Estimating labour market transitions and skills investment needs of the green transition : a new approach.
Date: 2025-03-19
Institutions: Directorate-General for Employment, Social Affairs and Inclusion
Subjects: EU employment policy, economic transition, green economy, investment, labour market, professional qualifications

Written by Fulvimari A., Garaffa R., Kunertova L., 
Van Der Vorst C. and Weitzel M.  
March 2025 

 
 
EUROPEAN COMMISSION 

Directorate-General for Employment, Social Affairs & Inclusion 
Directorate F — Employment and Social Governance, Analysis 
Unit EMPL.F3 — Fair Green and Digital Transitions, Research 

Contact: A. FULVIMARI, Unit EMPL/F3 

E-mail: 

 EMPL-FAIR-TRANSITIONS@ec.europa.eu 

European Commission 
B-1049 Brussels 

 
 
EUROPEAN COMMISSION 

Estimating labour market transitions 
and  skills  investment  needs  of  the 
green transition – a new approach 

Abstract 

The  green  transition  is  affecting  the  entire  economy  and  is  leading  to  significant 
transformations  in  some  specific  sectors,  including  sectors  such  as  the  energy  industries, 
mining  and  quarrying,  construction,  manufacturing,  or  waste  management.  The  ongoing 
transformations  have  impacts  on  the  demand  for  overall  labour  market,  skills,  occupations, 
wages  and  working  conditions.  The  paper  aims  at  providing  evidence  on  labour  market 
transitions in the context of the shift towards climate neutrality. Based on data from the EU 
Labour Force Survey we find that in recent years there was a net inflow of workers into all of 
the ‘transforming sectors’ except for mining and extraction in the EU. In addition, and contrary 
to  expectations,  we  find  that  workers  in  ‘energy-intensive  industries’  overall  make  less 
transitions towards non-employment (inactivity or unemployment) than those working in other 
sectors. This may be due to the higher incidence of trade union density in these sectors and 
also to the fact that these industries are significantly male-dominated hence less affected by 
transitions into inactivity due to caring responsibilities. While crucial in fostering the transition 
towards climate neutrality, we find that training and education in some sectors that are key in 
this  context  is  lagging  behind.  Our  paper  also  provides  novel  estimations  on  the  additional 
amount of workforce needed and the associated training costs from deployment of renewable 
energy at Member State level in 2030. Our findings show that the additional installations of 
wind turbines and solar panels to deliver on the EU Green Deal targets would require about 
130 000 to 145 000 additional skilled workers in the EU, with associated investment in skills 
reaching  1.1  to  1.4  billion  EUR  by  2030.  Job  creation  nonetheless  differs  across  Member 
States,  and those with  relatively  higher  shares  of  renewable capacity  already installed  may 
present lower re-training costs per worker in 2030.   

Keywords:  labour  market  transitions,  net-zero  economy,  green  transition,  social 
investment, skills needs 

JEL code: J21, J24, J62, Q42, Q47 

2025 

Directorate-General for Employment, Social Affairs & Inclusion 

 
 
 
 
 
 
 
 
 
Fair Transitions Working Papers 

Analytical publications related to fair green and digital transitions and research are published 
on an ad-hoc basis. These Working Papers present analytical findings providing new evidence 
or  insights  and  policy-relevant  conclusions  of  in-depth  in-house  analytical  work  and,  where 
relevant,  joint  projects,  notably  with  other  services  of  the  European  Commission  and  other 
stakeholders. Their main aim is to disseminate the outcomes of policy analysis and research, 
thereby informing the Commission’s policy-making activities and contributing to academic and 
policy debates. 

For further detail on policies and activities on fair green and digital transitions and research 
and  an  overview  of  related  publications  and  events,  please  see:  Fair  green  and  digital 
transitions,  research  -  Employment,  Social  Affairs  &  Inclusion  -  European  Commission 
(europa.eu) 

Acknowledgements  

The  views  expressed  in  this  paper  are  the  views  of  the  authors  and  may  not,  under  any 
circumstances, be interpreted as stating an official position of the European Commission. The 
authors  would  like  to  thank  Barbara  Kauffmann  and  Frank  Siebern-Thomas  for  their 
supervision  and  feedback;  Thibault  Delavenne,  Fabio  Domanico,  Maria  Garrone,  Claire 
Gavard, Anais Gradinger, Eva Schoenwald and Zsombor Cseres-Gergely for useful comments 
and  suggestions;  Andrea  Csepregi  and  Catherine  Furzer  for  their  support  during  the  whole 
process. 

Authors  

Alessia Fulvimari, European Commission, Directorate-General for Employment, Social Affairs 
and Inclusion.  

Rafael Garaffa, European Commission, Joint Research Centre. 

Linda Kunertova, European Commission, Directorate-General for Employment, Social Affairs 
and Inclusion.  

Camille Van Der Vorst, European Commission, Joint Research Centre. 

Matthias Weitzel, European Commission, Joint Research Centre. 

4 

 
 
 
 
 
 
 
 
Manuscript completed in October 2024 

This  document  has  been  prepared  for  the  European  Commission  however  it  reflects  the  views  only  of  the 
authors,  and  the  European  Commission  is  not  liable  for  any  consequence  stemming  from  the  reuse  of  this 
publication. More information on the European Union is available on the Internet (http://www.europa.eu). 

Luxembourg: Publications Office of the European Union, 2025 

© European Union, 2025 

The  reuse  policy  of  European  Commission  documents  is  implemented  based  on  Commission  Decision 
2011/833/EU of 12 December 2011 on the reuse of Commission documents (OJ L 330, 14.12.2011, p. 39). 
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PDF 

ISBN 978-92-68-25797-5 

doi: 10.2767/4332366 

KE-01-25-066-EN-N 

Estimating labour market transition and skills investment needs of the green transition – a new approach 

Contents 

1. 

Introduction .............................................................................................. 6 

2.  Exploring labour market transitions towards the net-zero economy .. 8 

2.1.  Literature review and definitions ............................................................ 8 

2.2.  Labour market transitions and demographical composition in ‘transforming 

sectors’ ................................................................................................ 10 

2.2.1.  Characterisation and demographical composition of EU ‘transforming sectors’

 10 

2.2.2.  Sectoral transitions in the total economy in the EU ................................. 14 
2.2.3.  Transitions out and into ‘transforming sectors’ ........................................ 15 

3.  Estimating skills investment needs of the green transition ............... 20 

3.1.  Data used and calculations .................................................................. 22 

3.2.  Additional jobs and re-training costs in 2030 ....................................... 24 

4.  Conclusions ........................................................................................... 29 

References ...................................................................................................... 33 

Annex .............................................................................................................. 38 

5 

 
 
 
 
 
 Fair Transitions Working Papers 

1. 

Introduction 

Reaching climate neutrality in the EU by 2050, as enshrined in the European Climate Law 
adopted in July 2021, requires a fast and effective decarbonisation of the European Union 
(EU)  economy.  This  includes  an  accelerated  roll-out  of  renewable  sources  of  energy, 
improvements in energy efficiency, low emission mobility, and a shift to leaner, more circular 
and  less  resource-intensive  modes  of  production  and  consumption.  Key  initiatives  have 
been introduced by the European Commission in recent years in the area of climate and 
energy  to  advance  the  EU’s  ability  to  achieve  climate  neutrality,  such  as  the  ‘Fit  for  55’ 
package (1), the Green Deal Industrial Plan (2) with its Net Zero Industry Act (3), the Critical 
Raw  Material  Act   (4),  and,  most  recently,  the  Communication  on  a  2040  Climate  Target 
Plan (5) which proposes an intermediate target of reducing net greenhouse gas emissions 
by  90%  by  2040  in  the  EU.  To  reach  the  goals  of  the  European  Green  Deal,  additional 
investments are paramount, and are estimated to be around EUR 520bn (billion) per year 
from  2021-2030,  in particular  in  the  energy  and transport  sectors,  and  help to  deliver  on 
environmental  objectives.  (6)  To  boost  the  EU’s  capacity  to  manufacture  net-zero 
technologies, additional investments amount to around EUR 92bn from 2023 until 2030 as 
estimated in the investment needs assessment accompanying the Net Zero Industry Act. (7)  

These  transformations  affect  labour  markets  and  employment  structures,  and  increasing 
attention is being paid to the need for policy measures to ensure that the necessary social 
investments  are  made  to  deliver  the  transition  to  a  net-zero  economy  by  2050  in  a  fair 
manner. However, while recognised already in the 2020 Green Deal Investment Plan (8), 
social investments linked to the green transition have been overlooked to some extent in 
policymaking and analysis. Various studies provide evidence that the Green Deal, with the 
right accompanying policies in place, can foster new job growth in the EU, with a limited but 
net positive impact on total employment overall across all skill levels, though with diverse 
impacts  on  regions,  sectors,  and  occupations.  Sectors  such  as  renewable  energy, 
manufacture of clean technologies and other electrical products, and construction as well 
as the circular economy will experience a net expansion of their labour force. (9) Energy- 
and  emission-intensive  industries,  on  the  other  hand,  need  to transform  their  production 
processes  and  supply  chains.  Yet,  changes  that  decarbonisation  and  greening  of  the 
economy bring on the labour market spread wider than that. While some sectors grow in 
demand, others may shrink. A significant share of existing jobs even outside of the sectors 
directly impacted will undergo changes due to an uptake of new environmentally-conscious 
production  methods  or  technologies  (e.g.  for  example  in  the  education  or  healthcare 
sectors).  

Investing  in  people  is  crucial  to  ensure  that  everyone  can  equally  benefit  from  the 
opportunities arising from the green transition. These investments take the form of re-skilling 
and up-skilling the workforce in sectors that are key to the green transition, supporting job-
to-job  transitions  and  changing  task  profiles,  and  promoting  quality  employment  and  the 

(1)  Completion of key ‘Fit for 55' legislation (europa.eu) 

(2)  COM(2023) 62 final  

(3)  COM(2023) 161 

(4)  COM(2023) 160 final 

(5)  COM(2024) 63 final and SWD(2024)63. 

(6)  COM/2022/83/final 

(7)  SWD(2023) 68 final  

(8)  COM(2020) 21 final  

(9)  For details see e.g., Aiskainen et al. (2021), Cedefop (2021), European Commission (2020 and 2023a). 

6 

 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

integration of under-represented groups (such as women, low-skilled, young people, people 
with migrant background, people with disabilities) in key sectors to the transition. This is in 
line  with  the  Council  Recommendation  on  ensuring  a  fair  transition  towards  climate 
neutrality.  (10)  Relevant  support to address  employment,  social  and training  needs  in  the 
context of the green transition is also mainstreamed across broader EU policy in multiple 
ways. At EU level, the Just Transition Mechanism supports people living in the regions most 
affected by the transition towards climate neutrality (11), including for example re-skilling, up-
skilling and job assistance. Provisions to address employment aspects of the transition can 
be found also under climate policies, such as the creation of Net-Zero Industry Academies 
that  are set to  develop training  programs to  help meet the  manufacturing  targets  set  out 
under the Net Zero Industry Act. Furthermore, the Recovery and Resilience Plans funded 
by the Recovery and Resilience Facility in place until 2030 (12) include reforms related to 
green skills and green jobs amounting to EUR 2.4 billion, while the European Social Fund 
provides investments of nearly EUR 10 billion in skills and jobs for the green transition.   

