Agricultural Yield and Price Distributions

1. Agricultural Yield and Price Distributions Unité d’économie rurale UCL Olivier Harmignie Bruno Henry de Frahan Philippe Polomé Frédéric Gaspart

2. Overview • Introduction • Data • Models • Results • Source of the variability of receipts • Conclusions

3. Introduction • Context: • Farms become more specialized and indebted • Trade liberalization • European Commission communicated possible risk management options (March, 2005) • Objective : Assess price, yield and receipt distributions for modelling and insurance purposes • Literature: Most used distributions are Normal, Beta and Lognormal, … => Is that justified for FADN data in Belgium?

4. RAW DATA : FADN sample during 7 years (1995-2001) PRICES YIELDS CROPS: CCHI : Chicory; OPOT : Potatoes for consumption; SUGB : Sugarbeet; WBAR : Winter Barley; WWHE : Winter wheat.

5. Estimated panel data models One-way model : Ynt = αn +ε1nt where Ynt : Yield or price per farm αn  : Constant specific to farm n, stratification variable representing structural variability εnt  : Residuals One-Way model + Trends  : Ynt = αn +β * t +ε2nt where β  : linear yield trends coefficient, t : year Two-way model  : Ynt = βn +γt +ε3nt where γt : Constant specific to each year t systemic variation that affect all farms equally

6. Results of the panel data estimation Source : FADN (1995-2001)

7. Results of the panel data estimation • Conclusions • Structural differences are important • Trend brings little information • Annual variations are due to a cyclical or a stochastic process • Results limited to the period 1995-2001

8. Residual correlations • “No” correlation across crops for the residuals of the two-way model

9. Residual correlations Correlations between yield and price Conclusions • Self-insurance • Little correlation across crops • Strong correlation between price and yield of one crop => Joint estimation needed for simulation purpose

10. One-Way model residuals distributions WINTER WHEAT YIELD RECEIPT (price*yield) POTATOES FOR CONSUMPTION YIELD RECEIPT

11. One-Way model residuals distibutions • Contrarily to the literature, the distributions that fit Belgian FADN data are For yield and Receipts: Logistic For prices: Logistic and other asymmetric distributions (Loglogistic,…) • Logistic vs. Normal distribution • More ‘peaked’ and fatter tail • Implications on insurance premia calculations

12. Origin of the variability Elasticities using a double-logarithmic regression on the residuals of the one-way model log(var(Receiptjn)) = αj * log(var(Pricejn)) + βj * log(var(Yieldjn))+ εjn j = product n = farm Source : FADN(1995-2001) ! Prices very stable for subsidized crops during the period 1995-2001 ! Potatoes: Variability of receipts are due mostly to variability of prices

13. Consequences for Insurance and Simulations • Simulations : • Joint estimation of yield and price • Logistic and Log-logistic distributions • Insurance : • Per farm (historical data needed) • Logistic and Log-logistic distributions • What instrument for income stabilization in the future? • Variability of receipt may no longer be caused by yield variability only • Are crop insurance or income insurance appropriate?