Managing Weather and Price Risks Using Index

Insurance and Risk-Contingent Credit

Apurba Shee, ILRI

International Conference on Revolutionising Finance for Agri-Value Chains

Nairobi, Kenya – July 15 2014

Outline

� Index Based Livestock Insurance (IBLI)�Motivations and Potential of index insurance� IBLI coverage, pricing and implementation�Opportunities and challenges

�Risk Contingent Credit (RCC)�Concept and features of risk contingent credit�Schematics, pricing and example

�Concluding comments

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Livestock- the pastoralist livelihood

• Livestock are a significant global asset; account for 20%-40% of agricultural GDP (Steinfeld et al., 2006; Herrero et al., 2013)

• Arid and semi-arid lands (2/3 of Africa) – 20 million pastoralists’ main livelihood is livestock grazing

• Livestock is the key productive asset • Low and erratic rainfall and poor soils prohibit crop production• Pastoralist systems adapted to variable climate, but very

vulnerable to severe drought events. In the past 100 years, northern Kenya recorded 28 major droughts, 4 occurred in last 10 years

• Droughts � forage shortage � livestock mortality � poverty trap and dependence on food aid

• Uninsured climate risk is main driver of persistent poverty

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Index insurance for the poor?: opportunities and ch allenges

� Make loss compensation based on a ‘well-defined ind ex’ (highly correlated with insurable loss and not manipulable by insure parties)

� Advantages: avoids market failures of traditional i nsurance:

• No transactions costs of measuring individual losses

• Preserves effort incentives (no moral hazard) as no one can influence index

• Adverse selection does not matter as payouts do not depend on the riskiness of those who buy the insurance

• Suitable for systemic (covariate) climate shock

• Spatial and temporal risk pooling

• Available on near real-time basis: faster response than conventional humanitarian

� Disadvantages: Basis risk

• Imperfect match of individual losses and insurance payout

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IBLI Coverage

� IBLI was commercially launched in the Marsabit district in Kenya in January 2010

� Launched in Borana Zone in southern Ethiopia in July 2012

� Have developed contracts for all arid counties of Kenya (108 divisions)

� Contract provision extended to Isiolo and Wajir in August 2013

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Designing the index

Find a reliable, objectively verifiable signal, that explains most of the variation in household’s seasonal livestock mortalityWe use functions of NDVI, a remotely sensed proxy for forage availability. An indicator of the level of photosynthetic activity in the vegetation.

Model a relationship between the risk to be insured (area-average livestock mortality) and the driving signal (NDVI)

DATA• Livestock Mortality• Remotely-Sensed

NDVI

Response Function

Index• Predicted Livestock

Mortality

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Satellite imagery solves the d ata challenges

Normalized difference vegetation index (NDVI)

1-10 May 2010 good vegetation 1-10 May 2011 bad vegetation

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Temporal/seasonal coverage

Source: Chantarat et.al 2012 JRI8

� Spatially explicit contract- scalable mortality inde x

� Drought being a covariate climate shock creates spatial dependence. Also in response to climate shocks livestock migrate from one place to another. Incorporating spatial interactions by using spatial lag model allow unbiased and more precise estimation

� Spatial method allow for maximal information extraction for missing data cases and provides scalable index construction

� Conditional premium pricing: Conditioning the premium rates on actual present condition eliminates inter-temporal opportunistic behavior for purchasing insurance.

� Risk coverage and pricing: Households are provided flexibility of choosing a strike/ deductible of either 10% or 15%

Contract features

Predicted mortality index readings

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• Key Findings

– Appropriately triggered payments indicative of product precision and building client trust

– ITC-based sales and information delivery platform reducing transactions costs

– Preliminary analysis showing potential welfare impacts:

• Key Challenges

– Catalyzing Informed Demand

• Extension challenge

• Uptake challenge

Opportunities and challenges

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Risk contingent credit

• Objective: Minimizing downside risks and unlocking credit to smallholder farmers

• Definition: Risk-contingent credit is a general term for any credit instrument that embeds within its structure a contingent claim which, when triggered, transfers a part of the borrower’s liability or debt service to the lender.

• The credit product is designed with actuarially fair interest rate (above base interest rate) that is determined by expected value of indemnified risk

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Schematic of risk contingent credit

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Milk/ commodity price

Loa

n re

paym

ent

Opt

ion

payo

ut

Put Option premium reflected in loan interest rate

Loan amount

Schematic of risk contingent credit

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Predicted mortality

Loa

n re

paym

ent

Opt

ion

payo

ut

Loan amount

Call Option premium reflected in loan interest rate

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Pricing of Commodity Linked Loan

Lender’s portfolio with commodity option PV=

Without option PV=

To hedge commodity price risk,

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Example: Risk Contingent Credit for Pulse Crops in India (Shee and Turvey, 2012)

Time (years) 1Loan amount (f) 20000Strike 2825Insurance Cost 215.43r** 12%Scale factor 7.079646r* 0.185446risk Premium 6.545%Loan at expiry 24075.11Loan without option 22549.94Difference 1525.168

New prices Loan repayment3531.25 24075.11

2825 24075.112542.5 22075.112260 20075.11

1977.5 18075.111695 16075.11

1412.5 14075.111130 12075.11847.5 10075.11

Commodity price vs loan obligation

0

5000

10000

15000

20000

25000

30000

0 500 1000 1500 2000 2500 3000 3500 4000

Ranchi Bengalgram prices

Loan

repa

ymen

t

Conclusions

• Uninsured climate (drought) risk is a major cause of food insecurity and poverty traps

• IBLI appears effective financial innovation for protecting pastoralists against drought related livestock mortality and could help households avoid poverty traps

• Considering the challenges it is important to encourage public private partnership and policy to make index insurance a sustainable development tool

• Index insurance can be embedded with structural credit product to reduce farmers default probability to weather risk and hence it not only can protect downside risk for the farmers but it also provides credit access for agricultural development.

• Risk-contingent loans virtually guarantee loan repayment relative to indemnified risk: reduce chance of poverty traps, scale up production, improve food security

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Thank you for your attention and comments