In light of these efforts, and against the backdrop of rising labour and skills shortages in 
some of the key sectors and occupations linked to the green transition, estimating the scope 
of  the  need  for  workers  that  are  key  for  implementation  of  clean  energy  targets  is  a 
prerequisite to any successful action in this area. This paper presents novel evidence on 
sectoral  labour  market  transitions  in  industries  that  are  key  to  the  green  transition  (i.e. 
sectors under considerable transformation – so-called ‘transforming sectors’ which include 
‘energy-intensive  industries’).  It  also  presents  a  corresponding  estimation  of  how  many 
additional skilled workers will be needed for the deployment of key net-zero technologies 
(e.g. wind and solar energy), and of the associated investments needs in Member States, 
as a result of the Net Zero Industry Act. (13) 

The paper is organised as follows. Section 2 explores sectoral transitions in the EU in the 
EU ambitious pathway towards climate neutrality. It starts with a literature review and an in-
depth  framing  of  the  sectors  analysed  (Section  2.1).  It  then  focuses  on  ‘transforming 
sectors’, and after characterising them and presenting their demographical composition it 
digs into sectoral transitions in and out of ‘transforming sectors’ (Section 2.2).  Section 3 
discusses the role of re-skilling and/or up-skilling in the ‘transforming sectors’ and explores 
whether workers are already engaging in lifelong learning and how this relates to workers’ 
sector-to-sector mobility. Section 4 provides estimations of skills investment needs of the 
green  transition  arising  from  additional  job  creation  and  re-training  requisites  due  to 
enhanced  production  of  solar  PV  and  wind  energy.  By  presenting  the  background  and 
detailed  methodology  on  the  estimations  regarding  additional  workforce  and  skills 
investments  needed  for  deployment  of  wind  and  solar  energy,  this  paper  supports  the 

(10) On 16 June 2022 Member States unanimously adopted the Council Recommendation on ensuring a fair transition towards 
climate neutrality (2022/C 243/04). The Recommendation invites Member States to adopt measures which address the 
employment  and  social  aspects  of  climate,  energy  and  environmental  policies.  The  Commission  proposal  was 
accompanied  by  a  Staff  Working  Document  (https://ec.europa.eu/social/BlobServlet?docId=25029&langId=en)  that 
provides  an  overview  and  discussion  of  the  available  analytical  evidence  underpinning  the  recommended  policy 
interventions, building on the analyses presented in relevant impact assessment reports accompanying the 2030 Climate 
Target Plan and the various initiatives of the ‘Fit for 55’ package. 

(11) Under the Just Transition Fund, EUR 40 billion is earmarked to assist Member States with providing training and education 
support to persons in regions most affected by the transition, including up-skilling and re-skilling programs to promote 
employment out of emission-intensive and into greener employment. 

(12) Recovery and Resilience Scoreboard (europa.eu) 

(13) The  analysis  presented  in  this  paper  has  been  developed  under  two  joint  projects  between  Directorate-General 
Employment, Social Affairs and Inclusion (DG EMPL) and the Joint Research Centre (JRC) of the European Commission. 
The two projects are: “Assessing and monitoring employment and distributional impacts of the Green Deal (GD-AMEDI)” 
running from 2020 to 2023; and “Assessing distributional impacts of geopolitical developments and their direct and indirect 
socio-economic implications, and socio-economic stress tests for future energy price scenarios (AMEDI+)” running from 
2023 until 2026. The two projects combine macro-economic modelling work and micro-economic modelling approaches, 
with the ultimate goal of enhancing the Commission’s modelling and analysis capacities for assessing and monitoring 
employment, social and distributional impacts of climate and energy policies as well as of energy market effects and price 
developments  caused  by  Russia's  war  of  aggression  against  Ukraine.  For  more 
information  see 
https://ec.europa.eu/social/main.jsp?langId=en&catId=1588 

7 

 
 Fair Transitions Working Papers 

evidence  on  this  matter  presented  in  the  2024  European  Semester  Country  Reports, 
notably Annex 8 (“Fair Transition to Climate Neutrality”). (14) Section 5 draws conclusions. 

2. 

Exploring labour market transitions towards 
the net-zero economy 

2.1. 

Literature review and definitions  

To  understand  the  impact  of  the  green  transition  on  the  labour  market,  it  is  important  to 
study  the  flows  of  workers  between  the  different  sectors  that  will  see  the  largest 
transformations.  This  is  because  the  green  transition  will  lead  to  the  expansion  of  some 
sectors (e.g. workers in renewable energy industries), decline of other sectors (e.g. mining), 
and  in  depth  transformation  related  to  low-carbon  requirements  in  some  industries  (e.g. 
construction, transportation, etc). The green transition will require more workers to transition 
into expanding sectors to avoid further exacerbating already high labour shortages in some 
of  the  most  affected  sectors  (e.g.  construction,  transportation,  etc.).  Understanding  the 
dynamics  of  flows  out  of  shrinking  sectors  is  key  in  order  to  design  effective  policies  to 
support  workers  transitioning  to  other  industries.  Relatively  high  degrees  of  labour 
transitions in the sectors most affected by the green transition should be seen as positive, 
as  it  would  facilitate  a  smoother  labour  market  adjustment  to  the  expected  sectoral 
changes. (15) Section 0 presents an analysis of the EU Labour Force Survey (LFS) (16) with a 
focus on sectors that are relevant in the context of the transition towards climate neutrality 
and complement and contextualise the findings along with a review of previous studies. 

We focus primarily on sectors that are experiencing significant changes due to the green 
transition, which we refer to as the ‘transforming sectors’ for the remainder of this paper. 
Box 1 provides a description of these sectors (including their NACE Rev. 2 section codes). 
The  selection  of  key  sectors  analysed  in  this  paper  covers  economic  activities  that  are 
based on energy-intensive, often greenhouse gas (GHG)-intensive, processes and outputs 
(e.g. mining) but also includes activities that are key to the implementation of the transition 
towards net-zero (manufacturing of electrical equipment, transportation), and are likely to 
expand in demand (waste management due to enhanced circular activity).  

All  of  the  ‘transforming  sectors’  will  experience  significant  changes  in  their  workforce 
because  of  the  transition  towards  climate  neutrality.  However,  the  exact  impact  varies 
across  the  different  sectors.  For  instance,  some  sectors,  like mining  and  quarrying,  may 
experience a decrease in the demand for workers. Other sectors may not see a decline, but 
the required skills and tasks of some occupations may change significantly. For example, 
by 2030, the construction sector is expected to have a higher demand for workers to install 
heat pumps or solar photovoltaic (PVs) (17), while the need for gas fitters to install gas stoves 
or  boilers  may  decrease.  Besides  the  construction  of  new  buildings  and  clean  energy 
infrastructure,  retrofitting  and  energy  efficiency  improvements  are  to  play  a  key  role  for 
projected demand in growth in the sector. The automotive industry, on the other hand, will 

(14) 2024 European Semester: Country Reports - European Commission (europa.eu) 

(15) See also EBRD (2023), OECD (2024). 

(16) The LFS, collected by national authorities and harmonised by Eurostat, is a large household sample survey that provides 

information on labour market participation and on people outside the labour force. 

(17) See Section 3 of this working paper. 

8 

 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

require  different  skills  when  production  shifts  from  cars  powered  by  internal  combustion 
engines to electric vehicles. (18)  

CEDEFOP  also  finds  that  by 2050,  the  European  Green  Deal  may  lead to large relative 
increases  in  employment  in  sectors  such  as  water  supply  and  waste  management, 
construction, and wholesale and retail trade and to decreases in sectors such as coke and 
refined  petroleum,  gas,  steam  and  air  conditioning,  and  mining. (19) The  European 
Commission’s impact assessments for the 2030, 2040 and 2050 European climate targets 
find similar reductions in employment in fossil fuel sectors and increases in sectors such as 
electricity supply or construction. (20) Similarly, according to Eurofound (21), the ‘Fit for 55’ 
package is likely to expand demand for sectors such as manufacturing of renewable energy 
source  equipment,  energy-efficient  appliances,  and  construction,  adding  to  net  marginal 
employment creation, provided the right policies are in place. However, this job creation will 
be counterbalanced by lower economic activity in carbon-intensive sectors. Hence, some 
workers  may  need  to  make  a  transition  from  the  sectors  in  decline  to  another  sector, 
including those in growing demand. On top of this, regardless of whether the green transition 
leads  to  expansion  or  contraction  of  employment  in  these  sectors,  the  transformation  of 
skills  and  occupations  could  increase  the  importance  of  workers  being  mobile  across  or 
within sectors, as well as geographically.  

Box  1:  An  overview  of  the  framework  and  approach  for  exploring  sectoral 
transitions 

The sectoral angle is preferred in the  analysis as decarbonisation takes more direct impact on 
sectors rather than occupations. Recent works by Causa et al. (2024) and OECD (2024) provides 
novel findings on occupational transitions in the economy greening.    

Definition of ‘transforming sectors’  

This paper explores transitions out and into sectors defined in this paper as ‘transforming sectors’. 
This category includes the selection of sectors that (i) are key to transition to climate neutrality for 
their role  in  implementation of climate targets (e.g. the  electricity,  gas, steam and air condition 
supply sector), or (ii) are expected to experience significant employment-related changes due to 
decarbonisation  (e.g.  construction,  mining  and  quarrying),  or  both.  The  employment-related 
changes can be either positive (net growth  in employment demand), neutral (no net change in 
employment demand but considerable changes to skills or tasks are expected) or negative (loss 
in demand for employment). The sectors considered under this definition are selected based on 
the NACE Rev. 2 Level 1 and include mining and quarrying (B), manufacturing (C)(22), electricity, 
gas,  steam  and  air  conditioning  supply  (D),  water  supply,  sewerage,  waste  management  and 
remediation activities (E), construction (F), and transportation and storage (H). The analysis takes 
note that parallel changes of opposing directions may be experienced among sub-sectors within 
the broader economic activity at NACE 1-digit level due to the decarbonisation’s requirements, 
such in the case of manufacturing where growth in demand for labour (e.g. linked to manufacturing 
of  equipment  linked  with  low-energy  produce)  as  well  as  decline  in  demand  in  some  carbon-
intensive manufacturing (e.g. metals) is anticipated. Nevertheless, due to data availability in the 
LFS,  the  report  provides  analysis  at  the  broadest  sector  level  (NACE  1-digit).  Because  of  the 
particular sensitivity of the mining and extraction sector to the energy transition, the results for this 
sector are occasionally discussed in this paper in additional detail. 

(18) Tamba et al. (2022). 

(19) Cedefop (2021). 

(20) European Commission (2018, 2020b and 2024c). 

(21) Eurofound (2023a). 

(22)  This includes also manufacture of motor vehicles, trailers and semitrailers (C29), the manufacturing subsector relevant 

to transformation to electromobility. 

9 

 
 
 Fair Transitions Working Papers 

Framework for sectoral transitions  

Sector-to-sector transitions represent one type of transitions that may occur in the labour market, 
next  to  occupational  transitions,  transitions  out  and  into  employment  or  inactivity,  transitions 
across  different  contractual  arrangements  and  wage  transitions.  The  analysis  of  sectoral 
transitions in ‘transforming sectors’ provided in the section 2.2.3 makes use of standard EU LFS 
variables on workers’ retrospective self-reported employment data (sector, employment status) of 
the year before. (23) Labour market transitions are estimated to track the movement of individuals 
between  each  possible  sector-pair  combination  on  a  yearly  basis  and  per  Member  State.  The 
methodology is repeated for different releases of the LFS between 2010  – 2020, taking note of 
the fact that the results for 2020 may be sensitive to the impact of the COVID-19 crisis. Hence, 
2019 is considered the main year of reference. The analysis is not possible for subsequent years 
as the retrospective question used to assess the transitions has been discontinued from the LFS. 

2.2. 

Labour market transitions and demographical 
composition in ‘transforming sectors’ 

2.2.1. 

