Growth potential of EU human resources and policy implications for future economic growth by Joaquín Ramos

Growth potential of EU human resources and policy implications for future economic growth Working Paper 3/2013 Jรถrg Peschner & Constantinos Fotakis

Social Europe Growth potential of EU human resources

Europe is confronted with important socio-economic challenges due to demographic ageing and the decline of the working-age population. Their impact on the size and structure of the European workforce represents one of the key challenges in this context. The paper focuses on what the demographic shift could mean for future employment growth over the period 2010-2060. The proposed methodology makes use of Eurostat's demographic projections (convergence scenario, Europop2010). It employs a set of assumptions related to future growth of the active population, building a high (maximum) and low (minimum) activity scenario. The paper then explores the potential of employment growth in the years ahead subject to these human resources constraints. Employment and social analysis portal: http://ec.europa.eu/social/main.jsp?catId=113&langId=en Contact: empl-analysis@ec.europa.eu Neither the European Commission nor any person acting on behalf of the Commission may be held responsible for the use that may be made of the information contained in this publication. The opinions expressed are those of the author(s) only and do not necessarily represent the European Commissionâ&#x20AC;&#x2122;s official position.

Europe Direct is a service to help you find answers to your questions about the European Union Freephone number (*): 00 800 6 7 8 9 10 11 (*) Certain mobile telephone operators do not allow access to 00 800 numbers or these calls may be billed. More information on the European Union is available on the Internet (http://europa.eu). Cataloguing data as well as an abstract can be found at the end of this publication. Luxembourg: Publications Office of the European Union, 2013 ISBN 978-92-79-32715-5 ISSN 1977-4125 doi: 10.2767/79370 ÂŠ European Union, 2013 Reproduction is authorised provided the source is acknowledged.

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Social Europe Growth potential of EU human resources

Table of Contents Summary ........................................................................................................ 4 1. Introduction................................................................................................. 5 2. A brief demographic profile of Europeâ&#x20AC;&#x2122;s workforce ............................................. 7 3. A quantitative assessment of the impact of workforce contraction on the growth potential of the economy. .................................................................................. 9 3. 1 The analytical framework ......................................................................... 9 3. 2 A stylised model.................................................................................... 10 3.3 What are the perspectives in terms of future potential employment growth at EU level?......................................................................................................... 14 3.4 Can Europe sustain employment and GDP growth in the years ahead? ........... 15 4. A brief assessment of relevant policy measures............................................... 23 4.1 Policies to increase overall employment..................................................... 23 4.1.1 Increasing working hours ................................................................... 24 4.1.2 Increasing labour market participation of age groups beyond age 65 .......... 26 4.1.3 Maximising the potential contribution of migration ................................. 28 4.1.4 Mobility: a barely tapped source of growth ........................................... 31 4.1.5 Reducing qualification mismatches ...................................................... 33 4.2 Policies to increase productivity................................................................ 34 4.2.1 Higher productivity through better education ........................................ 35 4.2.2 Higher productivity through training .................................................... 38 5. Conclusion and policy implications................................................................. 39 Bibliography .................................................................................................. 42 Annex 1: Modelling educational progression ....................................................... 46 Annex 2: Findings at EU Member State level ...................................................... 47

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Social Europe Growth potential of EU human resources

Summary Europe is confronted with important socio-economic challenges due to demographic ageing. Their impact on the size and structure of the European workforce represents one of the key challenges in this context. The paper focuses on what the demographic shift could mean for future employment growth over the period 2010-2060. The proposed methodology makes use of Eurostat's demographic projections (convergence scenario, Europop2010). It employs a set of assumptions related to future growth of the active population, building a high (maximum) and low (minimum) activity scenario. The paper then explores the potential of employment growth in the years ahead subject to these human resources constraints. The analysis shows that some of the economically strongest EU Member States will find themselves confronted with serious employment growth constraints due to labour supply bottlenecks already within the next 5 years, even under extremely high activity assumptions. Several other Member States will face labour constrains over the next decade. Given the strong inertia of demographics, even total EU employment will start shrinking in 10 to 20 years from now. Labour supply constrains will arise considerably earlier in the case of highly educated workers. The authors conclude that if European economies are to continue growing at a welfare-maintaining pace, the focus must be on productivity growth which will remain the only renewable source of economic growth in the long run. EU productivity growth will have to more than double within the next decade compared to the last two decades' relatively modest performance. How could these important productivity gains be generated in a socially sustainable manner? The paper makes use of model simulations to investigate this question â&#x20AC;&#x201C; focussing in particular on the potential impact of skills development and higher education.

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Social Europe Growth potential of EU human resources

1. Introduction The importance of the size and quality of human resources for competitiveness and economic growth has attracted particular attention both in economic literature1 and in policy making. It is generally acknowledged that the path of economic growth of a country is critically affected by the size, quality, and utilisation of its human resources. In the most recent years, the link between human resources and economic growth has gained further attention in most industrialised countries due to the accelerated pace at which the workforce is ageing and declining. This is taking place in an increasingly competitive global economic environment which necessitates ever-faster structural adjustments across economic sectors and the labour force. At global level, Europe is at the forefront2 of these demographic trends. Following a period of almost 40 years of declining demographic dependency, often referred to as the period of â&#x20AC;&#x2DC;demographic dividendâ&#x20AC;&#x2122;3 ,Europe is currently entering a period of workforce ageing and increasing demographic dependency as the baby-boom generation progressively exits the labour market and joins the ranks of dependent population. Although at first glance the economic downturn and its depressing impact on economic growth and labour demand in particular appear to defer the growing demographic pressure on labour supply, this is not confirmed by the analysis of demographic trends. More specifically, the quantitative analysis presented in this paper clearly shows that given how inert the ageing phenomenon is, this postponement effect is relatively small and does not substantially affect the demographic challenges ahead. Some of the best performing EU economies, namely Germany, the Netherlands, Finland and Austria, are already facing labour supply bottlenecks due to the speed at which their workforces are ageing and the lack of labour reserves. A number of important challenges arising from the on-going economic crisis are in direct interaction with the process of workforce ageing. In particular, during the last 5 years, there were substantial job losses in many of the traditional, labour-intensive sectors, in particular construction, manufacturing and trade. However, studies on Europeâ&#x20AC;&#x2122;s future skills needs4 indicate that demand for specific skills in the most dynamic sectors may continue to rise in the future, while demand for labour in a range of low-productivity sectors may keep declining. However, as age and education level appear to be critical factors for promoting skill and geographical mobility, it becomes increasingly difficult for policy makers to promote the employment of low skilled workers made redundant in declining sectors of the economy. This implies that even if there were to be a strong recovery in the years ahead, it would be practically impossible for many of the workers made redundant in these sectors to get an equivalent job since many of them show skills profiles which are different from those needed in the most dynamic sectors of the economy. This leads to the conclusion that a rapidly contracting and ageing workforce during a period of rapid structural change in the economy (and labour demand in particular) may imply a growing risk of labour mismatches which could worsen skill bottlenecks and hinder efforts to reduce unemployment.

1 For a literature overview on the link between Human Resources and Economic Growth see Platt et al (2012), Wilson/Briscoe (2004). 2 Japan is confronted with more advanced ageing of its workforce while South Korea, the Russian Federation, United States and China are among the major global economic powers that will also face increased demographic pressure over the years ahead. For more info see: UN World Population Prospects, the 2012 Revision http://esa.un.org/unpd/wpp/ExcelData/population.htm 3 Bloom et al (2003), Coomans (2012), p. 200. 4 See for example CEDEFOP (2012).

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Social Europe Growth potential of EU human resources

Another growing concern relates to the chronically high youth unemployment observed in many member-States across the EU. It represents a serious risk for the future labour market performance of these generations both in terms of labour market participation and productivity. These considerations show the need for a more systematic study of workforce contraction and its policy implications on future employment and economic growth. Defining an effective policy approach requires a profound understanding of the evolving demographic trends and their interactions with the on-going structural changes in the economy. This paper aims to contribute to this important policy debate by exploring a wealth of reliable information on the future size and quality of the EU labour market. The projection methodology used purposely avoids the hurdles of forecasting future economic trends. Instead, it makes use of a maximum and a minimum activity scenario based on socio-demographic projections and assumptions about qualitative population characteristics. This allows to get a clear insight on Europe’s potential to sustain employment growth during the period from 2010 to 2060 under different hypotheses about future economic performance. The findings suggest that, even in the most optimistic activation scenarios, workforce decline is practically unavoidable and that this will induce a decline in total employment at EU level within a time horizon already between 10 and 20 years. How policy makers will respond to short term and longer term policy priorities within this challenging policy context will be of critical importance for Europe’s future employment and economic growth. The quantitative analysis proposed in this paper provides policy implications clearing this context. Over the next decade, investment in human resources development, activation policies can and should help cushion the impact of both structural unemployment and labour force decline to the largest possible extent. It could help both to reduce unemployment and drive a faster economic recovery. However, the analysis shows that for the most dynamic EU countries like Germany, Austria, Finland and the Netherlands, this would not be enough, particularly if the economic outlook over the next decade becomes more favourable.5 The shrinking workforce will hinder employment growth unless spectacular progress is made in a range of relevant policies including further to activation policies, substantially higher investment in human resources development incentives for higher intra-EU mobility and more effective economic migration and integration policies. With employment set to decline in the long term, the paper provides evidence that Europe’s future welfare will increasingly rely on its potential to strongly accelerate productivity growth, at least until the effects of demographic transition on the EU workforce is expected to end, at some time beyond 2050. In the multi-polar and highly competitive globalised economy of tomorrow, it will be of utmost importance for Europe to retain and further develop its competitive edge by investing in innovation, education and skills and the range of relevant policies necessary to sustain high productivity growth in the years ahead. Following an introduction of the key issues related to the demographic challenge and the future availability of human resources, section 2 provides a brief demographic profile of Europe’s workforce. Section 3 focuses on the potential for future employment growth testing the sustainability of the available human resources at different levels of future employment growth. It assesses what productivity gains will 5 The analysis in chapter 3.4 shows that it will be difficult for these Member-States to sustain an annual employment rate of 1 %, equal to the EU average attained during the period 2000-2008, even for 5 years.

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Social Europe Growth potential of EU human resources

be necessary to sustain a hypothetical 2 % annual GDP growth path. Section 4 briefly assesses potential policy action to increase employment (4.1) before focusing on human resource policies aiming at higher productivity (4.2). It provides model-based evidence on the means by which a different educational mix and better skills formation can increase productivity growth. Section 5 concludes with policy-relevant implications. Country fiches in the annex illustrate the findings of the analysis at Member State level.

2. A brief demographic profile of Europeâ&#x20AC;&#x2122;s workforce According to Eurostatâ&#x20AC;&#x2122;s Europop2010 demographic convergence scenario,6 the EU working age population (aged 20-64 years) attained its maximum of 304 million in 2012. It is now starting to decline, setting off a long period of higher demographic dependency. Today, there are some 1.6 dependent people in total per person aged 20-64 years in the EU-27; by 2060 the ratio will have risen to almost 2. Graph 1: Long-term development of demographic dependency, EU-27 Annual changes in total demographic dependency rate (TDR), where ratio of total population / working-age population (aged 20-64) 0.8

TDR

the

% p.a.

>0: increasing demographic dependency

Zero-migration-scenrio

0.6 0.4 0.2 Convergence scenrio 0.0 -0.2 -0.4 -0.6 -0.8 -1.0

<0: demographic dividend

Sources: Eurostat Europop2010 population projection; before 1990: UN population estimates per country; illustration follows Coomans (2012), p. 199-200.

As people in the baby-boom generation get older, the demographic dividend which has been positive over the last 40 years will turn negative for at least an equally long period, see Graph 1. By 2030 the EU working age population will already have shrunk by 13 million, or more than 4 %.

For details on Europop2010 consult Eurostat on: http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Population_projections.

