Modeling the Uncertainty: the Farmers Behavior in the Alentejo Region of Portugal facing to the New CAP

1. Modeling the Uncertainty: the Farmers Behavior in the Alentejo Region of Portugal facing to the New CAP Coelho, Luís Alberto Godinho Serrão, Amílcar Joaquim da Conceição UNIVERSIDADE DE ÉVORA PORTUGAL

2. Contents 1- Introduction 2 - Methodology 3 - Data 4 - Results 5 - Conclusions 6 - Bibliography

3. 1 - Introduction The uncertainty of the farmer’s income has been one of the greatest concerns of the successive Common Agricultural Policy (CAP) reviews. These policies have looked for stabilizing the farmer’s income through subsidies. • Creation of CAP (1957) Sustainability of the incomes through the prices. Increase of the surplus and growth of the costs. • The 1992 Reform Creation of a set of direct aids Strong orientation for the market Restricting issues of the use of the production factors • The 1999 Reform Decrease of market support prices and of financial compensation in crop and livestock activities

4. The subsidies became one of the main criteria of the farmer’s decisions. Example: Before 1992 the durum wheat had a small production area in Portugal and the common wheat has the main crop produced in Portugal. The 1992 CAP review stabilised a subsidy of 297 ECUS/hectare for one maximum area of 59 000 hectares. The 1999 CAP review stabilised an increased of the durum wheat area to 118 000 hectares in Portugal and the subsidy per hectare has been increasing to € 344.50. The consequence of the CAP policy was the decrease of the common wheat (with small subsidies) and the durum wheat became the main crop in Portugal.

5. The mid-term review of the Common Agricultural Policy (2003) • Decrease in market support prices • Decoupling subsidies from production • Decrease of direct payments for large farms • Possibility of partial implementation of the decoupling subsidies Main problem for Portugal: Risk of abandonment of the crop production

6. The Problem With the mid-term review of the Common Agricultural Policy in 2003, that allows to decoupling total or partially the subsidies from agricultural production, the farmers will start to make agricultural production decisions based on the soils and climatic conditions and the signals revealed by agricultural markets. This situation can drive a decrease and even the abandonment of agricultural production in the Alentejo Dryland region of Portugal.

7. Research Objectives This research work have two objectives: The first one foresees the behaviour of the Alentejo Dryland farmers, when they are confronted with the mid-term of the Common Agricultural Policy with respect to two scenarios: • Full decoupling of income payment from agricultural production. • The Portuguese Government proposal (some subsidies are linked to beef cattle and sheep production). The last one evaluates the behaviour of selected farmers facing to the introduction of an area yield crop insurance in the context of the new Common Agricultural Policy.

8. Area Yield Crop Insurance • Considered by Halcrow in 1949 • It is an income insurance • Indemnities are based on the average production of the total production area • It allows to minimize damages of unfavorable climatic conditions • It is included in the "green box" of the World Trade Organization (WTO) • It prevents problems of Adverse Selection and Moral Hazard

9. 2 - Methodology The analysis of the farmers’ behaviour facing to the mid-term review of the Common Agricultural Policy is based on the Cumulative Prospect Theory, which is portrayed in the objective function of a discrete sequential stochastic programming model. The objective function

10. The Value Function • Principals characteristics: • Risk aversion for gains • Risk preferred for losses • Loss aversion The farmer's preferences for the construction of the value function were elicited by the “trade-off” method (Wakker and Deneffe, 1996).

11. Decision Weights

12. Probability Weighting Function Main characteristics: δ – Attractiveness γ – Diminishing Sensitivity The farmer's preferences for the construction of the probability weighting function were elicited by the certainty equivalent method.

13. Constraints The constraints describe the environment in that the farmers developed their crop and livestock activities in all their components: production (crop and livestock), financial, commercial and taxes.

