1

Attractive vocational education and training: what really matters?

Workshop

9 and 10 October 2012

Session 2

Trends and developments affecting attractiveness of initial vocational education and training

Background paper 1

This paper lays out the wider context for evaluating IVET attractiveness. The framework suggests that demographic trends are an important exogenous driver of both demand for IVET and IVET outcomes. Data are presented on two main demographic features of countries in Europe – the ageing workforce and patterns of immigration and emigration. Next, the chapter discusses the macroeconomic climate, including national output growth, the effects of the downturn and the state of the labour market across our countries of study. According to the framework, these factors help shape the economic attractiveness of IVET. Finally, the paper describes educational systems across Europe. The framework suggests that differences in the resources allocated to different forms of education affects both the relative attractiveness of IVET pathways (compared to other pathways into the labour market) and the absolute attractiveness of IVET in terms of the quality of the outputs of the system. Details of the calculation of these data and figures are presented in Annex C.

2.1 Demographics Most countries in Europe are ageing. Figure 2.1 shows that the old-age dependency ratio – the proportion of over 65s to the working age population – has increased in every country apart from two (Norway and Luxembourg).2 This is caused by more people retiring relative to new labour market entrants, coupled with rising life expectancy in retirement.

One reason for the rising dependency ratio is that birth rates have declined , meaning that many countries have experienced a declining number of young adults in the last decade. Figure 2.1 also shows that the proportion of the population aged between 18 and 24 years old has declined in many countries. There is not a clear correlation between rising dependency ratios and a declining youth population – for example, Germany’s had slightly more 18-24 year olds in 2010 than it did in 2000,

1 Extract from the Interim report 2Countries in Figure 2.1 are ordered by old age dependency ratio in 2000, from highest to lowest.

2

although its old age dependency ratio has risen dramatically. Of course, the age structure of the entire workforce is also relevant. Baby-boomers have started to leave the labour market, so even if the population of young adults was not declining, the retirement of this larger-than-average generation of workers will continue to increase the old-age dependency ratio.

Figure 2.1. Changes in young adult population and old age dependency ratio, 2000-2010. Source: Eurostat/UOE

A rising old age dependency ratio is relevant for IVET policy because it means there will be increased pressures to replace those retiring in larger numbers than those entering. Where this is linked to the retirement of a larger-than-average generation of workers, the particular skill needs in the labour market will reflect those previously supplied by those workers. In countries where the youth population is continually declining, this indicates a particular pressure on the education system, where an increasingly smaller number of new labour market entrants will be required to meet the skill gaps.

Immigration and emigration rates influence the skills being supplied to the labour market. If immigrants have been trained elsewhere, these could mean that they help a country meet its skills requirements. Similarly, if well-trained workers are leaving the country, this could generate skills shortages. Alternative, if immigrants are lowly skilled or relatively unqualified, then this could place additional demands on the VET system. Figure 2.2 shows gross immigration and emigration for 15-24 year olds separate from net immigration.3 If only the latter were included, the implicit assumption would be that, in terms of skills, immigrants and emigrants are close substitutes – this may not be the case.

% c

hang

e, 2

000-

2010

18-24 year oldpopulationOld age dependencyratio

3

Figure 2.2. Immigration and emigration rates, 2008, 15-24 year olds. Source: Eurostat/UOE.

Note: 2010 figures used for Greece and UK. Data missing for Belgium, Romania, Norway, Iceland data missing.

Most countries in Europe have positive net migration. The three main counter examples are Ireland, which has a high rate of both immigration and emigration, Greece, which experiences a much lower level of immigration but relatively high levels of emigration, and then a number of Eastern European countries, where both immigration and emigration rates are very low. Of the countries with positive net migration (and leaving aside countries with very high or very low rates of mobility), emigration is greater in countries such as Germany, Austria and Denmark, whereas countries like the UK, Spain, Italy and Slovenia lose proportionately less people than they receive each year.

2.2 Economic climate The past eleven years have seen two distinct phases in economic development. Between 2000 and 2007, most European economies have experienced real economic growth. Figure 2.2 compares real GDP per capita between 2000 and 2007, which shows that growth occurred across countries of all income levels. There was particularly rapid growth for a small number of high-income countries (Norway, Luxembourg and Finland) and many lower-income countries (particularly Czech Republic, Estonia and Slovakia). West and south European countries, in general, experienced less rapid growth in this time period.