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Social Europe Growth potential of EU human resources

Graph 2: The impact of demographic ageing on the working age population, EU-27 Change of working age population since 2010 (%)

…change by age group since 2010 (%)

2030, change from 2010 (%)

2020, change from 2010 (%) 0 50-64 -5 -10

35-49

-15 20-34

2060

2055

2050

2045

2040

2035

2030

2025

2020

2015

2010

-20 -20

-10

Source: Eurostat Europop2010 population projection, convergence scenario

Besides the quantitative effects of ageing on the workforce, one should also take into account its structural effects; i.e. the changes it brings about in the workforce age structure. This is particularly important since different age groups have different characteristics in terms of activity rates and education levels. Although the decline in size of EU working age population is just starting, the effects due to changes in the age structure of workers are already visible. This is because the bulk of baby boomers are by now part of the 50+ age group while the younger age cohorts are considerably smaller. This is important for at least two reasons. Firstly, the 50+ age group is traditionally less active than the prime age group. Secondly, since younger age groups tend to have higher education, the falling numbers of new entrants to the labour market considerably reduce the capacity of labour supply to adjust to the rapidly changing skills needed, particularly in the high-skill segment. Analysis produced jointly by the European Commission’s Directorate-General for Employment and Social Affairs (DG EMPL) and the OECD shows that the proportion of skilled workers among retirees will be significantly higher over the next decade compared to the previous one due to the progressive retirement of the baby boomers. New entrants to the labour force with tertiary education are projected to decrease from 3.5 entrants for each retiree to 1.4. As a consequence, despite progress made in terms of education levels, the study foresees a skills squeeze in the EU due to demographic ageing.7 Hence, the size of the highly skilled labour force is expected to increase much more slowly than before.8 The risk of a skills squeeze is a growing policy concern since signs of economic recovery and emerging new employment opportunities often go hand in hand with difficulties in satisfying the need for new skills in the fastest growing sectors of the economy. In turn, concerns over labour demand become predominantly qualitative rather than quantitative in nature.9 Several recent studies converge to the conclusion that skilled employment will keep growing in the decade ahead.10

OECD (2013, yet unpublished). OECD (2012), §§ 41, 45. 9 CEDEFOP (2012). 10 CEDEFOP (2010); World Economic Forum (2010). 8

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Social Europe Growth potential of EU human resources

3. A quantitative assessment of the impact of workforce contraction on the growth potential of the economy. 3. 1 The analytical framework The proposed methodology aims to explore how Europeâ&#x20AC;&#x2122;s future human resources will be able to sustain employment growth under different employment growth scenarios, in particular: How long could Europe as a whole - and each of its Member-States sustain employment growth at annual levels ranging between 0-1.5% before reaching maximum capacity? And then, what would that imply for Europeâ&#x20AC;&#x2122;s economic growth in a situation where employment cannot grow any more or even declines? What levels of productivity growth will be required to keep the EU economy growing? To investigate these questions the proposed methodology avoids the uncertainties associated with the traditional econometric exercise of active population forecasting. Economic behaviour is treated as a parameter of the model rather than its outcome. Instead, the proposed model delimits the range of feasible future active population growth paths by defining a low (minimum) and a high (maximum) activity scenario. This approach does not contest the strong interaction between the demand and the supply side in the labour market. The choice of this methodology is justified by the fact that it is extremely risky to rely on modelling of long-term economic trends or to anticipate future policy-making and its outcome. Instead, the proposed model is based on the idea that it is possible to set up a space of possible future active population growth scenarios which is delimited by an upper and a lower frontier.11 More specifically: The low activity rate scenario reflects a continuation of the current particularly unfavourable labour market situation. It describes a situation of persisting economic stagnation with no growth in activity and in which changes in activity rates relate only to (structural) demographic effects. In contrast, the high activity rate scenario assumes an exceptionally favourable economic outlook allowing for an extremely high mobilisation of human resources in the EU. This requires a number of very optimistic assumptions about future labour market participation behaviour. More specifically, the high activity scenario shows how many more people would participate in the labour market if the unused pools of human resources (namely women and older workers) could be better utilised and if the foreseen progress in education is fully reflected in terms of gains in participation (a well-educated and skilful workforce helps to improve both activity and employment rates). Obviously, the size of those benefits would also depend on a variety of factors, in particular: the global economic environment which affects the demand side of the economy, the effectiveness of policy making12 and the overall competitiveness of the economy including the optimal functioning of the domestic labour market. Therefore, the high activity scenario should be seen as an extreme situation combining all favourable trends on both the demand and the supply side.

To be methodologically in line with the EU2020-target to achieve a 75% employment rate for people aged 20-64 by 2020, it is first assumed that employment and active population growth can only come from the population aged 20-64. The assumption will be relaxed in section 4.1.2. below. 12 The high activity scenario assumes maximum policy outcomes also including the possibility of new policies which nevertheless do not require a change in the Eurostat definition of working age population. However, the potential from a further increase in the retirement age is treated separately in chapter 4.1.2.

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Social Europe Growth potential of EU human resources

3. 2 A stylised model The following technical assumptions are applied to the low and the high activity scenario: Low activity scenario The low activity scenario takes account only of the demographic effects as projected in the convergence scenario of Europop2010. That is, it includes the impact of workforce contraction and the effect of the changing age structure on activity, keeping all other factors unchanged. This implies that activity rates by age group, sex and educational attainment level are kept constant at 2011 levels. No further progress is assumed, so changing overall activity rates only reflect structural changes (in age, sex and educational structure). This appears realistic for the low activity scenario since the activity rates at the starting year 2011 reflect a labour market situation at the peak of the economic crisis. High activity scenario Alongside the purely demographic effects set out by Eurostat’s Europop2010 convergence scenario, the high activity scenario includes highly optimistic assumptions on future behavioural changes in terms of higher activity rates. More specifically: •

Educational progress is taken on board using Coomans’ method (see Annex 1 for details). Most Member-States have seen an increase in the number of highly educated young people at the expense of those holding basic degrees, while the share of medium educated people has stayed relatively stable. Based on the educational progression seen over the period 2000-2011 for those aged between 25 and 34, we include a log-linear projection of the observed trend into the coming decades. Graph 3a shows that higher education has a measurable positive effect on labour market participation. Looking at the activity rates, there is a 10 percentage point difference between high and medium-skilled people and a 13 percentage point gap between medium and low-skilled people.

Graph 3a: Activity rates by educational attainment level, 20-64 age group, EU-27 90 85 80 75

LOW educated MEDIUM educated

HIGH educated

65 60 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Source: Eurostat EU Labour Force Survey (EU LFS)

Therefore it appears safe to assume that the trend towards a higher proportion of highly educated people will continue to have a positive impact on activity

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Social Europe Growth potential of EU human resources

rates and hence on the size of the active population. However, following the log-linear trend prolongation, the pace at which the number of high-skilled (low-skilled) workers is projected to grow (decline) from now on will be much slower than it used to be in the recent past. Graph 3b: Projection of total workforceâ&#x20AC;&#x2122;s educational attainment structure, based on computed educational progression of the 25-34 age group, EU-27

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario, method based on Coomans (2012), p. 202/203.

Graph 3b shows the projected share of the total working age population holding high, medium and low educational degrees, following from the educational progression of the age group 25-34 years. The impact of progress in education on activity is shown separately in Graph 7. Note that no further educational progression is assumed for the age cohorts aged 35 years and older. If one combines the age- and gender-specific activity rates by educational attainment level with the projected population shares, this results in an increase of the overall EU activity rate from 75.7 % today to 77.7 % by 2040. This would be purely the effect of education, not combined with other effects (i.e., net of progress made in female and older workers participation). â&#x20AC;˘

The female convergence effect is a purely behavioural assumption on activity. It is assumed that by 2030 female activity rates will converge to male levels for every age group and educational level. The chart shows the female convergence effect, (net of other effects such as higher activity of older workers, higher education).

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Social Europe Growth potential of EU human resources

Graph 4: Female activity rate assumed to attain male activity rates by 2030 for each age group and educational attainment level: activity rates in %

90 80 70 60 50 40

Males, age 20-64 Females, age 20-64

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

â&#x20AC;˘

A further behavioural assumption includes the older-workers-effect:

Graph 5: Scenario of progression in the activity rate of older workers (age 55-64) to 60 % by 2030, activity rate in %

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

The high scenario assumes a 20 percentage-point increase of the activity rate among older workers by 2030. If there is an overlap with the female convergence effect (i.e. for women aged 55-64) it is assumed that the two effects cumulate. The chart shows the isolated older workers effect, i.e., net of other effects (higher female participation, higher education). The resulting high and low scenarios for the EU labour force growth are illustrated in Graph 6 in terms of number of people and in percentage of working age population. Graph 6 shows that in the low scenario, where the only changes are due to demographics, the decline in the labour force already starts in 2013. According to this scenario (with no progress in activity rates), by 2020, Europe will have lost 4 million active population compared to 2011. However, in the context of a more favourable economic environment and a more effective activation strategy reflected in the high activity scenario, Europe could mobilise some 14 million additional workers by 2020

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Social Europe Growth potential of EU human resources

and another 9 million by 2030, countering the effects of the shrinking and ageing workforce and maintaining positive growth of its active population until 2030. In fact, the activity rate would shift to 81% by 2020 and around 87% by 2030 and after. Graph 6: EU-27, high and low activity scenarios of future activity growth

EU-27 Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

306

Active Population, Low activity scenario

Active Population, High activity scenario

millions

Past employment

% of Working Age Population (20-64 years) 85.0

286

266

80.0

246 75.0 226

70.0 206

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

65.0

2000

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

186

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

The assumptions on activity rates among women and older workers are purely mechanical. Nevertheless, as the high activity scenario combines and accumulates a number of beneficial effects on activity resulting in activity rates close to 90%, it could well be seen as the upper threshold of what is possible. The gap between high and low activity scenarios then provides a measure of the maximum gains in activity to be expected under a very favourable economic and policy environment.

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Social Europe Growth potential of EU human resources

3.3 What are the perspectives in terms of future potential employment growth at EU level? After setting out the higher and lower scenarios of potential growth in the EU labour force (active population), the next step is to examine the sustainability of employment growth on the basis of this set of labour force growth constraints. To answer this question, we looked at the sustainability of four different employment growth scenarios ranging from 0 % p. a. to 1.5 % at 0.5 %-pt. intervals. Graph 7: EU-27, high and low scenarios of future growth of active population

EU-27 Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

306

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years) 85.0

286

Employment growth scemaro :

266

80.0

1.5% p.a. 246

1% p.a. 0.5% p.a. none EU2020

226

75.0

70.0 206

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

65.0

2000

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

186

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

Taking the scenario of low activity growth (red continuous line), we can see that, even at 0 % employment growth, the EU employment level will cross the low activity scenario level by 2040. This implies that if the future activity outlook is best described by the low activity scenario then all unemployment could have been absorbed by 2040 due to workforce decline. However, this is quite improbable since this would require absence of labour market mismatches. In reality, one would expect to see growing labour mismatches as the economy approaches its activity limits. In such a case, employment in volume will start shrinking much earlier than in 2040. At 0.5 % employment growth, the lower scenario limit will be reached by 2024. The remaining two scenarios of higher employment growth at 1 and 1.5 % correspond to even shorter periods of sustainable employment growth (2019 and 2017, respectively). Nevertheless, in practice it would be rather improbable to have a situation where relatively high employment growth - at or higher than 1 % - would be paired with such a pessimistic assumption on activity13 since in practice labour shortages tend to encourage activity.

That would imply that strong demand for workers would attract many unemployed people, yet people that have been inactive to date would still stay away from the labour market.

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Social Europe Growth potential of EU human resources

Turning to the high activity scenario (blue line), it is projected that, with employment growth at 1 %,14 the limit of active population will be reached around 2030. However, attaining such a dramatic improvement in terms of activity rates as set out in the high activity scenario would be extremely difficult given the extremely generous nature of the assumptions made. As a result, it is a question of years rather than generations until the workforce decline will start inhibiting employment growth. The situation is likely to be even more restrictive than follows from the simplistic approach presented so far. More specifically: • • •

•

The high activity scenario cumulates various effects which overlap in reality15 and is therefore to be seen as an upper, almost ideal, limit of what is possible in terms of active population growth. At aggregate EU-27 level, both scenarios implicitly assume perfect mobility of workers across the borders of the 27 Member States - a very generous assumption given the low levels of intra-EU mobility seen so far (section 4.1.4). As said earlier, the methodology employed here assumes that all unemployed people constitute a readily employable reserve of workers who could immediately respond to the arising labour market needs. This, however, is a highly optimistic assumption. The rapid structural changes in the economy imply that labour demand is changing quickly while labour reserves find it more and more difficult to respond due to their skill (and age) profiles. Skills mismatches are the result. They imply that an increase in labour demand will not automatically lead to an equivalent reduction in unemployment (section 4.1.5). Finally, the relatively high employment growth rates observed until 2008 (about 1% per year) were fuelled both by a strong global growth and an increasingly plentiful supply of labour (as children of the baby-boomers and migrants entered the job market); this in turn promoted economic activity expansion; In the future, in case of a strong recovery of labour demand, labour scarcity may represent a much stronger constraint for employment growth due to the advancement of workforce ageing and shrinking.

Relaxing the above assumptions would lead employment growth constraints to materialise much earlier and much more profoundly than those depicted by both activity scenarios.16

3.4 Can Europe sustain employment and GDP growth in the years ahead? A sustainable pattern of employment growth in the long run would theoretically require the active population and employment to grow at similar rates, a condition which, as we showed in the earlier section, will be practically impossible to fulfil in the future, even under very generous assumptions.17

14 1 % employment growth is equal to the annual average growth rate observed during the period 2000-08 (before start of the crisis) and also to the rate needed to attain the EU 2020 employment objectives. 15 For example: the older worker effect and the gender effect are assumed to cumulate for older women. Also, although higher female labour market participation is partly due to better female education, both effects are taken separately and hence cumulative in the high scenario. 16 In that sense, even the low activity scenario could be seen as a rather favourable limit. 17 Sustaining the EU working age population growth could require a doubling of net annual migration inflows over the next decade and even higher net inflows thereafter.

