annex to eq3 rev 23-4-08 - european...
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Agrosynergie Groupement Européen d’Intérêt Economique
Framework contract no 30-CE-0035027/00-37
Evaluations fruit and vegetables
Evaluation of the system of entry prices and export refunds in the fruit and vegetables sector
Annexes to EQ3
April 2008
1
LE GEIE AGROSYNERGIE EST CONSTITUE PAR LES SOCIETES
COGEA S.p.A
Via Po 9 - 00198 Roma ITALIE
Tél. : + 39 6 853 73 51 Fax : + 39 6 855 78 65
Mail : fantilici@cogea.it
Représenté par Massimo Ciarrocca
OREADE–BRECHE Sarl 64 chemin del prat - 31320 Auzeville FRANCE
Tél. : + 33 5 61 73 62 62 Fax : + 33 5 61 73 62 90
Mail : t.clement@oreade-breche.fr
Représentée par Thierry Clément
2
Table of contents
1. ANNEXES TO THE EVALUATION QUESTION 3 ............................................................................... 3
1.1 Annex to EQ 3 – Import growth ........................................................................................................... 3
1.2 Annex to EQ 3 – Monthly imports 1995-2001 ..................................................................................... 6
1.3 Annex to EQ 3 – Monthly imports 2002-2006 ................................................................................... 12
1.4 Annex to EQ 3 – Methodology of Gravity Model .............................................................................. 18
1.5 Annex to EQ 3 – Gravity Flows ........................................................................................................ 20
1.6 Annex to EQ 3 – Value and volume of imports growth..................................................................... 23
1.6.1 Tables based on COMTRADE database .................................................................................... 23
1.6.2 Tables based on COMEXT database ......................................................................................... 26
1.7 Annex to EQ 3 – Analysis of Preferences ......................................................................................... 28
1.8 Annex to EQ 3 – Seasonal value of Preferences................................................................................ 35
1.9 Annex to EQ 3 – The Trade Model ................................................................................................... 39
1.9.1 The Export Model ...................................................................................................................... 43
1.9.2 The Import Model ...................................................................................................................... 49
1.10 Annex to EQ 3 – Export growth ........................................................................................................ 61
1.11 Annex to EQ 3 – Export Refunds ...................................................................................................... 64
3
1. ANNEXES TO THE EVALUATION QUESTION 3
1.1 Annex to EQ 3 – Import growth
Tab. 1 - Percentage changes between average import volumes 1992/94 and 1995/97
Tomato Turkey Morocco Israel Extra EU
1 November to 14 May 7020010 26 -3 46 -1
15 May to 31 October 7020090 -73 2 161 -22
Onion Chile Australia New Zealand Extra EU
7031019 93 -19 41 18
Cucumber Turkey Hungary Romania Extra EU
7070005 -31 -43 1 -28
Beans Morocco Egypt Kenya Extra EU
1 October to 30 June 7082010 42 8 18 39
1 July to 30 September 7082090 42 46
Artichoke Egypt Extra EU
70910 -8 -18
Asparagus South Africa USA Chile Extra EU
7092000 76 -21 -18 39
Sweet peppers Turkey Hungary Israel Extra EU
7096010 26 -14 201 19
Courgettes Morocco Kenya USA Extra EU
70990 13 42 21 43
Oranges Brazil Morocco South Africa Extra EU
80510 0 -9 23 7
Grapefruit South Africa USA Israel Extra EU
80540 11 32 17 12
Table grapes South Africa Chile Turkey Extra EU
1 November to 14 July 8061015 23 -1 15
15 July to 31 October 8061019 165 61
Melons Brazil Israel Extra EU
8071090 -10 12 20
Apple (*) South Africa USA Chile Extra EU
Golden 1 January to 31 March 8081051 -49 -27
Granny 1 January to 31 March 8081053 -35 -29
Other Apples 1 January to 31 March 8081059 101 27
Golden 1 April to 31 July 8081081 19 156
Granny 1 April to 31 July 8081083 -10 35 5
New Zealand Chile Extra EU
Other Apples 1 April to 31 July 8081089 130 82 97
Golden 1 August to 31 December 8081031 -11 -13
Granny 1 August to 31 December 8081033 -9 -48
Other Apples 1 August to 31 December 8081039 -1 41
Pears South Africa Chile Argentina Extra EU
1 January to 31 March 8082031 -26 9 3 -3
1 April to 15 July 8082033 3 12 27 2
16 July to 31 July 8082035 122 159
1 Aug - 31 Dec 8082039 -75 50
Strawberries Morocco USA Extra EU
1 May to 31 July 8101010 -56 40 14
1 August to 30 April 8101090 37 -30 -7
Kiwifruit Chile New Zealand Extra EU
8105000 13 16 15
Clementines 80520 Morocco Extra EU
-18 -28
Source: COMEXT. Processed by Agrosynergie
Note: (*) Values for the initial period correspond to 1993 and 1994 for which COMEXT data (for 1992 no distinction between
varieties is offered in COMEXT)
6
1.2 Annex to EQ 3 – Monthly imports 1995-2001
Index of EU imports of selected F&V from major partners.
