Index Insurance to Enhance Productivity and
Incomes for Small-scale Agricultural and
Pastoral Households in Kenya & Mali
Chris Barrett
Michael Carter
Andrew Mude
Cornell University
University of California, Davis
International Livestock
Research Institute
Ag Sector Council Seminar Series
Washington, D.C.11 May 2011
The “Same Old Story” about Risk
• Commenting on the Feed the Future research strategy, Thomas
Lumpkin (DG of CIMYT) noted that small holders are currently only
getting 30% of the yields potentially available with already existing
technologies
• Why is this? Risk is a big part of the story
• Risk that is high and correlated across individuals creates a number
of development problems for small farm agriculture:
– Directly discourages investment in profitable, but costly innovations
– Undercuts the development of agricultural credit markets, forcing
families to rely on autarchic financial strategies, increasing liquidity
constraints and further undercutting investment
– Together these two forces undercut productivity, reduce growth and
make people poorer than they need be given the available
opportunities.
– Finally, risk and the absence of deep credit markets contribute to the
inter-generational transmission of poverty, lessening the long-term
human development impacts of even those incomes and growth that
are achieved.
The “Same Old Story” about Risk
• Wreckage of past agricultural credit market interventions
proves that simply cannot legislate these markets into
existence
• So is there another approach that might create a happier
ending to the seemingly inevitable story about risk and
smallholder agriculture?
• Our work begins with the idea that we can change the
ending if we can change a key structural condition
(uninsured, correlated risk) that underlies it
• As we will see, a number of technical & financial
innovations open the way for the innovation of ‘index
insurance contract’ to transfer this correlated risk out of
the system
• The goal is not to sell insurance per se, but to solve the
development problems of low growth and human
vulnerability that make risk matter
Crafting a New Ending to this “Same Old Story”
• With generous funding from USAID and other donors,
the Index Insurance Innovation Initiative (I4) is designing
& implementing pilots focused on boosting investment
and growth in:
– Small scale commercial agriculture (Cotton in Mali, Coffee in
Guatemala, Cacao in Cote d’Ivoire)
– Small scale food agriculture (Grains in Ethiopia; Rice in Ecuador; Maize
in Tanzania; Livestock in Ethiopia)
• Return to discuss these growth-oriented uses of index
insurance, but first let’s elaborate the basic concepts
using the example of index insurance as a productive
social safety net
The Genesis of Index Based Livestock Insurance
• Several years ago, DfID began to launch a cash transfer scheme
targeted at the indigent ‘failed’ pastoralist populations in Northern
Kenya where as much as 40% of the population may live on less than
$0.25/day
• Our question to DfID: If you
would pay $15/indigent family
per-month, would you pay
$7/year to keep a vulnerable
family from becoming indigent?
• While this appears as an aid
value proposition for DfID, our
bigger point is that index
insurance can be a productive,
value proposition for insured
pastoralist families
• Andrew and Chris will now
explain the operation and logic of
this project in more detail
• Or, see the movie version:
http://blip.tv/file/3757148
Piloting IBLI in Northern Kenya
• But can insurance (of any type) be sustainably offered in rangelands?
• Conventional (individual) insurance unlikely to work, especially among
pastoralists:
– Transactions costs
– Moral hazard/adverse selection
• 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
Piloting IBLI in Northern Kenya
• Pilot represents one of the efforts to test the risk-management promise
of Index-Based Insurance.
•
Why a Livestock Index in Northern Kenya?
-Pastoral production is key livelihood
facing a risk profile suitable for targeting
with an index insurance product.
- Availability of household data allows
precise contract design.
-Availability of potential sales delivery
infrastructure
Marsabit
Designing the Index
• Find a reliable, objectively verifiable signal, that explains most of the
variation in household’s seasonal livestock mortality
– We use functions of NDVI, a remotely sensed proxy for forage availability.
• Model a relationship between the risk to be insured (area-average
livestock mortality) and the driving signal (NDVI):
DATA
• Livestock
Mortality
• NDVI
Index
Response
Function
• Predicted
Livestock
Mortality
Testing the Index Performance
• Performance of “Predicted Mortality Index” in predicting areaaverage livestock mortality observed in ALRMP
– Out-of-sample prediction errors within 10% (especially in bad years)
– Predicts historical droughts well
Out of sample
Actual Vs. Predicted Seasonal Mortality Rate - Laisamis Cluster
50%
40%
30%
Predicted
Actual
20%
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
0%
1982
10%
Actual Vs. Predicted Seasonal Mortality Rate - Chalbi Cluster
50%
40%
30%
Predicted
Actual
20%
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
0%
1982
10%
Contract Features
• SPATIAL COVEARGE
– How wide a geographic area can a single index-cover?
