CAPRI
CAPRI
CAPRI-Dynaspat Project
2004 - 2007
Modelling
Details
MTR
Simulation
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Exploitation
Tools
WTO
Simulation
Sugar
Simulation
Technical
Problems
GHG Emission
Abatement
1
CAPRI-Dynaspat Project
CAPRI
CAPRI
• EU-financed FAIR project (2004- 2007)
• six main partners, each responsible
for specific working fields for each team
• co-operators almost all EU-member states
(data base, analysis of model runs)
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2
History of CAPRI
CAPRI
CAPRI
• 1995:
Project proposal and prototyping
• 1996-1999: FP4 project „CAPRI“: overall model design, data
base, first trial scenarios
• 2000:
„Agenda“ proposal fails, time is used for
consolidation
• 2001-2004: FP5 project „CAP-STRAT“: methdological rehaul,
new MS data base, scenario analysis, sensitivity
analysis, validation
• 2001-2002 DG-Env project: farm type, Ammonia module (=>
improved N balances), water scarsity indicators
• 2002/2003 MTR scenario work for DG-AGRI
• 2002/2003 „Sugar study“ for DG-AGRI
• 2004-2007 FP 6 Strep „EU-MedAgpol“: Trade with Mediterrean
countries
• 2004-2007 FP 6 Strep „CAPRI-Dynaspat “
• Pending:
• Pending:
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a Strep regarding trade with South America
IP „SEAMLESS“
3
CAPRI-Network
CAPRI
CAPRI
Norwegian Agricultural Economics
Research Institute, Oslo
University College Galway,
Department of Economics
FAT,
Tänikon
Institute for
Agricultural Policy
(IAP), University
+ EuroCare
Bonn
Vuze, Prague
Joint Research
Centre, Climate
Change Unit,
Ispra
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4
Organisation
CAPRI
Bonn:
CAPRI
Co-ordination & Training of partners,
Overall model design, Recursive-Dynamic
version, scenario analysis
Prague:
East expansion of CAPRI
Ispra:
GIS link, bio-phyiscal model for Green House
Gas Emissions, Landscape indicator
Galway:
Labour projections and labour demand
Tänikon: Energy use indicator
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5
Project Partners I
CAPRI
COUNTRY
CAP-STRAT PARTNER
CAPRI
INSTITUTION
Austria
Franz Weiss
WPR Department of Economics, Politics and Law
Belgium
Bruno Henry de Frahan
Catholic University of Louvain
Kamel Elouhichi
Research Unit of Agricultural Economics
Czech
Republic*
Yvan Foltyn
Tomas Ratinger
Research Institute of Agricultural Economics
(VUZE)
France
Guillermo Flichman
CIHEAM – IAMM
Institut Agronomique Mediterranee de Montpellier
Germany*
Heinz-Peter Witzke
EuroCare
Germany*
Wolfgang Britz
Institute for Agricultural Policy
Thomas Heckelei
University Bonn
Udo Bremer
Markus Kempen
Greece
Christos Karelakis
University of Thessaloniki
Ireland*
Michael Cuddy
National University of Ireland, Galway
Eoghan Garvey
Department of Economics, Faculty of Commerce
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6
Project Partners II
CAPRI
COUNTRY
CAP-STRAT PARTNER
CAPRI
INSTITUTION
Italy*
Adrian Leip
Maria-Luisa Paracchini
Renate Koeble
Declan Mulligan
Joint Research Centre, Climate Change unit
Italy
Giuseppe Palladino
DIPROVAL - Sezione Economica
Marco Setti
Cesare Zanasi
Norway
Klaus Mittenzwei
Norwegian Agricultural Economics Research Institute
Sjur Spildo Prestegard
(NILF)
Leif Jarle
Spain
Jose M. Garcia AlvarezCoque
Departamento de Economia y Ciencias Sociales
Miguel Villanueva
Margalef
Sweden
Anders Backstrand
Swedish Institute for Food and Agricultural Economics
Switzerland*
Gaby Mack
Tim Kränzlein
Federal Research Station for Agricultural Economics and
Engineering
Portugal
Raul Fernandes Jorge
University of Lisboa
Joao Madeira
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7
Overview on tasks
CAPRI
•
CAPRI
Regular updates, reference run, scenario writing and impact analysis
– Regular updates of the data base (WP1)
– Reference runs (WP2)
– Yearly scenario analysis (WP 3)
•
Methodological Improvements of the existing modelling system
– Dynamic version of supply module (WP 4)
– Dynamic version of market module module (WP 5)
– Employment module (WP 7)
•
Improved environmental indicators and
link to a Geographical Information system for landscape assessment
–
–
–
–
•
Energy use indicator (WP 6)
CAPRI GIS Link (WP 8)
Landscape indicator (WP 9)
Greenhouse gas process model link (WP 10)
Preparation for East Expansion
– CAPRI east expansion pilot study (WP 11)
– CAPRI east epxansion network (WP 12)
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8
CAPRI-Dynaspat: WPs
CAPRI
Data Base
Updates (WP1)
D1/2/3
CAPRI
D25/27
D22
D4-6
D7-9
Expansion
East (WP11)
CAPRI-Soil
(WP10)
Reference
Runs (WP2)
Scenario
Analysis (WP3)
D24
D23
D26
Process
Model
Coco Data Base
(consistent & complete
time series
at MS level)
Environmental
& Economic
Indicators
Economic
Core Model
CAPRI Data Base
(consistent & complete
base year data set
for farm types at NUTS)
D11
GIS
D21
D13
D19
D15
D17
Dynamic
Supply (WP4)
Dynamic
Market (WP5)
Landscape
(WP9)
CAPRI- GIS
(WP8)
Energy
Use (WP6)
Employment
(WP7)
D10
D12
D20
D18
D14
D16
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9
CAPRI
Regular updates, reference run, scenarios
CAPRI
• Download latest available data from EuroStat,
DG-AGRI, FAO
• Reconcile data base (fill gaps, remove
inconsistencies, re-estimate input allocation
...)
• Check for new projections from FAPRI/DGAGRI/FAO, and revise reference run
• Contact DG-AGRI, define scenarios, run
model and perform impact analysis
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10
Methodological improvements
CAPRI
CAPRI
• Switch from comparative static (= long run
equilibrium) to recursive-dynamic version
(=show adjustment path)
• Re-estimate non-linear cost functions with
adjustment costs, embed annual herd size for
cattle
• Introduce partial adjustment model in the
market model
• Employment module (projection + link to
activities)
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11
Environmental indicators
CAPRI
CAPRI
• Introduce „engineering factors“ for energy use
in agricultual activities => energy indicator
• GIS link  develop distribution algorithm
from NUTS II results to grid (econometrics,
data on climate, soil, elavation etc. necessary
at NUTS II level)
• Bio-Phyiscal process model for GHG 
requires GIS link
• Landscape indicators
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12
East expansion
CAPRI
CAPRI
• „Pilot study“: full regionalisation of CZ, PL and
HG, all other MS only at NUTS 0
• Document proceeding to ensure that process
can be repeated (in an improved manner) in
the remaining MS
• Build up a network of suitable contacts in the
new MS to apply and maitain CAPRI
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13
CAPRI
CAPRI
A. Modelling Details
A.1. General Model Layout
A.2. Supply Model of CAPRI
A.3. Market Model of CAPRI
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A.1. General Model Layout
CAPRI
CAPRI
Quantities
Supply
Markets
200 Regional
optimisation
models
Multi-commodity
spatial market model
with 11 regional
aggregate
and all EU MS
Perennial
sub-module
Iterations
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Prices
Comparative Static Equilibrium
A. MODELLING DETAILS
15
Overview of the Supply model
CAPRI
Regional
Optimisation
Perennial sub-module
Prices
Quantities at
Country-Level
Aggregation
Q
Q
Q
Q
Market Clearing
Young Animals
for EU
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A. MODELLING DETAILS
CAPRI
• Product-Supply
• Input-Demand
• Net-Trade of
Young Animals
Market
16
Regional Programming Module
CAPRI
CAPRI
Alternative technologies possible
Objective
Function
Production
Activities
Feed-Use
Activities
Net-Trade
Activities
+ Premiums
- Cost +PMP terms
PMP Feed
Prices
+
+
-
Products
Feed Requ.
Nutrients
+
Arable Land
&
Gras land
+
< ha
+
< ha
+/–
<0
Set-aside
&
Quotas
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+
+
+
–
–
Constraints
+
A. MODELLING DETAILS
=0
>0
= surplus
< quota
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Policy Coverage in Supply Module
CAPRI
CAPRI
• Per ha/head premiums can be coupled to specific
technologies (e.g. biological)
• Crop specific set-aside obligations
• Sale quotas
• Limits on environmental externalities (e.g. N surplus
or output of Global Warming Gases)
• Price related support can be easily embedded (since prices
are exogenous)
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A. MODELLING DETAILS
18
CAPRI
Positive Mathematical Programming
CAPRI
• Ensures calibration to base year levels
• Results in a smooth supply response to changes in
economic conditions by the introduction of quadratic cost
functions
• Approach in CAPRI:
• Animal activities: calibrated to exogenous
elasticities
• Crop activities: estimated by Maximum
Entropy approach
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A. MODELLING DETAILS
19
CAPRI
Overview of the Perennial Sub-Module
CAPRI
• Long-term investment decisions in perennials can not be
handled in an aggregated programming approach
• Data on the relevant economic variables (removals, new
planting, age compositions of tree, investment costs etc.)
are scarce
• Solution => econometrically estimated time series models
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A. MODELLING DETAILS
20
Overview of the Cattle Sub-Module
CAPRI
Beef
Milk Cows
Suckler
Cows
Fattening
female
Calves
Female
Calf
Male
Calf
Veal
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Fattening
male
Calves
A. MODELLING DETAILS
Young
cow
Breeding
Heifers
Raising
female
Calves
Young
heifer
Raising
male
Calves
Young
bull
Male adult
cattle
High/Low
CAPRI
Fattening
Heifers
High/Low
Beef
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Overview of the Market Model
CAPRI
CAPRI
• Multi-Commodity Model for major agricultural products (11
regional aggregates plus EU splitted in 14 Member
States, 26 primary and processed products)
• Spatial system with bilateral trade streams using an
Armington approach
• Synthetic parameters in well-behaved functions
• Calibrated to simulation year for quantity and price
framework of other studies
• Differences between farm gate and consumer prices
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A. MODELLING DETAILS
22
Policy coverage in market model
CAPRI
CAPRI
• (Bilateral) import tariffs, Tariff Rate Quotas, …
• Export Subsidies with WTO commitments
• Intervention stocks (with limits on them)
• PSE/CSE price elements
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A. MODELLING DETAILS
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Environmental indicators
CAPRI
CAPRI
• Integrated into supply models or linked to results
• N,P,K balances
• Output of NH3
• Output climate relevant gases
• Water balances for southern European countries
(under development)
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A. MODELLING DETAILS
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Major results
CAPRI
CAPRI
• Welfare analysis: agricultural income, consumer surplus,
FEOGA budget
• Market balances and bilateral trade streams for
agricultural products at a country level
• Acreages, herd sizes, yields, output and input use,
agricultural income indicators at per activity and region
• Environmental indicators at regional level
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A. MODELLING DETAILS
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Welfare Analysis
CAPRI
CAPRI
FEOGA Budget Composition:
Premium payments
= LEVL * PRME
Export subsidies
Subsidised volume
* (Padm-Pexp) * factor
Intervention
Purchased volume
* (Padm-PEU)
Stock holding cost
Base year cost/unit
inflated
Tariff income
Tariff income
= cost of administration
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A. MODELLING DETAILS
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Money Metric Utility
CAPRI
Indirect utility (GL):
g p 
vp, y   
y  f p 
p = prices, y = income
CAPRI
“how much expenditure
would be required at the
reference scenario prices
to reach the utility level of
the simulation“
Invert to expenditure:
g p 
ep,U   f p  
U
r