Since 2007, the global financial crisis and the subsequent recession have had differentiated impacts across Europe, as shown in Figure 2.3. Several countries have experienced severe drops in real GDP, such as Iceland, Ireland and the UK, with less severe, but still significant drops in many other northern, western and southern European countries, including Italy, Portugal, Spain and Greece. In contrast, Austria, the Netherlands and Germany had much less severe recession, with Germany actually growing over the three year period to 2010. In Eastern Europe, the effects were more mixed. Some countries achieved real growth, such as the Czech Republic, Poland Slovakia, but a number of others (most noticeably Romania, Hungary, Latvia and Estonia) experienced falling output.

4

Figure 2.3. Real GDP, 2000-2007. Source: Eurostat/UOE

There are two major effects resulting from the recent recession which are most relevant for initial vocational education and training. The first effect is on the labour market, particularly the labour market for young people and new entrants.4 The second effect has been seen in public finances, where increasing budget deficits resulting from cyclical adjustments – higher welfare payments, lower tax revenues - following fiscal stimulus as well as the cyclical effects of lower taxation and increased welfare transfer payments.

On the effects of the labour market, Figures 2.4 and 2.5 show patterns of unemployment rates for 15-24 year olds for 2000-2007 and 2007-2010 respectively. Figure 2.4 shows that between 2000 and 2007 there was a degree of convergence across Europe in youth unemployment rates. Some countries started the decade with high youth unemployment, and experienced a sizeable improvement in this measure up to the start of the global financial crisis. Other countries with lower initial youth unemployment rates seem to have experienced a mild worsening of the employment prospects of young people during this time. Since 2007, almost all countries have seen rising youth unemployment rates, with Germany and Malta being the two exceptions. A number of countries have experienced a very rapid increase in this rate, including Spain, Ireland, Latvia, Lithuania and Estonia.

4See Bell and Blanchflower (2011) for an evaluation of the current recessions short and long-term effects of youth unemployment.

5

Figure 2.4. Real GDP per capita, 2007-2010. Source: Eurostat

Figure 2.5. Unemployment rate, 15-24 year olds, 2000-2007. Source: Eurostat/European Labour Force Survey (EULFS)

6

Figure 2.6. Unemployment rate, 15-24 year olds, 2007-2010. Source: Eurostat/EULFS

Youth unemployment is an important factor in understanding the attractiveness and subsequent demand for IVET courses. Unemployment rate increases tend to fall unevenly across the workforce, so the differences between the unemployment rates of the low skilled, vocational graduates and those who took a more academic route (including university graduates) matters in assessing the economic return, and hence the attractiveness, of different pathways. Moreover, vocational routes are more closely linked to certain occupations or sectors, making demand for trainees reliant on the economic conditions in a particular sector. In contrast, university graduates are often more able to cross between sectors based on their less sector-specific general academic credentials.

Figure 2.6 shows that there is the expected positive correlation between overall unemployment and youth unemployment, suggesting that youth unemployment is strongly related to overall employment prospects in each country.

7

Figure 2.7. Unemployment for all workers compared to youth unemployment, 2010. Source: Eurostat/EULFS

Youth unemployment rates and employment rates are strongly and negatively correlated (see Figure 2.7). The lack of a one-for-one relationship shows that lower employment rates lead to both rising unemployment and rising inactivity.

Figure 2.8 Employment and unemployment rates, 15-24 year olds, 2010. Source: Eurostat/EULFS

8

Increases in unemployment rates across Europe have affected male and female members of the labour force different. Figure 2.9 and 2.10 show changes in unemployment rates by gender. In general, male unemployment was lower before the crisis, and has increased by greater proportions between 2007 and 2010.

Figure 2.9. Unemployment rate, 15-24 year olds, males, 2007-2010. Source: Eurostat/EULFS

Figure 2.10. Unemployment rate, 15-24 year olds, females, 2007-2010. Source: Eurostat/EULFS

9

The second key issue resulting from the financial crisis and subsequent recession relates to future limits of public spending whilst many countries are in the middle of consolidating their fiscal positions. This has been most noticeable, and will likely be most constraining in the short- to medium-term in countries that have received EU financial support in order to meet their debt obligations – Greece, Portugal, Ireland and Italy. However, there has also been voluntary austerity programmes in other European countries in an attempt to stave off future sovereign debt crises. These constraints may limit future policy interventions and place constraints on the existing system. For example, if austerity measures lead to falling pay for public sector employees, training schools may be unable to retain their most effective teachers.

