Docstoc

Structure Example

Document Sample
Structure Example Powered By Docstoc
					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                                        HOUSEHOLD

   Reallocate budget                              Depletion of Assets
    Funds move away from other activities;          Long term welfare declines
    government involvement

   Appeals to humanitarian agencies               Suboptimal investments
    Unpredictable flows; lag time in delivery       Continued use of basic technology and
                                                    lower revenues

   Trade restrictions                             Low risk crops and farming practices
    Disincentives for private sector                Low yields

   Price stabilization/ supports                  Reliance on humanitarian aid
    Fiscal burdens for government and
    eliminates private market                       Issues of dependency

                                                   Cut consumption and take children out of
   Building up strategic grain reserves            school
    Requires management of physical stocks          Health and welfare declines


          Can we move from ex-post to ex-ante?
INDEX BASED WEATHER RISK
      MANAGEMENT
                  TRADITIONAL VS. INDEX- BASED
   Multi-peril Crop Insurance              Index-Based Weather Insurance
        High Administrative Costs               Rainfall is a proxy for damage
        Moral Hazard                            Objective triggers and
        Adverse Selection                        structured rules for payouts
                                                 Improved correlation between
                                                  need and provision



More on 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
                       THE WEATHER MARKET
   First weather derivative transaction in U.S. 1997           Number of Contracts by Region
                                                                           (No CME Trades)
                                               5,000
   Market has rapidly grown
                                               4,500                                                     Other
      Non-energy applications
                                               4,000                                                     Europe
      New participants                        3,500
      Global development                      3,000                                                     Asia

      Broader product offering                2,500                                                     N. Amer. South
                                               2,000                                                     N. Amer. East
                                               1,500
   Diversification                            1,000                                                     N. Amer. Midwest
       New locations, new risks                 500                                                     N. Amer. West
       Enhances risk/return of portfolio          0
       Leads to more aggressive pricing           1998/9    99/00        2000/1       2001/2   2002/3
                                                                                        2002     2003
   Market players are interested in:                       2001 Survey                Survey   Survey
                                                               N=19                    N=20     N=19
      Expanding business growth and expansion
      Developing market liquidity
      Broadening product offering
      Expanding global network                  $4.6B 2003/2004
                                                 $8.36 2004/2005
                                              CONTRACT DESIGN

             Payout ($) 




                                                      Payout ($) 




                                                                                               Payout ($) 
                            Deficit Rainfall (mm)                   Deficit Rainfall (mm)                   Deficit Rainfall (mm) 



                              PHASE 1                                   PHASE 2                                     PHASE 3
                     Sowing & Establishment                          Growth & Flowering                       Yield Formation to Harvest




                                                                                                              Cropping Calendar 
 Sowing Window &
Dynamic Start Date


          Final Insurance Payout = min (Max Payout, Phase 1 + 2 + 3 Payouts)
                                                PAYOUT STRUCTURE
                                                         PAYOUT STRUCTURE
                                  Payout per Hectare for Maize Drought Protection, Lilongwe Region
                       9000


                       8000


                       7000

                                     Maximum Payout
Payout (MKW per hct)




                       6000
                                                                                $ per mm


                       5000


                       4000


                       3000                                                                Long-Term Average

                       2000


                       1000                           Trigger Level

                         0
                              0        10        20          30         40          50          60         70

                                                          Maize Rainfall Index
                                                         Groundnut Rainfall Index
                 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
         PILOT DETAILS
         Example Malawi
           Pilot Details

  Insurance            MET OFFICE
Association of
    Malawi




   MRFC/
                           NASFAM
   OIBM




    CLUB
                   APPLICATION 2:
    A contingent financing arrangement for government in
            case of a weather triggered food crisis


 An efficient response to drought risk requires contingency
  funds, which weather risk management instruments can
                          provide.


The aim is to secure timely and reliable funds to finance
   Government responses to drought in severe years.
              DROUGHT PROTECTION FOR MALAWI
          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

   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
                                                          Location:        21 Weather Stations
         Strike: 1,500,000 MT                            Start Date:    1st October 2006
         Limit: 1,000,000 MT                             End Date:      30th April 2007
         Payout Rate: $300 per MT                        Payout Date:    7th May 2007
                                                          Max Payout:    $150,000,000
                              HISTORICAL PAYOUTS
               $160,000,000                                  2,500,000



               $140,000,000




                                                                         Index Predicted National Production (MT)
                                                             2,000,000

               $120,000,000



               $100,000,000
Payout ($US)




                                                             1,500,000



               $80,000,000


                                 Histroical Payouts ($US)    1,000,000
               $60,000,000


                                 Index (MT)
               $40,000,000
                                                             500,000

               $20,000,000




                      $-                                     0



                                              Harvest Year
      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



                                                               Continued
                                                            disincentives to
 Although South Africa had                                private sector trade
    6 million metric tons




                                                                     …Leading to…
    surplus, commercial
  imports were not moving
      …Leading to…




                                                               Intervention
                                     Potentially
                                                                to maintain
 Increasing                       higher levels of
                     …Leading to…                  …Leading to… sales at
local prices                       humanitarian
                                                                subsidized
                                       need
                                                                   prices
                                    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
                         4000

                         3500   CBOT First Nearby
                                RSA Spot
Rand/ton (2000 prices)




                         3000
                                Malawi Average
                         2500

                         2000

                         1500

                         1000

                          500

                            0
          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

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:4
posted:2/1/2012
language:
pages:22