g
p
s
r
s
s
r
s
s




m  ep , vp , y   f p  
y

f
p
s
g p 
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A. MODELLING DETAILS
27
Agricultural income
CAPRI
CAPRI
• Primary factor income
• Gross concept – intermediary products both
outputs and inputs
• Simulation year’s price level
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A. MODELLING DETAILS
28
Processing cost
CAPRI
CAPRI
Profit function (normalised quadratic):
p   a   bi pi  12  cij pi p j
i
i
j
Netput supply function (from Hotelling‘s lemma)

xi p  
 bi   cij p j
pi
j
Parameter a is chosen so that the profit in the reference
equals output value minus fat and protein cost for dairy
products and 50% of output value for oil seeds.
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A. MODELLING DETAILS
29
Further features
CAPRI
CAPRI
• Module for stochastic analysis based on random yields at
NUTS II level integrated
• Trade module for emission permits
• Trade module for sale quotas (milk, sugar)
• Farm type module under development,
based on FADN data
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A. MODELLING DETAILS
30
Data Base Issues
CAPRI
CAPRI
REGIO
Eurostat
COCO
CAPRI
IAP/EuroCARE
Expert Data
CAPRI Data Base
1990-99, EU-Member States +
Norway
NUTS 2 level:
• Production activities: I/Ocoefficients and levels
• Political variables
MS-level (mainly COCO):
• Prices
• Farm & Market balances
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A. MODELLING DETAILS
31
CAPRI
Product/Activity coverage of data base
CAPRI
• 8 cereals, 5 oilseeds, 6 other annual crops,
fodder maize, fodder root crops, other fodder from arable
land, grass & grazing, fruits, vegetables, wine, nurseries,
flowers, other crops
• It entails a detailed description of animal activities: cattle,
pig fattening, sows, laying hens, poultry fattening, sheep
& goat for milk, sheep & goat for fattening
• 6 feeding stuff as inputs, 8 young animal categories,
4 fertiliser, 8 further inputs
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A. MODELLING DETAILS
32
Main elements of the data base
CAPRI
CAPRI
• Economic Accounts of Agriculture (EAA)
• Farm & market balances for outputs/inputs
• Unit value prices (consistent link between EAA
and market balances)
• Simultaneous estimation techniques under constraints
(it guarantees a closed and complete data base)
• Acreages and herd sizes
• Input/Output coefficients and income indicators for
activities
• Policy variables (premiums, tariffs, ...)
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A. MODELLING DETAILS
33
Software
CAPRI
CAPRI
• PC-based System (Windows NT/95)
• Data Base Management realized in FORTRAN 77
• Economic model based on GAMS
• Comfortable user interface
(C, commercial GUI, Java solution under development)
• Capri specific modules
• Ready-to-use tools (e.g. DAOUT for data viewing)
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A. MODELLING DETAILS
34
Result exploitation
CAPRI
CAPRI
• Direct link from GAMS model to
• Java-based mapping tools (Nuts 2)
• XML tables
• Backflow of output into the data base
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A. MODELLING DETAILS
35
A.2. Supply Model of CAPRI
CAPRI
CAPRI
• One aggregate programming model per NUTS II region
• Only limited number of constraints (arable/ grass land, setaside obligations) to steer allocation of activity levels
• Objective function maximizes regional income
• Regional income is defined as:
• revenues from selling outputs
• plus premiums
• minus purchases of variable inputs
• Theory behind: Mathematical programming under
inequality constraints (Kuhn-Tucker conditions)
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A. MODELLING DETAILS
36
An aggregate programming model
CAPRI
Margins m
(yield*price-variable cost)
Objective value
n
Objective
Function
Endogenous
variables,
here activity levels
max z   m j x j
x j 0
n
Constraints
j 1
s.t. aij x j  bi
 
j 1
I/O coefficients
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CAPRI
A. MODELLING DETAILS
Shadow prices
of constraints
Constraint vector
37
Theory: Mathematical programming
CAPRI
Programming model
Lagrange function
n
max z   m j x j
x j 0
n
n


max L   m j x j   i  bi   aij x j 
x j 0,
j 1
i 1
j 1


n
j 1
s.t. aij x j  bi
CAPRI
 
m
j 1
First order conditions (Kuhn - Tucker)
Revenue Exhaustion
(margin = opportunity
costs)
Constrains must hold
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A. MODELLING DETAILS
m
L
 m j   i aij  0  x j 0
x j
i 1
n
L
 bi   aij x j  0  i 0
i
j 1
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More Theory: Kuhn-Tucker I
CAPRI
CAPRI
How do Kuhn-Tucker conditions work for ACTIVITIES:
L
 m j   i aij  0  x j 0
x j
i 1
m
Complementary slackness
if
xj  0:
if
m


