Drawing from Lessons Learned on Index Insurance to Consider Financing Famine Relief Efforts

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Drawing from Lessons Learned on Index Insurance
to Consider Financing Famine Relief Efforts

• Dr. Jerry Skees
• HB Price Professor, U of KY
• President, GlobalAgRisk, Inc
• jskees_at_qx.net
• www.GlobalAgRisk.com

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Defining the Problem

• Famine Hunger are complex social problems
  created by numerous interrelated factors
• Low incomes
• Bad governments
• Chronic vs Transitory
• Crop failures (weather driven)
• High prices due to local shortages

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Defining the Problem

• The solutions today can help with
• Crop failures (weather driven)
• High prices due to local shortages
• Transitory shortages
• Less clear that they can help with
• Low incomes
• Bad governments
• Chronic shortages

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The most common response

• Emerging food aid has limitations
• Storage problem
• Transport problem
• Dependency problem
• Timing problem
• Bad government problem
• Political issue among the developed countries

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Proposition

• Getting cash to market participants before a
  transitory food shortage problem emerges is a
  superior food assistance program
• Cash is fungible it can be used for any food
  stuffs to mitigate the problem

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Searching for Solutions that get cash into the
country

• Food Insecurity in the Least Developed Countries
  and the International Response
• By Michael Trueblood and Shahla Shapouri
• This paper compares 3 alternatives
• Grain options
• Revolving import compensation fund
• Import insurance
• Conclusion All would cost significantly less
• 300-600 million per year vs 2.9 Billion

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Insurance based solutions from Trueblood and
Shapouri

• All involve protecting the cost of imports at
  some level
• Each is focused on the price side
• We consider insurance that protects the supply
  side

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Insuring crop/pasture failures

• Issues
• Traditional crop insurance is a failure
• Crop failures represent correlated losses in a
  classic sense they are not insurable
• Financial innovations are creating new
  opportunities
• Technological innovations enhance those
  opportunities

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Traditional Crop Insurance

• A failure
• Moral hazard/ adverse selection / high monitoring
  and administrative cost
• No successful crop insurance in the world when
  one measures the total cost of the program versus
  the transfers
• Have we targeted the wrong level?

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Cost Always Exceed Premiums
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Consider Drought Insurance

• A frequent event (1 in 5 / 1 in 7) with high
  correlated losses.. Everyone can have a wreck at
  the same time
• Loss function has a thick tail to the right with
  frequent-heavy losses much more likely than with
  earthquakes
• Classically NOT an insurable risk!
• Cause of loss is not easy to verify as a
  combination of events can cause a crop loss

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Financial and Technological Innovations Pave the
Way

• Financial Innovations
• Weather markets
• Index based insurance
• Catastrophe bonds
• Blending capital markets with reinsurance markets
• Technological Innovations
• Satellites are measuring weather
• Satellites images on vegetative cover
• Ground level real-time weather
• Computer models to give early warning (LEWS)

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Recent Market Innovations for Catastrophes

• Catastrophic Bonds in the equity markets
• Catastrophic Insurance options on the CBOT
• Crop Insurance Yield contracts on CBOT
• Over the Counter index trades
• Temperature Contracts on the CME
• Weather markets and agriculture

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Catastrophic BondsDebt instrument or Equity
instrument?

• Those at risk have a contingent claim on the Bond
  if the catastrophe occurs
• You give me your capital .. I give you a high
  rate of return unless the catastrophe hits then
  I either reduce your return or take your capital
• Since 1994..over 10 Billion in deals
• Fund managers like CAT Bonds as they are not
  correlated to other equity markets

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Area Yield Insurance

• Essentially, an option on county yield.
• Indemnity does not depend on farm-level yield!
• No moral hazard.
• No adverse selection.
• Low transactions costs.
• Geographic basis risk!

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Area Yield Insurance

• Need
• County yield history.
• Independent party to measure county yield for
  insured crop year.
• Dont need
• Farm yield history.
• Farm yield for insured crop year.
• Compliance officers.
• Loss adjusters to measure farm-level losses.

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US Group Risk Plan

• Payments are strictly based on estimates of
  county yields

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Need historic data to develop the PDF
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Paying on Index Contracts

• Expected county yield 100
• Payment is based on percentage below a trigger
  yield
• EX Payments begin yields of 90 or less
• Actual yield 70
• Percentage (90-70)/90 22.2
• Payment Liability Selected x .222
• Premium Premium rate x Liability

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Changing the Loss Function
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Alternatives to Area Yields

• Is there an objective index that is highly
  positively correlated with area yields and farm
  yields?
• Weather variables
• Rainfall.
• Temperatures.
• Satellite images

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Romanian Summer Rainfall
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Romanian Rain (drought or excess rain)

• Strike for drought at 100 mm or below
• Strike for excess rain 100 mm or above
• Simple contract
• We will pay for every 1 mm of rainfall below 100
  mm. You decide where to stop payment and the
  maximum level of insurance value

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Premium

• Premium rates are driven by the PDF and actuarial
  procedures for loading rates
• Premium payment Liability x Premium rate
• Question How does one determine how much
  liability to purchase? What is at risk?

