Xinshen Diao, Mia Ellis, Ian Masias, Karl Pauw, James Thurlow, and Duncan Boughton International Food Policy Research Institute

1. Myanmar’s Agrifood System
Structure and Drivers of Transformation
Xinshen Diao, Mia Ellis, Ian Masias, Karl Pauw, James Thurlow, and Duncan Boughton
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 did Myanmar’s food system look like in the economic transformation before the military coup?
• Decomposing value chains
How did different products contribute to the broader agrifood system?
• Growth and market structure
How was Myanmar’s agrifood system growing and transforming until 2019?
• Future drivers of inclusive agricultural transformation
Which value chains could be most effective?
2019
2011-2019
Future

3. Summary
Myanmar’s agrifood system (AFS) diagnostic results
Myanmar’s AFS had been transforming before the military coup
• Off-farm AFS GDP grew faster than primary agriculture
• Primary agriculture had a low and disappointing growth rate
AFS growth has been driven by value chains oriented both toward the domestic market and for export
• Exportable value chains made an important contribution to AFS growth due to their large size, but their growth was
disappointing
• Less-traded value chains’ important contribution to AFS growth came from their rapid growth
Cereals and livestock could drive more inclusive transformation
• Cereals and livestock had above-average growth in 2011–2019
• They have greater potential for hunger reduction and for improving dietary quality
Although Myanmar’s AFS transformation stalled following the military coup, looking forward, the structure of AFS
growth will be crucial for recovery
…but no single value chain is the most effective at driving all development outcomes
Jointly promoting livestock and horticulture 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 | Myanmar’s Agrifood System
GDP and employment in Myanmar’s agrifood system in 2019
• Part 1 focuses on the 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.)
• Myanmar estimates indicate that
• AFS makes up close to half of GDP
($32.3 billion AgGDP+) …
• … and two-thirds of total employment
(14.9 million AgEMP+)
• Primary agriculture (A) is still large, but off-farm
components (B–E) have been catching up
(more than half of AgGDP+, one-fifth of AgEMP+)
GDP
($ billions)
Employment
(millions of workers)
Total economy 69.4 100% 23.3 100%
Agrifood system 32.2 46.3% 14.9 64.0%
Primary agric. (A) 15.2 22.0% 11.5 49.2%
Off-farm AFS 16.9 24.4% 3.4 14.8%
Processing (B) 5.7 8.2% 0.6 2.5%
Trade & transport (C) 7.8 11.2% 2.0 8.7%
Food services (D) 2.3 3.3% 0.7 2.9%
Input supply (E) 1.2 1.7% 0.2 0.7%
Rest of economy 37.3 53.7% 8.4 36.0%

