This study is the first component of a multi-pronged research study on breaking the cycle of food insecurity in Malawi. Results from other components are to follow, including promoting nutritious value chains and understanding the drivers of food security and resilience. This study examines the impact of a food-based social transfers (MVAC) on household food security, diets, and nutrition status of young children during the lean season in Malawi. This was a quasi-experimental prospective study based on two rounds of a mixed methods surveys study in Zomba district in southern Malawi. Study outcomes include household expenditures and food consumption (7-day recall), child level dietary diversity (24-hour recall) and nutritional status (anthropometric measurements). We follow a mixed methods approach and undertake child and household surveys and assessments as well as in-depth interviews with household members. We estimate program impact by combining propensity score matching (PSM) and difference-in-difference (DID) methods. Qualitative data provides insights into community norms on targeting and sharing that may impact the effectiveness of the transfers. Food transfers appear to have a protective effect on food security, diets and nutrition status of young children. There was suggestion of a positive effect on micronutrient availability in diets, particularly for iron. At child level, highly significant positive effects were found on dietary diversity and food variety scores, corresponding to increases of 15% and 12% respectively, as well as a positive effect on stunting. But targeting did not appear to be progressive or aligned to MVAC criteria. Furthermore, the coverage of food transfers is extremely low compared to extent of food insecurity. Community norms about targeting and sharing may explain the targeting errors and also may be seen as a response to low coverage.

1. Evidence from a mixed-methods study in Malawi
Aulo Gelli, Noora-Lisa Aberman,
Amy Margolies, Marco Santacroce, Bob Baulch
and Ephraim Chirwa
The impact of lean season food transfers
on food security, diets and nutrition
status

2. Study objectives
• To estimate the impact and targeting of lean
season food transfers (MVAC) on households’
food security and children’s diets and nutrition
• To understand village-level norms on
allocation of food transfers and other
resources that may help explain those results

3. Study sites
• Data was collected
from 60 communities
randomly selected
among a set of
food-insecure villages
in MVAC targeted
region of Zomba
district in southern
Malawi

4. Study methods: Quantitative Data
• Longitudinal study based on two rounds of
surveys undertaken (as part of a cluster
randomized controlled trial of a pre-school
based agriculture and nutrition intervention):
– Baseline survey undertaken in the post-harvest
season (September 2015)
– Follow-up undertaken during the peak lean
season (February 2016) after scale-up of food
transfers
– Rich data set including ~1200 households, over
1,500 children

5. Study methods: Qualitative Data
• Qualitative data is made up of 45 in-depth
time-line interviews in the same communities
in Zomba, with women, men and adolescent
girls (March 2016)
– Translated and transcribed, then thematically
coded

6. Evaluation strategy
• First estimated a probit model to assess the
probability of targeting criteria to predict
program participation
– using range of household and community level
characteristics on sample of MVAC beneficiaries
and non-beneficiaries
• Then we evaluated the impact of MVAC by
combining propensity score matching and
difference in difference (DID) methods

7. Outcomes
• Two levels of outcomes:
1. Alternative measures of household food security
estimated from consumption and expenditure
modules using adult equivalents
2. Measures of diets and
nutrition status of
young children

8. MVAC programme characteristics
• Eligibility criteria for MVAC food assistance
included households headed by women, the
elderly or children, or households including
orphans, the chronically ill or households that
had lost their main source of income due to
chronic illness
• Household screening criteria also included asset
holdings (including livestock, land and small
durables), participation in other social assistance
programs (including social cash transfers, inputs
subsidy programme and school meals)

9. Food transfers
• Food rations were to be provided to households
on a monthly basis and included maize (50kg),
legumes (10kg) and fortified vegetable oil (1.84 kg)
• At endline, 175 (15%) out of 1,191 households
had received MVAC in the survey population
• Households consuming <1800 calories per capital
per day: 36% at baseline and 46% during lean
season

10. 0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
Schoolfeedingprogram
Pre-schoolfeedingprogram
MVAC
Seeds
Vocationaltraining
Foodforwork
Cashtransfer
Waterpurificationforhomeuse
Healthoutreach/training
FISP
Otherfreeagricultural
Assistancefromcommunity…
Remittancesfromwithinor…
Agriculturetools
Mosquitonets
Creditfrommicrofinanceagencies…
Educationalassistance
Vocationaltrainingother
Specializedkindsoffoodsfor…
Other
Cashforwork
Inputsforwork
NAPSA/SocialSecuirty/Pension…
Scholarshipforstudy/training
Clothes/shoes
Workman’scompensation…
ShareofHH.Covered
Social assistance coverage in survey
population (lean season)
Share of HH. receiving assistance
-33% of HHs receive no prog.
-33% of HHs receive 1 prog.
-20% of HHs Receive 2 progs.
…

