Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries : final report.
Date: 2020-06-04
Institutions: Directorate-General for Education, Youth, Sport and Culture
Subjects: EU Member State, data collection, diploma, education policy, integration into employment, labour market, teaching quality, vocational education, vocational training

Mapping the state of 
graduate tracking policies 
and practices in the EU 
Member States and EEA 
countries 
Final report 

Written by  

February  2020 

"Insert Logo"  

"Insert Logo"  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
This document has been prepared for the European Commission; however, it reflects the views only of the 
authors, and the commission cannot be held responsible for any use which may be made of the information 
contained therein. 

EUROPEAN COMMISSION 

Directorate-General for Education, Youth, Sport and Culture 
Directorate B — Youth, Education and Erasmus+ 
Unit B.1 — Higher Education 
E-mail:  EAC-UNITE-B1@ec.europa.eu 
European Commission 
B-1049 Brussels 

 
 
 
 
 
EUROPEAN COMMISSION 

Mapping the state of 
graduate tracking policies 
and practices in the EU 
Member States and EEA 
countries 
Final report 

Shane Beadle 

Patricia Vale 

Sigrid Mannsberger-Nindl 

Arthur Hannah 

Ali Zaidi 

Claudia Abdallah 

Andrea Kottmann 

Written by ICF S.A.                                                                                          
in association with  
3s Unternehmansberatung and CHEPS 

Directorate-General for Education, Youth, Sport and Culture 

Erasmus+ 

March, 2020 

EUR EAC-2019-0342 EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
         
                       
 
 
Printed by the Publications Office of the European Union in Luxembourg 

Manuscript completed in March 2020. 

The European Commission is not liable for any consequence stemming from the reuse 
of this publication.  

Luxembourg: Publications Office of the European Union, 2020 

© European Union, 2020 

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

Except otherwise noted, the reuse of this document is authorised under a Creative 
Commons Attribution 4.0 International (CC-BY 4.0) licence 
(https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed 
provided appropriate credit is given and any changes are indicated. 

For any use or reproduction of elements that are not owned by the European Union, 
permission may need to be sought directly from the respective rightholders.  

Print 

ISBN 978-92-76-18129-3 doi:10.2766/09070 NC-01-20-250-EN-C 

PDF 

ISBN 978-92-76-18130-9 doi:10.2766/62505 NC-01-20-250-EN-N 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table of Contents 

Final report 

Abstract .......................................................................................................... i 

Executive summary ............................................................................................ii 

Background and context ...................................................................................ii 
About this study ..............................................................................................ii 
Key findings ................................................................................................... iv 
Conclusions .................................................................................................. xiii 
Some recommendations ................................................................................ xiv 

1 

Introduction ................................................................................................ 1 

1.1 
Background and context ......................................................................... 1 
1.2  Objectives and scope of the study ............................................................ 2 
1.3  Overview of the methodology .................................................................. 3 

2  National policies and developments in graduate tracking ................................... 8 

2.1 
Policy focus on graduate tracking ............................................................. 8 
Responsibility for graduate tracking ........................................................12 
2.2 
2.3  Maturity of countries’ graduate tracking systems ......................................14 
2.4  Ongoing and planned reforms ................................................................17 
2.5  Main purposes and users of graduate tracking ..........................................19 
2.6  Drivers and obstacles to the development of graduate tracking ..................21 
Key summary points .............................................................................22 
2.7 

3  Characteristics of system-level tracking measures ...........................................25 

3.1  Number of system level measures in the EU and EEA ................................25 
3.2 
Key features of system-level graduate tracking measures ..........................27 
3.3  How graduate tracking data is being used ................................................38 
3.4  Other graduate tracking measures ..........................................................41 
Complementarity between system-level and other measures......................43 
3.5 
Key summary points .............................................................................44 
3.6 

4  Country’s progress towards meeting the Council Recommendation ....................47 

4.1 
4.2 
4.3 

Country overview..................................................................................47 
Coverage of benchmarking criteria ..........................................................53 
Key summary points .............................................................................56 

5  Compatibility of practices and comparability of graduate outcomes data among 
countries .........................................................................................................58 

5.1  Methodology for the analysis of comparability and compatibility of practices 
and graduate outcomes data ...........................................................................58 
Key summary points .............................................................................66 
5.2 

6 

Institutional graduate tracking in higher education ..........................................67 

6.1 
Prevalence and type of graduate tracking undertaken by higher education 
institutions ....................................................................................................67 
6.2  Use of quantitative and qualitative surveys ..............................................72 
6.3  Use of administrative data .....................................................................79 
6.4  Use of data mining ................................................................................82 
6.5 
Information collected in higher education institution graduate tracking 
measures ......................................................................................................85 
6.6  Main differences and commonalities between methods ..............................88 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Availability and types of contact information held by higher education 

6.7 
institutions ....................................................................................................89 
6.8  How higher education institutions use graduate tracking data.....................90 
Reasons for not undertaking graduate tracking .........................................91 
6.9 
Key summary points .........................................................................92 
6.10 

7  Conclusions ................................................................................................94 

7.1 
7.2 
7.3 

Addressing the research questions ..........................................................94 
Implications ....................................................................................... 104 
Some recommendations ...................................................................... 105 

Annex 1.  List of interviewees ......................................................................... 106 
Annex 2.  Annexes to chapter 2 ...................................................................... 111 
Annex 3.  Annexes to chapter 3 ...................................................................... 122 
Annex 4.  Annexes to chapter 4 ...................................................................... 136 

Benchmarking criterion ‘Inclusion of graduate programmes’ .............................. 139 
Benchmarking criterion ‘Inclusion of graduates’ ............................................... 142 
Benchmarking criterion for ‘Longitudinality’ ..................................................... 144 
Benchmarking criterion on the ‘Quality of data’ ................................................ 147 
Benchmarking criterion on ‘Dissemination and use of data’ ............................... 149 
Overview on results ..................................................................................... 153 
Methodology for assessing coverage of benchmarking criteria ........................... 154 
Methodology for assessing the timeline for countries to meet the Council 
Recommendation ......................................................................................... 159 

Annex 5.  Annexes to chapter 5 ...................................................................... 161 

 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Abstract 

This study maps the system-level approaches to higher education and vocational 
education and training graduate tracking across the European Union and the 
European Economic Area, and their progress towards achieving the requirements of 
the Council Recommendation on tracking graduates1. 

It finds that about two thirds of the countries have system-level graduate tracking in 
higher education and vocational education and training. The remainder will have to make 
considerable improvements if they are to establish system level graduate tracking in the 
next five years.  

Ongoing reforms indicate an increasing use of administrative data and a combination 
of administrative data and surveys to track graduates. The involvement and 
cooperation of key bodies, including those in charge of the policies and those holding 
the data and the methodological expertise, are key to successful tracking.  

A benchmarking of national graduate tracking measures shows that the most significant 
areas for improvement are a) the coverage of the whole graduate population in both 
vocational education and training and higher education; b) the inclusion of all (including 
cross-border) graduates and drop-outs; and c) having a longitudinal approach to 
tracking. 

A first survey among higher education institutions found that graduate tracking is 
generally well-embedded in higher education institutions across EU and EEA countries. 

1 Council Recommendation on Graduate tracking (2017/C 423/01) 

March, 2020 

i 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Executive summary 

Graduate tracking is ‘the collection of quantitative micro and aggregate data and/or 
qualitative information about the employment and social outcomes of people leaving 
higher education and vocational education and training (VET)2. This study, completed by 
the Inner City Fund (ICF), 3s Unternehmensberatung GmbH and the Centre for Higher 
Education Policy Studies (CHEPS) on behalf of the European Commission, captures what 
is happening in graduate tracking at system level (national or regional) for both higher 
education and vocational education and training, and at institutional level for higher 
education. It assesses how far countries are meeting the benchmarks for graduate 
tracking set out in the 2017 Council Recommendation and how far the measures they 
have in place would enable comparison at EU level.  

Background and context 

Tracking graduates can provide crucial intelligence about the quality of learning 
programmes in higher education and vocational education and training and the extent to 
which it meets labour market needs. This is a powerful instrument to further improve the 
design and update of curricula for the acquisition of relevant skills and employability; and 
to ensure skills matching to support competitiveness, innovation and the resolution of 
skills shortages. It can also be used for improving career guidance for prospective 
students, current students and graduates, and planning for and forecasting employment, 
educational and social needs. 

This has been underpinned by the European Commission’s New Skills Agenda for 
Europe (2016), which emphasised the need for countries to have a ‘better 
understanding of the performance of graduates’ and was supported by a mapping study 
of graduate tracking in vocational education and training completed in 2018. It was 
further emphasised by the Renewed EU Agenda for higher education (2017) and a range 
of initiatives to improve information on how graduates progress in the labour market, 
such as the Eurograduate Pilot Survey, and the establishment of an Expert Group on 
Graduate Tracking (2018-2020) to provide a forum for cooperation and mutual learning 
about graduate tracking and data analysis.  

Additionally, the Council Recommendation on tracking graduates (2017) proposes 
“making progress by 2020 on the establishment of graduate tracking systems”3. The 
Recommendation acknowledges that initiatives and systems for collecting information 
about higher education and vocational education and training leavers could benefit from 
improvement and standardisation and sets out minimum requirements for graduate 
tracking measures.  

It has also been underpinned by wider understanding that tracking graduates is a core 
component of effective quality assurance systems as it provides a mechanism for 
gathering intelligence on skills utilisation in the labour market and placement rates. This 
is recommended in both the Standards and Guidelines for Quality Assurance in the 
European higher education Area and the European Quality Assurance Framework for 
Vocational Education and Training. 

About this study 

Aims and objectives 

The main aim of this study is to capture the state of play in graduate tracking at system 
level (national or regional) for both vocational education and training and higher 
education; and at institutional level for higher education. It also aims to share effective 

2 Technical Specifications for Request for Services EAC/23/2019, Annex A, p. 1. 
3 https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX%3A32017H1209%2801%29#ntr12-
C_2017423EN.01000101-E0012  

March, 2020 

ii 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

practice in designing and implementing graduate tracking measures and disseminating 
and using their results. 

The study has the following objectives: 

  Specific objective 1: Mapping the state of play and types of graduate tracking in 

higher education and vocational education and training;   

  Specific objective 2: Comparative analysis of country graduate tracking 

measures;  

  Specific objective 3: Producing a set of guidelines on designing, implementing, 

disseminating and using the results of graduate tracking4; and 

  Specific objective 4: Mapping institutional graduate tracking in higher 

education.5  

To address these objectives, the key research questions that guided the study were: 

  What is the general coverage of graduate tracking at institutional and system-

level, both of higher education and of VET graduates? 

  What are the main methods used to track HE and VET graduates? 
  What is the content of data collected in graduate tracking?  
  To what extent do national graduate tracking systems meet the requirements of 

the Council recommendation on tracking graduates?  

  To what extent does graduate tracking conducted at system level allow for cross-

country comparability? 

  What are the key features of an effective system-level graduate tracking 

measure? 

The study covers all EU-27, the UK and EEA member countries (31 in total). The mapping 
focuses on the system level. In the countries where higher education or VET systems are 
fully or partially devolved to sub-national authorities, regional measures were also 
researched.6 The study covers higher education, initial VET and continuing VET. In terms 
of education levels, it focuses on upper secondary, post-secondary non-tertiary VET 
programmes, and higher education at EQF7/ISCED8 level 6. However, it has collected 
measures found relating to other groups, such as higher-level graduates (EQF/ISCED 
level 7 and above) and apprentices and learners in dual VET9 where they fall within the 
measures that meet the above criteria. 

Method  

The study consisted of two main research tasks: the mapping and description of system-
level approaches to VET and higher education graduate tracking, including  the analysis 
of these systems and their measures, and a questionnaire survey of higher education 
Institutions about their graduate tracking practices and the analysis of the responses. 
Findings from these processes fed into the development of a guidance publication on 
graduate tracking.  

4 The results of this part of the study are a guidance document, How to do graduate tracking, for policy makers 
and practitioners 
5 This is primarily the practices found in larger institutions (defined as having more than 200 students and 30 full-
time equivalent staff) that predominantly deliver programmes at EQF level 6 or above. 
6 In Belgium the mapping focuses on Flanders (BE-NL) and Wallonia (BE-FR); in Germany, Italy and Spain the 
research focused on the national and regional levels; in the UK, the mapping focuses on England and Scotland 
but specific examples have also been included for Wales and Northern Ireland.  
7 European Qualifications Framework. 
8 International Standard Classification of Education 
9 Vocational education and training combining periods in an educational institution or training centre and in the 
workplace.  

March, 2020 

iii 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Mapping system level approaches to graduate tracking 

The mapping and description of system level approaches to graduate tracking in EU and 
EEA countries was based on desk research and semi-structured interviews. As part of this 
exercise a total of 95 interviews were conducted with ministry officials, project managers, 
researchers and statisticians.10 The information collected included background 
information on graduate tracking in the country and a detailed description of each of the 
tracking measures identified at system level. The mapping exercise aimed to identify all 
of the system-level graduate tracking measures in place in EU and EEA countries, and in 
the UK.  

Inevitably, the level of information obtained about each measure varies. In some cases, 
it was not possible to capture all the details about the methodology applied or the use 
made of tracking results. This was due to lack of information in published sources or 
known by interviewees and the scale of the task in some countries within the time scale 
of the research.   

The information collected in the mapping has informed the comparative analysis, as well 
as the assessment of countries’ progress towards meeting the Council Recommendation 
and the comparability and compatibility of practices and graduate outcomes data among 
EU and EEA countries. 

The country factsheets completed for the mapping and a draft version of this report were 
shared with the members of the European Commission Expert Group on Graduate 
Tracking before its publication. Their feedback was incorporated into the final version of 
this report. 

Surveying higher education institutions about graduate tracking 

higher education institutions’ data on graduate tracking was collected using an online 
survey. The survey collected information on the type of graduate tracking measures 
used, the motivations for undertaking graduate tracking or, where tracking is not done, 
the reasons for not doing so. The survey was open to all higher education institutions 
between 5 November 2019 and 10 January 2020.   

A response of 615 valid survey returns was achieved, which are estimated to represent 
about a third (34%) of the total higher education institutions in scope for the study and 
representing about half (50%) of the graduates in these organisations. This gives a 
representative response rate which allows for a robust statistical analysis of the 
approaches to graduate tracking by higher education institutions in Europe. 

In 18 countries, the survey had responses from higher education institutions covering 
over 50% of the graduate population (AT, BE, BG, HR, CZ, DK, EE, FI, IS, IT, LI, LU, MT, 
PT, SK, SI, ES, SE). In the three countries where the survey received responses covering 
under 40% of the graduate population (UK, NO, DE), this may be explained by their 
participation in national measures which override the need for their own graduate 
tracking.  

Key findings  

National policies and developments in graduate tracking 

About two thirds of the countries have system-level graduate tracking in higher 
education and VET. The remainder will have to make considerable 
improvements if they were to establish system level graduate tracking in the 
next five years.  

  higher education and VET graduate tracking is an established practice in 18 

countries (AT, BE-NL, CZ, DE, DK, EE, ES, FI, FR, IE, IT, LU, LT, NL, NO, SE, SK, 
UK). 

10 In a few cases, due to lack of availability of the persons contacted, consultations were done via e-mail. 

March, 2020 

iv 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Three countries have system-level graduate tracking measures for one of the 

sectors only, higher education (BG, HU, PL) or VET (BE-FR, PT).   

  Two countries can be expected to have higher education graduate tracking in place 

over the next one or two years (LV, SI).  

  In RO and IS there are activities but not necessarily at system level. 
  In three countries without system level graduate tracking, the Eurograduate 

survey provided significant push to start developing a national system (HR, EL and 
MT).  

  In CY and LI there is little or no relevant experience with graduate tracking so far.  

The countries where graduate tracking is a legal obligation tend to have well-
established tracking systems. However, a legal basis is not a necessary 
condition for regular graduate tracking.  

In close to half of the countries, graduate tracking is both a legal obligation and a 
regular practice (AT, DE, DK, EE, ES, FI, FR, HU, IT, NL, PL, SE and UK).  

In another third of countries, graduate tracking is a well-developed practice 
despite not being a legal obligation (BG (in higher education), BE-NL, CZ, IE, LT, 
LU, NO and SK).  

In some of these countries, tracking is considered to be a policy objective (BG, 
CZ, IE, LT, SK) but in a few there is no policy focus on the topic (BE-NL, LU and 
NO). 

A few countries with poorly developed graduate tracking have included the aim to 
do so in recent policy documents (BE-FR, BG (in VET), HR, MT, RO, SI).  

In the remaining countries, graduate tracking is poorly developed and there are 
no policy objectives related to it (CY, EL, IS, LI). 

The responsibility for graduate tracking generally lies with the national or 
regional authorities which oversee higher education or VET policies. In the 
countries where no measures can be identified at system level, it was not possible to 
establish which level is responsible for graduate tracking  

in VET (BG), 

in higher education (RO),  

or both sectors (CY, EL, HR, IS).   

Ongoing reforms indicate an increasing use of administrative data and a 
combination of administrative data and surveys.  

New graduate tracking measures are currently under development in BG, LV and 
SI and have been announced in FR, HU, LI, LT, PL, RO and SK.11  

Reforms of existing tracking measures are ongoing in BE-NL, DE, ES, FI, and SE. 

Ongoing or announced reforms indicate an increase in the use of administrative 
data for graduate tracking (ES, FR and SK) and an awareness of the importance 
of combining administrative data and surveys.  

The involvement and cooperation of key bodies, including those in charge of the 
policies and those holding the data and the methodological expertise, are key to 
successful tracking. Graduate tracking requires the involvement of different ministries, 
national agencies and departments, including statistical offices and research agencies. 
Smooth cooperation between these entities as well as with other relevant parties, such 
as education and training providers and employer representatives, can be a key factor to 

11 A new graduate tracking measure based on administrative data collection was launched in 2019 in Slovakia. 
Information on the measure was not yet available at the time the research for this study was completed. 

March, 2020 

v 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

the successful implementation of graduate tracking. Common obstacles to the 
development of graduate tracking include lack of leadership or priority to foster 
cooperation between the different actors, restrictions due to differing legislation on 
personal data protection in Member States, insufficient methodological and technological 
capacity and insufficient funding. 

Characteristics of system level tracking measures 

The study identified 123 graduate tracking measures at system level across 29 
countries. Only EL and CY have no system level relevant measures except for the 
tracking of completers in European Social Fund-funded training. In the other countries, 
measures cover to varying degrees initial VET, continuing VET and higher education 
graduates. Continuing VET graduates are the least covered with just 34 measures 
identified. 

Measures do not necessarily include the entire graduate population. Measures 
generally focus on completers of study programmes across all education sectors.  

Around a third (39 measures) include students who dropped out before 
completing their degree; a higher proportion of these are initial VET measures.  

Only a few measures (15) include graduates who have migrated to another 
country, more of these are higher education measures than initial VET or 
continuing VET ones.  

Only a third of the measures (44) collect data on every cohort of graduates, 
others take place periodically at a variety of frequencies. 

Measures collect a wide range of data, which can be used for the purposes 
identified, although there are considerable variations in what is collected and in 
what detail. 

  The main variables collected relate to employment status, socio-biographical and 

socioeconomic information, further education and training pathways.  

  As expected, surveys are the main sources of satisfaction data about the quality of 

programmes and the relevance of acquired skills.  

  Fewer measures capture data, which can be of analytical value on graduate 
backgrounds (migration, ethnicity, parents’ education) and data on graduate 
education which can be used for linkage to administrative data. 

  Many measures (54) use unique identifiers enabling data to be linked. As a result, 

some of this data may not need to be collected through other means. 
  Very few measures (13) capture information on graduates’ social and civic 

activities. 

March, 2020 

vi 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 1.  Main indicators covered by the instrument 

Socio-biographical and socioeconomic information

Employment status

Further education and training pathways

Link to level, field of study and provider

Satisfaction

Relevance/utilisation of acquired skills at the…

Place of residence / migration to other countries

Social and civic activities and participation in these

13

110

94

84

68

61

60

54

Figure 2. 

Other indicators

45

20

0

40

60

80

100

120

Source: Mapping research conducted by ICF, 3s and CHEPS. 

