“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
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 nonprofit corporation, which promotes applied research and assures the link between fundamental 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 institutions. The Energy Economics Group (EEG) is within the Institute of Power Systems
and Energy Economics at Vienna University of Technology, Austria. EEG has managed and carried out many international as well as national research projects funded
by the European Commission, national governments, public and private clients in several 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
II
Review of approaches for employment impact assessment of renewable energy deployment
Table of Content
Summary ....................................................................................................................... 1 1 Background and objective of the report .............................................................. 4 2 Methodological approach of the review .............................................................. 6 3 2.1 Objective of the review and procedure .................................................. 6 2.2 Terminology .......................................................................................... 8 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 4 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 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
Review of approaches for employment impact assessment of renewable energy deployment
III
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 5 Discussion ........................................................................................... 75 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
Review of approaches for employment impact assessment of renewable energy deployment
IV
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
Review of approaches for employment impact assessment of renewable energy deployment
V
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
Review of approaches for employment impact assessment of renewable energy deployment
VI
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
number of jobs in the
RE industry
number of jobs in total
economy
gross studies
Figure 0-1:
impacts on employment
positive effects
positive and negative
effects
net studies
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 classify 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 supplying 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 adequately 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 promoting 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 employment 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, service and consumption (industries, households). To get the number of additional jobs
caused by RE deployment, they compare a situation without RE (baseline or counterfactual) to a situation under a strong RE deployment.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
1
In a second step, we characterize the studies inter alia by their scope, activities and impacts 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 positive and negative effects.
Table 0-1:
Overview of positive and negative effects caused by the economic impulses
Abbreviation
Positive effects
Negative effects
Investment
effect
Direct and indirect* effects by
investment in RE
Direct and indirect effects by avoided investment in conventional generation technology
O&M effect
Direct and indirect effects by
O&M in RE
Direct and indirect effects by avoided O&M in conventional generation
Fuel effect
Direct and indirect effects by
fuel demand
Direct and indirect* effects by avoided fuel demand
Price effect
(Induced effect through compensation 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 observe 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 approaches, 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 comprehensiveness. 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 IOmodelling 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 proFraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
2
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.
impact assessment studies
simple approach
complex approach
• impact: gross , RE industry
• effects: positive
employment factor
approach:
• data: capacity
data, employment factors
• complexity:
low (direct
effects)
Figure 0-2:
supply chain
analysis:
• data: capacity
and cost data
• complexity:
moderate
(mainly direct
effects)
gross IO-modelling:
• data: capacity
and cost data, IO
table
• complexity:
moderate (direct
& indirect effects)
• impacts: net, total economy
• effects: positive & negative
positive effects with
scenario:
• data: employment
factors (EF)
• complexity:
moderate (direct
& indirect effects,
scenario
comparison)
positive and
negative effects by
net IO modelling:
full economic
assessment
approach:
• data: IO-table
with consumption
vector
• complexity:
complex (direct,
indirect & induced
effects),
[scenarios]
• data:
• macro-economic
• energy sector
• trade relations
• complexity: very
complex (direct,
indirect & induced
effects, scenario
comparison)
Methodological approaches of impact assessment studies
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
3
1
Background and objective of the report
The use of renewable energy (RE) sources plays a significant role in increasing the security 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 promoting 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 development 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 economic impact of RE technologies is more or less fragmentary, concentrated on few experts and partly achieved on an ad hoc basis. The RETD intends to facilitate the assessment by elaborating a more structural approach to assess economic impacts and by contributing 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 considered 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 sustainable future, COM(2006) 848 final, Brussels, 10.1.2007.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
4
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 assessment studies. The relevant aspects of net and gross studies are outlined and discussed
within the corresponding Chapters, followed by a conclusion.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
5
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, methods or studies analysing the employment impacts of renewable energy (RE) deployment,
to show the respective research focus and methods and to suggest which impact assessment 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 research 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 industrialized 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 deployment but does not claim to be complete either in the number of studies or in key characteristics listed.
In a next step, we used two criteria - research focus and impact on employment - to classify 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 economic 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 objective 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 displaced employment in conventional energy industries and induced employment impacts
due to changes in energy prices or the competitiveness of industries.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
6
impact assessment studies
00
research focus
number of jobs in the
RE industry
number of jobs in total
economy
gross studies
Figure 2-1:
impacts on employment
positive effects
positive and negative
effects
net studies
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 regarding not only research questions or impacts but also the scope of the study and methodological 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 questions 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 economy 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 disaggregated 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
7
• 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 focus on technologies for electricity generation from renewable energy sources. Some
existing studies also include heat generation and fuels. Other studies have a more narrow 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 facilities. 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 expressions in this report:
• The renewable energy industry (RE industry) is considered to be a cross-sectional industry 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 account (e.g. demand effects, price effects). We also call this impact on the total economy.
• 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, studies, models or approaches assessing the employment impact of RE deployment, i.e. net
or gross studies.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
8
Table 2-1:
Year List of studies analysing economic impacts of renewable, nuclear or fossil energy deployment
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) E + H + T (all tech.) 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. E + H + T focus) (all tech.) (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‐ E + T depth analysis for (all tech.) selected regions) 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) E + H + T (all tech.) 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 gross industry generate in the US? Wei, Max; Patadia, Shana; Kammen, Dan Energy Policy 38 (2010) 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) net Germany (one‐country) 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‐
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
9
Year Title / author / type of publication Gross/
net Staiß, Frithjof; Kratzat, Marlene; Nitsch, Joachim; Lehr, Ulrike; Edler, Dietmar; Lutz, Christian Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Country/region RES‐ tech‐
nology (one‐country) (all tech.)
(+ reg. focus) Effects/description 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 Assessment of economic effects from the support of green electricity in Austria (IHS +2007 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 net Germany (one‐country) 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 direct + total employment and green • presentation of RES industry in Colorado technologies • compilation of findings resulting from analysis by ASES and MISI 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
three scenarios Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
direct and indirect employment (manufacturing, construction, 10
Year Title / author / type of publication Gross/
net Rutowitz, Jay; Atherton, Alison; Short, Rebecca; Teske, Sven
EREC & Greenpeace Country/region RES‐ tech‐
nology lected coutries Effects/description 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 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/ Gross Employment from RES in Germany – a first estimate and updates 08/09 O'Sullivan, Marlene; Edler, Dietmar; van Mark, Kerstin; Nieder, Thomas; Lehr, Ulrike; /10 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 Macroeconomic Effects of RES deployment – first results (2011) 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 Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
E, H, T direct and indirect employment, summary of different study results or statistics 11
Year Title / author / type of publication Gross/
net Country/region RES‐ tech‐
nology Effects/description • cost effects Peek, Markus; Gatzen, Christoph; Bartels, Michael; Kalies, Martin; Nill, Moritz; Hilleb‐
rand, Bernd; Bleuel, Michaela; Behringer, Jean Marc; Buttermann, Hans Georg EWI, IE, RWI 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 Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
12
Year Title / author / type of publication Gross/
net Country/region RES‐ tech‐
nology 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 Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
13
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 methodology 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 studies. 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?
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
14
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 nightwork? 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
15
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
development
Figure 3-1:
Planning
Site
preparation
Installation
of WPP
Operation of
WPP
Foundation
Construction of wind
turbine
Manuf. of
other
components
Manuf. of
tower
Manuf. of
nacelle
Manuf. of
rotor blades
Replacement of
WPP parts
Demolition
of WPP
Connection
to the net
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
16
• 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).
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
17
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
18
Table 3-1:
Overview of gross employment studies included in the comparison
Authors
Year of
publication
Employment factor approaches
2010
Wei et al.
Title
Regional
focus
RE Technology focus
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 cofiring
2004
Renewable Supply Chain Gap Analysis
UK
Mainly RE electricity
Supply chain analysis
DTI (ed.)
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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
19
Goal of the study/research question: The goal of the study determines the methodological 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
20
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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
21
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 employment 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 related 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 approaches.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
22
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.:
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
23
• 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).
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
24
Manufacturing,
Construction and
Installation
Operation & Maintenance
Biomass Supply
Figure 3-2:
New installed
capacity
[MW]
x
Job-years
per MW
=
Total Job-years
in MCI
Capacity
in use
[MW]
x
Jobs
per MW
=
Total Jobs in
O&M
Biomass input/
Energy output
[GWh]
x
Jobs
per GWh
=
Total Jobs
in BS
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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
25
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 sitespecific 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
26
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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
27
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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
28
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.
Methodological approach
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
29
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 indicators
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.
Direct and indirect impacts
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 technologies 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
30
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 impacts 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
31
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.
Methodological approach
Cost based IO modelling combines techno-economic data on RE technologies with inputoutput 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
32
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 inputoutput 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
33
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 indicators
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.
Direct and indirect impacts
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 multiregional 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 calculated with the same methodological approach (e.g. gross value added as a contribution to
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
34
GDP). This is the only approach able to fully take indirect and induced impacts into account. 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 employment factors used. Unfortunately, studies with thorough assessments of employment requirements 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 enhance the reliability of results, sound and well documented studies generating employment factors would be beneficial.
The supply chain method is a sophisticated approach to capture the complexity of activities 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
35
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 methodological 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 negatively 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 employment. In this report, we focus on impact assessment studies in the power sector. Before 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 certain 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 beyond, namely in all other industries as well as effects on households that in turn are affecting 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
36
Table 4-1:
Distinction between gross and net impact studies
Criteria
Impact on
Impulse
Gross
RE sector (output)
investments, O&M, exports and imports
Impact mechanism
positive effect:
• direct
• indirect
• induced type 1
as outlook for 20xx
Scenario
Indicators
Dynamic and other aspects
4.1.2
gross employment,
turnover, value added,
share of GDP
(productivity)
Net
Overall economy, welfare
investments, O&M, avoided investments, avoided O&M, trade
(export, import) and price
changes
positive and negative effects:
• direct,
• indirect,
• induced (type 2)
differences between scenarios
• RE deployment scenario
• Reference scenario
net employment change,
GDP
productivity, technological
change, multiplier effects; price
and structural changes
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 methodological 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
37
time dimension
regional level
research
question
economic dimension
economic impact indicators
input data (sources)
impact studies
quality of study
modelling approach (type)
RE technology
activities
impulses
scope of study
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 assessment of impact indicators in one single, a few selected or in all sectors (total economy). 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 turnover or gross output are fitting indicators.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
38
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 taking 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 studies 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 deployment on selected industries/economic sectors or the total economy, measured
by macroeconomic indicators such as changes in GDP, value added, net employment, ... at present and/or in the future in a region, country .... ?
