UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP

1. UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP Ulrich Hess Joanna Syroka PhD January 20 2004 UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP IFC PEP Ukraine Ulrich Hess Joanna Syroka PhD January 22 2004 Weather Index Insurance for Agriculture COMMODITY RISK MANAGEMENT GROUP The World Bank 13th October 2006 William J. Dick

2. OUTLINE • Overview of the Commodity Risk Management Group (CRMG), the World Bank • Index-based Weather Insurance • How to develop a Weather Insurance program? • Extending the index concept to flood insurance

3. CRMG Overview

4. CRMG facilitates…. • Market-based Risk Transfer Products • Weather index-based insurance • Price risk management contracts • New Applications • Disaster risk financing • Extension to new hazards • Access to risk capital • Access to global reinsurance markets • Knowledge Transfer and Education • Technical assistance in projects • Publications and training workshops • Existing Transactions • India, Ethiopia, Malawi, Ukraine.…

5. CRMG global activities 2005 2002 2004 2006 2001 2003 Feasibility Study Pilot Design Pilot Implementation

6. New Model: Index-based Weather Insurance

7. Motivation • Traditional crop insurance • Multi-Peril Crop Insurance (MPCI) • Yield-based insurance is not sustainable • Named peril Crop Insurance • Damage-based insurance is viable for selected localised perils • Main Problems • Loss adjustment and farm level data • Moral hazard • Adverse selection due to asymmetric information • High monitoring and administrative costs • Often heavily subsidised • Operationally difficult for small farmer agriculture

8. Experience with public crop insurance Financial performance of crop insurance • Condition for sustainability: (A+I)/P < 1 Where: A = average administrative cost I = average indemnities paid P = average premiums paid Source: Hazell

9. Index insurance • Challenge Design an alternative, efficient and cost-effective crop failure insurance program that facilitates risk transfer and is feasible for small farmers in low-income countries.

10. What are index insurance contracts ? • An index insurance contract indemnifies based on the value of an “index”- not on losses measured in the field • An index is a variable that is highly correlated with losses and that cannot be influenced by the insured • Example indices: rainfall, temperature, regional yield, river levels • Index insurance contracts overcome most of the supply side problems of traditional insurance contracts

11. Main characteristics of an index • Observable and easily measured • Objective • Transparent • Independently verifiable • Able to be reported in a timely manner • Stable and sustainable over time Weather indexes can form the basis of an insurance contract that protects farmers from weather risk

12. Maximum Payout Long-Term Average Rainfall Trigger Rainfall Level Payout structure: drought protection EXAMPLE OF PAYOUT STRUCTURE Financial payout - increment per mm Payout (unit per ha) Deficit Rainfall Index (mm.)

13. Index insurance: Advantages and challenges

14. How can index instruments be used ?

15. The global market • Deals transacted: • Argentina I – Weather insured seed credit • Argentina II – Dairy yield protection against low rainfall • South Africa – Apple co-operative freeze cover • India – Approximately 250,000 insured against poor monsoon • Mexico – Crop insurance portfolio reinsurance through weather derivative structure • Canada (Ontario) - Forage insurance with weather indexation • Canada (Alberta) - Heat index insurance for maize • Ukraine – Winter wheat protection against weather risks • Malawi – Weather insurance pilot for groundnut farmers • Ethiopia – WFP Drought Insurance • Under preparation: • Morocco – Wheat yield protection against drought • Zambia – Maize yield protection against drought • Nicaragua – Bank-intermediated weather insurance for groundnut farmers • Thailand – Bank-intermediated weather insurance

16. How to develop a weather insurance program ?

17. Developing a pilot program • Identify significant farmer exposure to weather • Quantify the impact of adverse weather on their revenues • Structure a contract that pays out when adverse weather occurs • Execute contract (with insurers and a delivery channel) • Secureinternational reinsurance

18. Low probability High Consequence Extremely low yields High probability Low Consequence Reduced yields Low probability High Consequence Extremely low yields Extreme weather events (droughts) Normal weather Extreme weather events (excess rainfall or flood) The producers generally perceive this as their risk High Probability, Low Consequence Risks Vs.Low Probability, High Consequence Risks

19. *Maize yields are particularly sensitive to rainfall during the tasseling stage and the yield formation stage – rainfall during the latter phase determines the size of the maize grain Sowing and establishment period is also critical crop survival Diagram taken from the FAO’s maize water requirement report* The cropping calendar • A rainfall index is normally split into 3 or more crop growth phases • Objective: maximise the correlation between index and loss of crop yield

20. Maize Rainfall Index - example

21. Index v. maize yield example

22. Distribution and risk transfer • Bank-intermediated weather insurance contracts to farmers Global Reinsurance Companies International Reinsurance treaty Insurance Company/ Syndicate National Contractual relationship (risk transfer, services, operations etc.) Agricultural Bank Weather insurance contracts Farmers

23. Weather index insurance - summary • The product is simple and weather measurements can be understood by farmers • Basis risk can be reduced by increasing the density of low cost weather stations • Low cost of distribution and loss adjustment • Less specialist knowledge needed to underwrite the product • The product is suited for catastrophe hazards • The product is highly flexible and can multiply in the insurance market • Reinsurers are interested to accept the risk

24. Extending the concept to flood insurance

25. The flood risk in Asia

26. Flood insurance concept Design a flood index which can proxy losses caused to crop • Rice is the strategic crop most exposed to flood • Flood impact is dependent on variety, time of occurrence, depth, speed and duration of flood water • Harness technology to support insurance underwriting and operations • 2 key components for index design phase • Flood modelling (FM) • Agro meteorological modelling (AMM) • 2 key components for operational phase • Geographical information system • Earth Observation (EO)

27. “Medium Risk” Pricing Zone “High Risk” Pricing Zone LA1 LA2 LA4 Pasak River LA3 LA5 “Low Risk” Pricing Zone

28. Summary: Combining the Technology Components FM + AMM Design a flood index that proxies crop loss FM+EO+GIS Define flood risk zones and pricing the contract EO+ GIS Loss adjustment for payout determination according to the index FM: flood modelling. AMM: Agro-meteorological modelling. EO: Earth observation. GIS: Geographical Information System.

29. Remote sensing can measure flooded areas Flood assessment based on SAR - Bangladesh 07/2004 Flood map River gauges

30. Challenges in indexing flood risk Types of flood risk • River inundation flood • Flash flood • Typhoon induced flood • Coastal surge flood Challenges • Zoning for insurance purposes • Defining “macro” or “micro” level insurance products • Pricing flood risk • Influence of flood management practices on risk • Avoidance of anti-selection • Simplifying the product CRMG is still in the research phase • Thailand, Vietnam and Bangladesh