Remarks:
The following tables show “Indices” of EU imports from selected partners.
The index is given by the vertical axis values and they are indicated by the ratio Xt/X1995
expressed in %, where Xt is the import volume in month “t” and X1995 is the average of monthly
imports in 1995, counting just the months when imports are not zero.
Consequently, Index 100 = Average of monthly imports for 1995.
The horizontal axis show the monthly period from January 1995 to December 2001.
We also include in the graphs the MFN levels of entry prices in Euro/T
(see legends at the bottom of each graph).
Sources: TARIC and COMEXT data base. Processed by Agrosynergie.
7
Tomato
0
500
1000
1500
2000
2500Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Turkey Morocco Israel
Oranges
0
100
200
300
400
500
600
700
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Morocco South Africa Brazil
8
Courgettes
0
200400
600
8001000
1200
14001600
1800
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Morocco
Clementines
0
100200
300
400500
600
700800
900
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Morocco
Pears
0
100200
300
400500
600
700800
900
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 South Africa Chile Argentina
9
Apples
0100200300400500600700800
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 South Africa
USA Chile New Zealand
Cucumbers
0
200
400
600
800
1000
1200
1400
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Turkey Hungary Romania Bulgaria
Table grapes
0
200
400
600
800
1000
1200
Jan. 1995
Jun
Nov
Apr
Sep
Feb
Jul
Dec
May
Oct
:Mar
Aug
Jan. 2000
Jun
Nov
Apr
Sep
EP level
Extra-EU15
Extra-EU25
Turkey
South Africa
Chile
10
Artichokes
0
200
400
600
800
1000
1200
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
EP level Extra-EU15 Extra-EU25 Egypt
Onions
050
100150200250300350400450500
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
AUSTRALIA CHILE Extra-EU15 Extra-EU25 New Zealand
Asparagus
050
100150200250300350400450500
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
CHILE Extra-EU15 Extra-EU25 UNITED STATES South Africa
11
Sweet Peppers
0
100
200
300
400
500
600
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
Extra-EU15 Extra-EU25 HUNGARY TURKEY
Melons
0
100
200
300
400
500
600
Jan. 1995
May
Sep
Jan. 1996
May
Sep
Jan. 1997
May
Sep
Jan. 1998
May
Sep
Jan. 1999
May
Sep
Jan. 2000
May
Sep
Jan. 2001
May
Sep
BRAZIL Extra-EU15 Extra-EU25 Israel
Kiwifruit
0
100
200
300
400
500
600
700
800
Jan. 199
5
:Mar
May Ju
lSep N
ov
Jan. 199
6
:Mar
May Ju
lSep N
ov
CHILE
Extra-EU15
Extra-EU25
New Zealand
12
1.3 Annex to EQ 3 – Monthly imports 2002-2006
Index of EU imports of selected F&V from major partners.
Remarks:
The following tables show “Indices” of EU imports from given partners.
The index is given by the vertical axis values and they are indicated by the ratio Xt/X2001
expressed in %, where Xt is the import volume in month “t” and X2001 is the average of monthly
imports in 2001, counting just the months when imports are not zero.
Consequently, Index 100 = Average of monthly imports for 2001.
We also include in the graphs the MFN levels of entry prices in Euro/T (see legends at the
bottom of each graph).
Sources: TARIC and COMEXT. Processed by Agrosynergie.
