COMMISSION STAFF WORKING DOCUMENT Energy Economic Develoments in Europe Accompanying the documentCOMMUNICATION FROM THE COMMISSION TO THE EUROPEANPARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONSEnergy prices and costs in Europe
Date: 2014-01-22
Institutions: European Commission
Subjects: distribution cost, electrical energy, electricity supply, natural gas, price net of tax, price of energy, production cost, tax, trans-European network













EUR-Lex - 52014SC0019R(01) - EN











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52014SC0019R(01)

COMMISSION STAFF WORKING DOCUMENT Energy Economic Develoments in Europe Accompanying the documentCOMMUNICATION FROM THE COMMISSION TO THE EUROPEANPARLIAMENT, THE COUNCIL, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONSEnergy prices and costs in Europe /* SWD/2014/0019 final/2*/









European Commission
Directorate-General
for Economic and Financial Affairs
Energy
Economic Developments in Europe
EUROPEAN ECONOMY                                                                                                        2014
COUNTRIES
AT          Austria
BE          Belgium 
BG          Bulgaria 
CY          Cyprus 
CZ          Czech Republic
CIS         Commonwealth of Independent
States
CN          China
DE          Germany 
DK          Denmark 
EE           Estonia 
EL           Greece 
ES           Spain 
FI            Finland 
FR           France 
HU          Hungary
IE            Ireland 
IT            Italy
JP            Japan
LT           Lithuania
LU          Luxembourg
LV          Latvia
MT         Malta
NL          Netherlands
NO          Norway
PL           Poland
PT           Portugal
RO          Romania
RU          Russia
SE           Sweden
SI            Slovenia
SK          Slovakia
TR          Turkey
UA          Ukraine
UK          United Kingdom
US           United States
UNITS
Btu                         British
Thermal Unit
GJ                           Giga joule
GWh                       Gigawatt hour
Ktoe                       Kilo ton of
oil equivalent
kva                         Kilovolt-ampere
kWh                       Kilowatt hour
MJ                          Megajoules
Mtoe                      Million
tonnes of oil equivalent
MWh                      Megawatt-hour
PPS                         purchasing
Power Standard
TCF                        Trillion
Cubic feet
TCO2                     Tons of carbon
dioxide emissions
TJ                            Terajoule
TWh                       Terawatt-hour
OTHERS
ARA                       Antwerp/Rotterdam/Amsterdam
ARDL                    Autoregressive
distributed lag
BEA                       Bureau of
Economic Analysis
BBL                       Oil barrel
CER                       Certified
emissions reductions
DSO                        Distribution
system operator
EC                          Energy Cost
ECM                      Error
correction model
EEX                        European
Energy Exchange
EIA                         Energy
Information Administration 
ENTSO                  European network
of transmission system operator
ERGEG                  European
Regulators' Group for Gas and Electricity
ERU                       Emissions
reductions units
ETS                        Emissions
trading scheme
EU                          European
Union
EUA                       European
Union allowances
EUR                       Euro
FiT                          Feed-in
tariff
GDI                        Gross
Domestic Income
GDP                        Gross
Domestic product
GO                          Gross
Output
GVA                       Gross Value
Added
GHG                       Greenhouse
gas
HHI                        Herfindahl-Hirschman
index
HICP                      Harmonized
index of consumer prices
HS                          Harmonized
System
IEA                         International
Energy Agency
ISO                         Independent
system operator
ITO                         Independent
transmission operator
LM                         Langrage
multiplier
LRMC                   Long run
marginal cost
MS                          Member
State
NAP                        National
allocation plan
NBP                        National
balancing point
NGO                       Non-Governmental
organisation
NUEC                    Nominal Unit
Energy Cost
OECD                    Organization
for Economic Cooperation and Development
OU                          Ownership
unbundling
PV                           Photovoltaic
RCA                       Revealed
comparative advantage
RES                        Renewable
energy sources
RTB                       Relative
trade balance
RUEC                    Real Unit
Energy Cost
TSO                        Transmission
system operator
TTF                        Title
transfer facility
TYNDP                  Ten year network
development plans
USD                        US Dollar
VAT                       Value added
tax
WIOD                    World
Input-Output Database
WFD                       Water
Framework Directive
This report was prepared in the Directorate-General for Economic and
Financial Affairs under the direction of Marco Buti, Director-General, Servaas
Deroose, Deputy Director-General, and Anne Bucher, Director of the Directorate
for Structural Reforms and Competitiveness.
The production of the report was
coordinated by Emmanuelle Maincent (Head of Unit - Economic Analysis of Energy,
Transport, Climate Change and Cohesion Policy).
The main contributors were Ricardo Amaro,
Paul Arnoldus, Fotios Kalantzis, Emmanuelle Maincent, Jerzy Pienkowski, Andras
Rezessy, Mirco Tomasi, and Arthika Sripathy.
Ricardo Amaro, Vittorio Gargaro, Andras
Rezessy, Arthika Sripathy and Mirco Tomasi provided statistical support.
Editorial assistance was provided by Vittorio Gargaro.
The report has benefited from useful
comments and suggestions received from colleagues in the Directorate-General
for Economic and Financial Affairs, Directorate-General for Agriculture and
Rural Development, Directorate-General for Climate Action, Directorate-General
for Energy, Directorate-General for Enterprise and Industry, Directorate-General
for Environment, Joint Research Center, Directorate-General for Employment,
Social Affairs and inclusion, the members of the Economic and Policy Committee
Working Group on Climate Change and Energy, the members of the Economic and
Policy Committee and as well as the Agency for the Cooperation of Energy
Regulator.
The Council of European Energy Regulator
and the Agency for the Cooperation of Energy Regulator are thanked for granting
us access to their database.
Comments on the report would be gratefully
received and should be sent to:
Directorate-General for Economic and
Financial Affairs            
Unit B4: Economic Analysis of Energy, Transport, Climate Change and Cohesion
Policies               
European Commission       
BE-1049 Brussels
or by e-mail to ECFIN-SECRETARIAT-B4@ec.europa.eu.
Executive
Summary  1
Part I:        Energy Costs and Competitiveness  5
Overview   7
1.    Unit Energy costs in Europe and the world  8
1.1.     Introduction  8
1.2.     Assessing Unit Energy costs 8
1.3.     Unit Energy Costs: an International Comparison  12
1.4.     Unit Energy costs: A sectoral comparison  17
1.5.     EU Member States assessment 22
1.6.     Conclusions 27
2.    The recent development of US shale gas and its
impact on EU competitiveness 29
2.1.     Introduction  29
2.2.     The impacts of the surge in US shale gas on the
US energy sector and EU and US energy mix  29
2.3.     Electricity and Gas prices: a US-EU comparison  33
2.4.     Energy Intensity : a US-EU comparison  36
2.5.     Trade  38
2.6.     Conclusions 40
References 42
A.1. Data and Methodology  44
A.2. Real unit energy cost in the world  46
A.3. Real Unit Energy Costs & Shift-share excluding
refining sector 47
A.4. Additional energy data on EU and US  49
Part II:       Energy and carbon prices: assessing the
impact of energy and climate policies  51
Overview   53
1.    The impact of energy policies on electricity and
natural gas prices: an empirical assessment 54
1.1.     Introduction  54
1.2.     Energy price developments in the EU   54
1.3.     The policy determinants of energy prices at EU
level 60
1.4.     Assessing the impact of energy and climate
policies on electricity and natural gas prices 66
1.5.     Conclusions 70
2.    Assessing the drivers of carbon prices: an
empirical estimate  72
2.1.     Introduction  72
2.2.     Stylised facts: evolution of carbon price  72
2.3.     Climate and Energy policy developments 74
2.4.     Assessing the drivers of carbon prices 77
2.5.     Conclusions 81
References 82
A.1. Electricity and Natural Gas Price Model and
Variables Description  85
A.2. Carbon Price model and variables description  87
Part III:      Renewables: Energy and Equipment Trade
Developments in the EU   89
Overview   91
1.    Renewables development in the EU and the world  92
1.1.     Introduction  92
1.2.     Evolution of renewable Electricity in EU-27 and
its main economic partners 92
1.3.     Support Schemes and renewables development 95
1.4.     Conclusions 100
2.    Renewables competitiveness development: the case of
wind and solar equipments 102
2.1.     Introduction  102
2.2.     Renewable components and equipment trade
flows  102
2.3.     International competitiveness of EU solar and
wind energy industries 109
2.4.     Conclusions 111
3.    Energy trade balance and Avoided fuel costs 112
3.1.     Introduction  112
3.2.     Total energy trade balance  112
3.3.     Avoided costs of imported fuel 113
3.4.     Conclusions 117
References 119
A.1. Data description for the model measuring the drivers
of trade in solar power and wind equipment 121
A.2. Data description for assessing avoided imported fuel
costs 122
Statistical annex  123
LIST OF Tables
I.1.1.        Average % annual change 1995-2009 -
Manufacturing  16
I.1.2.        Sectoral breakdown: decomposition of RUEC
and annual growth rates 1995-2009  19
I.1.3.        Sectoral breakdown: decomposition of RUEC
and annual growth rates 1995-2009  20
I.1.4.        Average % annual change 2000-2009 -
Manufacturing  27
II.1.1.       Results of Electricity price model 68
II.1.2.       Results of Natural gas price model 70
II.2.1.       Descriptive statistics of EUA, fuels and
electricity price changes (%), 2008-2012  74
II.2.2.       Results of the carbon model 80
III.1.1.      Renewable electricity support instruments
in member States 96
LIST OF Graphs
I.1.1.        Real Unit Energy Costs as % of value added,
manufacturing sector 12
I.1.2.        Real Unit Energy Costs as % of gross
output, manufacturing sector 13
I.1.3.        Real Energy Price levels - Manufacturing  13
I.1.4.        Energy Intensity levels - Manufacturing  13
I.1.5.        Average annual change 1995-2009 -
Manufacturing  14
I.1.6.        Shift share analysis of manufacturing
sector RUEC growth  15
I.1.7.        Decomposition of Real Unit Energy Costs -
Manufacturing  24
I.1.8.        Annual Growth Rates 2000-2009 -
Manufacturing  25
I.2.1.        Natural gas production in the US and share
of shale gas on total gas production  30
I.2.2.        Energy mix US  30
I.2.3.        Energy mix, EU   30
I.2.4.        Energy Import Dependency  33
I.2.5.        Wholesale natural gas prices in Germany,
Japan, UK and US compared with crude oil price  34
I.2.6.        Indices of real gas prices for end-users 35
I.2.7.        End-user gas prices for industry  35
I.2.8.        End-user electricity prices for industry  35
I.2.9.        Indices of real electricity prices for
end-users (2005=100) 35
I.2.10.      Energy intensity of industry  36
I.2.11.      Share of some Energy Intensive Sectors (EIS)
and share of Manufacturing in GDP - 2001-2012  37
I.2.12.      Energy intensity of industry, selected
sectors 38
I.2.13.      Energy trade balances as % of GDP, total and
per energy source - 2001-2011, EU-27 and US  39
I.2.14.      Current account balance, external balance
for goods and bilateral balance for goods, 2001-201 - US and EU-27  40
I.A3.1.     Real Unit Costs manufacturing sector
including vs. excluding coke, refined petrol & nuclear fuels 47
I.A3.2.     Shift-share analysis for the manufacturing
sector including vs. excluding coke, refined petrol & nuclear fuels 48
I.A4.1.     US Energy domestic production by source,
2000-2011  49
I.A4.2.     EU-27 Energy domestic production by source,
2000-2011  49
I.A4.3.     Electricity mix US, 2002-2011  49
I.A4.4.     Electricity mix EU-27, 2001-2010  49
I.A4.5.     Household expenditures for energy products,
2003-2010 - EU-27 and US  49
I.A4.6.     Electricity prices for industrial consumers
and households for the European countries in the OECD and for the US  50
I.A4.7.     Energy consumption of industry breakdown by
sources - US  50
I.A4.8.     Energy consumption of industry breakdown by
sources, EU   50
II.1.1.       EU-27 Average domestic and industrial
retail electricity price, wholesale price and crude oil price evolution
2004-2011  55
II.1.2.       EU average change per electricity tariff
component between 2008 and 2011  55
II.1.3.       Retail and wholesale electricity average
price changes by Member State 2004-2011  56
II.1.4.       Retail electricity prices - Households and
Industry  57
II.1.5.       Average ratio of Industrial to Household
electricity prices, relative to the EU-27 average, 2004-2011  58
II.1.6.       EU-27 average domestic and industrial
retail natural gas price and crude oil price evolution 2004-2011  58
II.1.7.       Retail natural gas price evolution by
Member State 2004-2011  58
II.1.8.       Retail natural gas prices - Households and
Industry  59
II.1.9.       Average ratio of Industrial to Household
natural gas prices, relative to the EU-27 average, 2004-2011  60
II.2.1.       Evolution of EUA Futures prices 73
II.2.2.       Evolution of carbon price, fuels and
electricity prices over 2008-2012  73
II.2.3.       Decomposition of Carbon Price Changes over
2008-2012  80
III.1.1.      Share of Solar PV, Wind, Hydropower and
other renewable sources in EU-27 gross electricity generation  92
III.1.2.      Share of renewable sources in gross
electricity generation by Member State in 2003, 2007 and 2011  93
III.1.3.      Share of solar PV, wind, hydropower and
other renewable sources in gross renewable electricity generation in 2011  93
III.1.4.      Share of EU-27, US, China, Japan and Brazil
in world net renewable electricity generation  94
III.1.5.      Share of Eu-27, US, China, Japan and Brazil
in world net electricity generation - solar PV (a) - Wind (b) 95
III.1.6.      EU Member States with the highest support
to renewable energy sources, 2010  96
III.1.7.      Share of rewewable sources (excluding
hydropower) in gross electricity generation and RES electricity support in EU
Member States -2010  100
III.2.1.      EU-27 exports and imports of solar
components from Extra-EU   102
III.2.2.      EU-27 exports and imports of wind
components from Extra-EU   103
III.2.3.      EU Member States intra and extra-EU imports
(M) and exports (X) of solar components and equipment in 2012  108
III.2.4.      EU Member States intra and extra-EU imports
(M) and exports (X) of wind components and equipment in 2012  108
III.2.5.      Average share of EU-27, US, China and Japan
in world's total, renewable, solar and wind patents from 2000 to 2011  109
III.2.6.      Average share of EU Member States in EU-27
total, renewable, solar and wind patents from 2000 to 2011  109
III.2.7.      Average Revealed Comparative Advantage
Indexes of solar and wind industries in the EU-27 Member States from 2007 to
2011  110
III.2.8.      Average Revealed Comparative Advantage
Indexes of solar and wind industries in the EU-27, USA, China and Japan from
2007 to 2011  110
III.2.9.      Average relative trade balance Index of the
solar industry in the EU-27, USA, China and Japan  110
III.2.10.    Average relative trade balance Index of the
wind industry in the EU-27, USA, China and Japan  111
III.2.11.    Relative Trade Balance Indexes of solar and
wind industries in the EU-27 Member States from 2007 to 2011  111
III.3.1.      EU-27 trade deficit in energy products and
crude oil prices, 2000-2012  112
III.3.2.      Member States trade balance in energy
products as % of GDP, 2012  113
III.3.3.      Avoided imported fuel costs thanks to
renewable electricity - 2010  115
III.3.4.      Avoided imported fuel costs thanks to
renewable electricity by Member States - 2010  116
III.3.5.      Renewable electricity generation and
avoided imported fuel costs - 2010  116
III.3.6.      Avoided total fuel costs and imported costs
thanks to renewable energy, 2010  117
III.3.7.      Avoided fuel costs thanks to renewable use
in heating and transport by Member States, 2010  117
LIST OF Boxes
I.1.1.        Real Unit Energy Cost (RUEC), Nominal Unit
Energy cost (NUEC), Energy Prices and Energy Intensity  10
I.2.1.        Potentials and Uncertainties for Shale Gas
Exploration in the EU and in the US  31
II.1.1.       Third Energy Package  62
II.1.2.       Literature Review   66
II.1.3.       Methodology and Data   67
II.2.1.       Literature on the interaction between
energy and climate polocies 76
II.2.2.       Methodology and Data   78
III.1.1.      Renewable Energy Policies in the main EU
economic partners 94
III.1.2.      Electricity tariff deficit in some Member
States 97
III.1.3.      Renewable and Employment 99
III.2.1.      Components in wind and solar industry  103
III.2.2.      Measuring the drivers of trade in solar
power and wind equipment 104
III.3.1.      Assessing avoided imported fuel costs 114
 Since 2008, the EU has made a huge leap forward in promoting the transition to a low carbon economy 
In recent years, the EU has set an ambitious
agenda to foster the transition to low carbon economies. The Climate and Energy
Package adopted in late 2008 sets an EU-wide 20% greenhouse gas emission
reduction target for the 27 Member States by 2020, 20 % share of energy from
renewable sources in EU gross energy consumption by 2020 and a 20% decrease in
primary energy use by 2020. At the core of this strategy is an objective of
achieving greenhouse gas emissions reduction while improving security of supply
and promoting the emergence of new green sectors. The recent crisis has not put
a brake on this level of ambition as these 20/20/20 targets are part of a broad
coordinated exercise of economic and fiscal policies in the context of the
European Semester.
 Energy costs matter… 
Recently, the cost of energy has emerged as an
important dimension of international competitiveness of European industries, in
particular in light of the "shale gas revolution" taking place in the
US. Energy matters for the competitiveness of our economies as it affects the
production costs of industries and services and the purchasing power of households.
Energy costs are not only driven by the type of fuel mix used and consumed, but
they have been influenced by our energy policy choices as well as by
technological evolutions that can contribute to reducing our energy needs. This
report provides analysis and evidence for the economic impact of energy
developments in the EU and Member States over the past years. It could
contribute to discussions about economic aspects of energy and climate policies
and how they can best contribute to fostering the transition to low carbon
economies. 
 …but the EU manufacturing has been successful in reducing its energy intensity 
The comparison of energy costs in Europe and
Member States and in the rest of the world helps assess our economies in terms
of energy cost competitiveness. Chapter I.1 develops unit energy cost
indicators that bring together the energy price and the energy intensity
dimensions. One salient feature is that the dynamics of energy costs has been
positive in the EU, but also in the rest of the world. Another salient
characteristic is that, in a global  context, the EU manufacturing sector
exhibits a low level of energy costs relative to both output and value added.
This positive outcome is mostly explained by the low energy intensity of the
sector. The EU manufacturing sector has so far responded to energy price
increases through sustained energy intensity improvements, thus maintaining its
relatively favourable position. Although not visible over the longer period
(1995-2009), the latest period analysed (2005-2009) shows that these
improvements have been driven partly by restructuring towards sectors with
lower energy costs as energy intensive industries have been more affected by
energy cost increase pressure. In addition, Member States with high share of
energy intensive industries are most exposed to unfavourable unit energy costs
developments.  
 High energy prices should remain a concern, taking account of the increasing  EU-US energy price gap. 
Against this background, one cannot ignore the
recent spectacular development of the production of shale gas and oil in the US
which has started in 2009-2010 and is often seen as a major competitiveness
threat in the near future. Chapter I.2 provides a focus on more recent
developments in the US and EU. While the surge in US shale gas has led to
marked changes in the US energy sector and a reduction in the US energy trade
balance in GDP terms, the impact on the EU is limited at the moment as no major
shift in the EU-US goods trade balance nor significant divergent trends in the
overall production structure of manufacturing industry are observed and can be
ascribed to the shale gas revolution. However, this should not imply
complacency on the widening EU-US energy price gap as the full impacts may
become visible only after some delay. Moreover, energy efficiency improvements
may slow down in the EU and speed up in US due to diminishing low cost options,
and increased policy effort. Consequently, high energy prices for EU industries
should remain a policy concern, even more so in case the EU-US energy price gap
will continue to increase. 
It is therefore strategic for the EU to see
whether and how energy prices have been affected by policy developments. This
report analyses three important components of energy cost – electricity and
natural gas retail prices, and carbon prices. EU electricity and gas markets
have been fundamentally reshaped by the significant energy and climate policy
initiatives over recent years, in the areas of market opening, renewables penetration,
climate change mitigation, and security of supply. The report explores the
impact of these policy reforms on end-user electricity and gas prices as after
all, these are what industries and households are ultimately paying. The report
also looks at carbon prices as it is expected to provide the price signal to
change our consumption behaviour and reduce our carbon footprint. 
 Market opening in electricity and natural gas has brought significant downward price effects. Renewable support has contributed to increasing electricity prices… 
Analysis shows that while fossil fuels still
remain key drivers of electricity and natural gas price formation, market
opening and competition appear to have significant downward price effects for
both household and industrial consumers. In both markets, empirical estimates
confirm that EU energy policies, such as unbundling of networks and market
opening lower retail prices. In addition to these positive developments,
natural gas and electricity prices are also affected by specific factors. In
the natural gas market, security of supply plays an important role. High import
dependency and low diversification of imports can significantly contribute to
increasing end-user prices for industries and households. Hence Member States
which rely on one foreign source are likely to be exposed to higher prices. In
the electricity market, support to less mature renewables technologies has
translated in higher electricity prices for both industry and households
segments. Furthermore, in some Member States, the burden has not been evenly
shared across consumer segments, i.e. industries and households.
 … while renewable production, among other factors have negatively affected carbon prices.  
By contrast, the carbon price is not found to have
any statistical significant impact on electricity retail prices. The latest
data on carbon price evolution show that its level is far lower than what was
expected when the Energy and Climate Package was adopted in 2008. As it is,
although the carbon price is seen as one of the key pieces for the transition
to low carbon economies, it fails to provide a strong price signal for
consumption behaviour and for investments in clean production technologies. The
empirical estimate carried out in chapter II.2 analyses the main drivers of
carbon prices and shows that economic factors have played a major role in
driving carbon prices in phase 2. Without any doubt, the recent economic crisis
has contributed to lowering the demand of allowances, contributing to a large
part to the ETS market imbalance, hence the decrease in the carbon price.
However, the European carbon market is not isolated from other shaping factors
such as the fuel switching behaviour of the conventional power producers and
the renewable penetration among other drivers. There is evidence that the
deployment of renewable production has also contributed to a lesser extent to
this ETS market imbalance, therefore lowering the carbon price. Such results
show the importance of economic factors in driving carbon prices, but highlight
the interplay between energy and climate policies and ultimately the trade-offs
policy makers are confronted to when designing climate change and energy
policies combining market instruments and support mechanisms.
 Compared to the rest of the world, the EU has been successful in developing wind and solar energy 
Finally, the Energy and Climate agenda
provides a comprehensive regulatory and policy framework that favours the
emergence of new green sectors. This means that energy markets in the context
of well-designed policies, can offer many opportunities for growth and
jobs ([1]). The report
scrutinises the development of new technologies and energy sources - solar and
wind - and their impact on trade flows as a way to assess one dimension of
competitiveness. Chapter III.1 provides an overview of what happened in the EU
and other parts of the world. In Europe, the support to renewable sectors
stepped up from 2007 and has represented a strong opportunity to accelerate the
expansion of less mature technologies such as wind and solar. Compared to the
rest of the world, the EU has been one of the frontrunner in developing wind
and solar energy although other countries have been catching up since. 
 The EU has developed strong positions in the wind equipment sector… 
The expansion of renewables provided
opportunities in terms of industrial equipment and trade flows. Chapter III.2
gives a closer look at trade developments in the EU and Member States in the
wind and solar sector. Evidence shows that the EU displays strong comparative
advantages in the wind industry, but has not managed to develop such position
in the solar industry. When analysing the drivers of trade of wind and solar
equipment, one interesting result is the role of knowledge in driving trade
flows, with the EU export performance being strong in technologies where the EU
has a strong portfolio of patents. This suggests that innovation and R&D
policies should be seen as key policies in promoting the emergence of new green
sectors. 
 … but the fuel costs avoided by renewable developments are still too low. 
Another expected benefit of developing
renewable is the impact on the energy trade bill and its contribution to
reducing our energy dependence. The EU dependence on fossil fuels is higher
than in the US, and the EU27 trade deficit in energy products amounted to 3.2%
of GDP in 2012. Chapter III.3 shows that renewables help reduce import fuel
costs and contribute to improving the energy trade balance, but only to a
limited extent. Nonetheless, the avoided fuel costs are expected to rise in the
coming years, due to increasing production of renewable energy in the EU and
projected increase in EU fossil import prices.
This part analyses energy cost
competitiveness. The cost of energy has emerged as an important dimension of
international competitiveness of European industries, in particular in light of
the "shale gas revolution" taking place in the US. Energy matters for
the competitiveness of our economies as it affects the production costs of
industries and services and the purchasing power of households.
Chapter 1 introduces the concept of Unit
Energy Costs (UEC). Similarly to Unit Labour Costs, the UEC indicator measures
the energy cost per one unit of value added, in a given sector or in an
aggregation thereof. This indicator enables to compare the relative importance
of energy inputs – or in other words the sensitivity to energy price shocks -
of a given sector over time. The UEC indicator brings together two key
components of energy competitiveness: the value of energy inputs and energy
intensity. 
Chapter 2 analyses the impacts of the
development of shale gas, always through the same integrated approach, i.e.
observing the parallel evolution of energy intensity and energy prices in the
EU and in the US. It discusses how the introduction of shale gas has affected
the US and EU energy sectors, the development in the EU-US energy price-gap and
in the trade balances for the EU and US in terms of energy trade, of current
accounts and trade of goods.
