USING INNOVATIVE MARKET BASED RISK MANAGEMENT INSTRUMENTS TO MANAGE

DROUGHT RISK

Erin BrylaCommodity Risk Management Group

The World Bank10/16/2006

Overview

Index Based Weather Risk Management Application 1: Managing weather risk at the

household level Application 2: Providing contingent weather risk

financing for governments Market Based Price Risk Management

Managing the impacts of price fluctuations on government during a food crisis

COMMODITY RISK MANAGEMENT GROUP, WORLD BANK

Provides technical assistance on: Market based price risk management instruments Index based weather insurance

Working to improve access to risk management opportunities by:

Researching risk management alternatives Introducing new products through pilot programs Working with regulators and governments Disseminating best practices and lessons learned

Works with: Banks, microfinance organizations, other financiers Insurance companies Ginners, processors Cooperatives and producer associations Governments

Traditional Strategies for Coping with Drought

GOVERNMENT

Reallocate budget Funds move away from other activities; government involvement

Appeals to humanitarian agencies Unpredictable flows; lag time in delivery

Trade restrictions Disincentives for private sector

Price stabilization/ supports Fiscal burdens for government and eliminates private market

Building up strategic grain reservesRequires management of physical stocks

HOUSEHOLD

Depletion of Assets Long term welfare declines

Suboptimal investments Continued use of basic technology and lower revenues

Low risk crops and farming practices Low yields

Reliance on humanitarian aid Issues of dependency

Cut consumption and take children out of school Health and welfare declines

Can we move from ex-post to ex-ante?

INDEX BASED WEATHER RISK MANAGEMENT

TRADITIONAL VS. INDEX- BASED

• Financial protection against adverse weather conditions• Contracts can be structured as insurance or derivatives• Based on the performance of a specified weather index during the risk

period• Payouts are made if the index crosses a specified trigger level at the end

of the contract period• Protect against yield volatility

Multi-peril Crop Insurance

High Administrative Costs Moral Hazard Adverse Selection

Index-Based Weather Insurance

Rainfall is a proxy for damage Objective triggers and structured

rules for payouts Improved correlation between

need and provision

More on Index Based. . .

THE WEATHER MARKET First weather derivative transaction in U.S.

1997

Market has rapidly grown Non-energy applications New participants Global development Broader product offering

Diversification New locations, new risks Enhances risk/return of portfolio Leads to more aggressive pricing

Market players are interested in: Expanding business growth and expansion Developing market liquidity Broadening product offering Expanding global network

$4.6B 2003/2004

$8.36 2004/2005

Number of Contracts by Region(No CM E Trades)

0500

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

1998/9 99/00 2000/1 2001/2 2002/3

Other

Europe

Asia

N. Amer. South

N. Amer. East

N. Amer. Midwest

N. Amer. W est

2001 SurveyN=19

2003SurveyN=19

2002SurveyN=20

Deficit Rainfall (mm)

Payou

t ($

)

PHASE 1Sowing & Establishment

PHASE 3Yield Formation to Harvest

Deficit Rainfall (mm)

Payou

t ($

)

Deficit Rainfall (mm)

Payou

t ($

)

Cropping Calendar Sowing Window &

Dynamic Start Date

PHASE 2Growth & Flowering

Final Insurance Payout = min (Max Payout, Phase 1 + 2 + 3 Payouts)

CONTRACT DESIGN

Payout per Hectare for Maize Drought Protection, Lilongwe Region

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 10 20 30 40 50 60 70

Maize Rainfall Index

Pa

yo

ut

(MK

W p

er

hc

t)

PAYOUT STRUCTURE

$ per mmMaximum Payout

Trigger Level

Long-Term Average

Groundnut Rainfall Index

PAYOUT STRUCTURE

APPLICATION #1: A weather insurance product that

compensates farmers for weather variability that negatively impacts yields

Because of drought risk farmers engage in negative coping strategies and suboptimal investment

activities.

An effective instrument could provide farmers greater access to finance, the ability to invest in higher risk, higher yielding agriculture, and allow

banks to expand their portfolio to agriculture.

PILOT PROGRAM FOR FARMERS IN MALAWI

Location: Four regions

• Kasungu, Nkhotakota, Chitedze, Lilongwe North Crop:

Groundnut

Period: 140 day season Season only starts after sowing approx Nov - April Sowing date changes depending on first rains

Index: Groundnut most susceptible:

• Lack of rainfall Index must pick up most critical periods of the

groundnut phenological cycle –• Sowing, Flowering, and Pod Filling

Yield data is unreliable so index is based on Water Requirements Stress Index

Contract: Three phases Dynamic start date

CLUB

Insurance Association of

Malawi

MRFC/ OIBM

NASFAM

MET OFFICE

CLUB

Insurance Association of

Malawi

MRFC/ OIBM

NASFAM

MET OFFICE

Example MalawiPilot Details

PILOT DETAILS

The aim is to secure timely and reliable funds to finance Government responses to drought in severe

years.

