challenges of renewable energy

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TOWARDS A SUSTAINABLE DEVELOPMENT IN THE EUROPEAN UNION: CHALLENGES OF RENEWABLE ENERGY

NS P

BLANCA MORENO ANA JESÚS LÓPEZ

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ISBN: 978-1-61209-139-6 2011

ENERGY POLICIES, POLITICS AND PRICES

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ENERGY POLICIES, POLITICS AND PRICES

TOWARDS A SUSTAINABLE DEVELOPMENT IN THE EUROPEAN UNION: CHALLENGES OF RENEWABLE ENERGY BLANCA MORENO AND

ANA JESÚS LÓPEZ

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CONTENTS Preface Chapter 1 Chapter 2 Chapter 3 Chapter 4

vii Introduction. The EU Strategy for Sustainable Development

1

Sustainable Development and Renewable Energies in the European Union

5

Evolution of Renewable Energies in the European Union: Shift-Share Analysis

13

Renewable Energies and Economic Growth in the European Union: Panel Data Models

19

Conclusion

25

References

27

Index

31

PREFACE The European Union Sustainable Development Strategy (EU SDS), initially proposed by the European Council in Gothenburg in 2001 and renewed in June 2006, aims at the continuous improvement of the quality of life for current and future generations. The strategy focuses on issues such as climate change, social equity and cohesion, public health and poverty. Within this framework, global climate stability is necessary to achieve further progress towards long-term sustainable development and renewable energy is expected to play an important role in constituting a global sustainable energy structure. The European Union has emphasized the need to control climate change and then it has assumed a binding unilateral greenhouse gas emission reduction target for 2020, according to which the EU is committed to reducing emissions to at least 20% below 1990 levels. In order to achieve this target the European Union is working on the development of renewable energy industries, the implementation of energy efficiency measures and saving energy technologies. However, each country tries to effectively implement renewable energies according to its own characteristics such as energy consumption, energy diversity or composition of electricity generation. The main objective of this work is to conduct an empirical analysis to explain some aspects of the differences between European Union member countries in the promotion of renewable energies. Therefore, this chapter analyzes the role of renewable energies in the European Union Sustainable Development Strategy, studying their evolution and shift-share components, thus identifying the competitive

viii

Blanca Moreno and Ana Jesús López

and structural effects of the different countries and Renewable Energy Sources. Furthermore, The EU Sustainable Development Strategy and the Lisbon Strategy for growth and jobs complement each other. Therefore, an econometric panel model is developed with the aim of explaining how sustainable energies have influenced economic growth within the European Union. Our data sets are provided by the Statistics Office of the European Communities (Eurostat) and refer to the 27 countries of the European Union during the period 1990-2007.

Chapter 1

INTRODUCTION. THE EU STRATEGY FOR SUSTAINABLE DEVELOPMENT “Sustainable development means that the needs of the present generation should be met without compromising the ability of future generations to meet their own needs. It is an overarching objective of the European Union set out in the Treaty, governing all the Union’s policies and activities. It is about safeguarding the earth's capacity to support life in all its diversity and is based on the principles of democracy, gender equality, solidarity, the rule of law and respect for fundamental rights, including freedom and equal opportunities for all. It aims at the continuous improvement of the quality of life and well-being on Earth for present and future generations. To that end it promotes a dynamic economy with full employment and a high level of education, health protection, social and territorial cohesion and environmental protection in a peaceful and secure world, respecting cultural diversity.” Renewed EU Sustainable Development Strategy, European Council on 15/16 June 2006 DOC 10917/06

The overall aim of the renewed European Union Sustainable Development Strategy (EU SDS) is to identify and develop actions to achieve the continuous improvement of the quality of life and well-being on Earth for present and future generations by using resources efficiently,

2


ensuring economic prosperity, environmental protection, social equity and cohesion. The renewed EU SDS adopted by the European Council in June 2006 has its roots in the Gothenburg strategy1 of 2001 (A Sustainable Europe for a better world: A European Strategy for Sustainable Development). Since then, the EU has implemented several initiatives and actions to achieve progress towards Sustainable Development. Subsequently in June 2005 the European Council approved a set of Guiding principles for sustainable development, COM/2005/0218, which serves as a basis for this renewed strategy, with the objectives and principles compiled in Table 1. Following this, in December 2005 the Commission presented a proposal for a Reviewed strategy and platform for further action, COM/2005/658. The result was a renewed strategy adopted by governments at the European Council of 15-16 June 2006 (Renewed EU Sustainable Development Strategy, DOC 10917/06). Table 1. Key objectives and Policy guiding principles of the EU Sustainable Development Strategy Key objectives

Policy guiding principles

Environmental protection

Promotion and protection of fundamental rights

Social equity and cohesion

Solidarity within and between generations

Economic prosperity

Open and democratic society

Meeting our international responsibilities

Involvement of citizens Involvement of businesses and social partners Policy coherence and governance Policy integration Use best available knowledge Precautionary principle Make polluters pay

Source: European Commission (2005). Guiding Principles for Sustainable Development. COM/2005/0218. 1

This was complemented by an external dimension in 2002 (European Council of Barcelona) in view of the World Summit on Sustainable Development in Johannesburg (2002).

