A demographic perspective on the future of European labour force participation.
Date: 2025-02-26
Institutions: Joint Research Centre
Subjects: competitiveness, demographic analysis, education, employment policy, gender equality, labour force, labour market, migration policy, population ageing, vocational training

A DEMOGRAPHIC 
PERSPECTIVE ON THE FUTURE 
OF EUROPEAN LABOUR 
FORCE PARTICIPATION

BEYOND THE DRAGHI REPORT

Joint
Research
Centre

This document is a publication by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide 
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Contact information 
Name: Fabrizio Natale  
Email: fabrizio.natale@ec.europa.eu

EU Science Hub
https://joint-research-centre.ec.europa.eu

JRC141153

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ISBN 978-92-68-25241-3 

doi:10.2760/0326281 

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How to cite this report: European Commission: Joint Research Centre, Biagi, F., Deuster, C. and Natale, F., A Demographic Perspective on the Future 
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TABLE 
OF CONTENTS

Abstract 
Introduction 

1. From static analyses to dynamic projections of the labour force   
Emancipation and increasing labour force participation of women - a cohort perspective 
Education is a key variable to consider when assessing gaps in labour force participation 
Migration increases the size of the future working-age population  

2. Simulating the effect of different forms of labour force activation 
Future EU working-age population will decline significantly 
Activating labour force potential of population subgroups has a large effect  
Labour force activation potential varies widely across MS    

3. Educational composition and GDP growth  
4. Conclusions and limitations  

References 
Acknowledgements 
Authors 

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ABSTRACT

While the Draghi report primarily focuses on increasing 
labour productivity, it also makes a compelling case 
for mitigating the decline in the workforce by using the 
untapped potential of labour force participation and 
employment. Forward-looking analyses of the EU labour 
force require taking into account the ongoing process 
of women’s empowerment and emancipation, changes 
in  the  population’s  educational  profile,  and  varying 
assumptions about international migration. By factoring 
in these elements and in particular the projected changes 
in the educational attainment of the EU workforce, we 
emphasise the importance of investing in skills for the 

future of EU competitiveness.  Our projections show that 
such investment will not be able to compensate for the 
EU’s demographic decline, which remains of concern, but 
can mitigate the reduction in the number of workers. In 
a hypothetical extreme positive scenario, the projected 
adverse decline in labour force could be offset through 
the simultaneous exploitation of the entire potential of 
different forms of labour force activation.  Estimates of the 
impact on GDP indicate that human capital growth, which is 
already embedded in the evolution of the EU population, is 
an area where the EU could have a competitive advantage.

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A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORTINTRODUCTION

The Draghi report [1] has been prominently cited in the 
mandate letters for the new Commission and is expected 
to have a significant impact on EU policies in the coming 
years.1 

The report emphasises that the EU’s loss of competitiveness, 
particularly in comparison to the US, stems from both a 
productivity disadvantage and the demographic challenges 
posed by population decline and ageing. 

As the report notes, “the EU is entering the first period in 
its recent history in which growth will not be supported by 
rising populations. By 2040, the workforce is projected to 
shrink by close to 2 million workers each year.”2 

The competitiveness challenge facing the EU is framed as 
an existential issue, with far-reaching implications for the 
EU’s geopolitical positioning and the sustainability of its 
social model. In the words of the report, “If Europe fails 
to become more productive, we will be forced to make 
difficult choices. We will not be able to simultaneously lead 
in new technologies, demonstrate climate responsibility, 
and maintain our independence on the world stage. We 
will not be able to finance our social model, and we will 
have to scale back some, if not all, of our ambitions.” 

While the Draghi report primarily focuses on increasing 
labour productivity, it also makes a compelling case 
for mitigating the decline in the workforce by using the 
untapped potential of labour force participation and 
employment. 

The report highlights that potential contributions to the 
number of active people3 in the EU could be in the range of 
8 million in the case of young aged 20-29, 12 million for 
those in the age group 55-64 and 17 million for women.  

These figures are based on a static analysis of current gaps 
in labour force participation rates in 2021. In this policy 
brief, we expand this static picture by adopting a forward-
looking and dynamic perspective, combining labour force 
participation rates with demographic projections between 
2021 and 2070. 

Such exercises are not new and have been a central 
element of social and budgetary outlooks for the EU, as 
seen in the 2023 ESDE Report [2] and the 2024 Ageing 
Report [3]. 

We complement these analyses by adding nuance to the 
projections of the EU workforce, in particular in relation 
to three key aspects: the ongoing process of women’s 
emancipation, changes in the population’s educational 
profile, and varying assumptions about migration. 

