the agricultural trade of the european union: consequences for virtual land trade and self-sufficien

The agricultural trade of the European Union

Consequences for virtual land trade and self-sufficiency

Steffen Noleppa and Matti Cartsburg

HFFA Research GmbH

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HFFA Research Paper 03/2015

The agricultural trade

of the European Union

Consequences for virtual land trade

and self-sufficiency

Steffen Noleppa

Matti Cartsburg

agripol – network for policy advice GbR

Content

List of figures ............................................................................................................. iii

List of abbreviations ................................................................................................... iv

1 Introductory remarks .............................................................................................. 1

2 Trends of the EU’s virtual agricultural land trade ................................................ 2

3 Current agricultural self-sufficiency ratios of the EU ........................................... 9

4 Concluding remarks .............................................................................................. 16

Reference list ............................................................................................................. 17

Annex ......................................................................................................................... 21

ii Noleppa, S.; Cartsburg, M. | EU agricultural trade: Consequences for virtual land trade and self-sufficiency


Acknowledgement

This research has been made possible, in part, by financial support from the Euro-

pean Crop Protection Association (ECPA). We particularly thank Euros Jones and

Claudia Michel from ECPA for valuable feedback throughout the entire study

phase. In addition, we gratefully acknowledge the opportunity to publish our report

as a research paper of HFFA Research GmbH. The results of this study are the sole

responsibility of the authors and have never been influenced by the supporter of

the study.

Noleppa, S.; Cartsburg, M. | EU agricultural trade: Consequences for virtual land trade and self-sufficiency iii


List of figures

Figure 1: Total virtual agricultural land net imports of the European

Union, 2000-2014 (in million ha) ............................................................ 2

Figure 2: Virtual agricultural land trade of the European Union

for crops and livestock products, 2000-2014, net imports (+),

net exports (–) (in million ha).................................................................. 4

Figure 3: Net imports (+) and net exports (–) in virtual agricultural land

of the European Union by crop and livestock commodity,

on average for 2012-2014 (in million ha) ................................................ 7

Figure 4: Regional distribution of net virtual agricultural land trade

of the European Union, on average for 2012-2014

(in million ha) .......................................................................................... 8

Figure 5: Self-sufficiency ratio of the European Union for some

major agricultural commodities, on average for 2012-2014

(in percent) ............................................................................................. 10

Figure 6: Aggregated agricultural self-sufficiency of the European

Union in terms of grain units, 2012-2014 and on average

(in percent) ............................................................................................ 11

Figure 7: Self-sufficiency of the European Union in wheat and

sunflowers, 2012-2014 (in percent) ....................................................... 12

Figure 8: Agricultural self-sufficiency of the European Union

for important commodities in terms of carbohydrates,

proteins and fats, average for 2012-2014 (in percent) .......................... 13


Union in terms of carbohydrates, 2012-2014 and on average

(in percent) ............................................................................................. 14


Union in terms of proteins, 2012-2014 and on average

(in percent) ............................................................................................ 15


Union in terms of fats, 2012-2014 and on average

(in percent) ............................................................................................ 15

iv Noleppa, S.; Cartsburg, M. | EU agricultural trade: Consequences for virtual land trade and self-sufficiency


List of abbreviations

CAP – Common Agricultural Policy

CETA – Comprehensive Economic and Trade Agreement

CIS – Commonwealth of Independent States

ECPA – European Crop Protection Association

EU – European Union

FAO – Food and Agriculture Organization

GU – Grain Unit

HFFA – Humboldt Forum for Food and Agriculture e.V.

HVO – Hydro-treated Vegetable Oil

IFPRI – International Food Policy Research Institute

MENA – Middle East and North Africa

SITC – Standard International Trade Classification

TTIP – Transatlantic Trade and Investment Partnership

TLL – Thüringer Landesanstalt für Landwirtschaft

UNEP – United Nations Environment Programme

Noleppa, S.; Cartsburg, M. | EU agricultural trade: Consequences for virtual land trade and self-sufficiency 1


1 Introductory remarks

Discussing agricultural trade issues of the European Union (EU) is a continuous

process. Currently, the apparent opportunities and the mainly perceived risks of

the Transatlantic Trade and Investment Partnership (TTIP) between the EU and

the United States and the Comprehensive Economic and Trade Agreement (CETA)

between Canada and the EU are hotly debated. The authors of this paper have con-

tributed to this discussion by looking at agricultural trade issues from another

point of view. A new perspective was particularly opened by introducing the con-

cept of virtual agricultural land trade (von Witzke and Noleppa, 2010), an ap-

proach, which has gained more and more attention in scholarly research (see, e.g.,

Louwagie, 2013; Qiang et al., 2013), statistical analysis (see, e.g., Destatis, 2013a;

b) and public as well as policy debates (see, e.g., van den Bergh and Grazi, 2013;

WWF Germany, 2012; 2015). The approach originally developed in von Witzke and

Noleppa (2010), slightly amended in von Witzke et al. (2011) and peer-reviewed

published in Kern et al. (2012) as well as Lotze-Campen et al. (2015) is also used as

the reference system for arguing in peer-reviewed scientific papers (see Meier et

al., 2014) and policy reports (see UNEP, 2015).

In addition, the authors of this study aimed at developing and applying a method-

ology to continuously, i.e. annually, measure agricultural self-sufficiency of the EU,

because the discussion of various arguments surrounding the renewal of the old,

post-war-driven agricultural self-sufficiency debate (see, e.g., Bouet and Laborde,

2008; de Schutter, 2011) has led to the conclusion that reliable data on self-

sufficiency are lacking to build respective arguments upon verifiable information,

as, for instance, in Häusling (2011) who argues that the EU suffers from an im-

portant protein deficit amounting to approximately 70 percent.

Against this background, a multi-annual research project was launched in the year

2013 to continuously provide (a) most recent information on the virtual agricultural

land trade of the EU and (b) a meaningful set of self-sufficiency indicators, which

offer detailed but also highly aggregated and easily understandable information.

The initial findings of this project were published in Noleppa and Cartsburg (2013);

and with Noleppa and Cartsburg (2014), a first update of respective data and in-

formation was provided.

This paper shall be considered the next update. In the following, the revisited

trends of the EU’s virtual agricultural land trade since the turn of the millennium

will be highlighted (chapter 2). It follows a visualisation and interpretation of most

recent agricultural self-sufficiency figures for the EU (chapter 3). Some conclusions

will finally be drawn (chapter 4). A comprehensive annex will give additional and

more detailed information on selected issues constituting the methodological and

data base of the research findings displayed in the following.