1.1.      Introduction
Energy is a key input in many production
processes. For this reason, its costs represent a competitiveness factor for
manufacturing industry, with the intensity of use next to the energy price as
the major drivers. However, another equally important factor is the intensity
of its use. In order to provide a more comprehensive assessment  of the role
that energy plays in determining industrial competitiveness, these factors
shall be looked at in combination, the same as it is done for other inputs such
as capital and labour.
The objective of this chapter is to assess
energy cost competitiveness using unit energy cost indicators. Section 1.2
describes the concept and methodology used to build these indicators. Section
1.3 provides an international comparison of unit energy costs in Europe and
other parts of the world. Section 1.4 focuses on sectoral developments while
section 1.5 assesses Member States unit energy costs development. Conclusions
are presented in section 1.6. 
1.2.      Assessing
Unit Energy costs
1.2.1.   Introductory remarks on the
role of energy in the production process
Energy is a key aspect of competiveness. This follows from the energy's essential role in the production
process of goods and services. Hence, an economic analysis of energy cost
competiveness cannot limit itself to energy prices but needs to consider
indicators which inform on how energy prices and energy use affect production
decisions. Energy costs, energy productivity and energy intensity are such
indicators which can be analysed. 
The role of energy in production can be
empirically analysed by using analytical frameworks firmly based on economic
theory. Often, the production function is employed
in such analysis, as it expresses in a mathematical form how the output of the
production process is related to the production inputs. Two basic assessment
methods rely on the production function concept, namely growth accounting and
econometric studies on the production function. Decomposition based on the
input-output method has a close relation to both methods. 
As regards the first method, growth accounting
is an empirical method which allows the identification of the sources of growth
of output. Under the conventional assumptions of
constant returns to scale and production input prices equal to their marginal
productivity, it is possible to derive from a further unspecified production
function that output growth is a weighted average of the growth of the
production inputs with the cost shares of the various inputs as weights plus a
remainder term called "multi-factor productivity" generally
associated with technical progress. However, growth accounting as a method
cannot be used to analyse the causes of changes in energy costs, intensity and
productivity.
Growth accounting is more complicated at
industry level than at macroeconomic level since intermediate deliveries
between industries and also within a given industry serve both as input and
output, rendering it more difficult to link the industry "multi-factor
productivity" terms to economy-wide measures of productivity (Hulten
2009). For a growth accounting analysis at macro level, production output can
be expressed in value added ([2]) since the costs of intermediate inputs cancel out against the
gross income of delivering these inputs in the derivation of GDP (which thus
equals GDI). At industry level, however, the intermediate deliveries do not
cancel out, so one can argue in favour of gross production rather than value
added as the appropriate output variable. For instance, O'Mahony and Timmer
(2009) present as basis for industry-level growth accounting the so-called
KLEMS production function which has gross production as output variable and
capital (K), labour (L), energy (E), materials (M) and services (S) as
production inputs. The contribution to overall growth by each production and
intermediate factor is given by the product of its share in total cost and its
growth rate. As observed by Hulten (2009), the weights for the primary
production factors, capital and labour, are smaller than is the case for a
"value added" production function, since industry gross output is
bigger than industry value added. Hulten (2009) also notes that the gross
output approach is sensitive to the degree of vertical integration of an
industry, as a vertical merger of an industry with some of its suppliers could
lead to the statistical elimination of intermediate flows. The same reasoning
applies when an industry decides to outsource some energy-intensive parts of
the production process either within the same industry or to other industries
in the same country or to low-energy cost countries. While Hulten (2009)
observes that the gross production approach is tainted by statistical problems
regarding intermediate deliveries, he recalls that the choice between value
added or gross output should take account of the specification of technical
change. Hence, he cautions against the use of value added as industrial output
variable since "it implies (improbably) that efficiency-enhancing
improvements in technology exclude material and energy" (ibidem, p28).
The second method using the production
function concerns direct econometric estimation of the production function (or,
relatedly, the cost function) at industry level.
This allows for estimating the output, substitution and price elasticity for
the different input factors such as energy. The economics literature provides a
wide array of studies varying considerably in aggregation level, in the
coverage of sectors, countries and time period; and estimation method. Also the
standard assumptions of constant returns to scale and competitive pricing (i.e.
the absence of mark-ups) can be relaxed (Ecorys & CE, 2011, ch.4) Often the
production function used has the shape of a translog function and mostly gross
production is the output variable of choice, but value added is occasionally
used as well, mostly for data availability and data quality reasons. For
example, Krishnapillai and Thompson (2012) estimate for the US a production
function for industrial value added, distinguishing capital, labour and
electricity as production inputs; the estimated price elasticity suggest that
electricity, capital and labour are substitutes.
The analytical framework underlying the
input-output-table allows for a rigorous analysis of differences in industrial
cost structures either over time or over countries / branches of industry. The point of departure is total gross production at industry
level. One can directly relate the change in output to the corresponding
changes in the cost shares of the various primary and intermediate inputs (up
to the desired level of aggregation), such as for energy as a whole. However,
this leaves out the indirect effects underlying the changes of the intermediate
inputs. More formal decomposition methods allow for assessing the relative role
of changes in input prices and input quantities in the overall change of
sectoral costs. Fujikawa et al. (1995) compare the cost structure for industry
sectors in Japan and US; they derive from the price version of the input-output
model a decomposition of cost differences into a primary input price component,
a primary input technology component and an intermediate input technology
component, all three of which can be further divided into a direct and indirect
component (i.e. following from deliveries from other sectors). The role of
energy in relative productivity developments between countries has been studied
with such decomposition methods, among others by Jorgenson and Kuroda (1992). 
In addition to these elaborated analytical
methods, one can also directly compare (unit) energy cost levels and
developments over time and /or between countries outside of the input-output
framework, hence without any restrictive assumption on the relation between
output and the defined inputs. This allows much more freedom in choosing the
output indicator, gross production, value added or even other indicators. These
statistical decomposition exercises tend not to be reported in the economics
literature, unless it involves an innovation in method. Among others, the US
Department of Energy (2003) decomposes the index of energy use into the
multiplicative relation of an activity index, an index on structure (changes in
the composition of the economy or sector at hand) and an index of energy
intensity or productivity. This index approach only accounts for changes
relative to a base year and not for difference in levels (in the base year). 
One of the advantages is that one can choose for each of the (sub)-sectors /
activities in the sector under study the best output variable possible. 
 (Continued on the next page) 
 Box (continued) 
In this chapter, the approach proposed uses
the input-output table as a starting point but it is not based on
input-output-analysis. Compared to the range of methods presented above, the
decomposition of energy costs proposed here is relatively straightforward. The
comparison is between many countries whereas the literature, as reviewed above,
tends to focus on a single or only a few countries. Because of the lack of
clear guidance from the literature whether to use value added or gross
production and for reasons of data availability and quality, the unit energy
cost concept used here has followed the convention of using value added as
benchmark (Box I.1.1). This seems fairly unproblematic
since this decomposition is statistical and not embedded in a theoretical
framework. Moreover, such a convention underlines the direct analogy with the
study of unit labour costs and its split labour costs per worker and labour
productivity. However, the analogy should be handled with care as energy is an
intermediate input and not a primary production factor.
1.2.2.   Unit Energy Costs: Concept
and Methodology
This section introduces the concept of Unit
Energy Costs (UEC). Similarly to Unit Labour Costs, the UEC indicator
measures the energy cost per 1 unit of value added, in a given sector or in an
aggregation thereof. This indicator enables to compare the relative importance
of energy inputs – or in other words the sensitivity to energy price shocks -
of a given sector over time ([3]). The analysis focuses on the manufacturing sector and 14
subsectors of manufacturing as these sectors are characterised by a relatively
higher use of energy than others. Services are not analysed due to their low
energy intensity([4]). 
As Unit Labour Costs combine wages and
labour productivity, the UEC indicator brings together two key components of
competitiveness: the value of energy inputs and energy intensity, which is the
reciprocal of energy productivity. In addition, in order to differentiate
between pure energy-related effects and macroeconomic developments such as
fluctuations in the exchange rate and inflation differentials, a distinction is
made between Real Unit Energy Cost (RUEC) measuring the energy-related effect
and Nominal Unit Energy Cost (NUEC) which incorporates both components (See Box
I.1.1 for more details). The RUEC can then
be decomposed into the real price of energy inputs – deflated with the value
added deflator, hence helping to measure energy inflation above the inflation
of the given sector – and energy intensity. 
To summarize the different factors of NUEC:
NUEC = RUEC * nominal effect = real energy
price * energy intensity * nominal effect
While the nominal effect is important from
an international competitiveness perspective as businesses make their decisions
on the basis of nominal values, the nominal effect of this decomposition is
determined by factors that are not related to energy markets such as monetary
policy, inflation expectations, financial market and labour market developments
and exchange rate evolution. This analysis focuses on the energy-related
effects, therefore it concentrates on the RUEC while the NUEC is presented only
to illustrate how nominal developments complemented the pure energy effect.
The RUEC and NUEC indicators should be
interpreted in comparison among different countries. While the level of RUEC
indicates the importance of energy inputs and sensitivity to energy price
shocks, an increase that is greater than in other countries can signal an
increased vulnerability of this sector to energy costs, but it could also
reflect a restructuring of production towards more energy intensive production
processes. Therefore, it is necessary to analyse the level and evolution of the
price of energy inputs and energy intensity as well. Moreover, to address the
issue of potential restructuring on changes in the RUEC, a shift share analysis
is carried out, which is a common method to disentangle the effects of
restructuring from the growth of an aggregate indicator (see below).
1.3.      Unit
Energy Costs: an International Comparison
This section analyses the developments of
energy costs and their drivers for the manufacturing sector in a global
comparison.
1.3.1.   Real Unit Energy Costs
As mentioned above the level of Real Unit
Energy Cost measures the amount of money spent on energy sources needed to obtain
1 unit of value added. Their evolution thus combines the energy component of
the sector's inflation and the energy intensity of the sector. 
Compared to its main economic partners,
the EU manufacturing industry had in 2011 the third lowest RUEC in terms of
value added after Japan while the US, after the
hike of 2008, falls back to the just below the level of the EU in 2011 (Graph
I.1.1). China, Russia and other major
economies such as Brazil and Indonesia show substantially higher values than
the EU ([5]). 
The evolution and levels of energy costs
over value added, and energy costs over gross output in manufacturing are
broadly similar across developed countries such as the EU, US and Japan. This prominent feature is to a large extent explained by the
industrial specialisation pattern towards high valued added sectors. By
contrast, this is not the case for developing countries. A part of this
difference can be explained by the fact that countries such as Russia, China or
India and Brazil have more energy intensive production structures, specialized
in sectors where energy inputs play a comparatively bigger role. Moreover,
these production processes are often characterized by lower value added. This
is confirmed when looking at the difference between the energy costs as a
percentage of value added (RUEC) and as a share of gross output (Graph I.1.2). For the EU, Japan and the US, the
RUEC are around three times higher than the share of energy costs in gross
output. For countries such as China, India and Brazil the RUEC are four to five
times higher, implying that the difference between gross output and value added
for these countries is greater. The exception is Russia where the difference of
RUEC and the share of energy costs in gross output is similar to that of the
EU. 
 Graph I.1.1:    Real Unit Energy Costs as % of value added, manufacturing sector 
 Source: Commission Services based on WIOD database. 
 Graph I.1.2:    Real Unit Energy Costs as % of gross output, manufacturing sector 
 Source: Commission Services based on WIOD database. 
It is interesting to note that, since
2006-2007, real energy costs as a share of gross output in the US increased
much more than in the EU and this evolution has been confirmed in 2010-2011. As
the  levels of RUEC expressed in terms of value added are similar, this may
imply that the US are able to extract higher value added from their production
than the EU.
The EU's RUECs have steadily but slowly
increased over time, a trend however that is also observed in the other major
world economies. This signals the increasing
importance of energy cost pressure on the manufacturing sector's value added on
a global scale: for all the countries considered the energy costs have, as a
matter of fact, increased proportionally more than the value added. If the
refinery sector is excluded from the calculation of the RUEC (Appendix 3) the
levels decrease substantially (more than halved) and the ranking of the
countries changes with the US displaying the lowest level of RUEC, followed by
the EU and Japan ([6]). This result
indicates the importance of the refining sector in the US and it also
highlights the fact that in the other industrial sectors, less dependent on
oil, the RUEC level is higher in the EU than in the US. However even excluding
the refinery sector, the EU RUEC remains among the lowest in the world.
1.3.2.   The drivers of the Real
Unit Energy Costs ([7])
The RUEC is decomposed into real energy
prices and energy intensity. 
Japan and the EU are the two regions
where the real energy prices are the highest in levels. However the evolution of real energy price has been similar for
the four countries considered and it appears highly linked to the global oil
price's fluctuation. With the oil price hike of 2008 however Japan and the US
have registered a more severe increase in real energy prices than the EU and
China signalling their greater sensitivity to oil prices.
 Graph I.1.3:    Real Energy Price levels - Manufacturing 
 Note: Energy prices deflated with value added deflator of the manufacturing sector (in 2005 USD) Source: Commission Services based on WIOD, ESTAT and World Development Indicators databases. 
 Graph I.1.4:    Energy Intensity levels - Manufacturing 
 Note: including feedstock Source: Commission Services based on WIOD, ESTAT, OECD and World Development Indicators databases. 
At the same time the EU and Japan have
the lowest levels of energy intensity while the US and China ([8]) show considerably higher levels. China
and to a limited extent the US have been converging towards the European and
Japanese levels. It is to note that graph I.1.4 shows energy intensity
including feedstock. The level and trends of energy intensity would change if
feedstock were excluded as shown in chapter 2 (graph I.2.10). Considering only
final energy consumption, the catching up process of the US seems to have
halted after 2009 while the EU performance keeps improving.  The difference
reveals another potential vulnerability for the EU industry, that is the cost
pressure on EU industries stemming from the supply of energy sources to be used
as raw material. 
Graph I.1.5 summarizes the annualised growth rates
of RUEC and of their two drivers. 
 Graph I.1.5:    Average annual change 1995-2009 - Manufacturing 
 Note: Energy Intensity includes feedstock Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT, OECD and World Development Indicators databases. 
Japan is the
country that faced the fastest increase in RUEC during the 15 years considered.
A result that was brought about by a large increase in real energy prices
compensated only partially by very little improvements in the terms of energy
intensity. This indicates that the country suffered from strong energy cost
pressure that was not compensated via a reduction of energy intensity. 
China on the
other hand shows the slowest increase in RUEC despite the fastest increase in
real energy prices; substantial energy intensity improvements have
counterbalanced the upward pressure of the real energy prices. China started
from very high levels of energy intensity and had therefore greater margins to
improve. 
The EU and US have evolved in a very
similar fashion and the increase in RUEC has been almost the same in the two
regions. On average the real energy price increase
has been slightly faster in the US than in the EU and was compensated by an
equally slightly faster improvement in energy intensity performances (bearing
in mind that the absolute levels of the two indicators are very different). The
EU and the US have followed therefore very similar patterns where the
differentials in real energy price levels have been matched by equally distant
levels of energy intensity which translated in almost equal levels of RUEC. 
1.3.3.   Disentangling the effect of
industrial restructuring on the growth of RUEC
It is also interesting to analyse to what
extent the developments in energy costs of the manufacturing sector were driven
by (1) energy cost pressures apparent in all subsectors and/or (2) a
restructuring taking place among subsectors. For instance when facing strong
energy cost pressures, the industry may respond by reallocating resources from
sectors with high energy costs to others with low energy costs. This would then
result in a decline in the market share of high energy cost industries, while
those with low energy costs would see a rise in their share.  
In order to investigate the effects of
these two factors, a shift share analysis is carried out. The RUEC in the total
manufacturing industry can be interpreted as the weighted average of the RUECs
of the subsectors making up the manufacturing sector with the weights being the
shares of subsectors in total manufacturing value added. This way, changes in
the RUEC of aggregate manufacturing can be broken down into two distinct
effects: a change in the RUECs of subsectors (energy cost effect) and a change
in the shares of subsectors in total manufacturing (restructuring effect) along
with a dynamic interaction component of the two effects ([9]). In particular, the shift-share analysis decomposes the growth of
RUEC into the following three components ([10]).
Within subsector effect: This shows what would be the growth of RUEC of the total
manufacturing sector if the shares of the subsectors had stayed unchanged
throughout the period of analysis. Therefore this effect shows the pure energy
cost pressure filtering out the effect of restructuring.
Restructuring effect: This measures the contribution of changes in value added shares of
the different subsectors to overall manufacturing RUEC growth keeping the RUECs
of subsectors unchanged. This component therefore shows the static
restructuring effect. For instance a negative restructuring effect could show
that the share of industries with high energy costs has fallen, thereby
reducing RUEC growth.
 Graph I.1.6:    Shift share analysis of manufacturing sector RUEC growth 
 Source: Commission Services based on WIOD. 
Interaction effect: This term captures the dynamic component of restructuring by
measuring the co-movement between RUECs and value added shares. If it is
positive, it signals that energy costs are rising in subsectors that are
expanding, and/or they are falling in shrinking sectors, i.e. the two effects
complement each other. If it is negative, then RUEC growth is positive in
shrinking sectors, and/or negative in expanding sectors, i.e. the two effects
are offsetting each other. A negative interaction effect could signal that
businesses in a country are reallocating resources from high to low energy cost
sectors in response to rising energy costs.
Looking at the shift share analysis of manufacturing
sector RUEC growth in the period 1995-2011, the main result is that the bulk of
RUEC growth in EU27, Japan and China were driven by the within effect; i.e.
energy cost increases within sectors (Graph I.1.6). There
is no evidence of a significant restructuring effect in the EU during this long
period. In contrast, RUEC growth in the US was dominated by the static
restructuring effect, i.e. by an increase in the share of high energy cost
industries, particularly of the coke and refined petrol industry. Overall these
developments may signal an increased specialisation of US manufacturing in high
energy cost production with respect to other countries ([11]).
 Table I.1.1:      Average % annual change 1995-2009 - Manufacturing 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT, OECD and World Development Indicators databases. 
The picture is changed if the shift
share analysis is decomposed into three shorter periods. The period 1995-2000 was characterised by a marked increase in
RUEC dominated by the within subsector effect in the EU, US and Japan. The
period 2000-2005, however, brought significant differences with the US being
the only country with a negative within subsector effect. At the same time the
US showed a very large positive restructuring effect which was mitigated to
some extent by a negative interaction term. Overall this indicates that the US
started specialising in high energy cost production already in this
period ([12]). Finally,
the last period – 2005-2011 – includes the beginning of the development of
shale gas in the US as well as the peak in oil prices of 2008 and the
subsequent fall in 2009 and has brought a significant adjustment and
restructuring on a global scale. While the RUEC of the EU rose only moderately,
this was due to a limited restructuring – both static and dynamic – away from
high energy cost sectors offsetting a pure energy cost effect which was
substantially higher than in the other countries. In the US, RUEC increased
visibly less than in the EU over this period. Once again a positive
restructuring effect can be observed, and is brought about by the continuous
growth of some energy intensive sectors, in particular coke and refined petrol.
Japan saw a positive within subsector effect with a positive restructuring
effect and its RUEC grew more than in the US and in the EU. Finally, China
experienced positive but modest within subsector effect and a similarly modest
negative restructuring effect. 
The shift share analysis of the
manufacturing sector excluding the coke, refined petrol and nuclear fuel sector
helps to single out the relevance of this sector in the evolution of the RUEC
and of the industrial composition of the countries (Appendix 3). The
restructuring effect observed with the full data set essentially disappears
once the refinery sector is excluded. This is most evident in the US where in
the period 1995-2011 the shift share analysis reported above in Graph I.1.6
displays a very big positive restructuring effect while excluding the refinery
sector this effect is no longer present. This points to the increased relevance
of this sector in the US economy over the past years which is also confirmed
when looking at the growing contribution of the sector to the total industrial
GVA of the US. Another important observation can be made looking at the period
2005-2011 which includes the shale gas production surge. By excluding the
refinery sector highly dependent on oil products, the RUEC growth in the US is
actually negative. This is probably due to the substantial reduction in
electricity and gas prices which shale gas has made possible. In the EU the
difference between the shift share analysis with or without the refinery sector
is also significant. For a start the growth of RUEC is greatly diminished, over
both the longer period 1995-2011 and the shorter period 2005-2011. This implies
that oil price dynamics play a major role in determining the energy costs of
the manufacturing sector. The less dependent a sector is from oil products the
less it appears to be exposed to real unit energy costs increase. The second
observation is that once the refinery sector is excluded from the analysis the
small negative restructuring effect observed over the period 2005-2011
disappears, implying that it was mostly related to this sector ([13]).
1.3.4.   Nominal Unit Energy Costs
Table I.1.1 presents the decomposition of the
different elements of NUEC and can be read from left to right in an
(approximately) additive manner. The nominal effect represents the difference
between RUEC and NUEC and it measures the combination of sectoral inflation and
exchange rate fluctuations. 
The table shows that nominal
developments have added some pressure to the energy costs of the EU over the
period 1995-2009 as compared to the US and Japan as
shown by the higher average growth rate of nominal effect for the EU than for
the US and Japan. With US dollar being the common currency of comparison, the nominal
effect of the US is close to 0 ([14]). On the other hand Japan has gone through a period of internal
deflation which resulted in a negative nominal effect partially offsetting the
evolution of the RUEC. China experienced the lowest annual change in RUEC
complemented by a sizeable increase of the nominal effect and therefore has
experienced the fastest increase in NUEC. This means that other sectoral price
and exchange rate dynamics have added upward pressure to the pure
energy-related effects captured by the RUEC in China.
1.4.      Unit
Energy costs: A sectoral comparison
A more disaggregated analysis involving 14
manufacturing subsectors shows that most of these subsectors in the EU have a
generally low unit energy costs per value added in an international
comparison ([15]).
Certain sectors in the EU show however a
significant vulnerability because of their high RUEC levels and/or RUEC growth
rates in a global comparison, indicating elevated sensitivity to energy-cost
pressures (Table I.1.3 and Table I.1.2).
Overall the sectoral analysis confirms that the low unit energy costs level for
the total manufacturing industry of the EU hides a substantial heterogeneity
among subsectors. This highlights the need for more disaggregated sectoral
analysis as it is possible that some subsectors of manufacturing show high
vulnerability to energy inputs despite the fact that energy costs are very low
for total manufacturing. A more detailed split could reveal even more vulnerabilities
within sectors. In this sense the top-down approach applied here – from a high
to a medium level aggregation – should be interpreted as complementary
information to more disaggregated sector-specific analyses.
In the food, beverages and tobacco
sector the RUEC of the EU were the second highest in 2009. They showed a
similar pattern to that of the US, but both of them were performing
significantly worse than China and Japan. Energy intensity improvements in the
EU have been rather limited but Japan and the US deteriorated their
performances. The real energy price increased faster in the EU than in either
Japan or US although in absolute levels the EU is still below Japan. Compared
to 2011 the RUEC of the EU have increased while in the US they have decreased,
this was however matched in both countries by a small decline in the share of
the sector in total manufacturing value added. 
The textile industry of the EU has
performed substantially worse than that of the US and Japan in terms of RUEC
and their level is also higher than in China, both in 2009 and in 2011. The
energy costs of the Chinese textile industry showed a marked upward trend and
reached similar levels to that of the EU at the end of the sample. The
increasing trend of China and the stable trend of the US could be a sign of
outsourcing although data availability does not allow the assessment of the
evolution of energy intensity and real energy prices in the two countries. The
good performances in terms of energy intensity in both the EU and Japan have
been met by opposite trends in terms of real energy prices which translated
into similar annual increases of RUEC. 
The developments in the leather and
footwear sector are in many ways similar to those of the textile industry.
The EU, Japan and China have reached similar levels in the second half of the
sample period in terms of RUEC. The US reached a considerably lower level by
2009, and again the opposite trends between the US and China raises the
possibility of potential outsourcing. As with most other sectors, Russia
exhibited by far the highest levels of RUEC throughout the entire period. Both
the textile and leather sectors have experienced a sharp decline in the share
of manufacturing value added in Japan, Russia and US, while the decline in the
EU and China was much less evident during this period. Data from 2011 confirms
the trend of the previous period. 
In the wood and wood product
industry the EU has shown the second lowest RUEC following Japan. The pattern
of marked improvement in 2009 for the US is not visible in this sector, in
fact, RUEC was trending upwards in US over the entire period of analysis, much
so than in any other of the five countries. China was slightly above the EU
while Russia was fluctuating at a considerably higher level. Unlike for other
sectors, the energy intensity performances of the EU and Japan have
deteriorated but have been matched by a moderate decrease in real energy prices
similarly to Japan. In the US the increase in real energy prices has been much
faster than the decrease in energy intensity. In 2011 however the RUEC in the
EU, Japan and China continues to increase while the opposite happens in the
US.  
 Table I.1.2:      Sectoral breakdown: decomposition of RUEC and annual growth rates 1995-2009 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT, OECD and World Development Indicators databases. 
In the pulp, paper and printing
sector the EU has been performing in line with the US with Japan also reaching
similar RUEC levels at the end of our sample. China and particularly Russia
showed higher levels of RUEC. The almost stable performances in terms of energy
intensity in the EU means that the increase in real energy prices has been
therefore almost symmetrically translated into higher energy costs for EU
industries although the trends in the US and Japan are broadly comparable. As
for the other sectors, data for 2011 show an increase in RUEC for EU, Japan and
China while the opposite is true in the US and to a lesser extent Russia. 
The production of coke, refined petrol
and nuclear fuel is the sector that shows the worst performance in the EU
with RUEC several times above the levels of US, Japan, China and Russia. RUEC
in this sector showed a steep upward trend 
 Table I.1.3:      Sectoral breakdown: decomposition of RUEC and annual growth rates 1995-2009 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT, OECD and World Development Indicators. 
in the period 1995-2009 in the EU unlike in
any other country analysed here which indicates an increasing vulnerability.
