Social situation monitor : quality of green jobs.
Date: 2021-01-28
Institutions: Directorate-General for Employment, Social Affairs and Inclusion
Subjects: EU Member State, green economy, humanisation of work, labour market, social indicator, social situation, vocational training, work-life balance, working conditions

Social Situation Monitor
Quality of Green Jobs 

Bob Hancke, Toon Van Overbeke, and Nikolas Neos 
July – 2020 

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Directorate-General for Employment, Social Affairs and Inclusion 
Directorate A — Employment and Social Governance 
Directorate A, Unit EMPL. A4 — Thematic Analysis 

Contact: Katarina Jaksic 

E-mail:  katarina.jaksic@ec.europa.eu

European Commission 
B-1049 Brussels

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Social Situation Monitor
Quality of Green Jobs 

Manuscript completed in July 2020  

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PDF 

ISBN 978-92-76-28929-6

doi: 10.2767/001616

KE-02-21-046-EN-N

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TABLE OF CONTENTS 

TABLE OF CONTENTS ................................................................................................... 5 
INTRODUCTION ................................................................................................ 6 
1. 
2.  METHODOLOGY AND DATA ................................................................................ 7 
3.  OVERALL QUALITY OF WORK ............................................................................ 9 
4.  SOCIO-ECONOMIC SECURITY (SES) ................................................................ 14 
5.  EDUCATION AND TRAINING ............................................................................ 20 
6.  WORKING CONDITIONS .................................................................................. 30 
7.  WORK-LIFE BALANCE AND GENDER ................................................................. 44 
8.  CONCLUSION .................................................................................................. 53 
REFERENCES .......................................................................................................... 56 
ANNEX ................................................................................................................... 57 

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1. 

Introduction 

In  the  last  two  decades,  following  the  political  attention  to  environmental  concerns, 
including carbon emissions and climate change, plastic pollution, and generally the need 
to  reduce  our  reliance  on  raw  materials  to  create  more  ecologically  sustainable  and 
balanced  economies,  labour  markets  have  started  to  change  to  reflect  those 
preoccupations. By some estimates green tasks in existing jobs and new, green jobs have 
emerged  and 
In  a  SSM  Research  Note 
that developed a taxonomy for green jobs in Europe (Bowen & Hancké 2019), which was 
the basis for the analysis here, the authors found that a large proportion of jobs in the EU 
had  a  green  component,  and that  the turn  towards  a  more  sophisticated manufacturing 
and service-oriented economy was likely to accelerate this process. Many companies, trade 
unions, local and national governments and consumer organizations have expressed their 
support for a just green transition and clamour for a speedier process. 

increased  substantially  everywhere. 

Yet  such  a  transition  is  not  without  adjustment  costs  and  the  faster  it  takes  place,  the 
likelier  it  is  that  costs  are  concentrated  among  specific  regions  and  sectors,  eliciting 
responses  from  small,  sometimes  well-organised  groups  in  society  that  might  raise 
important objections. If labour markets change in this regard, what happens to the number 
of  jobs  and  especially  the  quality  of  jobs?  While  generally  supportive,  trade  unions  and 
other  representatives  of  employees  have  expressed  some  concerns  about  a  rapid  and 
pervasive  transition  to  a  green  economy  that  does  not  explicitly  take  into  account  the 
effects  on  jobs,  including  wages  and  working  conditions  (see  Coutrot  &  Gadrey  2012; 
Galgóczi 2015; Galgózci 2019).1  

 This research note addresses that question through an examination of the situation today: 
how do green jobs compare in terms of job quality, both relative to brown jobs and between 
different types of green jobs, in countries and in sectors? This question, at the intersection 
between two major recent socio-economic initiatives – the European Green Deal and the 
European Pillar of Social Rights (also referred to as the (European) Social Pillar henceforth) 
– is a central preoccupation for many Europeans and their governments, precisely because 
of the possible distributive consequences associated with a green transition. Our field of 
study in this research note follows directly from the dimensions of quality of employment 
as  defined  by  Eurofound:  socio-economic  security,  education  and  training,  working 
conditions and representation, and work-life and gender balance. All these dimensions are 
also covered in the 20 principles of the European Pillar of Social Rights2.  

Our main findings can be summarised as follows: on the whole, the differences between 
green  and  brown  jobs  are  relatively  small,  and  this  relation  has  broadly  speaking  not 
changed  much  since  2005.  The  same  is  true  for  different  types  of  green  jobs.  If  we 
distinguish between jobs with an increased demand for green tasks (ID), jobs where green 
tasks  require  increased  skills  (IS)  and  new  green  jobs  (NG)  (see  Box  1  below  for 
definitions),  quality  of  work  in  these  three  types  has  evolved  along  stable,  similar  lines 
(see box 1 for definitions of these green jobs). Against the background of deep concern 
about the effect of greening the economy on employment (especially in the uncertain post-
Covid 19 world), this is a surprising outcome.  

This  research  note,  which  will  develop  this  insight  in  more  detail,  is  organized  in  three 
parts.  We  start  with  a  conceptual  and  methodological  section  2,  which  lays  out  key 
definitional and technical issues on how we see the key variables, how they are measured, 
and how we use different datasets to answer the actual question above, starting from the 

1Other concerns include where and how work changes, what the impact of the green transition on 
occupational  health  and  safety  might  be  and  how  to  ensure  that  the  European  Green  Deal  and 
enhancing job quality in new activities evolve alongside each other  
2https://ec.europa.eu/commission/priorities/deeper-and-fairer-economic-and-monetary-
union/european-pillar-social-rights_en 

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results of the analysis in Bowen & Hancké (2019). We rely on the European Pillar of Social 
Rights  for  our  approach  to  quality  of  work,  and  to  identify  the  four  broad  categories 
mentioned earlier. The next five sections (3-7) unpack quality of work in aggregate and in 
each of these four dimensions in ever more granular detail. The final section 8 discusses 
the findings and concludes.  

2.  Methodology and Data  

In  order  to  measure  the  quality  of  work  in  Europe  we  closely  follow  the  conceptual 
framework  set  out  in  the  Eurofounds  model  (see  IPOL-EMPL  2009):  socio-economic 
security;  education  and  training;  health  and  safety  at  work;  and  work-life  and  gender 
balance. Each of these four job quality subdimensions is itself composed of a number of 
indicators. (Table A1. in the appendix gives an overview of the indicators).  

We use survey data in order to calculate individual, country and sectoral level scores on 
each of these parameters. The data used here stem from the European Working Conditions 
Survey (EWCS) and are transformed in five steps. First, we identify questions that capture 
elements of each indicator (see table A1 in the appendix for reference). We then code, and 
where necessary recode, the answers to these questions on a scale from 0 to 100, where 
0  is  the  worst  possible  outcome  and  100  represents  the  best-case  scenario.  The  coding 
used  here  also  reflects  the  ordinal  scale  of  the  answers  found  within  the  EWCS  (for 
example,  if  a  question  has  five  possible  answers  then  the  scale  would  run  0-25-50-75-
100). The third step is to compute the scores on each subdimension of QWL. This is done 
by taking the mean of all its constitutive questions. Finally, we generate the overall quality 
of work indicator by taking the mean of the four subdimensions. We also generate sector 
and country means for all these dimensions in order to allow for easy comparison. As a 
result, throughout the paper most figures score results between 0 and 100. However, we 
also include some graphs which score the difference in quality between green and brown 
job  for  a  given  country  or  sector.  These  graphs  therefore  range  between  -100  and  100 
where a positive score signifies an advantage for green jobs and vise versa. We think such 
graphs give quicker and more intuitive insight into the relation of these two types of jobs.  

This approach has a number of advantages, perhaps most notably that it offers conceptual 
flexibility  to  researchers.  It  allows  users  to  gauge  job  quality  from  a  micro  to  a  macro-
level, while the individual indicators can easily be restructured depending on the desired 
questions. 

We construct the data so that comparisons both in time and across space are possible. Our 
analysis covers 36 countries for the period 2005-2015, including the EU-27 and the UK (an 
EU  member  at  the  time  of  data  collection)  as  well  as  a  number  of  non-EU  countries 
(Norway,  Turkey,  Northern-Macedonia,  Switzerland,  Serbia,  Kosovo,  Albania  and 
Montenegro).  We  present,  as  much  as  possible,  the  ‘national’  results  for  all  countries 
included in the EWCS data set, but in the rest of this research note we only use data for 
the EU27 + UK for the sectoral analyses between 2005-15.  

