Diao, Xinshen; Ellis, Mia; Pauw, Karl; Pradesha, Angga; Randriamamonjy, Josee; Thurlow, James. 2023

1. Bangladesh’s Agrifood System
Structure and Drivers of Transformation
Xinshen Diao, Paul Dorosh, Mia Ellis, Karl Pauw, Angga Pradesha, and James Thurlow
International Food Policy Research Institute
This diagnostic analysis was conducted by IFPRI with financial support from USAID and funders of the CGIAR Research Initiative on Foresight.
July 2023

2. Four Parts to the Diagnostics
• Current structure
What does Bangladesh’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 Bangladesh’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: Bangladesh’s agrifood system (AFS) diagnostic results
Bangladesh’s AFS has been transforming
• Off-farm AFS GDP particular processing has grown faster than primary agriculture GDP, and the share of off-farm components in
AgGDP+ increased during 2009–2019
• Off-farm components are close to 50% of AgGDP+ with about 20% of AFS employment, indicating average off-farm labor
productivity is higher than average on-farm labor productivity within AFS
AFS growth has been mainly driven by domestic-market-oriented value chains
• Maize, rice, cattle & dairy, and aquaculture, which are either importable or less traded value chains, have grown rapidly in the
past 10 years
• Dietary change led by urbanization and foods with higher income elasticities such as aquaculture and livestock products are
expected to play increasing roles in AFS transformation
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
• Maize and root crops are most effective at reducing poverty; cattle & dairy and horticulture are best for improving diet quality;
maize and jute have strong employment effects and large growth multipliers
Jointly promoting multiple value chains that have expanding market opportunities 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
agri-food 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 | Bangladesh’s Agrifood System Today
GDP
($ billions)
Employment
(millions of workers)
Total economy 348.0 100% 66.9 100%
Agrifood system 82.9 23.8 33.1 49.5
Primary agric. (A) 43.5 12.5 25.8 38.6
Off-farm AFS 39.5 11.3 7.3 10.9
Processing (B) 12.2 3.5 2.0 3.1
Trade & transport (C) 18.6 5.3 3.6 5.4
Food services (D) 3.7 1.1 1.1 1.7
Input supply (E) 4.9 1.4 0.5 0.7
Rest of economy 265.1 76.2 33.8 50.5
GDP and employment in Bangladesh’s agrifood system (2019)
Part 1 focuses on the current size and structure
of the national AFS
• Latest AgGDP+ and AgEMP+ estimates
• Decomposed into five AFS components
• Situates AFS within the broader economy
• Analysis uses official data sources
• GDP from national accounts
• Employment from various sources (i.e., population
census, labor force surveys, ILO, etc.)
• Bangladesh AFS estimates indicate that
• AFS makes up a quarter of GDP
($83 billion AgGDP+)…
• … and half of total employment
(33 million AgEMP+)
• Primary agriculture (A) is large, but off-farm
components (B–E) have been catching up
(almost half of AgGDP+, 20% of AgEMP+)

6. Structure2019 | Comparisons with Other Countries
• Importance and structure of the AFS varies at different stages of development
Bangladesh is a lower-middle-income country (LMIC)
• A: Bangladesh’s AgGDP+ share of total GDP is lower than most LMICs
• B: Bangladesh’s primary agriculture component of AFS lies between LMICs and upper-middle-income countries (UMICs)
• C: Bangladesh’s off-farm structure of AFS differs from the LMIC average with a large trade & transport component
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
12.5
8.2
13.4
11.9
10.6
6.6
11.3
All LIC LMIC UMIC HIC Bangladesh
Primary agriculture Off-farm AFS
33.7 37.8 38.4
46.9
26.1 31.0
31.7
42.8 38.6 21.4
35.9
47.1
23.1
13.7
11.2
18.2 27.8
9.4
11.4 5.8 11.8 13.5 10.3 12.5
All LIC LMIC UMIC HIC Bangladesh
Processing Trade and transport
Food services Input supply
34.0
66.2
58.6
40.2
15.6
52.4
66.0
33.8
41.4
59.8
84.4
47.6
All LIC LMIC UMIC HIC Bangladesh
Primary agriculture Off-farm AFS