The results of our exercise offer a slightly more optimistic 
outlook  for  the  decline  in  the  EU  workforce.  More 
importantly, they highlight the opportunities for economic 
growth and the EU’s competitive advantage in terms of 
human capital. 

The remainder of this policy brief is structured into three 
sections. The first section outlines the importance of 
adopting a fully dynamic perspective that incorporates 
education when projecting the EU labour force. The second 
section presents the results of our projections, while the 
third section offers brief considerations on the implications 
of the future educational composition of the labour force 
on productivity and GDP. We conclude by highlighting the 
limitations of our study and identifying areas for further 
research.

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As first, see “A Competitiveness Compass for the EU” COM(2025) 30 final.
EU official documents report a decline of around 1 million each year. The difference between these two figures is linked to the 
demographic projections used to produce the estimates. The Draghi report uses UNDESA projections that have less optimistic 
assumptions on migration with respect to Eurostat projections.  See also Figure 3.
Includes both employed (employees and self-employed) and unemployed people.

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT4

1. FROM STATIC ANALYSES TO 
DYNAMIC PROJECTIONS OF THE 
LABOUR FORCE  

cohorts of women and men in Germany born between 
1896 and 1997. 

This figure shows a general improvement in participation 
rates across all age groups. Notably, there has been a 
striking increase in labour force participation among 
women of childbearing age. For example, the participation 
rate of women at the age of 32 has risen from 42% for 
those born in 1970 to 80% for those born in 1987. 

Despite the persisting gender gap, the age profile of 
labour participation among younger cohorts of women 
now resembles that of men, with a peak at around 45 
years  of  age  and  a  decline  towards  retirement  age. 
This improvement in labour force participation rates is 
accompanied by two related processes: the reduction 
and postponement of fertility. There is an ongoing debate 
about whether low fertility is driven by higher participation 
rates, which would suggest a need to consider employment 
in the context of the ‘child penalty’,5 or whether both 
transformations are the result of wider societal changes 
in values related to partnership, marriage, and family. 

Regardless of the causes, it is essential for our purposes 
to acknowledge that the increase in women’s participation 
rates is a still partly ongoing demographic process that 
must be reflected in projections of the labour force, which 
in turn are input to macroeconomic evaluations.6 

Both the Ageing Report and the ESDE Report rely heavily 
on Eurostat demographic projections to provide an outlook 
on the trends of the EU labour force. The ESDE Report 
uses a static approach, assuming that the activity rates 
of the various population subgroups (by age and sex) 
remain constant in time: what changes is the size and 
share of each age-sex group in the workforce. In this case, 
the future evolution of the workforce follows a trajectory 
similar to that of the working-age population. In essence, 
projected figures on the number of workers remain a 
rescaled version of population projections.

The Ageing Report uses a dynamic approach, aimed at 
capturing the improvement of labour force participation 
across  generations,  in  particular  for  women.  This 
improvement  is  simulated  through  a  mechanism  of 
synthetic  cohorts,  established  around  2004  [4,5].  In 
simple terms, this mechanism applies varying labour 
force participation rates in the future based on entry 
and exit rates observed in recent years:4 improvements in 
labour force participation rates observed in recent years 
influence the projections for the future. In this way, the 
labour force in the future is influenced both by the ageing 
of the population and by a slight improvement in activity 
rates.

EMANCIPATION AND INCREASING LABOUR 
FORCE PARTICIPATION OF WOMEN - A 
COHORT PERSPECTIVE

The importance of accounting for the increase in labour 
force participation rates, particularly among younger 
cohorts of women, is illustrated in Figure 1. 

Using also in this case a synthetic cohort approach, we 
have reconstructed the participation rates by age for 

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In the projections, the new cohorts reaching working age and those ageing in the workforce inherit the entry and exit rates for each age 
observed in recent years. This allows them to improve their participation rates throughout their working life with respect to older cohorts. 
These dynamics, albeit an improvement with respect to a static approach, “remain mechanical” and stabilise over the projection period as 
all current workers are entirely replaced by younger cohorts.
Couples and in particular women in younger generations may be facing two forms of child-work penalty: being forced to renounce to 
the ideal family size because of the lack of economic means due to insufficient earnings from work or losing employment and career 
opportunities and earnings after childbirth. Furthermore, the child-work relation needs to be analysed both in terms of the implications for 
the total number of children and the postponement of childbearing.
The recent trends in women’s labour force participation may not be as impressive of what shown historically, for Germany but they are 
still present especially in countries with large gender gaps.

