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ITF CRM annual meeting, Pretoria, May 16, 2006

ITF CRM annual meeting, Pretoria, May 16, 2006. A Model for Lowering Inter-Annual Revenue Variability for the Cotton Chain in WCA Countries by Jean Cordier Professor, Agrocampus Rennes.

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ITF CRM annual meeting, Pretoria, May 16, 2006

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  1. ITF CRM annual meeting, Pretoria, May 16, 2006 A Model for Lowering Inter-Annual Revenue Variability for the Cotton Chain in WCA Countriesby Jean CordierProfessor, Agrocampus Rennes A model developed with the support of the French Foreign Ministry and the Agence Française de Développement (AFD)

  2. ITF CRM annual meeting, TUT, Pretoria, May 16, 2006 A Model for Lowering Inter-Annual Revenue Variability for the Cotton Chain in WCA Countries • Introduction : the « producer » problem • The model and its assumptions • Results • Advantages and limits

  3. INTRODUCTION : THE « PRODUCER* » PROBLEM • - Risk concern of the producer : price and quantity • Risk concern of the ginner : quantity and price • f(relationship P - G) • Risk on revenue FOB price (basis = 50) … Revenue = P.Q • Ft - 50 Cost of production Ft Reference market price Ft increase decrease * « Producer » = ginner + farmer

  4. INTRODUCTION : THE « PRODUCER » PROBLEM • Risk perception : • Revenue variability … σ • Value at Risk : Prob 5 % • Revenue(t) < 174 F.CFA σ • Impact on : • Short Term invest. choices • Long Term invest. choices • Impact on chain competitivity

  5. INTRODUCTION : THE « PRODUCER » PROBLEM Shock Crisis Productivity gains In a competitive market, price is fluctuating through time above and below cost of production

  6. THE « PRODUCER » PROBLEM AND ITS « ANSWER » FOB price (basis = 50) With a floor price And with the benefit of a price lift • Ft - 50 650 Cost of production Being profitable 700 Ft Reference market price Ft increase decrease

  7. OBJECTIVE OF THE MODEL • Reduce the revenue variability of the global Cotton Chain in WCA countries • Directly from price risk management • Indirectly from cultivated surface management • … nothing, to the present time, on crop yield/weather risk management • Improve the VaR(5%) of the cotton producer • Share the residual risk between ginners and producers

  8. CONTEXT OF THE MODEL = WCA COUNTRIES • Unicity of farmer cotton price through space • Unicity of price through time (within a crop year) • March(t) Posted Price for Oct-November delivery t • Posted price payment at delivery (Oct-Nov) and price bonus at the end of the crop year • Organisation of (most) WCA cotton chains

  9. CONTEXT OF THE MODEL = WCA COUNTRIES • A fixed exchange rate EUR/F.CFA • A devaluation between EUR/F.CFA in 1994

  10. THE PROPOSED MODEL AS A SECOND BEST FOB price (basis = 50) Cost of production Reference market price Ft increase decrease

  11. THE MODEL • Use of reference markets (NYBOT/Cotlook A and exchange rate USD/EUR to define a « fair » CIF-FCFA reference price • Define the basis Bt for eliciting the WCA FOB-FCFA price Bt = transportation cost minus quality premium • Design « price layers » with respect to probability of occurrence • Layer A : Risk retention layer Prob(Layer A)≈ 90% • Layer B : Market instrum. layer Prob(Layer A)≈ 10% • Layer C : Market failure layer Prob(Layer A)≈ 1-5% • Design tools matching each layer with portfolio consistency and governance potential • Define a formula pricing for sharing cotton value between ginners and producers

  12. THE PROPOSED MODEL FOB price (basis = 50) A C B Cost of production Reference market price Ft increase decrease

  13. « Risk retention layer » = Layer A • Intra-annual smoothing : selling diversification using futures and forward contracts (private basis) •  Inter-annual smoothing : price and revenue smoothing using a Buffer Fund and a Withdrawal Right (private professional basis) • « Market insurance layer » = Layer B • Risk transfer to market : price derivative contract • (« bear put spread ») • « Market failure layer » = Layer C • External support : local covered eventually by international • Governance of crisis (early signals, crisis procedure implementation) TOOLS ORGANIZATION IN THE MODEL