 

Only around a third of measures (45) track graduates more than twice to 
provide longitudinal data, which is of value to policy makers and other users of 
the data. Just under two thirds of countries (20) have at least one measure that gathers 
longitudinal data on graduates. Where cohorts are followed-up, this takes place mainly 
two or three times within a cycle of around two and four years after graduation. Thirty 
measures have at last three follow-ups; many of these are part of larger scale panel 
studies. 

Many countries use both survey and administrative data collection for tracking 
graduates since they complement each other in providing the data needed. 
Consequently, there are nearly an equal number of survey (mainly quantitative) and 
administrative data collection (mainly registers on education achievements, social 
security and unemployment) approaches identified.  

Fewer measures use sampling (49) than use of the total reference population 
(67).  

Administrative data-based measures more often draw on the total reference 
population for analysis and for sampling, than surveys which are more often 
based on achieved samples derived from contacting the entire graduate cohort 
(30) and from selected samples (44).  

In around a quarter of the measures (30), there are reportedly limitations in the 
use of the data because of inadequate achieved sample sizes either because of 
response bias or because of size limiting sub-group analysis.  

While many measures use robust methods for sampling (systematic and random), 
12 use convenience sampling which runs a higher risk of response bias. 

Eighty percent of measures have some data made publicly available for others 
to use but in many cases there are either limitations in the level of detail and 
the availability to potential users.   

  Data are mainly available with limitations, for example in aggregated form only, 

restricted to specific users. 

  For around a third of measures (39), anonymised case data are available, and for 

a greater number (55) data is available for providers. 

  Data is generally provided freely. 

March, 2020 

vii 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Data used for system level monitoring and evaluation of education policies and 
their development can be identified for over half of the measures. Some other 
uses are less frequently identified.  

  There are no significant differences in the use of data which are based on surveys 
and administrative data collection, and none between higher education and VET 
measures.  

  Around a third of measures are used to plan for employment, education and social 

needs, to support design and current curriculum and to strengthen career 
guidance.  

  Around 40% (50) of measures are used either in the funding or/and the appraisal 

and quality assurance of providers. 

  Only one in four measures are used in improving skills matches.  
  Only six measures have developed counterfactuals with comparison groups of non-

graduates for their analyses. 

Ten countries have systems to ensure the complementarity of system level measures and 
institutional level measures. These are: DK, FI, FR, HU, IE, IT, LV, NL, NO, UK. 

Country progress towards meeting the Council Recommendation on Graduate 
tracking (2017/C 423/01) 

The following progress benchmarking criteria were defined on the basis of the Council 
Recommendation: 

‘Inclusion of graduate programmes’: coverage of relevant programmes in 
higher education, initial VET and continuing VET. 

‘Inclusion of graduates’: coverage of the full graduate population, incl. cross-
border graduates & drop-outs. 

‘Longitudinality’: tracking of graduates at different points after they graduated.   

‘Quality of data’: use of a variety of quantitative and qualitative data. 

‘Dissemination and use of data’: use of data for different purposes and by 
different users. 

The assessment of countries’ progress towards achieving in full the Council’s 
Recommendation on graduate tracking is summarised in the table below. It shows: 

  Virtually complete coverage of the benchmarking criteria for Germany and Finland 
and nearly complete coverage for Austria, Denmark, Ireland, Sweden and United 
Kingdom.  

  Countries with (nearly) no coverage are Cyprus, Greece and Iceland.  
  Belgium (BE-Fr), Bulgaria, Croatia, Latvia, Liechtenstein, Luxembourg, Malta, 

Romania, Slovakia and Slovenia have limited coverage.  

  The other countries provide good coverage of the assessment against the criteria. 

There are improvements to be made against all the criteria of the Recommendation by 
the majority of countries. 

  The most significant areas for improvement for at least ten countries are coverage 
of all the graduate population in initial VET, continuing VET and higher education; 
the inclusion of all graduates; and having a longitudinal approach to tracking.   

  A more detailed analysis of this shows that there is considerable room for 
improvement, particularly in the following aspects of graduate tracking: 

-  The coverage of continuing VET across nearly all benchmarking criteria; 
-  The inclusion of drop-outs and mobile graduates in surveys; 
-  The follow-up of cohorts of learners at least twice within five years; 
-  The coverage of the main indicators across all sectors; and 

March, 2020 

viii 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

-  The quality of surveys to provide sufficient representative achieved samples in 

all case.  

 

Table 1.  Assessment of countries’ progress towards meeting the Council 

Recommendation on Tracking Graduates 

Table 2. 

Inclusion 
of 
graduate 
programm
es 

Inclusion 
of 
graduates 

Longitudi-
nality 

Quality of 
data 

Dissemi-
nation and 
use of data 

Average 
across 
benchmark 
areas 

Estimation 
of timeline 
for 
meeting 
the 
Recommen
dation 

3 years 

4 years 

5 years 

5 years 

4 years 

4 years 

4 years 

3 years 

3 years 

2 years* 

5 years 

2 years* 

6 years 

4 years 

2 years 

2 years 

5 years 

4 years 

3 years 

3 years 

ix 

Austria 

Belgium 
(Flanders) 

Belgium 
(French-
speaking)  

Bulgaria  

Croatia 

Cyprus 

Czech Republic 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

March, 2020 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Inclusion 
of 
graduate 
programm
es 

Inclusion 
of 
graduates 

Longitudi-
nality 

Quality of 
data 

Dissemi-
nation and 
use of data 

Average 
across 
benchmark 
areas 

Luxembourg 

Malta 

Netherlands 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United Kingdom   

Source: Mapping research conducted by ICF, 3s and CHEPS.  
* Timeline for further elaboration of graduate tracking measures. 

- 

Estimation 
of timeline 
for 
meeting 
the 
Recommen
dation 

3 years 

3 years 

3 years 

3 years 

5 years 

4 years 

6 years 

4 years 

4 years 

5 years 

3 years 

4 years 

Compatibility of practices and comparability of graduate outcomes data among 
countries  

There is potential for the comparison of the results of graduate tracking 
measures between many countries. Fifty-one measures met a minimum threshold in 
relation to employment classification, representativeness and cohort /periodicity. More 
countries could be compared for initial VET and higher education graduate indicators than 
for continuing VET. 

Many variables (described here as indicators) are commonly collected and are potentially 
comparable between many measures. Indicators with the highest country coverage 
across initial VET, continuing VET and higher education are employment status, socio-
biographical information and further education and training. For the 51 potentially 
comparable measures, ‘employment status’ is covered best of all – with 19 countries in 
initial VET, 9 countries in continuing VET and 21 countries in higher education. 

Other indicators in initial VET covering at least 10 countries and a maximum of 13 
countries are sustainable employment, further education and training, socio-biographical 
information, age, gender. In continuing VET none of the indicators has a coverage of 
more than 9 countries. Indicators with the highest coverage are – besides employment 
status – further education and training (9 countries), socio-biographical information as 
well as level, field of study and provider (8 countries each). In higher education 
indicators with higher country coverage are socio-biographical information (17 countries) 
and further education and training (15 countries).  

March, 2020 

x 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Comparability is only possible where measures have used the very similar if not the same 
approaches and use the same means for classifying indicators. These include standard 
international classifications such as ISCED and NACE12; standard definitions for 
socioeconomic/biographical data and satisfaction questions; similar periodicities for data 
collection; representativeness of the achieved sample or, in case of surveys, sufficient 
response rate; and data availability for comparative research.  

Many measures do not currently match these requirements which reduces the potential 
number of measures which can be used for comparison and benchmarking and 
consequently reduces the number of countries’ that can be included. 

Institutional graduate tracking in higher education 

The survey identified that graduate tracking is generally well-embedded in 
higher education institutions across EU and EEA countries. Four out of five survey 
respondents said their higher education institutions holds private email addresses for 
their graduates, while only around half said they store home address contact details. 
More than nine out of ten survey respondents said their higher education institution 
undertakes some form of graduate tracking. The existence of good measures at national 
level appears to save resources for higher education institutions in some countries that 
are less likely to undertake institutional graduate tracking. Examples include the UK and 
Norway. 

Figure 3.  Type of tracking measure(s) used by size of higher education institutions 

%
6
8

%
2
8

%
2
8

%
8
7

100%

80%

60%

40%

20%

0%

%
1
2

%
1
1

%
8

%
5

%
3
2

%
2
2

%
8
1

%
9
1

%
4
2

%
0
1

%
7

%
7

%
0
1

%
0
1

%
9

%
9

%
7

%
6

%
9

%
7

Quantiative
survey

Qualitative
survey

Data matching

Data mining

 Other

 None

HEIs with 5,000 or less students

HEIs with 5,001-15,000 students

HEIs with 15,001-25,000 students

HEIs with more than 25,000 students

Source: ICF graduate tracking higher education institution survey (5,000 or less: N=199, 
5,001-15,000: N=209, 15,001-25,000: N=96, More than 25,000: N=111). Multiple 
choice question.  

Most higher education institutions reported that they undertook a questionnaire 
survey to which they invited cohorts of graduates for whom they had contact 
details to complete online.   

  Quantitative surveys are the most common form of graduate tracking and are 
used by more than four out of five higher education institutions undertaking 
tracking, typically administered online. Smaller higher education institutions are 
more likely to do qualitative surveys, such as interviews and focus groups.  

12 Statistical Classification of Economic Activities in the European Community 

March, 2020 

xi 

 
 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  About three fifths of higher education institutions only use one tracking measure. 

Where higher education institutions use qualitative surveys or match 
administrative data, this is often supplementary to a quantitative survey of their 
graduates.  

  Higher education institutions typically limit their tracking to former students who 

complete their studies and remain in the same country.   

The quality of institutional tracking varies considerably. For quantitative graduate 
tracking surveys, around two thirds of higher education institutions said they use some 
form of random sampling and nearly half said they achieve a response rate of 50% or 
more. However, around a third of those sampling use a convenience sample. Sampling 
may account for some of the poor level of response higher education institutions receive 
to their quantitative surveys. For around a third it is reported to be lower than 30%. 
Under half (43%) of higher education institutions graduate surveys obtain more 
favourable response rates above 50%. Around a quarter (25%) achieve a response rate 
of above 70%, which would provide sufficient data for detailed sub-group analysis (by 
programme and graduate characteristics).  

Higher education institutions that only distribute their graduate tracking survey online 
more often achieve a lower response rate compared to those that use more than one 
survey method, particularly where the survey is administered via telephone too. Three 
quarters of higher education institutions using only online methods failed to achieve a 
50% response rate compared to just under a third (28%) of those using online and 
telephone. 

Quantitative survey response rates by method(s) used 

29

31

80

96

s
n
o
i
t
u
t
i
t
s
n

I

n
o
i
t
a
c
u
d
E
r
e
h
g
H

i

f
o
r
e
b
m
u
N

6

4

20

4

1

3

2

34

58

27

8

10

13

4

1

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

10

6

2

Online survey
only (n=236)

Online and
paper-based
survey (n=34)

Paper-based
survey only
(n=6)

Online and
telephone
survey (n=127)

Telephone
survey only
(n=28)

Online,
telephone and
paper-based
survey (n=18)

Response rate of 25% or less

Response rate of 26%-50%

Response rate of 51%-75%

Response rate of 76% or more

Source: ICF graduate tracking higher education institution survey (N=number of 
respondents shown above). ‘Don’t know’ responses and item non-responses removed 
from the analysis.  

March, 2020 

xii 

 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

A little over two thirds of higher education institutions implement their tracking measure 
within 18 months of graduation. The majority of higher education institutions do not 
track their graduates over more than one time period to collect longitudinal data.  

Tracking measures most commonly capture data on graduates’ employment status, job 
level and salary.  

  Less than a quarter of higher education institutions using each type of tracking 
measure capture data on participation in volunteering or civic/community 
activities, and similarly reasons for pursuing further education was a measure 
much less commonly collected by individual higher education institutions.  

  Overall, collected data typically has a larger impact on the careers’ advice higher 
education institutions give their students than other areas, such as the range and 
scope of courses they offer or financial contributions from alumni.  

Figure 4.  Impact of graduate tracking on different areas of higher education institutions  

Careers advice (n=487)

19%

28%

30%

14%

10%

The range and scope of the courses your
institution offers (n=478)

10%

25%

35%

19%

13%

Alumni contributions (n=474)

10%

20%

33%

19%

18%

0%

20%

40%

60%

80%

100%

5 - major impact

4

3

2

1 - no impact

Source: ICF graduate tracking higher education institutions survey. N=number of 
respondents answering each question.  

 

Conclusions    

The study shows that further action is needed to improve graduate tracking 
measures in all countries 

There are significant differences in the graduate tracking mechanisms in the 31 countries 
analysed. While the majority of countries have well-developed graduate tracking 
systems, there is room for improvement in the comparability of data at EU level and the 
effectiveness of the measures taken.   

The analysis of the comparability of the measures taken by the countries identifies the 
indicators that could be benchmarked among ten or so countries. Employment status, 
socio-biographical information and further education and training of graduates are the 
most often covered indicators across higher education, initial VET and continuing VET.  

The changes to measures that would be needed to enable comparability on a greater 
scale include increasing the use of standard international classifications such as ISCED 
and NACE; standard definitions for socioeconomic/biographical data and satisfaction 
questions; similar periodicities for data collection; representativeness of the achieved 
sample or, in the case of surveys, a sufficient response rate; and data availability for 
comparative research. Increasing convergence should focus on improving different 
aspects of measures (sampling, data collected, and the classification of data) in parallel.  

The results of the higher education institutions’ survey provide up to date information on 
the state of play of graduate tracking within the higher education sector across the EU, 
UK and EEA, and how graduate data are used. This shows considerable interest by higher 

March, 2020 

xiii 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

education institutions in tracking graduates, with nine out of ten survey respondents 
informing that their institution undertakes some form of graduate tracking. 

The survey also provides information on the limitations of these efforts in terms of data 
quality, representativeness and regularity. For instance, more than half of the higher 
education institutions using quantitative surveys failed to achieve a suitable response 
rate of 50% or more. For around a third it was under 30%. 

It is important to consider how higher education institutions might be better supported to 
receive the information they need from graduate tracking. Institution-level measures 
could provide a good basis for developing a national system in countries where it is not 
available, as buy-in of higher education institutions is crucial for a successful graduate 
tracking mechanism. 

Countries at some distance from meeting the Recommendation’s requirements 
can benefit from support and guidance 

This could be done through peer learning, expert support, self-organised consultancy and 
good practice sharing, in particular between countries facing similar challenges. For 
example, a group of countries in Mid-Eastern Europe have similar issues (BG, CY, EL, HR, 
RO, SI, SK), including a lack of systematic graduate tracking measures in some or all the 
sectors (especially in continuing VET), limited tracking data available (few indicators 
covered) and a lack of longitudinal data. However, a few of these countries have some 
well-developed tracking measures (SK, BG for higher education) and can share their 
experience. Small countries -with a low number of higher education institutions and 
vocational education and training providers- could also be grouped for peer learning 
activities or good practice sharing  (CY, LU, LV, MT, SI, SK), combining countries that 
have progressed both more and less towards the Council Recommendation on graduate 
tracking.  

Some recommendations 

  Encourage Member States to increase the coverage of their graduate tracking 

system across higher education and VET, including continuing VET graduates, and 
with all graduate cohorts tracked;  

  Encourage Member States to work towards greater convergence: particularly in 

relation to survey questions, data collected, representative data, and longitudinal 
data;  

  Consider providing additional capacity building support to share good practices in 
establishing and maintaining graduate tracking systems to overcome some of the 
gaps and deficiencies in their implementation. This could take the form of peer 
learning opportunities, mutual learning among country groups, task forces to 
support a specific country;   

  Consider introducing additional requirements than the ones specified in the Council 

Recommendation on tracking graduates, namely to include social and civic 
outcomes of higher education and vocational education and training to the data 
collected, and a specification of a minimum percentage of graduates in achieved 
samples; 

  Encourage European bodies representing higher education institutions to increase 
the advice and guidance they provide on graduate tracking and reflect on the 
findings of this study’s survey results about the quality/scope of surveys.  

  Encourage Member States and other countries to establish coordination between 
national and provider level graduate tracking activities to increase synergies and 
convergence. 

March, 2020 

xiv 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

1 

Introduction 

1.1  Background and context 

Tracking the destinations of graduates can provide crucial intelligence on the quality of 
learning programmes in higher and vocational education (higher education and 
vocational education and training) and the extent to which it meets labour market needs. 
This can be used for: 

  Strengthening career guidance systems for prospective students, current students 

and graduates;  

  Supporting the design and updating of curricula to improve the acquisition of 

relevant skills and employability; 

  Improving skills matching to support competitiveness and innovation at local, 

regional and national level, and to resolve skills shortages;  

  Planning for and forecasting evolving employment, educational and social needs; 

and 

  Contributing to policy development at both national and EU levels. 

The Commission’s New Skills Agenda for Europe (2016) emphasised the need for 
countries to have a ‘better understanding of the performance of graduates’. To achieve 
this the Commission proposed a new EU-level initiative on tertiary graduate tracking to 
improve information on how graduates progress in the labour market.13  

The Council Recommendation on tracking graduates (2017) was subsequently 
issued which proposed “making progress by 2020 on the establishment of graduate 
tracking systems”14. The Recommendation acknowledges that initiatives and systems for 
collecting information about higher education and vocational education and training 
leavers could benefit from improvement and standardisation.  

The ability to track graduates is also considered a core component of effective quality 
assurance systems as it provides a mechanism for gathering intelligence on skills 
utilisation in the labour market and placement rates. This is recommended in both the 
Standards and Guidelines for Quality Assurance in the European Higher Education Area 
(ESG) and the European Quality Assurance Framework for Vocational Education and 
training (EQAVET).  

In line with policy recommendations, the Commission has supported several initiatives to 
increase the knowledge of graduate tracking policies and practices in Europe, and to 
enhance the use and quality of graduate tracking.  

In 2017, the Commission published “The Mapping of vocational education and training 
graduate tracking measures at EU Member States” which described national and 
institutional practices in vocational education and training and discussed scenarios for 
cooperation at EU level.15 In the higher education sector, the Eurograduate Pilot Survey 
has recently tested the feasibility of implementing a European graduate survey across 
Erasmus+ countries.16 The Commission has also established the Expert Group on 
Graduate Tracking (2018-2020) which provides a forum for cooperation and mutual 
learning about graduate tracking and data analysis. The Expert Group recognised the 
need to have an up to date mapping of measures across higher education and vocational 
education and training in the EU.  

13 http://europa.eu/rapid/press-release_IP-16-2039_en.htm (12.07.2019). 
14 https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX%3A32017H1209%2801%29#ntr12-
C_2017423EN.01000101-E0012  
15 The study was conducted by ICF Consulting Services Limited, in association with 3s, under the framework 
contract EAC/47/2014 (Request for Services VT/2016/058). Available at: https://op.europa.eu/en/publication-
detail/-/publication/00d61a86-48fc-11e8-be1d-01aa75ed71a1/language-en/format-PDF/source-69741501 
16 https://www.eurograduate.eu/ 

March, 2020 

1 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Against this background, DG Education, Youth, Sport and Culture (DG EAC) 
commissioned this study ‘Mapping the state of graduate tracking policies and practices in 
the EU Member States and EEA countries’ in 2019 completed by ICF in association with 
3s and CHEPS. The study aims to update and add to existing intelligence on graduate 
tracking mechanisms in higher education and vocational education and training to inform 
the work of the Expert Group on Graduate Tracking, ahead of the reporting required on 
progress towards achieving the Recommendation in 2020. It also aims to draw on 
effective practice in countries to present guidance for policy makers on how to design 
and implement graduate tracking measures. 

This report presents the study findings. It is structured as follows: 

  Section 1 presents the study aim, objectives and scope; 
  Section 2 reports on the findings of the mapping of system-level graduate tracking 

measures in the EU-28 and EEA countries; 

  Section 3 analyses countries’ progress against the 2017 Council recommendation; 
  Section 4 discusses the comparability and compatibility of practices and graduate 

outcomes data among EU and EEA countries; 

  Section 5 reports on the findings of the survey conducted on institutional graduate 

tracking in higher education; 

  Section 6 presents the conclusions of the study and recommendations for future 

actions. 

Guidance material on how to design and implement graduate tracking measures is 
included in a separate document. 

1.2  Objectives and scope of the study 

The aim of this study is to capture the state of play in graduate tracking at system level 
(national or regional) for both vocational education and training and higher education, 
and at institutional level for higher education. It also aims to share effective practice in 
designing and implementing graduate tracking measures and disseminating and using 
their results. 