11. Effects of MVAC Food Transfer
• During the lean season, households in the
sample experienced substantive declines in
household food security
• Compared to control, MVAC food recipients
were better off:
– substantive positive impact on household food
consumption in 7 day recall period
– substantive positive impact on young children’s
diets and nutrition outcomes

12. Treatment effects: Household level
• Substantive positive impact on household
food consumption in 7 day recall period
– Per capita food expenditures + 19% / 35MK pppd
– Daily acquisition of iron +16% / 3.92mg pppd
** p<0.05.
MKw/day

13. Treatment effects: Child level
• Substantive positive impact on young
children’s diets (DDS +15% & FVS +13%)
• And nutrition outcomes: weight-for-height z-
scores (+14%)
Children 36-72m Children 6-59m
***
***
**
*** p<0.01; ** p<0.05.

14. MVAC targeting
• Findings indicate that MVAC targeting criteria are
not good predictors of program participation
• Data on MVAC participation also suggests that
~20% of most food secure households (by
quintile) received transfers
• Positive effects on food expenditures and
children’s diets are concentrated among the
poorer households
• SCTP recipients appear to be excluded from
receiving MVAC food

15. MVAC participation by socioeconomic
and food security status

16. MVAC participation by official
poverty line
Household expenditures
poor non-poor
MVAC 10% 5%
no MVAC 55% 31%

17. Qualitative Results

18. Resilience and Coping: tracking the
ups and downs
• Ups and downs: major life events cause
shocks, as well as annual lean season shock
• All households face dietary shifts during the
lean season, decreasing amount of food or
shifting to less preferred (though not always
less nutrient-dense) foods
– Few manage lean season without negative coping
(diets, schooling, assets)

19. Social norms, targeting & favoritism
• Village heads play a significant role in determining who
received MVAC and other social support programs.
– Primarily through control over beneficiary selection, also
through decrees about sharing
• Villages vary in terms of perceptions of extent of
consultation in the targeting process
• Perceptions of the extent (and definition) of favoritism also
varies
• Some complaints about chief intervention, e.g., inclusion
errors (favoritism) and forced sharing, but frequently this is
viewed as unavoidable and part of village norms
• Beyond some complaints about chief intervention, the
primary complaint about targeting is “not enough benefit”
related to feeling that “everyone should get something”

20. Social norms and sharing
• About half the time sharing is dictated by the chief. When
it’s not, HHs decide to share on their own due to kinship
obligations, social pressure, and hope for reciprocation
(often described as a moral or humanitarian requirement).
• Some people complained about forced sharing and
community pressure to share. No one complained about
sharing with relatives => social requirement.
• Sharing is required even if targeted recipient is objectively
poorer than those with whom they share (relative wealth
does not seem to be considered in sharing decisions)
• Sharing norms related to cash transfers may be different
=> possibly less sharing, fear of tracking

21. Female MVAC recipients in Zomba in favor of forced sharing:
Interviewer: Did you think this sharing was beneficial?
Respondent 1: Yes, it was beneficial because it could be
you next year not in the program, and your friends
would help you. But the owners of the program say not
to share, this only happens in the village to just help
each other.
Interviewer: Alright. Was the sharing fair?
Respondent 2: I can say that on this side of the village
it was fair. Because this village has two tribes; those
from the chief and those not related to the chief…So if
they need 8 people then they will take 4 from each
side.

22. Female MVAC recipients in Zomba unhappy with targeting and
forced sharing:
I: So what criteria were they using to select beneficiaries?
R: They were choosing people who had nothing to eat…But at
times they recorded names of people who had food but those
who lacked food were also being skipped…As per village level
problems, the chief said, “This maize should be shared amongst
you. You will see how you can share.” So people could share two
[households] per bag…
Male non-recipients in Zomba describing the unfair targeting processes:
R: I should just give an example of a certain year, where I was
really touched [hurt] in my heart. I received a coupon that I
should be receiving maize. After three months I discovered that
somebody was using my coupon to get my maize. Somebody
with a higher position in the village. The person came and
offered me 12 kilograms, and I said all the people were
receiving 25 kilograms, why should I get 12? No I cannot accept
that, you will consider me the next time.

23. Conclusions: Effects of MVAC
• Quantitative data suggests that MVAC food
transfers are effective in protecting food
security and nutrition status during the lean
season.
–Evidence of protective impact on household
food consumption, and on dietary diversity (of
3-6yr olds) and weight for height z-scores of
young children (0-5yrs)

24. Conclusions: Targeting and Coverage
• Targeting and coverage of MVAC:
– Overall coverage of transfers was low in the survey
population (~15% of HH)
– Data on targeting criteria are not good predictors of
program participation
– Evidence suggests that ~20% of the most food secure
households received transfers
• Effects on food expenditures and diets are greater for
poorer households (better targeting=>more efficient)
• Data also shows that those receiving SCTP are
excluded from receiving MVAC, even though SCTP
recipients should be among the poorest and most
food insecure.