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
39
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 scenarios 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 impulse 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 multiplier effects. The first is expressed by, e.g. different learning cost curves and productivity changes, and refers to RE technologies that are at a development stage where significant cost decreases and economies of scale effects are feasible, both of which affect productivity (see also Chapter 3). Even outside the RE sector, productivity changes
occur, structures adjust and the input-output relations between industries change. Furthermore, innovative advantages can be represented by changes in import/export relations 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 accelerator 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 impact 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 combinations and interdependences between three selected dimensions by a cube in Figure
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
40
4-3. The blue cube shows feasible combinations for gross studies, while a net study is
supposed to go beyond the blue cube.
transparency
activities
gov‘t support
marketing
dynamic aspects
R&D
export &
import
f uel supply &
generation
operation &
maintenance
installation,
reinvestment
manuf acturing
construction
gross
net
direct
indirect
1st type induced
2nd type induced
impacts
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 considered mechanisms and the calculations and data sources are transparent and comprehensible.
In general, quality aspects refer to the disaggregation level of data sources used to calculate 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 derived from surveys and interviews. The greater the number of technologies considered
and the more specific the research question, the higher the degree of disaggregated information 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
41
publicly available, others rely on individual data bases or surveys and some are endogenous data.
Regarding modelling types, there are several approaches (Rothengatter et al. 2008, Pfaffenberger 1995, Kratzat et al 2007) that use a variety of methods from simple analytical
approaches, input-output calculations, econometric models, optimization models to general equilibrium models as well as system dynamic models each aimed at specific research 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 criteria. 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 approaches. While the first approach allows integrating only a few impact mechanisms, relying on few aggregated factors and capturing selected impacts, the latter are more comprehensive regarding the dimensions selected and the data required. They apply macroeconomic 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
employment factors:
• data: labor input
per capacity,
production and
generation,
• effects: direct,
indirect & induced
impulses:
investment, O&M,
fuel.
Figure 4-4:
IO-model:
•
• data: IOcoefficients,
consumption
vector
• effects: direct,
indirect & induced
• impulses:
investment, O&M,
fuel and avoided
investment etc.,
RE income, price
macro-economic modelling approach
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.
Modelling approaches
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
42
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 impulses which have to be translated via an impact mechanism into economic impacts (effects). 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, production 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 impacts/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 employment - employment effects.
activities in
policies
impulses
positive & negative
impact mechanisms
impacts
RE
technologies
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 economic mechanisms can be grouped into clusters according their impact field demand for
RE/CT industry goods, consumption and production as well as innovation and competitiveness (see Figure 4-6):
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
43
• Impulses with a straight impact on demand for CE- and RE-related manufacturing, intermediate input, construction and services. They can be positive in the sense of additional 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 effect.
− 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 intermediate 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 decreases 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 technology 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 distinguish 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).
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
44
• 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 impact 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 activities, 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 unemployment is caused by a deficit in aggregate demand.
impulses of
activities
• investment impulse
• O&M impulse
• fuel demand
impulse
positive & negative impact mechanisms
direct&indirect
• investment (RE)
• O&M (RE)
• fuel demand (RE)
+
• avoided investment
• avoided O&M
• avoided fuel demand
• trade impulse
positive effect
negative effect
Figure 4-6:
+
-
induced effect
• RE income effect
(type 1)
• budget effect (type 2)
• cost effect (type 2)
• MO-effect
+
+
direct&indirect
• technology trade
• avoided technology
trade
• fuel im/export
• Dynamic and
economic
simulation
mechanisms:
RE demand
• productivity
change
• learning effects
(cost curves,
innovation
effect)
production
consumption
• multiplier
effect
employment
• RE income impulse
• price impulse
• additional
generation costs,
• CO2 price
• MO-effect
-
impacts on
• accelerator
effect
competitiveness
&innovation
+
-
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
45
• Investment and avoided investment impact mechanism (positive and negative investment effect):
Investments in generation technologies comprise manufacturing of equipment, construction and installations (MCI) of plants. While MCI of RE-power plants requiring investments 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 reduction of installations, e.g. in conventional power plants, since the demand for conventionally generated power decreases and hence investments and employment in this industry shrink. We call the mechanism that depicts the negative impact of RE investments on investments in conventional power, heat or fuel generation plants the
“avoided investment impact mechanism”. Both effects, investments and avoided investments, have a temporary employment impact, namely in the years of manufacturing, installation and construction, and therefore depend on the annual RE capacity installed or avoided fossil energy installations. The employment effects within the REindustry are direct effects; employment in upstream industries are described by indirect
effects.3 They are positive for RE investments and negative for avoided CE investments. The extent of the impact from investment on employment depends on the labour 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 employment 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 conventional 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
46
conventional fuels, thus affecting employment and trade in the RE fuel industry positively 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 “substitution 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 investments, 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 generation technologies and under the current prices - than fossil energy sources or conventional generation technologies. Subsequently, an increase in RE installations augments
electricity or heat generation costs. These higher costs are passed through to households 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 consumption or production (income effect) and a change in consumption pattern or input struc-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
47
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 substitution 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 imported 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 effects 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 induced employment effect of type 2. Overall, changes in the saving rate could compensate 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 unscheduled 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 energy 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
48
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 augmented 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 account 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 impulses 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 imports. 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
49
hence, low employment effects. Furthermore, the net exports of conventional generation 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 diminish 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. Therefore, 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 fuels and the shift in the fuel production chain to the national economy, fossil fuel exporting 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 employment indicators it is important to define terms of employment because referring to employment or jobs without indicating the duration could be misleading. Therefore we suggest 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, developing, managing, manufacturing, constructing, installing (MCI), operating and maintaining (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 existing facilities, manufacturers, project developers, etc in the respective phases of operation.
• Indirect employment effect: This includes the employment in upstream and downstream 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 equipment, 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 effects and are depicted in Figure 4-7, where the indirect effects stem from the intermediate input demand.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
50
Promotion of
RE use
trade of RE
equipment
increasing MCI,
O&M and fuel
supply of RE
technologies
falling MCI,
O&M and fuel
supply of CE
technologies
Figure 4-7:
RE
investment
demand
RE
intermediate
input demand
Change of
domestic
industry
output
labour
demand
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) employment and hence expenditure induced effects by households with employment in
RE industry and services. This leads to increased consumption which, in turn, results in more investments in all industries and services, affecting all incomes positively etc.7
− type 2, sets a negative impact in motion since it is initiated by higher prices for energy 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 services. This in turn affects production, income and again consumption, etc. The induced 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
51
impulse
primary effects
secondary effects
direct effects
installments,
O&M
services,
fuel demand,
...
induced effects (type 1)
income
of
households
from RE
industry
RE industry
1
upstream RE
industry
demand
for consumer
goods
production of
consumer
goods
employ
-ment
indirect effects
price impulse/
cost impulse
costs in
industry
2
income of
households
industry
production
demand
for invest.
private con- demand for
sumption consumer g.
employment
employment
induced effects (type 2)
Figure 4-8:
4.1.3.4
Primary and secondary effects
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 (multiplier, 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 input, increases annually leading to a lower labour input for the same output. Consequently, the change in productivity has a depressant effect on employment. Changes in
productivity might arise from efficiency increases due to technical changes and learning effects, especially in booming industries. In many cases these are linked to previous 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 service and generation, the latter might be reflected by market shares and exports. Initial
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
52
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 requires 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 effect on income and revenues beyond the demand pull or direct price effect. The multiplier effect multiplies effects along two impact pathways, i.e. the positive impacts of investment and O&M as well as the negative impacts of prices on income: increased investments 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 production and, therefore, employment in the consumption good and intermediate input
industries. In a second round, employment in the consumption good and upstream industries 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 impulses;
b) public households: via revenues or expenditures by augmented/reduced tax revenues 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 demand 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 compared, 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 represents 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 include 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
53
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 restrict our focus to RE policy/deployment impacts. In the following, some fundamental issues 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 assessments. 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 keeping 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 developments. This means, e.g. when analysing the national or domestic impact of a RE policy, 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 effects of global RE expansion at the national level are reflected and not the national efforts.
• 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 deployment.
• 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 assumptions on future economic and technological development and their effect on impulses
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
54
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 policies (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.
scenario
assumptions
Figure 4-9:
4.1.4.2
RE deployment
positive & negative
impact mechanisms
impulse
impacts
Scenario assumption as starting point of the functional chain
Drivers of RE deployment - scenario design
As mentioned above, to design a comprehensive and consistent scenario for RE deployment we have to investigate, which key factors and relations influence future RE deployment. In Figure 4-10 the principal aspects and key factors of future RE deployment are
depicted.
economic:
•GDP
•industrial
production
•transportation
•....
structural:
• housing area
•number of cars
•number of
houses
•....
technological:
•energy
efficiency
•insulation
• ...
demographic:
•population
•workier,
employees
•....
global
development
avoided
capital
expenditures
for fossil
energy
primary energy prices:
energy demand
•
•
•
•
primary
energy
consumption
oil, gas, coal
biomass
CO2
....
