Sustainable livestock insurance for
pastoralists
Evidence and Insights from the Index-Based Livestock
Insurance (IBLI) programs in Kenya and Ethiopia
Andrew Mude
December 2014

There is strong evidence of
poverty traps in the arid and
semi-arid lands (ASAL) of
northern Kenya and
southern Ethiopia. These put
a premium on risk mgmt.
Catastrophic herd loss risk
due to major droughts
identified as the major
cause of these dynamics.
Source: Lybbert et al. (2004 EJ) on Boran pastoralists in s.Ethiopia.
See also Barrett et al. (2006 JDS) among n. Kenyan pastoralists,
Santos & Barrett (2011 JDE) on s.Ethiopian Boran.
Motivation: Poverty Traps And Catastrophic Risk

Motivation: Standard Responses to Drought
Standard responses to major drought shocks:
1) Post-drought restocking
2) Food aid/Cash Aid
Key Problems:
- Slow
- Expensive (in part, because it’s slow)
- Targeting challenges
- Food aid can reinforce sedentarization/foster dependency
- Core issue: If transfers go only to the poor who are already in
the poverty trap, the numbers of poor will grow as shocks
knock others below the poverty trap threshold. In the long-
run, the ex ante poor worse off as others join their ranks and
compete for scarce social assistance resources. (see Barrett,
Carter & Ikegami 2012 for more general theory/illustrations)

Livestock Insurance as an Alternative
Commercially sustainable insurance can:
• Prevent downward slide of vulnerable
populations
• Crowd-in investment and accumulation by the
poor
• Induce financial deepening by crowding-in
credit
• Let us focus humanitarian resources on the
needy
But can insurance be sustainably offered in the ASAL?
Conventional (individual) insurance unlikely to work,
especially in small scale pastoral/agro-pastoral sector:
• Very high transactions costs, esp. w/little
financial intermediation among
pastoralists
• Moral hazard/adverse selection

Index Based Livestock Insurance (IBLI)
Index insurance is a variation on traditional insurance:
- Do not insure individual losses.
- Instead insure some “index” measure that is strongly
correlated with individual losses.
(Examples: rainfall, remotely sensed vegetation index, area
average yield, area average herd mortality loss).
- Index needs to be:
- objectively verifiable
- available at low cost in real time
- not manipulable by either party to the contract

The Major Challenges of Index Insurance
1. High quality data (reliable, timely, non-manipulable, long-
term) to design/price product and to determine payouts
2. Minimize uncovered basis risk through product design. Is it
insurance or a lottery ticket? All turns on basis risk!!!
3. Innovation incentives for insurers/reinsurers to design and
market a new product and global market to support it
4. Establish informed effective demand, especially among a
clientele with little experience with any insurance, much less a
complex index-based insurance product
5. Low cost delivery mechanism for making insurance available
for numerous small and medium scale producers

The IBLI Research and Development Agenda
1) Support development of
IBLI institutions and services
to improve market
effectiveness and catalyze
informed demand
2) Design of IBLI contracts
3) Assessing behavioral change
and welfare impacts due to
IBLI
4) Researching drivers of
change in pastoralist systems
(IBLI Plus)

ILRI’s Program in Summary
• Initial IBLI work (contract design, innovations platform,
willingness to pay etc) in 2008
• From HSNP Plus (Productive Safety Net) to Commercial
Orientation
• First launched in Marsabit in January 2010 with Equity
Insurance Agency and UAP Insurance
• First payout in Marsabit in October 2011. Missed
opportunity due to various implementation challenges
• Launched in Borana Zone of S. Ethiopia in July 2012 by OIC
insurance.
• IBLI Phase II commenced in late 2012 with reorientation
toward PPP
• Revised contract in August 2013 and developed product for 11 N. Kenya Divisions.
• Contract provision extended to Isiolo and Wajir in August 2013. APA underwriting in Isiolo and
Marsabit with support from World Vision and CARE. Takaful Insurance of Africa underwriting in Wajir
with support from Mercy Corps.
• Payout in March 2014 in Wajir and some places in Isiolo and Wajir
• Working closely with State Department of Livestock and World Bank in support of GOK IBLI intentions

• IBLI survey launched in Marsabit, Kenya in Oct 2009 and in Borana, Ethiopia, Mar 2012
both before the respective launch of IBLI sales
• Marsabit survey: 925 households over 16 locations – currently 5 rounds of panel data
• Borana survey: 515 households over 17 kebeles – currently 3 rounds of panel data
IBLI Pilots, and research design, in Ethiopia and Kenya

• First contract in initial pilot site, Marsabit: Based on satellite data on
forage availability- Normalized Differenced Vegetation Index (NDVI):
Pays out when forage scarcity is predicted to cause livestock deaths in
an area. Contract is for Asset Replacement
IBLI Contract Design
1-10 May 2010 good vegetation 1-10 May 2011 bad vegetation
Normalized difference vegetation index (NDVI)