Looking at energy costs as a share of output – not reported here – would show a
somewhat better relative performance of the EU suggesting that this sector is
suffering not only from high energy costs but also from low and drastically
worsening value added in a global comparison. The oil-price shock of 2008 had a
significant upward effect on the RUEC of all the five countries, the EU however
further increased its RUEC in 2009 while in the other four countries a
reduction took place, bringing the levels back to pre-2008. However, the share
of the sector in manufacturing valued added for the EU was and remained very
small. At the same time the sharp increase of the share in Russia and the US
need to be recorded as it signals the growing importance of coke and refinery
activities in these two countries. Data for 2011 show that while in the EU the
RUEC have further increased, an inverse trend is observed in the US where the
sector reached almost 10% of total manufacturing value added.  
In the chemicals and chemical products
sector the EU has shown the lowest RUEC together with the US in the period of
analysis ([16]). The low
levels of energy costs of the EU and US significantly outperformed the other
countries and also present the lowest growth rates. In 2011 RUEC increased in
both regions. Russia and China showed the highest levels of RUEC throughout
most of the period of analysis. A marked improvement is visible in Russian RUEC
in the years of the Russian financial crisis (1998-99). This pattern is visible
for many other sectors as well, but the improvement was only temporary and RUEC
returned to pre-crisis levels in the following years. For the EU the fast
increase in real energy prices which outpaced that of the US and to a lesser
extent that of Japan, was counterbalanced by significant improvements in energy
intensity which both in levels and progress way outperform the two competitors.
In the rubber and plastics sector,
during the period 1995-2009, the EU has performed relatively well together with
the US and Japan, while China and especially Russia exhibited much higher
levels of RUEC. However the EU registers in 2009 higher RUEC than Japan and US
and has the highest growth rate since 1995 mostly driven by the deterioration
of its energy intensity. Looking at the components of RUEC it is to note that
the EU had in 2009 the highest levels of energy intensity (compared to Japan
and US) and unlike the other two countries did not record any improvement. The
EU compensated partially with a lower real energy price than both Japan and US
and with lower growth rates. In 2011 the RUEC in the EU and Japan continued to
increase while in the US they significantly reduced, at the same time the
contribution of the sector to the manufacturing value added remained broadly
unchanged. 
In the non-metallic mineral sector and
the metals sector the EU showed a much lower level of RUEC than Japan,
China and Russia. The EU, however, was performing worse than the US and the gap
in favour of the US has increased also in 2011. RUEC growth rates in the EU
have been anyway the lowest among the five countries, mostly driven by energy
intensity good performances. Energy intensity in the EU was in 2009 the lowest
and it has experienced the most significant improvements while for Japan it
actually deteriorated. At the same time, while the level of real energy prices is
comparable in 2009 the EU experienced faster growth rates than both Japan and
the US. 
In the sector of machinery the RUEC
of EU, Japan and US have had comparable very low levels in the entire period.
The US is the country with the lowest level of RUEC and the only one for which
the growth rate is negative. This positive evolution has been mostly driven by
a decrease in real energy prices while energy intensity slightly deteriorated.
US RUEC further decreased in 2011 while in the EU they remained stable. This
happened in a context of increase in share of the sector in total manufacturing
value added, in both regions. China has shown a moderately increasing trend and
reached a level that is substantially higher than that of the other three
economies. Russia in turn exhibited the highest RUEC in this sector but lower
growth rates than China and also Japan. Energy intensity in the EU decreased
rapidly but on the other side real energy prices increased at almost the same
pace. In the US conversely energy intensity did not improve but real energy
prices decreased by an average of only 1% per year. 
In the electrical and optical equipment
sector the EU, US, Japan and China started from similar levels of RUEC but have
shown a remarkable divergence in the period of analysis. This concerns
primarily the US and China, where the opposing trend again suggest the
possibility of outsourcing of energy-intensive processes from the US to China.
The EU exhibited a relatively constant RUEC which put it at the second lowest level
after the US in 2009. Japan showed a mild increase over the period, while
Russia fluctuated again at a substantially higher level. The dramatic collapse
in energy intensity matched by an almost equally fast increase in real energy
price in the US tends to confirm the assumption that the country may have
experienced a substantial relocation of energy intensive activities. However
the simultaneous increase in the share of the sector in the manufacturing value
added signals that the US industry focused on innovation and higher valued
added activities. Japan also presents similar features. This trend is confirmed
also by looking at 2011, where the share of the sector in the manufacturing
value added further increased while RUEC decreased. The EU also recorded
remarkable improvements in energy intensity although compensated by a
significant increase in real energy prices.  
In the sectors of recycling and
transport equipment the EU has shown a significantly higher RUEC than the
US and also of Japan, a gap that has further widened in 2011. In transport
equipment the performance of the EU was more or less in line with that of
Japan. China was fluctuating at a higher level and Russia at an even higher
level in the transport equipment sector. However the collapse of energy
intensity registered in Japan in the transport equipment sector could be the
consequence of a drastic industrial restructuring and outsourcing of the most
energy intensive activities in favour of lower energy intensive production with
comparatively greater value added. EU RUEC in 2011 decreased slightly while an
increase was registered in the other countries. On the other hand in recycling
the EU has worsened its energy intensity performances while recording only a
moderate increase in real energy price. The US shows the opposite picture,
rapidly falling energy intensity matched by an increase in real energy prices
which resulted in small decrease of RUEC over the 15 years considered. 
In sum, the sectors that are most
exposed to energy price shocks in terms of high RUEC levels in the EU are coke
and refined petrol, chemicals, non-metallic mineral, metals, rubber and
plastics.  Coke and refined petrol stands out with
much higher RUEC levels than in other countries and a growth rate that is also
among the highest ones. This indicates significant vulnerability of this
sector, though its share in total manufacturing value added of the EU has been
low and stable. In contrast, US, Japan and Russia have seen a significant
increase in this share. In the other four sectors with high energy cost
vulnerability (chemicals, non-metallic mineral, metals, rubber and plastics)
the EU shows RUEC levels that are generally comparable with those of Japan. The
EU levels are, however, noticeably higher than the US in chemicals,
non-metallic mineral, and metals. Nonetheless in all four sectors the figures
of the EU remain substantially lower than those of China and Russia. In terms
of the growth rates of RUECs, the four sectors in the EU perform generally in
line with other countries with some variability observable. 
Data for 2011 show that for all sectors the
RUEC have generally increased in all countries, except in the US where the
picture is more mixed and most sectors actually recorded a decrease.  Although
EU RUEC are above the US for all sectors in 2011,  they are similar for total
manufacturing due to the different composition of the manufacturing value added
in the two regions. 
It is nonetheless interesting to note that two of the four sectors in the EU
where the contribution to the manufacturing value added has increased are among
the most energy intensive sectors such as: coke and refined petroleum products;
basic metals and fabricated metals.  
1.5.      EU
Member States assessment
The evolution of RUEC for EU Member States ([17]) between 2000 ([18]) and 2009 is in general characterised by an upward trend. With the exception of a handful of countries most Member States
saw their RUEC increase on average by 47%. The biggest increases in percentage
terms were recorded in Ireland (89%) followed by Malta (70%), Sweden, France
and Belgium (around 60%). The upward trend is broadly confirmed with the data
for 2011([19]) with the
exception of Ireland and Germany where RUEC have been reduced. Looking at the
evolution between 2000 and 2011 the Member States with the greatest percentage
increase were France (144%) Belgium (124%) and Finland (111%). On the other
hand Cyprus, Slovakia, Romania and the Czech Republic recorded a decrease in
RUEC. 
The heterogeneity in levels is rather
wide. For some Member States the RUECs are sensibly lower than the EU average
while others on the contrary display levels that are significantly higher, not
only than the average but also than the levels of their main international
competitors (Graph I.1.7). In absolute terms  Ireland and
Malta, together with Luxembourg, Slovenia and Austria, display the lowest
levels of RUEC in 2000, 2009 and 2011. The highest levels were reached by
Bulgaria which however recorded a percentage increase well below the EU average
(7.9%, between 2000 and 2011) and Lithuania, followed by the Netherland,
Greece, Belgium and France.
The evolution of energy costs at Member
States level is analysed in combination with the trends of energy intensity and
real energy prices presented in Graph I.1.7.

 Graph I.1.7:    Decomposition of Real Unit Energy Costs - Manufacturing 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT and OECD. 
The Member States with the highest
levels of energy intensity in 2009 were Lithuania, the Netherlands and Slovakia. However, it is to note that Bulgaria had until 2006 the highest
level of energy intensity, but lack of data for 2009 does not enable a full
comparison ([20]). The lowest
levels of energy intensity are found in Slovenia, Luxembourg and to a lesser
degree Latvia, Austria, Germany and Italy. At the same time real energy prices
were the highest in France, Slovenia and Italy, while Estonia, the Czech
Republic and Slovakia enjoy the lowest real energy prices, sometimes even below
the US levels.
 Graph I.1.8:    Annual Growth Rates 2000-2009 - Manufacturing 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD, ESTAT and OECD. 
By looking at the growth rates, some new
Member States (Czech Republic, Poland, Slovakia and Slovenia) stand out in
terms of energy intensity improvements and, for the Czech Republic also for the
low rates of real energy prices growth. These
factors contributed to determine a negative growth of RUEC for these countries;
except for Slovenia where the upward pressure of real energy prices determined
a minor increase in RUEC. In some Member States (Italy, Spain and Luxembourg),
despite worsening performances in terms of energy intensity, a moderate
increase (a decrease in the case of Luxembourg) in real energy prices resulted
in RUEC growth rates below the EU average and also the US. By contrast, some
Member States such as France, Sweden and Finland report fast growing real
energy prices, well above the EU average, which were not offset by sufficient
improvements in energy intensity, hence a growth rate in RUEC well above the
average of the EU and the US.
As said, an increase in Real Unit Energy
Costs means that the amount of money spent on energy sources to obtain one unit
of value added has increased and this negatively weights on the margins of the
sector. The growth rates of NUEC presented in Table I.1.4  show to what extent other
macroeconomic dynamics, such as sectoral price inflation and exchange rate
fluctuations, have either exacerbated or alleviated the growth of RUEC.
Spain had the fastest growing NUEC in
the EU followed closely by a group of other Member States which present all
similar features, i.e. an high increase of the nominal effect well above the EU
average (with the notable exception of France where
the NUEC growth is more linked to the energy costs components). Conversely the
lowest increases in NUEC have been in Poland, the Czech Republic and Slovakia.
However only in the case of Poland this result can be ascribed mostly to the
very low growth of the nominal effect. In Czech Republic and Slovakia the
improvement in their performances must therefore be found in the energy
components, notably in remarkable reductions of energy intensity.
1.6.      Conclusions
 Table I.1.4:      Average % annual change 2000-2009 - Manufacturing 
 Note: Energy Intensity includes feedstock. Due to data limitation the assessment of Energy intensity and Real energy prices stops at 2009. Therefore to allow comparability the growth rates of RUEC have also been computed only up to 2009. Source: Commission Services based on WIOD and ESTAT databases. 
The results shown above indicate that
the EU manufacturing sector has enjoyed some of the lowest Real Unit Energy
Costs together with Japan and similarly to the US.
This means that to obtain 1 USD of valued added they have spent a lower amount
of money on energy sources than Russia or China. In addition, the evolution of
RUEC plotted in Graph I.1.1 shows that the EU have suffered relatively less
than other countries the oil price shock of 2008 which has on the other hand
affected severely both Japan and the US. This impact is also clearly shown in
Graph I.1.3 where real energy prices are presented. This may be the outcome of
the energy mix composition of the US industry compared to that of the EU, since
the US industry is more reliant on oil products than EU manufacturers ([21]).
The trend of the EU RUEC could also be
determined by an industrial structure based on higher value added production.
The relatively higher real energy prices may have induced EU manufacturers –
together with Japan and US – to specialize in higher value added product
categories with lower energy intensity while conversely the industry in
countries such as China, Russia, India, Brazil lead by competitive energy
prices may have opted for more energy intensive production activities with a
comparatively lower value added.
The RUEC levels for the entire
manufacturing sector in 2011 signal a continuation of the upward trend for all
the countries. It is to note however that the EU overtakes the US, by a very
thin margin, and China further converges towards the US, Japan and the EU. 
The improvements of the EU industry in
terms of energy intensity have helped to offset the increase in real energy
prices. Despite the already low starting point the
EU manufacturers have steadily improved their energy intensity performances
converging towards the Japanese levels. The US and China have been catching up
but the difference in absolute levels remain substantial.
The sectors that are most exposed to
energy price shocks in terms of high RUEC levels in the EU are coke and refined
petrol, chemicals, non-metallic mineral, metals, rubber and plastics.  Coke and refined petrol stands out with much higher RUEC levels
than in other countries and a growth rate that is also among the highest ones.
This indicates significant vulnerability of this sector, though its share in
total manufacturing value added of the EU has been low and stable. In contrast,
US, Japan and Russia have seen a significant increase in this share. In the
other four sectors with high energy cost vulnerability (chemicals, non-metallic
mineral, metals, rubber and plastics) the EU shows RUEC levels that are
generally comparable with those of Japan. The EU levels are, however,
noticeably higher than the US in chemicals, non-metallic mineral, and metals.
Nonetheless in all four sectors the figures of the EU remain substantially
lower than those of China and Russia. The growth rates of RUECs of the EU in
the four sectors are generally in line with other countries with some
variability observable.
In 2011 data confirm that for all sectors,
EU RUEC are higher than in the US. While this points to additional cost
pressure on EU firms it is however to be noted that some typically
energy-intensive sectors (coke and refined petroleum and basic metal products)
have incremented their shares in the manufacturing value added of the EU.  
The situation of Member States, is
heterogeneous. On the one hand countries such as
Bulgaria, Lithuania and the Netherlands have the highest levels of RUEC
therefore their production structure is more sensitive to energy cost pressure
and any increase in energy prices not matched by improvements of energy
intensity may severely affect the margins of their manufacturing sectors. On
the other hand countries like Italy and Luxembourg have experienced a worsening
of their energy intensity performance which was however met by moderately
increasing real energy prices. The growth of their RUEC has been therefore
modest and their absolute levels remain low. More vulnerable in this sense
appears France where the very fast growth in real energy prices was not
sufficiently counterweighted by significant improvements in energy intensity.
The growth rate of RUEC in France is well above the average although its level
is still relatively low. Finally for some countries, especially Spain, the
nominal effect led to a fast increase in NUEC. These dynamics are outside the
scope of the present study but have nonetheless added cost-pressure on the
Spanish manufacturing sector exacerbating the energy cost component.
2.1.      Introduction 
The previous chapter on Unit Energy Costs
presented an empirical analysis based on the WIOD Database which provides data
only until the year 2009 for some of the indicators (namely energy intensity
and real energy prices) and for 2011 for the Real Unit Energy Costs. 
The period after 2009 has however been
marked by important events, some energy-related and some not. The development
of US shale gas belongs to first category. It has changed substantially the
energy system of the US and by consequence it has widely impacted on the global
energy markets. The extent of these changes and their implication for the EU
are the subject of this chapter. The economic and financial crisis that spread
after 2008 is instead part of the second category of events, not
energy-related. The economic recession that has affected the EU economic
economy has however made more urgent the need to look at energy prices for
consumers and industry, in a context of lacklustre domestic demand and loss of
competitiveness. 
The surge of the US shale gas ([22]) and the corresponding fall in energy prices for US manufacturers
has reignited the debate on the EU's industrial competitiveness and has led to
calls for policy changes aimed at reducing the energy costs for EU firms,
either through reducing the stringency of energy and carbon policies or through
stepping up EU gas production including shale gas ([23]). 
This chapter will endeavour to assess
impacts of the development of shale gas through a step-by-step comparison
between the EU and US, using data from Eurostat, OECD and the US Energy
Information Administration. Section 2.2 discusses how the introduction of shale
gas has affected the US energy sector. The impacts are assessed through an
EU-US comparison on the energy mix and on the energy import dependence. Section
2.3 addresses the development in the EU-US energy price-gap. The disparity in
energy intensity and some reflections on the impacts on the production
structure in the EU and US are presented in Section 2.4. Finally the
developments in the trade balances for the EU and US will be discussed in
section 2.5. The chapter is concluded by some preliminary remarks and open
questions for future discussions. 
2.2.      The
impacts of the surge in US shale gas on the US energy sector and EU and US
energy mix 
Many observers have noted the strong
surge in US gas production and consumption because of what has been coined the
"shale gas revolution." As depicted in
Graph I.2.1, shale gas was already produced in the
US in modest amounts at the turn of the century, but it became significant
after the middle of the last decade. 
The exponential growth in production
volume started to profoundly affect the make-up of the US natural gas supply
from 2007/2008 onwards. By 2011, the US has become
the biggest gas producer in the world, ahead of Russia, while shale gas constitutes
now over one third of the natural production in the US (while only about 5% in
2005).
The current impact of shale gas on the
overall make-up of the US energy sector has been significant but it should not
be overstated, both as regards the net impact on
the domestic gas sector and as regard the changes in the energy mix. Shale gas
has revived the domestic natural gas sector whose production had stagnated
earlier in the decade, and since a few years shale gas is also replacing
domestic supply of conventional natural gas.
 Graph I.2.1:    Natural gas production in the US and share of shale gas on total gas production 
 Source: Commission Services based on Energy Information Administration, US. 
Over the period 2000 – 2011 natural gas
production has increased by almost 20% and since the historic low in production
in 2005 it has increased by almost 27%.
However, the share of natural gas in the US
energy mix has only increased by 2 percentage points between 2000 and 2011,
while it increased from 18% to 25% in the electricity mix (Appendix 4, Graph
I.A4.3). 
 Graph I.2.2:    Energy mix US 
 Note: Expressed as share per source in Primary Energy Consumption Source: Energy Information Administration. 
 Graph I.2.3:    Energy mix, EU 
 Note: Expressed as share of source in Gross Inland Consumption Source: Eurostat. 
The resurgence of gas as primary energy
source in the US should be seen against the background of changes in the US
consumption and production of the other primary energy sources. Graph I.2.2 on the US energy mix in the period
2000 – 2011 shows a similar increase in importance of renewable energy sources:
its consumption share has risen from 6% in 2008 up to a share of 9% in 2011. On
the other hand, a relative decline of oil and coal as primary energy sources is
observed with their shares falling over the decade from 39% to 36% for oil and
from 23% to 20% for coal. 
These changes in shares reflect changes in
domestic production levels: renewable energy generation has increased by 49% in
the past ten years and natural gas, as already mentioned above, by 20%. Coal
production has fluctuated but in 2011 it had decreased by 2% compared to 2000.
In 2011 natural gas has for the first time overtaken coal as first source of
energy produced in the US. Oil production after a period of slow and steady decline,
culminated in 2008 has picked up again but in 2011 it was still 3% less than in
2000 (Appendix 4, Graph I.A4.1).
Together with renewables, US shale gas
has undoubtedly contributed to significantly reducing the energy dependence of
the United States and hence to decreasing their
exposure to global commodity prices fluctuation and geopolitical risks. 
As depicted in Graph I.2.4, the US energy import dependency has
reached 18% in 2011, the lowest point since 2000.
 (Continued on the next page) 
 Box (continued) 
 Graph I.2.4:    Energy Import Dependency 
 Source: Commission Services based on Energy Information Administration and Eurostat. 
However, the fall in energy import
dependency started around 2005 and hence somewhat before shale gas
production levels became significant. This can be explained by the expansion of
renewables and by the start of the increase in overall gas production.
In sharp contrast to the US, the EU's
import dependency has increased from 46% to 52% between 2000 and 2010 ([24]). This
reflects the combination of a decline in domestic energy production and an
increase in energy consumption, even when taking account for the abrupt
contraction of economic activities in 2008.
The production decline over the decade
concerns all primary energy sources except renewables. EU gas and oil production have fallen by a quarter and 40%
respectively. However coal, because of its sheer volume (still larger than for
all other energy sources combined), has been the major driver of the overall
decline with a production fall over 10%. In contrast, renewables increased
their output in caloric terms by 72%. 
Since the EU energy mix has similar make-up
and trends as the one of the US (with a higher share of nuclear power as the
major difference), the rise in consumption has been met by increasing imports.
Natural gas provides an apt illustration: the increase of consumption share by
2 percentage points over the decade has prompted an import increase of more
than 45%, whereas the US has satisfied the increased demand mainly from
domestic sources (gas imports in monetary terms decreased by 56%, compared to
their peak in 2005). 
There is another recent phenomenon
triggered by the development of shale gas and
observed mainly between 2011 and 2012: the US have decreased their consumption
of coal, exporting their excessive production and reducing their imports. This
has driven coal prices down. As gas has became relatively more expensive and
coal relatively cheaper in Europe a substitution is taking place: gas
consumption declined by 7% while coal consumption increased by about 20%
between the first half of 2011 and the first half of 2012. Notably imports of
coal from the US increased substantially especially in some Member States:
looking at the first half of 2012, Germany, Italy and the Netherlands
respectively imported 37%, 83% and 86% more hard coal from the US than in the
first half of 2011 ([25]). This shift
raises evident climate change concerns as currently carbon prices are too low
to offset the comparative advantage of coal over natural gas.
2.3.      Electricity
and Gas prices: a US-EU comparison
In the developed world, gas is increasingly
seen as an attractive substitute for oil as it is a relatively clean source of
energy and also because it has become relatively cheap (Graph I.2.5). For the purposes of this analysis,
however, it is not enough to look at the gas spot market price, for a number of
reasons. 
First, unlike oil, there exists no global
wholesale market and no global reference price for natural gas. In the European
Union the majority of natural gas is supplied through bilateral long-term
contracts which are negotiated between two parties, importer and exporter, and
traditionally indexed to the price of oil. Currently, half of natural gas
supply in the EU is still indexed to oil while across the EU a wide variation
in import prices of piped gas and LNG has been observed ([26]). This is remarkable as at the same time a growing share of gas is
traded on spot-markets ([27]) where
short-term contracts are concluded on the basis of the market price determined
by actual demand and supply. Spot market prices in the EU have been constantly
lower than long-term contracts' prices, at least since 2005 ([28]).
In addition, gas can be used directly for
heating or other purposes but can also be used as a primary energy source for
electricity generation: in both regions, the share of gas in the electricity
mix is currently around 25% and it has increased with a similar pace over the
past ten years. Consequently, the wider impact of shale gas on energy prices can
be illustrated by looking at the electricity prices.    
In both the US and in the EU,
spot-market gas prices have progressed in a similar fashion over the past
decade and have followed the movements in the oil price, as depicted in Graph I.2.5. In 2005, however, these gas prices
have started to clearly fall below the level of the oil price. Between 2008 and
2009 they fell significantly in both regions, likely as a consequence of
declining demand due to the economic downturn.
 Graph I.2.5:    Wholesale natural gas prices in Germany, Japan, UK and US compared with crude oil price 
 Source: European Commission (2012). 
The fall in energy consumption has led to
an excess supply of gas on the gas markets around the world and both US and the
UK spot markets temporarily converged, trading at around 4/5 USD/MBtu in
mid-2009, while the German hub prices fell less evidently, trading still above
8 USD/MBtu in 2009. From 2007 onwards, the US gas spot price has fallen under
the price level of the other gas spot markets, which most likely reflects the
effect of the surge in domestic shale gas supply. This becomes quite clear
after 2009, when energy consumption picked up again following the recovery of
the economy.
Statistics from more recent years show that
while the US spot prices remained low (around 4 USD/Btu in 2011), the EU spot
prices (both in the UK and German hub) kept increasing([29]). Wholesale gas prices have continued to rise in the EU while
economic activity contracted and consequently natural gas consumption in the EU
has been declining: the first half of 2012 represented the EU's lowest first
half year consumption of the last ten years. It was 7% and 14% less than the
first half of 2011 and 2010 respectively ([30]). 
The continued rise in EU wholesale gas
prices despite the slump in gas demand and the lower gas spot prices vividly
depicts the kind of vulnerability the EU is exposed to due to its high import
dependency: as the Asian markets offer higher
returns ([31]) and more
robust demand, gas producing countries have increased their trade with Asia
lowering supply to Europe. As a consequence wholesale gas prices in Europe have
increased while in the US, which now can rely more heavily on domestic
production, prices have remained low. US prices were shielded from potential
upwards pressure from export demand because of export restrictions (generally
expected to be gradually lifted). Furthermore, the impacts on the EU have been
further aggravated in this context due to the oil-price indexation of many
long-term gas import contracts.
The evolution of end-user's prices ([32]) for gas (Graph I.2.6 and I.2.7) follows a pattern similar to that of
the wholesale market.
 Graph I.2.6:    Indices of real gas prices for end-users 
 Note: "Real" price indices are the current price indices divided by the country specific producer price index for industrial prices, and by the consumer price index for the household sector. Source: OECD - Electricity Information (2012). 
 Graph I.2.7:    End-user gas prices for industry 
 Note: For the US prices it was not possible to identify a specific consumption band. The EU prices are for the consumption band I3 (I3.1 and I3.2 until 2006) that is between 10,000 and 100,000 GJ. Prices are nominal and the exchange rate used is from OECD. Taxes are included. Source: Energy Information administration and Eurostat data. 
A significant gap between the EU and the US
starts appearing in 2006, prior to the development of shale gas but coinciding
with the divergence observed between the oil price and the natural gas prices
on the wholesale markets in the various regions in the world.
While the EU gas end user prices seem to
stick closer to the oil prices and increased from 0.022 EUR/KWh in 2005 to
0.035 EUR/KWh, the US gas prices declined from about the same starting point of
the EU in 2005 to 0.010 EUR/KWh in 2011.