Graduate tracking can be defined as ‘the collection of quantitative micro 
and aggregate data and/or qualitative information about employment 
and social outcomes of people leaving vocational and higher education’17.  

The study has the following main objectives: 

  Specific objective 1: Mapping the state of play and types of graduate tracking in 

higher education and vocational education and training;   

  Specific objective 2: Comparative analysis of country graduate tracking 

measures;  

  Specific objective 3: Producing a set of guidelines on designing, implementing, 

disseminating and using the results of graduate tracking; and 

  Specific objective 4: Mapping institutional graduate tracking in higher education. 
This primarily examined practices taking place in larger institutions (defined as 
having more than 200 students and 30 full-time equivalent staff) that 
predominantly deliver programmes at EQF level 6 or above.  

The key research questions are: 

  What is the general coverage of graduate tracking at institutional and system-

level, both of higher education and of vocational education and training graduates? 

17 Technical Specifications for Request for Services EAC/23/2019, Annex A, p. 1. 

March, 2020 

2 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  What are the main methods used to track higher education and vocational 

education and training graduates? 

  What is the content of data collected in graduate tracking?  
  To what extent do national graduate tracking systems meet the requirements of 

the Council recommendation on tracking graduates?  

  To what extent does graduate tracking conducted at system level allow for cross-

country comparability? 

  What are the key features of an effective system-level graduate tracking 

measure? 

The study covers all EU-28 and EEA member countries (31 in total). The mapping focuses 
on the system level. In the countries where higher education or vocational education and 
training systems are fully or partially devolved to sub-national authorities, regional 
measures were also researched.18  

The study covers higher education, initial vocational education and training and 
continuing vocational education and training. In terms of education levels, it focuses on 
upper secondary, post-secondary non-tertiary vocational education and training 
programmes, and higher education at EQF19/ISCED20 level 6. However, it has collected 
measures found relating to other groups, such as higher-level graduates (EQF/ISCED 
level 7 and above).  

1.3  Overview of the methodology 

The study methodology combined two main research tasks: the mapping and description 
of system-level approaches to vocational education and training and higher education 
graduate tracking, and the analysis of graduate tracking practices by higher education 
institutions.  

Findings from these processes fed into the development of a guidance publication on 
graduate tracking. The two research tasks are described below. 

1.3.1  Mapping of system-level approaches to graduate tracking 

The mapping and description of system level approaches to graduate tracking in EU and 
EEA countries was based on desk research and semi-structured interviews. As part of this 
exercise a total of 92 interviews was conducted with ministry officials, project managers, 
researchers and statisticians (see 0).21  

The information collected included: 

  Background information on graduate tracking in the country: 

if there is a legal obligation and/or policy focus on graduate tracking;  

- 
-  whether graduate tracking is an established practice;  
-  main tracking measures;  
-  purposes of graduate tracking and main users of tracking results;  
-  and ongoing or planned reforms.  

  A description of each of the tracking measures identified at system level: 

-  coverage in terms of education sector (initial vocational education and 

training/continuing vocational education and training/higher education) and 
level, population included and geographical scope (national/regional);  

18 In Belgium the mapping focuses on Flanders and Wallonia; in Germany, Italy and Spain the research focused 
on the national and regional levels; in the UK, the mapping focuses on England and Scotland but specific 
examples have also been included for Wales and Northern Ireland.  
19 European Qualifications Framework. 
20 International Standard Classification of Education 
21 In a few cases, due to lack of availability of the persons contacted, consultations were done via e-mail. 

March, 2020 

3 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

-  entities responsible, history and rationale; 
-  data collected; 
-  use of standardised classifications; 
-  methodological approach (data collection approach, timing and frequency of 

data collection, sampling); 

-  data protection and accessibility; 
-  use and dissemination of results;  
-  costs; 
-  connection to other tracking instruments; 
-  strengths, weaknesses and future developments. 

Desk research was used to gather detailed information on the measures’ scope, methods 
and content, which is usually available from published sources such as reports or 
databases on tracking results. Interviews were used to complete missing information and 
gather insights on countries’ approach to graduate tracking, the strengths and 
weaknesses of existing measures and ongoing or foreseen developments regarding 
existing measures or new, upcoming ones. 

The mapping exercise aimed to identify all of the system-level graduate tracking 
measures in place in EU and EEA countries. This included all the national measures and a 
range of examples of regional measures where these are a core feature of a country’s 
approach to graduate tracking (mainly in BE, DE, ES, IT and UK).  

The list of graduate tracking measures initially identified was reviewed and a few 
measures were discarded for being outside the parameters of the study. These included, 
for instance, one-off tracking studies or statistics providing data on graduates’ 
employability that did not involve graduate tracking. Such measures were only kept in 
the list if no other relevant graduate tracking measures -in higher education or vocational 
education and training- could be identified in the country. 

The level of information obtained about each measure varies. In some cases, it was not 
possible to capture all the details about the methodology applied or the use made of 
tracking results because of the lack of information in published sources and the scale of 
the task in some countries within the time scale of the research. Country experts who are 
members of the Expert Group on Graduate tracking were asked to verify information 
collected and provide additional information.  

The information collected in the mapping informed the comparative analysis in section 2 
of this report, as well as the assessment of countries’ progress towards meeting the 
Council recommendation (section 3) and the comparability and compatibility of practices 
and graduate outcomes data among EU and EEA countries (section 4). 

1.3.2  Understanding institutional graduate tracking in higher education 

Data on institutional graduate tracking was collected from an online survey for higher 
education institutions to complete. The survey collected information on the type of 
graduate tracking measures used, the motivations for undertaking graduate tracking or, 
where tracking is not done, the reasons for not doing so. The survey was tested in 
October 2019 with a few institutions and was open to all higher education institutions 
between 5 November 2019 and 10 January 2020. It was available in six languages: 
English, French, German, Italian, Polish and Spanish.  

The availability of the survey was promoted to higher education institutions rectorates 
and relevant departments by international higher education institution umbrella 
organisations. We specifically approached EU bodies representing higher education 
institutions (EUA, The Guild and EURASHE), ENQA members and Expert Network 
members to do this. For EU bodies, we provided each organisation with a short 
promotion piece describing the purpose and benefits of the survey and reason for 
participating. This had little impact on responses. 

March, 2020 

4 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country researchers were tasked with making approaches to officials, the QA agency in 
their country and any relevant organisations representing higher education institutions 
(which exist in the larger EU countries), to see if they could support distribution or help 
identify any groups/networks of higher education institution staff (e.g. alumni 
coordinators) that country researchers could approach directly.   

To increase response rates, country researchers also contacted individual higher 
education institutions directly asking them to complete the survey, prioritising higher 
education institutions with larger shares of a country’s graduates in the first instance. By 
these means, the study has achieved a response of 615 valid survey returns, which are 
estimated22 to represent about a third (34%) of the total population of higher education 
institutions in scope for the study within the definition used and representing about half 
(50%) of the graduates. This gives a representative response rate which allows for a 
robust statistical analysis of the approaches to graduate tracking by higher education 
institutions in Europe. 

The aim of the survey was to achieve a response rate of higher education institutions 
covering at least 50% of higher education graduates in a given country. Data from the 
European Tertiary Education Register (ETER) was linked to the survey responses to 
examine the coverage of higher education institutions that have responded. ETER data 
was extracted in October 2019 on higher education institution characteristics and the 
number of higher education institutions and students in each country.  

Limitations in ETER data - including non-coverage of Latvia and Romania and missing 
cases and variables for a few other countries23- pose difficulties for the calculation of a 
European response rate including all the countries covered by the study. Estimated 
country response rates are presented in the table below together with the number of 
higher education institutions that responded to the survey. Estimates are likely to be 
lower than the actual graduate coverage of responding higher education institutions in 
some countries due to the way these estimates were calculated with the data available.  

The survey in total received responses from 615 higher education institutions in scope for 
the study across all 31 EU and EEA countries. In 18 countries the survey received 
responses from higher education institutions covering over 50% of the higher education 
student population (AT, BE, BG, HR, CZ, DK, EE, FI, IS, IT, LI, LU, MT, PT, SK, SI, ES, 
SE). In only three countries did the survey receive responses from higher education 
institutions that covered less than 40% of the higher education graduate population (UK, 
NO, DE). In all of them, this is probably linked to a limited number of higher education 
institutions conducting their own graduate tracking.  

In NO and the UK, low levels of graduate tracking by higher education institutions are 
linked to the existence of well-established national-level measures. In Norway, the 
graduate survey conducted by the Nordic Institute for Studies in Innovation, Research 
and Education (NIFU) has been in place since 1972 and only some higher education 
institutions carry out their own graduate surveys. In the UK, the Higher Education 
Statistics Agency (HESA) has delivered a survey of graduates since 1994/95, currently 
called the Graduate Outcomes Survey. Higher education institutions pay a statutory 
subscription fee to participate in it and can pay for selected additional questions from a 
question bank to ask their graduates. It is likely that most UK higher education 

22 Complete data on higher education institutions was not available for RO, LV, DK, EE, FR, IS, IT and LT to fully 
determine how many higher education institutions were in scope (meeting the criteria of 200+ students enrolled 
and 30+ FTE academic staff and more than 50% of students at ISCED Level 6 and above). For RO and LV 
estimates for the total population of higher education institutions in scope are extrapolated based on the 
percentage of each country’s students at ISCED Levels 6-8 which the higher education institutions responding to 
the survey teach. For DK, EE, FR, IS, IT and LT estimates for the total population of higher education institutions 
in scope are based on the overall number of institutions recorded in the ETER with students enrolled at ISCED 
Level 5+ (some of these institutions are likely to be out of scope so the response rate from higher education 
institutions in scope may be higher).  
23 DK, EE, FR, IS, IT and LT. 

March, 2020 

5 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

institutions do not see the need or have the resources to develop graduate tracking 
measures of their own. Some UK higher education institutions declined to invest time in 
participating in our survey for this reason. In Germany, 60 higher education institutions 
cooperate with a research institute of the University of Kassel24 under the KOAB project25 
and apply the same tracking methodology and survey questionnaire. As explained by 
some German higher education institutions contacted by the research team, it made no 
sense for all of them to provide the same response to the survey, and they chose not to 
participate. 

The responses by country for each country are presented in the table below.  

Table 3.  Survey for higher education institutions. Response rates 

Czech Republic 

34 

Country 

Austria 

Belgium 

Bulgaria  

Croatia 

Cyprus 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Number of 
survey 
responses 

Total 
number of 
higher 
education 
institution
s in scope 

Number of 
survey 
responses 
from higher 
education 
institutions 
in scope26 

Number of 
survey 
responses 
matched 
with ETER 
data 

Approx. % 
of total 
graduates 
in 
country27 

158** 

108* 

61 

22 

45 

29 

8 

32** 

21** 

37 

297 

39 

43 

7** 

24 

210** 

c.8*** 

29 

14 

18 

44* 

5 

19 

11 

7 

27 

54 

14 

13 

5 

10 

55 

5 

1 

10 

27 

13 

17 

10 

5 

15 

9 

7 

23 

93 

49 

12 

13 

4 

10 

51 

4 

1 

8 

27 

13 

17 

10 

5 

15 

8 

7 

23 

53 

48 

12 

13 

4 

10 

50 

0 

1 

8 

55% 

76% 

50% 

81% 

46% 

52% 

~50%** 

~78%** 

77% 

~43%** 

37% 

42% 

42% 

~96%** 

40% 

~59% 

~49%*** 

100% 

42%** 

Liechtenstein 

1 

Lithuania 

29** 

24 International Centre for Higher Education Research of Kassel (INCHER-Kassel). 
25 Cooperation project graduate studies. In German, Das Kooperationsprojekt Absolventenstudien (KOAB).  
26 Includes survey responses from higher education institutions that are not recorded in the ETER database but 
that self-reported being in scope based on a set of survey questions (meeting the criteria of 200+ students 
enrolled and 30+ FTE academic staff and more than 50% of students at ISCED Level 6 and above).  
27 Only calculated based on survey responses matched with ETER data. These estimates therefore don’t include 
all the survey responses in scope and are therefore likely to be underestimates.  

March, 2020 

6 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

Luxembourg 

Malta 

Netherlands 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

Number of 
survey 
responses 

Total 
number of 
higher 
education 
institution
s in scope 

Number of 
survey 
responses 
from higher 
education 
institutions 
in scope26 

Number of 
survey 
responses 
matched 
with ETER 
data 

Approx. % 
of total 
graduates 
in 
country27 

1 

1 

50 

33 

225 

57 

c.68*** 

20 

3 

78 

36 

1 

2 

12 

7 

51 

24 

26 

15 

3 

60 

30 

34 

1 

1 

11 

7 

47 

23 

25 

14 

3 

54 

24 

34 

1 

1 

11 

7 

45 

23 

0 

14 

3 

52 

24 

34 

100% 

100% 

41% 

31% 

45% 

65% 

>37%*** 

70% 

100% 

68% 

78% 

30% 

United Kingdom  154 

Total 

- 

714 

615 

540 

~50% 

 * Has a high number of responses from different faculties within the same higher 
education institutions, and a high number of faculty responses which cannot be linked to 
a higher education institution.  

**Due to limitations with the ETER data for these countries, estimates are based on the 
number of enrolled students at ISCED levels 5-7 rather than graduates at ISCED levels 
6-8. Estimates do not take account of the small number of missing cases in the ETER 
data, except for France.  

***Not based on ETER data; estimate calculated using national data on the total enrolled 
students in the country sourced by a country researcher alongside higher education 
institution survey responses on their enrolled students. This is likely to be an 
underestimate of graduate coverage given that some students in the country will be 
attending higher education institutions that are out of scope for this study.  

The information collected through the survey is analysed in section 6 of this report.   

March, 2020 

7 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

2 

National policies and developments in graduate tracking 

This chapter presents national policies and developments in graduate tracking in EU and 
EEA countries based on the mapping of measures. It specifically explores the extent to 
which graduate tracking is a policy objective in countries, the maturity of country 
graduate tracking systems (including planned reforms), how data from graduate tracking 
is used and barriers and obstacles to developing tracking measures. 

2.1  Policy focus on graduate tracking 

Graduate tracking is a policy objective in over two thirds of the EU and EEA countries 
(24 out of 3228) (see Table 4). In most cases, these countries have strategies and 
policies that cover both higher education and vocational education and training. However, 
in CZ, DE, PL, SE there are policies that cover graduate tracking in higher education only. 
In IT and LU the focus is on vocational education and training only. 

In most of these countries, graduate tracking is referenced in national strategies, 
legislation and other policy documents (listed in 0). These set out: 

  Objectives of developing new tracking systems (BE-FR, BG, HR, HU, IE in 

vocational education and training, IT in vocational education and training, LT in 
vocational education and training, LV, MT, RO, SI);   

  Current tracking systems, their continuity and/or strengthening (CZ, FI in 

vocational education and training, FR in vocational education and training, SK in 
higher education, UK in higher education);  

  The use of graduate tracking results as part of performance-based funding 

mechanisms (DK and FI in higher education); conditionalities for providers to 
receive public funding to start new study programmes (NL); or strategic planning 
of course offers (SK in vocational education and training). 

In EE it is indirectly linked to a policy strategy: the country intends to use tracking 
results to monitor the objectives of the Estonian Lifelong Learning Strategy 2020.  

In other countries (AT, DE, ES, PL, SE and UK (vocational education and training)), 
graduate tracking is not explicitly mentioned in published policy documents but the focus 
on graduate tracking is evidenced by ongoing policies and practices.  

Table 4.  Graduate tracking as a policy objective 

Country 

Policy 
objective 

Sector  

Country 

Policy focus  Sector  

AT 

BE-FR 

BE-NL 

BG 

CY 

Yes 

Yes 

No 

Yes 

No 

both 

both 

n.a. 

both 

n.a 

IS 

IT 

LI 

LT 

LU 

No 

Yes 

No 

Yes 

No 

n.a. 

vocational 
education 
and training 

n.a. 

both 

vocational 
education 
and training 

CZ 

Yes 

higher 
education 

LV 

Yes 

both 

28 Note that Belgium is counted twice as two separate templates were completed for the French-speaking 
Community (BE-FR) and the Dutch-speaking Community (BE-NL). 

March, 2020 

8 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

Policy 
objective 

Sector  

Country 

Policy focus  Sector  

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

Yes 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

Yes 

higher 
education 

both 

both 

both 

both 

both 

both 

both 

both 

both 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

Yes 

Yes 

No 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

both 

both 

n.a. 

higher 
education 

n.a. 

both 

both 

higher 
education 

both 

both 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

There is a legal obligation to conduct graduate tracking in half of the countries (16 out 
of 32) (see Table 5).29 In most cases it requires the tracking of both higher education 
and vocational education and training graduates. The exceptions are AT, DE, HU, PL and 
the UK where the obligation refers to higher education graduates only; and ES (in 13 out 
of 17 regions), NL, and PT where the obligation refers to vocational education and 
training only. 

The legal obligation to conduct tracking mostly lies with system-level authorities (national 
or regional). In a few countries the obligation to conduct tracking lies directly with 
providers meaning that they need to ensure that graduate tracking is done either by 
participating in relevant national or regional measures or by developing their own 
measures. This is the case for higher education institutions in DE, FI and the UK-E, SC, W 
and NI, and for vocational education and training providers in ES (in 13 regions), NL, and 
PT. In DK, EE and LV, although national authorities have the responsibility for tracking, 
the legislation establishes the obligation for education and training providers to collect 
the data needed for tracking and submit it to national level authorities.  

Table 5.  Legal obligation to track graduates 

Country  Level of 

Sector   Legal basis 

legal 
obligation 

AT 

National 

higher 
educati
on 

The Austrian University Law in §60 Abs. 1b Ziffer 1.j 
requires, that for information and guidance 
prospective students are to be informed about 
number of students enrolled in the programme, the 
average duration of studies, the pass rates and 
employment statistics. 

29 A legal obligation to track higher education graduates has been established in Greece in 2020 (Law 4653/2020, 
article 7). This piece of legislation was issued after the completion of the research for this study and is thus not 
included in the analysis. 

March, 2020 

9 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Level of 

Sector   Legal basis 

legal 
obligation 

DE 

Provider 

higher 
educati
on 

(1) Laws on Institutions of higher education of the 
Federal States 

(2) Contracts between Federal States and higher 
education institutions  

DK 

National 

Both 

Act on Statistics Denmark (Bekendtgørelse af lov om 
Danmarks Statistik) § 8, 3.  

National  

Both 

Government´s order on conducting the analysis 
‘Labour Market success of Vocational and higher 
education Graduates’ 

EE 

Provider 

vocatio
nal 
educati
on and 
training 

- National regulation: Royal Decree 1558/2005, of 
23 December, regulating the Integrated Centres of 
Professional training (affects a specific type of 
vocational education and training provider); and 
Royal Decree 1529/2012, of 8 November, 
developing the contract for training and learning and 
establishing the base of dual training (affects dual 
vocational education and training projects). 

- Regional regulation in 13 Autonomous 
Communities.30 

Both 

vocational education and training: The National 
Agency for Education Act 564/2016.31  

higher education: The Universities of Applied 
Sciences Act (data collection mandate)32; The 
University act (Section 51§ on Data collection 
mandate)33; The MinEdu Decree on the calculation of 
the UAS basic funding34; The MinEdu Decree on the 
calculation of universities’ basic funding.35  

higher education: Legal obligation for a national 
observatory on transition to labour market (Loi de 
l’Éducation, Article L611-5, modified 2018).  

vocational education and training: Order of 24 
January 2013 creating an automated processing of 
personal data on the integration into the working life 
of pupils and apprentices who have left the 
education system. 

higher education: Law 2011 CCIV on National higher 
education;36 

ES 

FI 

FR 

HU 

National 
(vocational 
education and 
training) and 
provider 
(higher 
education) 

National 

Both 

National 

higher 
educati
on 

30 https://tracktionerasmus.eu/wp-content/uploads/2019/05/Estudio_MedidasSeguimientoFP.pdf 
31 https://www.finlex.fi/fi/laki/ajantasa/2016/20160564   
32 https://www.finlex.fi/fi/laki/ajantasa/2014/20140932, section 45§  
33 https://www.finlex.fi/fi/laki/ajantasa/2009/20090558  
34 https://www.finlex.fi/fi/laki/alkup/2019/20190117 
35 https://www.finlex.fi/fi/laki/alkup/2019/20190119 
36 https://net.jogtar.hu/jogszabaly?docid=A1100204.TV 

March, 2020 

10 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Level of 

Sector   Legal basis 

legal 
obligation 

National, 
regional and 
local 

Both 

higher education: the higher education Quality 
Assurance system introduced by Law n. 240/2010 
and Legislative Decree n.19/2012. 2) 2a) 

vocational education and training: Art. 14 of 
D.P.C.M. (25 January 2008) of the 'Guidelines for 
the reorganisation of the education and training 
system and the constitutions of higher technical 
institutes';37 The Agreement between the State and 
the Regions (24 September 2015);38 As regards the 
ITS pathways, the Agreement between Government, 
Regions ed Local authorities (5 August 2014) 
includes a reference to a monitoring and evaluation 
system of ITS pathways. 