Substantial  changes  in  each  wave  of  the  EWCS  questionnaire  make  direct  comparisons 
across the different periods difficult; cursory analysis suggests problematic, method-driven 
variation in the results across the different waves. We circumvent this problem by creating 
three  different  versions  of  all  the  indicators:  one  based  on  the  2005  version  of  the 
questionnaire, one based on the 2010 version and finally one on the 2015 version. Each 
indicator is calculated solely using questions that were present in the survey during that 
particular  year,  which  allows  for  analysis  with  future  waves  based  on  the  benchmark 
provided by those questions. As a result, the 2005 indicator is the most compact indicator 
(in terms of the smaller number of questions it contains) but because it is the one with 
most questions in common across the three waves, we can use it to assess the evolution 
from  2005.  The  2010  indicator  is  much  broader  (it  only  omits  collective  interest 
representation) and allows us to compare the 2010 with the 2015 wave. Finally, the 2015 
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indicator is the most comprehensive one, but it does not allow any inferences over time. 
We have decided not to go back further than 2005 because substantial changes in survey 
structure would severely limit the credibility of such a comparison. As a consequence of 
the  substantive  differences  underlying  these  indicators  the  results  of  the  2015  indicator 
will show some variation with the analysis over time. 

The goal of this paper is to assess the relative quality of green jobs versus brown jobs, as 
well  possible  differences  between  different  types  of  green  jobs.  ‘Brown’  jobs  are  those 
occupations that have not seen any significant change in their tasks in the direction of de-
carbonisation and sustainability, while ‘green’ jobs are those that have witnessed such a 
shift. In addition, we follow Bowen and Hancké (2019) and identify three different types of 
green jobs; ‘Increased Demand’, ‘Enhanced Skills’ and ‘New and Emerging’, see Box 1. 

Box 1. Types of green jobs  

Source: Bowen & Hancké 2019 

Following on from work done by the US Department of Labor, Bowen and Hancké (2019) 

have  identified  three  distinct  types  of  jobs  that  are  connected  with  the  growing  green 

economy: 

1)  Green Increased Demand (Green ID) jobs are existing jobs that are expected to 

be in high demand due to greening, but do not require significant changes in 

tasks, skills, or knowledge. These jobs are considered as indirectly green because 

they support green economic activity, but do not involve any specifically green 

tasks. (e.g. bus drivers, counted in the occupational category ‘bus drivers, transit 

and intercity.’) 

2)  Green Enhanced Skills (Green ES) jobs are existing jobs that require significant 

changes in tasks, skills, and knowledge as a result of greening. (e.g. electric 

vehicle electricians: counted in the occupational category ‘automotive speciality 

technicians.’) 

3)  Green New and Emerging (Green NE) jobs are unique jobs (as defined by worker 

requirements) created to meet the new needs of the green economy. (e.g. fuel 
cell engineers). 

The operationalisation of these categories also follows the methodology outlined in Bowen 
and Hancké (2019) using ISCO_88 and ISCO-08 job categories (derived from O*NET) in 
order to  distinguish  between  green  jobs  and  brown jobs  on the  one hand,  and  between 
different types of green jobs on the other (see table A2 for reference). Note that, in this 
framework, job groupings do not need to be uniquely identified with a single green job’s 
category.  ISCO-08  codes  are  used  to  code  waves  2010  and  2015  of  the  surveys  while 
green jobs in the 2005 wave are identified using the corresponding ISCO-88 codes.  

It should be noted, however, that there are some limitations to applying this method to 
the EWCS. While O*NET offers information at the four and three-digit ISCO level, the EWCS 
only  reports  two-digit  ISCO  codes.  While  this  does  not  pose  serious,  problems  for  the 
explanatory power of the green/brown distinction, it does impair our analysis at the level 
of green sub-types. That is, much of the variation between these subtypes is driven by the 
differentiation within certain job categories on the basis of a four or three-digit ISCO code. 
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The aggregation of information, which happens at the two-digit level, therefore, washes 
away  most  of  the  relevant  information.  In  short,  the  two-digit  ISCO  codes  do  not  offer 
much leverage to types of jobs from each other, as it was done in previous studies. This is 
a substantial drawback and any analysis should therefore be read with caution.  

A final limitation regarding the job categorisations is the lack of observations for the Fishing 
and the Mining and Quarrying sectors on some indicators. These sectors only represents 
tiny  proportions  of  all  responses  in  our  dataset;  the  results  is  that  we  have  insufficient 
observations to make a meaningful comparison between green and brown jobs from 2005 
onwards. 

There  are  at  least  two  further  limitations  that  apply  to  this  research.  Firstly,  while  the 
indicators used here are the result of a holistic assessment of the quality of work, the data 
we present here are necessarily an imperfect approximation. We have used a wide range 
of questions for all dimensions and sub-indicators in order to reflect the complex nature of 
these  concepts.  However,  limitations  posed  by  data  availability  and  the  substantive 
composition of the surveys (particularly in terms of gender and workplace representation) 
mean our assessment is not as wide-ranging as we would have hoped.  

Secondly, the data used in this paper are the product of a subjective and highly context-
driven data collection process. The EWCS is a valuable source which gives us a good insight 
into how Europeans think about their own work. However, these surveys also have some 
drawbacks. Not only is it possible for respondents to give false/wrong answers (this might 
happen particularly when sensitive questions are asked) but many responses depend to a 
large  degree  on  subjective  interpretation,  meaning  they  may  vary  significantly  along 
geographic, religious, cultural, social and gender lines.  

A final limitation has to do with the aggregation of data into a single indicator. Like any 
indicator, aggregation has it benefits and drawbacks. On the one hand our indicator allows 
us to make a good inference about (perceived) job quality in Europe. On the other hand, 
aggregating  necessarily  means  a  loss  of  granularity  of  information.  As  such,  ‘positive’ 
results can potentially mask some underlying ‘negative’ results, and vice versa, which need 
to be taken into account as well.  

Combined this implies that the results presented here are not a definitive assessment of 
job  quality  in  Europe  but  rather  a  best  possible  approximation  based  on  subjective  and 
self-reported data (see IPOL-EMPL 2009). 

3.  Overall Quality of Work 

As we outlined earlier, the definition of job quality (QWL) has four main parameters. Before 
examining each of the four dimensions of quality of work (QWL) for this study in detail, we 
will present overall QWL scores in this section, which are averages (mean) of the individual 
scores on the different dimensions. These scores can hide a lot of variation, and may even, 
as with all averages, skew some of the findings as a result of significant outliers on one 
dimension. But they are, with these caveats, useful as a starting point for the analysis.  

We start with Figure 1.a, which gives the raw differences between green and brown jobs 
in different European countries in 2015. As is immediately obvious, differences between 
countries can be relatively important (a ten percentage point spread between the lowest 
and  the  highest  score),  while  differences  in  the  quality  of  jobs  in  green  versus  brown 
employment are, on the whole, relatively minor. In about half of the countries brown jobs 
score slightly higher, in about a third green and brown jobs score roughly the same and in 
the  remaining  quarter  green  jobs  score  higher.  While  the  Nordic  countries  have  higher 
green  scores,  a  few  further,  though  admittedly  weaker,  patterns  can  be  found  in  the 
remainder: old member states often seem to have higher green scores while higher brown 
job scores seem to be associated with new member states. QWL scores in EU-15 countries 
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are more or less evenly balanced: half of the member states record higher QWL scores in 
green  than  in  brown.  EU  member  states  that  became  capitalist  democracies  after  1989 
exhibit a slightly different profile: not only are there fewer member states with higher QWL 
scores for green jobs in 2015 (4 out of 11), the values for brown jobs are also higher (ie 
the difference between green and brown jobs is more negative). The variation in labour 
market arrangements in old and new member states seems to run through many of the 
subsequent more detailed analyses, which lends credence to this view.  

Figure 1 : Job Quality by Country 

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Figure 2 : Difference in Quality between Green and Brown Jobs and Country (2015)  

Figure 3 : Job Quality by Country (2005 – 2015) 

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Figure 3 presents the evolution of green and brown jobs in 2015 (the last year for which 
systematic survey data are available). The overall image is one of relative stability: most 
curves reporting overall job quality are flat or very slightly rising for both green and brown 
jobs; only in Germany and Romania did overall quality of green jobs fall slightly, while in 
France, Lithuania and the UK one or both rose slightly. 

Figure 4 reports quality of work in different types of green jobs: increased demand (ID), 
increased skills (IS) and new and emerging green jobs (NG). The evolution of job quality 
by sector and between 2005 and 2015 suggests a similar conclusion of relative stability, 
with two exceptions that will show up regularly in the balance of this research note: a sharp 
drop in job quality (in all types of green jobs in the fishing sector) and a rise in all three in 
the  education  sector.  The  same  differentiation  between  types  of  green  jobs  across 
European countries is reported in Figure 5: again, with very few exceptions the evolution 
of job quality over time is relatively stable for all three categories of green jobs, or slightly 
positive, with very few drops in any of the three categories (with the surprising exception, 
perhaps, of Germany). 

