WEATHER INSURANCE DERIVATIVES TO PROTECT RURAL LIVELIHOODS

International Workshop on Agrometeorological Risk Management

New Delhi, India 26 October 2006

Ulrich HessChief of Business Risk Planning, WFP

OVERVIEW

• Why Weather Insurance• What is a Weather Insurance/Derivative• Policy implications• Case Study: Livelihood Protection Risk

Financing• Role of AgroMet Services• What’s next: pushing the frontier of weather

risk management

WHY WEATHER INSURANCE

GROWTH• Access to finance• Allows for specialization – pursuit of higher

return activities• Signals cost of risk to farmersEQUITY• Safety net function• Accessible to smallholders

FUNDAMENTALS

• Weather shocks drive yield losses and emergency needs

HOW WEATHER INDEX INSURANCE WORKS

Payout

Payout structure for hypothetical rainfall contract

Rainfall index in mm

MAHABOBNAGAR, AP 2003: BIRTHOF MODERN WEATHER INSURANC

Farmers in Pamireddypally

Basis Risk manageable• Index Insurance offers

superior risk protection: overcomes moral hazard and adverse selection problems,

o but suffers from basis riskSuccess factor: accurate and sustainable index

“Index Insurance trades basis risk for transaction

costs”

THE CURRENT MARKET MARKETS AND PROJECTS

Weather Index insurance markets

Total Notional Value of weather risk contracts: 2000/1-2005/6(in millions of U.S. dollars)

Results

Note: CME Notional Values for all years have been revised to reflect CME-reported values.

$0$5,000

$10,000$15,000$20,000$25,000$30,000$35,000$40,000$45,000$50,000

2000/1 2001/2 2002/3 2003/4 2004/5 2005/6

CME WinterCME SummerOTC WinterOTC Summer

$2,517 $4,339 $4,188 $4,709$9,697

$45,244

Distribution of Total Number of Contracts by Region: 2000/1 – 2005/6

(Excluding CME Trades)

Results

0500

1,0001,5002,0002,5003,0003,5004,0004,5005,000

2000/1 2001/2 2002/3 2003/4 2004/5 2005/6

OtherEuropeAsiaNA SouthNA EastNA MwestNA West

Total Notional Value of weather risk contracts: 2000/1-2005/6

(in millions of U.S. dollars)

$0$5,000

$10,000$15,000$20,000$25,000$30,000$35,000$40,000$45,000$50,000

2000/1 2001/2 2002/3 2003/4 2004/5 2005/6

CME WinterCME SummerOTC WinterOTC Summer

$2,517 $4,339 $4,188 $4,709$9,697

$45,244

?

Distribution of Inquiries about Weather Risk Instruments,

by Sector of Potential End-User

69%

5% 4%

2%

13%

7%

Energy AgricultureRetailConstructionTransportationOther

12%

2005 Survey 2006 Survey

POLICY IMPLICATIONS I

• Clarity– Regulatory– Communication with end-users

• Data– Integrity of weather data– Integrity of indices

• Market Linkages– Credit– inputs

WEATHER INSURANCE IMPACT?Research Design

Authors: WB DECRG (Gine), Prof. Townsend, ICRISAT

• 2004: Household survey of 1052 households in selected villages.

• 2005: “Mini-survey”, follow-up of the same households from 2004.

• 2006: Direct randomized marketing of insurance to households and follow-up surveys.

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Survey Results

1st 2nd 3rd Security/risk reduction 139 53 20 40.1%Need harvest income 25 62 12 15.6%Advice from progressive farmers 17 28 12 8.8%High payout 9 27 11 6.8%Other trusted farmers purchased 16 11 16 6.3%Low premium 17 10 6 5.7%

Frequency by reason no.average

Why did households buy?

Survey ResultsWhy did households not buy?

1st 2nd 3rd Do not understand product 45 59 11 24.9%No cash / credit to pay premium 58 21 11 21.4%Rain gauge too far away 38 39 9 19.0%Too expensive 32 23 7 14.1%No castor, groundnut 13 6 1 4.9%

Frequency by reason no.average

POLICY IMPLICATIONS II: CONTINUUM ACROSS OBJECTIVES AND PLAYERS

PrivatePublic

Growth

Equity

Rajasthan –subsidized WI for

orange farmers

Rajasthan –subsidized WI for

orange farmers

2003: AP –weather insurance

for subsistence farmers

2003: AP –weather insurance

for subsistence farmers

Ontario, CanadaOntario, Canada

Alberta, CanadaAlberta, Canada

UP – subsidized drought disaster

insurance

UP – subsidized drought disaster

insurance

Australia, US, Europe

Australia, US, Europe

India: Salt Producer

India: Salt Producer

Ethiopia: Drought Insurance for

Livelihood Protection

Ethiopia: Drought Insurance for

Livelihood Protection

NAIS, IndiaNAIS, India

CASE STUDY ETHIOPIA: FINANCING EMERGENCY RISK

Understand, reduce and actively manage risks to protect

vulnerable people’s livelihoods and rural development gains

“We should be managing risks instead of

managing crises!” - Dr Aberra Deressa,Ministry of Agriculture and Rural Development of Ethiopia

PROBLEMTIMING OF INTERVENTIONS

Ethiopian Highlands

Oct/Nov

Aug Dec Jan 2007

Feb MarSept

Emergency Needs Assessment

Emergency Appeal

Apr May June July Aug

Life Saving Interventions (mostly food)

RATIONALE• CONTEXT: The Ethiopian safety net programme

promotes the livelihoods of 8.3 million people, while the humanitarian appeals system functions to save lives in emergencies.