 m j   i aij   0
i 1


m < OC
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xj  0:
m


 m j   i aij   0
i 1


m = OC
A. MODELLING DETAILS
One of them must be 0
m


 m j   i aij  x j  0
i 1


Realised activities are those
whose gross margin m cover the
opportunity costs OC,
i.e. constraints valued with
shadow prices (Euler’s theorem)
39
Kuhn-Tucker II
CAPRI
CAPRI
How do Kuhn-Tucker conditions work for CONSTRAINTS:
n
L
 bi   aij x j  0  i 0
i
j 1
Derivative wrt Lagrange multiplier
if
One of them must be 0
n


 bi   aij x j i  0


j

1


if i  0 :
i  0 :
n


 bi   aij x j   0


j 1


n


 bi   aij x j   0


j

1


A constraints gets a
positive value
only if it is scarce.
Constraint is not exhausted
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A. MODELLING DETAILS
40
Primal and Dual Model
CAPRI
“Primal” model
“Dual” model
m
min w   i bi
n
max z   m j x j
x j 0
n
i  0
j 1
s.t. aij x j  bi
 
j 1
Explicit technology
• Each primal model has a dual formulation
• Optimal objective values of both are equal
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CAPRI
A. MODELLING DETAILS
i 1
m
s.t. aij i  m j
x
i 1
Explicit valuation of
resources for each activity
(must be at least equal to
the gross margin m)
41
K.T. of the Dual Model
CAPRI
CAPRI
Lagrange function of the “Dual” model
m


min L   ibi   x j  m j   aij i 
i  0, x
i 1
j 1 
i 1

n
L
The Lagrange function
 bi   aij x j  0  i  0
i
j 1
of the dual model has
m
n
m
L
 m j   aij i  0  x j  0
x j
i 1
the same derivatives
as the primal model.
 As first order conditions are identical,
objective values are identical as well.
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A. MODELLING DETAILS
42
Conclusions of the Dual Model
CAPRI
CAPRI
• Objective values of both primal and dual model are equal:
 optimal primal objective value equals
resource endowment valued with optimal shadow prices.
(Euler’s theorem)
• Both models comprise the same optimal “primal” variables
(e.g. the activity levels) and “dual” ones (e.g. the shadow
prices of binding resources)
• The optimal solution is best understood by looking at the
First Order Conditions
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A. MODELLING DETAILS
43
A.3. Market Model of CAPRI
CAPRI
CAPRI
What is a Multi-Commodity Model (MCM) ?
• More than one output market, but not general equilibrium
• System of equations: no objective function
• Same number of endogenous variables
as equations (so called square system, CNS)
• Many examples:
• SWOPSIM (http://usda.mannlib.cornell.edu/data-sets/trade/92012/)
• AGLink OECD
• FAPRI (http://www.fapri.missouri.edu/)
• AgMemod (http://tnet.teagasc.ie/agmemod/public.htm)
• WATSIM (http://www.agp.uni-bonn.de/agpo/rsrch/wats_e.htm)
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A. MODELLING DETAILS
44
CAPRI
Elements of a Multi-Commodity Model
CAPRI
• “Behavioural functions”:
they define quantity, supply function
• “Price linkage function”:
it defines e.g. import prices from border prices
and tariffs
• How does it work ?
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A. MODELLING DETAILS
45
CAPRI
Flowchart of a Multi-Commodity Model
CAPRI
World Market
Balance
Solver
World Market
Prices
Regional
Prices Pr
Supply
Sr=f(Pr)
Regional
Prices Pr
Demand
Dr=f(Pr)
Net Trade
NTr=Sr-Dr
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A. MODELLING DETAILS
Supply
Sr=f(Pr)
Demand
Dr=f(Pr)
Net Trade
NTr=Sr-Dr
46
Differences between MCMs
CAPRI
CAPRI
• Comparative static (WATSIM, CAPRI) versus
recursive dynamic (FAPRI, AgLink)
• (At least partially) estimated parameters
(FAPRI, AGLink) versus calibrated,
synthetic parameters (WATSIM,CAPRI)
• Net trade approach (FAPRI, AgLink, CAPRI I) versus
spatial approach (CAPRI II, WATSIM II)
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A. MODELLING DETAILS
47
Spatial models
CAPRI
CAPRI
• Bilateral trade streams included
• Two standard types:
• Transport cost minimisation
(either per explicit welfare maximisation,
or by implicitly derived FOC => MCP solution)
• “Armington assumption”:
Quality differences between origins,
let consumers differentiate
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A. MODELLING DETAILS
48
Armington Approach
CAPRI
CAPRI
• Armington, Paul S. (1969)
"A Theory of Demand for Products Distinguished
by Place of Production,“ IMF Staff Papers 16, pp. 159-178.
• CES-Utility aggregator max xi ,r   i ,r   i ,r ,r1M i ,r ,r1  
 r1

for goods consumed
s.t.  M i ,r ,r1 Pi ,r ,r1  Y
from different origins
1 
r1
xi,r Aggregated utility from imports/domestic sales
Mi,r,r1 Import streams including domestic sales



shift parameter
share parameter
parameter related to substitution elasticity
i product, r importing regions, r1 origins
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A. MODELLING DETAILS
49
FOC of the Armington Approach
CAPRI
CAPRI
• First order conditions(FOC) from CES-Utility aggregator
M i , r , r1
M i ,r ,r 2
  i ,r ,r1 Pi ,r ,r 2 


  i ,r ,r 2 Pi ,r ,r1 
1 1  
• Relation between import streams is depending on:
• so called “share parameters”
• multiplied with the inverse import price relation
• exponent the substitution elasticity
• Imperfect substitution (“sticky” import shares)
MENU
A. MODELLING DETAILS
50
Flowchart of a 2 region Armington
CAPRI
Regional
Prices Pr
Regional
Prices Pr
Supply
Sr=f(Pr)
Domestic Sales
Imports

 
xi ,r   i ,r   i ,r ,r1M i ,r ,r1 
 r1

1 
Supply
Sr=f(Pr)
Domestic
Sales
Imports

 
xi ,r   i ,r   i ,r ,r1M i ,r ,r1 
 r1

Demand
Dr=f(Pr)
MENU
CAPRI
1 
Demand
Dr=f(Pr)
A. MODELLING DETAILS
51
CAPRI
Problems of the Armington Approach
CAPRI
• Few empirical estimations of the parameters
=> substitution elasticities are set by a “rule-of-thumb”
• A zero stream in the calibrated points
remains zero in all simulation runs
• The sum of physical streams (domestic sales + imports)
is not equal to the utility aggregate in simulations !!!
(demand “quantities” are not longer tons,
but a utility measurement ...)
MENU
A. MODELLING DETAILS
52
CAPRI
Why a new market model for CAPRI ?
CAPRI
• Endogenous (world market) prices are a must
• We cannot rely on third party models
(e.g. AgMemod or WATSIM) for our market part
• The current solution had some disadvantages:
• Only one rest-of-the-world aggregate
• Unsatisfactory functional forms (double-logs)
• Net-trade approach
MENU
A. MODELLING DETAILS
53
Two-Stage Armington in CAPRI
CAPRI
CAPRI
Demand (Arm1) =
Human consumption
+ Feed Use + Processing

Arm i ,r  sp1i ,r dpi ,r ,rwImports i ,r
Domestic Sales
(DSales)

 dpi ,r ,r DSales i ,r
Imports (Arm2)
Imports i ,r

 
 sp 2i ,r  dpi ,r ,r1Streamsi ,r ,r1 
 r1

Streams(R,R1,XX)
MENU

  1 
A. MODELLING DETAILS
....
1 
Streams(R,Rn,XX)
54
Why new functional forms ?
CAPRI
CAPRI
• Welfare analysis requires consistency to micro-theory:
• Homogeneity of degree zero in prices
(“inflation does not matter”/“only relative price matter”)
• Correct curvature: increasing marginal costs,
respectively decreasing marginal utility
• Symmetry of second derivatives
• Monotonic increasing/decreasing functions
• For double-log functions, conditions can only be imposed
at the calibrated point
• Double-log functions behave sometimes curiously
due to fixed elasticities
MENU
A. MODELLING DETAILS
55
Which functional forms I ?
CAPRI
CAPRI
• Normalised quadratic for supply and feed demand:
xi   i   bij
pj
pn
• Homogeneity in prices guaranteed by dividing each price
j
by normalisation price (“the non-agricultural product”)
• The matrix B is equal to the second derivatives with respect
to prices (with the exception of Pn)
• Cholesky decomposition can be used
to ensure globally correct curvature
• Monotonicity unfortunately not guaranteed
MENU
A. MODELLING DETAILS
56
Which functional forms II ?
CAPRI
CAPRI
• Generalised Leontief for Human consumption:
pj
b
ij
xi  d i 
j
 b
kj
k