Characterisation and demographical composition of EU 
‘transforming sectors’  

Employment in ‘transforming sectors’ across the EU 

Overall, the ‘transforming sectors’ made up around 30% of the European labour market in 
2023  (Figure  1).  Of  the  different  ‘transforming  sectors’,  manufacturing  employs  the  most 
workers  across  the  EU,  with  over  30  million  workers  in  2023.  The  second  largest 
transforming sector in terms of employment is construction, with almost 15 million workers 
in  2023.  The  sectors  mining  and  quarrying,  energy,  and  water  supply  and  waste 
management  make  up  a  much  smaller  share  of  the  European  labour  market,  jointly 
representing around 3.8 million workers.  

There  are  differences  across  Member  States  in  the  relative  importance  of  each  of  the 
‘transforming  sectors’  for  employment,  although  the  overall  pattern  remains  the  same. 
Figure  2  displays  the  relative  employment  in  the  NACE  1-digit  sectors  within  the  total 
‘transforming  sector’  group  for  each  Member  State.  While  manufacturing  employs  most 
workers in most Member States (often over 50% of the workers in ‘transforming sectors’), 
Cyprus and Luxembourg are exceptions to this, with a higher concentration of workers in 
the construction sector. Transportation and storage accounts for approximately 20-25% of 
workers in ‘transforming sectors’ across most Member States. Lastly, mining and quarrying 
employs the least amount of workers (less than, or around 1% in most Member States with 
the  exception  of  Bulgaria  and  Poland),  following  a  declining  trend  over  the  past  few 
decades.  

(23)  The analysis in this section makes use of both yearly and quarterly LFS variables which are weighted using the yearly 

weighting factor (COEFFY) rather than the quarterly weighting factor (COEFFQ). 

10 

 
 
 
 
 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

Figure 1: Employment in millions of workers in EU27 per NACE sector, 2023

Source: Eurostat, variable « lfsa_eisn2 ». 
Notes: ‘Transforming sectors’ are visualised in green. 

Figure 2: Share of workers employed in different ‘transforming sectors’ per Member State, 
2022

Source: Own calculations based on EU-LFS microdata (2022 wave). 

11 

 
 
 
 
 Fair Transitions Working Papers 

Demographic profiles of workers in ‘transforming sectors’ in the EU 

In  the  EU,  ‘transforming  sectors’  have  a  fairly  balanced  representation  of  different  age 
groups across the ‘transforming sectors’ (Figure 14 in Annex). However, in certain Member 
States,  there  is  a  higher  prevalence  of  workers  from  middle-aged  or  older  age  groups, 
including Greece, Spain, Italy, Luxembourg, Romania, and Slovenia. Compared to these 
Member  States,  Estonia,  Croatia,  and  Lithuania  have  slightly  younger  workforces  within 
these sectors. While water supply, sewerage, waste management is the oldest transforming 
sector across the EU (with a median age of 46 years, Figure 14 in Annex), the mining and 
construction  sectors  have  a  slightly  younger  workforce  (with  a  median  age  of  43  years, 
Table 2 in Annex).  

The age distribution in the mining sector in 2022 (Figure 3), showing that workers are mainly 
between  the  ages  of  30  –  50,  may  reflect  a  high  proportion  of  workers  going  into  early 
retirement  possibly  because  of  the  difficult  working  conditions.  Additionally,  this  sector 
shows fewer workers between the ages of 20 – 30 than the EU average across all sectors, 
which may reflect that the shrinking mining sector is less attractive to younger workers who 
enter  the  labour  market  for  the  first  time.  To  give  an  example,  in  Poland  which  has  the 
highest share of the workforce in the EU working in this sector (1.1% in 2022 according to 
LFS data), the average age of a miner worker is 39 years, while the statutory pension age 
for workers in hard mining is 50. (24)  

Figure 3: Age distribution in mining in the EU27, 2022 

Source: Own calculations based on EU-LFS microdata (2022 wave). 
Notes: Yellow dots indicate the EU average across all sectors. 

Women  are  widely  underrepresented  in  the  ‘transforming  sectors’  in  all  Member  States, 
representing between 20-30% of the workforce in these sectors. This is much lower than 
the  European  average  across  all  sectors  in  2023,  where  women  made  up  46.5%  of  the 
labour force. (25) Luxembourg, Belgium and Greece have the largest gender gaps for the 

(24) Frankowski et al. (2020). 

(25) Eurostat (2024d). 

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Estimating labour market transition and skills investment needs of the green transition – a new approach 

‘transforming  sectors’,  with  women  making  up  only  20%  of  the  workforce  (Figure  15  in 
Annex). Conversely, the gender gap is the smallest in Lithuania and Bulgaria, with women 
making up 31% of the workforce in the ‘transforming sectors’. Women constituted as little 
as 14% of all persons working in mining in 2022 (Figure 4), while the gender ratio is slightly 
higher  in  some  of  the  manufacturing  industries  for  computers,  electrical  and  optical 
equipment, and chemicals (around 30% in 2017). (26) 

Figure 4: Gender composition in mining in the EU27, 2022 

Source: Own calculations based on EU-LFS microdata (2022 wave). 
Notes: Yellow dots indicate the EU average across all sectors.  

The share of women in the energy sector has been steadily increasing over the past decade 
(+12% since 2013), yet women made up only 26.7% of the total energy workforce in 2023 
(according  to  LFS  data). Variation  exists  depending  on  the  type  of  energy  production. 
Worldwide, there is a larger share of women employed in renewable energy sectors (32%) 
compared to the oil and gas sector (22%). (27) Across the renewable energy sectors, there 
are relatively more women in the solar PV industry (40%) compared to the wind industry 
(21%). (28)  

At  the  same  time,  looking  through  the  gender  lens,  the  uneven  gender  composition  of 
‘transforming  sectors’  creates  two-fold  implications  of  the  labour  market  changes  in  the 
green transition. While job losses due to the transition to a net-zero economy are expected 
mainly  in  sectors  primarily  occupied  by  men,  such  as  mining,  employment  gains  are 
expected  in  sectors  of  construction  or  waste  management  where  men  are  also  more 
represented. To this end, increasing women’s employment in the clean energy sector that 
constitutes an important share of the new emerging jobs in the green transition is a key step 
to ensure a successful and gender-neutral energy transition. (29)  

(26) IEA (2022). 

(27) IRENA (2022). 

(28) IRENA (2022). 

(29) Murauskaite-Bull et al. (2024). 

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2.2.2. 

Sectoral transitions in the total economy in the EU 

In the EU, most of the sector-to-sector transition rates in the overall economy fall between 
1.8%  –  3.9%  (Figure  16  in  Annex). (30)  In  many  Member  States,  the  transition  rates 
remained  relatively  stable  over  the  observed  period  (2010-2019),  while  a  slight  upward 
trend that could be observed around the year of 2016 in some countries. For example, in 
Estonia,  Finland,  Hungary,  Luxembourg,  Malta  and  Slovenia,  there  were  years  with 
increases in the rate of sectoral transitions after 2017. (31)  

Worker  characteristics  can  typically  influence  one’s  sectoral  mobility.  Workers  at  various 
career  stages  may  encounter  different  circumstances  when  considering  a  shift  in  their 
sector of employment. For example, the opportunities for sectoral mobility may differ based 
on  whether  a  worker  is  entering  the  labour  market  for  the  first  time,  has  a  few  years  of 
experience, or is nearing retirement age. Figure 5 presents sector-to-sector transitions of 
workers  of  different  age  groups  in  the  EU  (Figure  14  in  Annex  for  Member  States 
breakdown). 

Figure 5: Age and gender distribution in ‘transforming sectors’ (magnitude of the bars) and 
sectoral mobility across all sectors of economy (colours of the bars) by age or gender, EU  

Source: Own calculations based on EU-LFS microdata (2019/2022 waves). 
Notes: The magnitude of the bars indicates the share of workers employed in ‘transforming sectors’ by age groups.  Colour 
indicates sector-to-sector mobility per age or gender group, based on sectoral transitions across all sectors of the economy.  

Overall, the descriptive analysis indicate that older workers tend to make fewer sector-to-
sector transitions in the EU. However, there are variations among countries. For instance, 
workers  in  Estonia  and  Finland  appear  to  be  generally  more  mobile  across  sectors 
compared  to  other  countries.  On  the  other  hand,  some  countries  exhibit  significant 
discrepancies  between  the  mobility  of  younger  and  older  workers,  including  Cyprus, 

(30) The calculation of sector-to-sector labour market transitions employs a method based on two LFS variables. The method 
involved creating "labour market transition matrices" that track the movement of individuals between all possible sector-
pair  combinations  within  NACE  rev.  2  Level  1  sectors  on  a  yearly  basis  and  per  Member  State.  The  sector-to-sector 
transition rates were calculated using the following LFS variables: the current sector of employment (NACE1D) and the 
sector of employment one year prior to the survey (NACE1Y1D), available until 2021. By comparing these variables, the 
method allowed for the identification of common sector-to-sector transitions and the calculation of transition rates (the 
percentage of individuals who changed sectors from one year to the next, out of all individuals who were employed in 
both years). The analysis made use of the LFS’ yearly weighting factor (COEFFY). 

(31) Notably,  the  percentage  of  sectoral  transitions  in  Germany  in  2020  was  much  higher  than  the  average  (around  8%), 

possibly influenced by the COVID-19 crisis. 

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Estimating labour market transition and skills investment needs of the green transition – a new approach 

Estonia, Finland, France, and Hungary. Notably, there are countries where sector-to-sector 
transitions  are  relatively  limited,  such  as  Germany,  Greece  and  Romania.  While  further 
research on labour mobility at Member State is required, the data seem to suggest that in 
these  countries,  workers  are  less  likely  to  move  between  different  sectors,  potentially 
indicating  more  stable  employment  patterns  in  the  economic  activity,  specific  structural 
factors influencing cyclicality, or even a more rigid labour market. (32) 

Our  data  show  no  substantial  differences  in  the  mobility  for  men  and  women  across  all 
sectors  of  the  economy  across  the  EU  (see  Figure  5  above  and  Figure  15  in  Annex  for 
Member States breakdown). One exception is Estonia, where women seem to make slightly 
more  sectoral  transitions  than  men.  Zooming  in  on  other  than  sectoral  labour  market 
transitions, recent evidence finds that women are flowing out and into  employment more 
frequently than men as they are more likely to drop out of the labour force due to caring 
responsibilities,  but  are  also  less  likely  to  transition  into  another  job  within  the  same 
industry, (33)  while  other  research  from  US  suggests  this  trend  has  been  historically 
improving. (34) 

The ease of transitioning specifically from a job in a more polluting sector to a job in a less 
polluting sector may also differ from one country to another. For example, Lim et al. (2023) 
found that workers in the US fossil fuel industry might possess transferable skills applicable 
to  green  energy  sectors  but  that  there  are  geographical  barriers  to  sectoral  transitions 
because the fossil fuel industries are not necessarily located in the same place as the green 
energy sectors. These geographical barriers, including associated moving costs, may vary 
from  country  to  country,  potentially  posing  greater  challenges  in  geographically  larger 
countries such as Spain compared to smaller countries like Estonia. 

On the other hand, OECD (2024) suggests that the ease of transitions from more to less 
polluting sectors  varies between the  low-skilled and  high-skilled  workers, finding that  the 
skillsets  of  workers  with  low-skilled  background  are  less  compatible  with  ‘greener’ 
opportunities  relative  to  their  high-skilled  counterparts. (35)  Moreover,  workers  in  some 
regions  with  higher  dependability  on  a  limited  number  of  traditional  emission-intensive 
sectors  may  face  higher  barriers  to  sectoral  transition,  making  the  transition  costs  more 
significant.  