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT1. FROM STATIC ANALYSES TO DYNAMIC PROJECTIONS OF THE LABOUR FORCE5

FIGURE 1.  Labour force participation rates in Germany by age and sex for cohorts born between 1896 (light yellow) 
and 1997 (dark green).  

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Source: synthetic cohorts were reconstructed with data from 1958 to 2019 for Germany (Western Germany between 
1958 and 2000) from GESIS [6].

EDUCATION IS A KEY VARIABLE TO 
CONSIDER WHEN ASSESSING GAPS IN 
LABOUR FORCE PARTICIPATION

Education plays a significant role in explaining differences 
in labour force participation and employment levels, trends 
in  employment  within  shortage  occupations,  gender 
disparities, and other key social indicators such as the 
risk of poverty, social exclusion, and in-work poverty.

As  2023  was  the  European  Year  of  Skills,  the  2023 
edition of the ESDE Report provides extensive accounts 
of the fundamental role of education for labour force 
participation.  The  report  demonstrates,  for  instance, 
through econometric estimates, that secondary education 
increases the probability of labour force participation 
by approximately 11 percentage points (pp) compared 
to lower levels of education. Furthermore, individuals 
with tertiary education have a 23 pp higher likelihood of 
working or actively seeking employment.

The influential role of education is further illustrated in Figure 2, 
which depicts the trends in average labour force participation 
rates across Member States (MS) for selected age groups, sex, 
and educational levels over the period 2014–2023.

participation levels, disparities, and trends in the labour 
force. As the level of education increases, labour force 
participation rises for all age and sex groups, while the gaps 
between men and women, as well as between younger 
and older workers, are narrowing. Regardless of education 
level, the participation rates of younger individuals have 
remained stable in recent years for both men and women, 
whereas participation among older individuals has been 
steadily increasing. This trend is likely due to the gradual 
implementation of pension reforms across most MS.

While the importance of education for social and labour 
outcomes is undeniable, forward-looking analyses face 
challenges in accounting for the positive contributions 
of anticipated improvements in educational attainment. 

To address this, the Ageing Report, as noted earlier, adjusts 
the projection of future labour force participation rates 
taking into account the changes observed in the recent 
past. This is an implicit way of accounting for unobserved 
characteristics that have driven progress across cohorts 
in the past. Still, this approach does not provide a direct 
focus on the role of education, as groups can only differ 
in terms of age and sex.

The figure enables a range of observations regarding 
the intersections of age, sex, and education in shaping 

In this report, we adopt a different approach, employing 
demographic projections that incorporate education as a 
dimension, as produced by IIASA. This method allows the 

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT1. FROM STATIC ANALYSES TO DYNAMIC PROJECTIONS OF THE LABOUR FORCE 
 
 
FIGURE 2.  Trends in labour force participation rates in the EU between 2014 and 2023 by education, selected age 
groups and sex.  

Primary

30-34
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60-64
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Short Post-Secondary

Bachelor

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60-64
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30-34
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60-64
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Master and higher
60-64
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Notes: the values are averages across MS; the grey areas show 95% confidence intervals.
Source: own elaboration from Eurostat LFS microdata.

main demographic characteristics (age-sex-education) 
to “speak for themselves”. The projected increase in 
education levels, combined with the gradual replacement 
of  older,  less-educated  cohorts  with  younger,  more-
educated cohorts in the workforce, naturally enhances the 
educational composition of the workforce without the need 
to separately model dynamic labour force participation 
rates.7

MIGRATION INCREASES THE SIZE OF THE 
FUTURE WORKING-AGE POPULATION 

Several institutions produce population projections for the 
EU. The left panel of Figure 3 shows the evolution of the 
projected EU working-age population between the years 
2022 and 2070 under baseline scenarios produced by 
Eurostat, IIASA, and UNDESA. All three institutions project 
significant declines in the working-age population over 
the next 45 years, albeit at very different rates. While 

the Eurostat projections (orange line) reveal a decrease 
from 285 million in 2022 to 244 million in 2070, IIASA 
(blue line) and UNDESA (red line) project a decrease to 
225 and 216 million respectively in 2070. 

