The agricultural trade of the European Union: Consequences for virtual land trade and self-sufficien

HFFA Research GmbH

Steffen Noleppa and Matti Cartsburg

The agricultural trade of the European Union

hffa RESEARCH

HFFA Research Paper 03/2015

Consequences for virtual land trade and self-sufficiency

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

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Acknowledgement This research has been made possible, in part, by financial support from the European 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.

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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

Figure 9:

Aggregated agricultural self-sufficiency of the European Union in terms of carbohydrates, 2012-2014 and on average (in percent) ............................................................................................. 14

Figure 10:

Aggregated agricultural self-sufficiency of the European Union in terms of proteins, 2012-2014 and on average (in percent) ............................................................................................ 15

Figure 11:

Aggregated agricultural self-sufficiency of the European Union in terms of fats, 2012-2014 and on average (in percent) ............................................................................................ 15

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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

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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 contributed to this discussion by looking at agricultural trade issues from another point of view. A new perspective was particularly opened by introducing the concept of virtual agricultural land trade (von Witzke and Noleppa, 2010), an approach, 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 methodology 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 selfsufficiency are lacking to build respective arguments upon verifiable information, as, for instance, in Häusling (2011) who argues that the EU suffers from an important 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 information 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.

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2 Trends of the EU’s virtual agricultural land trade The following discussion is based on results obtained from applying the methodology outline in annex A01 of this report. Accordingly trends of the EU’s virtual agricultural land trade are analysed for every single year since the turn of the millennium, 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 development 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)

35 30 25 20 15 10 5 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 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 lower 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

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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 agricultural 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 figure 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) agricultural 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 follows: 

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 considerably enlarged own wheat production and, hence, exports to maintain global food security and to profit from comparably high international commodity 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 apparent: 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

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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)

Crops 40

30

20

10

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Livestock 2

0

-2

-4 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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

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 Argentina, Brazil and the USA have increased soya yields between 10 and 20 percent 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 increase in palm oil imports for bioenergy generation (and so called Hydrotreated 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 conditions 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.

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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 virtual agricultural land for livestock products ever since 2009. In the year 2014, virtual 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 virtual 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 improve 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 imports 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 status 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 million 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

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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, especially 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 Source: Own figure based on own calculations.

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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

Source: Own figure based on own calculations.

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 million 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.

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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 selfsufficiency 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 selfsufficiency 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 respectively 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 particularly 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 commodities 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 figure 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 average 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.

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Figure 5:

Self-sufficiency ratio of the European Union for some major agricultural commodities, on average for 2012-2014 (in percent)

120

120

100

100

80

80

60

60

40

40

20

20

0

0 Wheat

Corn

120

120

100

100

80

80

60

60

40

40

20

20

0

Oilseed Rape

Soya

Beans

Peas

Tomatoes

Cucumbers

Eggs

Milk

0 Sugar (Raw)

Potatoes

120

120

100

115

80

110

60

105

40

100

20

95

0

90 Apples

Bananas

120

120

115

115

110

110

105

105

100

100

95

95

90

90 Beef

Pork

Source: Own figure based on own calculations.

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Figure 6:

11

Aggregated agricultural self-sufficiency of the European Union in terms of grain units, 2012-2014 and on average (in percent)

90

89

88

87 2012

2013

2014

Average Source: Own figure based on own calculations.

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 selfsufficiency 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.

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Figure 7:

Self-sufficiency of the European Union in wheat and sunflowers, 2012-2014 (in percent)

150 120 90 60 30 0 2012

2013 Wheat

2014

Sunflowers

Source: Own figure based on own calculations.

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 influencing feed availability and overall livestock performance certainly play a minor role.

Figure 8, now, depicts average self-sufficiency ratios for specific nutritional ingredients, 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, proteins and fats borne by livestock products, and not self-sufficient when these components have to come from crops and products thereof.

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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

106

107

106

Sugar Crops

82

82

82

Pulses

89

90

85

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

92

85

87

Roots

Vegetables

Total

13

Source: Own figure based on own calculations.

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 selfsufficiency in terms of proteins. Although more animal protein is available from domestic production than actually needed (plus 8 percent), the total protein 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 debate.



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.

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Based on figure 8 and the following three figures 9 to 11 depicting the EU’s selfsufficiency 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 biggest 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 components – 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)

93

92

91

90 2012

Source: Own figure based on own calculations.

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2013 Average

2014

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Figure 10: Aggregated agricultural self-sufficiency of the European Union in terms of proteins, 2012-2014 and on average (in percent) 87

86

85

84

83 2012

2013 Average

2014

Source: Own figure based on own calculations.

