of approaches for employment of renewable...

“Economic and Industrial Development” EID – EMPLOY

Final report – Task 1 –

Review of approaches for employment impact assessment of renewable energy deployment

Barbara Breitschopf

Carsten Nathani

Gustav Resch

November 2011

Study commissioned by IEA-RETD

Fraunhofer ISI, Rütter + Partner, Energy Economics Group II


Acknowledgments

The authors wish to thank the members of IEA RETD and its Project Steering Group, particularly Sascha Van Rooijen (RETD Operating Agent, NL) and Ulrike Lehr (GWS, Germany) for useful comments to previous versions of this study.

About IEA RETD

The RETD Implementing Agreement is one of the key outcomes from the International Conference for Renewable Energies in Germany in June 2004. Members of the RETD are countries that want to encourage the international deployment of renewable energy through improved policies. While the other IEA implementing agreements on renewable energy focus on specific technologies, the RETD is crosscutting from a technological point of view and intends to complement these.

About the consortium

The Fraunhofer Institute for Systems and Innovation Research (ISI) in Karlsruhe, Germany, is part of the Fraunhofer Society for Applied Research in Germany, a non-profit corporation, which promotes applied research and assures the link between fun-damental and industrial research. The Fraunhofer ISI complements the scientific and technological spectrum of the Fraunhofer Institutes through interdisciplinary research on the interdependence between technology, economy and society. The main fields of research of its Competence Center Energy Technology and Energy Policy are energy efficiency, renewable energy sources, energy economics analyses and energy and climate policy. Rütter + Partner is a private and independent research and consulting firm based in Rüschlikon, Switzerland. Its activities are focused on socio-economic research and consulting for government agencies, private enterprises and public insti-tutions. The Energy Economics Group (EEG) is within the Institute of Power Systems and Energy Economics at Vienna University of Technology, Austria. EEG has ma-naged and carried out many international as well as national research projects funded by the European Commission, national governments, public and private clients in sev-eral fields of research, especially focusing on renewable and new energy systems.

Consortium: Fraunhofer Institute for Systems and Innovation Research, Germany (Project Leader) Rütter + Partner Socioeconomic Research + Consulting, Switzerland Vienna University of Technology, Energy Economics Group (EEG), Austria

Contact: Barbara Breitschopf / Mario Ragwitz Breslauer Str. 48, 76139 Karlsruhe, Germany, Tel. +49 721 6809 356, Fax -272 E-mail: [email protected]

Fraunhofer ISI, Rütter + Partner, Energy Economics Group III


Table of Content

Summary ....................................................................................................................... 1

1 Background and objective of the report .............................................................. 4

2 Methodological approach of the review .............................................................. 6

2.1 Objective of the review and procedure .................................................. 6

2.2 Terminology .......................................................................................... 8

3 Review of gross employment impact studies ................................................... 14

3.1 Framework of evaluation ..................................................................... 14

3.1.1 Goals and research questions ............................................................ 14

3.1.2 Important aspects to be addressed in gross employment studies ................................................................................................. 15

3.1.3 Choice of employment studies ............................................................ 17

3.1.4 Comparison and evaluation criteria ..................................................... 18

3.2 Evaluation and comparison of existing studies ................................... 21

3.2.1 Employment factor approaches .......................................................... 23

3.2.2 Supply chain analysis .......................................................................... 28

3.2.3 Cost based IO modelling ..................................................................... 31

3.3 Discussion ........................................................................................... 35

4 Review of studies with net effects ..................................................................... 36

4.1 Framework of evaluation ..................................................................... 36

4.1.1 Differences between net and gross impact studies ............................. 36

4.1.2 Approach for the review ...................................................................... 37

4.1.3 Choice of impulses, impact mechanisms and effects .......................... 43

4.1.3.1 Impulses in net impact studies ............................................................ 43

4.1.3.2 Impact mechanisms ............................................................................ 44

4.1.3.3 The impacts - effects in net impact studies ......................................... 50

Fraunhofer ISI, Rütter + Partner, Energy Economics Group IV


4.1.3.4 Dynamic and simulation mechanisms ................................................. 52

4.1.4 Scenarios ............................................................................................ 53

4.1.4.1 Scenario development ........................................................................ 54

4.1.4.2 Drivers of RE deployment - scenario design ....................................... 55

4.1.4.3 General aspects of a scenario design ................................................. 59

4.2 Evaluation and comparison of net impact studies ............................... 61

4.2.1 Calculation of employment impacts based on positive effects and scenarios ...................................................................................... 64

4.2.2 Calculation of employment impacts based on positive and negative effects ................................................................................... 67

4.2.3 Assessment of employment impacts based on a complex modelling approach ............................................................................. 70

4.3 Discussion ........................................................................................... 75

5 Conclusion ........................................................................................................... 77

5.1 Gross impacts ..................................................................................... 77

5.2 Net impacts ......................................................................................... 79

5.3 Generic conclusion .............................................................................. 80

References .................................................................................................................. 82

Annex: Overview of detailed evaluation of impact studies .................................... 85

Fraunhofer ISI, Rütter + Partner, Energy Economics Group V


Figures

Figure 0-1: Classification of impact assessment studies .............................................. 1

Figure 0-2: Methodological approaches of impact assessment studies ....................... 3

Figure 2-1: Classification of impact assessment studies .............................................. 7

Figure 3-1: Example of the life cycle and supply chains of a wind power plant ......... 16

Figure 3-2: Calculation of employment using employment factors ............................. 25

Figure 4-1: Level and dimensions of net studies ........................................................ 38

Figure 4-2: Dimension of research questions............................................................. 39

Figure 4-3: Combination of three selected scope dimensions ................................... 41

Figure 4-4: Modelling approaches .............................................................................. 42

Figure 4-5: Functional impulse chain ......................................................................... 43

Figure 4-6: Impulses of activities and their impact mechanisms ................................ 45

Figure 4-7: Direct and indirect and induced (type 1) effects ....................................... 51

Figure 4-8: Primary and secondary effects ................................................................ 52

Figure 4-9: Scenario assumption as starting point of the functional chain ................. 55

Figure 4-10: Overview of factors affecting the RE deployment scenarios .................... 55

Figure 4-11: Definition of potential terms ..................................................................... 57

Figure 4-12: Export scenario in dependence of RE investments ................................. 61

Figure 4-13: Simplified calculation scheme .................................................................. 65

Figure 4-14: Calculation of net effects with positive and negative effects .................... 67

Figure 4-15: General procedure and components in a net impact assessment study ........................................................................................................ 71

Figure 4-16: General components of a net impact study, simplified illustration ........... 72

Figure 5-1: Methodological approaches of impact assessment studies ..................... 77

Fraunhofer ISI, Rütter + Partner, Energy Economics Group VI


Tables

Table 0-1: Overview of positive and negative effects caused by the economic impulses .................................................................................... 2

Table 2-1: List of studies analysing economic impacts of renewable, nuclear or fossil energy deployment ....................................................................... 9

Table 3-1: Overview of gross employment studies included in the comparison .............................................................................................. 19

Table 4-1: Distinction between gross and net impact studies ................................... 37

Table 4-2: Overview of selected net impact studies for discussion ........................... 62

Table 4-3: Overview scheme for net impact studies ................................................. 64

Table 4-4: Greenpeace study, 2009 ......................................................................... 66

Table 4-5: Study of Wei et al. 2009 ........................................................................... 66

Table 4-6 BEI 2003 study ........................................................................................ 68

Table 4-7: IHS 2007 study ........................................................................................ 69

Table 4-8: EPIA 2009 study ...................................................................................... 70

Table 4-9: EEFA 2005 study ..................................................................................... 73

Table 4-10: DIW et al. study 2010/11.......................................................................... 73

Table 4-11: BMU 2011 study ...................................................................................... 74

Table 4-12: EmployRES, EU 2009.............................................................................. 75

Fraunhofer ISI, Rütter + Partner, Energy Economics Group 1


Summary

The objective of this study is to provide an overview of existing impact assessment studies that analyse employment impacts of renewable energy (RE) deployment and to show which methodological approaches are best suitable to assess employment effect in the field of RE- electricity.

A first review shows a large variety of impact assessment studies in the field of energy deployment applying a rather broad array of methodological approaches. Bounding the studies to RE-electricity considerably reduces the number of studies, but not necessarily the number of approaches. Due to different approaches the questions answered by the impact assessment studies cover a wide range that captures e.g. limited impacts in the RE industry as well as overarching employment impacts in the overall economy.

impact assessment studies

00 research focus impacts on employment

number of jobs in the RE industry

number of jobs in total economy

positive effects positive and negative effects

gross studies net studies

Figure 0-1: Classification of impact assessment studies

Note: Further possible criteria for classification are the development of scenarios, here not included.

First, based on the research focus of the studies and their impacts (Figure 0-1), we clas-sify the assessed studies on employment impacts into two groups: gross employment studies and net employment studies. They aim to answer different policy questions and capture different effects:

• Gross employment studies focus on the economic relevance of the RE industry in terms of employment, thus on the number of jobs provided in the RE industry and the structural analysis of employment in the RE industry. Furthermore employment in sup-plying industries are also included as indirect or induced impacts. The aim is to provide transparency on employment in an industry that is in the public interest but not ade-quately represented in official statistics, and, furthermore, enabling monitoring of this industry in the course of RE promotion. Gross studies take into account positive effects of RE deployment.

• Net employment impact studies aim to assess the overall economic impact of promot-ing RE deployment, thus the change of the number of jobs in the total economy. For this, they take into account negative and positive effects of RE deployment on em-ployment in all economic sectors and hence provide a full picture of the impacts of RE deployment on the total economy - covering all economic activities like production, ser-vice and consumption (industries, households). To get the number of additional jobs caused by RE deployment, they compare a situation without RE (baseline or counter-factual) to a situation under a strong RE deployment.



In a second step, we characterize the studies inter alia by their scope, activities and im-pacts and show the relevant positive and negative effects that are included in gross or net impact assessment studies. The effects are briefly described in Table 0-1. While gross studies mainly include the positive effects listed here, net studies in general include posi-tive and negative effects.

Table 0-1: Overview of positive and negative effects caused by the economic impulses

Abbrevia-tion

Positive effects Negative effects

Investment effect

Direct and indirect* effects by investment in RE

Direct and indirect effects by avoided investment in con-ventional generation technology

O&M effect Direct and indirect effects by O&M in RE

Direct and indirect effects by avoided O&M in conven-tional generation

Fuel effect Direct and indirect effects by fuel demand

Direct and indirect* effects by avoided fuel demand

Price effect (Induced effect through com-pensation of additional costs**)

Induced effect due to additional generation costs for households (budget effect) and industry (cost effect)

RE income effect

Induced effect by RE incomes in RE industry

(Avoided income in conventional generation industry***)

Trade effect Trade of RE technology and fuel

Avoided trade of conventional technology and fuel

Dynamic effects

Reinforcing effects: changes in productivity, learning effects, multiplier effects, ...

* indirect effects include effects on upstream and downstream industries and services while direct effects only directly refers to the industry producing RE equipment or servicing operation of RE plants or producing fuels; ** hitherto additional generation costs of RE are positive and CO2-pricing or merit-order-effects have partly a compensating effect; *** in many studies not discussed.

Third, we distinguish between methodological approaches assessing impacts. We ob-serve that the more effects are incorporated in the approach, the more data are needed, the more complex and demanding the methodological approach becomes and the more the impacts capture effects of and in the whole economy – representing net impacts. A simple approach requires a few data and allows answering simple questions concerning the impact on the RE-industry – representing gross impacts. We identify six main ap-proaches, three for gross and three for net impacts. They are depicted in Figure 0-2. The methodological approaches are characterized by their effects captured, the complexity of model and additional data requirement (besides data on RE investments, capacities and generation) as well as by their depicted impacts reflecting the economic comprehensive-ness. A detailed overview of the diverse studies in table form is given in the Annex to this report.

Finally, we suggest to elaborate guidelines for the simple EF-approach, the gross IO-modelling and net IO-modelling approach. The first approach enables policy makers to do a quick assessment on gross effects, while the second is a more sophisticated approach for gross effects. The third approach builds on the gross IO modelling approach and pro-



vides a rough assessment of net impacts without detailed macroeconomic modelling. For the full economic assessment approach we suggest to briefly sketch the main relevant elements, but do not provide data, methods or calculations.

complex approach

• impacts: net, total economy• effects: positive & negative

simple approach

• impact: gross , RE industry• effects: positive


employment factor approach:

• data: capacity data, employ-ment factors

• complexity:low (direct effects)

gross IO-modelling:

• data: capacity and cost data, IOtable

• complexity:moderate (direct & indirect effects)

positive effects with scenario:

• data: employment factors (EF)

• complexity:moderate (direct & indirect effects, scenario comparison)

full economic assessment

approach:

• data:• macro-economic• energy sector • trade relations

• complexity: very complex (direct, indirect & induced effects, scenario comparison)

supply chain analysis:

• data: capacity and cost data

• complexity:moderate (mainly direct effects)

positive and negative effects by net IO modelling:

• data: IO-table with consumption vector

• complexity:complex (direct, indirect & induced effects), [scenarios]

Figure 0-2: Methodological approaches of impact assessment studies



1 Background and objective of the report

The use of renewable energy (RE) sources plays a significant role in increasing the secu-rity of energy supply and mitigating climate change. Whereas this role is undisputed, there is an ongoing discussion about the economic and employment costs and benefits of pro-moting renewable energy deployment. Whether RE promotion will bring high dividends or cause high economic costs is still disputed among policy makers and researchers. These economic returns are mostly measured in employment or economic growth. As stated in the Renewable Energy roadmap1, studies vary in their estimates of the employment or GDP impact, some suggesting a small increase and others a small decrease. In the past years several studies have aimed at clarifying this issue, but so far no consensus has emerged on the economic impact of RE deployment. Since there is strong growth in the renewable energy industry, there is a public interest in monitoring its economic develop-ment and its impact on employment and welfare.

In order to support an impartial discussion on the economic and employment effects of enhanced RE deployment, it is crucial to have transparent guidelines based on a sound methodological approach and reliable data sources. So far, the knowledge on the eco-nomic impact of RE technologies is more or less fragmentary, concentrated on few ex-perts and partly achieved on an ad hoc basis. The RETD intends to facilitate the assess-ment by elaborating a more structural approach to assess economic impacts and by con-tributing to insights in impact mechanisms for modelling RE deployment effects. Therefore RETD Implementing Agreement has agreed to commission a project that:

• gives an overview of impact assessment studies,

• provides guidelines for an impact assessment of RE deployment in the power sector, and

• proves the feasibility of the guidelines for gross impact studies, by applying them to selected countries.

The project is carried out by a consortium led by Fraunhofer ISI in response to the call for tender "Economic and Industrial Development (EID - EMPLOY)" by the IEA-RETD. The consortium partners are Rütter + Partner and the Energy Economics Group of the Vienna University of Technology.

This report is the first outcome of the project and its objective is to give an overview of existing models, approaches, methods and studies assessing the employment impacts of an enhanced RE deployment in the power sector. This review of approaches is consid-ered to be a first step towards the elaboration of guidelines. The aim is to learn from the best practices of existing studies. Therefore, relevant aspects for gross and net impact 1 Communication from the Commission to the European Council and the European Parliament -

Renewable Energy Road Map Renewable energies in the 21st century: building a more sus-tainable future, COM(2006) 848 final, Brussels, 10.1.2007.



studies are discussed and the selected studies, models or methods assessing gross and net employment impacts in the power sector are evaluated respectively. Since gross and net employment impact studies differ strongly with regard to the level of aggregation, the methodological approach and the data sources used, we perform the review separately for the two types of studies. Thereby, we intend to answer:

• What is the research focus or goal of the study?

• Which impulses, impact mechanisms or effects are included?

• What is the scope of the study?

• Which methodological approach is chosen?

• What can be learnt in the sense of a best practice?

In this report, first, the methodological approach is briefly outlined for the review of impact assessment studies, followed by a Chapter on gross and another on net impact assess-ment studies. The relevant aspects of net and gross studies are outlined and discussed within the corresponding Chapters, followed by a conclusion.



2 Methodological approach of the review

2.1 Objective of the review and procedure

The aim of this review is to give a comprehensive overview of existing approaches, meth-ods or studies analysing the employment impacts of renewable energy (RE) deployment, to show the respective research focus and methods and to suggest which impact as-sessment approach is best suited to assess employment effects.

In a first step, an extensive literature/internet research was conducted based on keywords referring to renewable energy and employment or economic impacts. The keyword re-search was done in a rather broad manner to avoid a too limited pre-selection to start with. At a first glance, many of the studies, methods, papers and discussions found are rather similar in their approach, based on comparable models or approaches, while others comprise a rather different approach and apply heterogeneous impulses and impact mechanisms. Further, some studies focus on one technology, whereas others encompass several or all RE technologies, though sometimes in a less specific way. Following the RETD mandate, we focused our literature review on national studies addressing RE use for electricity generation. But we have not excluded studies dealing with power and heat or transportation. Overall, some studies take rather simple approaches, others represent complex models. Unfortunately, the geographical coverage is concentrated on a few in-dustrialized regions. Table 2-1 lists the diverse studies or approaches and briefly outlines some key characteristics such as gross or net effects, as well as geographical coverage and time horizon. It represents an overview of studies dealing with impacts of RE deploy-ment but does not claim to be complete either in the number of studies or in key charac-teristics listed.

In a next step, we used two criteria - research focus and impact on employment - to clas-sify the studies found (see Figure 2-1). The research question of impact studies focuses to employment impacts in the RE industry or to changes in the number of jobs in all eco-nomic sectors of a country. The impact on employment could comprise only positive or also negative effects. We broadly distinguish between gross and net employment impact studies. Gross employment studies aim to outline the level and structure of employment in the renewable energy (RE) industry and its supporting industries in a country. The objec-tive of net employment impact studies is to estimate the economic impact of renewable energy deployment on employment and welfare in the whole economy. This includes dis-placed employment in conventional energy industries and induced employment impacts due to changes in energy prices or the competitiveness of industries.




00 research focus impacts on employment

number of jobs in the RE industry

number of jobs in total economy

positive effects positive and negative effects

gross studies net studies

Figure 2-1: Classification of impact assessment studies

Note: Further possible criteria for classification are the development of scenarios, here not included.

However, within the respective group of gross and net impact studies are differences re-garding not only research questions or impacts but also the scope of the study and meth-odological approaches. The research focus partly influences the scope of the study as well as the methodological approach. Therefore, we briefly outline the research aspects and scope of reviewed studies.

Research question

Even within the respective group of gross and net employment impact stuResearch ques-tions of the reviewed studies comprise several aspects:

• Time horizon: This dimension includes past, present and future impacts. While past and present impacts can be analysed using rather simple approaches, the assessment of future impacts requires a more sophisticated approach. Impacts on the overall econ-omy are normally not assessed for the past.

• Regional level: This level comprises impacts on regional, national, supranational or global economies. It addresses the area that is included in the study. Rather disaggre-gated impact studies, e.g. at a local level, or highly aggregated impacts such as global impact studies are challenging with respect to data.

• Economic dimension: This dimension refers to the economic focus, i.e. whether we are interested in and look at impacts in a specific field such as a single RE technology or a RE sector broken down into heat, power or transportation, or the industrial RE sectors or the total economy. Even impacts on social groups could be considered.

• Impact indicators: This refers to the type of indicator that is chosen to show the impact. In our review, the focus is on employment as an important economic indicator. Other indicators may include turnover, gross output, gross value added or changes in GDP. Beside the number of employees, their qualifications or the quality of work may also be of interest.

Scope of analysis

Studies can also differ with regard to the scope of analysis that may influence the level of detail, the choice of model or the available data sources. The scope of the study includes the RE technologies and activities but also other aspects such as scenarios, impulses and impact mechanisms that are outlined in Chapters 3 and 4.



• RE technologies (RET): RET refer to the range of technologies that are covered in the study and to the differentiation within and between technologies. In this project, we fo-cus on technologies for electricity generation from renewable energy sources. Some existing studies also include heat generation and fuels. Other studies have a more nar-row focus on a single or only a few technologies. For the analysis of future employment impacts, technological changes in RET also need to be taken into account.

• RE activities: These refer to activities over the life cycle of renewable energy use facili-ties. These comprise the manufacturing of components, construction and installation of the RE facility (MCI), reinvestments (repowering), operation and maintenance (O&M) and finally demolition of the facilities. In particular, the RE activity biomass generation has to be included if the RET cover biomass combustion technologies. Some studies include all the activities, whereas others focus on selected RE activities. At some point it is necessary to draw a boundary between those activities counted as part of the RE industry and those taking place in the rest of the economy.

2.2 Terminology

To facilitate reading and understanding, we briefly explain or define frequently used ex-pressions in this report:

• The renewable energy industry (RE industry) is considered to be a cross-sectional in-dustry that includes economic activities that are specifically related to the generation and installation of facilities for RE use such as manufacturing, construction, planning, selected upstream suppliers and services. It usually comprises the complete life cycle of renewable energy facilities including demolition.

• The conventional energy industry (CE industry) is used analogously, referring only to energy generation from fossil and nuclear energy sources.

• Renewable energy technology (RET) refers to energy generation technologies based on RE sources.

• Conventional technology (CET) refers to energy generation technologies based on fossil and nuclear sources.

• The overall economic impact comprises impacts of the RE-industry on all economic sectors or industries in an economy, taking all relevant impact mechanisms into ac-count (e.g. demand effects, price effects). We also call this impact on the total econo-my.

• RE-industry-specific impacts mainly comprise effects within the RE industry.

• RS stands for a reference scenario, a situation without or low RE deployment

• ADS stands for an advanced RE deployment scenario.

To facilitate our work, in the following, we apply the term ‘studies’ to all the methods, stud-ies, models or approaches assessing the employment impact of RE deployment, i.e. net or gross studies.