Introduction

3

The EU SDS promotes environmental protection by moving towards sustainable patterns of consumption and sustainable production systems with reduced pollution and waste. Therefore, renewable energies are expected to play an important role in constituting sustainable development through the creation of sustainable energy structures. The development of renewable energy industries and energy-saving technologies provides several positive effects, mainly with regard to the expected increase in energy self-sufficiency, employment, investment and production. Therefore, environmental protection should contribute to the overarching objective of the Lisbon Strategy primarily in focusing on economic growth and job creation. The EU SDS and the Lisbon Strategy recognise that economic, social and environmental objectives can reinforce each other and they should therefore advance together. The aim of this work is to examine how renewable energy can be a key driver for economic growth in the European Union. Firstly, we analyze the role of renewable energies in the Sustainable Development Strategy goals. Secondly, we study the evolution of renewable energies in the European Union identifying the shift-share components related to the different countries and energy sources. Afterwards, we develop an econometric panel model in order to explain economic growth as a function of renewable energies and other economic variables such as investment and labor force. This econometric technique fits well to the available information since each country has its own technological, structural and economic path and tries to effectively implement energy policies according to its own characteristics. Therefore the development of renewable energies in each region could bring outstanding benefits.

Chapter 2

SUSTAINABLE DEVELOPMENT AND RENEWABLE ENERGIES IN THE EUROPEAN UNION The EU sustainable development strategy sets overall objectives and concrete actions for seven key priority challenges compiled in Table 2, many of which are predominantly environmental. Therefore, sustainable energy is at the heart of the EU’s Sustainable Development and climate change strategy. The EU has to progress towards renewable energies in order to reduce environmental pollution and to break the link between economic growth and environmental degradation. The Kyoto protocol of the United Nations Framework Convention on Climate Change (UNFCCC, Kyoto, 11 December 1997) has been crucial in promoting the use of renewable energies. Within this framework countries pledged to make substantial efforts in their energy policy in order to reduce their greenhouse gas emissions. More recently, during the Copenhagen Climate Conference (December 2009) more than 180 states signed and ratified the protocol, with an agreement for an average reduction of 5.2% from 1990 levels by the year 2012. In agreement with this goal, the European Union1 has made the commitment to reduce their emissions by 8% during the period 20081

The Kyoto Protocol requires the EU (consisting of the 15 Member States before May 2004) to reduce greenhouse gas emissions by 8% below 1990 levels by 2008-2012.

6


2012 and by at least 20% below 1990 levels by 2020. In order to achieve these objectives, different strategies2 have been implemented to promote the development and growth of the renewable energy sector in order to reach a 12% share of primary energy consumption and increase by 22% the generation of electricity by 2010. Table 2. Key challenges of the EU SDS Key Challenge

Overall objective

Climate Change and clean energy

To limit climate change and its costs and negative effects to the society and the environment

Sustainable Transport

To ensure that our transport systems meet society’s economic, social and environmental needs whilst minimizing their undesirable impacts on the economy, society and the environment

Sustainable consumption and production

To promote sustainable consumption and production patterns

Conservation and management of natural resources

To improve management and avoid over exploitation of natural resources, recognising the value of ecosystem services

Public Health

To promote good public health on equal conditions and improve protection against health threats

Social inclusion, demography and migration

To create a socially inclusive society by taking into account solidarity between and within generations and to secure and increase the quality of life of citizens as a precondition for lasting individual well-being

Global poverty and sustainable development challenges

To actively promote sustainable development worldwide and ensure that the European Union’s internal and external policies are consistent with global sustainable development and its international commitments

Source: Renewed EU Sustainable Development Strategy, European Council on 15/16 June 2006.

Most of the 10 new Member States have the same target. For Hungary and Poland the target is -6% while Cyprus and Malta have no target since they are not Parties to the UNFCCC (these are the only EU-27 Member States without target reduction under the Kyoto Protocol). 2 These objectives have been established in the communication COM(97)599 “Energy for the future, renewable sources of energy” of the European Commission, and the Directive 2001/77/EC of the European Parliament and of the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market.

Sustainable Development and Renewable Energies…

7

Regarding the transport sector, a wide range of measures was established3, covering emission reduction, energy efficiency measures and the promotion of biofuels for the transport sector. More recently, the Community Directive 2009/28/EC on the promotion of the use of energy from renewable sources has agreed European targets for 2020. More specifically, according to this directive the European Union should achieve by 2020 a 20% share of Renewable Energy Sources (RES) in the Community’s gross final consumption of energy and a 10% share of energy from renewable sources in transport energy consumption. Moreover, the new Directive on renewable energy sets targets for all Member States (as shown in Table 3) and requires national action plans that establish pathways for the development of RES. The increased use of electricity produced from RES, together with energy savings and increased energy efficiency, constitutes an important part of the package of measures needed to comply with the Kyoto Protocol to the United Nations Framework Convention on Climate Change4. The new Directive also improves the legal framework for promoting renewable electricity and since the adoption of Directive 2001/77/EC the EU has tried to encourage the growth in the share of electricity from RES, which has risen from 13.8% in 2000 to 15.6% in 2007. EU sustainable development strategy recognises that investments in environmental capital as well as technological innovation are the prerequisites for long-term competitiveness and better environmental protection. Therefore, the development of renewable energy industries and energy-saving technologies provides several positive effects, mainly with reference to the expected increase in energy self-sufficiency, employment, investment and production, but it also has some costs

3 4

More specifically, the directive 2003/30/EC established the goal of reaching a 5.75% share of renewable energy in the transport sector by 2010. According to the International Energy Agency (2009) today´s energy policies have a severe impact on climate change and, since energy (which accounts for 75% of the greenhouse-gas emissions) is at the heart of this problem it should also form the core of the solution.

