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, 24-26 June 2019 1

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.

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

The Index-based livestock Insurance (IBLI) 2008 - IBLI R&D agenda launched, 2010 - First commercial product offered in Marsabit by a consortium of private partners 2011 - drought triggered contracts in all covered areas serving as an important proof- of-concept indicator. 2012 - IBLI began to scale in Kenya beyond pilot site in Marsabit into Isiolo. Program launched in Ethiopia

The Index-based livestock Insurance evolution 2015 - Kenya Livestock Insurance Program (KLIP) issues first policies to 5000 pastoralist households across Wajir and Turkana. 2016 - KLIP has further scaled provision of IBLI across 8 counties (18k households) 2017 - Increasing momentum toward scale, particularly with substantial payouts (over 7 million USD) in 2016/2017 2018 - Government of Ethiopia discussing scaling IBLI program, design efforts in Uganda, Somalia, Niger and Senegal

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.

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?

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

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

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)

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

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

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

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

THANKS! f.fava@cigar.org THANK YOU! f.fava@cgiar.org

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.