The right panel indicates that the differences between the 
three population projections are mainly driven by different 
assumptions about future net migration. The hypothetical 
scenario eliminating international migration produced 
by all three institutions yields working-age population 
projections that are remarkably similar in terms of size, 
varying by only about 8 million (between the 185, 192, 
and 193 million projected, respectively, by the UNDESA, 
IIASA, and Eurostat for 2070).8

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It is worth noting, however, that this approach captures only the effect of education and not other individual characteristics, which may 
affect participation rates such as childbearing. Furthermore, the participation rates by age, sex, and education level are assumed to 
remain constant, implying no change in the relationship between these variables and labour force participation rates in the future. We 
assume constant marginal return of education and ignore the possibility that as education attainment keeps improving beyond a certain 
point, the positive employability effects could decline.
There is nothing inherently wrong or right in the different outcomes of different projections, but what it important to keep in mind is that 
the apparent certainty in the baseline version of the projections hides a lot of uncertainties which in the case of EU are nowadays mostly 
linked to the demographic component of migration which is more volatile and therefore more difficult to predict in respect of fertility 
and mortality. A sensible way to deal with these uncertainties is to use alternative scenarios and different projections depending on the 
intended use and context of analysis.

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT1. FROM STATIC ANALYSES TO DYNAMIC PROJECTIONS OF THE LABOUR FORCE 
 
 
 
7

FIGURE 3.  Different projections of the EU working age population according to a baseline and no migration scenario  

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2025 2030 2035 2040 2045 2050 2055 2060 2065 2070

2025 2030 2035 2040 2045 2050 2055 2060 2065 2070

Source: Eurostat (EUROPOP23), UNDESA (WPP 2024) and IIASA (SSP projections).

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT1. FROM STATIC ANALYSES TO DYNAMIC PROJECTIONS OF THE LABOUR FORCE 
 
8

2. SIMULATING THE EFFECT OF 
DIFFERENT FORMS OF LABOUR 
FORCE ACTIVATION

The results of our simulation exercise are best presented by 
illustrating the evolution of the labour force over the next 45 
years under various scenarios, accounting for the dynamic 
processes and factors outlined above. Figure 4 depicts the 
percentage and absolute difference in the labour force in the 
EU between the years 2025 and 2070 for different scenarios. 
These scenarios are not predictions but “what if” scenarios. 
The purpose of these intentionally optimistic scenarios is 
not to indicate a likely future but to highlight through a 
demographic simulation, the opportunity - and hence the 
policy importance - to invest on human capital improvements 
to at least partly contrast demographic decline.

decades. In the standard ‘Static’ scenario (green line), 
which aligns with the approach of the ESDE Report and 
assumes that participation rates for each age-sex group 
remain constant at the average level observed between 
2011 and 2022, population ageing will lead to a decline in 
the size of the labour force by 20.2 pp. This is equivalent 
to around 42.8 million fewer people in the labour force by 
2070. It is important to note that, by design, this decrease 
almost entirely coincides with the decline in the size of 
the working-age population. As acknowledged in the ESDE 
Report, this is due to the fact that the ESDE approach does 
not introduce new dynamics into the projections.  

FUTURE EU WORKING-AGE POPULATION 
WILL DECLINE SIGNIFICANTLY

Populations in Europe are ageing and, as a result, the 
working-age  population  will  shrink  over  the  coming 

Adopting the cohort synthetic model (CSM) from the Ageing 
Report leads to a narrow improvement in terms of labour 
supply by enhancing the participation rate assigned to 
new cohorts. The line depicting the CSM scenario (yellow 
line) shows a slightly higher future working population 
compared to the standard scenario, with a decrease in 

FIGURE 4.  Projections of the percentage (left y-axis) and absolute (right y-axis) decline of the labour force in EU 
countries between 2025 and 2070 under different scenarios.

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Source: Eurostat (EUROPOP23) and IIASA (SSP projections).

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A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT2. SIMULATING THE EFFECT OF DIFFERENT FORMS OF LABOUR FORCE ACTIVATION 
 
 
 
 
 
 
 
9

the labour force of 18.4 pp or 40.1 million workers. This 
positive effect results from the CSM’s partial accounting of 
the increasing labour force participation of women observed 
in recent years. Overall, however, the figure indicates only 
marginal differences between the approach of the ESDE and 
Ageing Report in terms of the projected future workforce. 

ACTIVATING LABOUR FORCE POTENTIAL OF 
POPULATION SUBGROUPS HAS A LARGE 
EFFECT 

In the counterfactual scenario accounting for progress in 
emancipation, we assume that the female labour force 
participation rates gradually converge to the higher male 
participation rates (‘Women->Men’ scenario, red line). By 
2070, this trend towards labour market emancipation 
will have almost halved the effects of population ageing. 
Under this scenario, the labour force is projected to 
decline by 11.0 pp, or 23.2 million people, by 2070. This 
underlines the great potential of harnessing women’s 
active participation in labour markets. 