8


related to the adjustments in production, prices and transportation systems5. Table 3. National overall targets for the share of energy from renewable sources in final gross consumption of energy in 20206

EU members Austria Belgium Bulgaria Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania Slovak Republic Slovenia 5

Share of RES in gross final consumption of energy. 2007 23.8 3.1 4.7 2.4 4.7 17.3 10 22.6 7 8.3 5 5.3 2.9 6.9 29.7 8.9 2.5 0 3.6 5.1 17.6 11.9 5.5 10

Target for share of RES in gross final consumption of energy. 2020 34 13 16 13 13 30 25 38 23 18 18 13 16 17 40 23 11 10 14 15 31 24 14 25

Several studies have reviewed the effects of the introduction of renewable energies at EU country levels. This is the case of Connor (2003) for United Kingdom or Hillebrand et al. (2003) for Germany. Other studies as Moreno and López (2008) have analysed the macroeconomic RES impact at local level. 6 According to the definitions in Internal Market in Electricity Directive (Directive 2003/54/EC) Energy from renewable sources means energy from renewable nonfossil sources, namely wind, solar, aerothermal, geothermal, hydrothermal and ocean energy, hydropower, biomass, landfill gas, sewage treatment plant gas and biogases. Final gross consumption of energy means the energy commodities delivered for energy purposes to industry, transport, households, services including public services, agriculture, forestry and fisheries, including the consumption of electricity and heat by the energy branch for electricity and heat production and including losses of electricity and heat in distribution and transmission.


EU members Spain Sweden United Kingdom EU-27

Share of RES in gross final consumption of energy. 2007 7 30.9 2.1 7.8

9

Target for share of RES in gross final consumption of energy. 2020 20 49 15 20

Source of data: Eurostat and Directive 2009/28/EC.

Regarding the positive effects, renewable energies induce investments in power generation technologies which lead to increases in production and employment. In the European Union the largest part of the investments for electricity production was devoted to new wind power stations and Photovoltaic and Solar thermal systems (see Table 4) whose main beneficiaries are sectors concerning construction and machinery, electrical and optical equipment. Moreover, metal industries increase their production due to the rising number of new photovoltaic installations. The expansion of renewable energies does not only require investments into alternative production technologies but also affects investments in transportation grids. Moreover, there are some indirect benefits as there are industries that deliver intermediate products or supply services that also benefit from the renewable investment impulse. The increase in production has an outstanding effect on employment, and renewable energies are expected to create more jobs in Construction and Installation than in Operation and Maintenance. In contrast to the investment-induced positive production and employment effects, since the majority of renewable energy technologies are not profitable at current energy prices they are expected to increase energy costs. In addition, environmental taxes in general have a significant negative effect on European economic growth. It seems that the cost disadvantage of renewable compared to conventional energies is crucially dependent on future prices of energies used in power plants as well as on the amount of CO2 emission permits. The expansion of renewable energies results in an increase of electricity prices. A cost efficient allocation that achieves the targets referring to both green house gases (GHG) and renewable energy sources (RES) is expected to lead to substantially different impacts across the EU. An estimation of the total amount of increased energy system costs and mitigation costs for the non-CO2 gasses while achieving both GHG and RES targets has been developed (Impact assessment, SEC2008/85)

10


although it does not include co-benefits such as benefits from reduced air pollution7. As it is showed in Table 5, all Member States with a GDP per capita below the EU average, with the exception of Spain, Cyprus and Malta, are expected to have an energy cost increase (expressed as a percentage of GDP) at least 50% higher than the EU average (which is 0.58% of GDP). Table 4. EU infrastructure for electricity production. Net installed capacity (Megawatt)

1990

1995

2000

2007

Δ2000-2007 (%)

Thermal power stations

342642

371871

407144

449129

10.31

Nuclear power stations

121822

128314

137292

132829

-3.25

Hydro power stations

125941

132016

137414

140266

2.08

Pumped storage plants

33469

34719

36448

38306

5.10

483

2472

12796

56270

339.75

Infrastructures

Wind-turbines

Year

Geothermal plants

:

:

604

698

15.56

Steam turbine power plants

:

321678

:

:

:

Gas turbine power plants Combined cycle power plants Internal combustion engine plants

18897

23861

:

:

:

3639

17076

49490

:

:

:

5464

:

:

:

:

577891

651297

730596

12.18

Autoproducer power plants

:

54723

43528

54258

24.65

Photovoltaic systems

7

47

180

4753

2540.56

Public power plants

Solar thermal systems

84

0

1

13

1200.00

Municipal solid wastes

916

1538

2261

5452

141.13

Biogas

380

455

1169

3720

218.22

:

:

380

301

-20.79

Industrial wastes

Source of data: Eurostat.

7

These costs are the net increase in the total sum of (annualized) investment costs and changes in energy costs (Operating & maintenance and fuel costs). These are increased cost estimates but do not constitute a net loss to GDP.


