Modelling the EU agriculture and policy: Departing from the first best world

1. Modelling the EU agriculture and policy: Departing from the first best world Alexandre Gohin Alexandre.Gohin@rennes.inra.fr 122 EAAE Seminar February 17-18 2011 Ancona (Italy)

2. Operational market models • PE models • AGLINK COSIMO • CAPRI • ESIM • AGMEMOD • FAPRI • PEATSIM • IMPACT • ATPSM • CGE models • GTAP Agri • MIRAGE • LEITAP(MAGNET) • LINKAGE(ENVISAGE) • GLOBE • GTAPPEM • « ID3-Momagri »

3. Messages of the presentation • PE models should be used with CGE thinking • Impact of energy prices on agriculture • Wealth effects of direct payments • CGE models should be used in second best world • Labor market rigidities • Imperfect price transmission • More modelling efforts should be devoted to dynamic, stochastic and financial issues • The issue of expectations and the costs of information • Downside risk aversion

4. 1.a. Impacts of energy prices on agricultural prices • Biofuels + • Quid of the contribution of market forces / policy instruments • Production costs + • Transport/processing costs – • Macro-economic effects ? • Mostly ignored in PE analysis • CGE results : macro-economic closure matters

5. Our methodological approach • Starting point : GTAP standard model (GTAP 6 database) • Introduction of GTAP-E and GTAP-Agr specifications • Latent separability here • Three macro-economic closures • Da = f(Pa) : No budget constraint • Da = f (Pa, Pe, Income=Income0) Fixed income • Da = f(Pa,Pe,Income) CGE • 20% decrease of oil reserve

6. Impact on EU price

7. 1.b. Wealth effects of direct payments • Large literature on the coupling effects of lump sum payments • No longer production neutral with market failures (fixed costs, credit constrained, …) • Wealth effects of risk averse farmers (with DARA) • Overall limited effects • What is wealth ?

8. Standard specification Our modelling contribution :

9. Illustration on US corn

10. 2. CGE results in second best • Welfare computed by CGE models can be decomposed in initial distortions and endowments effects : • EV = sum(i, tmi*Mi) + sum(f, wf*Qf) • By definition all policies should be removed. A policy can be welfare improving only due to the presence of other policies. • Where are the market imperfections ? Public goods, externalities, imperfect competition, informational failures?

11. 2.a. First illustration • Starting with the standard GTAP framework : • A PE version where prices and productions of other goods, regional incomes and wages are fixed • A « Distorted » GE model with wage rigidity and unemployment (like Harrison et al (1993) or Mercenier (1995)). • Simulation of a complete removal of the CAP.

12. “Producer surplus” (cap+land) Crop Animal Services Taxpayer “surplus” Values of preceding taxes/subsidies -24.0 -41.8 +32.8 +51.0 Standard GE -24.8 -42.2 - +50.2 PE +49.7 -24.4 -42.0 +2.5 Distorted GE “Consumer surplus” Disposable income EV -13.4 +8.9 - +29.7 -40.8 -19.1 “Total Welfare” +8.9 +12.8 -19.1 Welfare impacts

13. 2.b. « Real » figures • Using the own made CGE model on EU • Removing the CAP • Without imperfections • With imperfect price transmission • With unemployment

14. Welfare impacts (billion euros)

15. 3. Dynamic, stochastic analyses • Most available models are not truly dynamic, nor stochastic (no risk aversion) • Dynamics involve expectations • Two main theories in the past : rational expectations (forward looking) and nerlovian expectations (backward looking) • The information is not costless. What is the structure of information used by economic agents in our models, in real life ?

16. 3.a. Dynamic effects : trade reforms • First version : Gtap agri static • Second version : consistent dynamic CGE model with rational expectations (more difficult to solve) • Third version : Temporary GE with succession of static CGE models where dynamic decisions are made with imperfect knowledge of the future • Simulation of trade liberalisation by the EU and US

17. Trade reform with rational expectattions

18. Trade reform with nerlovian expectations

19. Trade reforms with nerlovian expectations and investment

20. 3.b. Policy implications • When designing policy reforms, trade off between economic and political economy pressures • Because people need to learn, there may be an optimal way of implementing policy reforms • How long should be the implementation period of CAP reforms ?

21. The EU wheat price following CAP reform

22. The EU welfare following CAP reform

23. 3.c. Risk analyses to third order • Use of the mean variance approach does not recognize that price series may be skewed (due to storage issues in particular) • Downside risk aversion not really taken into account • Analysis of the interaction between biofuel and food markets with focus on volatility

24. Effects of the US biofuel policy on corn

25. Concluding comments • Coupling models is interesting • But efforts should also be spend on dynamic and stochastic issues • Our direction : understand future markets and interaction with real economy • More generally analyse one fondamental issue justifying agricultural policy: risk in agriculture