2.3 The labour market The demand for certain skills has altered significantly over the last few decades. Figure 2.11 shows the average change in employment shares across Europe in five occupational groups. These occupational groups are the most connected to vocational skills and qualifications –managerial and professional occupations are omitted, as these are more likely to be accessed via completion of higher education, as well as elementary occupations, agricultural workers and those in the armed forces.

Figure 2.11. Changing occupational structure in EU27 countries, 2000-2010.

Source: Eurostat/EULFS. Note: occupations coded by single-digit ISCO groups

The figure illustrates the phenomena known as “routinisation” (Autor, Katz and Kearney, 2003) where the occupational structure has shifted away from “routine” occupations (such as administrative clerks and semi-skilled process operatives) and towards “non-routine” work (including highly skilled professionals, managers and technicians, and lower-skilled service occupation workers). This is sometimes also referred to as polarisation (Goos and Manning, 2007) as the declining occupations have tended to be associated with middle-wage, middle-skill work. This leads to a “hollowing-out” of the labour market as occupational growth takes place in higher-wage and lower-wage occupations.

10

There is considerable variation in these patterns across countries, however. Figure 2.12 shows the same changes by occupational group employment share by individual Member States. Two countries – Bulgaria and Poland – had a declining number of technicians and associate professionals between 2000 and 2007, while four countries – Cyprus, Iceland, Italy and Luxembourg – has fewer service occupation workers at the end of the decade. In contrast, a number of Eastern European countries saw a rise in the employment share of administrative clerks (most notably Bulgaria, Estonia and Latvia).

The occupational structure of the labour market matters for attractiveness of initial vocational education because courses are linked to particular sectors or occupations. Hence, employment opportunities and earnings for graduates of craft trade courses, for example, are likely to be lower, all other things being equal, in countries where such jobs have declined significantly. Moreover, the growth of higher skilled jobs which traditionally recruit heavily from university graduates will lower the relative attractiveness of IVET compared to higher education as employment prospects and earnings improve in those occupations. On the other hand, an increase in service sector jobs and service occupations will improve the attractiveness of courses in retail or tourism.

Figure 2.12. Changing occupational structure, by country, 2000-2010. Source: Eurostat/EULFS

11

2.4 Education systems It is a role of the education system to provide the skills to meet labour market requirements. The pressures and demands on the system should reflect, in part, the economic, demographic and structural factors highlighted in the framework and the previous sections. Figure 2.13 shows that European governments spend a significant proportion of their total national output on education at ISCED levels 2-4. The EU27 average in 2008 was 2.24% of GDP. Total public spending in 2008 accounted for around 46.0% of total GDP, meaning that expenditure on education at level 2-4 accounted for 4.87% of all public expenditure in that year. Many countries appear to have spent a similar amount of this level of education at the beginning and end of the decade. A small number of countries – including Lithuania, Latvia, Slovenia and Slovakia – spent noticeably less on education in 2008 than in 2001, as a proportion of GDP. This may reflect some form of fiscal restraint on education spending during a period of economic decline. A number of other countries have increased their secondary education spending quite noticeably – in particular, Cyprus, Malta, Ireland, Norway and Poland.

Figure 2.13. Total public expenditure on secondary education (ISCED 2-4), % of GDP, 2001-2008.

Source: Eurostat. Note: Data missing for Greece and Romania in 2009.

12

In terms of spending on IVET programmes, data on vocational education at ISCED levels 3-4 is not as readily available across the countries studied in this report and as such is not sufficiently useful for comparative purposes. Figure 2.14 shows this data where it is available.

Figure 2.14.Total public expenditure on upper secondary education (ISCED 3-4), % of GDP, 2008. Source:

OECD Stat/UOE (Data available for: Austria, Czech Republic, Finland, France, Germany, Luxembourg, Netherlands, Poland and Sweden) and Cedefop website (Data available for: Bulgaria, Cyprus, Estonia, Hungary, Latvia, Lithuania, and Slovakia). Data missing (not broken down by ISCED level) for Belgium, Denmark, Greece, Ireland, Italy, Malta, Portugal, Romania, Slovenia, Spain, UK, Iceland and Norway)

Of course, not all spending is from public sources. Figures 2.15 and 2.16 show the balance of students currently in level 3 and 4 vocational programmes by the type of provider. Most countries provide almost all vocational study at level 3 through public institutions, although a small number of countries rely more on private provision (or private providers with public funding). Portugal is the only country with a large number of students enrolled in independent private providers, and the UK, Belgium and France are the only countries with more than 40% of students enrolled outside of public sector providers. More of level 4 vocational education takes place outside of public institutions. In several countries, including Bulgaria, Poland and France, independent private institutions are the dominant providers. In addition, firms act as provider or co-providers of IVET in some instances. Figure 2.17 shows the proportion of firms in each country providing IVET5.