2 Noleppa, S.; Cartsburg, M. | EU agricultural trade: Consequences for virtual land trade and self-sufficiency


2 Trends of the EU’s virtual agricultural land trade

The following discussion is based on results obtained from applying the methodolo-

gy outline in annex A01 of this report. Accordingly trends of the EU’s virtual agri-

cultural land trade are analysed for every single year since the turn of the millen-

nium, and for each agricultural commodity or group of commodities.

Before analysing the development of the EU’s virtual agricultural land trade in

detail, i.e. by single crop and/or livestock, it is worth putting emphasis on the de-

velopment of the EU’s entire virtual agricultural land trade. Figure 1 visualises the

outcome.

Figure 1: Total virtual agricultural land net imports of the European

Union, 2000-2014 (in million ha)

Source: Own figure based on own calculations.

First, it becomes apparent that land trade figures – based on the methodology and

data set described in annex A01 – are somewhat lower than in previous years for

reasons to be discussed below. Nevertheless, the overall situation has not changed:

The EU was and still is a major net importer of virtual agricultural land at global

scale. Since the turn of the millennium, it was at no point a net exporter of virtual

agricultural land. Looking backwards, two remarkable aspects become obvious:

In the year 2000, net imports of virtual agricultural land of the EU were low-

er than 15 million ha but rose steadily until they peaked in the year 2007

with slightly over 31 million ha virtually imported. During this time, the EU

lost some competitiveness in major agricultural markets following a loss of

0

5

10

15

20

25

30

35

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014



former protection, i.e. a further liberalisation of the Common Agricultural

Policy (CAP).

Since then, a rather steep decline had been witnessed leading to a virtual

agricultural land net import of slightly more than 14 million ha in the past

year. This is the lowest value since the turn of the millennium, but still more

than the entire arable land of Germany or the territory of Greece. Obviously,

EU farmers have been able to increase production in times of additional agri-

cultural demands and re-gained a lot of formerly lost competitiveness. This

was mainly achieved by increasing agricultural productivity and productivity

downstream the entire agricultural value chain.

However, only by going more into detail, it is possible to look behind this recent

development. First insights can be provided by splitting the graph depicted in fig-

ure 1 into two charts displaying the development of net virtual agricultural land

imports or exports based on the trade of crops and the trade of livestock products.

The result is visualised in figure 2.

Accordingly, the EU continues to be a large net importer of virtual agricultural

land that can be attributed to crops. The calculated values have ranged between 20

and 30 million ha since the year 2000. The highest net virtual import values were

reached in the years 2006 and 2007; during the last three years (2012 to 2014) ag-

ricultural land was net imported at roughly 20 million ha. This is still slightly more

than the initial virtual land trade value at the turn of the millennium (15.5 million

ha) and marks the need for further resource-saving productivity increases in EU

agriculture.

Behind this development are various more specific determinants. Looking at the

annexes A02 to A15, it becomes apparent that not only liberalisation effects of the

CAP reform, but also other drivers have been important. Major factors are as fol-

lows:

Taking the example of wheat (see annex A02), first, it becomes obvious that

the EU took responsibility during the food price crises in recent years, when

some of the major wheat exporting nations banned further exports, and con-

siderably enlarged own wheat production and, hence, exports to maintain

global food security and to profit from comparably high international com-

modity prices. Virtual wheat area exports have risen from 2 million ha to 8

million ha since the year 2007, already explaining half the development in

virtual crop area trade since that year. The importance of yields becomes ap-

parent: While the average EU wheat yield was around 5 tons per hectare in

the years 2006 and 2007, it has been approximately 10 percent higher in the



most recent years covered in this report. In addition, the area cultivated with

wheat grew by 2 percent.

Using similar arguments, coarse grains contributed another million ha to the

improvement of our – still negative – virtual land trade balance during past

years (see annex A04). Barley yields today are also 10 percent higher.

Figure 2: Virtual agricultural land trade of the European Union for

crops and livestock products, 2000-2014, net imports (+), net

exports (–) (in million ha)


0

10

20

30

40

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Crops

-4

-2

0

2

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Livestock



Taking the year 2007 as a reference year, the development in virtual soya

area imports is astonishing, too. This virtually imported acreage dropped by

approximately 5 million ha (see annex A06). The reasons here, however, are

different. Behind this development are no remarkable compensation effects of

substituting soya for feed. In fact, it is – again – yield development, but this

time abroad, that contributed to an enhancement of our own EU virtual land

trade balance (according to FAO, 2015b, major export nations such as Argen-

tina, Brazil and the USA have increased soya yields between 10 and 20 per-

cent since 2007), on the one hand; and, on the other hand, it is a considerable

increase in EU net exports (i.e. a re-export of formerly virtually traded land)

which can be associated to exported vegetable oil separated from domestically

used soya meal after having crushed already imported soy beans in the EU.

In opposite to that, the agricultural land trade balance of the EU became

worse for some other commodities. Palm is a remarkable example (see annex

A07): Between 2000 and 2014, the EU almost tripled the amount of palm land

that was virtually net imported. This is most probably due to the large in-

crease in palm oil imports for bioenergy generation (and so called Hydro-

treated Vegetable Oil (HVO) production in the most recent tree years), hence

due to an emerging new demand. This accumulates to an extra virtual land

import of more than 1.0 million ha since the year 2007. Such an additional

demand might also be the reason for the worsening of the land trade balance

for oilseed rape by 2.0 million ha since 2007 (see annex A08).

Other crops show less obvious changes over time when it comes to assessing

virtual land trade of the EU. The situation is rather stable, for instance, in

the cases of coffee and cocoa (see annex A10) and other stimulants such as tea

and tobacco (see annex A11) as well as pulses (see annex A14).

The case of pulses is particularly interesting from another perspective, too.

Despite often politically announced protein deficits and needs for increasing

quantities of supplied pulses (see, e.g. Häusling, 2011), the EU market actors

obviously still refused to take action. Apparently, market framework condi-

tions offer more efficient solutions to cope with challenges than policy may

advice.

Finally, a note on sugar crops (see annex A15), which tend to become more

and more important with respect to their contribution to the EU’s virtual net

land imports, most likely as an effect of policy activities in most recent years

towards more liberalised sugar markets. In the last years, the additional

acreage used abroad rose by almost 1.0 million ha.



The virtual land trade of livestock products is as diverse as the crops-related land

trade of the EU. However, here the EU is in a net export position. This becomes

obvious by looking at figure 2 and the annexes A16 to A21. Around the turn of the

millennium, the EU was already a net exporter of virtual agricultural land devoted

to livestock products (see the negative prefix in figure 2). However, between the

years 2003 and 2007 the EU turned into a net importer of livestock-related land.