National 

Both 

higher education: higher education law;39  

Both: State Educational Information System 
regulations.40 

Vocational education and training and higher 
education institutions are required to inform 
prospective students about their programmes. For 
vocational education and training institutions, there 
is a legal arrangement (Regulations for vocational 
education and training studies leaflet41) which 
specifically addresses which indicators they have to 
use to inform potential students one of which is the 
percentage of graduates with a job.        

Law on higher education, which entered into force in 
October 2014. 

vocational education and training: Decree-Law 
92/2014 

Provider  

National 

Provider 

vocatio
nal 
educati
on and 
training 

higher 
educati
on 

vocatio
nal 
educati
on and 
training 

National 

Both 

§ 9 Regulation (2015: 1047) with instructions for 
the National Agency for Education;42 Ordinance (SFS 
2012:810) with instruction for the Swedish Higher 
Education Authority;43 Ordinance (SFS 2011: 1162) 

IT 

LV 

NL 

PL 

PT 

SE 

37 https://www.cliclavoro.gov.it/normative/d.p.c.m_25_gennaio_2008.pdf 
38http://www.sistemaduale.anpal.gov.it/documentazione/Documents/accordo_stato_regioni_24_settembre_2015.p
df 
39 https://likumi.lv/doc.php?id=37967 
40 https://likumi.lv/ta/id/307796-valsts-izglitibas-informacijas-sistemas-noteikumi 
41 Regeling studiebijsluiter mbo (https://wetten.overheid.nl/BWBR0042000/2019-03-20)  
42 https://www.riksdagen.se/sv/dokument-lagar/dokument/svensk-forfattningssamling/forordning-20151047-med-
instruktion-for_sfs-2015-1047 
43 https://www.riksdagen.se/sv/dokument-lagar/dokument/svensk-forfattningssamling/forordning-2012810-med-
instruktion-for_sfs-2012-810 

March, 2020 

11 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Level of 

Sector   Legal basis 

legal 
obligation 

National and 
provider  

higher 
educati
on 

UK 

with instructions for the Agency for Higher 
Vocational Education incl. SFS 2019:58644 

Implicit in sections 64 and 65 of the Higher 
Education and Research Act 2017.45 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Consequently, the inclusion of policy objectives on graduate tracking goes together with 
the legal obligation to track in close to half of the countries;46 in another third of the 
countries, there is a policy focus but not a legal obligation.47 In one case (PT) there is a 
legal obligation on vocational education and training providers but not a policy focus on 
graduate tracking. In the remaining countries, there is neither a policy objective nor a 
legal obligation to track graduates.48 

2.2  Responsibility for graduate tracking 

Responsibility for graduate tracking commonly lies at the system-level across EU and EEA 
countries. In most countries, system-level refers to national authorities (see Table 6). 
The exceptions are: 

  Belgium: the different regions (French-speaking and Dutch-speaking) are 

responsible for tracking both in higher education and vocational education and 
training;  

  Spain: responsibility for graduate tracking is shared by the central government 

and the regions (autonomous communities);  

  Similarly, both the UK government and those of its nations have competences in 
graduate tracking. Currently, in higher education, graduate tracking is done at 
national (cross-nation) level whereas in vocational education and training it is 
done by the different nations;  

  Germany and Italy: the national government oversees tracking in higher education 

and lander/regions are responsible for tracking in vocational education and 
training;  

  Romania: the government has devolved the competences of vocational education 
and training graduate tracking to the sub-regional County School Inspectorates 
(CSI), decentralized public services of the Ministry of Education.49  

In Spain, competences in vocational education and training and higher education are 
shared by the central government and the autonomous communities (regions) and, 
thus, so is the responsibility for graduate tracking. 

In vocational education and training, there is currently one main measure for graduate 
tracking at national level, the survey on education-training transitions and labour 

44 https://www.riksdagen.se/sv/dokument-lagar/dokument/svensk-forfattningssamling/forordning-20111162-med-
instruktion-for_sfs-2011-1162 
45 http://www.legislation.gov.uk/ukpga/2017/29/contents/enacted 
46 AT, DE, DK, EE, ES, FI, FR, HU, IT, LV, NL, PL, SE and UK. 
47 BE-fr, BG, CZ, HR, IE, LT, MT, RO, SI, and SK. 
48 BE-nl, CY, EL, IS, LI, LU and NO. 
49 There are 41 County School Inspectorates in Romania, one in each of the 41 counties, plus the Bucharest 
School Inspectorate, https://www.edu.ro/inspectorate-scolare-judetene.  

March, 2020 

12 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

insertion (ETEFIL50), conducted by the national statistics office.51 In addition, 
according to the study Tracktion,52 most autonomous communities (15 out of 17, 
except for the Valencian Community and Extremadura), have at least one regular 
measure to track vocational education and training graduates in their territory, which 
is implemented on a periodic basis. The most commonly used method is surveys (16 
out of 23 measures). 

In higher education, there are two main measures for graduate tracking at national 
level, the survey of the labour insertion of university graduates (EILU53), conducted by 
the national statistics office, and the analysis of the labour insertion of university 
graduates, based on administrative data, conducted by the Ministry of Science, 
Innovation and Universities. In addition, a few autonomous communities (3 out of 17) 
have systematic measures to analyse the labour insertion of university graduates in 
their territory. These include surveys in Catalonia54 and the Basque Country55 and one 
tracking measure based on administrative data in Andalusia56. In two other 
autonomous communities there are relevant measures which appear to be less 
systematic (Aragon57 and Galicia58) and, in the remaining territories, no evidence has 
been found of tracking at regional level. Across all autonomous communities, most 
universities have regular measures to track their graduates.  

Only in two countries (AT and FI) does the main responsibility for graduate tracking lie 
with providers when it comes to higher education. In the case of Finland,  it is shared 
between the government and higher education institutions. Tracking based on 
administrative data is conducted by Vipunen (Education Statistics Finland). Universities - 
through the Aarresaari network of university career services – are responsible for the 
development and management of tracking surveys. The data are collected nationwide 
and aggregated by Research Stats Service TUPA of the University of Tampere and CSC – 
the IT Centre for Science, in collaboration with Aarresaari. The universities of applied 
sciences are developing a similar approach (in spring 2019 the first survey was 
conducted in collaboration with CSC).  

Table 6.  Responsibility for graduate tracking 

Country 

vocational 
education 
and training 
graduates 

higher 
education 
graduates  

Country 

vocational 
education 
and training 
graduates 

higher 
education 
graduates  

AT 

BE-NL 

BE-FR 

BG 

National 

Provider 

Regional 

Regional 

Regional 

Regional 

N/a 

National 

IS 

IT 

LI 

LT 

N/a 

N/a 

Regional 

National 

National 

National 

National 

National 

50 In Spanish, Encuesta de Transición Educativo-Formativa e Inserción Laboral (ETEFIL). 
51 A new measure combining administrative and survey data is currently being developed. 
52 Romero Garcia & Diego Rodriguez (2019). Mapping of vocational education and training Graduate Tracking 
Measures in Spain (Tracktion project): https://tracktionerasmus.eu/outputs/ 
53 In Spanish, Encuesta de Inserción Laboral de los Titulados Universitarios (EILU). 
54 http://www.aqu.cat/aqu/publicacions/insercio_laboral.html 
55 https://www.ehu.eus/es/web/gardentasun-ataria/enplegagarritasuna#Empleabilidad2 
56 
https://www.juntadeandalucia.es/organismos/empleoformacionytrabajoautonomo/servicios/publicaciones/detalle/7
8869.html 
57 https://www.aragon.es/-/transicion-educativa-laboral-e-insercion-laboral#anchor2 
58 http://www.acsug.es/es/documentacion/publicacions/inserci%C3%B3n-laboral 

March, 2020 

13 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

vocational 
education 
and training 
graduates 

higher 
education 
graduates  

Country 

vocational 
education 
and training 
graduates 

higher 
education 
graduates  

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

N/a 

N/a 

National 

National 

Regional 

National 

National 

National 

National 

National 

N/a 

N/a 

National & 
regional 

National & 
regional 

National 

National & 
provider 

National 

National 

N/a 

N/a 

N/a 

National 

National 

National 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

National 

N/a 

National 

National 

National 

National 

National 

National 

National 

National 

N/a 

National 

National 

National 

Regional 

N/a 

National 

National 

National 

National 

National 

National 

Regional 

National 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

N/a: not applicable. The level of responsibility for graduate tracking in these countries and sectors 
(higher education/vocational education and training) is unclear. There are no system-level 
measures and, in some cases, tracking is being done at regional or provider level but not 
systematically. In Iceland, although all higher education institutions conduct graduate tracking 
surveys, graduate tracking is not a requirement and cannot be considered providers’ responsibility. 

There are countries where graduate tracking is only being developed by regions (BG, PL) 
or vocational education and training providers (BG, EL, HR) or higher education 
institutions (EL, HR, IS, LU, RO) but this does not mean that the responsibility for 
tracking lies at these levels. Rather, it signifies that no relevant measures exist at system 
level. These situations have been classified as ‘not applicable’ (n/a) in the table above. 

2.3  Maturity of countries’ graduate tracking systems 

Graduate tracking systems are an established practice in both higher education and 
vocational education and training in 18 countries (see Table 7). In these countries 
graduate tracking has been conducted on a regular basis over recent time. In some 
countries tracking systems are well established in higher education but not vocational 
education and training (BG, HU and PL), or vocational education and training but not 
higher education (BE-FR and PT). 

Overall, graduate tracking is more developed in higher education than in vocational 
education and training (BG, FI, HU, IS, LV, LT, PL,59 SI, SK, UK). The opposite holds true 
for BE-FR, PT and RO. 

59 Tracking in the higher education sector is a national-level systemic practice, while tracking studies of INITIAL 
vocational education and training graduates were developed in Poland as decentralised initiatives of regional 
labour offices (NUTS 2 level, voivodships). A system-level initiative for vocational education and training 
graduates is now being developed. 

March, 2020 

14 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

In most countries the inclusion of policy objectives on graduate tracking and/or a legal 
obligation to track are the background to the established practice: AT, CZ (higher 
education), DE (higher education), DK, EE, ES, FI, FR, HU, IE, IT, NL, PL, SE, SK and UK. 
However, in BE-NL, CZ (vocational education and training), DE (vocational education and 
training), LU (vocational education and training) and NO, graduate tracking is an 
established practice despite not being a policy objective and /or legal obligation. 

Table 7.  Experience of tracking – overall approach (vocational education and training 

and higher education) 

Graduate tracking… 

Countries  

Is an established practice 

AT, BE-FR (vocational education and training), BE-NL, BG 
(higher education), CZ, DE, DK, EE, ES, FI, FR, HU (higher 
education), IE, IT, LT, LU,60 NL, NO, PL (higher education), PT 
(vocational education and training), SE, SK, UK 

Is a poorly developed practice   BE-FR (higher education), BG (vocational education and 

training), EL, HR, HU (vocational education and training), IS 
(higher education), LV, MT, PL (vocational education and 
training), PT (higher education), RO, SI 

Is not used at all  

CY, IS (vocational education and training), LI 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Graduate tracking is poorly developed in 10 countries. From these, BG (vocational 
education and training), LV and SI have established policy objectives on graduate 
tracking and are taking steps towards the implementation or improvement of systematic 
graduate tracking. 

In Bulgaria, measures for implementing vocational education and training 
graduate tracking are stated in the 'Strategy for the development of vocational 
education and training in the Republic of Bulgaria 2015-2020'. At present there 
are no such measures at system level. There are local and regional initiatives 
(at the level of regional educational authorities), which collect limited data on 
whether graduates continue in higher education and if they get employed in the 
year following their graduation. There is also a pilot project under the 
Erasmus+ programme (2019-2021) led by the Ministry of Education and 
Science that expects to develop a mechanism for vocational education and 
training graduate tracking. This measure will combine administrative data and a 
survey and it will cover three regional educational authority areas - Vratsa, 
Stara Zagora and Burgas. 

In Latvia, the development of graduate tracking for both higher education and 
vocational education and training is covered in the ‘Guidelines for the 
Development of Education for 2014-2020’. The current reforms focus on higher 
education, where a tracking tool is nearly developed (2017-2020). A tool for 
vocational education and training tracking is also being developed but is at an 
early stage, with a concept report expected in 2020. 

60 Note: In Luxembourg no evidence has been found of higher education graduate tracking at system level. 
However, the only Luxembourgish higher education institution that falls within the scope of this study -the 
University of Luxembourg- conducts an annual survey to track its graduates. Therefore, as the country does in 
fact track its graduates, it has been classified as having an established graduate tracking practice. 

March, 2020 

15 

 
 
 
  
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Slovenia piloted the measure ‘Monitoring the employability of graduates of 
upper-secondary vocational and technical schools’ in 2011 and 2013, but at 
present there is no vocational education and training graduate tracking 
measure in place. However, in higher education, there have been more 
promising developments.  In 2019, as part of the EU co-funded project 
‘Establishing a system for monitoring employability of higher education 
graduates in Slovenia and upgrading the records and analytical information 
system for higher education in the Republic of Slovenia (eVŠ)’, the eVŠ system 
is being upgraded with the ‘employability module’ that will enable gathering and 
analysis of data relevant for graduate tracking. This should put in place 
measures to establish a fully operational graduate tracking system in the 
future. 

In BE-FR, IS (higher education) and PT there are some relevant measures but there has 
been little development towards more robust and comprehensive systems over the past 
few years.  

In Belgium (FR), the development of a new measure to track higher education 
graduates was announced in 2014 but has not yet been launched. Tracking is 
more developed in vocational education and training with the Ulysses Survey. 

In Iceland, all higher education institutions conduct annual/biannual tracking 
surveys. The four public higher education institutions all use the same 
questionnaire and same approach to data analysis and most higher education 
institutions use the data to review their course offer and as an internal quality 
assurance mechanism. However, there are no system-level policies or measures 
on graduate tracking. higher education institutions use their own, limited funds 
to conduct surveys and there is no longitudinal tracking or analysis of trends 
over time. National authorities are interested in a possible future participation 
in a Europe-wide graduate tracking study (Eurograduate).  

In Portugal, the government has developed an indicator on the percentage of 
recent higher education graduates registered in the public employment service 
but has not developed a tracking system that follows graduates on an individual 
basis over time. To provide data for the indicator, the public employment 
service interviews unemployed people and collects data on their previous 
studies (programme and provider). Vocational education and training graduates 
are, however, tracked through a survey covering all upper secondary graduates 
which has been conducted systematically since 2010. 

In HR, MT and RO there have been relevant pilot studies or one-off initiatives, but it is 
not clear if systematic tracking will take place in the near future. 

In Croatia, graduate tracking has so far been conducted mostly at provider 
level and there have been some one-off pilots of tracking measures at system 
level covering higher education graduates. Recently, the country has 
participated in the Eurograduate project, a measure which could become 
regular. 

Although graduate tracking is not an established practice in Malta, there is a 
growing interest in graduate tracking in higher education as well as in both 
general and vocational education and training systems. This is reflected in Malta 
participating in the Eurograduate survey. 

In Romania, there is a national methodology for vocational education and 
training graduate tracking but it is not being applied systematically. It has been 
piloted by some County School Inspectorate areas, on an ad-hoc basis 

March, 2020 

16 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

depending on funding. At present, there are no ongoing pilots. In higher 
education, there is no national graduate tracking measure. There was a pilot 
project which ended in 2012 and a new one is now starting.   

In EL graduate tracking is a poorly developed practice, and in CY, LI and IS (vocational 
education and training) there is no evidence of tracking being done at all. 

In Greece there are no measures at system level and no policy focus on the 
topic. Some tracking is done at provider level but it is not believed to be a 
common practice. The country has, however, participated in the Eurograduate 
project. 

In Iceland, there is no evidence of graduate tracking in vocational education 
and training at system or provider level. 

In Cyprus, graduate tracking is not done at system level and no evidence was 
found of tracking at provider level. However, the government is planning to 
develop a platform to connect initial vocational education and training and 
continuing vocational education and training graduates with employers in the 
country. Through this platform, the development of a tracking method could be 
possible. 

Liechtenstein is a unique case in the sense that 90% of upper secondary 
school leavers move abroad to study, mainly to Switzerland and Austria. As 
such, tracking is problematic. Currently, the National Statistical Office collects 
data on its own students and graduates and Austria and Switzerland provide 
data on students and graduates from Liechtenstein enrolled there. However, 
data received from the Swiss and Austrian statistical offices is anonymised and, 
thus, cannot be used to track the progression of students through different 
higher education institutions or their entry into the labour market after 
graduation. 

2.4  Ongoing and planned reforms 

There are some ongoing and planned reforms in graduate tracking across EU and EEA 
countries. In some cases, these refer to reforms of existing measures (see box below). 

In Belgium (NL), a pilot project is currently running on the School Leavers 
Study (which covers both higher education and initial vocational education and 
training). Changes might be implemented from 2021-22 onwards. The changes 
aim to include more data in the measure and to start tracking graduates 
several times over a specified time period. They also intend to make data on 
graduate performance available to institutions. 

In Germany, two major panel studies managed by the German Centre for 
Higher Education and Research Studies (the German graduate panel and the 
Panel Study on School Leavers with higher education entrance qualification) are 
to be integrated into one panel: the Student Life Cycle Panel (SLC).61 

In Finland, work is ongoing to identify options for improving the qualitative 
data about vocational education and training graduates. 

In Spain, a measure on the labour market insertion of initial vocational 
education and training graduates is being developed. It is a follow-up to a study 
conducted in 2015 but back then the necessary mechanisms to match data 

61 Information at: https://www.dzhw.eu/en/forschung/projekt?pr_id=583 

March, 2020 

17 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

from different services were not in place. The new measure, which is still being 
designed, is expected to use administrative data from several services and 
supplement this with a survey. 

Statistics Sweden is investigating if current surveys (used for higher education 
and vocational education and training) need to be adjusted as a consequence of 
the EU recommendation on graduate tracking. The measurement used for 
‘establishment in the labour market’ is under revision and an updated version is 
planned for the end of 2019. 

In several countries, new measures are planned or already under development. Ongoing 
reforms in BG, LV and SI were discussed in the previous section. In FR, HU, LI, PL, RO 
and SK there are ongoing discussions and projects to introduce new tracking measures 
but there is little evidence of concrete developments so far (see box below): 

In France, the statistical services of the Ministry of National Education (DEPP) 
and Ministry of Labour (DARES) have recently launched a project to measure 
the professional integration of young people into the labour market following 
apprenticeships or vocational training. It involves the development of a new 
information system resulting from the matching of several administrative 
sources.62  

In Hungary, the 2019 government policy strategy for vocational education and 
training (Vocational education and training 4.0) refers to the development of a 
national graduate tracking scheme that would build on data reported by 
vocational education and training providers.63 

In Liechtenstein, there are plans for the national office for schools and the 
National Statistical Office to develop a national tracking system. This would 
involve the integration of information about educational pathways into national 
data sets. There are however no details at yet on the methodologies that will be 
used. 

In Lithuania, the tracking of vocational education and training and higher 
education graduates at the national level is carried out by the Government 
Strategic Analysis Centre through the analysis of administrative data. The 
country has also been trying to use graduate tracking surveys but with little 
success as they have achieved very low response rates. Lithuania has 
participated in the pilot survey of Eurograduate, which could contribute to the 
implementation of tracking surveys at the national level.  

In Poland, there is an ongoing project by the Institute for Educational Research 
(governmental research agency) which aims at developing a model for tracking 
labour market outcomes for vocational education and training graduates at 
system-level by 2019.64 The results of this project are not yet known. 