2.2.3. 

Transitions out and into ‘transforming sectors’ 

Sectoral mobility is affected by several factors, including seasonality, cyclicality, structural 
changes such as digitisation or decarbonisation, exogenous events like climate change or 
COVID-19, but also phenomena such as job upgrading. (36) Moving from sectoral transitions 
in the overall economy to those occurring across ‘transforming sectors’ we find that most of 
the sectoral transitions occur between manufacturing and construction, with a comparable 
level of transitions in both directions. Additionally, there is a fair amount of mobility between 
the  sectors  of  manufacturing  and  transportation,  equally  in  both  directions.  Figure  6 
presents  the  different  sectoral  connections  between  the  ‘transforming  sectors’  in  the  EU 

(32)  Existing  literature  has  already  established  that  there  is  much  variation  in  sector-to-sector  mobility  across  different 
countries and over time. For instance, Cardi and Restout (2015) estimated the labour market mobility in 14 OECD countries, 
revealing substantial frictions within each country, with notable differences between them. Among the countries analysed, the 
US displayed the highest labour market mobility, while the Netherlands exhibited a more rigid labour market. 

(33) Causa et al. (2024). 

(34)  Molloy et al. (2016). 

(35)  OECD (2024). 

(36) See  JRC  Publications  Repository  -  Global  Shifts  in  the  Employment  Structure  (europa.eu)  for  more  details  on  job 

upgrading.  

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 Fair Transitions Working Papers 

from 2018 to 2019 (37), with the intensity of the arrows indicating the frequency of sectoral 
transitions in this direction. 

Mining is the only sector that experienced a net outflow of workers between 2018 and 2019 
in the EU out of the ‘transforming sectors’ considered. This sector is characterised by high 
emission-intensity and is expected to face a marginal net job loss in the transition towards 
net-zero by 2030. Remaining sectors experience net inflows, with the volumes of transitions 
notably reflecting sectoral size. While the energy sector recorded a net inflow of workers, it 
should  be  noted  that  the  figure  may  conceal  a  considerable  within-sectoral  variation  in 
labour mobility, as the sector category under NACE currently includes all types of energy 
production,  including  low-carbon  energy  (renewables)  as  well  as  high-carbon  energy 
(production of gas from coal or manufacture of gaseous fuels) that may be experiencing 
marginal shrinking. 

Figure  6:  A  network  visualisation  of  the  most  frequent  sector-to-sector  transitions  in  the 
‘transforming sectors’ in the EU from 2018-2019 

Source: Own calculations based on EU-LFS microdata (2019 wave). 
Notes: The colour indicates whether sectors had a net inflow or outflow of workers, based on sectoral transitions between all 
sectors of the economy. B - Mining and quarrying, C - Manufacturing, D - Electricity, gas, steam and air conditioning supply, 
E - Water supply; sewerage, waste management, F - Construction, H - Transportation and storage. The different shades of 
the arrows indicate more frequent (darker green) and less frequent (lighter green) sector-to-sector transitions. 

Compared  to  some  of  the  services  sectors,  the  ‘transforming  sectors’  seem  to  retain 
relatively more workers, with the exception of water supply, sewerage, waste management 
where slightly more workers leave for other sectors (Figure 17 in Annex). The study of Artuç 
and McLaren (2015) provides more detail regarding where workers who are leaving different 

(37) As mentioned in Box 1 the variable used to calculate sectoral transitions was discontinued from the LFS in 2020. In this 
paper it was decided to use 2019 data instead of 2020, to avoid using a wave much influencfed by the Covid-19 pandemic. 

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Estimating labour market transition and skills investment needs of the green transition – a new approach 

sectors may be moving when they make sectoral transitions. For example, the authors find 
relatively more mobility  from  sectors  such  as  utilities,  retail  trade,  and  entertainment  into 
sectors such as transportation, communication, and finance. 

The energy transition will require a significant amount of re-skilling and/or up-skilling in the 
‘transforming sectors’, and hence we also explore whether workers are already engaging in 
lifelong  learning.  Figure  7  shows  the  share  of  workers  according  to  their  age  group  that 
have received training or education in ‘transforming sectors’ in the EU. (38)  

Figure 7: Percentage of workers in ‘transforming sectors’ in the EU that has received training 
or education in the four weeks prior to participating in the LFS, 2022 

Source: Calculations based on EU-LFS microdata (LFS, 2022).  
Notes: B - Mining and quarrying, C - Manufacturing, D - Electricity, gas, steam and air conditioning supply, E - Water supply; 
sewerage, waste management, F - Construction, H - Transportation and storage 

Younger workers do not only make more sector-to-sector transitions on average, they also 
participate much more frequently in education and training on average in all sectors of the 
economy (39), as shown in Figure 8. As workers get older, the participation rate decreases 
in  all  sectors.  Within  each  age  group,  participation  in  education  and  training  is  relatively 
similar  across  the  different  sectors.  Nonetheless,  workers  in  the  energy  sector  receive 
slightly more education and training in all age groups. The participation rate is around 50% 
for  individuals  aged  15  –  24 (40)  and  remains  at  around  10%  for  those  aged  25  –  54  in 
energy, which is almost twice the participation rate for 25 – 54 year olds in some of the other 
sectors.  Kuokkanen  (2023)  equally  finds  that  workers  in  the  energy  supply  services 
participate more often in education and training compared to workers in manufacturing. 

(38) This includes any formal or non-formal education training received during the reference period. This LFS variable is 

used as the measure for the ‘adult learning’ indicator in the EU. 

(39) However, it should be noted that the 15 – 24 age group is potentially also capturing some workers who are employed 

while being enrolled in formal education programmes. 

(40)  The high value can be likely explained by the fact that the employed persons in this age group are typically still enrolled 

in different forms of formal education. 

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 Fair Transitions Working Papers 

While this trend is consistent across all Member States, the average participation rates vary 
widely.  Figure  8  shows  that,  in  Finland  and  Sweden,  more  than  24%  of  workers  in  the 
‘transforming sectors’  participate  in education and training,  compared to less than  5%  in 
Bulgaria,  Croatia,  Greece,  Romania and  Slovakia.  These results  are in  line  with  findings 
from  previous  studies.  Kuokkanen  (2023)  finds  that  for  energy  supply  services  and 
manufacturing, workers in Sweden, the Netherlands, Denmark and Finland have the highest 
participation  rates  (20-40%)  while  this  rate  is  much  lower  in  countries  such  as  Bulgaria, 
Greece and Hungary (1-5%). 

Figure  8:  Percentage  of  workers  in  ‘transforming  sectors’  that  has  received  training  or 
education in the four weeks prior to participating in the LFS, 2022 

Source: Own calculations based on EU-LFS microdata (2022 wave). 

Box 2: Labour market transitions in ‘energy-intensive industries’ 

We  now  introduce a second  category  of  industries  for  analysis,  the so-called  ‘energy-
intensive industries’ (EII).  (41) This group is a subset of the ‘transforming sectors’ and 
includes  industries  that  can  be  characterised  by  high-emission  intensity  and  are 
particularly susceptible to economic transformation. To obtain granularity, the emission-
intensive industries are grouped together based on the NACE Rev.2 Level 2, covering 

(41) To be noted that while an official definition on EII does no exist, there are different criteria to the one proposed in Box 1 
to  define  this  group  of  sectors.  For  example,  the  Annual  Single  Market  Report  of  2021  (page  209)  includes  other 
manufacturing sectors among EII (i.e. NACE codes 16, 17, 19, 20, 22, 23, 24). 

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Estimating labour market transition and skills investment needs of the green transition – a new approach 

mining and quarrying (B05-09), manufacture of chemicals and chemical products (C20), 
manufacture of other non-metallic mineral products (C23), manufacture of basic metals 
(C24), manufacture of motor vehicles, trailers and semi-trailers (C24). 

In this Box we use the Eurostat’s ‘labour market transitions’ statistics (42) for the custom 
category  of  EII  subsectors.  The  ‘labour  market  transitions’  are  experimental  statistics 
derived  from  the  longitudinal  component  of  the  EU-LFS  data.  They  identify  the  flows 
between different labour market statuses between consecutive quarters.  

The data show that that ‘energy intensive industries’ (EII) (43) are overall less dynamic 
than  the  total  economy,  both  when  it  comes  to  remaining  in  employment,  and  when 
considering transitions from employment towards inactivity and unemployment (Figure 
9). During the 10-year time span analysed, from 2014 to 2023, the share of workers in 
EII who remained in employment (although not necessarily in the same sector of activity) 
between  one year  and  the  next  was constantly above  that for the total economy.  The 
overall trend of both groups, however, is very similar (left-hand side in Figure 9). At the 
same time,  workers  in EII  experienced  less  outflows  into  inactivity and unemployment 
(right-hand side in Figure 9).   

Figure 9 Transitions from employment to employment (left) and employment to inactivity 
and unemployment (right) in ‘energy-intensive industries’ (EII) and in the total economy, 
2014-2023, EU27 

Source: Experimental statistics on labour market transitions. Estimates developed by Eurostat, based on LFS longitudinal 
data, custom extractions for ‘energy-intensive industries’. 

Notes: For the sake of this chart ‘energy intensive industries’ (EII) are defined at the NACE 2-digit level as: mining and 
quarrying  (B05-09);  manufacturing  of  other  non-metallic  minerals  (C23);  manufacturing  of  basic  metals  (C24); 
manufacturing  of  chemicals  (C25);  and  manufacturing  of  motor  vehicles,  trailers  and  semi-trailers  (C29).  The  full 
methodology is explained on the Eurostat website (https://ec.europa.eu/eurostat/cache/metadata/en/lfsi_long_esms.htm). 
“E_E” indicates employment to employment transitions meaning people employed either in EII or in the total economy in 
t-1 who remained employed in t (but not necessarily in the same NACE sector); “E-I” indicates transitions from employment 
to inactivity between t-1 and t; “E_U” indicates transitions from employment to unemployment between t-1 and t. Due to 
limited reliability 2021 data cannot be presented. 

Demographic profile of the workforce in EII is likely to be a factor behind the relative lower 
mobility  into  unemployment  and  inactivity  as  they  are  relatively  male  dominated. 
Nevertheless,  less  employment  mobility  in  EII  also  corroborates  the  fact  that  these 
sectors are characterised by a high degree of labour market stability, which is positive for 
workers in terms of perceived job security, and can possibly be explained by the fact that 
these are relatively well-paid industries in which wage premiums are reported in some 

(42)  Labour market transitions - LFS longitudinal data (lfsi_long) (europa.eu) 

(43) Based on the greenhouse gas (GHG) emissions levels of their production or products, sectors considered energy intensive 
are: mining and quarrying (B05-09); manufacturing of other non-metallic minerals (C23); manufacturing of basic metals 
(C24); manufacturing of chemicals (C25); and manufacturing of motor vehicles, trailers and semi-trailers (C29). 

19 

 
 
 
 
 
 
 
 
 Fair Transitions Working Papers 

Member  States, (44)  although  recent  evidence  by  OECD  shows  that  high-emission 
industries are also characterized by a higher incidence of low pay. (45)  

Analysis  by  OECD  based  on  linked  employee-employer  data  also  shows  that  when 
changing employment, workers from high-emission industries are slightly more likely to 
change  a  sector,  but  their  destination  is  highly  likely  to  be  another  emission-intensive 
occupation. (46)  Re-skilling  and  up-skilling  as  well  as  broader  and  comprehensive 
employment support is thus needed to address challenges to sustainable employment 
outcomes  of  workers  in  the  sectors  that  are  affected  and  need  to  adapt  to  advance 
towards  climate  neutrality.  Moreover,  recent  work  by  Causa  et  al.  (2024)  shows  that 
workers  in  high-carbon  jobs  face  higher  displacement  risks  than  workers  in  non-high-
polluting occupations, with 20% higher odds of unemployment. 

