functions for each biofuel crop35. Area is a function of input prices, direct payments, output prices for all other crops and the special energy crop premium. In the ROW and the US, the supply of each biofuel crop is modelled by isoelastic supply functions that do not distinguish between a yield and an area component.
35 The model recognises two isoelastic areas: non-set-aside area and set-aside area. However, now that obligatory set-aside has been abolished, the distinction is no longer operative in the baseline. The area for biofuel crops produced on set-aside area was a function of input prices, direct payments, and output prices only for those crops used for biofuel production, which could alternatively have been grown on non-set-aside area
Oilseeds are not direct inputs into the biofuel production activity, but are first crushed and yield plant oils and meal.
Processing demand (PDEM) for each oilseed is defined as
Explanatory variables are wholesale prices (PD) for processing outputs (meal, oil), contained in the subset “ospro”, and the processing input (the respective oilseed). The intercept (cr_int) as well as the elasticities of processing demand with respect to input and output prices (elast_ cr) are exogenous parameters, the former being calibrated according to base-year data. The parameter (pdem_tr) is a time trend to represent
the evolution of the oilseed processing capacity. Equation (1) is restricted to be homogeneous of degree zero in all input and output prices36.
The supply (SUPPLY) of processed oilseed products (meal, oil) is defined as processing demand multiplied by the respective extraction factor, called in the model a technical parameter for oilseed processing (oilsd_c):
36 Price elasticities with respect to inputs other than oilseeds are taken into account in imposing the homogeneity condition.
(1)
(2)
The oilseed extraction coefficients are 0.82 for soybean, 0.68 for rapeseed and 0.76 for sunflower seed. The calculation of crushing parameters for oilseeds to oil and meal is based on FAO data.
Palm oil is produced in the ROW only and the supply of palm oil is modelled without consideration of by-products such as palm kernel oil, palm kernel meal, tree stem and skin. The supply of palm oil is a direct function of its
own domestic price and the prices of competing outputs, and of technical progress.
4.1.3. Production of biofuels and biofuel by- products
The production of each biofuel is modelled as an isoelastic function of its own price, and the weighted net prices of the respective inputs:
JRC Reference Reports
61
Im
pa
ct
s
of
th
e
EU
B
io
fu
el
T
ar
ge
t o
n
A
gr
ic
ul
tu
ra
l M
ar
ke
ts
a
nd
L
an
d
U
se
: A
C
om
pa
ra
tiv
e
M
od
el
lin
g
A
ss
es
sm
en
where (sup_int) is an intercept, (PI) is the respective biofuel price, (BCI) the price index of inputs in biofuel production and (pdem_tr) a trend for the production of biofuels.
ESIM distinguishes four by-products: gluten feed (in the case of wheat and maize) and meals from three different oilseed crops. The production of gluten feed is defined as the sum of the different cereals used in biofuel processing each multiplied by its respective technical extraction factor. The extraction factor describes how much by-product results from the processing of the feedstock to the corresponding biofuel. The gluten feed extraction
coefficients are 0.230 and 0.285 for processing ethanol from maize and soft wheat respectively. The conversion coefficients for rapeseed, soy bean and sunflower seed to the corresponding oil seed meal are 0.68, 0.81 and 0.77.
The net price of a feedstock crop is defined as its market price minus the price of the related feed by-product derived from its processing into biofuel, multiplied by its technical extraction factor. The unscaled input shares (i.e. shares of feedstocks) in biofuel production are determined by a CES function based on net energy crop prices:
(4)
where (biof_CES_int) is an intercept in input shares in biofuel production, (biof_CES_shr) is a share parameter of biomass inputs in biofuel production, (NetPD) are net prices for inputs in biofuel production, (biof_CES_el) are the CES elasticities of substitution among inputs.
(biof_CES_el) and (biof_CES_shr) are calibrated parameters of the CES function.
In addition, equation (5) scales the unscaled quantities such that they add up, after technical conversion, to the total quantity of biofuel production:
(5)
where (PDEM_BF) is the demand of inputs in biofuel production and (convbfcc) is the relevant conversion factor. The full set of these coefficients is given in Table 4.1.
4.1.4. Human demand for biofuels
Human demand for each biofuel is a function of the respective biofuel price, the
price of crude oil, and the tax rates on biofuels and on mineral oil.
4.2. Implementation of biofuel policies
The main biofuel policy assumptions include:
JRC Reference Reports
62
4. R
es
ul
ts f
ro
m t
he E
SI
M m
od
el
1. The price of crude oil in USD per barrel and the related annual increase;
2. The tax reduction on biofuel relative to tax on mineral oil in percentage;
3. The special biofuel crop premium, which is modelled as a subsidy for the production of biofuels, assuming that it accrues largely to biofuel producers, as it results in lower prices of biofuel inputs (this premium is discontinued after 2009).
In addition, EU targets with respect to the share of biofuels in total transport fuels as set out in the Renewable Energy Directive of December 2008 are met. This is achieved in the baseline simulation with the use of shift variables (‘shifters’). The shifters enter as multiplicative factors attached to the trend parameters in the human demand functions, and in the oilseed crushing and biofuel production activities
4.3. Data needs
In the EU project AGRI -2006-G4-01, data for production of oil and meal were separated into production of energy oilseed and oilseed for food production based on plausibility assumptions. FAO data on production of rape meal and rape oil include both meal and oil production from energy and food rapeseed. This is also the case for sunflower seed.