Tomato
0
200
400
600
800
1000
1200
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP MFN Extra-EU15 Extra-EU25 Turkey Morocco Israel
13
Oranges
0
50
100
150
200
250
300
350
400
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Morocco South Africa Brazil
Courgettes
0
100200
300400
500600
700800
900
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Morocco
Clementines
0
100
200
300
400
500
600
700
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Morocco
14
Pears
0
100
200
300
400
500
600
700
800
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 South Africa Chile Argentina
Apples
0
100
200
300
400
500
600
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 South Africa
USA Chile New Zealand
Cucumbers
0
200
400
600
800
1000
1200
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Turkey Romania Bulgaria
15
Table grapes
0
100
200
300
400
500
600
700
800
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Turkey South Africa Chile
Artichokes
0100020003000400050006000700080009000
10000
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
EP level Extra-EU15 Extra-EU25 Egypt
Onions
0
100200
300400
500600
700800
900
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
AUSTRALIA CHILE Extra-EU15 Extra-EU25 New Zealand
16
Asparagus
0
100
200
300
400
500
600
700
Jan. 2002
May
Sep
Jan. 2003
May
Sep
Jan. 2004
May
Sep
Jan. 2005
May
Sep
Jan. 2006
May
Sep
CHILE
Extra-EU15
Extra-EU25
UNITED STATES
South Africa
Sweet Peppers
0
100
200
300
400
500
600
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
Extra-EU15 Extra-EU25 HUNGARY TURKEY
Melons
0
50100
150200
250300
350400
450
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
BRAZIL Extra-EU15 Extra-EU25 Israel
17
Strawberries
0
1000
2000
3000
4000
5000
6000Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
Extra-EU15 Extra-EU25 Israel MOROCCO UNITED STATES
Kiwifruit
0
100200
300400
500600
700800
900
Jan. 2002
Apr
Jul
Oct
Jan. 2003
Apr
Jul
Oct
Jan. 2004
Apr
Jul
Oct
Jan. 2005
Apr
Jul
Oct
Jan. 2006
Apr
Jul
Oct
CHILE Extra-EU15 Extra-EU25 New Zealand
18
1.4 Annex to EQ 3 – Methodology of Gravity Model
The econometric modeling
In its most basic application, the gravity model of international trade posits that the level of
imports to one country from another is a function of each country’s gross domestic product
(GDP) and its population, as well as the distance between the two countries. Additional
explanatory variables can indicate a country’s membership in a specific trade agreement or
trade bloc. The model proponed is a modified version of the Standard gravity that will include
two sets of fixed effects (variables with the value of one or zero) that respectively identify
specific importing countries and specific seasons (peak season and off-season periods). A
fixed effect for the entry price will control the effect of the system. The trade-agreement
variables are country-specific in order to address the possibility that the impact of an
agreement varies among its participants.
The products chosen for the analysis are:…. - the 8 products listed in Tab. 1 (Chapter 4 in the report) with EP (tomatoes, artichokes,
cucumbers, courgettes, oranges, , apples, pears, table grapes ). We also considered clementines
because of their relevance as a fruit imported from preferential partners.
- the 8 products listed in Errore. L'origine riferimento non è stata trovata. (Chapter 4 in the
report) without EP (onion, beans, asparagus, sweet peppers, grapefruits, melons, strawberries,
kiwifruit).
Import changes will be assessed in relative terms by calculating the average values for 1993-94, 1995-
96, 2001-02 and 2005-2006. The model proposed is simpler than most gravity equations used to
capture the forces that either attract or inhibit bilateral trade. The equations proposed take the
following form:
∆ Ln Xijkt= β0+ β1 ln (D1) + β2 ln(Di) +β3 ln(Dj) + β4 ln(Dk) + β5 ln(D2) + β6 ln(D1 Di) + β7 ∆ ln(Yj) +β8 ∆
ln(Y) + uijt
[1]
Where,
Xij: is the bilateral exports from country i to country j in period t.
Yjt: is the GDP of the main exporting countries (j) in time t.
Y is the EU’s GDP in time t
D1: is a dummy variable for capturing the existence of entry prices.
D2: is a dummy variable for capturing the existence of “reduced” entry prices (preferential
imports).
Di: is a vector of dummy variables for each product “i” including those not subjected to the
entry price system.
Di: is a vector of dummy variables for each origin “j” including those not subjected to the
entry price system.
Dk: is a vector of dummy variables for each month, grouping the products in four or five
categories according to their pattern of intra-EU monthly supply.
19
D1 Di is a vector of multiplicative dummy variables for taking into account the impact of the
entry price system applied to specific products.
For treating specific sectors, such as F&V, and bilateral agreements, the interpretation of models like
the presented above needs some note of caution. The model approach ignores the explicit assessment
of specific policy instruments unless applied tariffs in the EU are included in the RHS of the equation.
However, the model must provide for an ex post test of statistical significance of a simple question.
The effect of the entry prices on imports can be studied from the significance of the coefficients of the
binary variables.