5

Firms in these data are defined as providing IVET if they provide training for upward of six months leading to a vocational qualification at a recognised ISCED level. This

is wider definition of IVET than considered elsewhere in this report, and may include training at a relatively low level. However, these data, taken from the 2005

Continuous Vocational Training Survey, are the best available on firm involvement in IVET at a European level.

Two specific issues are acknowledged. Firstly, these data are out-of-date. Data from the next wave of the survey (completed in 2011) will hopefully be available for

comparison in the final report. Secondly, some country figures do not accord well with other estimates – for example, the German and UK figures have been noted as

being particularly high. At this stage, these figures should be interpreted as illustrative of country-level differences in firm involvement; this issue will be further investigated

for the final report.

13

Figure 2.15. Types of ISCED level 3 vocational provision, % of enrolled students, 2009.

Source: Eurostat/UOE. Data missing for Greece and the Netherlands

Figure 2.16. Types of ISCED level 4 vocational provision, % of enrolled students, 2009. Source: Eurostat/UOE. Data missing for Cyprus, Greece, Netherlands, Spain and UK

14

Figure 2.17. Firm involvement in IVET, % of all firms, 2005. Source: Eurostat/Continuous Vocational Training Survey (CVTS). Notes: question asked participants firms if they provided IVET, defined here as training for upward of six months leading to a vocational qualification at a recognised ISCED level. Data missing for Iceland.

15

2.5 Educational attainment One measure of the level of attainment across different education systems is the early leaver rate. Figure 2.18 shows the proportion of early leavers from education. Early leavers are 18-24 year olds with lower level qualifications (no higher than ISCED 2 or ISCED 3c short) and are not currently in further education or training. The general trend across Europe is for this rate to decline as young people reach higher levels of attainment before entering full-time work.6

Figure 2.18. Early school leaving rates, 2004-2010. Source: Eurostat/UOE.

Despite the general trend of falling leaving rates, the figure shows that there is a wide range in achievement across countries. Some countries, most noticeably Spain, Portugal and Malta, have a very high proportion of young people not reaching ISCED level 3 or above in either general or vocational programmes.

These early leaving rates correspond closely to the overall educational attainment of the workforce. Figure 2.19 shows the proportion of the working age population who have completed at least upper secondary education (ISCED3 and above) and those who have then gone on to complete tertiary education (ISCED 5 and above).

6The two outliers in this figure are Norway and Denmark – in both cases there is a methodological break in the data between 2004 and 2010, leading to a large upward jump in the leaving rate. Outside of these breaks, leaving rates in these countries has remained constant.

16

Figure 2.19. Highest educational attainment of working age population, 2010. Source: Eurostat/EULFS

Figure 2.19 shows the relative size of the tertiary sector, relative to the secondary sector. The figure shows that, in terms of the education or skills supply in the labour market, different countries can be more or less heterogeneous. The Czech Republic and Slovakia, for instance, have a very high proportion of the workforce with educational attainment at or above ISCED level 3, but few of these workers complete tertiary courses. Some countries, such as the UK, Finland, Cyprus, Ireland and Spain, have a much larger proportion of those completing upper secondary schooling moving onto university or advanced vocational programmes. The case of Spain is particularly interesting – it gives an example of a country with a high proportion of low attainment adults (below ISCED level 3), but with a tertiary sector that generates proportionally more graduates than both other low-attainment countries (such as Italy), but also higher attainment countries.

The next section focuses on the part of the education system which produces higher level vocational skills prior to labour market entry. Figure 2.20 gives the number of 15-24 year old students completing ISCED level 3 or 4 vocational programmes in any one year as a proportion of that cohort’s total population7.

7This is referred to as the graduation rate. It is worth noting that students can only graduate from a programme in one year out of the ten year age group looked at, so the highest value anticipated by this measure is 10%. This would correspond to all individuals in the cohort graduating from a given programme at some point between the ages of 15 and 24.

17

Figure 2.20. Graduation rates from vocational programmes, 15-24 year olds, 2009, Source: Eurostat/UOE. Note:

Data missing for Czech Republic, Germany, Greece, Spain and UK. Level 4 data missing for Cyprus. Level 3 data missing for Ireland.

