Renewable resources gain in importance in our modern society. The line of reasoning is based on their positive effects on agriculture, the environment and the economy. To support renewable energy from biomass the EU promotes the cultivation of energy crops. A spatial equilibrium model is applied based on the concept of maximizing net welfare, to provide information whether energy crop production competes with food production for land area. The Model of Interregional Trade of Energy Crops (ITEC) refers to Eastern Germany and adjacent areas of Poland. First results show that the regions have enough feedstocks to meet the required demand for food and biofuel production. In many cases both food crops and biofuels are either traded on interregional basis or exported to "Rest of Europe" indicating that there is no competition between food and energy crops. Only green maize for biogas production strongly competes in areas where the crop is required as feed for cattle.Energy crops, spatial equilibrium analysis, interregional trade, International Relations/Trade,

Haring, Anna Maria

Khachatryan, Armen

Khachatryan, N.

Zeller, Heiko

English

Research Papers in Economics

  1 
Modelling Interregional Trade of Energy Crops in Eastern Germany 
Khachatryan N. 
1, Zeller H. 
2, Häring A.M. 
2 and Khachatryan A. 
1 
1 University of Hohenheim, Institute for Analysis, Planning and Organisation of Agricultural Production, Stuttgart, Germany 
2 University of Applied Sciences Eberswalde, Unit for Agricultural Policy and Markets, Eberswalde, Germany 
Abstract— Renewable resources gain in importance in 
our modern society. The line of reasoning is based on 
their positive effects on agriculture, the environment 
and the economy. To support renewable energy from 
biomass the EU promotes the cultivation of energy 
crops. A spatial equilibrium model is applied based on 
the concept of maximizing net welfare, to provide 
information whether energy crop production competes 
with food production for land area. 
The Model of Interregional Trade of Energy Crops 
(ITEC) refers to Eastern Germany and adjacent areas of 
Poland. First results show that the regions have enough 
feedstocks to meet the required demand for food and 
biofuel production. In many cases both food crops and 
biofuels are either traded on interregional basis or 
exported to "Rest of Europe" indicating that there is no 
competition between food and energy crops. Only green 
maize for biogas production strongly competes in areas 
where the crop is required as feed for cattle.  
Keywords— Energy crops, spatial equilibrium 
analysis, interregional trade 
I. INTRODUCTION  
Biomass energy has attracted increasing attention as 
energy source that can increase security of supply, 
reduce exhaust emissions and provide a new income 
source for farmers. Currently the dependency on 
energy imports in the EU is 50% and expected to rise 
over the next years if no action is taken. Furthermore, 
the EU has recognized the need to tackle the climate 
change issue to reduce greenhouse gas emissions. 
Energy crops are used to produce a broad spectrum of 
fuels including biodiesel, ethanol and power 
generation via biogas. To support renewable energy 
from biomass the EU promotes the cultivation of 
energy crops with area payments and reduced taxation 
of biofuels. 
Commodity markets are strongly influenced by 
crude oil prices. A rise in oil prices increases 
production cost in agriculture but also creates 
economic incentives for biofuel production, thus 
representing a stimulating source of demand for 
agricultural commodities with effects on prices for 
agricultural products. With gradual liberalization of 
agricultural trade, market oriented production 
structures become more important and determine the 
profitability of farm enterprises in terms of 
comparative advantages. 
Bioethanol, biodiesel and biogas can be produced 
from a wide range of crops. In Germany 
approximately 15% of UAA are used for energy crop 
production [1]. The most important energy feedstocks 
are rapeseed, wheat, rye and green maize. Increasing 
biofuel and biogas production require substantial 
amounts of feedstocks that can be hardly provided on 
a regional level. An example may illustrate the 
significant land requirements. In 2005 a large 
bioethanol processing plant with a production capacity 
of about 600,000 t of rye per year has been established 
in the federal state of Brandenburg. Assuming an 
average yield of 5 t per ha an acreage of 120,000 ha is 
needed.  
The objective of this research is to determine if 
policy support for bioenergy sources is still justified 
and if energy crop production competes with food 
production for land area.  
II. MODEL SPECIFICATION 
Spatial equilibrium analyses are generally 
concerned with the establishment of equilibrium prices 
between regions, quantities of commodities supplied 
and demanded at each region. The Interregional Trade 
Model (ITM) approach applied for this research is a 
standard spatial equilibrium model, based on the 
concept of maximizing net welfare, in order to identify 
regions with comparative advantages for the 
production of specific agricultural products. The 
formulation of an ITM can be explained by using a 
"back to back" diagram. Figure 1 shows supply and 
12
th Congress of the European Association of Agricultural Economists – EAAE 2008   2 
demand functions
1 of two regions trading a 
homogenous product.  
 