Table 2-1: List of studies analysing economic impacts of renewable, nuclear or fossil energy deployment Year Title / author / type of publication Gross/

net Country/region RES‐ tech‐

nology Effects/description

2003 Employment Potential of Renewable Energy in South Africa Austin, Greg; Williams, Anthony; Morris, Glynn; Spalding‐Fecher, Randall; Worthing‐ton, Richard AGAMA Energy Ltd prepared for Sustainable Energy and Climate Partnership Johan‐nesburg

gross South Africa (one‐country)

E + H + T (all tech.)

direct and indirect employment (invest + operation), imports

2004 Renewable Supply Chain Gap Analysis Department of Trade and Industry (DTI)

gross United Kingdom (one‐country)


direct and indirect employment (invest + operation), exports /imports + accelerator

2006 The effect of renewable energy on employment ‐ The Case of Asturias (Spain) Moreno, Blanca; López, Ana Jesús (University of Oviedo)

gross Asturias (ES) (reg. focus) (one‐country)


direct employment (invest + operation)

2009 Energy Sector Jobs to 2030: A global analysis (final report) (Greenpeace 2009) Rutovitz, Jay; Atherton, Alison Prepared for Greenpeace International by the Institute for Sustainable Futures, Uni‐versity of Technology, Sydney

gross/ net

worldwide (in‐depth analysis for selected regions)

E + T (all tech.)

direct employment (invest + operation), exports/ imports

2009 Regional Employment and Income Opportunities provided by RES Gerardi, Walter; Knapp, Simon Mc Lennan Magasanik Associates for the Climate Institute in Australia

gross

Australia (reg. focus) (one‐country)


direct and indirect employment (invest + operation), exports/ imports

2009 Direct employment in the wind energy sector: An EU study Blanco, Maria Isabel; Rodrigues, Glória (University of Alcala de Henares)

gross

European Union E (wind energy only)

direct employment (invest + operation)

2003 Evaluation of jobs and employment effects in the context of Renewable Energy Pfaffenberger, Wolfgang; Nguyen, Khanh; Gabriel, Jürgen for Bremer Energie Institut (BEI)2003

net Germany (one‐country)

E (all tech.)

direct and indirect employment (invest + operation), neg. invest‐ment effect, budget effect

2004 Putting Renewables to Work: How many Jobs can the clean Energy Industry generate? Kammen, Daniel; Kapadia, Kamal; Fripp, Matthias (University of California) RAEL Report

gross USA (one‐country)

E (all tech.)

direct and indirect employment (invest + operation), neg. invest‐ment effect

2010 Putting renewables and energy efficiency to work: How many Jobs can the clean energy industry generate in the US? Wei, Max; Patadia, Shana; Kammen, Dan Energy Policy 38 (2010)

gross USA not specified direct and indirect employment (invest + operation), neg. invest‐ment effect, induced effects

2005 Expansion of renewable energy and employment effects in Germany (EEFA) Hillebrand, Bernhard; Buttermann, Hans Georg; Behringer, Jean Marc; Bleuel, Michae‐la Energy Policy 34 (2006)


E (all tech.)

direct and indirect investment effect, neg. investment effect multiplier, accelerator, budget effect

2006 Renewable Energy – Employment Effects net Germany E + H + T direct and indirect employment (invest + operation), neg. invest‐



Year Title / author / type of publication Gross/net

Country/region RES‐ tech‐nology

Effects/description

Staiß, Frithjof; Kratzat, Marlene; Nitsch, Joachim; Lehr, Ulrike; Edler, Dietmar; Lutz, Christian Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU)

(one‐country) (+ reg. focus)

(all tech.) ment effect, exports/ imports, multiplier, accelerator, budget + cost effect

2009 The impact of renewable energy policy on economic growth and employment in the EU (EmployRES 2009) Ragwitz, Mario; Schade, Wolfgang; Breitschopf, Barbara; Walz, Rainer; Helfrich, Nicki; Rathmann, Max; Resch, Gustav; Panzer, Christian; Faber, Thomas; Haas, Reinhard; Nathani, Carsten; Holzhey, Matthias; Konstantinaviciute, Inga; Zagamé, Paul; Fougey‐rollas, Arnaud; Le Hir, Boris Fraunhofer ISI, Ecofys, Energy Econonics Group, Rütter + Partner Socioeconomic Research + Consulting, EU‐Commission, Lithuanian Energy Institute (LEI), Société Européenne d'Économie (SEURECO)

net European Union E + H + T (all tech.)

direct and indirect employment (invest + operation), neg. invest‐ment effect, exports/ imports, multiplier, accelerator, budget + cost effect

2009 Solar Photovoltaics in Europe – The role of public policy for tomorrow’s jobs EPIA et al. (EPIA 2009)

net European Union E (PV only)

direct and indirect employment (invest + operation), neg. invest‐ment effect, exports/ imports, budget

2009 Wind at Work Blanco, Isabel; Kjaer, Christian; European Wind Energy Association (EWEA)

gross European Union E (wind energy only)

direct and indirect employment (invest + operation)

2009 Study of the effects on employment of public aid to renewable energy sources Álvarez, Gabriel Calzada; Jara, Raquel Merino; Julián, Juan Ramón Rallo; Bielsa, José Ignacio García for the University Rey Juan Carlos

gross Spain (+USA) E (all tech.)

direct and indirect employment (invest + operation)

2004 +2007

Assessment of economic effects from the support of green electricity in Austria (IHS 2007) Bodenhöfer, H.‐J. for Institute for advanced studies Kärnten (Wien)

net Austria (one‐country)

E (all tech.)

direct and indirect employment (invest + operation), induced effects, exports/ imports, multiplier, budget effect

2004 Employment Effects of the expansion of Renewable Energy Hentrich, Steffen; Wiemers, Jürgen; Ragnitz, Joachim for IWH (Halle Institute for Economics)

net Germany E + H (all tech.)

direct and indirect employment (invest + operation), exports/ imports, multiplier, accelerator, budget effect

2006 The German PV‐Market 2006/2007 – From Decline in Sales to Competition Hoehner for EuPD Research


E (PV only)

direct and indirect employment (invest + operation), exports/ imports, budget effect

2008 Defining, Estimating and forecasting the RE and energy efficiency industries in the US and in Colorado; The American Solar Energy Society Boulder, Colorado Management and Information Services, Inc. Washington, D.C.

gross US and Colorado E, H, T and EE and green technologies

direct + total employment • presentation of RES industry in Colorado • compilation of findings resulting from analysis by ASES and MISI three scenarios

2007 Renewable Energy and Energy Efficiency: Economic Drivers for the 21st century Bezdek, Roger; Management and Information Services, Inc. Washington, D.C., for the American Solar Energy Society Boulder, Colorado

gross US and Ohio E, H, T and EE direct + total employment

2009 Working for the climate, RE and the green Job revolution gross World and se‐ E + H + T+ EE direct and indirect employment (manufacturing, construction,





Effects/description

Rutowitz, Jay; Atherton, Alison; Short, Rebecca; Teske, SvenEREC & Greenpeace

lected coutries O&M, fuel) plus scenario development

2008 Green Jobs: towards a decent work in a sustainable, low‐carbon world; UNEP, ILO, IOE, ITUC Green Jobs Initiative; produced by Worldwatch Institute, sup‐ported by Cornell University, ILR Scholl Global Labor Institute

gross world E, H, T direct and indirect employment, summary of different study results or statistics

2008 Green Economics and Employment: Possibilities for Massachusetts Pollin, Robert University of Massachusetts Amherst

gross Massachusetts • gross employment effects of green jobs (direct and indirect) • focus on Massachusetts (USA) • approach: employment per investment

2007 New Hampshire's Green Economy and Industries: Current employment and future opportunities Gittell, Ross; Magnusson, Matt; Shump, Matt (University of New Hampshire) New Hampshire Employment Security

New Hampshire • overview of the Green Economy in New Hampshire • green jobs legislations • brief employment estimates

2008 Assessment of Regional Employment Effects of RES Integration in the Energy Sector of Latvia Kudrenickis, Ivars; Klavs, Gaidis University of Latvia

gross Latvia • presentation of RES impact on employment in Latvia • gross employment effects (direct and indirect) • employment ratio (jobs per GWh) • PCA Model (Production Chain Assessment)

2004 Job and Economic Development Impact (JEDI) National Renewable Energy Laboratory

gross US states (Cali‐fornia, Colorado, Iowa, Minnesota, Texas)

• spreadsheet‐based wind model based of project lists • input‐output analysis (direct and indirect effects) • multipliers for income, output, jobs (gross employment) • no price effects are taken into account

2007/ 08/09/10

Gross Employment from RES in Germany – a first estimate and updates O'Sullivan, Marlene; Edler, Dietmar; van Mark, Kerstin; Nieder, Thomas; Lehr, Ulrike; Ottmüller, Marion Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU)

gross Germany E, H, T • gross employment (direct and indirect) • investments, O&M, fuel supply • update of former study for the current year

2010 (2011)

Macroeconomic Effects of RES deployment – first results Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU 2011) (Short‐ and long‐term effects of RE deployment on the German labour market, GWS et al.)

net Germany E, H, T • re‐evaluation of “RES Employment Effects (BMU 2006)” • net employment with updated database and methodical en‐

hancement • re‐evaluation of export scenarios

2007 Situational Analysis of the Canadian Renewable energy Sector with a Focus on Human Resource Issues, Final Report, Prepared by “The Delphi Group”, Jan. 2007

gross Canada E, H • direct employment with focus on required skills • estimations are based on interview results and employment

factors

2009 Study of the Macroeconomic Impact of Renewable Energies in Spain, 2009 Edited by Spanish Renewable Energy Association

gross Spain E, (H), T • direct, indirect and induced effects • GDP and employment impact

2006 Gesamtwirtschaftliche, sektorale und ökologische Auswirkungen des EEG (economic, sectoral and ecological effect of the German FIT law)

gross Germany net • marginal not average sizes • direct, indirect and induced effects





Effects/description

Peek, Markus; Gatzen, Christoph; Bartels, Michael; Kalies, Martin; Nill, Moritz; Hilleb‐rand, Bernd; Bleuel, Michaela; Behringer, Jean Marc; Buttermann, Hans Georg EWI, IE, RWI

• cost effects

2009 NREL Response to the Report Study of the Effects on Employment of Public Aid to Renewable Energy Sources from King Juan Carlos University (Spain) Lantz, Eric; Tegen, Suzanne National Renewable Energy Laboratory (NREL)

US, Colorado

2006 Digest of Green Reports and Studies Kammen, Daniel; Kapadia, Kamal; Fripp, Matthias University of California

US

ohne Jahr

JOB GROWTH FROM INVESTMENT IN RENEWABLE ENERGY: AN OVERVIEW n.n.

US

2008 Climate change, innovation and jobs Frankhauser, Samuel; Sehlleier, Friedel; Stern, Nicholas Climate Policy 8 ‐ Earthscan

2010 The Employment Impacts of Economy‐wide Investments in Renewable Energy and Energy Efficiency Garrett‐Peltier, Heidi University of Massachusetts ‐ Amherst

2009 Economic Development Impacts of Community Wind Projects: A Review and Empirical Evaluation Lantz, Eric National Renewable Energy Laboratory

2009 LITERATURE REVIEW OF EMPLOYMENT IMPACT STUDIES OF POWER GENERATION TECHNOLOGIES Phares, Lisa National Energy Technology Laboratory

2004 Economic Impact of Renewable Energy in Pennsylvania Kane, Michael; Pletka, Ryan; Wynne, John; Abiecunas, Jason; Scupham, Sam; Lindstrom, Nate; Jacobson, Ryan; Stevens, Bill Black & Veatch Corporation

US, Pennsylvania

2009 The impact of renewable energy policy on economic growth and employment in the European Union Ragwitz, Mario; Schade, Wolfgang; Breitschopf, Barbara; Walz, Rainer; Helfrich, Nicki; Rathmann, Max; Resch, Gustav; Faber, Thomas; Haas, Reinhard; Panzer, Christian; Nathani, Carsten; Holzhey, Matthias; Zagamé, Paul; Fougeyrollas, Arnaud; Konstanti‐naviciute, Inga

EU





Effects/description

Fraunhofer ISI; ECOFYS; EEG; rütter + partner; Seureco; LEI

2004 Putting Renewables to Work: How Many Jobs Can the Clean Energy Industry Generate?Kammen, Daniel; Kapadia, Kamal; Fripp, Matthias University of California Berkeley

no year

Solar photovoltaic employment in Europe ‐ the role of public policy for tomorrow's solar jobs PV‐Employment; EPIA; WIP‐Renewable Energies; University of Flensburg; National Technical University of Athens

EU

2007 MEASURING STRUCTURAL FUNDS EMPLOYMENT EFFECTS European Commission

2007 International Workshop "Renewable Energy: Employment Effects" ‐ Models, Discussions and Results Kratzat, Marlene; Lehr, Ulrike ZSW; DLR; BMU

2009 Measuring employment effects of technical cooperation interventions Kluve, Jochen; Boldemann, Hanka; Weidnitzer, Eva GTZ

2006 Study on Measuring Employment Effects Centre for Strategy & Evaluation Services, Kent

2009 Werkgelegenheid door Kernenergie Schepers, Benno; De Jorg, Femke

2007 COMMUNICATION FROM THE COMMISSION TO THE COUNCIL AND THE EUROPEAN PARLIAMENT‐ Renewable Energy Road Map: Renewable energies in the 21st century: building a more sustainable future Commission of the European Community

n.n. Review of Green Job Studies

n.n. Renewable Energy Development Creates More Jobs than Fossil Fuels Lehmer, Aaron Ella Baker Center for Human Rights

n.n. Canadian Renewable Electricity Development: Employment Impacts Pembina Institute

Canada



3 Review of gross employment impact studies

In this Chapter gross employment impact studies are reviewed. Since our aim is to identify best practices for the development of methodological guidelines, we focus on methodolo-gy and data sources in our evaluation, less on the actual results of the reviewed studies. In the following subchapter we present the framework used for the evaluation of the stu-dies. Starting with the goals and research questions of gross employment studies, we derive some important aspects that these studies should address in our view. We then present the selection of studies we have reviewed and the evaluation criteria. In Chapter 3.2 the selected studies are reviewed according to the framework presented. The Chapter closes with a brief discussion.

3.1 Framework of evaluation

3.1.1 Goals and research questions

Gross employment impact studies estimate the size or relevance of the renewable energy (RE) industry as a job creator in a country. Since the renewable energy industry is not adequately covered by official business statistics, specific studies are necessary to provide the relevant information. They make the economic activities in an industry that is subject to political regulation transparent and thus provide a reliable information basis for political discussion on the promotion of renewable energy use. Similar cross-sectional industry studies have also been performed for other industries of public interest, e.g. the tourism industry (e.g. Eurostat et al. 2001) or the environmental goods and services industry (OECD 1999). Apart from the RE industry itself, gross employment studies also analyse the extent to which other industries of the economy depend on the RE industry (indirect and induced impacts). Gross employment impact studies can provide answers to questions such as the following:

• How many jobs does the renewable energy industry provide? Which technologies are relevant for job provision?

• Which other industries and how many jobs depend on the renewable energy industry?

• How many jobs are supported by RE product exports?

• What is the position of a country in the various technology fields in comparison with other countries? What are its strengths and weaknesses? Will mainly domestic or foreign enterprises benefit from political RE support?

• How is the RE industry evolving in the course of public RE promotion and what are the future prospects?



Other questions may focus on qualitative aspects of employment:

• How knowledge-intensive and innovative are the economic activites and jobs and how vulnerable are they to relocation to other countries, e.g. low-wage countries?

• What is job quality like in the RE industry with regard to safety issues, shift- and night-work? Which qualification profiles are needed in the RE industry and will they be available in the future if renewable energy use continues to be promoted?

Occasionally gross employment impact studies are also used to argue in favour of promoting RE use. Here we need to stress that gross employment impact studies are partial assessments because they only include the positive employment impacts of renewable energy technology deployment. Potential negative impacts related to the displacement of conventional energy technologies or to reduced household real income due to higher energy prices are not taken into account. In order to assess the full economic impact of promoting renewable energy use, a net impact study that takes all the relevant impact mechanisms into account is clearly necessary.

Despite this, gross impact studies can be helpful in evaluating the overall economic or employment impacts of RE promotion. Since they are usually more technology-specific and more detailed than net impact studies, they can serve to validate the results of net impact studies with regard to the renewable energy industry.

3.1.2 Important aspects to be addressed in gross employment studies

To answer the questions mentioned above, several important aspects should be included or clearly defined in a gross employment impact study.

Definition and system boundary of the renewable energy industry: Gross impact studies focus on the “renewable energy industry”. Whereas in economic statistics industries are usually grouped as enterprises that produce similar goods, the renewable energy industry can be seen as a cross-sectional industry that spans those economic activities that are closely related to the use of renewable energy. The term “use of renewable energy” ideally comprises the complete life cycle of renewable energy facilities, starting with project development and planning, including site preparation, construction and installation of the facility, operation and maintenance, replacement of parts during the operation period and finally their demolition and disposal (see the following Figure for an example of a wind power plant (WPP)).

Each of these activities is supported by a supply chain of other activities which are more or less characteristic of RE use. Installation of a wind turbine, for example, requires a foundation, construction of the wind turbine, manufacturing of the other components



needed to put the wind turbine into operation and connection of the wind turbine to the power grid. Before constructing the wind turbine on location, the various components have to be manufactured and transported to the site, i.e. the tower, the nacelle and the rotor blades. Each of these components is made of various sub-components that need to be manufactured. The further upstream we follow the supply chains, the less specific the components become with regard to the RE technology (e.g. the steel eventually used for wind turbine towers could also be used for other products). At some point it is necessary to draw a boundary between activities counted as part of the RE industry and activities belonging to the rest of the economy.

Project develop-

mentPlanning Installation

of WPPOperation of

WPPDemolition

of WPPSite

preparation

Manuf. of tower

Manuf. of nacelle

Manuf. of rotor blades

Replace-ment of

WPP parts

Construc-tion of wind

turbine

Manuf. of other

components

Connection to the netFoundation

Figure 3-1: Example of the life cycle and supply chains of a wind power plant

Allocation of technologies to the renewable energy field: One question is whether the attribution of a technology and the related economic activities to the field of renewable energy use is always unambiguous or whether cases exist where a technology should only be partly counted? For pure RE technologies like photovoltaics or wind power, the answer is straightforward. In other cases there may be some room for discussion, as the following examples show:

• Pumped storage hydropower plants are partly used as storage facilities for electricity, also using non-renewable electricity to pump water to a higher altitude and then releasing the water when (peak) electricity is needed. Should these plants be counted as belonging completely or only partly to the renewable energy industry?

• Incineration of biomass in municipal solid waste (MSW) incineration plants or other incineration plants: The biogenous fraction of household waste is incinerated together with a fossil fraction in MSW incineration plants. Furthermore waste incineration can be seen as having two functions: waste disposal and energy use. Should the costs of the plants and the related economic activities be completely attributed to the RE industry or partitioned and allocated to the different waste fractions and plant functions and if so, what would be an appropriate allocation method? Similar questions may apply to other technologies for co-incineration of biomass waste.



• Supply of biomass: Cultivation and supply of biomass is usually included in the analysis. How should the collection and supply of biomass waste be dealt with? Where is the boundary between waste management and RE use?

Direct, indirect and induced impacts: When communicating the results of job impact studies, the terms “direct”, “indirect” and “induced” are often used. Usually jobs in the RE industry are communicated as “direct”, whereas jobs in the supporting industries are called “indirect”. Jobs in industries that benefit from consumption expenditures by employees in the direct or indirect industries are defined as induced impacts. These terms and the boundaries between them are not precisely defined and may vary among the existing studies. The boundary between direct and indirect impacts is also related to the system boundary of the renewable energy industry mentioned above.

Consideration of international trade: Supply chains usually stretch across national borders. Therefore the deployment of RE technologies in one country will lead to economic activities in other countries. Thus it is necessary to include import/export relations in the analysis of impacts.

Dynamic aspects: Many RE technologies are in a rather early stage of development. Future development is expected to see significant cost degression and economies of scale, factors that are also likely to change cost structures and labour productivity. For a given technology, the labour input per unit of energy output is expected to decrease due to, e.g.:

• increased automation, scale effects,

• increased specific output (e.g. from solar cells) due to technological progress, and

• learning effects due to greater experience.

Labour productivity outside the RE industry can also be expected to change, i.e. to decline, in the future. Furthermore, the overall economic structural changes over time and thus the links between the RE industry and rest of the economy are not constant. These aspects should ideally be included in studies analysing future employment impacts.

3.1.3 Choice of employment studies

In the course of policy discussions about the pros and cons of public promotion of renewable energy use, a large number of studies has been conducted on the gross impacts of RE deployment. Most of these studies are from OECD countries2. Some of

2 Exceptions include Agama (2003) and Openshaw (2010).



them have been published in reviewed journals. Many belong to the so called “grey literature”. They vary with regard to:

• the range of RE technologies included,

• the scope of impacts,

• the region of analysis (international, national, state or district), or

• the methodological approach.

Since our aim is to identify best practices for employment assessment, we focus on empirical studies that actually generate RE related employment data with a transparent and reproduceable methodology. Thus e.g. we did not include studies that present overviews of employment data from various available sources, e.g. expert judgement, enterprise surveys by industry associations etc. Even though these studies are valuable overviews of the state of the RE industry (e.g. Delphi, 2007), their value for identifying best practices is limited. Our first priority was to include studies at the national or international level with comprehensive treatment of electricity generating RE technologies. We also included selected studies at the sub-national level (especially for the USA) that have an innovative approach or use data sources that could also be used at the national level. If studies are very similar in the method and data sources used, we only analysed one reference study in depth as an example and cited the others as related to it. Table 3-1 contains an overview of the studies that were included in our comparison.

3.1.4 Comparison and evaluation criteria

Based on the above mentioned aspects that we consider to be important for gross employment studies, a number of evaluation criteria were generated to compare and evaluate the studies and identify best practices. These criteria are meant to contribute to the following goals:

• soundness of methods and data used,

• transparency of methods, data and assumptions, and if possible replicability,

• comparability between technologies, countries and over time.



Table 3-1: Overview of gross employment studies included in the comparison

Authors Year of publication

Title Regional focus

RE Technology focus

Employment factor approaches Wei et al. 2010 Putting renewables and energy efficiency to work:

how many jobs can the clean energy industry generate in the US?

US RE electricity

Rutovitz/Atherton 2009 Energy Sector Jobs to 2030: A Global Analysis 10 world regions

RE electricity

Pembina n.y. Canadian Renewable Electricity Development: Employment Impacts

Canada RE electricity

Peterson/Poore (EPRI)

2001 California Renewable Technology: Market and Benefits Assessment

California RE electricity

Singh et al. (REPP)

2001 The work that goes into renewable energy. US PV, wind power, biomass co-firing

Supply chain analysis DTI (ed.) 2004 Renewable Supply Chain Gap Analysis UK Mainly RE electricity Cost based IO modelling Ragwitz et al. 2009 EmployRES: Employment and economic growth

impacts of sustainable energies in the European Union

EU27 RE electricity, heat and fuels

Lantz 2009 Economic Development Benefits from Wind Power in Nebraska: A Report for the Nebraska Energy Office

Nebraska Wind power

Staiss et al. 2006 Wirkungen des Ausbaus der erneuerbaren Energien auf den deutschen Arbeitsmarkt unter besonderer Berücksichtigung des Aussenhandels

DE RE electricity, heat and fuels



Goal of the study/research question: The goal of the study determines the metho-dological approach and the data sources used. Different goals will lead to different approaches. Therefore only studies with common goals can be compared meaningfully.

Scope of the study: Which RE technologies are covered in the study? Is their use for generating electricity covered completely or are some elements missing?

Activities of RE use: Which generic activities related to the use of renewable energy are taken into account? Operation and maintenance of plants, manufacturing and installation, fuel generation and supply? Is reinvestment in existing plants included? To what extent are RE-related supply chains considered? Are exported RE products accounted for?

Impact indicators: Which impact indicators are used to communicate the results (e.g. turnover, gross output, gross value added, number of employed persons or full time equivalent person years)?

Disaggregation of results: Are the results disaggregated with regard to industry, region or social group? Are qualitative job aspects considered, e.g. qualification levels, extent of shift- or night-work, job-related accidents?

Direct and indirect impacts: How are direct impacts defined? Are indirect and induced impacts included and if so, to what extent? Do indirect impacts cover complete supply chains in the rest of the economy?

Methodological approach: Which methodological approach is used and is it appropriate for answering the policy questions posed?

Leakage: Does the analysis take into account that some of the activities triggered by domestic RE facilities take place in foreign countries? Are imports thus considered?

Specific requirements for dynamic studies: Studies that analyse developments over time should ideally include the relevant factors that change over time, e.g. declining costs of RE technologies, changes in labour productivity, cost structures or structural change in the economy.

Data sources and data requirements: Which kinds of data sources are used to calculate jobs and economic impacts? Are they technology-specific or industry averages? Are costs and cost structures based on real project data, studies or expert knowledge?

Based on these evaluation criteria, the strengths and limitations of each approach were analysed and best practices to be included in the guidelines were derived.



3.2 Evaluation and comparison of existing studies

A detailed evaluation of the studies included in the comparison according to the above mentioned criteria is included in the Annex to this report. In this Chapter, we present a synthesis of the comparison.

The examined studies fall into three groups with regard to the methodological approach:

• employment factor approaches, • supply chain analysis, and • cost-based IO modelling.

