EU ENERGY POLICY Bart Castermans European Commission DG ENER Energy

OUTLINE CONTEXT THE 2030 FRAMEWORK STUDY ON EMPLOYMENT EFFECTS OF SELECTED SCENARIOS FROM THE ENERGY ROADMAP 2050

The backdrop: Rising global energy demand CONTEXT The backdrop: Rising global energy demand Global energy demand to go up by a third by 2035

CONTEXT Import dependence Japan Gas Imports 100% 2010 2035 80% European Union 60% 40% 20% China India United States 0% 20% Gas Exports 20% 40% 60% 80% 100% Oil imports While dependence on imported oil & gas rises in many countries, the United States swims against the tide Data Source: Gould, IEA 05/03/2013

Dependence by supply country CONTEXT Dependence by supply country

Managing external policy risks CONTEXT Managing external policy risks

Challenge 2: Climate Change CONTEXT Challenge 2: Climate Change

Challenge 2: Climate Change CONTEXT Challenge 2: Climate Change Source IEA 2013

Towards 2030 Challenge 3: Competitiveness

Challenge 3: Competitiveness CONTEXT Challenge 3: Competitiveness 10

Challenge 4: Investment CONTEXT Challenge 4: Investment As just outlined: EU is competing globally for investments. Massive investment needs and a financial sector that is still recovering from financial crisis and needs to prepare itself for the specificities of long term infrastructure financing. Investments: Decarbonisation: requires transition from old energy system to a modern and flexible grid that can accommodate intermittent and small scale capacity and also allow responsiveness. In addition to this the EU s current energy infrastructure is anyhow in a need for modernisation due to its age - a large share of the installed capacity in the EU is 40 years or older. All of this results in an investment challenge of 1 trillion euro by 2020. Big issue in Europe: Public acceptance!

The three EU policy objectives

A 2030 framework for climate and energy policies 22 January 2014 EC proposal Energy

Agreement on 2030 framework essential for: Towards 2030 Agreement on 2030 framework essential for: Investment security Economic recovery and energy security UNFCCC 2015

Towards 2030 On instruments

Towards 2030 On targets

Towards 2030 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 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

Proposal: Energy Efficiency Towards 2030 Proposal: Energy Efficiency 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

Towards 2030 The context: ETS price Concerns about energy prices and energy security ETS price ETS:

Proposal: Reform of ETS Towards 2030 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)

Towards 2030 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)

OUTLINE CONTEXT THE 2030 FRAMEWORK STUDY ON EMPLOYMENT EFFECTS OF SELECTED SCENARIOS FROM THE ENERGY ROADMAP 2050

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

Employment 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.)

Employment 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 Approach Combined input from ESTAT LFS, ESTAT SBS, commercial providers (such as Bureau Van Dijk and the EurObserv’ER consortium) Methodology Prioritization of data sources by relevance and importance (ESTAT LFS, ESTAT SBS, Amadeus micro data, EurObserv’ER, Consortium calculations) Apportioning used. The tables are filled gradually giving priority of the first choice data source. If elements of the tables are not available, then a lower order data choice is taken and the data from it is apportioned to match comparable aggregated values from the higher order data choice. The statistical chapter contains detailed tables and charts on: • Number of companies per relevant sector; • Direct and indirect employment in the renewable sectors (including a split on manufacturing, installation, operation and maintenance); • Direct employment by MS and by NACE sector with the power generation sector broken down by generation technology

Employment 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

3. Main results 3.3 The decarbonisation scenarios Employment 3. Main results 3.3 The decarbonisation scenarios S1 : Higher Energy Efficiency   S2 : Diversified Supply technologies S3 : High RES S4 : Delayed CCS S5 : Low Nuclear S1 : Energy Efficiency standards apply to household appliances, new buildings and electricity generation   S2 : No specific support measures for EE and RES; Nuclear and CCS are not constrained S3 : Achievement of high overal RES share and high RES penetration in power generation S4 : Diversified, but constraints on CCS S5 : Diversified, but constraints on Nuclear

3. Main results 3.3 Selected empl. results – broader economy Employment 3. Main results 3.3 Selected empl. results – broader economy General shift to more communications and business services

3. Main results 3.3 Selected empl. results – broader economy Employment 3. Main results 3.3 Selected empl. results – broader economy

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

Employment 3. Main results (10) 3.3 Selected empl. results – power gen sector Baseline

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

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