• Response Function: Regress historic livestock mortality data onto
transformations of historic cumulative standardized NDVI.
• In Borana, contract more precisely defined as a forage scarcity
contract: only based on transformations of NDVI
• Ethiopia contract much simpler to develop, explain and scale up:
however, cannot define “basis risk” of a forage scarcity contract
DATA
Response
Function Index
IBLI Contract Design

Covariate risk is important but
household losses vary a lot …
and the index does not
perfectly track covariate losses.
- Only such study of index-insurance products that we know off. Crucial for
assessing value and precision of the contract.
Jensen, Barrett & Mude 2014
IBLI Marsabit Contract: An Imperfect Product

IBLI Contract Design Evolution (Northern Kenya)
• For scale out, needed to design IBLI contracts for
11 additional northern Kenyan districts.
However, available mortality data less complete
than for Marsabit.
• Employed spatial methods to fill in missing
mortality observations and estimated spatially-
explicit division-specific index response
functions (Woodard et al., JRI, 2014)
• Improved remote sensing data and processing
algorithms (Vrieling et al., IJAEOG 2014)
• Model has performed dismally in contract sites (Marsabit, Isiolo, Wajir)
• Agreement to move away from predicted mortality contracts to forage
scarcity contracts similar to Borana, S. Ethiopia.
• Also working with the GoK/WB to design NDVI-based asset protection
contracts. Our insurance partners also interested.

IBLI Uptake Significant … But So Is Disadoption
Marsbit survey respondents uptake patterns (n=832)
Sales window New1
Replace-
ment2
Augment-
ing3
Hold-
ing4 Reenter5 Lapsed6 Total7
J-F 2010 233 0 0 0 0 0 233
J-F 2011 65 62 0 0 0 171 298
A-S 2011 65 0 31 96 22 149 363
A-S 2012 19 25 0 0 33 305 382
1First time purchasers. 2Replaced a policy about to expire. 3Purchased additional coverage that
overlapped with existing coverage. 4No purchase but had existing coverage. 5Let policy lapse for at
least one season but purchased this season. 6Past policies have lapsed and did not purchased
additional coverage.7Total number of households that have purchased to date.

Capacity to predict uptake patterns is reasonably strong:
Unconditional observed / predicted
(Cond. FE) likelihood of buying IBLI
Observed / predicted (Cond. FE) level
of purchases (|buying IBLI)
IBLI Uptake Significant …

Key determinants of IBLI uptake
General uptake findings — robust across specifications and surveys
Price: Responsive to premium rate (price inelastic). Price elasticity grows
w/design risk.
Design Risk: Design error reduces uptake; greater effect at higher premium rates.
Idiosyncratic Risk: Hh understanding of IBLI increases effect of idiosyncratic risk
Understanding: Extension/marketing improves accuracy of IBLI knowledge but no
independent effect of improved understanding on uptake.
Herd size: Likelihood of uptake increasing in HH herd size
Liquidity: IBLI purchase increasing w/HSNP participation and HH savings
Intertemporal Adverse Selection: HHs buy less when expecting good conditions.
Spatial Adverse Selection: HHs in divisions with covariate risk are more likely to
purchase and with greater coverage (spatial adverse selection).
Gender: no gender diff in uptake. Women more sensitive to risk of new product.
Bageant 2014; Jensen, Mude & Barrett 2014; Takahashi et al. 2014

Implementing IBLI: Into the real world
Implementation of IBLI is a joint effort between ILRI (with support of
its technical and development partners), commercial underwriters
and implementing partners on the ground (government, NGOs, CBOs
etc).
CAPACITY DEVELOPMENT, EXTENSION, MARKETING, SALES

Implementing IBLI: Challenges and Debates
• Initial push for commercial sustainability was met with the challenge of low sales.
• Variety of reasons for low sales: Implementation is complex and more still with
microinsurance in the challenging terrain of N. Kenya and Southern Ethiopia.
• Can we get to a critical mass of IBLI adoption necessary for sustaining the industry
without consistent public support at the early stages?

The Challenge of Sustainability
Commercial
Viability
Productive
Social Safety Net
• International experience shows that agricultural insurance programs that have
scaled up have strong public and private sector pillars, as part of overall agriculture
risk management strategy
• Research showing positive social and economic impacts provide some justification
for public support.

IBLI Impacts: Herd mortality risk
Proportion of households for whom IBLI improves their
position with respect to each statistic
Jensen, Barrett & Mude 2014
Statistic Proportion
Loaded &
Unsubsidized
Subsidized
Mean 0.232 1.000
Variance 0.359 0.359
Skewness 0.817 0.817
Semi-Variance 0.374 0.609

IBLI Impacts: Livestock productivity/income
IBLI coverage:
•Increases investments in
maintaining livestock through vet
expenditures
•Increases total and per TLU income
from milk.
Note: TLU veterinary expenditures are
pos/sign related to milk productivity
IBLI (FE-IV)
Production strategies:
Herd Size -2.639
(2.190)
[0.079]
Veterinary Expenditures (KSH) 592.1**
(295.2)
[0.090]
Household is Partially or Fully Mobile 0.184
(0.142)
[0.247]
Production outcomes:
Milk income (KSH) 4,605**
(1,995)
[0.161]
Milk income per TLU (KSH) 671.3***
(197.8)
[0.170]
Livestock Mortality Rate (X100) -0.0466
(0.0512)
[0.175]
A complete list of covariates, coefficient estimates, and model
statistics can be found in Jensen, Mude & Barrett (2014). Clustered
and robust standard errors in parentheses. R2 in brackets. ***
p<0.01, ** p<0.05, * p<0.1.
Jensen, Mude & Barrett 2014