RE deployment
policy
measures:
• feed-in tariffs,
quota
• subsidies,
obligations
• .....
energy supply
socioeconomic:
• diffusion &
adoption
• costs/prices
• ....
policy targets:
• RE
deployment
• efficiency
• CO2 emission
• ....
Figure 4-10:
technological:
• energy
conversion
efficiency
• CO2 efficiency
• innovation, ....
potential:
• technological
• economic
• geographic
• realisable
• ....
capital
expenditures
for RE
(investment)
final energy
prices
(additional
generation
costs)
RE cost
curves /
learning
rates
trade impulse
global RE
deployment
global market
shares
Overview of factors affecting the RE deployment scenarios
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
55
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 deployment. 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 distinguished between short and long term perspective and between local and global resolution. 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 resulting 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 potential assuming that all existing barriers can be overcome and all driving forces are active. 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 recent, 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-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
56
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).
Energy generation
Theoretical potential
Technical potential
R&D
Long-term
potential
(Total) Realisable potential
up to 2030
Barriers
(non-economic)
Maximal
time-path for
penetration
(Realisable
Potential)
Additional
realisable
potential
(up to 2030)
Policy,
Society
Historical
deployment
Economic Potential
(without additional support)
2000
Figure 4-11:
2007 2010
2020
2030
Achieved
potential
(2007)
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. Besides, technological developments that further reduce CO2-emissions as well as other
innovations affect energy supply. They can be incorporated into the causal chain via dynamic 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
57
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. Estimates for learning rates of energy technologies can be found broadly in many publications, 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 measured as changes in GDP, industrial production, transportation, etc. Further, structural factors 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 determined by demographic development – population, working force, etc. Finally, technological 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 primary 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 certificates (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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
58
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 demand. In addition, to depict and integrate the impact of trade relations, a scenario on export 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 (assumed) 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 estimations 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 hypothetical 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 scenario 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 question, 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 proceeds. 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
59
Scenario on demand, growth and fossil energy prices
Why do we need scenarios on demand and fossil energy prices? Under limited fossil energy 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 alleviate the demand push, assumptions on efficiency changes as well as global RE deployment (targets) have to be taken into account when elaborating a price path for fossil energy 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 local (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 assessment studies are based on investment impulses that derive from domestic capacity
increases of RE generation plants. However, machinery and equipment can be domestically produced or imported. In case of imports, we have to reduce the impulse by deducting import expenditures from capital expenditures for newly installed generation capacities. 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 deployment. 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 multiplied with the tradable share of RE investments that is based on current trade relations. Then, the product is further multiplied with export shares of Germany for RE
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
60
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 export shares e.g. assuming in-, decreasing or a constant export volumes or shares reflect 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, future 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 production of RE-technologies for home installations from the total RE installations of a
country. This reduces investment impulses.
Capital expenditures
for RE-technologies
global
and
per country
Market shares
Cost components
Domestic production volume of
global investment needs per
economic sector (per country)
Domestically produced
equipment for domestic
demand per economic sector
RE Exports per economic
sector and per country
Figure 4-12:
4.2
Export scenario in dependence of RE investments
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
61
Table 4-2:
Overview of selected net impact studies for discussion
Title
Abbreviation
Authors
year
characteristics of
approach
Energy sector jobs to 2010: a global analysis – final report, Greenpeace
Greenpeace
Rutovitz, Atherton
2009
Putting renewable energy efficiency to work: How many jobs can the
clean energy industry generate in
the US?
Wei
Wei, Patadia,
Kammen
2010
Ermittlung der Arbeitsplätze und
Beschäftigungswirkungen im Bereich Erneuerbarer Energien
(assessment of jobs and
employment effects in RE)
Bewertung der volkswirtschaftlichen Auswirkungen der Unterstützung von Ökostrom in Österreich
(Assessment of economic impacts
of the support of green electricity
in Austria)
Solar Photovoltaic employment in
Europe – The role of public policy
for tomorrows solar jobs
BEI
Pfaffenberger,
Nguyen, Gabriel
2003
Positive effects, direct
effects; comparison of
2010 and 2030; employment factors from
diverse studies;
Positive effects; direct
& indirect effects for
RE; scenario comparison; employment
factors from diverse
studies;
Positive & negative
effects; direct, indirect
& induced effects; IOmodel
IHS
Bodenhöfer, Bliem,
Weyerstraß
2007
Positiv&negative
effects; direct, indirect
and induced effects,
IO-table
EPIA
2009
Positive & negative
effects; direct, indirect
& induced effects; IOtable and GE-model
The expansion of renewable energies and employment effects in
Germany
EEFA
University Flensburg, WIPRenewable Energies Munich, National Technical
University of Athens
Hillebrand, Buttermann, Behringer,
Bleuel
2005
Gesamtwirtschaftliche und
sekorale Auswirkungen des Ausbaus erneuerbarer Energien
(economic and sectoral impacts of
RE deployment)
DIW
Kemfert,
Blazejczak, Braun,
Edler, Schill
2010
Kurz- und langfristige Auswirkungen des Ausbaus erneuerbarer
Energien auf den deutschen Arbeitsmarkt (short- and long-term
impacts of RE deployment on the
German job market)
EmployRES: The impact of renewable energy policy on economic
growth and employment in the EU
BMU
2011
Lehr, Lutz, Edler,
O’Sullivan,
Nienhaus, simon,
Nitsch, Breitschopf,
Bickel, Ottmüller
2011
EU 2009
Ragwitz, Schade,
Breitschopf, Walz,
Helfrich, Rathmann,
Resch, Panzer,
Faber, Haas, Nathani, Holzhey, Konstantinaviciute, Zagamé, Fougeyrollas
2009
Positive &negative
effects; direct, indirect
& induced effects;
scenario comparison;
structural model
Positive & negative
effects; direct, indirect
& induced effects;
scenario comparison;
macro-economic
model
Positive & negative
effects; direct, indirect
& induced effects;
scenario comparison;
macro-economic
model
Positive & negative
effects; direct, indirect
& induced effects;
scenario comparison;
macro-economic
model
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
62
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, scenarios 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 effects 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 economic sectors. The calculation of employment impacts is very often based on IO tables and captures positive and negative effects.
c)
Assessment of employment impacts in all economic sectors. It is based on a complex model featuring an energy sector module, a macroeconomic module and an
export module capturing negative and positive effects as well as differences between scenario outcomes.
A description of the main net studies is given in the following. They are screened according to the scope of their study, including integrated impact mechanisms (complexity), impulses, 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 developments (scenarios) are compared. The Table below illustrates all the impact mechanisms, 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 comprehensively 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, Hillenbrand et al. 2006, Frondel et al. 2010, Pfaffenberger et al. 2003).
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
63
Table 4-3:
Overview scheme for net impact studies
Title of study:
Research question:
impact mechanisms
+
investment
‐
+
O&M
‐
+
fuel demand
‐
+
techn. trade
‐
+
fuel trade
‐
productivity change
‐
direct AGC ‐
indirect AGC
‐
merit order, CO2 price, ... +
multiplier effect
+/‐
accelerator effect
+/‐
feasible for a net study
pointless for a net study
direct indirect induced activity fields:
installation
reinvestments
O&M
fuel generation
RE trade fuel trade
time horizon:
past present
future
regional extent:
local
national
regional
global
AGC: additional generation costs
does not exist
scenario
difference between scenarios
national scenario
global scenario
export scenario
+ positive, ‐ negative effect
IS‐eff: income & substitution effec
B‐eff: budget effect
C‐eff: cost effect
The same Table is used in the following subchapters to present the main elements or features for the net impact studies reviewed. However, blank fields in any Tables do not necessarily 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 different 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 similar. In Rutowitz et al. 2009, annually installed, exported or cumulative capacities are multiplied 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 average indirect multiplier for the indirect effect taken from three other studies. The generation 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
64
Applying two different deployment scenarios (reference and advanced scenario) and multiplying the employment effects by the projected capacities and generation gives the total
in/direct employment under a reference and advanced deployment scenario for all technologies. 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 direct (indirect) “net” employment effect, since it compares situations with different REsettings. The reference and energy(R)evolution scenarios reflect the deployment of different 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 deployment 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.
scenario (2010)
or scenario ADS installations
exports
capacity
generation
scenario (2030)
or scenario RS
positive direct
(regional & local
factors), indirect
and dynamic
effects
employment
effect
installations
exports
capacity
generation
employment
effect
„net“ impact
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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
65
Table 4-4:
Greenpeace study, 2009
Title of study:
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
AGC: additional generation costs
pointless for a net study
Table 4-5:
does not exist
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
Study of Wei et al. 2009
Title of study:
pointless for a net study
Greenpeace 2009: Energy jobs to 2030: a global analysis; 2009; J. Rutowitz, Atherton; editor Greenpeace International
What is the potential job creation associated with the two scenarios energy (r)evolution and reference ?
direct indirect induced activity fields:
scenario
+
installation
difference between years
‐
reinvestments
+
O&M
‐
fuel generation
+
RE trade global scenario:
‐
fuel trade
Reference
+
Energy(R)evolution
‐
time horizon:
+
past ‐
present
2005
‐
future
2030
‐
regional extent:
‐
local
+
national
+/‐
regional
+/‐
global
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.
direct
indirect
induced activity fields:
scenario
+
installation
difference between ‐
reinvestments
scenarios
+
O&M
‐
fuel generation
+
RE trade ‐
fuel trade
+
global scenario
‐
time horizon:
+
present
2010
‐
future
2030
‐
export scenario
‐
regional extent:
‐
local
+
national
+/‐
regional
+/‐
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
66
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 technologies. 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 different RE-deployment situations, but from the addition of single effects. The sum of negative 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 multipliers 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 investments etc. Examples of such studies are IHS 2007 or BEI 2003, EPIA 2009. In these studies, (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 difference 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
generation in MWh
positive and
negative
employment
factors (in/ direct
effects)
employment
multipliers
(induced effect
of type 1)
in/direct and induced positive employment
price effect
(negative
induced effect
of type 2)
induced negative employment
net employment effect
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-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
67
eration facility. There is no comparison between a reference and an ambitious RE deployment 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 employment 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 biomass 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
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
pointless for a net study
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
direct
indirect
induced activity fields:
scenario
+
installation
difference between ‐
reinvestments
scenarios:
+
O&M
‐
fuel generation
national scenario: const. +
RE trade prices
‐
fuel trade
+
‐
time horizon:
+
past present
‐ purchasing power of export countries
‐
future
regional extent:
‐
B‐eff
‐
local
+
national
+/‐
regional
+/‐
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
The IHS 2007 study relies on a rather simple procedure. Based on investments and revenues, 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, profits, salaries) and adjusted for savings and imported goods. Multiplying the consumer
budget by a secondary effect multiplier for value added and employment shows the induced effects. The multiplier is derived from the IO-table. However, the reported employment effect refers to EUR invested. It does not rely on the difference in employment effects between two different deployment scenarios. The main focus of the study is on the
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
68
economic and employment contribution of different RE deployments, i.e. how much employment 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 additional generation costs (budget effect) while power generation with biomass and CHP reveal 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 several multiplication rounds.