Figure 1 Equilibrium prices and trade illustrated by 
"back to back" diagram [2] 
Region 2 illustrates a potential deficit region, while 
Region 1 shows a potential surplus region. In the 
absence of trade prices and quantities are determined 
by the domestic supply and demand curve for each 
region. When trade flows between the two regions, 
traders in Region 2 recognizing the lower price in 
Region 1 would arbitrage the products from Region 1 
to Region 2. Under the new equilibrium condition 
prices in both regions are equal (pE). Production and 
consumption in Region 1 are qS1, qD1 and in Region 2, 
they are qS2, qD2. The trade between the two regions 
has an effect on net gain in welfare. Encouraged by the 
comparative advantage Region 1 will intensify and 
further specialize in the production causing a shift in 
the supply curve from S2 to S2'. This in turn will create 
new equilibrium conditions and generate further 
intensification and specialization effects. According to 
this concept, regional demands and supplies of the 
commodities can be represented by price dependent 
exponential functions with constant elasticities to 
deduce price and quantity conditions of spatial 
equilibrium. Hence, the interregional activity is 
formulated as non-linear programming problem. The 
analytical framework of the following welfare oriented 
non-linear programming model is described in detail 
by Takayama and Judge [3] and von Oppen and Scott 
[4]. 
                                                           
1 These are shown in linear forms for ease of illustration only. 
The general form of the net-welfare function (the 
objective function to be maximized) for a commodity 
or group of commodities is determined by the sum of 
the line integrals of the regional demand functions 
Dj(yj) and the negative line integral of the regional 
supply functions Si(xi) over the appropriate quantity 
domains and the negative sum of the unit transport 
costs Tij multiplied by the transported quantities of the 
commodity  Xij [3]. The subscripts i and j indicate 
supply and demand regions respectively. The net 
welfare function NW is generally stated as follows: 
 
∫∫ − − =
y x
ij ij i i i j j j X T dx x S dy y D X x y NW
00
) ( ) ( ) , , (  (1) 
 
Processing costs are treated in the same way as 
transportation costs and are determined exogenously. 
In forming the quasi net welfare function, the 
exogenous costs incurred in making spatial allocations 
from region i to j are subtracted from the total quasi 
welfare function (W). Thus the quasi net-welfare 
function can be expressed as:  
 
∑ − ≡ ij ijX T W NW      (2) 
 
where T is a matrix of exogenous costs associated with 
the spatial allocation of each unit of X from i to j.  
The model of Interregional Trade of Energy Crops 
(ITEC) refers to Eastern Germany with the Federal 
States of Brandenburg, Mecklenburg-Western 
Pomerania, Saxony, Saxony-Anhalt and Thuringia and 
adjacent areas of Poland including the Voivodships 
Western Pomerania, Lubusz, Greater Poland, Lower 
Silesia, Pomerania and Opole. As an additional trading 
region a hypothetical residual "Rest of Europe" is 
implied. 
For each region the crops; wheat, rye, rapeseed and 
green maize are taken into account which can be used 
either as food (incl. foreage) or as energy crop. Area 
payments for energy crops are not taken into account. 
On the basis of given processing costs and 
transformation rates the model considers the analysis 
of the following bioenergy sources:  
 
•  production of biogas from green maize 
•  production of bio-diesel from rapeseed 
S 2 D 2
p 2
S 1
D 1
p 1
P
Q
Regi on 1 Regi on 2
p E
q S1 q D1 q D2 q S2
S 2`
Q
I n ten s if ica tio n
Pr oduct  A
We l f a r e  gai ns
Sp ecia liz atio n
12
th Congress of the European Association of Agricultural Economists – EAAE 2008   3 
•  production of bio-ethanol from rye and 
wheat 
 
Selected data of input data from Eastern Germany is 
presented in Table 1.  
Table 1 Crop activities, yields and market prices in the base 
run [5] 
  Rye  Rape-
seed 
Wheat  Green 
Maize 
Brandenburg       
Area [`000 ha]  164  147  151  105 
Yield [t]  4.0  3.3  5.4  23.7 
Supply Price [€/t]  125  212  125,0  25 
Mecklenburg-W. 
Pomerania 
      
Area [`000 ha]  50  243  328  88 
Yield [t]  4.5  3.8  7.3  30.7 
Supply Price [€/t]  127  245  126  25 
Saxony        
Area [`000 ha]  28  130  179  34 
Yield [t]  4.7  3.5  6.1  34.7 
Supply Price [€/t]  127  244  123  25 
Saxony-Anhalt      
Area [`000 ha]  63  159  331  63 
Yield [t]  4.7  3.8  6.9  28.7 
Supply Price [€/t]  127  244  122  25 
Thuringia        
Area [`000 ha]  9  114  218  38 
Yield [t]  6.2  3.7  6.7  40.0 
Supply Price [€/t]  127  243  120  25 
 
