1) The document discusses a study on using dairy hubs to improve farmers' access to milk markets in Kenya, with a focus on the gender implications. 2) The results found that female-headed households participated less in dairy hubs than male-headed households, possibly due to women's reluctance to lose control over income from milk sales. 3) However, the study also found that dairy hub participation increased annual cash income from milk sales, indicating its economic benefits. Addressing gender issues around control of income is important to ensure all dairy farming households can benefit from collective milk marketing.

1. Using Dairy Hubs to Improve Farmers’ Access to Milk
Markets in Kenya: Gender and its Implications
Omondi, I., Zander, K., BauerBaltenweck, I. Siegfried 2, Kerstin 3
Tropentag 2014: Bridging the Gap between Increasing Knowledge and Decreasing Resources,
Prague, Czech Republic, 17-19 September 2014
Photo: ILRI and eadairy

2. 2
Presentation scope
Background
Methodology
Results and Implications

3. 3
Background
Control of productive assets has a direct impact on:
• Men, women, boys and girls forge life enhancing
livelihood strategies (WB-FAO-IFAD 2009)
Men and women have different access to markets,
infrastructures and related services (WB-FAO-IFAD 2009)
Rural women face obstacles in access to resources
• These hinder their adoption of new technologies or
increasing economies of scale (Korinek 2005)

4. 4
Background
Compared to their male
counterparts, women:
• Make crucial contribution in
agriculture and rural
development in all developing
countries
• Yet, they face more severe
constraints in accessing
productive resources, markets
and services (FAO 2011) Photo: eadairy

5. Background … (contd.)
5
In dairy sector,
• A major socio-economic pillar in Sub-saharan Africa (Mubiru
et al. 2007)
• Women contribute substantial labor to dairy enterprise
activities (Abdulai and Birachi 2009)
•Consequently, in pro-poor development efforts
• It is important to understand the challenges facing women
in dairy

6. Background … (contd.)
Analysis of factors affecting participation in dairy hubs
6
FARMERS
TRANSPORTERS
FIELD DAYS
FEED SUPPLY
VILLAGE BANKS
AI & EXTENSION
HARDWARE SUPPLIERS

7. 7
Methodology

8. 8
Study Area

9. 9
Sampling method and design
Structured Household Interviews
301 Households
• Household socio-economic data collected
• Farmer characteristics
• Farm Characteristics
• Participation in dairy hubs
• Farmer preferences
Hub Non-member
Households (44%)
Hub Member
Households (56%)

10. 10
Analysis
Logit regression
i i i Y   x  e *  ~Logistic(0,1)

1 0 *




 Y max{ 0, z} i 
Yi i '  1, 
,
i n
if Y
Otherwise
• is a latent variable indexing adoption
• is the observed response for the ith farmer
• a vector of explanatory variables
*
i Y
Yi
x j

11. Analysis … contd
11
Censored tobit regression
iid
Y *   x  e  | x N (0, 
2 ) i i i i i
~* *

 Y max{ 0, z} i 
i i '  1, 
,
0 *
i n



Y if Y c
if Y c
Yi
i


• Y
*
is a latent variable indexing adoption
i • Yi
an observable measure of intensity of use
• x j
a vector of explanatory variables
• c is an unobservable threshold, β is a vector of unknown
parameters, and ε are residuals

12. 12
RESULTS AND
IMPLICATIONS

13. 13
Results
The results indicate:
• Relatively low participation of women in dairy hubs
• Female household heads:
• Are older, with more years of farming experience, than their
male counterparts;
However,
• They are worse off in education, household size, level of
education among adults in the households, and number of
income sources

14. Table 1: Determinants of Sale of Milk to the dairy hubs
Dependent Variable: selling milk to dairy hubs
Independent Variables Coefficient
Total milk sold by household to all channels per day 0.62** (0.13)
Household keeps exotic cattle (level of intensification -
4.41* (1.79)
advanced)
14
Household keeps cross cattle (level of intensification -
emerging)
4.30* (1.92)
Household not registered in milk marketing hub) -3.01** (0.95)
Household heads years of farming experience -0.07* (0.03)
Female-headed household (Gender of household head) 2.79* (1.25)
Household size (number of household members) 0.36* (0.16)
Female household member deciding on where to sell milk -2.46* (1.23)
χ2=166.36 20df, p=0.00 log likelihood = -39.92 pseudo-R2 = 0.68
* an average day in July/Aug 2010 *, ** indicate significance at 5% and 1%, respectively
Robust standard errors are indicated in parenthesis

15. Table 2: Determinants of Volume of Milk Sold to the Dairy Hubs
Dependent Variable: proportion of total daily milk sales to hubs
Independent Variables Coefficient
Gender: female-headed household 0.65** (0.19)
Decision on milk sales channel: made by male 0.51** (0.15)
Decision on milk sales channel: joint male & female 0.36* (0.17)
Household not registered in EADD hub -0.74** (0.14)
Joint hub membership (both head and spouse) 0.52* (0.24)
Education: head's years of schooling 0.04* (0.02)
Household size 0.07* (0.03)
Level of intensification: keeping exotic cattle 0.52** (0.18)
Level of intensification: keeping cross cattle 0.58** (0.21)
Milk production per day 0.01* (4.7E-3)
χ2=128.44, 20df, p=0.00 log likelihood = -111.62 pseudo-R2 = 0.38
15
* an average day in July/Aug 2010 *, ** indicate significance at 5% and 1%, respectively
Robust standard errors are indicated in parenthesis

16. 16
Discussion and Implication
The results reveal strong evidence of:
• Women’s apparent reluctance to participate in dairy hubs
• Arguably, due to loss of control of income from milk sales
Why participate in dairy hubs?
• Comparatively high economic endowment
• Evidenced from a propensity matching analysis
• Hub participation increased the annual cash income from sale
milk

17. 17
Discussion and Implication
The results reveals a gender puzzle that:
• Underscores the importance of intra-household
distribution of income
• Needs to be surmounted
• To ensure dairy households accrue the
benefits of collective marketing
Gender issues in the study area
• Are culturally deep-rooted
• Require careful, evidence-based approaches
Photo: eadairy

18. Acknowledgements
This work is financed by:
• International Livestock Research Institute (ILRI)
• German Academic Exchange Services (DAAD)
It contributes to:
• The CGIAR Research Program on livestock and Fish