Table 4-7:
IHS 2007 study
Title of study:
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
pointless for a net study
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 Kärnten
What are the economic effects of green electricity support/promotion? Assessment of value added and employment per investment and generation.
direct
indirect
induced activity fields:
scenario
+
installation
difference between scenarios:
‐
reinvestments
+
O&M
national scenario
‐
fuel generation
+
RE trade ‐
fuel trade
+
‐
time horizon:
global scenario
+
present
2003
‐
future
2010
‐
regional extent:
‐
B‐eff
‐
local
export scenario
+
national
+/‐
regional
+/‐
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
B‐eff: budget effect
IS‐eff: income & substitution effect
C‐eff: cost effect
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 equilibrium model has been applied. The outcomes show the impact of the diverse effects on
employment. Not surprisingly, the avoided investment and budget effect considerably reduce 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 international relations and induced effects with a focus on consumption. The study investigates
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
69
exclusively impacts of PV deployment. The outcome shows a small positive employment
effect of PV.
Table 4-8:
EPIA 2009 study
Title of study:
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
pointless for a net study
4.2.3
EPIA 2009: Solar Photovoltaic Employment in Europe: PV employment, EPIA, WIP, University of Flensburg, NT University of Athens, 2009
What are the net employment effects of PV ‐ based on the sum of negative and positive effects.
direct
indirect
induced activity fields:
scenario
difference between +
installation
scenarios:
‐
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
‐
export scenario
regional extent:
const. export share of 15%
‐
B‐eff
‐
local
+
national
+/‐
regional
EU
+/‐
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
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 assessment 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 comprising 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 impacts 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 economy 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 translated into economic impacts in the macro module. The modules are fed with different REdeployment data by two scenarios. After several feedback loops or simulation rounds, we
receive the calculated employment effects of each scenario which already include nega-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
70
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 economic, demographic development as well as in exports, prices and finally in RE deployment. Hence the outcome also depends largely on the development – the drivers – of the
scenarios.
scenario RS
scenario ADS
energy sector
trade module
macro module
impulses
(in/direct , induced effects, dynamic)
employment and
economic effect
energy sector
trade module
macro module
employment and
economic effect
net impact
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 additional 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 discussed 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 modules in Figure 4-16 and how these are classified should not be considered a strict definition, but an open one, meaning that elements of the macroeconomic module such as en-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
71
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.
scenario:
•
•
•
macroeconomic data + demographic data Æ PEC
domestic and global RE development (objectives and policies) Æ RE deployment
export development (scenario)
macroeconomic
module:
energy sector
module:
• technologies&investments, O&M, fuel
• positive & negative
impact mechanisms
• prices: merit-order,
CO2-certificates,
additional in/direct
generation costs,
• interaction
mechanisms,
intermediate goods,
IO-coefficients
impulses
• learning effects
• demand & supply
• sectors (power, heat,
housing,
transportation, ...)
• economic
subjects/actors
trade
module:
• general trade pattern
(intra-EU, world,
regions, ...)
• RE deployment world
impulses
• export: Share of
tradable share of RE
installations, national
share of RE world trade
• imports (fossil energy
and RE technology)
output
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 comprehensive 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 consumption 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 different 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
72
and restricted availability of resources, other production activities have to shrink. In addition 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
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
EEFA 2005: The expansion of Renewable Energies and employment effects in Germany, B. Hillebrand et al., Energy Policy 34 (2006), 3484‐3494
Quantification of positive and negative effects of RE deployment and calculation of a net effect.
direct
indirect
induced activity fields:
scenario
difference between +
installation
scenarios:
‐
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
‐
regional extent:
‐
B‐eff, C‐eff
‐
local
export scenario
+
national
+/‐
regional
+/‐
global
feasible for a net study
AGC: additional generation costs
pointless for a net study
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
Table 4-10: DIW et al. study 2010/11
Title of study:
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC indirect AGC
merit order, CO2 price, ...
multiplier effect
accelerator effect
feasible for a net study
pointless for a net study
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. Schill
medium and long term impact of RE deployment on economic growth and employment
scenario
direct
indirect
induced activity fields:
+
installation
difference between ‐
reinvestments
scenarios:
+
O&M
‐
fuel generation
national scenario
+
RE trade null RE deployment
‐
fuel trade
advanced RE deployment
+
‐
time horizon:
export scenario
+ avoided fossil fuel import
past ‐
present
2000
‐
future
2030
‐
regional extent:
B‐eff., C‐eff.
‐
local
+
national
+/‐
+/‐
regional
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
B‐eff: budget effect
IS‐eff: income & substitution effect
C‐eff: cost effect
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
73
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 incorporation of endogenous technology change and competitiveness into the model. The updated study (2010) elaborated regional and trade effects in more detail and relies on current 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
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC
indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
feasible for a net study
pointless for a net study
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.
What are the gross and net employment impacts of RE deployment in Germany ‐ past and future effects?
direct
indirect
induced activity fields:
scenario
+
installation
difference between ‐ (in BMU 2006, 2011: substitution effect)
scenarios:
reinvestments
+
O&M
‐
fuel generation
national scenario
+
RE trade Leitszenario 2009 (national)
‐
fuel trade
RE‐null scenario (1995)
+
‐
time horizon:
links in trade +
present
2009 global scenario
module
‐
future: 2020, 2030 Energy(R)evolution
‐
‐
regional extent:
B‐eff, C‐eff
‐
local
export scenario
CO2 price
+
national
4 export scenarios
+/‐
regional
+/‐
global
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
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 activities, 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-
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
74
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 policies.
Table 4-12:
EmployRES, EU 2009
Title of study:
Research question:
impact mechanisms
investment
O&M
fuel demand
techn. trade
fuel trade
productivity change
direct AGC indirect AGC
merit order, CO2 price
multiplier effect
accelerator effect
EU 2009: Impact of Renewable Energy policy on economic growth and employment in the EU (EmployRES), 2009; R. Ragwitz et al., contractor: DG TREN
What is crucial for the analysis of employment impacts of RE deployment? direct
indirect
induced activity fields:
scenario
+
installation
difference between ‐
reinvestments
scenarios:
+
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
‐
‐
export scenario:
B‐eff, IS‐eff, C‐eff regional extent:
‐
local
1. pessimistic
CO2 price
+
national
2. moderate
+/‐
regional
EU
3. optimistic
+/‐
global
feasible for a net study
pointless for a net study
AGC: additional generation costs
does not exist
+ positive, ‐ negative effect
IS‐eff: income & substitution effect
B‐eff: budget effect
C‐eff: cost effect
Astra can be seen as a recursive simulation approach, and follows system analytic concepts, 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 variables 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 effects 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 approaches. The simple assessment based on positive effects and a scenario comparison is
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
75
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 employment 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 onetime 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 different 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, reflects 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 mechanism 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).
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
76
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 requirements 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 elaboration of guidelines.
impact assessment studies
simple approach
complex approach
• impact: gross , RE industry
• effects: positive
employment factor
approach:
• data: capacity
data, employment factors
• complexity:
low (direct
effects)
Figure 5-1:
5.1
supply chain
analysis:
• data: capacity
and cost data
• complexity:
moderate
(mainly direct
effects)
gross IO-modelling:
• data: capacity
and cost data, IO
table
• complexity:
moderate (direct
& indirect effects)
• impacts: net, total economy
• effects: positive & negative
positive effects with
scenario:
• data: employment
factors (EF)
• complexity:
moderate (direct
& indirect effects,
scenario
comparison)
positive and
negative effects by
net IO modelling:
full economic
assessment
approach:
• data: IO-table
with consumption
vector
• complexity:
complex (direct,
indirect & induced
effects),
[scenarios]
• data:
• macro-economic
• energy sector
• trade relations
• complexity: very
complex (direct,
indirect & induced
effects, scenario
comparison)
Methodological approaches of impact assessment studies
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 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 adequately represented
in official statistics, thus also enabling monitoring of this industry in the course of RE promotion. 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.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
77
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 enterprise data. The quality of the results largely depends on the quality of the employment
factors used. Unfortunately, studies with thorough assessments of employment requirements 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 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 activities 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 related to RE deployment and the induced employment. It allows to cover indirect employment outside the RE industry and yet is flexible enough to integrate technology or company specific data.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
78
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 methodological 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 deployment. It is in mainly based on employment factors (EF) that are derived either from empirical 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 investments, trade and generation, employment factors and changes over time are required. 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-todate, 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 disaggregated 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 official statistics. Overall, the approach is considered as suitable to reflect and compare effects 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
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
79
(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 approach - complex macro-economic modelling -, which, however is with respect to data and
modelling requirements not applicable in many countries. Under feasibility and practicability aspects, therefore, we suggest to elaborate guidelines for the application of a net IOmodel 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 impacts 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 investigates 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 incorporated and system boundaries are set. The same applies to gross impacts.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
80
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 methodologies: 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 economic impact of RE deployment in the overall economy.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
81
References
Agama, 2003. Employment Potential of Renewable Energy in South Africa. Study prepared for The Sustainable Energy and Climate Change Partnership, Johannesburg.