The model assesses the import change between a couple of years (for example between 1993/94 and
1995/96) by specifying regression equations as follows:
Gravity model specification
∆ Denotes changes between period "x" and period "y"
Dependent variable: ∆ Log of imports from country “i” to EU15 (in tons)
Explanatory variables:
Intercept
∆ Log of GDP of country i
∆ Log of GDP per capita of country i
∆ Log of domestic production of commodity j for country i (in tons)
∆ Log of EU production of commodity j (in tons)
Trade-agreement variables – dummy variables that identify
country i’s participation in a particular trade agreement in year t
Egypt: Equals one for imports from Egypt for comparisons 2000-2001 to 2005-2006 and zero otherwise
Israel: Equals one for imports from Israel for comparisons 1995-96 to 2000-01, 2000-01 to 2005-06 and zero otherwise
Chile: Equals one for imports from Chile for comparisons 2000-2001 to 2005-2006 and zero otherwise
Morocco: Equals to one for imports from Morocco for comparisons 1995-96 to 2000-01, 2000-01 to 2005-06 and zero
otherwise
South Africa: Equals one for imports from South Africa for comparisons 2000-2001 to 2005-2006 and zero otherwise
Fixed effects denoting entry price
The fixed effect for EP equals one if the commodity has entry price and zero otherwise
Fixed effects denoting neighbouring countries
The fixed effect for neighbouring country equals one if the partner country is neighbour to EU15, and zero otherwise
For example, the dummy variables equal one for Bulgaria, Egypt, Hungary, Israel, Morocco, Romania and Turkey.
20
1.5
Annex to EQ 3 – Gravity Flows
Tab
. 1 E
xis
ten
ce o
f n
on
-zer
o i
mp
ort
flo
ws
of
fres
h F
&V
in
th
e E
U15 (
*)
Pro
du
cts
AR
AU
BG
BR
CL
CN
CR
EG
HU
ILK
EM
ON
ZP
AR
OS
NT
RU
SU
YZ
AN
º fl
ow
s
Tom
ato
+-
++
+-
++
++
-+
--
++
++
-+
14
On
ion
++
+-
++
-+
++
++
+-
--
++
-+
14
Cu
cum
ber
--
+-
--
-+
++
++
--
+-
+-
--
8
Bea
ns
--
--
-+
-+
++
++
--
-+
++
-+
10
S.
Pep
per
s-
-+
+-
+-
++
++
+-
--
-+
--
+1
0
Cou
rget
tes
--
--
--
-+
++
++
--
--
++
++
9
Art
ich
ok
es-
--
--
--
+-
++
+-
--
-+
++
+8
Asp
ara
gu
s+
-+
++
--
-+
-+
+-
--
--
+-
+9
Ora
ng
es+
+-
++
+-
++
+-
+-
--
-+
++
+1
3
Cle
men
tin
es+
--
++
--
++
+-
+-
--
-+
-+
+1
0
Gra
pef
ruit
++
-+
++
-+
++
-+
--
--
++
++
13
Tab
le g
rap
es+
+-
++
+-
++
+-
++
+-
-+
+-
+1
4
Mel
on
s+
--
++
++
++
++
+-
+-
++
--
+1
4
Ap
ple
s+
+-
++
+-
-+
+-
-+
++
-+
++
+1
4
Pea
rs+
+-
++
+-
-+
--
-+
--
-+
++
+1
1
Str
aw
ber
ries
++
-+
++
-+
++
-+
-+
--
++
++
14
Kiw
ifru
it+
+-
-+
+-
-+
--
-+
--
--
+-
-6
Co
un
try
of
ori
gin
of
imp
ort
s:
Note
: (*
) “+
” den
ote
s ex
iste
nce
of
non-z
ero i
mport
s/ “
-“ d
enote
s no e
xis
tence
of
non-z
ero i
mport
s
Sourc
e: C
OM
EX
T d
ata
pro
cess
ed b
y A
gro
syner
gie
.
Leg
en
d:
Ab
b.
Co
un
try
AR
Arg
en
tin
a
BR
Bra
zil
AU
Au
stra
lia
BG
Bu
lga
ria
CL
Ch
ile
CN
Ch
ina
CR
Co
sta
Ric
a
EG
Eg
ypt
HU
Hu
ng
ary
ILIs
rae
l
KE
Ke
ny
a
MO
Mo
rocc
o
NZ
Ne
w Z
ea
lan
d
PA
Pa
na
ma
RO
Ro
ma
nia
SN
Se
ne
ga
l
TR
Tu
rke
y
US
Un
ite
d S
tate
s o
f A
me
rica
UY
Uru
gu
ay
ZA
So
uth
Afr
ica
22
Source: Regression results
Results of one-tailed t-test of parameter significance of estimate:
***Passes at 99-percent confidence level;
**passes at 95-percent level; and
*passes at 90-percent level.
Model 1: Import changes from 1993/94 to 1995/96
Model 2: Import changes from 1995/96 to 2000/2001
Model 3: Import changes from 2000/2001 to 2005/2006
Model 4: Import changes from 1993/94 to 2005/2006
Note:
n.a. Not applicable.