 Y   d k pk 
pk p j 
k

pi
j
• d = consumption quantities independent of prices/income
• the corresponding expenditures are subtracted from income
• the remaining income is distributed according to B
and price relations
• Homogeneity in prices guaranteed (price relations)
• if all off-diagonal elements of B are positive,
curvature is correct <=> only substitutive relations !
• Monotonicity is not guaranteed
MENU
A. MODELLING DETAILS
57
How to define parameters I
CAPRI
Original
elasticities
Consistent
elasticities
CAPRI
Consistent
parameters
Objective:
keep close
to original ones
Constraints of minimisation problem
Homogeneity
Symmetry
Correct
Curvature
Restrictions:
Micro theory
MENU
A. MODELLING DETAILS
58
How to define parameters II
CAPRI
CAPRI
• Search for matrix of elasticities as close as possible
to the given ones (it works for feed and supply)
• so that
(1) homogeneity,
(2) definition of second derivatives,
(3) symmetry,
(4) and curvature
are fulfilled at the calibrated points
• The H matrix is equal to the B
matrix of the NQ for supply and feed,
min  e
ij
e
s.t. (1)

given 2
ij
e
i, j
e
ij
0
j
qi
(2) H ij  eij
pj
(3) H ij  H ji
(4) H ij   Lik L jk
k
if pn is set to unity in the base year
MENU
A. MODELLING DETAILS
59
Further Complications: Policy
CAPRI
CAPRI
• Standard Multi-commodity models comprise policy
only as price wedges (tariffs, PSE/CSE concept)
• CMO (Common Market Organisations) comprise
additional instruments (trigger prices: PADM; flexible levies;
intervention purchases: INTP),
with complications as WTO limits on subsidised exports
• “Kinked” behaviour for the policy agent:
IntPi  0  PMrki  PADM i
MENU
A. MODELLING DETAILS
60
“Kinked” policy instruments
CAPRI
CAPRI
• Solution either by “Mixed-Complementary Programming”
• + Complementary slackness conditions defined explicitly
• - Require specific solvers
• Or by “fudging functions” which smooth out kinks
• + no switch of solver necessary
• + no 0/I solution by behavioural functions for policy agent
• - steep derivatives can render solution difficultly


i

IntPi  IntM i 1  1 exp  
PMrki  PADM i
  i PADM i


MENU
A. MODELLING DETAILS




61
Function for intervention stocks
CAPRI


i
IntPi  IntM i 1  1 exp  
PMrki  PADM i
  i PADM i


• INTPi
• INTMi
•
•
CAPRI




purchases to intervention stocks
maximum intervention purchases allowed
defines steepness of function
percentage of PADMi at which INTPi is 50% of INTMi
PMrk
PADM
 PADM
INTP
50% INTM
MENU
A. MODELLING DETAILS
INTM
62
Function for subsidised exports
CAPRI


i
ExpSi  QutEi 1  1 exp  
PMrk i  PADM i
  i PADM i


• EXPSi
• QUTEi
•
•
CAPRI




quantity of subsidised exports
WTO commitment on subsidised exports
defines steepness of function
percentage of PADMi at which EXPSi is 50% of QUTEi
PMrk
PADM
 PADM
EXPS
50% QUTE
MENU
A. MODELLING DETAILS
QUTE
63
Base year data
CAPRI
CAPRI
• 11 non-EU country aggregates:
USA,CAN,IND,CHN,CEE,HIT (High tariff traders),
CAD (Cairns developed), ANZ (Australia & New Zealand),
ACP, MED, ROW
• EU is broken down in 14 Member States (Belgium+Lux!)
• Data for EU stem from COCO/CAPREG
• Data for non-EU stem from WATSIM <= FAO
• Bilateral flows stem from Trains (WTO ?)
MENU
A. MODELLING DETAILS
64
Balanced base year data I
CAPRI
CAPRI
• Market balance sheet data for EU Member States
and EU aggregate are balanced in COCO already
• Transport streams from trade statistics are not in line
with given market balances
• Private Stock Changes should be removed
in a comparative static model
• Adjustment of non-EU data and transport streams
necessary
• Minimise squared normalised differences
for adjustable positions s.t. consistent balances
MENU
A. MODELLING DETAILS
65
Balanced base year data II
CAPRI
min  x
pos
i ,r
x , flows
s.t.
1
2
    flows
pos 2
i ,r
 xbas
r ,i , pos
i , r , r1
 flowsbasi ,r ,r1
CAPRI