Constantia.
Black & Veatch 2004. Economic Impact of Renewable Energy in Pennsylvania. Report to
Community Foundation for the Alleghenies and Heinz Endowments Overland Park,
Kansas.
Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (BMU) 2010. Renewably employed: Short and long-term impacts of the expansion of renewable energy on
the German labour market. Berlin.
Bodenhöfer et al. 2007, (IHS 2007). Bewertung der volkswirtschaftlichen Auswirkungen
der Unterstützung von Ökostrom in Österreich (Assessment of economic impacts of
the support of green electricity in Austria), H.J. Bodenhöfer, M. Bliem, K. Weyerstraß, IHS Kärnten, September 2007.
APPA 2009. Study of the Macroeconomic Impact of Renewable Energies in Spain, ed.
Spanish Renewable Energy association (APPA), elaborated by Deloitte, 2009.
Delphi 2007. Situational Analysis of the Canadian Renewable Energy Sector with a Focus
on Human Resource Issues, Final Report prepared by The Delphi Group for the
Human Resources and Social Development Canada, Jan. 2007.
DTI 2004. Renewable Supply Chain Gap Analysis. Department of Trade and Industry
(ed.), London.
EPIA 2009. Solar Photovoltaic employment in Europe: PV employment, EPIA, WIP, Uni
Flensburg, NTUA, 2009.
EPRI 2001. California Renewable Technology Market and Benefits Assessment. Electric
Power Research Institute, Palo Alto.
Eurostat et al. 2001. Tourism Satellite Account: Recommended Methodological Framework. Eurostat, OECD, WTO, UN, Luxembourg, Madrid, New York, Paris.
Frondel et al. 2010. Economic impacts from the promotion of renewable energy technologies: The German experience, M. Frondel, N. Ritter, Ch.M.Schnidt, C. Vance, in Energy Policy 38 (2010) 4048-4056.
Gittell, Magnusson 2007. Economic Impact of a New Hampshire Renewable Portfolio
Standard. R. Gittell, M. Magnusson, University of New Hampshire.
Goldberg et al. 2004. Job and Economic Development Impact (JEDI) Model: A UserFriendly Tool to Calculate Economic Impacts from Wind Projects. National
Renewable Energy Laboratory, Golden, Colorado.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
82
Haas et al, 2006. Technologien zur Nutzung Erneuerbarer Energieträger- wirtschaftliche
Bedeutung für Österreich, EEG, TU Wien, R. Haas, T. Biermyr, L. Kranzl, January
2006.
Heavner/Churchill 2002. Renewables Work: Job Growth from Renewable Energy Development in California. B. Heavner, S. Churchill, CALPIRG Charitable Trust, Sacramento.
Hillebrand et al. 2006 (EEFA 2005). The expansion of Renewable Energies and employment effects in Germany, B. Hillebrand et al., Energy Policy 34 (2006) 3484-3494.
Huber et al. 2004. Green-X – Deriving optimal promotion strategies for increasing the
share of RES-E in a dynamic European electricity market. Final report. Vienna University of Technology, Energy Economics Group (EEG).
ISI et al. 2010. Einzel- und gesamtwirtschaftliche Analyse von Kosten- und Nutzenwirkungen des Ausbaus Erneuerbarer Energien im deutschen Strom- und Wärmemarkt,
Fh-ISI, GWS, DIW, IZES; B. Breitschopf, M. Klobasa, F. Sensfuß, J. Steinbach, M.
Ragwitz, U. Lehr, J. Horst, U. Hauser, J. Diekmann, F. Braun, M. Horn, May 2010.
Kammen et al. 2004 update 2006(RAEL 2004). Putting Renewables at work: How many
jobs can the clean energy industry generate? 2004, updated 2006, M. Kammen et
al.
Kratzat, M., Lehr, U. 2007. International Workshop on “Renewable Energies: employment
effects”, models, discussions and results, BMU 2007.
Lantz 2009. Economic Development Benefits from Wind Power in Nebraska: A Report for
the Nebraska Energy Office. National Renewable Energy Laboratory, Golden, Colorado.
Lehr et al. 2008. Renewable energy and employment in Germany, U. Lehr, J. Nitsch, M.
Kratzat, Ch. Lutz, D. Edler, Energy Policy 36 (2008) 108-117.
Lehr et al. 2011. Kurz- und langfristige Auswirkungen des Ausbaus der erneuerbaren Energien auf den deutschen Arbeitsmarkt (short- and longterm impacts of RE deployment on the German job market); U. Lehr, C. Lutz, D. Edler, M. O’Sullivan, K. Nienhaus, S. Simon, J. Nitsch, B. Breitschopf, P. Bickel, M. Ottmüller; GWS, DIW, FhISI, ZSW, February 2011.
Loomis/Hinman 2009. Wind Energy Development in Illinois. D. G. Loomis, J. L. Hinman,
Center for Renewable Energy, Illinois State University.
Moreno/Lopez 2008. The effect of renewable energy on employment. The case of Asturias (Spain). B. Moreno, A. J. Lopez. In: Renewable and Sustainable Energy Reviews, 12 (2008) 732–751.
OECD 1999. The Environmental Goods and Services Industry: Manual for Data Collection
and Analysis. Paris.
Openshaw 2010. Biomass energy: Employment generation and its contribution to poverty
alleviation. Biomass and Bioenergy 34 (2010) 365 – 378.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
83
Pembina (n.y.). Canadian Renewable Electricity Development: Employment Impacts. Prepared by Pembina Institute for the Clean Air Renewable Energy Coalition.
Pfaffenberger et al. 2003 (BEI 2003). Ermittlung der Arbeitsplätze und Beschäftigungswirkungen im Bereich EE (Assessment of jobs and employment by using RE), W., Pfaffenberger, K. Nguyen, J. Gabriel, Bremer Energie Institut, 2003.
Pfaffenberger, W., 1995. Employment effects of energy systems, expertise, 1st edition,
Frankfurt am Main, Verl.- und Wirtschaftsgesellschaft der Elektrizitätswerke VWEW,
Energiewirtschaflticheh Studien 6, 1995.
Ragwitz et al. 2009 (EU 2009). Impact of Renewable Energy policy on economic growth
and employment in the EU (EmployRES), 2009; R. Ragwitz et al., contractor: DG
TREN.
Ratliff et al. 2010. An Analysis of State-Level Economic Impacts from the Development of
Wind Power Plants in San Juan County, Utah, D. Ratliff, C. L. Hartman, E. R. Stafford, Prepared for the US Department of Energy.
Rothengatter W., Schaffer A., 2008. Macro compact, Basics of macro economics, 2nd edition, Physica Verlag Heidelberg, Heidelberg 2008.
Rutowitz/Atherton 2009. Energy sector jobs to 2030: a global analysis, 2009, J. Rutowitz,
A. Atherton. Prepared for Greenpeace International by the Institute for Sustainable
Futures, University of Technology, Sydney.
Singh /Fehrs 2001. The work that goes into renewable energy, V.Singh, J. Fehrs, Renewable Energy Policy Project, Research report No. 13, Washington D.C.
Staiß et al. 2006 (BMU 2006). Renewable Energies: Employment effects, 2006, Staiß et
al., editor: BMU 2006; (forthcoming: Renewable Energies: Short and longterm effects in the German labour market, 2010; U. Lehr et al., editor: BMU 2010).
UBA 2003. Systematische Analyse der Eigenschafte von Energiemodellen im Hinblick auf
ihre Eignung für möglichst praktische Politikberatung zur Fortentwicklung der Klimaschutzstrategie, M. Koch, J. Harnisch. K. Blok, Umweltbundesamt, February 2003.
Wei et al. 2010. Putting renewables and energy efficiency to work: How many jobs can the
clean energy industry generate in the US? M.Wei, S. Patadia, D.M. Kammen, in Energy Policy 38 (2010) 919-913.
Weiss et al, 2003. Wirtschaftsfaktor Sonnenenergie, AEE INTEC, W. Weiss, Ch. Isaksson, by order of Ministry of Transportation, Innovation and Technology, Austria, Dec.
2003.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
84
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 accompanies this report. The Table is presented below.
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
85
Type of study
Authors
Employment factor approaches
Singh, V. et al. (REPP) 2001
Title
Year of publication
The Work that goes into Renewable
Energy.
2001
Institution
Region
Base year
Goal of study
Impact indicators
Peterson/Poore (EPRI), 2001
Pembina, 2004
Renewable Energy Policy Project
US
2000
California Renewable Technology:
Market and Benefits Assessment
2001
Electric Power Research Institute
(EPRI), Global Energy Concepts, LLC
California
2000 (- 2010)
Canadian Renewable Electricity
Development: Employment Impacts
2004(?)