In Romania, there are plans to revise the national methodology for vocational 
education and training graduate tracking, diversify the data collection methods 
and implement the measure at national level. The changes are planned for 
2020. However, no evidence has been found of progress towards this target 
date. In higher education, the project ‘Quality in higher education: 
internationalisation and databases to enhance the Romanian education system’ 

62 In French, système d’information statistique consolidé académique-déclaration sociale nominative (SYSCA-
DSN). 
63 https://www.nive.hu/Downloads/Hirek/DL.php?f=szakkepzes-4.0.pdf 
64 Monitoring the educational and professional paths of graduates and young adults, 
http://www.ibe.edu.pl/pl/projekty-krajowe/badanie-losow-absolwentow 

March, 2020 

18 

 
 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

proposes the development of a survey on employability as well as a platform 
aimed at interconnecting student databases and other national databases with 
relevant information on employees.   

In Slovakia, proposals on tracking higher education graduates are being 
intensively discussed. The Ministry of Labour and Ministry of Education decided 
to link their data at an aggregated level and plan to launch a website with 
anonymised data accessible for all.65 

2.5  Main purposes and users of graduate tracking 

In vocational education and training, the most common purposes of collecting 
graduate data across EU and EEA countries are the monitoring of education policies 
(identified in 20 out of 32 countries included in the analysis), quality assurance (20) and 
the provision of information and guidance to prospective students (20). These are 
followed by the strategic planning of course offers (15) and access to funding (7) (see 
Table 30 in annex). 

Other purposes of graduate tracking in vocational education and training include 
informing policies at system or provider level to help match supply with labour market 
demand (DE, EE, PL, SE), providing data for research (DK, EE, PL) and the use of data by 
vocational education and training schools in marketing material (SE).66 

The main users of vocational education and training graduate tracking results are 
governments (26), including national and regional governments in the case of Spain. 
These are followed by vocational education and training providers (19), researchers (15), 
current and prospective students and graduates (13), and employers (7) (see Table 5 in 
annex). Other users include employment services (BE-NL, CZ), bodies for cooperation in 
vocational education and training (the National Council for vocational education and 
training in Norway and National vocational education and training programme councils in 
SE), career guidance counsellors (CZ), student families (SI) and wider society (LV).67 

Examples of uses of vocational education and training graduate 
tracking results 

In Portugal the data from the ‘Observatory of secondary students’ trajectories. 
Youth in post-secondary survey’ is used by the National Agency for 
Qualifications and vocational education and training (ANQEP) to support: 

  The annual planning of vocational education and training provision in the 

country; 

  The computation of EQAvocational education and training indicators; and  
  Discussions at the ‘Higher employability network’ (network of schools 
providing vocational education and training) annual meetings about 
employability). 

In Belgium (NL), the School Leavers Study is the main graduate tracking 
measure and covers initial vocational education and training and higher 
education. The Service for Employment and Vocational training (VDAB), leading 

65 A new graduate tracking measure based on administrative data collection was launched in 2019 in Slovakia. 
Information on the measure was not yet available at the time the research for this study was completed. 
66 Please note that these ‘other’ purposes were referred to by country researchers under an open-ended question. 
As such, the mapping of countries against purposes is not complete. Some of these purposes might also be 
considered in other countries not listed here.  
67 As above, these ‘other’ purposes were mentioned by country researchers under an open-ended question and 
the mapping may not be complete. 

March, 2020 

19 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

the study, provides an interactive online tool to inform prospective students’ 
choice of study by showing the employability prospects of specific degrees.68   

In higher education, the provision of information and guidance to prospective students 
is the most common purpose for collecting graduate data (23) followed by quality 
assurance (22), the monitoring of education policies (18), strategic planning of course 
offers (16), and access to funding (9) (see Table 4 in annex). 

Other purposes of graduate tracking in higher education include (with examples): 

  Informing policies at system or provider level to help match supply with labour 

market demand (DE);  

  Providing data for research (EE) and the returns of education (DE);  
  Supporting institutional development (FI);  
  Providing support to career centres at higher education institutions (PL); and 
  Building mutual understanding between higher education institutions and 

employers (PL).69 

The list of users is headed by governments (27) and higher education institutions (25). 
These are followed by researchers (21), current and prospective students and graduates 
(17), and employers (8) (see Table 6 in annex). The fact that the provision of 
information and guidance is highest on the list of purposes, but students and graduates 
are fourth indicates that tracking data is aimed more at higher education institution staff 
such as student advisors and counsellors than students and graduates directly.    

Other users include employment services (BE-NL) and trade unions (FI). In NO, users 
include the Councils for Cooperation with Working Life (RSA) which encourage 
collaboration between higher education institutions and social partners in the country.70 

Examples of use of higher education graduate tracking results 

Indicators using tracking data feature in the Bulgarian University Ranking 
System which is used in: 

  Performance-based funding: in 2020, 60% of state funding to higher 

education institutions is determined by their results in the ranking;  

  Deciding on the number of students to be admitted to public higher 

education institutions and the criteria to be used; and  

  Decisions on revisions to the List of Priority Professional Areas and the List 

of Protected Specialities.  

In Ireland, the ‘2016 Follow Up Surveys of Further Education and training 
(FET) Programme Participants’ are mainly used by SOLAS (the FET authority) to 
inform their national funding strategy on which programmes to support. 

In Lithuania graduate tracking results have been used in a variety of research 
studies. For instance, in 2019, tracking data informed the development of a 
forecasting model of demand for healthcare specialists up to 2028. This model 
is based on the analysis of data on the employment and career of medical 
students (progression and drop out).  

68 https://www.onderwijskiezer.be/v2/secundair/sec_schoolverlater.php 
69 Please note that these ‘other’ purposes were referred to by country researchers under an open-ended question. 
As such, the mapping of countries against purposes is not complete. Some of these purposes might also be 
considered in other countries not listed here.  
70 As above, these ‘other’ purposes were mentioned by country researchers under an open-ended question and 
the mapping may not be complete. 

March, 2020 

20 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

2.6  Drivers and obstacles to the development of graduate tracking 

A few key messages emerge from the system-level information about the implementation 
of tracking on the drivers of and obstacles to graduate tracking. Well-functioning 
graduate tracking measures seem to be characterised by: 

  Fruitful cooperation between the different key bodies holding relevant data for 

tracking (BE-NL);  

  Interest and involvement (including funding) from relevant ministries and national 

agencies (IE, FR); and  

  The participation of well-established agencies and institutions with sound 

methodological expertise, such as national statistical offices (SE) and educational 
research agencies (DE, UK).  

Additionally, the motivation of higher education institutions in tracking for reasons of 
institutional development can be a driver too (FI). Finally, time or tradition in graduate 
tracking and data-informed policy-making brings acceptance and can help consolidate 
tracking in a country (NL, SE). 

The study also identified a range of obstacles that can inhibit graduate tracking. These 
include:  

  Tracking not being a national priority or a legal requirement, which makes it 

harder to instigate (SI, LT).  

  Lack of political interest in developing graduate tracking. 
  Lack of leadership to foster cooperation between different government 

departments (ministries of education and employment, social security, etc.) (PT). 

  Restrictions due to legislation on personal data protection (SI, HR, PT). This can 

cause difficulties when databases from different ministries and services need to be 
linked (HR, PT).  

  Insufficient methodological and technological capacity at institutional level which 

can hinder the development of tracking measures (BG, RO, SI),  

  Insufficient funding from government to take forward the initiative (RO, IS).  

The involvement of different stakeholders is considered important to the development of 
tracking but ensuring smooth cooperation between them can also be challenging. For 
instance, in LT, the lack of social dialogue on skills between vocational education and 
training/higher education providers and representatives of employers may be acting as 
an obstacle to the further development of tracking. In BE-FR, the development of a 
tracking measure in higher education appears to be taking longer than expected due to 
difficulties in reaching an agreement on the data to be collected.  

The variety and complexity of qualifications covered by tracking measures can create 
challenges to the development of standardised data collection tools. In the UK, the fact 
that tracking in vocational education and training is less developed than in higher 
education could be explained by the fact that there are fewer higher education providers 
than vocational education and training providers and the main types of courses offered in 
higher education are more standardised than the diverse range of courses available 
across nations in initial vocational education and training and continuing vocational 
education and training, making standardised data and standardised tracking less 
straightforward. In LT, a lack of a coherent national database of qualifications, as well as 
continuing reforms in the national system of qualifications, may have slowed down the 
development of tracking in the past.71 

71 This situation has improved with the introduction of the national occupational standards and the implementation 
of the Lithuanian Qualifications Framework. 

March, 2020 

21 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

2.7  Key summary points 

Eighteen countries have system-level graduate tracking in higher education and 
vocational education and training; the remainder have considerable ground to 
make up and while improvements are being made, the pace of change would 
have to be faster if they were to establish system level graduate tracking in the 
next five years.  

  higher education and vocational education and training graduate tracking is an 

established practice in 18 EU and EEA countries (AT, BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, IE, IT, LU, LT, NL, NO,  SE, SK, UK). 

  Five countries have system-level graduate tracking measures for one of the 

sectors only, higher education (BG, HU, PL) or vocational education and training 
(BE-FR, PT). Of these, BG, HU and PL could have fully developed measures for the 
two sectors over the next few years. In HU and PL, vocational education and 
training graduate tracking measures are currently under development. In BG, 
there is an ongoing pilot study which, if successful, could eventually be 
mainstreamed across the country.  

  Two countries can be expected to have higher education graduate tracking in place 
over the next one or two years (LV, SI). Of these, LV may have fully developed 
measures for the two sectors in 3-4 years’ time. 

  In IS system-level higher education graduates tracking could be in place relatively 
quickly by building on the existing measures at institutional level. However, it 
would take longer to develop vocational education and training graduate tracking 
as there is no provider experience to build on.  

  In RO, the situation is the opposite. Vocational education and training graduate 

tracking could be in place sooner by supporting the completion of pilots, 
refinement and mainstreaming of the existing measure. In higher education, a 
new ESF co-funded project involves the development of a graduate tracking 
measure. The success of this project and the availability of national funds to 
mainstream the new measure will determine whether graduate tracking will 
become a regular practice in the future. 

  In three countries, the Eurograduate survey has created an opportunity for the 

development of regular higher education graduate tracking (HR, EL and MT). They 
are likely to continue participating in the EU-level measure if this is extended. 
There are no initiatives in vocational education and training. 

  In CY and LI there is little or no relevant experience so graduate tracking would be 
starting from scratch though their size and scale could make this achievable in a 
relatively short time. 

The countries where graduate tracking is a legal obligation, tend to have well-
established tracking systems. However, a legal basis is not a necessary 
condition for regular graduate tracking. 

  In around one third of countries, graduate tracking is both a legal obligation and a 
regular practice (AT, DE, DK, EE, ES, FI, FR, HU, IT, PL, SE and UK). In PT there is 
a legal obligation to track vocational education and training graduates and there is 
a relevant, regular measure covering this population. In LV, a legal obligation to 
track concurs with recent reforms to establish tracking measures in higher 
education and vocational education and training.  

  In another third of countries, graduate tracking is a well-developed practice 

despite not being a legal obligation (BG (in higher education), BE-NL, CZ, DK, IE, 
LT, LU, NL, NO and SK). In some of these countries, tracking is considered to be a 
policy objective (BG, CZ, DK, IE, LT, NL, SK) but in a few there is no policy focus 
on the topic (BE-NL, LU and NO). 

  A few countries with poorly developed graduate tracking have included in recent 

policy documents the aim to create new tracking measures (BE-FR, BG (in 
vocational education and training), HR, MT, RO, SI). 

March, 2020 

22 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  In the remaining countries, graduate tracking is poorly developed and at the time 

of the research there are no policy objectives related to it (CY, EL, IS, LI). 

The responsibility for graduate tracking generally lies with the national or 
regional authorities which oversee higher education or vocational education and 
training policies.  

  In most countries, the responsibility for graduate tracking lies with national 

authorities.  

  In six countries regional authorities have partial or full responsibility for graduate 

tracking (BE, DE, ES, IT, RO, UK). 

  Regions are more often responsible for vocational education and training than 

higher education graduate tracking. Vocational education and training graduate 
tracking is a regional competence in DE, IT, RO and UK. In BE, regional authorities 
have full responsibility for higher education and vocational education and training 
graduate tracking. In ES, responsibility is shared between the national and 
regional governments for both sectors.  

  Only in one country (FI) do providers share the responsibility of tracking, in higher 

education.  

  In the countries where no measures can be identified at system level, it was not 
possible to establish which level is responsible for graduate tracking in vocational 
education and training (BG), higher education (RO), or both sectors (CY, EL, HR, 
IS). In some of these countries, there are examples of regional or provider level 
measures, but these are not conducted systematically.  

  In PL, tracking studies of initial vocational education and training graduates were 

developed as decentralised initiatives of regional labour offices but a national-level 
initiative for vocational education and training graduates is now being developed. 
In LU, the only higher education graduate tracking measure identified is conducted 
by the University of Luxembourg but it is not clear if the responsibility for tracking 
lies on the institutional level.  

Ongoing reforms indicate an increasing use of administrative data and 
combination of administrative data and surveys  

  New graduate tracking measures are currently under development in BG, LV and 
SI and have been announced in FR, HU, LI, LT, PL and RO. Reforms of existing 
tracking measures are ongoing in BE-NL, DE, ES, FI, SE and SK.  

  Ongoing or announced reforms indicate an increase in the use of administrative 

data for graduate tracking (ES, FR and SK) and an awareness of the importance of 
combining administrative data and surveys. For instance, new measures in BG and 
RO and a renewed measure in ES will combine survey and administrative data. LT 
is trying to develop surveys to complement administrative data.  

  Other improvements to tracking include collecting more or better-quality 

information on graduates (BE-NL, FI) and collecting data at several points in time 
to allow for longitudinal tracking (BE-NL). 

Quality assurance, the provision of information and guidance to prospective 
students, and the monitoring of education policies, are the main purposes for 
collecting graduate data 

  Graduate tracking data has multiple purposes and potential users.  
  The three main purposes for collecting graduate data -quality assurance, the 

provision of information and guidance to prospective students, and the monitoring 
of education policies- coincide in higher education and vocational education and 
training.  

  In vocational education and training, the monitoring of education policies leads the 
list of purposes of graduate tracking and, accordingly, the main users of such data 
are governments. 

March, 2020 

23 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  In higher education, the most common purpose of tracking data is the provision of 

information and guidance to prospective students. The main users are 
governments and higher education institutions. It is likely that tracking data is 
particularly aimed at higher education institution staff such as students’ advisors 
and counsellors. 

The involvement and cooperation of key bodies, including those in charge of the 
policies and those holding the data and the methodological expertise, are key to 
successful tracking 

  Graduate tracking requires the involvement of different ministries, national 

agencies and departments, including statistical offices and research agencies. 
  Smooth cooperation between these entities as well as with other relevant parties, 
such as education and training providers and employer representatives, can be a 
key factor to the successful implementation of graduate tracking.  

  Common obstacles to the development of graduate tracking include lack of 

political interest or leadership to foster cooperation between the different actors, 
restrictions due to legislation on personal data protection, insufficient 
methodological and technological capacity and insufficient funding. 

March, 2020 

24 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

3 

Characteristics of system-level tracking measures 

This chapter presents the characteristics of system-level graduate tracking measures 
drawing on the country research. It examines the scale and variety of measures 
identified in EU and EEA countries, the key features of these systems (coverage, data 
collected, comparability of data and the methodologies used) and the complementarity 
between system measures and measures at other levels.  

3.1  Number of system level measures in the EU and EEA 

The mapping identified 123 system level graduate tracking measures from 29 
countries.72 Annex 3 provides a detailed overview of each measure in country code order, 
title in English and in original language, system coverage (initial vocational education and 
training, continuing vocational education and training, higher education, Others), the 
general type/source of data collection (survey, administrative data, census, other 
source), area/level of intervention (national, federal/regional), the coverage of the data 
(total reference population, sample), and reasons for tracking (policy, institutional, 
other).  

In the following table/s each measure is listed with a country code and a number. By this 
code the measure can be identified in the annex table.  

Table 8.  System coverage of the graduate tracking measures 

continuing 
vocational 
education and 
training 

AT1, BE-FR1, BE-
FR2, BE-NL2, BE-
NL3, DE1, DE3, 
DE4, DK2, DK5, 
EE2, ES1, FI1, FI7, 
FI8, FI9, FR1, HU2, 
IE1, IE4, IE5, LV3, 
MT1, NL3, NO1, 
NO5, PL1, PT3, 
RO1, SE5, SE6, 
SE7, UK2, UK4 

initial vocational 
education and 
training 

AT1, AT2, BE-FR2, 
BE-NL1, BE-NL3, 
BG1, CZ4, CZ5, DE1, 
DE2, DE3, DE4, DE5, 
DE9, DK1, DK3, 
DK5, DK7, EE1, EE2, 
ES1, ES2, ES3, ES4, 
ES5, FI1, FI7, FI8, 
FI9, FR1, FR2, FR3, 
HU2, HU3, IE1, IE2, 
IE4, IE5, IT1, IT2, 
IT3, IT8, IT9, IT10, 
LT1, LU1, LV3, MT1, 
NL3, NO1, NO4, PL1, 
PT2, PT3, RO1, SE1, 
SE2, SE7, SI1, SK1, 
UK2, UK3, UK4 

higher education 

Other 

AT2, BE-FR2, DE2, 
DE9, DK1, DK4, 
ES1, ES3, ES5, FI1, 
FI9, FR1, NL5, NO1, 
SE1, SE2, SE7 

AT1, AT3, AT4, AT5, 
BE-FR2, BE-NL1, BE-
NL3, BG2, CZ1, CZ2, 
CZ3, CZ4, DE1, DE2, 
DE3, DE4, DE6, DE7, 
DE8, DE9, DE10, 
DE11, DK1, DK3, DK6, 
EE1, EE3, ES1, ES2, 
ES6, ES7, FI1, FI2, 
FI3, FI4, FI5, FI6, FI8, 
FI9, FR1, FR4, FR5, 
HR1, HU1, IE3, IE6, 
IT3, IT4, IT5, IT6, IT7, 
LI1, LT1, LT2, LV1, 
LV2, MT1, MT2, NL1, 
NL2, NL4, NL5, NL6, 
NO1, NO2, NO3, PL2, 
PT1, RO2, SE3, SE4, 
SI2, SK1, SK2, UK1, 
UK2 

72 The measure ‘Graduate tracking based on administrative data collection’ (SK) was launched after the research 
for this study was completed and is thus not included in the analysis. In NL, in addition to the measures mapped 
in this study, the national statistics office publishes information on the labour market position of vocational 
education and training graduates every year based on administrative data. This information, together with the 
measure BVE-monitor (NL3) are both used to gather the necessary information for the Dutch ‘macro efficiency 
policy’ and to inform prospective vocational education and training students. 

March, 2020 

25 

 
 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

initial vocational 
education and 
training 

continuing 
vocational 
education and 
training 

higher education 

Other 

63 

34 

76 

17 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

The mapping identified 76 measures in higher education; 63 measures in initial 
vocational education and training; 34 measures in continuing vocational education and 
training; and 17 other measures. However, some measures covered more than one 
education area. 77 measures targeted only one education sector; 27 covered two and 18 
covered three or more areas.  

Other measures covered specific subsets of the education system (e.g. dual vocational 
education and training) or specific thematic alignments (e.g. graduates from art schools). 

Only two countries (EL and CY) have no graduate tracking measures at system level 
except for the tracking of completers in ESF-funded training. In EL some graduate 
tracking takes place at institutional level, by higher education institutions or sectoral 
bodies. In CY, no evidence was found of graduate tracking at institutional level. 

Tracking of completers in ESF-funded training 

According to ESF requirements, responsible authorities must collect information 
on the employment status of participants six months after leaving any ESF-
funded measure.73 This information is required at least twice in the funding 
period, in 2018 and 2023. 

This study identified tracking systems of ESF-funded training in 9 countries (BE-
NL, CY, DK, EL, FI, IT, PT, ES, SE). In all cases, the information on the 
employment status of participants had been collected by the organisations 
implementing the training and collated by the ESF managing authorities in 
2018. 

The architecture of ESF implies that a variety of organisations are involved in 
data collection. This includes managing authorities, ESF beneficiaries and 
intermediaries. For instance, in Finland, in the Operational Programme 
Sustainable Growth and Jobs 2014-2020, the managing authority (the Ministry 
of Employment and Economy) has established guidelines on tracking 
programme completers. Based on this, the Centres for Economic Development, 
Transport and the Environment (ELY-centres) undertake regional 
implementation and guide training providers (recipients of ESF funding) to 
collect participants’ information. An external evaluator (TK-Eval) conducted the 
long-term tracking (after 6 months) based on the data originally collected by 
the course providers. 

