Index Insurance to Enhance Productivity and Incomes for Small-scale Agricultural and Pastoral Households in Kenya & Mali Chris Barrett Michael Carter Andrew Mude International Livestock Cornell University University of California, Davis 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 Marsabit with an index insurance product. - Availability of household data allows precise contract design. -Availability of potential sales delivery infrastructure 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 Index • Livestock Response • Predicted Mortality Function Livestock • NDVI Mortality Testing the Index Performance • Performance of “Predicted Mortality Index” in predicting area- average 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 20% Actual 10% 0% 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Vs. Predicted Seasonal Mortality Rate - Chalbi Cluster 50% 40% 30% Predicted 20% Actual 10% 0% 1986 1997 2008 1982 1983 1984 1985 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2009 2010 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 NDVI- DUKANA EL-HADI DARADE FUROLE Livestock Mortality BALESA NORTH HORR HURRI HILLS Response Functions MOITE EL GADE GALAS KALACHA MAIKONA GAS LOIYANGALANI TURBI ARAPAL LARACHI KURUGUM OLTUROT MT. KULAL BUBISA MAJENGO(MARSABIT) •Five Separate Index KARGI JIRIMEQILTA HULAHULA SAGANTE KURUNGU OGUCHODIRIB GOMBO KITURUNI SONGA KARARE JALDESA Coverage Regions SHURA SOUTH HORR(MARSA)HAFARE KAMBOYE KORR ILLAUT(MARSABIT) LOGOLOGOGUDAS/SORIADI LONYORIPICHAU NGURUNIT LAISAMIS LONTOLIO KOYA IRIRMERILLE 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) Legend ILLERET SABARET MarsabitIBLI DUKANA HSNP, IBLI Game_HSNP, No IBLI Game No IBLI EL-HADI FUROLE HSNP, IBLI Game DARADE BALESA Game NORTH HORR HURRI HILLS HSNP, No IBLI Game MOITE GALAS EL GADE No HSNP, IBLI Game HSNP 4 sites 4 sites GAS KALACHA MAIKONA No HSNP, No IBLI Game LOIYANGALANI TURBI ARAPAL LARACHI KURUGUM No 5 sites 3 control OLTUROT MT. KULAL MAJENGO(MARSABIT) KARGI JIRIMEQILTA BUBISA HSNP sites KURUNGU HULAHULA SAGANTE OGUCHODIRIB GOMBO KITURUNI SONGA KARARE JALDESA SHURA SOUTH HORR(MARSA)HAFARE KAMBOYE KORR ILLAUT(MARSABIT) Sample selection: 924 households LOGOLOGOGUDAS/SORIADI LONYORIPICHAU NGURUNIT LAISAMIS LONTOLIO • Sample/site proportional to relative pop. sizes 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 long- run, 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 50 Prob. = 0.03 Expected herd size 10 years ahead Prob. = 0.06 40 Implication: 30 Need to alter herd Prob. = 0.12 dynamics to cope with 20 increasing drought risk. IBLI is one possible tool 10 to avert collapse. 0 0 10 20 30 40 50 60 Initial herd size 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 • In Mali, smallholders leave • Instead can reduce variability significant „money on the while increasing mean income 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!
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