Andrew G. Mude (ILRI). Building Climate Resilient Livelihoods through Index-Insurance in Northern Kenya. Presented at CCAFS Science Meeting, 1-2 December 2010

1. Building Climate Resilient Livelihoods
Through Index-Insurance:
Piloting IBLI in Northern Kenya
Andrew G. Mude
International Livestock Research Institute
December 2 2010, CCAFS Cancun

2. The Case for IBLI Managing Risk in the ASALs
• ASALs more than half of Africa’s
landmass
• Pastoral livestock production is the
principle livelihood
• Pastoralist livestock and livestock services
comprise a substantial portion of
agricultural GDP for many African
countries.
• ASALs remote, infrastructure deficient,
politically marginalized
• Pastoralists particularly vulnerable to severe
droughts
• Presence of asset-based poverty traps
accentuates the risk

3. The Case for IBLI Insurance and Development
 Sustainable insurance can:
• Prevent downward slide of vulnerable populations
• Stabilize expectations & crowd-in investment and
accumulation by poor populations
• Induce financial deepening by crowding-in credit
supply and demand
 But can insurance be sustainably offered in rangelands?
 Conventional (individual) insurance unlikely to work,
especially among pastoralists:
• Transactions costs
• Moral hazard/adverse selection

4. The Case for IBLI Index Insurance: Advantages
 Index insurance avoids problems that make individual
insurance unprofitable for small, remote clients:
• No transactions costs of measuring individual losses
• Preserves effort incentives (no moral hazard) as no
single individual can influence index.
• Adverse selection does not matter as payouts do not
depend on the riskiness of those who buy the insurance
• Available on near real-time basis: faster response than
conventional humanitarian relief
 Index insurance can, in principle, be used to create an
effective safety net to alter poverty dynamics and help
address broad-scale shocks

5. The Case for IBLI Index Insurance: Challenges
 ‘Big 5’ Challenges of Sustainable Index Insurance:
1. High quality data (reliable, timely, non-manipulable, long-
term) to calculate premium and to determine payouts
2. Minimize uncovered basis risk through product design
3. Innovation incentives for insurance companies to design
and market a new product
4. Establish informed effective demand, especially among a
clientele with little experience with any insurance, much
less a complex index insurance product
5. Low cost delivery mechanism for making insurance
available for numerous small and medium scale producers

6. The Case for IBLI Solutions to Challenges
 Solutions to the ‘Big 5’ Challenges:
1. High quality data:
• Satellite data (remotely sensed vegetation index: NDVI)
2. Minimize uncovered basis risk:
• Analysis of household data on herd loss
3. Innovation incentives for insurers:
• Researchers do product design work, develop awareness
materials and assist with capacity building
4. Establish informed effective demand:
• Simulation games with real information & incentives
5. Low cost mechanism:
• Delivery through partners

7. The Case for IBLI Remotely Sensed Data
Deviation of NDVI from long-term average
NDVI February 2009, Dekad 3
NDVI Data February 2009, Dekad 3
 Real-time
available in 8×8
km2 resolution
 27 years
available since
late 1981
NASA NDVI Image Produced By: USGS-EROS Data Center. Source: Famine Early Warning System Network (FEWS-NET)
Laisamis Cluster, zndvi (1982-2008)
Historical droughts

8. The Case for IBLI Livestock Mortality Index
 NDVI-based Livestock Mortality Index
IBLI contract is based on area average livestock mortality
predicted by remotely-sensed (satellite) information on
vegetative cover (NDVI):

9. The Case for IBLI Livestock Mortality Index
 Geographical Clusters:
Estimate 2 separate livestock
mortality-NDVI response
functions for distinct clusters
in Marsabit District:
-- Chalbi (Upper Marsabit)
(arid, camel-smallstock
based)
-- Laisamis (Lower Marsabit)
(semi-arid, cattle-smallstock
based

10. The Case for IBLI Livestock Mortality Index
 Index
Performance

11. The Case for IBLI Livestock Mortality Index
 Index Performance
Index predicts large-scale losses very well

12. The Marsabit Pilot
• Launched the pilot in Jan 2010
• Sales beat all expectations
– Almost 2000 contracts sold
– $46,000 in total premiums collected
– Total Value of Livestock Insured 1,193,080
PROMISING
BUT
TOO
EARLY
TO
TELL,
LOTS
OF
LESSONS
TO
LEARN
AND
IMPROVEMENTS
TO
MAKE

13. The Way Forward
 Integrated long-term survey design for impact evaluation to
inform program and policy formation
• HH survey in pilot and control locations
• Comparative assessment with unconditional cash transfer
program (the Hunger Safety Nets Program: HSNP)
• Discount coupons randomly allocated to eligible
subpopulations
 Scaling up across ASAL regions in Kenya
 Investigating feasibility of IBLI in the region – recently
launched a Southern Ethiopia program

14. Research and Policy Questions
 Investigate Alternative Contract Structures
• Group-­‐based
insurance
markeEng
• Linked
credit
and
insurance
• Risk
layering
• CondiEonal
insurance
transfers
 IBLI impact on livestock holdings, spatial distribution and
condition of the rangelands

15. Research and Policy Questions
 Determinants of demand and adoption?
 Developing processes to establish rules of implementation
amidst challenging public/private relationships
 Data availability and collection coupled with improved
response function modelling for better scale-up

