shu-ling chen - apec typhoon chen.pdf · shu-ling chen department of finance and cooperative...
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Shu-Ling ChenDepartment of Finance and Cooperative Management, NTPU
Taiwan Typhoon and Flood Research Institute, NARLABS
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Source: https://tw.images.search.yahoo.com/
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Classified by the payoff measurement Indemnity-based insurance Parametric/Index-based contract
Classified by the nature of the intended policyholder and the uses in risk management strategies Micro (individual) insurance Meso insurance Macro insurance
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Indemnity-Based
• Pay-off depends on the principle of indemnity• Losses are measured in the individual yield either after the loss event or
through yield measurement at harvest time
Index-Based
• Pay-off is determined by an objective and independent parameter that serves as a proxy for significant losses to crop, livestock, or other property
• The index must be highly correlated with losses and cannot be influenced by the insured
• An index can be based on a verifiable variable with a long and consistent history that will allow the contract to be accurately rated
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Indemnity-Based Insurance
pay-off depends on the actual amount of losses
problems of asymmetric information and systemic risks
high administrative cost
high loss-adjustment cost
high political influence
Weather Index-Based Contract
pay-off depends on the values of a weather index, not verifiable losses
eliminate moral hazard and adverse selection
low administrative and monitoring costs
require reliable, timely, and high quality data at weather station networks
uncertain access to weather data
existence of basis risk
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Thailand Disaster Declarations
Source: Sapra, 3rd Asia Agricultural Insurance Conference, 2016
Loss assessment monitoring
Government wants payouts for political gain
Indemnity-Based Insurance
pay-off depends on the actual amount of losses
problems of asymmetric information and systemic risks
high administrative cost
high loss-adjustment cost
high political influence
Weather Index-Based Contract
pay-off depends on the values of a weather index, not verifiable losses
eliminate moral hazard and adverse selection
low administrative and monitoring costs
require reliable, timely, and high quality data at weather station networks
uncertain access to weather data
existence of basis risk
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Source: J-PAL, CEGA, and ATAI Policy Bulletin, 2016.
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• Held by individuals/farmers to manage individual-level production or financial risks
MICRO-Products
• Held by businesses/corporations that provide financial intermediation to large groups of individuals or farmers (e.g., banks, input suppliers, processors & cooperatives)
MESO-Products
• Used primarily by national governments, regional administrative agencies, and non-governmental relief organizations
MACRO-Products
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Source: J-PAL, CEGA, and ATAI Policy Bulletin, 2016.
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Source: World Bank, 2012
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Crop Groundnut
Participants National Smallholder Farmers Association of Malawi(NASFAM) members
Peril Covered Drought
Proxy to Peril Rainfall Deficiency
Weather Station Chitedze Research Station
Term One crop cycle (three stages)
Trigger 60 mm (in establishment and vegetative growth stage)160 mm (in flowering and pod formation stage)100 mm (in pod filling and maturity phase)
Maximum Payout Loan given by bank
Source: Syroka, 2007
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Source: Syroka, 2007
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Catastrophic rain and floods are single greatest risk endured in
Piura, Peru’s richest agricultural region. associated with major El Niños
caused by sea-surface temperature.
During severe El Niños, rains increase in intensity, duration and geographic scope – rainfall can reach levels more than 40 times normal.
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The risk of El Niño constrains access to agricultural credit in northwest Peru.
With support from USAID, a financial risk transfer product was developed to help microfinance institutions (MFIs) in Piura, Peru protect their agricultural and rural loan portfolios against the adverse effects of catastrophic El Niño weather events.
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Contract that indemnifies when sea-surface temperatures (SST) are high would allow agricultural banks in Piura to transfer El Niño risk to international reinsurers.
Contract triggers when SST in the ENSO 1.2 zone(0-10S, 90W-80W) measured and reported by NOAA Climate Prediction for November and December exceeds 24 degree Celsius.
ENSO Index = (Nov ENSO 1.2 + Dec ENSO 1.2)/2
Insured bank receives maximum indemnity if ENSO index exceeds a stop loss point, say 27 degree Celsius.
Indemnities between the trigger and stop loss are proportionate.
Premium rates depend on distributional model of El Niño Southern Oscillation index, adjusted for administrative cost.
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Contract indemnifies before losses due to catastrophic flooding would be incurred.
Average ENSO 1.2 measures for November and December predicts extreme flooding events in February through April with a high confidence level.
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Source: Skees and Murphy, 2009
More than 80% of electricity in Uruguay is generated from hydropower plans.
Administración Nacional de Usinas y Trasmisiones Eléctricas (UTE), Uruguay’s state –owned public electric company, exposed to the risk of drought and high oil prices when rainfall and/or accumulated water reserves is low.
On December 18, 2013, the World Bank executed a $450 million weather and oil price insurance transaction for UTE for the next 18 months.
Daily rainfall data is collected at 39 weather stations spreading throughout the two river basins: the Rio Negro and the Rio Uruguay, where UTE’s hydropower is dependent on.
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Type of Contract Hydropower energy index-lined weather derivative
Maximum Payout US$ 450 million (cumulative)
Term 18 months from Jan 1, 2014 to June 30, 2015
Weather Index Uruguay Potential Hydropower Energy Index (“UPHEI”)
Strike Specified units of the UPHEI index
Settlement Dates Semi-annual (for a total of 3 semesters)
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Source: World Bank, 2014
UTE receives a payout from the World Bank when the weather index is below the pre-determined trigger.
The trigger was selected by UTE, based on coverage and cost considerations.
The amount of the payout depends on the level of the rainfall index and market oil prices at that time.
The World Bank entered into a mirroring agreement with Nephila/Allianz and Swiss Re and effectively transferred the risk onto these entities.
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Source: World Bank, 2014
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Source: Gao, 3rd Asia Agricultural Insurance Conference, 2016
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• Growing phases and stages are sensitive to timing
• Growing season differs by crops and by regions
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Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
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Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
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Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
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Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
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Source: Shynkarenko, 3rd Asia Agricultural Insurance Conference, 2016
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Risk financing is as important as risk prevention and risk reduction.
With the growth of capital market and technology advanced, weather risk becomes insurable. Risk financing techniques, such as index insurance or non-insurance transfer contract, serve as alternative risk transfers for weather risk management.
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Project leads PepsiCo, WRMS, ICICI LombardClient Potato farmers participating in PepsiCo contract
farming programmeInsurer ICICI Lombard (insurer) and WRMS (technical and
infrastructure support)Weather data provider Weather Risk Management Services (WRMS)Crops Potatoes Risks Late blight diseaseIndex Humidity and temperaturePremium US$30/acre
PepsiCo offers an incentive in the buy-back price of RS 0,15/kg (US$ 0,002/kg) with purchase of index insurance
Resource: AgroInsurance.com