Presented by Elizabeth Waithanji at the 7th African Dairy Conference and Exhibition, Dar es Salaam, 25–27 May 2011

1. Women’s Participation in the Dairy
Value Chain in Tanzania and Kenya:
Benefits, Constraints and Opportunities
Elizabeth Waithanji
A Presentation at The 7th African Dairy Conference and Exhibition,
Dar es Salaam, May 25th – 27th 2011
1

2. Outline
• Introduction
• Patterns of Dairy cattle ownership
• Dairy Marketing
– Women’s Participation in Marketing
– Income management and intra-household
decision making
– Women’s livestock ownership and household
food security
• Opportunities and challenges in increasing
women’s benefits from markets
2

3. 3

4. Introduction
• Livestock are productive assets as livestock
and livestock products contribute to food
and income security of the rural poor
• 70% of the rural poor are women (DFID
2000)
• Livestock are among the few assets that
women can own
• Even where women do not control livestock,
they may control products e.g. Milk
4

5. Introduction
• Money from sales of livestock and their
products constitute a most important
income source for women
• Women livestock owners are more
constrained than men because women have
limited
– decision making powers
– access to and ownership of capital and assets
– access to information and marketing
opportunities
5

6. Introduction
• Women’s control of household income from sales
is often challenged because they
– are more likely to sell in informal local markets
– pay higher costs than men to access information
– pay male intermediaries to have some things done
• Women are, therefore, relegated to less
profitable positions of small scale retailers of
perishable goods in local village markets (Escola
2005)
• Because women play a key role in making choices
on household food consumption, diet quality and
intra-household allocation, women’s status within
the household is key if good food security choices
are to be made
6

7. Objectives of Study
• To investigate the gendered patterns of dairy
cattle ownership, milk marketing, dairy income
management, and opportunities and constraints
to milk marketing for women in Kenya and
Tanzania
– To add onto the scarce information on the gender
asset gap in dairy in these two countries
– To identify potential ways of closing the gender asset
gap as productivity increases in the dairy, and
hopefully, other livestock value chains in both these
countries
– To initiate a conversation about, and commitments
towards closing the gender asset gap in dairy
7

8. Methodology
• The study was conducted in 5 districts in Tanzania
(Kilombero, Kibaha, Gairo, Mvomero and
Morogoro); and 4 districts in Kenya (Kiambu,
Kajiado, Meru and Tharaka)
– Factors considered in sample collection were
agricultural potential, production systems and access to
markets
• Both quantitative and qualitative data were
collected
– Quantitative – Household survey questionnaires with a
module for household head and for female spouse in
male headed households. Data analyzed statistically.
– Qualitative – gender disaggregated FGDs whereby tools
such as ranking, rating and market chain maps were
used. Data analyzed inductively.
8

9. Results and Discussion
9

10. Dairy Cattle Ownership by HH Headship
In Tanzania, FHH owned 54.5% of the
number of cattle owned by MHH
In Kenya, FHH owned 78.2% of the
number of cattle owned by MHH
Dairy Cattle Numbers -Tanzania
Dairy Cattle Numbers - Kenya
6
3
5
2.5
4
2
3
1.5
2
1
1
0.5
0
0
Male headed
Female headed
Male headed
Female headed
•The difference in numbers of dairy cattle in Tanzanian and Kenyan households might be
associated with the difference in the marketing systems in these two countries
•Existence of more commercialized dairy marketing systems in Kenya might explain the
narrowed gap – in terms of cattle numbers owned – between MHH and FHH
10

11. Who Markets milk Where
Tanzania
Kenya
120%
70
60
100%
50
80%
40
60%
30
20
40%
10
20%
0
Farmgate Farmgate Delivery to
to farmers to traders traders
0%
From home to other farmers
Men
Village
market
Collection
centre
Chilling
plant
Delivered to traders/shops/hotels
Women
Joint
Men
Women
Joint
•Fewer milk-market options exist for both women and men in Tanzania than in Kenya
•Women’s involvement in markets beyond the farm gate declined remarkably in both
countries
•Deliveries outside the farm gate are mainly done by men alone or jointly by men and
women
11

12. What determines market participation by
women in Kenya
Milk
Variables
Eggs
Coefficien
t
z
P>z
Price of milk
0.014
3.930
0.000
Belong to group=1
0.114
-2.510
0.012
Age
-0.003
-2.060
0.040
Transport asset
0.017
0.530
Household size
-0.011
Primary education
Variables
Coef.
z
P>z
Price of eggs
0.001
-3.11
0.002
Belong to group=1
-0.501
-6.17
0.000
Age
0.000
-0.01
0.990
0.596
Transport asset
0.008
0.25
0.806
-1.400
0.161
Household size
-0.036
-3.81
0.000
-0.093
-1.590
0.113
Primary education
0.124
1.56
0.120
Secondary education
-0.077
-1.210
0.225
Secondary education
0.158
1.83
0.068
College education
-0.104
-1.170
0.242
Sold from home to
traders
0.160
3.580
0.000
College education
0.254
2.32
0.020
Delivered to traders
0.167
3.070
0.002
Sold from home to
traders
0.038
1.05
0.294
Sold in village market
-0.012
-0.090
0.932
Delivered to traders
0.081
1.5
0.133
Constant
0.618
4.500
0.000
Sold to city markets
0.136
1.43
0.153
Constant
1.469
7.99
0.000
/sigma
0.173
19.18
0.000
/sigma
0.108304
7
11.49
0
12