A side note on enterprise surveys

Another possibility – apart from the above mentioned approaches - to determine employment in the RE industry is to directly conduct a survey of enterprises active in the RE field.

The main objective of the enterprise survey is to obtain first hand data on employment from the enterprises in the RE industry. Furthermore it is possible to obtain additional information, e.g. on enterprise characteristics, field of activity, economic variables such as turnover, exports or value added, job qualification or R&D activities. With a survey the characteristics of the RE industry can be directly captured. This information can be useful for various policy purposes. On the other hand its resource requirements are much higher than those of the approaches listed above. Enterprise surveys have been conducted in two of the studies included in this review (DTI, 2004 and Lehr et al., 2011). Apart from these studies an enterprise survey was also used in a project for the European Wind Energy Association to analyse direct employment in the European wind energy industry (Blanco/Rodrigues, 2009). Due to the rather large resource requirements and since our review focuses on calculation or estimation methods, enterprise surveys as a method are not included in the review, but briefly outlined in the following.

The approach includes the following steps:

• Identification of enterprises active in the RE field: Since the official industry classification does not sufficiently allow to identify enterprises that are active in the RE field, other sources need to be evaluated. These may e.g. include member lists of RE industry associations, other special enterprise lists, trade fair catalogues. The aim is to identify all relevant companies in the RE field. To initially set up the enterprise database may require large resources.

• Survey of relevant company information: A questionnaire is sent to the identified



companies to collect the relevant information. The questionnaire will usually also include questions on economic variables such as turnover or exports or may include questions on qualitative aspects of employment (e.g. qualification of employees).

• Examples for topics in the questionnaire:

− Is the company active in the RE field (definition of RE activities)?

− Which kind of activity (e.g. operation of RE facilities, manufacturing of products for RE use, supplier of intermediate inputs or investment goods, service providers, trad-ing company).

− Which field of technology (e.g. wind power, biogas, photovoltaics).

− Total number of employees, share of employees in the RE field.

− Qualification levels of employees.

− Total turnover, turnover in the RE field.

− Export of products for RE use.

• Analysis of results: The results of the survey are used to extrapolate total em-ployment of the RE industry with an appropriate method.

The survey method has several strengths:

• The data on the RE industry have a high validity, since they are surveyed and indus-try specific. There is no or less need to work with larger industry average data such as in modelling approaches.

• The enterprises in the RE field are identified. Their type of activity or technology field is known. This information is important to assess the potential of the RE industry of a country and to tailor industry support strategies.

• Information on exports can only be taken from company data, since many RE relat-ed products can not be identified in the official trade statistics.

The limitations of this method include the following:

• It is difficult to identify companies that supply dual use goods and to clearly allocate them to the RE industry. These are goods that can be used for RE technologies but also for other technologies (e.g. generators, pumps). The dual-use-problem mainly relates to components of RE technologies, less to the final products.

• The resources needed for enterprise surveys are larger than for the other ap-proaches.



3.2.1 Employment factor approaches

Overview of studies

Employment factor approaches date back to the second half of the 1990s. We included five studies using this approach in our comparison.

Two studies (Singh et al. 2001 and Peterson/Poore, 2001) were published at the beginning of this decade and are included because they are still an important data source for other more recent studies. Singh et al. (2001) performed a detailed labour requirement analysis of PV roof systems, wind power plants and biomass co-firing. Peterson and Poore (2001) analysed the labour requirements of various RE technologies to estimate RE-related jobs as part of the economic benefits of promoting RE deployment in the state of California. Scenarios to the year 2010 were calculated.

An analysis of the gross employment impacts related to increased electricity generation from renewable energy in Canada was published by Pembina (2004). The deployment of the most important RE technologies was analysed to the year 2020. Rutovitz and Atherton (2009) studied the global employment impacts of RE deployment. They calculated and compared employment in the RE sector and conventional electricity generation for two global scenarios with different assumptions on electricity generation from renewable energy sources and efficient use of electricity to the year 2050. Wei et al. (2010) can be seen as an update of the Kammen et al. (2004) study. Based on a comparison of employment factors for the relevant RE technologies in various studies, an analytical model is set up that allows employment to be projected to the year 2030 under various renewable portfolio standards, energy efficiency and low carbon energy scenarios.

The following studies have similar approches and were thus partly included, but not evaluated in detail: Agama (2003), Heavner/Churchill (2002), Kammen et al. (2004), Gittell/Magnusson (2007) and Moreno/Lopez (2008).

Objectives

Most of the studies aim to:

• describe the present economic significance (or the “size”) of the renewable energy industry in terms of employment, and

• partly estimate the future significance of the RE industry in the course of further promotion of RE technologies (Pembina 2004, Rutovitz/Atherton 2009 and Wei et al (2010).

Further aspects of RE promotion are occasionally in the focus of the authors, e.g.:



• the regional distribution of jobs, and

• job qualifications or working conditions (Singh et al., 2001).

In many studies, the results of the gross employment impact studies are implicitly used to argue in favour of policy support to intensify renewable energy deployment, even though this would clearly require a net impact study that accounts for displaced jobs in conventional energy industries.

Scope

Most of the studies focus on RE use for electricity generation. Singh et al. (2001) analyse the employment requirements for selected technologies in detail, i.e. PV rooftop systems, wind power plants and biomass co-firing in coal power plants. The other studies are more comprehensive and generally include the relevant technologies. Large hydropower plants are not included in the reviewed studies.

System boundaries

System boundaries are not a prominent issue in the studies under consideration. Generally, the system boundaries of the technologies included are not explicitly defined. Most studies include planning, manufacturing, construction and installation (MCI) and operation and maintenance (O&M) as the most important life cycle phases of RE facilities. Demilition of plants is usually not included. The most relevant activities in the RE-related supply chain are generally included, although exact system boundaries are not explicitly mentioned. Singh et al. (2001) explicitly mention the activities included in their employment analysis.

Methodological approach

Employment factor approaches estimate the job impacts of RE use by multiplying the installed capacities of RE facilities, capacity additions (e.g. in MW) or energy production (in GWh) by employment factors (jobs per MW or GWh). Usually the employment factors are technology-specific and estimated separately for the various life cycle phases. These phases often differentiate the manufacturing and installation phase, the operation and maintenance phase and the fuel supply phase for biomass use. Occasionally the life cycle phases are further broken down into distinct production activities (e.g. planning, manufacturing of components and final products, transport to the installation site, construction work and installation).



New installedcapacity

[MW]x

Manufacturing,Construction and

Installation

Job-yearsper MW

= Total Job-yearsin MCI

Capacityin use[MW]

xOperation & Maintenance Jobsper MW

= Total Jobs in O&M

Biomass input/Energy output

[GWh]xBiomass Supply Jobs

per GWh= Total Jobs

in BS

Figure 3-2: Calculation of employment using employment factors

Among the reviewed studies only Rutovitz and Atherton (2009) account for imports and exports. For each world region a share of imported equipment and the regions from where the equipment is imported are roughly estimated across all technologies. Exports are included in a similar way. Pembina (2004) consider leakage via imports though the assumptions are not clear. The other studies neglect imports and exports.

Generation of employment factors

Potentially, this approach has the advantage of being very technology-specific. The employment factors can be based on data from actual RE facilities or feasibility studies or from enterprises in the RE industry. Some examples: Singh et al. (2001) made a detailed analysis of the working hours required in the various life cycle phases of installing and operating wind power plants and roof-based PV-systems. The data were generated using a survey of companies in the RE industry. Jobs needed for biomass co-firing were based on a technical literature review. Peterson/Poore (2001) base their job factors on cost estimates from detailed feasibility studies for the installation and operation of various RE technologies. In contrast, the employment costs for installation and maintenance are estimated with rather simplifying assumptions used across all technologies, thus losing technology specificity. Other studies quoting enterprise data for their employment factors include Pembina (2004), though no specific details are provided. Employment factors can in principal be derived from any employment analysis regardless of the methodological approach by relating employment results to energy capacity and output data (see, e.g. some examples in Rutovitz/Atherton, 2009). Various studies compare the employment factors from other existing studies and choose “appropriate” factors (e.g. by calculating mean values) for their own analyses (e.g. Heavner/Churchill, 2002, Kammen et al., 2004, Rutovitz/Atherton, 2009 and Wei et al., 2010).

In their study of RE-related employment impacts in all world regions, Rutovitz/Atherton were confronted with the specific problem of estimating job factors for developing world



regions for which data availability tends to be poor. They use differences in labour productivity between world regions to adapt job factors from OECD countries to other world regions.

A major problem with the empirical use of the employment factor approach is the large variation in employment factors for seemingly identical technologies which can differ by a factor of three or four (see Wei et al., 2010 for a comparison of employment factors). The reasons for these large differences are not clear. Possible explanations could be site-specific variations or differences due to different technology scales or system boundaries. Especially with regard to biomass use, different technology definitions seem to play a role including, e.g. dedicated biomass power plants, biomass co-firing in coal power plants or MSW incineration plants.

Employment indicators

Most studies distinguish between temporary jobs related to the manufacturing, construction and installation (MCI) phase and permanent jobs related to operation and maintenance and biomass supply. Temporary jobs in the MCI phase are usually communicated in job-years, whereas permanent jobs are shown as the number of jobs or employed persons. This also holds for the employment factors used to calculate the employment impacts.

Some studies explicitly communicate jobs or the number of employed persons as full-time equivalents (FTE, e.g. Singh et al., 2001, Wei et al., 2010). This makes it possible to adequately take full-time and part-time employees into account. In some studies this is implicitly done by calculating the number of jobs from labour costs by assuming average annual salaries (e.g. Peterson/ Poore, 2001). When comparing employment impacts across countries or over different time periods, one has to bear in mind that the annual working hours of a full-time equivalent job change differ significantly between countries and over time periods. Thus, e.g. a full-time equivalent in the United States or in South Korea has more working hours than a full-time equivalent in France or the Netherlands. Most studies using FTE job factors determined for other countries do not account for these differences.

To calculate employment impacts, employment factors for the MCI and the O&M phase are usually related to peak plant capacity (e.g. MWp). Employment factors for the biomass supply phase are often related to the energy output of the biomass plant as the most adequate determinant of biomass input. Given the effective operating time of a plant (hours per year) or a capacity factor (effective operating time divided by maximum operating time), employment factors per unit of energy output can be transformed into employment factors per unit of capacity.



Since different energy technologies are characterised by different capacity factors, Kammen et al. (2004) propose to present employment factors by relating the number of jobs to average plant capacity (e.g. MWa), thus allowing employment intensity to be compared between technologies. They also divide MCI jobs by the average plant lifetime, thus distributing jobs across the plant’s life and making them comparable to O&M and biomass supply jobs. Since MCI jobs are concentrated at the beginning of a plant’s life, information about the timeline of job creation is lost in this approach. It may also pose a problem for calculating scenarios of future RE technology deployment, though to a lesser extent if there is a continuous deployment of RE facilities.

Direct and indirect impacts

Most employment factor studies focus on direct jobs in the “renewable energy industry”. These direct jobs usually include activities in the RE supply chain that have a clear link to renewable energy use and can be seen as characteristic for renewable energy use. Even though they are termed as direct, the activities often belong to different levels of the supply chain. Example: Direct jobs in PV installations often include manufacturing solar cells, solar modules and the installation of the final PV system. These successive activities form a supply chain, each producing an input for the next activity. Still, they are usually considered to be direct RE impacts. Thus, what the existing studies term “direct” is not constrained to the first level of a supply chain. It can include activities producing intermediate inputs for other activities that are also considered characteristic for the RE industry. At some point of the supply chain a boundary is drawn that separates the RE supply chain from the rest of the economy. This boundary is not always clearly defined in the existing studies.

Most studies term jobs in the “RE industry” as direct and jobs in the rest of the economy supplying the RE industry as indirect. Induced impacts are not considered in the employment factor approaches. The different system boundaries used generally make a comparison between studies difficult.

Dynamic aspects

Three of the five reviewed studies analyse the future development of jobs in the renewable energy industry due to promotion of RE deployment. Dynamic aspects are considered in different ways and to different extents. Pembina (2004) does not consider any dynamic aspects in the projection to the year 2020. The same employment factors are used throughout the whole projection period. In their projections to the year 2030, Wei et al. (2010) also neglect probable changes in the employment factors, especially cost decreases of RE technologies and changes in labour productivity. Thus, in these two



studies, the employment projections for the years 2020 and 2030 are probably overestimated. Wei et al. (2010) mention this shortcoming in their discussion and give a rough estimate of how large this overestimation could be in the year 2020. In their projections to the year 2030, Rutovitz and Atherton (2009) take dynamic aspects into account to a large extent. Future job factors are adjusted for declining costs or technology learning rates. For each RE technology, the annual decline of job factors (jobs per MW capacity) is based on cost degression assumptions.

Conclusions

The employment factor approach has the potential to be accurate and technology-specific if the data sources for the employment factors are accurate and reliable. Unfortunately, there are only a few data sources that are used in several studies and the job factors for the same technologies vary greatly between the sources (up to a factor of four). In many cases the generation of employment factors is poorly documented so that definitions or the system boundaries of technologies are not always transparent. Since the existing employment factors are often applied to different countries or time periods, it is difficult to judge whether the employment factors are suitable. Due to the large variations between studies we consider the results generated using this method to contain rather large uncertainties. For future projections of RE related employment, it is necessary to appropriately take employment factor changes into account.

3.2.2 Supply chain analysis

Overview of studies

Cost-based supply chain analysis is a method that, to our knowledge, has only been used by DTI (2004). This study was done in order to estimate the current and future size of the renewable energy industry in the United Kingdom with a special focus on Scotland. It employs a detailed analysis of the supply chains connected to RE technology deployment.

Objectives

The main objective is to estimate the current and future size of the renewable energy industry in the United Kingdom with a special focus on Scotland. Apart from employment, the “monetary value”, which is similar to turnover, is measured. The study identifies the companies active in this industry and their position in the RE-related supply chains. For the estimation of the future development of the RE industry, the implementation of national and Scottish RE goals in the year 2020 is assumed. Furthermore gaps in the existing supply chains and opportunities and constraints for British RE industry are



determined. From this analysis, recommendations are derived for the further development of the RE industry.

Scope

The study covers all the relevant RE technologies for electricity and heat generation and for the production of biofuels, with the exception of large hydropower plants. Mature as well as emerging technologies are considered. Furthermore, the analysis also takes several connected technologies into consideration, such as energy storage technologies, fuel cells and hydrogen production. In some cases (e.g. biomass, production of biofuels), only the generic technologies are mentioned without further specification.

System boundaries

Each technology is represented by a technology tree that maps its supply chain. The supply chain is illustrated as a pyramid with various tiers. The top tier consists of the project developer, the turnkey contractor responsible for constructing the RE facility and the operator. The next tier contains the suppliers of the technology’s main components. The suppliers of sub-componentes are located in the following tier and so on down to the raw material suppliers in the bottom tier. An example of the supply chain pyramid is given for a wind power plant, but no details are presented for other technologies.

The supply chain is generally traced to the third tier. Only activities or products that are specific to renewable energy use are included.


A typical template project is defined for each technology. The templates contain information about the capacity of a RE facility, fixed and variable project costs and the duration of development, construction and operation periods. Also, for each technology, a typical supply chain is constructed. The monetary value (cost + profit margin) of each step in the supply chain is determined and subdivided into material costs, labour costs and a profit margin. Labour costs are then transformed into labour requirements by assuming typical wages. The material costs are then further subdivided into components of the next tier of the supply chain. In this way, labour requirements are estimated for each component of the supply chain and then added up to arrive at the total labour requirement of a RE technology. These labour requirements are then related to the typical capacity of the project in order to calculate job factors per unit of capacity. For each RE technology the job factors are then multiplied by the capacities in development, construction or operation and added up to yield the total number of jobs related to the use of renewable energy in the UK.



The study accounts for imports by estimating the import content for each technology component at each tier, i.e. the share of supply by foreign enterprises. On the other hand jobs in export activites are added. Thus foreign trade is fully taken into account.

Data sources

Data on the technical and economic features of technologies (e.g. specific costs, cost structures) are based on expert knowledge. In addition, an extensive survey of almost 560 companies from the RE industry and expert interviews were used to gather further information (e.g. on exports).


Employment is presented in full-time equivalent jobs. It is broken down by life cycle phase (development, construction and operation) and by the supply chain tier.


Due to the supply chain approach that covers several tiers of the supply chain, it is not possible to make a distinction between direct and indirect jobs as defined for this review (Chapter 3.2). The authors speak of direct and indirect jobs in the RE supply chain. Since the supply chains of the technologies are not specified in the report, it is not possible to assess the extent of indirect impacts taken into account or to compare them to other studies. Induced job impacts are roughly estimated by using a multiplier of 0.25 for all technologies.

Dynamic aspects

Cost degression and advances in labour productivity are accounted for when estimating the future costs and labour requirements of each technology. The import content of future capacity additions is assumed to decline. Here two scenarios are considered, one with 100% domestic content and one with import content remaining at the level of 2003.

Conclusions

The supply chain approach is a sophisticated one that takes the complexity of technolo-gies and supply chains into account and analyses them on a detailed level. Data on the activities of British companies in the RE field is based on an extensive company survey. The resource requirements of this approach are probably rather large. A downside of the study is the missing documentation of the RE technology supply chains in the report. Only



one example is given for wind power. The costs and cost structures used in the study are also not specified. This makes it difficult to evaluate the results.

3.2.3 Cost based IO modelling

Cost-based IO modelling is widely used to estimate the economic and employment im-pacts of RE use. It combines techno-economic data with input-output modelling.

Overview of studies

In our review we focus on three exemplary studies. Lantz (2009) analyse the economic benefits of wind power in the state of Nebraska and of extending wind power deployment by 7800 MW which was envisioned by the US Department of Energy as Nebraska’s contribution to the 20% wind scenario for the year 2030. The study is an example of applying the JEDI (Jobs and Economic Development Impacts) model. This model is commonly used in the United States, mostly at state level (Goldberg et al. 2004). The JEDI model was originally developed for wind power plants but has since been applied to other RE technologies.

Lehr et al. (2011) study the job impacts of RE deployment in Germany. They estimate the current size of the RE industry in Germany and the gross and the net employment impacts of further RE technology deployment. The study is included, since it is one of the most advanced examples of the IO modelling approach. It is the most recent version of a suite of studies that started with Staiss et al. (2006). An english summary of the study was published as BMU (2010).

Ragwitz et al. (2009) analyse the past and current size of the RE industry in terms of the gross value added and employment for each of the EU 27 member states. The gross and net employment impacts of an intensified use of renewable energy, that meets the policy targets for the years 2020 and 2030, are also estimated. A distincitve feature of this study is the application of the same approach to a larger number of countries and the estimation of cross-boundary effects by using a multiregional IO model.

This evaluation focuses on the gross employment parts of the latter two studies. Similar studies from a methodological viewpoint, that were not analysed in detail include Black & Veatch (2004), Haas et al. (2006), Loomis/Hinman (2009) and Ratliff et al. 2010.

Objectives

Lantz (2009) focuses on the employment impacts of increased wind energy promotion in the state of Nebraska. The main objective of the other two studies is to estimate the



significance of the RE industry in terms of its contribution to GDP and employment. Ragwitz et al. (2009) include the past development since 1990, the current status (2005) and the potential to the years 2020 and 2030. Lehr et al. (2011) provide a status report on the employment related to RE energy use for the year 2009. Apart from the number of employees, qualitative aspects of employment and the export potential of German companies are analysed. Furthermore, they make a projection of gross employment to the year 2030 under various scenarios.

Scope and system boundaries

As already mentioned, Lantz (2009) focuses on wind energy only. The other two studies comprehensively cover RE use for electricity generation, heat generation and biofuels production. The studies take the relevant life cycle phases of RE facilities into account (planning, manufacturing, construction and installation, and operation and maintenance). Demolition of plants is not considered. Of the three studies, Ragwitz et al. (2009) and Lehr et al. (2011) take reinvestment in existing RE facilities into account. Lantz (2009) only mentions the installation of new facilities. Furthermore Lantz (2009) does not consider “export” activities of the Nebraska wind power industry, i.e. manufacturing activities for wind power plants outside Nebraska. The other two studies fully account for exports.


Cost based IO modelling combines techno-economic data on RE technologies with input-output modelling. In short, an input-output (IO) model contains data on the flow of goods and services between the industries of a national economy and from the industries to final demand. In an underlying input-output table, the supply of goods to other industries and final demand is represented for each industry. The table also contains the cost or input structures of every industry as well as information on gross value added and employment. This information makes it possible to calculate the indirect economic (and job) impacts triggered by an additional demand for goods in all the industries of the economy while taking supply chain effects into account. The level of disaggregation in input-output models ranges from about 60 industries for European countries to about 500 industries for the US or Japan. Multi-regional IO models link single-country IO models to each other via detailed trade flow tables, thus allowing supply chain impacts to be calculated across country borders.

Starting point for the calculation of employment impacts are the installed capacities, capacity addition and energy production of RE facilities in the considered year. For each of the technologies, the specific installation costs, O&M costs and fuel supply costs per unit of capacity or energy output are determined. Multiplied by the capacity data, we



obtain the total annual investment expenditures, operation and maintenance expenditures and biomass fuel expenditures of RE use. The costs are then distributed to cost components (e.g. the PV module, the inverter and the rest of the system in the case of PV technology). These are allocated to the supplying industries as represented in the input-output model. At the cost component level, or at the industry level, import shares are determined which indicate the share of goods or services that are delivered from outside the country or region under consideration.

The allocation of expenditures to supplying industries can be seen as the interface between the techno-economic information and the IO model. Based on this information, the IO model is then applied to estimate (1) the direct gross value added and employment in these industries and (2) the indirect economic and employment impacts triggered by the RE industry in the rest of the economy. Induced impacts can also be calculated with the IO model. Indirect and induced impacts are often directly calculated using impact multipliers that have been generated with IO models.

Lantz (2009) uses IO multipliers for the state of Nebraska from the widely used IMPLAN database. In the JEDI model, similar multipliers also exist for other US states and have been used in similar studies of RE deployment. Lehr et al. (2011) estimate present employment in the RE industry with a static IO model for Germany. Ragwitz et al. (2009) use the static, multi-regional IO model MULTIREG that covers almost all the EU member states and their most important trading partner countries.

A different approach is used to estimate export-related impacts. Exports of RE-related products can only be partially identified from trade statistics (e.g. wind turbines, hydro turbines, energy wood) since, in most cases, the commodity classification of trade statistics is not detailed enough to capture RE products (e.g. PV cells or modules are grouped together with other similar products). Therefore it is necessary to base RE exports on other sources. Lehr et al. (2011) take their export data from a survey of enterprises active in the RE field. Ragwitz et al. (2009) use existing studies and surveys and company information to generate world market shares of the EU countries for selected products in the RE field (silicon wafers, PV cells, PV modules and the major wind turbine components (towers, nacelles and rotor blades)). For other RE technologies, exports are estimated within the multi-regional IO model.

Data sources

Data on technical and economic features of the technologies (e.g. specific costs, cost structures) are usually based on technical literature and expert knowledge. Lehr et al. (2006) additionally conducted an extensive survey of companies in the RE field to obtain better information on the cost structure of technologies and on import and export



relationships. Ragwitz et al. (2009) used data from the dedicated Green-X database (Huber et al., 2004), which contains extensive techno-economic data on RE technologies in all EU countries as well as other, mainly developed, countries.


Employment impacts are presented in full-time equivalent jobs. The results in Lehr et al. (2010) refer to the number of employed persons. Generally the results are subdivided by life cycle phase (construction, operation and maintenance and fuel supply) and RE technology.