On the other hand, the impacts of the fall
in the gas price on electricity end user prices is much less evident yet it can
still be observed. As shown in Graph I.2.8, electricity prices in the US have
historically been much lower than in the EU.
 Graph I.2.8:    End-user electricity prices for industry 
 Note: For the EU prices refer to average of consumption bands Ie If Ig until 2007, after 2007 consumption band ID. Prices are nominal and the exchange rate used is from the OECD. For the US no consumption band was available. 2011 provisional data. Taxes are included. Source: Eurostat and Energy Information Administration. 
 Graph I.2.9:    Indices of real electricity prices for end-users (2005=100) 
 Note: "Real" price indices are the current price indices divide by the country specific producer price index for industrial prices, and by the consumer price index for the household sector. Source: OECD - Electricity Information (2012). 
The gap has been persistent at least since
2001 (Graph I.2.8). Also in this case, the price
difference predates the development of shale gas. 
The price differential has however been
widening in the past few years as the European prices increased over the period 
(although not in a linear manner) while the US prices remained more or less
constant.
The development of US shale gas is
likely to be at the root of this widening gap mainly because its increased
energy independence and export restrictions in the
US has to some extent sheltered them from fluctuations on the global energy
markets; in addition it has reduced the supply costs of gas for electricity
generation. At the same time the EU energy dependence has increased and this
has led to a higher exposure of the EU to energy prices volatility. 
Finally it is to note that shale gas prices
in the US do not fully reflect external costs as the current regulatory regime
exempts shale gas projects from a number of pieces of federal environmental
legislation, including the provisions of the US Safe Drinking Water Act. 
2.4.      Energy
Intensity ([33]): a
US-EU comparison
Over the past years, the European
industrial sector has been able to successfully decouple its performance in
terms of value added from its energy consumption.
The remarkable wide energy price gap between EU and US should be considered
next to the equally remarkable energy intensity gap between the two regions. 
The EU industry's energy intensity has been
substantially lower than its US counterpart. In addition it has improved by
almost 19% between 2001 and 2011 while in the US the improvement over the same
period was only 9%.
 Graph I.2.10:  Energy intensity of industry 
 Note: Final energy consumption industry divided by gross value added in 2005 reference year, ktoe in billion of euros. Source: Eurostat, Energy Information Administration, Bureau of Economic Analysis USA. 
It appears that the increase in the
European energy prices is likely to have provided manufacturing industry with
the incentive to improve their energy intensity in order to limit the cost of
their production inputs. Conversely, the relatively cheaper energy supply in
the US did not provide similar incentives. 
The development of shale gas has
exacerbated this difference as it has further lowered electricity and gas
prices. This seems to have halted the gradual improvement in the energy
intensity of the US industry: after 2006 energy intensity performances remained
constant and actually started to slowly deteriorate in the last two years
considered.
There appear no significant divergences
in the production structure between the two regions which can explain the
marked difference in energy intensity performance between EU and US industry. First, the general picture of the EU-US energy intensity
divergence also emerges when looking at various branches within manufacturing
industry (Graph I.2.12).
Second, in terms of contribution to GDP,
the European manufacturing sector is still larger than its US counterpart,
although the difference seems to have become smaller during the decade.
A similar convergence can be observed in
the energy intensive industry sector, whose GDP share has become smaller in the
EU than in the US but the difference in size seems to slightly widen only in
2011. 
 Graph I.2.11:  Share of some Energy Intensive Sectors (EIS) and share of Manufacturing in GDP - 2001-2012 
 Note: For the EU-27 energy intensive sectors include Fabricated metal products, Basic metal, Other non-metallic mineral products, Chemicals and chemical products, Coke and refined petroleum products, Paper and paper products, Mining and quarrying. For the USA, energy intensive sectors include Mining, Non-metallic mineral products, Paper products, Petroleum and coal products, Chemical products, Primary metals, Fabricated metal products. Source: Own calculations on Eurostat and US Bureau of Economic Analysis. 
The better performance of the EU's
manufacturing industry in terms of energy intensity has therefore happened in
the context of comparable overall production structures. Nonetheless, a certain
process of restructuring away from energy intensive sectors is observed in the
EU from 2005 (see the shift-shares analysis carried out in chapter 1). Graph I.2.11 corroborates this insight as it shows
that it is around 2005 that the share of energy intensive sectors in the US
exceeds that of the EU. However as shown in chapter 1 and Appendix 3 this is
largely driven by the increased importance of the refinery sector in the US
economy. 
This suggests that while European business
as a whole has been able to compensate for the higher energy prices through
improvements in energy intensity and possibly also through other
non-energy-related efficiency gains - facilitating the substitution of energy
with other production factors ([34]) - the energy intensive sectors have been relatively more strongly
affected. Yet the restructuring started already before the development of shale
gas and might therefore accelerate as the energy price gap widens. .
 Graph I.2.12:  Energy intensity of industry, selected sectors 
 Note: Final energy consumption in Ktoe per billion EUR, reference year 2005. Paper Industry for the EU includes Paper and paper products and Printing and reproduction of recorded media. For the US: Paper; Printing and Related support Chemical Industry for the EU includes Chemicals and chemical products and Basic pharmaceutical products and pharmaceutical preparations. For the US: Chemicals, Pharmaceuticals and Medicines. Non-metallic minerals for the EU includes Other non-metallic mineral products. For the US: Non-metallic Mineral Products. Basic Metals for the EU includes Basic metals. For the US: Primary Metals. Source: Eurostat, Energy Information Administration and US Bureau of Economic Analysis. 
2.5.      Trade
2.5.1.   Energy trade
The most evident effect on trade of the
US shale gas development has been the sizeable reduction of the US energy trade
deficit over the past few years. While for the
first eight years of the decade the energy trade deficits of EU and US
deteriorated in very similar fashion, after 2008 they developed quite
differently. 
The US energy trade deficit improved much
more in 2009 than the EU counterpart, while in later years it has deteriorated
much less pronouncedly, also in part because of its higher share of oil in its
energy imports that experienced larger volatility than the other energy
carriers. This has resulted in a wider gap in GDP terms between the US and EU
energy trade deficit. 
 Graph I.2.13:  Energy trade balances as % of GDP, total and per energy source - 2001-2011, EU-27 and US 
 Source: Commission Services on Eurostat and US Bureau of Economic Analysis. 
The drive to self-sufficiency in domestic
gas consumption and the related increase in coal exports which took place after
2008 help to explain this trend. In contrast, the EU became more dependent on
gas and coal. Graph I.2.13 illustrates these divergent
developments.
While the US gas trade has tended to
move closer to balance, the EU's gas trade deficit has actually increased. This trend has its origins well before 2008 but the gap in GDP
terms has widened considerably after 2008. The difference is likely to become
bigger when the US starts to export shale gas; this tendency could be countered
if the EU could rely more on domestically produced gas ([35]).
The significantly larger trade surplus for
coal in GDP terms from 2008 onwards reflects the US excess coal supply. As a
consequence, the relative price of coal vis-à-vis that of other primary energy
sources has fallen, triggering a process of partial substitution in the
European energy mix. 
Finally, with the current near balance in
both coal and gas trade, the US energy trade balance appears now basically
driven by the developments in the oil trade balance. The US oil trade deficit
has also been significantly reduced compared to its 2008 levels, indicating,
next to a fall in oil prices from a peak level, a shift in US energy use away
from oil towards gas (and renewables). In contrast, the EU energy trade balance
is driven by the trends in all three main tradable primary energy sources (oil,
gas and coal) and for each of them the deficit has worsened over the past ten
years considered, although more for oil and gas than for coal. The increase in
import dependency may expose the EU as a whole more to supply disruptions and
geopolitical risks, and to the related danger of increased price volatility. 
2.5.2.   Trade of goods
The developments in the energy trade
deficit should be seen in the context of the trends in the overall current
account balance. 
As it is well-known, the US has had a
persistent large current account deficit, for a part fuelled by the global
finance trends before the onset of the current financial and economic
recession. However, it is of note that already in the years just before the
outbreak of the financial crisis, the current account deficit had already started
to fall.  
 Graph I.2.14:  Current account balance, external balance for goods and bilateral balance for goods, 2001-201 - US and EU-27 
 Source: Commission Services based on Eurostat and US Bureau of Economic Analysis. 
The sharp reduction in this deficit between
2008 and 2009 appears to have a close connection with a sharp reduction in
domestic demand due to the onset of the economic crisis, as the goods trade
balance moves in tandem ([36]). However
after 2008, the goods trade deficit widens again, while the current account
deficit more or less stabilises on a level close to 3%.
At the same time the US energy trade
deficit has been reduced by about 1%-point of GDP,
this suggests that the increasing self-reliance in energy has helped the US to
get the current account more in balance. From this perspective, the US energy
sector has helped to address one of the more prominent global imbalances.
Interestingly, the EU-US goods balance
has shown a persistent surplus for the EU without any clear sign of
deterioration. Since the direct trade in goods
constitutes one of the key indicators for assessing (changes in)
competitiveness, one can tentatively conclude that the widening EU-US energy
price gap has so far not visibly affected the EU industry's market performance
vis-a-vis their US counterpart, at least on the EU and US markets. This can for
some part be explained by a better overall energy intensity performance in the
EU; the relatively large share of services in US exports which are less
energy-intensive than goods; the success of EU industry to realise cost
improvements through a heavier reliance on global supply chains ([37]); the "income effect" of cheaper energy on US consumers'
demand and for parts of the EU industry the cost benefit of cheaper US
intermediary goods. 
2.6.      Conclusions 
The findings of this chapter point to the
importance to carefully check the on-going trends and to put them into
perspective. The surge in US shale gas since 2007/2008 has led to marked
changes in US energy sector and energy trade balance, as gas has replaced coal
as dominant energy source in domestic production and the US energy trade
deficit in GDP terms has been reduced since the dip of 2008. This improved
performance of domestic US energy production and subsequent price differential
has occurred in absence of any opening up of export of US shale gas to the rest
of the world. Any such opening might limit future price differentials with the
EU. 
However, the investigated energy and trade
data do not reveal any major shift in the EU-US goods trade balance nor
significant divergent trends in the overall production structure of
manufacturing industry which can be directly ascribed to the shale gas
revolution. 
In contrast to the US, the EU economy and
industry have ever more heavily relied on energy imports, including gas
imports, but the data strongly suggest that the EU industry has so far also
responded to the persistently higher energy prices through the realisation of
significant improvements in the use of energy as reflected in a secular decline
in its energy intensity. By contrast, the US industry's energy intensity seems
to have risen with the surge in consumption of the cheap shale gas. This
divergence in EU-US energy intensity trends has partially helped  EU industry
to offset the energy price differential with the US and hence might have acted
as a buffer to the US shale gas surge. The EU has been somewhat restructuring
away from energy intensive sectors while maintaining an overall share of
manufacturing in value added above that of the US. Moreover, although not
demonstrated by the data presented in this chapter, one may surmise that cheaper
US intermediate goods and the (future) availability of cheap (US) shale gas on
the EU gas markets ([38]) can act as
further buffers to the shale gas shock ([39]). The price gap with the EU may also be reduced should the shale
gas producers be mandated to fully internalize external costs, on the
environment and human health, as it is not currently the case. 
However, this should not imply complacency
on the widening EU-US energy price gap. Firstly because the impacts may become
visible only after some delay and they may have in fact been obscured by the
divergence in timing of the economic crisis between EU and US.  Finally and
importantly, energy efficiency improvements may slow down in the EU and speed
up in US due to diminishing low cost options; but that would seem to require
increased policy effort. Similarly the magnitude of opportunities to increase
the foreign part of the EU industry’s supply chain remains unclear. 
Consequently, high energy prices for EU
industries should remain a policy concern, even more so in case the EU-US
energy price gap will continue to increase. For this reason, EU energy and
carbon policies have to be  cost efficient while maintaining their ambition.
Hence, on-going efforts to improve the efficiency of energy markets in the EU
should be vigorously pursued, namely to diversify the energy mix, including a
shift to multiple gas suppliers, increase the effective competition on the
global and EU energy markets, and by integrating the various national energy
markets in the EU into regional or EU energy markets. 
Finally, since steady energy intensity
improvements have proven to be one of the best asset of the EU industry to
maintain their competitiveness, the EU should maintain and perhaps intensify
its policy to bolster the EU industry's energy efficiency efforts.
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2012; (iii) Issue 5: 4th quarter 2012.
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2013.
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Milana (1995), "A comparison of cost structures in Japan and US using
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Unit Energy Costs: description of the data
The sectoral data on quantities of energy
used, energy costs and value added in constant prices are collected from the
World Input Output Database (WIOD) ([40]). The advantage of using this source is that it provides a large,
consistent dataset of globally comparable sector-level data for a relatively
long period of time 1995-2011, while its drawbacks are that it does not include
the developments of the most recent years and data for some countries and sectors
for 2009-2011 are estimated. In addition data limitations do not enable to
compute energy intensity and real energy prices for the years 2010 and 2011.
Data from WIOD allows the calculation of Real Unit Energy Costs for 27 EU
Member States plus 13 other countries. These indicators are computed for the
manufacturing sector and its 14 subsectors on the basis of the Nace Rev.1.
nomenclature. The 14 subsectors of manufacturing are the following: food,
beverages and tobacco; textile and textile products; leather and footwear; wood
and products of wood and cork; pulp, paper, printing and publishing; coke,
refined petroleum and nuclear fuel; chemicals and chemical products; rubber and
plastics; other non-metallic mineral; basic metals and fabricated metal; machinery;
electrical and optical equipment; transport equipment; manufacturing NEC,
recycling. This is the most detailed sectoral breakdown available in the
database. It is worth noting that in certain cases these sectoral aggregates
could hide substantial variability in terms of lower subsectors. 
Data is taken from national Use Tables of
WIOD in purchasers' prices, because these prices reflect the total cost of
inputs payable by the sector, as opposed to basic prices, which exclude taxes
and margins (both of which can be substantial for energy products). Data from
WIOD was complemented with constant price value added are taken from Eurostat
for EU countries, from the OECD for the US and Japan and from the World
Development Indicators for China. This enables the calculation of Nominal Unit
Energy Costs, energy intensities and real (deflated) energy prices for these
countries and sectors. 
The analysis focuses only on direct energy
costs. These are defined as the costs incurred by companies to directly
purchase energy inputs including feedstock. The energy inputs considered here
are the sum of 4 products categories: i) coal and lignite; ii) peat crude
petroleum and natural gas, services incidental to oil and gas extraction
excluding surveying; iii) coke, refined petroleum products and nuclear fuels;
iv) electrical energy, gas, steam and hot water. The indirect energy costs are
not analysed in the present note. These are defined as the share of energy
embedded into the other production inputs used by the various sectors (for
instance the energy inputs contained in the chemicals used by textile
industry). Although admittedly the indirect energy costs could be significant
for certain sectors, data availability and methodological issues represent
important trade-offs that limit the usefulness of incorporating indirect costs
into the analysis.
The methodology of shift share analysis
The shift share analysis presented in the
paper is based on the following decomposition of the growth of RUEC between
period 0 and period T:
 within subsector effect 
 restructuring effect 
 interaction effect 
Where , i denotes
a given subsector of total manufacturing, mi,T­ denotes the share of
sector i in the value added of total manufacturing in period T,
and .
Source: Commission Services based on WIOD
database
 Graph I.A3.1:  Real Unit Costs manufacturing sector including vs. excluding coke, refined petrol & nuclear fuels 
 Source: Commission Services based on WIOD, ESTAT, OECD & World Development Indicators. 
 Graph I.A3.2:  Shift-share analysis for the manufacturing sector including vs. excluding coke, refined petrol & nuclear fuels 
 Source: Commission Services based on WIOD, ESTAT, OECD & World Development Indicators. 
 Graph I.A4.1:  US Energy domestic production by source, 2000-2011 
 Source: US Energy Information Administration, conversion from BnBtu to Mtoe (1 BnBtu= 2,51996E-05 Mtoe ) 
 Graph I.A4.2:  EU-27 Energy domestic production by source, 2000-2011 
 Source: DG ENERGY factsheet 
 Graph I.A4.3:  Electricity mix US, 2002-2011 
 Note: Due to statistics collection differences, the US measures its electricity mix in terms of net electricity generation while the EU uses the gross electricity generation. 2011 provisional data Source: Commission Services based on Eurostat data and Energy Information Administration of the US. 
 Graph I.A4.4:  Electricity mix EU-27, 2001-2010 
 Due to statistics collection differences, the US measures its electricity mix in terms of net electricity generation while the EU uses the gross electricity generation. Source: Commission Services based on Eurostat data and Energy Information Administration of the US. 
 Graph I.A4.5:  Household expenditures for energy products, 2003-2010 - EU-27 and US 
 Note: Convention factor - OECD Dataset: 4. PPPs and exchange rates. Source: Commission Services based on Eurostat and US Energy Information Administration. 
 Graph I.A4.6:  Electricity prices for industrial consumers and households for the European countries in the OECD and for the US 
 Source: Commission Services based on OECD Electricity Information (2012). 
 Graph I.A4.7:  Energy consumption of industry breakdown by sources - US 
 Source: Commission Services based on US Energy Information Administration 
 Graph I.A4.8:  Energy consumption of industry breakdown by sources, EU 
 Note: In order for the data to be comparable with the US, Industry includes also agriculture and fishing. Source: Commission Services based on Eurostat database. 
Part I has shown that, despite the good
performance of EU industries in terms of energy intensity, high energy prices
should remain a policy concern, even more so in case the EU-US energy price gap
will continue to increase. This is why it is important to investigate how
energy prices have been affected by policy developments. This part analyses
three important components of energy costs – electricity and natural gas retail
prices, and carbon prices. 
Electricity and natural gas are a
substantial part of energy costs; hence they have a significant impact on the
welfare of European citizens and on the competitiveness of industries. Over
recent years, EU electricity and gas markets have been fundamentally reshaped
by the significant energy and climate policy initiatives in the areas of market
opening, renewables penetration, climate change mitigation, and security of
supply. Chapter 1 explores the impact of these reforms on end-user electricity
and gas prices for households and industries, while controlling for other
factors such as fossil fuels.
The carbon price represents a cost
component of electricity prices and is expected to play a crucial role in the
transition to low carbon economies. However, it fails to provide a strong price
signal for consumption behaviour and for investments in clean production
technologies. The empirical estimate carried out in chapter 2 analyses the main
drivers of carbon prices, assessing the role of economic and energy factors.
1.1.      Introduction 
The last two decades have seen a number of
significant changes in EU energy policy, designed to tackle the fundamental
challenge of sustaining economic competitiveness amidst rising global
competition for scarce natural resources and the risks associated with climate
change ([41]). Several
major EU policy initiatives in the areas of market opening and integration,
renewables policy and climate change mitigation have contributed to reshaping
energy markets. 
Since 1996, the EU has engaged in a process
of market opening in network industries, including in the energy markets. In
2009, the process made a huge leap forward with the adoption of the Third
Energy Package, which aims to create a single electricity and gas market. In
parallel, the Climate and Energy package adopted in 2009 has introduced a
policy framework to reach the three "20" targets: achieving a 20%
reduction in EU-wide greenhouse gas emissions, a 20 % share of energy from
renewable sources in overall EU energy consumption and a 20% decrease in
primary energy use by 2020 compared to a pre-defined baseline. 
While these measures may be aimed primarily
at fulfilling the competitiveness, security of supply, and sustainability
objectives of EU energy policy, what ultimately matters for consumers is the
retail price they will have to pay for their gas and electricity. These
consumers are not only limited to households; they are also industries
including SMEs. Thus any increase in retail prices has an impact both on
welfare of households and on the competitiveness of the European economy ([42]). In particular, between 2004 and 2011, retail electricity and gas
prices have increased considerably by 65% and 42% respectively compared to 18%
for inflation ([43]) over the
same period.
The objective of this chapter is to assess
the impact of market opening reforms, and energy and climate policies, on
retail gas and electricity prices in the EU 27 over the period 2004 – 2011.
Section 2 presents price evolution over the two past decades. Section 3
describes the key policy drivers of energy prices in the EU. Then data and
methodology are discussed, and results from the empirical analysis are
presented. Lastly, the main conclusions and policy implications based on these
results are outlined.
1.2.      Energy
price developments in the EU
1.2.1.   Electricity Market
Retail prices in the electricity sector
have risen much more than wholesale prices over the period 2004-2011 (Graph II.1.1). In the electricity market, both
industrial and household end-user prices ([44]) have followed an increasing trend since 2004, rising by more than
50% on average across Member States, compared to a 23% increase in average
wholesale prices over the same period. The latter has shown greater fluctuation
compared to retail prices, which have been rising continuously. Between 2008
and 2009, the average wholesale price fell by over a third, reflecting the
negative demand shock following the economic and financial crisis and the
increasing penetration of renewable technologies.
The largest percentage increase among
the components of end-user electricity prices was observed in taxes and levies (Graph II.1.2). This fact may partly explain the
observation that retail prices in both consumer segments have risen more than
wholesale prices. Over the period 2008-2011, average electricity taxes and
levies in the EU have risen by 43% and 67% in households and industrial
customers respectively ([45]), whereas
the equivalent changes in average energy and supply costs were 3% and -2% and
in network cost 17% and 21% ([46]). 
Retail electricity prices have also
roughly followed the trend of international oil prices over the first half of
the sample period, but the co-movement has diminished since 2008. This pattern observed post-2008 may be due to the presence of price
regulation which may have become more responsive to oil price movements from
2008 onwards, in order to smooth electricity price developments in the face of
increased crude oil price volatility ([47]). This is in contrast to wholesale electricity prices where, as
expected, the co-movement with international oil prices is much closer and more
evident over the period.
 Graph II.1.1:   EU-27 Average domestic and industrial retail electricity price, wholesale price and crude oil price evolution 2004-2011 
 (1) The Consumption bands used were DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for Industry (500 MWh < Consumption < 2000 MWh), wholesale prices are average spot prices from different European power exchanges and pools. Source: Eurostat. 
 Graph II.1.2:   EU average change per electricity tariff component between 2008 and 2011 
 (1) The Consumption bands used were DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for Industry (500 MWh < Consumption < 2000 MWh), wholesale prices are average spot prices from different European exchanges and pools. Source: Eurostat. 
These aggregate figures mask large
differences in the experiences of individual Member States. The evolution of
wholesale and end-user prices over the sample period have been highly
heterogeneous across Member States. In Poland, the country experiencing the
largest wholesale price increase in percentage terms in 2011 compared to 2005,
the wholesale market weathered a price hike of around 82%. In the Netherlands,
the United Kingdom and Spain however, wholesale prices fell over the same
period, with Spain experiencing a decrease of approximately 7%. On an annual
basis, the average rate of change in wholesale prices has ranged from 24% in
Slovenia to -6% in Estonia (Graph II.1.3). These differences in wholesale
price dynamics may be explained by the vast heterogeneity in the maturity of
wholesale markets across the EU, the fuel production mix that affects the
degree of sensitivity of domestic electricity markets to external energy
shocks, as well as the degree of interconnection with neighbouring countries. 
Retail price evolution has been equally
varied. Malta, Cyprus and Latvia had the largest
increases in end-user prices in both household and the industrial sector with
prices more than doubling on average, while the Netherlands was the only Member
State to experience a fall in prices in both markets over the same period. These
rankings were mirrored to some extent in the relative performance of these
countries in the various components of the end-user electricity price between
2008 and 2011. Latvia had the largest percentage hike in taxes and levies, and
relatively large increases in energy and supply and network costs, in the
households' segment ([48]). Similarly,
Malta had the third highest percentage hike in energy and supply costs in the
industrial segment. At the other end, Netherlands had one of the largest
percentage decreases in taxes and levies and energy and supply costs in the
industrial sector, and relatively low changes in the household price
components. The average annual rate of change in industrial end user prices
over 2004-2011 has ranged from 17% in Malta to -0.15% in the Netherlands. The
equivalent figures for household consumers were 15% and -0.03%, again in Malta
and the Netherlands respectively ([49]).
 Graph II.1.3:   Retail and wholesale electricity average price changes by Member State 2004-2011 
 Note:The Consumption bands used were DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for Industry (500 MWh < Consumption < 2000 MWh) Source: Eurostat. 
Given these diverging paces and
trajectories, there has been significant heterogeneity in end-user price levels
across Member States over the sample period ([50]). Certain countries, such as Italy and
Germany, have had relatively high average retail prices in both their household
and industrial segments over the years 2004 and 2011. Similarly, others such as
Estonia and Bulgaria have had the lowest retail prices across the EU 27 in both
markets. 
Moreover, household end-user prices have
been much more varied than industrial prices. For
example, in households the average end-user price in the five countries with
the highest retail prices over the sample period was almost 150% above the
average end-user price in the bottom five countries, whereas the equivalent
figure was around 100% in the industrial segment. An important observation here
is that taxes and levies constitute a much larger share in household end-user
prices than in industries', whereas energy and supply costs are the dominant
drivers of industrial end-user prices. More precisely, the respective EU
average shares of energy and supply costs and taxes and levies in end-user
prices over the period 2007-2011 were 44% and 22% in the households, whereas
the equivalent figures in the industrial sector were 66% and 6%. The
Commission's recent Communication on the internal energy market lends support
to the claim that a large portion of variation in retail prices between Member
States are driven by taxes and levies, as these elements, along with network costs,
"fall within the remit of the national legislations in each Member
State" ([51]).
 Graph II.1.4:   Retail electricity prices - Households and Industry 
 Note: The Consumption bands used were DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for Industry (500 MWh < Consumption < 2000 MWh) Source: Eurostat. 
