USING INNOVATIVE MARKET BASED RISK MANAGEMENT INSTRUMENTS TO MANAGE DROUGHT RISK Erin Bryla Commodity Risk Management Group The World Bank 10/16/2006

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 reserves Requires 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  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 $ /2005

Deficit Rainfall (mm)  Payout ($)  PHASE 1 Sowing & Establishment PHASE 3 Yield Formation to Harvest Deficit Rainfall (mm)  Payout ($)  Deficit Rainfall (mm)  Payout ($)  Cropping Calendar  Sowing Window & Dynamic Start Date PHASE 2 Growth & Flowering Final Insurance Payout = min (Max Payout, Phase Payouts) CONTRACT DESIGN

PAYOUT STRUCTURE $ per mm Maximum Payout Trigger LevelLong-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 Malawi Pilot 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: 1 st October 2006 End Date: 30 th April 2007 Payout Date: 7 th May 2007 Max 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 $160,000, Harvest Year Payout ($US) 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 Index Predicted National Production (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 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 …Leading 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 Mar-96Mar-97Mar-98Mar-99Mar-00Mar-01Mar-02Mar-03Mar-04 Rand/ton (2000 prices) CBOT First Nearby RSA Spot Malawi 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