The figure shows that the majority of IVET takes place at level 3 (in a few instances, the data on level 4 graduation are missing), although a few countries – such as Belgium, Austria, Hungary and Estonia – have a significant number of level 4 graduates. There are some differences by gender in this measure. Figures 2.21. and 2.22. show male and female graduation rates. Countries appear in the same order as in Figure 2.16, to show the variation by gender (for example, Romania clearly has a larger number of male graduates than female graduates, whereas Austria has very little gender difference).

18

Figure 2.21. Graduation rates from vocational programmes, 15-24 year olds, males, 2009, Source: Eurostat.

Note: Data missing for Czech Republic, Germany, Greece, Spain and UK. Level 4 data missing for Cyprus. Level 3 data missing for Ireland.

Figure 2.22. Graduation rates from vocational programmes, 15-24 year olds, females, 2009, Source: Eurostat. Note: Data missing for Czech Republic, Germany, Greece, Spain and UK. Level 4 data missing for Cyprus. Level 3 data missing for Ireland.

19

To make these graduation rates comparable, Figure 2.23 plots the graduation rates at level 3 general programmes against those from level 3 academic programmes. There is a clear negative relationship between the two, indicating that countries appear to face a trade-off between producing more graduates from either vocational or general academic programmes. Countries such as France and Finland are above this trade-off line, whilst Italy and Portugal are below it – this suggests relative outperformance or underperformance across the entire level 3 system.

Figure 2.23. Graduation rates from vocational and general programmes at ISCED level 3, 15-24 year olds,

2009, Source: Eurostat.

20

Finally, Figure 2.24 shows the participation rate in IVET programmes, which is calculated as the number of students in level 3 and level 4 vocational programmes, as a proportion of all those in any level 3 and level 4 programme8. This variable is not available for young people only. Hence, it measures the balance of the system between vocational and general programmes across the entire population of those in these programmes.

Figure 2.24. Participation rate in vocational programmes at ISCED level 3 and 4, Source: Eurostat/UOE. Note:Participation is the proportion of all those in ISCED level 3 and 4 education in a vocational programme.

8As this is calculated as a proportion of all those in an educational programme, this measure does not give any indication of the size of the system or the number of students it produces. A high participation rate cannot be interpreted as meaning a country produces a large number of students, without knowing something about the total number of students and the overall population of that age group. For this reason, both the participation and graduation rates are included together to give a better description of the outputs of each country’s VET system.

21

2.6 Summary There are a wide range of factors influencing the levels of attractiveness identified above. This chapter has discussed the demographic and economic factors. There are a number of common trends, around all of which there is significant variation between countries. The past decade has seen an economic boom followed by a recession in the wake of a global financial crisis. This has fostered labour markets which have first tightened then experienced significant increases in rates of joblessness. It has also led to significant fiscal pressures, with many countries facing or requiring a programme of austerity measures and deficit reduction in the medium term. The skills needs of these labour markets are also changing. Almost all countries in Europe are ageing, with more people retiring than entering the labour market, creating significant replacement demand. Moreover, there are underlying structural changes. Many European countries have falling employment shares in administrative and skilled or semi-skilled manual work, and increased firm demand for service sector jobs and higher-level occupations.

Education systems experience varying degrees of success in producing suitably skilled or qualified future workers to meet these demands. Countries exhibit both low attainment and high attainment (in terms of both early leaving rates and less qualified workforces). In each case, the mix of skills possessed by those that are highly qualified can vary considerably. Two distinctions immediately jump out from the data – the proportion of those who achieve level 3 or 4 qualifications going on to tertiary education, and the proportion of those in upper secondary education engaged in general academic or vocational programmes.

22

Annex C: Notes on Quantitative Data

The table below summarises the source and method of calculation for the quantitative data presented in chapter 2 and 3, as well as the country fiches.

The UOE data on demographic and collected by Eurostat is provided by national statistics agencies. Demographic data is collected through Censuses, administrative data and national surveys.

The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS), the OECD and Eurostat.

The EU-LFS is a quarterly household sample survey carried out in the Member States of the European Union, Candidate Countries and EFTA countries (except for Liechtenstein). It is the main source of information about the situation and trends on the labour market in the European Union. The EU-LFS is organised in 12 modules covering demographic background, labour status, employment characteristics of the main job, atypical work, working time, employment characteristics of the second job, previous work experience of persons not in employment, search for employment, main labour status, education and training, situation one year before the survey and income.