Figure 11: Aggregated agricultural self-sufficiency of the European Union in terms of fats, 2012-2014 and on average (in percent) 88

87

86

85 2012

2013 Average

2014

Source: Own figure based on own calculations.

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Concluding remarks

This research paper highlights that the EU is currently net importing a still remarkable 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 decreased since the year 2007. That the EU is using today fewer agricultural resources abroad than in past years can also be seen by looking at most recent agricultural self-sufficiency indicators. Although still below 100 percent – thus indicating an overall higher import than export of crop and livestock commodities and products thereof – agricultural self-sufficiency has slightly improved over time being 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 productivityoriented 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 smalland medium-scale enterprises and also large input suppliers towards investing into research and development for, e.g., new and better crop protection products, improved plant varieties and/or novel nutritional options may increase due to associated 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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Reference list Allan, J.A. (1993): Fortunately there are substitutes for water otherwise our hydropolitical futures would be impossible. In: Priorities for Water Resources Allocation and Management 1993, p. 13-26.

Allan, J.A. (1994): Overall perspectives on countries and regions. In: Rogers, P.; Lydon, P. (eds.): Water in the Arab world: Perspectives and prognoses, p. 65100. Cambridge, MA: Harvard University Press.

Bouet, A.; Laborde, D. (2008): The lure of attaining food security for Europe through self-sufficiency. Washington, DC: IFPRI. de Schutter, O. (2011): Mandate of the Special Rapporteur on the Right to Food: The Common Agricultural Policy towards 2020: The role of the European Union in supporting the realization of the right to food. New York: United Nations.

Destatis (2013a): Ernährungsproduktion zunehmend auf Flächen im Ausland. In: Agra-Europe 54, 02.September 2013, p. Dok1-Dok20.

Destatis (2013b): Flächenbelegung von Ernährungsgütern 2010. Wiesbaden. Destatis.

Eurostat (2015a): Statistics by theme: Agriculture: Agricultural production: Crops products: Area and productions. Luxembourg: Eurostat.

Eurostat (2015b): Statistics by theme: International trade: International trade detailed data: EU trade since 1988 by SITC. Luxembourg: Eurostat.

FAO (Food and Agriculture Organization) (2015a): FAOSTAT: Food balance: Food supply. Rome: FAO. FAO (Food and Agriculture Organization) (2015b): FAOSTAT: Production: Crops.

Rome: FAO. FAO (Food and Agriculture Organization) (2012): Technical conversion factors for agricultural commodities. Rome: FAO. Häusling, M. (2011): Motion for a European Parliament resolution on the EU protein deficit: what solution for a long-standing problem? Brussels: European Parliament.

Hoekstra, A.Y. (2003): Virtual water: An introduction. In: Hoekstra, A.Y. (ed.): Virtual water trade: Proceedings of the international expert meeting on virtual water trade. Value of water research report series (11), p. 25-47. Delft: IHE.

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Hoekstra, A.Y.; Hung, P.Q. (2002): Virtual water trade: A quantification of virtual water flows between nations in relation to international crop trade. Delft: IHE Delft.

Kern, M.; Noleppa, S.; Schwarz, G. (2012): Impacts of chemical crop protection applications on related CO2 emissions and CO2 assimilation of crops. In: Pest Management Science 68, p.1458-1466.

Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. (2015): Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany. In: Agricultural Systems 136, p. 79-84.

Louwagie, G. (2013): Introducing virtual land use in land-related resource efficiency. Paper presented at the Global Soil Week 2013: Balancing trade-offs: How to assess ‘virtual land imports’, Berlin, Germany, 29 October 2013.

Meier, T.; Christen, O.; Semler, E.; Jahreis, G.; Voget-Kleschin, L.; Schrode, A.; Artmann, M. (2014): Balancing virtual land imports by a shift in the diet. Using a land balance approach to assess the sustainability of food consumption.

Germany as an example. In: Appetite 75, p. 20-34.

Mekonnen, M.; Hoekstra, A. (2011). National water footprint accounts: the green, blue and grey water footprint of production and consumption. Volume 1: Main Report. Delft: IHE Delft.