IBLI Impacts: Less adverse post-drought coping
Janzen & Carter 2013 NBER
Marsabit HHs received IBLI indemnity payments in October 2011,
near end of major drought. Survey HHs with IBLI coverage report
much better expected behaviors/outcomes than the uninsured:
- 36% reduction in likelihood of distress livestock sales, especially
(64%) among modestly better-off HHs (>8.4 TLU)
- 25% reduction in likelihood of reducing meals as a coping
strategy, especially (43%) among those with small or no herds
IBLI appears to provide a flexible safety net, reducing reliance on
the most adverse behaviors undertaken by different groups.

IBLI Impacts: Household subjective well-being
Borana survey HHs report subjective well-being
In principle, insurance helps risk averse people even when it doesn’t pay
out. But an imperfect product with commercial loadings might not.
Subjective well-being measures to assess welfare gains even w/o
indemnities.
• IBLI has a positive, stat sig effect on HH well-being, even after premium
payment and w/o any indemnity payments
• IBLI coverage for 5 TLU moves a HH 1 step up the SWB scale
• Ex post of contract, purchasers exhibit some buyer’s remorse in the absence
of indemnity payments.
• But the positive effect of IBLI coverage is significantly higher than the
negative effect of buyer’s remorse.
Hirfrot , Barrett, Lentz and Taddesse. 2014

• Although IBLI offers incomplete and imperfect coverage against herd loss, IBLI has
clear favorable impacts on purchasers.
• IBLI offers a promising option for addressing pastoralist vulnerability and poverty
arising from catastrophic drought risk.
• Positive impact results help provide strong evidence base in support of public
support to insurance programs covering drought risk for pastoralist
• IBLI can, in principle, offer a timely, sustainable, safety net against catastrophic
drought shocks. Can help accelerate herd recovery and reduce human suffering.
• ILRI working together with World Bank’s Agricultural Insurance Development
program to support Government of Kenya’s effort to rollout the Kenya Livestock
Insurance Program (KLIP) for Kenya’s pastoralists
• Critical to the success of the KLIP will be capacity building across the various key
actors in the value chain and a comprehensive extension and sensitization
campaign
Summarizing IBLI Program

Other Key Complementary Activities for 2015
• Developing Web-based Systems Automating IBLI Contract Design, Index
Updates, Information Provision
• Using ICT/Mobile-applications to assess impact of extension and
monitoring interventions for IBLI sales agent
• Developing the Extension and Capacity Agenda for the Kenya Livestock
Insurance Program Agenda
• Crowd-Sourcing of Rangeland Conditions
• Investigating other related research topics
• Livelihood portfolio diversification
• Livestock market integration
• Forage and feed supplementation markets
• Village livestock banking

Crowd-Sourcing Rangeland Conditions
• OVERVIEW:
1. There is a need for higher temporal and spatial resolution data on the
environmental conditions and nutritive value of rangelands to improve the
information content with receive from satellite-based data.
2. As mobile technologies and networks improve, it raises the possibility of live
crowd-sourcing such information on a board scale.
• PROJECT OBJECTIVE:
• Citizen Science proof-of-concept to understand how we may incentives pastoralists
to provide regular, accurate, real-time, micro-level data on the conditions of the
rangelands.
• POTENTIAL OUTPUTS:
1. Identify spectral signatures that ca be used to develop filters for remotely sensed
data for the purpose of improve IBLI design.
2. Dataset that can feed into research on topics such as land use, resilience, social
coordination and interaction, resource selection, citizen science, extension etc.
3. Forage condition maps that can update in near-real time for pastoralists’ herd and
range management and for agencies’ early warning systems.

Crowd-Sourcing Rangeland Conditions
Conceptual Approach for Developing Rangeland Conditions Model

Procedural Approach for Developing Rangeland Conditions Model
Crowd-Sourcing Rangeland Conditions

Web-Based Contract Design and Assessment Tool
• TASK:
• Build a Web-Based Platform to: automate data receipt and index updating
procedures; automate contract-related information dissemination protocols
across a range of output and format types; and allow for real time analysis
of contract performance
• Key Work Elements:
1. Index Automation Module: Provide near-real time automated updates on
the status of the index across all program areas.
2. Contract Design and Assessment Module: Develop functionality that
allows users to manipulate various contract features and test their impact
on key contract parameters
3. Information Provision and Dissemination Module: Allow for index and
other relevant program data to be regularly updated, queried and
disseminated in a suite of output types to be jointly agreed with the
project team.

For related information, visit www.ilri.org/ibli
Thank youMany thanks for your support, interest and
comments
STAY TUNED!