11

Table 5. Costs per GDP (increased energy system costs and Non-CO2 mitigation costs) to achieve both the GHG and RES target cost efficiently for the whole EU

EU members Austria Belgium Bulgaria Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania Slovak Republic Slovenia Spain Sweden United Kingdom EU-27

Increased cost of total Energy system and cost of mitigation non CO2 as percentage of GDP in 2020 0.7% 0.8% 2.2% 0.1% 1.1% 0.3% 1.6% 0.5% 0.4% 0.6% 1.0% 1.2% 0.5% 0.5% 1.1% 1.0% 0.5% 0.3% 0.3% 1.2% 0.9% 0.9% 1.2% 0.9% 0.7% 0.7% 0.5% 0.58%

Source: Primes/Gains, this includes the costs to achieve cost efficient reductions in the EU-ETS and RES targets.

According to the impact assessment of renewable energy (SEC/2008/85) as a result of establishing a 20% target for the EU annual CO2 emissions should fall, annual fossil fuel demand should decrease and a slightly positive effect on GDP growth could be expected as a consequence of employment and technological/industrial development.

12


These results are summarized in Table 6. Moreover, according to the Institute for Prospective Technology Studies (2006) the target of reaching a 14% biofuels would probably lead to an increase of 0.23% in the GDP and the creation of 144,000 new jobs8. In this context, the development of renewable energy industries and energy-saving technologies is becoming a way to achieve environmental objectives and a means of increasing energy self-sufficiency and economic growth. In contrast, the increasing power prices generally have counteractive effects as do environmental taxes and transportation costs. Table 6. Summary of impacts at EU level of a 20% renewable energy target for 2020 Impact Cumulative additional production costs (2005-2020) €bn Annual average additional costs €bn Additional cost in 2020 €bn Reduction in Green House Gases (Mt p.a.) Reduced fossil fuel Mt Δ GDP (%) Δ employment

20% target* 125-290 13-18 0-31 600-900 200-300 -0.05 - 0.5 ~ +650,000

* range chiefly reflects oil price range $48-$78. Source: The impact assessment of the renewable energy (SEC/2008/85).

8

These forecasts are elaborated on the basis of specific assumptions regarding macroeconomic conditions and the agricultural and trade policy environment among others. Moreover, some assumptions rely on the different pathways considered for the fuels by EUCAR (the European Council for Automotive R&D), CONCAWE (the oil companies’ European association for environment, health and safety in refining and distribution) and JRC/IES (the Institute for Environment and Sustainability of the EU Commission’s Joint Research Centre) in "Well-to-wheels analysis of future automotive fuels and powertrains in the European context, version 2b"; http://ies.jrc.ec.europea.eu/WTW.html.

Chapter 3

EVOLUTION OF RENEWABLE ENERGIES IN THE EUROPEAN UNION: SHIFT-SHARE ANALYSIS The overall EU target of achieving the 20% share of RES by 2020 implies that Member States have to encourage renewable energies according to their own potential and specific characteristics such as energy consumption, energy diversity or composition of electricity generation. The success depends on the respective framework conditions in each individual Member State and also on the promotion measures. Reiche and Bechberger (2004) identify a number of success conditions for an increased use of RES: long-term planning security for investors, technology-specific remuneration for green power, strong efforts in the field of the power supply systems (grid extension, fair access to the grid, etc.) and measures to reduce local resistance against RES projects. Those conditions include the different starting positions in energy policy as well as the different pathways for the development of renewable energy sources in the EU members. In global terms, the information available for the decade 1997-2007 shows an outstanding increase of renewable energy, both in production and consumption (Table 7). More specifically, the production of renewable energy in the EU has grown 50.3% while the consumption increased 52.3% during the same period, and the highest taxes of variation correspond to Germany, the Czech Republic, Hungary and

14


Ireland, while Romania is the only country showing a negative evolution of renewable energies. The specific evolution of different renewable energy sources in the countries of the European Union can be studied through shift-share analysis (Dunn, 1960), allowing the identification of three different growth components, respectively denoted as European, Structural and Competitive Effects1. Table 7. Variation of Renewable Energy Production and Consumption 1997-2007 (%) EU members Austria Belgium Bulgaria Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania

1

Variation of Production (%) 31.0 101.1 103.9 54.8 257.2 82.2 26.9 27.2 5.7 264.6 25.1 173.7 147.0 41.5 17.3 50.0 78.3 : 61.3 29.6 22.9 -3.0

Variation of Consumption (%) 34.4 148.6 101.7 57.1 224.2 101.4 1.9 26.1 7.4 264.4 25.3 176.8 156.9 45.3 8.0 49.5 154.3 : 95.1 29.1 22.1 -2.3

Some extensions of the classical shift-share have been developed by different authors. Among them, Berzeg (1978) provides a statistical basis for shift-share analysis in terms of Analysis of Variance (ANOVA), allowing the testing of the significance of the different effects.

Evolution of Renewable Energies in the European Union... Variation of Production (%) 124.4 45.2 52.7 13.5 110.9 50.3

EU members Slovakia Slovenia Spain Sweden United Kingdom EU-27

15

Variation of Consumption (%) 126.9 39.2 52.8 13.5 124.4 52.3

Source of data: Eurostat.

