Insurance of Climate Risk in Agriculture Martin Odening Department of Agricultural Economics and Social Sciences, Humboldt-University Berlin, Germany Presentation at the ICAR Forum 2008 October 14, 2008, Bucharest

2 Motivation

3 Mitigation Reduction of Greenhouse Gases Immission Certificates Insurance Adaptation Crop rotation New seeds Irrigation Crop insurance Weather derivatives CAT bonds Strategies for Coping with Climate Risk

4 Insurance coverage Premium subsidies Catastrophe aidParticipationReinsurance Germany hail, supplementary insurance noneonly for uninsurable risks approx. 35% for hail < 1% for MPCIprivate insurance France Multiple peril crop Insurance 60% government aid for natural disasters (drought, earthquake, flooding) 20% private insurance Greece comprehensive insurance 50%n.a. Italy hail, frost, drought 50% for hail 80% for MPCI only for uninsurable risksn.a private insurance Canada Multiple peril crop insurance 50% for extreme and uninsurable disasters 50% private and public insurance Luxembourg comprehensive insurance up to 50%n.a10%n.a. Austria comprehensive insurance 50% for hail- and frost insurance only for uninsurable risks 78% for hail 56% for MPCI private insurance exclusively Spain comprehensive insurance 55%only for extreme disastersapprox. 42% private and public insurance USA Multiple peril crop insurance 35 up to 100%only for uninsurable disasters80% private and public insurance Agricultural Insurance Systems

5 Source: PricewaterhouseCoopers million USD Weather derivatives: Market Development

6 no moral hazard no adverse selection no assessment of damage required (low transaction costs) payoffs not only in case of extreme weather events Advantages of index-based insurance high basis risk sometimes difficult to price lower familiarity by users Disadvantages of index-based insurance Index-based Insurance / Weather Derivatives

7 1. Rainfall sum 2. Rainfall deficit = rainfall at day t = reference level for minimum daily rainfall R 2 = 0.22 R 2 = Rainfall and Temperature R 2 = 0.85 Weather Indexes for Wheat

8 Rainfall deficit De-correlation function for precipitation in Brandenburg, Germany

9 Probability (€/ha) Revenue Distribution with and without Hedging

10 1 ENSO – El Nino Southern Oscillation is the index measuring the Pacific sea surface temperature Overview about Practical Experiences with IBI

11 Factors determining the demand for IBI -Risk exposure of the farms -Hedging effectiveness of the instrument -Risk attitude of the decision maker -(Non) Existence of effective alternative risk reduction instruments -Transparency of insurance products -Cost of insurance -Policy environment Preconditions and Success Factors of IBI in Agriculture

12 Factors determining the supply for IBI -Cost of insurance product development -Cost of delivery -Cost to control adverse selection and moral hazard -Cost of loss adjustment -Market potential and volume -Risk premium -Political, legal and institutional factors Preconditions and Success Factors of IBI in Agriculture

13 Indicators for the Potential of IBI in ECA Countries (1)

14 Indicators for the Potential of IBI in ECA Countries (2)

15 Factors Influencing the Potential of IBI in ECA Countries

16 Example of a Country Profile

17 good poor low high Bulgaria Hungary Croatia Uzbekistan Azerbaijan Tajikistan Armenia FYR of Macedonia Belarus Russia Turkey Albania Georgia Serbia Kosovo Kyrgyzstan Ukraine Demand for IBI Preconditions for establishment of IBI Romania Moldova Kazakhstan Portfolio Analysis for ECA Countries

18 Weather constitutes one of the most important risk exposures in agriculture; it may hamper the economic development of the agricultural sector Farmers: awareness of risk and active risk management Insurers: supply of tailored and affordable insurance products Science: rigorous evaluation of existing pilot projects; design and rating of index-based weather insurance Governments/donors: -Improvements in legal and regulatory environment -Improvement in data collections -Assistance in product development -Knowledge transfer and educational efforts -Financial support for the coverage of catastrophe losses Conclusions & Recommendations

19 Willingness to pay for Weather Insurance in Germany

20  actuarially fair price (= expected payoff) = 13.5% of the insured revenue  Premium loading = 20-25% surcharge on the fair price depending on the type of insurance  Insurance premium = fair price + loading = 16.54% of the insured revenue  WTA exceeds WTP => emergence of insurance market is unlikely Cost of Weather Insurance

21 SaxonyThuringia Actuarially Fair Price Crop rotation in Brandenburg Indifference Prices for a Put Option on a Weather Index in Different Regions in Germany (in €)

22 Profit Short future Weather index on expiration Present index value a) Futures b) Put-Option Profit Weather index on expiration Strike Production revenue Hedged position Hedged position Production revenue Long put Hedging Strategy Using Weather Derivatives

23 Success Factors / Preconditions for IBI Indicators Theoretical AnalysisExperiences with IBI Quantification ‘Portfolio Matrix’ Aggregation Data on ECA Pre-Assessment of Feasibility of IBI in ECA Recommendations for Donors / Goverments Methods and Data Sources

24 recoveries insurance premium farm insurance transaction insurerinvestor weather bond price principal & coupons compensation payment when weather event occurs unconditional payment securitization Securitization of Weather Risk