The counterfactual scenario addressing the expansion 
of educational attainment in the EU relies on population 
projections of sub-populations of educational groups 
provided by IIASA (‘Education’ scenario, orange line). Since 
more educated individuals tend to have a higher labour 
force participation rate, the projected relative increase in 
the size of more educated sub-populations will lead to 
a larger total labour supply compared to the standard 
scenario.9 Hence, this counterfactual approach explicitly 
accounts for educational growth, and the labour force is 
projected to decrease by 15.6 pp, equivalent to 33.2 million 
less people in the labour force in 2070. Nevertheless, 
unlocking the potential for educational improvement offers 
only about half of the potential that appears to be hidden 
in emancipatory progress.  

Among all MS, Sweden emerges as the country with the 
highest labour force participation rates. We simulate 
the effect on future projected labour force participation 
in the EU if all MS were to gradually converge towards 
the advanced level of participation of each population 
subgroup by age, sex, and education that characterises 
Sweden (‘MS->Sweden’ scenario, blue line). The figure 
shows that such a convergence would almost completely 
offset the projected negative impact of ageing on labour 
supply, with a projected labour force decline by only 2.8 
pp, or just 5.9 million people, by 2070.

The Draghi Report makes explicit reference to the problems 
arising from a falling “ratio of working to retired people”. 
The challenges associated with shrinking working-age 
populations and the sustainability of pension systems 
have fuelled public debates in many European countries 
on the need to raise the retirement age. At the same time, 
data on current trends reveal that retirement ages have 
already been rising in many OECD countries in recent 
years (OECD, 2019). Furthermore, the ESDE Report notes 
that demographic challenges call the “sustainability of the 
EU pension [systems] into question”. The Ageing Report 
also contains a number of coarse scenarios assessing 
the effects of different types of pension reforms, such 
as linking the retirement age to life expectancy.10 In an 
additional scenario, we examine the potential impact of 
increasing the labour force participation of older cohorts. 
We very crudely assume that the labour force participation 
rates of the 65-69 age group gradually converge to the 
participation rates of the 60-64 age group (’60-64->65-
59’ scenario, light blue line). It should be noted that our 
approach only roughly accounts for the potential effects of 
pension reforms, not capturing all nuances of the complex 
discussion about the issue. Nevertheless, it can provide 
indicative results, as our assumption leads by design to 
higher labour market engagement of older people and 
simulates the impact of extending the lifetime employment 
duration. The simulation indicates that such a prolongation 
of active working life will bring about advances in labour 
force development, with 11.9 pp or 25.2 million fewer 
people in the labour force by 2070. While these advances 
exceed the potential generated by educational expansion, 
they are very similar in magnitude and slightly below the 
improvements in the labour force potentially resulting 
from progress in emancipation.  

Finally, we analyse the effects of migration on future 
labour force participation. We simulate in a counterfactual 
scenario the hypothetical effects of eliminating migration 
to the EU (‘No migration’ scenario, purple line). Of all 
the scenarios analysed in this brief, this one results in 
the largest reduction in the future labour force, with a 
substantial drop of 26.7 pp, or 55.9 million people, by 
2070. This underlines the large potential of migration to 
partly offset the projected adverse impact of ageing on 
labour markets over the coming decades.  

In  summary,  our  simulation  exercise  reveals  that 
compositional demographic change can be expected to 
mitigate some of the adverse effects of population ageing 
on the size of the future labour force, as illustrated by 

9 

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It should be noted that our approach does not take into account potential variations in the positive trends in education. For example, 
recent results from the Programme for International Student Assessment (PISA) or the Survey of Adult Skills (PIAAC) may suggest that 
there is no guarantee that the educational progress of recent years will be sustained indefinitely into the future. Nevertheless, in our 
simulation of a counterfactual scenario accounting for education trends, we use the official projections provided by IIASA as a tool to 
approximate future education dynamics.
This is in line with existing legislation in a large number of EU MS. In ten MS, the retirement age is linked to increases in life expectancy. 
In addition, in most MS characterised by a gap between male and female legal retirement ages, the lower statutory retirement age 
for women can be expected to be adjusted under current legislation. Furthermore, the academic literature on the effects of raising the 
retirement age is extensive. See for example [7] or [8] for two most recent contributions to this literature.

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT2. SIMULATING THE EFFECT OF DIFFERENT FORMS OF LABOUR FORCE ACTIVATION10

the ‘CSM’ or ‘Education’ scenario. Both scenarios take 
the  changing  compositions  of  populations  and  the 
characteristics  of  certain  population  subgroups  into 
account, which can be seen as more or less given. In 
contrast to these given dynamics, the remaining scenarios 
point to the potential of labour activation policies and 
pension reforms for alleviating some of the effects of 
population ageing on future labour markets. Combining 
all forms of activation, as illustrated by the scenario 
simulating the adoption of the Swedish labour force 
participation rates, would almost fully compensate for 
the decline in the workforce.