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Social Europe Growth potential of EU human resources

Graph 8 illustrates the employment growth constraint and its implications for GDP growth. It depicts the situation shown in Graph 7, but in terms of (per-annum) growth rates rather than levels. The graph is divided into three parts. The first part on the left illustrates the pre-crisis situation in terms of employment (green line) and productivity (red line) growth rates. It shows that between 2000 and 2008 Europe achieved average annual employment growth of 1 %. Together with an average annual productivity gain of approximately 1 %, this led to annual average GDP growth (dark blue) of 2 %. The economic downturn has interrupted this relatively stable pattern of growth. Between 2008 and 2011 (middle part of the Graph 8) both employment and productivity growth collapsed18 with employment growth turning negative and average productivity growth averaging at a mere 0.4 % p.a. The third part of the graph refers to the future. Based on the scenarios of high and low activity rates presented in section 3.2, it aims to provide an answer to the question posed at the beginning of this section: Can Europe sustain employment and GDP growth in the years ahead? More specifically: will it be possible for the EU economy to sustain 2 % annual GDP growth in the future as it did between 2000 and 2008? The projection illustrated in Graph 8 (at right) assumes that, from 2012 onwards, a ‘sustainable’ employment growth path (green line) of 1 % will be achieved at first. 2 % GDP growth, the level deemed necessary to maintain current welfare standards, would require annual productivity growth of 1 % from 2012 onwards (red line). In other words, productivity growth is a residual variable equal to the difference between the GDP growth target (blue line) and employment growth (green line). The continuation of the 1+1=2 average annual growth path observed between 2000 and 2008 will be possible as long as employment growth is not constrained. However, as employment growth will start falling due to the declining working-age population, productivity growth will have to grow faster in order to compensate, i.e., to keep GDP growth at 2 %. This is projected to happen by 2020 in the low activity scenario and 2031 in the high activity scenario. Hence, the duration of the period during which Europe will still be able to maintain its 1+1=2 growth path depends on two labour sources: •

Firstly, it depends on the size of the active population. This will have to take account of both the accumulated stock of unemployed at the starting point and projected demographic developments that determine future balances between labour market entries and exits. The evolution of the low activity scenario illustrates the potential of labour resources in that respect.

•

Secondly, it depends on how successful policies will be in further increasing employment and activity rates across all ages, genders and education levels. The high activity scenario outlines an upper limit of what could be obtained if policies of this kind were to be highly successful. The difference between the two scenarios represents this policy component. It offers the feasible outcomes depending on the extent to which the available human resources are mobilised.

It is worth noting that this fall in productivity is to some extent due to short-term job protection measures which diverted some of the pressure on employment towards cuts in hours worked to prevent an even steeper employment decline.

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Social Europe Growth potential of EU human resources

Graph 8: Future employment growth potential and levels of productivity growth required to sustain 2 % GDP growth in EU-27

3.0 2.5

Projected employment growth rate, low activity scenario

Projected employment growth rate, high activity scenario

Productivity growth required to have 2 % GDP growth, low activity scenario

Productivity growth required to have 2 % GDP growth, high activity scenario

GDP growth assumed

Past employment growth

Past productivity growth

Past GDP growth

avg 2000-2008

avg 20082011

2.0

annual growth in %

productivity growth needed to sustain 2% GDP growth (low sc.)

1.5 1.0

High activity scenario future employment growth potential: +1% possible until 2019 (low sc.)

0.5 0.0 -0.5

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.0 Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

Under the low activity scenario (green line), Europe could sustain an employment growth path at 1 % no longer than 2019 despite its current high levels of unused labour reserves. The declining working-age population would actually drag employment growth down to negative values as from 2021. In turn, Europe would find it difficult to sustain 2 % GDP growth after 2020 since it would be impossible to sustain positive employment growth any longer. Compensating for this drop in employment would require a dramatic increase in productivity growth (red line) from 1 % to as much as 2.5 % already required by 2021. In the case of the high activity scenario, policies providing for a maximum utilisation of the available human resources (dashed green lines) would extend the possibility for growth at the‘1+1=2 %’ growth pattern for 12 more years, that is, from 2020 as set out in the low scenario to around 2032 in the high scenario. Hence, mobilising unused human resources could provide the European economy with an additional decade of employment growth needed to sustain GDP growth at 2 %. However, it will be practically impossible to sustain this growth path beyond 2032. The predicted workforce decline will require ever higher rates of productivity growth (red dashed line) to sustain positive GDP growth. In fact, even assuming the high activity scenario, productivity growth rates would have to be at levels up to 2.5% annually in the long run, more than twice as high as in the pre-crisis period up to 2008.Those would still have to be combined with employment rates beyond 85 %, as seen in Graph 7 above (right). Although the situation varies considerably between EU Member States and even regions within Member States,19 the pattern of future workforce shrinking is a common challenge affecting all Member States - with differences in terms of intensity and

Peschner (2011 and 2012) looks into Europe’s NUTS-2 regions. He shows that even under very optimistic assumptions about employment performance in those regions which have lagged behind so far, the EU would still have to multiply precrisis-level productivity gains over the decades to be able to compensate for the inevitable overall employment losses.

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timing. We have made use of the same methodology as above for each individual Member State in the country fiches set out in Annex 2. Graph 9a brings together the most salient information from the country analysis: it shows how long each EU Member State could sustain a rate of employment growth at 1 %. The length of the red bars indicate the number of years between the low and high activity scenario or, in other words, the extra period of time a country will gain if it employs effective activation policies to make the best use of its unused labour reserves. The chart shows a diverse situation in terms of future workforce constraints. A first grouping of countries, and in particular Germany, the Netherlands, Finland, Austria and Bulgaria20, face more immediate risks of labour supply bottlenecks because of their very limited unused labour capacities and a rapid decline of working-age population as projected according to Europop2010. In this context, the labour market situation in Germany is the most interesting case, both due to its advanced ageing pattern and to its impact on the European economy as a whole. The decline of the working-age population in Germany has been underway for a number of years. In addition, German labour market figures show relatively low levels of unemployment. As a result, further activation policies show relatively limited potential to generate further active population growth so that the difference between the two scenarios is less pronounced. The results indicate that Germany could not sustain a 1 % employment growth path beyond 2019 even with maximum activation of its unused reserves, see Graph 9b. Over the next decade Germany will find it difficult to sustain employment and its GDP growth path without recourse to much higher inflows of foreign workers and a substantial increase in its annual productivity growth (the Netherlands, Finland and Austria face similar challenges). As a result, for a 2% GDP growth, necessary productivity growth levels in Germany would peak at levels around 3% annually in both scenarios, three times the pre-crisis productivity growth levels.

Despite above-average unemployment, Bulgaria faces similar workforce shortages. It could sustain employment growth at 1 % until 2020 at best. The working-age population is set to continue to shrink particularly quickly in that country.

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Graph 9a: Critical year after which 1 % employment growth will not be possible any more, EU countries 2040

2035

Critical year, high activity scenario

2030

2025

Critical year, low activity scenario

2020

Netherlands Germany Malta Austria Finland Bulgaria Czech Republic Romania Denmark Poland Slovenia EU-27 Belgium France Estonia Italy Latvia Hungary United Kingdom Lithuania Sweden Portugal Slovakia Greece Luxembourg Spain Cyprus Ireland

2015

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection, convergence scenario

Another, more diversified, group of Member States have relatively larger reserves of unused labour capacity (longer bars in Graph 9a). These are countries with either a relatively favourable demographic profile in terms of workforce growth (Ireland, UK, Belgium, Cyprus, Luxembourg) and/or countries with substantial pools of unused labour capacity due, for instance, to low female participation or faster educational progress (as in the Mediterranean countries). These countries could extend their labour supply potential considerably through more effective activation policies.

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Social Europe Growth potential of EU human resources

Graph 9b: Future employment growth potential and levels of productivity growth required to sustain 2 % GDP growth, example of Germany

4.0

Projected employment growth rate, low activity scenario

Projected employment growth rate, high activity scenario

Productivity growth required to have 2 % GDP growth, low activity scenario

Productivity growth required to have 2 % GDP growth, high activity scenario

GDP growth assumed

Past employment growth

Past productivity growth

Past GDP growth

avg 2000-2008

3.0

avg 20082011

annual growth in %

2.0

1.0

High activity scenario

0.0

-1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0 Source: Own calculations based on Eurostat EU-LFS and Eurostat Europop2010 population projection, convergence scenario

Labour market constraints appear more striking when focusing specifically on highskilled labour needs. This is of critical importance given that high-skilled employment is a decisive determinant of economic growth due to its direct link with productivity, investment and total employment.21 How long could Europe sustain a 1% growth path of highly educated employment against the background of a rapid shrinkage of the highly educated workforce? Graph 9c is based on the low activity scenario.22 The black squares indicate the year after which a total employment growth path of 1 % stops being feasible. These points correspond to the lower end of the bars of Graph 9a. The bright circles indicate the same figure, but only for highly educated workersâ&#x20AC;&#x2122; employment. The graph shows that employment growth at 1 % for the highly educated will be inhibited well before the entire workforce becomes scarce although educational progress is projected to continue. This is because the demand for the highly educated is considerably stronger than average labour demand and the corresponding unused labour resources are therefore much more limited.23

See section 4.2 below. We limit the analysis here to the low activity scenario. This is because in the vast majority of Member States the bottlenecks in terms of highly skilled workers appear already within the current decade and therefore the results in the case of high activity scenario would not be substantially different. . 23 In 2011, average unemployment amongst the highly educated was 5.6 % whereas total unemployment was 9.7 % according to Eurostat EU Labour Force Survey. 22

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Graph 9c: Critical year after which 1 % employment growth will not be possible for total and for highly educated employment: EU countries in the low activity scenario

2045 2040

critical year, total critical year, high-skilled

2035 2030 2025 2020 2015 Malta Czech Republic Germany Austria Finland Bulgaria Hungary Netherlands Italy Cyprus Romania EU-27 Belgium France Ireland Poland Slovenia Portugal Slovakia Estonia Denmark United Kingdom Spain Sweden Greece Latvia Lithuania Luxembourg

2010

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projections, convergence scenario

In most EU Member States the bottlenecks for the highly educated arise within the current decade, several years before total employment growth at 1 % becomes unsustainable. It is particularly interesting to see that this kind of labour constraint also happens to countries with relatively larger overall labour reserves, such as Ireland, Cyprus and Spain. This is mainly because the economic crisis had less of an impact on the employment/activity of highly skilled people than the corresponding averages. In turn, due to the long economic crisis, the majority of Member States have accumulated a human resources â&#x20AC;&#x2DC;bufferâ&#x20AC;&#x2122; which is mainly composed of mediumand low-skilled workers. This buffer does not exist to that extent for high-skilled workers.24 In most EU Member States employment rates among the highly educated are currently above the pre-crisis level. Hence, in the absence of adequate and proactive human resources policies, a lack of skilled labour could constitute an early brake on growth even for countries that have significant labour reserves. It should be underlined that this holds also true from the perspective of productivity growth: If the economy grows and absorbs the unused labour capacity, the average skill level in employment will decrease. Scarcity of labour, particularly of the highly skilled, has the potential to impede future economic growth. However, it is often argued that, although GDP may stagnate or even decline, demographic ageing could result in an increase in per capita income. There is no evidence to support this rather simplistic view. Quite the contrary: looking at the next four decades, the way in which the total population is expected to evolve relative to the working age population is likely to add to rather than solve the problem in most EU Member States.

The bottleneck at the high-skill end is actually a combination of two competing factors. On one hand, as mentioned above, education attainment keeps rising and the overall supply of skilled labour grows at the expense of low-skilled labour. However, this is more than offset by the fact that most unused labour capacity (the unemployed) are less-well educated. If and when the EU economy restarts its growth and demands more labour, it will be constrained by the available unused manpower as it is low-skilled.

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This is because in most Member States the decline of the working age population will start much earlier than the decline of the total population. Graph 10a provides evidence of this phenomenon. The red dots indicate the year when the working age population will start to decline. The opposite end of the blue bar shows when the total population will start to decline. A red dot on top of a blue bar shows that the total population will start shrinking earlier than the population at working age. This is true only for Hungary, Lithuania and Romania. At EU level, the gap separating the two events is 30 years. The EU total population will continue to increase and is set to decline only from 2043, while the working age population will start to decline in 2013 already. This time differential will mean that, for a relatively long period, a declining working-age population will have to generate income for an increasing total population, reflecting higher rather than lower economic dependency and thus more pressure on future productivity gains.