3. 

Estimating skills investment needs of the 
green transition 

The green transition has substantial implications for human capital, which can be defined 
as  the  stock  of  skills  that  the  labour  force  possesses. (47)  The  EU  climate  ambition  will 
accelerate this transition, affecting the number of skilled workers in a range of activities, in 
particular  those  related  to  renewable  electricity  generation.  The  labour  market  impacts 
directly  translate  into  training  needs  for  both  workers  and  jobseekers,  but  with  markedly 
differences across sectors and regions.  

Figure 10 visualises the evolution over time of the participation of works in education and 
training per sector in the EU. Overall, there appears to be a slight increase in the share of 
workers receiving education and training over time, with a sharp drop during the COVID-19 
crisis  and  a  recovery  from  2021  onwards.  Workers  in  the  energy  sector  (NACE  D) 
participate much more frequently in training and education compared to other sectors. The 
two sectors that consistently see some of the lowest share of workers participate are mining 
(NACE B) and construction (NACE F). Achieving the EU Green Deal targets in 2030, will 
heavily require  skilled workers in the construction sector (e.g. installation of heat pumps, 
solar  panels,  construction  of  wind  farms,  new  civil  engineering  skills,  etc.),  hence  it  is 
noteworthy that relatively few workers in this sector participate in training. In particular, the 
participation  rate  in  the  construction  subsector  that  includes  heat  pumps’  installation 
(specialised  construction  activities,  NACE  Division  43)  is  similar  to  that  of  the  overall 
construction sector, as illustrated by the dashed blue line in Figure 10.  

(44) European Commission (2023c); OECD (2024). 

(45) OECD (2024). 

(46) OECD (2024, Chapter 3). 

(47) Goldin (2019). 

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Estimating labour market transition and skills investment needs of the green transition – a new approach 

Figure 10: Percentage of workers in the EU that has received training or education in the four 
weeks prior to participating in the LFS, by NACE Section (workers aged 25 – 65) 

Source: Own calculations based on LFS microdata (LFS, 2010 – 2022). 
Notes: Includes workers aged 25 – 65. The dashed blue line represents workers in the construction subsector "specialised 
construction  activities"  (NACE  Division  43),  which  also  includes  activities  such  as  electrical  installation  and  heat  and  air 
conditioning installation. 

There  is  also  considerable  variance  across  Member  States  in  the  participation  rate  in 
education and training. For instance, when looking at  ‘energy-intensive industries’ (sectoral 
coverage defined in Box 2), the participation rate in education and training has increased to 
10.9% in 2023 (9.4% in 2015) but remains below the whole economy average in the EU 
(12.7%). Croatia, Hungary, Poland and Czechia (3.1%, 7.6%, 7.9% and 8.2% respectively) 
rank  lowest  in  terms  of  participation  rate  in  education  and  training  in  ‘energy  intensive 
industries’,  while  Sweden,  Denmark,  Finland  and  Netherlands  report  the  highest  shares 
(above 23%). (48) (49) 

In this section we focus in two relevant sectors for the green transition. Our interest is in 
estimating the number of jobs related to the deployment and installation of wind and solar 
power  generation,  with  respect  to  job  creation  across  the  whole  value  chain.  We  pay 
particular  attention  to  the effects  on  construction,  services and transport,  as sectors  that 
contribute the  most  to the  number  of jobs  generated  due to  the  deployment  of  wind  and 
solar power generation. Compared to previous analyses (50), here the focus is in estimating 
those figures by Member States. Beyond providing a closer look at the number of additional 
jobs  created  due  to  the  deployment  of  wind  and  solar  PV,  we  estimate  the  related 
investment needs for re-training/re-skilling/up-skilling workers at Member States level.  

(48)  High variance also exists in yearly changes as the variable used to monitor adult learning in EU-LFS data (‘Participation 

in education and training of the age group 25-64’) uses 4 weeks as the reference period.  

(49)  Data is unavailable for BG, EL, LV, MT, IE, CY, LU due to limited sample size of the observed workforce in these industries 

under EU-LFS data. 

(50) European Commission (2022a and 2022b). 

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 Fair Transitions Working Papers 

3.1. 

Data used and calculations 

Following  the  steps  presented  in  Figure  11,  this  section  describes  the  calculations  and 
presents  the  data  sources  used  to  estimate  the  skills  investment  needs  of  the  green 
transition.  We  take  the  wind  and  solar  capacity  expansions  to  calculate  the  additional 
investment needed to deliver on the European Green Deal 2030 targets. From the additional 
investment  needs,  we  further  obtain  the  additional  jobs  and  re-training  costs  related  to 
deployment of wind and solar power generation technologies by Member States in 2030.  

Figure 11: Flowchart – steps used in the calculations of additional jobs and re-training costs 
in 2030 

Source: Own elaboration. 

Step  1:  As  a  starting  point,  we  take  the  installed  capacity  reported  at  the  ENTSO-E 
Transparency  Platform (51)  to  obtain  the  current  power  generation  installed  capacity  by 
Member States. (52) Precisely, we take the average installed capacity additions for wind and 
2023), which 
solar power generation (𝑖) by Member State (𝑟) over 2021-2023 (𝐸𝑁𝑇𝑆𝑂𝐸_𝐶𝑎𝑝 𝑖,𝑟
we  assume  as  a  proxy  of  what  is  the  current  annual  rate  of  deployment  of  these 
technologies (in MW/y).  

Next, we need to calculate what is the additional installed capacity projected to be consistent 
with the EU Green Deal targets. For that we use the average installed capacity over 2025-
2030) informed by the energy models that include the policy impacts of the ‘Fit for 
30 (𝐴𝑑𝑑𝐶𝑎𝑝 𝑖,𝑟
55’  and  RePowerEU  packages.  We  use  information  from  both  PRIMES  and  POTEnCIA 
energy  models (53)  to  calculate  the  annual  capacity  additions  for  wind  and  solar  power 
2030), averaging across both models. Using the 
generation by Member States (𝐺𝐷𝑡𝑎𝑟𝑔𝑒𝑡_𝐶𝑎𝑝 𝑖,𝑟
information from both energy models reduces the uncertainty in the projections at Member 
States level, as the models have different characteristics (54). It also provides a range (min-
max) of the average annual capacity additions, hence of the additional jobs and associated 
re-training  expenses.  In  Equation  1a,  the  capacity  additions  of  wind  or  solar  power 

(51) ENTSO-E (2024). 

(52) Table 14.1.A of the ENTSO-E platform shows the historical installed net generation capacity equalling to or exceeding 1 

MW effectively installed on January 1st of a given year. 

(53) European Commission (2024a). 

(54) There are several reasons why energy models may take different decisions on where to install the additional capacity of 
wind and solar. Here we refer to the models’ documentation for further details, because it is out of the scope of this work to 
go  specifically  into  their  features.  Nonetheless,  an  example  of  potential  drivers  of  those  differences  is  how  the  electricity 
market balance is achieved and what the role electricity trade plays across the EU27 Member States in a context of intermittent 
renewable sources. 

22 

 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

generation  (𝑖)  by  Member  State  (𝑟)  represent  the  expansion  rate  of  installed  capacity 
additions needed to deliver on the European Green Deal targets by 2030. 

𝐴𝑑𝑑𝐶𝑎𝑝 𝑖,𝑟

2030 (

𝑀𝑊
𝑦

) =   𝐺𝐷𝑡𝑎𝑟𝑔𝑒𝑡_𝐶𝑎𝑝 𝑖,𝑟

2030 (

𝑀𝑊
𝑦

) − 𝐸𝑁𝑇𝑆𝑂𝐸_𝐶𝑎𝑝 𝑖,𝑟

2023 (

𝑀𝑊
𝑦

𝐼𝑁𝑉 𝑖,𝑟

€
2030  (
𝑦

) =   𝐴𝑑𝑑𝐶𝑎𝑝 𝑖,𝑟

2030  (

𝑀𝑊
𝑦

) ∗   𝐶𝐴𝑃𝐸𝑋 𝑖,𝐸𝑈27 (

€
𝑀𝑊

) 

)  

(1a) 

(1b) 

To  conclude  the  first  step  of  our  calculations,  in  Equation  2b  we  multiply  the  projected 
2030) by the investment cost in wind 
average installed capacity additions in 2030 (𝐴𝑑𝑑𝐶𝑎𝑝 𝑖,𝑟,𝑚
and  solar  (𝐶𝐴𝑃𝐸𝑋 𝑖,𝐸𝑈27)  underlying  the  EU  2020  Reference  scenario  (55),  to  obtain  the 
additional  investment  needed  for  the  deployment  of  such  technologies  to  deliver  on  the 
2030). Therefore, our estimates capture the 
European Green Deal targets (56) by 2030 (𝐼𝑁𝑉 𝑖,𝑟,𝑚
additional jobs required by 2030, while we further refer to re-training expenses in 2030 as 
we use annual re-training costs estimates, hence assuming a one-time off expenditure in 
2030. 

The capacity additions trigger investment upstream of the value chain of these technologies. 
For  example,  investment  in the  wind  energy  sector  requires  the  manufacturing  sector  to 
produce equipment goods (e.g., nacelle, rotors and generators) and the construction sector 
to  build  the  physical  infrastructure  (e.g.,  construction  workers  to  clean  and  prepare  the 
construction sites, welders to merge metal parts). Differently from the analysis done in the 
context  of  the  Net-Zero  Industry  Act  policy  proposal (57),  where  equipment  goods’ 
manufacturing could happen in different places, here the technology deployment actually 
happens in the EU Member States. Therefore, we focus on a subset of upstream sectors 
(namely construction, services and transport), related to the installation of wind and solar 
power  generation  technologies.  These  are  upstream  sectors  whose  economic  activity  is 
positively affected by investments in these power generation technologies. 

Step 2: In the second step of our calculations we move to the additional investment needed. 
First, we calculate the labour share in total value added for the EU27 (𝐿𝑉𝐴 𝑗,𝐸𝑈27) using the 
input-output  (IO)  tables  projected  for  the  year  2025  in  the  Global  Energy  and  Climate 
Outlook  (GECO)  2021. (58) (59)  Next,  we  obtain  the  share  of  investment  supplies 
(𝐼𝑁𝑉𝑆𝐻 𝑗,𝐸𝑈27) to wind or solar power generation from the investment matrix of the JRC-GEM-
E3 model for the EU27. (60) Therefore, the parameter 𝐼𝑁𝑉𝑆𝐻 𝑗,𝐸𝑈27 informs what is the share 
of the investment supplied by upstream sectors given one unit of investment in the investing 
sectors (wind and solar). Finally, we obtain the share of labour payments (𝐿𝐴𝐵𝑆𝐻 𝑗,𝐸𝑈27) in 
the upstream sectors (𝑗) as described in Equation 2a. For example, if the labour share in 

(55) In line with the EU Reference 2020 scenario and RePowerEU (European Commission, 2021; 2022), here we assume a 
CAPEX of 1,250 EUR/kW for wind and of 600 EUR/kW for solar power generation in the EU27. The information is available 
for more disaggregated technologies in the file REF2020_Technology Assumptions_Energy.xlsx (Power&Heat sheet) of the 
EU Reference 2020 scenario (European Commission, 2021). As a simplification, we assume that the same CAPEX applies 
to all EU Member States. 
(56) While Member State specific targets for renewable deployments would be a preferred source, the draft updates of the 
National  Energy  and  Climate  Plans  (NECPs)  submitted  in  2023  are  not  yet  sufficient  to  reach  the  2030  climate  target 
(European Commission, 2023b). Therefore, here we rely on scenarios incorporating the relevant Fit for 55 and RePowerEU 
policies to meet the EU climate target for 2030. For more details of the policies represented, see Annex 6, Section 3.1.1 of 
European Commission (2024c). 