2
r , r1
xr ,i , prdt   flowsr1,r ,i  int sr ,i
r1
xr ,i , feed  xr ,i , Hcon  xr ,i ,Proc   flowsr ,r1,i
r1
X, xbas = corrected/given positions from balance sheets
flows, flowsbas = corrected/given bilateral physical trade streams
i = products;
r,r1 = regions
prdt = production,
ints = interventions sales
Feed = Feed Use,
Hcon = Human consumption,
Proc = Processing
...the real program is slightly more complex!
MENU
A. MODELLING DETAILS
66
Trends in the market model I
CAPRI
CAPRI
• For non-EU country (aggregates),
shifters are borrowed from FAO @2030
• Human consumption:
captures the combined effect of population and income
growth as well as taste shifts
• Supply: the shifters comprise technical progress
and all other changes (land & water availability ...)
• The behavioural functions for these countries (aggregates)
are trimmed to shifted quantities and trend shifted prices
(based on world bank long term time series)
MENU
A. MODELLING DETAILS
67
Trends in the market model II
CAPRI
CAPRI
• For EU member states, human consumption
is shifted with population and income growth,
the latter applied to the calibrated income parameters
• where necessary, taste shifters had been introduced
• Supply and feed demand are re-calibrated
in each iteration to the aggregated results
from the programming models
MENU
A. MODELLING DETAILS
68
Overview of a country aggregate
CAPRI
CAPRI
Regional
Prices
Supply
Intervention sales
Armington
Stage 2
Aggregate
Domestic Sales
Export
subsidies ?
Export streams
Import Streams
and prices
Armington
Stage 1
aggregate
Processing
MENU
Human
consumption
Feed Use
A. MODELLING DETAILS
69
Processing
CAPRI
CAPRI
• Processing from primary to secondary products
is modelled explicitly for:
• Oilseeds
• Milk
• For other products, final demand includes the
processed raw quantities (e.g. the consumption
of cereals includes the processing to Pasta
or beer)
MENU
A. MODELLING DETAILS
70
Processing of oil seeds
CAPRI
CAPRI
• Fixed crushing yields for oil seeds
e.g. 0.4 t of cake and 0.6 t of oil per processed ton:
• Soya beans
• Rape seed
• Sunflower seed
 Soya oil and cake
 Rape oil and cake
 Sunflower oil and cake
• where crushed quantities of oil seed
depend on behavioural function:
log( crsh i )  a i  log( pi ) crshi
MENU
A. MODELLING DETAILS
71
Processing of milk
CAPRI
CAPRI
• Constraints ensure closed fat and protein balances
for processing of milk to outputs i = butter, skimmed
milk powder and other milk products:
%fat milkI milk   %fat i Oi
i
%prt milkI milk   %prt i O i
i
• Price of derived products of milk butter, skimmed
milk powder and butter equal to price of fat and
protein content plus processing costs
MENU
A. MODELLING DETAILS
72
Parameters and Variables
in the Market Module
CAPRI
Fixed parameters
•Elasticities:
•Supply
•Processing
•Human consumption
•Feed Use
•Technical parameters:
•Crushing yield
•Fat & protein content
of milk products
•Prices:
•Base year price
producer
•Marketing span
for final products
MENU
CAPRI
Scenario parameters
Endogenous Variables
•Demand shifts:
•Population growth
•GDP development
•Changes in
consumption pattern
•Production shifts
•Quantities:
•Supply
•Processing
•Human consumption
•Feed Use
•Intervention sales
•Bilateral trade flows
•Subsidised exports
Policy instruments:
•Import Tariffs
•Quotas on
subsidised exports
•Non market PSEs
•CSEs
•Tariff Rate Quotas
A. MODELLING DETAILS
•Prices:
•Producer price
•Consumer price
•Import prices
•Export subsidies
73
CAPRI
CAPRI
B. Exploitation Tools
B.1. XML Reporting Tool
B.2. Mapping Reporting Tool
B.3. Accessing the Data Base
MENU
74
B.1. XML Reporting Tool
CAPRI
• Go to the directory:
• NUTS 0
• NUTS II
• Farm
->
->
->
CAPRI
XML0
XML2
XML999
• In each directory three pre-defined files
• scenario.xml
-> access to results
• styles.xsl
-> change style of tables
• table.xsl
-> program code ... don’t bother about
• + lots of *.xml files containing the results from different runs
• e.g. USA98Expost.xml
• e.g. EU00000098Agenda.xml
MENU
B. EXPLOITATION TOOLS
75
Use of the XML Tool
CAPRI
CAPRI
• Order of the tables in the ‘selection menu’
• Welfare + EAA
• For product list of supply part of model
•Product + Demand balances
•Prices (EU,MS)
•Environmental indicators
•Tables with further information
• For product list of market part of model
•Product balances
•Prices
•Import/Export flows
•Tariff information
MENU
B. EXPLOITATION TOOLS
76
How to manipulate XML-tables
CAPRI
CAPRI
• General procedure
• Open scenario.xml with Editor
• Make change
• Save
• Re-open scenario.xml in Browser (or: reload over DOS-Prompt;
‘reload button’ in Browser doesn’t work !!! )
• Dimensions in each table
• Scenarios
• Regions
• Products/Activities
• Items
MENU
B. EXPLOITATION TOOLS
77
Manipulate scenario view - general
CAPRI
CAPRI
• Add/Delete a scenario
Comparison
(percentage or
absolute differences)
against ... Result type
Define title of scenario
Show in ALL tables
Result type of scenario
or only in certain ones (SCEN)
MENU
B. EXPLOITATION TOOLS
78
Manipulate view of certain table I
CAPRI
CAPRI
• All tables have the same default view
• Manipulate default view for certain tables, here: Tariff information table
Show only certain scenarios
(those under SCEN)
MENU
B. EXPLOITATION TOOLS
Use the market product list
for the rows
79
Manipulate view of certain table II
CAPRI
CAPRI
• If you want to change columns and rows in the table, e.g. to compare
tariffs for one product over all countries
Rows of the table contain now
Products of market product list
the countries of the market part
are in selection menu now
MENU
B. EXPLOITATION TOOLS
80
Don’t do…
CAPRI
CAPRI
• Introduce blank line in first row of scenario.xml in Editor
• Try to compare scenarios where don’t have data for in the directory
• In the scenario definition: no blank after result type
<key>98MTRC</key>
and not
<key>98MTRC </key>
MENU
B. EXPLOITATION TOOLS
81
B.2. Use of the Mapping Tool
CAPRI
• Go to the directory:
• NUTS 0
• NUTS II
->
->
CAPRI
Map\nuts0
map\nuts2
• In each directory several pre-defined files
• caprimap.htm
-> access to results
• *.class
-> program code ... don’t bother about
• + lots of *.csv files containing the results from different runs
• e.g. Oilseeds98_Expost.csv
• e.g. Income_per_ha_98Agenda.csv
MENU
B. EXPLOITATION TOOLS
82
New feature in mapping tool
CAPRI
CAPRI
Include here all scenarios
you want to compare
•
•
•
•
Open caprimap.htm with editor
Change scenario
Save
Open caprimap.htm with browser (evtl. reload)
MENU
B. EXPLOITATION TOOLS
83
B.3. Accessing the Data Base
CAPRI
CAPRI
Depending on what you want to see, the following settings make sense:
Input file
Base year
& type
What does it
mean?
CAPREG.tab NNCOMCON National data
NNRAWDAT Raw national
data
NNCAPREG Regionalised
data
REGIO data
NNREGIO
Political data
NNPOLV
Simulation
CAPSIM.tab e.g. 98TESB
results
MENU
B. EXPLOITATION TOOLS
COCO
RC
Periodicity
Coco data Regio data 00
A3
base
base
X
X
X
X
X
X
X
X
X
X
X
X
X
84
Base year data for simulation runs
CAPRI
CAPRI
• Table column: *
• Table row: *
• Regions: DE???
• Years: 98
• Periodicity: A3
• NNCAPREG
MENU
B. EXPLOITATION TOOLS
85
CAPRI
Export data of data e.g. to a gams file
CAPRI
1. Select the data you want: e.g. all the base data for one region, all
NUTS1 regions or a complete MS
2. Put them with the “turn around” in the order you want to have in
the gams file
3. Click the export facility button
4. Choose the right format for the export: GAMS table format
5. With “Change” go to the directory you want to store them to
6. Type a name for the file e.g. test.gms
7. CLOSE Daout !!!!
8. Open the the gams file
9. You might want to rename the TABLE.
MENU
B. EXPLOITATION TOOLS
86
How to see original REGIO data ?
CAPRI
CAPRI
NEW: change STRUCTURE
CO Coco data base => RC Regio data base
by double-clicking on CO Coco data base
Table column: *
• Table row: *
• Regions: DE???
• Years: 90:99
• Periodicity: 00
• NNRegio
Store settings in a parameter file: e.g. regio.par
MENU
B. EXPLOITATION TOOLS
87
Overview of Columns and Rows
CAPRI
COLS
Everything is defined
in : SETS.GMS
MENU
Crop production activities
Fodder production act.
Animal production act.
Farm balance
Imports & Exports
Market balance
Prices
EAA
Aggregates
Political variables
Activity aggregates
Nutrient contents
...
B. EXPLOITATION TOOLS
CAPRI
ROWS
OUTPUTS
Crop outputs
Fodder outputs
Animal outputs
Young animal output
Manure output
INPUTS
Fertiliser
Other crop specific
Feed
Other animal specific
General inputs
Young animal input
EAA position
LEVL
Political variables
Secondary products
...
88
CAPRI
CAPRI
C. Technical Problems
(experience from Training Sessions)
MENU
89
Errors with older GAMS versions
CAPRI
CAPRI
Possible Errors with older GAMS versions:
• in „sets.gms“ and „ammo\ammo.gms“ :
- substitute DACT__TO_PACT through D_TO_PACT
• in „arm\market_model.gms“:
- delete „MULTREG.WORKFACTOR=1.5“
• in „reports\htmout“:
- substitute $goto afterStochy through $goto afterS
- substitute $label afterStochy through $label afterS
• WARNING: if there is a result file from a older run,
the result are loaded even if GAMS failed (no errors)
MENU
C. TECHNICAL PROBLEMS
90
Errors with older GAMS versions
CAPRI
CAPRI
• „Error in PRESCAN09“: it means that your setting for
max. code size is too small; you have to edit in your
gams installation directory the file:
- gmsprm95.txt or
- gmsprmnt.txt
and insert a line with
CODEX 9
• comment out or delete MultReg.Workfactor=1.5 in
Market_model.gms
•If you still have some problems.... sorry about that...
you should contact your administrator. In any case you
have a copy of the “Original Listing” in each folder.
MENU
C. TECHNICAL PROBLEMS
91
CAPRI
CAPRI
D. MTR Simulation
MENU
92
Direct payments in MTR
CAPRI
CAPRI
Modulation
€
Coupling-
(MS)
table
MENU
D. MTR SIMULATION
-
DPGRCU
DPPULS
DPDWHETR
DPDWHEES
DPNONF
DPPARI
DPPARI_fa
DPSCOW
DPBULF
DPDCOW
DPSHGM
DPNE_SHGM
DPNE_DCOW
DPNE_MEAT
DPSL_ADCT
DPSL_CALV
-
DPMTR
Direct payment to cereals
Specific payment for pulses
Traditional durum wheat premium
Established payment to durum wheat
Direct payment for non food crop
Specific rice premium
Farm income rice premiums
Suckler cow premium
Special premium to bulls and steers
Direct income support to dairy cows
Direct payment for sheep and goat
National envelope for sheep and goat
National envelope dairy cows
National envelope bovine meat cattle
Slaughter premium for adult cattle
Slaughter premium for calves
The MTR decoupled payment
93
Processing of premiums
CAPRI
Initialisation:
Break down to
lower regional level
and individual activities
Policy
definition
Manually edited policy file in
\capri\gams\policy\
\capri\gams\policy\policy.gms
Policy.gms
Parameters PP_EPAY()
and PPDATA()
Expanded
policy
definition
\capri\gams\policy\prmcut.gms
In DATA-parameter, row PRME
Effective
payments/
activity
Iterative adjustment:
Cut individual premiums
to fit into tightest ceiling
before each iteration
Prmcut.gms
Supply
models
MENU
D. MTR SIMULATION
CAPRI
Reports
94
CAPRI
Data processing MTR premiums
Premium
def. MTR
modulation
Size
distrib.
Coupling
decision
MENU
Modulated
premiums
CAPRI
Base year
production
policy.gms
Reference
payments
premcut.gms
Sum up
payments
MTR
premium
D. MTR SIMULATION
Simulations...
95
CAPRI
Market policies
Policies
2009
Market
calibration
CAPRI
Market
calibrated
Trends
New policy
MENU
D. MTR SIMULATION
Simulations...
96
Storage of policy data
CAPRI
CAPRI
Policy files in capri\gams\policy
Base year
Agenda 2000
MTR
Harbinson
Premiums
pol00n.gms
Polagnd09
polMTRc09
-no change-
Historic yield
Data base
-no change-
-no change-
-no change-
PADM
pol00_padm
Pol09_padm
Polmtrc_09_padm -no change-
TRQ/tariffs
Trq_ucl
trq_iap
trq_aglink
-no change-
-no change-
Wto_harb
Capri\gams\arm\
MENU
D. MTR SIMULATION
97
Incremental policy definition
CAPRI
CAPRI
Explanation: Only policy changes are added up
to the previous implemented policy
Policy:
Scenario:
MENU
Base year
(2000)
Ex post
D. MTR SIMULATION
Agenda
2000
Agenda
MTR
MTR
98
Definition, detail
CAPRI
CAPRI
Base level for
premium defined
per MS
Payment
name
DPGRCU
Apptype can be:
1: per level
2: per slaughtered head
3: per main output
4: per historic yield
MENU
D. MTR SIMULATION
Specification of
payment per crop
group
99
CAPRI
Data processing premiums
Before iterations
Premium
file
CAPRI
Between iterations
Production
in last
step
policy.gms
premcut.gms
Premium
per activity
in all
regions
MENU
D. MTR SIMULATION
Effective
premium
100
CAPRI
CAPRI
E. WTO Simulation
MENU
101
Table of contents
CAPRI
CAPRI
• Overview on market instruments + modelling aspects
• Ad valorem and specific tariffs (applied/bound tariffs) for each
product
• TRQs (global + bilateral ones)
• Behavioural functions for export subsidies and intervention
purchases
• Bilateral agreements
• Implementation of WTO scenarios
• Model outputs
MENU
E. WTO SIMULATION
102
Tariffs
CAPRI
CAPRI
• Ad valorem tariffs (%)
• Specific tariffs (€/t)
• In data base stored under TARV and TARS
• During model run stored under parameter:
STariff(RM,RM1,XX) and ATariff(RM,RM1,XX)
• Defined as “stand-alone” policy instrument and as a function of TRQ if
TRQ is present
If TRQ is present
• Tariffs are variables in model (calculation of applied tariff):
Tariffs(RM,RM1,XX) and Tariffa(RM,RM1,XX)
• Equations in market model for definition of endogenous tariff:
Tariffs_(RM,RM1,XX) and Tariffa_(RM,RM1,XX)
MENU
E. WTO SIMULATION
103
Tariff Rate Quotas I
CAPRI
CAPRI
• Market access regulated over quota
-> Within the quota, share of imported goods to domestically produced goods
is determined over price mechanism
-> two prices: import price and internal market price
-> must come in line when both types of goods are consumed on a market
MENU
E. WTO SIMULATION
104
Tariff Rate Quotas II
CAPRI
CAPRI
• TRQ mechanism needs 3 pieces of information:
• Volume of quota (t)
TrqNT
• In-quota tariff: preferential tariff
TsPref/TaPref
• Over-quota tariff: MFN tariff
TsMFN/TaMFN
• Distinction between global TRQs and bilateral TRQs
• Global TRQ:
e.g. TrqWor(RM
,XX,"TrqNT","CUR")
• Bilateral TRQ:
e.g. TrqReg(RM,RM1,XX,"TsPref","CUR")
• Variables:
• Endogenously defined tariff
• Fill rate of quota (=import quantity)
MENU
E. WTO SIMULATION
Tariffs/Tariffa
TRQimports
105
Tariff Rate Quotas III
CAPRI
CAPRI
• In the observed data for base year situation (and trimming point in
simulation year) should hold:
• Fill rate of TRQs defined by import streams -> quota rent when underfill
• Relation of import prices to domestic market prices should be in
plausible range
• Ensure binding TRQs (if not, manual adjustment):
• When imports fall slightly over TRQ
• When prohibitive MFN tariffs: over-quota imports would lead to
unreasonably high market prices for imported quantities (e.g. beef in
EU)
• No trimming of TRQ function, steepness of sigmoid function set manually
(currently  = 100,  = 1)
MENU
E. WTO SIMULATION
106
Basics of sigmoid functions
CAPRI
CAPRI
• TRQs, export subsidies, intervention purchases are modelled on basis
of a sigmoid function in order to represent “kinked” policy behaviour
Sigmoid x   exp  min x,0
 1  exp  absx   
• Symmetric S-shaped form
• Overall differentiable
Sigmoid(x)
• Between 0 (if x = -) and 1 (if x = +),
1
• Sigmoid(0) = 0.5
0.5
+
MENU
E. WTO SIMULATION
0
+
x
107
CAPRI
From sigmoid to behavioural function



