WEATHER INSURANCE DERIVATIVES TO PROTECT RURAL LIVELIHOODS International Workshop on Agrometeorological Risk Management New Delhi, India 26 October 2006 Ulrich Hess Chief of Business Risk Planning, WFP
OVERVIEW Why Weather Insurance What is a Weather Insurance/Derivative Policy implications Case Study: Livelihood Protection Risk Financing Role of AgroMet Services What s next: pushing the frontier of weather risk management
WHY WEATHER INSURANCE GROWTH Access to finance Allows for specialization pursuit of higher return activities Signals cost of risk to farmers EQUITY Safety net function Accessible to smallholders
FUNDAMENTALS Weather shocks drive yield losses and emergency needs
HOW WEATHER INDEX INSURANCE WORKS Payout structure for hypothetical rainfall contract Payout Rainfall index in mm
AHABOBNAGAR, AP 2003: BIRTH F MODERN WEATHER INSURANC
Farmers in Pamireddypally
Basis Risk manageable Index Insurance offers superior risk protection: overcomes moral hazard and adverse selection problems, o but suffers from basis risk Success factor: accurate and sustainable index Index Insurance trades basis risk for transaction costs
Weather Index insurance markets THE CURRENT MARKET MARKETS AND PROJECTS
Results Total Notional Value of weather risk contracts: 2000/1-2005/6 (in millions of U.S. dollars) $50,000 $45,000 $40,000 $35,000 $30,000 $25,000 $20,000 $15,000 $10,000 $5,000 $0 $45,244 $9,697 $2,517 $4,339 $4,188 $4,709 2000/1 2001/2 2002/3 2003/4 2004/5 2005/6 CME Winter CME Summer OTC Winter OTC Summer Note: CME Notional Values for all years have been revised to reflect CME-reported values.
Distribution of Total Number of Contracts Results by Region: 2000/1 2005/6 (Excluding CME Trades) 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1,000 Other Europe Asia NA South NA East NA Mwest NA West 500 0 2000/1 2001/2 2002/3 2003/4 2004/5 2005/6
Total Notional Value of weather risk contracts: 2000/1-2005/6 (in millions of U.S. dollars) $50,000 $45,244? $45,000 $40,000 $35,000 $30,000 $25,000 $20,000 $15,000 $9,697 $10,000 $2,517 $4,339 $4,188 $4,709 $5,000 $0 2000/1 2001/2 2002/3 2003/4 2004/5 2005/6 CME Winter CME Summer OTC Winter OTC Summer
Distribution of Inquiries about Weather Risk Instruments, by Sector of Potential End-User 2005 Survey 2006 Survey 7% 5% 4% 69% 2% 13% Energy Agriculture Retail Construction Transportation Other 12%
POLICY IMPLICATIONS I Clarity Regulatory Communication with end-users Data Integrity of weather data Integrity of indices Market Linkages Credit inputs
WEATHER INSURANCE IMPACT? Research Design Authors: WB DECRG (Gine), Prof. Townsend, ICRISAT 2004: Household survey of 1052 households in selected villages. 2005: Mini-survey, follow-up of the same households from 2004. 2006: Direct randomized marketing of insurance to households and follow-up surveys.
Anantapur Mahabubnagar Andhra Pradesh
Survey Results Why did households buy? Frequency by reason no. 1st 2nd 3rd average Security/risk reduction 139 53 20 40.1% Need harvest income 25 62 12 15.6% Advice from progressive farmers 17 28 12 8.8% High payout 9 27 11 6.8% Other trusted farmers purchased 16 11 16 6.3% Low premium 17 10 6 5.7%
Survey Results Why did households not buy? Frequency by reason no. 1st 2nd 3rd average Do not understand product 45 59 11 24.9% No cash / credit to pay premium 58 21 11 21.4% Rain gauge too far away 38 39 9 19.0% Too expensive 32 23 7 14.1% No castor, groundnut 13 6 1 4.9%
POLICY IMPLICATIONS II: CONTINUUM ACROSS OBJECTIVES AND PLAYERS Growth Australia, US, Europe Ontario, Canada Alberta, Canada NAIS, India Rajasthan subsidized WI for orange farmers India: Salt Producer Public 2003: AP weather insurance for subsistence farmers Private Ethiopia: Drought Insurance for Livelihood Protection UP subsidized drought disaster insurance Equity
CASE STUDY ETHIOPIA: FINANCING EMERGENCY RISK Understand, reduce and actively manage risks to protect vulnerable people s livelihoods and rural development gains We should be managing risks instead of managing crises! - Dr Aberra Deressa, Ministry of Agriculture and Rural Development of Ethiopia
PROBLEM TIMING OF INTERVENTIONS Ethiopian Highlands Emergency Appeal Emergency Needs Assessment Life Saving Interventions (mostly food) Aug Sept Oct/ Dec Jan Nov 2007 Feb Mar Apr May June July Aug
RATIONALE CONTEXT: The Ethiopian safety net programme promotes the livelihoods of 8.3 million people, while the humanitarian appeals system functions to save lives in emergencies. PROBLEM: Up to 5 million livelihoods of transient food insecure people may be lost under the current system APPROACHING A SOLUTION: Predictable funding to protect vulnerable people s livelihoods.