– What is the spatial precision range of the response function?
– At what level of resolution is the necessary data available?
SABARET
ILLERET
•Two Separate NDVILivestock Mortality
Response Functions
DUKANA
EL-HADI
DARADE
FUROLE
BALESA
NORTH HORR
HURRI HILLS
MOITE
EL GADE
GALAS
KALACHA
GAS
MAIKONA
LOIYANGALANI
TURBI
ARAPAL
LARACHI
KURUGUM
OLTUROT
MT. KULAL
•Five Separate Index
Coverage Regions
KURUNGU
BUBISA
MAJENGO(MARSABIT)
KARGI
JIRIMEQILTA
HULAHULA
SAGANTE
OGUCHODIRIB GOMBO
KITURUNI
SONGA
KARARE JALDESA
SOUTH HORR(MARSA)HAFARE
KAMBOYE
KORR
ILLAUT(MARSABIT)
LOGOLOGOGUDAS/SORIADI
LONYORIPICHAU
NGURUNIT
LAISAMIS
LONTOLIO
KOYA
IRIRMERILLE
SHURA
Contract Features
• TEMPORAL COVEARGE
– Over what time span should the index cover?
– Function of the production system being modelled?
– Administrational and liquidity considerations?
Contract Features
• RISK COVERAGE AND PRICING
• Need to select an index strike point to trigger indemnity
– Trade off: Higher Strike  Lower Risk Coverage  Lower Cost
– Conditional or Unconditional?
– Payoff structure: Linear, Segmented, All or Nothing, No claims bonus?
Contract Cluster
Consumer Price
Upper Marsabit
5.5%
Lower Marsabit
3.25%
Implementation
• Launched in January 2010 in collaboration with commercial
partners.
• Two sales periods of varying experience
– Jan/Feb 2010: Sold ~2000 contracts: Premiums collected ~ $46,000: Value
of livestock covered ~$1,200,000
– Jan/Feb 2011: Sold ~750 contracts: Premiums collected ~ $9,500
• Key ongoing considerations/challenges:
•
Delivery Channel
•
Extension/Education
•
Information Dissemination and Trust Building
•
Regulation
Impact Assessment
 Site selection: 16 sites
Confounding factor: ongoing implementation of cash transfer (HSNP)
Encouragement design
•Insurance education game: played among 50% sample in game site
•Discount coupon of the first 15 TLU: (no subsidy for 40% of sample,
10%-60% subsidies for the rest)
MarsabitIBLI
SABARET
ILLERET
DUKANA
IBLI Game
No IBLI
Game
4 sites
4 sites
HSNP, IBLI Game_HSNP, No
EL-HADI
HSNP, IBLI Game
DARADE
FUROLE
BALESA
HSNP, No IBLI Game
NORTH HORR
HURRI HILLS
MOITE
HSNP
Legend
No HSNP, IBLI Game
EL GADE
GALAS
KALACHA
GAS
No HSNP, No IBLI Game
MAIKONA
LOIYANGALANI
TURBI
ARAPAL
LARACHI
KURUGUM
No
HSNP
5 sites
3 control
sites
 Sample selection: 924 households
• Sample/site proportional to relative pop. sizes
OLTUROT
MT. KULAL
BUBISA
MAJENGO(MARSABIT)
KARGI
JIRIMEQILTA
HULAHULA
SAGANTE
OGUCHODIRIB GOMBO
KURUNGU
KITURUNI
SONGA
KARARE JALDESA
SHURA
SOUTH HORR(MARSA)HAFARE
KAMBOYE
KORR
ILLAUT(MARSABIT)
LOGOLOGOGUDAS/SORIADI
LONYORIPICHAU
NGURUNIT
LAISAMIS
LONTOLIO
KOYA
IRIRMERILLE
•For each site, random sampling stratified by livestock wealth class (L, M, H)
IBLI and the Escape from Poverty Traps
Strong prior evidence of poverty traps
in the arid and semi-arid lands (ASAL)
of east Africa
Standard humanitarian response to
shocks/destitution: food aid.
But if transfers go only to the poor who
are already in the poverty trap, the
numbers of poor will grow. In the longrun, today’s poor grow worse off as the
unnecessarily poor join their ranks and
compete for scarce and insufficient
transfers.
