Land O Lakes presentation at GAAP final technical workshop
1. The gender impacts of the Land O’Lakes -
Manica Smallholder Dairy Development
Program (MSDDP)
—preliminary findings
Marinho Nhambeto, Liz Waithanji, Nancy Johnson, Lizz Hutchinson,
Martha Rogers, Edna Ogwangi, Mimoso Agostinho
GAAP Final Technical Workshop
ILRI-Addis Ababa
10 January 2013
2. Background
Funded by United States Department of
Agriculture (USDA)
Location and duration of program: 2009-
2012, Manica Province, Mozambique
Objectives: 1) rebuild Mozambique’s
dairy industry and 2) increase incomes
for smallholder farmers in a dairy value
chain.
3. Program distributed 500 improved dairy
cows to 327 qualified beneficiary
households and trained 2 members per
household in dairy management
4.
5. GAAP Research
Hypothesis/Questions for MSDDP
1. What direct and indirect benefits and
constraints do women experience in a gender-
blind asset distribution program?
2. What decision-making roles do women play in
the management of dairy cows?
3. Who controls the benefits (milk, income) from
the project?
6. Methods
1) Qualitative
- April 2011, 15 single-gender FGDs with members
of 15 of 17 farmer groups
- April 2012 - 6 single-gender FGD from 3 dairy
associations in the Vanduzi Dairy Cooperative
2011 Focus Group Discussions
Average # Groups Average
# Groups Participants- without Cows participants-
with Cows Cows (Anticipating) Anticipating
Female FGD 5 6.8 2 9.5
Male FGD 6 7.2 2 12
7. 2) Quantitative analysis
- 3 households surveys conducted:
April, 2009 (LOL), April-May 2011
(GAAP), April-May 2012 (LOL+GAAP)
- Different populations surveyed in
each round. For impact evaluation,
we focus on at beneficiary
households in 2011 and 2012 rounds
8. Comparison groups
For assets we can look at changes
between 2008 and 2011 based on
recall
For all other outcome variables, the
comparison groups are:
1) Received cows vs. still waiting
2) Length of time since cow was received (months)
3) Households that had a woman trained
4) Households where woman was primary trainee
9. Outline of results
Assets
Food security
Dairy
production
Milk sales and
income
10. Assets
• Qualitative focused on understanding asset
ownership and control
• Quantitative: 2 measures
– Total household assets
• Non-land asset index
– Women’s share of individually-owned assets
• Value of asset index for women/(value for men +
value for women)—joint asset no included
• Higher means less disparity
11. Qualitative findings
• Men and women use same asset categories—
domestic, productive, transport
• In general, people struggled to differentiate
between ownership, control and use
• Most people said that in male-headed
households, men make decisions
– Decision making powering is “bigger” than claim
to ownership
– But claim to ownership is one factor that may
influence decision-making
12. • Completion of training increased women’s
self-esteem and confidence
– Their ability to take care of cows was recognized
– Joint decision making with husbands was
enhanced
13. Descriptive statistics on assets
From 2011 survey, with retrospective asset question
2008 2011
Non Recipients Non Recipients
Recipients Recipients
73.84 84.77 80.16 110.96
Household asset index (n=125 ) (100.10) (92.07) (87.96) (115.73)
.39 .13 0.17 .18
Women’s share of assets (n= 125 ) (.92) (.43) (.36) (.33)
From beneficiaries in 2011 and 2012 surveys
Non Recipients Recipients All beneficiary
households
Mean S.D Mean S.D Mean S.D
Household asset index 80.16 87.96 100.91 100.20 99.04 99.15
Women’s share of assets 0.17 0.36 0.21 0.33 0.20 0.33
Number of observations 25 198 223
14. Determinants of change in total and women’s share
of assets, 2008-2011
Change in total HH Change women’s share
assets of assets
HH received cattle 16.6760** 18.3263*** 0.3514 0.3065
(6.4327) (6.2075) (0.3012) (0.2754)
Primary or secondary dairy trainee was
female 2.3529 -0.0882
(5.6049) (0.1345)
Primary dairy trainee was female -2.8895 0.1164
(8.1888) (0.1250)
Observations 102 102 63 63
Estimates controlled for household and community characteristics
15. Food security
• Participants in qualitative studies perceived
that improved family nutrition was a major
benefit of the program
• 2 quantitative measures
– # of months of adequate food provisioning
– Dietary diversity index
– No pre-project baseline data so we compared early
v late beneficiaries in 2011 and 2012 surveys
Non-recipients Recipients All beneficiaries