Pembina Institute for Appropriate
Development
Canada
2004 - 2020
Analysis of jobs and skills needed for
installing and operating PV roof
systems, wind power plants and
biomass co-firing
To estimate employment created from
Employment Benefits from Deployment deployment of low-impact renewable
electricity generation
of RE technologies
Turnover
Gross output
Gross value added
Jobs
job-years / number of permanent jobs
Number of employees
Fulltime equivalents
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and CHP
Large hydro power
Small hydro power
Wind onshore
Wind offshore
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-incineration
Other biomass
Geothermal
Auxiliary technologies
Storage technologies
Grid technologies
Activities (which and how)
Operation of RES plants
working hours transformed into FTE
person years, assuming 1960 working
hours per FTE
FTE jobs
yes
yes
100 kW plant
37.5 MW onshore wind farm near highvoltage transmission line, excluding
manufacturing of transformers,
hydraulics and safety equipment
50 MW onshore wind farm
fixed roof-based 2 kW PV-system (no
tracking)
10 kW PV system
100 MW plant
yes
yes
yes
yes
yes
no
yes
2 MW landfill gas / biogas plant
co-firing of wood wastes and energy
crops in coal power plants
biomass unspecified
yes
no
no
no
no
yes
yes
Manufacturing, construction yes in the case of PV and wind, partly
and installation of new RES (biomass feeders) in the case of
biomass
plants
yes
yes
Replacement in existing RES
n.a.
plants
Fuel generation and supply yes
Demolition
no
no
only transport
no
no
yes
no
Export of RES products
no
no
Manufacturing of RE
production facilities
10 years of servicing
50 MW biomass plant
50 MW geothermal power plant
no
no
Basic research &
development
Government activities
no
no
no
no
no
Marketing of green
electricity
no
no
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
86
Type of study
Authors
Impacts included
Direct
Indirect
Intermediate input
impact
Investment impact
Induced
Employment factor approaches
Singh, V. et al. (REPP) 2001
Peterson/Poore (EPRI), 2001
Pembina, 2004
yes
no
yes
??
yes
probably not, but not specified
no
no
no
Leakage (imports from
outside the region)
Impact definitions
yes, but assumptions not clear
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.
n.a.
n.a.
n.a.
Definition induced
Methodological approach
Employment factors
Supply chain analysis
yes
yes
yes; labour costs calculated as an
estimated fraction of capital or O&M
costs and then converted into FT
employees
Cost-based IO modelling
Supply-side approach
Employment 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
Cost degression (changes in
specific costs)
n.a.
no
no
Changing cost structures
due to technological
learning
n.a.
no
n.a.
n.a.
no
no
n.a.
no
not reproduceable
n.a.
n.a.
n.a.
• 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
• 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
Data sources for RE related
employment
Requirements for dynamic analysis
Changes in labour
productivity
Regional shifts of
production sites
Structural change in the
economy
Strengths
Limitations
Remarks
• Discusses future trends in labour
intensity
• Discusses future trends in labour
intensity
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
87
Type of study
Authors
Rutovitz/Atherton, 2009
Wei et al., 2010
Supply chain analysis
DTI (Ed.) 2004
Title
Year of publication
Energy Sector Jobs to 2030: A Global
Analysis
2009
Putting renewables and energy
efficiency to work: How many jobs can
the clean energy industry generate in
the US?
2010
Renewable Supply Chain Gap Analysis
2004
Institution
Region
Base year
Institute for Sustainable Futures
10 world regions and G8 countries
2009 - 2030
University of California, Berkeley
USA
2009 - 2030
Goal of study
Impact indicators
Estimation of job development in the
clean energy industry (RE, EE and
Analysis of the potential job creation in CCS) until 2030 under various
scenarios, compared to loss of jobs in
the global energy sector associated
the coal and natural gas sector
with two energy scenarios
Turnover
Gross output
Gross value added
Mott MacDonald, Bourton Group
UK
2003
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
Jobs
Number of employees
Fulltime equivalents
RES sector
electricity
yes
FTE person years
FTE jobs
yes
yes
partly
yes
heat
fuels
RES technologies (which and how)
Electricity and CHP
Large hydro power
Small hydro power
yes
no
< 20 MW
Wind onshore
Wind offshore
yes
yes
yes
yes
yes
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-incineration
yes
yes
"ocean"
yes
yes
yes
no
in the future
landfill gas
Other biomass
Geothermal
Auxiliary technologies
Storage technologies
Grid technologies
Activities (which and how)
Operation of RES plants
landfill gas
energy from waste
biomass unspecified
yes
biomass unspecified
yes
no
no
no
no
yes
yes
yes
yes
yes
implicitly?
yes
no
probably not
yes
no
Manufacturing, construction
and installation of new RES
yes
plants
no, if new capacity is calculated as
Replacement in existing RES difference of installed capacity
between two time periods
plants
Fuel generation and supply yes
no
Demolition
biomass waste and energy crops
no
yes
yes
Export of RES products
yes
no
yes
Manufacturing of RE
production facilities
no
no
no
Basic research &
development
Government activities
no
no
no
no
no
no
Marketing of green
electricity
no
no
no
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
88
Type of study
Authors
Impacts included
Direct
Indirect
Intermediate input
impact
Rutovitz/Atherton, 2009
Wei et al., 2010
yes
no
yes
Supply chain analysis
DTI (Ed.) 2004
yes
Only within RE supply chain
with simple multiplier, calculated as
average from three studies
no
probably not
no
estimated by applying a factor of 0.25
yes
no, all jobs assumed to be in US
import content estimated at each level
of supply chain
Definition direct
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
Definition indirect
supplier effect of upstream/
jobs in secondary industries supporting downstream suppliers to direct
activities
the primary industry sector
Investment impact
Induced
Leakage (imports from
outside the region)
Impact definitions
Definition induced
Methodological approach
Employment factors
Supply chain analysis
expenditure induced effects in the
general economy due to economic
activity and spending of direct and
indirect employees
yes
n.a.
FTE jobs per MW peak
Cost-based IO modelling
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
Supply-side approach
Enterprise survey
Data sources for RE related
employment
Requirements for dynamic analysis
Employment factors: Literature review;
Labour productivity data from ILO
statistics
Employment factors: literature review
Costs and cost structures: Real project
data, feasibility studies
Typical salaries: Available statistics
Cost degression (changes in
yes
specific costs)
no
Changing cost structures
due to technological
learning
n.a.
no
yes
no
yes
no
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 indexnumbers
• Detailed technology-specific analysis
• simple approach, easy to understand of supply chains and cost structures
Changes in labour
productivity
Regional shifts of
production sites
Structural change in the
economy
Strengths
Limitations
Remarks
• simplifying assumptions due to global • No consideration of dynamic aspects
analysis
for future projections
• 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
yes
yes
• Indirect impacts outside the RE
sector not covered
• Boundary between direct and indirect
not clear, thus comparison to results
from other studies difficult
• High costs for enterprise survey
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
89
Type of study
Authors
Cost-based IO modelling
Ragwitz et al., 2009
Lehr et al., 2011
Title
Year of publication
EmployRES: Employment and
economic growth impacts of
sustainable energies in the European
Union
2009
Kurz- und langfristige Auswirkungen
des Ausbaus der erneuerbaren
Energien auf den deutschen
Arbeitsmarkt;
english summary: BMU (ed., 2010):
Renewably employed: Short and longterm impacts of the expansion of
renewable energy on the German
labour market
2011
Institution
Region
Base year
Fraunhofer ISI et al.
EU 27
1990 - 2005, 2005 - 2030
GWS/DIW/DLR/ZSW/ISI
Germany
2007-2030
Economic Development Benefits from
Wind Power in Nebraska: A Report for
the Nebraska Energy Office
2009
National Renewable Energy
Laboratory
US state of Nebraska
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
Goal of study
Impact indicators
Turnover
Gross output
Gross value added
Lantz 2009
yes
yes
yes
Jobs
yes
Number of employees
Fulltime equivalents
RES sector
electricity
yes
yes
yes
yes
heat
fuels
RES technologies (which and how)
Electricity and CHP
Large hydro power
Small hydro power
yes
yes
yes
yes
yes
yes
yes
yes
Wind onshore
Wind offshore
yes
yes
yes
yes
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-incineration
yes
yes
yes
yes
yes
yes
yes
yes
Other biomass
Geothermal
Auxiliary technologies
Storage technologies
Grid technologies
Activities (which and how)
Operation of RES plants
yes
yes
biomass unspecified
yes
no
no
no
no
no
no
wind power
yes
yes
yes
yes
yes
Manufacturing, construction
and installation of new RES
yes
plants
yes
yes
Replacement in existing RES
estimates
plants
Fuel generation and supply yes
no
Demolition
yes calculated with multiregional IO
model, for wind and PV based on
world market shares
Export of RES products
yes
yes
no
yes. based on enterprise survey and
scenarios of world trade development
and shares of German enterprises
no
n.a.
no
no
Manufacturing of RE
production facilities
yes, estimated via depreciation of RE
industry
yes
no
Basic research &
development
Government activities
no
no
yes
yes
no
no
Marketing of green
electricity
no
no
no
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
90
Type of study
Authors
Impacts included
Direct
Indirect
Intermediate input
impact
Investment impact
Induced
Leakage (imports from
outside the region)
Impact definitions
Cost-based IO modelling
Ragwitz et al., 2009
Lehr et al., 2011
Lantz 2009
yes
yes
yes
yes
yes
yes, IO model
yes, IO model, estimated via
depreciation
no
yes, multiregional IO model; domestic
content assumed for selected
technologies
yes, IO model
yes
probably not
no
no
yes
yes, domestic content based on
enterprise survey
yes, domestic content based on
assumptions
Definition direct
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)
Definition indirect
All upstream activities in the economy
supplying goods to the direct activities,
also includes manufacturing of
investment goods used by the RE
All upstream activities in the economy
industry
supplying goods to the direct activities
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.
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.
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.
Definition induced
Methodological approach
Employment factors
Supply chain analysis
Cost-based IO modelling
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
Supply-side approach
Data sources for RE related
employment
Requirements for dynamic analysis
Operating companies and activities
belonging to the cost components of
operation and installation costs
n.a.