expsi, r  QutEi, r 1  sigmoid  E
pmrki, r  iE, r PADMi
  PADM

ir
 i, r

with
sigmoid x   exp  min x,0
CAPRI





 1  exp  absx   
• Two parameters to define: alpha + beta
• Alpha: defines steepness (slope) of the function (the bigger,
the more edge-like representation)
• Beta: manipulates turning point of the function (away from
symmetry shape)
• Trimming of the functions means:
-> find slope and turning point so that observed data are met
MENU
E. WTO SIMULATION
108
Export subsidies
CAPRI
CAPRI
• Function is rotated to the right
• WTO commitment levels (tons) define upper limit (sigmoid(x) = 1)
• No subsidisation when PMrk > PADM
Trimming
• Observed quantities and prices from 3-year average 1998 (2000)
•  = LPAR,  = C_Exps
PMrk
EXPSi quantity of subsidised exports
QUTEi WTO commitment on subsidised exports

defines steepness of function

percentage of PADMi at which EXPSi
is 50% of QUTEi
PADM
 PADM
EXPS
50% QUTE
MENU
QUTE
E. WTO SIMULATION
109
Intervention purchases
CAPRI
CAPRI
• Function is rotated to the right
• No clearly defined quantity limit exists
-> assumption that limit when INTP = 0.5 * (base year production)
• As steep as possible as Comm. must buy in at a certain trigger price
Trimming
• Observed quantities and prices from 3-year average 1998 (2000)
•  = LPAR = 30,  = C_ToSt
PMrk
INTPi
INTMi


