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February 10, 2023
9:00 – 10:00 AM MMT
MAPSA Learning Series
Promising Indicators for Effectively Targeting the Poor
in Myanmar
SPEAKERS
Salauddin Tauseef
Associate Research Fellow,
International Food Policy Research Institute
Derek Headey
Senior Research Fellow,
International Food Policy Research Institute
MODERATOR
Ian Masias
Senior Program Manager,
International Food Policy Research Institute

TARGETING IN SOCIAL ASSISTANCE
• Two school of thought – (1) targeted intervention (2) universal programs.
• Targeting selected categories, families, or individuals can play a valuable
role in anti-poverty interventions
• To reduce poverty, concentrating a greater share of benefits on the poorest
is more cost-effective than expanding coverage more broadly.
• While targeting has costs, these are usually low or within an acceptable
range, and must be balanced against the potential gains of focusing
resources on those most in need.
• There is no ‘one size fits all’ targeting method and customization is key -
• What are the policy objectives for a particular intervention?
• What data are available or can be easily obtained?
• What counts as success?

TODAY’S PRESENTATION
• We try to identify a set of poverty indicators that are observable and
verifiable and, therefore, hold promise in effectively identifying the poor.
• We use data from a nationally representative household welfare survey
collected in August 2022.
• We show how different combinations of indicators increase targeting
efficiency.
• We caution on the existence of heterogeneity in poverty indicators across
regions.
• We show our indicators to have an acceptable rate of exclusion error.

•Nationwide phone survey of 12,128 households
•Completed over July 8th – August 10th,2022
•State/Region representative:
•310 of 330 townships
•7 townships excluded (Wa SAZ)
•6 townships in Kachin and 1 in Yangon with
very small population sizes
•MHWS sets education, gender and farmer survey
targets to reduce biases from phone surveys
•Constructed households, individual & population
weights to estimate representative statistics
MYANMAR HOUSEHOLD WELFARE
SURVEY (MHWS)

CORE INDICATORS
1. Households with walls made of rudimentary materials such as
hemp/hay/bamboo, etc.
2. Household with rudimentary electricity connection such as solar,
battery, water mill or nothing.
3. Household located more than 2 hours away from the nearest
township center.
4. Household whose primary source of income is agricultural wage
work.

PERCENTAGE OF HOUSEHOLDS WITH WALLS MADE
OF RUDIMENTARY MATERIALS BY INCOME GROUP
27
29
21
14
9
22
28
24
16
10
34
28
17
11
9
0
5
10
15
20
25
30
35
40
1 (lowest) 2.0 3.0 4.0 5 (Highest)
Percent
of
households
per adult equivalent income quintiles
national rural urban

PERCENTAGE OF HOUSEHOLDS WITH RUDIMENTARY
ELECTRICITY CONNECTION BY INCOME GROUP
28
27
20
14
11
23
26
22
17
13
35
29
14 13
8
0
5
10
15
20
25
30
35
40
1 (lowest) 2.0 3.0 4.0 5 (Highest)
Percent
of
households
per adult equivalent income quintiles
national rural urban

HOUSEHOLDS MORE THAN 2 HOURS FROM NEAREST
TOWNSHIP CENTER BY INCOME GROUP
29
28
18
14
10
26
28
21
16
10
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
1 (lowest) 2.0 3.0 4.0 5 (Highest)
Percent
of
households
per adult equivalent income quintiles
national rural

PERCENTAGE OF HOUSEHOLDS WHOSE PRIMARY
SOURCE OF INCOME IS AGRICULTURAL WAGE WORK
BY INCOME GROUP
32
34
20
10
4
23
36
23
13
5
33
35
21
7
3
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
1 (lowest) 2.0 3.0 4.0 5 (Highest)
Percent
of
households
per adult equivalent income quintiles
national rural urban

ADDITIONAL INDICATORS
Test additional indicators strongly associated with poverty:
1. Households with floor not made of improved materials, wood, tile,
vinyl, etc.
2. Households without improved toilet facility (has open pit, hanging
latrine or no facility).
3. Households without any fridge.
4. Households without any wardrobe.
5. Households without any agricultural land ownership.

ADDITIONAL INDICATORS: DEMOGRAPHIC GROUPS
Certain demographic groups are also highly vulnerable to poverty:
1. Household has at least one child aged 0 to 5 years.
2. Household has at least two adolescent girls aged 12 to 20 years.
3. Household has at least two school aged children 5 to 14 years.
4. Household with school age children 5 to 14 years not going to
school.
5. Households with highest education of adults’ below primary level.