The distinction between direct and indirect jobs is linked to the representation of RE expenditures in the IO model. The industries to which the expenditures are allocated are considered direct. Indirect are all the other industries that supply inputs to these industries. Induced are impacts in industries that supply goods and services to the employees in the direct and indirect industries.

Dynamic aspects

For the estimation of past employment impacts, Ragwitz et al. (2009) use a static multi-regional IO model that does not capture structural change in the EU countries. Changes in labour productivity as an important determinant of employment are adequately taken into account. For their future projections of gross employment, Ragwitz et al. (2009) and Lehr et al. (2006) account for cost degression and advances in labour productivity when estimating the future costs and labour requirements of each technology. Different future import and export relationships are illustrated in scenarios since they are difficult to project. Lantz (2009) also considers future cost degression in his projection to the year 2030. Future import shares are varied in several scenarios at a detailed technology level. The impact multipliers used in the model seem to remain constant over the projection period. Thus structural change in the economy is neglected. It is unclear whether employment coefficients per unit of economic output are also held constant. If so, this would lead to an overestimation of indirect and induced employment impacts.

Conclusions

Cost-based IO modelling combines technology specific data on capacities, costs and cost structures with economic modelling. It allows gross employment in the RE industry to be estimated within a consistent framework that also enables economic impacts to be calcu-lated with the same methodological approach (e.g. gross value added as a contribution to



GDP). This is the only approach able to fully take indirect and induced impacts into ac-count. A major assumption of this approach is that the industries included in the IO model are sufficient proxies for the companies of the RE industry and its supply chain with regard to cost structures, import relations or employment per unit of output. The impact of this assumption can be reduced by including additional technology-specific information in the IO model, e.g. by incorporating new RE-related industries or by using data from enterprise surveys. Enterprise data are also important to estimate the exports.

3.3 Discussion

The review of existing studies has revealed the strengths and limitations of the various approaches. Employment factor approaches are easy to understand and to communicate. They have the potential of being very technology-specific and based on actual project or enterprise data. The quality of the results largely depends on the quality of the employ-ment factors used. Unfortunately, studies with thorough assessments of employment re-quirements for RE technology deployment and use are scarce. Employment factor studies are often based on the same few sources, even though a lack of documentation and transparency make it difficult to compare and use the employment factors. Moreover, the existing employment factors show large differences for the same technologies. To en-hance the reliability of results, sound and well documented studies generating employ-ment factors would be beneficial.

The supply chain method is a sophisticated approach to capture the complexity of activi-ties and supply chains related to renewable energy use. Combining this with an enterprise survey should provide reliable results, but such a study would require rather large financial and personal resources.

Cost-based IO modelling combines the strengths of technological specificity (e.g. costs and cost structures) with economic comprehensiveness (indirect and induced impacts). A consistent methodological framework allows economic and employment impacts to be calculated simultaneously, thus making plausibility checks possible. One limitation that comes with the use of an input-output model is the assumption of industry averages for sectoral input structures, import relations and employment coefficients. This limitation can be relaxed by integrating specific enterprise data into the IO model.

For all three approaches, the reliability of the results strongly depends upon the quality of the input data and the assumptions. Therefore, in general, a good documentation of input data and assumptions is needed to be able to assess the results.



4 Review of studies with net effects

In this Chapter net employment impact studies are reviewed. Since our aim is to identify best practices for the development of methodological guidelines, we focus on methodolog-ical aspects and not on current results of the reviewed studies. In the following subchapter we present first the framework used for the evaluation of the studies. Starting with basic differences between net and gross impacts, looking at research questions and scope of employment studies, discussing impulses and impact mechanisms as well as scenarios, we elaborate some important aspects that these studies should address or include in our view. For the quick reader who is not interested in methodological aspects we suggest to start with Chapter 4.2 where we review the selected studies according to the framework presented.

4.1 Framework of evaluation

4.1.1 Differences between net and gross impact studies

While gross impact studies focus on the effects only within the RE industry, the overall goal of net studies is to answer how or to what extent RE deployment positively and nega-tively affects overall employment and welfare. Similar aspects have been analysed for other areas of research, e.g. impact of climate mitigation measures on welfare or em-ployment. In this report, we focus on impact assessment studies in the power sector. Be-fore we begin reviewing net impact studies, we give a brief characterization of net studies enabling the reader to distinguish them from gross studies. To do so, we make use of cer-tain terms which are explained in the following Chapters.

In general, a various economic mechanisms with different modelling approaches (types) are incorporated in net studies. This makes them rather complex. As already mentioned, net studies focus on the overall economic impact of RE deployment. This encompasses not only the demand effects of the RE-industry, but goes beyond, and affects household consumption and the production of non-RE industries. A net impact study should take into account positive and negative effects of RE deployment within the RE industry and be-yond, namely in all other industries as well as effects on households that in turn are affect-ing production and consumption. Negative effects are those that have a negative impact on employment and reduce employment in other sectors of the economy, i.e. “outside” the RE sector. To be clear net effects: represent the difference between a situation (scenario) with and without RE deployment. So they show the actual net impact of advanced RE deployment.



Table 4-1: Distinction between gross and net impact studies

Criteria Gross Net Impact on RE sector (output) Overall economy, welfare Impulse investments, O&M, ex-

ports and imports investments, O&M, avoided in-vestments, avoided O&M, trade (export, import) and price changes

Impact mechanism positive effect: • direct • indirect • induced type 1

positive and negative effects: • direct, • indirect, • induced (type 2)

Scenario as outlook for 20xx differences between scenarios • RE deployment scenario • Reference scenario

Indicators gross employment, turnover, value added, share of GDP

net employment change, GDP

Dynamic and other as-pects

(productivity) productivity, technological change, multiplier effects; price and structural changes

4.1.2 Approach for the review

The review of net studies is quite challenging since net impact studies show many facets, can be done with a variety of approaches and differing complexity. Therefore, we develop a taxonomy for the various aspects, factors or elements of net studies. First, we classify the main determining factors of net impact studies into three groups (see also Figure 4.1) that we call levels, which have influence on the dimensions of each other. They comprise:

• research questions of net impact studies,

• quality aspects for studies, and

• scope of net impact studies.

Second, we assign to each level relevant features or elements of net impact studies, which we call dimensions. The scope of the study determines to a certain extent its meth-odological approach but the research question influences the scope of the study and, in turn, the quality requirements. Despite the interdependence of the levels, the aim is to provide a systematic approach for the analysis of net studies and to answer the questions posed in Chapter 2.



impact studies

researchquestion

time dimension

regional level

economic dimension

economic impact indicators

quality of study

input data (sources)

modelling approach (type)

scope of study

RE technology

activities

impulses

impact mechanism & impacts

dynamic aspects

scenario

leakage, ...

Figure 4-1: Level and dimensions of net studies

Research questions

In contrast to gross impact studies, the analytical focus of the research question in net impact studies is on the overall economic impact, not on the economic relevance of the RE industry. Thus, the research focus always considers overall impacts no matter what the time, regional or economic dimensions or impact indicators are (Figure 4.1, see also Chapter 2). While the time dimension comprises the time horizon of the study and the regional dimensions the geographic coverage, the economic dimension refers to the as-sessment of impact indicators in one single, a few selected or in all sectors (total econ-omy). However, given the research focus to be on overall economic effects, the feasible combinations of the dimensions limits the research focus on:

• Time horizon: What is the present and future impact of RE deployment on ......?

• Impact indicator: What is the .... impact of RE deployment on employment or GDP, .... in .....?

• Economic dimension: What is the .... impact of RE deployment on ... in the sector x or in all sectors (total economy) ....?

• Aggregation level: What is the .... impact of RE deployment on ... in ..... the region, country, EU, ... ?

Impact indicators such as net employment or GDP are usually applied to depict the impact of RE deployment on the economy and not on a RE sector, while e.g. turnover is suited to reflect impacts in sectors or RE-technologies. Impact assessments on a global level rely on indicators such as GDP or net employment while for assessments at a local level turn-over or gross output are fitting indicators.



Besides these dimensions, the research focus could be much more distinct. For example some studies aim at the impact of technologies – which technology induces the highest number of jobs - or just aims at a comparison between two technology paths without tak-ing into account different energy demand, supply or changes in consumption. Figure 4-2 shows which combinations of elements represent proper research questions.

Figure 4-2: Dimension of research questions

The overall economic impact can then be broken down to industries. In general, net stud-ies always represent the effect on the overall economy, even if only effects in one industry are reported. The term “overall economy” refers here not the spectrum of the reported industries and sectors, but to the spectrum of industries and sectors included in modelling the impact mechanisms and effects that go beyond the RE-industry.

Furthermore, net as well as gross impact studies investigate the impact of RE deployment due to different RE policy schemes, e.g. quota or feed-in tariffs, and specific promotion schemes, e.g. for single technologies.

Closing, it can be said that the general research question addressed by a net study is:

What is the overall economic impact of RE policy, RE support RE technology or de-ployment on selected industries/economic sectors or the total economy, measured by macroeconomic indicators such as changes in GDP, value added, net employ-ment, ... at present and/or in the future in a region, country .... ?



Scope of impact studies

The scope of a net impact study encompasses several dimensions that are briefly outlined or explained in the following. The impact mechanisms are one of the principal factors of any model assessing economic impacts. In addition, dynamic aspects, leakages and sce-narios are necessary to capture diverse deployment impacts with differing degrees:

• RE technologies (see Chapter 3).

• RE activities (see Chapter 3).

• Impulses: economic impulses initiate the impact mechanisms. They arise from (avoided) investments (MCI), (avoided) operation and maintenance activities, (avoided) fuel supply, prices, trade and supporting activities. They are triggered by RE activities but their significance goes beyond the RE sector. They induce macroeconomic changes – changes at an aggregated level.

• Impact mechanism and impacts: the impact mechanism translates the economic im-pulse into an economic effect. Mechanism stands for the way and mode of actions of the diverse economic impulses that translates into economic impacts expressed as e.g. employment effect. We distinguish between direct, indirect and induced effects (of type 1 and 2), all triggered by diverse impulses.

• Dynamic aspects: In this report these include technology changes, learning and multi-plier effects. The first is expressed by, e.g. different learning cost curves and productiv-ity changes, and refers to RE technologies that are at a development stage where sig-nificant cost decreases and economies of scale effects are feasible, both of which af-fect productivity (see also Chapter 3). Even outside the RE sector, productivity changes occur, structures adjust and the input-output relations between industries change. Fur-thermore, innovative advantages can be represented by changes in import/export rela-tions that in turn are due to price or quality advantages. The second aspect refers to induced effects that are not cut off after one year or cycle but run for several rounds – are self energizing – and hence should be taken into account as multiplier and accel-erator effects over a long period.

• Leakages: The development and deployment of RE stretch across country borders and cause technological and economic changes. Therefore, impacts on economic activities in other countries could be included via export and import activities.

• Scenario: Scenarios with different policies, prices etc. are developed to compare the RE deployment between two different policy paths. Normally, comprehensive net im-pact studies estimate the net impact on GDP as the difference between the GDP of a zero-RE (or low-level) deployment (no RE policy) and an advanced RE deployment scenario.

The various dimensions with their differing degree of detail and complexity offer a broad array of impact studies with diverging comprehensiveness. We depict the various combi-nations and interdependences between three selected dimensions by a cube in Figure



4-3. The blue cube shows feasible combinations for gross studies, while a net study is supposed to go beyond the blue cube.

export & import

impacts

operation & maintenance

direct

indirect

1st type induced

installation, reinvestment

fuel supply & generation

transparency

marketing

R&D

2nd type induced

netgross

activities

dynamic aspects

manufacturingconstruction

gov‘t support

Figure 4-3: Combination of three selected scope dimensions

Data and modelling issues – quality aspects

The focus on quality aspects should help to answer the questions whether the chosen models and the used data are appropriate for the research objective and whether the con-sidered mechanisms and the calculations and data sources are transparent and compre-hensible.

In general, quality aspects refer to the disaggregation level of data sources used to calcu-late jobs and economic impacts. The sources could rely on technology-specific or industry averages, and be based on costs and cost structures, on real project data, studies, or expert knowledge. Further, data could be collected from secondary data sources or de-rived from surveys and interviews. The greater the number of technologies considered and the more specific the research question, the higher the degree of disaggregated in-formation and the less suitable are data based on industry averages or cost structures. However, the type of data required also depends on the methodological approach. In the case of net studies, the quality standard of data is very difficult to define since the models encompass a broad array of data that stem from various data sources, some of them are



publicly available, others rely on individual data bases or surveys and some are endoge-nous data.

Regarding modelling types, there are several approaches (Rothengatter et al. 2008, Pfaf-fenberger 1995, Kratzat et al 2007) that use a variety of methods from simple analytical approaches, input-output calculations, econometric models, optimization models to gen-eral equilibrium models as well as system dynamic models each aimed at specific re-search questions and economic theory. While the first two are usually applied by (gross) impact studies modelling effects of RE deployment at sector level with just few inputs for scope dimensions, the latter are comprehensive models used to depict overall economic effects (net impacts) by combining many scope dimensions under rather challenging crite-ria. The more complex and comprehensive the modelling type, the more sophisticated the results.

With respect to studies in which the authors claim to assess net effects we make a rough distinction between analytical approaches and complex macro-economic modelling ap-proaches. While the first approach allows integrating only a few impact mechanisms, rely-ing on few aggregated factors and capturing selected impacts, the latter are more com-prehensive regarding the dimensions selected and the data required. They apply macro-economic models either an econometric, general equilibrium, or system dynamic models and they strive to incorporate all impact mechanisms. The modelling approaches applied in net impact studies are depicted in Figure 4-4.

modelling approaches in net impact studies

00 analytical modelling approach macro-economic modelling approach

employment factors:

• data: labor input per capacity, production and generation,

• effects: direct, indirect & induced impulses: investment, O&M, fuel.

IO-model:•• data: IO-

coefficients, consumption vector

• effects: direct, indirect & induced

• impulses: investment, O&M, fuel and avoided investment etc., RE income, price

macro-economic model:

• types: general equilibrium model, econometric model, system dynamics model

• data:• macro-economic data (economic and

demographic data, IO-table), • energy sector data (supply, demand, prices)• trade relations

• effects: direct, indirect & induced effects, • impulses: investment, O&M, fuel and avoided

investment etc., RE income, price, trade and others.

Figure 4-4: Modelling approaches



4.1.3 Choice of impulses, impact mechanisms and effects

To derive a solid idea on how RE policies/deployment lead to economic effects we need a scheme that shows the relationship and the intermediate steps. Therefore, we use a causal chain that points out the steps between RE policies/RE deployment and impacts. The principal idea is that policies induce RE activities that in turn cause economic im-pulses which have to be translated via an impact mechanism into economic impacts (ef-fects). Figure 4-5 depicts the main functional chain caused by RE policies, RE support schemes or RE deployment. The economic impulses (e.g. investments) generated by RE technologies and activities (MCI) have direct (intermediate) impacts on demand, produc-tion and consumption as well as on competitiveness that evolves into further impacts. To capture and quantify these impacts, a mechanism to translate these impulses into im-pacts/effects is needed. The translation mechanisms are called impact mechanisms and are part of the complex macroeconomic module encompassing links or interdependences between diverse economic actors and/or sectors. The impact mechanism also translates the (intermediate) impacts on consumption or productions into final impacts on employ-ment - employment effects.

activities in

RE technologies

impulses positive & negative impact mechanisms impactspolicies

Figure 4-5: Functional impulse chain

In the following we show which impulses are taken into account, which mechanisms are applied and which impacts on employment (effects) are shown when modelling economic RE deployment impacts.

4.1.3.1 Impulses in net impact studies

Impulses are considered as the activator of an economic mechanism leading to economic effects. Impulses lead to positive and negative effects. The key impulses (of activities) in net studies that arise from certain policies (or external shocks) and that activate the eco-nomic mechanisms can be grouped into clusters according their impact field demand for RE/CT industry goods, consumption and production as well as innovation and competi-tiveness (see Figure 4-6):



• Impulses with a straight impact on demand for CE- and RE-related manufacturing, in-termediate input, construction and services. They can be positive in the sense of addi-tional investments, O&M, fuel or negative in the sense of avoided investments:

− Investment impulse: occurs only during investment period and is called investment effect.

− O&M impulse: occurs during lifetime of the generation plant and is called O&M ef-fect.

− Fuel demand impulse: occurs during life time of the generation plant and is called fuel-effect.

• Impulses with a straight impact on other (no RE-related) production and consumption sectors affecting final demand for consumption goods as well as for investment and in-termediate inputs:

− Price impulses by additional direct and indirect generation costs as a budget effect (households) or cost effect (industry) generally called price effect.

− Other price impulses: merit order (MO-effect), CO2 prices as costs or as credits.

− RE income impulse, e.g. additional income in RE sector leads to higher demand of households with RE-sector employment (often indirectly included in model set up) often called RE-income effect. (In principle, when employment in CT industries de-creases and hence income shrinks for affected households we could speak of CT avoided income impulse.).

• Impulses from international (trade) relations affecting demand for RE investments and competitiveness:

− Trade impulse: exports of technologies enforce investment effect, import of technol-ogy enforce O&M effect.

− Trade impulse on fuels: avoided imports of fossil fuels, additional import of RE-fuels.

4.1.3.2 Impact mechanisms

Impact mechanisms refer to the mechanisms that translate economic impulses or shocks into economic effects, e.g. into change of employment or economic growth. We distin-guish the impact mechanisms by their impact field like impact on demand for RE industry, consumption and production and label them after their respective positive and negative economic impulse:

• Mechanism via demand in RE and CE technology manufacturing industry (investment effect, O&M effect, fuel demand effect).

• Mechanism via consumption and overall production (RE income effect, price effect (budget and cost effect), MO-effect and others).



• Mechanism via trade and competitiveness (technology trade effect, fuel trade effect, others).

In the following, the main impact mechanisms applied or discussed in net studies beyond those already illustrated in Chapter 3 are described in detail. An overview of various im-pact mechanisms integrated in net studies is depicted in Figure 4-6. It illustrates along the functional chain, the impulses like investments, O&M, price change, that arise from activi-ties, the mechanisms that translate the impulses, in a first step into “intermediate” impacts on demand in the RE related industry, on consumption and production (non RE) and on innovation and competitiveness and via multiplier into impacts on employment. The mechanism via demand relies on the Keynesian approach where it is assumed that un-employment is caused by a deficit in aggregate demand.

• Dynamic andeconomicsimulationmechanisms:

• productivitychange

• learning effects(cost curves, innovationeffect)

• multipliereffect

• acceleratoreffect

• investment impulse• O&M impulse• fuel demand

impulse

production

consumption

• RE income impulse• price impulse

• additional generation costs,

• CO2 price• MO-effect

RE demand

• trade impulse

competitiveness&innovation

inducedeffect• RE income effect

(type 1)• budgeteffect (type 2)• cost effect (type 2)• MO-effect

direct&indirect• investment (RE)• O&M (RE)• fuel demand(RE)

• avoided investment• avoidedO&M• avoided fuel demand

direct&indirect• technology trade• avoided technology

trade• fuel im/export

impulses ofactivities positive & negative impactmechanisms impacts on

employm

ent

negative effect

positive effect

-

+

-

+

-+-

+-

+

Figure 4-6: Impulses of activities and their impact mechanisms

Mechanism via demand in RE and CE technology manufacturing sector

The impact mechanism via demand in RE- and CE-related industries are induced by three impulses, causing negative and positive effects: investments, operation and maintenance (O&M) and fuel supply.



• Investment and avoided investment impact mechanism (positive and negative invest-ment effect): Investments in generation technologies comprise manufacturing of equipment, con-struction and installations (MCI) of plants. While MCI of RE-power plants requiring in-vestments in RE industries (direct) as well as in RE upstream industries (indirect) cause a demand pull for the construction and equipment manufacturing sector and hence positive incentives for employment in this industry, this may also cause a reduc-tion of installations, e.g. in conventional power plants, since the demand for conven-tionally generated power decreases and hence investments and employment in this in-dustry shrink. We call the mechanism that depicts the negative impact of RE invest-ments on investments in conventional power, heat or fuel generation plants the “avoided investment impact mechanism”. Both effects, investments and avoided in-vestments, have a temporary employment impact, namely in the years of manufactur-ing, installation and construction, and therefore depend on the annual RE capacity in-stalled or avoided fossil energy installations. The employment effects within the RE-industry are direct effects; employment in upstream industries are described by indirect effects.3 They are positive for RE investments and negative for avoided CE invest-ments. The extent of the impact from investment on employment depends on the la-bour intensity in the respective industry as well as on the share of imported equipments (and their changes), i.e. a low labour intensity mitigates the impact.

• Operation and maintenance (O&M) and avoided O&M impact mechanism (positive and negative O&M effect): Analogous to the investment effect, a higher demand for, e.g. RE power, heat or fuel requires more operation and maintenance services and therefore augments employ-ment in this part of the service sector. In contrast, the substitution of conventional energy generation technologies by RE technologies lowers not only investments in conventional technologies but also the corresponding services and subsequently has a negative effect on O&M in the conventional energy sector. This mechanism is called “avoided O&M impact mechanism”. The effects last as long as the economic/technical life of the installation (generation period) and depend on the cumulative installed RE capacity as well as on the substituted cumulated conventional energy capacity, i.e. avoided capacity. O&M cause direct, indirect and induced4 effects. They are positive for RE and negative for avoided CE O&M activities.

• Fuel demand and avoided fuel demand impact mechanism (positive and negative fuel effect): Increased installations of RE-generation plants and decreased installations of conven-tional generation plants cause a higher demand for RE fuels and lower the demand for

3 Employment in other sectors induced by an increased consumption (only of households with

employment in the RE industry) due to higher income in RE industries are tagged as induced effects of type 1. They are described under 4.3.2.2.

4 Due to income from employment in RE-related sectors.



conventional fuels, thus affecting employment and trade in the RE fuel industry posi-tively and negatively in the fossil fuel industry. Fuel demand has three effects: A direct one referring to fuel-related demand, which gives increased impulses to forestry and agriculture and fewer impulses to oil processing industries; an indirect one for upstream industries and an induced effect caused by higher consumption due to higher income in the fuel or fuel-related sector. These effects are summarized in the RE fuel demand and avoided fossil fuel demand impact mechanism. They have a long lasting impact on employment and depend on cumulative RE capacities.

In some studies the avoided impact mechanisms are summarized under the term “substi-tution effect”, meaning that investment, O&M and fuel in the conventional energy sector is substituted by O&M, fuel and investments in the RE industry.

Mechanism via consumption and other production sectors

The impact mechanism on consumption and other production sectors is activated by changes in prices and income. They are impulses that affect the consumption and non RE-related production sectors and lead to negative and positive effects, respectively. The RE-income and price impulse are translated by different mechanisms and impact ways:

RE-income mechanism (RE-income effect or induced effect of type 1): Additional income in households with an employment in RE-related industries leads to an increase in consumption with positive effects on employment in this sector. Whereas a decrease of income in households with CE-related employment due to falling CE invest-ments, O&M and fuel supply has a negative effect on the consumption sector. In many studies only the positive effects of RE-related income increases are taken into account while the negative effect – small in comparison to the RE income effect – is neglected. Furthermore, the impact on employment depends on the labour intensity and share in this sector.

Price changes (via consumption and production mechanism):

• Additional direct generation costs (AGC) mechanism of RE (negative price effect): Power, heat or fuels from RE sources entail higher generation costs – for most genera-tion technologies and under the current prices - than fossil energy sources or conven-tional generation technologies. Subsequently, an increase in RE installations augments electricity or heat generation costs. These higher costs are passed through to house-holds and industries via tariffs, quotas or other market mechanisms and decrease the relative income of households or increase production costs in industries. This effect is classified as induced effect of type 2. We differentiate the price effect according to its starting point, namely, its effect on households or industry into budget effects or cost effects, respectively. Furthermore, at the microeconomic level, the price increase translates into two effects: lower consump-tion or production (income effect) and a change in consumption pattern or input struc-



ture (substitution effect) that leads in summary into lower employment. Therefore, we distinguish how the effect is modelled, whether it is split into a substitution and income effect or just considered as an overall restriction to income or production.