All countries had household retail
prices that were higher on average than industrial prices, with the exceptions
of Greece, Malta and Romania. However, the absolute size of the price
difference was highly dispersed across Member States. While in countries like Romania the price for households was around
90% of the industrial price, the respective ratio was 240% in Denmark. Graph II.1.5 illustrates individual Member States'
average industrial-household retail price ratios relative to the EU average. It
gives a good indication of those countries where the relative industrial price
was much higher than the EU average, and those countries where it was
significantly lower. These outliers may be explained by active state
intervention to pursue different objectives in industrial and social policy.
For example, some Member States may allocate the cost of renewables support
unevenly across different consumer groups. Denmark and Sweden stand out as
countries where the industrial price relative to households' was much lower on
average than for the EU-27 as a whole, at 54% and 70% of the EU average respectively.
This suggests that industries in these countries might enjoy a relatively more
favourable environment and lower costs than on average. Perhaps expectedly,
Denmark and Sweden also had some of the highest shares of taxes and levies and
the lowest shares of energy and supply costs in household end-user prices
across Member States, while Sweden also had one of the lowest shares of taxes
and levies in industrial end-user prices between the years 2007 and 2011.
Romania, Malta and Greece, on the other hand, had a higher relative industrial
price compared to the EU average, with the average at around 137 % of the EU
27. 
 Graph II.1.5:   Average ratio of Industrial to Household electricity prices, relative to the EU-27 average, 2004-2011 
 Note: The Consumption bands used were DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for Industry (500 MWh < Consumption < 2000 MWh). The measure is calculated as the sample period average ratio of industrial to household retail electricity prices, for a given Member State, divided by the EU-27 average ratio of industrial to household prices over the same period. Given that a "normal" level of relative industrial prices, in the absence of any cross subsidisation, is difficult to identify, it may be assumed that the EU average is an imperfect proxy of a "normal" price ratio and the best available benchmark to determine the likely direction and extent of cross subsidisation in individual Member States. When the ratio is above one, relative industrial prices are above the EU average, which may be taken as an indicator of cross-subsidisation from industries to households. Source: Commission Services based on Eurostat database. 
1.2.2.   Natural Gas Market
Both industrial and household natural
gas prices have been rising over the sample period,
aside from a decreasing trend between 2008 and 2009 (Graph II.1.6). In percentage terms, natural
gas ([52]) prices have
risen more than electricity prices over the sample period, and have been more
volatile. Average household gas prices have increased by 77% between 2004 and
2011 (against 50% for electricity), whereas average industrial prices have more
than doubled (against a 53% increase in industrial electricity prices). The
diverging paces of retail price growth in the two consumer segments is
reflected in the average industrial-household price ratio, which has risen by 14%
over the period, highlighting the relatively faster growth in industrial
prices. More precisely, industrial gas prices rose at an average annual rate of
11 %, compared to a 9 % average annual change in household prices. 
 Graph II.1.6:   EU-27 average domestic and industrial retail natural gas price and crude oil price evolution 2004-2011 
 Note: The Consumption bands used were D2 for Households (20 GJ < Consumption < 200 GJ) and I3 for Industry (10 000 GJ < Consumption < 100 000 GJ Source: Eurostat. 
 Graph II.1.7:   Retail natural gas price evolution by Member State 2004-2011 
 Note: The Consumption bands used were D2 for Households (20 GJ < Consumption < 200 GJ) and I3 for Industry (10 000 GJ < Consumption < 100 000 GJ) Source: Eurostat. 
Retail natural gas prices also loosely
followed the trend of the Brent crude oil price between 2004 and 2011 (Graph II.1.6). This co-movement was much stronger
than in the case of electricity prices, explained by the still large share of
EU natural gas trade that is conducted via oil-indexed bilateral contracts. 
As with electricity prices, however,
cross country variations in the evolution of end-user natural gas prices are
evident. In households Hungary experienced the
highest overall percentage increase in natural gas prices over the sample
period, with a hike of around 90%, whereas Romania was the only Member State to
experience a fall in prices over the same period (by 17%). In the industrial
sector, the changes were more profound. Although all countries experienced a rise
in industrial prices over the sample period, the range of these increases in
percentage terms stretched from 126% in Denmark to 32% in Austria. 
 Graph II.1.8:   Retail natural gas prices - Households and Industry 
 Note: The Consumption bands used were D2 for Households (20 GJ < Consumption < 200 GJ) and I3 for Industry (10 000 GJ < Consumption < 100 000 GJ) Source: Eurostat. 
Moreover, not all countries displayed
similar price performances relative to other Member States across the two
consumer markets. Hungary, Denmark and Romania were
particularly distinct in this respect. While Denmark ranked at the top of the
sample in terms of industrial gas price increases, it had a relatively small
price increase in the household sector. The reverse was true for Hungary, which
had the highest period price rise in the household sector, but ranked below the
average in the industrial sector. Romania, which showed the only decrease in household
prices over the period, experienced a simultaneous above average increase in
industrial gas prices ([53]). Graph II.1.8 illustrates the annual average change
in household and industrial natural gas prices by Member State. Denmark and
Hungary, as expected, also had the largest annual price increases in the two
sectors.
There has also been notable
heterogeneity in the levels of end-users prices across Member States over the
sample period, with a slightly higher range of prices for the household sector
compared to industries ([54]). In the industrial segment, the
average end-user price in the five countries with the highest prices for 2004
was more than double the average among the five countries with the lowest
prices for the same year.
This gap shrunk marginally by 2011, where
the former figure was around 86% higher than the latter. For households, the
highest-priced five countries had end user prices that were on average 130%
higher than the lowest-priced group in 2004, with the equivalent figure falling
to around an 84% premium in 2011.  
The relative prices of households and
industries reveal significant outliers in certain Member States, implying the presence of some level of state intervention to
satisfy different distributional preferences in industrial and social policy.
Graph II.1.9 illustrates individual Member States'
sample period-average industrial-household retail price ratios, benchmarked
against the EU average ratio. This highlights those countries where the
relative industrial price was much higher than the EU average, and those
countries where it was significantly lower. Portugal and Spain stand out as
countries where the industrial price relative to households' was much lower on
average than for the EU-27 as a whole, at 69% and 72% of the EU average
respectively. Conversely, Romania and Hungary, had a higher relative industrial
price compared to the EU average, exceeding the average EU 27 level by almost
39 %.
 Graph II.1.9:   Average ratio of Industrial to Household natural gas prices, relative to the EU-27 average, 2004-2011 
 The Consumption bands used were D2 for Households (20 GJ < Consumption < 200 GJ) and I3 for Industry (10 000 GJ < Consumption < 100 000 GJ) The measure is calculated as the sample period average ratio of industrial to household retail natural gas prices, for a given Member State, divided by the EU 27 average ratio of industrial to household prices over the same period. Given that a "normal" level of relative industrial prices, in the absence of any cross subsidisation, is difficult to identify, it may be assumed that the EU average is an imperfect proxy of a 'normal' price ratio and the best available benchmark to determine the likely direction and extent of cross subsidisation in individual Member States. When the ratio is above one, relative industrial prices are above the EU average, which may be taken as an indicator of cross-subsidisation from industries to households. Source: Commission Services based on Eurostat database. 
In summary, end-user electricity and
natural gas prices have risen substantially in the majority of Member States
over the period 2004-2011. While electricity prices have evolved similarly for
both households and industries, natural gas prices have increased much more for
industries. Despite these common trends, a number of notable heterogeneities
exist between individual Member States, which may be explained by the national
energy mix, fragmented national policies including taxation, and other forms of
state intervention which is illustrated by the variation in relative levels and
relative evolutions of household and industrial prices across Member States. 
1.3.      The
policy determinants of energy prices at EU level
The period 2004-2011 has revealed some
interesting trends in the evolution of end-user energy prices in the EU, which
took place in a changing EU climate and energy policy landscape. 
Since the 1990s, significant energy market
reforms and policy initiatives have been introduced in the EU. On the one hand,
the EU has launched a process of domestic and cross-border market opening of
electricity and gas markets. On the other hand, the Energy and Climate change
package adopted in 2009 significantly reoriented the energy production and
consumption towards low carbon energy sources. This section aims to assess
their potential impacts on recent end user price developments in the EU on the
basis of economic rationale ([55]). 
1.3.1.   Market Opening in
Electricity and Gas 
The Commission's Third Energy Package of
2009 introduced a set of Directives and Regulations to further consolidate and
open up the Internal Energy Market. While broadly adopted, these reforms have
been implemented to varying degrees across Member States. The Commission's
Communication on the Internal Energy Market in 2011 expressed concern about
delayed implementation and the tendency toward "inward-looking or
nationally inspired policies" in some Member States ([56]). These factors are hindering the achievement of full
market-opening and effective competition. In 2011, more than 80% of power
generation in eight Member States was still controlled by the historic
incumbent, while in the natural gas market, the market share of the largest
retailer was more than 50% in thirteen Member States and over 80% in eight of
these cases. The Commission is currently undertaking a number of actions to
tackle the non-transposition of the Package's reforms, including infringement
procedures against Member States for incomplete or improper
implementation ([57]), in view of
its target of completing the internal energy market by 2014.
Market functioning is one of the key
determinants of prices in the energy markets, and the main objective of market
opening is to ensure cost reflective energy prices and, where possible, to
minimise the cost of energy supply. The natural gas and electricity markets, as
with network industries in general, entail a unique combination of competitive
activity, namely in generation and supply, and natural monopoly features in
transmission and distribution. This has resulted in varying drivers of price
formation along the supply chain - the competitive market vs. regulation –
which are all combined in the final end-user price. 
To identify the precise segment of price
formation where market opening and competition are expected to have their
largest impact, it is useful to start by distinguishing between the different
components of end-user energy prices: energy and supply costs, network costs,
and taxes and levies. The energy and supply component is determined by
production, importation or generation costs, as well as market power and supply
and demand dynamics in the wholesale and retail markets. Network costs entail
the tariffs paid by suppliers to network operators for the use of transmission
and distribution infrastructure. In a properly regulated system, these costs
can be expected to take account of long term infrastructure maintenance and
supply costs to give operators an incentive to make necessary long term
investments. Finally, taxes and levies entail any state intervention to pursue
a certain distribution of energy and supply costs, or to incentivise certain
kinds of market (investment) behaviour.
This process of market opening in the
wholesale and retail markets should gradually lessen the influence of market
power in driving the energy and supply component of energy prices. That segment
of end-user price formation has become increasingly driven by competitive
pricing, generation cost fundamentals, market liquidity and supply and demand
dynamics. Moreover, the independent regulation of TSOs and DSOs that form a key
part of the competitive model broadly adopted should help ensure that network
costs provide sufficient incentives for long term infrastructure investment,
whilst ensuring non-discriminatory access to the networks.  
The main direct benefits to be expected
from reforms promoting competition include:
- Lower wholesale prices from higher
competition among domestic generators, resulting from reforms such as the
unbundling of TSOs and third party access to transmission networks: competition
puts downward pressure on the profit margins of these players and provides an
incentive to reduce costs. 
- Lower end user prices from greater
competition among retailers, through retail market opening legislation and the
unbundling of DSOs from supply activities: competition puts downward pressure
on retail price mark-ups above the wholesale price, as retailers compete for
consumers that are eligible and enabled to choose their own suppliers. 
- Price convergence from increased
electricity trade: reform facilitating cross-border trade in electricity and
gas increase price competition from external generators and suppliers,
providing a further incentive for inefficient incumbent domestic players to cut
costs and lower prices. 
- More cost-effective achievement of the
other two objectives of EU energy policy, security of supply and
sustainability: security of supply will be supported by more diversified energy
sources, and any generation cost savings from RES-E deployment will only be
passed onto consumers in a competitive wholesale and retail environment. 
Effective competition in production and
supply, along with strong cross-border interconnections between neighbouring
Member States and efficient regulation of the monopoly network companies,
should mean that end-user prices can only vary significantly to the extent that
there are genuine differences in the cost of transmission, distribution and
supply. Otherwise, arbitrage by consumers and wholesale traders would
eventually force suppliers to equalise their prices in order to remain
competitive. It is important to note, however, that these effects of market
opening on energy prices can only be expected to hold in the absence of market
failures and distortive price regulation ([58]). A traditional reason for government regulation of energy prices
has been to prevent monopoly producers and suppliers from pricing substantially
above long run marginal cost (LRMC) ([59]). Effective competition, however, removes the need for such
intervention. The continuation of price regulation following market opening, to
subsidise certain segments of customers for political reasons, can therefore be
distortive ([60]). There is,
however, a case for subsidising electricity consumption for vulnerable
consumers on welfare and social grounds. 
A price subsidy is present when the price
is held below the marginal cost of supply, which indicates the
economically-efficient level of pricing. When prices are held above marginal
costs, there is over-pricing, and the surplus may go toward monopoly profits or
to cross-subsidise other segments of the market. In fully liberalised markets,
with long run marginal cost pricing, retail prices for industrial customers
would be lower than for households. Supply costs to industry are much lower, as
electricity is supplied at higher voltages which permit economies of scale.
Moreover, capacity costs are also lower, as industrial customers tend to have
flatter load profiles than households ([61]). According to the Energy Charter Secretariat (2003), electricity
prices are very close to long run marginal costs in most Western European
countries, where industrial prices are on average 50% of household prices. This
is much lower than the EU-wide average ratio of 75% observed in the stylised
facts, but it may give a rough indication of the efficient ratio of industrial
to household prices.
Retail prices are still regulated in some
countries and they are often held below production cost. In particular, when
markets are liberalised and price regulation is lifted in parallel, a
'catching-up' effect may be observed: prices may initially rise following
market liberalisation if they were previously held below costs under price
regulation. Price adjustment towards the level of long run marginal cost could
have the added benefit of providing the right investment signals to producers,
to invest in new capital and infrastructure where capacity is constrained,
especially in the lower marginal cost generation technologies. In the longer
term however, once this initial adjustment is achieved, the expected negative
price effect from market liberalisation are likely to be observed. 
1.3.2.   Achieving a low carbon
economy
The Climate and Energy Package of 2009,
combined with the Energy Efficiency Directive, has provided a common framework
and a set of targets both at the EU and Member State level to accelerate the
shift to a low carbon economy. The three headline targets of the 2009 Package
are:
- A 20% reduction in total EU greenhouse
gas emissions from 1990 levels by 2020. This entails an EU-level 21% reduction
from 2005 levels in emissions from ETS sectors, and country-specific reduction
targets for non-ETS sectors under the Effort Sharing Decision amounting to 10%
reductions compared to 2005.
- A 20% share of renewable energy sources
in gross final consumption of energy by 2020.
- A 20% improvement in the EU's energy
efficiency.
The EU ETS has been established as the main
market-based instrument to facilitate the achievements of these targets in the
energy supply and industry sectors, but it has also been supplemented by
national policies facilitating the achievement of the emission target in the
other sectors not covered by the ETS, supporting the development and deployment
of renewable energy sources and measures to improve energy efficiency. Recent
assessments show that the EU is on track to meet the climate and renewables
targets by 2020, while the indicative efficiency target might not be fully
achieved even with the recently adopted Energy Efficiency Directive. However,
the potential impact of these policies on energy costs in the EU has become an
issue of concern.
1.3.2.1.  EU Climate change policy:
the Emission Trading Scheme (ETS)
Since 2005, the EU ETS has been used as a
market-based instrument which aims to internalise the external costs of GHG
emissions through a cap and trade system. The amount of emissions originating
in the energy-intensive and power industries has seen a rapid decrease since
2008. This coincided with a steep fall in the carbon price over 2008-2009;
since then, the carbon price has decreased further.
The ETS gives flexibility to operators on
how to meet their compliance obligations, and will therefore incentivise them
to reach the cap at the least cost across the EU. Independently of other
measures, an emissions trading scheme (ETS) such as the EU ETS can be expected
to raise GHG emission costs for conventional fossil fuel generators. As long as
these plants set the wholesale electricity price, this would raise the
wholesale and ultimately the retail electricity prices. This increases the
incentive to invest in renewable energy and energy efficiency measures, in
particular those that are most cost-effective. As it also increases wholesale
electricity prices, the ETS also incentivises sufficient investment in conventional
generation if the cost is passed on (in particular those which are less
carbon-intensive), which will continue to be necessary for a secure supply of
energy.  
1.3.2.2.  Renewables policy
The binding targets set by the Renewables
Directive 2009/28/EC for 2020 have supported the growth of renewable energy
sources (RES-E) in electricity generation. The combined share of wind, solar
and photovoltaic energy in electricity generation has been rising continuously
over the sample period, with an increase in the average growth rate since 2010.
This is true both on average and in a large majority of Member States ([62]). 
The intermittent nature of availability
along with the high capital investment cost of renewable energy technologies
make them under the prevailing market conditions in the EU less competitive
than the conventional power units. As a result, the majority of RES-E
generation beyond pumped storage hydro units is supported by public support
schemes, most of which are financed via a special levy imposed on consumers,
which are subsequently claimed to raise the retail electricity price ([63]). Moreover, the intermittency of renewables production, and the
consequent fixed and maintenance costs for back-up capacity, as well as the
need for higher investments in networks infrastructure, entail an additional
cost to the end-consumer for ancillary services and networks use.
However, there is one possible way in which
RES-E could have the opposite effect on the retail electricity price,
independently of support schemes. As renewable energy is characterised by
negligible marginal costs relative to conventional fossil fuel technologies,
high levels of RES-E penetration would drive the conventional thermal plants
with higher marginal costs out of the market. Given sufficient competition at
the wholesale level, this should lower the wholesale electricity price, which
is a significant component of retail tariffs ([64]). In addition, when the development of renewables is combined with
an emission trading scheme (ETS), higher RES substitution of conventional
fossil fuel generation technologies would lower the demand for ETS allowances
in the generation sector, which would lower the price of these allowances. This
would reduce costs for conventional electricity generators and, hence the
wholesale electricity price (Saenz de Miera et al. 2008) ([65]). 
What is fundamental in these arguments is
which impact renewables will have on retail prices. Generally, it seems that
the wholesale price effects on retail prices have been limited so far and the
RES-E production increase the overall cost of electricity supply to end users.
Hence, under the current pricing regimes for RES-E production and the low
levels of RES-E penetration, the wholesale market dynamics may not compensate
for the investment cost associated with the RES-E promotion that most
categories of electricity consumers tend to pay. 
1.3.3.   Security of supply 
Security of supply has been one of the main
objectives of EU energy policies. It has several dimensions; import dependence
and diversification constitute two important elements ([66]). Threats to energy security of supply, among others, "include
the reliance on imported and insufficiently diversified energy sources, the
political instability of several energy-producing and transit countries, (and)
global competition over energy sources" ([67]). 
A country’s import dependence is measured
as the share of its net imports in total final inland consumption. In the case
of natural gas, this measure has been highly volatile across the EU 27 on
average over the sample period, but this result is clearly driven by volatility
in a handful of countries. The import dependence of the majority of countries
has remained relatively stable across the sample period, as compared to the
mean trend. 
The higher the energy import dependence,
the greater the exposure to external supply disruptions, and sudden price
hikes. While this channel may be important for price changes in the short term,
the often higher cost of imported energy sources, such as natural gas, may be a
driver of long term prices. It is important to note, however, that the impact
of import dependency on end-user energy prices is likely to be highly mediated
by the degree of import diversification. The more diversified a country’s
import sources, the more room it will have to negotiate favourable contracts
and secure the cheapest sources. The price impact of import dependency is also
likely to be affected by the degree of competition amongst the energy importers
and suppliers, as this will determine the price mark-ups that local consumers
face, as well as the degree of diversification in the energy mix. 
Security of supply is an issue of
particular in the natural gas market, given the high level of gas import
dependency in the EU ([68]). The EU natural
gas market always has had, and will continue to have, a large international
dimension. It is estimated that even with complete integration in the internal
natural gas market, the introduction of meaningful competition among domestic
players, and the exploitation of potential domestic gas reserves, the EU will
continue to import a large share of its natural gas consumption from third
countries ([69]). Hence the
scope for lowering import dependency is limited. The natural gas market, given
its significant external dimension, thus differs from electricity in the sense
that national and EU policies on market liberalisation and the completion of
the internal market can only have a limited impact on prices. 
In electricity, the notion of security of
supply is very different. Given the non-storability of electricity,
transportation depends significantly on the distance and takes place only in
cases where this is economic viable in relation to energy losses. This factor
significantly reduces the international dimension to supply risks. What is more
important for secure electricity supplies is rather the proper management of
the grid and sufficient investment in generation and network infrastructure.
Security of supply in electricity is nevertheless ameliorated to some extent by
the on-going deployment of renewables. When governments decided to promote
renewables, this was not only with a focus on sustainability but also in view
of reducing import dependence, diversifying their energy sources, and, to a
lesser extent, promoting security of supply in electricity. 
1.4.      Assessing
the impact of energy and climate policies on electricity and natural gas prices
In this section, an empirical estimation of
the impact of energy and climate policies on final consumer prices - industry
and households - is presented. For this reason, the analysis focuses on retail
electricity and natural gas prices, which are part of the last stage of the
energy value chain and include four main components: 
- Network costs, which are the costs of
transporting electricity from the generators to customers via the transmission
and distribution networks. 
- Energy costs, which are mainly the costs
of purchasing energy from generators and suppliers on the wholesale level in
the electricity and natural gas market respectively.
- Support scheme costs and taxes, which
represent the costs of complying with specific targets of the EU energy legislation
and national taxation.
- Retail costs and margin, which includes
the costs of running the retail business.
1.4.1.   Drivers of electricity
prices
One of the main factors driving the cost of
electricity is the fuel used in generation activity. The results (Table II.1.3) indicate that the price of
electricity depends significantly on the structure of each market's fuel mix
for both consumer groups ([70]). In particular, a shift in the generation fuel mix from natural
gas ([71]) to coal
generation units would at least reduce retail prices, as this would entail a
substitution of peaking or inter-medium load generation units with lower
marginal cost base load units, though these units require higher capital
investment cost and produce higher GHG emissions.
On the contrary, the coefficient of RES
penetration in the electricity sector implies that a shift in the generation
fuel mix from natural gas to wind, solar-thermal and photovoltaic power will
increase the industrial and household end-user prices. This variable might be
considered as a proxy for the size of supporting schemes for RES production or
the RES levy used for the reimbursement of RES production, which are usually
paid by the consumers. However, this effect might not be applicable to specific
consumer categories that might be protected from the RES levies increase  ([72]). 
 Table II.1.1:     Results of Electricity price model 
 Note: *, **, *** Indicates significance at 10%, 5% and 1% confidence level. In (1) and (3), the models for households and industry are estimated including the explanatory variable 'Relative Price Deviation' which measures a country's industrial-households electricity price ratio relative to the EU average ratio in year t-1. This is taken to indicate the presence and extent of cross-subsidisation in retail tariffs, and therefore acts as a proxy for end user price regulation. In (2) and (4), this variable is excluded, and instead the models are estimated including an interaction term between a) a dummy variable that takes a value of one in cases where the 'Relative Price Ratio' is below one, and zero otherwise, and b) the share of renewables in electricity generation ('RES'). In cases where the 'Relative Price Deviation' is below one, we can assume that there is greater cross-subsidisation of industrial tariffs by households, relative to the EU average benchmark. In such cases, it may be reasonable to expect that households bear a greater share of the costs from renewables support schemes, and therefore that the expected overall positive effect of RES on end-user prices will be higher for households and lower for industries relative to the counterfactual with no cross-subsidy. Source: Commission Services. 
As expected, the measure of
cross-subsidization between industrial and household tariffs is statistically
significant and has the expected sign for both consumer groups. An increase in
the benchmarked industrial-household end user price ratio in the previous year
will raise industrial prices and lower household prices in the current period.
Whether such an increase in the benchmarked ratio constitutes a removal of
cross-subsidies depends on the initial level of the ratio. When this ratio is
below one, an increase towards one would imply a reduction in the
cross-subsidisation of industrial tariffs by households, whereas when it is
above one, an increase would entail a strengthening of the cross-subsidisation
of households by industrial consumers.  
When testing the interaction of
cross-subsidization from households to industries with renewables penetration,
the results are significant for the household segment and carry some
interesting implications. As predicted, where industrial tariffs are likely to
be cross-subsidised by household consumers (i.e. where the benchmarked ratio is
below 1), the deployment of renewables has a greater overall effect in raising
household prices relative to the case of no cross-subsidisation, implying that
households bear a larger share of the cost of renewable support schemes in
these cases. 
The prices of electricity are also broadly
aligned with the price of crude oil, the coefficient of which is positive and
statistically significant for both consumer groups – households and industry.
This linkage is stronger for industrial consumers than for households. Given
that crude oil is one of the most important global commodities, the fluctuation
in its price has a direct impact on the global economy. The crude oil price variation
directly influences sentiments and hence the volatility of markets worldwide,
especially those such as the electricity markets that depend on energy
commodities.
Conversely, as expected the carbon price
does not influence retail prices, due to relatively low levels observed over
the recent years.
Consistent with most of the existing
literature ([73]), the
results support the hypothesis that the higher the competition among suppliers,
the lower the expected end user prices. The retail market competition variables
are statistically significant and have the expected sign in both regressions. A
plausible explanation is that greater competition amongst suppliers in formerly
highly concentrated markets puts downward pressure on profit margins, and
provides an incentive to reduce costs and achieve higher levels of efficiency. 
Particularly, the retail competition effect is higher for households relative
to industrial consumers. Along the same lines, results indicate that unbundling
of distribution networks leads to lower electricity prices, perhaps due to the
removal of entry barriers and greater competition among retailers in formerly
vertically integrated activities. This effect is slightly larger for industries
and highly significant for both consumer types.