Insig. = Insignificant at 90-percent level.
Posit. = Positive coefficient, significant at 90-percent level.
Neg. = Negative coefficient, significant at 90-percent level
23
1.6
Annex to EQ 3 – Value and volume of im
ports growth
1.6.1
Tables based on COMTRADE database
So
urc
e: C
OM
TR
AD
E d
ata
pro
cess
ed b
y A
GR
OS
YN
ER
GIE
28
1.7 Annex to EQ 3 – Analysis of Preferences
Tab. 1 - Products to which a reduced entry price applies
Source: Commission Regulation (EC) No 1789/2003 and Euro-Mediterranean Agreements
Note: Notice that quotas indicated for Jordanian citrus and cucumbers correspond to the ad valorem tariff quotas.
29
Tab. 2. - Periods for separate analysis. Tomatoes
Tab. 3. - Periods for separate analysis. Cucumbers
Tab. 4 - Periods for separate analysis. Artichokes
November
December
Tab. 5 - Periods for separate analysis. Courgettes
January
1-20April
October
November
December
Tab. 6 - Periods for separate analysis. Oranges
December
January
February
March
April
1-15 May
16-31 may
30
Fig. 1 - Comparison between value of preferential trade and specific gain. Moroccan tomatoes.
0
20
40
60
80
100
120
140
160
Campaign
2003/2004
Campaign
2004/2005
Campaign
2005/2006
Campaign
2006/2007
Million €
Preferential trade
Specific gain
Source: own calculations based on Comext and Taric data. Caveat: calculations for the marketing year 2006/2007 correspond
only to the period October to December 2006.
Fig. 2 - Comparison between value of preferential trade and specific gain. Moroccan cucumbers.
0
500
1000
1500
2000
2500
3000
3500
4000
Campaign
2003/2004
Campaign
2004/2005
Campaign
2005/2006
Thousand €
Preferential trade
Specific gain
Source: own calculations based on Comext and Taric data.
31
Fig. 3 - Total trade value, VPM and specific gain. Moroccan artichokes
- 5.000 10.000 15.000
Euro
20.000 25.000 30.000 35.000
Campaign 2004
Campaign 2005
Campaign 2006
Trade value
VPM
M Specific gain
Source: own calculations based on Comext and Taric data.
Fig. 4- Total trade value, VPM and specific gain. Moroccan clementines
0 20 40 60
Campaign
2003/2004
Campaign
2004/2005
Campaign
2005/2006
Million €
Total trade
VPM
Specific gain
Source: own calculations based on Taric data.
32
Fig. 5 - Values of trade, VPM and specific gain. Jordanian tomatoes.
Source: own calculations based on Comext and Taric data.
Fig. 6 - Values of trade, VPM and specific gain. Jordanian cucumbers.
Source: own calculations based on Comext and Taric data.
33
Fig. 7 - Average SIVs (€/100Kg) and EPs since January 2004. Israel oranges.
0
10
20
30
40
50
60
70
Dece
mbe
rApril
Marketing year 2003/2004 Marketing year 2004/2005 Marketing year 2005/2006
MFN EP Preferential EP
Source: own calculations based on Taric data.
Fig. 8 - Average SIVs (€/100Kg) and EPs since June 2004. Egypt oranges.
0
10
20
30
40
50
60
Dec
ember
Januar
y
Febru
ary
Mar
chApr
il
1-15 M
ay
16-31
May
Marketing year
2004/2005Marketing year
2005/2006MFN EP
Preferential EP
Source: own calculations based on Taric data.
34
Fig. 9- Evolution of Moroccan courgette imports and quota in force (tonnes).
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
Quota
Marketing year 2003/2004
Marketing year 2004/2005
Marketing year 2005/2006
Marketing year 2006/2007
Source: Agrosynergie calculations based on Taric data and EU-Morocco Agreement
35
1.8 Annex to EQ 3 – Seasonal value of Preferences
The VPM has been split into two different addends. The first addend assesses the gain due to the
specific tariff cut, which in turn is caused by the EP reduction. The second addend of the expression
corresponds mostly to the gain due to the cutting of the ad valorem part of the tariff. We call the first
addend “specific gain” and the second is the “ad valorem gain”. It is worth emphasising that the
specific gain is equivalent to an entry price quota rent, as discussed above.
Tomatoes
The next table shows the periods analysis for the tomatoes.