Close to 2 million ha were net imported as a virtual input in livestock products.

Since then, the situation changed again leaving the EU to be a net exporter of vir-

tual agricultural land for livestock products ever since 2009. In the year 2014, vir-

tual land exports of approximately 3.3 million ha were realised. Major contributors

to that were:

Beef with 2.0 million ha (see annex A16) and the other meat markets together

contributing an additional 2.0 million ha to the improvement of the EU’s vir-

tual land trade position, but also

Dairy products (see annex A21) adding another 0.5 million ha (especially in

most recent years).

Obviously, the EU livestock sector was able to increase its competitiveness or im-

prove its land use productivity. Indeed, entrepreneurial EU agriculture seems to

have been able to re-gain a substantial part of the competitiveness it apparently

lost around the turn of the millennium when the EU agricultural markets were

confronted with a more liberalised CAP of the EU leading to a considerable loss of

market protection.

Looking not only at the long-term trends, but additionally analysing the net im-

ports and exports of virtual agricultural land by crop and livestock category more

particularly for the most recent years, i.e. 2012-2014 (or what we consider: the sta-

tus quo), leads to even more insights. As becomes clear by looking at figure 3, the

current situation is rather complex. While the EU in total virtually net imports

roughly 17.5 million ha (last update: 18.6 million ha), there are big differences in

the trade balance for individual crops and livestock groups:

As in previous analyses, oilseed crops as well as coffee and cocoa products still

facilitate the vast majority of net virtual land imports into the EU. The, by

far, most important driver of virtual land imports is again soya with 13.1 mil-

lion ha (last update: 13.4 million ha), followed by coffee and cocoa with 5.7

million ha (last update: 5.9 million ha), oilseed rape with 2.6 million ha (last

update: 2.7 million ha), palm with 2.3 million ha (last update: 1.8 million ha)

and other oilseeds with almost 3.4 million ha (last update: 3.3 million ha).

Net virtual land imports of corn with 1.1 million ha (last update: 1.0 million



ha) and rice with 0.5 million ha (last update: also 0.5 million ha) still play a

comparably minor role, herein.

Accordingly, net virtual exports of agricultural land are dominated by wheat

with 6.3 million ha (last update: 5.2 million ha) and coarse grains with 3.4

million ha (last update: 3.1 million ha) as well as livestock products, especial-

ly pork with 2.4 million ha (last update: also around 2.4 million ha), dairy

products with 0.7 million ha (last update: 0.5 million ha) and poultry with 0.5

million ha (last update: 0.4 million ha).

A closer look at the world regions affected most by the current virtual agricultural

land trade of the EU is finally provided with figure 4.

Figure 3: Net imports (+) and net exports (–) in virtual agricultural land

of the European Union by crop and livestock commodity,

on average for 2012-2014 (in million ha)


-10 -5 0 5 10 15 20

Wheat

Corn

Coarse Grains

Rice

Soya

Palm

Oilseed Rape

Other Oilseeds

Coffee and Cocoa

Tea and Tobacco

Fruits

Vegetables and Potatoes

Pulses

Sugar Crops

Beef

Sheep and Goat meat

Pork

Poultry

Eggs

Dairy

Cotton

Total



Figure 4: Regional distribution of net virtual agricultural land trade

of the European Union, on average for 2012-2014 (in million ha)

North America Asia Africa CIS

3.004 0.946 1.747 3.901

South America MENA Countries Rest of Europe Rest of the World

14.825 –7.481 –2.239 2.827


The region affected most by virtual net agricultural land imports of the EU is – as

in previous analyses – South America. Over 14.8 million ha (last update: 14.3 mil-

lion ha) of agricultural area in that region are virtually occupied by the EU. The

vast majority of this imported area certainly comes from soya (10.6 million ha),

followed by coffee and cocoa (1.5 million ha). The most important regions in which

virtual agricultural land from the EU is net exported are the Middle East and

North Africa (MENA) regions with 7.5 million ha (last update: 6.4 million ha). The

majority of virtual land being exported to the MENA region is devoted to wheat

(4.4 million ha) and coarse grains (1.5 million ha). Such regional and crop-specific

figures are summarised with annex A22.



3 Current agricultural self-sufficiency ratios of the EU

Methodological particularities leading to the results discussed in the following can

be obtained from annex A23 of this report. Accordingly, figure 5 visualises the self-

sufficiency ratio of the EU for major agricultural commodities using average values

for the years 2012-2014.

Looking at the graphs displayed, it becomes apparent that the EU is currently able

to produce more agricultural raw materials and marketed products thereof than

necessary for domestic consumption of some major crops and livestock. The self-

sufficiency surplus, e.g. in wheat is 17 percent, and it is 7 percent in potatoes; in

pork it is 14 percent, and in eggs and milk full self-sufficiency is exceeded by 2 re-

spectively 7 percent.

However, it is obvious, too, that with respect to other crops and livestock products

the EU is, partially by far, not self-sufficient. The deficit in self-sufficiency is par-

ticularly large in some fruits, such as bananas – the self-sufficiency ratio here is

only 12 percent –, but also in major oilseed crops and some protein crops.

This becomes even more obvious by looking at annex A24 to the report. The annex

depicts all the crop-specific and livestock-specific self-sufficiency ratios covered by

this analysis not only for the average of the years 2012 to 2014, but annually. By

and large, it turns out that latest findings (see Noleppa and Cartsburg, 2014) can

be confirmed: Agricultural self-sufficiency in the EU is very diverse indicating that

EU member states are well integrated into world markets exporting various com-

modities for which the EU obviously has a comparative advantage in exchange to

importing other products which should be produced more efficiently abroad.

Using now ‘grain units’ (GU) (see also the methodological considerations in annex

A23) as a means to sum up product-specific self-sufficiency ratios to a single figure

indicating overall agricultural self-sufficiency for the EU as a whole enables to argue

on a different, but more general level. Against this background, the following fig-

ure 6 describes to what extent the EU has been self-sufficient from an aggregated

nutritional point of view in the past three years and on average for the years 2012

to 2014.

It turns out that – on aggregate – the EU is not self-sufficient in terms of all the

nutrients normally locked in agricultural products and principally available for

different usages: The respective self-sufficiency ratio is only 88.9 percent on aver-

age for the years 2012 to 2014. However, there seems to be a tendency to improve

agricultural self-sufficiency a bit. It has been 88.2 percent in 2012 and 89.1 percent

in 2013; according to latest figures, agricultural self-sufficiency of the EU reached

89.4 percent in 2014.



