Bart Minten, Joey Goeb, Jon Keesecker, Derek Headey POLICY SEMINAR COVID-19 and Food Market Disruptions in Myanmar OCT 15, 2020 - 09:00 AM TO 10:30 AM +0630

2. Assessing the impacts of
COVID-19 on food markets in
Myanmar
2
Dr. Bart Minten, Senior Research Fellow, IFPRI

3. Introduction
High importance of food markets,
even in rural areas
• In urban areas: 94% of food
consumption (calories) purchased
• In rural areas: 71% of food
consumption purchased
• Annual value food retail in
Myanmar:
‐ 17.3 trillion kyat (13.3 billion usd)
‐ 360,100 kyat/capita (277 usd/capita)
3
0
10
20
30
40
50
60
70
80
90
100
Urban Rural
Share calories (%)
purchased home‐produced in‐kind gifts

4. Introduction
Food markets important for poor and
rich alike
• Poorest quintile (q1):
‐ 76% of calories purchased
‐ 20% home‐produced
‐ 4% gifts
• Richest quintile (q5):
‐ 81% of calories purchased
‐ 13% home‐produced
‐ 5% gifts
4
0
10
20
30
40
50
60
70
80
90
100
q1 q2 q3 q4 q5
Share calories (%)
purchased home‐produced in‐kind gifts

5. Research & survey teams
Research team
• IFPRI/MAPSA: Derek Headey, Joey Goeb, Bart Minten, Isabel Lambrecht, Than
Zaw Oo, Sophie Goudet
• IPA survey implementation team: Zin New Win, Afke Jager, Ricardo Morel
• Mercy Corps: Jon Keesecker
5

6. Food Vendor Survey ‐ September 2020
Purpose of survey: to assess
the impacts of the COVID19
crisis on
1/ COVID19 prevention
measures in markets
2/ changes in shopping
behavior
3/ difficulties in operations of
food vendors
4/ changes in availability and
prices of food
5/ perceived changes in
consumption
6

7. Survey design
Objectives:
• Assess and monitor impacts of C19 on
food vendors and markets
Survey design:
• Rural & urban communities in all S/R
• Interviewed 1 food vendor in 216
communities, mix 17% urban – 83% rural
Questionnaire content
• Prevention measures, availability/prices
of products, changes shopping behavior,
effect on business of COVID19
7

8. Key results – 1: Prevention measures for COVID‐19
followed in most food markets but intensity varies
1. Mask wearing is widely practiced
2. Additional efforts – spraying of
markets, handwashing stations, and
proper distancing between vendors –
are done in most villages/townships
Prevention measures, percentage of markets
8
0% 50% 100%
Presence handwashing
stations
Disinfection markets
Distancing vendors
Mask wearing vendors
Mask wearing consumers
Intensity
No Some Most All

9. Key results – 2: Operations of markets restricted,
but not the number of customers
1. A quarter of markets have reduced
opening hours
2. Few markets have a restriction in
number of people on market
3. This combination may increase
congestion and contagion
Restrictions in markets, percentage of markets
9
0 5 10 15 20 25 30
Reducing the number of hours of
operation
Reducing the number of days of
operation
Restricting number of people on
market
Restricting number of vendors
% of markets

10. Key results – 3: Business of food vendors
impacted by COVID19
1. 24% of food vendors state that
their business has not been
affected – majority states that
profits are lower
2. Few problems mentioned on the
supply side or with transportation
(in September)
Effects of COVID‐19 on food vendors in
Myanmar, percentage of vendors affected
10
0% 20% 40% 60% 80%
Lost/let go of employees
Less visits customers
Deline in profits
No effect on business
Barriers in transportation
Difficulty local suppliers
Difficulty suppliers from outside
Share of food vendors

11. Key results ‐ 4: Availability of products not yet
very much affected
1. Most of the vendors reported
availability of food products in
their village/township was the
same as normal.
2. Relatively more availability issues
with animal source foods (fish,
pork)
Availability of food products compared to normal periods
(% of food vendors)
11
0% 50% 100%
Rice
Potatoes
Pulses
Fruits
Onions
Green leafy vegs
Chicken
Pork
Dried/smoked fish
Fresh fish
Cooking oils
Share of food vendors
Less than normal More than normal Same

