other oilseeds 39.4%
Pulses (4.1%) Pulses 100%
Roots (0.9%) Sweet potatoes 40.1% | Other roots 59.9%
Vegetables (6.5%) Vegetables 100%
Fruits and nuts (7.4%) Nuts 1.8%| Bananas 23.2% | Other fruits 75.0%
Cotton (0.2%) Cotton 100%
Other crops (5.7%) Sugarcane 37.2% | Tea 1.6% | Other crops 61.2%
Livestock (44.1%)
Cattle meat 28.8% | Raw milk 35.2% | Poultry meat 2.5% | Eggs 1.5% | Small ruminants
20.8% | Other livestock 11.2%
Fish (1.3%) Aquaculture 10.7% | Capture fisheries 89.3%
Forestry (2.3%) Forestry 100%