(57) European Commission (2023a). 

(58) In GECO 2021, we calibrate the JRC-GEM-E3 model to the base year 2014 using the GTAP10 database (Aguiar et al., 
2019). The input-output tables are further projected in 5-year intervals over 2015-50. To perform the calculations of additional 
jobs in 2030, we take the year 2025 IO table, as investment decisions in JRC-GEM-E3 are based on the capital stock of the 
previous period. See Keramidas et al. (2021) for more details. 

(59) Wojtowicz et al. (2021), Keramidas et al. (2021). 

(60) Norman-López et al. (2023). 

23 

 
   
 
 Fair Transitions Working Papers 

total value added of the construction sector is 18% and the share of investment supplied by 
the construction sector in the installation of a wind mill is 12%, then we obtain a 2.2% share 
of labour payments to the construction sector. 

𝐿𝐴𝐵𝑆𝐻 𝑗,𝐸𝑈27 (%) =   𝐿𝑉𝐴 𝑗,𝐸𝑈27 (%) ∗ 𝐼𝑁𝑉𝑆𝐻 𝑗,𝐸𝑈27 (%)  

(2a) 

𝐿𝐴𝐵 𝑗,𝐸𝑈27  (

𝑤𝑜𝑟𝑘𝑒𝑟
€

) =  

𝐿𝐴𝐵𝑆𝐻 𝑗,𝐸𝑈27 (%)
€
𝑤𝑜𝑟𝑘𝑒𝑟

𝐴𝑣𝑔𝑊𝑎𝑔𝑒 𝑗,𝐸𝑈27 (

)

(2b) 

Next,  using  the  share  of  labour  payments  (𝐿𝐴𝐵𝑆𝐻 𝑗,𝐸𝑈27)  and  the  average  wage  of  the 
upstream sectors in the EU27 from the JRC-GEM-E3 model (𝐴𝑣𝑔𝑊𝑎𝑔𝑒 𝑗,𝐸𝑈27), we  calculate 
a  job  intensity  indicator  (𝐿𝐴𝐵 𝑗,𝐸𝑈27 ),  expressed  in  number  of  workers  per  labour 
compensation, as described in Equation 2b. Therefore, this indicates the job intensity, from 
the capacity additions of wind and solar, to the delivery on the EU Green Deal targets. 

Step 3: In the final step, by multiplying the additional investment needed for the technology 
deployment  by  the  job  intensity,  we  calculate  the  number  of  additional  jobs  by  2030 
2030) in upstream sectors (𝑗) by Member State (𝑟). Hence, Equation 3a informs the 
(𝐽𝑜𝑏𝑠𝑗,𝑟
number  of  jobs  implied  by  the  additional  installed  capacities  of  wind  and  solar  power 
generation:  

𝐽𝑜𝑏𝑠𝑗,𝑟

2030 (

𝑤𝑜𝑟𝑘𝑒𝑟
𝑦

€
) = 𝐼𝑁𝑉 (
𝑦

) ∗   𝐿𝐴𝐵 𝑗,𝐸𝑈27  (

𝑤𝑜𝑟𝑘𝑒𝑟
€

)  

(3a)              

         Investment           Job intensity 

𝑆𝑘𝑖𝑙𝑙𝑠𝑗,𝑟

€
2030 (
𝑦

) =  𝐽𝑜𝑏𝑠𝑗,𝑟

2030 (

𝑤𝑜𝑟𝑘𝑒𝑟
𝑦

) ∗   𝑅𝑒𝑆𝑘𝑖𝑙𝑙 𝑗,𝐸𝑈27  (

€
𝑤𝑜𝑟𝑘𝑒𝑟

) 

(3b)              

After  calculating  the  additional  jobs  created,  in  Equation  3b  we  take  re-training  costs 
estimates  at  the  EU  level  (𝑅𝑒𝑆𝑘𝑖𝑙𝑙 𝑗,𝐸𝑈27)  per  person  per  year (61)  to  calculate  the 
corresponding  investment  needs  for  re-training/re-skilling/up-skilling  by  Member  States 
2030). The re-training costs (𝑅𝑒𝑆𝑘𝑖𝑙𝑙 𝑗,𝐸𝑈27 ) are scaled to the Member States by service 
(𝑆𝑘𝑖𝑙𝑙𝑠𝑗,𝑟
worker wage using the labour cost levels from Eurostat (2023). For example, if the training 
cost is EUR 1 000 for the EU average, then for a Member State with 80% wage level relative 
to the EU average, we reduce the cost by 20% to reach a training cost 800 euro, assuming 
that the training can be done in the same time in all Member States but at a lower cost. 

3.2. 

Additional jobs and re-training costs in 2030 

In this section we present the results of the calculations described in section 4.1. In addition 
to  the  projected  additional  jobs  and  re-training  costs  in  2030,  we  show  indicators  of  the 
current share of renewable energy in power generation and the projected capacity additions 
to better contextualise our findings. We also develop two further indicators that show the 
number of additional jobs and the value of re-training costs per person in the labour force 
by Member States.  

Table  1  shows  the  projected  number  of  additional  skilled  workers  needed  for  the 
deployment of wind and solar energy and the investment in skills by EU Member State in 

(61) European Commission (2020a), Vandeplas, A. et al. (2022). 

24 

 
 
  
 
 
 
 
 
 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

2030. Overall, we find that the installations of wind turbines and solar panels would require 
about 130 000 to 145 000 additional skilled workers in construction, services and transport 
sectors in 2030 (Table 1). The number of additional skilled workers is in line with, if not more 
optimistic,  than  figures  in  the  Employment  and  Social  Developments  in  Europe  (ESDE) 
2023 review, which estimated 100 000 additional workers (62), based on the scenarios from 
the Net Zero Industry Act. Eurofound (63) estimates 204 000 additional jobs when accounting 
for the full range of investments needed for the implementation of the Fit for 55 package 
(i.e., not only wind and solar PV related investments). These figures are also in the range 
of the additional 286 000 jobs in the energy sector to deliver on the EU Green Deal targets 
in 2030 projected by Cedefop. (64) According to our analysis, the main sectors affected by 
the  investment  in  wind  and  solar  power  generation  are  the  construction  and  services 
sectors, where the bulk of these jobs are concentrated on (about 90%). These sectors are 
followed  by  the  transport  sector,  where  the  additional  jobs  come  mainly  from  the 
infrastructure development for the installation of windmills. 

At the Member States level, Germany and Italy stand out as the countries where additional 
skilled  workers  would  be  the  most  needed for  the deployment  of  wind  and  solar  energy. 
This  reflects  the  higher  expansion  rate  of  installed  capacity  additions  in  these  countries 
compared  to  other Member  States.  Although economies  of  scale  and scope  are  present 
when installed capacity expands (e.g., logistics and transportation costs may not increase 
proportionally to the installed capacity expansion), this result reflects the investment needs 
associated to deliver the installed capacity rates projected by the energy models (65) – about 
17GW/year  and  15GW/year,  for  Germany  and Italy,  respectively,  by  2030.  On the  other 
hand, smaller economies (e.g., Cyprus, Malta) and Member States where renewables have 
gone through faster deployment in the past years (e.g., Denmark, Sweden) show expansion 
rates  lower  than  1GW/year,  meaning  that  investment  and,  hence,  job  creation  are  not 
projected  to  be  as  high  as  in  e.g.  Germany  and  Italy  in  the  coming  years.  The  capacity 
additions  per  capita  nonetheless  suggest  Member  States  gravitating  around  the  EU27 
average  of  0.15  GW/capita  in  2030,  with  the  exception  of  Luxemburg,  due  to  its  small 
population size (Table 1). 

(62) European Commission (2023c). 

(63) Eurofound (2023a and 2024a). 

(64) Cedefop (2021). 

(65) European Commission (2024a). 

25 

 
 Fair Transitions Working Papers 

Table 1: Projected number of additional skilled workers needed for the deployment of wind 
and solar energy and investment in skills (in million Euro) by EU Member State and EU27 total 
in 2030. Average share of renewable energy sources in electricity generation over 2020-2022 
(%) 

Member State 

Capacity 
additions  

Additional jobs                                              

costs                   

Re-training 

(000 jobs) 

(in million EUR) 

Share of 
renewables 
(avg.2020-22) 

(%) 

min 

min 

max 

max 

GW / 
year 

 2.0  
 2.4  
 0.5  
 0.4  
 0.3  
 2.2  
 16.9  
 0.1  
 3.5  
 0.2  
 0.9  
 4.4  
 2.0  
 0.4  
 1.3  
 15.1  
 0.3  
 0.3  
 0.3  
 0.1  
 3.3  
 3.2  
 1.7  
 2.0  
 0.5  
 0.3  
 0.9  
65.4 

Austria 
Belgium 
Bulgaria 
Croatia 
Cyprus 
Czechia 
Germany 
Denmark 
Spain 
Estonia 
Finland 
France 
Greece 
Hungary 
Ireland 
Italy 
Lithuania 
Luxembourg 
Latvia 
Malta 
Netherlands 
Poland 
Portugal 
Romania 
Slovakia 
Slovenia 
Sweden 
EU27 

GW / 
capita 
 0.22  
 0.21  
 0.08  
 0.09  
 0.29  
 0.20  
 0.20  
 0.01  
 0.07  
 0.14  
 0.16  
 0.06  
 0.19  
 0.04  
 0.25  
 0.26  
 0.12  
 0.52  
 0.18  
 0.10  
 0.19  
 0.08  
 0.16  
 0.11  
 0.09  
 0.16  
 0.08  
0.15 
Source: Own calculations; share of renewables in electricity from Eurostat (2024b). 
Notes: Number of additional jobs obtained from JRC-GEM-E3 calculations using the input-output (IO) tables projected for the 
year 2025 in the Global Energy and Climate Outlook 2021 (Wojtowicz et al., 2021; Keramidas et al., 2021).  Training costs 
estimates per person per year from European Commission (2020a) and Vandeplas et al. (2022). Capacity additions, additional 
jobs and re-training costs for the EU27 are the sum of the individual Member States, while the share of renewables in electricity 
reflect the EU average over 2020-22 from Eurostat (2024b). 