LABOUR FORCE ACTIVATION POTENTIAL 
VARIES WIDELY ACROSS MS   

In addition to aggregate projections for the entire EU, our 
simulation exercise allows us to disaggregate our results 
by scenario at the country level. Figure 5 depicts for the 
single MS the potential of each scenario for boosting 
labour force participation in the year 2070.

Figure 5 illustrates the heterogeneous level of workforce 
engagement across MS. In the standard ‘Static’ scenario, 
the projected labour force participation rate in Sweden 
accounts for 56.4%, while it amounts to only 38% in Italy. 
This means that the participation rate in the country with 
the largest labour force share will be almost 20 pp higher 
than in the country with the lowest. 

Unsurprisingly, these different levels of labour market 
engagement imply that the potential of labour force 
activation varies considerably across EU countries. The 
figure shows this by depicting for each individual country 
how much the labour force under the different scenarios 
would deviate from the projected labour force under the 
‘Static’ standard scenario, which is used as a reference. 
Presenting the effects as deviations neutralises the effects 
of demographic change and population ageing, meaning 
that the deviations are purely driven by differences in the 
educational composition of the population and labour 
supply across the scenarios. For example, Italy’s labour 
force participation rate would be 41.5% higher in 2070 
if it were able to eliminate barriers and adopt the higher 
level of labour market participation of Sweden. Similarly, 
advances in female labour force activation or accounting 
for educational progress would increase the labour force 
in Italy by 24.8 and 13.9% respectively compared to the 
standard projections. At the other end of the spectrum, in 
Sweden, the hidden potential in all forms of labour force 
activation is well below an increase of 10%. 

For instance, simulating the extension of the lifetime 
employment duration or progress in emancipation would 
increase the future labour force participation in Sweden 
by 8.3 and 7.2%, respectively. Furthermore, figure 5 shows 
that, compared to the standard projections, labour force 
participation rates in MS would be between 4 and 15% 
lower in the absence of migration in 2070. 

FIGURE 5.  Projections of the percentage deviation of the labour force participation rate from the standard Static 
scenario in individual MS in 2070 for different counterfactual scenarios. Countries are ranked on the y-axis according 
to their participation rate in 2070 under the Static scenario. The number on the y-axis next to the country code indicate 
the projected labour force participation rate in 2070 under the Static scenario.

65-69->60-64
CSM
Education
MS->Sweden
No migration
Women->Men

SE 56.4%
EE 53.8%
NL
53.7%
DK 53.7%
IE
52.2%
LV 51.4%
LT
51.0%
49.6%
FI
DE 49.5%
CZ 48.5%
HU 47.5%
AT
47.3%
FR 47.3%
47.3%
PT
BG 46.4%
SI
46.2%
SK 45.8%
BE 44.1%
PL
43.5%
RO 43.2%
LU 43.0%
ES 42.3%
HR 42.2%
40.7%
EL
38.0%
IT

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

40%

Deviation in labour force from the static scenario (2070)

Source: Eurostat (EUROPOP23) and IIASA (SSP projections).

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT2. SIMULATING THE EFFECT OF DIFFERENT FORMS OF LABOUR FORCE ACTIVATION12

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3

3. EDUCATIONAL COMPOSITION 
AND GDP GROWTH 

Figure 6 presents the projections of the educational 
composition of the workforce and of the total labour 
force under the “Education” scenario, at the level of EU27.
To assess the impacts of these demographic changes on 
GDP, we have joined the more disaggregated educational 
groups (based on ISCED 2011) so as to obtain three macro 
educational groups.11 

This is useful when trying to reflect on the implication 
of education (and the educational composition of the 
workforce) for growth since most growth models are based 
on the distinction between low, middle and high skills.

First of all, education has a positive impact on individuals. 
This is usually represented by the concept of (individual) 
returns to education. In essence, this captures the causal 
impact of attending an additional year/level of education 
on (net) wages. A cross-country analysis of the returns to 
education in Europe [9] estimates that, on average, in the 
EU15 one additional year of education yields increases in 
(net) wages between 4.1% (SE) and 9.7% (PT) for males 
and between 3.8% (SE) and 13.7% (IE) for females. 