Data collection on employment status can be done through administrative data 
(such as public employment services or social security), which is the case in BE-
NL, IT, PT. DK, FI, IT, ES and SE or through participant follow-up surveys. 
Often, a variety of methods is used within the same country depending on the 
operational programme, region, or intermediate entities involved. For instance, 
in ES, entities responsible for some operational programmes have agreements 
with the Department for Social Security to access their data for tracking while 
the public employment service uses its own employment data where it is a 
training provider and beneficiary of ESF funds. 

73 Regulation (EU) No 1304/2013 of the European Parliament and of the Council of 17 December 2013 on the 
European Social Fund and repealing Council Regulation (EC) No 1081/2006. 

March, 2020 

26 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

No links have been identified between the tracking systems developed for ESF-
funded measures and other graduate tracking systems. 

3.2  Key features of system-level graduate tracking measures 

3.2.1  Coverage (target population) 

Most (114) of the graduate tracking measures only collect data on students that have 
completed their learning programme (graduates). Only 39 measures include people who 
have left without completing, a higher number of these measures take place in the initial 
vocational education and training sector (29).  

18 measures collect information on students before they completed their course (see 
table below), 12 of them in the initial vocational education and training and/or higher 
education sector, 7 in continuing vocational education and training.  

Very few (15) tracking measures collect information on graduates that have migrated to 
another country, most of them in the higher education sector (11). Thirty-five measures 
are applied in a broader sense to residents in a country in general and 20 measures are 
targeted at specific groups of students, such as early school leavers, young people not in 
employment, education and training (NEETs) and people registered in public employment 
services. One measure also collects information on the employers of the graduates. 

Table 9.  Graduate population which is included in the tracking measure 

Measures per education sector 

Survey 
population 

 Initial vocational 
education and training 

Completers 

AT1, AT2, BE-FR2, BE-
NL1, BG1, CZ4, CZ5, 
DE1, DE2, DE3, DE4, 
DE5, DE9, DK1, DK3, 
DK6, DK7, EE1, EE2, 
ES1, ES3, ES4, ES5, 
FI1, FI7, FI8, FI9, FR1, 
FR2, FR3, HU2, HU3, 
IE1, IE2, IE4, IE5, IT1, 
IT2, IT3, IT8, IT9, IT10, 
LT1, LU1, MT1, NL3, 
NO4, PL1, PT2, PT3, 
RO1, SE1, SE2, SE7, 
SI1, SK1, UK2, UK3, 
UK4  

(59) 

Continuing 
vocational 
education and 
training 

AT1, BE-FR1, 
BE-FR2, BE-
NL2, DE1, DE3, 
DE4, DK2, EE2, 
ES1, FI1, FI7, 
FI8, FI9, FR1, 
HU2, IE1, IE4, 
IE5, MT1, NL3, 
NO5, PL1, PT3, 
RO1, SE5, SE6, 
SE7, UK2, UK4  

(30) 

higher education 

Total* 

114 

AT1, AT3, AT5, BE-
FR2, BE-NL1, BG2, 
CZ1, CZ2, CZ3, CZ4, 
DE1, DE2, DE3, DE4, 
DE6, DE7, DE8, DE9, 
DE10, DE11, DK1, 
DK3, DK6, EE1, EE3, 
ES1, ES6, ES7, FI1, 
FI2, FI3, FI4, FI5, 
FI6, FI8, FI9, FR1, 
FR4, FR5, HR1, HU1, 
IE3, IE6, IT3, IT4, 
IT5, IT6, IT7, LI1, 
LT1, LT2, LV1, LV2, 
MT1, MT2, NL1, NL2, 
NL4, NL5, NL6, NO2, 
NO3, PL2, PT1, RO2, 
SE3, SE4, SI2, SK1, 
SK2, UK1, UK2  

(72) 

People who 
have left 
without 
completing 

AT1, AT2, BE-FR2, BE-
NL1, CZ4, DE1, DE3, 
DE4, DE5, DK1, EE1, 
FI1, ES1, ES3, ES5, FR1, 
FR2, FR3, HU3, IE2, IE4, 

AT1, BE-FR2, 
DE1, DE3, DE4, 
DK2, ES1, FI1, 
FR1, IE4, PL1, 
PT3, UK2  

(13) 

39 

AT1, AT3, BE-FR2, 
BE-NL1, CZ4, DE1, 
DE3, DE4, DK1, EE1, 
ES1, FI1, FI2, FR1, 
LI1, PL2, SE3, SE4, 
SI2, UK2  

March, 2020 

27 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Measures per education sector 

Survey 
population 

 Initial vocational 
education and training 

Continuing 
vocational 
education and 
training 

higher education 

Total* 

LU1, PL1, PT2, PT3, SE1, 
SE2, SI1, UK2  

(29) 

(20) 

Students 
(before 
completion) 

CZ5, DE1, DE3, DE4, 
DE9, DK1, FI1, HU3, 
IE4, IT3, PL1, PT2  

DE1, DE3, DE4, 
DK2, FI1, IE4, 
PL1  

AT4, DE1, DE3, DE4, 
DE9, DK1, EE3, FI1, 
HU1, IT3, LI1, SI2  

18 

Residents in 
country 

Those who 
migrate to 
another 
country after 
graduation 

Others 

(12) 

(7) 

(12) 

AT1, AT2, BG1, DE1, 
DE2, DE3, DE4, DE5, 
ES1, FR1, LT1, LV3, 
NO1, PT2, SE1, SE2, 
UK2, UK3, UK4 

(19) 

AT1, DE1, DE3, 
DE4, ES1, FR1, 
LV3, NO1, SE5, 
SE6, UK2, UK4 

(12) 

AT1, AT3, AT5, BG2, 
DE1, DE2, DE3, DE4, 
DE10, ES1, ES6, ES7, 
FI2, FI3, FR1, LI1, 
LT1, LT2, MT2, NL6, 
NO1, SE3, SE4, UK2 

35 

AT2, DE3, HU3, LV3, 
PT2 

DE3, LV3 

(2) 

(5) 

(24) 

AT5, DE3, DE10, ES7, 
FI2, FI3, FI4, FI5, 
MT2, NL4, NL6 

15 

(11) 

AT1, DE2, DE3, DE9, 
ES1, ES2, ES3, ES5, 
FI9, NL3, SE7 

(11) 

AT1, DE3, ES1, 
FI9, NL3, SE7 

(6) 

AT1, AT5, CZ1, CZ2, 
DE2, DE3, DE6, DE9, 
DE10, ES1, ES2, FI9, 
NL5, NO3, PT1 

20 

(15) 

Source: Mapping research conducted by ICF, 3s and CHEPS. * Including 17 measures 
covering also other education sectors than initial vocational education and training, 
continuing vocational education and training, higher education.  

3.2.2  Information collected from graduate tracking measures 

The most commonly collected information generally matches the types of information 
specified in the Council Recommendation on tracking graduates. In 110 of 123 measures 
information on employment status is collected, followed by socio-biographical and socio-
economic information (94), further education and training pathways (84) and links to 
level, field of study and provider (68) (see Figure 1below). It is recognised that 
information about graduates’ satisfaction with courses of learning and the relevance of 
their skills for their employment, for example, will only be drawn from survey measures.   

March, 2020 

28 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 5.  Main indicators covered by the instrument 

Socio-biographical and socioeconomic information

Employment status

Further education and training pathways

Link to level, field of study and provider

Satisfaction

Relevance/utilisation of acquired skills at the…

Place of residence / migration to other countries

Social and civic activities and participation in these

13

110

94

84

68

61

60

54

Other indicators

45

20

0

40

60

80

100

120

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Examples of most commonly collected indicators  

  Employment status: employment status (employed, full-time, part-time, 

unemployed, self-employed, in maternity leave etc.), NACE code of 
employer, duration of employment/unemployment, length of job search, 
salary level, geographical/sectoral mobility, job history, ways of access to 
job (via WBL, PES, friend/family, advertisements, other), job search time, 
career pathways, location of work, satisfaction with job 

  Socio-biographical and socioeconomic  information: age, sex, 

nationality, place of residence, social background (level of education, 
occupation of parents), disability, mother tongue, ethnic background, 
country of birth, children, age of children, marital status, household income, 
completed formal education and training, highest educational attainment, 
year of graduation 

  Further education and training pathways: participation in training, 

number of days in education, level and type of education and training, fields 
of study, further qualifications achieved 

  Link to level, field of study and provider: level and field of study, type 
of study (full-time, part-time, while in employment), type of provider, 
factors for the choice of institution and field of study, duration of study, 
recognition of earlier learning and work experience / ways of access to the 
programme 

  Satisfaction: satisfaction with study program/training (partly with 

assessment of detailed aspects such as content, balance of theory and 
practice, teachers, exams, attractiveness of the program), satisfaction with 
study conditions, satisfaction with current job, satisfaction with current 
income/salary, satisfaction with career progress, satisfaction with relevance 
of education/training for current job 

  Relevance/utilisation of acquired skills at the workplace: usability of 
study for current employment, matching of skills acquired during education 
and their utilisation in employment, relevance of study for career 
progression 

  Place of residence / migration to other countries: current place of 

residence/employment, place of residence during study, intra-

March, 2020 

29 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

country/international mobility, migration background, country of birth, 
migration of the parents, country of birth of parents 

  Social and civic activities and participation in these: democratic 
values, attitudes towards Europe, active citizenship, social and civic 
engagement, social media presence and profiling, voluntary/unpaid work, 
activities in associations, leisure activities 

Other indicators that are collected in graduate tracking measures include: motives for 
studying, student grants/financial aid, living conditions and living expenses, international 
mobility, information about different student groups (e.g. with health impairments, 
disabilities, students on PhD programmes, students with children), social inclusion, 
health, satisfaction with the course/programme, student well-being (e.g. support 
services, study environment equity), NEETs.  

The following box provides examples of some of the variables collected and their 
frequency (see also further information on comparative indicators in chapter 5.1.2).   

Examples of frequencies of collected indicators 

  Ethnic background: covered in 21 measures (AT1, AT5, CZ3, DE5, DE9, 

FI2, FI4, FI7, FI8, HU1, IE2, IT7, LI1, NL4, NL6, NO2, NO4, PT2, RO1, SI1, 
UK2); different indicators such as migration background, migration status, 
migration to other countries, in-country migration, migration of the parents, 
ethnic background, ethnic-national origin, ethnicity, mother tongue, 
language of parents 

  Country of birth: covered in 7 measures (AT4, LU1, NL1, NL2, NL4, NL5, 

SI2; country of birth of parents is covered in LU1, NL5, NO2) 

  Parent educational background: covered in 10 measures (AT3, AT4, IT5, 

MT1, NL3, NL4, NO2, RO2, SE1, SE2); different indicators: educational 
background, socio-biographical/socio-economic information relating to 
parents, parents with higher education degree 

  Quality of education (including work-based or lecture-based 

learning): covered in 27 measures (AT5, CZ1, CZ2, CZ3, CZ5, DE1, DE4, 
DK6, EE2, EE3, ES7, FI2, FI5, FI6, FI7, HU1, IT2, IT7, IT9, LV2, MT1,MT2,  
NL3, NL5, NO2, NO5, SE5); different indicators such as quality of university, 
perception of quality/relevance of education and training for finding 
employment and for current job, quality of teachers, quality of exams; 
overlap with indicator ‘satisfaction’: satisfaction with (content/organisation 
of) education/study programme, satisfaction of individuals with vocational 
education and training training/skills/practical training received 

  Mismatch between skills acquired and those used at the workplace: 
covered in 3 measures (CZ1, CZ2, LT2) but also covered in the indicator 
“relevance/utilisation of acquired skills at the workplace” 

3.2.3  Methodology of data collection 

There is a reasonably equal mix of surveys (78) and administrative data collection 
instruments (79) (see table below). Only one measure is based on census data, and this 
is in higher education. Two measures are based on other sources of discrete data: NL6 
uses data of LinkedIn users gathered directly from LinkedIn (though not through scraping 

March, 2020 

30 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

or data mining);74 and IE4 uses results from exams after completing a course for 
supplementary information. 

Surveys are dominated by quantitative approaches. These were used for 68 of the 78 
survey measures, with most (58) being online surveys. The other methods were mostly 
telephone surveys, comprising Computer-Assisted Personal Interviews (CAPI), Computer-
Assisted Telephone Interviews (CATI) or Computer-Assisted Web Interviews (CAWI).  

Table 10.  Data collection approach 

Data collection approach 

Total 

Survey 

     Qualitative survey 

          Interviews 

          Focus groups 

          Other 

     Quantitative survey 

          Telephone survey 

          Paper survey 

          E-Survey 

          Other 

Administrative data collection instruments 

     Population register 

     Social security register 

     Register on education achievements 

     Unemployment register 

     Tax register 

     Register of ESF beneficiaries 

     Other 

Census 

Other source of discrete mass-data 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

78 

12 

9 

1 

9 

68 

18 

22 

58 

8 

79 

29 

39 

59 

38 

23 

5 

26 

1 

2 

Examples of surveys 

DZHW Panel Study of School Leavers with a Higher Education Entrance 
Qualification (DE9): This measure, covering initial vocational education and 

74 In the Netherlands, web scraping of online job vacancies is being used by the Foundation for Cooperation on 
Vocational Education, Training and Labour Market (SBB) for an indicator on future job prospects for vocational 
education and training graduates. 

March, 2020 

31 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

training and higher education, is conducted by the German Centre for Higher 
Education Studies and Science Studies (DZHW) since 1976 every three years. 
Several survey waves are conducted for each cohort at different times before 
and after acquiring the Higher Education Entrance Qualification (first wave: 0,5 
years before graduation, second wave: 0,5 years after graduation, third wave: 
2,5 years after graduation, fourth wave: 4,5 years after graduation, later 
waves: different intervals up to 20 years after graduation). It is based on a 
quantitative survey, a mixture of paper survey and an e-survey.  

Graduates’ employment condition (AlmaLaurea Consortium) (IT6): This 
measure in higher education is based on a combination of a qualitative and 
quantitative survey, using CAWI and CATI design, a census and administrative 
data collected by the universities. Cohorts are followed up with the surveys 
being conducted 1, 3, and 5 years after graduation.  

Administrative data commonly use registers of education achievements (59 measures), 
social security recipients or unemployment (39 measures each), and to a less extent 
population (29 measures) and tax (23 measures). Other administrative data use data 
from the chamber of commerce, a state database on people with disability, student 
registers, and pensions data. 

Example for administrative data 

Transition from school to further education and work (FI1): This 
measure, covering initial vocational education and training, continuing 
vocational education and training and higher education, is based on 
administrative data collection. Statistics Finland produces its core data for 
graduate tracking through combining Statistics Finland's extensive person-
based data with its degree register. Information on further education is 
produced from Statistics Finland's student registers and data on employment 
and labour which are collected by combining several registers 

The table below provides an overview of the measures for each type/source of data 
collection.  

Table 11.  Type and source of data collection 

Census  Other 

I IT6 

source 

IE4, 
NL6 

Survey 

Administrative data 

AT2, AT4, AT5, BE-FR1, BG1, 
CZ1, CZ2, CZ3, CZ5, DE1, DE2, 
DE4, DE6, DE7, DE8, DE9, DE10, 
DE11, DK5, DK6, EE2, EE3, EL1, 
ES3, ES4, ES5, ES7, FI2, FI3, FI5, 
FI6, FI7, FI9, FR1, FR2, FR3, FR4, 
FR5, HR1, HU1, HU3, IE1, IE2, 
IE3, IT1, IT2, IT4, IT5, IT6, IT7, 
IT9, IT10, LI1, LT2, LV1, MT1, 
MT2, NL1, NL2, NL3, NL5, NO2, 
NO3, NO4, NO5, PL1, PT1, PT2, 
RO1, RO2, SE1, SE3, SE5, SI1, 
SK2, UK1, UK3, UK4 

AT1, AT2, AT3, BE-FR1, BE-FR2, 
BE-NL1, BE-NL2, BE-NL3, BG1, 
BG2, CZ4, DE1, DE3, DE5, DK1, 
DK2, DK3, DK4, DK5, DK6, DK7, 
EE1, ES1, ES2, ES4, ES5, ES6, 
ES7, FI1, FI2, FI3, FI4, FI5, FI6, 
FI7, FI8, FI9, HU1, IE3, IE4, 
IE5, IE6, IT1, IT2, IT3, IT4, IT5, 
IT6, IT7, IT8, IT9, IT10, LT1, 
LT2, LU1, LV1, LV2, LV3, NL1, 
NL3, NL4, NL5, NL6, NO1, NO2, 
PL1, PL2, PT1, PT2, PT3, SE1, 
SE2, SE3, SE4, SE6, SI2, SK1, 
UK2, UK4 

78 

79 

1 

2 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

32 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

3.2.4  Data protection and ability to link data on an anonymised basis 

All tracking measures have to comply with European and national data protection 
guidelines. This commonly sets requirements for: 

  The anonymization of personal data. 
  The aggregation of data for too small groups.  
  Access to data only for accredited people. 
  Access for researchers who want to work with data via secure data centres or 

secure work rooms.  

  Data handing and storage. 

For 54 measures the use of unique identifiers is used to ensure anonymity and to offer 
the possibility to link data on an anonymised bias. These were AT1, AT2, AT3, AT4, AT5, 
BE-FR1, BE-FR2, BG1, BG2, CZ1, DE2, DE3, DE6, DE10, DK1, DK2, DK3, DK4, EE1, ES1, 
ES4, FI1, FI2, FI3, FI4, FI5, FI6, FI7, FI8, IE2, IE5, IE6, IT1, IT2, IT3, IT5, IT6, IT9, LU1, 
MT1, NL3, NL4, NO1, NO3, NO4, NO5, SE1, SE3, SE5, SE6, UK1, UK2, UK3 and UK4.  

Example for the use of unique identifiers 

For education-related employment career monitoring (BibEr, AT1) in 
Austria administrative data about education and the labour market are 
processed in a structured way and merged by an anonymous key (target 
swapping). this is when a certain percentage of individual characteristics of data 
sets is swapped with those of other data sets. 

In Sweden (SE1, SE3) a person number per respondent is used to enable 
the linkage of different data sources.  

3.2.5  Timing and frequency of data collection 

Around a third (44 of 116) of measures are collected on an annual cycle for a cohort of 
learners. For 70 measures another cycle was used which ranges from 6 months up to 6 
years. The most common cycle is between 2 and 4 years. This means that not each 
cohort is included.  

Table 12.  Frequency of data collection 

Frequency  Measures 

Annually 

Another 
cycle 

AT1, BE-FR1, BE-NL1, BE-NL2, BG2, DE1, DE7, DK1, DK3, DK4, 
DK7, EE1, ES1, FI1, FI2, FI3, FI4, FI8, FR2, FR3, FR4, HU3, IE3, 
IE4, IE6, IT2, IT5, IT6, IT8, LU1, LV2, NL1, NL3, NL4, NL5, PL2, 
PT1, SE2, SE4, SE5, SI2, UK2, UK3, UK4 

AT2, AT3, AT4, AT5, BE-FR2, BG1, CZ1, CZ2, CZ3, CZ4, CZ5, 
DE2, DE3, DE4, DE5, DE6, DE8, DE9, DE10, DE11, DK5, DK6, 
EE2, EE3, ES2, ES3, ES5, ES6, ES7, FI5, FI6, FI7, FI9, FR1, FR5, 
HR1, HU1, IE1, IE2, IE5, IT1, IT3, IT4, IT7, IT9, IT10, LI1, LT1, 
LT2, LV1, MT1, MT2, NL2, NL6, NO1, NO2, NO3, NO4, NO5, PT2, 
PT3, RO1, RO2, SE1, SE3, SE6, SI1, SK1, SK2, UK1 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Total 

44 

70 

Over a third of measures (45) track graduates multiple times to gather longitudinal 
tracking data. These are presented in the table below. 