56.8 
59.9 
4.7 
1.3 
1.8 
12.2 
473.7 
12.1 
55.3 
1.7 
2.9 
178.5 
24.2 
2.2 
31.7 
249.0 
0.5 
4.5 
2.1 
0.5 
151.7 
20.7 
14.8 
6.2 
4.9 
1.7 
11.0 
1,386.7 

45.5 
47.9 
3.7 
1.1 
1.4 
9.8 
379.0 
9.7 
44.2 
1.4 
2.3 
142.8 
19.3 
1.7 
25.4 
199.2 
0.4 
3.6 
1.7 
0.4 
121.3 
16.6 
11.9 
4.9 
3.9 
1.4 
8.8 
1,109.4 

 3.5  
 4.2  
 0.7  
 0.2  
 0.4  
 2.3  
 32.7  
 0.2  
 7.2  
 0.3  
 0.2  
 4.5  
 3.0  
 0.6  
 2.6  
 25.8  
 0.1  
 0.3  
 0.5  
 0.1  
 3.4  
 5.1  
 2.8  
 2.0  
 1.0  
 0.2  
 0.8  
 130.2  

 4.4  
 6.1  
 1.7  
 1.2  
 0.6  
 6.6  
 36.6  
 0.8  
 12.9  
 0.6  
 3.6  
 13.3  
 5.1  
 1.4  
 2.8  
 33.8  
 1.5  
 1.1  
 1.0  
 0.1  
 11.4  
 9.0  
 3.5  
 6.0  
 1.3  
 1.0  
 2.4  
 144.7  

 75.6  
 26.7  
 21.7  
 54.3  
 14.6  
 14.9  
 45.2  
 71.8  
 46.6  
 28.9  
 42.4  
 25.6  
 38.1  
 13.6  
 37.4  
 37.1  
 22.6  
 14.7  
 52.7  
 9.8  
 33.2  
 18.1  
 59.1  
 43.3  
 22.8  
 35.7  
 77.9  
38.8 

In general, the literature estimates employment factors for the construction and installation 
ranging from 2.0 to 6.2 (full-time equivalent) jobs/MW of wind power installed, and from 3.5 
to  13.0  jobs/MW  of  solar  power  installed. (66)  These  estimates  are  typically  derived  from 
bottom-up  technology  models  and  provide  a  useful  reference  to  cross-check  the 
employment factors obtained in our Input-Output (IO) estimates. In our analysis, we find 2.4 
jobs/MW installed of wind power and 2.1 jobs/MW installed of solar power when looking at 
the EU27 average. While the employment factors for wind are within the range observed in 
the literature, we note that our results for solar are conservative compared to the existing 
literature.  

The deployment of wind and solar energy affects human capital, as more trained workers 
are  needed  to  support  the  capacity  expansion  of  these  technologies.  Following  our 
calculations, we find that the additional installed capacities of wind and solar to deliver on 

(66) Cameron and Van der Zwaan (2015), Fragkos and Paroussos (2018), Ortega et al. (2020), Pai et al. (2021), European 

Commission (2022a and 2022b). 

26 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

the EU Green Deal targets may require at minimum an investment in skills of EUR 1.1 to 
1.4  billion  by  2030  (Table  1).  The  investment  in  skills  is  also  similar  to  the  ESDE  2023 
estimate of EUR 0.9 billion by 2030, which was based on the Net-Zero Industry Act policy 
proposal  scenarios  (European  Commission,  2023a). (67)  Putting  it  into  perspective,  the 
investment is about 1% of the average annual investment needs in power plants (142 billion 
EUR)  projected  in  Europe's  2040  climate  target  impact  assessment report for  the  period 
2031-2050 (European Commission, 2024c).   

Figure 12: Job creation per thousand people in the labour force for the deployment of wind 
and solar power generation by EU27 Member State (in 2030) 

Source: Own calculations based on European Commission (2021; 2024a) and Eurostat (2023). 
Notes: Number of additional jobs obtained from JRC-GEM-E3 calculations using the input-output (IO) tables projected for the 
year 2025 in the Global Energy and Climate Outlook 2021 (Wojtowicz et al., 2021; Keramidas et al., 2021). 

The job creation in 2030 negatively correlates with the current share of renewables in power 
generation.  The  correlation  coefficient  between  jobs  created  and  the  current  share  of 
renewables is not substantially high (-0.16), nonetheless indicates that job creation in 2030 
should occur more prominently in Member States with a lower share of renewables today. 
This result becomes more evident when looking at Figure 12, in which we use the average 

(67) European Commission (2023c). 

27 

 
 
 
 
 
 Fair Transitions Working Papers 

installed  capacity  informed  by  the  two  energy  models  to  calculate  the  job  creation  per 
person in the labour force by Member States. In  

Figure 12, we observe countries like Belgium, Italy and Ireland with about 1 job created per 
thousand people in the labour force in 2030, due to the deployment of wind and solar power 
generation. When looking at the share of renewables obtained from Eurostat (2024b), the 
average  share  between  2020  and  2022  shows  a  range  of  26.7%  to  37.7%  for  these 
countries (last column in Table 1). Conversely, job creation should be close to 0.4 jobs per 
thousand people in Portugal or Sweden, which currently have a higher share of renewables 
in power generation (59% and 78%, respectively). 

When looking at re-training costs per person across the EU labour force, Figure 13 shows 
a similar regional pattern as observed in Figure 12. In general, Member States with relatively 
higher installed capacity today show lower re-training expenses per person in the labour 
force  as  additional  job  creation  is  not  as  high  as  in  other  Member  States.  For  instance, 
Belgium, Italy or Ireland apparently undergo a ‘catching-up’ process in terms of wind and 
solar deployment over 2025-30. These Member States are typically exploring their available 
renewable potential  and  increasing the share  of wind  and solar  in the  power mix,  hence 
stimulating  different  skillsets  and  tasks  in  those  sectors  (e.g.,  drivers  bringing  blades  for 
wind power generation on site or service workers doing site permitting). On the upper range 
of the  distribution,  we  calculate  values  between  EUR  10 (Italy) to  EUR  13 (Belgium)  per 
person in the labour force as re-training expenses in 2030.  

Figure 13: Investments in skills: re-training costs in EUR per person in the labour force (in 
2030) 

Source: Own calculations based on European Commission (2021; 2024a) and Eurostat (2023).  
Notes: Training costs estimates per person per year from European Commission (2020a) and Vandeplas et al. (2022). 

28 

 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

On the other hand, Eastern Member States feature more prominently in the lower range of 
the distribution. For instance, re-training expenses range around EUR 1 (Bulgaria, Hungary) 
per person in the labour force in 2030. Although we also observe this ‘catching-up’ effect, 
this result seems to be mainly driven by the relatively lower training costs in those Member 
States, as training expenses are scaled by country-specific labour cost levels. 

4. 

Conclusions 

While  the  green  transition  will  affect  the  entire  economy,  it  will  lead  to  significant 
transformations in some specific sectors, the so called ‘transforming sectors’, which  include 
mining  and  quarrying,  manufacturing,  energy  industries,  water  supply  and  waste 
management, construction and  transportation. The sectoral transformations will have an 
impact  on  the  demand  for  overall  labour,  skills,  occupations  and  wages  in  the  sectors. 
Ultimately, this may cause some workers to make sectoral labour transitions. In this paper, 
we employ the EU LFS data to gain more insight into sectoral and employment mobility in 
the ‘transforming sectors’, the sectors that are likely to be affected by the transition one way 
or other, in combination with other factors such as age, gender or participation in education 
and training. (68)  

Based on the data available, which unfortunately were discontinued in 2020, we found that 
on average across the whole economy, the rate of workers making year-on-year sector-to-
sector  transition falls  between  1.8  –  3.9  in the  EU  and  this  is  relatively  stable  over  time, 
following a slightly increasing trend around the year of 2016 in some Member States. From 
2018 – 2019, there was a net inflow of workers into all of the ‘transforming sectors’ except 
for mining and extraction in the EU. In all Member States, older workers make less sectoral 
transitions compared to younger workers, but no significant difference in sectoral transitions 
can be observed between men and women. Women are still heavily underrepresented in 
the ‘transforming sectors’. Although the share of female workers in energy industries has 
risen  over  the  past  decade,  it  amounted  to  only  26.7%  in  2023.  The  smallest  share  of 
women  can  be  found  in  the  mining  sector  (14%).  In  the  case  of  ‘energy-intensive 
industries’, (69) we find that workers in these industries overall make less transitions towards 
non-employment (inactivity or unemployment) than those working in other sectors.  

The  evidence  gathered  in this  paper  seems  to broadly  reflect the  sectoral  outlook  in  the 
changing  economy  in  the  green  transition  where  anticipated  employment  losses  are 
primarily  accumulated  in  mining  whereas  other  sectors  experience  mixed  (or  positive) 
employment changes in the long run. However, the analysis focuses on impacts of climate 
policies only, omitting any effects that the changing climate and increased occurrence of 
extreme  weather  events  themselves  may  have  on  economic  activity  across  different 
Member States, including on sectors that are more susceptible to these conditions such as 
tourism  and  agriculture.  Further  research  could explore  these  aspects  to  provide  the  full 
spectrum of changes in sectoral employment induced by the climate change and related 
mitigation  and  adaptation  policies.  It  is  also  important  to  recognise  that  several  other 
significant structural and other trends are working in parallel in shifting sectoral employment 
patterns, including cyclicality and digitisation (accelerated due to COVID-19). 

Contrary to the intuition, ‘energy-intensive’ industries that are generally considered as the 
most  ‘vulnerable’  sectors  into  decarbonisation  for  their  high  GHG  emissions,  have  seen 
their  workforce  flow  out  of  employment  significantly  less  than  other  sectors  in  the  past 

(68) Additionally,  at  the  detailed  sectoral  country-level,  there  were  some  instances  where  the  low  number  of  observations 
warranted notes about potential low reliability of results or even the removal of results to comply with LFS requirements.  

(69)  These are the sectors that are expected to face some degree of loss in demand or substantial recompositing of their 
workforce. The definition includes mining and quarrying, manufacturing of automotives, minerals, chemicals and metals.   

29 

 
 Fair Transitions Working Papers 

decade.  Anecdotal  evidence  from  some  Member  States (70)  can  suggest  that  the  higher 
incidence of trade union density in these sectors may be one of the possible explanations. 
Another plausible factor may be that these male-dominated sectors see relatively less flows 
out  of  employment  over  time  as  men  make  relatively  less  employment  transitions  than 
women (due to their lower participation in care). (71) However, it should be noted that our 
descriptive analysis finds no difference in the frequency of transitions that men and women 
make  between  sectors.  Yet,  it  is  in  some  of  the  ‘transforming  sectors’  that  new  job 
opportunities  are  expected  in  the  twin  green  and  digital  transition  context,  including 
engineering,  technician,  maintenance  and  installation  professions  in  clean  energy 
technologies production and roll out.  

Our paper also provides novel estimations on the additional amount of workforce needed 
and the associated training costs from renewable power generation deployment at Member 
State level in 2030. Our findings show that the additional installations of wind turbines and 
solar panels to deliver on the EU Green Deal targets would require about 130 000 to 145 
000 additional skilled workers in the EU, with associated investment in skills reaching EUR 
1.1 to 1.4 billion by 2030. This investment is about 1% of the average annual investment 
needs in power plants projected in Europe's 2040 climate target impact assessment report 
for the period 2031-2050 (European Commission, 2024c). Job creation nonetheless differs 
across  Member  States,  and  those  with  relatively  higher  shares  of  renewable  installed 
capacity today may present lower re-training costs per worker in 2030.  While we focus on 
sectors  related  to the  installation  of  wind  and  solar  power  generation  technologies  (e.g., 
construction  and  services  sectors),  future  studies  may  expand  the  sectoral  coverage  to 
assess job creation and re-training costs due to investments in other sectors in the EU (e.g., 
electric vehicles manufacturing) (72).  

Yet, while crucial in ensuring inclusion and productivity in the changing EU labour market, 
training  and  education  in  some  sectors  that  are  key  to  the  transition  towards  climate 
neutrality  is  lacking  behind  others.  While  energy  records  highest  rates  of  participation  in 
training and education out of the ‘transforming’ sectors, workers in mining and construction 
receive below-average training. Overall, participation in training in ‘transforming sectors’ is 
relatively similar across the different sectors per age group and follows a slightly increasing 
trend over time. Older workers receive least training across ‘transforming’ sectors. Although 
‘energy-intensive  industries’  are  more  exposed  to  employment  restructuring  in the  green 
transition,  only  10.9%  of  their  workers  received  training  in  2023  in  the  EU  against  an 
average  of  12.7%  in  the  whole  economy.  At  the  same  time,  growing  skills  and  labour 
shortages hamper hiring into new green job opportunities, including for occupations relevant 
in  construction,  energy production  and distribution  or transport  sectors which  are  key  for 
advancing EU climate ambitions. Boosting upskilling and reskilling efforts in these sectors 
are therefore most  urgently required  to  ensure a workforce  equipped  with the  necessary 
competencies, and increased attention on participation rates in these sectors, and namely 
in  construction  with  lowest  adult  learning  scores,  is  needed  to  avoid  protracting  skills 
shortages in the future.  