Graph 10a: Starting years of decline of total population and working age population

2060 2050 trend in total population starts shrinking

2040 2030

trend in WAP starts shrinking

2020 2010

both total population and WAP were already shrinking shrinking in 1992

1990

EU-27 Belgium Bulgaria Czech Republic Denmark Germany France Ireland Greece Spain Estonia Italy Cyprus Latvia Lithuania Luxembourg Hungary Malta Netherlands Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden United Kingdom

2000

Source: Own calculations based on Eurostat Europop2010 population projection, convergence scenario

Graph 10b shows the current situation in the EU-27, whereby 2 % average annual GDP growth is currently equivalent to a necessary 2.3 % growth in GDP per capita as the total EU population is growing by some 0.3 % per year. However, the difference will narrow in future decades (see thin blue line) and turn negative only after 2040. As a result, the pressure on productivity will become even stronger as the total EU population continues to grow (see thin orange lines). Only after 2040 will the decline in total population give relief, and even then, it will not exceed 0.2 percentage points by 2060. Hence, the result in per-capita terms stays the same as in nominal terms: productivity in the EU will have to grow twice as quickly as it grew before the crisis in order to counterbalance the impact of a declining workforce on economic growth.25

Even for countries that are already facing small gaps between total and working age population decline, such as the Baltic States and Germany, this lower economic dependency will not provide real relief when the current high levels of public indebtedness are taken into account. During the crisis, average government gross debt in the EU-27 soared to 82 % of GDP. Government debt will have to be repaid over the coming years. If the population shrinks, the per capita debt burden will be heavier when repayment is due. Hence, at given employment levels, higher productivity growth is needed to sustain welfare levels and pay down the accumulated debts.

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Graph 10b: Future employment growth potential and levels of productivity growth required to sustain 2 % GDP growth at EU27 â&#x20AC;&#x201D; taking into account total population change Projected employment growth rate, low activity scenario Projected employment growth rate, high activity scenario Productivity growth required to have 2 % GDP growth, low activity scenario Productivity growth required to have 2 % GDP growth, high activity scenario GDP growth assumed Productivity growth required, taking into account population change 4.0

3.0

2.0

1.0

0.0

-1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projections, convergence scenario

The analysis so far showed that for a number of EU Member States, including Germany, Europeâ&#x20AC;&#x2122;s largest economy, and for Europe as a whole, it may be impossible to reach a sustainable path of employment growth at 1 % due to labour force shortages that will become apparent already before the end of this decade. Policies that seek to expand labour supply will be particularly important in the next decade to make best use of the available human resources. Looking further into the future, the analysis indicates that even if successful labour supply policies are introduced within the next decade, they will not prove sufficient for sustaining employment growth in the EU over the longer term due to the shrinking workforce. The results suggest that Europeâ&#x20AC;&#x2122;s GDP growth will depend largely on its ability to strongly accelerate productivity growth over the coming decades.

4. A brief assessment of relevant policy measures 4.1 Policies to increase overall employment However, from short to medium-term perspective, policies to increase overall employment can and should help offset the labour force decline to the largest possible extent. They could also contribute to a faster economic recovery. It is still crucial to introduce an effective policy mix involving investment in human resources development, activation, incentives for higher intra-EU mobility and effective economic migration. Nevertheless, these policies should be carefully assessed, taking into account the specific characteristics of each economy and the realities of an ageing workforce. The brief overview of policies discussed in this section is far from exhaustive, providing only some critical input to this important policy debate.

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4.1.1 Increasing working hours One frequently mentioned policy measure is to increase working hours. This appears quite relevant since productivity as represented in the above analysis is defined as per-capita production, i.e., (1) P = GDP / person employed. Technically, this is (2) P = Ph * h / employed,

with Ph = GDP / h

i.e., the product of hourly productivity (Ph) and the total hours worked (h) per person employed. Therefore, one could consider relieving the pressure on per-capita productivity P by just working longer hours (increase h). Without discussing the idea at length, some reservations on this approach deserve mentioning. The first concern is with regard to its feasibility. Actual weekly working hours have had a strong tendency to decline since decades. Reversing the trend will be extremely difficult as it is anchored in gradual but fundamental changes in the world of labour which have been taking place in recent decades. These include higher proportions of women and older workers in the workforce, new types of labour contracts, technical innovations and the increasing significance of part-time work. Many of these changes have been beneficial for the quality of work, flexibility and higher productivity. Graph 11: Actual weekly working hours in main job in the EU - statistical breaks (marked in red) in 1995 (EU15), 2005 (EU25), 2007 (EU27) 39.5 39.0 38.5 38.0 37.5 37.0

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

36.5

Source: Eurostat EU LFS

Secondly, increasing working hours appears to be a finite rather than a sustainable source of higher production in the long term. Even if the EU could succeed in increasing weekly working hours over the coming decades from, say, 37 to 38 hours per week on average, this could happen only once. From the political perspective, a subsequent increase from 38 to 39 hours would be even harder to achieve. Thirdly, there is strong theoretical and empirical evidence that Ph and (h/employed) are not mutually independent. Increasing labour units by simply letting people work longer may increase production per worker but, all things being equal, may also result

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in lower hourly productivity Ph, following Gossenâ&#x20AC;&#x2122;s law of a productive factorâ&#x20AC;&#x2122;s decreasing marginal productivity. Studies find evidence for this micro-theoretic restriction.26 In fact, evidence provided by the International Labour Organization suggests that factors related to the quality of work such as physiological aspects, motivation and work organisation have an impact on individual productivity as the number of hours worked changes.27 Finally, there could be a similar effect as regards the number of people in employment. If an increase in h were to be at the expense of employment growth to a certain extent, this would imply that P in equation (2) would grow less than proportionally to h. Graph 12 shows the average proportional employment gains per year between 2000 and 2008 (excluding the crisis) for EU-27 Member States (blue curve). The red curve depicts the difference between the annual average percentage change in P and the change in Ph - which according to (2) is equivalent to the change in the number of hours worked per person employed. There is a negative crosscountry correlation between the two. Graph 12: Employment change and changes in working hours per person employed between 2000 and 2008, annual average in EU countries Correlation: -0.4 4.0%

0.6%

empl

0.4%

3.0%

Diff (shift working hours)

0.2%

2.0%

0.0% -0.2%

1.0%

-0.4% 0.0%

-0.6% -0.8%

-1.0%

-1.0% -2.0%

-1.2%

United Kingdom

Finland

Sweden

Slovakia

Slovenia

Romania

Poland

Portugal

Austria

Malta

Netherlands

Hungary

Luxembourg

Latvia

Lithuania

Italy

Cyprus

Spain

France

Ireland

Greece

Estonia

Denmark

Germany

Bulgaria

Czech Republic

EU-27

-1.4%

Belgium

-3.0%

Source: Own calculations based on Eurostat EU LFS, National Accounts

This finding is far from suggesting causalities, and evidence on that point is anything but clear.28 But particularly in the case of older workers or women, where employment gains have been by far the strongest, it becomes intuitive: In order to attract those groups for the labour market, they would need to be offered attractive working conditions, including part-time work, gradual phasing out and the possibility to combine working life with family commitments - all resulting in reduced working time. In conclusion, the quantitative evidence supporting the hypothesis of a positive relation between hours worked per worker and production per capita as suggested by equation (2) has not yet been firmly established. Depending on many parameters, namely in relation to the job and workersâ&#x20AC;&#x2122; profiles, working longer hours may have quite a diverse impact on labour market participation or/and hourly productivity. For 26

Golden (2005) presents evidence on p. 5. For an overview: International Labour Organization (2004). 28 In fact, there are also studies finding that reducing working hours could bring about employment losses via adaptations of wages (increasing labour costs). See, for example, Steiner and Peters (2000) for Western Germany. 27

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older workers or other categories of workers with a high dependency on working time flexibility, such policy may prove counter-effective. In turn, increasing working hours across the board may not have the expected positive effects on per-capita productivity since parts of the positive impetus may be absorbed by counter-effects on hourly productivity or employment. There are also questions about how feasible it would be to implement since it would entail reversing decades-long trends in established work organisation and production processes. Finally, increasing working hours, even if successful, is not a permanent source of growth.

4.1.2 Increasing labour market participation of age groups beyond age 65 The analysis presented in this paper so far has defined the working age population as the number of people aged between 20 and 64. This definition was introduced in the EU at the launch of the ‘Europe 2020’ strategy back in 2010, when the EU defined its 75 % employment rate objective for the 20 to 64 year-olds. However, recent policy initiatives to activate older workers and, in particular, legislation introduced by some Member States to increase the statutory retirement age for state pensions beyond the age of 65,29 have also drawn policy attention to the labour market outcomes of those aged over 65. In fact, maximising the benefits of living longer while being more active was one of the concerns addressed by the European Year for Active Ageing and Solidarity between Generations (2012).30 Currently, the EU average employment rate for older people (those aged 65 to 69) does not exceed 10 %. As more numerous and better educated baby boom generation has just started to enter this age group, their potential contribution to the labour market may increase considerably in the coming decades. This is why many policy makers are increasingly interested in this age group. Recent experience is encouraging. After the launch of the Lisbon strategy, in the years between 2000 and 2010, Member States made considerable efforts to improve older people’s labour market outcomes. As can be seen in Graph 13, there are reasons for optimism when looking at people aged between 55 and 64 years, for whom the Lisbon target is a 50 % employment rate. Employment in that age group has grown by more than 9 million in the EU-27 (over 7 million for EU-15). Employment policies targeted at older people were successful, although the target was not fully met. Research carried out by the European Commission has also shown that a number of policy measures to activate older workers could continue to be effective tools to further shift older people’s employment rates in the future.31

According to MISSOC (Mutual Information System on Social Protection), Bulgaria, Finland, France, Germany, Ireland, Italy, Poland, Sweden, and the UK have either introduced or envisage pensionable ages beyond 65 years for at least part of the workforce. See http://www.missoc.org/MISSOC/comparativeTables. 30 European Commission (2012:7), p. 28. 31 See European Commission (2011:1), p. 221 – 229, on for a simulation with DG EMPL’s Labour Market Model, particularly on the impact of increasing statutory retirement ages, reducing labour costs for older workers, and training subsidies.

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Graph 13: Older workersâ&#x20AC;&#x2122; employment rate, EU27 % 50.0 45.0 40.0 35.0 30.0 25.0 20.0 15.0

From 55 to 64 years From 65 to 69 years

10.0 5.0 0.0

Source: EU-LFS

However, recent experience shows that it could be more difficult to activate people aged over 64. It would be excessively optimistic to assume that policies designed to increase activity among 65 to 69 year olds could have equivalent success to those achieved for people aged 55 to 64. Even if they were equally successful, the relief would be relatively insignificant and would, in any case, be of a temporary nature given the intensity and lasting pattern of the working population ageing trend. This conclusion is illustrated in Graph 14 in which employment refers to the age group between 20 and 69 years. It assumes that there will be a 20 percentage point increase in activity for both men and women between 65 and 69 to catch up by 2030 (the same as illustrated above for the 55-64 age cohort). The thin lines indicate the changes resulting from the inclusion of people aged between 65 and 69 in the working age population group. Given the low numbers of people employed in that age group, the redefinition of the workforce would not result in a visible change in the employment growth path. The low activity scenario is therefore practically identical to the approach presented above for the 20 to 64 yearsold workforce because it does not contain the older workers or the gender effect. In the high activity scenario, Europe would gain two more years of sustainable 1 % employment growth, making it possible until 2034 instead of 2032. In conclusion, activating people aged 65 and older may have a positive effect on employment growth, but given its relatively limited impact, it can only be seen as part of a comprehensive policy package.

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Graph 14: Future employment growth potential and levels of productivity growth required to sustain 2 % GDP growth in EU-27 â&#x20AC;&#x201D; taking into account population aged 65 to 69 years including 65-59 including 65-59 including 65-59 including 65-59 GDP growth assumed Projected employment growth rate, low activity scenario Projected employment growth rate, high activity scenario Productivity growth required to have 2 % GDP growth, low activity scenario Productivity growth required to have 2 % GDP growth, high activity scenario

4.0

High activity scenario without the 65-69 year-olds

3.0

2.0 High activity scenario including the 65-69 year-olds, (+20%-pt activity rate)

1.0

0.0

-1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

-2.0 Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projections, convergence scenario

4.1.3 Maximising the potential contribution of migration The high activity scenario in Graph 6 assumes that maximum use will be made of the available human resources will be attained by 2030. An implicit part of the assumption for reaching this high activation level would be to substantially improve the labour market performance of third-country migrants already legally residing in the EU. Migration inflows has been the main source of EU population increase in the past decade with a substantial contribution to both employment and economic growth during the period 1996-2008 and limited impacts on domestic wages and employment.32 However, since 2008 the economic crisis has considerably deteriorated the labour market outcomes of the migrant workers. In 2012, there were some 14.8 million non-EU nationals of working age (20 to 64 years) living in the EU-27 and these offer considerable human resource potential.33 According to the Labour Force Survey, only 57 % of them were employed, compared to a 69 % of nationals in the EU countries. The gap is particularly significant for migrant women: only 47 % are employed, compared to 63 % of the EUâ&#x20AC;&#x2122;s native female population. 32 33

European Commission (2008), p. 15. See also Vasileva (2012).