Figure 5: Self-sufficiency ratio of the European Union for some major

agricultural commodities, on average for 2012-2014 (in percent)


0

20

40

60

80

100

120

Wheat Corn

0

20

40

60

80

100

120

Oilseed Rape Soya

0

20

40

60

80

100

120

Sugar (Raw) Potatoes

0

20

40

60

80

100

120

Beans Peas

0

20

40

60

80

100

120

Apples Bananas

90

95

100

105

110

115

120

Tomatoes Cucumbers

90

95

100

105

110

115

120

Beef Pork

90

95

100

105

110

115

120

Eggs Milk




Union in terms of grain units, 2012-2014 and on average

(in percent)


Distinguishing crop products from livestock products gives additional insights:

Although in total not self-sufficient, the EU is self-sufficient in livestock

products; the average surplus in terms of GU (not visualised in figure 6) is

around 7 percent.

On the opposite, the EU’s self-sufficiency deficit is – as in previous years –

quite large in crop products and amounts to 14 percent, i.e. the self-

sufficiency ratio is about 86 percent for the average of the years 2012 to 2014.

The yearly ratios here were 85.0 percent (in 2012), 86.2 percent (in 2013) and

86.5 percent (in 2014). Accordingly, a slow improvement can be observed

which surely has been supported by overall agricultural productivity growth

in the EU.

Fluctuations are obvious, especially in crop production, and become apparent when

looking at single commodities, as in figure 7 which displays, on an exemplified

base, ups and downs with respect to wheat and sunflowers, two major agricultural

commodities domestically produced at a rather large scale.

87

88

89

90

2012 2013 2014

Average



Figure 7: Self-sufficiency of the European Union in wheat and

sunflowers, 2012-2014 (in percent)


An extraordinarily good harvest for both crops in 2013 (compared to 2012) led to a

considerable increase in the EU’s crop-specific self-sufficiency ratio for the year

2013 (compared to 2012): It rose for wheat from 109 percent to 119 percent and for

sunflowers from 54 percent to 74 percent. In the year 2014, the self-sufficiency in

wheat further increased (to 123 percent), whereas self-sufficiency in sunflowers

decreased (to 70 percent). This highlights the dependency of crop production on

natural framework conditions (such as weather), but also the overall importance of

crop productivity (growth) for improving the overall agricultural performance and

development in the EU.

In opposite to that, self-sufficiency ratios for livestock products are rather stable as

annex A24 displays. Here, ad-hoc disturbances such as weather conditions influ-

encing feed availability and overall livestock performance certainly play a minor

role.

Figure 8, now, depicts average self-sufficiency ratios for specific nutritional ingre-

dients, namely carbohydrates, proteins and fats (or vegetable oils). By and large,

the argument discussed with respect to the general nutritional value (based on GU)

does not change. The EU is self-sufficient in the provision of carbohydrates, pro-

teins and fats borne by livestock products, and not self-sufficient when these com-

ponents have to come from crops and products thereof.

0

30

60

90

120

150

2012 2013 2014

Wheat Sunflowers



Figure 8: Agricultural self-sufficiency of the European Union

for important commodities in terms of carbohydrates,

proteins and fats, average for 2012-2014 (in percent)

Commodity Group Carbohydrates Proteins Fats

Cereals 107 109 104

Oilseeds 80 73 83

Roots 106 107 106

Sugar Crops 82 82 82

Pulses 89 90 85

Vegetables 105 104 105

Fruits 79 79 72

Total, Crops 90 83 84

Meat 111 109 111

Eggs 102 102 102

Milk 107 107 107

Total, Livestock 109 108 109

Total 92 85 87


Interesting are differences between carbohydrates, proteins and fats originating

from crops and livestock, respectively:

More particularly, a carbohydrate surplus provided in livestock production of

around 9 percent is overcompensated by an “energy” deficiency occurring in

crop production of approximately 10 percent.

Even more pronounced is the difference in the EU’s agricultural self-

sufficiency in terms of proteins. Although more animal protein is available

from domestic production than actually needed (plus 8 percent), the total pro-

tein balance is negative because the EU suffers from a protein deficiency in

crop production accumulating to around 17 percent. However, this deficit is –

by far – less than what has been argued in, e.g., Häusling (2011) or public de-

bate.

Looking finally at the vegetable oil content of crops, the EU also envisages a

high deficit (16 percent). In opposite to that the EU is still self-sufficient in

animal fats. The surplus here amounts to 9 percent. However, it does not

compensate the deficit in crop production.



Based on figure 8 and the following three figures 9 to 11 depicting the EU’s self-

sufficiency picture for single nutrients, a few final but important facts shall be

highlighted:

The average agricultural self-sufficiency for the years 2012 to 2014 is the big-

gest with respect to carbohydrates, but reaching not more than 91.6 percent

(see figure 9).

It is lowest in proteins and sums up, here, to approximately 85.1 percent (see

figure 10).

For fats, the agricultural self-sufficiency of the EU is in between and slightly

below 87 percent (see figure 11).

All in all, it turns out that the EU is not self-sufficient in all three basic nutrients.

However, the nutrient-specific situation has improved in past years. All three com-

ponents – carbohydrates, proteins and fats (vegetable oils) – show an upward

trend, as figures 9 to 11 visualise. Again, the particular importance productivity

growth plays for such a development shall be highlighted.

Figure 9: Aggregated agricultural self-sufficiency of the European Union

in terms of carbohydrates, 2012-2014 and on average (in percent)


90

91

92

93

2012 2013 2014

Average




in terms of proteins, 2012-2014 and on average (in percent)



in terms of fats, 2012-2014 and on average (in percent)


83

84

85

86

87

2012 2013 2014

Average

85

86

87

88

2012 2013 2014

Average



4 Concluding remarks

This research paper highlights that the EU is currently net importing a still re-

markable amount of virtual agricultural land – almost 18 million ha on average for

the years 2012 to 2014. However, the amount of land virtually imported has de-

creased since the year 2007. That the EU is using today fewer agricultural re-

sources abroad than in past years can also be seen by looking at most recent agri-

cultural self-sufficiency indicators. Although still below 100 percent – thus indicat-

ing an overall higher import than export of crop and livestock commodities and

products thereof – agricultural self-sufficiency has slightly improved over time be-

ing currently at around 89 percent, if measured in terms of GU.