The  final  review  of  the  composite  job  quality  indicator  is  presented  in  Figures  5-6.  The 
difference between green and brown jobs in the 16 NACE sectors in 2015 (figures 6 and 7) 
shows some variation, with the financial sector, energy and water, and transport as cases 
where the quality of green jobs is considerably lower than that of brown jobs (for Mining 
and  Fishing  insufficient  data  are  available).  This  is,  as  can  be  deduced  from  Figure  8, 
primarily a result of the increase in brown job quality in that sector.  

Figure 4 : Job Quality by Green Type and Sector (2005-2015)  

Concluding this first approach to the question, the most remarkable observation, and which 
will also reappear in the more detailed analyses of sub- indicators of quality of work life 
(QWL) is that the differences between green and brown jobs are not very large, are not 
necessarily very systematic, and that they appear both to have been quite stable during 

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the  first  two  decades  of  the  21st  century.  The  next  four  sections  will  develop  a  parallel 
study  of  the  different  dimensions  of  QWL  and  the  different  sub-indicators  that  we  have 
isolated  for  analysis.  We  start  with  (material)  socio-economic  security,  followed  by 
education and training, working conditions and work-life balance including gender issues.  

Figure 5 : Job Quality Sector (2015) 

Figure 6 : Job Quality by Sector (2005 – 2015) 

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4. 

Socio-economic Security (SES) 

The  picture  for  overall  socio-economic  security,  aggregating  the  different  constituent 
indicators — job security and earnings — are captured in figures 7 – 10. The main take 
away from these descriptive data is that today (2015, the latest year for which consistent 
data are available) SES is at roughly two-thirds (around 65% of respondents consider it 
sufficient or high) and that differences between green and brown jobs are relatively small 
in general. importantly, differences that exist are almost always in favour of brown jobs. 
This probably reflects the fact that carbon-intensive jobs are older, more stable (almost by 
definition in our case, since green jobs have changed or are new) and therefore are more 
institutionalised  in  ‘traditional’  dimensions  that  are  reflected  in  standard  employment 
security and wage indicators. Figure 7 summarises the situation for 2015. Scores for brown 
jobs are frequently higher than for green jobs, but only in France and Latvia do they exceed 
5%.   

These observations do not change much when we examine the evolution of quality of work 
in different countries and sectors. figure 8 reports the evolution of SES for the period 2005-
15. With very few exceptions, these curves are flat and stable around the 65% level. Drops 
in SES only exist in Lithuania, Luxembourg, Austria, Croatia and Albania. Moreover, there 
is  relatively  little  difference  in  the  SES  scores  for  different  types  of  green  jobs  across 
Europe: increased demand for green tasks (ID), increased skills (IS) and new green jobs 
(NG) all have roughly the same SES scores everywhere. Figure 9 reports parallel data for 
the 16 NACE sectors of the EU27 + UK (an EU member state at the time of data collection). 
The basic findings are very similar. Self-reported SES is stable almost everywhere around 
the  65%  level  over  the  decade  between  2005  and  2015,  with  only  fishing  reporting  an 
important drop. Green and brown jobs also follow a roughly similar pattern, and there are 
few differences between the types of green jobs (ID, IS and NG). Only fishing is slightly 
different: SES scores for NG are stable, while the others fall. 

Figure 7 : Difference in SES of green and brown jobs by country (2015) 

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Figure 8 : Difference in SES of green and brown jobs by country (2005 - 2015) 

Figure 9 : Difference in SES of green and brown jobs by sector (2005 - 2015) 

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Figure 10 : SES by green type and sector (2015) 

4.1  Income Security 

Unpacking the aggregate SES indicator into its constituent elements, income security and 
job security, yields a slightly different picture in some respects. First of all, in 2015 income 
stability, measured as perceived income adequacy, is higher in brown jobs than green jobs 
in 12 of the 16 NACE sectors, and is more or less equal across brown and green jobs in the 
remaining four (Figure 11). This probably reflects (again) that brown jobs are older and 
therefore have a higher degree of institutional protection than newer (or modified) green 
jobs.  The  evolution  over  time,  as  presented  in  Figure  12  suggest  that  income  stability 
remains  at  roughly  70%  in  the  majority  of  sectors  rises  for  green  jobs  in  fishing  and 
finance,  while  it  falls  quite  significantly  in  brown  jobs  in  fishing  and  green  jobs  in 
construction. 

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Figure 11 : Adequate earning by sector (2015) 

Figure 12 : Adequate earning by sector (2005 – 2015) 

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4.2  Job Security 

An  examination  of  job  security  yields  a  similar  overall  picture  but  with  some  minor 
variations.  In  2015,  there  were  relatively  few  differences  in  this  respect  between  green 
and brown jobs — green jobs are usually perceived to be slightly more secure but not by 
much.  The  only  exceptions  are  Romania  and  Hungary,  where  brown  jobs  have  higher 
scores.  Importantly,  though,  the scores  on  the  indicator  are,  independent  of  the  green-
brown distinction, somewhat lower, between 50 and 60%, than for other indicators in this 
category.  

Job security by country 2005-15, in Figure 13, is in line with the general trend: relatively 
small differences between green and brown jobs, usually a flat or slowly rising curve over 
time. There are a few exceptions: Greece and Turkey, for example, where both rise, Malta, 
where  both  fall,  and  Cyprus,  where  both  converge.  The  same  applies  more  or  less  to 
sectors: between 2005 and 2015, the self-reported sense of job security has been mostly 
flat  or  has risen  only  slightly  between  2005  and  2015. The  reported  difference between 
green and brown jobs is relatively small as well (figure 14). Only fishing (an initial sharp 
rise followed by a steep decline in job security), construction (a significant decline in brown 
jobs) and work in extraterritorial organisations (a decline in job security for brown jobs) 
deviate from that general picture. Finally, the graphic representation of differences in job 
security  between  green  and  brown  jobs  (in  figure  15)  summarises  the  situation  today: 
there  are  mostly  small  differences  between  green  and  brown  jobs  with  respect  to  job 
security.  In  real  estate,  manufacturing  and  education,  however,  job  security  scores  of 
green  jobs  are  significantly  higher  than  in  other  sectors  which  is  somewhat  surprising, 
especially for manufacturing, where all jobs, but older ones in particular, would be expected 
to benefit from strong employment protection.  

Figure 13 : Career and job security by country (2005 – 2015) 

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Figure 14 : Career and job security by sector (2015) 

Figure 15 : Career and job security by sector (2005 – 2015) 

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4.3  Socio-economic Security: Discussion 

Perhaps  the  most  important  results  from  this  analysis  are  that  the  distinction  between 
green  and  brown  jobs  is  of  little  significance  when  assessing  traditional  but  important 
dimensions  of  socio-economic  security  examined  here  —  job  an  income  security.  These 
differences do not matter much today, and they did not matter much in the mid-2000s. 
Even the more granular conceptual differences between different types of green jobs (ID, 
IS and NG) seem not to yield much significant variation in terms of self-reported perceived 
job security. If differences emerge, they are usually in favour of brown jobs. That should 
not  be  a  surprise,  as  these  are  the  types  of  (usually  older)  jobs  that  have  built  up 
institutional mechanisms of income and job protection in the second industrial wave during 
the post-war era, and which is very difficult to change without major social conflict. That, 
of course, casts something of a question mark over the relatively small differences between 
green and brown jobs: it is quite likely that green jobs have simply been able to adopt the 
protective  measures  of  brown  jobs  in  the  sector  (through  some  form  of  erga  omnes 
clauses).  However,  that  does  not change the most  important  conclusion  of  this  section: 
both green and brown jobs are, have been and remain roughly equal in terms of basic job 
and income security.  

5.  Education and Training 

For the purposes of this research note, and following the definitions in the European Pillar 
of  Social  Rights,  the  broad  category  of  education  and  training  is  treated  here  in  two 
dimensions:  complexity  of  work  and  development  of  skills  through  training;  and 
employability (new skills acquired through on the job training).  