Noleppa, S.; Cartsburg, M. (2014): Another look at agricultural trade of the European Union: Virtual land trade and self-sufficiency. HFFA Research Paper 01/2014. Berlin: HFFA Research GmbH. Noleppa, S.; Cartsburg, M. (2013): Agricultural self-sufficiency of the European Union: Statistical evidence. agripol research paper 2013-02. Berlin: agripol GbR. Noleppa, S.; von Witzke, H.; Cartsburg, M. (2013): The social, economic and environmental value of agricultural productivity in the European Union: Impacts on markets and food security, rural income and employment, resource use, climate protection, and biodiversity. HFFA Working Paper 03/2013. Berlin: HFFA. Peljor, N.; Minot, N. (2010): Food security and food self-sufficiency in Bhutan.

Summary report of the ‘Agricultural and Food Policy Research and Capacity Strengthening Project’. Washington, DC: IFPRI.

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Qiang, W.; Liu, A.; Cheng, S.; Kastner, T.; Xie, G. (2013): Agricultural trade and virtual land use: The case of China’s crop trade. In: Land Use Policy 33, p.

141-150.

Schmid, W.; Goldhofer, H. (2015): Getreide. In: LEL; LfL (eds.): Agrarmärkte: Jahresheft 2015, p. 33-55. Schwäbisch Gmünd: LEL. Schulze-Mönking, S.; Klapp, C. (2010): Überarbeitung des Getreide- und Vieheinheitenschlüssels. Endbericht zum Forschungsprojekt 06HS030. Göttingen: Georg-August-Universität.

TLL (Thüringer Landesanstalt für Landwirtschaft) (2013): Getreideeinheitenschlüssel. Jena: TLL. UNEP (United Nations Environment Progamme) (2015): International trade in resources: a biophysical assessment. Report of the International Resource Panel. Nairobi: UNEP. van den Bergh, J.C.J.M.; Grazi, F. (2013): Ecological footprint policy? Land use as an environmental indicator. In: Journal of Industrial Ecology 18, p. 10-19. von Witzke, H.; Noleppa, S.; Zhirkova, I. (2011). Fleisch frisst Land. Ernährung, Fleischkonsum, Flächenverbrauch. Studie im Auftrag des WWF. Berlin: WWF Germany. von Witzke, H.; Noleppa, S. (2010): EU agricultural production and trade: Can more efficiency prevent increasing ‘land grabbing’ outside of Europe? Piacenza: OPERA Research Centre of Università Cattolica del Sacro Cuore.

Woermann, E. (1944): Ernährungswirtschaftliche Leistungsmaßstäbe. In: Mitteilungen für die Landwirtschaft 59, p. 787-792.

WWF (World Wide Fund for Nature) Germany (2015): Das große Fressen. Berlin: WWF Germany.

WWF (World Wide Fund for Nature) Germany (2012): Tonnen für die Tonne. Berlin: WWF Germany.

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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

Annex A03:

Virtual agricultural land trade of the European Union for corn and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................ 25

Annex A04:

Virtual agricultural land trade of the European Union for coarse grains and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) .................................. 26

Annex A05:

Virtual agricultural land trade of the European Union for rice and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................ 26

Annex A06:

Virtual agricultural land trade of the European Union for soya and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................ 27

Annex A07:

Virtual agricultural land trade of the European Union for palm and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha)................................................................... 27

Annex A08:

Virtual agricultural land trade of the European Union for oilseed rape and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) .................................. 28

Annex A09:

Virtual agricultural land trade of the European Union for other oilseeds and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) .................................. 28

Annex A10:

Virtual agricultural land trade of the European Union for coffee and cocoa and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) .................................. 29

Annex A11:

Virtual agricultural land trade of the European Union for tea and tobacco and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) .................................. 29

Annex A12:

Virtual agricultural land trade of the European Union for fruits and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha)................................................................... 30

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Annex A13:

Virtual agricultural land trade of the European Union for vegetables and potatoes and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ..................................30

Annex A14:

Virtual agricultural land trade of the European Union for pulses and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................31

Annex A15:

Virtual agricultural land trade of the European Union for sugar crops and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................31

Annex A16:

Virtual agricultural land trade of the European Union for beef and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................32

Annex A17:

Virtual agricultural land trade of the European Union for sheep and goat meat and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ..................................32

Annex A18:

Virtual agricultural land trade of the European Union for pork and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................33

Annex A19:

Virtual agricultural land trade of the European Union for poultry and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................33

Annex A20:

Virtual agricultural land trade of the European Union for eggs and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................34

Annex A21:

Virtual agricultural land trade of the European Union for milk and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) ............................................................34

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

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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 production 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 internationally 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 different 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 products 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.

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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 agricultural 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 analysis. This includes (see also annexes A02 to A21): 

Wheat, corn, coarse grains, rice, soya, palm, oilseed rape, other oilseeds, coffee 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.