• Budget effect: Many studies do not apply specific mechanisms for income and substitu-tion effects, but translate the price increase for, e.g. power, as a budget decrease for other consumption goods while keeping the total consumption budget constant. In this case the total available income, saving rates and imported consumption as well as the consumption pattern remains unchanged apart from energy consumption (and im-ported goods). This means that the consumption of other goods is proportionately cut without taking into account different income or price elasticities. Applying distinct elasticities allows to depict:

Substitution effect: An increased power price changes the consumption pattern of a household (or the input structure of an industry). Thus, a high (substitution) elasticity for power leads to power being replaced by other normal consumption goods, while a low elasticity results in hardly any substitution of power but to a lower demand for other consumption goods (input factors).

Income effect: This compensates the substitution effect of a normal good (input factor) and represents the dominant effect of a price increase. A price increase causes a loss in purchase power, and thus, reduces relative income (production budget). Consequently, overall consumption (production) shrinks.

• Cost effect: Analogous to the budget effect, price increases could have the similar ef-fects on industry behaviour. Productions shrinks due to budget limits production costs and hence the final product price increase, leading to a decrease in demand. If different elasticities are taken into account, the effect could be disaggregated into a substitution and income effect as well.

High energy prices due to additional generation cost generally have a negative effect on employment via changes in consumption or production. This is classified as an in-duced employment effect of type 2. Overall, changes in the saving rate could compen-sate the cut in relative income, but due to complexity problems, model variables can not always be modelled as endogenous variables.

• Price effect due to additional indirect generation costs (AGC) of RE: Since power from RE sources, in particular wind, shows larger fluctuation than power from fossil energy sources, the grid regulators have to provide a higher level of un-scheduled power flows or operating power reserves. Furthermore, if wind farms as well as planned and existing coal fire plants are concentrated at a few sites, grid extensions might be necessary. Both factors - grid expansion as well as power reserves - lead to higher indirect generation costs, causing a price impulse that evolves along the same impact paths as the direct AGC impulse. In addition, the promotion of RE, as is the case in Germany, causes expenditures for administration and transactions in the en-ergy sector as well as in public households. To be accurate, these additional indirect costs paid by industry (ultimately by consumers) and private households via taxes should be included, especially if increases in employment in the administrative sector



due to RE use is regarded. However, the indirect AGC are presently notably lower than the direct AGC but might increase significantly for future RE deployment5. This is also an induced effect of type 2.

• Merit order (MO) or supply effect: Under a feed-in system, power generation from RE leads to an increased power supply at the stock exchange and to a change of the merit order curve such that the supply curve shifts to the right while the demand for power remains unchanged. As a result, power prices fall. This decrease is only passed through to final consumers in a perfect market. Therefore, the price effect of RE on power prices at the stock exchange frees up funds for private consumption or industrial production. In addition to the effect on the (domestic) stock market, a lower demand for fossil energy sources due to increased RE supply on the global market also affects the world market prices for fossil energy sources and hence could have a positive effect on welfare; this is called the energy price-GDP-effect.6 These effects are considered to be a counter effects to the aug-mented AGC.

• Other price effects: Other prices affecting power prices such as the CO2-prices for certificates represent feasible impulses for macroeconomic effects. They should be included either as costs for conventional electricity generation or as a credit for RE electricity generation to ac-count for the additional external costs of fossil energy sources. They are of particular interest when designing climate policies and also represent a very positive effect of RE deployment which should be integrated into macroeconomic approaches.

Mechanism via trade and competitiveness

• Technology trade: An increase in exports generates a positive investment impulse while a decrease in CT exports results in a negative impulse. Imports of RE technologies stimulate O&M im-pulses while avoided imports of CT technologies provide a negative impulse for O&M. RE deployment can affect export via price and quality advantages: Greater numbers of national RE installations and construction very often go hand in hand with falling prices for RE installations since production costs decrease due to economies of scale and learning effects. Besides price competitiveness, a competitive advantage arises due to higher quality standards and first mover advantages. The price spread and competitive technology advantage clears the way for rising net exports, leading to higher national production and hence increased employment. However, this development depends largely on the RE deployment (RE policy) worldwide and on im-ports. A very ambitious national RE deployment but a concurrent very low global RE target or high imports might have very small demand effects at the national level, and

5 See ISI et al. 2010. 6 See ISI et al. 2010.



hence, low employment effects. Furthermore, the net exports of conventional genera-tion technologies might decrease over time since their price and technology advantage diminish due to the falling number of installations, even though global demand remains at a constantly high level. This represents a negative trade impact, which we call the “avoided technology trade impact”. Overall, impulses from exports should take imports into account and, to be comprehensive, should also include shrinking net exports of conventional technologies.

• Fuel trade: Imports of fossil fuels decrease as conventional power generation or capacities dimin-ish over time This is called avoided fossil fuel import impact. Fossil fuels are replaced by RE sources which are either imported or exploited/produced domestically. There-fore, either there is an increase in the imports of RE resources (RE fuel import impact) or, if competitive, in the domestic production of RE fuels affecting the domestic value added positively (fuel effect). However, due to the replacement of fossil fuels by RE fu-els and the shift in the fuel production chain to the national economy, fossil fuel export-ing countries might experience a loss in purchasing power and hence are inclined to import fewer goods, so the (global) demand for investment goods shrinks. Therefore, a reduced fuel trade could negatively influence the terms of trade.

4.1.3.3 The impacts - effects in net impact studies

Economic impulses lead to in diverse effects reflecting the impact of RE deployment e.g. on employment, measured by e.g. number of jobs. However, when discussing employ-ment indicators it is important to define terms of employment because referring to em-ployment or jobs without indicating the duration could be misleading. Therefore we sug-gest to use job or employment as full time job or full time equivalent or job-year which are equivalent to a full time job for one year and one person. Regarding employment effects we distinguish between direct, indirect and induced (of type 1 and 2) effects that are all triggered by RE activities and induced by impulses.

• Direct employment effect: This refers to employment caused directly by planning, de-veloping, managing, manufacturing, constructing, installing (MCI), operating and main-taining (O&M) different components of a RE technology or a power plant ignoring the effects on upstream linked industries. The data can be collected directly from the exist-ing facilities, manufacturers, project developers, etc in the respective phases of opera-tion.

• Indirect employment effect: This includes the employment in upstream and down-stream industries that supply and support the RE activities. This could be the demand for intermediary inputs like steel, synthetics, software, etc. for RE plants, or for equip-ment, facilities, maintenance and operation. These industries are not directly linked to any RE activity field. Both effects, the direct and indirect effects are called primary ef-fects and are depicted in Figure 4-7, where the indirect effects stem from the interme-diate input demand.



Promotion ofRE use

increasing MCI, O&M and fuelsupply of RE technologies

RE investment

demand

RE intermediate input demand

trade of RE equipment

falling MCI, O&M and fuelsupply of CE technologies

Change ofdomesticindustryoutput

labourdemand

Figure 4-7: Direct and indirect and induced (type 1) effects

• Induced employment effect: This is reported in net studies as well as in some gross studies as an effect on employment in industries not related to RE MCI, O&M or fuel etc. It is considered to be a secondary effect that occurs along two impact paths:

− type 1: drives a positive impact and is induced by additional (direct and indirect) em-ployment and hence expenditure induced effects by households with employment in RE industry and services. This leads to increased consumption which, in turn, re-sults in more investments in all industries and services, affecting all incomes posi-tively etc.7

− type 2, sets a negative impact in motion since it is initiated by higher prices for en-ergy leading to additional costs for electricity use in industry and households. This entails changes in consumption or in production leading to lower demand either for consumption goods and services or for investment and intermediate goods and ser-vices. This in turn affects production, income and again consumption, etc. The in-duced effect is called a secondary effect of type 2. The induced effects are illustrated in Figure 4-8.

Gross employment effects comprise in general direct, indirect and in some cases induced (type1) effects while net impact studies generally include also induced effects of type 2.

7 Theoretically, avoided income in CT industry could have a negative effect on consumption of

households with CT employment.



demandfor invest.

installments,O&M

services,fuel demand,

...upstream RE

industry

RE industry

price impulse/cost impulse

industryproduction

pro-duction of consumer

goods

employ-ment

incomeof

house-holds

from RE industry

demandfor con-sumergoods

1

direct effects

indirect effects

induced effects (type 1)

induced effects (type 2)

private con-sumption

income ofhouseholds

demand forconsumerg.

costs in industry

employ-ment

employ-ment

2

impulse primary effects secondary effects

Figure 4-8: Primary and secondary effects

4.1.3.4 Dynamic and simulation mechanisms

In this report, the term “dynamic” refers to several rather different mechanisms: First, to a mechanism that transmits impulses from the first round (year) into subsequent rounds such that the initial impulse still affects production or consumption in future periods (multi-plier, accelerator). Second, a mechanism that translates initial impulses into lower prices for RE technology or favourable terms of trade and, finally, a mechanism that improves general production conditions and is not directly dependent on RE deployment.

• Productivity change: On average, labour productivity, measured as BIP per labour in-put, increases annually leading to a lower labour input for the same output. Conse-quently, the change in productivity has a depressant effect on employment. Changes in productivity might arise from efficiency increases due to technical changes and learn-ing effects, especially in booming industries. In many cases these are linked to previ-ous investments. In an environment where investments directly affect production, the productivity increasing effect is greater than in an end-of-pipe system. The specific productivity effects of a strong RE deployment are hard to assess, so the annual sector productivity increase of similar sectors has to be taken into account when assessing macroeconomic impacts.

• Innovation impact: It is commonly agreed that promoting technology development and supporting market development lead to technical changes and higher competitiveness. The first is reflected in new products and efficiency improvements in industry and ser-vice and generation, the latter might be reflected by market shares and exports. Initial



high energy prices exert a pressure to innovate and to reduce costs or create new highly qualitative products in order to become competitive.

• Accelerator effect: This effect accounts for the investments to provide the capacity needed to produce additional goods. High demand causes demand for investments in backward linked industries leading to higher production and revenues which in turn re-quires further investments etc. Real simulation models run this effect over several rounds while, in an analytical approach, it is incorporated along the impact path.

• Multiplier effect: This effect accounts for the spending of income generated by demand effects outside the RE industry. Based on the Keynesian model, there is a multiplier ef-fect on income and revenues beyond the demand pull or direct price effect. The multi-plier effect multiplies effects along two impact pathways, i.e. the positive impacts of in-vestment and O&M as well as the negative impacts of prices on income: increased in-vestments cause demand in upstream industries and where the production growth leads to higher income and hence, to an increase in consumption. Further, a change in (relative) income due to price changes affects consumption which in turn affects pro-duction and, therefore, employment in the consumption good and intermediate input industries. In a second round, employment in the consumption good and upstream in-dustries affects income and thus again consumption, etc. The effect on employment via consumption represents an induced effect which is applied for several rounds and, hence, is called a multiplier effect. To be more specific, it influences two economic agents: a) private households: via income due to increased/decreased production caused by changes in consumption stemming from price impulses or investments and O&M im-pulses; b) public households: via revenues or expenditures by augmented/reduced tax reve-nues or increased/decreased social transfers due to more/less employment.

4.1.4 Scenarios

In many cases scenarios are elaborated to depict the future development of energy de-mand and prices and to assess - based on this development - future impacts of different policies and RE deployment. They are tools to point out feasible developments but no means to forecast developments. In general, at least two different situations are com-pared, one with low or zero RE deployment and one with advanced RE deployment. The difference between the impact assessments calculated based on the two scenarios repre-sents the net impact of RE deployment. Overall, scenarios are an appropriate way to compare two situations where the main impact – e.g. RE deployment - is varied while other factors are kept constant. However, to include the influence of, e.g. prices or growth on economic development, economic and other model parameters such as fossil fuel prices, demographic or economic growth are also varied. In addition, scenarios can in-clude further options such as extending the operation of nuclear power plants. In such cases, the research question may be slightly moderated to investigate how strongly



prices, prolonging nuclear power etc. affect economic output under a given RE policy. Consequently, scenarios can widen the dimensions of the research question, but we re-strict our focus to RE policy/deployment impacts. In the following, some fundamental is-sues for the application and development of scenarios are outlined:

• The main drivers of energy demand are demographic and economic development as well as energy intensity. Global RE deployment depends on energy demand, prices as well as on policies, and is e.g. projected by international agencies like the IEA.

• At least one reference scenario without RE or with only low RE deployment and one advanced RE deployment scenario are the minimum requirements for impact assess-ments. Often, a larger number of RE deployment scenarios are developed, varying with respect to the RE deployment level and structure and prices for fossil fuels while keep-ing other factors constant. Studies with several scenarios can reveal the extent to which RE employment impacts depend on other factors such as fossil fuel prices or certain technologies.

• National or domestic scenarios should be combined with corresponding global devel-opments. This means, e.g. when analysing the national or domestic impact of a RE pol-icy, a national or domestic advanced RE scenario should be connected to a global scenario with a lower or the same level of advanced RE deployment. In contrast, if a globally advanced RE deployment is applied with a national reference scenario, the ef-fects of global RE expansion at the national level are reflected and not the national ef-forts.

• The reference scenario has to be realistic, reflecting the actual RE deployment without additional policies, while the accelerated/advanced RE deployment scenario should be based on potential policy measures, price developments and the potential global de-ployment.

• The scenarios should not date back into the distant past and a zero RE scenario should be avoided since RE deployment not only takes place due to policies but also for economic reasons.

• Predicted prices of fossil energies should rely on generally accepted projections, e.g. on IEA scenarios.

In the following we show and discuss some selected details of scenarios.

4.1.4.1 Scenario development

Scenarios are used to show feasible future developments but are not suited to predict a certain development. Modelling net impacts of future RE uses requires assumptions on factors that influence the RE deployment. RE deployment is determined by RE activities that, in turn, are influenced by policies measures and targets, demographic, economic and technological developments, structural and technological changes and prices. The as-sumptions on future economic and technological development and their effect on impulses



are best summarized by scenarios. In our functional chain of impact assessment analysis we replace “policy” by “scenario assumptions” that are based on future RE support poli-cies (Figure 4-9). Then we identify a consistent set of assumptions about key drivers of RE deployment and provide references for the development of these factors.

impulse positive & negative impact mechanisms impactsRE deploymentscenario

assumptions

Figure 4-9: Scenario assumption as starting point of the functional chain

4.1.4.2 Drivers of RE deployment - scenario design

As mentioned above, to design a comprehensive and consistent scenario for RE deploy-ment we have to investigate, which key factors and relations influence future RE deploy-ment. In Figure 4-10 the principal aspects and key factors of future RE deployment are depicted.

energy demand

energy supply

avoidedcapital

expendituresfor fossil energy

capitalexpenditures

for RE (investment)

final energyprices

(additional generation

costs)

trade impulse

RE deployment

global RE deployment

global marketshares

global development

economic:•GDP•industrialproduction•transportation•....

structural:• housing area•number of cars•number ofhouses•....

demographic:•population•workier, employees•....

technological:•energyefficiency•insulation• ...

technological:• energy

conversionefficiency

• CO2 efficiency• innovation, ....

policy targets:• RE

deployment• eff iciency• CO2 emission• ....

potential:• technological• economic• geographic• realisable• ....

socio-economic:• diffusion &

adoption• costs/prices• ....

primaryenergyconsump-tion

primary energyprices:• oil, gas, coal• biomass• CO2• ....

RE costcurves / learningrates

policymeasures:• feed-in tariffs,

quota• subsidies,

obligations• .....

Figure 4-10: Overview of factors affecting the RE deployment scenarios



Two main factors affect primary energy consumption, first, energy demand and, second, energy supply, both are shaped by diverse drivers such as technological, demographic, economic changes etc. Together with fossil energy prices determined by global demand, RE policy measures such as feed-in tariffs or quotas and finally learning effects and cost reductions induced by technological changes energy consumption affects future RE dep-loyment. The scenarios applied for impact assessments are quantitative approaches where detailed data on supply, demand, prices etc are required, as opposed to qualitative narratives.

Energy supply

Energy supply is restricted by the technical and realisable potential of RE technologies and the limited availability oil, gas, coal and biomass. With regard to RE it has to be dis-tinguished between short and long term perspective and between local and global resolu-tion. Depending on the perspective taken the RE potential can become a restriction for RE deployment or not. Therefore it is important to apply a common terminology as introduced in the following:

• Theoretical potential: For deriving the theoretical potential general physical parameters have to be taken into account (e.g. based on the determination of the energy flow re-sulting from a certain energy resource within the investigated region). It represents the upper limit of what can be produced from a certain energy resource from a theoretical point-of-view – of course, based on current scientific knowledge;

• Technical potential: If technical boundary conditions (i.e. efficiencies of conversion technologies, overall technical limitations as e.g. the available land area to install wind turbines) are considered the technical potential can be derived. For most re-sources the technical potential must be seen in a dynamic context – e.g. with in-creased R&D conversion technologies might be improved and, hence, the technical potential would increase;

• Realisable potential: The realisable potential represents the maximal achievable poten-tial assuming that all existing barriers can be overcome and all driving forces are ac-tive. Thereby, general parameters as e.g. market growth rates, planning con-straints are taken into account. It is important to mention that this potential term must be seen in a dynamic context – i.e. the realisable potential has to refer to a certain year; Figure 4-11 provides an illustration of the derived realisable potential for the year 2030. For a better illustration, the connections between the different potential terms – as used above or in literature – are depicted.

Technical potentials of energy resources have been widely discussed in literature. A re-cent, comprehensive assessment at the global scale can for instance be found in the 2010 Survey of Energy Resources published by the World Energy Council (WEC, 2010). The realizable potential is much more dependent on local conditions and should therefore ra-



ther be assessed context specific. For instance, for the European RES electricity sector a comprehensive assessment has been conducted within the European project OPTRES (Resch et al., 2006).

Barriers (non-economic)

AdditionalAdditionalrealisablerealisablepotential potential (up to 2030)(up to 2030)

2000 2007 2020

Historical deployment

Theoretical potential

Ener

gy g

ener

atio

n

Economic Potential(without additional support)

Technical potential R&D

2030

Policy, Society

Achieved Achieved potential potential (2007)(2007)

Maximal time-path for penetration (Realisable Potential)

Long-term potential

(Total) Realisable potential up to 2030

2010

Figure 4-11: Definition of potential terms

Technological factors and their changes especially for energy conversion efficiency affect supply to a large degree and have to be taken into account when designing a scenario. Information on new technologies and expected developments of the conversion efficiency can be found e.g. in reports finalized in the framework of the EU project NEEDS8. Be-sides, technological developments that further reduce CO2-emissions as well as other innovations affect energy supply. They can be incorporated into the causal chain via dy-namic cost curves (see socio-economic factors) that are based on yearly changing costs and potentials subject to policies, deployment levels and other framework conditions.

Beyond technological changes, policy targets play a key role in energy supply, when they focus on regulation such as setting standards for emissions and efficiencies or obligations on RE use. These effects are captured by the element “policy measures” in the middle part of Figure 4-10.

Socio-economic factors such as adoption and diffusion of new technologies determine energy supply via expected demand, but prospective data on these are difficult to derive.

8 http://www.needs-project.org/index.php?option=com_frontpage&Itemid=1.



However, power generation costs or prices for generation technologies are crucial for the merit order and, hence, for the investment impulse.

Indicators for current costs of energy technologies can be observed from the markets or are published on some occasions in the literature, albeit hard to verify. With regard on future cost developments usually the concept of technological learning is applied. Esti-mates for learning rates of energy technologies can be found broadly in many publica-tions, in the rather practical as well as in the research oriented literature. A recent survey including a broad technology coverage provides for instance the book “Technological Learning In The Energy Sector Lessons for Policy, Industry and Science” by Junginger et al. (2010).

Energy demand

Energy demand is influenced by main economic factors such as economic growth meas-ured as changes in GDP, industrial production, transportation, etc. Further, structural fac-tors like development of housing area, number and type of cars, number and type of houses etc. have a significant impact on energy demand. Also energy demand is deter-mined by demographic development – population, working force, etc. Finally, technologi-cal changes regarding energy efficiency of domestic appliances and industrial machinery, insulation of buildings have a reducing effect on energy demand. In the German energy concept, efficiency increases of e.g. 1.7% to 2.5% p.a. (Prognos 2010) have been applied.

Primary energy prices reflect scarcity of primary energy sources, which is a result of global supply and demand. A regular publication that includes assumptions on future pri-mary energy prices of oil or gas is “EU Energy Trends to 2030” published by the European Commission, DG Energy (EC, 2010). Price paths should go hand in hand with economic growth and energy demand.

Cost(potential) curves for RE technologies are crucial for designing investment and price impulses. This information is contained in many economic-engineering models of the energy sector, but can rarely by found published.

Policy measures and targets encompass assumption for simulated support schemes like feed-in tariffs with technology-specific settings, quota obligations based on green certifi-cates (TGC) or tax reliefs. They determine the share of RE in power generation as well as the additional generation costs for consumers. E.g. within the EU each country had to submit a national renewable energy action plan indicating measures how to achieve the targets set.



4.1.4.3 General aspects of a scenario design

To estimate net impacts we need to design future developments, namely domestic and global developments of RE deployment. In case we only investigate the global impact of RE deployment, we just apply the global RE development path. Further, we elaborate a price path for fossil energy prices influenced by global economic growth and energy de-mand. In addition, to depict and integrate the impact of trade relations, a scenario on ex-port and import shares based on future RE installments is required. Therefore, we have three scenarios designs:

• Domestic prospective RE deployment, • Global RE deployment and energy prices, • Trade scenario.

Scenario on domestic RE capacity development

Many countries or institutions provide information, reports or studies on a prospective RE deployment based on demographic, economic, structural, technological and political (as-sumed) developments as depicted in the left part of Figure 4-10. Some estimations are based on an energy sector model which takes into account demographic and economic developments to model energy consumption on cost based optimization. Other estima-tions are more target-oriented and assume strong RE deployments and efficiency changes to achieve the targets set or are rooted in macroeconomic modelling traditions.

The reference scenario plays a key role in assessing net impacts. It reflects a hypotheti-cal low level or zero RE deployment under a situation where no (further) policy support or deployment target is given for RE. Subject to the research question, the reference sce-nario could refer to:

• the current situation assuming no (further) change in policies, addressing the question, what would happen if there is a change in future RE promotion? Or alternatively,

• a past situation assuming no (further) promotion since that time, addressing the ques-tion, what has been the effect of the current (and future) policies in comparison to e.g. ten years ago?

Under an advanced RE deployment scenario it is assumed that further policy support is provided or ambitious targets are pursued such that the RE deployment strongly pro-ceeds. The assumed RE deployment should be combined with a corresponding domestic and global economic development. Therefore, we also have to make assumption on global economic development and energy prices.



Scenario on demand, growth and fossil energy prices

Why do we need scenarios on demand and fossil energy prices? Under limited fossil en-ergy resources demand for fossil energy is the main driver of prices. Subsequently, high economic growth pushes demand for energy and hence prices. Since technological changes improving energy efficiency (productivity) and increasing RE deployments allevi-ate the demand push, assumptions on efficiency changes as well as global RE deploy-ment (targets) have to be taken into account when elaborating a price path for fossil en-ergy sources.

Diverse price paths of fossil energy are provided in World Energy Outlook of the IEA.