March, 2020 

33 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 13.  Follow up of cohort – longitudinal studies 

Measures with follow up of cohort 

AT1, AT2, AT3, BE-FR2, BE-NL2, CZ5, DE1, DE2, DE6, DE7, DE8, DE9, DE11, 
DK1, DK2, DK3, DK4, ES5, ES6, FI1, FI6, FI7, FI8, FR1, FR4, FR5, HU1, HU3, 
IE5, IE6, IT1, IT2, IT6, IT7, LT2, LU1, LV2, PL1, PL2, PT2, PT3, RO1, RO2, SE2, 
UK2 

Total 

45 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

The frequency of the follow up in measures varies – most common are two or three 
follow ups.  

Table 14.  Follow up of cohort – frequency 

Frequency of follow up 

Measures 

Total 

1 

14 

14 

5 

7 

4 

1 follow up 

2 follow ups 

3 follow ups 

4 follow ups 

PL1 

DE2, DE7, ES5, FI6, FI7, FR4, FR5, 
HU1, IT1, IT2, IT7, PT3, RO1, RO2 

CZ5, DE6, DE8, DE11, FI1, FI8, FR1, 
HU3, IE5, IE6, IT6, LT2, PT2, SE2 

AT1, BE-NL2, DE9, DK3, ES6 

5 or more follow ups / yearly follow 
ups 

AT3, BE-FR2, DK1, DK2, DK4, LV2, 
PL2 

Other designs (e.g. multi-cohort, 
multi-method design with different 
follow up frequencies) 

AT2, DE1, LU1, UK2 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Examples for follow ups are presented in the box below.   

Examples for follow ups  

In AT2 (Austria) administrative data have been collected at multiple 
measurement points after 6 months, 1 year, 2 years, 3 years, 4 years and 5 
years after graduation.  

In HU3 (Hungary) the cohort is followed up in three waves: students in their 
final year, 7-8 months after graduation, and 19-20 months after graduation.  

In RO2 (Romania) cohorts are followed twice – one year and five years after 
graduation.  

3.2.6  Sampling approaches and representativeness 

Over half of tracking measures (67) draw on the total reference population, whereas 49 
use a sample. The total reference population provides the basis more often in 
administrative data collection (49 cases) than in surveys (30 cases). Sampling is applied 
more often in surveys (44 cases), than in administrative data measures (25 cases). 

Where this is known, the sampling techniques vary: 

  18 of the measures use systematic sampling, which is selecting from the reference 
population by some criteria (e.g. gender, age, region) that are then applied to 
select randomly.  

  14 measures use random sampling with all members of the reference population 

with an equal probability.  

March, 2020 

34 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  12 measures are based on convenience sampling with reference population 

members who indicate they are available/willing to participate. 

The sampling techniques of measures where these are identified are presented in Table 
3.8 below, including a differentiation between surveys and administrative data collection.  

Table 15.  Sampling approach in surveys and administrative data collection 

Basis for 
tracking 
measure 

Total 
reference 
population 

Sample 

Total
* 

67 

Survey 

Administrative data 
collection 

AT4, EE2, EE3, FI2, FI3, FI5, 
FI6, FI7, FR2, FR3, FR4, FR5, 
HR1, HU1, IE3, IT5, IT6, NL1, 
NL2, NL3, NL5, NO4, NO5, PT1, 
PT2, RO1, RO2, SE5, UK1, UK4 

(30) 

AT1, AT3, BE-FR2, BE-NL1, BE-
NL2, BG2, CZ4, DE5, DK1, DK2, 
DK3, DK4, EE1, ES2, ES6, FI1, 
FI2, FI3, FI4, FI5, FI6, FI7, FI8, 
HU1, IE4, IE5, IE6, IT3, IT5, 
IT6, IT8, LT1, LU1, LV2, NL1, 
NL3, NL4, NL5, PL2, PT1, PT2, 
PT3, SE2, SE4, SE6, SI2, SK1, 
UK2, UK4 

(49) 

AT2, AT5, BE-FR1, BG1, CZ1, 
CZ2, CZ3, CZ5, DE1, DE2, 
DE4, DE6, DE7, DE8, DE9, 
DE10, DE11, DK6, ES3, ES4, 
ES5, ES7, FI9, FR1, HU3, IE1, 
IE2, IT1, IT2, IT4, IT7, IT9, 
IT10, LI1, LT2, LV1, MT1, MT2, 
NO2, NO3, PL1, SE1, SE3, SI1, 
SK2, UK3 

(44) 

AT2, BE-FR1, BG1, DE1, DE3, 
DK6, ES1, ES4, ES5, ES7, FI9, 
IT1, IT2, IT4, IT7, IT9, IT10, 
LT2, LV1, NL6, NO1, NO2, PL1, 
SE1, SE3 

49 

(25) 

Systematic 
sampling 

BE-FR1, CZ5, DE1, ES3, FI9, 
FR1, HU3, IE1, IE2, IT1, IT9, 
LT2, PL1, SE1, SE3, UK3 

BE-FR1, DE1, FI9, IT1, IT9, LT2, 
NL6, NO1, PL1, SE1, SE3 

18 

(11) 

(16) 

Random 
sampling 

AT2, AT5, CZ3, DE2, DE4, DE6, 
DE9, DE10, DE11, ES7, IT4, 
SK2 

AT2, DE3, ES1, ES7, IT4, NL3 

14 

(6) 

(12) 

Convenience 
sampling 

CZ1, CZ2, DE7, IT2, IT10, LI1, 
LV1, MT1, MT2, NO2, NO3, SI1 

IT2, IT10, LV1, NO2 

12 

(4) 

(12) 

Source: Mapping research conducted by ICF, 3s and CHEPS.  

Thirty measures indicated that they have limitations due to the lack of 
representativeness of the achieved sample (see table below and box). This applies to 
surveys (25 measures) as well as to administrative data-based measures (20). In 
surveys, low response rates were the most common issue (reported for 18 measures). 
This meant that either particular sub-groups were too small for analysis or the overall 
sample was biased.  

March, 2020 

35 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 16.  Data limitations 

Data 
limitations 

Are there 
limitations 
because of 
representative
-ness of the 
sample? 

Is a survey 
response rate 
too small or 
biased for 
sub-analysis? 

Yes - Survey 

CZ2, CZ5, DE1, ES5, FI7, FI9, 
HR1, HU1, HU3, IE2, IT1, IT2, 
IT4, IT7, LT2, LV1, MT1, NL2, 
NO2, NO4, PT1, SE1, SE3, SI1, 
UK3 

(25) 

AT2, BG1, CZ2, CZ5, EE2, EE3, 
FI9, FR5, IE1, IT2, LT2, NO2, 
NO4, NO5, PT2, SI1, SK2, UK3 

(18) 

Yes – Administrative data 
collection 

AT1, AT3, BG2, DE1, ES5, FI7, 
FI9, HU1, IE5, IT1, IT2, IT4, 
IT7, LT2, LV1, NL6, NO2, PT1, 
SE1, SE3 

Total
* 

30 

(20) 

AT2, BG1, BG2, FI4, FI9, IT2, 
LT2, NO2, PT2 

20 

(9) 

Source: Mapping research conducted by ICF, 3s and CHEPS.   

Examples of limitations  

AlmaDiploma - Choices of diploma holders (IT2): The schools and training 
providers involved in the measure only cover 18 regions, hence this is not 
representative of the graduate population nationally. 

Monitoring of employability of graduates of upper-secondary vocational 
and technical schools (SI1): The surveys are based on convenience 
sampling and the response rates are low (particularly in the 2013 survey with a 
net sample size of 264 and a response rate of just 21%) which makes them 
unrepresentative.  

3.2.7  Availability of data 

Only 39 measures make all the data available. Most (58) have limitations (see table 
below). These limitations are mostly that the data is available in aggregated form only. 
For many measures the data is only available under specific conditions (e.g. follow data 
protection rules, sign a user agreement, on-site access only) for research purposes. 

Table 17.  Availability of data 

Availability of data  Measures 

Data are available 
publicly 

BE-FR2, BG2, CZ4, DK6, ES2, ES3, ES5, ES6, ES7, FI8, 
FR4, HR1, HU3, IE1, IE2, IE5, IE6, IT3, LI1, LT1, LT2, 
NL1, NL5, NO1, NO2, NO4, NO5, PL1, PL2, PT1, PT2, 
PT3, SE1, SE2, SE3, SE4, SE5, SE6, UK2 

at institutional/ 
provider level 

CZ4, DK6, ES6, FI8, FR4, IT5, IT6, IT7, LI1, NO2, PL2, 
PT1, SE2, SE4, SE6, UK2 

at local level 

DK6, IE5, IE6, PL2, SE2 

at regional level 

ES5, HU1, IE5, IE6, NO2, NO5, PL2, RO1 

at national level 

BG2, DK6, ES2, ES5, ES7, FI8, FR1, FR4, HR1, HU3, IE1, 
IE2, IE5, IE6, IT3, LT1, LT2, LV1, NL1, NL5, NO1, NO2, 
NO4, NO5, PL2, PT1, PT2, PT3, SE1, SE2, SE3, SE4, SE5, 
SE6, UK1 

Total 

39 

16 

5 

8 

35 

March, 2020 

36 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Availability of data  Measures 

Data are available 
with limitations 

AT1, AT2, AT3, AT4, AT5, BE-FR1, BE-NL1, CZ5, DE1, 
DE2, DE3, DE4, DE5, DE6, DE7, DE8, DE9, DE10, DE11, 
DK1, DK2, DK3, DK4, EE1, EE2, EE3, ES1, FI1, FI2, FI3, 
FI4, FI5, FI6, FI7, FR1, HU1, IE3, IT1, IT2, IT4, IT5, IT6, 
IT7, IT8, IT9, LU1, LV1, LV2, LV3, MT1, NL2, NL3, RO1, 
RO2, SI1, SI2, SK1, UK1 

Total 

58 

No availability of data  BE-NL2, BG1, CZ1, CZ2, CZ3, FI9, FR2, FR3, FR5, IE4, 

17 

IT10, NL4, NL6, NO3, SK2, UK3, UK4 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

For 55 of the measures it is possible to use the graduate tracking measure data to 
provide performance information to specific vocational education and training providers/ 
higher education institutions or specific vocational education and training provider/ 
higher education institutions groups. Additionally, 16 measures provide other locally 
relevant benchmarking data (for example for providers to compare their performance to 
their peers). See table below. 

Table 18.  Availability of user information at provider-level 

Item 

Measures 

Possibility to create 
feedback for specific 
vocational education 
and training/higher 
education providers 

AT1, AT3, AT4, BE-NL1, BE-NL2, BG1, CZ2, CZ5, DE7, 
DE8, DE11, DK1, DK2, DK3, ES5, ES6, FI1, FI2, FI3, 
FI4, FI5, FI6, FI7, FI8, FI9, FR4, HR1, HU1, IE4, IT2, 
IT5, IT6, IT7, IT8, LT1, LU1, LV2, LV3, NL1, NL3, NL5, 
NO2, PL2, PT1, PT3, SE2, SE4, SE5, SE6, SI2, SK1, 
SK2, UK1, UK3, UK4 

Total 

55 

Provision of other local 
relevant data 

AT3, BE-NL1, BG1, ES6, FI1, FI2, FI3, FI4, FI8, HU1, 
LT1, NO2, PT1, SE2, SE6, UK1 

16 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

For most of the measures the graduate tracking data is available free of charge. 
However, this commonly related only to aggregated data. For 9 measures data has to be 
purchased.  

Table 19.  Availability of data 

Availability of data  Measures 

Free of charge 

AT2, AT4, AT5, BE-FR1, BE-FR2, BE-NL1, BG1, BG2, 
CZ1, CZ2, CZ3, CZ4, CZ5, DE1, DE3, DE6, DE8, DE9, 
DE10, DE11, DK1, DK2, DK3, DK4, DK6, EE1, EE2, EE3, 
ES1, ES2, ES3, ES5, ES6, ES7, FI2, FI3, FI4, FI5, FI6, 
FI7, FI8, FR1, FR4, HR1, HU1, IE1, IE2, IE3, IE5, IE6, 
IT1, IT2, IT3, IT4, IT5, IT6, IT7, IT8, IT9, LI1, LT1, LT2, 
LU1, LV1, LV2, LV3, MT1, NL1, NL2, NL4, NL5, NO4, 
NO5, PL1, PL2, PT1, PT2, PT3, RO1, RO2, SE1, SE2, SE3, 
SE4, SE5, SE6, SI1, SI2, SK1, SK2, UK2, UK3 

Total 

92 

Has to be purchased  AT1, AT3, DE2, DE4, DE7, FI1, NL3, NO1, UK1 

9 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

3.2.8  Approaches to measure the counterfactual 

For 6 measures (1 in Austria, 2 in Italy, 3 in Sweden) a comparison group is used to 
measure the added value of vocational education and training and higher education 

March, 2020 

37 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

provision. These were typically non-participants of programmes or non-graduates (see 
examples in box).  

Table 20.  Use of comparison groups 

Comparison 
group 
implemented 

Measures 

Yes 

No 

AT2, IT9, IT10, SE1, SE2, SE3 

AT4, BE-FR1, BE-FR2, BE-NL1, BE-NL2, BG1, CZ1, CZ2, CZ3, 
CZ5, DE1, DE2, DE3, DE4, DE5, DK1, DK2, DK3, DK4, EE1, 
EE2, EE3, ES1, ES2, ES3, ES6, ES7, FI1, FI6, FI9, FR1, FR2, 
FR3, FR4, FR5, HU1, HU3, IE1, IE2, IE3, IE5, IE6, IT1, IT2, 
IT3, IT4, IT5, IT6, IT7, IT8, LI1, LT1, LT2, LU1, MT1, MT2, NL1, 
NL2, NL3, NL4, NL5, NL6, NO1, NO2, NO3, NO4, NO5, PL1, 
PT1, PT2, PT3, SE4, SE5, SE6, SI1, SI2, SK2, UK3, UK4 

Total 

6 

79 

Information not 
available 

AT3, AT5, DE6, DE7, DE8, DE9, DE10, DE11, DK6, ES4, ES5, 
HR1, LV1, RO1, RO2, UK1 

16 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Examples for comparison groups 

After graduation of dual vocational education and training (AT2): The 
group of drop-outs is regarded as an unintended comparison group to the 
sample. 

Youth Guarantee (IT9): The comparison group is represented by similar 
individuals who are registered in the job centre but have not participated in the 
activities of the programme.  

Entrance to the labour market after upper secondary school (SE1): The 
comparison group is represented by those who did not graduate. 

Establishment in the labour market – What young people do after upper 
secondary education (SE2): The comparison group consists of young people 
who started in year 3 but did not graduate and young people that have only 
participated in years 1 and 2 and are the same age as the young people who 
graduated. The comparison group is included in the total reference population. 

Establishment in the labour market after higher education (SE3): The 
comparison group consists of non-graduates with enough ECTS to graduate. 

3.3  How graduate tracking data is being used 

Table 19 shows how graduate tracking information is used. It is most commonly used to 
monitor and evaluate education policies and contribute to policy developments at a 
national level – this applies to measures based on surveys as well as to administrative 
data collections. However, over a third of measures have also been used to plan for 
employment, education and social needs, to support design and current curriculum and 
to strengthen career guidance. There are no significant differences between measures 
based on surveys and those based on administrative data in what they are used for.  

Table 21.  Use of data  

Use of data 

Survey 

Administrative data 
collection 

Total 

Strengthen career 
guidance 

CZ2, CZ5, DK6, ES4, ES7, 
FI2, FI3, FI5, FI6, FI7, HU1, 

AT3, BE-NL1, BG2, CZ4, 
DK1, DK6, DK7, EE1, ES4, 

55 

March, 2020 

38 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Use of data 

Survey 

HU3, IT1, IT2, IT4, IT5, IT6, 
IT7, LT2, MT1, NL1, NL2, 
NL3, NL5, NO2, NO3, PL1, 
RO1, RO2, SE1, SE3, SE5, 
SI1, SK2, UK1  

(35) 

Total 

Administrative data 
collection 
ES6, ES7, FI2, FI3, FI4, FI5, 
FI6, FI7, FI8, HU1, IT1, IT2, 
IT4, IT5, IT6, IT7, LT1, LT2, 
LV2, LV3, NL1, NL3, NL5, 
NO1, NO2, PL1, PL2, SE1, 
SE2, SE3, SE4, SE6, SK1, 
UK2  

(43) 

Support design and 
current curriculum 

BE-FR1, CZ5, DE7, DE8, DK6, 
FI2, FI3, FI5, FI6, FI7, FR1, 
HU1, HU3, IE1, IE2, IE3, IT1, 
IT2, IT5, IT6, IT7, IT10, LT2, 
NL1, NL2, NL3, NL5, NO2, 
NO3, PL1, RO1, RO2, SE5, 
UK1, UK3, UK4  

(36) 

53 

AT3, BE-FR1, BE-NL1, BE-
NL2, DK2, DK6, DK7, EE1, 
FI2, FI3, FI4, FI5, FI6, FI7, 
FI8, HU1, IE3, IT1, IT2, IT5, 
IT6, IT7, IT8, IT10, LT1, 
LT2, LU1, LV2, LV3, NL1, 
NL3, NL5, NO1, NO2, PL1, 
SE2, SI2, UK4  

Improve skills 
matching 

FI2, FI3, FI6, FI7, HU1, HU3, 
IT2, IT5, IT6, IT7, LT2, MT1, 
NO2, NO3, RO2, SE5  

(16) 

(38) 

DK2, DK7, EE1, FI2, FI3, 
FI4, FI6, FI7, FI8, HU1, IT2, 
IT5, IT6, IT7, IT8, LT1, LT2, 
LV2, LV3, NO1, NO2, SE2, 
SK1  

28 

(23) 

Plan for 
employment, 
education and 
social needs 

DE1, DE2, DE8, EE2, EE3, 
ES7, FI2, FI6, FI7, HU1, HU3, 
IT1, IT2, IT4, LT2, MT1, NO2, 
NO3, NO4, NO5, PL1, PT1, 
PT2, SE1, SE3, SE5, SI1  

(27) 

45 

AT1, DE1, DK1, DK7, EE1, 
ES7, FI1, FI2, FI4, FI6, FI7, 
FI8, HU1, IT1, IT2, IT3, IT4, 
LT1, LT2, LV2, LV3, NO1, 
NO2, PL1, PL2, PT1, PT2, 
SE1, SE2, SE3, SE4, SE6, 
SI2, SK1  

Monitor and 
evaluate education 
policies 

Contribute to policy 
development at a 
national level 

(34) 

BE-FR1, BG1, CZ2, CZ5, DE1, 
DE6, DE9, EE2, EE3, ES5, 
FI2, FI3, FI6, FI7, FI9, FR1, 
HR1, HU1, IE1, IT1, IT4, IT5, 
IT9, IT10, LV1, NL1, NL2, 
NL3, NL5, NO2, NO3, NO4, 
NO5, PL1, PT2, RO2, SE1, 
SE3, SE5, SK2, UK1, UK3, 
UK4  

(43) 

70 

AT1, BE-FR1, BE-FR2, BE-
NL1, BG1, BG2, DE1, DK1, 
DK2, DK4, DK7, EE1, ES5, 
FI1, FI2, FI3, FI4, FI6, FI7, 
FI8, FI9, HU1, IE4, IE5, IE6, 
IT1, IT3, IT4, IT5, IT9, 
IT10, LT1, LV1, LV2, LV3, 
NL1, NL3, NL5, NO1, NO2, 
PL1, PT2, PT3, SE1, SE2, 
SE3, SE4, SE6, SI2, SK1, 
UK2, UK4 (52) 

AT4, CZ5, DE1, DE2, DE6, 
DE9, DK6, EE2, EE3, FI3, FI7, 
FR1, HU1, HU3, IE2, IE3, IT1, 
IT4, IT9, LT2, LV1, MT1, NL1, 
NL3, NL5, NO2, NO3, NO4, 
NO5, RO2, SE1, SE3, SE5, 
SI1, UK1, UK3, UK4  

AT1, BG2, CZ4, DE1, DK1, 
DK2, DK4, DK6, DK7, EE1, 
FI1, FI3, FI4, FI7, FI8, HU1, 
IE3, IE4, IE5, IE6, IT1, IT3, 
IT4, IT8, IT9, LT1, LT2, LV1, 
LV2, LV3, NL1, NL3, NL5, 
NO1, NO2, SE1, SE2, SE3, 

64 

March, 2020 

39 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Use of data 

Survey 

(37) 

Administrative data 
collection 
SE4, SE6, SI2, SK1, UK2, 
UK4  

Total 

(44) 

Other 

AT2, AT4, AT5, CZ1, DE1, 
DE4, DE6, DE7, DE10, DE11, 
ES3, ES4, ES5, FI5, HR1, IE3, 
LI1, LV1, MT1, NL2, PT1  

AT1, AT2, AT3, BE-NL2, BE-
NL3, DE1, DE5, DK4, ES4, 
ES5, FI1, FI4, FI5, LV1, LV2, 
LV3, NL4, PT1, PT3, SE2  

34 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

(21) 

(20) 

Other use of data includes being used as a condition for performance-based funding (see 
box below), as an information source for policy on national and/or European level, and to 
support lifelong learning by collecting data on the experiences and needs of graduates. 

