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EU ENERGY POLICY

EnergyEnergy

Bart Castermans European Commission

DG ENER

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OUTLINE

.CONTEXT

.THE 2030 FRAMEWORK

.STUDY ON EMPLOYMENT EFFECTS OF SELECTED SCENARIOS FROM THE ENERGY ROADMAP 2050

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The backdrop: Rising global energy demand

Global energy demand to go up by a third by 2035

CONTEXT

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While dependence on imported oil & gas rises in many countries,

Import dependence

0%

20%

40%

60%

80%

100%

20% 40% 60% 80% 100%Oil imports

Gas Imports

United States

ChinaIndia

European Union

Japan20102035

20%Gas Exports

the United States swims against the tide Data Source: Gould, IEA 05/03/2013

CONTEXT

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Dependence by supply country

CONTEXT

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Managing external policy risks

CONTEXT

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Challenge 2: Climate Change

CONTEXT

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Challenge 2: Climate Change

Source IEA 2013

CONTEXT

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Towards 2030

Challenge 3: Competitiveness

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Challenge 3: Competitiveness

CONTEXT

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Challenge 4: Investment

CONTEXT

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The three EU policy objectives

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EnergyEnergy

A 2030 frameworkfor climate andenergy policies

22 January 2014EC proposal

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Agreement on 2030 framework essential for:

Towards 2030

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On instruments

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On targets

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Proposal: GHG

.GHG target found to be least cost pathway to a low carbon economy

.Binding Target GHG reduction 40% (vs 1990)to be translated into binding national targets» ETS Sector: 43%» Non ETS: 30% (both vs 2005)

Towards 2030

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Proposal: RES

.Focus on market based approach

.Binding target at global EU level 27% (minimum) of the energy consumed» No national binding targets. » MS flexibility on individual commitments » "Governance" mechanism to monitor and foster progress

.Review of Directive on renewable energy

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Proposal: Energy Efficiency

Towards 2030

.Assessment of the EE Directive in 2014 (transposition deadline June 2014)

.Shortfall vs the 20% 2020 is expected.

.Review could lead to proposal for amendments

.Current EC estimate: need of 25% EE to meet the GHG target of 40% in 2030

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The context: ETS price

Concerns about energy prices and energy security

ETS price

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Proposal: Reform of ETS

.Dec 2013 decision to postpone auction of 900 Million tons ETS until 2019/2020

.Address structural surplus through a "market stability reserve" to start 2021 (Phase 4) –

.Automatic adjustments, based on rules to be further elaborated (no discretionary measures)

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Proposal: IEM.Target: operational by end 2014

.Avoid distortive effects:

» DG COMP cases (ia UK HPC, RES in DE,…)

» costs/prices and state aids/subsidies (study)

Towards 2030

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OUTLINE

.CONTEXT

.THE 2030 FRAMEWORK

.STUDY ON EMPLOYMENT EFFECTS OF SELECTED SCENARIOS FROM THE ENERGY ROADMAP 2050

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1. Context and timeline (1) - The Energy Roadmap to 2050

• Nov. 2008 2nd SER: EC to prepare an energy policy roadmap towards a low carbon energy system; in line with the EU growth agenda set out in the Europe 2020 strategy

• Feb. 2009, Oct. 2009 The European Parliament and the EU Council support an EU objective to reduce GHG by 80-95% 1990 levels, as estimated by IPCC

• Feb. 2011 The EU Council reconfirms the reduction commitment, recognizes it will require a revolution in the EU energy systems; fixing intermediary targets discussed

• Dec. 2011 The EC adopts the Communication, IA and scenario analysis of the Energy Roadmap to 2050

Employment

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1. Context and timeline (2)The study of empl. effects of RM2050 scenarios

• 2012 Following a recommendation from the IAB, DG ENER commissioned a study analysing potential impacts of decarbonisation scenarios on jobs and skills

• Dec. 2012 - Oct. 2013 Work on the study

• Nov. 2013 – Dec. 2013 Discussion of results with stakeholders

• Dec. 2013 – Jan. 2014 DG ENER to decide on the dissemination of the findings and conclusions of the report

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2. Project details

The tender under an existing framework contract was awarded to a Consortium led by

•COWI

which included •Cambridge Econometrics, •Exergia E3M Lab, NTUA, •Enrst&Young•Warwick Institute for Employment Research

Final draft (159 p.) & appendices (57 p.)

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3.1 Collection of disaggregated statistical and market employment data in the energy sector

• 2,5 million people directly employed in the energy sectors across EU28(1% of the total employment in all sectors)

• 0.6 million directly employed in power generation• fossil fuels (32 800), • hydro (160 400), • nuclear (141 700), • solar (88 200), • wind (55 200), • geothermal (8 000), • biomass (106 500) and tidal (100)

• 0.5 million directly employed in transmission (67 500) and distribution (425 900) of electricity and about 140 000 were employed in transmission and distribution of natural gas

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3.3 The models

Cambridge Econometrics uses E3ME, a structural (Keynesian) macroeconometric model of Europe’s economic and energy systems and the environment.  Exergia E3M Lab from the National Technical University of Athens uses GEM-E3, a multi-regional, multi-sectoral, recursive dynamic computable general equilibrium (CGE) model which provides details on the macro-economy and its interaction with the environment and the energy system.

Employment in the models is determined by a combination of structural change, the revenue recycling, aggregate GDP effects and the reaction in the labour market

Employment

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3. Main results3.3 The decarbonisation scenarios

Employment

S1 : Higher Energy Efficiency 

S2 : Diversified Supply technologies

S3 : High RES

S4 : Delayed CCS

S5 : Low Nuclear

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3. Main results3.3 Selected empl. results – broader economy

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3. Main results3.3 Selected empl. results – broader economy

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3. Main results (9)3.3 Selected empl. results – energy sector

• Decomposed results for the whole energy sector by NACE (such as in Section 3.1) are not available (energy sector spread around several lines in the previous slide)

• Employment results in the power generation sector in the electricity sector are determined by:

input assumptions on the electricity fuel mix (consistent between the models);

coefficients used to determine number of jobs per unit of generation capacity.

(Not by differences in modelling specification)

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3. Main results (10)3.3 Selected empl. results – power gen sectorBaseline

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3. Main results (11)3.3 Selected empl. results – power gen sectorBaseline vs other scenarios

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3. Main results (11)3.3 Selected results – sensitivity analysis

Results across models are fairly robust.

•Relatively low sensitivity Labour intensity of new technologies (measured as jobs per GW

capacity); baseline rates of GDP growth

•Relatively high sensitivity (E3ME) Recycling options of carbon tax revenues(E3ME)

Fossil fuel prices (oil price depends partly on the level of decarbonisation ambitions of the EU trading partners)(E3ME)

Investment crowding out effects

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Thank you