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 the 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 ($1.45 bil.) Imports ($18.06 bil.)
52.4%
14.7%
32.8%
$1.12 bil.
77.4%
$0.33 bil.
22.6%
Primary agriculture
Agrifood processing
$8.71 bil.
48.2% $9.36 bil.
51.8%
40.0%
47.2%
12.8%
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 ( > 0.8%)
• Importable value chains have above-average import-demand
ratios (> 10.0%)
• Less-traded value chains make up the rest
• Domestic market dominates AgGDP+ (63.6%) – six less-traded
value chains, and rice is the country’s largest value chain;
relatively smaller off-farm share (56.8%) and larger on-farm
(primary) share (69.8% of total), with cattle & dairy a
significant exception
• Only two export-oriented value chain groups (jute and capture
fish); relatively small share of AgGDP+ (9.9%)
• Four import-substitutable value chains account for a
disproportionate share of off-farm AFS (31.3%); these value
chains compete with processed agrifood imports
 Promoting some importable value chains and cattle & dairy
(less traded) could be effective at driving agricultural
transformation by boosting value added & employment in off-
farm AFS
Share of total GDP (%) Exports /
output
(%)
Imports /
demand
(%)
Total
AFS
Primary
agric.
Off-farm
AFS
Total 100 100 100 0.8 10.0
Exportable 9.9 11.4 8.3 10.6 0.4
Jute 1.8 2.2 1.5 33.2 0.0
Capture fish 8.1 9.2 6.8 3.9 0.5
Importable 24.8 18.8 31.3 0.2 29.0
Maize & wheat 3.2 1.7 4.9 0.2 27.7
Pulses & oilseeds 3.8 3.1 4.6 0.1 37.1
Horticulture 5.8 6.5 4.9 0.0 26.4
Other crops 12.0 7.5 17.0 0.3 26.3
Less traded 63.6 69.8 56.8 0.0 1.2
Rice 21.0 26.3 15.1 0.0 0.5
Roots 2.4 3.0 1.8 0.0 0.0
Cattle & dairy 11.1 6.5 16.3 0.0 3.4
Other livestock 6.2 9.3 2.8 0.0 2.3
Aquaculture 8.4 13.0 3.3
Forestry 14.4 11.6 17.5 0.0 0.0
Breakdown of Bangladesh’s agrifood system (2019)

9. Growth2009-2019 | Agrifood System Performance
• Bangladesh’s AFS has been transforming over time
• Both AgGDP+ and agricultural shares of total GDP fell during 2009-2019
• Share of off-farm components in total AgGDP+ rose (43.8% to 47.6%)
• Agricultural employment fell significantly (47.6% to 38.6%)
• An indication of economic structural change and rising average 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
16.9
30.0
43.8
47.6
12.5
23.8
47.6
38.6
Agricultural GDP share AgGDP+ share Off-farm share of
AgGDP+
Agricultural employment
share
Share
(%)
2009 2019

10. Growth2009-2019 | Value Chain Performance
• Modest AgGDP+ and primary agriculture
growth (4.2% and 3.5% p.a., respectively)
during 2009–2019, compared with national
GDP growth of 6.6%
• Value chains with above-average AgGDP+
growth rates (*) (> 4.2%) are in importable
and less-traded groups
• Less-traded value chains account for three-
quarters of total AFS growth with their large
size and above-average growth
• AgGDP+ growth driven by strong growth in
off-farm AFS (5.1%), including processing
(7.8%)
• Fast-growing value chains experienced faster
off-farm growth
Indicative of increased market orientation of
the AFS; associated with increased demand
for trade, transport, and processing
Value chain growth in Bangladesh (2009-2019)
Average annual GDP growth rate (%)
Total
AFS
Primary
agric.
Off-farm
AFS
Process-
ing
Total AFS 4.2 3.5 5.1 7.8
Exportable 3.3 3.5 3.1 4.6
Jute 2.3 2.8 1.4 2.2
Capture fish 3.6 3.6 3.5 7.0
Importable 2.9 1.3 4.1 7.7
Maize & wheat* 4.8 3.0 5.6 10.7
Pulses & oilseeds 3.7 2.3 5.0 7.9
Horticulture 0.4 -0.5 1.8 9.1
Other crops 3.6 2.4 4.6 6.5
Less traded 4.7 4.2 5.5 7.8
Rice* 4.3 4.0 4.8 6.8
Roots 2.4 3.0 1.5 22.3
Cattle & dairy* 4.9 3.5 5.4 8.7
Other livestock 2.2 1.9 3.4 22.0
Aquaculture* 6.6 6.9 5.4
Forestry* 5.9 4.4 7.2 6.7