13. Proportion of Milk Income Controlled by Men, Women, and
Jointly in Kenya and Tanzania
• Most (63%) of the milk income was
controlled jointly in both countries
70
60
• In Tanzania, women controlled
more (31%) of the remaining
income than men
50
40
• In Kenya, men controlled more
(21%) of the remaining income
than women
30
20
10
0
Men
Women
Kenya
Joint
• This gendered difference in milk
income control in both countries
could be attributed to the fact that
milk production in Kenya is more
commercialized and markets more
formalized than in Tanzania
Tanzania
13

14. Decision Making on Livestock and their
products
Tanzania - number and amount
of animals and products to keep
Kenya - number and amount of
animals and products to keep
14

15. Decision Making on use of Income from
Sales of Livestock and their Products
Tanzania- use of money from sale of
livestock and livestock products
Kenya - use of money from sale of
livestock and livestock products
15

16. Patterns of Decision Making
• In both countries, women made sole
decisions more than men for milk and
poultry products and the income accrued
from these
• If a woman can make a decision on what
commodity to keep and how much to
produce, then she is most likely to have
control over income from the sale of that
commodity
• This finding suggests that an intervention in
dairy and poultry is likely to have more
women benefitting than an intervention in
other livestock value chains
16

17. Women’s Livestock Ownership and
Household Food Security
Influence of women's livestock ownership
on HDDS and MIHFP in Tanzania
Influence of women's livestock ownership
on HDDS and MIHFP in Kenya
HDDS
HDDS
HH where
women
own
livestock
Dairy cattle
0.69
HH where
women do
not own
livestock
0.55
MIHFP
MIHFP
T-values
1.44
(0.151)
11
HH where
women do
not own
livestock
8.77
HH
where
women
do not
own
livestock
t-values
HH
where
women
own
livestoc
k
HH
where
women
do not
own
livestoc
k
Dairy cattle
HH where
women
own
livestock
HH
where
women
own
livestock
0.73
0.65
3.105***
4.3
5.8
2.272**
Exotic
chicken
0.82
0.66
4.376***
3.7
5.5
1.689
Local chicken
0.71
0.66
2.118**
5.3
5.4
0.242
Goats
0.61
0.69
2.564**
5.1
5.4
0.403
T-values
tvalues
3.67 (0.047)
Exotic chicken
0.58
0.55
2.8 (0.006)
11.5
8.77
5.08 (0.077)
Local chicken
0.63
0.55
0.92
(0.365)
8.84
8.67
0.416
(0.679)
Goats
0.51
0.56
0.35
(0.781)
8.5
8.83
0.51 (0.617)
HDDS – Household Dietary Diversity Score; MIHFP – Months of Inadequate
Household Food Provisioning
17

18. Women’s Livestock Ownership and
Household Food Security
• Results on the difference in HDDS were more
dramatic in Kenya than Tanzania where the
differences were significant between all households
where women owned livestock and those where
women did not own livestock
– Households where women own livestock have access to
more diverse foods
• Results on the differences in MHIFP were significant
only in households where women owned dairy
cattle in Kenya. The pattern on MIHFP was less clear
in Tanzania
– When women own dairy cattle, the households are
likely to experience fewer months of food inadequacy
18

19. Opportunities for Women’s Increased
Participation in Dairy Markets
• It appears like with an increase in commercialization of dairy
production and market formalization, the inter-household asset gap –
in terms of dairy cattle numbers – narrows ( 22.8% in Kenya and 45.5%
in Tanzania)
• Intervention in dairy development projects are most likely to benefit
women directly since women are able to control production and
income obtained from sale of milk.
• For women’s participation in the dairy industry to be sustained, it
appears necessary to integrate gender in projects since under the
current circumstances, women’s participation diminishes remarkably
beyond selling at the farm gate
• Joint milk income control does not appear to be affected by degree of
commercialization of production or market formalization: the
“jointness” concept needs to be explored and if beneficial for women,
it should be exploited during dairy development interventions
19

20. Challenges for Women’s Increased
Participation in Dairy Markets
• Commercialization of production and formalizing markets of
most farm commodities is associated with marginalization of
women from the markets of these commodities
– Can milk be an exception?
– How?
• Formal markets are mostly located in urban areas and most
farms in rural areas. Women participate poorly beyond the farm
gate. Consequently;
– “Mainstream” production commercialization and market
formalization interventions are doomed to fail if they do not
address gender issues
– and innovative ways of involving rural women in formal farm
commodity markets must be established urgently
• The “jointness” concept remains a methodological and
discursive challenge owing to its nuanced as well as fluid nature
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21. Acknowledgements
• Participating Tanzanian and Kenyan Farmers
• Data collection Field teams
• ILRI PGI Team
• IDRC
• FORD Foundation
21

22. Thank You
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