Furthermore, global RE deployments (targets) lead to demand for RE technologies at lo-cal (domestic) and international markets and hence influence trade relations and terms of trade. Therefore, we have to take into account global RE capacity installations and their prospective developments.

IEA World Energy Outlook, Greenpeace Energy(R)evolution 2008 are few studies that provide estimations on potential prospective global RE deployments.

Scenario on export

What is the role of exports and imports in impact assessment studies? Many impact as-sessment studies are based on investment impulses that derive from domestic capacity increases of RE generation plants. However, machinery and equipment can be domesti-cally produced or imported. In case of imports, we have to reduce the impulse by deduct-ing import expenditures from capital expenditures for newly installed generation capaci-ties. Hence, no domestic employment effects arise from the manufacturing of imported machinery.

Exports of power generating technologies provide a positive impulse for the economy, since they increase the net product in the domestic economy. They are not captured in the capital expenditures for newly installed generation plants and, hence, have to be added to the impulse. For some countries exports make up a significant economic effect of RE de-ployment. So far, two comprehensive net impact assessment studies have developed and applied an approach for export scenarios. They are briefly outlined:

• Impact Assessment of RE deployment on the German job market (GWS et al. 2011: The main idea is to derive future exports in dependence of global RE investments. The future global RE investments (without German investments) are derived from installed capacities according to Energy(R)evolution scenario (Greenpeace 2008) and are mul-tiplied with the tradable share of RE investments that is based on current trade rela-tions. Then, the product is further multiplied with export shares of Germany for RE



technologies, also based on current trade relations. The final product represents the German exports of RE technologies to other regions. It enters the macroeconomic model as a trade impulse. Variations of tradable shares as well as of the German ex-port shares e.g. assuming in-, decreasing or a constant export volumes or shares re-flect different export scenarios all based on the future global RE deployment.

• EmployRES (ISI et al. 2009): This approach also relies on future installations (new capacities) within and outside (rest of world) the EU that are founded on the IEA world energy outlook (2007) for the rest of world and the Green-X scenarios (ISI et al. 2009) for the EU. The market shares are estimated based on indicators for future technology development e.g. patents and exports. The RE technologies are decomposed into cost components and assigned to industry sectors such that for each sector the production volume of the RE technology is known. The difference between the total domestic contribution (production volume) to the global investments and the domestic production of the home investments represents the exports of the RE-related domestic industry (see Figure 4-12). Thus, fu-ture exports (scenario) depending on future RE installations and changes in market shares become relevant impulses for macroeconomic models. In analogy to exports, imports are taken into account by deducting the domestic pro-duction of RE-technologies for home installations from the total RE installations of a country. This reduces investment impulses.

Cost components

Capital expendituresfor RE-technologies

global and per country

Domestically producedequipment for domestic

demand per economic sector

Market shares

Domestic production volume ofglobal investment needs per

economic sector (per country)

RE Exports per economicsector and per country

Figure 4-12: Export scenario in dependence of RE investments

4.2 Evaluation and comparison of net impact studies

A detailed evaluation of the studies included in the comparison according to the above mentioned criteria is given in the Annex. In this Chapter, we present a synthesis of the literature review. Table 4-2 provides an overview of the reviewed papers discussing net impact studies. These studies are outlined in the following subchapters.



Table 4-2: Overview of selected net impact studies for discussion

Title Abbre-viation

Authors year characteristics of approach

Energy sector jobs to 2010: a glob-al analysis – final report, Green-peace

Green-peace

Rutovitz, Atherton 2009 Positive effects, direct effects; comparison of 2010 and 2030; em-ployment factors from diverse studies;

Putting renewable energy efficien-cy to work: How many jobs can the clean energy industry generate in the US?

Wei Wei, Patadia, Kammen

2010 Positive effects; direct & indirect effects for RE; scenario com-parison; employment factors from diverse studies;

Ermittlung der Arbeitsplätze und Beschäftigungswirkungen im Be-reich Erneuerbarer Energien (assessment of jobs and employment effects in RE)

BEI Pfaffenberger, Nguyen, Gabriel

2003 Positive & negative effects; direct, indirect & induced effects; IO-model

Bewertung der volkswirtschaftli-chen Auswirkungen der Unterstüt-zung von Ökostrom in Österreich (Assessment of economic impacts of the support of green electricity in Austria)

IHS Bodenhöfer, Bliem, Weyerstraß

2007 Positiv&negative effects; direct, indirect and induced effects, IO-table

Solar Photovoltaic employment in Europe – The role of public policy for tomorrows solar jobs

EPIA University Flens-burg, WIP-Renewable Ener-gies Munich, Na-tional Technical University of Athens

2009 Positive & negative effects; direct, indirect & induced effects; IO-table and GE-model

The expansion of renewable ener-gies and employment effects in Germany

EEFA Hillebrand, Butter-mann, Behringer, Bleuel

2005 Positive &negative effects; direct, indirect & induced effects; scenario comparison; structural model

Gesamtwirtschaftliche und sekorale Auswirkungen des Aus-baus erneuerbarer Energien (economic and sectoral impacts of RE deployment)

DIW Kemfert, Blazejczak, Braun, Edler, Schill

2010 Positive & negative effects; direct, indirect & induced effects; scenario comparison; macro-economic model

Kurz- und langfristige Auswirkun-gen des Ausbaus erneuerbarer Energien auf den deutschen Ar-beitsmarkt (short- and long-term impacts of RE deployment on the German job market)

BMU 2011

Lehr, Lutz, Edler, O’Sullivan, Nienhaus, simon, Nitsch, Breitschopf, Bickel, Ottmüller


EmployRES: The impact of renew-able energy policy on economic growth and employment in the EU

EU 2009 Ragwitz, Schade, Breitschopf, Walz, Helfrich, Rathmann, Resch, Panzer, Faber, Haas, Na-thani, Holzhey, Kon-stantinaviciute, Za-gamé, Fougeyrollas




The reviewed net studies apply diverse methodological approaches to depict the overall economic impacts. The term “methodological approach” encompasses here not only the data and modelling type, but also further elements of the scope, such as impulses, sce-narios or impact mechanisms.

Regarding the reviewed studies we classify them into three main groups, based on the methodological approach that in turn affects the research focus and the impulses or ef-fects taken into account or vice versa. The three main types are:

a) Assessment of jobs under different technology development paths. Calculation of employment impacts are mainly based on technology-specific employment factors to capture positive effects.

b) Assessments addressing the contribution of technologies to employment in all eco-nomic sectors. The calculation of employment impacts is very often based on IO ta-bles and captures positive and negative effects.

c) Assessment of employment impacts in all economic sectors. It is based on a com-plex model featuring an energy sector module, a macroeconomic module and an export module capturing negative and positive effects as well as differences be-tween scenario outcomes.

A description of the main net studies is given in the following. They are screened accord-ing to the scope of their study, including integrated impact mechanisms (complexity), im-pulses, RE activities, dynamic aspects, scenarios as well as with respect to their research question. The economic extent of these net studies is aimed at the overall economy, meaning that negative and positive effects as well as primary and secondary effects are considered with varying specification. Furthermore, in many studies, two different devel-opments (scenarios) are compared. The Table below illustrates all the impact mecha-nisms, potential effects, RE activities and scenario applications that a net study could take into account. The blue fields form a pattern indicating an ideal approach and representing the feasible depth, complexity and scope of such an approach. It shows which impact mechanisms, activity fields and scenario applications are considered necessary to com-prehensively answer the research question of which present and future overall economic impacts RE policy/deployment will have on the total economy or on selected industries or sectors. Non-feasible or pointless effects are marked in black or grey. The signs + and - represent positive and negative effects, respectively. The ideal approach comprises those aspects that have been intensively and controversially discussed in papers focusing on overall economic impacts (Wei et al. 2010, Kammen et al. 2004, Lehr et al. 2008, Hillen-brand et al. 2006, Frondel et al. 2010, Pfaffenberger et al. 2003).



Table 4-3: Overview scheme for net impact studies

Title of study:Research question:impact mechanisms direct indirect induced activity fields: scenario

+ installation‐ reinvestments+ O&M‐ fuel generation national scenario+ RE trade ‐ fuel trade global scenario+ ‐ time horizon: export scenario+ past ‐ present

productivity change ‐ futuredirect AGC ‐ regional extent:indirect AGC ‐ local

merit order, CO2 price, ... + nationalmultiplier effect +/‐ regionalaccelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effec

pointless for a net study B‐eff: budget effect C‐eff: cost effectdoes not exist

AGC: additional generation costs

fuel trade

difference between scenarios

investment

O&M

fuel demand

techn. trade

The same Table is used in the following subchapters to present the main elements or fea-tures for the net impact studies reviewed. However, blank fields in any Tables do not nec-essarily indicate that these studies do not take them into account, but only might simply indicate missing information on this issue.

4.2.1 Calculation of employment impacts based on positive effects and scenarios

This approach calculates the number of jobs under different technology deployment paths without taking into account any negative impacts or change in prices, trade, production etc. The main question is, whether a RE or CE technology path results in more jobs. This approach relies on employment factors and has been applied in Greenpeace 2009 (Rutowitz et al. 2009) and by Wei et al. 2010. Both assess the employment effect of dif-ferent RE deployment scenarios with a given set of defined generation technologies. While Rutowitz et al. 2009 focus only on direct effects of RE and CE, Wei et al. 2010 also include indirect effects and energy efficiency. However, the basic approach is rather simi-lar. In Rutowitz et al. 2009, annually installed, exported or cumulative capacities are multi-plied by an employment factor, adjusted by a regional job multiplier or local manufacturing share and, for future years, by a dynamic factor. In addition, Wei et al. 2010 used an av-erage indirect multiplier for the indirect effect taken from three other studies. The genera-tion as well as fuel supply is also multiplied by employment factors, multipliers and local factors. The result is the in/direct employment per MW and MWh for each energy source.



Applying two different deployment scenarios (reference and advanced scenario) and mul-tiplying the employment effects by the projected capacities and generation gives the total in/direct employment under a reference and advanced deployment scenario for all tech-nologies. The difference between the two outcomes (of year 2010 and 2030 in Rutowitz et al. 2009 and of scenario RS and ADS in Wei et al. 2010) provides us with a so-called di-rect (indirect) “net” employment effect, since it compares situations with different RE-settings. The reference and energy(R)evolution scenarios reflect the deployment of differ-ent energy technologies with more (less) CE and less (more) RE but do not project energy prices. However they build on assumptions on economic and demographic development, both shaping energy demand. The analysis excludes changes in exports or imports and hence impacts from trade. The research question focuses on two feasible energy deploy-ment situations and asks in which situation higher employment prevails? It also provides information about the contribution of different energy technologies. The mix of energy technologies include RE technologies as well as CT technologies with decreasing shares of nuclear power.

employmenteffect

scenario (2010)or scenario ADS

employmenteffect

installationsexportscapacity

generation

scenario (2030)or scenario RS

„net“ impact

positive direct(regional & localfactors), indirectanddynamic

effects

installationsexportscapacity

generation

Figure 4-13: Simplified calculation scheme

The principal procedure in Rutovitz et al. 2009 and Wei et al. 2010 is illustrated in Figure 4-13 while Table 4-4: depicts impact mechanisms, effects, activity fields and scenarios for the Greenpeace study 2009 (Rutovitz et al. 2009). Table 4-5 illustrates the same features for Wei et al. 2010. In addition to Greenpeace 2009, Wei et al. 2010 address also indirect effects, that is why the fields with indirect effects are marked in Table 4-5. Both studies are not considered as real net impact studies according to the definition of net impacts in this review.



Table 4-4: Greenpeace study, 2009

Title of study:

Research question:

impact mechanisms direct indirect induced activity fields: scenario+ installation‐ reinvestments+ O&M‐ fuel generation+ RE trade global scenario:‐ fuel trade Reference+ Energy(R)evolution‐ time horizon:+ past ‐ present 2005

productivity change ‐ future 2030direct AGC ‐ regional extent:indirect AGC ‐ local

merit order, CO2 price + national

multiplier effect +/‐ regionalaccelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effect

pointless for a net study B‐eff: budget effect C‐eff: cost effect

O&M

Greenpeace 2009: Energy jobs to 2030: a global analysis; 2009; J. Rutowitz, Atherton; editor Greenpeace InternationalWhat is the potential job creation associated with the two scenarios energy (r)evolution and reference ?

investmentdifference between years

fuel demand

techn. trade

fuel trade


does not exist

Table 4-5: Study of Wei et al. 2009

Title of study:

Research question:impact mechanisms direct indirect induced activity fields: scenario

+ installation‐ reinvestments+ O&M‐ fuel generation+ RE trade ‐ fuel trade+ global scenario‐ time horizon:+ present 2010‐ future 2030

productivity change ‐ export scenariodirect AGC ‐ regional extent:indirect AGC ‐ local




techn. trade

fuel trade


does not exist

Wei 2010: Putting Renewables and Energy Efficiency at work: How many jobs can the clean energy industry generate in the US?, 2004 Kammen et al., updated 2006 and 2010, Wei et al.Meta analysis on employment effects of RE and energy efficiency.

investmentdifference between scenarios

O&M

fuel demand



4.2.2 Calculation of employment impacts based on positive and negative effects

The research focus of this approach is more on the effect of a single or a set of technolo-gies. Questions like ”Which technology contributes the most to employment?” should be answered by this type of approach. These studies calculate net impacts just by applying impact mechanisms with positive and negative primary and/or secondary effects and do not use any scenarios. Hence the “net“ effect is not derived from a comparison of two dif-ferent RE-deployment situations, but from the addition of single effects. The sum of nega-tive and positive effects per RE-technology - called net effect in these studies - shows a more or less comprising economic impact of one or more RE technologies on the total economy. The principal procedure of such an approach is to calculate the positive job effects from MCI and O&M activities based on IO-tables, labour coefficients and multipli-ers and deduct the secondary (induced) employment effects, which are based on average consumption vectors and IO-tables as well as the negative effects from avoided invest-ments etc. Examples of such studies are IHS 2007 or BEI 2003, EPIA 2009. In these stud-ies, (in)direct and induced effects from MIC and O&M or prices are taken into account using primary and secondary effect multipliers. Dynamic effects are considered via changes in industry specific productivity. Scenarios are partly developed to show different development paths and negative (in)direct effects but not necessarily to provide the differ-ence between the overall economic outcome of two scenarios. The net effects assessed in these studies represent not “real” net impacts according to the definition in this report.

investments in € or MW

net employment effect

in/direct and induced positive employment

positive andnegative

employmentfactors (in/ direct

effects)

employmentmultipliers

(induced effectof type 1)

price effect(negative

induced effectof type 2)

generation in MWh

induced negative employment

Figure 4-14: Calculation of net effects with positive and negative effects

The BEI 2003 study is a net study that focuses on the specific employment effects of technologies, i.e. it assesses how many jobs (fte) result from the installation of one gen-



eration facility. There is no comparison between a reference and an ambitious RE de-ployment scenario but the negative price effect is taken into account. Calculations are based on a static input-output model (IO-model). To assess the price effect, an average consumption vector is applied. The consumption structure as well as the savings rate and import shares are kept unchanged. Data collection relies on primary statistics, surveys, secondary statistics and own calculations. The research question focuses on the employ-ment effects of RE technologies and aims to reveal which RE technologies have a strong impact on employment and which not. The outcome shows that employment effects per generation unit for small hydropower are the largest, followed power generation with bio-mass while all other RE technologies show negative employment effects – with PV as the largest. The negative employment impacts is caused by the strong negative budget effect due to very high additional generation costs for PV.

Table 4-6 BEI 2003 study

Title of study:

Research question:

impact mechanisms direct indirect induced activity fields: scenario+ installation‐ reinvestments+ O&M‐ fuel generation+ RE trade ‐ fuel trade+ ‐ time horizon:+ past ‐ purchasing power of export countries present

productivity change ‐ futuredirect AGC ‐ B‐eff regional extent:indirect AGC ‐ local




techn. trade

fuel trade


does not exist

BEI 2003: Ermittlung der Arbeitsplätze und Beschäftigungswirkungen im Bereich EE (Assessment of jobs and employment by using RE), 2003; Bremer Energie Institut, W., Pfaffenberger, K. Nguyen, J. Gabriel, assessment of specific employment effects (employment/installation kW) in context of RE development ‐ comparison of different technologies

investmentdifference between scenarios:

O&Mnational scenario: const. prices

fuel demand

The IHS 2007 study relies on a rather simple procedure. Based on investments and reve-nues, the value added and employment is calculated with primary direct effect multipliers for value added and employment. The consumer budget is based on income (wages, prof-its, salaries) and adjusted for savings and imported goods. Multiplying the consumer budget by a secondary effect multiplier for value added and employment shows the in-duced effects. The multiplier is derived from the IO-table. However, the reported employ-ment effect refers to EUR invested. It does not rely on the difference in employment ef-fects between two different deployment scenarios. The main focus of the study is on the



economic and employment contribution of different RE deployments, i.e. how much em-ployment is generated by strong RE biomass or solar development? Results show that wind and solar power have in total negative employment effects due to their high addi-tional generation costs (budget effect) while power generation with biomass and CHP re-veal positive employment impacts. Studies by Haas et al., 2006, Weiss et al. 2003 are based on the same approach. It should be noted that the expression “multiplier” refers to a one time multiplication and is not identical with the multiplier effect which stands for sev-eral multiplication rounds.

Table 4-7: IHS 2007 study

Title of study:

Research question:

impact mechanisms direct indirect induced activity fields: scenario+ installation‐ reinvestments+ O&M national scenario‐ fuel generation+ RE trade ‐ fuel trade+‐ time horizon: global scenario+ present 2003‐ future 2010

productivity change ‐direct AGC ‐ B‐eff regional extent:indirect AGC ‐ local export scenariomerit order, CO2 price + national

multiplier effect +/‐ regionalaccelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effectpointless for a net study B‐eff: budget effect C‐eff: cost effect

techn. trade

fuel trade

AGC: additional generation costsdoes not exist

IHS 2007: Bewertung der volkswirtschaflichen Auswirkungen der Unterstützung von Ökostrom in Österreich (Assessment of economic impacts of the support of green electricity in Austria), H.J. Bodenhöfer et al., 2007, IHS KärntenWhat are the economic effects of green electricity support/promotion? Assessment of value added and employment per investment and generation.


O&M

fuel demand

The approach in the EPIA 2009 study is similar to the IHS study. Positive and negative direct and indirect effects of production, installation, operation and maintenance have been taken into account via an IO-model. Furthermore, trade effects are also included. To assess the negative effects of additional generation costs on consumption a general equi-librium model has been applied. The outcomes show the impact of the diverse effects on employment. Not surprisingly, the avoided investment and budget effect considerably re-duce employment while investment and O&M effects strongly increase employment. The difference between the negative and positive employment effects is called in this study the “net” employment effect. The approach relies on two models, an IO-table assessing (in)direct positive and negative effects and a general equilibrium model depicting interna-tional relations and induced effects with a focus on consumption. The study investigates



exclusively impacts of PV deployment. The outcome shows a small positive employment effect of PV.

Table 4-8: EPIA 2009 study

Title of study:


+ installation‐ reinvestments+ O&M‐ fuel generation national/regional scenario+ RE trade 1. moderate PV impl.‐ fuel trade 2. advanced PV impl.+‐ time horizon: global scenario+ present 2005‐ future 2030

productivity change ‐ export scenariodirect AGC ‐ B‐eff regional extent: const. export share of 15%indirect AGC ‐ localmerit order, CO2 price + national

multiplier effect +/‐ regional EU

accelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effect


techn. trade

fuel trade


does not exist

EPIA 2009: Solar Photovoltaic Employment in Europe: PV employment, EPIA, WIP, University of Flensburg, NT University of Athens, 2009What are the net employment effects of PV ‐ based on the sum of negative and positive effects.


O&M

fuel demand

4.2.3 Assessment of employment impacts based on a complex modelling approach

This approach aims at the assessment of the employment impact in the overall economic, namely on all economic sectors. Studies in this Chapter are considered as net impact as-sessment studies according to the definition of net impacts in this report. This approach integrates negative and positive effects, in/direct, dynamic and induced effects as well as comparing scenario outcomes – a reference scenario (RS) with a low RE deployment level and an advanced deployment scenario (ADS). Therefore, a complex model compris-ing several modules is necessary to capture, display and assess all the economic impacts and mechanisms. The main difference to the approach before is, that full economic im-pacts of RE deployment are assessed under different scenarios and then the differences of outcomes are reported as net impacts. The basic components include an energy sector module, a macro module and an export module, providing impulses to the macro econ-omy through trade volume and prices. The principal set-up and components are depicted in Figure 4-15. To start with, the impulses from the energy and trade module are trans-lated into economic impacts in the macro module. The modules are fed with different RE-deployment data by two scenarios. After several feedback loops or simulation rounds, we receive the calculated employment effects of each scenario which already include nega-



tive and dynamic effects. The difference between the employment effect under the ADS scenario and that under the RS scenario represents the net employment effect of a policy or RE deployment illustrated in the ADS scenario. The scenarios include changes in eco-nomic, demographic development as well as in exports, prices and finally in RE deploy-ment. Hence the outcome also depends largely on the development – the drivers – of the scenarios.

energy sector

trademodule

employment andeconomiceffect

macromodule

scenarioADS

energy sector

trademodule

employment andeconomiceffect

macromodule

scenarioRS

net impact

impulses(in/direct ,

inducedeffects, dynamic)

Figure 4-15: General procedure and components in a net impact assessment study

The crucial factors determining the outcome in these models are specific settings like:

• Choice of impact mechanisms: negative and positive mechanisms of RE deployment, dynamic effects.

• Assumptions on drivers (scenarios), especially (global) RE deployment (or reference) scenario, energy demand and energy prices for fossil energy that are reflected in addi-tional generation costs.

• Export and import development: assumption about globally traded shares or trade or market shares in RET.

The key elements of the diverse “net” model components are depicted in Figure 4-15. An essential element of the macro module is the Input-Output-table (IO-table), which is dis-cussed in Chapter 2. Other elements could be demand and supply effects as well as the behaviour of the main economic agents, e.g. revenues of public households due to taxes, expenditures due to social transfers. However, the number of elements in the three mod-ules in Figure 4-16 and how these are classified should not be considered a strict defini-tion, but an open one, meaning that elements of the macroeconomic module such as en-



ergy demand could be included in the energy sector model/module instead. In addition, some elements are modelled in detail, e.g. consumers with different elasticities, while in other models consumers are only reflected, e.g. by a consumption budget with a fixed consumption structure.

macroeconomicmodule:

• positive & negative impact mechanisms

• interactionmechanisms, intermediate goods, IO-coefficients

• demand & supply

• economicsubjects/actors

impulses impulses

energy sectormodule:

• technologies&invest-ments, O&M, fuel

• prices: merit-order, CO2-certificates, additional in/directgeneration costs,

• learning effects

• sectors (power, heat, housing, transportation, ...)

trademodule:

• general trade pattern(intra-EU, world, regions, ...)

• RE deployment world

• export: Share oftradable share of RE installations, national share of RE world trade

• imports (fossil energyand RE technology)

output

scenario:• macroeconomic data + demographic data PEC • domestic and global RE development (objectives and policies) RE deployment• export development (scenario)

Figure 4-16: General components of a net impact study, simplified illustration

The EEFA 2005 study conducted by Hillebrand et al. 2005 investigates in detail the com-prehensive effects of investment and price impulses. It points out that investments in RE expansion create a strong demand not only within the RE industry but also in the con-sumption sector due to higher incomes. It shows that the positive impact of investment on employment lasts for the one period, while the price effect also prevails in subsequent years. This is due to declining investments and long lasting high feed-in tariffs. Two differ-ent deployment situations are considered and the net effect is defined as the difference in the scenario outcome. The focus is on investments and their effects on production and costs. Employment effects are the results of different income elasticities for goods and marginal changes.