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The speed of the process of labour market integration represents another challenge. There are important differentials in employment rates when comparing recently arrived migrants with those already established for a number of years. Here again an important gender dimension is observed. According to the Labour Force Survey, Employment rates for migrant women established for less than 3 years in the country of destination are as low as 29% while migrant women with more of 3 years of stay attain an employment rate of 47.9%. Another important challenge relates to the labour market outcomes of the migrantsâ&#x20AC;&#x2122; descendants, which represents a key indicator for the integration of migrants in the host societies. Migrants - both native-born offspring of migrants and foreign-born who immigrated before adulthood - account for almost ten per cent of young adults (aged 20-29) in the labour market. Evidence from the OECD has shown that children of immigrants tend to have much lower employment outcomes than the native children in most countries.34 This, according to OECD analysis, is only partly due to their lower educational attainment since a substantial gap remains even when education is controlled for. Graph 15 illustrates a very diverse picture in terms of integration across individual EU Member States.

Graph 15: Employment rates of nationals and people from third countries in the EU27, 2011 Extra EU-27

Declaring country

90 80 70 60 50 40 30

Source: Eurostat EU LFS

The graph shows very significant differences among the Member States regarding their ability to integrate the immigrant workforce pointing to the complexity of factors affecting the process of integration. These are some of the key issues which need to be tackled in order to attain the activity level set for 2030 in the high activity scenario. Closing the employment rate gap between third-country and EU workers would result in 10 million more people in employment and an overall employment rate increase of 0.8 percentage points. It could also provide strong arguments for those in favour of higher migration inflows as a way to address the ageing challenge. This debate has often been polarised, yet it is high on the political agenda. 34

Liebig and Widmaier (2009).

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Many experts and policy-makers in Europe and across the industrialised world converge to the idea that opening pathways for economic migration through a better analysis of the present and future labour market needs and a more effective selection and monitoring of migrant inflows could substantially improve the labour market outcomes of future migrant inflows.35 The impact of migration on employment and GDP growth of the receiving country depends a lot on migrantsâ&#x20AC;&#x2122; skills and on their compatibility and complementarity to the domestic labour supply. The idea of complementarity does not restrict policies towards more low-skilled migrants per se36, but there is evidence that better migrant skills contribute to a better economic and labour market development.37 A simulation with DG EMPLâ&#x20AC;&#x2122;s Labour Market Model confirms these theoretical considerations. Taking France as an example, additional migration flows to increase the domestic population by 5 % would boost employment in the long run by 6 %, labour productivity by 3 % and GDP and capital formation by no less than 9 % and 12 %, respectively, if the additional migrants were only to be high skilled people. Highly skilled migration would help to both boost employment and increase productivity, fuelling both sources of growth in the long run. However, if those migrants were to be low-skilled, investment would actually shrink by 3 % following a fall in labour productivity. This effect would be combined with relatively moderate employment growth (+4 %) while GDP would grow by a mere 2 %.38 Demand for highly skilled labour has been increasing and is projected to continue to increase over the years to come. According to estimates from the European Centre for the Development of Vocational Training (CEDEFOP), although overall job openings in the EU will nearly stagnate in the current decade, demand for highly skilled workers will increase, while demand for low-skilled workers will further decline, by more than 20 %.39 More targeted approaches to attract highly skilled migrants will therefore be needed. However, establishing an optimal selection mechanism does not appear enough for improving the labour market outcomes of migrant inflows. Analysing the differences between Member States seen in Graph 15, Coomans40 underlines the particular role of policy environment and traditions of the host countries in terms of labour market functioning. He points to the quality of integration policies and emphasises the importance of a non-discriminatory deployment. The latter refers to a process of mutual adaptation between migrants and host societies whereby newcomers and native population learn to accept and live with one another. These aspects determine the extent to which such policy approach could be effective or not in the long run. However, relying on migration inflows alone cannot provide a sustainable answer to the EU workforce shrinking. This would imply an ever-increasing pace of migrant inflows to compensate for the decline of working age population. Besides, early waves of migrant workers would progressively leave the labour market, populating, in their turn, the older dependent population. A mechanical estimation of the inflows required by 2060 to preserve economic dependency over time produces a figure of more than 40 million.41 35

See OECD's International Migration Outlook 2013 p. 43-53 European Migration Network: Satisfying labour demand through migration. Synthesis report 2011 p.108. 36 Low-skilled labour working in domestic services helping to allow high-skilled labour (women, in particular) to deploy would be complementary to the domestic skills needs. 37 European Commission (2008), Chapter 2, esp. p. 50-54. 38 Simulation results for other countries go in the same direction. The model supports 14 countries in total. See section 4.2 and the references there for details on the Labour Market Model, particularly the capital- skills-complementarity, which is important in explaining these results. 39 CEDEFOP (2010), p. 100. 40 Coomans (2012). 41 Economic dependency ratio being defined as the number of non-employed in total population. See Peschner (2012), p. 219.

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Taking all these considerations into account leads to the conclusion that migration policy alone cannot be the answer to the workforce decline and its expected impact on employment and growth in the long run. But it can and should be part of the comprehensive policy response to address the challenge. It requires further efforts for making best use of the potential of migrants already living legally in the EU. It also requires opening pathways for new migrant workers, not only on the basis of specific labour vacancies but also on the basis of much broader human capital criteria. An increased and more skilful mix of migrant inflows would have better labour market integration potential and could help attenuating the impact of domestic workforce ageing at least for the next two decades.

4.1.4 Mobility: a barely tapped source of growth Mobility is one of EU citizens’ fundamental rights. Economically, mobility between regions and countries can be a very important guarantee of optimal resource allocation across Europe as people could go where there are vacancies that offer the best fit for their specific skills. In its 2011 European Employment and Social Developments report, the Commission examined the driving forces and the economic and labour market influences on mobile workers in Europe, both in sending and in receiving countries.42 The report concluded that there was ‘an overall positive effect of mobility flows on economies of receiving countries, despite some caveats’43 and that there were ‘some risks for the sending countries but overall no massive brain drain’44. To better show how mobility could contribute to better resource allocation and help European regions grow faster, Graph 16 plots those NUTS-2 regions that combine low unemployment and high employment rates (i.e. regions of potential demand, coloured blue) against those where unemployment is high and employment low (potential regions of supply, coloured red). In a hypothetical world without language barriers and other cultural or administrative obstacles, workers from excess labour supply regions would move to where there is demand, increasing overall employment and contributing to a more sustainable long-term EU employment growth path.

42 43 44

European Commission (2011:1), Chapter 6. Ibidem, p. 280. Ibidem, p. 281.

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Graph 16: Employment / Unemployment gaps in the EU in 2010

NUTS-2 regions combining: employment rate ≤ 65 %, unemployment rate ≥10 % employment rate ≥75 %, unemployment rate ≤ 6 %

Source: Eurostat EU LFS, DG EMPL mapping

However, the reality is more complex and mobility one of the least exploited sources of employment growth. Less than 3 % of the EU’s working-age population are currently mobile EU citizens. Progress in the last decade has been modest, despite enlargement. The number of people in the EU coming from outside the EU is still much higher (almost 5 %) than the number of mobile EU citizens. It is hardly possible to estimate the potential to employment from further advances in policy making in this field. However, given how polarised labour market conditions have become in the EU over the last 5 years and without underestimating the emerging brain drain issues in some EU regions, there is evidence that mobility could still make a very significant contribution to overall employment and GDP growth. In fact, Peschner has shown that even within a country (where language barriers are less important), current mobility patterns across Europe impede in most cases rather than fuel population dynamics and employment growth in the regions.45

Peschner (2012), p. 225.

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Graph 17: EU-15 and EU-27 population aged 20-64 years by citizenship, 2011 7%

2005

2011

5% 4% 3% 2% 1% 0% EU15

EU10

EU2

Extra EU-27

EU27

EU10

EU2

EU15

Extra EU-27

citzenship residence

Source: Eurostat EU LFS

4.1.5 Reducing qualification mismatches In the analysis presented in section 3 it was implicitly assumed that there are no labour mismatches. This means that the stock of unemployed people would be ready for recruitment once labour demand is getting stronger. However, this is not true, particularly in the aftermath of a deep economic crisis when skill mismatches tend to persist. The Commission’s annual report ‘Employment and Social Developments in Europe 2012’ devotes a chapter to the skills mismatch challenge in Europe. It sets out plenty of evidence about the determinants, the impact and the policies to address skills and qualification mismatches.46 According to the report, there is evidence that overqualified people ‘work below their potential in their current job due to some kind of productivity ceiling’.47 Likewise, as regards under-qualified workers, their ‘productivity is found to lag behind that of matched colleagues in the same job’.48 One conclusion is that ‘qualification mismatches entail economic and welfare costs’.49 It is difficult to quantify how much productivity growth would increase if jobs and workers’ qualifications were better matched, but the effect is significant, especially in the context of the current labour market situation. The sources listed in the report provide evidence that both over-and under-qualification are common in Europe. Further sources hint at similar conclusions.50 More specifically, there is evidence that over-qualification becomes all the more significant in times of recession and poor labour market conditions. It reflects a mismatch between jobs and skills as well as regional disparities. In periods of weak labour demand, high- and medium- educated people will compete with people holding low levels of education for jobs below their actual skills level. This effect might explain, at least in part, differences in the employment rates between workers of different education levels. Data from the EU Labour Force Survey confirms that the phenomenon of over-qualification has become more pronounced over the last decade. 46

European Commission (2012:1), Chapter 6, pp. 351 and following. European Commission (2012:1), p. 365. Ibidem. 49 Ibidem, p. 364. 50 According to the 5th European Working Conditions Survey (2010) by the European Foundation for the Improvement of Living and Working Conditions, 13 % of workers in the EU-27 claim that they ‘need further training to cope well with duties’ whereas the proportion of workers who are convinced that they have ‘the skills to cope with more demanding duties’ is around one third. Both figures have remained stable since 2005. Increasing the skills of under-qualified workers to help them better meet the current requirements of their jobs would directly lead to better job performance and higher productivity in their current jobs. Eurofound (2010), question 60. Weblink: http://www.eurofound.europa.eu/surveys/smt/ewcs/ewcs2010_08_02.htm. 47 48

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Half of all workers in elementary occupations held at least upper secondary education in 2011 (classifying them as medium- or highly skilled), a gradual increase by 10 percentage points since 2000.51 Likewise, OECD studies suggest that, across OECD countries, more than one third of workers could actually be over-qualified.52 Reducing over-qualification could bring benefits in terms of both employment and productivity growth. If there were to be more favourable prospects for the labour market, overqualified workers would find it easier to get highly skilled jobs. In turn, this would reduce over-qualification and lead to productivity gains. It could also lead to a better allocation of human resources with more job opportunities for low-skilled workers.

4.2 Policies to increase productivity The analysis presented in section 3 showed that the declining workforce will progressively constrain employment growth. In the long run, the economy will increasingly rely on productivity gains. Strong productivity gains will have to be made in the decades to come if Europe is to maintain sustainable economic growth. The impact of higher education on activity rates is depicted in Graph 7 above. In this context, no qualitative (productivity) consideration was taken into account. However, there are strong indications that higher education would strongly promote stronger productivity growth. The main objective of this section is therefore to highlight the role of education and skills in generating those productivity increases. Using DG EMPL’s Labour Market Model (LMM), we look at two specific measures seeking to increase workers’ productivity: We simulate the impact of an increase in skills towards higher education (section 4.2.1) and the impact of subsidising higher investment in firm-sponsored training (4.2.2) on the labour market as well as on GDP and productivity. LMM is a general equilibrium model for policy simulation with a special focus on the labour market.53 LMM currently supports 14 countries. For the analysis presented in the following, France is taken as the reference country. The two measures presented here are only showcase for policies to improve productivity gains from both from the supply (higher education) and the demand side (support firm-sponsored training) perspective of the labour market. In fact, it is important to include labour demand and job production in a comprehensive policy strategy towards more and better jobs. There must be jobs matching the better educated and well-skilled workforce, and investing in skills and education does by no means reduce the necessity for structural reforms on both product and labour markets. In fact, both better skills and more jobs are necessary conditions towards higher productivity and faster economic growth. However, elaborating on job production is beyond the scope of this paper.54

Eurostat EU LFS, table lfsa_egised. See http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database. Quintini (2011). 53 LMM was developed for DG EMPL by the Institute for Advanced Studies (Vienna) and the University of St. Gallen. It is a multi-generation general equilibrium model which allows for equilibrium unemployment as it takes on board imperfections on the labour market such as mismatches. It describes explicitly firms’ motivation to offer vacancies and workers’ consideration to search for jobs and takes on board the complex wage bargaining process. Its strength lies in this kind of micro-economically founded modelling of labour supply and demand behaviour, but also in its detailed depiction of the respective countries’ labour and institutional framework relevant for the labour market. In addition, LMM includes education as major determinant for investment and growth. For a non-technical description see European Commission (2010), Chapter 2, Annex 2 on pp. 113 and following. See the reports by the model's developers in Berger et al (2009), especially part II; Berger et al (2012). 54 The European Commission, using the LMM, has recently elaborated on the impact of measures to lower labour cost (shifting labour tax towards VAT) in order to support job production, see European Commission (2012:1), chapter 4, p. 275-279. 52

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4.2.1 Higher productivity through better education At the beginning of their careers, each person analysed in the LMM decided individually on the educational level they wished to choose. In doing so, they weigh up the costs of higher education against its merits, including higher life-time income. Using the French example, the aim of the exercise is to see what the transmission channels of higher education into the labour market and the economy will be. The starting point is Franceâ&#x20AC;&#x2122;s particular situation in terms of labour force bottlenecks and the extent to which Coomansâ&#x20AC;&#x2122; method55 predicts that education levels will increase. Graphs 3b and 7 above are replicated for France:

Graph 18: France, high and low scenarios of future growth of active population Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

millions

% of Working Age Population (20-64 years)

85.0

33 Employment growth scemaro :

80.0

1.5% p.a.