12. Key results ‐ 5: Customers purchase less
animal sourced foods
1. Food vendors reported quantities
purchased stayed at similar levels
as normal for most of the food
products.
2. That “same” category varied
between 96% for rice and 85% for
smoked fish.
3. 13% of food vendors state that
pork and dried/smoked fish are
less purchased.
Changes in quantities purchased compared to normally
12
0% 50% 100%
Rice
Potatoes
Pulses
Fruits
Onions
Green leafy vegs
Chicken
Pork
Dried/smoked fish
Fresh fish
Cooking oils
Share of food vendors
Less than normal More than normal Same

13. COVID‐19 Market Disruptions:
Urban Food Retailers
13
Dr. Joey Goeb, Research Associate, MSU

14. Urban Food Retailer Phone Survey
• Traditional family‐owned general goods stores account for a large share of consumer goods sales in Myanmar
(estimates up to 85%)
• A large share of their revenues come from food products
• >50% of revenue for our sample
• Mostly dry, packaged foods and beverages
• Conducted with mom&pop – a Myanmar‐based business intelligence company 14
Source: Myanmar Times

15. Survey Design
15
Objectives:
• Assess and monitor impacts of C19 on urban food retailers
Survey design:
• 440 shops
• Yangon (330) and Mandalay (110)
• 5 interviews with each shop
• July 15 / July 25 / Aug 11 / Aug 27 / Sept 29
Questionnaire content
• COVID‐19 effects on business, responses and adaptations, gender effects,
employment, changes in food product buying and selling prices (tracking
specific product prices over time)

16. 0% 20% 40% 60% 80% 100%
Tobacco or betel nut…
Alcoholic beverages
Coffee and tea mix
Soft drinks
Dry noodles
Snacks and bakery
Cooking oil, sugar, salt
Dairy products
Eggs
Pulses (beans)
Rice
Kitchen crops (onions, garlic)
Sausage, meat, chicken, fish
Fruits and vegetables
Key results – 1: Lower sales in early July 2020, but
shops sell same products as 2019
1. Shops sell mostly dry,
packaged foods and
beverages
2. Only 2 shops reported selling
a new food category in 2020
compared to 2019
3. Lower sales reported in early
July compared to same time
in 2019 for 64% of all food
products sold 16
Food products sold, percent of shops
Share reporting
lower sales in
early July
56%
56%
51%
47%
56%
61%
66%
67%
62%
73%
65%
63%
66%
54%

17. Key results – 2: Large disruptions from 2nd wave
1. 75% of shops had a lockdown
in their township in late Sept
2. 50% of shops have supply and
demand disruptions
3. 90% of shops adopted safety
practices
a. Face coverings (77%), hand
washing (70%), distance (58%)
Disruptions by survey round, percentage of shops
17
0% 20% 40% 60% 80% 100%
Adopt safety practices
Demand disruptions
Supply disruptions
Lockdown on street
Lockdown in township
Curfew
Late Sept Mid‐Aug Mid‐July

18. Key results – 3: Robust supply chains, and
wholesalers fill supply gaps
1. Supply chains have been largely
robust to 2nd wave restrictions
a. 90% of the food products in our
survey were sourced from shops’
regular suppliers
2. Wholesalers fill supply gaps
a. From other wholesalers (4%)
b. From other suppliers (5%)
18
5% 4% 1%
0% 5% 10%
to wholesaler
different wholesaler
Other
Changes in suppliers, percent of food products

19. Key results – 4: Modest food price increases
during COVID‐19 crisis
1. Small price increases for
processed, packaged foods
2. Larger price increases for raw
foods in both waves
a. Partly due to seasonality
3. Township lockdowns  3%
increase in consumer‐facing prices
of foods on average
a. Higher increases for raw foods
19
Selling price changes as a percentage of pre‐COVID‐19 prices
Product
First wave
(March‐August)
Second wave
(Sept)
High price Low price
Raw foods
Rice 4% ‐1% 5%
Onion 8% 0% 41%
Chickpeas 1% 0% 7%
Eggs 3% 0% 6%
Packaged foods & beverages
Dry noodles 2% ‐1% 6%
Vegetable oil 3% ‐3% 4%
Coffee mix 0% 0% 0%
Beer 2% ‐2% 1%
Average price changes as a percentage of March 2020 prices