1.4.2.   Drivers of natural gas
prices
Measures related to security of supply such
as import dependency and diversification of imports are found to be highly
significant drivers of household natural gas prices. Given the relatively low
levels of domestic natural gas reserves in Europe and the limited
diversification in supply sources in the present scenario, this suggests
considerable scope for policy action in this area. A greater dependence on
natural gas imports leads to higher retail prices in both the industrial and
household markets, although the coefficient of the industrial customers found
not to be significant. In addition to this, more concentrated import sources of
supply also lead to higher prices for household consumers. It seems that
industries are relatively less exposed to price dynamics from the external
dimension of security of supply. This might be either a result of
cross-subsidization between the two consumer categories or a result of the
industrial customer's access to natural gas hubs where market to market
competition takes place.
In particular, the measure of the
cross-subsidization between the two consumer groups, as in the electricity
price model, is represented as the price ratio of industrial to residential
tariffs relative to the respective average price ratio of the EU-27. It
displays the expected sign and is significant for both industrial and
residential consumers. For households this effect is significantly greater than
for industrial customers. In other words, an increase in the relative price
ratio during the previous year will lead to an increase in industrial natural
gas prices and a decrease in household natural gas prices. As discussed in the
previous section, whether this is an adjustment in the right direction (i.e. a
removal of cross-subsidies) depends on the level of the benchmarked ratio. For
instance, this adjustment would entail a reduction in the cross-subsidisation
of industrial tariffs by households only in cases where this ratio is initially
below one.
The unbundling of TSO networks from gas
production and importation activity appears to have a highly significant but
small effect in lowering industrial prices, and although the direction of the
effect is the same and as expected for households, the price effect in this consumer
segment is insignificant. The unbundling of DSO network ownership from natural
gas retail activity, however, leads with high significance to lower prices for
both consumer groups. While the unbundling of DSO networks is currently not a
requirement under EU legislation, these results suggest that there may have
been significant competitive energy price benefits to such a policy in the
Member States that have pursued it. 
The measure of retail market competition
does not appear to be a significant determinant of prices for either consumer
type, whereas legal market opening, that is the capacity for all consumers to
choose their own natural gas supplier, has a significant effect in lowering
mainly industrial end-user prices. The effect of retail market opening is
insignificant for household consumers. A plausible interpretation of this
result may be the presence of informational constraints and switching costs
that might be larger for households with low consumption, and which may pose a
greater obstacle to switching suppliers and achieving any potential price
reductions despite the legal ability to do so. 
Although wholesale gas trading hubs are
still limited both in number and accessibility in the EU, it seems that access
to a spot trading hub does lead to lower natural gas prices for industries and
households. This is intuitive, as spot prices tend to be lower on average than
oil-indexed prices set in long-term contracts which have been the most
prevalent form of gas trade in the EU. Population density also has a large and
significant effect in lowering end-user prices for both consumer types, despite
a slightly larger effect on households. Again, this is to be expected, as more
dense populations are associated with lower unit network costs. 
 Table II.1.2:     Results of Natural gas price model 
 Note: *, **, *** Indicates significance at 10%, 5% and 1% confidence level Source: Commission Services. 
1.5.      Conclusions
Fossil fuels remain key drivers of
electricity and natural gas prices. Gas prices followed the evolution of crude
oil prices, as large part of EU gas trade is still based on oil-indexed
contracts, while electricity prices were strongly affected by the generation
fuel mix. Moreover, market opening and competition in the energy sectors can
have significant downward price effects for both household and industrial
consumers. In both markets, empirical estimates confirm that EU energy
policies, such as unbundling of networks and market opening decrease retail
prices. 
In the electricity market, whereas greater
market competition may have been successful in lowering end-user prices, and
thereby improving industrial competitiveness and consumer's welfare, the
empirical estimates indicate that the early penetration of not yet mature
renewable technologies may have the opposite effect. At levels of deployment
observed for these technologies between 2004 and 2011, the cost for retail
consumers as a whole from RES support schemes seems still to outweigh the merit
order effect whereby the wholesale price is lowered with RES deployment. As
indicated, some literature highlights that this may be different with higher
deployment levels of more mature technologies, e.g. wind. Moreover, in cases where
households were likely to be subsiding industrial tariffs, they were also
likely to bear a greater share of the cost of these support schemes, meaning
the overall positive price effect of RES deployment for households was higher
in such cases.
In the natural gas market, lowering import
dependency and improving security of supply can have greater downward price
effects, relative to market competition in the retail segment. Given the high
degree of import dependency within the EU, along with the high degree of
concentration ratio of importers, this result is not surprising and shows the
need to ensure diversification into alternative energy source and improve
energy efficiency. 
Finally, in cases where there is
cross-subsidisation of one consumer category by another, this plays a crucial
role in the following year's price formation through the asymmetric application
of taxes and levies. Although such state intervention may be motivated by
different distributional preferences, it nevertheless increases distortions and
negates the effectiveness of market opening in delivering competitive price
signals. This result is of high importance when considering the Commission's
insistence on phase-out timetables for regulated prices as part of Member
States' structural reforms.  
2.1.      Introduction
In 2007, the EU made a unilateral
commitment to reduce overall Greenhouse Gas Emissions (GHG) from its 27 Member
States by 20% compared to 1990 levels by 2020. This commitment is enshrined in
the Energy and Climate package agreed in late 2008. In addition, it is also one
of the headline targets of the Europe 2020 strategy, along with two other
energy targets –achieve 20% of share of renewables in final energy consumption
and increase energy efficiency by 20%. 
In order to achieve the transition to a low
carbon economy, the EU has always promoted the use of market based instruments.
In that spirit, the ETS (Emission Trading Scheme) is a market based instrument
that provides incentives to reduce GHG emissions at least cost. A cap on the
allowed carbon emissions set by EU legislation, alongside various other market
fundamentals, delivers a carbon price which is expected to provide the signal
to invest in clean technologies and to reduce carbon emissions. Moreover, the
carbon price is expected to translate into higher electricity final prices.
However, as seen previously, the carbon price did not have any impact on
electricity retail price, probably due to its low level observed since the
onset of the financial and economic crisis in late 2008. 
The low level of the carbon price has
triggered discussions among academia, think tanks, business and NGOs about the
design and the effectiveness of this instrument and its combination with other
energy target. In late 2012, the Commission published a first carbon market
report ([74]) assessing
the supply-demand balance in the European carbon market, with particular
consideration on issues arising due to some regulatory decisions in the
transition from phase II to phase III of the ETS (on top of the economic
crisis). The report found a large growing surplus of allowances that is likely
to weigh heavily on the carbon price and related incentives for many years to
come.
The objective of this chapter is to assess
the carbon price drivers and especially the interaction with other energy
policies that contribute to the greenhouse gas emissions reduction, such as the
deployment of renewables. Section 2 describes the carbon price developments
over the three phases of the Emissions Trading System (ETS) and analyse the
factors underlying the evolution of carbon emissions. Section 3 describes the
policy framework in which the carbon price has developed. Section 4 proposes an
empirical model to assess the carbon price drivers. Conclusions are presented
in section 5.
2.2.      Stylised
facts: evolution of carbon price
2.2.1.   Carbon price evolution
2005-2013
The evolution of the European carbon
price (European Union Allowances-EUA) has been influenced by the regulatory
design of the different phases ([75]). During the first phase of the
implementation of the ETS (2005-2007), the carbon price was below 10€/tCO2
until mid-2005 before rising to a peak at just above 30€/tCO2 in April 2006.
Then it fell sharply, followed by a small rebound during the second part of
2006. The publication of the first verified emissions data at the start of the
second quarter of 2006 has revealed the existence of a large surplus of
allowances in the first phase which was mostly due to the regulatory feature
chosen by most Member States, i.e. not to allow for banking allowances([76]). Such a surplus has led to an abrupt decrease in the carbon price
at the end of the first phase. The Commission's strict assessment of national
allocation plans defining inter alia the caps per Member State for the
second period has contributed to strengthening the price at the beginning of
the second phase. However, during this phase (2008-2012), the economic crisis
has contributed to lowering the number of CO2 emissions as well as output,
leading to a decrease in the carbon price. In early 2009 the carbon price
plunged to a level below 10€/tCO2. After some recovery in 2009-2010, the price
returned to single digits in 2011 mainly as a result of the slow recovery and
the correspondingly weak demand for allowances (along with the effect of
possible other factors such as energy policies and international offsets).
 Graph II.2.1:   Evolution of EUA Futures prices 
 Source: Bluenext, Bloomberg. 
The start of the third phase in 2013 was
characterised by one of the lowest levels of carbon prices since the beginning
of 2007. This low price level is to a large extent due to the regulatory change
in late 2012 with the initiation of large-scale auctioning of free allowances.
In 2013 on average some 12 to 15 million allowances are auctioned per
week ([77]). In
addition, this decreasing trend of prices can also be attributed to some extent
to the slow progress in discussions on back-loading. The Commission announced
its intention to propose back-loading in April 2012 and make formal proposals
in July 2012. The market has seemingly priced in a back-loading premium and the
slow progress in decision-making has reduced or eliminated this premium.
Finally, other factors such as international offsets and the transferred EUA
from phase II to phase III are also likely to have played a role in carbon
price evolution. 
2.2.2.   The evolution of other fuel
prices
The carbon price evolution follows the
pattern of other commodities prices except the short term variations of electricity
prices (EEX spot price). Electricity prices tend to
fluctuate in the short-term due to day-to-day and seasonal variations in supply
and demand, but in general, they revert toward a long-term equilibrium. Since
mid-2011, the carbon price has been decoupled from the other fuel prices, in
particular from natural gas and coal prices, as the difference of prices
between those two fuels shrank significantly. It is likely that the emergence
of the allowance surplus has made the carbon price more sensitive to market
expectations around regulatory action proposed to restore scarcity and market
confidence.
 Graph II.2.2:   Evolution of carbon price, fuels and electricity prices over 2008-2012 
 Source: Ecowin. 
Carbon prices have been less volatile
than electricity prices, but almost as volatile as most other primary energy
sources (Table II.2.1). This can be explained by the
differences in the underlying characteristics of supply, and in the behaviour
of demand in those different energy commodities. 
 Table II.2.1:     Descriptive statistics of EUA, fuels and electricity price changes (%), 2008-2012 
 Source: ECOWIN, Bloomberg. 
2.3.      Climate
and Energy policy developments 
2.3.1.   The ETS design
The ETS is a market-based instrument which
aims to internalise CO2 external cost through a cap and trade system. The
overall level of emissions allowed is capped and within that limit,
participants in the system can buy and sell allowances as they require. The cap
on the total number of allowances creates scarcity in the market, allowing the
market to set the equilibrium price. The market price of allowances would
correspond to the equalisation of marginal abatement costs of buyers and
sellers. 
The ETS is linked to other parts of the
world through project based mechanisms leading to a reduction of emissions.
Industrial installations can meet part of their emission reductions with Kyoto
offsets – Certified Emissions Reductions (CER) and Emission Reduction Units
(ERU). This mechanism gives some flexibility to operators while allowing a transfer
of low carbon technologies to foreign countries. At the same time the use of
international credits allows companies to collectively emit above the cap.
A lot of experience has been gained which
contributed to the improvement of the regulatory practice and design over the
different phases. In particular, the first phase 2005-2007 was a learning
process. Member States were responsible for drawing up National Allocation
Plans (NAPs), by specifying how many allowances they intend to allocate, and
how the total will be distributed between the covered installations, while
respecting the criteria of Annex III of the Directive on ETS (2003/87/EC). To
this end, Member States submitted National Allocation Plans to the Commission,
while the Commission was mandated to assess these plans and could reject them
if the Annex III criteria were considered to be violated. In the second phase
(2008-2012), Member States were obliged to show that their planned allocation,
together with other policies and measures, would enable them to meet the Kyoto
commitments. Furthermore, during these two phases, the directive obliged Member
States to allocate most of the allowances for free – they may auction at most
5% for the 2005-2007 period, and at most 10% for 2008-2012. 
The third phase started in 2013 and will
end in 2020. Compared to the previous periods, substantial design changes have
been brought in. The most important change concerns the cap. The system of
National Allocation Plans was discontinued and the Directive determined the cap
for 2013 onwards. By means of a linear factor (a percentage defining by how
many allowances the cap is reduced each year) an expectation was also created
how the cap would evolve beyond the end of phase 3. The linear factor of 1.74 %
implies that by 2050 the annual amount of allowances put in circulation would
be more than 70 % lower than the second phase cap. A significant amount of
carbon allowances are auctioned. The level of auctioning for non-exposed
industries will increase in a linear manner with a view to reaching 100% by
2027. Industries exposed to carbon leakage are allocated allowances for free.
Subject to state aid approval, Member States may also be entitled to compensate
certain installations for CO2 costs passed on in electricity prices. Certain
Member States are allowed an optional and temporary derogation to continue free
allocation for power plants up to 2019 ([78]). 
According to Chevallier (2011), regulatory
decisions on the ETS, as much as evolving market fundamentals, are likely to
influence the carbon price. For example, during the second year of the first
phase, in 2006, companies reported to Member States and the Commission on the
actual emissions. In their report, it became obvious that the market had been
over-supplied, which led to a fall of the carbon price by 50% in a few days
(Chevallier, 2011). Another example is the decision taken by most Member States
not to allow for the transfer of any banked allowances from phase I to phase
II, leading to a discrepancy between spot phase I and future prices for phase
II (Chevallier 2011). 
2.3.2.   Policy developments and the
interactions with energy policies
In addition to a reduction in greenhouse
gas emissions from 1990 levels, the "20-20-20" targets set two more
key objectives for 2020 in order to fight against the climate change. 
The first one is to raise the share of
renewables in gross final consumption of energy to 20%. The development of
renewables has been costly compared to conventional energy sources ([79]) and has required support from authorities to ensure their take up.
The most common support schemes of renewables have been feed-in tariffs,
feed-in premiums and green certificates. The feed-in tariff provides the
renewable producer with a guaranteed price for the power they infuse into the
grid. Compared to the feed-in tariff, the feed-in premium offers a guarantee
(premium) over the electricity price, which means that the renewable producer
has to cope with the variation of the electricity price. Green certificates are
based on quota obligations where consumers or suppliers must have a certain
percentage of the electricity produced by renewable sources ([80]). The development of renewables has been promoted through the use
of support systems mostly financed via the electricity market ([81]), but more recently, Member States have started to revise the level
of their support schemes, as some technologies have become more mature. 
The second objective refers to a 20%
improvement in the EU's energy efficiency. The new Energy Efficiency Directive
proposes different way to achieve energy efficiency – e.g. by an energy savings
obligation on suppliers, etc.
Overall, the identification of these three
targets had a common objective: accelerating the reduction of GHG emissions in
a cost effective way. At the same time the renewables and energy efficiency
targets are pursued by wider motivations like enhanced supply security and
industrial policy and competitiveness considerations. The impact
assessment ([82])
accompanying the Energy and Climate Package acknowledges the interactions
between renewable and climate policy, in particular the extent to which they
reinforce each other in order to achieve both targets. More specifically,
modelling results show that each policy alone is less effective in reducing carbon
emissions and the combination of both carbon and renewable policies contribute
to reaching both targets by 2020. At the same time, the impact assessment
stresses that renewable policies contribute to lowering the carbon price needed
to achieve the 20% GHG emissions reduction (from 49€/tCO2 to 39€/tCO2).
Since the discussions on the three 2020
targets, there has been discussion in the literature on the overlap between
renewable and climate instruments and their impact on carbon prices. Most of
the papers reviewed focused on the price interactions and found that the
combination of both policies reduces the allowance price. Furthermore, the
interaction of policies leads to two fold effects (second order effects): a
decrease in the carbon price and an increase in carbon emissions (see box II.2.1).
2.4.      Assessing
the drivers of carbon prices
In this section, an empirical estimation of
drivers of carbon prices is presented. 
2.4.1.   Main drivers of green-house
gas emissions and prices
Greenhouse gas emissions generated by
industrial and non-industrial activities depend mostly on economic and energy
factors (Kaya, 1990). As regards the ETS sectors, the demand and supply of
allowances derived from greenhouse gas emissions will drive the carbon price.
Market equilibrium depends mainly on the following: 
a) The fixed supply of allowances,
as defined by the ETS cap.
b)Macro-economic factors that drive carbon emission. The recent economic crisis has
contributed to a significant drop in carbon emissions. Therefore, it expected
that the carbon price will be positively correlated with economic growth. 
c) Energy prices (oil, gas and coal)
that influence the fuel switching behaviour of power producers which account
for the majority of ETS emissions. 
d) Weather conditions (including
precipitation patterns) that drive the short-term demand for heating and
cooling and hence the demand for allowances, as well as the operation of
hydroelectric units. 
e) Institutional factors that
influence the behaviour and expectations of market agents, such as decisions
about back loading, directives etc.
f) International environment and
number of CERs and ERUs surrendered in the ETS. Surrendered CERs
and ERUs add to the domestic supply of allowances and can be expected to modify
allowance prices. 
g) Energy policies that influence
overall carbon emissions, hence the carbon price.
h) Innovation and technological
developments with influence the marginal abatement costs and demand for
allowances.
 (Continued on the next page) 
 Box (continued) 
2.4.2.   Main drivers impact on
carbon prices
In this section, the impact of economic
activity and energy factors on carbon prices is tested ([83]). Table II.2.2 reports the short and long-run
coefficient estimates obtained from the Error Correction Model (ECM) version of
the ARDL model. All the estimated coefficients have emerged with the
theoretically expected signs and many are statistically significant. 
In the long run model, economic activity
and renewable policy as well as the coal price have had an impact on the carbon
price in the period 2008-12. The long-run model
reveals that the coefficient of the variable that represents the economic
activity is positive and statistically significant, indicating that business
cycles have a strong influence on the carbon price by affecting the demand for
allowances. For the same reason, the renewable penetration impacts negatively
the carbon price as it substitutes part of the conventional units operation and
thus lowers the demand for allowances. Similarly, the negative coefficient of
coal prices suggests the possibility of fuel switching by electricity
producers, when coal prices increase, towards a less carbon intensive energy
source, such as natural gas. Conversely, the hydro production found to be
statistically insignificant, which implies that the weather conditions (dry or
wet year) would in this five year period not have had any systematic impact on
the fuel electricity production mix, hence on the carbon price formation. The
coefficient of the error-correction term (ut-1) reveals that any deviation from
the long-run carbon prices path, due to changes in the explanatory variables,
is corrected by approximately 50% over the following month. Moreover, the
negative sign of this term implies that the carbon prices series is
non-explosive, implying that price revert to its  long-run equilibrium after an
unexpected insistent. In terms of time, the speed of convergence of carbon
price to its long-run equilibrium after a shock is at least two months,
resulting in the high volatility of the market ([84]).  
 Table II.2.2:     Results of the carbon model 
 Note: *, **, *** Indicates significance at 10%, 5% and 1% confidence level. Source: Commission Services. 
On the short-run the effect of most of
the explanatory variables on the carbon price is still statistically
significant, but lower than in the long run relationship. Allowance price changes have a long memory, as they depend
strongly on the previous period price changes. Once again the renewable
penetration and the evolution of coal prices are one of the most important
factors influencing price formation in the short-run. Consistent with the
long-run results, both affect prices negatively by lowering the demand for
allowances. By contrast, the results indicate that economic activity, as well
as the hydro production, despite that their coefficients have the expected
sign, do not affect the carbon price in the short run.
Moreover, the coefficients of the dummies
included in the regression in order to test the impact of institutional factors
on prices, indicate that institutional as well as policy factors play an
important role in the carbon price formation. The proposal on energy efficiency
made by the Commission in June 2011, as well as the discussions on the ETS
market imbalance led to the lowest levels since the recession-led sell off in
March 2009. Apparently, the news was integrated immediately by market agents,
who adjusted accordingly their demand for allowances.
 Graph II.2.3:   Decomposition of Carbon Price Changes over 2008-2012 
 Source: Commission Services 
Finally, in order to identify the degree of
influence of the independent variables on the change of carbon prices during
the ETS phase 2, a decomposition analysis based on the estimated coefficients
of the model (Table II.2.2) was carried out. The contributions
of these determinants were analysed on a yearly basis. Results (Graph II.2.3) indicate that there has been
significant changes in carbon prices over the sample period and that the
economic activity, as well as the power producers fuel preferences (fuel
switching), along with the renewables penetration were the main determinants of
these changes until 2011. At the beginning of phase 2 the economic crisis was
the most important factor contributing to a significant decrease of carbon
prices by cutting down GHG emissions and consequently the demand for EUAs. This
variable exhibited a high volatility compared to the other variables such as
fuel switching behaviour and renewables penetration. Renewables displayed a
constant downward effect on carbon prices, while the influence of the power
producers operating preferences was positive in 2008 and negative after, due to
the evolution of coal prices in relation to the natural gas prices. By
contrast, in 2012, it seems that other factors than those variables played a
crucial role in the carbon price formation. Such factors could be the
international carbon offsets, policy initiatives, or institutional decisions
etc. 
2.5.      Conclusions
The ETS was introduced as the main
instrument to achieve greenhouse gas emissions reduction in the most
cost-effective way. However, the main feature of this market-based instrument
-  the fixed supply of allowances (ETS cap) and the elastic demand - has made
the carbon price more sensitive and responsive to demand factors. Among these
demand factors, the economic activity which is a key driver of GHG emissions
resulted into the lowest levels of carbon prices. Based on the empirical
results, the economic recession impact becomes more apparent in the long-run,
as market agents appear to adjust their expectations and demand for allowances
in the long-run, rather than in the short run. 
Other factors also contribute to carbon
price evolution, even though to a lesser extent, i.e. the conventional power
producers operating preferences and the RES deployment. As already indicated in
the 2008 Commission impact assessment for the Climate and Energy Package,
renewables do not emit CO2, and the renewables penetration in electricity
decreases the demand for allowances and hence contributes to lowering the
carbon price-- as would do the spreading of any other significant abatement
activities falling within the scope of the scheme. It was observed that
renewables affect carbon prices and not vice versa. The latter could be
explained by the low level of carbon prices and the fact that the renewables
deployment in many Member States has not been driven by the carbon prices, but
by guaranteed supporting schemes very often disconnected from market evolution.
Finally, the impact of the accelerated use of international credits in the ETS
could not be tested in the present analysis due to data limitations. However,
the role of other drivers in recent years points to the importance of this
factor as well as institutional factors.
Along the same lines, the on-going
discussions on the ETS made the market participants and the market more
sensitive to regulatory and institutional factors such as the discussions about
the appropriate policy response to the growing supply-demand imbalance in the
carbon market. It seems that market participants, such as power producers which
account for the majority of ETS reductions, respond to any type of pricing
relevant information and especially on the evolution of the relative fuel
prices. This underlines that abstracting from the over-supply problem in
principle the carbon market performs well as a tool to allow for cost-effective
emission abatement.
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Electricity Price
Natural Gas Price
([1])  COM(2012)663.
([2])  This chapter uses gross value added at
basic prices. The National Accounts define it as the output at basic prices
(i.e. the sales revenues of the products without the taxes and subsidies) minus
the costs of the products used up in the production process, valued at
purchaser prices (i.e. without VAT)
([3])  See the description of the data used in
Appendix 1.
([4])  Transport services are characterised by
high energy intensity, but they are not included in the analysis. 
([5])  Brazil and Indonesia (and the other
world countries) are reported in Appendix 2.
([6])  It is worth to note that excluding
refineries from the manufacturing sector reduces the RUECs to levels of around
3-4% in gross output in the EU implying that energy costs play a smaller role
in this segment of the economy.
([7])  Due to data limitation the assessment
of Energy intensity and Real energy prices stops at 2009. Therefore to allow
comparability the growth rates of RUEC have also been computed only up to 2009
(Graph I.1.5).
([8])  The high level of energy intensity in
China can be partly explained by the PPP effect which however is not captured
by the dataset used. 
([9])  The decomposition of manufacturing is
done with 14 subsectors on the basis of the NACE Rev.1 nomenclature. It is
possible that there is some restructuring taking place at a lower aggregation
level which may not be captured by this analysis.
([10]) See the technical details of the
shift-share analysis in Appendix 1.
([11]) In order to check the sensitivity of
these results to the start and end date of the analysis, we carried out the
calculations for the period 1998-2006 as well, which gave similar conclusions.
([12]) This evolution could be explained by a
domestic restructuring or investment of foreign companies in the US. The
analysis here does not differentiate between these factors. 
([13]) It is important to keep in mind that
there may be restructuring taking place at a lower level of aggregation than
the available data which cannot be captured by this analysis.    
([14]) For the US the nominal effect measures
only the sectoral value added inflation, since all figures are expressed in
USD. Between 1995 and 2009 the US had a sectoral deflator evolution somewhat
U-shaped which after a period of inflation came back down to its initial
levels. This explains the annual growth figure being close to 0 in the table.
([15]) As for the total RUEC, data limitation
does not enable a full decomposition after 2009. For this reason data for 2011 are
presented separately.
([16]) This sector includes basic chemicals as
well as cosmetics and pharmaceuticals.
([17]) There are two preliminary observations,
first these data are aggregated to include all the manufacturing sectors hence
the indicator can be affected by outliers; second, the occurrence in 2008 of a
significant price increase for crude oil may have had more severe impacts on
those countries with production activities more dependent on oil such as the
refinery industry. 
([18]) Due to data limitation, the analysis at
Member States level starts with 2000 and not 1995.
([19]) As for the other sections, data
limitations for real energy prices and energy intensity are not available after
2009.
([20]) Note that energy intensity in this
framework includes feedstock, which is a particularly important factor for the
coke and refinery sector and to a lesser extent the chemicals sector. Moreover,
energy intensity levels may be influenced by the PPP effect which is not
captured by the present dataset.
([21]) See in Appendix 3, Graph I.A3.7 and Graph
I.A3.8. 