If we denote by Xij the initial value for a specific energy source i in the country j, Xij´ being the final value of the same magnitude, then the change undergone by this variable can be expressed as follows:

(

)

ΔX ij = X ij´−X ij = tX ij + (t i − t )X ij + t ij − t i X ij

The three terms of this identity correspond to the shift-share effects. Thus, tXij represents the European Effect (EE), summarizing the global European renewable energy growth while the other two terms measure the Net Effect, understood as positive or negative contributions derived from each country. Two different components can be distinguished in this net effect: the Structural Effect, SE = (t i − t )X ij , which collects the positive or negative influence on the growth of the specialization in energy sources with growth rates over or under the average, respectively and the Competitive Effect, CE = t ij − t i X ij measures the special dynamism of a specific

(

)

energy source in a country with regard to the European evolution of this source. Once the structural and competitive effects are computed for each energy source, their sum provides a null result, a property which is usually known as “zero deviation”. This shift-share analysis can be applied to the information about primary energy production (1000 toe) provided by Eurostat for biomass, hydro, geothermal, wind and solar energy2 and the results referring to the 2

Renewable energy primary production includes primary production in biomass, hydro, geothermal, wind and solar energy: biomass (heat content of the produced biofuels or

16


renewable energies evolution in the decade 1997-2007 allow the identification of different patterns in the structural and competitive effects. Our data show that the European production of renewable energies has registered the highest increases in wind (1323.02%) and solar (287.73%) while hydro is the only source showing a negative evolution (-6.75%). Thus, our results lead to positive structural effects for solar and wind energies, whose evolution is more satisfactory than the average, while negative effects are found in the case of hydro, geothermal and biomass. Table 8 summarizes the top five countries for different renewable energy sources showing that Germany and Spain have experienced the most positive evolution. Table 8. Top five countries according to structural effects 1997-2007 in different RES Solar

Wind

Biomass

Greece

Germany

France

Germany

Denmark

Sweden

Austria

Spain

Germany

Cyprus

United Kingdom

Finland

Spain

The Netherlands

Spain

Since the Competitive Effect allows the identification of different country patterns according to their dynamism in the use of renewable energies the study of this effect is especially interesting. According to our analysis the most positive behaviour corresponds to Germany, which shows the highest result for total competitive effect (Fig. 1) and also for all the energy sources with the exception of wind, which is lead by Spain.

biogas; heat produced after combustion during incineration of renewable wastes); hydropower covers potential and kinetic energy of water converted into electricity in hydroelectric plants (the electricity generated in pumped storage plants is not included); geothermal energy comprises energy available as heat emitted from within the earth's crust, usually in the form of hot water or steam; wind energy covers the kinetic energy of wind converted into electricity in wind turbines; solar energy covers the solar radiation exploited for solar heat (hot water) and electricity production.

Evolution of Renewable Energies in the European Union...

Figure 1. Total competitive effects 1997-2007 for Renewable Energy.

17

Chapter 4

RENEWABLE ENERGIES AND ECONOMIC GROWTH IN THE EUROPEAN UNION: PANEL DATA MODELS European Union Sustainable Development Strategy and the Lisbon Strategy, with its renewed focus on growth and jobs, recognise that economic, social and environmental objectives can reinforce each other and they should therefore advance together. In order to show how EU SDS through its environmental objectives can generate economic growth we conduct an empirical analysis. In fact, we explore in which way renewable energy can be a key driver for economic development in the European Union by proposing a panel data model for the EU-27 based on the information provided by Eurostat. More specifically, we use an unbalanced panel covering 25 countries during the time period 1990– 20071. The causal relationship between renewable energy and economic growth has been investigated in several recent studies, leading to different conclusions2. Thus, unidirectional causality running from GDP 1

2

Information about Malta and Bulgaria is not available for the considered time period and therefore both countries have been excluded while estimating the panel model. For an overview of the extensive literature on the causal relationship between energy consumption and economic growth see Payne (2010), Ozturk (2010) or Huang et al. (2008) among others. Some of the empirical analyses have focused in some members of EU-27. For example Wolde-Rufael and Menyah (2010) tested the causal relationship between nuclear energy consumption and real GDP for nine developed countries for the period 1971-2005 by including capital and labour as additional variables. They found a unidirectional causality running from nuclear energy

20


to renewable energy consumption is found in some investigations such as Menyah and Wolde-Rufael (2010) for the US and Sadorsky (2009) referred to the G-7 countries, while other studies find bi-directional causality (this is the case of Apergis and Payne (2010) in a panel of OECD countries), and some others do not find any significant evidence of causality (for instance Bowden and Payne (2009) and Payne (2009)). The heterogeneity of the obtained results suggests that energy and environmental policies could produce differences in the causal relationship observed for different countries. Focusing on the European Union, we propose a panel model with the aim of determining the degree to which renewable energy promotion influences growth. Given the relatively limited time series data on renewable energy the unit root and cointegration tests can not be properly applied and therefore we propose the following model for the economic activity Y (Gross Domestic Product, GDP, measured in millions of euros at 2000 constant prices3):

