1. ILRI Campus, Addis Ababa, 24-26 June 2019
Designing index-based insurance for livestock
Francesco Fava
International Livestock Research Institute
INDEX-INSURANCE FOR LIVESTOCK IN THE IGAD REGION MINISTERIAL POLICY ROUNDTABLE & TECHNICAL WORKSHOP
ILRI Campus, Addis Ababa, June 2019 1

2. Rationale for livestock Insurance
GOAL - Offer a timely, sustainable, safety net against catastrophic drought shocks
Provide an opportunity for early response
Prevent vulnerable to fall into poverty trap by losing their key productive assets.
Crowd-in investments from the private sector.

3. What is Index-insurance
Conventional insurance
Loss Claim Verification Indemnity
Very high transactions costs for verification, etc.
Moral hazard
Index-based insurance
It does not insure individual losses
It is based on an “index” strongly correlated with impacts (no claims)
The Index is objectively verifiable, available at low cost

4. The Index-based livestock Insurance (IBLI)
IBLI R&D agenda launched,
First commercial product offered in Marsabit by a consortium of private partners
drought triggered contracts in all covered areas serving as an important proof- of-concept indicator.
IBLI began to scale in Kenya beyond pilot site in Marsabit into Isiolo. Program launched in Ethiopia

5. The Index-based livestock Insurance evolution
Kenya Livestock Insurance Program (KLIP) issues first policies to 5000 pastoralist households across Wajir and Turkana.
KLIP has further scaled provision of IBLI across 8 counties (18k households)
Increasing momentum toward scale, particularly with substantial payouts (over 7 million USD) in 2016/2017
Government of Ethiopia discussing scaling IBLI program, design efforts in Uganda, Somalia, Niger and Senegal

6. Pillars
HOW A GOOD SCIENTIFIC IDEA BECOMES AN EFFECTIVE OPERATIONAL PROGRAM?
Precise contract design;
2. Evidence of value and impact;
3. Establishing informed effective demand;
4. Low cost, efficient supply chain;
5. Policy and institutional infrastructure.

7. Index Insurance is a variation on traditional insurance
How Index-Insurance works
Index Insurance is a variation on traditional insurance
Indicator (e.g. rainfall, field data, NDVI, etc.)
Index (correlated with the risk)
Payouts/Indemnities
WHY SOME DESIGN WORK?
AND SOME OTHERS NOT?

8. 1. Satellite Indicators Rainfall Station-data limited Accuracy issues
Meteorological drought
Vegetation indices
NDVI (or EVI, fAPAR)
Available from many satellites
Agricultural drought
Alternatives indicators
Soil moisture
Evapotranspiration (from LST)
cimss.ssec.wisc.edu

9. 1. Satellite Indicators - NDVI
NIR
red
Indicator of the presence/amount of green vegetation

10. 2. Index design The Asset Replacement Index Design
Response Function: livestock mortality data modelled from NDVI
Asset Replacement: Pays out when livestock deaths are predicted in an area based on an empirical function
Nice but…
Limited mortality data availability for scaling-up, issues with data accuracy
Why replacing rather than protecting livestock (much cheaper)?
NDVI
Response Function
Mortality
Chantarat, Mude, Barrett and Carter (2013, JRI)

11. Standardization and deviation from ‘historical’ mean
2. Index design
The Asset Protection Index design
Response function:
Pays out when forage availability during the rainy season is lower then normal
 ealier!
Asset protection
It insures the cost of keeping the animal alive
lower!
Data for calibration are not necessary
Seasnal forage scarcity
Vrieling et al., 2014, IJAEG
Standardization and deviation from ‘historical’ mean
Temporal accumulating
March-June
Seasonal cumulated NDVI
Temporal aggregation
NDVI spatially aggregated
1-10 May 2011
MODIS NDVI image (10 day)
Spatial aggregation
400 km

12. 3. Payouts/Indemnities Payout function
Proportional do the severity of forage scarcity
When to trigger payouts, with what frequency, how big?
MORE PAYOUTS
Impact on premium!
LESS FORAGE

13. 3. Payouts/Indemnities KLIP Product in Kenya
Covers 5 Tropical Livestock Units for targeted households. Total covered value is Ksh 70,000
Payment triggers below 20th percentile (every 5 seasons).
Two risk periods (long rains and short rains) with payouts in June and December

14. How to design a good product?
Making the right choices
Understanding the local context, needs, drought impacts mechanisms
Use well-established and simple indicators (quality and awareness)
Design quality assessment processes and respond to stakeholders feedbacks

15. THANKS!
THANK YOU!

17. The Prosopis dilemma
Are NDVI-based Indices affected by the presence of invasive non-palatable species such as Prosopis?
NDVI is a greenness indicator. It is NOT related to the quality of forage
However, the Index is designed to minimize the impacts of species variability with the objective of detection drought.
Masking non usable areas (low interannual variability, signal or using land cover maps)
Averaging (spatially) over large areas (units): local changes in composition have minimal impacts on the averaged NDNVI
Comparing each unit with itself over time: the reference for the detection of forage scarcity is the historical average in the same location (i.e. same type of rangelands).
The argument theoretically is sound. Practically no evidences of impacts on the Index.