Price information is generally obtained from EUROSTAT. For energy crops, producer and market prices are the same regardless of whether the output is used for food or feed purposes, or as a fuel feedstock. Prices of palm oil and ethanol are obtained from the FAPRI Outlook database. Quantity data for first generation biofuels are based on data published in F.O. Licht’s Interactive Data and World Ethanol and Biofuels Report. Extraction coefficients for the processing of cereals and sugar are taken from KTBL (2006).
4.4. Baseline construction
4.4.1. Baseline assumptionsThis section explains the assumptions regarding agricultural and trade policies, and the macroeconomic environment, that have been incorporated into the baseline. These working hypotheses were defined on the basis of exchanges with DG AGRI according to what was considered to be most plausible at the time the analysis was conducted.
(1) A continuation of the Common Agricultural Policy (including Health Check decisions adopted by the Agricultural Council in November 2008) until 2015, including notably: (a) Phasing out milk quotas: Milk quotas are
increased by 1% per quota year between 2009/10 and 2013/14. For Italy, the 5%
Table .4.1: Conversion factors in ESIM
Conversion of 1 ton of input into 1 ton of output Oilseed to oil Oilseed to meal Oil to biodiesel
Oilseeds
Rapeseed 0.32* 0.68* 1.00
Soy bean 0.18* 0.81* 1.00
Sunflower seed 0.24* 0.77* 1.00
Grain to gluten feed Grain to ethanol
Cereal/sugar Soft wheat 0.29 0.29
Maize 0.23 0.30
Sugar 0.39
JRC Reference Reports
63
Im
pa
ct
s
of
th
e
EU
B
io
fu
el
T
ar
ge
t o
n
A
gr
ic
ul
tu
ra
l M
ar
ke
ts
a
nd
L
an
d
U
se
: A
C
om
pa
ra
tiv
e
M
od
el
lin
g
A
ss
es
sm
en
increase is introduced immediately in 2009/10. Milk quotas are abolished by April 2015.
(b) Intervention mechanisms: Intervention is set at zero for barley and sorghum. For wheat, butter and skimmed milk powder intervention purchases are possible at guaranteed buying- in prices up to 3 million t, 30 thousand t and 109 thousand t respectively. Beyond these limits, intervention is possible by tender. (c) Decoupling: The coupled payments retained
by some Member States after the 2003 CAP reform are assumed to be decoupled and moved into the Single Payment Scheme (SPS) by 2010 for arable crops, durum wheat, olive oil and hops, and by 2012 for processing aids and the remaining products. Member States are assumed to keep current levels of coupled support for suckler cows, goats and sheep.
(d) The Member States currently applying the
single area payment scheme (SAPS) are
assumed to adopt the regionalised system from 2014 onwards.
(e) Set-aside: The requirement for arable farmers to leave 10% of their land fallow does not apply within the simulation period.
(f) The energy crop premium is abolished following the 2009 Health Check reform. (h) Modulation (shifting money from Pillar I
to Pillar 2): direct payments exceeding an annual €5,000 are progressively reduced each year, starting with 7% in 2009 and reaching 10% in 2012. An additional cut of 4% is made on direct payments above €300,000 a year. ‘Effective’ country-specific modulation rates are introduced in the model taking into account the franchise level.
(2) All commitments made in the Uruguay
Round Agreement on Agriculture regarding
market access and subsidised exports are assumed to be fully respected. No assumptions are made about a possible conclusion to the Doha Development Round.
(3) Assumptions regarding the macro- economic environment consider the following variables. The country-specific average annual rate of change of real GDP between base and 2020 is equal for the EU to 1.37%. The country- specific average annual rate of change of Consumer Price Index between base and 2020 is equal for the EU to 1.73%. EU population projections have been revised on the basis of the latest population statistics and the Eurostat projection EUROPOP2008. On average, for EU27 as a whole, population growth is expected to slow down gradually from 0.4% p.a. in the period 2009-2014 to 0.3% p.a. in the period from 2015-2020. The average price of crude oil is assumed to be 76 USD per barrel in the base year, and increases thereafter to about 80 USD per barrel in 2020
.
4.4.2. Simulating the baseline
Once the agricultural and trade policies, and the macro-economic environment assumptions, have been incorporated into the model, the
biofuels shifters for the EU are adjusted. The
shifters to be adjusted are: human demand shifters for biodiesel and ethanol, shifters of biodiesel and ethanol processing capacities and shifters of oilseed crushing capacity. The biofuel shifters are adjusted in order to meet the biofuel target percentage over total fuel consumption used for transport as set by Renewable Energy Directive of December 2008. The projections used for total fuel consumption are from PRIMES 2007. Biofuel shifters are adjusted in order to meet a 7% target from first generation biofuel by 2020. Adjusting the with-policy baseline so as to reach fixed quantity targets is quite labour- intensive, as it involves considerable fine tuning of the shift parameters.
JRC Reference Reports