16. Thank you
For more information please visit:
www.ilri.org/ibli/

17. The Marsabit Pilot Contract Features
• The Risk
• Designed to provide compensation in the event of widespread drought –
related livestock losses.
• The Index
• Predicted area-based livestock mortality
• The Insurable Livestock Unit
• Camel, Cattle, Sheep and Goat
• Insurance provided on standardized Tropical Livestock Unit (TLU)
o 1 Cattle = 1 TLU.
o 1 Camel = 1.4 TLU.
o 1 goat/sheep = 0.1 TLU.
Example: To insure 4 cattle, 7 camel, and 12 goats/sheep,
TLU insured is 4×1 + 7×1.4 + 12×0.1 = 15 TLU.
• Value of the Insured Herd
• 1 TLU = Ksh 15,000
• To insure 15 TLU, insured value is thus: Ksh 225,000

18. The Marsabit Pilot Contract Features
• Payout Structure
• Payouts are made when predicted livestock mortality is above the
“Trigger” index level. Trigger set at 15%

19. The Marsabit Pilot Contract Features
Geographical Coverage
- Two response function clusters ,
Upper and Lower Marsabit
- Index calculated at Division level.

20. The Marsabit Pilot Contract Features

21. The Marsabit Pilot Contract Premiums
• Premiums for contract with trigger level 15%, providing
annual coverage with two potential payout periods
Contract
Actuarially
Target
Net
to
Total
GIFF
Cluster
Fair
Price
Consumer
Reinsurer
Market
Subsidy
Price
Price
Request
Upper
4.75%
5.5%
7.3%
9.2%
3.7%
Marsabit
Lower
2.2%
3.25%
4.3%
5.4%
2.15%
Marsabit
• To insure 15TLU valued at Ksh 225,000
• Upper Marsabit: Ksh 12, 375
• Lower Marsabit: Ksh 7, 312.50

22. The Marsabit Pilot Contract Sales Jan/Feb 2010
SHEEP/
TOTAL
VALUE
TO
VALUE
OF
CATTLE
CAMELS
PREMIUM
CONTRACTS
GOATS OF
INSURED
COLLECTED
NO.
NO.
RATE SOLD NO.
LIVESTOCK PREMIUMS
INSURED INSURED
INSURED (USD) (USD)
UPPER 5.5% 556 371 11,081 185 347,620 19,119
LOWER 3.25% 1,423 3537 4,745 154 845,460 27,477
TOTAL 1,979 3908 15,826 339 1,193,080 46,597

23. Contract Features
Geographical Coverage
Premiums for 15% Strike Contracts in Marsabit
Contract
Cluster Consumer
Price
Upper
Marsabit 5.5%
Lower
Marsabit 3.25%

24. Contract Features

25. How will IBLI work?
Consider 1-year contract for a pastoralist who would like to insure a herd valued at
KSh150,000.
During the sale period at the beginning of the coverage year, he pays an annual
premium (Ksh) = % × insured value
Value of Herd Insured Upper Marsabit Cost Lower Marsabit Cost
(5.5%) (3.25%)
Ksh 150,000 Ksh 8250 Ksh 4875
Depending on Predicted Mortality Index reading in two potential payout periods
across the year, he receives indemnity payment
(KSh) = (predicted mortality rate - M*)% × insured value
Index: Payout rate Total amount paid =
Predicted payout rate*insured value
Mortality
5% 0% 0%*150,000=0 Ksh
15% 15%-15%=0% 0%*150,000=0 Ksh
25% 25%-15%=10% 10%*150,000=15,000 Ksh
35% 35%-15%=20% 20%*150,000=30,000 Ksh

26. Establishing Informed, Effective Demand
Experimental IBLI Game
(i) Teach how IBLI works and how IBLI can affect herd dynamics
(ii) Game with real monetary stakes. Pretested in 2008.
(iii) Used lessons from Game to design extension training program

27. Establishing Informed, Effective Demand
Willingness to pay (WTP) experiments using
contingent valuation methods

28. IBLI Contract Sales Figures for Jan/Feb 2010
SHEEP/
TOTAL
VALUE
TO
VALUE
OF
CATTLE
CAMELS
PREMIUM
CONTRACTS
GOATS OF
INSURED
COLLECTED
NO.
NO.
RATE SOLD NO.
LIVESTOCK PREMIUMS
INSURED INSURED
INSURED (USD) (USD)
UPPER 5.5% 556 371 11,081 185 347,620 19,119
LOWER 3.25% 1,423 3537 4,745 154 845,460 27,477
TOTAL 1,979 3908 15,826 339 1,193,080 46,597
• Note:
• Consumer premium rate not total market premiums which
are 9.2% in upper and 5.4% in lower.

29. The Marsabit Pilot Establishing Demand
Some preliminary statistics from WTP study
(1) Proportion of respondents whose WTP exceed the pure premium, and
pure premium+20% loading:
10% Strike 30% Strike
Pure Premium 20% loading Pure Premium 20% loading
50% 34% 69% 69%
(2) And for respondents whose WTP exceeds the pure premium…
Proportion of herd that respondents would like to insure:
Contract type Proportion of Herd would like to insure
1/4 1/2 3/4 Full
10% strike 18% 24% 13% 45%
30% strike 4% 17% 18% 62%