An efficient response to drought risk requires contingency funds, which weather risk management

instruments can provide.

APPLICATION 2: A contingent financing arrangement for

government in case of a weather triggered food crisis

DROUGHT PROTECTION FOR MALAWI

Malawi Maize Production Index (MMPI) is the output of rainfall-based index model for maize production

Details: Malawi Met Office developed, CRMG adapted Crop balance water model, FAO’S WRSI Variable input is daily rainfall data only 21 primary weather stations throughout the

country tracking local maize yields

Protection Structure: Trigger to protect against maize output below

1,500,000 MT Strike: 1,500,000 MT Limit: 1,000,000 MT Payout Rate: $300 per MT

Location: 21 Weather Stations

Start Date: 1st October 2006End Date: 30th April 2007Payout Date: 7th May 2007Max Payout: $150,000,000

Coverage to protect against the impact of deficit/erratic rainfall on national maize production

Structure designed to reflect conditions which would impact national maize production and food security, resulting in GoM maize imports

HISTORICAL PAYOUTS

$-

$20,000,000

$40,000,000

$60,000,000

$80,000,000

$100,000,000

$120,000,000

$140,000,000

$160,000,000

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006Harvest Year

Pay

ou

t ($

US

)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

Ind

ex P

red

icte

d N

atio

nal

Pro

du

ctio

n (

MT

)

Histroical Payouts ($US)

Index (MT)

CONCLUSIONS – WEATHER RISK MANAGEMENT

At the household level: Gives farmers greater flexibility in investment decisions Banks have greater interest in lending Farmers see potential in investing in their farms

For governments: Provides government contingent financing Allows the cost of drought risk to be smoothed over time Provides some predictability to drought financing and buys

time for other emergency responses to take affect May lessen the effects of drought (asset depletion etc) by

getting the needed resources into the hands of the government and beneficiaries sooner ie protect livelihoods

Provides government a level of autonomy

MANAGING THE IMPACTS OF PRICE FLUCTUATIONS ON GOVERNMENT DURING

A FOOD CRISIS

PREPARATION FOR THE 2005 FOOD CRISIS

During 2005, MVAC predicted 270,000 - 400,000 mt food shortage predicted for Malawi

In the months leading up to the “hungry period” there was a low level of preparation either to obtain the grain required or to mobilize the finance for it

The commercial sector waited to see the governmental and humanitarian response

Humanitarian agencies would be needed but limited involvement prior to crisis onset

Government did not want to be soley responsible for all importing was planning to rely on commercial sector for part of the needs and humanitarian response for the remainder

But, government was concerned about: Local price increases and regional (S.African) price increases Private sector’s ability & willingness to bring in commercial import Response from humanitarian appeals

Given the uncertainty and the magnitude of the food needs the Government wanted to be prepared in case

any of the above went wrong

THE VICIOUS CIRCLE

Although South Africa had 6 million metric tons surplus, commercial

imports were not moving

Increasing local prices

Potentially higher levels of humanitarian

need

Intervention to maintain

sales at subsidized

prices

Continued disincentives to

private sector trade

…Le

adin

g to

…

…Leading to… …Leading to…

…Le

adin

g to

…

THE PRODUCT

Innovative use of SAFEX-based call option by a Southern African government ex ante approach to managing food security risks

A call option Gave Gov’t the right but not the obligation to buy Gave Gov’t protection against prices moving up Provided capped price level for imports….if and when they were needed Could be triggered (exercised) in tranches

Government paid a premium to access the instrument

Physical – SAFEX + transport Transport cost Cost of bagging, etc. Premium for GMO free Maize

Flexibility on delivery periods, volumes, and packing Two expiration dates / two delivery periods 60,000 mt total Ceiling prices varied depending on location

SAFEX vs. MALAWI vs. CBOT

0

500

1000

1500

2000

2500

3000

3500

4000

Mar

-96

Mar

-97

Mar

-98

Mar

-99

Mar

-00

Mar

-01

Mar

-02

Mar

-03

Mar

-04

Ran

d/to

n (2

000

pric

es)

CBOT First NearbyRSA SpotMalawi Average

CONCLUSIONS – PRICE RISK MANAGMENT Governments have difficulty giving up interventionist policy

without good alternatives Market solutions exist, are good alternatives, but need to be

tested in practice before governments will believe in them

Private sector traders are constrained from operating in fully commercial ways b/c of ad hoc policy

Need support to build capacity to manage imports Need incentives to do so that depend on better signals from

gov’t and donors

• Donor interventions can be just as disruptive to the market as government

Need new mechanisms which transfer business to local traders Donor investment in risk management strategies may help

maximize value of food aid dollar

• Better coordination and ex ante planning needed overall so not always operating in crisis mode with very high costs