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Index-Based Insurance Products

• Example
• Farmer purchases an insurance policy that will
  pay an indemnity if cumulative precipitation
  measured at a given location is below a specified
  level over a period of time.
• Indemnities are not based on farmers yield they
  are paid on an independent source of information

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Index-Based Insurance Products

• Advantages
• No moral hazard.
• No adverse selection.
• Low administrative costs (no individual farm loss
  adjustments).
• Easy to understand.
• Protects against correlated risk

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Weather Index Insurance

• Need
• Reliable historical weather data for a given
  weather station.
• Secure and objective source of current weather
  measurements.
• Dont need
• Farm yield history.
• Farm yield for insured crop year.
• Compliance officers.
• Loss adjusters to measure farm-level losses.

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Potential Applications

• Weather index insurance can be
• Sold to households at risk
• Sold to importers
• Sold to governments for disaster aid
• Sold to groups of households
• Sold to agribusinesses
• Used for commercial risk and for emergency
  assistance

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Mexico

• Same infrastructure can be used
• To sell direct to farmers
• To reinsure the crop insurance program
• Sold to collective groups (Fondos)
• Used for natural disaster relief (Funden)
• Wider Press Chapter
• Can Financial Markets be Tapped to Help Poor
  People Cope with Weather Risks?

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Mexico Case Study

• December 2001, Agroasemex was the first emerging
  economy ever to use weather derivatives to
  reinsure the Mexican crop insurance program
• Motivation Obtain a price for the upper layer of
  reinsurance (the biggest risk) was lower than
  other alternatives in the market
• Much more activity in Mexico now to use weather
  measures for disaster payments and insurance

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Countries

• Argentina (use area yield for disaster pay)
• Morocco (rainfall insurance this fall)
• Mexico (first reinsurance with weather)
• Canada (Alberta Ontario use rain)
• Mongolia (to use mortality rate of animals)
• Ukraine (progress toward using rain)
• Romania (recommended area yield)

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Linking Rainfall Insurance and Water Markets

• Rain feeds the system of reservoirs
• Rainfall insurance sold to the Irrigation
  Authority (IA) offers new opportunities
• IA could sell quota rights to water with 3
  characteristics 1) ownership and right to use
  water 2) right to lease water and 3) a
  guarantee that replaces lost water with insurance
  payments

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Linking Rainfall Insurance and Water Markets

• How does a quota with these characteristics
  change the political economy of water markets?
• IA sells these quotas to obtain the capital
  needed to make infrastructure improvements
• Burden is on IA to fix things and make certain
  that they can deliver water to quota owners
• The IA reinsures the indemnity payments with the
  rainfall insurance

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Moving to a Proposal for Famine

• Use the early warning systems to index emerging
  problems and offer index insurance
• Issues
• Who will pay premium?
• Who should purchase?
• How might such a system be implemented?

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Global Livestock CRSP - LEWS
Livestock Early Warning System for East Africa.
..blending monitoring/modeling and spatial
technologies to improve food security of
pastoral communities in East Africa
Lead InstitutionTexas AM University System
Dr. Jerry Stuth, PI
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Biophysical Models, Technologies and Spatial
Analysis Tools Currently Used in the LEWS Project
Process

• PHYGROW - hydrologic based, spatially explicit
  multiple-species plant growth/hydrology/animal
  grazing model.
• NUTBAL - nutritional balance analyzer used to
  assess nutrient requirements, nutrient intake,
  milk production, and performance in cattle,
  sheep, goats and horses with least cost mediation
  solutions..
• Near Infrared reflectance spectroscopy of (NIRS)
  Allows fecal profiling of livestock to
  determine the quality the forage recently
  consumed prior to defecating.
• Spatial Characterization and GIS tools - GPS
  units, ACT, ArcView, GS
• Satellite Imagery - NOAA RFE weather and EROS
  NDVI data

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Systems can focus on local problemsGrid of 12 x
12 km
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Using Early Warning Systems for Insurance
Contracts

• These systems index the deviations from normal
• These systems give early warning (up to 90 days)
• Insurance model could be indexed with deviations
  from normal and the early warning information
• Insurance would likely have layered payment
  structure (1 early payment with another payment
  should certain excess conditions be meet)

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Who Could Purchase?

• Governments
• NGOs who want resources when there is a serious
  problem
• Importers within the country (remember.. If they
  are concerned about price increases they should
  purchase more liability)
• Microfinance entities within the country for
  local problems
• Villages / households

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Who will pay?

• Some level of payment could come from the G-8
  (for the worst catastrophes)
• Some level should come from the end-users
• Some payments could be in the form of food stamps
• Some payments could come from NGOs
• Charity Catastrophe Bonds

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Who will supply these index contracts?

• A consortium of international reinsurers
• Investment banks via famine CAT Bonds
• Charity CAT Bonds
• Keeping some market base is important!
• Relative risk pricing..
• Proper design of contracts
• Pooling of global risk to make undiversifiable
  risk diversifiable

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Is this doable?

• Yes.. I have visited with some key market makers
  there is an interest
• Developing such a system helps them spread global
  risk / helps them with an enhanced social image
• What is needed?

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Rules for Successful Indexes

• Easy to understand
• Replication
• Frequency of Publication
• Representative of True Economic Value
• Break-down of alternative hedging
• (Drs. Richard Sandor and Joseph Cole)

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Benefits

• Gets cash to important stakeholders in the
  developing country BEFORE the problem gets too
  serious
• Paves the way for more risk management
  instruments by providing the important
  infrastructure for a variety of commercial and
  social risk problems
• Enhances the opportunity to spread global risk