Y = α + β1K + β2 L + β3 RES + u where K, L and RES are explicative variables respectively related to investment (K, gross fixed capital formation, in millions of euros at 2000 constant prices), labour force (L, total employment in thousands of persons, estimated by the European Union Labor Force Survey4) and renewable energy (RES, final renewable energy consumption in thousand tonnes of oil equivalent, TOE) and u is a random error. All the considered variables are expressed in natural logarithms. consumption to economic growth in Netherlands and France, the opposite unidirectional causality in Sweden, and a bi-directional causality in France, Spain and the United Kingdom. 3 Variables Y and K have been computed in constant prices through chain-linked volume indexes. 4 The European Union Labour Force Survey (EU-LFS) provides population estimates for the main labour market characteristics, such as employment, unemployment, inactivity, hours of work, occupation, economic activity and other labour related variables, as well as important socio-demographic characteristics, such as sex, age, education, household characteristics and regions of residence. The definitions of these characteristics follow the definitions and recommendations of the International Labour Organisation. The definition of unemployment is specified in Commission Regulation (EC) No 1897/2000 and further details are available at the webpage: http://circa.europa.eu/irc/dsis/employment/info/data/eu_lfs/index.htm.

Renewable Energies and Economic Growth…

21

The specification of the proposed model can be explained in two different ways: first, it can be considered as an extension of the classical Cobb-Douglas function, including the renewable energy sources as a complement of the traditional inputs. Furthermore, since our objective is to explain how renewable energy influences economic growth, this multivariate model could be helpful in order to avoid the omitted variable bias. Moreover, following the studies by Apergis and Payne (2010) and Payne (2009), the causal relationship between renewable energy consumption and economic growth will be conducted with the inclusion of measures of investment and employment. Although we could estimate an ordinary least squares (OLS) regression model by pooling all the data, this option would not be adequate since it would ignore specific country and temporal effects. Therefore, considering that EU Member States have different technological, structural and economic patterns, and each of them tries to effectively implement energy policies according to its own characteristics, we can test the existence of individual effects5. In fact, panel data models allow us to test the “poolability” of cross-country panel data, also increasing the degrees of freedom and reducing the level of collinearity among the explanatory variables. In this context, our panel data model can be specified as follows:

Yit = α i + β1K it + β 2 Lit + β3 RESit + u it where i and t respectively denote the number of cross-section units (i = 1,…,N) and time observations (t = 1,…,T), while αi represents the specific country effects and uit is the disturbance term, which is taken as independently and identically distributed (iid) random variable with mean zero and variance σ 2u . In the proposed panel data model, homogeneity is assumed for the parameters β1, β2 and β3, which do not depend on the considered country (only the level of economic activity may differ over countries).

5

When individual country effects exist the pooled OLS estimates are inconsistent and inefficient and panel data estimation could be appropriate. Panel data econometrics is described in Baltagi (1995), Hsiao (1990) and Wooldridge (2001), among others.

22


Regarding the estimation method, most studies attempt to estimate both the fixed effects and the random effects models. According to the first option (fixed effects model) αi is considered as a regression parameter while the random effects model treats this term as a component of the random disturbance. Since the random effects model cannot be consistently estimated when the effects αi are correlated with the explanatory variables, it is advisable to implement the Hausman test (1978) with the aim of comparing the fixed effects and random effects slope parameters (according to this test, a significant difference between both estimated parameters indicates that the random effects model is inconsistently estimated, due to correlation between the explanatory variables and the error components). In order to identify the most suitable specification, our panel data model has been estimated considering both fixed and random effects. The existence of a country specific effect has been checked though the F test (whose null hypothesis is the existence of equal αi for all the countries)6. The obtained results are summarized in Table 9, leading to the rejection of random effects (Hausman test is significant at the 1% level) and confirming the existence of country-specific effects (the F test statistic leads to the rejection of the null hypothesis at the 1% level). As a result, different αi are assumed in order to control for unobserved heterogeneity of EU-27 members. The fixed effects estimated model has a good explanatory power (the overall goodness of fit, as measured by the R-squared, is 99%) and all the explanatory variables are significant at least at the 10% level according to the t-test. The chi-squared normality test provides a result of 6.59 following that the normality of the obtained residuals should not be rejected at the 1% level of significance. As expected, all the estimated parameters result to be positive and since all the considered variables are expressed in natural logarithms, they can be interpreted as elasticities. Thus, we can conclude that an

6

Since the individual effects (αi) capture the unobserved specific country characteristics, which could be correlated with explanatory variables, omitting these terms could lead to biased estimates.

Renewable Energies and Economic Growth…

23

increase of 1% in Final renewable energy consumption is expected to increase GDP by 0.035% (holding constant all other variables). Table 9. Estimated Panel data model for GDP (Panel data set covering 26 EU countries during the period 1990–2007) Explanatory Variables Investment Employment RES

Estimated parameters 0.5774*** 0.2476* 0.0348***

R2 Hausman test F test (country-specific effects)

0.99 192.501*** 186.35***

(1) **significant at 5%; ***significant at 1%. (2) Robust regression is used to adjust the results for heterokedasticity.

Regarding the estimated country-specific effects, according to our model the highest results correspond to United Kingdom, Germany and France while Estonia, Latvia and Romania show the lowest effects.