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
Enterprise survey to identify cost
structures, import shares and exports
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
economic information on each
Domestic expenditures, exports, import Costs, cost structures, domestic
technology in every country; Cost
structures: Literature review and expert shares and cost structures: Enterprise content, employment multipliers: JEDI
model, expert judgement
survey
judgement
Cost degression (changes in
yes
specific costs)
yes
yes
Changing cost structures
due to technological
learning
no
no
no information available
yes
yes for dynamic technologies (wind,
PV)
yes
partly, via assumptions for export
scenarios
probably not
Strengths
no
• Coherent methodology, also for
calculation of exports
• Impacts across country borders
included (multiregional IO model)
• Dynamic requirements largely met
no information available
• Coherent methodology, also for
calculation of exports
• High quality of input data due to
enterprise survey
• Dynamic requirements largely met
Limitations
• Weaker database for Eastern Europe
than for Western Europe
• Loss of RE specificity due to use of
• Loss of RE specificity due to use of
industry averages in IO model
industry averages in IO model
Changes in labour
productivity
Regional shifts of
production sites
Structural change in the
economy
Remarks
• High costs for enterprise survey
yes, via scenario assumptions
probably not (constant multipliers from
the IMPLAN model)
• Coherent methodology for calculation
of economic and employment impacts
• State impact multipliers based on
IMPLAN model
• No consideration of exports
• Dynamic requirements only partly
met
• Loss of RE specificity due to use of
industry averages in IO model
• JEDI model is often used at the subnational level
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
91
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 use
Name of project
Authors/editor
Year of publication
Institution
Contracting body
Region/Country
Base year
Goal of study
Impact indicators/output
Turnover
Investment
Gross output
Gross value added
Jobs (gross)
Number of employees
Fulltime equivalents
GDP
Jobs (net, change in ... compared to)
Number of employees
Fulltime equivalents
other indicators
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and KWK
Hydro large
Hydro small
Wind
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-generation
Other biomass
Geothermal
Heat
Solar thermal
Biogas
Wood
Other biomass
Waste incineration
Waste co-generation
Heat pumps
Deep Geothermal
Fuels
1st generation
2nd generation
Activities (which and how)
Operation of RES plants
Installation of new RES plants
Reinvestment in old RES plants (Repowering)
Fuel generation and supply
RES-related supply chains
Export of RES products
administration, R&D, ...
Rest of economy
Energy Sector Jobs to 2030: A global
analysis; Greenpeace 2009
Rutovitz et al.
2009
Institite for Sustainable Futures
Greenpeace International
world and 10 regions
2005, 2010, 2020, 2030
Putting Renewables to Work: How many Jobs
can the clean Energy Industry generate in the
US? REAL 2010
Wie, Patadia, Kammen
2010 (update of RAEL 2004)
USA
2009 - 2030
discussion on methodology, comparison of
potential job creation associated with two energy
existing studies, assessment of impact on net
scenarios until 2030 (net employment effect is not
employment by using an analytical model (net =
assessed explicitly but it can be calculated as
comparison between two scenarios with positive
the difference between both scenarios)
(in)direct effects )
x
x
x (no negative effects)
x
x (no induced effect for RE)
x
x
x
x
x (aggregated as hydro)
x
x
x
x
x
x (solarthermal)
x
x (aggregated as biomass)
x
x (biomass in general, not specified)
x
(x) energy supply
x
x
x
x
x
x
x (manufacturing is divided into domestic use &
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
92
Included impact regions
Domestic
Other countries / imports
Impacts included
direct
investment
operation and maintenance
Indirect
Intermediate input impact
Investment impact
Induced
Impact mechanisms
investment effects RES
"de"investment effect fossil
O&M effekt RES
"de" O&M effect fossil
price and cost effect on
households
industry
accelerator effect
multiplier effect
productivity effects
export effects
price effect of RES on electricity, heat (MO)
dynamic effect
lead market /innovation effect
Scenarios
domestic reference scenario
x
x (%local production)
x (USA)
x
x
x
x
x
(x)
(only for energy efficiency not for RE)
no mechanisms, just employment factors from
other studies
(x)
(x)
(x)
(the investigation ist not restricted to a certain
BAU based on EIA reference data 2009
use of employment factors
domestic scenario
world scenario
export scenario
advanced RES deployment scenario
(scenarios with differing energy demand for energy
efficiency)
reference scenario (IEA World Energy Outlook
domestic scenario
world scenario
export scenario
sectors included
price projections (fossil, CO2)
Methodological approach
Index-based / analytical
Cost-based approach
Supply-side approach
(macroeconomic) equilibrium model
(macroeconomic) econometric model
(macroeconomic) systems dynamics
Type of data source
Real project data
Estimated project data
Costs
Cost structures
Census
Estimation
Expert estimation
statistics on economic & demographic data
survey, interviews
data from associations
Greenpeace Energy [R]evolution Scenario
(targeting a reduction of 50% below 1990
greenhouse emission)
x (Employment factors)
employment factors
data from other studies
data from other studies
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
93
Comparison of studies for the estimation of job impacts related to renewable energy use
Name of project
Authors/editor
Year of publication
Institution
Contracting body
Region/Country
Base year
Goal of study
Bewertung der volkswirtschaftlichen
Auswirkungen der Unerstützung von
Ökostrom in Österreich; IHS 2007
Bodenhöfer et al. / IHS Kärnten
2004 (updated 2007)
IHS Kärnten
Austria
2004-2006, 2018
Ermittlung der Arbeitsplätze und
Beschäftigungswirkungen im Bereich
Erneuerbarer Energien; BEI 2003
Pfaffenberger et al. / Bremer-Energie-Institut
2003
Bremer-Energie-Institut
Hans-Böckler-Stiftung
Germany
2001-2003, 2025
makro economic effects caused by new law 2006 Asessment of direct and indirect employment
(Ökopstromgesetz) (net = investment + operation - effects with I-O model (net = investment +
budget), effects per RE-technology
operation - budget), effects per RE-technology
Impact indicators/output
Turnover
Investment
Gross output
Gross value added
Jobs (gross)
Number of employees
Fulltime equivalents
GDP
Jobs (net, change in ... compared to)
Number of employees
Fulltime equivalents
other indicators
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and KWK
Hydro large
Hydro small
Wind
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-generation
Other biomass
Geothermal
Heat
Solar thermal
Biogas
Wood
Other biomass
Waste incineration
Waste co-generation
Heat pumps
Deep Geothermal
Fuels
1st generation
2nd generation
x
x
(x) no scenario comparison
x (job/kW or kWh, no scenario comparison)
x
x
x
x
x (aggregated as hydro)
x
x
x
x
x
x
x
x
x
x
x (aggregated as biomass)
x (large and small)
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
94
Activities (which and how)
Operation of RES plants
Installation of new RES plants
Reinvestment in old RES plants (Repowering)
Fuel generation and supply
RES-related supply chains
Export of RES products
administration, R&D, ...
Rest of economy
Included impact regions
Domestic
Other countries / imports
Impacts included
direct
investment
operation and maintenance
Indirect
Intermediate input impact
Investment impact
Induced
Impact mechanisms
investment effects RES
"de"investment effect fossil
O&M effekt RES
"de" O&M effect fossil
price and cost effect on
households
industry
accelerator effect
multiplier effect
productivity effects
export effects
price effect of RES on electricity, heat (MO)
dynamic effect
lead market /innovation effect
Scenarios
domestic reference scenario
x
x
x
x
agriculture and forestry
x
"other economic sectors" + as part of budget
effect
x
value added is subdivided into domestic and
abroad (based on different import ratios)
x (Germany)
x
x
x
x
x (budget effect)
x
x
x
x (IO model)
?
x
x (budget effect)
x
x
x
x
x
x
x
(discussed but not included)
(explicitely no learning effects, ...)
own assumptions for each technology (IHS
Kärnten)
with import figures
domestic scenario
world scenario
export scenario
advanced RES deployment scenario
domestic scenario
world scenario
export scenario
sectors included
price projections (fossil, CO2)
Methodological approach
Index-based / analytical
Cost-based approach
Supply-side approach
(macroeconomic) equilibrium model
(macroeconomic) econometric model
(macroeconomic) systems dynamics
Type of data source
Real project data
Estimated project data
Costs
Cost structures
two market prices
x IO model
IO model (IKARUS)
own estimation for each technology (model
installations)
own estimation for each technology (model
installations)
own estimation for each technology (model
installations)
Census
Estimation
Expert estimation
statistics on economic & demographic data
survey, interviews
data from associations
own estimation for each technology
x
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
95
Comparison of studies for the estimation of job impacts related to renewable energ
Name of project
Authors/editor
Year of publication
Institution
Contracting body
Region/Country
Base year
Goal of study
Impact indicators/output
Turnover
Investment
Gross output
Gross value added
Jobs (gross)
Number of employees
Fulltime equivalents
GDP
Jobs (net, change in ... compared to)
Number of employees
Fulltime equivalents
other indicators
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and KWK
Hydro large
Hydro small
Wind
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-generation
Other biomass
Geothermal
Heat
Solar thermal
Biogas
Wood
Other biomass
Waste incineration
Waste co-generation
Heat pumps
Deep Geothermal
Fuels
1st generation
2nd generation
Activities (which and how)
Operation of RES plants
Installation of new RES plants
Reinvestment in old RES plants (Repowering)
Fuel generation and supply
RES-related supply chains
Export of RES products
administration, R&D, ...