25. Conclusions: Sharing and Favoritism
• Insufficient public social support reinforces high
dependence on kinship networks and community
support
• Favoritism in community-based targeting seen as
unavoidable (villagers cannot contest/ it’s chief’s
prerogative)
• A more objective targeting system (e.g., UBR)
could improve targeting to some extent, but
pressure to reallocate once transfer arrive in the
village are likely to remain

26. Policy Implications
• Putting in place a targeting system separate from village politics
and norms would likely increase impact. But how?
• Most people face dietary shocks each year: suggesting that
other social support mechanisms (productive and protective)
must be scaled up to meet the current need.
• However, all program targeting mechanisms must consider
sharing & reallocation.
• Possible approaches:
– Increased village-level transparency about targeting criteria
– Parallel village-level institutions to assist/monitor targeting, distinct from
village governing structures could bypass village norms and politics
– Whole village targeting, when feasible
– Universal (vulnerable sub-group) targeting, as in Ntchisi, to all families
with under-fives, or to all elderly
• Educating villagers on good local governance practices, may slowly
begin to alter norms that yield exclusion and inclusion errors, but
weak social support system reinforces these practices.

27. Open Questions
• Next round of data collection ongoing
• Will examine any effects of MVAC on stunting.
• Will explore village head’s perceptions of
favoritism and their role in targeting.
• Are targeting errors due to sharing or
targeting process?
• Do sharing norms differ for different types of
programs/transfers? (e.g. cash)?

28. Annexes

29. Post-harvest and lean season
summary statistics

30. Survey population
• Baseline household
characteristics
mean sd Obs.
Houeshold size 5.33 1.8 1,199
Number of children 0-36 months 0.51 0.58 1,199
Number of children 36-72 months 1.13 0.36 1,199
Number of children 6-14 years 1.45 1.17 1,199
Number of adults 14-65 years 2.25 0.98 1,199
Number of elders 65+ years 0.04 0.23 1,199
Dependency Ratio* 1.58 1 1,199
HH head completed primary education? 0.35 0.48 1,199
Household head's age 36.5 10.5 1,199
Polygamous households 0.03 0.17 1,199
Female headed household 0.28 0.45 1,199
Assets owned:
-Large livestock (Oxen or cattle) 0.04 0.43 1,199
-Small livestock (Goats, pigs, rabbits) 0.8 2.43 1,199
-Fowl (Chickens, guinea fowl…) 2.57 5.25 1,199
-Bees/Beehives 0 0 1,199
-Fish pond or fishing equipment 0 0 1,199
-Farm equipment (Non-mechanized) 3.12 2.74 1,199
-Farm equipment (Mechanized) 0.01 0.17 1,199
-Non-farm business equipment 0.16 2.94 1,199
-Houses or other structures 0.32 0.88 1,199
-Large consumer durables 0.23 1.14 1,199
-Small consumer durables (Radio…) 14 30.19 1,199
-Cell phones 0.62 0.75 1,199
-Other land not used for agriculture 0.05 0.32 1,199
-Means of transportation (bicycle…) 0.54 0.7 1,199
-Total asset count 22.5 33.5 1,199
Total expenditure (pp, day)* 242 188 1,139
Food expenditure (pp, day)* 186 150 1,139
Share of food expenditure on total exp.* 0.78 0.17 1,139
Chidlren (6-59 months)
-Height-for-age (z-score) -1.74 5.87 1,383
-Weight-for-height (z-score) 0.09 4.29 1,402
Prop. Obs.
-Prevalence of Stunting (6-59m) 42% 1,379
-Prevalence of Wasting (6-59m) 1% 1,402
Notes: *Table excludes outliers for food consumption and total expenditure

31. MVAC Coverage by Cluster
0
5
10
15
20
25
30
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
Kasimu
Utwe
Sunuzi
Thabwani
StPius
Gologota
Namakun…
Makoka
Tsabola
Chikala
Chanda
Mpata
ST.Anthon
Machereni
Nalikukut
Nazithimb
chimwalir
Nsala
Nachiswe
Nsenjere
Coverage (% of HH in cluster)
Coverage (HH covered in cluster)

32. MVAC=175 Cash=69
FFW=52
Total=1,192 households
6
24

33. Programme participation (probit) model

34. MVAC targeting
0.000.250.500.751.00
0.00 0.25 0.50 0.75 1.00
Inclusion of Non-Vulnerable (1 - Specificity)
Area under ROC curve = 0.4957
Households with Female, Child or Elderly Head or Orphans