Tab. 1 - Periods for in-marketing year analysis. Tomatoes
This breakdown makes it possible to identify patterns of seasonal variations in the use of the reduced
EP. As the next graph shows, there are a number of periods in which the relevance of the EP quota is
very large in all the marketing years considered: over 80% of the total tariff revenue foregone.
Namely, these periods are February and April. Practically, it means than in these periods Moroccan
tomatoes are priced at the EU border between 92% of MFN EP and its preferential EP. Thus Morocco
takes the highest advantage from this preference, since it is “saving” the MTE if it was treated as
MFN and simultaneously not paying any specific tariff, being considered as preferential.
In a second category, October, November and the two periods in December and March are months in
which Morocco did not take advantage of the preferential EP in all the marketing years, mainly
because of the high SIVs in the marketing year 2004/2005. Therefore, it indicates that in these periods
Morocco is able to benefit from the reduced EP, but the margin of manoeuvre for Morocco is less than
in previous months - if it wants to take full advantage of the preferential EP.
Finally, January and the two periods in May indicate that in some cases Morocco has not taken any
advantage of the reduced EP, but the reasons are different. In January 2004, it exported so cheaply
that average SIV was below 92% of preferential EP, therefore it would have paid the MTE (if the
36
customs clearance of the products had been made on the basis of the standard import value). One can
notice that the situation was not repeated over the next periods and marketing years, perhaps showing
that Moroccan exporters “learnt” to price their tomatoes properly. This result is consistent with the
high AVE calculated for January 2004 in the previous section, clearly over MFN AVE.
The opposite situation happened in several marketing years for the other periods (both parts of May):
average SIV in these periods were often over MFN EP, indicating that the concession was useless in
the period. Nevertheless, it is worthwhile highlighting the fact that the preference was used except on
one occasion in these two periods: as will be shown below, for other products there are periods in
which the preferential EP has not yet been used.
Fig. 1 - Share of EP quota rent of overall preferential rent, by periods and marketing years. Moroccan tomatoes.
0% 20% 40% 60% 80% 100%
Oc tober
November
1-20 Dec ember
21-31 Dec ember
J anuary
F ebruary
Marc h
A pril
1-14 May
15-31 May
Marketing year 2006/2007
Marketing year 2005/2006
Marketing year 2004/2005
Marketing year 2003/2004
Source: own calculations based on Comext and Taric data. Caveat: calculations for the marketing year 2006/2007 correspond
only to the period October to December 2006.
Cucumbers
With regard to the period-by-period analysis, the first thing to stress is the fact that the distribution of
gains by period is quite uneven, even though at the end of the marketing year they are quite similar in
value.
Thus, it can be observed in the next graph that gains happen basically in March and April, once the
“learning process” has occurred in the first marketing year. In these two periods, border prices are
located between preferential EP and 92% MFN EP levels, ensuring the greatest savings for Moroccan
exporters.
37
Fig. 2- Share of EP quota rent of overall preferential rent, by period and marketing year. Moroccan cucumbers.
0% 20% 40% 60% 80% 100%
1-10 November
11-30 November
December
J anuary
F ebruary
Marc h
April
1-15 May
16-31 May
Marketing year 2005/2006
Marketing year 2004/2005
Marketing year 2003/2004
Source: own calculations based on Comext and Taric data.
At any rate, these conclusions should be viewed with caution, since only two marketing years with
specific gains have been analysed and also, great changes in border prices are reported, and their
relationship with different Entry Prices determines the amount of the specific gain. The next graph
compares these series.
Fig. 3- Average SIVs (€/100Kg) in two consecutive marketing years and EPs. Moroccan cucumbers.
0,00
20,00
40,00
60,00
80,00
100,00
120,00
140,00
160,00
180,00
1-10 N
ovem
ber
11-30
Nov
ember
Dec
ember
Januar
y
Febru
ary
Mar
chApr
il
1-15 M
ay
16-31
May
Marketing year
2004/2005
Marketing year
2005/2006
Reduced EP
MFN EP
Source: own calculations based on Taric data.
38
Courgettes
The period-by-period analysis clearly shows that Morocco is taking advantage of the reduced EP only
in the period 1-20 April. In all other periods, border prices are above MFN EP, and thus the
concession is irrelevant. This circumstance apparently happens because in this period the difference
between preferential EP and MFN EP widens compared with other periods, when the gap between
both is quite narrow. The situation is shown in the next graph.
Fig. 4 - Average SIVs (€/100Kg) in two consecutive marketing years and EPs. Moroccan courgettes.
0,00
20,00
40,00
60,00
80,00
100,00
120,00
140,00
160,00
Oct
ober
Novem
ber
Decem
ber
Januar
y
1-20April
Marketing year
2004/2005Marketing year
2005/2006Preferential EP
MFN EP
Source: own calculations based on Taric data.