The rather recent study of Kemfert et al 2010 takes into account investment, O&M, fuel and technology trade effects as well as avoided fuel imports. Furthermore it assesses net impacts under different additional generation costs. Special focus is on supply and growth effects during the RE deployment phase regarding mobilization of production factors and changes in productivity. In case of increasing inputs of resources due to RE deployment



and restricted availability of resources, other production activities have to shrink. In addi-tion to other models, international interdependences are depicted by common market for goods, capital and money.

Table 4-9: EEFA 2005 study

Title of study:Research question:impact mechanisms direct indirect induced activity fields: scenario

+ installation‐ reinvestments+ O&M‐ fuel generation+ RE trade national scenario‐ fuel trade 1. constant RE at 2003 level+ 2. RE expansion, 12,5%‐ time horizon:+ present 2004‐ future 2010 global scenario

productivity change ‐direct AGC ‐ B‐eff, C‐eff regional extent:indirect AGC ‐ local export scenariomerit order, CO2 price + national



techn. trade

fuel trade


does not exist

EEFA 2005: The expansion of Renewable Energies and employment effects in Germany, B. Hillebrand et al., Energy Policy 34 (2006), 3484‐3494Quantification of positive and negative effects of RE deployment and calculation of a net effect.


O&M

fuel demand

Table 4-10: DIW et al. study 2010/11

Title of study:

Research question:impact mechanisms direct indirect induced activity fields:

+ installation‐ reinvestments+ O&M‐ fuel generation national scenario+ RE trade ‐ fuel trade+ ‐ time horizon:+ avoided fossil fuel import past ‐ present 2000

productivity change ‐ future 2030

direct AGC ‐ B‐eff., C‐eff. regional extent:indirect AGC ‐ local

merit order, CO2 price, ... + nationalmultiplier effect +/‐ regionalaccelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effect


export scenario

fuel demand

techn. trade

fuel trade


does not exist

difference between scenarios:

null RE deployment

advanced RE deployment

DIW 2010: Gesamtwirtschaftliche und sektorale Auswirkungen des Ausbaus erneuerbarer Energien (economic and sectroral impacts of RE deployment); C. Kemfert, J. Blazejeczak, F. Braun, D. Edler, W.P. Schillmedium and long term impact of RE deployment on economic growth and employment

investment

O&M

scenario



One of the earlier comprehensive net studies that takes negative effects into account and assesses employment under two different RE deployment scenarios combined with two different export scenarios is the BMU 2006 study, updated and extended in 2010 (Lehr et al. 2011). This study relies on a global trade model (GINFORS) as well as on an extended macroeconomic model that is integrated in a (econometric) simulation model (PANTA RHEI). Energy sector specific data such as additional generation costs for consumers or industries are based on a very detailed and specific scenario development. Challenges are still the combination of RE-deployment with global market shares as well as the incor-poration of endogenous technology change and competitiveness into the model. The up-dated study (2010) elaborated regional and trade effects in more detail and relies on cur-rent data about installations, investments, production, exports etc. at the national and global levels. Further studies on climate change and energy policy effects in Germany are based on the same simulation model.

Table 4-11: BMU 2011 study

Title of study:

Research question:

impact mechanisms direct indirect induced activity fields: scenario+ installation‐ (in BMU 2006, 2011: substitution effect) reinvestments+ O&M‐ fuel generation national scenario+ RE trade Leitszenario 2009 (national)‐ fuel trade RE‐null scenario (1995)+‐ time horizon:+ present 2009 global scenario‐ future: 2020, 2030 Energy(R)evolution

productivity change ‐direct AGC ‐ B‐eff, C‐eff regional extent:indirect AGC ‐ local export scenariomerit order, CO2 price + CO2 price national 4 export scenarios



BMU 2011: Kurz‐ und langfristige Auswirkungen des Ausbaus der erneuerbaren Energien auf den deutschen Arbeitsmarkt (short‐ and long‐term impacts of RE deployment on the German job market); update fo BMU 2006, Renewable Energies: Employment effects, 2006, Staiß et al.; 2011, Lehr et al.

fuel tradelinks in trade module


does not exist

What are the gross and net employment impacts of RE deployment in Germany ‐ past and future effects?


O&M

fuel demand

techn. trade

The EU 2009 study applies four different models, first an energy sector model (GreenX) that depicts the RE development, costs, realized and avoided installations, M&O, fuel ac-tivities, exports and imports. Second, an extended IO-table (MULTIREG) that includes indirect and direct effects as well as trade effects and assesses past and present gross effects. Third and fourth, two macroeconomic models (NEMESIS and Astra) that assess future net effects. While Astra is an integrated assessment model based on system dy-



namics, NEMESIS relies on econometric calculations. It is a sectoral, macro econometric model covering 30 production sectors and 27 consumption categories and European countries. Each national economy is represented by three different agents: households, government and firms. Each country and each production sector is modelled separately and linked together through external trade. The strong interactions between sectors, agents (consumers, firms, government) and countries through external trade are crucial when studying the potential impacts of structural policies such as RES deployment poli-cies.

Table 4-12: EmployRES, EU 2009

Title of study:


+ installation‐ reinvestments+ O&M national scenario:‐ fuel generation 1. no policy+ RE trade 2. BAU‐ fuel trade 3. accelerated deployment+‐ RE technology imports time horizon: global scenario:+ present 2005 1. IEA reference‐ fuel imports fuel imports future 2030 2. IEA Alternative

productivity change ‐direct AGC ‐ B‐eff, IS‐eff, C‐eff regional extent: export scenario:indirect AGC ‐ local 1. pessimisticmerit order, CO2 price + CO2 price national 2. moderate

multiplier effect +/‐ regional EU 3. optimisticaccelerator effect +/‐ globalfeasible for a net study + positive, ‐ negative effect IS‐eff: income & substitution effect


techn. trade

fuel trade


does not exist

EU 2009: Impact of Renewable Energy policy on economic growth and employment in the EU (EmployRES), 2009; R. Ragwitz et al., contractor: DG TRENWhat is crucial for the analysis of employment impacts of RE deployment?


O&M

fuel demand

Astra can be seen as a recursive simulation approach, and follows system analytic con-cepts, which assume that the implemented real systems can be conceived as a number of feedback loops that are interacting with each other. The model is calibrated for key vari-ables and the spatial coverage extends over the more than 29 European countries. In both models impulses from investment, M&O, exports and imports and prices as well as from avoided technology trade, investment and O&M are taken into account. Hence, the induced negative effects of RE deployment as well as dynamic aspects and multiplier ef-fects are modelled. The results – net employments of a RE deployment situation – are depicted as difference to a reference scenario.

4.3 Discussion

The review of existing studies reveals the strengths and limitations of the various ap-proaches. The simple assessment based on positive effects and a scenario comparison is



easy to understand and to communicate. It could be applied for single technologies and be based on actual project or enterprise data. However, it neglects the impact of price changes on consumption and production and, therefore, neither supplies a real net em-ployment effect nor unveils the overall impact on all economic sectors.

The approach based on IO modelling combines the strengths of technological specificity with economic comprehensiveness, namely it applies technology specific costs and cost structures and takes into account indirect and induced effects as well. It is still easy to communicate. However, the price effect on relative income is only incorporated via a one-time change in the consumption vector, changes in cost and consumption structures due to price changes cannot be directly depicted in the model and, hence, are mostly ignored. In addition, the use of input-output coefficients is limited to industry averages for sectoral input structures, import relations and employment inputs. Employment effects under dif-ferent scenarios could be calculated, however, based on given (historical) input-output relations. Up-to-date and sectoral disaggregated data are required but difficult to get. Overall, this approach, when adjusted for induced effects in industry and households, re-flects an appropriate proxy for recent but not for future net employment effects.

The full economic method is the most promising approach, and quite a few studies have applied so far a rather sophisticated and RE sector adjusted economic model to assess net employment of RE deployment. The knowledge to apply this kind of model is very specific, the required resources and data quantity as well as quality are high. The mecha-nism to calculate the main direct, indirect and induced effects (negative and positive) can be included in detail in these models. The comparison of the model results under different scenarios discloses a comprehensive (net) impact of RE on employment. A comparison between the results of two models that received exactly the same impulses has only been done once (EmployRES 2009). In general the results proved to be rather similar apart from differences in temporal dynamics, which are explained by differences in theoretical foundations (Keynesian behaviour vs. neoclassical or evolutionary assumptions).



5 Conclusion

In this Chapter we draw some conclusions with regard to the further development of the methodological guidelines. We have discussed several types of employment assessment studies by looking at their research focus, scope and methodological approach, data re-quirements and impacts. Figure 5-1 provides an overview of the discussed approaches for gross and net impact studies and highlights those approaches we suggest for the elabora-tion of guidelines.

complex approach

• impacts: net, total economy• effects:positive & negative

simple approach

• impact: gross , RE industry• effects: positive


employment factor approach:

• data: capacity data, employ-ment factors

• complexity:low (direct effects)

gross IO-modelling:

• data: capacity and cost data, IOtable

• complexity:moderate (direct & indirect effects)

positive effects with scenario:

• data: employment factors (EF)

• complexity:moderate (direct & indirect effects, scenario comparison)

full economic assessment

approach:

• data:• macro-economic• energy sector • trade relations

• complexity: very complex (direct, indirect & induced effects, scenario comparison)

supply chain analysis:

• data: capacity and cost data

• complexity:moderate (mainly direct effects)

positive and negative effects by net IO modelling:

• data: IO-table with consumption vector

• complexity:complex (direct, indirect & induced effects), [scenarios]

Figure 5-1: Methodological approaches of impact assessment studies

5.1 Gross impacts

Gross employment studies focus on the economic relevance of the RE industry in terms of employment, thus on the number of jobs provided in the RE industry and the structural analysis of employment in the RE industry. Furthermore employment in supplying indus-tries are also included as indirect or induced impacts. The aim is to provide transparency on employment in an industry that is in the public interest but not adequately represented in official statistics, thus also enabling monitoring of this industry in the course of RE pro-motion. An assessment of the overall economic impact of RE promotion is not possible with gross studies, since these only include the positive impacts of RE deployment, but not the negative impacts of reduced conventional energy deployment.

The review of existing studies has distinguished three major approaches:

• the employment factor approach, • supply chain analysis, and • cost based IO modelling.



These approaches have their respective strengths and limitations.

Employment factor (EF) approaches are easy to understand and to communicate. They have the potential of being very technology-specific and based on actual project or enter-prise data. The quality of the results largely depends on the quality of the employment factors used. Unfortunately, studies with thorough assessments of employment require-ments for RE technology deployment and use are scarce. Employment factor studies are often based on the same few sources, even though a lack of documentation and trans-parency make it difficult to compare and use the employment factors. Moreover, the exist-ing employment factors show large differences for the same technologies. To enhance the reliability of results, sound and well documented studies generating employment factors would be beneficial. The EF approach usually focuses on direct employment in the RE industry.

The supply chain method is a sophisticated approach to capture the complexity of activi-ties and supply chains related to renewable energy use. Combining this with an enterprise survey should provide reliable results, but such a study would require rather large financial and personal resources.

Cost-based IO modelling combines the strengths of technological specificity (e.g. costs and cost structures) with economic comprehensiveness (indirect and induced impacts). A consistent methodological framework allows economic and employment impacts to be calculated simultaneously, thus making plausibility checks possible. One limitation that comes with the use of an input-output model is the assumption of industry averages for sectoral input structures, import relations and employment coefficients. This limitation can be relaxed by integrating specific enterprise data into the IO model.

For all three approaches, the reliability of the results strongly depends upon the quality of the input data and the assumptions. Therefore, in general, a good documentation of input data and assumptions is needed to be able to assess the results.

With regard to the development of guidelines we propose to focus on the employment factor approach and the IO modelling approach. The employment factor approach is a less demanding method with regard to data requirements and modelling know-how. Yet it relies on adequate and well documented employment factors which may not be available for a specific country. Its focus is on direct employment. The IO modelling approach is a more comprehensive framework that ensures a consistent treatment of expenditures re-lated to RE deployment and the induced employment. It allows to cover indirect employ-ment outside the RE industry and yet is flexible enough to integrate technology or com-pany specific data.



5.2 Net impacts

In the field of net impact assessment there exist many approaches that intend to assess net impacts. Regarding three aspects, the application of scenarios, the effects captured in these studies and the modelling approach, we can distinguish between three main meth-odological types:

• Simple assessment based on positive effects and a comparison of two scenarios. • Net IO-modelling approach including positive and negative effects. • Macroeconomic modelling approach.

The first approach does not focus on the full economic impact but more on a comparison of two situations, one with a fossil/nuclear energy deployment and one with RE deploy-ment. It is in mainly based on employment factors (EF) that are derived either from em-pirical studies or from calculations with statistical data like employment and turnover. This approach is easy to understand, to calculate and to communicate. Besides data on in-vestments, trade and generation, employment factors and changes over time are re-quired. However, the quality of results is limited since the EF represent average values that are applied at a rather aggregated level. The price effect, which is considered as a strong negative effect, is neglected. Furthermore, the quality of the results depend very much on the quality of the EF, which should be country and technology specific, up-to-date, i.e. adjusted in line with the (dynamic) development in the field of RE deployment, and the economy.

The second approach focuses on the question how many jobs – net number of jobs - a single RE-technology provides by taking into account positive and negative effects. The assessment is generally conducted with an IO-model. This approach is more challenging with respect to data and modelling know-how but the method and results are still easy to communicate. The approach capture the RE deployment impulses at a more disaggre-gated level, although in comparison to a macroeconomic modelling approach the data provide an excerpt of the full economic picture. It is difficult to include changes over time of input-output relations, especially when looking at future development. Up-to date and sectoral disaggregated IO-data are necessary but in some cases difficult to get from offi-cial statistics. Overall, the approach is considered as suitable to reflect and compare ef-fects of technologies, but a comparison between scenarios is missing and induced effects are not fully integrated. Therefore, this approach reflects a good proxy for net employment effects but represents no real net employment effects.

The macroeconomic approach is the most comprehensive assessment to capture overall economic effects. It addresses employment in all economic sectors and shows to which extent the number of jobs in the total economy changes when RE deployment increases



(scenario). The approach is difficult to understand and to communicate since there exists a variety of macroeconomic models with different modules, impact mechanisms and loops. The requirements regarding data are high since macroeconomic data as well as energy sector specific data are used. The results are of high quality, if the data are good and if the modelling approach includes all relevant impulses and effects. Besides the model, the scenario development – in particular assumption on prices, exports – is crucial for the quality of the impact assessment and the size of the impact. This full economic assessment approach is best suited to assess net impacts but for non-modeller it looks like a black box.

Many studies/works have assessed impacts of RE deployment that are called net effects but they do not all match the criteria we defined for net impact studies. Under a scientific point of view, the best model for impact assessment is the full economic assessment ap-proach - complex macro-economic modelling -, which, however is with respect to data and modelling requirements not applicable in many countries. Under feasibility and practicabil-ity aspects, therefore, we suggest to elaborate guidelines for the application of a net IO-model approach. This approach could be applied for the assessment of gross and net effects. In addition to the above described approach, a change in the consumption vector should be included to capture induced effects. Furthermore, we suggest to assess im-pacts under two scenarios – reference and advanced RE deployment - and compare the results.

5.3 Generic conclusion

This review has looked in detail into the diverse approaches to assess the employment impact of RE. Here, we like to emphasize some very important but more generic points:

• Net and gross studies address two very different research questions: the first investi-gates the impact on all economic sectors including thereby negative impacts, while the latter estimates the growth, significance and relevance of the RE industry in job units but does not analyse effects beyond this industry.

• The quality of the data is most crucial for a high quality assessment. With high quality data simple approaches like the employment factor approach might provide better data than a full economic model based on mediocre data quality. High quality data should be very technology specific, country specific, very recent and disaggregated as well as with transparent and clear system boundaries and comprehensible assumptions.

• Net impacts of different studies do not always reflect the same impacts. To compare them, it must be clear what the baseline and advanced deployment scenario is, which positive and negative effects are included (or excluded), which technologies are incor-porated and system boundaries are set. The same applies to gross impacts.



Overall, we arrive at the conclusion that, for developing guidelines for studies exploring the employment impacts of RE deployment, it would be advisable to focus on four meth-odologies: the employment factor approach, the gross IO model approach, a net IO model approach, and a full economic model. The first two are gross impact methods. They look for the number of jobs created in the RE industry while the last two aim to unveil the eco-nomic impact of RE deployment in the overall economy.



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Annex: Overview of detailed evaluation of impact studies

Gross impact studies: detailed overview

The results of a detailed comparison and analysis are included in an Excel table that ac-companies this report. The Table is presented below.



Type of study Employment factor approachesAuthors Singh, V. et al. (REPP) 2001 Peterson/Poore (EPRI), 2001 Pembina, 2004

TitleThe Work that goes into Renewable Energy.

California Renewable Technology: Market and Benefits Assessment

Canadian Renewable Electricity Development: Employment Impacts

Year of publication 2001 2001 2004(?)

Institution Renewable Energy Policy ProjectElectric Power Research Institute (EPRI), Global Energy Concepts, LLC

Pembina Institute for Appropriate Development

Region US California CanadaBase year 2000 2000 (- 2010) 2004 - 2020

Goal of study

Analysis of jobs and skills needed for installing and operating PV roof systems, wind power plants and biomass co-firing

Employment Benefits from Deployment of RE technologies

To estimate employment created from deployment of low-impact renewable electricity generation

Impact indicatorsTurnoverGross outputGross value added

Jobs job-years / number of permanent jobsNumber of employees

Fulltime equivalents

working hours transformed into FTE person years, assuming 1960 working hours per FTE FTE jobs

RES sectorelectricity yes yes yesheatfuels

RES technologies (which and how)Electricity and CHP

Large hydro powerSmall hydro power 100 kW plant yes

Wind onshore

37.5 MW onshore wind farm near high-voltage transmission line, excluding manufacturing of transformers, hydraulics and safety equipment 50 MW onshore wind farm yes

Wind offshore yes

Solar PVfixed roof-based 2 kW PV-system (no tracking) 10 kW PV system yes

Concentrating solar 100 MW plant noWave and tide yesBiogas 2 MW landfill gas / biogas plantWoodWaste incinerationWaste co-incineration

Other biomassco-firing of wood wastes and energy crops in coal power plants 50 MW biomass plant biomass unspecified

Geothermal 50 MW geothermal power plant yesAuxiliary technologies

Storage technologies no noGrid technologies no no

Activities (which and how)Operation of RES plants 10 years of servicing yes yes

yes in the case of PV and wind, partly (biomass feeders) in the case of biomass yes yes

n.a. no noFuel generation and supply yes only transport yesDemolition no no no

Export of RES products no no

no no no

no noGovernment activities no no

no no

Replacement in existing RES plants

Basic research & development

Marketing of green electricity

Manufacturing, construction and installation of new RES plants

Manufacturing of RE production facilities



Type of study Employment factor approachesAuthors Singh, V. et al. (REPP) 2001 Peterson/Poore (EPRI), 2001 Pembina, 2004Impacts included

Direct yes yes yesIndirect no ?? probably not, but not specified

Intermediate input impact

Investment impactInduced no no no

yes, but assumptions not clearImpact definitions

Definition direct

• for wind and PV: manufacturing of all finished parts incorporated in power plant, delivery to power plant, construction and installation of power plant, O&M for 10 years; • for biomass co-firing: cultivation and collection of biomass, delivery of biomass to plant, manufacturing of biomass feeder system no explicit definition no definition

Definition indirect n.a. n.a. n.a.

Definition induced n.a. n.a. n.a.

Leakage (imports from outside the region)

Methodological approachEmployment factors yes yesSupply chain analysis

Cost-based IO modelling

yes; labour costs calculated as an estimated fraction of capital or O&M costs and then converted into FT employees

Supply-side approachEmployment factors: Enterprise data on employment requirements for wind and PV, literature review and expert judgement for biomass co-firing

Employment factors: Feasibility studies, with rough estimates for the fraction of labour costs

Employment factors: Partly literature review and partly expert judgement

Requirements for dynamic analysis

n.a. no no

n.a. no n.a.

n.a. no no

n.a. no not reproduceable

n.a. n.a. n.a.

Strengths• Detailed technology-specific analysis of labour requirements

• Detailed technology-specific analysis of costs and operation employees

• use of terms: jobs sustained, market size instead of job impacts

Limitations

• Rough estimates of maintenance and MCI employees• No consideration of dynamic aspects for future projections

• Weak reproduceability of assumptions• No consideration of dynamic aspects for future projections

Remarks• Discusses future trends in labour intensity

• Discusses future trends in labour intensity

Changes in labour productivityRegional shifts of production sitesStructural change in the economy

Data sources for RE related employment

Cost degression (changes in specific costs)Changing cost structures due to technological learning



Type of studyAuthors

TitleYear of publication

Institution

Supply chain analysisRutovitz/Atherton, 2009 Wei et al., 2010 DTI (Ed.) 2004

Energy Sector Jobs to 2030: A Global Analysis

Putting renewables and energy efficiency to work: How many jobs can the clean energy industry generate in the US? Renewable Supply Chain Gap Analysis

2009 2010 2004

Institute for Sustainable Futures University of California, Berkeley Mott MacDonald, Bourton GroupRegionBase year

Goal of studyImpact indicators

TurnoverGross outputGross value added

JobsNumber of employees

Fulltime equivalentsRES sector

electricityheatfuels


Large hydro powerSmall hydro power

Wind onshoreWind offshore

Solar PVConcentrating solarWave and tideBiogasWoodWaste incinerationWaste co-incineration

Other biomassGeothermal

Auxiliary technologiesStorage technologiesGrid technologies

Activities (which and how)Operation of RES plants

Fuel generation and supplyDemolition

Export of RES products

Government activities






10 world regions and G8 countries USA UK2009 - 2030 2009 - 2030 2003

Analysis of the potential job creation in the global energy sector associated with two energy scenarios

Estimation of job development in the clean energy industry (RE, EE and CCS) until 2030 under various scenarios, compared to loss of jobs in the coal and natural gas sector

Estimate the current and future size of the UK renewables industry in terms of "monetary value" and jobs; assess the gaps in RE supply chains; identify key opportunities and threats and make recommendations for a better exploitation of the potential

"monetary value"

number of jobs without further specification

FTE person years FTE jobs

yes yes yespartlyyes

noyes < 20 MW

yes yes yesyes yes

yes yes yesyes yes no"ocean" in the future

landfill gas landfill gas

energy from waste

biomass unspecified biomass unspecified biomass waste and energy cropsyes yes no

yesno no yesno no

yes yes yes

yes yes yesno, if new capacity is calculated as difference of installed capacity between two time periods implicitly? probably notyes yes yesno no no

yes no yes

no no no

no no nono no no

no no no




Supply chain analysisRutovitz/Atherton, 2009 Wei et al., 2010 DTI (Ed.) 2004

Impacts includedDirectIndirect


Investment impactInduced

Impact definitions

Definition direct

Definition indirect

Definition induced


yes yes yesno Only within RE supply chain

with simple multiplier, calculated as average from three studies

probably notno no estimated by applying a factor of 0.25

yes no, all jobs assumed to be in USimport content estimated at each level of supply chain

jobs in the primary industry sector, e.g. the industry directly related to renewable energies, esp. In fuel production, manufacturing, construction , operation and maintenance

jobs created in the design, manufacturing, delivery, construction/installation, project management, O&M of the dif ferent components of the technology or power plant under consideration

The study focuses on the supply chains of RE technologies, there is no separation of direct and indirect activites; since mainly activities are included, that are specific to RE use, direct impacts should dominate

jobs in secondary industries supporting the primary industry sector

supplier effect of upstream/ downstream suppliers to direct activities

expenditure induced effects in the general economy due to economic activity and spending of direct and indirect employees n.a.

