Getting REDD Right: Best Practices that Protect Indigenous Peoples´ Rights and Enhance Livelihoods
WEATHER INSURANCE DERIVATIVES TO PROTECT RURAL LIVELIHOODS · WEATHER INSURANCE DERIVATIVES TO...
Transcript of WEATHER INSURANCE DERIVATIVES TO PROTECT RURAL LIVELIHOODS · WEATHER INSURANCE DERIVATIVES TO...
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