39
1.9 Annex to EQ 3 – The Trade Model
The proposed model approach unites the following characteristics:
• It is a partial equilibrium model, tailored to model trade impacts of specific policy
instruments.
• It considers imports from different sources as imperfect substitutes, which can be undertaken
through a non-linear Armington type model, which differentiates commodities by their
country of origin (national product differentiation)1.
• The modelled market is the EU-25.
• Composite demand is formed by different sources, including intra-EU25 sources plus the
most important EU-25 suppliers.
• The projections are based on comparative static simulations. In the first versions of the model,
there is no significant interdependence between consuming and producing decisions between
any given pair of monthly periods. A certain degree of dynamism is included through a
shifter, to be applied on the supply and demand equations. Future versions of the trade model
will define more complex structures on monthly price expectations, which consider monthly
production and consumption across the year as the result of a one step choice.
The model offers value added by a detailed specification of policy impacts, through a detailed
specification of policy measures and the specific estimation of policy impacts on a seasonal basis, if
possible at the monthly level.
Model equations
Let us define the main model variables and parameters:
Pj is the internal price of the good originating at j
P is a composite index of internal prices of a product originating at various sources.
Wj is the export price of a good originating at j
αi is the allocation parameter to aggregate imports from different sources.
E is total expenditure on EU imports at internal prices.
kM
is a constant term for the demand for total imports
kEj
is a constant term for the export supply of a good originating at j
σ is the elasticity of substitution
1 A recent comprehensive explanation of the Armington approach and its implications for modelling trade is
presented in P.J. Lloyd and X.G. Zhang (2006): “The Armington Model”, Australian Government, Productivity
Commission, Staff Working Paper, January 2006.
See http://www.pc.gov.au/__data/assets/pdf_file/0012/60411/armingtonmodel.pdf
40
t jo
is the extra-quota total duty (or the only duty when TRQ is not defined)..
t jw
is the price wedge on country j imports.
η is the demand for total imports, including intra-EU and extra-EU partners’ goods.
µj is the export supply of a good originating at j to the EU market.
Mqj is the total quota volume for a product originating at j
Mj = import flow originating at j
q = total composite demand.
Xj = export flow originating at j
Model description
For the sake of simplifying the model description, we assume in the equations below that preferential
suppliers are not constrained by tariffs (though they could be restricted by TRQs). However, the
model extension to the case where tariffs also apply to preferential suppliers is straightforward.
Moreover, the actual empirical exercises are based on the assumption that preferential suppliers are
actually facing tariffs.
Demand side:
We first define the composite good, q, as a Constant Elasticity of Substitution (CES) composite of
intra-EU goods and imports from different regions. Total composite goods demand can be described
by a demand standard equation:
q= kM
Pη
[1]
The price P is an index of prices of the imports originated at various regions:
Import price index:
ρ
σσα
/11
1
1
−
=
−
= ∑
n
i
ii PP , where ρ = (σ-1)/σ
While equation [1] represents the total EU import demand, i.e., for tomato, we need to describe the
specific demand for imports from the considered regions. Thus, the import demand of good
originating at region j is:
EPP
Mjj
j 1−
= σ
σα
[2]
Consequently, the demand side is defined by a composite import demand plus specific demands for
imports from different exporting regions.
Supply side:
Supply functions are specified as a function with constant supply elasticity. Again, imports
originating at various regions are separately modelled. Thus, supply of imports originating at j:
41
Xj = k j
E [Wj ]µ
j
[3]
The relation between internal prices and export prices being this:
)1( w
j
j
t
PWj
+=
where w
jt ≤ o
jt .
Note that a price wedge is defined when imports face TRQs. In the basic formulation a preferential
supplier not constrained by TRQs, when these are not binding, t jw
= 0. When TRQs are binding, then
a price wedge is defined and has to be calculated endogenously. When exports are over the TRQ
limits, then the maximum price wedge is applied, which is, for this case, equal to the maximum tariff
t jo
.
Actually, in the first applications of the model, a differentiation is made, for each supplier, between
the actual tariff applied, on the one hand, and the price wedge resulting from the implementation of
TRQs, on the other.
System equations:
The model is finally constructed through a system of non-linear equation, which can be written and
solved through the use of GAMS programming2..