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Annex A02: Virtual agricultural land trade of the European Union for wheat and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0

-2

-4

-6

-8

-10 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A03: Virtual agricultural land trade of the European Union for corn and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 4

2

0

-2 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A04: Virtual agricultural land trade of the European Union for coarse grains and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0

-2

-4

-6

-8 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A05: Virtual agricultural land trade of the European Union for rice and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.6 0.5 0.4 0.3 0.2 0.1 0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A06: Virtual agricultural land trade of the European Union for soya and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 20

16

12

8

4

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A07: Virtual agricultural land trade of the European Union for palm and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 3

2

1

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A08: Virtual agricultural land trade of the European Union for oilseed rape and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 4

3

2

1

0

-1 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A09: Virtual agricultural land trade of the European Union for other oilseeds and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 8

6

4

2

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A10: Virtual agricultural land trade of the European Union for coffee and cocoa and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 8

6

4

2

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A11: Virtual agricultural land trade of the European Union for tea and tobacco and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.6 0.5 0.4 0.3 0.2 0.1 0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A12: Virtual agricultural land trade of the European Union for fruits and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 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 Source: Own figure based on own calculations.

Annex A13: Virtual agricultural land trade of the European Union for vegetables and potatoes and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 1

0

-1

-2 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A14: Virtual agricultural land trade of the European Union for pulses and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.6

0.4

0.2

0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A15: Virtual agricultural land trade of the European Union for sugar crops and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 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 Source: Own figure based on own calculations.

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Annex A16: Virtual agricultural land trade of the European Union for beef and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 3

2

1

0

-1 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A17: Virtual agricultural land trade of the European Union for sheep and goat meat and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 2.0

1.5

1.0

0.5

0.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A18: Virtual agricultural land trade of the European Union for pork and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0

-1

-2

-3 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A19: Virtual agricultural land trade of the European Union for poultry and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.5

0.0

-0.5

-1.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

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Annex A20: Virtual agricultural land trade of the European Union for eggs and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.5

0.0

-0.5

-1.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

Annex A21: Virtual agricultural land trade of the European Union for milk and products thereof, 2000-2014, net imports (+), net exports (–), (in million ha) 0.5

0.0

-0.5

-1.0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Source: Own figure based on own calculations.

HFFA Research Paper 03/2015

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

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)

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

North 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

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

Russia

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

Source: Own figure based on own calculations.

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

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 commodities, i.e. food, feed, fuel, and fibre products, allow for a calculation of the agricultural 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 International 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 production rather than by (net) importing. Hence, agricultural self-sufficiency is defined 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 imports 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-

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ic) definition (see Woermann, 1944), a GU is equivalent to the aggregated nutritional 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 improvements, etc. Nowadays all agricultural products and commodities thereof are compared 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 agricultural 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 production and trade are needed:

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



Agricultural production data in tons for almost all crop and livestock commodities 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 exceptional 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 balance. 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 agricultural produce (measured in tonnage) domestically marketed in the EU respectively traded internationally by the EU. This allows to draw an almost complete picture of the EU’s agricultural self-sufficiency. The following commodities respectively 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,

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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.

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

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

109 92 112 66

119 90 116 65

123 85 114 60

117 89 114 64

84 3 56 89

86 4 74 88

90 3 70 88

87 3 67 88

107 96

106 95

107 94

107 95

83

79

84

82

84 97

84 95

82 96

83 96

104 109 100 101 82

106 109 101 102 88

104 111 101 101 97

105 109 101 101 89

17 105 312 13 64 59 84 59 80 109 98

13 102 223 12 66 52 84 59 81 102 97

12 106 351 11 71 48 86 59 79 109 98

14 104 288 12 67 53 85 59 80 107 98

103 114 87 106

102 114 88 107

103 114 89 108

102 114 88 107

102 107

103 107

103 108

102 107

Cereals Wheat Corn Other Cereals Rice Oilseeds Oilseed Rape Soya Sunflowers Other Oilseeds Root Crops Potatoes Other Roots Sugar Crops Sugar (Raw) Pulses Peas Beans Vegetables Tomatoes Onions Carrots Cucumbers Garlic Fruits Avocados Apples Apricots Bananas Berries Oranges Citrus Fruits Figs Melons Pears Grapes Meat Beef Pork Sheep/Goat Poultry Other Livestock Eggs Milk

Source: Own figure based on own calculations.

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

HFFA Research Paper 03/2015

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 BĂźlowstraĂ&#x;e 66, 10783 Berlin, Germany E-Mail: steffen.noleppa@hffa-research.com Web: www.hffa-research.com

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