Herd wealth dynamics in southern Ethiopia
Source: Lybbert et al. Econ. J. 2004
IBLI and the Escape from Poverty Traps
In theory, sustainable livestock insurance for pastoralists can:
• Prevent downward slide of vulnerable populations
- Enables concentrating humanitarian resources on
those truly unable to lift themselves from poverty
• Stabilize expectations and crowd-in investment and
accumulation by poor populations
What we hope to learn via careful impact evaluation of IBLI
1) For whom is IBLI most attractive and effective?
- simulation-based answer: IBLI most valuable among the
vulnerable non-poor
- simulation-based and WTP survey based answer: Highly price
elastic demand for IBLI
Research objective 1: Use survey data to test these hypotheses
in quasi-experimental setting with real insurance.
Policy question: Potential for targeted subsidies of IBLI as a
productive safety net?
What we hope to learn via careful impact evaluation of IBLI
2) Does IBLI induce increased asset accumulation and escapes
from poverty? Does it reduce asset loss and falls into poverty?
How does it perform relative to cash transfers? Are there spillover
effects on the stockless poor?
-simulation-based answers: Yes on first two points. Don’t know
on latter two questions.
Research objective 1: Use survey data to test these hypotheses
in quasi-experimental setting with real insurance in a survey
designed to test IBLI and cash transfers under Kenya’s new
Hunger Safety Nets Program.
Policy question: Which instrument performs best in terms of
poverty reduction and economic growth? Are IBLI and HSNP
complements or substitutes?
IBLI in the Face of Climate Change
Arid and semi-arid lands (ASAL) comprise ~ 2/3 of Africa,
home to ~20 mn pastoralists - extensive livestock grazing.
Pastoralist systems adapted to climate regime, but vulnerable
to drought. Rapid shift in climate could bring catastrophe.
An implication of most climate change predictions is increased
rainfall variability, so increased risk of drought.
IBLI in the Face of Climate Change
Herd dynamics differ markedly between good and poor rainfall
states. As a result, herd dynamics change with drought (rainfall
<250 mm/year) risk. Halving the current risk would enhance
resilience and eliminate apparent poverty trap. By contrast,
doubling drought risk would lead to system collapse in expectation.
60
Prob. = 0.03
Expected herd size 10 years ahead
50
Prob. = 0.06
40
Implication:
Need to alter herd
dynamics to cope with
increasing drought risk.
IBLI is one possible tool
to avert collapse.
30
Prob. = 0.12
20
10
0
0
10
20
30
Initial herd size
40
50
60
Source: Barrett and Santos, 2011
From Protection to Growth: Gueleya Nyesigi in Mali
• IBLI illustrates the development
benefits from stabilizing livelihoods
• The the I4/PlaNet Guarantee project
in Mali illustrates the growth potential
of index insurance
• Key insight: Interlinking insurance
with growth opportunity
• Avoids the tradeoff of reduced
variability at the cost of reduced
average income
• Instead can reduce variability
while increasing mean income
• In Mali, smallholders leave
significant ‘money on the
table’ every year by planting
only 1 hectare in cotton
• An interlinked contract that
crowds in supply & demand
for credit for that 2nd hectare
of cotton can create growth
• Requires a high quality
contract that is understood
From Protection to Growth: Contract Design
• Credit supply in
Mali is currently
generously, if
unsustainably,
supplied through a
parastatal
infrastructure
• Yet small farmers
remain reluctant to
borrow under
group credit
scheme
• Working with
farmers, I4
researchers
designed a novel
contract approach
• Identified farmer “loss aversion focal point” of
750kg/hectare
• Devised a double trigger contract that radically
reduces basis risk while protecting against
moral hazard
From Protection to Growth: Farmer Education
• Even a good contract will
have no impact on
growth if neither trusted
nor understood
• Building on IBLI, the Mali
team is employing
games, a network of
VIPs, and a variety of
user-friendly educational
material
• Outreach implemented
by Oxfam and its local
partners
• Contract on sale now
• Using a spatially randomized rollout, will be
monitoring whether insurance crowds in
greater entrepreneurial risk taking
• Next challenge will be when credit supply
shifts following privatization
In Summary …
• As researchers, we are excited by the potential of index insurance to
provide a new ending to an old story about risk
• While built on a number of technical and contractual innovations,
these two & the other I4 projects are all implemented by commercial
partners
• This modality opens the door to scale up of these ideas
• I4 has upcoming, industry- & government-oriented outreach events
in East Africa and the Andean region
• While we are keen to share what we have learned, we are also
acutely aware of the need to monitor the impacts of our work on
human development and agricultural growth
• Stay tuned!