1. Creating Pro-poor Value Chains: Sorghum Beer in Kenya
Alastair Orr (ICRISAT) Catherine Mwema (ICRISAT) Wellington Mulinge (KARI)

2. What’s ahead….
Why sorghum beer?
The Kenya beer market
The business model
Data and methods
Results
Some conclusions

3. Drivers of demand for beer
Consumer power : Africa’s growing middle class (313 million or 34% of the population (ADB, 2011).
Urbanisation: 55 African cities with populations over 1 million
Slowing beer markets in developed countries
Competition between 4 multinational Companies with 90% of African beer market
Sorghum beer targeted at ‘aspirational’ consumers trading up from illicit brews ($3 billion market)
Barley- Rising prices and import duties
Consumer power- increased consumer spending representing about ¼ africa’s GDP. Potential market for breweries.
Urbanization- ½ of Africans live in the cities. Nairobi 12th largest city in Africa. Urban consumers a concentrated mkt
Sorghum beer- Launched as a response to effects of local brews (chang’aa). Was zero rated by the govt
9/14/2018

4. The beer market in Kenya
East African Breweries (EABL) (Diageo plc 51 %) has 93 % of the market
Strong market growth since 2000
‘Senator’ keg sorghum beer launched in 2004
No excise duty until 2013
One-third price of malted beers
Senator Kenya’s best-selling beer by volume, 35 % of EABL revenues
EABL sorghum demand expected to reach 60,000t by 2015
9/14/2018
EABL boasts of 7 companies
Taxes- structural adjustments in the 90s. Increased consumption of illicit brews.
Senator Keg introduced mainly for the low income earners, it is sold in barrels and attracts youthful consumers.

5. The Smart Logistics business model
Smart Logistics Solutions, Kenyan-owned, founded 2009, contract with EABL
Buys from small scale farmer groups and appointed agents
Sorghum aggregated in collection centres
SL transports to EABL
Payments from 1-4 Wks through bank or mpesa
Pays 26 US cents/kg compared to 7 cents paid by local traders
Three research questions:
How inclusive is this business model?
What are the benefits for smallholders?
Can it be scaled out?
SLS only uses groups for aggregation to cut down on transactional costs
EABL- checks quality of sorghum and payments made to SL after a month, no incentive for quality
PAYMENT- Mpesa is electronic money transfer using mobile. Most farmers paid 3-4wks
9/14/2018

6. Data and methods Data Methods
A household survey in Kitui county, semi-arid eastern Kenya .
High poverty levels (64%) with frequent droughts.
Multi-stage stratified sampling used to select 150 members & 150 non-members of Smart Logistics groups
2012 crop year (short and long rains).
Methods
Sellers to Smart Logistics include both members and non members
Propensity Score Matching (PSM) of sellers, non-sellers
Selling influenced by membership of Smart Logistics group
Use predictive value of membership as independent variable for participation in sorghum sales
9/14/2018
Kitui-High poverty levels (63.5%). Constant droughts. Multistage- explain the clusters and sample. Short rains more reliable
Logit regression was run to get a predictive value .

7. Specification Group membership Sorghum sale
Distance to collection centre
Age
Gender
Education
Consumer/worker ratio
Household food security
Occupation
Farm size
Sorghum sale
Distance to market
Qty maize production
Qty sorghum production
Dummy if household buys sorghum
Predicted value of group membership
9/14/2018
Gender a dummy with 1 for female headed
Occupation a dummy with 1 for farming

8. Socio-economic profile
Variables
Sellers
(n=198)
Non-sellers
(n=99)
Sig
(P value)
Members of SL groups
127 71
.000
Household size
6.5
6.2
.306
De facto female-headed households (no.) 88 32
.045
Adults >15yrs full time in sorghum production (no)
1.9
.746
Crop production,
Total land planted (acres)
5.0
.935
Area planted to sorghum (acres)
1.2
0.9
Total maize production (kg)
841
732
.445
Total sorghum production (kg)
463
337
.455
Households buying maize (no.)
162 70
.037
Total household income (000 Ksh)
255
324
.050
Income per capita (000 Ksh) 46 58
.049
Income from crops (000 Ksh) 53 50
.774
Income from livestock (000 Ksh)
131
181
.021
Value of household assets (000 Ksh)
115
121
.712
9/14/2018
Factors influencing decision to join SL group
Start with positive factors then negative

9. Decision to join SL group
Variable
Coefficient
S.E.
Sig. (P > )
Constant
-1.582
0.608
.009
TIME_CENTRE
0.000
0.003
.996
FHH_DEFACTO
0.613**
0.272
.024
AGESQ
0.000**
.011
SCHOOLYRS
0.110**
0.039
.005
CWRATIO
0.248**
0.121
.040
BUYMAIZE
-0.100***
0.035
FARMER
0.691**
0.286
.016
LAND_PADULT
-0.122**
0.058
.034
LAND_PCAPITA
-0.280**
0.136
School yrs- quite interesting
9/14/2018

10. Mean standardized bias Sample size on common support
PSM results
Matching algorithm
Mean standardized bias
Sample size on common support
Before matching
After matching
Caliper (bandwidth 0.01)
12.1
6.5
267
Kernel (bandwidth 0.06)
13.4
276
Nearest neighbor with replacement (k=1)
14.5
Nearest neighbor without replacement (k=1)
18.6
182
9/14/2018
Treated and control are balanced

11. Treatment effects on treated
Variable
Sample
Treated
Control
Difference Z
P > z
INCOME_PCAP
ATT
46,801
49,975
-3,174
(18,922)
-0.57
0.571
INCREASE_ASSETS
28,204
39,332
-11,128
(9,169)
-1.28
0.200
SCHOOL_FEES
34,832
49,177
-14,334
(27,063)
-1.70*
0.090
CHANGE IN ECONOMIC CONDITION
0.85
0.66
0.18
(0.070)
2.39**
0.017
SELL SORGHUM AS COPING STRATEGY IN DROUGHT
0.51
0.31
0.21
(0.078)
2.03**
0.042
9/14/2018

12. How inclusive….?
Group members more likely to be older, full-time farmers, from households headed by women, with higher dependency ratios, and less land per adult member of the household…
The business model is inclusive because poorer households have fewer alternative opportunities for cash income
Better-off households don’t join because they have more opportunities to earn cash income, and less time to attend group meetings
9/14/2018

13. How beneficial...? Average annual income from sorghum ($116)
No significant differences in income per capita or value of assets bought since 2009
Significant differences in perceived improvement in economic condition since 2009, and in selling sorghum as a coping strategy, increasing resilience to climatic shocks.
Sellers spent significantly less than non-sellers on school fees ($400 compared to $565)
But two-thirds of sellers ranked expenditure on school fees and materials as most important use of sorghum income.
Benefits from sorghum are being invested in human capital
9/14/2018

14. How easy to scale out...?
The average annual sales volume per Household to smart logistics (430kg) Low Profit margins (1-2 US cents/kg) Erratic supply: sales fall in drought years as households prioritize food security Smart Logistics reaches about 3,000 growers In 2012,Kenya’s sorghum growers supplied only 8,000 t of the 24,000 required by EABL
9/14/2018

15. Preliminary conclusions
Domestic consumer markets like sorghum beer provide opportunities for smallholders in semi-arid areas
Poorer households can participate
Benefits invested in human capital
Low yields, small sales volumes, drought, limit the scope for scaling out
9/14/2018