UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT
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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.

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UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP

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Ukrainian agricultural weather risk management world bank commodity risk management group

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


Outline

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


Crmg overview

CRMG Overview


Crmg facilitates

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.…


Ukrainian agricultural weather risk management world bank commodity risk management group

CRMG global activities

2005

2002

2004

2006

2001

2003

Feasibility Study

Pilot Design

Pilot Implementation


New model index based weather insurance

New Model: Index-based Weather Insurance


Motivation

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


Experience with public crop insurance

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


Index insurance

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.


What are index insurance contracts

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


Main characteristics of an index

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


Payout structure drought protection

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.)


Index insurance advantages and challenges

Index insurance: Advantages and challenges


How can index instruments be used

How can index instruments be used ?


The global market

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


Ukrainian agricultural weather risk management world bank commodity risk management group

How to develop a weather insurance program ?


Developing a pilot program

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


High probability low consequence risks vs low probability high consequence risks

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


Ukrainian agricultural weather risk management world bank commodity risk management group

*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


Maize rainfall index example

Maize Rainfall Index - example


Ukrainian agricultural weather risk management world bank commodity risk management group

Index v. maize yield example


Distribution and risk transfer

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


Weather index insurance summary

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


Extending the concept to flood insurance

Extending the concept to flood insurance


The flood risk in asia

The flood risk in Asia


Flood insurance concept

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)


  • Ukrainian agricultural weather risk management world bank commodity risk management group

    “Medium Risk” Pricing Zone

    “High Risk” Pricing Zone

    LA1

    LA2

    LA4

    Pasak

    River

    LA3

    LA5

    “Low Risk” Pricing Zone


    Summary combining the technology components

    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.


    Remote sensing can measure flooded areas

    Remote sensing can measure flooded areas

    Flood assessment based on SAR - Bangladesh 07/2004

    Flood map

    River gauges


    Challenges in indexing flood risk

    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


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