These foremost positive developments can largely be associated with an increasing

agricultural productivity in the EU, but also abroad. Hence, it becomes apparent

that investing into and allowing for additional productivity growth is beneficial not

only to agricultural producers and traders as well as food and other consumers, but

for the environment and, therefore, the society at large.

On the one hand, future agricultural productivity growth not only but especially in

the EU is deeply needed in order to meet the continuously increasing demand for

food, feed, fibre, and fuel; and this requires a multidisciplinary approach driven by

science, technology and innovation. On the other hand, the necessary agricultural

productivity increases are endangered. The public perception of productivity-

oriented agriculture often displays a remarkable indifference and even outright

scepticism relative to such modern farming practices, and policy debates mirror

this perception. Recent discussions on the enforcement of various EU regulations,

e.g., have pointed at additional administrative burdens and entrepreneurial costs

for input suppliers and at the farm level.

This may jeopardise a continuous flow of resources into research and development

aiming at further productivity increases in EU agriculture. Reluctance of small-

and medium-scale enterprises and also large input suppliers towards investing into

research and development for, e.g., new and better crop protection products, im-

proved plant varieties and/or novel nutritional options may increase due to associ-

ated uncertainties and real costs which cannot be easily borne. Hence, a slowing

down of the productivity progress might be the result.

If the EU not only wants to improve its real and virtual agricultural trade balances

but to pay its fair share and a remarkable contribution towards better conditions

for world food security and global resource protection, it should attract innovation

instead of hampering it.



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Annex

Annex A01: Methodological remarks on the calculation of the

virtual agricultural land trade of the EU ........................................... 23

Annex A02: Virtual agricultural land trade of the European Union

for wheat and products thereof, 2000-2014, net imports (+),

net exports (–), (in million ha) ............................................................ 25


for corn and products thereof, 2000-2014, net imports (+),



for coarse grains and products thereof, 2000-2014,

net imports (+), net exports (–), (in million ha) .................................. 26


for rice and products thereof, 2000-2014, net imports (+),



for soya and products thereof, 2000-2014, net imports (+),



for palm and products thereof, 2000-2014, net imports (+), net

exports (–), (in million ha)................................................................... 27


for oilseed rape and products thereof, 2000-2014,



for other oilseeds and products thereof, 2000-2014,



for coffee and cocoa and products thereof, 2000-2014,



for tea and tobacco and products thereof, 2000-2014,



for fruits and products thereof, 2000-2014, net imports (+), net

exports (–), (in million ha)................................................................... 30




for vegetables and potatoes and products thereof, 2000-2014,



for pulses and products thereof, 2000-2014, net imports (+),



for sugar crops and products thereof, 2000-2014, net imports (+),



for beef and products thereof, 2000-2014, net imports (+),



for sheep and goat meat and products thereof, 2000-2014,



for pork and products thereof, 2000-2014, net imports (+),



for poultry and products thereof, 2000-2014, net imports (+),



for eggs and products thereof, 2000-2014, net imports (+),



for milk and products thereof, 2000-2014, net imports (+),


Annex A22: Virtual agricultural land trade of the European Union,

net imports (+), net exports (–), by region and commodity and

as an average of the years 2012-2014, (in million ha) ........................ 35

Annex A23: Methodological remarks on the calculation of the agricultural

self-sufficiency of the EU .................................................................... 36

Annex A24: Specific self-sufficiency ratios of agricultural commodities

for the European Union in recent years and on average

(in percent) .......................................................................................... 40



Annex A01: Methodological remarks on the calculation of the virtual

agricultural land trade of the EU

The virtual agricultural land trade approach used here is based on the concept of

virtual inputs initially developed by Allan (1993; 1994) for water. The basic idea is

as follows: Any good being produced requires inputs. The inputs used in the pro-

duction of a good are then considered a virtual part of this good. Hence, when a

good is traded internationally the virtual input is traded simultaneously (see also

Mekonnen and Hoekstra, 2011; Hoekstra, 2003; Hoekstra and Hung, 2002).

Here, this concept is modified so it can be applied to the input ‘land’ in agricultural

commodity production. By analogy, we define virtual land as the amount of land

that is required to produce one unit of a given agricultural good. For instance, if it

takes ‘X’ ha of land to produce one metric ton of wheat, the ‘X’ is the number of ha

of virtual land contained in one metric ton of wheat. Exporting (importing) one

metric ton of wheat from one country to another is then equivalent to the export

(import) of ‘X’ ha of virtual land. In essence, the import of agricultural goods adds

land to the domestic resource base, while the export acts to reduce it.

An essential to calculate meaningful virtual land trade figures is therefore reliable

and up-to-date foreign trade statistics. Looking at the EU, data of Eurostat have

been proven to be consistent in this respect. Eurostat (2015b) data have now been

used to analyse the EU’s virtual agricultural land trade.

Point of departure for the particular analysis are international agricultural trade

volume flows, i.e. export and import tonnages, which are based on an international-

ly agreed classification of commodities and are available for each trading partner of

the EU. In particular, the Standard International Trade Classification (SITC), one

of the most widely used classification systems in international trade analysis, is

used hereafter. The SITC categories distinguish various degrees of processing,

meaning that goods from identical raw materials (e.g. wheat) may end up in differ-

ent classifications (e.g. wheat flour, feed preparations, pasta, etc.). However, they

can also be always attributed to their raw material again.

In this analysis of international agricultural trade not only suitable categories of

SITC 0 (Food and live animals) and SITC 1 (Beverages and tobacco) are included

but additionally numerous categories of SITC 22 (Oilseeds and oleaginous fruits),

SITC 263 (Cotton) and SITC 4 (Animal and vegetable oils, fats and waxes). In total,

almost 300 different SITC categories of tradable agricultural commodities and prod-

ucts thereof are included in the analysis. For all these SITC categories, export and

import data in terms of volume (i.e. tons) were generated from Eurostat (2015b) for

the EU and for the years 2000 to 2014.



The conversion of agricultural trade data into land trade information requires the

application of a rather complex methodology and several intermediate steps to be

performed for each SITC category:

First, it is essential to re-convert traded agricultural goods back into their

respective raw material using consistent technical parameters and suitable

conversion factors.

Looking particularly at agricultural raw materials that can be processed into

more than one good to be categorised into different SITC numbers – this is,

e.g., the case with oilseeds, which are usually processed into oil and cake, or

dairy products, namely butter, cheese and milk – a potential double counting

of hectares has to be avoided, too. FAO (2012) data allow to do so.

The resulting trade volumes (in terms of agricultural raw products) have then

to be related to annual regional yields. The respective information is now

taken from FAO (2015b) and allows to compute region-specified land used for

exports or imports.