The  overall  category Education  and  Training  (E&T)  in  2015  across Europe  is reported in 
Figures  16  and  17  What  is  immediately  obvious  is  that  there  are  very  large  differences 
between countries: the proportion of respondents confirming E&T related outcomes varies 
between less than 40% in Greece and approaching 60% in Denmark, the UK and Ireland, 
and most other West European countries. But there are sometimes important differences 
between  green  and  brown  jobs:  brown  jobs  score  higher  in  Hungary,  Lithuania,  Poland, 
and  Malta,  while  green  job  scores  are  higher  or  equal  elsewhere.  A  pattern  is  not 
immediately visible, but it would appear as if both level of E&T generally and higher training 
in green jobs is more prevalent in the old member states. That said, Figure 16 suggests 
that the largest differences between green and brown jobs (in favour of green jobs) are 
not geographically. Figure 18 gives the evolution of E&T in European countries between 
2005 and 2015. The evolution in the majority of countries is relatively flat for both green 
and brown jobs, and the differences are not large if they exist. Yet in a large minority, the 
patterns change over time, even though, green and brown jobs very rarely follow different 
trajectories  –  only  the  Czech  Republic  stands  out,  really,  reflecting  the  current  large 
difference in favour of E&T in green jobs today (Figure 20). 

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Figure 16 : Differences in E&T between green and brown jobs by country (2015) 

Figure 17 : E&T by country (2015) 

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Figure 18 : E&T by country (2005 – 2015) 

Figure 19 : E&T by sector (2015) 

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Figures 18 – 19 offer similar data on sectors. Between 2005 and 2015. E&T in green and 
brown  jobs  followed  different  paths  in  fishing,  energy,  construction,  finance,  and 
extraterritorial organisations (Figure 19). A clear pattern in favour of brown or green jobs 
fails  to  emerge;  however,  Figures  20  and  especially  21  suggest  that  E&T  now  is 
considerably more present in green than in brown jobs. Only finance and the energy and 
water sectors show a net score in favour of brown jobs.  

Figure 20 : E&T by sector (2015) 

Figure 21 : Differences in E&T between green and brown jobs by sector (2015) 

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Looking at types of green jobs (increased demand ID, increased skills IS and new green 
jobs  NG),  as  reported  in  Figure  22,  we  see  that  in  most  countries  the  three  curves  are 
more or less flat and run more or less in parallel. But there are a few important exceptions. 
Germany  has  witnessed  a  large  rise  in  IS  and  NG  2005-10,  followed  by  an  equally 
important  drop  between  2010  and  2015.  In  south-eastern  Europe  (Greece,  Cyprus, 
Romania and Turkey) ID rises while IS and NG fall. Generally, there are very few instances 
where IS and NG green jobs score higher on education and training, and equally very few 
where the E&T scores of ID, usually associated with older jobs, fall.  

Sectoral  differences  between  green  and  brown  jobs,  in  turn,  are  not  very  pronounced. 
Figure 22 reports no cases with significant divergence between the three types over time: 
practically  all  curves  are  flat  and  run  in  parallel.  Only  the  fisheries  sector  has  a  slightly 
different profile, with drops in IS and NG.  

Figure 22 : E&T by type of green job and sector (2015) 

5.1  Complexity of Work and Skill Development 

The first sub-dimension of E&T deals with the claims on intellectual abilities and skills in 
jobs and their development (shorthand ‘Development’ and abbreviated DEV below). The 
2015 distribution of DEV in green and brown jobs across different European countries is 
presented in Figure 23. One thing is immediately obvious: the scores exhibit a tremendous 
range: fewer than 40% of respondents in Greece think their jobs are complex and require 
(or are offered) training, while almost 65% of Finns think that is the case; many jobs in 
Europe remain, in contrast to the ‘knowledge economy’ and life-long learning manifestoes 
of many governments, relatively undemanding in intellectual terms. The contrast between 
green and brown jobs is also quite enlightening. In 20 European countries, including many 
that emphasise skill development and thus score high on training in general, brown jobs 
receive more training than green jobs. This could reflect the fact that training is both more 
easily defined for brown jobs and institutionally protected in collective agreements in such 
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more traditional job and sectors. It could also be that green jobs simply have a different 
skill profile, where training is done not in workplaces but in formal learning and as a result 
of ‘job-hopping’.  

Figure  24,  which  presents  the  basic  data  by  sector  for  2015,  suggests  that  in  about  a 
quarter of the sectors (including some large ones such as finance and education) brown 
jobs are both more complex and are subject to more training than green jobs. But in about 
ten sectors the opposite is true. From the data it is unclear if the skills required and the 
training offered is actually directly related to the green v. brown character of the job, but 
some correlation is likely (and to some extent expected), since these are newer jobs, and 
newer  jobs  often  rely  more  on  conceptual  activities  than  purely  on  execution  of  tasks 
conceived elsewhere.  

The development of skills between 2005 and 2015 is presented in Figures 25 (by country) 
and by sector (Figure 26). Things have changed little for skill development in green and 
brown jobs in different countries, as Figure 25 suggests. The curves are relatively flat over 
the ten-year period everywhere, and both lines usually develop in parallel. Yet there are a 
few exceptions: the Czech Republic, where the relative orders have inverted in favour of 
green jobs, Germany and France where skill development rises in all jobs, and Albania and, 
surprisingly given its international reputation in the area of skills, Switzerland, where skill 
development falls in all jobs.  

Figure 23 : Skills and development by country (2015) 

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Figure 24: Skills and development by sector (2015) 

Figure 25 : Skills and development by country (2005 – 2015) 

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Figure 26 : Skill and development by sector (2005 – 2015) 

5.2  Employability 

The second E&T dimension examined here is the extent to which employees estimate that 
their  jobs  would  allow  them  to  find  jobs  elsewhere  —  employability.  Figure  27,  which 
presents  the  data  for  different  countries  in  2015,  leads  to  the  unmistakable  and  very 
interesting conclusion that green jobs lead to higher (perceived) employability practically 
everywhere in Europe. To some extent this might be related to the fact these are possibly 
newer  jobs,  with  a  more  general  and  thus  intrinsically  more  portable  skill  content.  New 
employers can easily recognise the skills that new employees offer, usually expressed in 
recognisably similar occupational categories, for example. The picture by sector for 2015, 
however, is more mixed (Figure 28): in some sectors, brown jobs are more ‘employable’. 
Among them are finance, energy and construction. 

The  evolution  over  time  can  be  found  in  Figures  29  and  30.  Between  2005  and  2015 
employability increased slightly or remained stable practically everywhere, with the stark 
exception of Germany (both for green and brown jobs) and Romania, where only brown 
jobs were affected (Figure 29). The evolution between 2005 and 2015 in different sectors 
(Figure 30) is very similar: very flat in most cases for both green and brown jobs, with one 
important exception: fisheries, where employability seems to have collapsed, especially for 
brown jobs (possibly related to generally dire employment perspectives in that sector).  

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Figure 27 : Employability by country (2015) 

Figure 28 : Employability by sector (2015) 

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Figure 29: Employability by country (2005 - 2015) 

Figure 30: Employability by sector (2005 – 2015) 

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5.3  Education and Training: Discussion 

One of the implicit expectations in many circles with regards to green jobs, especially in 
light of the turn towards a knowledge economy, has often been that they are more skill-
based, and rely on more abstract skills that can be deployed in different settings, especially 
when  compared  to  ‘older’  brown  jobs.  This  expectation  is  only  partially  correct,  as  the 
results  in  this  section  suggest.  There  certainly  seems  to  be  some  evidence  that 
employability is higher in green jobs, but it is not entirely clear to what extent this is related 
to higher, more sophisticated or permanently updated skills in those jobs. Green and brown 
jobs  are,  actually,  and  against  expectations  perhaps,  quite  similar  in  terms  of 
characteristics that pertain to actual skills and their development. The benign interpretation 
is that both brown and green jobs in Europe are now so skill-intensive that they are very 
similar (but that green jobs have a more future-oriented profile that would explain their 
higher employability scores); the less benign interpretation, underpinned perhaps by the 
low skill development scores reported in Figure 27 (by country 2015), is that many workers 
are (still) employed in jobs that appear to require relatively few sophisticated skills. This 
observation on the perception of skill requirements stands in contrast to arguments that 
suggest that green jobs might to some extent fill the ‘hole’ in the middle segment of the 
skill distribution, which has emptied as a result of automation and globalisation. It might 
therefore warrant further research.  

6.  Working Conditions 

Working conditions are defined here as the field of health and safety, work intensity, work 
autonomy and collective interest representation. The evolution of green and brown jobs 
may differ across different European countries. Figures 31 and 32 present data for 2015: 
working conditions do not differ much between green and brown jobs but when they do, 
brown jobs offer better ones (Figure 31). This image is reinforced by figure 32, in which 
the  differences  between  green  and  brown  jobs  are  positive  (for  green  jobs)  only  in  a 
handful of countries: Norway, Netherlands, Finland, Montenegro, UK and Italy. Combining 
the data  from both  figures  suggests  that  this  is not  just  due  to the  general  low  level  of 
working conditions, as all except for Montenegro are located in the upper third (and even 
top 5) of the distribution in Figure 31. The evolution of working conditions in green and 
brown  jobs  between  2005  and  2015  (Figure  33)  follows  the  now  familiar  pattern  of 
relatively few countries where significant changes have taken place, but with a few outliers, 
such as Portugal, Romania and Slovakia, where curves diverge slightly over time, in favour 
of brown jobs, and Albania, where they converge but end up significantly lower in 2015. 