• PROBLEM: Up to 5 million livelihoods of transient food insecure people may be lost under the current system

• APPROACHING A SOLUTION: Predictable funding to protect vulnerable people’s livelihoods.

PROBLEMTIMING OF INTERVENTIONS

Oct/Nov

Aug Dec Jan 2007

Feb MarSept

Emergency Needs Assessment

Emergency Appeal

Apr May June July Aug

Life Saving Interventions (mostly food)

Enrolment of LHP Beneficiaries

Support of transient food insecure

population

APPROCHING A SOLUTION PART I: DROUGHT INSURANCE

PILOT• Contingency funding established through transaction

with Reinsurer AXA Re

• Data flow secured through National Meteorological Agency (NMA) capacity building

• Drought index accurately tracks agricultural season

• Implementation Rulebook designed by Government of Ethiopia

ETHIOPIA DROUGHT INDEX

2002

17th ten day period11-20 June

50% Correlation

2002

1984

2006

LESSONS LEARNED SO FAR

Pilot Drought Insurance Project demonstrated:

• it is possible to develop objective, timely and accurate indices for triggering drought response;

• it is feasible to use markets to finance drought risk in Ethiopia;

• contingency plans can better be designed with predictable resources.

Early Warning System

with reliable baseline and trigger points

Contingency Planning

for appropriate and timely response

Ex-Ante Financing

of contingency plans

Capacity Buildingfor effective plan implementation

RISK MANAGEMENT FRAMEWORKIII. Develop budgeted contingency plans

I. Establish timely emergency financing through use of contingency financing

II. Build a Livelihood Protection Index (LPI)

IV. Build planning and implementation capacity at regional and woredalevel

0

2

4

6

8

10

12

14

16

18

0 0 0 0 30 60 90 120 150 180

Early Livelihood protection costs ($US million)

Num

ber o

f yea

rs b

y dr

ough

t sev

erity

CATASTROPHIC DROUGHTMILD DROUGHTNO DROUGHT0

2

4

6

8

10

12

14

16

18

0 0 0 0 30 60 90 120 150 180

Early Livelihood protection costs ($US million)

Num

ber o

f yea

rs b

y dr

ough

t sev

erity

CATASTROPHIC DROUGHTMILD DROUGHTNO DROUGHT

I. INTEGRATED CONTINGENCY FINANCING

PSNPInsurance

8.3 mn Safety Net PSNP Beneficiaries (2006) 5 mn Livelihood Protection Target Beneficiaries

Drought severity

Occ

urre

nce

(no.

of y

ears

)

Cont.

Debt

Flash Appeal

Contingency Fund

Contingent Grant

IIA. LIVELIHOOD PROTECTION INDEX FOR AGRICULTURAL AREAS

• Risk Drought

• Coverage Safety Net Woredas (districts) in highlands

• Exposure Resource requirements of transient food insecure beneficiaries (outside the safety

net) who would receive fixed amounts of food or cash for work (if appropriate) based on budgeted contingency plans

• Modelling Weather station and RFE based WRSI Index localized agro-meteorological

coefficients, more weather stations

IIB. LIVELIHOOD PROTECTION INDEX FOR PASTORAL AREAS

• Risk Drought; later water access and flood risk

• Coverage Pastoralist Woredas in Afar, Somali, Borena

• Exposure Budgeted drought contingency plans at woreda level

• Modelling Livestock early warning system (LEWS) that translates weather data and NDVI (satellite generated) into point based forage status

III. CONTINGENCY PLANNING IN CONTEXT

Livelihood AnalysisLivelihood Analysise.g. Somalie.g. Somali

III. CONTINGENCY PLANNING IN CONTEXT

LP IndexLP

Index

LivelihoodsLivelihoods

Appropriate and timely response

Appropriate and timely response

Contingent Financing

Contingent Financing

protects

triggers activates

implement

Contingency Plans

Contingency Plans

Livelihood AnalysisLivelihood Analysise.g. Somalie.g. Somali

• Drought Scenarios

Types of intervention needed

Timing of intervention

Target population

Costs

•Implementing partners

IV. CAPACITY BUILDINGat Regional and Woreda levels

• Planning– Elaboration and updating of contingency plans

(incl. 'shelf plans' which support local coping strategies)

• Implementation– Through state and non-state actors– Co-ordination of line ministries– Supervision and Quality control

ROLE OF AGRO-MET SERVICES

Early Warning System

with reliable baseline and trigger points

Contingency Planning

for appropriate and timely response

Ex-Ante Financing

of contingency plans

Capacity Buildingfor effective plan implementation

Woreda allocation according to assessments, Livelihood Stress Indicators, and Contingency plans

HOW WOULD IT WORK in 2008-10? An illustrative example

Livelihood Protection Population (Beneficiaries)

Regions

Payouts contingent on Livelihood Protection costIndex (LPCI)

Insurance

Cont.

Debt

Flash Appeal

Contingency Fund

Contingent Grant

WHATS NEXT: pushing the frontier

• New Countries• Social Protection and Emergency finance• Data Sources

– Satellite data• Data Providers• Global Risk Portfolio

REFERENCES(Available upon request)

WEATHER RISK INSURANCE TO PROTECT LIVELIHOODS

Ulrich HessChief of Business Risk Planning, WFP

International Workshop on Agrometeorological Risk Management

New Delhi, India 26 October 2006