In another study that looks at returns to education in a 
comparative context [10], the authors consider “returns to 
education” across the world. Focusing on Europe (and Central 
Asia), they estimate an average return to each additional 
year of education equal to 7.3% (in Latin America and in 
Sub-Saharan countries they are equal to, respectively 11% 
and 10.5%, while in the Middle East and in North Africa 
they are 5.7%). Rates of return are, on average, higher for 
females than for males (9.8% against 7.9%) and higher in 
low-income countries (9.3% versus, respectively, 9.2% and 
8.3% in middle and high-income countries).

However, individual returns are just one part of the picture. 
Equally, if not more important, are the social returns to 
education. This term refers to the net social benefits 
accruing to society as a result of individual educational 
decisions and captures the many positive effects that 
education can produce at the societal level: from higher 
health to lower crime to higher innovation and productivity. 
In practical terms, it is often difficult to provide reliable 
monetary measure of all such positive effects (to be 
weighed against the cost on educational investments) and 
this explains why, when discussing the impact of education 

on social welfare, the focus is restricted to GDP or GDP 
growth. From a welfare perspective, this is an undesirable 
simplification. First, the focus is on levels or growth rates of 
a variable (GDP) that does not capture the many positive 
aspects (externalities) of educational advancements. Second, 
the focus is just on averages, not considering what happens 
along the whole distribution of wealth or income (which is 
often more important when dealing with educational policies 
that also have an equity dimension). This is also the reason 
that has led many to reconsider the impact of educational 
policies under the lenses of equality of opportunity, as an 
alternative to the standard efficiency-based approach implicit 
when one only looks at GDP. 

On the other hand, the focus on GDP or GDP growth 
has a positive aspect: it captures at least some of the 
externalities related to human capital investment (those 
that produce an effect on the variables that ultimately 
are captured by GDP), which would not be captured by the 
estimate of the private return to education.

One way to assess the impact of education on income 
and growth is to use macro-economic models, in which 
human  capital  is  treated  as  a  factor  of  production, 
along with physical capital and land. Technology plays 
a fundamental role as an engine of growth, because it 
determines the efficiency with which given levels of human 
and physical capital (for a given amount of land) can 
produce output.  Human capital has a special role though: 
besides being a factor of production it also affects the 
rate of technological change (through R&D activities which 
are mainly human-capital driven). In essence, it is human 
capital that generates long-run growth. 

It should not be a surprise that many economists have 
tried to analyse the long-run implications of educational 
policies (for a review see [11]).

To simulate the long-run implications of the “Education” 
scenario previously described, we refer to a joint DG 
ECFIN – JRC publication [12] that considers the general 
equilibrium effects of increasing the skill composition of 
the workforce on long-run GDP.12 We use their estimates 
to provide some (lower-bound) simulation of the observed 
changes in the composition of the labour force under the 
“Education” scenario.

11 

12 

Level 1: those with up to lower secondary education (corresponding to ISCED 0, 1 and 2); Level 2: those with upper secondary education 
(ISCED 3 and 4); Level 3: those with tertiary education or higher (ISCED 5, 6, 7 and 8).
Similar exercises can be found in [13].

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT 
 
 
 
 
 
13

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FIGURE 6.  Projections of the educational composition of the workforce (left axis and blue area) and the labour force 
(right axis and black line) (2020-2070; education scenario).

Level 2

100%

Level 1

90%

Level 1

e
c
r
o

f

r
u
o
b
a
L

l

t

a
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T

f

o
%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Level 1 - No Education
Level 1 - Primary
Level 1 - Lower Secondary
Level 2 - Upper Secondary
Level 3 - Short Post-Secondary
Level 3 - Post Secondary
Level 3 - Bachelor
Level 3 - Master and higher

220M

200M

180M

160M

140M

120M

100M

80M

60M

40M

20M

0M

e
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r
o

f

r
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o
b
a
L

Level 3

Level 3

Level 3

2020

2025

2030

2035

2040

2045

2050

2055

2060

2065

2070

The paper considers two basic scenarios: a one pp increase 
in the share of medium skills (and a corresponding decrease 
of the share of low skilled) and a one pp increase in the 
share of high skilled (and a corresponding decrease of the 
share of middle skilled). In the first case, the simulated 
impacts on the long run GDP are between 0.27 and 0.9 
pp, while in the second case, the impacts are between 
0.32 and 0.82 pp.13 

For what matters here, we can use the results above with 
some caveats (their definition of low, medium and high 
skilled is different)14. If we consider the period 2020-
2045, the demographic projections on the educational 
composition of the workforce document an increase of 
14.15 pp in the share of high-skilled and an equal decrease 
of middle and low skilled shares. We can hence use the 
lowest value reported in [12] to get a lower bound of the 
aggregate GDP effects of such changes. A reasonable 

hypothesis is that an increase in one pp of high skilled 
produces a long-run increase of GDP per capita of 0.3 pp 
(after 50 years) and of 0.15 pp after 25 years. This implies 
that the impact in 2070 of the changes in the educational 
composition of the workforce observed between 2020 and 
2045 would amount to, respectively, 4.24 pp in 2095 and 
2.12 pp in 2070. These are indeed economically relevant 
changes, pointing to the long-term impacts of human 
capital development. 