According to recent Commission assessment, re-skilling and up-skilling policies have been 
so far the most frequently used tool by Member States to navigate employment and social 

(70)  Duell et al. (2023). 

(71)  OECD (2024). 

(72)  Some studies are available on national assessment of employment projections in automotive manufacturing in the green 
transition. See Černý et al. (2022) and Umweltbundesament (2022) for analysis on Czechia and Germany where the car 
industry plays an important role. While marginal relative employment drop is typically found, findings also suggest that the 
shift  towards  electric  vehicle  manufacturing  will  result  in  job  upgrading  in  the  industry  (Černý  et  al.,  2022).  See  also 
Eurofound (2023) for horizontal analysis of sectoral employment changes resulting from ‘Fit for 55’ package and  2040 
climate targets impact assessment (European Commission, 2024c).  

30 

 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

outcomes  in  the  transition  towards  climate  neutrality. (73)  Taking  different  shapes  and 
centres of focus, often supported by EU funds such as the Just Transition Fund, Recovery 
and  Resilience  Facility  (RRF)  or  European  Social  Fund  Plus  (ESF+),  they  encompass  a 
wide range of measures to foster skills for the workforce. They include targeted training to 
promote  employment  of  workers  out  of  emission-intensive  sectors  or  into  green sectors, 
training  provisions  in  relevant  occupations   (74),  initiatives  to  green  and  broaden  relevant 
formal  or  non-formal  education  curricula (75),  programs  to  launch  or  adapt  national  skills 
anticipation  strategies  to  better  understand  future  demands  in  the  green  transition,  or 
conceptualisation of key labour market elements in the green transition (including definition 
of ‘green’ jobs or skills).  

But  ensuring  that  workers  are  left  with  good  employment  outcomes  in  the  economic 
transition cannot rely solely on skills. Promoting quality greener jobs in the labour market 
requires  a  comprehensive  policy  approach.  This  should  focus  on  employment  in  a  more 
well-rounded spirit, including on areas such as active support to quality employment and 
education (of underrepresented groups too). Policies should also promote hiring incentives 
in  greener  parts  of  the  economy, fair  and  favourable  tax-benefit  and  social  protection 
systems, and increasing working conditions to attract workforce into professions that are 
instrumental to a sustainable and resilient society. (76) This includes not only jobs in green 
sectors, but also in the so-called ‘white’ jobs, such as in healthcare, education or hospitality, 
that have been facing widespread shortages in recent years. 

Working  conditions  is  an  important  aspect  of  exploring  the  employment  changes  in  the 
transition towards climate neutrality. Recent foresight study by EU-OSHA (2023) finds that 
overall,  renewable  energy  production  carries  significantly  lower  occupational  health  and 
safety  risks  than  fossil-fuel  heavy  production.  Yet,  some  risks  emerge  in  demolition  and 
other  works  related  with  phase  out  of  the  old  production  plants. (77)  While  the  largest 
expansion of new green opportunities is mainly expected for middle-paying, middle skill jobs 
over the long run, (78) the category of occupations that has been found to grow the fastest 
so far also includes many high-skilled professions (including professionals and technicians) 
that tend to have  a  better  job  quality  advantage. (79)  Nevertheless,  working conditions  in 
‘green  jobs’  will  not  be  of  high  quality  by  default.  According  to  Eurofound  (2024b),  their 
quality is not homogeneous. While workers in high-skilled ‘green’ professions enjoy better 
working  conditions,  including  pay,  (80)  working  autonomy,  flexibility  of  working  hours  or 
training, (81), the low-skilled jobs created in the transition towards climate neutrality seem to 
be associated with lower pay, (82) and, in some sectors, including waste and management 
in circular economy, poorer health and safety conditions. In a similar vein, the impacts of 
climate  change,  such  as  a  rising  frequency  and  intensity  of  weather  extremes  (e.g. 
heatwaves, wildfires, storms, floods), pose health and safety risks, in particular in outdoor 
occupations  (e.g.  construction,  agriculture),  and  affect  labour  productivity,  especially  in 

(73)  Key messages from EMCO and SPC on the implementation of the Council Recommendation on ensuring a fair transition 

towards climate neutrality, 14 November 2023. 

(74) e.g. Ireland, Italy, Luxembourg and Sweden in construction and zero-emission buildings. 

(75) This includes vocational education and training. 

(76)  Recommendations 5-6 of the Council Recommendation on ensuring a fair transition towards climate neutrality. 

(77)  See the full report by EU-OSHA: Foresight-circular-economy-key-findings_en.pdf (europa.eu) 

(78)  SWD (2020) 176 final. 

(79)  OECD (2024). 

(80)  OECD (2024). 

(81)  Eurofound (2024). 

(82)  OECD (2024).  

31 

 
 Fair Transitions Working Papers 

vulnerable regions, including in the tourism sector. (83) To this end, the quality of green jobs, 
equal  opportunities,  and  job  creation  throughout  the  economy,  play  a  pivotal  role  for 
ensuring  a  decent  job  standards  in  the  context  of  the  changing  climate  and  green 
transformation. 

(83)  García-León et al. (2021).  

32 

 
 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

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37 

 
 
 
 
 
 
 
 
 
 
 Fair Transitions Working Papers 

Annex 

Figure 14: Age distribution in ‘transforming sectors’, and sectoral transitions across the 
whole economy, by Member State, 2022 

Sources: Own calculation based on EU LFS micro-data 2019-2022. (84) 
Notes:  The  height  of  the  bars  indicates  the  share  of  workers  employed  in  ‘transforming  sectors’  by  age  groups.  Colour 
indicates sector-to-sector mobility per age group, calculated based on sectoral transitions across all sectors of the economy. 
Grey indicates insufficient observations for reliable estimates. No sectoral transition data is available for Ireland. 

(84) The  data for sectoral transitions  is  calculated  based  on  individuals  from  different  age  groups  across  all sectors  of the 
economy  (not  just  the  ‘transforming  sectors’),  measuring  the  proportion  of  workers  that  changed  their  sector  of 
employment between 2018-2019. As mentioned above, 2019 was chosen as the reference year because it is the most 
recent year for which reliable sectoral transition data could be calculated.  It is important to note that the data on these 
transitions, based on the LFS 2019, comes with certain limitations: Around half of the observations related to age-based 
mobility come with reliability warnings as defined by Eurostat. Additionally, the grey bars in Figure 14 indicate age groups 
in Member States for which the number of observations related to sectoral mobility fell below the minimum reliability limit 
and which are not sufficiently reliable for publication. 

38 

 
 
 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

Table 2: Median age in the ‘transforming sectors’ per Member State in 2022 

 Member States 

(C) 
Manufacturing 

(B) 
Mining 
and 
quarrying 

(F) 
Construction 

(H) 
Transportation 
and storage 

(D) 
Electricity, 
gas,  steam 
and 
air 
conditioning 
supply 

(E)  Water 
supply, 
sewerage, 
waste 
management 
and 
remediation 
activities 

AT 

BE 

BG 

CY 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IT 

LT 

LU 

LV 

PL 

PT 

RO 

SE 

SI 

EU27 

45 

36 

47 

34 

44 

51 

45 

39 

47 

38 

40 

43 

47 

45 

44 

NA 

40 

41 

49 

46 

40 

43 

43 

40 

44 

45 

43 

44 

46 

43 

44 

44 

43 

43 

41 

42 

45 

43 

46 

44 

42 

44 

44 

45 

43 

44 

43 

42 

47 

50 

42 

44 

45 

44 

41 

41 

43 

48 

46 

43 

43 

39 

47 

46 

45 

49 

46 

46 

44 

45 

43 

48 

42 

46 

50 

50 

50 

45 

42 

44 

44 

46 

49 

49 

41 

54 

45 

50 

45 

43 

46 

46 

41 

40 

44 

43 

44 

41 

43 

46 

46 

42 

41 

42 

43 

46 

43 

46 

41 

41 

46 

43 

40 

42 

43 

44 

43 

47 

43 

45 

47 

49 

46 

46 

43 

45 

44 

46 

46 

44 

41 

49 

43 

44 

43 

46 

45 

45 

Source: Own calculations based on EU LFS micro-data (2022 wave). 
Notes: Data not available for CZ, IE, MT, NL and SK. 

39 

 
 
 
 Fair Transitions Working Papers 

Figure 15: Gender composition in ‘transforming sectors’ and sectoral transitions across the 
economy, by Member State, 2022 

Source: Own calculations based on EU LFS micro-data 2022. 
Notes: Colour indicates sector-to-sector mobility for men vs. women, calculated based on sectoral transitions across all sectors 
of the economy. Source: EU LFS 2019-2022. No sectoral transition data is available for Ireland. 

40 

 
 
Estimating labour market transition and skills investment needs of the green transition – a new approach 

Figure 16: Yearly percentage of workforce making sector-to-sector transitions in the overall 
economy, 2010-2020 

Source: Own calculations based on EU LFS micro-data (2010-2020 waves).  
Notes: Percentages are calculated based on transitions across all sectors of the economy at NACE 1-digit level. The green 
line indicates the average. (85) 

(85) For some Member States, the percentage of labour transitions is missing for certain years. This is because 
the number of observations of individuals making sector-to-sector transitions in this particular year fell below the 

41 

 
 
 
 Fair Transitions Working Papers 

Figure 17: Percentage of workers leaving to another sector in different years 

Source: Own calculations based on LFS microdata (LFS, 2010/2015/2019). 
Notes: The figure displays outward sectoral mobility, i.e., the share of workers that leaves each of the sectors because they 
have found employment in another sector. 

Figure 17 provides insight regarding the outward sectoral mobility of workers per sector in 
different years. Additionally, the figure serves as a kind of robustness check for the method 
and data used to calculate sectoral mobility in Section 2 of this paper. As described in Box 
1, the calculations for sectoral mobility rely on LFS microdata and in particular an individual’s 
self-reported current sector of employment as well as their sector of employment one year 
prior. Information on both the current and past sector of employment was not available for 
all individuals, which in some instances led to small sample sizes. As a result of these small 
sample sizes, some of the results in this report could not be displayed, or are displayed with 
a  reliability  warning,  in  accordance  with  Eurostat  guidelines  for  LFS  microdata.  Hence, 
Figure 17 visualises outward sectoral mobility in different years so that the results can be 
cross-checked  with  other  data  sources.  The  results  in  the  figure  display  overall  lower 
sectoral mobility in 2015 compared to 2010 or 2019. This is in line with the data in the left-
hand  panel  of  Figure  7  in  Section  2.3,  which  relies  on  a  different  data  source  and 
methodology  (Eurostat  experimental  statistics  on  labour  market  transitions).  Moreover, 
Figure 7 displays a spike in sectoral transitions in 2019, which is also mirrored in the results 
in Figure 17. This supports the robustness of the results for sectoral labour transitions in 
‘transforming sectors’ in Section 2.  

LFS reliability limit for this Member State and hence the results cannot be displayed. The results for Romania 
in 2010 and 2011 were removed from Figure 16Error! Reference source not found. as the percentages for 
these years were around 30%, which is an entirely different order of magnitude compared to other years for 
Romania or the results for other Member States. Hence, the results for Romania in 2010 and 2011 were treated 
as outliers and also removed from the calculations for the average over time.  

42 

 
 
 
 
 
 
 
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