CONCLUSION The European Union Sustainable Development Strategy aims at the continuous improvement of the quality of life for current and future generations and focuses on issues such as climate change. Renewable energy is expected to play an important role to prevent and reduce environmental pollution and to break the link between economic growth and environmental degradation. The European production of renewable energy has considerably increased during the decade 1997-2007, the most outstanding evolution corresponding to wind and solar energies. According to the shift-share analysis carried out for the last decade, Germany is the country with the most dynamic behaviour, showing the highest competitive effects in all the energy sources with the only exception of wind. The role of renewable energy sources in the economic development has been analyzed through the estimation of a panel data model which also includes capital and employment as explanatory variables. This model has been estimated over a panel of 25 countries during the period 1990-2007, confirming the significant positive effect of renewable energy over the GDP, and also the existence of country specific effects. These results suggest the existence of significant differences between countries implying that financial, technological, social or cultural variables should be considered at country level in order to make a Joint European Union Environmental Policy. Obviously, the proposed models can be extended in different directions. First, since we have detailed information about different renewable energies, these explanatory variables could be separately

26


included in the models, and in fact this would be our objective in further research. Furthermore, in order to test the causal relationship between GDP and renewable energy consumption for the European Union we would try to increase the availability of temporal data, thus allowing the implementation of panel co-integration and Granger causality tests.

REFERENCES Apergis, N., & Payne, J.E. (2010). Renewable energy consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy, 38, 656-660. Baltagi , B.H. (1995). Econometric Analysis of Panel Data. Wiley. Berzeg, K. (1978). The empirical content of shift-share analysis. Journal of Regional Science, 18, 463-469. Bowden, N., & Payne, J.E. (2009). Sectoral analysis of the causal relationship between renewable and non-renewable energy consumption and real output in the US. Energy Sources, Part B: Economics, Planning, and Policy, forthcoming. Bowden, N., & Payne, J.E. (2009). The causal relationship between U.S. energy consumption and real output: A disaggregated analysis. Journal of Policy Modeling, 31, 180-188. Connor, P.M. (2003). UK renewable energy policy: a Review. Renewable and Sustainable Energy Reviews, 7, 65-82. Dunn, E.S.(1960). A statistical and analytical technique for regional analysis. Papers of the Regional Science Association, 6, 97-112. European Commission and European Council (2005). Guiding Principles for Sustainable Development. COM/2005/0218 final: Brussels European Commission (1997). White Paper: Energy for the future renewable sources of energy. COM(97) 599 final: Brussels. European Commission (2001). A Sustainable Europe for a better world: A European Strategy for Sustainable Development. COM(2001)264 final: Brussels. European Commission (2002). Towards a global partnership for Sustainable Development. COM(2002)82 final: Brussels.

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European Commission (2005). Reviewed strategy and platform for further action– A platform for action. COM(2005) 658 final: Brussels. European Commission (2008). Impact assessment - Document accompanying the package of implementation measures for the EU's objectives on climate change and renewable energy for 2020 Commission staff working document- SEC/2008/0085 final: Brussels. European Council (2006). Renewed EU sustainable development strategy. DOC 10917/06: Brussels. European Parliament & European Council (2001). Directive 2001/77/EC of the European Parliament and the Council of 27 September 2001 on the promotion of electricity produced from renewable energy sources in the internal electricity market. L283/33-40: Brussels. European Parliament & European Council (2003). Directive 2003/30/EC of the European Parliament and of the Council of 8 May 2003 on the promotion of the use of biofuels or other renewable fuels for transport: Brussels. European Parliament & European Council (2003): Directive 2003/54/EC of the European Parliament and the Council of 2003-06-26 concerning common rules for the internal market in electricity and repealing Directive 96/92/EC: Brussels. European Parliament & European Council (2009): 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 and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC: Brussels. Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46, 1251-1271. Hillebrand, B., Buttermann, H.G, Behringer, J.M., & Bleuel, M. (2006). The expansion of renewable energies and employment effects in Germany. Energy Policy, 34, 3484-3494. Hsiao, C. (1990). Analysis of panel data. Cambridge. Cambridge: University Press. Huang, B.N., Hwang, M.J. & Yang, C.W. (2008). Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach. Ecological Economics, 67, 41-54.

References

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Institute for Prospective Technology Studies-European Commission (2006). Prospects for agricultural markets and income 2006-2013: Brussels. International Energy Agency (2009). How the energy sector can deliver on a climate agreement in Copenhaguen. Special early excerpt of the World Energy Outlook 2009 for the Bangkok UNFCC meeting, october 2009. López, A.J. & Moreno (2010). Renewable Energy in the European Union: An Econometric Approach to Trends and Effects. Biosciencesworld, The First International Conference on Biosciences, 732-751. Menyah, K., & Wolde-Rufael, Y. (2010). CO2 emissions, nuclear energy, renewable energy and economic growth in the US. Energy Policy, 38, 2911-2915. Moreno, B., & López, A.J. (2008). The effect of renewable energy. Renewable and Sustainable Energy Reviews, 12, 732-751 Ozturk, I. (2010). A literature survey on energy–growth nexus. Energy Policy, 38, 340-349. Payne, J.E. (2009). On the dynamics of energy consumption and output in the US. Applied Energy, 86, 575–577. Payne, J.E. (2010). A survey of the electricity consumption-growth literature. Applied Energy, 87, 723-731 Reiche, D., & Bechberger, M. (2004). Policy differences in the promotion of renewable energies in the EU member states. Energy Policy, 32, 843-849. Sadorsky, P. (2009). Renewable energy consumption and income in emerging economies. Energy Policy, 37, 4021-4028. Wolde-Rufael, Y., & Menyah, K. (2010). Nuclear energy consumption and economic growth in nine developed countries. Energy Economics, 32, 550-556. Wooldridge, J. M. (2001). Econometric Analysis of Cross Section and Panel Data. MIT Press.