The data on biogas and biofuels are obtained from 
specialized reports [6]. Consumption quantities have 
been estimated on the basis of total national 
consumption and projected at regional level [7;8]. 
Consumer prices, reflecting actual market prices are 
compiled from market reports [5]. The supply and 
demand elasticities have been consulted with experts 
and verified by technical literature [9]. No regional 
differences in elasticities were allowed for as these 
were not available. Processing costs are generated 
from different sources [1;10]. To account for transfer 
costs a transportation cost matrix between regions, 
taking distance and cost into consideration was 
formulated. The transportation costs were generated 
based on current fright data from a german transport 
company [11]. The reference year is 2006. 
The formulated non-linear programming model was 
solved using GAMS/MINOS.  
III. RESULTS OF ESTIMATION 
First results for Eastern Germany show that green 
maize and rapeseed are predominantly used for 
bioenergy purposes. Table 2 illustrates that over 80% 
of green maize is used as biogas substratum and in the 
case of rapeseed around 70% of the crop is converted 
to biofuels. Sole exception are Saxony and Saxony-
Anhalt were more than 50% of the produce is used as 
food crop. To satisfy the demand of biodiesel Saxony 
imports 63,000  t of biodiesel from Thuringia and 
Saxony-Anhalt. Another large amount of 199,000 t of 
the produce is exported from Mecklenburg-Western 
Pomerania to "Rest of Europe" indicating a 
comparative advantage for biodiesel (Table 3). Until 
now biogas is used on a regional basis and is not 
traded. The same applies for green maize due to the 
high transportation costs of the bulky produce over 
long distances. The equilibrium prices from green 
maize and rapeseed differ from the reference prices 
and rise around 11% up to 14% which are the basis for 
further calculations. Area increases for both crops 
average out at 4%.  
In the western voivodships of Poland the food-
energy crop-ratio for green maize is higher and ranges 
between 20% and 50%. The increase in area amounts 
to 10%. Rapeseed is used as food crop. In some areas 
(Lubusz, Opole) the utilization as food crop amounts 
to 90%. 
Table 2 Food-Energy Crop-Ratio for different crops in 
Eastern Germany 
  Rape-
seed 
Rye Wheat Green 
Maize 
Brandenburg [%]  31.4 54.6  100.0  17.9 
Mecklenburg- W. 
Pomerania [%] 
19.4 66.1  70.8  1.2 
Saxony [%]  58.3  75.8  100.0  7.0 
Saxony-Anhalt [%]  55.1  56.2  98.1  4.6 
Thuringia [%]  26.3  75.8  98.4  2.6 
Source: computed from model 
 
The regions do not trade with Eastern Germany but 
with "Rest of Europe". 
Biofuels are produced from rye and wheat 
respectively. The model suggests an increase in wheat 
production of about 5% up to 7% for Eastern 
Germany. Generally the use of wheat to produce 
bioethanol is of minor importance except 
12
th Congress of the European Association of Agricultural Economists – EAAE 2008   4 
Mecklenburg-Western Pomerania where almost 30% 
of the wheat production is used for bioethanol 
production. The excess supply of both the crop and 
ethanol is mainly exported to "Rest of Europe". This 
indicates that there is no competition between energy 
and food crop. Rye is the preferred crop for bioethanol 
production since it has a better conversion ratio and is 
produced at lower cost than wheat. The model 
suggests an area increase of about 10%. In 
Brandenburg almost 46% of rye is used for bioethanol 
production. Ethanol from rye is exported in large part 
from Brandenburg to "Rest of Europe" (Table 3). 
Lower quantities are traded from Brandenburg to 
Saxonia and From Saxony-Anhalt to Thuringia. The 
equilibrium prices do not significantly differ from the 
reference prices which show the competitiveness of 
the regional markets for these crops.  
Table 3 Exported biofuel quantities from Eastern Germany 
to "Rest of Europe"  
Biofuel Federal  State  Exported quantity to "Rest 
of Europe" 
Brandenburg  
Mecklenburg- W. 
Pomerania 
199,501 
Saxony  
Saxony-Anhalt  
B
i
o
d
i
e
s
e
l
 
Thuringia  
Brandenburg 89,829 
Mecklenburg- W. 
Pomerania 
19,381 
Saxony  
Saxony-Anhalt 30,815 
E
t
h
a
n
o
l
 