Mean S.D Mean S.D Mean S.D
Months of adequate HH food
10.48 2.24 11.18 1.48 11.10 1.59
provisioning
Household dietary diversity score 5.80 2.61 6.42 2.60 6.35 2.60
16. Determinants of Months of adequate household
food provisioning
HH received cattle 2.0155* 1.9502*
(1.0900) (1.0710)
Months since HH received first cow 0.0551** 0.0546**
(0.0236) (0.0250)
Primary or secondary dairy trainee was
-0.2868 -0.2302
female
(0.4058) (0.3578)
Primary dairy trainee was female -0.5537 -0.3955
(0.4206) (0.4072)
Observations 163 153 163 153
Estimates controlled for household and community characteristics
17. Determinants of dietary diversity score
HH received cattle 1.8731*** 2.0621***
(0.5473) (0.6050)
Months since HH received first cow -0.0421 -0.0469
(0.0517) (0.0517)
Primary or secondary dairy trainee was female 0.7773 0.5972
(0.6946) (0.8497)
Primary dairy trainee was female 0.1567 -0.0526
(1.0005) (1.0373)
Observations 163 153 163 153
Estimates controlled for household and community characteristics
18. Dairy cow management
• Qualitative analysis
looked at who does
what and who makes
decisions
• Quantitative analysis
focused on total cost
and household labor
use in dairy
19. Key qualitative findings
• Dairy activities are gendered, with some
overlap
• “Both men and women said that the
introduction of the dairy cow enabled
them to become more diligent planners
because of its demand on their time.”
– Everyone’s responsibilities increased with
improved cow
– Women may be most affected because they
had to stay home more and could not hire
help the way men did
20. • Men traditionally make
decisions about cows but
“women are developing an
interest in improved cows”
– Women are gaining
authority and decision
making power around dairy
• At household level women
are more concerned with
milk quality
– Many said the benefit from
training related to hygiene
21. Cost of production and labor for
recipients and non recipient
households
Non-recipients Recipients All beneficiaries
Mean S.D Mean S.D Mean S.D
Total dairy costs in last month
(MZM) 46.56 101.7 581.0 740.3 539.7 725.8
Total HH male labor hours on
dairy activities 4.50 10.42 18.48 16.04 16.91 16.11
Total HH female labor hours on
dairy activities 1.15 3.29 18.13 21.33 16.23 20.83
Total HH child labor hours on dairy
activities 3.34 10.05 19.27 19.33 17.49 19.18
22. Determinants of total dairy costs last month
(MZM)
HH received cattle 257.432** 246.44***
(98.4012) (82.8502)
Primary or secondary dairy trainee
was female -84.1539 -93.3024
(185.263) (198.960)
Months since HH received first cow 10.6395 12.1344
(12.4131) (12.2075)
Primary dairy trainee was female 90.0300 132.6012
(365.883) (363.653)
Observations 161 152 161 152
Estimates controlled for household and community characteristics
23. Determinants of household male labor
(hours spent on dairy)
HH received cattle 11.4581** 11.3406**
(4.7583) (4.9038)
Primary or secondary dairy trainee was
female -0.3805 1.2055
(3.5829) (3.7896)
Months since HH received first cow 0.4406** 0.4577**
(0.1817) (0.1929)
Primary dairy trainee was female 2.7140 4.4576
(7.2095) (6.4491)
Observations 163 153 163 153
Estimates controlled for household and community characteristics
24. Determinants of household female labor
(hours spent on dairy)
HH received cattle 17.991*** 17.341***
(6.2307) (6.4795)
Primary or secondary dairy trainee was
female -2.7002 2.3768
(4.8822) (3.9246)
Months since HH received first cattle 1.8959*** 1.9117***
(0.3022) (0.3163)
Primary dairy trainee was female -1.3249 5.7621
(10.7911) (9.3753)
Observations 163 153 163 153
Estimates controlled for household and community characteristics
25. Determinants of household child labor
(hours spent on dairy)
HH received cattle 14.092*** 14.130***
(4.6111) (4.7187)
Primary or secondary dairy trainee was
female 0.6609 3.1349
(3.8385) (4.2271)
Months since HH received first cattle 0.8903*** 0.9711***
(0.2416) (0.2817)
Primary dairy trainee was female 13.8598 17.7639
(13.5895) (12.4791)
Observations 163 153 163 153
Estimates controlled for household and community characteristics
26. Milk production and income
• Qualitative analysis explored: Who makes
decisions about milk consumption and
sale and who control income from milk
• Quantitative analysis looked at impact on:
– Quantity of milk sold
– Dairy income
– Income control in 2012 (descriptive only)
27. Findings from qualitative
• “All milk worth talking about is from
improved cows.”