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Figure 31: Working conditions by country (2015) 

Figure 32: Difference in working conditions between green and brown jobs by country 
(2015) 

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Figure 33: Working conditions by country (2005 – 2015) 

The three types of green jobs — ID, IS and NG — evolve in a similar way over time, as 
Figure 34 suggests: there are very few countries where working conditions in any of the 
three job types moves sharply up or down, or where generally the rank order changes over 
time. This is confirmed in the sectoral analysis presented in Figure 35. Different types of 
green jobs move alongside the same broad axes, and do not display much change. The 
only exception is fishing, where all three converge from quite different starting points (and 
extraterritorial organisations). 

Continuing the  sectoral analysis with  the  help  of  Figures  36-38,  yields a few  interesting 
insights. In 2015, working conditions varied relatively little across sectors (Figure 37): with 
the  exception  of  the  hospitality  sector,  their  minimum  score  is  close  to  60%  and  the 
maximum below 80% -- the lowest range of all the indicators examined in this research 
note. However, while green jobs are slightly better in terms of working conditions in some 
sectors,  brown  jobs  offer  the  most  visible  outliers.  Figure  38  succinctly  presents  these 
observations. Figure 36 gives the evolution of working conditions in green and brown jobs 
across different sectors over time. The picture is, as in many other cases, one of relative 
stability, with very few important exceptions.  

In the following four subsections, we unpack the general area of working conditions into 
its four sub-dimensions: health and safety, work intensity, work autonomy and collective 
interest representation. 

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Figure 35 : Working conditions by green job type and country (2015) 

Figure 34: Working conditions by green job type and sector (2015) 

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Figure 37: Working conditions by sector (2005 - 2015) 

Figure  36:  Differences  in  working  conditions  between  green  and 
brown jobs by sector 

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Figure 38: Working conditions by sector (2015) 

6.1  Health and Safety 

Health and Safety (H&S) in 2015 in the different European countries is presented in Figure 
39.  The  first  remarkable  conclusion  from  these  data  is  that  H&S  varies  relatively  little 
across the continent and that it has quite high scores (though a maximum of 80% does 
suggest that one in five employees thinks H&S is not up to the standard that it should be). 
That said, in the vast majority of countries, H&S in brown jobs is considered much better 
than in green jobs: only seven countries have a reported H&S score in green jobs above 
brown jobs, and the difference is often not very large. The evolution of H&S indicators over 
time, as reported in Figure 40, suggests that very few countries have witnessed a dramatic 
shift in H&S between 2005 and 2015. The same can be said about the sectoral distribution. 
In 2015, H&S scores were high in every sector, and green-brown differences were quite 
small (Figure 41). Between 2005 and 2015, this sectoral picture changed relatively little, 
as  Figure  42  demonstrates.  In  the  vast  majority  of  sectors,  the  evolution  of  green  and 
brown jobs was relatively flat with regard to H&S, and in very few instances did the relative 
order change. Only agriculture, fishing and construction deviate from this general pattern 
of stability.  

One of the main reasons why differences between countries and sectors in H&S are rather 
small (and possibly also why brown jobs score better) is related to the fact that this is a 
highly regulated area of working conditions everywhere, and which is vigorously policed by 
labour inspectors, trade unions and employers, the press and labour ministries. Brown jobs 
almost certainly have a more institutionalised regime in this regard, and green jobs may, 
on average, only just be emerging as new regulatory arenas in H&S matters. If this quasi-
evolutionary interpretation holds sway, H&S indicators of green jobs will increase over time 
to match those of brown jobs. 

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Figure 39 : Health and safety by country (2015) 

Figure 40 : Health and safety by country (2005 - 2015) 

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Figure 41 : Health and safety by sector (2015) 

Figure 42 : Health and safety by sector (2005 – 2015) 

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6.2  Work Intensity  

Brown jobs are more often more intense than green jobs, as Figure 43 suggests. The most 
important  outliers  are  practically  all  countries  where  brown  jobs  face  significantly  more 
intense  work  arrangements  than  green  jobs.  Figure  44  reports  the  green  -  brown  job 
evolution between 2005 and 2015 shows, with very few exceptions, the usual pattern of 
relative  stability  everywhere,  with  a  few  cases  that  break  this  mould.  In  Malta  and 
Romania, work intensity has increased in brown jobs but elsewhere they followed a parallel 
trajectory to green jobs, with only small increases in intensity over time.  

The sectoral picture, in Figure 45, is very similar in logic. Brown jobs are more intense in 
all  sectors  with  a  significant  difference  between  green  and  brown  jobs.  In  most  other 
sectors,  the  intensity  of  work  is very  similar  or  green  jobs  report  a usually only  slightly 
higher level. The evolution across sectors over time (Figure 46) has slightly more variation 
than  for  many  other  indicators.  While  brown  and  green  jobs  often  follow  a  similar 
trajectory,  when  differences  exist,  brown  jobs  seem  to  face  slightly  more  intense  work 
situations. Furthermore, in several sectors green and brown jobs seem to follow different 
trajectories, even if they end up in the same place in 2015: fishing and construction.  

Figure 43 : Work intensity by country (2015) 

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Figure 44: Work intensity by country (2005 - 2015) 

Figure 45: Work intensity by sector (2015) 

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Figure 46 : Work intensity by sector (2005 – 2015) 

6.3  Autonomy at work 

Job autonomy follows a similar pattern as work intensity. In countries where differences 
are important (Figure 47), this usually means that  brown jobs have more autonomy; in 
most  other  cases,  the  differences  between  green  and  brown  jobs  are  relatively  small. 
Figure 48 presents the evolution of autonomy in green and brown jobs in different countries 
over time between 2005 and 2015. The general picture here is the usual one of relative 
stability in the majority of cases, with some exceptions: the Czech Republic and Portugal, 
for example. The data for sectors, in Figure 49 leads to a very similar conclusion. If there 
are differences between green and brown jobs, brown jobs usually have higher autonomy 
(in 2015), as Figure 49 suggests. Between 2005 and 2015, autonomy in green and brown 
jobs  followed  a  similar  trajectory  in  most  sectors,  but  there  is  possibly  slightly  more 
variation than we have found for other indicators. In about half the cases one of the curves 
reflecting the evolution over time has an important inflection point, or the relative ranking 
between green and brown jobs changes  

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Figure 47 : Autonomy by country (2015) 

Figure 48 : Autonomy by country (2005 – 2015) 

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Figure 49: Autonomy by sector (2015) 

6.4  Collective Representation 

Collective representation yields a very similar picture as the two preceding dimensions of 
‘working conditions’. When differences are important (2015), as Figure 50 suggests, brown 
jobs  are  significantly  better  represented  than  green  jobs  —  though  there  are  a  few 
countries  where  green  jobs  have  an  advantage.  This  is  almost  certainly  related  to  the 
deeper and more extensive institutionalisation of representation in brown jobs. Figure 51 
gives  this  distribution  for  sectors  in  2015  and  the  overall  image  that  emerges  is  very 
similar:  when  the  differences  are  large,  collective  representation  is  more  developed  in 
brown jobs than in green jobs, with very few exceptions. What is, perhaps, remarkable is 
not that brown jobs ‘win’, given that they are usually older, more institutionalised and on 
average more unionised; it is that green jobs in many sectors actually have a regime of 
collective representation that roughly matches (or even exceeds) that of brown jobs. These 
are:  education,  public  administration,  health  and  social  services,  electricity  and  gas, 
manufacturing –  all  relatively  established  sectors,  with  highly  institutionalised  forms  of 
representation. 

Data collection on collective representation only started after 2010, and as a result, it is 
impossible to compare this dimension through time. However, we suspect that there will 
not  have  been  many  important  shifts  on  this  dimension  between  2005  and  2015.  Any 
changes  that  will  have  occurred  will  likely  have  been  to  the  detriment  of  workers 
representation.  