6. Structure2019 | Comparing to Other Countries
• Importance and structure of the AFS varies at different stages of development
Myanmar is a lower-middle-income country (LMIC)
• A: Myanmar’s AgGDP+ share of total GDP is higher than most LMICs and close to the low-income country (LIC) average
• B: Myanmar’s primary agriculture component is smaller than the LMIC average (i.e., more off-farm value added in AgGDP+)
• C: Myanmar’s agro-processing is smaller than expected, and trade & transport is 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
22.0
8.2
13.4
11.9
10.6
6.6
24.4
All LIC LMIC UMIC HIC Myanmar
Primary agriculture Off-farm AFS
34.0
66.2
58.6
40.2
15.6
47.4
66.0
33.8
41.4
59.8
84.4
52.6
All LIC LMIC UMIC HIC Myanmar
Primary agriculture Off-farm AFS
33.7 37.8 38.4
46.9
26.1
33.6
31.7
42.8 38.6 21.4
35.9
45.8
23.1
13.7
11.2
18.2 27.8
13.5
11.4 5.8 11.8 13.5 10.3 7.1
All LIC LMIC UMIC HIC Myanmar
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
• Processing agriculture 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 ($5.44 bil.) Imports ($2.35 bil.)
47.4%
17.7%
35.0%
$3.13 bil.
57.5%
$2.31 bil.
42.5%
Primary agriculture
Processing agriculture
$1.70 bil.
72.5%
$0.65 bil.
27.5%
26.8%
65.9%
7.3%
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 (> 9.7%)
• Importable value chains have above-average import-
demand ratios (> 4.4%)
• Less-traded value chains make up the rest
• Strong comparative advantage in exports – seven
exportable value chains dominate AgGDP+ (58%);
relatively smaller off-farm share (51.3%) and larger on-
farm (primary) share (65.7% of total)
• Importable covers two value chains and less traded
covers four value chains. Many of these value chains
have larger on-farm share than off-farm share
Share of total GDP (%) Exports /
output
(%)
Imports /
demand
(%)
Total
AFS
Primary
agric.
Off-farm
AFS
Total 100 100 100 9.7 4.4
Exportable 58.1 65.7 51.3 16.8 1.1
Maize 1.7 2.2 1.3 35.1 3.9
Rice 27.2 22.0 32.0 10.6 0.3
Pulses 3.7 6.8 0.9 45.4
Horticulture 12.5 16.3 9.0 10.4 1.7
Other export crops 1.0 1.8 0.3 37.5 0.1
Fish 9.6 14.7 5.1 27.1 1.2
Forestry 2.4 2.0 2.8 33.7 11.2
Importable 8.7 9.3 8.1 1.6 19.4
Other cereals 2.9 1.4 4.2 0.1 23.4
Oilseeds 5.8 7.9 3.9 2.6 16.6
Less traded 25.2 25.0 25.4 1.1 4.2
Roots 2.6 3.9 1.4
Other crops 9.7 4.5 14.3 2.6 2.0
Cattle & dairy 9.1 9.8 8.6 0.1 8.3
Other livestock 3.8 6.8 1.1 0.4 0.4
Breakdown of Myanmar’s agrifood system (2019)

9. Growth2011-2019 | Agrifood System Performance
Myanmar’s AFS had been transforming before the military coup
• Agricultural share of total GDP fell significantly during 2011–2019 (30% to 22%)
• Off-farm share of AgGDP+ rose
• Share of agricultural employment also fell (55% to 49%), an indication of improved agricultural productivity
and structural change in the entire economy
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
29.8
50.9
41.4
54.8
22.0
46.3
52.6
49.2
Agricultural GDP share AgGDP+ share Off-farm share of AgGDP+ Agricultural employment
share
Share
(%)
2011 2019

10. Growth2011-2019 | Value Chain Performance
• AgGDP+ grew at 4.3% p.a. during 2011–2019
• AgGDP+ growth was driven by rapid off-farm
growth (7.5%), while primary agriculture had
disappointed growth (1.6%)
• Exportable and less-traded value chains
dominate AFS growth, either with their large
size (i.e., exportable) or above-average growth
(i.e., less traded), contributing, respectively, 55%
and 37% of AFS growth in 2011–2019
• Value chains with above-average growth (*)
• The exportable value chain – rice – has a growth
rate of more than 6%
• The importable value chain – other cereals – has
a growth rate of 10%
• Two less-traded livestock value chains – cattle &
dairy and other livestock – have above 6%
growth rate
Value chain growth in Myanmar (2011-2019)
Average annual GDP growth rate (%)
Total
AFS
Primary
agric.
Off-farm
AFS
Process-
ing
Total AFS 4.3 1.6 7.5 10.0
Exportable 3.3 0.9 6.8 8.6
Maize 2.1 3.1 0.8 8.5
Rice* 6.6 3.5 9.1 10.3
Pulses -4.7 -4.5 -5.8
Horticulture 1.6 -1.1 8.1 14.2
Other export crops 1.9 1.7 2.7 10.4
Fish* 4.3 3.6 6.6 17.5
Forestry -2.4 -1.7 -2.8 -5.9
Importable 3.2 -0.2 8.2 6.9
Other cereals* 10.1 -3.1 21.0 22.3
Oilseeds 0.9 0.4 1.8 3.3
Less traded 5.7 4.4 7.0 11.1
Roots -3.1 -3.5 -2.0
Other crops* 5.9 2.4 7.0 10.3
Cattle & dairy* 9.7 10.3 9.1 11.8
Other livestock* 6.2 5.7 9.2 14.1

