Presented by Omondi I.A., Rao E.J.O., Karimov A.A. and Baltenweck, I. at the ILRI Institute Planning Meeting, Nairobi, 4-7 October 2016

1. Processor linkages, Farm Productivity and
Household Income in Dairy Farm Households in
East Africa
Omondi I.A., Rao E.J.O., Karimov A.A., and Baltenweck, I.
ILRI Institute Planning Meeting
4-7 October 2016

2. Foresight & Policy
Gender & Social
Equity
Enhancing Nutrition
through Livestock
Value chains for
competitive
smallholders
systems
Gender equitable
control of assets and
resources
Improved capacity
of women and
youth to participate
in decision-making
Increased access to
diverse nutrient rich
foods
Increased livelihood
opportunities
Reduced market
barriers
Conducive Policy
Environment
Our Theory of Change…
* Livestock keepers &
their communities
* Private sector
* Development partners
* Government agencies
* Policy & decision makers
* Research partners
Research teams
(Sphere of Control)
Research & near development outcomes
(Sphere of Influence)
Sub- IDOs
(Sphere of Interest)
Monitoring,
Evaluation &
Impact Assessment
Decision
making is
based on
evidence
Demand for
livestock
(products) is
adequate
Actors are willing
& able to invest in
new approaches
Gender
transformative
approaches
translate into
lasting benefits
Nutrition
interventions
are win-win

3. Background
• Why the study?
• Linking smallholder farmers to large enterprises:
• could be a powerful mechanism to improve access to:
• input and output markets
• other productivity-enhancing services
especially for liquidity constrained smallholders
• What we did:
• We conducted the study under EADD project
• We analysed the effects of household linkages to milk
markets via dairy hubs

4. Background … contd.
• The dairy hubs:
• act as a linkage between the processors and farmers
• differ in levels of growth towards sustainability
• Forms of linkages:
1. “pure processor” 2. “mixed-linkage”
• Hypothesis:
• Differences in linkages and growth:
• influences revenues, certainty of income, access to inputs
• thus impacting on income and farm performance

5. • Data from 993 dairy households in Kenya and Uganda
• 36% farmers operated under “pure processor linkage” hubs
• 64% of farmers operated under “mixed linkage” hubs
• Main analyses :
• Propensity score matching
• Technical efficiency – DEA model
• No significant differences in socioeconomic characteristics
between these two groups
• except herd size in Uganda
Method and Results

6. • Statistical matching results reveal:
• That participation in hubs leads to higher dairy revenues and total
household income, ceteris paribus
• implying a multiplier effect of dairy revenue
• Higher effects for households participating in “pure processor” hubs
• Data Envelop Analysis results and statistical test reveal
1. no strong influence at farm level from processor linkages
2. Hub maturity, linked to PO efficiency,
- does not sufficiently translate to more productive farmers
Results …. contd.

7. • Linking farmers to large enterprises produces positive
impacts on income
• Yet no evidence of the trickle effect to households’
productivity and input use in dairy
• It is imperative to assess and design linkages that translate
into increased farm productivity
Implications and Conclusions

8. This work is financed by:
EADD project Donors
Livestock and Fish program of the CGIAR
It contributes to the CGIAR Research Program on
Livestock and Fish
We also thank all donors who supported ILRI’s research through
their contributions to the CGIAR Fund
Acknowledgements

9. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
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ILRI thanks all donors and organizations who globally supported its work through their contributions
to the CGIAR system