Transcript Modelling the EU agriculture and policy: Departing from

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
–
–
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–
–
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AGLINK COSIMO
CAPRI
ESIM
AGMEMOD
FAPRI
PEATSIM
– IMPACT
– ATPSM
• CGE models
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–
–
–
–
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GTAP Agri
MIRAGE
LEITAP(MAGNET)
LINKAGE(ENVISAGE)
GLOBE
GTAPPEM
– « ID3-Momagri »
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
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
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
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
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 ?
Standard specification
1

2
2
max EC  W0   PY .Y  PCI .I  R.T  DP  .
.
Y
.

PY
Y , I ,T
2 W0  E ~ 
s.t. E ~    .Y  P .I  R.T  DP
PY
s.t. Y   0 .  1 .I

s.t. DP  dp.TH
CI
 1

 1   1 .T
 1



 .
Our modelling contribution :
 R dp 
.TP
W0  WNF  




R
dp


 1
Illustration on US corn
Standard
specification
Direct payments
Market price support
Production
Final wealth
-0.067
-7.98
-3.58
-0.51
-1.18
-8.31
-39.79
-14.94
Our specification
Direct payments
Market price support
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?
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.
Welfare impacts
Standard GE
PE
Distorted GE
“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 income
EV
-13.4
+8.9
+29.7
-40.8
-19.1
“Total Welfare”
+8.9
+12.8
-19.1
2.b. « Real » figures
• Using the own made CGE model on EU
• Removing the CAP
– Without imperfections
– With imperfect price transmission
– With unemployment
Welfare impacts (billion euros)
4
2
0
-2
-4
-6
-8
-10
-12
-14
-16
First best
Transmission
Chomage
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 ?
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
Trade reform with rational expectattions
Prix du blé européen
0,0%
1
2
3
4
5
6
7
-0,2%
-0,4%
-0,6%
-0,8%
-1,0%
-1,2%
-1,4%
-1,6%
Sans erreurs
8
9
10
11
Trade reform with nerlovian expectations
40%
30%
20%
10%
0%
1
2
3
4
5
6
7
8
-10%
-20%
-30%
-40%
-50%
Sans erreurs
Avec erreurs
9
10
11
Trade reforms with nerlovian expectations
and investment
40%
30%
20%
10%
0%
1
2
3
4
5
6
7
8
-10%
-20%
-30%
-40%
-50%
Avec erreurs
Investissements
9
10
11
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 ?
The EU wheat price following CAP
reform
25
20
15
10
5
0
2011
2016
2021
2026
2031
2036
2041
2046
2051
2056
-5
-10
Rational-Brutal
Rational-gradual
Imperfect-Brutal
Imperfect-gradual
The EU welfare following CAP
reform
1500
1000
500
0
2011
2016
2021
2026
2031
2036
2041
2046
2051
2056
-500
-1000
-1500
Rational-Brutal
Rational-gradual
Imperfect-Brutal
Imperfect-gradual
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
Effects of the US biofuel policy
on corn
Price
Production
Without risk Total
26%
11.6%
2nd order
Total
risk aversion
27%
11.4%
3rd order
Total
risk aversion
30%
5.6%
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