Methodological approachEmployment factorsSupply chain analysis


Supply-side approach


Strengths

Limitations

Remarks




yes FTE jobs per MW peak

Detailed supply chain analysis for each technology; generation of technology trees spreading across several tiers/layers; cost breakdown of each element of technology tree, estimation of labour content with typical labour costs and value added

Enterprise survey

Employment factors: Literature review; Labour productivity data from ILO statistics Employment factors: literature review

Costs and cost structures: Real project data, feasibility studiesTypical salaries: Available statistics

yes no yes

n.a. no

yes no

yes no yes

n.a. no

• global scope of analysis• comparison of employment factors from various studies• Dynamic aspects largely considered

• Clarification of definitions and appropriate calculation of index-numbers• simple approach, easy to understand

• Detailed technology-specific analysis of supply chains and cost structures

• simplifying assumptions due to global analysis

• No consideration of dynamic aspects for future projections

• Indirect impacts outside the RE sector not covered

• calculation of "net" job impacts incomplete, since higher energy prices due to RE deployment and lower purchasing power leading to reduced employment not taken into account

• Boundary between direct and indirect not clear, thus comparison to results from other studies difficult• High costs for enterprise survey




TitleYear of publication

Institution

Cost-based IO modellingRagwitz et al., 2009 Lehr et al., 2011 Lantz 2009

EmployRES: Employment and economic growth impacts of sustainable energies in the European Union

Kurz- und langfristige Auswirkungen des Ausbaus der erneuerbaren Energien auf den deutschen Arbeitsmarkt;english summary: BMU (ed., 2010): Renewably employed: Short and long-term impacts of the expansion of renewable energy on the German labour market

Economic Development Benefits from Wind Power in Nebraska: A Report for the Nebraska Energy Office

2009 2011 2009

Fraunhofer ISI et al. GWS/DIW/DLR/ZSW/ISINational Renewable Energy Laboratory

RegionBase year

Goal of studyImpact indicators

TurnoverGross outputGross value added

JobsNumber of employees

Fulltime equivalentsRES sector

electricityheatfuels


Large hydro powerSmall hydro power

Wind onshoreWind offshore

Solar PVConcentrating solarWave and tideBiogasWoodWaste incinerationWaste co-incineration

Other biomassGeothermal

Auxiliary technologiesStorage technologiesGrid technologies

Activities (which and how)Operation of RES plants

Fuel generation and supplyDemolition

Export of RES products

Government activities






EU 27 Germany US state of Nebraska1990 - 2005, 2005 - 2030 2007-2030 2011 - 2030

Gross impact part: Estimation of development of value added and jobs in RE sector in EU 27 between 1990 and 2005; Estimation of development until 2030

Gross impact part: Estimation of employment in the RE industry (2007, 2008 , 2009) and projection to 2030 according to 3 scenarios of domestic deployment + 4 export scenarios

Estimation of employment impacts of wind power deployment to reach the national 20% wind energy goal until 2030

yesyes

yes

yes

yes yes

yes yes wind poweryes yesyes yes

yes yesyes yes

yes yes yesyes yes

yes yesyesyesyes yesyesyesyes

yes biomass unspecifiedyes yes

no no nono no no

yes yes yes

yes yes yes

estimates yes noyes yes n.a.no no noyes calculated with multiregional IO model, for wind and PV based on world market shares

yes. based on enterprise survey and scenarios of world trade development and shares of German enterprises no

yes, estimated via depreciation of RE industry yes no

no yes nono yes no

no no no




Cost-based IO modellingRagwitz et al., 2009 Lehr et al., 2011 Lantz 2009

Impacts includedDirectIndirect


Investment impactInduced

Impact definitions

Definition direct

Definition indirect

Definition induced


yes yes yesyes yes

yes, IO model yes, IO model yesyes, IO model, estimated via depreciation probably not nono no yesyes, multiregional IO model; domestic content assumed for selected technologies

yes, domestic content based on enterprise survey

yes, domestic content based on assumptions

Activities belonging to the cost components of operation and installation costs; partly also includes RE related supply chain activities (e.g. manufacturing of wafers, solar cells, modules)

Operating companies and activities belonging to the cost components of operation and installation costs

Direct impacts accrue from expenditures in the wind industry. Direct beneficiaries generally include wind energy developers, construction companies, operations and maintenance personnel, landowners, and equity investors.

All upstream activities in the economy supplying goods to the direct activities, also includes manufacturing of investment goods used by the RE industry

All upstream activities in the economy supplying goods to the direct activities

Indirect impacts accrue in supporting industries as a result of increased demand for basic goods and services. Indirect beneficiaries include material and component suppliers as well as accountants and legal personnel.

n.a. n.a.

Induced impacts result from reinvestment and spending by direct and indirect beneficiaries. Induced benefits are often associated with increased business at local restaurants and retail establishments. In short, they include all increases in economic activity driven by increased spending of direct and indirect beneficiaries.

Methodological approachEmployment factorsSupply chain analysis


Supply-side approach


Strengths

Limitations

Remarks




Operation and installation costs, allocated to cost components and supplying industries; Multiregional IO model to calculate direct and indirect employment, including supply chains across country boundaries

Operation and installation costs, allocated to cost components and supplying industries; IO model to calculate direct and indirect employment; exports and import shares of RE technologies from enterprise survey

Operation and installation costs, allocated to cost components and supplying industries; IO model to calculate direct, indirect and induced employment; assumptions for "domestic" shares for wind technology products and components

Enterprise survey to identify cost structures, import shares and exports

economic information on each technology in every country; Cost structures: Literature review and expert judgement

Domestic expenditures, exports, import shares and cost structures: Enterprise survey

Costs, cost structures, domestic content, employment multipliers: JEDI model, expert judgement

yes yes yes

no no no information available

yes yes probably notyes for dynamic technologies (wind, PV)

partly, via assumptions for export scenarios yes, via scenario assumptions

no no information availableprobably not (constant multipliers from the IMPLAN model)

• Coherent methodology, also for calculation of exports• Impacts across country borders included (multiregional IO model)• Dynamic requirements largely met

• Coherent methodology, also for calculation of exports• High quality of input data due to enterprise survey• Dynamic requirements largely met

• Coherent methodology for calculation of economic and employment impacts• State impact multipliers based on IMPLAN model

• Weaker database for Eastern Europe than for Western Europe• Loss of RE specificity due to use of industry averages in IO model

• Loss of RE specificity due to use of industry averages in IO model

• No consideration of exports• Dynamic requirements only partly met• Loss of RE specificity due to use of industry averages in IO model

• High costs for enterprise survey• JEDI model is often used at the sub-national level



Net impact studies: detailed overview

Note: the activity installation of RE plants includes also manufacturing and construction.

Comparison of studies for the estimation of job impacts related to renewable energy useName of project Energy Sector Jobs to 2030: A global

analysis; Greenpeace 2009

Putting Renewables to Work: How many Jobs can the clean Energy Industry generate in the US? REAL 2010

Authors/editor Rutovitz et al. Wie, Patadia, KammenYear of publication 2009 2010 (update of RAEL 2004)Institution Institite for Sustainable FuturesContracting body Greenpeace InternationalRegion/Country world and 10 regions USABase year 2005, 2010, 2020, 2030 2009 - 2030Goal of study

potential job creation associated with two energy scenarios until 2030 (net employment effect is not assessed explicitly but it can be calculated as the difference between both scenarios)

discussion on methodology, comparison of existing studies, assessment of impact on net employment by using an analytical model (net = comparison between two scenarios with positive (in)direct effects )

Impact indicators/outputTurnoverInvestmentGross outputGross value addedJobs (gross) x

Number of employees xFulltime equivalents

GDPJobs (net, change in ... compared to) x (no negative effects) x (no induced effect for RE)

Number of employees xFulltime equivalents

other indicatorsRES sector

electricity x xheatfuels x

RES technologies (which and how)Electricity and KWK x

Hydro large x (aggregated as hydro)Hydro small xWind x xSolar PV x xConcentrating solar x (solarthermal)Wave and tide xBiogasWoodWaste incinerationWaste co-generationOther biomass x (aggregated as biomass) x (biomass in general, not specified)Geothermal x x

HeatSolar thermalBiogasWoodOther biomassWaste incinerationWaste co-generationHeat pumpsDeep Geothermal

Fuels1st generation (x) energy supply2nd generation

Activities (which and how)Operation of RES plants x xInstallation of new RES plants x xReinvestment in old RES plants (Repowering)Fuel generation and supply x xRES-related supply chainsExport of RES products x (manufacturing is divided into domestic use & administration, R&D, ...Rest of economy



Included impact regionsDomestic x x (USA)Other countries / imports x (%local production)

Impacts includeddirect x x

investment xoperation and maintenance x

Indirect xIntermediate input impactInvestment impact

Induced (only for energy efficiency not for RE)Impact mechanisms use of employment factors no mechanisms, just employment factors from

other studiesinvestment effects RES (x) (x)"de"investment effect fossilO&M effekt RES (x) (x)"de" O&M effect fossilprice and cost effect on

households industry

accelerator effectmultiplier effectproductivity effectsexport effectsprice effect of RES on electricity, heat (MO)dynamic effectlead market /innovation effect

Scenariosdomestic reference scenario (the investigation ist not restricted to a certain BAU based on EIA reference data 2009

domestic scenario (scenarios with differing energy demand for energy efficiency)

world scenario reference scenario (IEA World Energy Outlook export scenario

advanced RES deployment scenario

domestic scenario

world scenario Greenpeace Energy [R]evolution Scenario (targeting a reduction of 50% below 1990 greenhouse emission)

export scenario sectors included

price projections (fossil, CO2)Methodological approach

Index-based / analytical x (Employment factors) employment factorsCost-based approach

Supply-side approach(macroeconomic) equilibrium model(macroeconomic) econometric model(macroeconomic) systems dynamics

Type of data source data from other studies data from other studiesReal project dataEstimated project dataCostsCost structuresCensusEstimationExpert estimationstatistics on economic & demographic data xsurvey, interviews data from associations



Comparison of studies for the estimation of job impacts related to renewable energy useName of project Bewertung der volkswirtschaftlichen

Auswirkungen der Unerstützung von Ökostrom in Österreich; IHS 2007

Ermittlung der Arbeitsplätze und Beschäftigungswirkungen im Bereich Erneuerbarer Energien; BEI 2003

Authors/editor Bodenhöfer et al. / IHS Kärnten Pfaffenberger et al. / Bremer-Energie-InstitutYear of publication 2004 (updated 2007) 2003Institution IHS Kärnten Bremer-Energie-InstitutContracting body Hans-Böckler-StiftungRegion/Country Austria GermanyBase year 2004-2006, 2018 2001-2003, 2025Goal of study

makro economic effects caused by new law 2006 (Ökopstromgesetz) (net = investment + operation -budget), effects per RE-technology

Asessment of direct and indirect employment effects with I-O model (net = investment + operation - budget), effects per RE-technology

Impact indicators/outputTurnoverInvestmentGross outputGross value added xJobs (gross)

Number of employeesFulltime equivalents x

GDPJobs (net, change in ... compared to) (x) no scenario comparison x (job/kW or kWh, no scenario comparison)

Number of employeesFulltime equivalents x x


electricity x xheatfuels


Hydro large x (aggregated as hydro) xHydro small xWind x xSolar PV x xConcentrating solarWave and tideBiogas x xWood xWaste incinerationWaste co-generationOther biomass x (aggregated as biomass)Geothermal x (large and small)


Fuels1st generation2nd generation



Activities (which and how)Operation of RES plants x xInstallation of new RES plants x xReinvestment in old RES plants (Repowering)Fuel generation and supply agriculture and forestryRES-related supply chains xExport of RES products

administration, R&D, ...Rest of economy "other economic sectors" + as part of budget

effectIncluded impact regions

Domestic x x (Germany)Other countries / imports value added is subdivided into domestic and

abroad (based on different import ratios)Impacts included

direct x xinvestment x xoperation and maintenance x x

Indirect x x (IO model)Intermediate input impact ?Investment impact x

Induced x (budget effect) x (budget effect)Impact mechanisms

investment effects RES x x"de"investment effect fossilO&M effekt RES x x"de" O&M effect fossilprice and cost effect on x x

households industry

accelerator effectmultiplier effect xproductivity effectsexport effects (discussed but not included)price effect of RES on electricity, heat (MO)dynamic effect (explicitely no learning effects, ...)lead market /innovation effect

Scenarios own assumptions for each technology (IHS Kärnten)

domestic reference scenario with import figuresdomestic scenarioworld scenarioexport scenario

advanced RES deployment scenariodomestic scenarioworld scenarioexport scenario sectors included

price projections (fossil, CO2) two market pricesMethodological approach

Index-based / analyticalCost-based approach x IO model IO model (IKARUS)Supply-side approach(macroeconomic) equilibrium model(macroeconomic) econometric model(macroeconomic) systems dynamics

Type of data sourceReal project dataEstimated project dataCosts own estimation for each technology (model

installations)own estimation for each technology (model installations)

Cost structures own estimation for each technology (model installations)

own estimation for each technology

CensusEstimation xExpert estimationstatistics on economic & demographic datasurvey, interviews xdata from associations x



Comparison of studies for the estimation of job impacts related to renewable energName of project

Solar Photovoltaic Employment in Europe; EPIA 2009

Authors/editor PV employmentYear of publication 2009Institution EPIA, WIP, University Flensburg, National

Technical University of AthensContracting bodyRegion/Country EU27Base year 2005, 2020, 2030Goal of study Emphasise the positive employment net effect of

lang-run PV projects; (net = investment + operation - avoided investments - budget), effect per RE technology

Impact indicators/outputTurnoverInvestmentGross outputGross value addedJobs (gross) x

Number of employeesFulltime equivalents x (person years)

GDPJobs (net, change in ... compared to) x (no scenario comparison)

Number of employeesFulltime equivalents x


electricity x (just PV)heatfuels


Hydro largeHydro smallWindSolar PV xConcentrating solarWave and tideBiogasWoodWaste incinerationWaste co-generationOther biomassGeothermal


Fuels1st generation2nd generation

Activities (which and how)Operation of RES plants xInstallation of new RES plants xReinvestment in old RES plants (Repowering)Fuel generation and supplyRES-related supply chains xExport of RES products xadministration, R&D, ... xRest of economy



Included impact regionsDomestic x (EU)Other countries / imports x (rest of world

Impacts includeddirect x

investment xoperation and maintenance x

Indirect x (IO model)Intermediate input impactInvestment impact

Induced x (consumption)Impact mechanisms

investment effects RES x"de"investment effect fossil xO&M effekt RES x"de" O&M effect fossilprice and cost effect on x

households industry

accelerator effectmultiplier effect xproductivity effectsexport effectsprice effect of RES on electricity, heat (MO)dynamic effectlead market /innovation effect

Scenarios yes to show different development paths, but no comparison between scenarios

domestic reference scenario moderate implementation scenario (cumulative installation of 274GW until 2030)

domestic scenario

world scenarioexport scenario static import/export figures along the value chain

(30%/15%)advanced RES deployment scenario advanced implementation scenario (cumulative

installation of 860GW until 2030) domestic scenario

world scenarioexport scenario static import/export figures along the value chain

(30%/15%) sectors included


Index-based / analyticalCost-based approach x IO model (University of Flensburg)Supply-side approach(macroeconomic) equilibrium model x (University of Athens)(macroeconomic) econometric model(macroeconomic) systems dynamics

Type of data sourceReal project dataEstimated project dataCostsCost structuresCensusEstimationExpert estimationstatistics on economic & demographic data xsurvey, interviews data from associations x



Comparison of studies for the estimation of job impacts related to renewable energy useName of project

The expansion of renewable energies and employment effects in Germany; EEFA 2005

Economic and sectoral impacts of RE deployment; DIW 2010

Authors/editor Hillebrand et al. / Energy Policy Kemfert, Blazejczak, Braun, Edler, SchillYear of publication 2006 2010Institution EEFA GmBHContracting bodyRegion/Country Germany GermanyBase year 2003 -2006, 2010 2000 - 2030Goal of study

Quantifying two effects (investments, price increase) in order to compute an overall net effect

net effects of RE deployment

Impact indicators/outputTurnoverInvestmentGross outputGross value addedJobs (gross)

Number of employeesFulltime equivalents

GDP x x (change to reference scenario)Jobs (net, change in ... compared to) x (relative change to reference scenario)

Number of employees x xFulltime equivalents


electricity x xheat xfuels x

RES technologies (which and how)Electricity and KWK x x

Hydro large x (aggregated as hydro) x (aggregated as hydro)Hydro smallWind x xSolar PV x xConcentrating solarWave and tideBiogas x xWoodWaste incinerationWaste co-generationOther biomass x (aggregated as biomass) x (aggregated as biomass)Geothermal x x

HeatSolar thermal xBiogasWoodOther biomassWaste incinerationWaste co-generationHeat pumpsDeep Geothermal

Fuels1st generation x2nd generation

Activities (which and how)Operation of RES plants xInstallation of new RES plants x xReinvestment in old RES plants (Repowering)Fuel generation and supply xRES-related supply chainsExport of RES products xadministration, R&D, ...Rest of economy



Included impact regionsDomestic x (Germany) x (Germany)Other countries / imports world

Impacts includeddirect x

investment x xoperation and maintenance x

IndirectIntermediate input impact x xInvestment impact x x

Induced x x Impact mechanisms

investment effects RES x x"de"investment effect fossil x xO&M effekt RES x"de" O&M effect fossilprice and cost effect on x x

households x x (reduced income)industry x

accelerator effectmultiplier effect xproductivity effects xexport effects xprice effect of RES on electricity, heat (MO)dynamic effect x (learning effect)lead market /innovation effect

Scenarios adapted from "0-Szenario" and "doublin szenario" (reference see comment)

domestic reference scenario status-quo reference scenario (share of RES contrafactual null scenario (no further RE domestic scenarioworld scenarioexport scenario

advanced RES deployment scenario"simulation scenario" (achieving 12,5% RES in 2010)

LEAD scenario 2009 (BMU 2010) with variations (export, competitivness, availability of employees)

domestic scenario

world scenarioexport scenario x sectors included


Index-based / analyticalCost-based approach

Supply-side approach(macroeconomic) equilibrium model(macroeconomic) econometric model structural model with several modules, marginal

effects x (NiGEM)

(macroeconomic) systems dynamicsType of data source

Real project dataEstimated project dataCosts x xCost structures xCensusEstimationExpert estimationstatistics on economic & demographic data x xsurvey, interviews data from associations



Comparison of studies for the estimation of job impacts related to renewable energy useName of project

EmployRES 2009; EU 2009

Renewable Energies: employment effects (2006) BMU 2006, update: Renewable employed!; Short- and longterm effects of RE deployment on the German job market, BMU 2011

Authors/editorRagwitz et al., EC DG TREN

Lehr, O'Sullivan, Lutz, Edler, Nitsch, Nienhaus, Bickel, Breitschopf (2011);Staiß et al./BMU Germany (2006),

Year of publication 2009 2011/2006Institution Fh-ISI, Energy Economics Group, Ecofys,

Seureco, rütter+partnerGWS/DLR/DIW/ZSW/ISI (2011); ZSW/ DLR/ DIW/GWS (2006)

Contracting body EU commission BMU, GermanyRegion/Country member states of EU 27 GermanyBase year 1990 - 2005, 2005 - 2030 2007, 2008, 2009, 2010, 2020, 2030 (2011); 2004,

2010, 2020, 2030 (2006)Goal of study gross and net employment and GDP effects of

RE deployment in EUgross and net employment effects of RE deployment in Germany

Impact indicators/outputTurnover xInvestment xGross outputGross value added xJobs (gross)

Number of employees xFulltime equivalents x

GDP x x (2011)Jobs (net, change in ... compared to) x x

Number of employees xFulltime equivalents x


electricity x xheat x xfuels x x


Hydro large x x (not differeniated)Hydro small xWind x x (offshore/onshore)Solar PV x xConcentrating solar x xWave and tide x xBiogas x xWood x xWaste incineration xWaste co-generation xOther biomass x xGeothermal x x

Heat x xSolar thermal x xBiogas x xWood x xOther biomass x xWaste incineration complete plant, biomass shareWaste co-generation biomass share, which part of plant?Heat pumps x xDeep Geothermal x x

Fuels x x1st generation x x (Biomass)2nd generation x

Activities (which and how)Operation of RES plants x xInstallation of new RES plants x xReinvestment in old RES plants (Repowering) estimates xFuel generation and supply x xRES-related supply chains x xExport of RES products

calculated with multiregional IO model, based on world market shares; scenario

calculated from world trade in RES goods based on world market shares and traded shares of investment,

administration, R&D, ... xRest of economy x x



Included impact regionsDomestic x (EU and member states) x (Germany)Other countries / imports x (rest of world) x (world by 10 regions)

Impacts includeddirect Operation or installation costs broken down to

cost components / primary activitiesOperation or installation costs broken down to cost components / primary activities

investment yes, estimated direct value added. x, (investments, production value, employment)operation and maintenance yes, estimated direct value added. x (turnover, production value, employment)

Indirect All indirect economic activities in the economy All indirect economic activities in the economyIntermediate input impact x (IO model) x (IO model)Investment impact x (IO model) x (IO model, wind, PV and other RE as new

"branch")Induced x (price effect on consumption, income effect) x (price effect on consumption)

Impact mechanismsinvestment effects RES x x"de"investment effect fossil x x (called here: substution effect)O&M effekt RES x x"de" O&M effect fossil xprice and cost effect on

xbudget effect: additional generation costs, paid by firms, households, gov't leading to lower demand for other goods

households x xindustry x x

accelerator effect x xmultiplier effect x xproductivity effects x xexport effects x xprice effect of RES on electricity, heat (MO) x (via negative additional generation costs)dynamic effect capital stock, wages, productivty via capital stock, wage rigidity, price and

productivity developmentlead market /innovation effect based on patent shares etc. exogenous value based on historic development,

included via (labour)coefficients Scenarios

domestic reference scenario x xdomestic scenario no policy own scenario with zero investment in RE since

1995; Energy Report IV, updated to 2050 (2006)world scenario IEA reference IEA reference (2002)export scenario pessimistic World market shares

advanced RES deployment scenariox x

domestic scenario BAU and advanced deployment own scenario NatPlus-2005: based on Energy Report IV, focused on climate and RE targets,

world scenario IEA alternative Energy[r]evolution (2011); EREC DCP (2001) for primary energy use (2006)

export scenario moderate and optimistic w.r.t. market shares based on lead market factors

4 possible developments of world market shares (pessimistic, moderate, optimistic, max)

sectors included heat, power, fuel heat, powerprice projections (fossil, CO2) IEA 2007 LEAD Scenario, IEA (2011); Energy Report IV,

updated to 2050 (2006)Methodological approach

Index-based / analyticalCost-based approach Operation and installation costs (Green-X);

allocated to supplying industries; IO model (Multireg)

Operation and installation costs, allocated to supplying industries; IO module (Inforge)

Supply-side approach(macroeconomic) equilibrium model(macroeconomic) econometric model NEMESIS Panta Rhei(macroeconomic) systems dynamics Astra

Type of data sourceReal project dataEstimated project dataCosts RE deployment in Green-X LEAD Scenario (Leitstudie)Cost structures Studies, expert judgement survey + expert informationCensusEstimationExpert estimationstatistics on economic & demographic data x xsurvey, interviews x, to support statistical datadata from associations (x) x

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