14. Main characteristics of the model • Modeling the animal feeding (three technologies of beef cattle and two of sheep) • Possibility to buy and to sell straw and hay • Partition of the subsidies in productionsubsidies and decoupled subsidies • Possibility to constitute loans for financing the farm activity • Possibility to subscribe the area yield crop insurance • Free variables (net incomeand incomebefore taxes) • The net income by state of natureare transferred to the objective function • Non linear objective function with two components (negative part (losses) and positive part (gains)) • The Model was solved by an optimization software called “MINOS PROGRAM”, because it allows to program the objective function in FORTRAN.

15. 3 – Data • The development of an optimization model is extraordinarily demanding in terms of data. • The data and other information can be collected from studies and research works, Government Agencies and European Union. • The main information source was obtained through interviews to a set of farmers in the Alentejo dryland region. • These farmers were selected by a nonprobabilistic judgmental sampling. • The interviews, besides they intended to determine the farmers’ risk attitudes, allowed collecting same farm specific data to develop farmer’s optimization model.

16. 4 – Results The behavior of farmers face the risk Parameters of the Value Function

18. The value functions are used to estimate the probability weighting functions, whose values are represented in the following table: Parameters of the Probability Weighting Function

20. RESULTS Production activity of farmers before the New CAP Notes: Crop activities in hectares, livestock activities in animal units and monetary values in Euros. Source: Model Results.

21. RESULTS Model Results with the new CAP– Total Decoupling Payments Notes: Crop activities in hectares, livestock activities in animal units and monetary values in Euros. Source: Model Results.

22. RESULTS Model Results with the new CAP– Partial Decoupling Payments Notes: Crop activities in hectares, livestock activities in animal units and monetary values in Euros. Source: Model Results.

23. RESULTS New CAP and Area Yield Crop Insurance – Total Decoupling Notes: Crop activities in hectares, livestock activities in animal units and monetary values in Euros. Source: Model Results.

24. RESULTS New CAP and Area Yield Crop Insurance – Partial Decoupling Notes: Crop activities in hectares, livestock activities in animal units and monetary values in Euros. Source: Model Results.

25. RESULTS Value of the Alternatives Source: Model Results. • Total decouplingof the subsidies from the production is the scenario preferred by the farmers of this study. • They also preferred the area-yield crop insurance program with the full decoupling of subsidies.

26. 5 - Conclusions • The total decoupling of the subsidies leads to the decrease of the sheep and crop (durum wheat) production, as well as the abandonment of farmers’ activities without livestock production; • The Portuguese Government proposal allows keeping sheep production; • The farmers want to subscribe the area yield crop insurance program since the Government pays a part of the premium; • The introduction of the area yield crop insurance allows a small increase of crop production, when it is compared with the scenario without insurance; • When the insurance is introduced in the Portuguese Government proposal leads to the increase of sheep production, when it is compared with the scenario without insurance; and, • The area yield crop insurance can constitute a way to prevent the decrease of the agricultural production facing to the new Common Agricultural Policy.

27. 6 - Bibliography Hardaker, J., R. Huirne and J. Anderson. 1997, Coping with Risk in Agriculture, Wallingford: CAB International. Kahneman, D. and Tversky, A. 1979, Prospect theory: an analysis of decisions under risk. Econometrica 47, 263-291. Gonzalez, R and G. Wu, 1999, On the Shape of the Probability Weighting Function, Cognitive Psychology 38, 129-166. Miranda, Mario J. (1991). “Area -Yield Crop Insurance Reconsidered”, American Journal of Agricultural Economics 73, 233-242. Quiggin, J.C. 1982, A theory of anticipated utility. Journal of Economic Behavior and Organization 3, 323-343. Tversky, Amos; Daniel Kahneman, 1992, Comulative Prospect Theory: an analysis of decision under uncertainty, Journal of Risk and Uncertainty 5, 297-323. Wakker, Peter and Daniel Deneffe, 1996, Eliciting von Neumann-Morgenstern Utilities when Probabilities are Distorted or Unknown, Management Science, 42, 1131-1150.