PADM
 PADM
purchases to intervention stocks
maximum intervention purchases allowed
defines steepness of function
percentage of PADMi at which
INTPi is 50% of INTMi
INTP
50% INTM
MENU
INTM
E. WTO SIMULATION
110
Bilateral agreements
CAPRI
CAPRI
• Bilateral agreements
– Double Zero Agreement: EU - CEE, USA - CAN
– Cotonou Agreement:
EU - ACP
Double Zero
• Interpretation as zero tariffs for trade in both directions
• Implementation: Dbl_Zero("EU000000","CEE",XX,"Y") = 1.0
Coutonou Agreement:
• Implemented as tariff reductions for beef
MENU
E. WTO SIMULATION
111
WTO scenarios
CAPRI
Reference (2009)
TRQs
No change (bound tariffs)
URAA formula
(-36% in average)
No change (final WTO commitments)
Double-Zero
Export Subsidies
No change
(final WTO commitments)
LCDs
Coutonou
MENU
Harbinson (2009)
MTR proposal January 2003:
- Further decrease of administrative prices
- Almost completely decoupled payment scheme
CAP
MFN Tariffs
EU Proposal (2009)
CAPRI
E. WTO SIMULATION
Average cut of 45%
-60% if tariff >90%
-50% if 15%<tariff<90%
-40% if tariff <15%
At least 10% of demand
Reduce in-quota tariffs
if fill rate <= 65%
Average cut of 50 %
Duty free and quota free access for ACPs
112
Model results
CAPRI
CAPRI
• Best accessed over XML-tables for market part
• Product balances
• Prices
Arm2P import price of Armington aggregate 2
(mixture of goods of all other countries)
Arm1P price for Armington aggregate 1
(composition between domestic and imported goods)
Market Price: domestic reference price
(starting point for all calculations)
• Welfare
• Import flows
• Export flows
• Tariff Rate Quotas
MENU
E. WTO SIMULATION
113
Model results (June 2003)
CAPRI
EU
WTO EU prop. [2009]
TSPREF
Butter &
cream
TSMFN
948
0%
CEE
ANZ
869
0%
1271
-36%
1271
-36%
1271
-36%
TRQNT
10
0%
77
0%
CAPRI
WTO Harbinson prop. [2009]
Imports
10
2%
0
-1%
78
1%
TSPREF
-100%
-100%
TSMFN
794
-60%
794
-60%
794
-60%
TRQNT
-100%
-
-100%
Imports
128
1186%
0
-44%
98
28%
• Example for market affected by changes in MFN tariffs
• Main import flows in the reference run under bilateral TRQs
• EU proposal: No effects on import structure
• Harbinson proposal: reduced MFN tariff lower than old in-quota tariff,
drastic expansion of imports, disappearance of the TRQ mechanism
MENU
E. WTO SIMULATION
114
CAPRI
CAPRI
F. Sugar Simulation
MENU
115
Modelling sugar reform options
with the CAPRI system
CAPRI
CAPRI
Content
• Background
• Modifications
• New data
• New variables and equations
• Sensitivity analysis
• Simulations
MENU
F. SUGAR SIMULATION
116
Sugar reform options & CAPRI
CAPRI
CAPRI
Study to assess the impact of future options
for the future reform of the sugar common
market organisation
4 Models:
•Background
•Modifications
• new data
• new variables
WATSIM (world markets)
CAPSIM (EU)
CAPRI (regional impacts on supply, income)
and equations
•Sensitivity
analysis
•Simulations
(modifications not in standard model!!)
Farm-level analysis (farm types, quota trade)
MENU
F. SUGAR SIMULATION
117
Sugar reform options & CAPRI
CAPRI
CAPRI
Model modifications necessary because:
•Background
• No data on regional sugar beet quotas
• No distinction between A-, B- and C- beets
• Almost all MS produce above their quotas
=> CAPRI so far treated all production
as under quota
=>
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
the model is insufficient specified to
simulate changes in the Sugar CMO
MENU
F. SUGAR SIMULATION
118
Sugar reform options & CAPRI
CAPRI
CAPRI
Regional sugar beet quotas:
•Background
• Estimation of sugar beet quotas per farm
for almost all beet producing farms in FADN
•Modifications
• new data
• new variables
and equations
•Sensitivity
• Aggregation of quota estimates
from farms to NUTS II regions
MENU
F. SUGAR SIMULATION
analysis
•Simulations
119
Sugar reform options & CAPRI
CAPRI
Beet
prices
CAPRI
•Background
A quota
•Modifications
PA
• new data
• new variables
B quota
and equations
PB
Prod/quot = 106%
•Sensitivity
analysis
PC
•Simulations
Production
Aund
MENU
Abind Bund Bbind
F. SUGAR SIMULATION
Cprod
120
Sugar reform options & CAPRI
CAPRI
BL000000
DK000000
DE000000
EL000000
ES000000
FR000000
IR000000
IT000000
NL000000
AT000000
PT000000
SE000000
FI000000
UK000000
Aund
100%
100%
4%
-
Abind
12%
-
Bund
2%
1%
2%
23%
0%
8%
11%
5%
-
Bbind
12%
6%
10%
45%
1%
70%
46%
61%
2%
15%
80%
1%
Prod/ Prod/
Cprod Quota EU
86% 116%
5%
93% 128%
3%
88% 121% 23%
82%
2%
32% 104%
7%
99% 139% 28%
22% 107%
1%
43% 109% 11%
34% 110%
6%
98% 126%
3%
19%
0%
85% 117%
2%
5%
103%
1%
99% 133%
8%
CAPRI
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
70%
MENU
F. SUGAR SIMULATION
121
Sugar reform options & CAPRI
CAPRI
CAPRI
Additional information from single Farm data:
• Classification of producer types:
• Quota endowment
• Production ex post
• Share on all producer types
• For each MS we specify
• A,B,C prices
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
• share of A- and B- quota on total quota
MENU
F. SUGAR SIMULATION
122
Sugar reform options & CAPRI
CAPRI
CAPRI
• Producer types now in all sugar relevant
model equations, variables and parameters
making use of the technology dimension (A)
•Background
•Modifications
• new data
• new variables
and equations
• Distinction between A,B,C beet sales,
but still only one activity
MENU
F. SUGAR SIMULATION
•Sensitivity
analysis
•Simulations
123
Sugar reform options & CAPRI
CAPRI
CAPRI
Introduction of yield uncertainty:
• Maximisation of expected profits
over three state of nature with different yields
•Background
•Modifications
• new data
• new variables
• Optimum now characterised by
marginal cost
= expected marginal revenue
MENU
F. SUGAR SIMULATION
and equations
•Sensitivity
analysis
•Simulations
124
Sugar reform options & CAPRI
CAPRI
CAPRI
Introduction of quota uncertainty:
• Producers expect that their quota can be
reduced or increased
• and that these quota changes
•Background
•Modifications
• new data
• new variables
and equations
depend on production
•Sensitivity
analysis
•Simulations
MENU
F. SUGAR SIMULATION
125
Sugar reform options & CAPRI
CAPRI
CAPRI
Example quota cut:
• Reduction of quotas in following years
• Expected profit losses
• Farmers assume that quota cuts
•Background
•Modifications
• new data
• new variables
and equations
are a function of production/quota
• C-production works like an
•Sensitivity
analysis
•Simulations
“insurance against quota cuts”
• Similar mechanism for quota increases
MENU
F. SUGAR SIMULATION
126
Sugar reform options & CAPRI
CAPRI
•Background
Assumptions:
• expected quota cut
CAPRI
•Modifications
= 2.5%
• expected quota increase = 0.5%
• new data
• new variables
and equations
of regional quota
•Sensitivity
• planning horizon
= 20 years
• yearly interest rate
= 5%
MENU
F. SUGAR SIMULATION
analysis
•Simulations
127
Sugar reform options & CAPRI
CAPRI
CAPRI
Introduction of quota uncertainty:
• Producers expect quota changes
depending on their production
• Optimum now characterised by
marginal cost =
expected marginal revenue
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
+ expected quota cuts/extension
* discounted quota rent of producer type
MENU
F. SUGAR SIMULATION
128
Sugar reform options & CAPRI
CAPRI
CAPRI
Sensitivity analysis :
•Background
Virtual mark up (€/t) for C-beets
in DK at different prices and quotas
quota beet prices (€/t)
quotas (1000 t)
1907
1525
1144
763
381
0
MENU
56.7
49.6
42.4
35.3
•Modifications
• new data
28.1
21.0
• new variables
and equations
8.37
7.39
6.02
4.48
2.33
0.00
6.91
6.17
4.45
3.44
1.83
0.00
F. SUGAR SIMULATION
5.43
4.24
3.57
2.57
1.37
0.00
3.84
3.35
2.44
1.77
0.93
0.00
2.22
1.81
1.27
0.91
0.47
0.00
0.00
0.00
0.00
0.00
0.00
0.00
•Sensitivity
analysis
•Simulations
129
Sugar reform options & CAPRI
CAPRI
CAPRI
Sensitivity analysis :
•Background
Beet production (1000t) in DK
at different prices and quotas
quota beet prices (€/t)
quotas (1000 t)
1907
1525
1144
763
381
0
MENU
•Modifications
• new data
• new variables
56.7
49.6
42.4
35.3
28.1
21.0
2834
2607
2356
2149
1987
1834
2700
2506
2240
2079
1954
1834
2554
2331
2170
2020
1924
1834
2454
2240
2075
1964
1895
1834
2212
2069
1966
1902
1865
1834
1834 •Sensitivity
1834 analysis
1834 •Simulations
1834
1834
1834
F. SUGAR SIMULATION
and equations
130
Sugar reform options & CAPRI
CAPRI
CAPRI
Simulation procedure:
• No market model, fixed prices
• Exogenous changes in beet prices,
quotas or premiums
according to CAPSIM scenario results
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
MENU
F. SUGAR SIMULATION
131
Sugar reform options & CAPRI
CAPRI
CAPRI
Reference run characterised by:
• AGENDA 2000 fully implemented (2011)
•Background
•Modifications
• Exogenous trends
• new data
• new variables
• Prices for all other products
from MTR simulations (inflated to 2011)
and equations
•Sensitivity
analysis
• Higher sugar imports (EBA, fructose..)
(no levies => no distinction between A- and Bprices - all beet prices increase)
•Simulations
=> quota cuts necessary (-23%)
MENU
F. SUGAR SIMULATION
132
Sugar reform options & CAPRI
CAPRI
CAPRI
Cuts of quotas follow a declassification key
•Background
0%
-10%
-20%
-30%
-40%
Base year
-50%
-60%
-70%
Reference
-80%
-90%
% Reduction
-100%
5000
Sugar quotas (1000 t)
4000
3000
2000
1000
0
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
FR DE IT UK ES NL BL DK AT SE EL IR FI PT
MENU
F. SUGAR SIMULATION
133
Sugar reform options & CAPRI
CAPRI
CAPRI
Beet production 2001 [reference/base 1998]
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
Alentejo -0.6%
Calabria -27%
MENU
F. SUGAR SIMULATION
134
Sugar reform options & CAPRI
CAPRI
Price cut scenario characterised by:
• further reduction in guarantee prices for quota
beets in CAPSIM (about -27%)
compared to reference scenario
• slight increase in C-beet prices (1%)
CAPRI
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
• same quotas as in the reference
MENU
F. SUGAR SIMULATION
135
Sugar reform options & CAPRI
CAPRI
CAPRI
Beet production 2011 [price cut / reference]
EU - 10%
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
Portugal - 25%
analysis
•Simulations
Toscana -1.4%
MENU
F. SUGAR SIMULATION
136
Sugar reform options & CAPRI
CAPRI
Full liberalisation scenario characterised by:
CAPRI
•Background
•Modifications
• new data
• Quotas abolished
• C- beet price for all beets
(~20 €/ton of beets)
MENU
F. SUGAR SIMULATION
• new variables
and equations
•Sensitivity
analysis
•Simulations
137
Sugar reform options & CAPRI
CAPRI
CAPRI
Beet production 2011 [liberalisation/ reference]
EU - 36%
Flevoland -18%
•Background
•Modifications
• new data
• new variables
and equations
•Sensitivity
analysis
•Simulations
Calabria -77%
MENU
F. SUGAR SIMULATION
138
Note on sugar treatment in CAPRI
CAPRI
CAPRI
• The specification in case of sugar and sugar
beet is slightly different in the standard
version of CAPRI.
– The quota uncertainty motive is not implemented
– Expected revenues are no longer calculated of
three states of nature but with normal distributed
yields.
– Beet prices are linked to the domestic sugar price
in the market model
MENU
F. SUGAR SIMULATION
139
CAPRI
CAPRI
G. GHG Emission Abatement
MENU
140
Abatement cost curves
CAPRI
CAPRI
• Abatement = reduction of negative externality
• Abatement cost curves (ACC)
= relation between emission reduction level and total costs
• Marginal abatement cost curves (MACC)
= relation between emission reduction level
and costs for the last abated unit
• MACC allow
(a) to set up an optimal abatement strategy
(b) to calculate regional cost differences
under a certain environmental policy
(e.g. Kyoto Protocol, nitrate directive, ...)
MENU
G. GHG SIMULATION
141
Global Warming Gases in CAPRI
CAPRI
CAPRI
• Distinction between direct and indirect emissions
• Direct emission stem directly from agricultural activities
(Methane from animals and rice, emissions during fertilizer application or
storage, background emission from soils)
• Indirect emission stem from other sectors
and are linked to input use in agriculture
(fertilizer and energy production)
• Both are linked to activities levels (hectares/heads) in the
supply model via emission factors
• Aggregated to Global Warming Potential
via the definition of CO2 impact equivalents
MENU
G. GHG SIMULATION
142
Global Warming Gases in CAPRI
CAPRI
CAPRI
• Content of nutrients in harvested material
(kg/ton)
• Atmospheric deposition at Nuts 0 level (kg/ha)
• Available nutrient per crop from atmospheric
deposition: available nutrient component for the
crop coming from the atmosphere.
• Biological fixation: ”self-made fertiliser”
• Mineralisation: nitrate from soils available for the
crop (kg/ha)
• NPK balances
(fertiliser
application)
• Optimal
activity Levels
• Global warming potential of different gases
• Gas output per ton of mineral fertiliser produced
(indirectly applied)
• CH4 Output of animals kg per animal and year
MENU
G. GHG SIMULATION
Emissions
(passive
indicator)
143
Why Global Warming?
CAPRI
CAPRI
• GW is a global externality: it does not matter where the
emission takes place
- damage costs are equal among emitters
- no regional pricing is therefore necessary
- it allows differentiation through abatement costs
• Most studies look at a comparison across sectors
• Agriculture interesting:
subsidies <=> cross compliance <=> low costs for society
• MACC contain the necessary information for an effective
use of agri-environmental instruments
=> new orientation of the CAP (multi-functionality)
MENU
G. GHG SIMULATION
144
Modellierung von GWE in CAPRI
CAPRI
CAPRI
• CAPRI offers:
- a complete analysis of the agricultural sector
=> analyse different strategies inside agriculture
- direct modeling of GWP reductions
(ex-post indicator)
- a microeconomic orientation
(optimisation problem, shadow values)
- modelling of permit markets
(hot issue in the actual international negotiations)
MENU
G. GHG SIMULATION
145
Methodology
CAPRI
AB_COST =
CAPRI
MAX_Inc(s.t. g>0, GWP unrestricted)
- MAX_Inc(s.t. g>0, GWP <Kyoto)
where: g
restrictions in models
(land, set aside,quotas ...)
MENU
GWP
output of GWP from agriculture
MAX_Inc
maximal agricultural income
Kyoto
reduction objective
G. GHG SIMULATION
146
Introduction of GWE Abatement
CAPRI
CAPRI
An additional 1% abatement objective is introduced iteratively in the
optimisation problem; dual values for each iteration build up the MACC
max profit  f ( x)
s.t. g ( x)  G  