The equations to be solved are:
Excess of demand good originating at j must be zero:
Mj - jX = 0
Replacing import demand (equation [2]) and import supply (equation [3]) the excess demand
condition is:
[ ] njWjkEPP
jE
j
j
j......101 ==−
− µσ
σα
Replacing Wj by its value in terms of Pj:
njt
PkEP
P
j
w
j
jE
j
j
j......10
)1(
1 ==
+−
−
µ
σ
σα
[4]
Total import demand. This can be expressed as follows:
01 =−+ EPk M η
2 The General Algebraic Modelling System (GAMS) is a high-level modelling system for mathematical
programming and optimization. It consists of a language compiler and a stable of integrated high-performance
solvers. In the case of the import model, GAMS 20.7 142 version with CONOPT-3 solver were used.
42
Note that the equation above is specified just by multiplying the composite demand for the composite
price and rearranging.
Total price index: 0
/11
1
1 =
−
−
=
−∑ρ
σσαn
i
ii PP [5]
Then the system to solve is formed by n + 2 equations and n + 2 unknown variables (n prices, total
expenditure E and composite price P).
TRQs:
As indicated above the price wedge for preferential suppliers can get three kinds of value, depending
on the size of imports compared to the applied TRQs. For cases where preferential tariffs are nil:
a) M j < Mqj then t j
w
= 0
b) M j = Mqj then 0 < t j
w
< t jo
, and t jw
is estimated endogenously.
c) M j > Mqj then t j
w
= t jo
Calibration
Calibration is based on unit price normalisation, so that all constants are equal to benchmark
expenditures. If a TRQ is binding we have to propose a value for the reference price wedge. However,
if Mj >Mqj then the price wedge is taken as the initial out-of-quota tariff t j
o
.
Adjustment to study export refunds
Equation 3 can be adjusted to consider shifts in the total EU supply in the non-EU market related to
export refunds. To study the effect of export refund changes we will take the same modelling
approach and the supply function including constant supply elasticity. Again, imports originating
from various regions are separately modelled. Thus, supply of imports originating from the EU in the
world market being:
X [ ]µEUk= [3]
Where U is the EU internal price (including the export refund per physical unit), and the relation
between world and EU export prices being this:
PSU )1( +=
where S is the export refund per ton.
Trade policy scenarios
The preliminary version of the F&V trade model is applied to study the trade impacts of several
scenarios of trade liberalisation. These scenarios are the following:
43
• Eliminating Entry Prices. If entry prices are phased out, this has an impact on both
preferential suppliers as well as MFN imports.
• Eliminating export subsidies. What has been the impact of the export refund reduction and
what would be the impact of its complete elimination?
1.9.1 The Export Model
Basic data and assumptions
48
Calculation of the deadweight loss
Benchmark figures
EU15 Export value (Euros) Total ER (Euros)
2000 2005 2000 2005
Tomatoes 205585367 269851811 1014.0 1051.0
Oranges 175962536 180180117 22738.0 8608.0
Apples 236452775 239490388 4353.0 3255.0
Table grapes 170070869 235728205 1338.0 756.0
Source; COMTRADE, DG AGRI, processed by Agrosynergie
Price and volume changes in EU exports
Price change (%) Volume change (%) Volume change (euros)
2000 2005 2010 2015 2020 2025
Tomatoes -0.2 -0.1 -1.6 -1.3 -3289366 -3508074
Oranges -3.9 -1.5 -32.6 -14.4 -57363787 -25945937
Apples -0.6 -0.5 -5.7 -4.5 -13477808 -10777067
Table grapes 0.5 0.2 -2.6 -1.0 -4421843 -2357282
Source; COMTRADE, DG AGRI, processed by Agrosynergie
Exporter losses (million euros)
2000 2005
Tomatoes -0.4 -0.3
Oranges -6.9 -2.7
Apples -1.4 -1.2
Table grapes 0.9 0.5
Total -7.8 -3.7
Source; COMTRADE, DG AGRI, processed by Agrosynergie
49
1.9.2 The Import Model
Assumption on Elasticities Import Model
Assumption 1 Assumption 2
EU domestic demand elasticity 1 0,5
EU intra trade supply elasticity 2 1
Third countries supply
elasticity 10 5
Elasticity of substitution 5 2,5
Assumptions on elasticity import model - TOMATOES
Assumptions on elasticity import model - CUCUMBERS
50
The next tables show the raw data used to run the import model. All of them come from official EU
data (trade values, EP levels, average SIV by periods, TRQs and duties).
The figure under “in-quota tariff reduction” indicates the reduction -from the MFN level- of the ad
valorem tariff if trade is within the TRQ for the preferential supplier. Hence, “1” means total
elimination of the tariff. Similarly, the “out-of-quota” tariff reduction is the reduction of the MFN ad
valorem tariff that applies for the preferential partner for quantities traded over the TRQ. Hence, the
figure “0,6” indicates a 60% tariff reduction.
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