As  a  final  caveat,  one  should  always  consider  that 
such macroeconomic models, typically based on three 
educational levels, do not take into account the sectoral 
and  geographical  composition  of  the  economy.  The 
skill composition of human capital, in conjunction with  
educational levels, plays and important role in making 
sure that the right skills are available in the sector and 
places where they are needed.

13  Notice that the full long-run impacts are realised after 50 years. If we consider only the first 25 years after the changes, then the impacts 

14 

are as follows: a) between 0.15 and 0.5 in the case of the increase in middle skilled; b) between 0.17 and 0.44 in the case of high skilled.
The study is based on QUEST III model, a DSGE model that incorporates the basic feature of the New Growth Theory together with some 
New-Keynesian features (like the presence of liquidity constrained individuals). As for the diving forces of growth and their relationship 
with HC and skills, the model is based on the assumption that there is an R&D sector, which employs high skilled individuals (engineers 
and natural scientists tertiary graduates) and uses the stock of ideas generated domestically or abroad to create new ideas, which are 
then applied in production. Low skilled individuals are those who have ISCED 0-2 and middle skilled individuals are all the other workers 
that do not belong to either high or low skilled. Low skilled and medium skilled work in the intermediate manufacturing sector or in the 
final production of goods.

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT 
 
 
 
 
 
 
 
 
 
 
4. CONCLUSIONS AND 
LIMITATIONS 

•  The impact of migration is studied through a scenario 
which does not consider migrants as subpopulation with 
specific labour force participation rates, for instance 
depending on birthplace, length of stay, age at arrival. In 
this way, we cannot test the effect of a reduction of the 
labour force participation rates gap between migrants 
and natives nor the effect of progressive integration 
of migrants in the labour market since their time of 
arrival or the effect of education when migrants arrive 
at young ages or for second-generation migrants who 
are born and educated in the country. 

•   Furthermore,  migrants  are  kept  indefinitely  in  the 
destination countries and are therefore contributing to 
the ageing of populations. 

•   In the final section, we very crudely elaborate on the 
economic implications of demographic changes, but we 
are not able to directly couple a demographic model 
with a macroeconomic model.

These limitations will be addressed in future work using 
a microsimulation model where labour force participation 
of women will be endogenous and interacting with fertility 
and more characteristics of migrants will be introduced. 

In this policy brief, we presented projections of the EU 
workforce using a dynamic accounting of demographic 
changes in the EU population including education.

The EU population is already more educated than other 
major world economies, and the educational attainment 
of the population is expected to continue to rise. 

As the Draghi report emphasises, investing in skills will be 
crucial for the future of EU competitiveness, particularly 
in light of the dire demographic outlook. 

Our projections show that such investment will not be 
able to compensate for the EU’s demographic decline, 
which remains of concern, but can mitigate the reduction 
in the number of workers. In the most optimistic scenario, 
if all the existing potential of labour force activation 
were  harnessed  simultaneously  moving  to  Swedish 
labour force participation rates, the projected adverse 
effects of population ageing could be almost fully offset.  
Furthermore, the estimate of the impact on GPD indicates 
that the increase in skill set, already embedded in the 
evolution of the EU population, could provide the EU with 
a competitive advantage.

The model used in this policy brief remains relatively 
simple and crude. It has the following main limitations:

•  The changes in labour force participation rates are 
only linked to the education dimension and not to 
other characteristics, such as childbearing and family 
formation which could also play a role.

14

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4

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT 
 
 
15

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ACKNOWLEDGEMENTS

We thank Argyrios K. PISIOTIS (DG EMPL), Luca BARANI (DG HOME), Anne GOUJON (IIASA) and Guillaume MAROIS 
(IIASA) for their comments. 

AUTHORS

Federico Biagi
Christoph Deuster
Fabrizio Natale

A DEMOGRAPHIC PERSPECTIVE ON THE FUTURE OF EUROPEAN LABOUR FORCE PARTICIPATION BEYOND THE DRAGHI REPORT 
 
 
 
 
 
 
 
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