  14. ASSUMPTIONS OF MODEL SIMULATION FOR BURKINA FASO • Lognormal price distribution for the world cotton price in cts/lb (NYBOT or Cotlook A) LN(St) has a normal distribution : N(0 ; 0,20) • Normal distribution for the exchange rate USD/EURO : N(1,15 ; 0,22) • Normal distribution for farm cotton yield : N(1063 ; 113) • Normal distribution for cultivated area : N(700000 ; 70000) • No current distribution on FOB-to-CIF cost or quality premium

  15. Moving Average smoothing

  16. PARAMETRIZATION TESTED • Pivot price calculated using first order exponential smoothing (4 years and α= 0,7) • Price layers : A > 700, 600 > B > 700 and C < 600 • Upper bound = 110 % of pivot price Lower bound = 90 % of pivot price • Percentage of surplus given to the Buffer Fund (BF) = 100 % • Maximum size of the Buffer Fund = 15 % of pivot price Maximum size of the Withdrawal Right (WR) = 15 % of pivot price • Formula for sharing cotton FOB value between the ginner and the producer : • Ginner margin : M = 200 + 0,1*P • Producer price : PProd. = (PFOB – M)* 0,42

  17. THE BUFFER FUND « AUGMENTED » WITH WITHDRAWAL RIGHT Example of simulation :

  18. Current situation Example of simulation : Impact of the model

  19. Crise Shock

  20. RESULTS OF MONTE CARLO SIMULATION • Robust model under current hypothesis (Monte Carlo simulation) • Risk decrease for WCA cotton chains • 35-40 % decrease of the coeff. of variation of the producer price • 30-35 % decrease in standard deviation of the producer price • Value at Risk (5%) improvement  : 20-25 % • Use of Layer C : 3 to 5 % for an average of 37 MM F.CFA (Burkina Faso – 700.000 ha), 1 or 2 times every 30 years (37 or 74 MM F.CFA)

  21. MODEL ADVANTAGES • Effective risk reduction for WCA cotton chains • VaR(5%) improvement • Non-distorting mechanism • « clear principles » and parametrization to reach local objectives • Non manipulable therefore « sustainable » • Linked to « market » through the use of market signals (exponential smoothing) and instruments (futures-forward, options) • Cultural acceptability in merging « buffer funds » and « market instruments » therefore « locally acceptable » … in addition to parametrization

  22. MODEL LIMITS • Jumps are not considered (FCFA devaluation, strong production cost changes – i.e. GMO – strong cotton area increase) … therefore additional « governance » mechanisms are required to handle jumps consequences • Requirement of a national agreement for sharing the world cotton value and risk in between ginners and producers (formula margin and productivity targets) • Unknown derivative market liquidity, inducing transaction costs on the knockout option through market intermediaries (banks, international trading firms, specialized intermediaries) • Requirement of an agreement between the local Cotton Chain (Interprofession) and the Government for « Layer C management »

  23. … IMPLEMENTATION ISSUES • Need to move from current national situations (objective and also constraint of pilot tests) • Set theoretical and practical layers limits (A, B and C) • Premium issue (perceived cost/benefit, how much, flexible/fixed) • A need for normative costs (ginners) • Adaptation to national ginners structure (one or several ginners) • Institutional, legal, initial endowments issues THANKS FOR YOUR ATTENTION ITF CRM annual meeting, Pretoria, May 16, 2006

  24. Besoin d’un « plan marketing » et d’un suivi Plan MKG : Fondement du suivi

  25. Compatibilité des aides par rapport à l’O.M.C. • Notion de choc et de crise • Amélioration possible de la règle de « catastrophe naturelle » telle que rédigée en annexe 2 – paragraphe 7 de l’accord de Marrakech - Autor. OMC - Aide prévue

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