CVTS is an enterprise-level survey given to enterprises with 10 or more employees in certain sectors.

The second table summarises the sample size for the two European-wide surveys.

23

Data Relevant figures(s) Data source Notes on calculation

Young adult population 2.1 UOE, Eurostat Number of 18-24 year olds as percentage of total population

Old age dependency ratio 2.1 As above Number of 65+ year olds as percentage of number of those aged 15-64.

Migration rate 2.2

Real GDP 2.3, 2.4 UOE, Eurostat Directly reported (in Euros, converted at purchasing power parity, and adjusted by the nominal GDP deflator)

Unemployment rate 2.7 EULFS, Eurostat Directly reported as % Youth unemployment rate 2.5, 2.6, 2.7, 2.8 As above Directly reported as % Youth employment rate 2.8 As above Directly reported as %

Occupational structure 2.9, 2.10 As above Number of workers by ISCO-1 occupations as % of total number of workers

Expenditure on secondary education 2.11 UOE, Eurostat

Directly reported expenditure on ISCED 2-4 level programmes in public institutions as % of GDP, calculated in national currency terms

Expenditure on upper secondary and post-compulsory education

2.12 Cedefop website (cited as Eurostat); OECDStat (where available)

Directly reported expenditure in public institutions as % of GDP, calculated in national currency terms

Firm participation in IVET 2.13 CVTS, Eurostat Number of firms offering IVET as % of all firms in survey

Early school leaving rate 2.14 EULFS, Eurostat

Directly reported as %, defined aspopulation aged 18-24 having attained at most lower secondary education and not being involved in further education or training. The numerator of the indicator refers to persons aged 18 to 24 who meet the following two conditions: (a) the highest level of education or training they have attained is ISCED 0, 1, 2 or 3c short and (b) they have not received any education or training in the four weeks preceding the survey. The denominator in the total population consists of the same age group, excluding the respondents who have not answered the questions 'highest level of education or training attained' and 'participation to education and training'.

Educational attainment of working age population 2.15 EULFS, Eurostat

Number of working age population (18-64) with upper secondary or tertiary education as highest qualification, as % of total working age population

IVET graduate rates 2.16 UOE, Eurostat Number of students completing ISCED3 and ISCED4 vocational programmes (aged 18-24 years old) as a % of total 18-24 population

Participation rates 3.4, 3.5, 3.6 UOE, Eurostat

Number of students in ISCED 3 and 4 vocational programmes (aged 15-64) as % of number of students in all ISCED 3 and 4 programmes. Data on 15-24 age unavailable – this measure reflects overall focus of system across all ages, and should be interpreted as such.

Positive image of IVET 3.1, 3.5 Eurobarometer Special 369 - QA9

Directly reported % stating 'very positive' or 'fairly positive'

Recommendations for school leavers 3.3

Eurobarometer Special 369 (QA8) and Eurobarometer Special 216 (Q1)

Directly reported as % recommending vocational education and % recommending general education

Relative esteem indicator 3.2, 3.3, 3.6, 3.7, 3.11

Eurobarometer 369 (QA8) and Eurobarometer Special 216 (Q1)

Difference between % recommending vocational and general education.

Vocational education as pathway to employment 3.10, 3.11 Eurobarometer Special 369

QA12 Directly reported % stating 'more likely' 2011 (QA12) and % stating 'less likely'

24

EU LFS CVTS 2005

Sample size (2009 survey) Sample size Usable responses

Belgium 20800 7576 2959

Bulgaria 27600 3200 2788

Czech Republic 46300 9993 8011

Denmark 40000 2841 884

Germany 132400 10615 2857

Estonia 4000 3022 2112

Ireland 56500 8100 4500

Greece

Spain 129200 11784 0

France 75600 8577 4745

Italy 123000 38341 15470

Cyprus 7700

Latvia 8100 3935 2681

Lithuania 13200 4300 4100

Luxembourg 3600 1683 799

Hungary 56500 5951 4510

Malta 5100 1425 1077

Netherlands 35500 5838 4495

Austria 35500 3435 1456

Poland 41100 17997 15945

Portugal 31500 9834 4425

Romania 48000 9813 8143

Slovenia 16500 2262 1831

Slovakia 20900 2120 1748

Finland 34100 2983 1240

Sweden 50000 3109 1208

United Kingdom 82400 21604 336

Iceland 3100

Norway 20700 2798 916

Switzerland 43900