20. Results summary
1. Shops report smaller sales this year
2. Most shops affected by lockdowns; 50% report disruptions to
demand, supply
3. Supply chains are still functioning, wholesalers fill gaps
4. Modest but significant food price increases during lockdowns
20

21. Thank you
• Full policy notes available at this link
21

22. Rakhine
Market Analysis Unit
Paddy Farmer Snapshot
October 15, 2020
Jon Keesecker, Team Leader, Market Analysis Unit, Mercy Corp

23. Agenda
1. MAU Introduction
2. Farmer Profile (5 min)
3. Challenges, Adaptation & Expectations (4 min)

24. MAU Introduction
Audience: Humanitarian and market development orgs operating in Rakhine State,
donors, private sector actors and policy makers

25. MAU Introduction
Past MAU releases
• Market Snapshot (8 twp): Trader / Input Supplier (Sept. 1)
• Market Snapshot (8 twp): Trader / Input Supplier (Sept. 16)
Forthcoming MAU releases (October)
• Market Snapshot (8 twp): Transport / logistics Providers
• Commodity Price Tracker (5 twp): 5 product categories
• Farmer Snapshot (6 twp): Paddy / winter crops / food security
Forthcoming MAU releases (Nov/after)
• Study (4 twp): COVID-19 Impact on Crab value chain (Nov.)
• TBD

26. Farmer Snapshot: Disclaimers
*Today we focus only on paddy cultivation*
(excludes data on winter crops expectations / food security)
*Data are preliminary*

27. Farmer Snapshot: Objective & Methodology
Research Objectives: Seek to capture…
1. Farmer profile
2. Challenges (COVID, conflict, weather, etc.)
3. Adaptation
4. Expectations
Methodology:
• Mode: Phone survey
• Collection period: Oct. 7-10, 2020
• Sampling: Convenience sample of Mercy Corps “Key Farmers” (n=165)
• Topics: Monsoon paddy, winter crops, food security

28. Farmer Snapshot: HH & Land Profile
Household & Land Characteristics
• HH size: median = 5
• Primary livelihood (monsoon): 99% paddy
• Primary livelihood (winter): 99% winter crops
• Acres (paddy): median = 6
• Land: 93% own land, 36% is “far” from village
Land Ownership Status
Paddy Acres
Household Size
Paddy Field Location

29. Farmer Snapshot: Production Profile
Paddy Products & Channels
• Grew in 2019: 93% grew last year
• Input purchases: >66% invest in various inputs
• Paddy duration: Variable
• Product: Few market rice (24%)
• Sales channels: Traders (55%)
Paddy Products
Paddy Duration
Primary Sales Channel (2019)
Paddy Inputs Purchased/Rented (2019)

30. Farmer Snapshot: Challenges, Adaptation & Expectations
• Baskets per acre: median = 54
• Expectations for 2020: 28% of HH expect lower output (usually 10-20% lower)
Paddy Output by HH in 2019 (reported) Percent change in 2020 (expected)

31. Farmer Snapshot: Challenges, Adaptation & Expectations
• Challenges selling paddy: 2019 v. 2020 (expected)
• Adaptation to challenges selling paddy (2019)

32. Farmer Snapshot: Challenges, Adaptation & Expectations
• Livelihood Challenges (past 30 days)
• Outlook (next 30 days)

33. Farmer Snapshot: What’s Next
• Analyze: Data for winter crops (expectations) and food security (FIES module)
• Writeup: Release findings by end of October.
• Further data collection: Survey same farmers again in early/mid November

34. Thank You!

36. Assessing disruptions to food
markets at the community level
23
Dr. Derek Headey, Senior Research Fellow, IFPRI

37. Community Survey ‐ September 2020
Purpose of survey: to assess
the impacts of the COVID19
crisis on communities
1/ C19 prevention measures
2/ economic impacts on
poverty, migration, agriculture
3/ assistance from
government, NGOs, charities
4/ Other shocks & disruptions
24