1% p.a. 0.5% p.a. none EU2020

75.0

25 70.0 23

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

65.0

2000

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

The situation resembles that in the EU-27 as a whole. In the low activity scenario, a 1 % employment growth path will no longer be possible already around 2020. After that, a stagnating working-age population will drag down employment growth. In the maximum potential scenario the bottleneck will materialise around one decade later. The effect that education has on activity is significant but moderate compared to the assumed behavioural changes of women and older workers in the high activity scenario.

See Annex 1 for further information.

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Graph 19: Future employment growth potential and levels of productivity growth required to sustain 2 % GDP growth, France

2.5

Projected employment growth rate, low activity scenario

Projected employment growth rate, high activity scenario

Productivity growth required to have 2 % GDP growth, low activity scenario

Productivity growth required to have 2 % GDP growth, high activity scenario

GDP growth assumed

Past employment growth

Past productivity growth

Past GDP growth

avg 2000-2008

2.0

avg 20082011

annual growth in %

1.5

1.0

High activity scenario

0.5

0.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-0.5 Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

Around 2021, employment growth will stagnate around zero, so that 2 % economic growth would require a level of productivity growth of around 2 % per annum - more than twice its average pre-crisis productivity growth rate. Graph 20: Projection of change in total workforceâ&#x20AC;&#x2122;s educational attainment structure, based on computed educational progression of the 25-34 age group, France Population by educational attainmelt levels

160 140 120 100 80

Educational 2010=100 progression: Population by educational attainmelt levels Population 20-64, HIGH educated (ISCED 5-6) Population 20-64, MEDIUM educated (ISCED 3-4) Population 20-64, LOW educated (ISCED 1-2)

60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projection, convergence scenario

The projected educational change underlying the education effect is also very similar to that projected for EU-27 above. Medium education would be relatively stable while the number of highly skilled people would increase by 40 %. At the same time there would be a decline in the number of low-skilled workers, falling by some 40 % by 2030. By 2040 these relative changes would be around 50 %.

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Looking at the longer term, these relative changes resulting from the Coomans model imply that the proportion of highly skilled workers in total working age population would rise from 31 % today to around 45 % in 2040 (+15 percentage points, whereas the number of low-skilled workers would decline from 26% today to around 15 % (11 percentage points). For medium-skilled workers there is a slight decrease from 43 % to 40 % (-3 percentage points). For the simulation the endogenous skills decision variable is ‘switched off’ and replaced by an exogenously determined change in the skills mix which resembles the relative change assumed for France up to 2040 as just described (resulting from the Coomans model). In other words: The changes in the skills mix are technically considered as a ‘policy shock’ that would have an impact on both the labour market and the real economy. In LMM, people (with perfect foresight) decide about which educational step to take at the beginning of their careers. It is assumed that 15 % (3 %; 11 %) of them decide to change their education plans towards high (away from medium; low) education. The new skills mix is assumed to stay constant over generations so that in the very long term the total workforce will have adapted correspondingly. The comparative-static model results describe the very long term effects, i.e., the impact of the skills change on macroeconomic and labour market magnitudes in a new long-term steady-state equilibrium. Those results are described in Graph 21. LMM takes on board a capital-skills complementarity which suggests that higher education will promote higher overall productivity and higher investment - the main drivers for higher output. Looking at the high-skilled segment, the following observation holds (for the other skill groups the reverse is true): given the increased stock of high-skilled people, higher demand would match higher supply only at lower wages. Labour productivity for the high-skilled would decline. This is a technical effect resulting from the massively increased headcount of high-skilled employment. However, overall productivity clearly increases due to the changed composition of skills, which pulls up overall wage levels and capital formation and, in turn, leads to higher production and higher total employment. GDP gains would be considerable, 12 % higher than in the initial steady state. However, such a change in young people’s educational choice would require a relatively long period before it would have any significant effect on the total workforce and on the wider economy.

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Wage rate

Employment

Graph 21: Changing educational mix towards high skills, Labour Market Model simulation exercise for France, relative change in %

High-skilled Medium-skilled Low-skilled Total High-skilled Medium-skilled Low-skilled

Labour Productivity

Total High-skilled Medium-skilled Low-skilled Total Investment GDP -40% -30% -20% -10%

10%

20%

30%

40%

50%

Source: Own calculations based on DG EMPL's Labour Market Model

A policy of this kind may only deliver its full benefits over a time frame of 30 years.56 If so, a 12 % long-term increase in France’s real GDP would be equivalent to some 0.4 % higher real GDP-growth per annum. This would be a substantial gain in terms of France’s long-term growth potential. After such measure the necessary productivity shift would still be considerable in order to maintain France’s sustainable long-term GDP growth path, as demonstrated in Graph 19. However, one has to consider that Coomans’ model (with its log-linear trend-prolongation of high and low-skill shares), implies a rather modest, i.e., less-than-linear further increase in levels of education; and that such measure can only be part of a broader policy approach to shift productivity. 4.2.2 Higher productivity through training Improving skills to increase productivity is not restricted to formal higher education. A comprehensive policy package to strengthen skills would also include non-formal lifelong learning and training measures. For example, using LMM, it can be shown that government investment in training measures can have similarly beneficial effects on capital formation, employment and GDP as has better education, with some structural differences. Again, we use France as a template. We assume moderate government spending of 0.1 % of GDP (corresponding to an annual amount of some EUR 2 billion in France) to subsidise firm-sponsored training. This sponsorship would be neutrally financed by lump sum transfers from households. Such spending would deliver the steady-state results displayed in Graph 22.57

LMM assumes a discrete skills decision, i.e., agents decide only once, only at the beginning of their working life. Under such assumption the transmission may take much longer than 30 years. However, one could assume that more cohorts than just the youngest could be targeted at a time. 57 The European Commission has already provided evidence based on LMM simulations that support employer-sponsored training in Germany, restricted to older workers. See European Commission (2011:1), Chapter 5, Section 4.1.3.

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The employment impact of the subsidy is strongest for low-skilled workers because a given amount of subsidy reduces labour costs relatively more if wages are low. The incentive effect for employers to open up more vacancies is therefore the strongest in the case of the low-skilled. The massive employment effect on low-skilled workers causes their average labour productivity to decline despite increasing individual productivity (which increases due to higher training participation). Overall, the picture is similar to that subsidy strengthens skills formation productivity, despite a less favourable As a result, investment and GDP go up

resulting from higher education: The training on the job, triggering higher overall labour educational mix among the employed workers. by some 0.13 % to 0.14 %.

In conclusion: Investment in higher education contributes both to higher productivity and to higher capital formation. On the other hand, informal skills formation will also pay: Government support of workersâ&#x20AC;&#x2122; training in a wider life-long learning policy mix can boost employment opportunities, particularly for the most vulnerable people, induce firms to invest directly in workersâ&#x20AC;&#x2122; individual skills, and attract more people to join the labour market as wage levels increase. In other words, human capital investment, be it in higher education or training, strengthens both sources of growth: employment and productivity.

Employment

High-skilled Medium-skilled Low-skilled Total

Wage rate

High-skilled Medium-skilled Low-skilled Total

Labour Productivity

Graph 22: Government spending of 0.1 % of GDP on workplace training, Labour Market Model simulation exercise for France, relative change in %

High-skilled Medium-skilled Low-skilled Total

0.40%

0.35%

0.30%

0.25%

0.20%

0.15%

0.10%

0.05%

0.00%

-0.05%

-0.10%

Investment GDP

Source: Own calculations based on DG EMPL's Labour Market Model

5. Conclusion and policy implications The challenge The analysis of future demographic and labour market scenarios presented in this paper clearly indicates a growing EU labour supply challenge as the working age

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population will keep shrinking over the next 40 years. The quantitative evidence shows that in less than 20 years EU employment will almost inescapably start declining in volume due to the intensity of workforce shrinking, It is worth noting than even when assuming just a modest economic recovery at 1%, workforce decline appears to drive some of the strongest EU economies including Germany, Austria, The Netherlands and Finland into serious labour supply constraints already by the end of the current decade. Several other Member States and the EU as a whole will face similar difficulties a few years later. As seen in Graph 7, sustaining an average level of 1 % employment growth until 2030 at EU level would require that the EU employment rate grows from the present level of 68 % towards a level well beyond 85 %. This requirement exceeds the quite optimistic ‘EU2020’ employment rate target by 10 percentage points. This practically “full employment” state would require a number of impressive policy achievements in terms of activation policies and progress in education, it would not allow for any gender gap in activity and imply a quantum leap in older workers’ labour market participation. However even if all these assumptions were fulfilled: shortly after 2030, employment will still start declining since it would not be possible any more to compensate for the workforce shrinking through increases of the employment rate. It appear evident that in the absence of employment growth, the only source of economic growth could come from productivity gains – which then will have to more than double compared to the levels obtained during the decade before the economic crisis, to compensate for the foreseen decline in employment growth.58 Undeniably, in the current policy context unemployment represents the main EU concern obscuring by its intensity any other policy issue. However, policy making should not undermine the labour supply challenges presented in this analysis. A meaningful policy strategy should try to address both the short and long term policy concerns: In the short and medium run: keep employment growing as long as possible It is a crucial condition for economic growth to keep employment growing in the short to medium term, making best use of the available human resources. Increasing employment and participation rates will help extending the period of employment growth for the next 10-15 years. A range of activation policies targeting at pools of unused labour capacities and at extending working life are very important at the short to medium term. The paper elaborates explicitly on the potential of women and older workers as these groups represent important targets for activation policies.59 The analysis shows that they could provide a substantial contribution to further employment over the next years. In the same context it will be crucial to also address policy areas of higher political sensitivity: There is clear evidence that geographical mobility could make a very significant contribution to overall employment and GDP growth - without underestimating the emerging brain-drain problems mobility can bring about for some regions. Economic 58

Looking at past trends reveals the extent of the challenge: Real labour productivity growth per person employed in the EU since 1995 was moderate (+1.1% a year on average) - significantly lower than in the US (+1.7 %). Van Ark et al (2013) confirm that past (pre-crisis) slow economic growth in the EU was mainly due to weak productivity performance, particularly in the service sector. They underline the significance of future productivity growth for Europe's economic performance but insist that "a weak outlook for population growth, together slow productivity growth, lack of ICT contribution to productivity growth, weakness in productivity growth in service sector and rising cost levels, doesn’t bode well for the future growth performance of the economy" (p.17). 59 The European Commission has repeatedly set out the core of its ‘EU2020’ strategy. Fighting labour market segmentation, investing in skills and focusing on sectors with the highest growth potential such as health and social care, ICT and the green economy are all part of the employment package. See European Commission (2012: 2 to 6).