INDEX A agricultural market, 29 agriculture, 8 ANOVA, 14 assessment, 9, 28 Austria, 8, 11, 14, 16

B Belgium, 8, 11, 14 bias, 21 biomass, 8, 15, 16 Bulgaria, 8, 11, 14, 19

C causal relationship, 19, 21, 26, 27 causality, 19, 26 clean energy, 6 climate, vii, 5, 6, 7, 25, 28, 29 climate change, vii, 5, 6, 7, 25, 28 climate stability, vii CO2, 9, 11, 29 coherence, 2 color, iv combustion, 10, 16 common rule, 28

competitiveness, 7 composition, vii, 13 constant prices, 20 consumption, 3, 6, 7, 8, 9, 13, 19, 21, 23, 26, 27, 29 copyright, iv correlation, 22 cost, 9, 10, 11, 12 Cyprus, 6, 8, 10, 11, 14, 16 Czech Republic, 8, 11, 13, 14

D damages, iv data set, viii, 23 democracy, 1 demographic characteristics, 20 demography, 6 Denmark, 8, 11, 14, 16 developed countries, 19, 29 deviation, 15 diversity, vii, 1, 13 dynamism, 15, 16

E economic activity, 20, 21 economic development, 19, 25

32

Index

economic growth, viii, 3, 5, 9, 12, 19, 21, 25, 27, 29 economy, 1, 6 ecosystem, 6 electricity, vii, 6, 7, 8, 9, 10, 13, 16, 28, 29 emission, vii, 7, 9 employment, 3, 7, 9, 11, 12, 20, 21, 25, 28 energy consumption, vii, 6, 7, 13, 19, 20, 27, 28, 29 energy efficiency, vii, 7 environmental degradation, 5, 25 environmental protection, 1, 2, 3, 7 equipment, 9 equity, vii, 2 Estonia, 8, 11, 14, 23 European Commission, 2, 6, 27, 28, 29 European Parliament, 6, 28 European Union, i, iii, vii, viii, 1, 3, 5, 6, 7, 9, 13, 14, 19, 20, 25, 26, 29 exploitation, 6

H heterogeneity, 20, 22 homogeneity, 21 Hungary, 6, 8, 11, 13, 14

I impact assessment, 11, 12 impacts, 6, 9, 12 infrastructure, 10 integration, 2, 26 International Labour Organisation, 20 investors, 13 Ireland, 8, 11, 14 Italy, 8, 11, 14

J job creation, 3

K

F Finland, 8, 11, 14, 16 fisheries, 8 France, 8, 11, 14, 16, 20, 23 freedom, 1, 21 fuel costs, 10 full employment, 1

G GDP per capita, 10 gender equality, 1 Germany, 8, 11, 13, 14, 16, 23, 25, 28 governance, 2 Greece, 8, 11, 14, 16 greenhouse gas emissions, 5 grids, 9 growth rate, 15 guiding principles, 2

Kyoto protocol, 5

L labor force, 3 labour force, 20 labour market, 20 Latvia, 8, 11, 14, 23 level of education, 1 Lisbon Strategy, viii, 3, 19 Lithuania, 8, 11, 14

M machinery, 9 majority, 9 management, 6 migration, 6

Index

N natural resources, 6 Netherlands, 8, 11, 14, 16, 20 nuclear energy, 19, 29 null hypothesis, 22

O oil, 12, 20 opportunities, 1

33

renewable energy, vii, 3, 6, 7, 9, 11, 12, 13, 14, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 29 renewable fuel, 28 residuals, 22 resistance, 13 resources, 1 rights, iv, 1, 2 Romania, 8, 11, 14, 23 rule of law, 1

S P

Parliament, 28 pathways, 7, 12, 13 permission, iv plants, 10, 16 platform, 2, 28 Poland, 6, 8, 11, 14 polluters, 2 pollution, 3, 5, 10, 25 Portugal, 8, 11, 14 poverty, vii, 6 power plants, 9, 10 production costs, 12 prosperity, 2 public health, vii, 6 public service, 8

Q quality of life, vii, 1, 6, 25

R radiation, 16 recommendations, iv, 20 regression, 21, 22, 23 regression model, 21 rejection, 22

savings, 7 SEC, 11, 12, 28 sewage, 8 sex, 20 Slovakia, 15 solid waste, 10 solidarity, 1, 6 Spain, 9, 10, 11, 15, 16, 20 specialization, 15 storage, 10, 16 survey, 29 sustainable development, vii, 2, 3, 5, 6, 7, 28 sustainable energy, vii, 3, 5 Sweden, 9, 11, 15, 16, 20

T target, 31 technologies, 31 test statistic, 22 testing, 14 threats, 6 time series, 20 trade policy, 12 transmission, 8 transport, 6, 7, 8, 28 transportation, 8, 9, 12

34

Index

U United Kingdom, 8, 9, 11, 15, 16, 20, 23 United Nations, 5, 7

W waste, 3 wind turbines, 16