emission ( x)  P  
Objective
Emission
Level
profit
f
g
emission
0


x
x
x
x
 (Iteration)
Iteration
Number
or
Marginal Cost
emission ( Iteration) _ up  emission (" Initial " ) * (1  0.01 * IterationNumber )
MENU
G. GHG SIMULATION
147
Aggregation of Emissions
CAPRI
CAPRI
DK000144
(„Denmark Various Field Crops“)
All Activities
DK000144
(„Denmark Various Field Crops“),
Activity: Soft Wheat
• Total CO2 Emissions: 731.6 t GAS or t CO2eq
Aggregation
over activities
• Total N2O Emissions: 3.24 t Gas  1004.4 t CO2eq
• Total CH4 Emissions: 216.2 t Gas  4540.2 t CO2eq
• CO2 Emissions: 420 kg Gas/ha
• N2O Emissions: 1.9 kg Gas/ha
DK000000
(„Denmark“)
Activity: Soft Wheat
Aggregation
over farm
types
• Total CO2 Emissions: 253.6 t Gas or t CO2eq
• Total N2O Emissions: 1.69 t Gas  349.5 t CO2eq
DATA AGGREGATION
Emission
coefficients
per ton/head
„Various Field Crops“
„Rest“
FARM
TYPES
MENU
„Specialist Pigs“
„Specialised COP“
G. GHG SIMULATION
„Field crops and granivores“
148
MACC Results: countries
CAPRI
CAPRI
Marginal Abatement Cost Curves
250
Marginal Cost (€/ton CO2-eq)
Italy
Belgium
200
Denmark
Greece
Portugal
150
France
Austria
Netherlands
100
Sweden
Spain
50
Germany
Finland
United Kingdom
0
Ireland
S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15
Emission Reduction Objective (%)
MENU
G. GHG SIMULATION
149
CAPRI
CAPRI
END
MENU
150