WEATHER INSURANCE DERIVATIVES TO PROTECT RURAL LIVELIHOODS

Transcription

1 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

2 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

3 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

4 FUNDAMENTALS Weather shocks drive yield losses and emergency needs

5 HOW WEATHER INDEX INSURANCE WORKS Payout structure for hypothetical rainfall contract Payout Rainfall index in mm

6 AHABOBNAGAR, AP 2003: BIRTH F MODERN WEATHER INSURANC

7 Farmers in Pamireddypally

8 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

9 Weather Index insurance markets THE CURRENT MARKET MARKETS AND PROJECTS

10 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, /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.

11 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 /1 2001/2 2002/3 2003/4 2004/5 2005/6

12 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

13 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%

14 POLICY IMPLICATIONS I Clarity Regulatory Communication with end-users Data Integrity of weather data Integrity of indices Market Linkages Credit inputs

15 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 : Direct randomized marketing of insurance to households and follow-up surveys.

16 Anantapur Mahabubnagar Andhra Pradesh

17 Survey Results Why did households buy? Frequency by reason no. 1st 2nd 3rd average Security/risk reduction % Need harvest income % Advice from progressive farmers % High payout % Other trusted farmers purchased % Low premium %

18 Survey Results Why did households not buy? Frequency by reason no. 1st 2nd 3rd average Do not understand product % No cash / credit to pay premium % Rain gauge too far away % Too expensive % No castor, groundnut %

19 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

20 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

21 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

22 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.

23 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

24 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

25 ETHIOPIA DROUGHT INDEX 17 th ten day period June 50% Correlation

26 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.

27 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

28 I. INTEGRATED CONTINGENCY FINANCING Number Occurrence of years (no. by drought of years) severity 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 Drought 30 severity Early Livelihood protection costs ($US million)

29 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

30 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

31 III. CONTINGENCY PLANNING IN CONTEXT Livelihood Analysis Livelihood Analysis e.g. Somali e.g. Somali

32 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

33 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

34 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

35 HOW WOULD IT WORK in ? 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)

36 WHATS NEXT: pushing the frontier New Countries Social Protection and Emergency finance Data Sources Satellite data Data Providers Global Risk Portfolio

37 REFERENCES (Available upon request)

38 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