• Morning milk sold to milk collection
center (MCC), generally by men
• Evening milk consumed or sold locally,
generally by women
29. Milk sales and income for
recipients and non-recipients
Non-recipients Recipients All beneficiaries
Mean S.D Mean S.D Mean S.D
Liters of milk sold or bartered in
last month 4.69 18.75 112.41 154.66 104.00 151.35
Money received from milk sales in
last month (MZM) 60.00 232.4 1540.8 2051.8 1430.8 2012.7
30. Determinants of liters of milk sold to MCC
village or bartered last month (MZM)
HH received cattle 73.7820*** 75.0157***
(27.5877) (27.4968)
Primary or secondary dairy trainee was
female 8.6903 6.9587
(32.1106) (34.6512)
Months since HH received first cattle 0.0196 0.2898
(2.7204) (2.7834)
Primary dairy trainee was female 47.0947 50.5377
(54.3564) (56.4264)
Observations 158 149 158 149
Estimates controlled for household and community characteristics
31. Determinants of income from milk sales
(MZM)
HH received cattle 1247.42** 1244.97**
(515.3749) (611.6042)
Primary or secondary dairy trainee was
female 1053.341** 1019.53**
(460.2119) (498.0601)
Months since HH received first cattle -11.4963 -14.5877
(34.3267) (34.3921)
Primary dairy trainee was female 618.9363 617.5980
(821.3166) (827.2487)
Observations 155 147 155 147
Estimates controlled for household and community characteristics
32. Some conclusions
• Overarching: Gender roles are shaped by socio-
cultural, economic and political norms
• Assets
– Care must be taken when interpreting “ownership”
data
– As expected, receipt of a cow improves households
assets. Does not appear to increase gender asset gap.
– People say that putting the cow in both names or in
woman’s name will have no practical effect but this
should be tested
• Food security
– Receipt of cow seems to have positive impact on food
security and nutrition, though mechanisms not clear
33. • Management
– Male HH heads traditionally make decisions, but there is
evidence that women are getting more involved in
management
– Costs increase with high-producing cows
• hypothesis that household needs 2-5 improved cows to
profitable—this is something to watch in next phase of project
– Impacts on women’s labor need to be monitored carefully,
especially in early stages of commercialization
• Production and income
– Production and income increase with receipt of improved
cow
– Men control most of dairy income
– Having a female trainee is associated with higher income,
possibly through better milk quality
--a few people seem to have it clear.Jointness example (own one together, each own some)
Human capital Which hh lost its cow?
Emphasize jointowenrshipWomen’s share of assets in non-recipient households dropped dramatically from 2008 to 2011. Need to look more at this to see why.
Receiving cattle increases toalhh assets but does not increase disparity. Seems inconsistent with qual results that all cows went to men. If no assets in index, then we see primary trainee female has significant negative relationship with change in total hh assets
Need better measures of consumption. Looked at fraction of sales but since people bought before this could actually go down.
Both men and women said that the introduction of the dairy cow enabled them to become more diligent planners because of its demand on their time. Men noted that the increase in their workload had necessitated them to employ labourers to attend to other duties as they and their wives attended to the dairy cow. Women had to juggle between cropping and dairying activities. In addition, women noted that specific household members had to be assigned specific chores. Women had to leave very specific instructions, on the cow, to the children and house help before going to tend the crops. Women could no longer stay away from home for long because the cow required them to come back and chop and mix feed, and feed and water it.Women’s activities tied them to the home more than men’s activities, which is typical in almost all societies whereby women’s productive roles are tied to their child rearing and other reproductive activities and performed close to home (Brown 1970). The fact that men could hire labourers and women could not – women juggled chores and delegated to family and existing workers – could suggest that men had more money or accessed money to pay labourers more easily than women. The additional cow-related activities that took much of the beneficiary time were gendered. For men and women, cutting and chopping grass and mixing this green forage with hay was most time consuming. For men only, selling milk and looking for milk customers took the most time. For women only, fetching water and watering the cows as well as the general care work was a main time-consuming added responsibility. In this division of labour, men were involved in both near and away from home activities more than women who were only involved in near home activities.
results consistent with all, all went up but especially women
possible drop
Both cow and time with cow have positive impact on male labor
while they don’t talk about milk productin, it is clear that the majority of production comes from improved cows
What is jointness (maybe clear) This question was only asked in 2012. All respondents had cows then. We can’t say how much this changed, but we do know that income is higher now than it was pre-improved cows
Number of cows is weighted by hh size.Need to check consistency of these numbers because they seem not to add up.
just describe
Link to qualitative result on importance of women of training women since they are the ones who do the work ,and produce milk of higher quality