([22]) Shale gas refers to natural gas that is
trapped within shale formations. Shales are fine-grained sedimentary rocks that
can be rich sources of petroleum and natural gas. Over the past decade, the
combination of horizontal drilling and hydraulic fracturing has allowed access
to large volumes of shale gas that were previously uneconomical to produce.
([23]) PISM (2011) and Artus P (2013).
([24]) European Commission (2013b)
([25]) European Commission (2012b) (ii).
([26]) European Commission ( 2012b) (iii).
([27]) European Commission (2012c) and (2012d
which reports on p182 that one quarter of continental European gas is spot
traded).
([28]) European Commission (2012b) (i).
([29]) On average in Q2 2013 wholesale
consumers on the UK’s NBP – traditionally the lowest priced hub in the EU,
which however in March 2013 experienced a price spike  - paid more than double
the price paid by consumers on Henry Hub in the US. The gap between Henry Hub
in the US and German border prices was even larger, with German border prices
almost three times higher than Henry Hub prices over the first four months of
2013. European Commission (2013a).
([30]) European Commission (2012) (ii).
([31]) European Commission (2012b) (ii). Average LNG
price in Europe in 2012 was between $9 or $10/MMBtu, in Japan it was
$17/MMBtun, in Korea $16.6/MMBtu. The price differences suggest that, in vivid
contrast to oil, the world is divided in various regional gas markets. Some
commentators have hinted at the possibility that the price differences may be
reduced in the next decade due to an increase in gas consumption; the
abandonment of the practice to base long-term gas contracts on the
international oil price; and the world-wide surge in gas exploration and
exploitation, including but not exclusively shale gas.
([32]) Comparing end-user prices is
complicated as there are differences in statistical conventions between the two
regions as well as different taxation regimes. Nonetheless both the OECD data
and the Eurostat data provide a similar picture (Appendix 4, Graph I.A4.6).
([33]) It is to note that for the calculation
of energy intensity in this section data taken from Eurostat and Energy
information administration of the US have been used. Unlike in section 1,
energy consumption does not take into consideration feedstock (ie. energy
sources used as raw material). In addition the definition of Industry is
broader than the 14 Manufacturing sectors included in the analysis of section 1
and it includes also agriculture, construction and electricity and gas supply.
Differences in levels and evolution with respect to what observed in section 1
can therefore be explained by these statistical differences.
([34]) The extent and nature of this
adaptation would require more in-depth empirical research.
([35]) This is possible when, for instance,
Cyprus’ large offshore gas reservoirs turn out to be commercially viable for
exploitation. Moreover, a number of EU countries report large potential
reservoirs of shale gas.
([36]) The analysis focuses on overall trade
balance changes and it does not explicitly adress the impacts which run through
changes in the exchange rate. It is of note however that over the period of
study the Euro has almost steadily appreciated vis-à-vis the US dollar.
([37]) These first three points are corroborated
by the elaborate empirical analysis of WIOD data 1995-2009 in section 3.2 of the Commission's 2012 European Competitiveness Report which shows that,
next to improving its energy efficiency, the EU export sector has maintained
its competitiveness by exploiting the opportunities from globalisation to
source their intermediate inputs more cheaply. Table 3.2 of that publication
shows that the total energy inputs embodied in one unit of goods exports has
more or less stayed constant for the EU15 (and has fallen dramatically for the
EU 12) where it has on balance increased for the US. Moreover, the share of
embodied foreign energy inputs per unit of goods export has increased much more
significantly in the EU than in the US. For services exports, a similar picture
emerges, but with a smaller share of energy embodied per unit services exports
than is the case for goods exports and with a level for the US exceeding that
for the EU15.
([38]) This implies as well that so far the
effects of the US shale gas on the EU have run through US goods production and
the export of other energy sources such as coal, since US shale gas has not
(yet) been exported to other parts of the world in signficant amounts.
([39]) Another counter-argument further
explored in box 1.2.1 is that US gas prices may be unsustainably low and will
inevitably increase to match production costs or decline in supply.
([40]) The WIOD project was funded by the
European Commission as part of the 7th Framework Programme for Research.
([41]) Delgado et al. (2007); European
Commission (2007).
([42]) Although industries in certain Member
States are exempted from charges that increase the retail prices or have
long-term fixed contracts.
([43]) HICP, Eurostat.
([44]) The electricity prices of the consumption
bands DC for Households (2500 kWh < Consumption < 5000 kWh) and IC for
Industry (500 MWh < Consumption < 2000 MWh) were selected and are
considered as a representative household and industrial customer, respectively.
([45]) These upward dynamics were, however,
largely driven by a few countries: Latvia and Estonia in the household segment
and Finland and Estonia in the industrial segment.
([46]) Eurostat data on end user price
components are only available for the years 2007-2011. Data from 2007 was not
considered due to a large number of missing data points. In the Household
category, data from 22 countries were used to calculate the average changes in
the price components. In the Industrial category, due to a greater degree of
missing data, only 20 countries were included in the calculated average
changes. Arithmetic average is used; it follows the same evolution as the
weighted average changes. 
([47]) There may also be other reasons, for
example lower demand than expected and overcapacity as a result of the crisis.
([48]) While data was unavailable to calculate
the equivalent change in taxes and levies in the industrial sector in Latvia, this
country also had the highest percentage increase in energy and supply costs and
the second highest increase in network costs in this market.
([49]) Note that prices are illustrated in
nominal terms. While only the Netherlands experienced an overall fall in
electricity prices in its industrial and household segments in nominal terms,
once we control for inflation, Bulgaria, Hungary, Italy, Luxembourg, Romania
and the Netherlands reveal a net fall in real electricity prices over the
sample period (Hungary and Luxembourg in the Industrial market, Italy in the
Household market, and Bulgaria and the Netherlands in both markets).
([50]) This may be due to cross-country
differences in taxation, since end-user prices including all taxes except VAT
have been used. It may also reflect differing degrees of price regulation.
([51]) European Commission (2012b)
([52]) As in footnote 4, the natural gas
prices of the consumption bands D2 for Households (20 GJ < Consumption <
200 GJ) and I3 for Industry (10 000 GJ < Consumption < 100 000 GJ) were selected
as they are considered as a representative household and industrial customer,
respectively.
([53]) As with electricity, natural gas prices
are taken in nominal terms. Unlike the case with electricity, however, there is
no substantial change in natural gas price evolution in Member States over the
sample period when prices are taken in real terms.
([54]) European Commission (2012b)
([55]) See Box II.1.2 for a brief summary of
the literature review.
([56]) European Commission (2012b)
([57]) European Commission (2012b)
([58]) The predicted price effect of market
opening is also based on the assumption that market opening has a direct and
positive impact on market concentration. However, it may be that the absence of
sufficient competition and sustained dominant incumbent positions, despite
legal market opening, may hold back the expected downward price effects.
([59]) Energy Charter Secretariat (2003): LRMC
includes the investment and capital costs for any new generating, transmission
and distribution capacity necessary, as well as short run operating costs and
variable network costs.
([60]) There is, however, a case for
subsidising electricity consumption for vulnerable consumers on welfare
grounds.
([61]) Energy Charter Secretariat (2003)
([62]) See part III on renewables
([63]) Moreno and Lopez (2011)
([64]) Jensen and Skytte 2003; Saenz de Miera
et al. 2008; Senfuss et al. 2008
([65]) Note that greater RES-E promotion may
also raise costs for conventional thermal plants with high capital
costs, since these fixed costs will have to spread over fewer load hours,
leading to calls for capacity payments.
([66]) Other sources of security of supply
concerns can come from the intermittency of renewables and the phase-out of
nuclear production in some Member States.
([67]) European Commission (2013b)
([68]) Security of supply is also a huge
concern in the oil market, which is beyond the scope of this paper.
([69]) Parmigiani (2013)
([70]) Wooldridge (2006): As the fixed effects
estimator controls for time-constant, country-specific heterogeneities that are
correlated with explanatory variables, the effect of certain explanatory
variables such as the generation fuel mix that are relatively stable over time
may get swept away by the fixed effects transformation. This will result in
less significant coefficients than in the absence of the fixed effects control.

([71]) Natural gas was used as a reference
case for the generation fuel variables as a result of the technical
characteristics of the regression analysis, in order to avoid perfect
multicollinearity. The results are robust regardless of the reference case fuel
choice.
([72]) Note that when  using the electricity
prices of heavy energy intensive industries (band ID) as a dependent variable,
this coefficient was negative and insignificant, perhaps as a result of the
exemption of these industries from the RES levy in some countries.
([73]) Steiner (2001); Martin & Vansteenkiste
(2001); ECB (2010); Dee (2011)
([74]) The ETS Directive provides for the
Commission to produce an annual carbon market report as of the third phase of
the EU ETS, which started in 2013.
([75]) The third phase started in 2013 and
will end in 2020.  The first phase took place in 2005-2007 and the second phase
between 2008 and 2012.
([76]) Carry-over of unused allowances into
the second phase.
([77]) Auctioning allowances implies that
allowances have to make it "through the market" and cannot be
silently absorbed on registry accounts (as free allocation is) but translates
on a one-to-one basis into market supply.
([78]) Bulgaria, Cyprus, Czech Republic, Estonia,
Hungary, Lithuania, Poland and Romania submitted applications, which have all
been approved by the Commission.
([79]) Although the marginal cost of
renewables is lower.
([80]) See Canton and Johannesson Linden
(2010).
([81]) If not, leading to the emergence of
tariff deficit in the electricity system (Spain, Portugal for example).
([82]) SEC(2008)85, vol.II.
([83]) Due to data availability, variables
corresponding to international offsets (CERs, ERUs), to weather and to energy
efficiency could not be included.  
([84]) The formula for calculating the number
of months needed for prices to convert on its long-run equilibrium is
ln(0.5)/ln(1+β1).
The Energy and Climate agenda provides a
comprehensive regulatory and policy framework that favours the emergence of new
green sectors. This means that energy markets in the context of well-designed
policies, can offer many opportunities for growth and jobs. The report
scrutinises the development of new technologies and energy sources - solar and
wind - and their impact on trade flows as a way to assess one dimension of
competitiveness. 
Chapter 1 provides an overview of renewable
developments in the EU and other parts of the world. In Europe, the support to
renewable sectors stepped up from 2007 and has represented a strong opportunity
to accelerate the expansion of less mature technologies such as wind and solar.

Chapter 2 gives a close look at trade
developments in the EU and Member States in the wind and solar equipment
sector. It also analyses the drivers of trade of wind and solar equipment,
including the role of research and innovation. 
Chapter 3 analyses the impact of renewable
developments on the energy trade bill. More specifically, it provides some
estimates on the avoided fuel costs. 
1.1.      Introduction 
The development of renewable energy in the
EU has been promoted with a view to reaching a 20% share in gross final
consumption of energy by 2020 as defined by the European Council in 2007 and
Directive 2009/28/EC on renewable energy ([1]). Before these targets, an indicative target to have 21% of its
electricity coming from renewable energy sources by 2010 has been formulated in
Directive 2001/77/EC on the promotion of renewable electricity. Over the last
decade, the EU-27 has increased the share of renewable sources in gross
electricity generation by 50%, from 13.6% in 2000 to 20.4% in 2011. EU share in
world's total renewable electricity generation went from 14.8% in 2000 to 16.5%
in 2011. Only China generates more electricity through renewable sources than
the EU. 
Renewables expansion increases
diversification and security of energy supply while contributing to the
reduction of greenhouse gases emissions. Despite strong research and innovation
efforts, some types of renewable energies were too costly to expand through
market forces. Therefore, development of some renewable technologies has been
accompanied by support through feed-in tariffs and feed-in premiums, green
certificates, priority in the grid, tax incentives and other support measures.
Annual subsidies to renewable energy in the EU amounted to EUR 36 billion in
2011, more than half of worldwide subsidies to renewables. 
This chapter presents an overview of
renewable development, especially of renewable electricity,  in the EU and its
main economic partners. It also looks at the development of support schemes in
Member States as these are the main instruments used to promote renewables.
Section 2 reviews the evolution of renewable electricity generation in the EU
and other parts of the world Section 3 analyses whether this evolution was
guided by the support schemes in place. Conclusions are presented in section 4.
1.2.      Evolution
of renewable Electricity in EU-27 and its main economic partners
1.2.1.   Evolution of renewable electricity in EU-27 
The share of renewable sources in gross
electricity generation grew by 50% over the decade, from 13.6% in 2000 to 20.5%
in 2011. However, this evolution has not been
monotonic over time (Graph III.1.1). After a slight decrease between
2001 and 2003, renewables share have increased at a high rate, in particular
from 2007 onwards when the EU agreed to have a target for renewables, i.e. to
reach a share of 20% of gross final consumption of energy by 2020.
 Graph III.1.1:   Share of Solar PV, Wind, Hydropower and other renewable sources in EU-27 gross electricity generation 
 Source: Commission Services based on Eurostat database. 
The evolution of renewables has not been
homogeneous across renewable sources (Graph III.1.1). The target agreed at EU level did
not include any obligation on the renewable mix to be achieved. 
Until 2007, hydropower was the most
important renewable source and it remained the highest (renewable) contributor
to gross electricity generation despite a slight decrease of its share over the
last decade. This relative evolution could be explained by the efforts made to
support the other renewable sources, but also by the implementation of the EU
Water Framework Directive (WFD) initially established in 2000, and which limits
the approval of new hydropower projects and allocation of concessions and
permissions ([2]). The share
of hydropower in electricity generation showed substantial variability from one
year to another, depending on annual rainfalls and water levels.
By contrast, solar photovoltaic (PV)
displayed the largest expansion during the same period, from 2007 onwards.
Solar PV grew on average 87 % per year between 2007 and 2011, starting from a
0.11 % share in 2007 to 1.37 % in 2011. The combination of initial high level
of support and a learning curve effect leading to a fall of solar modules
prices contributed to making this technology more and more attractive. 
The share of wind increased during the same
period. In 2011, it contributed to 5.46% of EU-27 gross electricity generation
comparing to a 0.74 % share in 2000. This expansion has been monotonic over
time, with a higher growth rate in the last years. 
Finally, the share of other renewable
sources has increased from 0.5% in 2000 to reach 4.3% of gross electricity
generation in 2011. A vast majority of electricity under this category is
produced from solid biomass, biogas and waste, with minor contribution of
geothermal, offshore wind and thermal solar power. 
The same evolution is observed across
Member States. Overall, the share of renewables in
gross electricity production has increased in all Member States between 2003
and 2011 (except Latvia) but at a different pace (Graph III.1.2). The highest increases are observed
in Estonia, Denmark, Lithuania and Ireland. While renewables account for more
than 40% of gross electricity generation in Latvia, Portugal, Sweden, Austria
and Denmark, their share is rather low in small countries such as Malta and
Cyprus. Arguably, the size of these countries does not allow them to fully
exploit the economies of scale associated with renewables. However, larger
countries such as the United Kingdom, France, Netherlands, Belgium, Poland,
Czech Republic and Bulgaria still do not use renewables as extensively as the
relatively good natural conditions for wind energy ([3]) would predict.
 Graph III.1.2:   Share of renewable sources in gross electricity generation by Member State in 2003, 2007 and 2011 
 Source: Eurostat 
The renewable mix differs across Member States. Denmark and Ireland mostly use wind onshore to produce renewable
electricity (above 70% in 2011). By contrast, a large number of Member States
obtain most of their renewable electricity from hydropower. As regards solar
PV, it is still marginal in most Member States except in Czech Republic,
Germany, Belgium and Italy where it already accounts for one sixth to one
quarter of their renewable electricity.
 Graph III.1.3:   Share of solar PV, wind, hydropower and other renewable sources in gross renewable electricity generation in 2011 
 Source: Commission Services based on Eurostat database. 
1.2.2.   Evolution of RES-E in EU-27
and main economic partners
Over the past years, the expansion of
renewable electricity has been observed in the rest of the world. Similarly to the EU, other major countries have adopted policies
promoting the use of renewable energy (Box III.1.1). World renewables electricity net
generation has increased by 45% between 2000 and 2010 ([4]) with the highest growth for China (+245%), the EU27 (+62 %)
followed by the US, Brazil and Japan. 
China more than doubled the electricity
generated through renewables sources during this period. The growth of renewables has been particularly significant since
2007, when the government launched the national plan for renewable energy
development setting medium (Box III.1.1). Over the past decade, China has
been catching up on renewable and has become the largest renewable producer
with around 18.6% of the world electricity net generation through renewable
sources in 2010 followed by EU27 (Graph III.1.4). 
 Graph III.1.4:   Share of EU-27, US, China, Japan and Brazil in world net renewable electricity generation 
 Note: Data correspond to the net electricity generation. Net electricity is the gross electricity minus electricity consumed within the plant for auxiliary services. Source: United States Energy Information Administration. 
Compared to the rest of the world, EU-27
has strong positions in solar PV and wind (Graph III.1.5). It produced around 70% of world's
electricity net generation from solar PV sources. This share has been
increasing considerably over time, which suggests that EU-27 has been investing
much more in this source than its main economic partners. Almost 44% of world's
electricity net generation through wind in 2010 was produced in EU-27, which
makes it the world leader also in this source. However, the EU-27 share has
been decreasing over time, due to a quick expansion of wind sources in the US
and China.
 Graph III.1.5:   Share of Eu-27, US, China, Japan and Brazil in world net electricity generation - solar PV (a) - Wind (b) 
 Source: United States Energy Information Administration 
1.3.      Support
Schemes and renewables development
The generation cost of renewable
electricity remains generally higher than that of conventional technologies,
with some exceptions. Solar power plants traditionally had very high generation
costs, but these costs have fallen substantially over the last years. On-shore
wind power and small hydro costs are also more expensive than those of
coal-fired plants, although they have the potential to compete with them if
local conditions are in their favour. 
1.3.1.   Support instruments 
Due to higher costs of renewable energy,
Member States provide various forms of support in
order to increase their share in energy production and consumption to the
levels required by the Renewable Directive ([5]). The objective is to compensate for the relative higher costs of
this energy source compared to other fossil fuels. There are also huge fixed
costs that create economies of scale as the average cost per unit produced
decreases as the quantity increases. With subsidies, private firms can invest
in renewables and have similar rate of returns as conventional energy sources.
Finally, as renewables develop, one could expect that there will be further
technology development, which will reduce the costs of these technologies over
time and render them competitive in the longer run ([6]). 
The most common renewable electricity
support schemes include feed-in tariffs, feed-in premiums and green
certificates (Table III.1.1). Feed-in tariffs provide the
eligible renewable power producer with a guaranteed price for the power they
feed into the grid. Feed-in premiums provide the producers with a guaranteed
premium in addition to the electricity market price. Both of them may be capped
with a ceiling related to electricity wholesale prices. Green certificates are
normally based on a quota obligation to have a certain percentage of the
electricity sourced from renewable sources. The authorities issue these
certificates to producers of renewable energy, who sell them separately from
the electricity. 
1.3.2.   Development of support
schemes
 Table III.1.1:    Renewable electricity support instruments in member States 
 Source: SWD(2012) 164 
Total amount of subsidy to electricity
generation from RES amounted in 17 Member States ([7]) to EUR 25.2 billion in 2010 ([8]). These 17 Member States accounted for
92% of RES electricity generation in the EU; assuming similar level of support
in the other Member States, the level of subsidy in the EU-27 would have
amounted to some EUR 27 billion ([9]). Three countries accounted jointly for 70% of the support to
renewables: Germany, Spain and Italy followed by France and UK. However,
according to more recent data, the costs of support to renewables have
substantially risen in 2011 and 2012. For instance, in Germany, they increased
from EUR 9.5 billion in 2010 to EUR 12.7 billion in 2012, and in Spain from EUR
5.4 billion to EUR 8.4 billion in 2012.  
According to International Energy Agency
(2013), subsidies to renewable energy in the EU-27 (including not only
subsidies to electricity but also to transport and heating) amounted to EUR 27
billion in 2010 and to EUR 46 billion in 2012. IEA applied a different
methodology than CEER. 
In order to compare the burden of RES
incentives on electricity consumers, one can divide the overall support level
by final electricity consumption. The average weighted support level was 9.3
EUR/MWh in 2010, compared to average end-user electricity price in EU in 2010
of 128 EUR/MWh for industrial consumers and 173 EUR/MWh for households. The
average level of support per unit of electricity produced was the highest in
Spain (18 EUR/MWh), followed by Germany, Portugal and Italy (Graph III.1.6). 
 Graph III.1.6:   EU Member States with the highest support to renewable energy sources, 2010 
 Source: CEER (2012) 
 (Continued on the next page) 
 Box (continued) 
The costs of support are usually borne by
electricity consumers as a surcharge on retail electricity price. Usually the
amount of this surcharge is set by the energy regulator, on the basis of actual
costs, but in some countries the government approves the tariffs. In some
countries, like Spain and Portugal, setting electricity tariffs at a too low level,
not sufficient to cover the costs, led to a deficit of electricity system
(electricity tariff deficit – Box III.1.2), which may be a contingent
liability of the state budget and therefore a burden on public finance. 
The Graph below shows that Spain,
Germany and Portugal, which have the highest average level of support per unit
of electricity produced, have also the highest combined share of wind and solar
power in electricity generation ([10]). This would suggest that providing
high level of support per kWh was effective in these countries to stimulate the
development of renewable electricity in these countries ([11]). In the other Member States, the correlation between the support
level and share of wind and solar power is however weaker. For instance, Italy
and Austria have a similar level of wind and solar energy in the electricity
mix, but the support level per unit of electricity produced is more than twice
higher in Italy. This weaker relationship could be largely explained by the
fact that the level of support guaranteed to the investors in each renewable
technology varied from one country to another, and changed in time. Other
factors, such as differences in renewable energy potential of each country,
state policies concerning award of licenses etc. should be also taken into
account.
Some countries agreed in the past to
provide overgenerous long-term support to renewables, especially to the solar
power. More specifically, when comparing the remuneration to renewable
generators with electricity (and heat) generation costs, substantial
differences in remuneration and profitability between Member States are
observed ([12]). For
instance, as regards onshore wind, in 2011 support levels were too high in
comparison to generation costs in Italy, Romania, Slovakia, the United Kingdom
and some other countries. Support to solar power was in this year overly
generous in Greece, Italy, Spain and Cyprus ([13]).
 Graph III.1.7:   Share of rewewable sources (excluding hydropower) in gross electricity generation and RES electricity support in EU Member States -2010 
 Source: Eurostat and CEER (2012) 
1.4.      Conclusions
Renewable energy production expanded
substantially in the EU over the last decade. The share of renewable
electricity in the EU electricity production increased from 13.6% to 20.4%
between 2000 and 2011. Most of this growth can be attributed to wind, solar
power, which increased its share in electricity production from almost zero a
decade ago to 5.4% for wind and 1.4% for solar in 2011. Some Member States,
like Denmark, Spain and Portugal, produce 15-20% of their electricity from wind
and solar. Electricity produced from biomass also increased substantially over
the last decade.
As the generation cost of these renewable
sources remain generally higher than that of conventional technologies, their
increased deployment required generous subsidies to renewable energy investors.
These subsidies were necessary to respond to some market failures: positive
externalities of renewables such as avoided greenhouse gas emissions and
pollution, huge fixed investment costs, contribution to technological progress
and decreased generation costs in the longer run.  
The development of renewables should be
seen in the global context. World renewables electricity net generation has increased
by 45% between 2000 and 2010, with the highest growth in China, followed by the
EU, US, Brazil and Japan.  The EU has strong position in solar PV and wind, as
it produced in 2010 around 70% of world's electricity generated from solar PV
and 44% of global wind production. These developments provide opportunities and
risks for the EU renewable sector and the whole economy. They are related to
trade flows in renewable energy equipment, maintaining the leading position in
green technologies and possible expansion to non-EU markets, as well as
possibilities to avoid some imported fuel cost.
2.1.      Introduction
The development of renewable energy fulfils
several objectives, including the reduction of greenhouse gas emissions,
security of supply, job creation and strengthening industrial
competitiveness ([14]). This
chapter analyses how the recent expansion of renewables, most notably solar PV
and wind sources, has contributed to EU-27 trade performance and
competitiveness in this sector. 
The competitiveness of the EU-27 renewable
industry is looked at in two ways. Firstly, trade performance in renewables
equipment and components is analysed, as trade developments have followed the
renewables expansion and the EU has been able to build competitive strength in
some components (wind). Second the drivers to trade, including the role of
innovation, are assessed. The EU-27's share in the world's clean energy patents
was around 40% in 2011. 
This chapter is organized as follows.
Section 2 presents an overall picture of EU27 trade in solar and wind
components and equipment and discusses innovation in solar and wind in the EU27
and its Member States. Section 3 describes the international competitiveness of
EU27 in these sectors. Conclusions are presented in section 4.
2.2.      Renewable
components and equipment trade flows ([15])
The expansion of renewable energy
sources has contributed to increasing trade flows in renewable components and
equipment (see Box 1 for a brief description of the
industry). More specifically, intra and extra EU27 trade in wind and solar
components have increased considerably between 2000 and 2012 ([16]). 
2.2.1.   EU27 renewable component
and equipment trade flows
2.2.1.1.  EU-27 components and
equipment trade with Extra-EU
The EU-27 has a considerable trade
deficit with the rest of the world in solar components and equipment. This trade deficit became more pronounced from 2006 onwards when
Chinese exports to the EU started to increase (Graph III.2.1). The worsening of the EU's trade
position has been driven by the evolution of imports. 
EU imports of solar components are very
concentrated. In 2012, 75% of EU-27 imports of
solar components came from China (31% in 2006). Despite the decrease in EU
imports over the two last years, China has managed to remain the first exporter
of solar components to the EU. By contrast, extra-EU-27 exports of solar
components are more diversified. In 2012, 60% of extra-EU exports went to 5
countries. In 2012, 25% of extra-EU-27 exports of solar components went to
Japan, and 14% to the US.