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migration represents another essential element of the policy response to address the challenge of workforce decline. It requires a thoroughly new policy approach at EU level aiming both at making best use of the potential of migrants already living legally in the EU while opening clear and stable pathways for new migrant workers on the basis of specific labour vacancies but also on the basis of much broader human capital criteria60. A successful economic migration policy will also require a range of policy measures including effective monitoring of labour market needs, effective systems to recognise skills, successful policies against discrimination and a range of other actions to integrate immigrants faster in the labour market and the host society. In the long run: Higher productivity gains over human capital investment Those activation policies are not to be seen as renewable sources of employment growth. In the simplified model presented above, they will stop contributing to economic growth once employment and activity touch their assumed maximum levels. However, they will provide some more time to implement the range of necessary long term reforms and investments on human resources development, technology and innovation in order to attain the substantially higher levels of productivity growth required in the long run, most probably before 2030, when the shrinking of the workforce will eliminate any possibility of further employment growth. Then productivity growth will remain the only possible source of sustainable economic growth in the EU. Without undermining other factors contributing to productivity growth61, the role of human resources will remain of critical importance. Historically, Europeâ&#x20AC;&#x2122;s long tradition of high quality workers has been one of its key economic assets. In the highly competitive globalised economy of tomorrow, it is of utmost importance that Europe retains this competitive edge by investing in the development of skills and education. Model simulations presented in section 4.2 show that these policies can contribute to making up for the productivity gains needed in the coming decades. In this context, securing a continuous supply of highly skilled workers in the years ahead is a strategic priority for Europe. This is even more important since Europe will not be able to compete with the emerging economies on the global markets in a range of labour intensive, low-productivity sectors for both demographic and economic reasons. Furthermore, improving work organisation and investing in a better work environment are also sources of both higher labour market participation and higher productivity growth. Similar win-win effects for both employment and productivity growth are achieved when fighting over-qualification and promoting mobility. In general terms, there is evidence that good human resource policies lead to both better employment performance and higher productivity.62 Besides they help containing the depreciation of human capital. This represents a major concern particularly for the younger generations in times of long-lasting economic downturn.63

As for instance in the case of Canada. Examining the range of policies aiming at increasing productivity outside the context of labour market is beyond the scope of this paper. 62 Based on a sample of some 1.000 firms in the US, Huselid (1995) finds evidence that â&#x20AC;&#x2DC;investments in [strong human resource practices] are associated with lower employee turnover and greater productivity and corporate financial performanceâ&#x20AC;&#x2122; (p. 667). 63 For example, see Mincer and Ofek (1982). 61

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Bibliography van Ark, B., Chen, V., Colijn, B., Jaeger, K., Overmeer, W., and Timmer, M.: Recent Changes in Europe’s Competitive Landscape — How the Sources of Demand and Supply Are Shaping Up, in: European Economy, Economic Papers 485, April 2013. http://ec.europa.eu/economy_finance/publications/economic_paper/2013/pdf/ecp485 _en.pdf Berger, J., C. Keuschnigg, M. Keuschnigg, M. Miess, L. Strohner, and R. WinterEbmer (2009), ‘Modelling of Labour Markets in the European Union — Final Report’, http://ec.europa.eu/social/BlobServlet?docId=4275&langId=en Berger, J., M. Gstrein, C. Keuschnitgg, M. Miess, S. Müllbacher, L. Strohner, and R. Winter-Ebmer (2012), ‘Development/Maintenance of the Labour Market Model’, Final report of the research study carried out for DG EMPL ec.europa.eu/social/BlobServlet?docId=8952&langId=en Bloom, D., Canning, D., Sevilla, J., The Demographic Dividend: A New Perspective on the Economic Consequences of Population Change, RAND Corporation, (2003). CEDEFOP (2010): Skills Supply and Demand in Europe, Medium-term forecast up to 2020, Thessaloniki 2010 http://www.cedefop.europa.eu/en/Files/3052_en.pdf CEDEFOP (2012): Europe’s skill challenge, Briefing Note, March 2012 http://www.cedefop.europa.eu/EN/Files/9068_en.pdf Coomans, G. (2004): Atlas of Prospective Labour Supply 2005, GeoLabour, Brussels. Coomans, G. (2012): The EU workforce and future international migration, in OECD (2012). Free Movement of Workers and Labour Market Adjustment: Recent Experiences from OECD Countries and the European Union, p. 197-211 http://www.oecd-ilibrary.org/social-issues-migration-health/free-movement-ofworkers-and-labour-market-adjustment_9789264177185-en European Commission (2008), Employment in Europe 2008, Luxembourg: Publications Office of the European Union, esp. Chapter 2. http://europa.eu/rapid/press-release_MEMO-08-719_en.htm European Commission (2010), Employment in Europe 2010, Luxembourg: Publications Office of the European Union, esp. Chapter 2. http://ec.europa.eu/social/main.jsp?catId=738&langId=en&pubId=593&type=2&furth erPubs=no European Commission (2011:1), Employment and Social Developments in Europe 2011, Luxembourg: Publications Office of the European Union, esp. chapter 5. http://ec.europa.eu/social/main.jsp?langId=en&catId=89&newsId=1137&furtherNews =yes European Commission (2011:2), European Agenda for the Integration of ThirdCountry Nationals, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. COM(2011) 455 final, Brussels 20.7.2011

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http://ec.europa.eu/home-affairs/news/intro/docs/110720/1_EN_ACT_part1_v10.pdf European Commission (2012:1), Employment and Social Developments in Europe 2012, Luxembourg: Publications Office of the European Union, esp. chapters 4 and 6. http://ec.europa.eu/social/BlobServlet?docId=7294&langId=en European Commission (2012:2), Towards a job-rich recovery, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, COM(2012) 173 final, Strasbourg, 18.4.2012. http://ec.europa.eu/social/main.jsp?catId=89&langId=en&newsId=1270&moreDocum ents=yes&tableName=news European Commission (2012:3), Commission Staff Working Document on Exploiting the Employment Potential of Green Growth, SWD(2012) 92 final, Strasbourg, 18.4.2012. Link to European Commission (2012:3 to 6): http://eur-lex.europa.eu/SECMonth.do?year=2012&month=04 European Commission (2012:4), Commission Staff Working Document on An Action Plan for the EU Health Workforce, SWD(2012) 93 final, Strasbourg, 18.4.2012. European Commission (2012:5), Commission Staff Working Document on Exploiting the employment Potential of ICTs, SWD(2012) 96 final, Strasbourg, 18.4.2012. European Commission (2012:6), Commission Staff Working Document on Open, dynamic and inclusive labour markets, SWD(2012) 97 final, Strasbourg, 18.4.2012. European Commission (2012:7), Demography, Active Ageing and Pensions, Social Europe guide, Volume 3, Luxembourg 2012. http://ec.europa.eu/social/main.jsp?catId=738&langId=en&pubId=6805&type=2&furt herPubs=yes European Commission (DG ECFIN) and the Economic Policy Committee (Ageing Working Group), The 2012 Ageing Report: Underlying Assumptions and Projection Methodologies, European Economy 4/2011 http://ec.europa.eu/economy_finance/publications/european_economy/2011/pdf/ee2011-4_en.pdf Huselid, M. A., The Impact of Human Resource Management Practices on Turnover, Productivity, and Corporate Financial Performance, in: Academy of Management Journal, Vol. 38, No 3 (1995), p. 635 â&#x20AC;&#x201C; 672. GĂśbel, C., Zwick, T., Which Personnel Measures are Effective in Increasing Productivity of Old Workers?, ZEW Discussion Paper 10-069, Mannheim 2010 Golden, L., The Effects of Working Time on Productivity and Firm Performance: a research synthesis paper, International Labour Office, Conditions of Work and Employment Series No 33 (2011). International Labour Office, Working time and productivity, Information Sheet No. WT18, June 2004.

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Liebig, T. and S. Widmaier (2009), Children of Immigrants in the Labour Markets of EU and OECD Countries: An Overview, in: OECD Social, Employment and Migration Working Papers, No. 97, OECD Publishing. http://dx.doi.org/10.1787/220823724345 Mincer, J., Ofek, H., Interrupted work careers: Depreciation and Restoration of Human Capital, The Journal of Human Resources, Vol. 17, No 1 (Winter, 1982), pp. 3-24 OECD (2011): Trends in Migration Flows in the Immigrant Population, in: International Migration Outlook 2011. OECD Publishing. OECD (2012): Working Party on Migration, DELSA/ELSA/WP2(2012)2, Current and future skills of the workforce: the demography of educational attainment and the role of migration. OECD (2013): (draft not yet published), Current and future skills of the workforce: The demography of educational attainment and the role of migration OECD (2013): Recent developments in international migration movements and policies, in: International Migration Outlook 2013. OECD Publishing. Quintini, G.: Over-Qualified or Under-Skilled: A Review of Existing Literature, OECD Social, Employment and Migration Working Papers, No 121, OECD Publishing, 2011. Peschner, J. (2011): Europe’s long-term welfare vis-à-vis a shrinking workforce — A regional perspective, presentation on ‘Conference on Social and economic impact of migration: Central and East-European perspectives’ jointly organised by the Polish Ministry of Labour and Social Policy and Eurofound on November 17 and 18, 2011, in Warsaw. http://www.eurofound.europa.eu/events/2011/migrants1711/presentations.htm Peschner, J. (2012): Exploring conditions for EU growth given a shrinking workforce, in OECD (2012), Free Movement of Workers and Labour Market Adjustment, Recent Experiences from OECD countries and the European Union, p. 213-233. http://www.oecd-ilibrary.org/social-issues-migration-health/free-movement-ofworkers-and-labour-market-adjustment_9789264177185-en Platt, W. J., Alexander-Frutschi, M. C.: Human Resources and Economic Growth, Literary Licensing 2012 David Bloom, David Canning, Jaypee Sevilla: The Demographic Dividend: A New Perspective on the Economic Consequences of Population Change by , RAND Corporation, (2003). Steiner, V., Peters, R.-H., Employment Effects of Work Sharing — An econometric analysis for West Germany, Zentrum für Europäische Wirtschaftsforschung (ZEW), Discussion Paper 00-20, Mannheim, 2000. Vasileva, K., Nearly two-thirds of the foreigners living in EU Member States are citizens of countries outside the EU-27, in: Eurostat, Statistics in focus, 31/2012. http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-SF-12-031/EN/KS-SF-12031-EN.PDF

September 2013 I

Social Europe Growth potential of EU human resources

Wilson, R. A., Briscoe, G.: The impact of human capital on economic growth: a review, CEDEFOP Reference series, 54, 2004 World Economic Forum (in collaboration with The Boston Consulting Group): Stimulating Economies through Fostering Talent Mobility, 2010.

September 2013 I

Social Europe Growth potential of EU human resources

Annex 1: Modelling educational progression Educational progress is projected by extrapolating past trends in the educational structure of the working age population, i.e., the proportion of people holding high, medium and low educational attainment according to the Labour Force Survey. Following Coomans,64 the proportion of people aged between 25 and 34 holding high and low degrees are projected using log-linear trend-prolongation of the respective series between 2000 and 2011 for each sex. The share of medium education is the residual. The result is that if there has been an increase in the recent past in the proportion of highly skilled people (fall in the share of low skilled), log-linear projection will result in the continuation of this trend, albeit at a slower pace. The chart shows the approach for the EU-27.

Graph 23: Proportion of people holding low and high educational degrees by sex, Aged 25-34 years, EU-27

MALES

FEMALES

0.45

0.40

historic values

projected share of HIGH skilled

0.35

historic values

0.30

projected share of HIGH skilled

0.35 0.30 0.25

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2002

2000

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2010

historic values

0.15 2000

0.15

projected share of LOW skilled

0.20

2008

projected share of LOW skilled

historic values

2006

0.20

2004

0.25

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop2010 population projections, convergence scenario; following Coomans (2012)

The procedure is done separately for men and women. It is assumed that older cohorts (aged 35 and older) will not make any further educational progress. For example: the proportion of 35 to 44 year-old women in t with higher degrees is the same as the respective share of the 25 to 34 year-olds in t-10.

Coomans (2012), p. 202 â&#x20AC;&#x201C; 203; the method is also used in Coomans (2005), applied to regions.

September 2013 I

Social Europe Growth potential of EU human resources

Annex 2: Findings at EU Member State level The growth potential of EU human resources and policy implications for future economic growth

Graphs for each Member State: Page 1: • Employment growth potential in the High and the Low Activity Scenarios • Productivity increases necessary to attain 2 % economic growth assuming potential employment growth in the High and Low Activity Scenarios Page 2: Assumptions employed on: • the structure of the working age population with respect to educational attainment (to give the education effect); • female activity rates to catch up to those of men by 2030 (gender effect); • older workers’ activity rates to increase by 20 Percentage points by 2030 (older workers effect).