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 millions 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. Individual outcomes
(per unit change in agriculture GDP, ordered by poverty outcome)
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 mil. $)
1.64
2.74
3.36
1.09
1.13
0.85
1.47
0.79
0.58
1.83
2.24
0.13
1.81
0.06
0.06
0.15
0.18
-0.03
0.11
0.22
0.24
0.41
0.26
0.80
0.97
0.19
0.38
0.10
0.04
0.08
0.07
0.16
0.09
-0.03
-0.05
-0.04
0.00
-0.10
-0.02
-0.05
-0.02
-0.02
-0.14
-0.01
-0.47
-0.46
-0.28
-0.21
-0.17
-0.15
-0.15
-0.14
-0.12
-0.11
-0.06
Livestock
Horticulture
Cattle & milk
Fish
Oilseeds
Pulses
Root crops
Other export crops
Maize
Rice
Other crops
0.89
0.65
0.43
0.24
0.22
0.22
0.19
0.13
0.10
0.08
0.08
Horticulture
Cattle & milk
Livestock
Oilseeds
Other crops
Rice
Fish
Root crops
Pulses
Other export crops
Maize
Total
Horticulture
Cattle & milk
Livestock
Oilseeds
Other crops
Rice
Fish
Root crops
Pulses
Other export
crops
Maize
Poverty Growth Jobs Diets

13. Future Drivers | Key Messages
AFS growth is pro-poor
• Growth led by all value chains reduces poverty, but horticulture and the two livestock value chains are most effective
AFS growth is effective in improving food security (hunger) and diet quality
• Most value chains reduce hunger; rice, other cereals, and oilseeds are most effective
• Most value chains improve diet quality; horticulture and cattle & dairy are 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
• Horticulture is the most effective value chain in creating jobs in the overall economy and within the AFS
Agricultural growth has strong growth multiplier effect generating income beyond agriculture
• Cattle & dairy and horticulture have strongest growth 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 outcomes we consider
• Horticulture and cattle & dairy value chains rank highly in the combined outcome scores for poverty, diet, jobs, and growth
• Promoting horticulture and livestock together 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 AFS GDP
Individual product’s share of group's Agriculture GDP
Maize (3.1%) Maize 100%
Rice (25.8%) Rice 100%
Other cereals (2.7%) Wheat 12.7%| Sorghum & millet 52.9% | Other cereals 28.1%
Oilseeds (6.2%) Groundnuts 44.9% | Other oilseeds 55.1%
Pulses (3.9%) Pulses 100%
Roots (2.6%) Cassava 47.3% | Irish potatoes 17.9% | Sweet potatoes 34.8%
Horticulture (12.1%)
Leafy green vegetables 14.2% | Other vegetables 24.4% | Bananas 18.3% | Other fruits
43.0%
Other export crops (1.0%) Nuts 73.5%| Rubber 23.1% | Cut flowers 3.4%
Other crops (9.5%)
Sugarcane 29.3% | Cotton & fibers 3.2% | Coffee 19.8% | Tobacco 20.3% | Tea 9.8% |
Other crops 17.5%
Cattle & dairy (9.2%) Cattle meat 38.1% | Raw milk 61.9%
Other livestock (4.0%) Poultry meat 77.5% | Eggs 22.5% | Small ruminants 46.7% | Other livestock 53.3%
Fish (9.6%) Aquaculture 12.9% | Capture fisheries 87.1%
Forestry (2.4%) Forestry 100%