modelling the eu agriculture and policy: departing from the first best world
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Modelling the EU agriculture and policy: Departing from the first best world. Alexandre Gohin [email protected] 122 EAAE Seminar February 17-18 2011 Ancona (Italy). Operational market models. PE models AGLINK COSIMO CAPRI ESIM AGMEMOD FAPRI PEATSIM IMPACT ATPSM. - PowerPoint PPT PresentationTRANSCRIPT
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Modelling the EU agriculture and policy: Departing from the first best world
Alexandre Gohin
122 EAAE Seminar
February 17-18 2011
Ancona (Italy)
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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 »
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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
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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
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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
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Impact on EU price
Wheat Beef Dairy
No budget 3.6 1.3 0.8
Fixed income
2.6 0 -0.5
CGE 1.8 -1.5 -2.1
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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 ?
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Standard specification
H
CIP
PCIPTIY
TdpDPts
TIYts
DPTRIPYEts
YEW
DPTRIPYWEC
Y
YY
...
.1....
...~..
..~.2
1...max
1.
1
1
1
10
22
00
,,
PdpR
TdpR
WNFW .0
Our modelling contribution :
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Illustration on US cornProduction Final wealth
Standard specificationDirect paymentsMarket price support
-0.067-7.98
-3.58-0.51
Our specification
Direct paymentsMarket price support
-1.18-8.31
-39.79-14.94
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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?
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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.
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Welfare impacts
“Producer surplus” (cap+land) Crop Animal Services
-24.0-41.8+32.8
-24.8-42.2
-
-24.4-42.0+2.5
Taxpayer “surplus”Values of preceding taxes/subsidies
+51.0
+50.2
+49.7
“Consumer surplus”Disposable incomeEV
-13.4+8.9
-
+29.7
-40.8-19.1
“Total Welfare” +8.9 +12.8 -19.1
Standard GE PE Distorted GE
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2.b. « Real » figures
• Using the own made CGE model on EU
• Removing the CAP– Without imperfections– With imperfect price transmission– With unemployment
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Welfare impacts (billion euros)
-16
-14
-12
-10
-8
-6
-4
-2
0
2
4
First best Transmission Chomage
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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 ?
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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
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Trade reform with rational expectattions
Prix du blé européen
-1,6%
-1,4%
-1,2%
-1,0%
-0,8%
-0,6%
-0,4%
-0,2%
0,0%
1 2 3 4 5 6 7 8 9 10 11
Sans erreurs
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Trade reform with nerlovian expectations
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
1 2 3 4 5 6 7 8 9 10 11
Sans erreurs Avec erreurs
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Trade reforms with nerlovian expectations and investment
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
1 2 3 4 5 6 7 8 9 10 11
Avec erreurs Investissements
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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 ?
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The EU wheat price following CAP reform
-10
-5
0
5
10
15
20
25
2011 2016 2021 2026 2031 2036 2041 2046 2051 2056
Rational-Brutal Rational-gradual Imperfect-Brutal Imperfect-gradual
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The EU welfare following CAP reform
-1500
-1000
-500
0
500
1000
1500
2011 2016 2021 2026 2031 2036 2041 2046 2051 2056
Rational-Brutal Rational-gradual Imperfect-Brutal Imperfect-gradual
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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
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Effects of the US biofuel policy on corn
Price Production
Without risk Total 26%
11.6%
2nd order risk aversion
Total 27% 11.4%
3rd order risk aversion
Total 30% 5.6%
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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