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Figure 50 : Collective interest representation by sector (2015) 

Figure 51 : Collective interest representation by country (2015) 

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6.5  Working Conditions: Discussion 

The  single  most  important  conclusion  from  this  analysis  of  different  aspects  of  working 
conditions is that institutionalisation matters. The formal and informal regulation of work 
through  law,  social  partners  and  labour  administration  appears  as  a  key  background 
condition to understand different outcomes. Health and safety overall scored higher, with 
smaller differences between green and brown jobs, and in less regulated areas, older, more 
established  brown  jobs  often  scored  higher  than  green  jobs.  The  only  indicator  that, 
somewhat counterintuitively, (also) followed this brown jobs advantage is work intensity 
— despite the probably higher institutionalisation and regulation of brown jobs. Production 
processes have, of course, changed to include more sophisticated skills and tasks than in 
the past, which may produce a higher sense of intensity; green jobs may have started at 
such a higher level of conceptual work, often reflecting the higher prior training and the 
novelty of the job, and thus the sense of intensity has not actually increased by much. To 
some extent this obviously confirms the institutionalisation hypothesis: the more regulated 
nature of brown jobs makes such increases stand out now, while they do not really appear 
on  the  dashboard  of  the  possibly  less  regulated  green  jobs.  While  we  can  only  offer 
reasoned interpretations here, we think this hypothesis is worth exploring in more detail 
in future research. It suggests that higher levels of better regulation may protect green 
jobs and thus mitigate many of the legitimate concerns about job quality voiced by trade 
unions.  

7.  Work-life Balance and Gender 

Balancing the claims on time made by our jobs and the ability to organise a family life has 
become a preoccupation of many governments in Europe, now also enshrined in the Pillar 
of Social Rights of the EU. Similarly, over the last decade European countries have adopted 
policy orientations that would reduce gender imbalances in the workplace – especially the 
mostly  implicit  career  discrimination  against  women  who  remain  often  primarily 
responsible for family matters, including raising children.  

The composite indicator ‘work-life and gender balance’ (WLG), reported in Figures 52 and 
53 suggests that in many countries today (2015) WLG is very similar and that differences 
in WLG between green and brown jobs are relatively small (figure 52). However, Figure 
53,  which  magnifies  the  differences,  suggests  a  less  sanguine  interpretation:  in  many 
countries differences remain important, even though in about half they go in one way and 
in the other half in the opposite direction. The evolution of WLG in green and brown jobs 
between 2005 and 2015, as reported in Figure 54, suggests the now familiar pattern of 
relatively  few  and  mainly  small  differences  in  the  majority  of  cases,  but  with  a  few 
exceptions. Surprisingly, perhaps, in most countries brown jobs seem to have a better WLG 
score than green jobs. 

A  more  granular  look  at  different  types  of  green  jobs  (increased  demand  ID,  increased 
skills IS and new and emerging green NG jobs) suggests very few differences. Figure 55, 
presenting the evolution of WLG in the three types of green jobs between 2005 and 2015, 
leaves us with the conclusion that all three types have followed a broadly similar evolution. 
The curves for the three types of green jobs have similar shapes practically everywhere, 
regardless of the actual evolution of WLG. The same appears to be true when comparing 
sectors, as in Figure 56: in most sectors, WLG in ID, IS and NG jobs have developed along 
similar  lines.  The  main  exceptions  are  fishing  and  extra-territorial  organisations  (two 
sectors that have often been outliers in the previous analyses).  

Continuing this focus on sectors with Figures 57-58, we see that WLG scores for green and 
brown  jobs  in  2015  were  quite  similar  across  sectors  (Figure  57),  but  that  brown  jobs 
(again, somewhat surprisingly, perhaps) do better than green jobs. The differences in WLG 
between green and brown jobs are, as we can infer from Figure 58, usually relatively small 

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(below 3%) and evenly spread across sectors. They also follow a quite predictable pattern, 
with green jobs in education and public administration having a net positive WLG score, 
and construction and manufacturing a net positive score for brown jobs. Figure 58 which 
presents data on the evolution of WLG for green and brown jobs between 2005 and 2015, 
suggests  that  both  have  roughly  followed  the  same  pattern,  regardless  of  increases, 
decreases and inflection. 

Figure 52 : WLF by country (2015) 

Figure 53 : Differences in WLG between green and brown jobs by country (2015) 

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Figure 54 : WLG by country (2005 -2015) 

Figure 55 : WLG by green job type and country (2005 – 2015) 

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Figure 56 : WLG by green job type and sector (2005 – 2015) 

Figure 57 : WLG by sector (2015) 

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Figure 58 : WLG by sector (2005 – 2015) 

7.1  Work-life Balance  

Decomposing the general WLG indicator into its constituent dimensions is our next task. 
Figures  59  -  62  present  data  on  work-life  balance  (WLB).  In  figure  59  we  see  the 
distribution of WLB for green and brown jobs in different European countries in 2015. Two 
things  stand  out:  one,  the  relatively  small  range  of  scores  across  different  countries 
(between about 50% and slightly over 60%), and the small differences between green and 
brown  jobs.  However,  positive  differences  usually  exist  for  green  jobs  (in  only  nine 
countries do brown jobs yield a better WLB score), and many of those are among the new 
member states. Figure 60 examines the evolution of WLB over green and brown jobs across 
European countries since 2005 and suggests very few important differences between the 
two.  That  said,  while  in  most  cases  the  two  curves  evolve  in  parallel,  in  a  few  cases 
developments are a bit more complex. In Poland, for example, the curves converge from 
relatively significant initial starting points, while in Romania, Greece and Malta, the curves 
switch relative positions.  

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Figure 59 : WLB by country (2015) 

Figure 60 : WLB by country (2005 - 2015) 

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The sectoral distribution of WLB over green and brown jobs can be found in Figure 62. The 
differences between sectors are small, as are differences between green and brown jobs 
within  sectors.  Brown  jobs  only  score  visibly  higher  in  construction  and  extraterritorial 
organisations, while in the education and energy sectors, green jobs perform best. Between 
2005  and  2015  WLB  in  green  and  brown  jobs  also  evolved  in  broadly  similar  ways  in 
different  sectors  (Figure  61).  Fishing  is  the  only  important  exception  to  this  general 
observation. 

Figure 61 : WLB by sector (2005 – 2015) 

Figure 62 : WLB by sector (2015) 

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7.2  Gender Balance  

Figures 63 - 66 present the final set of indicators, which cover gender balance (GB). In 
2015, brown jobs scored remarkably higher on GB in many European countries than green 
jobs. Almost all stark differences between green and brown jobs in terms of GB go in favour 
of the latter, and there are surprisingly many of them. The evolution over time, found in 
Figure 66, also presents a more varied picture than for many other indicators. In fact, only 
a  relatively  small  number  of  countries  show  similar  curves  for  both,  and  divergence  is 
frequently driven by brown jobs increasing their WLB scores. This may well reflect the fact 
that GB as a relatively new but highly politicised field in labour relations has stirred many 
member states into action, starting with brown jobs, which appear more regulated. 

The  situation  of  GB  in  different  sectors  in  2015  is  reported  in  Figure  64.  Important 
differences  can  be  found  in  almost  half  the  sectors,  all  in  favour  of  brown  jobs.  The 
relatively female-friendly educational and public administration sectors are the only ones 
where green jobs score significantly higher in terms of GB. Between 2005 and 2015, GB in 
green  and  brown  jobs  also  evolved  differently  in  more  sectors  than  for  many  other 
indicators in this research note. Even though in most sectors both curves seem to follow a 
similar  pattern,  there  are  quite  a  few  cases  with  inflection  points,  and  instances  of 
divergence  and  convergence.  As  mentioned  earlier,  this  may  reflect  the  politically 
contingent nature of GB as a new field, which has introduced new regulations that have to 
be adopted.  

Figure 63 : Gender balance by country (2015) 

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Figure 64: Gender balance by sector (2015) 

Figure 65: Gender balance by sector (2005 - 2015) 

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Figure 66: Gender balance by country (2005 - 2015) 

7.3  Work-life and Gender Balance: Discussion 

If  there  is  one  overarching  conclusion  to  be  drawn  from  this  analysis  of  work-life  and 
gender balance (WLG) issues, it is the importance of political and institutional frameworks 
that influence and structure outcomes in these areas. Both WLB and GB are relatively new 
areas in employment and have become politically more important over the last two decades 
(despite equal pay laws and anti-discrimination regulations having been in force since the 
1970s in most European countries). The political attention and subsequent regulation fell 
on  more  fertile  soil  in  older  industries,  with  more  brown  jobs,  where  enforcement  of 
regulations was more developed than in newer settings. That means that in this particular 
area of employment relations, the ‘natural’ shift that could equalise green and brown jobs 
is  less  powerful,  and  that  a  role  for  governments  in  imposing  and  enforcing  regulations 
that  further  gender  equality  directly  and  indirectly  remains  a  necessity,  at  least  for  the 
foreseeable future.  