Finally, it is necessary to calculate the net imports respectively net exports

for every single SITC category, therefore for every internationally traded ag-

ricultural commodity, and for each trading partner of the EU.

Using this gradual approach of SITC by SITC category, it is possible to sort the

traded agricultural goods into 57 different crop and livestock groups of agricultural

raw materials. These 57 groups can pragmatically be concentrated into altogether

21 groups of primary crops and livestock, which will be used here for proper analy-

sis. This includes (see also annexes A02 to A21):

Wheat, corn, coarse grains, rice, soya, palm, oilseed rape, other oilseeds, cof-

fee and cocoa, tea and tobacco, fruits, vegetables and potatoes, pulses, sugar

crops, and cotton as well as

Beef, sheep and goat meat, pork, poultry, eggs and milk.



Annex A02: Virtual agricultural land trade of the European Union for

wheat and products thereof, 2000-2014,

net imports (+), net exports (–), (in million ha)



corn and products thereof, 2000-2014,



-10

-8

-6

-4

-2

0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

-2

0

2

4

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




coarse grains and products thereof, 2000-2014,




rice and products thereof, 2000-2014,



-8

-6

-4

-2

0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0.0

0.1

0.2

0.3

0.4

0.5

0.6

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




soya and products thereof, 2000-2014,




palm and products thereof, 2000-2014,



0

4

8

12

16

20

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0

1

2

3

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




oilseed rape and products thereof, 2000-2014,




other oilseeds and products thereof, 2000-2014,



-1

0

1

2

3

4

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0

2

4

6

8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




coffee and cocoa and products thereof, 2000-2014,




tea and tobacco and products thereof, 2000-2014,



0

2

4

6

8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0.0

0.1

0.2

0.3

0.4

0.5

0.6

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




fruits and products thereof, 2000-2014,




vegetables and potatoes and products thereof, 2000-2014,



-0.8

-0.4

0.0

0.4

0.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

-2

-1

0

1

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




pulses and products thereof, 2000-2014,




sugar crops and products thereof, 2000-2014,



0.0

0.2

0.4

0.6

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

-1.0

-0.5

0.0

0.5

1.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




beef and products thereof, 2000-2014,




sheep and goat meat and products thereof, 2000-2014,



-1

0

1

2

3

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

0.0

0.5

1.0

1.5

2.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




pork and products thereof, 2000-2014,




poultry and products thereof, 2000-2014,



-3

-2

-1

0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

-1.0

-0.5

0.0

0.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014




eggs and products thereof, 2000-2014,




milk and products thereof, 2000-2014,



-1.0

-0.5

0.0

0.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

-1.0

-0.5

0.0

0.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

HFFA ResearchPaper 03/2015

Annex A22: Virtual agricultural land trade of the European Union, net imports (+), net exports (–), by region

and commodity and as an average of the years 2012-2014, (in million ha)

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North America 0.418 0.082 -0.384 0.005 2.228 0.062 0.076 0.214 0.082 0.033 -0.079 -0.315 0.161 0.169 0.112 0.000 -0.086 -0.004 0.002 -0.044 0.273 3.004

USA 0.180 0.029 -0.232 0.006 1.770 0.000 0.003 0.052 -0.338 0.030 -0.069 -0.181 0.057 0.012 0.116 0.000 -0.059 0.000 0.002 -0.012 0.222 1.589

Canada 0.346 0.058 -0.010 -0.001 0.461 0.000 0.076 0.138 -0.069 -0.003 -0.108 -0.076 0.094 0.000 0.004 0.001 -0.009 -0.001 0.000 -0.001 0.030 0.928

South America 0.055 0.313 -0.089 0.054 10.568 0.073 0.049 0.046 1.501 0.144 0.562 -0.203 0.043 0.098 1.222 0.036 0.002 0.330 0.000 -0.006 0.028 14.825

Brazil 0.052 0.237 -0.067 0.009 5.587 0.019 0.000 0.031 0.606 0.122 0.195 -0.171 0.000 0.065 0.700 0.000 0.000 0.302 0.000 -0.001 0.021 7.706

Argentina 0.000 0.053 0.025 0.005 3.674 0.000 0.046 0.000 -0.006 0.019 0.068 0.004 0.038 0.002 0.248 0.007 -0.001 0.010 0.000 0.000 0.006 4.198

Asia -1.146 -0.188 -0.475 0.478 0.474 1.955 -0.159 1.425 0.757 0.102 -0.149 -0.320 0.009 0.159 -0.180 -0.049 -1.557 0.036 -0.009 -0.210 -0.010 0.946

China -0.008 -0.016 -0.070 0.000 0.075 0.000 -0.084 0.046 0.018 0.057 -0.041 -0.021 0.010 0.000 -0.022 -0.001 -0.618 0.013 0.000 -0.059 -0.015 -0.737

India 0.000 -0.001 0.015 0.229 0.398 0.001 -0.062 0.450 0.161 0.070 0.010 -0.034 -0.003 0.136 0.000 0.000 0.000 0.000 0.000 -0.007 0.226 1.590

Japan -0.005 -0.059 -0.150 0.000 0.001 0.000 -0.002 -0.007 -0.056 -0.046 -0.085 -0.137 0.000 0.000 -0.001 0.000 -0.244 -0.004 -0.002 -0.009 -0.006 -0.812

MENA region -4.380 -0.300 -1.502 -0.002 -0.395 0.000 -0.156 -0.090 -0.247 -0.090 -0.008 0.904 -0.033 -0.029 -0.230 -0.095 -0.008 -0.190 -0.011 -0.243 -0.375 -7.481

Africa -1.524 -0.229 -0.378 -0.005 -0.323 0.100 -0.004 -0.030 4.314 0.300 0.082 -0.145 0.012 0.129 -0.175 -0.015 -0.155 -0.441 -0.013 -0.107 0.353 1.747

GUS 0.428 1.390 -0.148 0.000 0.640 -0.031 1.436 2.058 -0.381 -0.092 -0.440 -0.145 0.048 0.115 -0.302 -0.001 -0.444 -0.153 -0.016 -0.054 -0.008 3.901

Russia 0.153 0.147 -0.138 0.001 0.151 -0.030 0.430 0.300 -0.229 -0.061 -0.410 -0.103 0.030 0.055 -0.244 0.000 -0.292 -0.062 -0.014 -0.037 -0.001 -0.355

Developed Pacifics 0.059 -0.004 -0.045 -0.001 0.000 0.000 1.619 -0.005 -0.077 -0.002 0.162 -0.069 0.003 0.029 0.203 0.777 -0.069 0.000 0.000 0.006 0.000 2.587