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 effects within value chains 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
Average across outcomes
(averaged normalized scores, reordered)
4.33
3.31
4.91
0.86
1.09
1.68
1.76
1.15
3.06
0.19
-0.20
3.22
0.05
0.03
-0.04
-0.02
-0.01
-0.15
Maize
Root crops
Jute
Pulses & oilseeds
Horticulture
Rice
Aquaculture
Other livestock
Cattle and milk
0.47
0.09
0.16
0.25
0.60
0.03
0.15
0.10
0.74
Maize
Root crops
Jute
Pulses & oilseeds
Horticulture
Rice
Aquaculture
Other livestock
Cattle and milk
-1.21
-0.38
-0.23
-0.25
-0.06
-0.59
-0.06
0.05
0.18
0.65
0.65
0.39
0.32
0.31
0.19
0.16
0.12
0.05
Maize
Jute
Cattle and milk
Root crops
Horticulture
Pulses & oilseeds
Aquaculture
Rice
Other livestock
Total
-1.04
-0.60
-0.43
-0.41
-0.34
-0.30
-0.26
-0.05
-0.02
Maize
Root crops
Jute
Pulses & oilseeds
Horticulture
Rice
Aquaculture
Other livestock
Cattle & dairy
Maize
Jute
Cattle & dairy
Root crops
Horticulture
Pulses &
oilseeds
Aquaculture
Rice
Other livestock
Poverty Growth Jobs Diets
Individual outcomes
(per unit change in agriculture GDP, ordered by poverty outcome)
Poverty
(change in %-point)
Hunger
(change in %-point)
Diet quality
(change in %)
Jobs
(change in 1,000)
GDP
(change in mil. $)

13. Future Drivers2019+ | Key Messages
AFS growth is pro-poor
• Growth led by most AFS value chains reduces poverty, but maize and root crops are most effective
AFS growth is effective in improving food security (hunger) and diet quality
• Most value chains reduce hunger; maize and rice are most effective
• Most value chains improve diet quality; cattle & dairy and horticulture are most effective
Agricultural growth creates jobs but not necessarily on-farm
• All value chains are associated with an increase in total employment, but most AFS jobs are created off-farm
• Jute is a most effective value chain in creating jobs in the overall economy and within the AFS
Agricultural growth has a strong growth multiplier effect, generating income beyond agriculture
• Maize and jute have the strongest growth multiplier effects both for AFS income and total GDP growth
In conclusion, promoting multiple value chains can achieve broad impacts
• No single value chain group is the most effective in achieving all the outcomes we consider
• Maize, jute, and cattle & dairy rank highly in the combined outcome scores for poverty, diet, jobs, and growth
• Maize, aquaculture, and livestock grew rapidly in recent years; promoting these value chains that have expanding market
opportunities is also important

14. Note: Value Chain Groups and Agricultural Sectors in Individual VC Groups
Value chain group
and share of AFS GDP
Individual products and their share of group’s agriculture GDP
Rice (21.0%) Rice 100%
Maize & wheat (3.2%) Maize 75.3% | Wheat 24.7%
Pulses & oilseeds (3.8%) Pulses 36.1% | Oilseeds 63.9%
Roots (2.4%) Irish potatoes 100%
Horticulture (5.4%)
Leafy green vegetables 12.3% | Other vegetables 38.3% | Nuts 5.6%| Bananas 12.5% |
Other fruits 31.3%
Jute (1.8%) Jute 100%
Other crops (12.0%) Sugarcane 4.9% | Cotton 0.2% | Tobacco 24.0%| Tea 6.5% | Other crops 64.5%
Cattle & milk (11.1%) Cattle meat 63% | Raw milk 37%
Other livestock (6.2%) Poultry meat 22.0% | Eggs 17.3% | Small ruminants 50.4% | Other livestock 10.4%
Aquaculture (8.4%) Aquaculture 100%
Capture fish (8.1%) Capture fisheries 100%
Forestry (14.4%) Forestry 100%