8.  Conclusion 

This research note started by registering concern over the employment effects of the green 
transition.  While  we  are,  quite  rightly,  rethinking  economic  processes  to  minimise  their 
ecological  impact,  there  are  worries  that  we  jump  headfirst  into  a  process  with  unclear 
social  consequences  and  their  distributive  and  political  effects.  An  understanding  of  the 
costs  of  transition  is  therefore  a  crucial  element  in  the  political  process  of  greening  the 
economy.  

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The  findings  in  this  research  note  suggest  that  the  quality  of green  jobs  does  not  differ 
systematically from those of brown jobs and that the same is true for different types of 
green jobs. Moreover, an analysis over time, between 2005 and 2015 (the last year for 
which  data  were  available  at  the  time  of  writing)  suggests  that  for  most  countries  and 
sectors,  green  jobs  and  brown jobs  evolved along  similar lines.  Any  concerns  about  the 
quality of work should therefore primarily be addressed to employment systems as a whole, 
and  not  attached  just  to  green  jobs.  There  are  important  methodological  considerations 
that limit the extent to which these findings can be generalised, as we explain in section 
2, but taken at face value this is an important finding. It does not mean that we can ignore 
the  social  consequences  of  the  green  transition,  but  that  the  aggregate  outcomes  are 
relatively balanced.  If problems with  jobs  exist, they  may  be  more  local or  in  particular 
sectors, for which specific adjustment instruments exist or can be developed.  

One of the sectors that is very likely to require such careful accompanying measures is the 
energy (electricity and gas) sector, where we expect many changes to take place over the 
next few years and decades. De-carbonising the economy in the EU means, possibly more 
than  anything  else,  reducing  the  carbon  footprint  associated  with  industrial  and  service 
activities.  Changing  the  energy  mix  from  brown  to  renewable  and  sustainable  energy  is 
the strategy to accomplish that. As a result, the skill mix and associated characteristics of 
work are likely to change quite dramatically in that sector., which will lead to claims about 
reconversion not unlike those that we saw in the mining and quarrying industries several 
decades ago.  

this 

there 

is  one 

‘negative’ 

However, 
finding. 
important  conclusion  beyond 
Institutionalisation  –  shorthand  here  for  the  degree  to  which  employment  and  work  are 
governed by formal and informal sanctioning and monitoring arrangements – matters for 
quality of work. First of all, brown jobs in established sectors, which can often be assumed 
to be more institutionalised in this sense, regularly score higher, sometimes significantly 
so,  than  green  jobs.  In  addition,  quality  of  work  is  higher  in  areas  that  have  more 
institutionalised  protection  and  enforcement,  particularly  wages  and  health  &  safety. 
Finally, the highly politicised but far from fully institutionalised area of work-life and gender 
balance across EU member states shows the largest variation of any set of indicators. We 
attribute that to the fact that this is still an emerging policy area, with notable differences 
across EU economies and sectors of economic activity.  

This brings us to the main policy recommendations that follow from this report. The first 
two are directly related to the key findings discussed here. One, while the labour market 
effects of the green transition seem to be relatively benign on the whole, there will almost 
certainly  be  sectors  and  regions  where  these  effects  will  be  considerably  less  sanguine. 
Policy-makers should therefore consider developing policies and accompanying measures 
that  address  such  geographically  and  sectorally  specific  adjustment  problems.  This 
approach has supported  restructuring  in the textile,  coal and  steel industries  in the  late 
twentieth century, and is still the main approach for current restructuring in the automotive 
industry;  many  governments  (and  social  partners)  therefore  have  experience  with  this 
approach. In addition, it can easily be organised to suit the local institutional and socio-
economic conditions.  

Two,  promoting  institutional  protection  of  aspects  of  employment  will  contribute  to  the 
manageability  of the  transition.  Raising  formal  and  informal  employment  protection  and 
enforcement  across  all  jobs  will  alter  the  perception  of  the  distributive  effects  of  this 
transition from a problem of green versus brown jobs to one of employment adjustment 
more  generally,  and  will  therefore  lower  resistance  and  facilitate  the  deployment  and 
development of relevant policies. In addition to these considerations that speak directly to 
the results presented here, we see two wider policy concerns.  

The  third  policy  idea  is  the  simple  one  that  investment  in  skill  upgrading  is  crucial  – 
especially in Southern Europe. One of the key problems is quite a low investment in skills 

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generally, and in Southern Europe in particular. In Southern Europe this may be related to 
the relative importance of tourism in the economy (with the Hotels and Restaurants sector 
having  the  lowest  skill  development  figures  by  far).  Tourism  can  obviously  be  a 
comparative advantage worth developing but it can also be a relative dead end based on 
extensive  growth  (ie  where  productivity  remains  low  and  growth  only  takes  place  by 
increasing the number of hotels, restaurants, etc. and not by increasing the value added 
per room or meal). Not only can it stifle growth, it also makes an economy vulnerable to 
cyclical  swings  in  demand;  however,  its  low-skill  profile  makes  it  hard  to  transfer 
employees  to  higher  value-added  industries  during  downturns,  seasonal  or  otherwise. 
Investing in skill development alongside the industrial upgrading and greening is therefore 
key, particularly as a way of supporting the green transition, since many green jobs require 
skill upgrading or new skills altogether.  

Fourth  and  finally,  job  and  career  security  are  (somewhat  surprisingly  in  our  view) 
perceived  as  being  very  low  across  the  board,  suggesting  that  many  European  workers 
think of themselves as being in a precarious professional situation. These employees are 
not very likely to embrace the social changes associated with the green transition, which 
could make an already insecure situation even more so. More ‘Social Europe’, generating 
legislation on social dumping, zero-hour contracts and the like, could tackle this problem. 
This also reaffirms the importance of investing in skills. High-skilled work is, all other things 
equal, more secure work both in terms of job security (better contracts and less cyclical 
employment) but also in terms of careers (producing transferable skills, leaving workers 
with more options). 

The green transition, coming as it does on the tails of two massive economic crises – the 
financial shock of 2008 and the Covid-19 crisis of 2020 – heralds an era of deep economic 
insecurity.  Many  workers  will  understandably  worry  about  their  jobs,  both  their  survival 
and existence, and about the type of work they do. Even if green and brown jobs do not 
differ  much  in  QWL  terms,  any  downward  shift  will  produce  uncomfortable  outcomes  in 
terms  of  equality  and  life  chances,  which  will  endanger  the  success  of  the  necessary 
greening  of  the  economy.  Policies  geared  toward  greening  could  therefore  meaningfully 
take into account a process of ‘social assessment’ in the same way that we have introduced 
technology assessment to evaluate the effects of new technologies on society in general 
and employment in particular.  

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References 

Bowen,  Alex.,  &  Hancké,  Bob.  2019.  ‘The  Social  Dimension  of  ‘Greening  the  Economy’: 
Developing a taxonomy of labour market effects related to the shift toward environmentally 
sustainable economic activity’, SSM Research Note. 

Coutrot, Thomas & Gadrey, Jean. 2012. ‘Green growth is called into question. ETUI Policy 
Brief No 3/12 

Galgóczi, Béla (ed.). 2015. Europe’s energy transformation in the austerity trap. Brussels: 
ETUI 

Galgóczi, Béla. 2019. Phasing out coal – a just transition approach. ETUI Working paper 
2019.04, Brussels: ETUI. 

Muñoz  de  Bustillo,  Rafael.,  Fernández-Macías,  Enrique.,  Ignacio  Antón,  José.,  &  Esteve, 
Fernando. 2009. ‘Indicators of Job Quality in the European Union’, DG EMPL ET 429972. 

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Annex 

Subdimension 

Sub-
indicator 

EWCS code 

Survey Questions 

Table A1. Job Quality Indicator definitions 

A household may have different sources of 
income  and  more  than  one  household 
member may contribute to it. Thinking of 
your household’s total monthly income, is 
your household able to make ends meet…? 