Rest of Europe -0.219 0.075 -0.348 -0.035 -0.048 -0.012 -0.217 -0.285 -0.264 -0.044 -0.178 -0.075 -0.003 0.029 -0.355 -0.003 -0.115 -0.090 -0.020 -0.013 -0.020 -2.239

Switzerland -0.039 -0.015 -0.060 -0.008 -0.035 -0.003 -0.023 -0.029 0.013 0.004 -0.158 -0.042 -0.003 -0.005 -0.036 -0.006 0.015 -0.018 -0.017 0.012 -0.002 -0.454

Norway -0.067 -0.024 -0.101 -0.003 0.093 -0.001 -0.144 -0.026 -0.061 -0.005 -0.091 -0.013 -0.011 -0.013 -0.028 -0.005 -0.002 -0.001 0.000 0.000 -0.001 -0.504

Turkey -0.080 -0.030 -0.113 -0.014 -0.070 0.000 -0.042 -0.167 -0.086 -0.044 0.135 0.029 0.015 0.000 -0.089 -0.004 -0.001 -0.001 0.000 -0.001 -0.012 -0.576

Rest of the World -0.003 0.000 -0.003 0.000 0.000 0.194 0.000 0.022 0.040 0.000 -0.001 -0.002 0.000 0.000 -0.002 0.000 -0.003 -0.001 0.000 -0.001 0.000 0.240

Total -6.311 1.140 -3.372 0.494 13.142 2.341 2.644 3.355 5.725 0.352 -0.049 -0.370 0.241 0.699 0.293 0.651 -2.434 -0.513 -0.067 -0.672 0.241 17.530




Annex A23: Methodological remarks on the calculation of the agricultural

self-sufficiency of the EU

Basically, data on the production and/or the consumption of agricultural commodi-

ties, i.e. food, feed, fuel, and fibre products, allow for a calculation of the agricul-

tural self-sufficiency, but only if additional information on net foreign trade, i.e.

export and import flow balances, of crop and livestock specific commodities is

available. This is necessarily so, because – using a common definition of the Inter-

national Food Policy Research Institute (IFPRI) (see, e.g., Peljor and Minot, 2010) –

self-sufficiency is defined as being able to meet consumption needs from own pro-

duction rather than by (net) importing. Hence, agricultural self-sufficiency is de-

fined as a ratio.

For any agricultural commodity (respectively food, feed, fuel or fibre products

thereof) equation (1) applies:

(1) SSREU = PREU / (PREU – NTEU)

with: SSREU – self-sufficiency ratio of the EU,

PREU – domestic production of the EU, and

NTEU – net trade of the EU.

Within this rather simple accounting framework, the net trade is defined as the

difference of exports and imports. Accordingly, domestic consumption is equal to

domestic production minus net trade, and positive values for NTEU indicate a net

export situation, whereas negative values for NTEU indicate a net import situation.

According to equation (1), the self-sufficiency ratio is without any dimension (i.e.

without any unit); instead it can be measured in terms of percentages: A SSREU

value of 1.10, e.g., indicates a self-sufficiency ratio of 110 percent leading to the

conclusion that domestic production in the EU is 10 percent higher than domestic

consumption (and the net trade balance is positive, i.e. the EU exports more than it

imports). Consequently, a SSREU value of 0.80, e.g., indicates a self-sufficiency ratio

of 80 percent and points to the fact that domestic production is 20 percent lower

than domestic consumption (and the net trade balance is negative, i.e. the EU im-

ports more than it exports). Based on scientifically accepted conversion factors, it is

then possible to calculate a meaningful but aggregated agricultural self-sufficiency

indicator for the EU, respectively a set of such indicators.

Initial basis to do so is the definition of a ‘grain unit’ (see, e.g., Schulze-Mönking

and Klapp, 2010; TLL, 2013). The ‘grain unit’ (in the following: GU) is an indicator

for the aggregated nutritional value of a particular agricultural product. By (histor-



ic) definition (see Woermann, 1944), a GU is equivalent to the aggregated nutri-

tional value of 100 kg of barley. The initial values given by Woermann (1944) have

been updated on a regular base to meet genetic progresses, technological improve-

ments, etc. Nowadays all agricultural products and commodities thereof are com-

pared to 100 kg of barley using GU data mainly provided by Schulze-Mönking and

Klapp (2010) and TLL (2013). Accordingly, 100 kg of wheat, e.g., are set equal to

1.07 GU; 100 kg of soybeans are then defined as 2.60 GU; 100 kg of cow milk can

thus be valued at 0.86 GU (being the amount of feed to produce the respective

amount of milk); and 100 kg of beef (veal) are considered to be equal to 5.90 (4.10)

GU, etc.

Simply weighting EU production and EU net trade volumes of individual agricul-

tural products (see equation (1) above) with respective product-specific GU-values

allows for an aggregation and the discussion of an aggregated self-sufficiency ratio

(across all – crop and livestock – commodities) for the EU as a whole.

In addition, another indicator (set) shall be used to accentuate the discussion of the

EU’s agricultural self-sufficiency. Technical conversion factors recently provided by

FAO (2012) and specific nutritional values delivered with FAO (2015a) allow for

the calculation of aggregated self-sufficiency indicators not only in terms of the

aggregated nutritional value of the product, but also and even more detailed in

terms of specific nutritional components of it, i.e. the carbohydrates, proteins

and/or fats an agricultural commodity, be it a crop or livestock product, consists of.

Again, using proper algebraic weighting procedures with carbohydrate, protein and

fat concentrations as weighting factors allows for an aggregation of crop-specific

and livestock-specific production and trade volumes. Hence, the following set of

self-sufficiency indicators can be calculated and discussed on the basis of equation

(1):

SSREU, A non-aggregatable EU self-sufficiency ratio for commodity A,

SSRGUEU, A aggregatable EU ‘grain units’ self-sufficiency ratio for commodity A,

SSRCAEU, A aggregatable EU carbohydrates self-sufficiency ratio for commodity A,

SSRPREU, A aggregatable EU proteins self-sufficiency ratio for commodity A, and

SSRFAEU, A aggregatable EU fats self-sufficiency ratio for commodity A.

In order to do so, reliable statistical data and information on EU agricultural pro-

duction and trade are needed:



Agricultural production data in tons for almost all crop and livestock com-

modities are available from Eurostat (2015a). For the purpose of this study,

most recent data for the years 2012 to 2014 were obtained. In very few excep-

tional cases (due to missing information), data had to be gathered from FAO

(2015b) as well as from Schmid and Goldhofer (2015).