R
y
e
 
Thuringia  
Brandenburg  
Mecklenburg- W. 
Pomerania 
224,466 
Saxony  
Saxony-Anhalt  
E
t
h
a
n
o
l
 
W
h
e
a
t
 
Thuringia 46,925 
Source: computed from model 
 
In Poland the results for rye as energy crop are 
inconsistent. For example, in Western-Pomerania and 
Greater Poland 75% of rye is used for bioethanol 
production, while the crop is only used as food crop in 
Lower-Silesia and Opole. The crop is not traded as 
food crop but exported as bioethanol to "Rest of 
Europe". 
IV.  CONCLUSIONS 
Concerning the present issue "food versus energy" a 
spatial equilibrium model is developed to assess the 
potential impacts of energy crop on food production. 
The results of the model clearly indicate that most 
regions have enough feedstocks to meet the required 
demand for food and biofuel production. Typical food 
crops like wheat and rye are predominantly used as 
food crops. In many cases both food crops and 
biofuels are either traded on interregional basis or 
exported to "Rest of Europe" which indicates that 
there is no competition between food and energy 
crops. Moreover the export quantities of biodiesel and 
bioethanol imply the competitive advantage of 
producing energy crops and processing it into biofuels. 
Sole exception is green maize which is mainly used as 
biogas substratum and strongly competes in areas, 
where maize is required as feed for cattle.  
The possibility to utilize crops as energy source has 
lead to a bioenergy boom where market prices are in 
constant flux. In order to test whether policy support is 
still justified, the energy crop premium was not 
considered in the model. The results show that there is 
no need to promote energy crops. Further promotion 
of energy crops would even distort market oriented 
production structures. 
The regarded crops in the model require on average 
65% of UAA, which means that there is still growth 
potential. However, the numbers approach a limit in 
terms of crop rotational aspects and the share of 
grassland.  
Further steps are planned to extent the model. These 
imply the inclusion of short rotation coppices, 
"Biomass to Liquid" fuels (BtL) and the expansion to 
other regions. 
REFERENCES  
 
1.  Agency for Renewable Resources (2007) Daten und 
Fakten zu nachwachsenden Rohstoffen. FNR, Gülzow 
2.  Khachatryan N (2002) Assessing the Potential of 
Brandy Produced in Armenia. Margraf, Weikersheim 
3.  Takayama T, Judge G G, (1971) Spatial and temporal 
price and allocation models. North Holland Publishing 
Company, Amsterdam. 
12
th Congress of the European Association of Agricultural Economists – EAAE 2008   5 
10. Association for Technology and Structures in 
Agriculture (2006) Energiepflanzen. Daten für die 
Planung des Energiepflanzenanbaus. KTBL, Darmstadt 
4.  von Oppen M, Scott T (1976) A spatial equilibrium 
model for plant location and interregional trade. 
American Journal of Agricultural Economics J 58:437-
445  11. Raiffeisen Waren-Zentrale Rhein-Main eG (RWZ) at 
http://www.rwz.de 
Corresponding Author 
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Marktbilanz Getreide Ölsaaten Futtermittel 2007. ZMP, 
Bonn 
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Report. TunbridgeWells/GB (2006-2007)  •  Dr. Heiko Zeller 
7.  EUROSTAT at http://epp.eurostat.ec.europa.eu  •  University of Applied Sciences Eberswalde, Unit for 
Agricultural Policy and Markets  8.  FAO at http://faostat.fao.org/ 
9.  Gardinger W, Roninger V, Liu K (1989) Elasticities in 
the Trade Liberalisation Database. ERS/USDA, 
Washington, D.C. 
•  Friedrich-Ebert-Str. 28 
•  16225 Eberswalde 
•  Germany 
•  hzeller@fh-eberswalde.de 
 
 
 
12
th Congress of the European Association of Agricultural Economists – EAAE 2008 

(various issues) World Ethanol and Biofuels Report. TunbridgeWells/GB (2006-2007) • Dr. Heiko Zeller

A spatial equilibrium model for plant location and interregional trade.

Agency for Renewable Resources

Assessing the Potential of Brandy Produced in Armenia.

Association for Technology and Structures in Agriculture

Elasticities in the Trade Liberalisation Database.

EUROSTAT at http://epp.eurostat.ec.europa.eu • University of Applied Sciences Eberswalde, Unit for Agricultural Policy and Markets 8. FAO at http://faostat.fao.org/

Spatial and temporal price and allocation models.

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Modelling Interregional Trade of Energy Crops in Eastern Germany

Modelling Interregional Trade of Energy Crops in Eastern Germany

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