 Graph III.2.1:   EU-27 exports and imports of solar components from Extra-EU 
 Source: Commission Services based on Eurostat database. 
In 2012, EU-27 had a trade surplus of
around 2.45 billion EUR in wind components and equipment with the rest of the
world. This trade performance has been constant
since 2008 with the exception of 2009, when the surplus was around 1.6 billion
EUR (Graph III.2.2). These good performances are driven
by the presence of positive trade balances with a large number of countries.
EU exports of wind components are quite
diversified. In 2012, 55% went to 5 countries, and
one third to US and Canada. Similarly, 59% of extra EU imports of wind
components come from 5 countries, including 40% from China. Once again, imports
from China started to increase after 2006 (imports from China represented a low
share until 2006, around 4%).
 Graph III.2.2:   EU-27 exports and imports of wind components from Extra-EU 
 Source: Commission Services based on Eurostat database. 
 (Continued on the next page) 
 Box (continued) 
 (Continued on the next page) 
 Box (continued) 
 (Continued on the next page) 
 Box (continued) 
2.2.1.2.  Member States trade of
components and equipment with extra and intra-EU
In general, most Member States display a
trade deficit in solar components, and a trade surplus in wind components. Trade volumes differ significantly across Member States. Germany
and Netherlands have the largest trade volumes, both inside and outside the EU.
Germany had the largest trade deficit (intra and extra EU) in solar components
in 2012 (1.9 billion EUR). Most of the deficit with the rest of the world comes
from China. Italy had the second largest trade deficit in 2012 (1.86 billion
EUR). Only the Czech Republic displayed a small trade surplus (Graph III.2.3). 
 Graph III.2.3:   EU Member States intra and extra-EU imports (M) and exports (X) of solar components and equipment in 2012 
 Source: Commission Services based on Eurostat database. 
As regards wind components, Germany,
Denmark and Spain have the largest trade volumes in the EU. In 2012, these
three countries displayed a trade surplus (1.9, 1.5 and 1.2 billion EUR
respectively). Italy and Austria also had trade surpluses in wind components,
while the other Member States faced a trade deficit, with the United Kingdom
and Sweden having the largest ones (873 and 302 million EUR respectively). In
both cases, the overall trade deficit was driven by a large trade deficit with
Intra-EU countries (Graph III.2.4).
 Graph III.2.4:   EU Member States intra and extra-EU imports (M) and exports (X) of wind components and equipment in 2012 
 Source: Commission Services based on Eurostat database. 
2.2.2.   Innovation and trade
performances
This section analyses whether this trade
evolution is consistent with the innovation position of these industries.
Innovation is measured by patents, which reflect the output of the innovative
activity. 
Over the last decade, the share of EU-27
in total world patent applications was 32.5%. This share is even higher in the
renewable energy sector (39.6%), probably
reflecting the fact that the EU was an early mover in most renewable industries
(Graph III.2.5). The performance in wind and solar
have differed during 2000-2011. The EU-27 share in solar energy patents was
only 28.5% during this period. Moreover, between 2007 and 2011, when the trade
performance of the sector deteriorated in Europe, the share was only 24.8%. By
contrast, in the wind industry the EU-27 share was 55% of world applications,
well above any other country and well above the EU average in all industries.
Compared to the EU, the share of the US in renewable patents is lower. Japan
displays a relatively high share of patents in solar panels. The share of China
is still low in renewables, including solar and wind; however, its share more
than doubled between 2007 and 2011.
 Graph III.2.5:   Average share of EU-27, US, China and Japan in world's total, renewable, solar and wind patents from 2000 to 2011 
 Note: Data on applicant's country of residence have been used. They measure the country's ownership of inventions. The same measure has been used in graph 6. The count of patents related to renewable, solar and wind industries are directly provided by the OECD, and therefore follow their definition of these industries. Source: OECD Patents Statistics 
Germany is the main contributor to EU
patents in the renewable energy sectors, including the solar sector (45%) (Graph III.2.6). Around 23.5% of EU patents in the
wind energy sector were registered by Danish companies, which is in line with
the trade and competitiveness performances of Denmark in this sector. The share
of Spain in wind is also quite high (9.1% compared to a 2.4% share in the
overall economy and 7.1% in the renewable sector).
 Graph III.2.6:   Average share of EU Member States in EU-27 total, renewable, solar and wind patents from 2000 to 2011 
 Source: Commission Services based on OECD Patents Statistics database. 
2.3.      International
competitiveness of EU solar and wind energy industries  
In this section, international
competitiveness is assessed using two indicators - revealed comparative
advantage (RCA) ([17]) and the
relative trade balance (RTB) ([18]).
2.3.1.   Revealed comparative
advantages
EU-27 and the US do not display a
revealed comparative advantage in the solar industry. In the wind industry, EU-27 presents the highest RCA index. Japan
has performed above the world average both in the solar and wind industry.
China has revealed comparative advantage in the solar industry (Graph III.2.8).
The situation is heterogeneous across
Member States (Graph III.2.7). Denmark, Germany, Estonia,
Austria, Slovakia and Finland perform better than the world average in both
solar and wind. Denmark presents a particularly high RCA in the wind industry,
which reflects the support policy to wind since the 1970s. In the solar
industry, only Cyprus presents a strong revealed comparative advantage,
followed by Czech Republic and Finland.
 Graph III.2.7:   Average Revealed Comparative Advantage Indexes of solar and wind industries in the EU-27 Member States from 2007 to 2011 
 Note: RCA for Member States include both intra and extra EU trade. Source: Commission Services based on UNComtrade database. 
 Graph III.2.8:   Average Revealed Comparative Advantage Indexes of solar and wind industries in the EU-27, USA, China and Japan from 2007 to 2011 
 Note: In this section, the UN Comtrade was used instead of the Comext provided by the Eurostat. This is explained by the fact that Comext provides limited data to Non-EU countries, which would not allow the computation of these indexes. Source: Commission Services based on UNComtrade database. 
2.3.2.   Relative trade balance
The EU-27 displays a negative relative
trade balance ([19]) in the
solar industry which has worsened over time (Graph III.2.9). In comparison, the situation of
the US has remained relatively stable. Japan presents a positive and constant
pattern, while China has improved its position during the same period. 
By contrast, the EU-27 performs very
well in the wind industry (Graph III.2.10), once again having a RTB index
around 0.5 in both periods. Only Japan presents a slightly higher value, but
this has decreased over time. Both China and the USA present negative index
values, although China improved significantly during the second period.
Once again, the situation is
heterogeneous at the Member State level (Graph III.2.11). Some countries display a positive
relative trade balance in both solar and wind components (Denmark, Estonia,
Finland and Slovakia) while others present a negative RTB in both solar and
wind components. Almost one third of the Member States combine a negative
relative trade balance in solar components with a positive one in wind
components.
 Graph III.2.9:   Average relative trade balance Index of the solar industry in the EU-27, USA, China and Japan 
 Source: Commission Services based on UNComtrade database. 
 Graph III.2.10: Average relative trade balance Index of the wind industry in the EU-27, USA, China and Japan 
 Source: Commission Services based on UNComtrade database. 
 Graph III.2.11: Relative Trade Balance Indexes of solar and wind industries in the EU-27 Member States from 2007 to 2011 
 Note: RCA for Member States include both intra and extra EU trade. Source: Commission Services based on UNComtrade database. 
2.4.      Conclusions
The wind and solar power sector has
benefitted from massive support across the world (chapter 1) which has stepped
up its development and the related trade of equipment and components.
Compared to the rest of the world, the
EU-27 has built a strong position in wind energy components that led to a trade
surplus of around 2.45 billion EUR in 2012. This coincides with a large share
in world wind patents since the 2000s. Within the EU, Germany, Denmark and
Spain display good performances both in trade and innovation. 
By contrast, the EU-27 has not yet managed
to build such a position in the trade of solar energy components, mostly due to
a negative trade balance with China, which has emerged as a key player over the
past years. Overall, the EU-27 deficit in 2012 was 9 billion EUR, while in 2010
the figure was 21 billion EUR. Only a few Member States (Czech Republic and
Cyprus) display a trade surplus in these components and it is mostly driven by
a surplus with other EU countries.
3.1.      Introduction
The development of renewable energy sources
has been promoted to increase diversification and security of energy supply. It
is also considered as a way to reduce pollution and emissions of greenhouse
gases, caused by combustion of conventional fuels. It is also expected to
improve security of supply and to be positive for the EU external energy trade
balance. The EU is traditionally net importer of energy and its import
dependency has increased over the past years, from 47% in 2000 to 54% in
2011 ([20]). Renewables
can help EU avoiding some fuel imports and thus reducing its trade deficit in
energy sources. 
This chapter analyses the impact of
renewable on the energy trade balance. More specifically, it assesses the scale
of avoided costs of imported fuels, in the context of EU huge deficit in energy
products. Section 2 provides an overview of the EU energy trade balance.
Section 3 assesses the avoided fuel costs. Conclusions are presented in section
4. 
While the previous parts of this paper
focused on renewable electricity, the current part adopts a broader perspective
and analyses not only avoided costs of imported fuels thanks to the use of
renewables in electricity, but also in heat production and transport. This
approach is necessary to have a full picture of avoided costs of imported
fuels, as they are higher in heating and transport than in electricity.
3.2.      Total
energy trade balance
The EU has a strong trade deficit in
trade in energy products with non-EU countries,
which reached EUR 421 billion (3.3% of EU GDP) in 2012. The EU spent EUR 545
billion on imports of energy products from outside the EU, while extra-EU
exports in this category amounted to EUR 124 billion
The deficit has increased over the last
years as it was only EUR 150 bn in 2004 (in current
prices). As Graph III.3.1 shows, the value of EU energy trade
balance seems to be linked to the price of crude oil, as the increase of the
oil price in 2005-2008 and 2010-2012 has contributed to aggravating the trade.
This can be explained by the high share of oil in extra-EU energy
imports ([21]) (63% in
2012) and by the fact that import prices of gas are frequently indexed to oil
prices. Apart from changing prices of oil and other fuels, EU trade deficit was
influenced by changes in demand for imported fuels resulting from diminishing
domestic production of fuels, energy efficiency efforts, the expansion of
renewables, changes in the economic activity and in households' purchasing
power. The overall EU dependence on imported fuels increased gradually until
2006, and since then remained stable around 53-54% (53.8% in 2011).
 Graph III.3.1:   EU-27 trade deficit in energy products and crude oil prices, 2000-2012 
 Source: Eurostat, World Bank 
Among the energy products, crude oil and
refined petroleum products contributed the most to the energy trade deficit. Oil deficit was equal to EUR 275 bn, or 2.2% of GDP in 2011 Trade
deficit in gas amounted to EUR 105 bn and a smaller deficits was recorded for
coal and electricity. 
Within the EU, new Member States (EU-12)
tend to have a larger energy trade deficit than the EU-15 countries: seven EU-12 countries had over 2007-2011 an average deficit larger
than or equal to 5% of GDP (Bulgaria, Cyprus, Lithuania, Slovakia, Hungary,
Slovenia and Latvia), whereas none of the EU-15 countries exceeds this threshold.

 Graph III.3.2:   Member States trade balance in energy products as % of GDP, 2012 
 Source: Eurostat 
EU negative trade balance in energy
products and high energy imports have several negative macroeconomic
implications. They imply substantial transfer of wealth from EU energy
consumers to energy producers outside the EU, especially to the Gulf States,
which have particularly low crude oil production costs ([22]). Moreover, high energy imports make Member States vulnerable to
the inflationary pressures originating from energy price shocks and their
impact on GDP. In particular, energy-intensive economies run risk of
competitiveness erosion, depending on the energy intensity and energy
efficiency performance ([23]).
3.3.      Avoided
costs of imported fuel 
EU external trade deficit in energy
products may be partially reduced thanks to the development of renewables,
which are largely produced domestically. Renewables replace a part of
non-renewable fuels in the EU energy mix, which saves some costs of imported
fuels. 
This section provides an estimate of the
amount of the savings in imported fuels cost, achieved thanks to the deployment
of renewables. The main assumption is that the renewable energy replaces the
same amount of energy received from non-renewable sources, i.e. from fossil
fuels and other sources such as nuclear power. 
The assessment is made separately for three
main energy sectors: electricity, heating and transport (including
cooling) ([24]) (Box III.3.1). These three sectors represent
together over 90% of EU final energy consumption, heating accounting for almost
half of it. In 2010, heating represented 43% of EU final energy consumption,
compared with 21% for electricity and 32% for transport. 
 (Continued on the next page) 
 Box (continued) 
3.3.1.   Avoided fuel cost in
electricity
In 2010, the avoided imported fuel cost
in electricity generation amounted to EUR 10.2 billion for EU-27 in 2010, including EUR 5.8 billion for hydro power, EUR 2.2 billion for wind
power, EUR 1.8 billion for biomass and EUR 0.3 billion for solar power. While 2011
and 2012 data are not available yet ([25]), the avoided fuel costs  increased in these years in comparison to
2010, due to increased renewable production and rising oil and gas import
prices.  
It is important to remember that wind,
solar or hydro power investments made in a given year save fuel costs over the
entire lifetime of these installations, during at least 20-25 years. For
instance, thanks to wind and solar installations which were put into operation
in 2010, some EUR 460 million of imported fuel costs were saved in 2011, but
some EUR 7.5 billion can be saved over the lifetime of this equipment ([26]).
 Graph III.3.3:   Avoided imported fuel costs thanks to renewable electricity - 2010 
 Source: Commission Services based on Eurostat and International Energy Agency databases. 
Among Member States, avoided costs of
imported fuels thanks to the use of renewable energy were the highest in Italy
and Spain, followed by Austria, Germany and Portugal (Graph III.3.4). One could in principle expect that
countries with higher production of renewable electricity would have higher
avoided imported fuel costs. Graph III.3.5 shows that this is not always the
case. For instance, Italy saves more imported fuel costs than Germany and
Spain, which have higher RES production. Austria saves twice more imported fuel
costs than Sweden or France, although produces less renewable electricity than
these countries. This could be explained by differences in the fuel mix for
non-renewable electricity generation in these countries, and by differences in
the share of imports in fuel consumption. Italy produces its non-renewable electricity
mainly from gas and uses relatively much oil for electricity generation; these
fuels are usually more expensive and fully imported. Spain and Germany use more
coal for electricity generation, which is cheaper and partially domestically
produced, than Italy. France and Sweden have high shares of nuclear power. As
we assume that renewable energy replaces the same amount of energy received
from non-renewable sources, i.e. from fossil fuels and nuclear, a high share of
nuclear means that each unit of renewable electricity produced replaces less
imported fossil fuels than in the countries without or with low nuclear power.
This concerns also the other countries with high share of nuclear power, such
as Belgium, Hungary or Slovakia. 
 Graph III.3.4:   Avoided imported fuel costs thanks to renewable electricity by Member States - 2010 
 Source: Commission Services based on Eurostat and International Energy Agency databases. 
 Graph III.3.5:   Renewable electricity generation and avoided imported fuel costs - 2010 
 Source: Commission Services based on Eurostat database. 
3.3.2.   Avoided fuel costs in
heating and transport
The production of renewables contributes to
replacing fossil fuel costs used not only in electricity, but also in heat
production and transport. 
In heating, fossil fuels provide some 80%
of energy used for this purpose, with the highest share of gas (43%) followed
by solid fuels (29%). Renewable energy – biomass – represented in 2010 some 15%
of energy used for heat production. Most of the biomass used for heating in the
EU is domestically produced, and the imports of biomass are rather marginal. In
2010, EU consumption of biomass used for heating amounted to 72.5 Mtoe, while
imports accounted for some 3 Mtoe only ([27]).
In transport, oil products represented
almost 95% of fuel consumption ([28]). The EU is highly dependent on oil imports, which in 2010
represented 84% of EU oil consumption. EU dependency on oil products was
growing over the recent year due to depletion of domestic oil reserves and
diminishing of crude oil production.  Biofuels represented in 2010 3.8% of
final energy demand in transport. However, not all EU biofuels production was
domestic: some 35% of bioethanol used in the EU and 22% of biodiesel was
imported.  Moreover, a part of feedstock for production of biofuels by EU
industry is also imported.   
As regards the calculation of avoided fuel
costs in heating and electricity, the methodology has been similar to the
methodology applied to electricity (Box III.3.1).
According to our calculation, the
avoided costs of imported fuels, replaced by biomass used for heating, amount
at EUR 12.2 billion in 2010. This includes EUR 6.9
billion of imported gas costs, EUR 3.3 billion of imported oil and EUR 2
billion of imported coal. France and Sweden, followed by Germany, Finland and
Italy, had the highest amounts of avoided costs of imported fuels due to
biomass use among Members States (Graph III.3.7).
As regards transport, the avoided costs
of imported fuels, replaced by biofuels, amounted at EUR 7.6 billion in 2010. This included EUR 5.8 billion saved thanks to the production of
biodiesel and EUR 1.8 billion thanks to bioethanol. ([29]). Among Member States, avoided costs of imported fuels thanks to
the use of renewable energy in transport  were the highest in Germany, France,
Italy and Spain (Graph III.3.7).
 Graph III.3.6:   Avoided total fuel costs and imported costs thanks to renewable energy, 2010 
 Source: Commission Services based on Eurostat and International Energy Agency databases. 
Altogether, the avoided costs of imported
fuel saved thanks to the use of renewable energy amounted to some EUR 30
billion in the EU in 2010. This estimate given in this paper applies rather
cautious assumptions and should be considered as a low estimate ([30]).
 Graph III.3.7:   Avoided fuel costs thanks to renewable use in heating and transport by Member States, 2010 
 Source: Commission Services based on Eurostat and International Energy Agency databases. 
However, EU production of renewables is
expected to substantially increase over the coming years in order to reach the
objective of 20% share of energy from renewable sources in gross final
consumption of energy in 2020. Total renewable energy production amounted to
150 Mtoe in 2010 and is expected to increase to 238 Mtoe by 2020 ([31]), i.e. by 59%.  With unchanged fuel prices, this would imply an
increase in the avoided imported fuel costs to some EUR 50 billion in 2020 (in
2010 prices). The actual increase in avoided fuel costs is likely to be much
more significant as most reference scenarios for 2020, including IEA's, EIA's
and the Commission's, project for substantial price increases for EU fossil
import prices.
3.4.      Conclusions 
The development of renewables allows Member
States to save a part of costs of imported fossil fuels and thus to reduce its
trade deficit in energy products. According to our calculations, these avoided
imported fuel costs amount to some EUR 30 billion a year in 2010. This amount
is in 2010 still rather limited in comparison to EU external trade deficit in
energy products (EUR 304 billion in 2010, but increased to EUR 421 billion in
2012). It is also comparable to the amount of subsidies received by the
renewable sector in 2010 (some EUR 27 billion). Our calculation applies,
however, rather cautious assumptions and should be considered as a low
estimate.
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Energy Unit Costs in Europe and the world
* including feedstock
EU-27 Member States average (2010-2012) intra
and extra-EU imports and exports of Solar components, in million EUR
Note: the solar components include the
hscodes presented in box III.3.2
EU-27 Member States average (2010-2012)
imports and exports of Solar components to China, Japan and the USA, in million
EUR
Note: the solar components include the
hscodes presented in box III.3.2
EU-27 Member States average (2010-2012) intra
and extra-EU imports and exports of Wind components, in million EUR
Note: the wind components include the
hscodes presented in box III.3.2
EU-27 Member States average (2010-2012)
imports and exports of Wind components to China, Japan and the USA, in million
EUR
Note: the solar components include the
hscodes presented in box III.3.2
EU28 Member States average (2010-2012)
exports of Solar components to the other EU Member States, in million EUR
Note: that the solar components include the
hscodes presented in box III.3.2)
Note: The values represent exports from the
Member State in column A to the trade partner in the other columns
EU28 Member States average (2010-2012)
exports of Wind components to the other EU Member States, in million EUR
Note: the solar components include the
hscodes presented in box III.3.2
Note the values represent exports from the
Member State in column A to the trade partner in the other columns
([1])  Before these targets, an indicative
target to have 21% of its electricity coming from renewable energy sources by
2010 has been formulated in Directive 2001/77/EC on the promotion of renewable
electricity
([2])  Strategic Energy Technologies
Information System (SETIS), European Commission. http://setis.ec.europa.eu/technologies/Hydropower/info.
Ecologic Institute (2011) presents a discussion on the Water Framework Directive
and hydropower.
([3])  European Environment Agency (2009).
([4])  US Energy Information Administration.
([5])  Directive 2009/28/EC of the European
Parliament and of the Council of 23 April 2009 on the promotion of the use of
energy from renewable sources
([6])  Canton  and Johannesson Lindén (2010)
([7])  Data based on replies to CEER
questionnaire, to which 17 Member States replied. 10 Member States have not
replied to the questionnaire:  Bulgaria, Cyprus, Denmark, Greece, Ireland,
Lithuania, Latvia, Malta, Poland, Slovakia.
([8])  CEER (2013).
([9])  If the other countries had the same
average support as the 17 Member States accounting for 92% of renewable
electricity generation, EU-27 would receive 27.3 bn. Assuming a lower support
than average of the remaining countries would lead to a total around 27 bn.
([10]) Denmark and Ireland, which also have
very high shares of wind energy in electricity mix, are not mentioned here as
they have not provided data to the CEER Status Review, on which this section is
based.
([11]) This is an indicative comparison. A
more detailed analysis is included, for instance, in the RE-SHAPING project
reports (see footnote below). A new study on cost-efficiency of subsidies to
electricity generation has been launched by the European Commission services.
([12]) http://www.reshaping-res-policy.eu
. EU-funded RE-SHAPING project, implemented by a consortium led by Fraunhofer
Institute. The remuneration level was calculated as a sum of the net present
value of the expected support payments (plus energy price, in case of feed in
premiums and green certificates, or if support lasts less than 20 years). The
remuneration level was normalised to a common payback period of 20 years and is
based on an assumption of the same discount rate. The comparison was carried
out per technology category, while the tariffs within one category might differ
significantly. The remuneration level was compared to electricity and heat
generation costs, distributed over the whole lifetime of the renewable power
plant.
([13]) Re-Shaping project (2011)
([14]) Philibert (2011)
([15]) This section focuses on trade in
renewable equipment. Chapter 3 deals with the energy part.
([16]) Depicting trade flows of renewable
components with the Harmonised System (HS) nomenclature is rather difficult, as
many of these components are also used in other end-use sectors. After a
careful analysis of the HS nomenclature and existing literature, four main wind
and two solar HS items have been included. This rather restrictive approach
probably under-estimates the total trade affected by these two renewable
sources. However, it leads to more accurate figures on the evolution of the
trade associated with these sources
([17]) The RCA index compares the share of the
solar and wind sector exports in the EU's total goods exports with the share of
the same sector's exports in the total world's exports. This measure is also
computed for the EU main trade partners, for comparability. Values higher
(lower) than 1 mean that the solar or wind industry in the EU (or EU economic
partner) performs better than the world average, and is interpreted as a sign
of comparative (dis)advantage. The RCA index for product "i" is
defined as follows:  where  is the value of exports, and w is the reference group, the world
economy. The final index is constructed as a simple average of the annual
indexes computed for the period 2007-2011 (the last five years of available
data).
([18]) The relative trade balance index
measures the trade balance relative to the total trade in the sector. The RTB
indicator for product "i" is defined as  where   i is the value of product's
"i" exports and   imports. The relative trade balance index ranges
between -1 and 1 in a symmetric manner, and it is usually used for comparisons
across countries and time. By comparison, the revealed comparative advantage is
asymmetric, as relative disadvantage area ranges between 0 and 1, while the
relative advantage area between 1 and infinite. See Sanidas and Shin (2010).
([19]) In this case the index was calculated
for two periods of five years each (2002-2006 and 2007-2011), as the symmetry
of this index allows for comparability across time.
([20]) European Commission (2013a) provides an
analysis of energy dependence of the EU and Member States 
([21]) European Commission (2013c)
([22]) According to Kelley and Bishop (2010),
the wealth transfer to Gulf States (from all the importers, not only from the
EU) was estimated at USD 490 billion per year when crude price was $75 per
barrel. With current prices exceeding $100/bbl, this transfer must be even
higher. A part of this transferred wealth returns to the EU and other oil
importers, for instance in form of goods and services purchased in these
countries.
([23]) Ciscar et al (2004). According to one
of the calculations, every $10 rise in the price of oil per barrel leads on
average to a 0.94 per cent decline in GDP for those importing oil.
([24]) The Renewable Directive set a specific
mandatory target on the transport sector: a 10% share of energy from renewable
sources in transport by 2020. Electricity and heating are included in the
overall target of 20% share of renewable energy in the final energy consumption
by 2020.
([25]) In particular, data on the costs of
fuel input to electricity generation are not available yet for 2011 or 2012.
([26]) Assuming average lifetime of 25 years
and using 4% discount rate
([27]) Data from the Impact Assessment on
biomass sustainability (under preparation). One of the limitations in the
calculation is the fact that imported wood, biomass and the feedstock for
biofuels can be used for energy purposes but also for other non-energy
purposes: wood for furniture or paper, biofuel feedstock – as edible oil.
([28]) Including maritime bunkers.
([29]) For comparison, the support to biofuels
in the form of tax exemptions was estimated at some EUR 3 billion a year in
EU-27, not taking into account market transfers resulting from mandatory
blending requirements,
([30]) For instance, European Wind Energy
Association (2012) calculated the avoided fuel cost thanks to wind energy (i.e.
including avoided costs of domestic and imported fuels) at EUR 5.7 billion in
2010
([31]) European Commission (2013b)