Rest of economy
Solar Photovoltaic Employment in Europe;
EPIA 2009
PV employment
2009
EPIA, WIP, University Flensburg, National
Technical University of Athens
EU27
2005, 2020, 2030
Emphasise the positive employment net effect of
lang-run PV projects; (net = investment +
operation - avoided investments - budget), effect
per RE technology
x
x (person years)
x (no scenario comparison)
x
x (just PV)
x
x
x
x
x
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
96
Included impact regions
Domestic
Other countries / imports
Impacts included
direct
investment
operation and maintenance
Indirect
Intermediate input impact
Investment impact
Induced
Impact mechanisms
investment effects RES
"de"investment effect fossil
O&M effekt RES
"de" O&M effect fossil
price and cost effect on
households
industry
accelerator effect
multiplier effect
productivity effects
export effects
price effect of RES on electricity, heat (MO)
dynamic effect
lead market /innovation effect
Scenarios
domestic reference scenario
x (EU)
x (rest of world
x
x
x
x (IO model)
x (consumption)
x
x
x
x
x
yes to show different development paths, but no
comparison between scenarios
moderate implementation scenario (cumulative
installation of 274GW until 2030)
domestic scenario
world scenario
export scenario
advanced RES deployment scenario
static import/export figures along the value chain
(30%/15%)
advanced implementation scenario (cumulative
installation of 860GW until 2030)
domestic scenario
world scenario
export scenario
sectors included
price projections (fossil, CO2)
Methodological approach
Index-based / analytical
Cost-based approach
Supply-side approach
(macroeconomic) equilibrium model
(macroeconomic) econometric model
(macroeconomic) systems dynamics
Type of data source
Real project data
Estimated project data
Costs
Cost structures
Census
Estimation
Expert estimation
statistics on economic & demographic data
survey, interviews
data from associations
static import/export figures along the value chain
(30%/15%)
x IO model (University of Flensburg)
x (University of Athens)
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
97
Comparison of studies for the estimation of job impacts related to renewable energy use
Name of project
Authors/editor
Year of publication
Institution
Contracting body
Region/Country
Base year
Goal of study
Impact indicators/output
Turnover
Investment
Gross output
Gross value added
Jobs (gross)
Number of employees
Fulltime equivalents
GDP
Jobs (net, change in ... compared to)
Number of employees
Fulltime equivalents
other indicators
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and KWK
Hydro large
Hydro small
Wind
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-generation
Other biomass
Geothermal
Heat
Solar thermal
Biogas
Wood
Other biomass
Waste incineration
Waste co-generation
Heat pumps
Deep Geothermal
Fuels
1st generation
2nd generation
Activities (which and how)
Operation of RES plants
Installation of new RES plants
Reinvestment in old RES plants (Repowering)
Fuel generation and supply
RES-related supply chains
Export of RES products
administration, R&D, ...
Rest of economy
The expansion of renewable energies and
employment effects in Germany; EEFA 2005
Economic and sectoral impacts of RE
deployment; DIW 2010
Hillebrand et al. / Energy Policy
2006
EEFA GmBH
Kemfert, Blazejczak, Braun, Edler, Schill
2010
Germany
2003 -2006, 2010
Germany
2000 - 2030
Quantifying two effects (investments, price
net effects of RE deployment
increase) in order to compute an overall net effect
x
x
x (change to reference scenario)
x (relative change to reference scenario)
x
x
x
x
x
x
x (aggregated as hydro)
x
x (aggregated as hydro)
x
x
x
x
x
x
x (aggregated as biomass)
x
x (aggregated as biomass)
x
x
x
x
x
x
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
98
Included impact regions
Domestic
Other countries / imports
Impacts included
direct
investment
operation and maintenance
Indirect
Intermediate input impact
Investment impact
Induced
Impact mechanisms
investment effects RES
"de"investment effect fossil
O&M effekt RES
"de" O&M effect fossil
price and cost effect on
households
industry
accelerator effect
multiplier effect
productivity effects
export effects
price effect of RES on electricity, heat (MO)
dynamic effect
lead market /innovation effect
Scenarios
domestic reference scenario
domestic scenario
world scenario
export scenario
advanced RES deployment scenario
x (Germany)
x
x
x (Germany)
world
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x (reduced income)
x
x
x
x (learning effect)
adapted from "0-Szenario" and "doublin szenario"
(reference see comment)
status-quo reference scenario (share of RES
contrafactual null scenario (no further RE
"simulation scenario" (achieving 12,5% RES in
2010)
LEAD scenario 2009 (BMU 2010) with
variations (export, competitivness, availability
of employees)
domestic scenario
world scenario
export scenario
sectors included
price projections (fossil, CO2)
Methodological approach
Index-based / analytical
Cost-based approach
Supply-side approach
(macroeconomic) equilibrium model
(macroeconomic) econometric model
(macroeconomic) systems dynamics
Type of data source
Real project data
Estimated project data
Costs
Cost structures
Census
Estimation
Expert estimation
statistics on economic & demographic data
survey, interviews
data from associations
x
structural model with several modules, marginal
effects
x (NiGEM)
x
x
x
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
99
Comparison of studies for the estimation of job impacts related to renewable energy use
Name of project
EmployRES 2009; EU 2009
Authors/editor
Ragwitz et al., EC DG TREN
Year of publication
Institution
Contracting body
Region/Country
Base year
Goal of study
Impact indicators/output
Turnover
Investment
Gross output
Gross value added
Jobs (gross)
Number of employees
Fulltime equivalents
GDP
Jobs (net, change in ... compared to)
Number of employees
Fulltime equivalents
other indicators
RES sector
electricity
heat
fuels
RES technologies (which and how)
Electricity and KWK
Hydro large
Hydro small
Wind
Solar PV
Concentrating solar
Wave and tide
Biogas
Wood
Waste incineration
Waste co-generation
Other biomass
Geothermal
Heat
Solar thermal
Biogas
Wood
Other biomass
Waste incineration
Waste co-generation
Heat pumps
Deep Geothermal
Fuels
1st generation
2nd generation
Activities (which and how)
Operation of RES plants
Installation of new RES plants
Reinvestment in old RES plants (Repowering)
Fuel generation and supply
RES-related supply chains
Export of RES products
administration, R&D, ...
Rest of economy
2009
Fh-ISI, Energy Economics Group, Ecofys,
Seureco, rütter+partner
EU commission
member states of EU 27
1990 - 2005, 2005 - 2030
gross and net employment and GDP effects of
RE deployment in EU
Renewable Energies: employment effects
(2006) BMU 2006, update: Renewable
employed!; Short- and longterm effects of RE
deployment on the German job market, BMU
2011
Lehr, O'Sullivan, Lutz, Edler, Nitsch, Nienhaus,
Bickel, Breitschopf (2011);Staiß et al./BMU
Germany (2006),
2011/2006
GWS/DLR/DIW/ZSW/ISI (2011); ZSW/ DLR/
DIW/GWS (2006)
BMU, Germany
Germany
2007, 2008, 2009, 2010, 2020, 2030 (2011); 2004,
2010, 2020, 2030 (2006)
gross and net employment effects of RE
deployment in Germany
x
x
x
x
x
x
x
x (2011)
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
complete plant, biomass share
biomass share, which part of plant?
x
x
x
x
x
x
x
x
x (not differeniated)
x (offshore/onshore)
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x (Biomass)
x
x
estimates
x
x
x
x
x
x
x
calculated from world trade in RES goods based
calculated with multiregional IO model, based on
on world market shares and traded shares of
world market shares; scenario
investment,
x
x
x
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
100
Included impact regions
Domestic
Other countries / imports
Impacts included
direct
investment
operation and maintenance
Indirect
Intermediate input impact
Investment impact
Induced
Impact mechanisms
investment effects RES
"de"investment effect fossil
O&M effekt RES
"de" O&M effect fossil
price and cost effect on
x (EU and member states)
x (rest of world)
x (Germany)
x (world by 10 regions)
Operation or installation costs broken down to
cost components / primary activities
yes, estimated direct value added.
yes, estimated direct value added.
All indirect economic activities in the economy
x (IO model)
Operation or installation costs broken down to
cost components / primary activities
x, (investments, production value, employment)
x (turnover, production value, employment)
All indirect economic activities in the economy
x (IO model)
x (IO model, wind, PV and other RE as new
"branch")
x (price effect on consumption)
x (IO model)
x (price effect on consumption, income effect)
x
x
x
x
x
households
industry
accelerator effect
multiplier effect
productivity effects
export effects
price effect of RES on electricity, heat (MO)
dynamic effect
lead market /innovation effect
Scenarios
domestic reference scenario
domestic scenario
world scenario
export scenario
advanced RES deployment scenario
domestic scenario
world scenario
export scenario
sectors included
price projections (fossil, CO2)
Methodological approach
Index-based / analytical
Cost-based approach
Supply-side approach
(macroeconomic) equilibrium model
(macroeconomic) econometric model
(macroeconomic) systems dynamics
Type of data source
Real project data
Estimated project data
Costs
Cost structures
Census
Estimation
Expert estimation
statistics on economic & demographic data
survey, interviews
data from associations
x
x
x
x
x
x
capital stock, wages, productivty
based on patent shares etc.
x
no policy
IEA reference
pessimistic
x
BAU and advanced deployment
IEA alternative
moderate and optimistic w.r.t. market shares
based on lead market factors
heat, power, fuel
IEA 2007
Operation and installation costs (Green-X);
allocated to supplying industries; IO model
(Multireg)
x
x (called here: substution effect)
x
budget effect: additional generation costs, paid by
firms, households, gov't leading to lower demand
for other goods
x
x
x
x
x
x
x (via negative additional generation costs)
via capital stock, wage rigidity, price and
productivity development
exogenous value based on historic development,
included via (labour)coefficients
x
own scenario with zero investment in RE since
1995; Energy Report IV, updated to 2050 (2006)
IEA reference (2002)
World market shares
x
own scenario NatPlus-2005: based on Energy
Report IV, focused on climate and RE targets,
Energy[r]evolution (2011); EREC DCP (2001) for
primary energy use (2006)
4 possible developments of world market shares
(pessimistic, moderate, optimistic, max)
heat, power
LEAD Scenario, IEA (2011); Energy Report IV,
updated to 2050 (2006)
Operation and installation costs, allocated to
supplying industries; IO module (Inforge)
NEMESIS
Astra
Panta Rhei
RE deployment in Green-X
Studies, expert judgement
LEAD Scenario (Leitstudie)
survey + expert information
x
x
x, to support statistical data
x
(x)
Fraunhofer ISI, Rütter + Partner, Energy Economics Group
Review of approaches for employment impact assessment of renewable energy deployment
101