UNIVARIATE ASSOCIATIONS (NO CONTROLS)
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
-.1 0 .1 .2 .3 -.1 0 .1 .2 .3
Income poor Hunger
Low FCS Low adult DD

MULTIVARIATE ASSOCIATIONS (WITH ALL CONTROLS)
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
-.1 0 .1 .2 .3 -.1 0 .1 .2 .3
Income poor - Rsq .18 Hunger - Rsq .08
Low FCS - Rsq .09 Low adult DD - Rsq .07

UNIVARIATE ASSOCIATIONS BY REGION (NO CONTROLS)
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
household land ownership <= 2 acres
Primary income source is agricultural wage work
HHs with rudimentary electricity
Time to nearest township >= 120 min
HHs with walls made of hemp/hay/bamboo, etc.
HHs with floor not made of improved materials
HHs without improved toilet facility
HH has no fridge
HH has no wardrobe
HH does not own agricultural land
HHs with at least a child 0 to 5 years
HHs with at least two adolescent girl aged 12 to 20 years
HHs with at least two school age 5-14 years child
HHs with highest education of adults below primary level
household land ownership <= 2 acres
-.1 0 .1 .2 .3 -.1 0 .1 .2 .3
Hills Dry
Delta Coastal

ERRORS OF EXCLUSION
Since prediction by any model is never exact, it is expected that –
1. Some poor will be incorrectly identified as nonpoor – Error of exclusion
2. Some nonpoor will be incorrectly identified as poor – Error of inclusion.
The two errors generally work against each other (tradeoffs)
No. of
indicators
Core Core + housing Core + asset
Core + asset +
land
Core + asset +
housing
1 30% 28% 21% 19% 19%
2 46% 46% 47% 44% 42%
3 53% 55% 66% 65% 60%
4 54% 61% 78% 80% 72%
5 - 62% 84% 89% 80%
6 - 63% 84% 93% 85%
7 - - - 93% 87%
8 - - - - 87%
Core indicators = rudimentary walls + rudimentary electricity + remote + agricultural wage worker
Core + housing = Core + not improved flooring + not improved toilet facilities
Core + asset = Core + no fridge + no wardrobe
Core + asset + land = Core + asset + no agricultural land ownership
Core + asset + housing = Core + no fridge + no wardrobe + not improved flooring + not improved toilet

EFFECT OF VARIOUS MONTHLY TRANSFERS ON POVERTY
Core
Core +
housing
Core + asset
Core + asset +
land
Core + asset
+ housing
Poverty rate (%) 61% 61% 61% 61% 61%
Monthly
transfer
amount
(USD)
$30 59% 58% 55% 54% 55%
$50 57% 56% 51% 49% 51%
$100 53% 50% 41% 37% 40%
$200 47% 42% 27% 20% 25%
$300 46% 40% 23% 16% 20%
Core indicators = walls of rudimentary walls + rudimentary electricity +remote +agricultural wage worker
Core + housing = Core + not improved flooring + not improved toilet facilities
Core + asset = Core + no fridge + no wardrobe
Core + asset + land = Core + asset + no agricultural land ownership
Core + asset + housing = Core + no fridge + no wardrobe + not improved flooring + not improved toilet
Note: We categorize a households as poor if that household meets at least 2 of the proposed criteria

FURTHER CONSIDERATION
• Indicators identified here are more suited to addressing structural poverty.
• However, recent shocks have highlighted the importance of social
protection systems that can respond quickly to shocks, assisting the newly
vulnerable as well as those already in need.
• Income dynamics and shocks make the determination of eligibility
challenging.
• Therefore, targeting social protection should always remain a dynamic
process according to the objective of the program.

POTENTIAL USES
• We propose a set of indicators that are observable and verifiable
• Using a nationally representative data collected in August 2022
• Specific to the context of Myanmar and its regions
• Can easily be incorporated in surveys for selection
• We welcome suggestions on what additional info would be useful.
For more information visit –
For survey and questionnaire: https://doi.org/10.7910/DVN/LPNMTK
For research note: http://dx.doi.org/10.2499/p15738coll2.136558
MAPSA webpage: https://myanmar.ifpri.info/

ေကျးဇူးတင်ပါတယ်
Thank you

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