38. COVID Community Survey (Round 3)
25
Overview
• Three rounds of a community level survey covering rural and urban
communities spread across all states/regions
• Late June & early July (end of first wave)
• early August (recovery)
• Late August and early September (start of second wave)
Geographical Zone
Delta/South 135
Dry Zone/Central 166
South‐East 55
North 105
West 19
Rural/Urban
Urban 114
Rural 366
Total 480

39. Mobility restrictions have come back in most communities
• By end of 1st wave most
communities had a wide range of
mobility restrictions to prevent
spread of C19
• Prevention measures fell away by
early August
• Quickly came back by late‐August
and early September
• 68% have some restriction on food
traders entering
• Over half restrict residents from
existing community
• 80% impose curfews
• Few communities cited problems
with accessing transport or banks
(<10%)
26
Mobility restrictions came back quickly as 2nd wave hit
69%
64%
53% 56%
84%
35% 35% 33% 34%
71%
77%
68%
55% 56%
79%
0%
25%
50%
75%
100%
Entry
restrictions:
social
Entry
restrictions:
food trade
Exit
restrictions:
shopping
Exit
restrictions:
work/trade
Curfews
Late June‐early July Early August Late Aug‐Early Sep

40. Disruptions to ag production are now less common
Ag
production
lower
Reasons for low agricultural production
Bad
weather
Pests
COVID‐19
restrictions
Low output
prices
Not
enough
traders
Shortage
of ag
inputs
Shortage
of farm
labor
Shortage
of feed
Conflict
Jan‐July 55% 72% 33% 18% 17% 7% 7% 3% 1% 0%
August 42% 89% 36% 1% 7% 7% 0% 1% 0% 0%
August‐Sep 33% 85% 37% 1% 10% 2% 2% 0% 0% 0%
• Fewer communities say ag production is lower than normal in late August‐early September
• Over half of communities cited problems in Jan‐July period, now down to one‐third
• Most commonly cited problem has been bad weather (too little rainfall, or too erratic)
• Pests also widely cited (1/3rd), and remained a persistent problems
• Series of COVID‐19 related problems were widely cited in Jan‐July, but rarely cited by early Sep.
• However, 10% of communities still cited low output prices

41. Disruptions to ag trade are picking up again however
• In June 50% of communities
said it unusually difficult for
farmers to sell produce
• This fell to 23% in early
August, but rose again to 36%
by late Aug/early September
• Most common problems:
• Lower crop price
• Miscellaneous C19 restrictions
• Fewer traders coming to villages
• Closures of both village and
town/city markets
28
Mobility restrictions came back quickly as 2nd wave hit
87%
40%
19%
12%
11%
4%
2%
0% 20% 40% 60% 80% 100%
Low crop price
COVID‐19 related restrictions
Fewer traders coming to village
Closure of village markets
Closure of town/city markets
Pests
Bad weather

42. Respondents feel that extreme poverty is rising rapidly again
“Let us say that extremely poor households are those that are very short of food, suffering from
hunger, and in urgent need of some kind of assistance. What is the proportion in this village/street
would you currently say are currently extremely poor?
29
17% 18%
16%
13%
18%
20%
18%
16%
11% 12% 11%
8%
11%
13% 12% 11%
27%
29% 29%
23% 24%
27% 28% 27%
0%
10%
20%
30%
40%
50%
Total Urban Rural Delta Dry Zone South‐East North West
Share estimated to be extremely poor
Late June‐early July August August‐September

43. Recommendations summary
• Ag production & marketing are disrupted, poverty rising
• Important to keep ag value chains functioning safely and smoothly
• Evaluate low, medium and high‐risk activities
• Standardize some basic regulations to improve consistent across
states/regions and over time: chopping and changing is highly disruptive
• Offer technical advice to local governments for making markets safer:
• Longer opening hours; physical distancing measures, entry limits, promote
home delivery – look at best practice measures from other countries
• Further close monitoring of these markets is important both for C19
prevention and to ensure smooth functioning
30