Q100 (2010 
onwards) 

inc_deciles 
(2010 

onwards)  Within country income decile 

1.1 Adequate 
earnings 

1. Socio-
economic 
security 

1.2 Job and 
career security 

2.1 Skills 
development 

2. Education 
and training 

2.2 
Employability 

Q89a 

Q27 

Q11 

Q89b 

Q89g 

Q53e 

Q53f 

Q65a 

Q65b 

Q65c 

Q106 

Q30i 

A  -  Considering  all  my  efforts  and 
achievements in my job, I feel I get paid 
appropriately 
Besides your main paid job, do you have 
any other paid job(s)? (IF YES) Is it / are 
they ….? 
What kind of employment contract do you 
have in your main job? 
To what extent do you agree or disagree 
with the following statements about your 
job? B - My job offers good prospects for 
career advancement 
To what extent do you agree or disagree 
with the following statements about your 
job?  To  what  extent  do  you  agree  or 
disagree  with  the  following  statements 
about 
job? 
your 
G  -  I  might  lose  my  job  in  the  next  6 
months 
Generally, does your main paid job involve 
... ? E - complex tasks  
Generally, does your main paid job involve 
... ? F - learning new things 
Over  the  past  12  months,  have  you 
undergone  any  of  the  following  types  of 
training  to  improve  your  skills?  A  - 
Training  paid  for  or  provided  by  your 
employer 
Over  the  past  12  months,  have  you 
undergone  any  of  the  following  types  of 
training  to  improve  your  skills?  B  - 
Training paid by yourself 
Over  the  past  12  months,  have  you 
undergone  any  of  the  following  types  of 
training to improve your skills? C - On-the-
job training (co-workers, supervisors) 
What  is  the  highest  level  of  education  or 
training 
that  you  have  successfully 
completed  ?  
 Please tell me, using the same scale, does 
your main paid job involve ...? I - Working 

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3.1 Health and 
safety at work 

3. Work 
conditions 

Q89h (2010 
onwards) 

Q29a 

Q29b 

Q29c 

Q29d 

Q29e 

Q29h 

Q29i 

Q80b 

Q81c 

Q73 

Q33 

Q24 

3.2 Work 
intensity 

Q46 (2010 
onwards) 

with  computers,  laptops,  smartphones 
etc. 
H - If I were to lose or quit my current job, 
it  would  be  easy  for  me  to  find  a  job  of 
similar salary 
Please  tell  me,  using  the  following  scale, 
are  you  exposed  at  work  to  ...?  A  - 
Vibrations  from  hand  tools,  machinery, 
etc. 

Please  tell  me,  using  the  following  scale, 
are you exposed at work to ...? B - Noise 
so loud that you would have to raise your 
voice to talk to people 
Please  tell  me,  using  the  following  scale, 
are you exposed at  work to ...? C  - High 
temperatures  which  make  you  perspire 
even when not working 

indoors 

Please  tell  me,  using  the  following  scale, 
are  you  exposed  at  work  to  ...?  D  -  Low 
or 
temperatures  whether 
outdoors" 
Please  tell  me,  using  the  following  scale, 
are  you  exposed  at  work  to  ...?  E  - 
Breathing  in  smoke,  fumes  (such  as 
welding  or  exhaust  fumes),  powder  or 
dust (such as wood dust or mineral dust) 
etc. 
Please  tell  me,  using  the  following  scale, 
are  you  exposed  at  work  to  ...?  G  - 
Handling  or  being  in  skin  contact  with 
chemical products or  substances 
Please  tell  me,  using  the  following  scale, 
are  you  exposed  at  work  to  ...?  I  - 
Handling  or  being  in  direct  contact  with 
materials which can be infectious, such as 
waste, bodily fluids, laboratory materials, 
etc. 
Over the last month, during the course of 
your work have you been subjected to.. B 
- unwanted sexual attention? 
And over the past 12 months, during the 
course  of  your  work  have  you  been 
subjected to…C - bullying / harassment? 
Do  you  think  your  health  or  safety  is  at 
risk because of your work ? 
Regarding  the  health  and  safety  risks 
related  to  performance  of  your  job,  how 
well informed would you say you are? 
How many hours do you usually work per 
week in your main paid job?  
Over the last 12 months, how often have 
you worked in your free time to meet work 
demands?  

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Q49a 

Q49b 

Q84a (2010 
onwards) 

Q54a 

Q54b 

Q54c 

3.3 Autonomy 

Q50a 

3.4 Collective 
Interest 
Representation 

Work-life and 
gender 
balance 

4.1 Work life 
balance 

Q50d 

EWCS 50e 

Q71a (2015 
onwards) 

EWCS 71b 
(2015 
onwards) 

Q71c (2015 
onwards) 

Q39d 

Q43 

Q42 

Q47 (2010 
onwards) 

Q44 

Q39d 

Q43 

Q42 

a 

similar 

And, does your job involve ... ? A - working 
at very high speed 
And, does your job involve ... ? B- working 
to tight deadlines 
Over  the  past  12  months  did  you  work 
when you were sick ?  
Are you able to choose or change ... ?  A - 
your order of tasks 
Are you able to choose or change ... ? B - 
your methods of work 
Are you able to choose or change ... ?  C - 
your speed or rate of work 
On  the  whole,  is  your  pace  of  work 
dependent on  ... ?  A  -  the  work  done  by 
colleagues 
On  the  whole,  is  your  pace  of  work 
dependent on ... ? D - automatic speed of 
a machine or movement of a product 
On  the  whole,  is  your  pace  of  work 
dependent on ... ? E the direct control of 
your boss 
Does the following exist at your company 
or organisation…? A - Trade union, works 
council 
committee 
or 
representing employees? 
Does the following exist at your company 
or  organisation…?  B  -  Health  and  safety 
delegate or committee? 
Does the following exist at your company 
or organisation…? C - A regular meeting in 
which employees can express their views 
about  what 
the 
organisation?  
Do  you  work...?  D  -  Fixed  starting  and 
finishing times 
Do  changes 
time 
arrangements  occur  regularly?  (IF  YES) 
How  long  before  are  you  informed  about 
these changes? 
 How are your working time arrangements 
set? 
Would  you  say  that  for  you  arranging  to 
take  an  hour  or  two  off  during  working 
hours  to  take  care  of  personal  or  family 
matters is ... ? 
In general, how do your working hours fit 
in with your family or social commitments 
outside work? 
Do  you  work...?  D  -  Fixed  starting  and 
finishing times 
Do  changes 
time 
arrangements  occur  regularly?  (IF  YES) 
How  long  before  are  you  informed  about 
these changes? 
 How are your working time arrangements 
set? 

to  your  working 

to  your  working 

is  happening 

in 

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4.2 Gender 
balance 

Q46 (2010 
onwards) 

Q62 

Over the last 12 months, how often have 
you worked in your free time to meet work 
demands?  
Is  your  immediate  boss  a  man  or  a 
woman?  

Table A2. Green Job Types categorisation (See Bowen and Hancké 2019) 

Type 

ISCO-88 

ISCO-08 

Increased 
Demand (ID) 

13, 21, 22, 24, 31, 34, 

13, 21, 22,  25, 31, 33, 42, 

42, 41, 54, 71, 72, 74, 

43, 54, 71, 72, 74, 75, 81, 

81, 83, 92, 93 

82, 83, 92, 93 

Green Jobs 

Increased Skill (IS)  12, 13, 21, 31, 51, 71, 

13, 21, 22,  25, 31, 33, 42, 

72, 73, 74 81, 83,  93 

43, 54, 71, 72, 74, 75, 81, 

83, 93 

New 
emerging (NE) 

and 

9,  12,13,  21,  24,  31, 

12, 13, 21, 24,  25, 31, 33, 

34, 74 

96 

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Figure A3 Country profile Belgium (2015) 

Figure A4 Country profile Bulgaria (2015) 

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Figure A5 Country profile Croatia (2015) 

Figure A6 Country profile Cyprus (2015) 

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Figure A7 Country profile Czech Republic (2015) 

Figure A8 Country profile Germany (2015) 

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Figure A9 Country profile Denmark (2015) 

Figure A10 Country profile Spain (2015) 

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Figure A11 Country profile Estonia (2015) 

Figure A12 Country profile Finland (2015) 

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Figure A13 Country profile France (2015) 

Figure A14 Country profile Greece (2015) 

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Figure A15 Country profile Hungary (2015) 

Figure A16 Country profile Ireland (2015) 

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Figure A17 Country profile Italy (2015) 

Figure A18 Country profile Kosovo (2015) 

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Figure A19 Country profile Lithuania (2015) 

Figure A20 Country profile Latvia (2015) 

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Figure A21 Country profile Luxembourg (2015) 

Figure A22 Country profile Montegro (2015) 

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Figure A23 Country profile Northern Macedonia (2015) 

Figure A24 Country profile Netherlands (2015) 

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Figure A25 Country profile Norway (2015) 

Figure A26 Country profile Poland (2015 

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Figure A27 Country profile Portugal (2015) 

Figure A28 Country profile Romania (2015) 

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Figure A29 Country profile Serbia(2015) 

Figure A30 Country profile Slovenia (2015) 

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Figure A31 Country profile Slovakia (2015) 

Figure A32 Country profile Sweden (2015) 

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Figure A33 Country profile Switzerland (2015) 

Figure A34 Country profile Turkey (2015) 

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Figure A35 Country profile United Kingdom (2015) 

Figure A35 Country profile United Kingdom (2015) 

77 

 
 
 
 
 
 
 
 
 
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