Most recent agricultural trade data – for the years 2012 to 2014, were taken

from Eurostat (2015b). However, trade data are not available on a crop and/or

livestock commodity basis. Instead, so-called Standard International Trade

Classification (SITC) categories have to be used. SITC categories are usually

set for primary agricultural commodities, but in addition also for products

thereof. A good example is wheat: Trade data, i.e. export and import volumes

in tons, are available for durum and other wheat, but also for wheat flour,

(wheat-based) pasta and feed preparations etc. All those SITC categories

have to be aggregated to allow for the calculation of an appropriate trade bal-

ance. The methodology to be applied is the same which was used to calculate

the virtual land trade of the EU and its change using SITC categories and

can be studied in detail in von Witzke and Noleppa (2010) or Noleppa et al.

(2013) or by looking at annex A01; therefore it shall not be repeated here once

again.

In total, the included commodities cover more than 90 percent of the volume of ag-

ricultural produce (measured in tonnage) domestically marketed in the EU respec-

tively traded internationally by the EU. This allows to draw an almost complete

picture of the EU’s agricultural self-sufficiency. The following commodities respec-

tively commodity groups are covered within the study (listed are, first, the primary

commodity for which production data are available and, second, the corresponding

SITC category for which corresponding export and import data could be obtained

for the years 2012 to 2014):

Wheat; SITC categories: 4108, 4110, 4120, 4608, 4610, 4620, 8126;

Rice; SITC categories: 4208, 4210, 4220, 4231, 4232, 8125;

Corn; SITC categories: 4408, 4410, 4490, 4711, 4719, 4721, 4811, 4813, 8124;

Other Cereals; SITC categories: 4300, 4308, 4508, 4510, 4520, 4530, 4591,

4592, 4593, 4599, 4708, 4722, 4723, 4729, 4808, 4812, 4814, 4815, 4820, 4830,

4841, 4842, 4849, 4850, 8111, 8129 11230;

Oilseed Rape; SITC categories: 8136, 22261, 42171, 42179;

Soya; SITC categories: 8131, 9841, 22220, 42111, 42119;

Sunflowers; SITC categories: 8135, 22240, 42151, 42159;

Other Oilseeds: 8138, 22320, 42221, 42229, 42241, 42249, 8132, 22211,

22212, 42131, 42139, 5771, 8137, 22310, 42231, 42239, 22250, 42180, 22350,



42250, 9843, 22262, 22270, 8134, 22340, 42211, 42219, 8133, 22230, 42121,

42129, 42161, 42169, 42121, 42122, 42129;

Potatoes; SITC categories: 5410, 5611, 5641, 5642, 5661, 5676;

Other Roots; SITC categories: 5481, 5645;

Sugar (Raw); SITC categories: 5487, 6112, 6121, 6129, 6159, 5488, 6111,

6151, 11102;

Peas; SITC categories: 5421, 5422;

Beans; SITC categories: 5423, 5425, 5429;

Other Pulses; SITC category: 5424;

Tomatoes; SITC categories: 5440, 5672, 5673, 5992, 9842;

Onions; SITC categories: 5451, 5612;

Carrots: SITC category: 5455;

Cucumbers; SITC category: 5456;

Garlic; SITC category: 5452;

Avocados; SITC category: 5797;

Apples; SITC categories: 5740, 5994;

Apricots; SITC categories: 5793, 5895;

Bananas; SITC category: 5730;

Berries; SITC categories: 5794, 5831, 5832, 5839, 5995;

Oranges; SITC categories: 5711, 5910;

Citrus Fruits; SITC categories: 5712, 5721, 5722, 5729, 5894, 5920, 5930;

Figs; SITC category: 5760;

Melons; SITC category: 5791;

Pears; SITC category: 5792;

Pineapples; SITC categories: 5795, 5893, 5991;

Grapes; SITC categories: 5751, 5752, 5993, 11211, 11213, 11215, 11217;

Beef; SITC categories: 0111, 0119, 1108, 1111, 1112, 1121, 1122, 1251, 1252,

1681, 1760;

Pork; SITC categories: 0131, 0139, 1221, 1222, 1253, 1254, 1611, 1612, 1750;

Sheep/Goat; SITC categories: 0121, 0122, 1211, 1212, 1213, 1255, 1256;

Poultry; SITC categories: 0141, 1231, 1232, 1233, 1234, 1235, 1740;

Eggs; SITC categories: 2508, 2510, 2521, 2522, 2530; and

Milk; SITC categories: 2211, 2212, 2213, 2221, 2222, 2223, 2224, 2231, 2232,

2233, 2241, 2300, 2308, 2408, 2410, 2420, 2430, 2491, 2499.



Annex A24: Specific self-sufficiency ratios of agricultural commodities

for the European Union in recent years and on average

(in percent)

Commodity 2011 2012 2013 Average

Cereals

Wheat 109 119 123 117

Corn 92 90 85 89

Other Cereals 112 116 114 114

Rice 66 65 60 64

Oilseeds

Oilseed Rape 84 86 90 87

Soya 3 4 3 3

Sunflowers 56 74 70 67

Other Oilseeds 89 88 88 88

Root Crops

Potatoes 107 106 107 107

Other Roots 96 95 94 95

Sugar Crops

Sugar (Raw) 83 79 84 82

Pulses

Peas 84 84 82 83

Beans 97 95 96 96

Vegetables

Tomatoes 104 106 104 105

Onions 109 109 111 109

Carrots 100 101 101 101

Cucumbers 101 102 101 101

Garlic 82 88 97 89

Fruits

Avocados 17 13 12 14

Apples 105 102 106 104

Apricots 312 223 351 288

Bananas 13 12 11 12

Berries 64 66 71 67

Oranges 59 52 48 53

Citrus Fruits 84 84 86 85

Figs 59 59 59 59

Melons 80 81 79 80

Pears 109 102 109 107

Grapes 98 97 98 98

Meat

Beef 103 102 103 102

Pork 114 114 114 114

Sheep/Goat 87 88 89 88

Poultry 106 107 108 107

Other Livestock

Eggs 102 103 103 102

Milk 107 107 108 107




Imprint

The agricultural trade of the European Union:

Consequences for virtual land trade and self-sufficiency

Steffen Noleppa, Matti Cartsburg

Berlin, November 2015

HFFA Research GmbH

Bülowstraße 66, 10783 Berlin, Germany

E-Mail: [email protected]

Web: www.hffa-research.com

the agricultural trade of the european union: consequences for virtual land trade and self-sufficien

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