PROBLEM TIMING OF INTERVENTIONS Emergency Appeal Emergency Needs Assessment Enrolment of LHP Beneficiaries Life Saving Interventions (mostly food) Support of transient food insecure population Aug Sept Oct/ Dec Jan Nov 2007 Feb Mar Apr May June July Aug
APPROCHING A SOLUTION PART I: DROUGHT INSURANCE PILOT Contingency funding established through transaction with Reinsurer AXA Re Data flow secured through National Meteorological Agency (NMA) capacity building Drought index accurately tracks agricultural season Implementation Rulebook designed by Government of Ethiopia
ETHIOPIA DROUGHT INDEX 17 th ten day period 11-20 June 50% Correlation 1984 2002 2002 2006
LESSONS LEARNED SO FAR Pilot Drought Insurance Project demonstrated: it is possible to develop objective, timely and accurate indices for triggering drought response; it is feasible to use markets to finance drought risk in Ethiopia; contingency plans can better be designed with predictable resources.
RISK MANAGEMENT FRAMEWORK II. Build a Livelihood Protection Index (LPI) III. Develop budgeted contingency plans Early Warning System with reliable baseline and trigger points Contingency Planning for appropriate and timely response I. Establish timely emergency financing through use of contingency financing Ex-Ante Financing of contingency plans Capacity Building for effective IV. plan Build planning and implementation implementation capacity at regional and woreda level
I. INTEGRATED CONTINGENCY FINANCING Number Occurrence of years (no. by drought of years) severity 18 16 14 12 10 8 6 4 2 0 PSNP NO DROUGHT Contingency Fund Contingent Grant 8.3 mn Safety Net PSNP Beneficiaries (2006) 5 mn Livelihood Protection Target Beneficiaries MILD DROUGHT Cont. Debt Insur ance Flash Appeal CATASTROPHIC DROUGHT 0 0 0 0 Drought 30 severity 60 90 120 150 180 Early Livelihood protection costs ($US million)
IIA. LIVELIHOOD PROTECTION INDEX FOR AGRICULTURAL AREAS Risk Drought Coverage Safety Net Woredas (districts) in highlands Exposure Resource requirements of transient food insecure beneficiaries (outside the safety net) who would receive fixed amounts of food or cash for work (if appropriate) based on budgeted contingency plans Modelling Weather station and RFE based WRSI Index localized agro-meteorological coefficients, more weather stations
IIB. LIVELIHOOD PROTECTION INDEX FOR PASTORAL AREAS Risk Drought; later water access and flood risk Coverage Pastoralist Woredas in Afar, Somali, Borena Exposure Budgeted drought contingency plans at woreda level Modelling Livestock early warning system (LEWS) that translates weather data and NDVI (satellite generated) into point based forage status
III. CONTINGENCY PLANNING IN CONTEXT Livelihood Analysis Livelihood Analysis e.g. Somali e.g. Somali
III. CONTINGENCY PLANNING IN CONTEXT LP LP Index triggers Contingent Financing activates Contingency Plans Livelihood Analysis Livelihood Analysis e.g. Somali e.g. Somali Drought Scenarios Types of intervention needed Timing of intervention Target population Costs Implementing partners implement Appropriate and timely response protects Livelihoods
Planning IV. CAPACITY BUILDING at Regional and Woreda levels Elaboration and updating of contingency plans (incl. 'shelf plans' which support local coping strategies) Implementation Through state and non-state actors Co-ordination of line ministries Supervision and Quality control
ROLE OF AGRO-MET SERVICES Early Warning System with reliable baseline and trigger points Contingency Planning for appropriate and timely response Ex-Ante Financing of contingency plans Capacity Building for effective plan implementation
HOW WOULD IT WORK in 2008-10? An illustrative example Contingency Fund Contingent Grant Cont. Debt Insur ance Flash Appeal Payouts contingent on Livelihood Protection cost Index (LPCI) Regions Woreda allocation according to assessments, Livelihood Stress Indicators, and Contingency plans Livelihood Protection Population (Beneficiaries)
WHATS NEXT: pushing the frontier New Countries Social Protection and Emergency finance Data Sources Satellite data Data Providers Global Risk Portfolio
REFERENCES (Available upon request)
WEATHER RISK INSURANCE TO PROTECT LIVELIHOODS Ulrich Hess Chief of Business Risk Planning, WFP International Workshop on Agrometeorological Risk Management New Delhi, India 26 October 2006