September 2013 I

Social Europe Growth potential of EU human resources

Belgium Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

6.8

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years) 83.0

6.3 Employment growth scemaro :

5.8

78.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

5.3

73.0

4.8 68.0 4.3

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

63.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

3.8

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Future employment growth potential and levels of productivity growth required to sustain 2% GDP growth Projected employment growth rate, low activity scenario Projected employment growth rate, high activity scenario Productivity growth required to have 2 % GDP growth, low activity scenario Productivity growth required to have 2 % GDP growth, high activity scenario GDP growth assumed Past employment growth Past productivity growth Past GDP growth

annual growth in % 2.5

avg 20082011

avg 2000-2008 2.0

future scenario

1.5

1.0

0.5

0.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-0.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Belgium Population by educational attainmelt levels, with and without computed educational progression

130

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Any remaining difference in 2030 is due to different age structure development (while educational structure is static in "gender effect" scenario). Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Bulgaria Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

5.1

millions 94.0 4.6

% of Working Age Population (20-64 years)

89.0

84.0

Employment growth scemaro :

4.1

79.0 1.5% p.a. 3.6

1% p.a. 0.5% p.a. none EU2020

3.1

74.0

69.0

64.0 2.6 59.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

54.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

2.1

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 8.0

avg 20082011

avg 2000-2008 6.0

future scenario

4.0 2.0 0.0 -2.0 -4.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-6.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Bulgaria Population by educational attainmelt levels, with and without computed educational progression

110

100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Czech Republic Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

6.9

millions

% of Working Age Population (20-64 years) 88.0

6.4

Employment growth scemaro :

5.9

83.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

5.4

78.0

73.0

4.9

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

68.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

4.4

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 5.0

avg 20082011

avg 2000-2008 4.0

future scenario

3.0 2.0 1.0 0.0 -1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Czech Republic Population by educational attainmelt levels, with and without computed educational progression

130

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Denmark Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

91.0

millions

% of Working Age Population (20-64 years)

3.3

89.0

87.0 3.1 Employment growth scemaro : 2.9

85.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

2.7

83.0

81.0

79.0

77.0

2.5

75.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

73.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

2.3

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008

2.5 2.0

future scenario

1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Denmark Population by educational attainmelt levels, with and without computed educational progression

130

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Germany Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

96.0

millions

% of Working Age Population (20-64 years)

48 91.0

Employment growth scemaro :

86.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

81.0

76.0 33 71.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

66.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008 3.0

future scenario

2.0

1.0

0.0

-1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Germany Population by educational attainmelt levels, with and without computed educational progression

110

100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

France Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

millions

% of Working Age Population (20-64 years)

85.0

33 Employment growth scemaro :

80.0

1.5% p.a. 29

1% p.a. 0.5% p.a. none EU2020

75.0

25 70.0 23

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

65.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 2.5

avg 20082011

avg 2000-2008 2.0

future scenario

1.5

1.0

0.5

0.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-0.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

France Population by educational attainmelt levels, with and without computed educational progression

160

140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Ireland Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

3.1

Active population Low activity scenario

Active Population, High activity scenario

89.0

millions

2.9

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

84.0

2.7

Employment growth scemaro :

2.5

79.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

2.3

2.1

74.0

69.0 1.9 64.0 1.7

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

59.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

1.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 5.0

avg 20082011

avg 2000-2008

4.0 3.0

future scenario

2.0 1.0 0.0 -1.0 -2.0 -3.0 -4.0 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-5.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Ireland Population by educational attainmelt levels, with and without computed educational progression

160

140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Greece Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

6.8

millions

% of Working Age Population (20-64 years) 83.0

6.3

Employment growth scemaro :

5.8

78.0

1.5% p.a. 5.3

1% p.a. 0.5% p.a. none EU2020

4.8

4.3

73.0

68.0

63.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

58.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

3.8

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008

3.0 2.0

future scenario

1.0 0.0 -1.0 -2.0 -3.0 -4.0 -5.0 -6.0 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-7.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Greece Population by educational attainmelt levels, with and without computed educational progression

130

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Spain Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

30 89.0

millions

% of Working Age Population (20-64 years)

28 84.0 26 Employment growth scemaro :

79.0

1.5% p.a. 22

1% p.a. 0.5% p.a. none EU2020

74.0

69.0 18 64.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

59.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008 3.0

future scenario

2.0 1.0 0.0 -1.0 -2.0 -3.0 -4.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-5.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Spain Population by educational attainmelt levels, with and without computed educational progression

140 130 120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Estonia Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

0.82

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

0.77

85.0

0.72

Employment growth scemaro :

0.67

80.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

0.62

75.0

0.57 70.0 0.52

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

65.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.47

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 7.0

avg 20082011

avg 2000-2008

6.0 5.0

future scenario

4.0 3.0 2.0 1.0 0.0 -1.0 -2.0 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-3.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Estonia Population by educational attainmelt levels, with and without computed educational progression

120

110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Italy Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years) 80.0

33 Employment growth scemaro :

75.0

1.5% p.a.

1% p.a. 0.5% p.a. none EU2020

70.0

65.0

23 60.0 21

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

55.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5 -1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Italy Population by educational attainmelt levels, with and without computed educational progression

160

140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Cyprus Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

millions

92.0

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

0.55

87.0

0.50 Employment growth scemaro :

0.45

82.0 1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

0.40

77.0

0.35

72.0 0.30

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

67.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.25

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.5

avg 20082011

avg 2000-2008

4.0 3.5

future scenario

3.0 2.5 2.0 1.5 1.0 0.5 0.0 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-0.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Cyprus Population by educational attainmelt levels, with and without computed educational progression

Educational 2010=100 progression: Population by educational attainmelt levels

180

Population 20-64, HIGH educated (ISCED 5-6) Population 20-64, MEDIUM educated (ISCED 3-4) Population 20-64, LOW educated (ISCED 1-2)

160 140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

100

90 80 70 60 50 Males, age 20-64 40

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

Females, age 20-64 2000

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Latvia Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

1.5

millions

% of Working Age Population (20-64 years) 86.0

1.4

1.3 81.0

Employment growth scemaro :

1.2

1.1

1.0

1.5% p.a.

76.0

1% p.a. 0.5% p.a. none EU2020

71.0

0.9 66.0 0.8

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

61.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.7

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 8.0

avg 20082011

avg 2000-2008 6.0

future scenario

4.0 2.0 0.0 -2.0 -4.0 -6.0 -8.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-10.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Latvia Population by educational attainmelt levels, with and without computed educational progression

130

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Lithuania Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

2.1

millions

87.0

% of Working Age Population (20-64 years)

2.0 1.9 82.0 1.8

Employment growth scemaro :

1.7

77.0 1.5% p.a. 1.6

1% p.a. 0.5% p.a. none EU2020

1.5

72.0

1.4 1.3

67.0

1.2

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

62.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

1.1

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 8.0

avg 20082011

avg 2000-2008 6.0

future scenario

4.0

2.0

0.0

-2.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-4.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Lithuania Population by educational attainmelt levels, with and without computed educational progression

120

110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Luxembourg Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

millions

85.0

0.36

0.31

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

80.0

Employment growth scemaro : 1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

0.26

0.21

75.0

70.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

65.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.16

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008 3.0

future scenario

2.0 1.0 0.0 -1.0 -2.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-3.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Luxembourg Population by educational attainmelt levels, with and without computed educational progression

180

160 140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Hungary Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

6.0 79.0

5.5 Employment growth scemaro :

74.0

5.0

1.5% p.a.

4.5

1% p.a. 0.5% p.a. none EU2020

69.0

64.0

4.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

59.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

3.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008 3.0

future scenario

2.0

1.0

0.0

-1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Hungary Population by educational attainmelt levels, with and without computed educational progression

140 130 120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

75 70 65 60 55 50 45

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

Females, age 20-64

2004

35 2002

Males, age 20-64

2000

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Malta Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

0.26

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years) 86.0

0.24 81.0 0.22

Employment growth scemaro :

0.20

76.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

0.18

71.0

0.16

66.0

0.14

61.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

56.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.12

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Malta Population by educational attainmelt levels, with and without computed educational progression

200

180 160 140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

60 50

40 30 20

Low activity scenario

10 0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Netherlands Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

92.0

millions

% of Working Age Population (20-64 years)

9.9

90.0 88.0

9.4 86.0

Employment growth scemaro :

8.9

84.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

8.4

7.9

82.0 80.0 78.0 76.0

7.4 74.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

72.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

6.9

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5 -1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Netherlands Population by educational attainmelt levels, with and without computed educational progression

Educational 2010=100 progression: Population by educational attainmelt levels

130

Population 20-64, HIGH educated (ISCED 5-6) Population 20-64, MEDIUM educated (ISCED 3-4) Population 20-64, LOW educated (ISCED 1-2)

120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

100

90 80 70 60 50 Males, age 20-64 40

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

Females, age 20-64 2000

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Austria Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

88.0 5.3

millions

% of Working Age Population (20-64 years) 86.0 84.0

4.8

82.0

Employment growth scemaro :

80.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

4.3

78.0 76.0 74.0

3.8 72.0 70.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

68.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

3.3

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Austria Population by educational attainmelt levels, with and without computed educational progression

120

110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Poland Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

85.0

millions 24

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

80.0 22 Employment growth scemaro :

75.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

70.0

65.0

60.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

55.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 5.0

avg 20082011

avg 2000-2008 4.0

future scenario

3.0 2.0 1.0 0.0 -1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Poland Population by educational attainmelt levels, with and without computed educational progression

180

160 140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Portugal Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

millions

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years) 87.0

6.3

Employment growth scemaro :

5.8

82.0

1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

5.3

77.0

72.0

4.8

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

67.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

4.3

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 4.0

avg 20082011

avg 2000-2008 3.0

future scenario

2.0 1.0 0.0 -1.0 -2.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-3.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Portugal Population by educational attainmelt levels, with and without computed educational progression

180

160 140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

80 70 60 50 40 30 20 10 0

% Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Romania Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

millions

% of Working Age Population (20-64 years) 81.0

12 Employment growth scemaro :

76.0

11 1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

71.0

9 66.0 8

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

61.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 10.0

avg 20082011

avg 2000-2008 8.0

future scenario

6.0 4.0 2.0 0.0 -2.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-4.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Romania Population by educational attainmelt levels, with and without computed educational progression

160

140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Slovenia Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

1.4

Active Population, Education Effect

Past employment

84.0

millions

% of Working Age Population (20-64 years) 82.0

1.3 80.0 Employment growth scemaro :

1.2

78.0

1.5% p.a. 1.1

1% p.a. 0.5% p.a. none EU2020

1.0

76.0

74.0

72.0

70.0 0.9 68.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

66.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

0.8

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 5.0

avg 20082011

avg 2000-2008 4.0

future scenario

3.0 2.0 1.0 0.0 -1.0 -2.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-3.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Slovenia Population by educational attainmelt levels, with and without computed educational progression

140 130 120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

60 50

40 30 20 10

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Slovakia Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

3.7

millions

% of Working Age Population (20-64 years)

3.5

86.0

3.3 81.0

Employment growth scemaro :

3.1

2.9

2.7

2.5

1.5% p.a.

76.0

1% p.a. 0.5% p.a. none EU2020

71.0

2.3 66.0 2.1

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

61.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

1.9

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 8.0

avg 20082011

avg 2000-2008

7.0 6.0

future scenario

5.0 4.0 3.0 2.0 1.0 0.0 -1.0 2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-2.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Slovakia Population by educational attainmelt levels, with and without computed educational progression

140 130 120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

70 60 50 40 30 20 10 0

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Finland Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

3.3

millions

88.0

% of Working Age Population (20-64 years)

86.0

3.1

84.0 Employment growth scemaro :

2.9

2.7

2.5

82.0

1.5% p.a.

80.0

1% p.a. 0.5% p.a. none EU2020

78.0

76.0

74.0 2.3 72.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

70.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

2.1

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5 -1.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Finland Population by educational attainmelt levels, with and without computed educational progression

110

100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Sweden Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

5.8

Active population Low activity scenario

Active Population, High activity scenario

millions

94.0

5.3

Active Population, Education Effect

Past employment

% of Working Age Population (20-64 years)

89.0

Employment growth scemaro : 1.5% p.a. 1% p.a. 0.5% p.a. none EU2020

4.8

4.3

84.0

79.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

74.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

3.8

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.5

avg 20082011

avg 2000-2008 3.0

future scenario

2.5 2.0 1.5 1.0 0.5 0.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-0.5

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

Sweden Population by educational attainmelt levels, with and without computed educational progression

Educational 2010=100 progression: Population by educational attainmelt levels

160

Population 20-64, HIGH educated (ISCED 5-6) Population 20-64, MEDIUM educated (ISCED 3-4) Population 20-64, LOW educated (ISCED 1-2)

140 120 100 80 60 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

100

90 80 70 60 50 Males, age 20-64 40

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

Females, age 20-64

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

120 100

80 60

Low activity scenario

40 20

Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

Social Europe Growth potential of EU human resources

United Kingdom Potential development of employment at given growth scenarios Assumption: Further shift of activity rates, different scenarios Working age popul. (age 20-64)

Active population Low activity scenario

Active Population, High activity scenario

Active Population, Education Effect

Past employment

millions

91.0

% of Working Age Population (20-64 years)

36 86.0

Employment growth scemaro :

1.5% p.a. 32

1% p.a. 0.5% p.a. none EU2020

81.0

76.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2000

2002

71.0

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

annual growth in % 3.0

avg 20082011

avg 2000-2008 2.5

future scenario

2.0 1.5 1.0 0.5 0.0 -0.5

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

-1.0

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

100

Social Europe Growth potential of EU human resources

United Kingdom Population by educational attainmelt levels, with and without computed educational progression

140 130 120 110 100 90 80 70 60 50 40

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

Female and male activity rates, "gender effect" scenario: females' activity rate catches up to male activity rate by 2030 for each age group and educational attainment level

80 70 60 50 Males, age 20-64

2040

2038

2036

2034

2032

2030

2028

2026

2024

2022

2020

2018

2016

2014

2012

2010

2008

2006

2004

2002

2000

Females, age 20-64 30

Older workers (age 55-64) activity rate in the low activity scenario and in the low activity scenario including the imputed older-workers-effect

90 80 70 60 50 40 30 20 10 0

Low activity scenario Low activity scenario with olderworkers-effect

Source: Own calculations based on Eurostat EU LFS and Eurostat Europop 2010 population projection

September 2013 I

101

Social Europe Growth potential of EU human resources

KE-EW-13-003-EN-N

European Commission Growth potential of EU human resources and policy implications for future economic growth – DG EMPL Working Paper 03/2013 Luxembourg: Publications Office of the European Union, 2013 2013 — 102 pp. — 21 × 29.7 cm ISBN 978-92-79-32715-5 ISSN 1977-4125 doi: 10.2767/79370 This publication is available in electronic format in English.

September 2013 I

102