Example of the use of graduate tracking data on performance-based 
funding mechanisms 

In Bulgaria, the results of the ‘Bulgarian University Ranking System’ (BG2) are 
used for quality assurance and performance-based financing of public higher 
education institutions. 

In Denmark, funding for higher education programmes has become dependent 
on graduates’ employment rates 12 to 23 months after graduation since 2017. 

In Finland, the results in the ‘Finnish Bachelor Graduate Survey’ (FI5) and the 
‘AVOP Graduate feedback questionnaire for Universities of Applied Sciences 
(UAS)’ (FI6) also influence the allocation of performance-based funding to 
higher education institutions. The new higher education and science strategy 
"Vision for higher education and science 2030" brought in a new funding 
allocation model for universities and UAS. From the beginning of 2021, 
graduate tracking will determine 2% of the performance-based funding for 
universities and 3% for UAS. 

In the Netherlands, a small share of the public funding for vocational 
education and training and higher education institutions is linked to 'quality and 
investment plans' developed by institutions and reviewed by an independent 
commission put in place by the ministry. These plans contain indicators on 
policy objectives which make use of graduate tracking information. 

Graduate tracking data is also commonly used to inform the funding and appraisal of 
providers: In total, the results of 26 measures are or were part of external quality 
assurance and/or accreditation mechanisms. The results of 24 measures are/were 
included in performance-based funding mechanisms, performance agreements and/or 
funding formulae. 

In 52 measures (see below; 36 of them are based on surveys, 36 on administrative data) 
the information from graduate tracking measures is used to inform provider 
development. This includes supporting:  

  Provider quality assurance and for planning of course/programme offer  
  Analysis of the quality of education and its relevance to labour market needs 
  Updating curricula 

March, 2020 

40 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Planning of new course/studies offer 
  Placement information to identify issues affecting the employability of graduates 
  Guidance of students. 

Table 22.  Use of results for a ‘feedback-mechanism’ between graduates’ experiences and 

provider development 

Survey 

Administrative data collection 

BE-FR1, BG1, DE6, DE7, DE8, DE11, 
DK6, EE2, EE3, FI2, FI3, FI5, FI6, 
FI7, FI9, HR1, HU1, HU3, IE3, IT1, 
IT2, IT5, IT6, LT2, NL1, NL2, NL3, 
NL5, NO2, NO3, NO5, RO2, SE5, SI1, 
SK2, UK1, UK3  

(36) 

AT3, BE-FR1, BE-NL1, BE-NL2, BG1, DK2, 
DK3, DK6, EE1, FI1, FI2, FI3, FI4, FI5, 
FI6, FI7, FI9, HU1, IE3, IT1, IT2, IT5, 
IT6, IT8, LT2, LU1, LV2, LV3, NL1, NL3, 
NL5, NO2, PL2, SE2, SE6, SK1  

(36) 

Total 

52 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

For 66 measures (see below; 41 of them are based on surveys, 46 on administrative 
data) it was reported that they are used to inform national education strategic priorities. 
These include:  

  Informing the measurement of strategic goals 
  Informing objectives of national lifelong learning strategy 
  Identifying the need for improvements to the quality of teaching, training and 

course offers 

  Identifying potential improvements to students’ learning experience and learning 

outcomes  

  Helping to understand skills demand and supply, and identify skills shortages 
  Helping to improve the labour market relevance of vocational education and 

training 

  Increasing transparency and access to provider information 

Table 23.  Tracking information supports national strategic objectives  

Survey 

Administrative data collection 

AT2, AT4, BE-FR1, BG1, CZ5, DE1, 
DE2, DE6, DE7, DE8, DE10, DE11, 
EE2, EE3, FI2, FI3, FI5, FI6, FI7, 
HR1, HU1, HU3, IE1, IE3, IT2, IT5, 
IT6, IT9, LV1, NL3, NO2, NO3, NO4, 
NO5, RO1, SE1, SE3, SE5, UK1, UK3, 
UK4 (41) 

AT1, AT2, AT3, BE-FR1, BE-FR2, BE-NL2, 
BG1, BG2, DE1, DK2, DK4, EE1, FI1, FI2, 
FI3, FI4, FI5, FI6, FI7, FI8, HU1, IE3, 
IE6, IT2, IT3, IT5, IT6, IT8, IT9, LT1, 
LU1, LV1, LV2, LV3, NL3, NO1, NO2, PL2, 
SE1, SE3, SE4, SE6, SI2, SK1, UK2, UK4 
(46) 

Total 

66 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

3.4  Other graduate tracking measures 

Alongside system-level graduate tracking measures, there are additional graduate 
tracking measures undertaken by higher education or vocational education and training 
providers, sub-regional authorities, sectoral bodies and others. The table below provides 
an overview of these measures identified by country.  

There are in total, 26 countries with further graduate tracking measures in higher 
education and 17 in vocational education and training. In four countries graduate 
tracking measures are undertaken by sub-regional authorities and in six countries they 
are undertaken by sectoral bodies. In seven countries there are measures undertaken by 
other organisations, which included Trade Unions in Finland, the Agency for Science and 
Higher Education in Croatia, the Chamber of Commerce and Industry and Institute for 

March, 2020 

41 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Economic and Enterprise Research in Hungary, a private entity in the Netherlands, 
Universities UK International in UK, the Ladok Consortium of higher education 
institutions, and Statistics Sweden.    

Table 24.  Existence of other graduate tracking measures 

Graduate tracking by … 

Country  higher 

education 
Institutions 

vocational 
education 
and 
training 
providers 

sub-regional 
authorities 

sectoral 
bodies 

others 

AT 

BE-NL 

BE-FR 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x  

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

March, 2020 

42 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Graduate tracking by … 

Country  higher 

education 
Institutions 

SI 

SK 

UK 

Total 

x 

x 

26 

sub-regional 
authorities 

sectoral 
bodies 

others 

vocational 
education 
and 
training 
providers 

x 

16 

4 

6 

x 

x 

7 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Graduate tracking measures at institutional or sectoral level are often based on graduate 
surveys (42 measures). Fourteen of the indicated measures are based on administrative 
data and, 5 combine survey and administrative data sets (see table 23). 

Table 25.  Methods used for other graduate tracking measures  

Method 

Graduate surveys 

Administrative data 

Combination of survey and data 

Other measures 

Total 

42 

14 

5 

13 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

3.5  Complementarity between system-level and other measures 

Ten countries have in place mechanisms to ensure complementarity of system-level 
measures with measures undertaken at institutional or other levels (DK, FI, FR, HU, IE, 
IT, LV, NL, RO and UK). Examples of these mechanisms are described in the table below. 

Table 26.  Mechanisms to ensure complementarity between system-level measures and 

measures at institutional or other levels 

Country  Specification of mechanism 

DK 

In the measure EducationZOOM, the survey was developed together with 
higher education institutions and it allows higher education institutions to 
add their own questions.   

FI 

Through meetings at the Contact Committee for Education Statistics, 
stakeholders are able to provide feedback to Statistics Denmark with regard 
to data quality and publications. The educational institutions/course 
providers are obliged to provide their records to Statistics Denmark, on 
request. 

Technical implementation by the CSC - IT Centre for Science is now used in 
all higher education tracking systems. higher education tracking systems 
also allow institutions to specify additional questions. The 'Kandipalaute' 
(Bachelor feedback for universities) includes specific questions added by 
trade unions in the field of business, law and engineering. Synergy is 
provided by VIPUNEN which publishes all tracking related statistics (along 
with other education statistics) which can be edited in multiple ways, 
including data visualisations. The Platform "Toissa.fi" provides user-friendly 

March, 2020 

43 

 
 
 
 
 
 
 
 
 
 
 
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Specification of mechanism 

FR 

HU 

IE 

IT 

LV 

NL 

RO 

UK 

data visualisation of graduate tracking results covering both university and 
vocational education and training results for the purposes of study and 
career guidance in upper secondary and higher education. 

Communication between bodies conducting national surveys and regional 
authorities (labour-market, education) has led to the production of regional 
analyses and reports. Sometimes, regional reports are co-authored by 
representatives from national agencies (Céreq).  

As a result of a recent revision of the questionnaire, higher education 
institutions can request specific questions to the national higher education 
tracking survey. Relevant results are required to be published on the higher 
education providers' websites, while national results are published by the 
Educational Office. 

The higher education graduate survey provides the opportunity for higher 
education institutions to add their own questions at the end of the survey. 
These questions are specific to the higher education institution and are not 
returned as part of the national dataset. 

In the Almalaurea survey higher education institutions have the chance to 
personalise the questionnaire by adding local questions. 

Synergy between system and higher education institutions will be 
implemented in the new monitoring system. The administrative data register 
of vocational education and training will be part of the State Education 
Information System (SEIS). The storage and circulation of data will be 
ensured by the Ministry. The State Revenue Service, the State Employment 
Agency and the Central Statistical Bureau will prepare and submit to the 
Ministry data on the monitoring of graduates.  

There is some mutual consultation on the design of the surveys between the 
project teams in the HBO-monitor and the National Alumni Survey. It is also 
done between the HBO-monitor and the BVE monitor, resulting in a 
convergence on graduate tracking questions at national level.  

The HBO monitor also offers institutions the opportunity to include their own 
institution specific questions (up to 5 questions).  

For the vocational education and training survey, 80% of the survey is 
standard and 20% can be amended by the country school inspectorates 

The national Graduate Outcomes survey allows higher education institutions 
to opt-in to pay for selected additional questions from a question bank to ask 
their graduates. 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

3.6  Key summary points 

The study identified 123 graduate tracking measures at system level across 29 
countries.  

  Only EL and CY have no system level relevant measures except for the tracking of 

completers in ESF-funded training.    

  In the rest of countries, measures cover to varying degrees initial vocational 

education and training, continuing vocational education and training and higher 
education graduates. Continuing vocational education and training graduates are 
the least covered with just 34 measures identified. 

  Measures generally focus on completers of study programmes across all education 
sectors. 39 measures include students who dropped out before completing their 

March, 2020 

44 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

degree; a higher proportion of these are initial vocational education and training 
measures.  

  Only some measures (15) include graduates who have migrated to another 

country, more of these are higher education measures than initial vocational 
education and training or continuing vocational education and training. 

  Only a third of the measures (44) collect data on every cohort of graduates, others 

take place periodically at a variety of frequencies 

Measures collect a wide range of data which can be used for the purposes 
identified, although there are considerable variations in what is collected and in 
what detail. 

  The main variables collected relate to employment status, socio-biographical and 

socioeconomic information, further education and training pathways.  

  Surveys as expected are the main sources of satisfaction data about the quality of 
programmes and the relevance of acquired skills and these data are generally 
obtained.  

  Fewer measures capture data on graduate backgrounds (migration, ethnicity, 
parents’ education) which can be of analytical value and data on graduate 
education which can be used for linkage to administrative data. 

  Many measures (54) use unique identifiers to enable data to be linked so may not 

require some of this data to be collected. 

  Very few measures (13) capture information on graduates’ social and civic 

activities. 

Over a third of measures (45) track graduates more than twice to provide 
longitudinal data which is of value to policy makers and other users of the data. 

  At least one of these measures can be found in just under two thirds of countries 

(20). 

  Where cohorts are followed up, this takes place mainly two or three times within a 

cycle of around two and four years after graduation. 

  Thirty measures have at last three follow-ups; many of these are part of larger 

scale panel studies. 

Many countries use both methods for tracking graduates since they complement 
each other in providing the data needed. 

  Consequently, there is nearly an equal number of survey (mainly quantitative) and 
administrative data collection (mainly registers on education achievements, social 
security and unemployment) approaches identified.  

  Fewer measures use sampling (49) than use the total reference population (67). 
  Administrative data-based measures more often draw on the total reference 

population for analysis and for sampling, than surveys which are more often based 
on achieved samples derived from contacting the entire graduate cohort (30) and 
from selected samples (44). 

  In around a quarter of the measures (30), there are reportedly limitations in the 
use of the data because of inadequate achieved sample sizes either because of 
response bias or because of size limiting sub-group analysis. 

  While many measures use robust methods for sampling (systematic and random), 

12 use convenience sampling which runs a higher risk of response bias. 

Around eighty percent of measures have some data made publicly available for 
others to use but in many cases there are either limitations in the level of detail 
and the availability to potential users.   

  Data are mainly available with limitations, for example in aggregated form only, 

restricted to specific users. 

  For around a third of measures (39) anonymised case data are available, and for a 

greater number (55) data is available for providers. 

March, 2020 

45 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Data is generally provided freely. 

Data used for system level monitoring and evaluation of education policies and 
their development can be identified for around half of the measures. Some other 
uses are less frequently identified.  

  There are no significant differences in the use of data which are based on surveys 

and administrative data collection.  

  Around a third of measures are used to plan for employment, education and social 

needs, to support design and current curriculum and to strengthen career 
guidance.  

  Around 40% (50) of measures are used either in the funding or/and the appraisal 

and quality assurance of providers. 

  Only one in four measures are used in improving skills matches.  
  Only six measures have developed counterfactuals with comparison groups of non-

graduates for their analyses. 

Ten countries have systems to ensure the complementarity of system level measures and 
institutional level measures. These are: DK, FI, FR, HU, IE, IT, LV, NL, NO, UK. 

March, 2020 

46 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

4 

Country’s progress towards meeting the Council 
Recommendation 

This chapter draws on the information collected through the mapping of system-level 
graduate tracking measures to assess countries’ progress against the Council 
Recommendation. This is expected to contribute to a progress report required as part of 
the Recommendation. 

4.1  Country overview 

4.1.1  Methodology for assessing progress 

The following benchmarking criteria were defined on the basis of the Recommendation to 
enable an assessment of progress:  

 

 

 

 

 

‘Inclusion of graduate programmes’: Coverage of relevant programmes in 
higher education, initial vocational education and training and continuing 
vocational education and training by regular survey and administrative data 
analysis. 
‘Inclusion of graduates’: Coverage of the full graduate population, including 
people who migrate to another country after graduation, and, also, people who left 
without completing/drop-outs. 
‘Longitudinality’: Tracking of graduates at different points after they have 
graduated.   
‘Quality of data’: Use of a variety of quantitative and qualitative data which meet 
a wide variety of needs. 
‘Dissemination and use of data’: The use of data for different purposes and by 
different users. 

The following table presents the results of the comparative assessment. Complete 
coverage is indicated in dark green, nearly complete coverage in light green, good 
coverage in yellow, limited coverage in orange, and (nearly) no coverage in red. Details 
of the methodology followed for the assessment can be found in Annex 4. The table also 
includes an estimate of the timeline which it is expected countries might need to meet 
the Council Recommendation. This takes into account on the one hand the assessment of 
each country’s progress to date; and on the other hand, the scale and complexity of the 
improvements required. In practice, this will also be affected by further variables such as 
political engagement, the complexity of stakeholder involvement or the willingness/ability 
of stakeholders to cooperate. 

The table shows that: 

  In relation to the Recommendation the traffic light assessment finds that two 

countries (DE, FI) have virtually complete coverage of the criteria; five countries 
(AT, DK, IE, SE, UK) have nearly complete coverage; 12 countries have good 
coverage (BE nl, CZ, EE, ES, FI, HU, IT, LT, NL, NO, PL, PT); ten countries have 
limited coverage (Be fr, BU, HR, LV, LU, MT, RO, SK, SI) and three countries have 
no/hardly any coverage of the criteria (CY, EL, IS). 

  There are improvements to be made in all of the criteria of the Recommendation 

by the majority of countries. 

  The most significant areas for improvement for at least ten countries (orange and 

red ratings) are coverage of all the graduate population in initial vocational 
education and training, continuing vocational education and training and higher 
education; the inclusion of all graduates; and having a longitudinal approach to 
tracking.   

March, 2020 

47 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 27.  Assessment of countries’ progress towards meeting the Council 

Recommendation on Tracking Graduates 

Inclusion 
of 
graduate 
program
mes 

Inclusion 
of 
graduate
s 

Longitudi
-nality 

Quality of 
data 

Dissemi-
nation 
and use 
of data 

Average 
across 
benchma
rk areas 

Estimatio
n of 
timeline 
for 
meeting 
the 
Recomme
ndation 

3 years 

4 years 

5 years 

5 years 

4 years 

4 years 

4 years 

3 years 

3 years 

2 years* 

5 years 

2 years* 

6 years 

4 years 

2 years 

2 years 

5 years 

4 years 

3 years 

3 years 

3 years 

3 years 

48 

Austria 

Belgium 
(Flanders) 

Belgium 
(French-
speaking)  

Bulgaria  

Croatia 

Cyprus 

Czech Republic 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

Luxembourg 

Malta 

March, 2020 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Inclusion 
of 
graduate 
program
mes 

Inclusion 
of 
graduate
s 

Longitudi
-nality 

Quality of 
data 

Dissemi-
nation 
and use 
of data 

Average 
across 
benchma
rk areas 

Netherlands 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United Kingdom   

Estimatio
n of 
timeline 
for 
meeting 
the 
Recomme
ndation 

3 years 

3 years 

5 years 

4 years 

6 years 

4 years 

4 years 

5 years 

3 years 

4 years 

Source: Mapping research conducted by ICF, 3s and CHEPS. * Timeline for further 
elaboration of graduate tracking measures. 

In the sub-sections below, the assessment of each country’s progress is described.  

4.1.2  Countries with complete coverage 

Germany, has a total of eleven measures – three of them covering all sectors (DE1, 
DE3, DE4). DE2 focuses on initial vocational education and training and higher education, 
as well as DE9. DE5 covers initial vocational education and training, whereas DE6, DE7, 
DE8, DE10 and DE11 cover higher education. Only DE1 is based on the combination of 
survey and administrative data, the other measures are either based on a survey (DE2, 
DE4, DE6, DE7, DE8, DE9, DE10, DE11) or on administrative data (DE3, DE5).  

All groups of graduates are covered in the tracking measures, including people who 
migrate to another country after graduation and drop-outs. Longitudinal data on 
graduates are collected - cohorts are followed in DE1, DE2, DE6, DE7, DE8, DE9. With 
regards to tracking data collected, all Recommendation indicators are covered in the 
measures – socio-biographical and socioeconomic information, employment status, 
further education and training pathways, satisfaction, relevance of acquired skills at the 
workplace and the link to level and field of study and provider. 

Of the nine measures reported for Finland, three cover all sectors (FI1, FI8, FI9), 
whereas in FI2, FI3, FI4, FI5, FI6 the focus is on higher education. FI7 addresses initial 
vocational education and training and continuing vocational education and training. FI2, 
FI3, FI5, FI6, FI7, FI9 are based on a combination of survey and administrative data 
approaches, FI1, FI4, FI8 on administrative data. All groups of graduates are covered in 
the tracking measures, including people who migrate to another country after graduation 
(in Career Monitoring surveys) and drop-outs (Education Statistics Finland). Longitudinal 
data on graduates are available; longitudinal data is collected in FI1, FI6, FI7, FI8. All 
Recommendation indicators are covered in the measures. 

March, 2020 

49 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

4.1.3  Countries with nearly complete coverage 

In Austria, AT1 covers all sectors (initial vocational education and training, continuing 
vocational education and training, higher education), and AT2 focuses on initial 
vocational education and training. higher education is also covered in AT3, AT4 and AT5. 
Most measures are either based on a survey (AT4, AT5) or on administrative data (AT1, 
AT3) although AT2 combines them. All groups of graduates, including emigrants after 
graduation, and drop-outs are covered. Longitudinal data on graduates are available; 
cohorts are followed in AT1, AT2, AT3. All Recommendation indicators are covered in the 
measures. 

In Denmark, initial vocational education and training is covered in four measures (DK1, 
DK3, DK5, DK7), continuing vocational education and training in two measures (DK2, 
DK5) and higher education in three measures (DK1, DK3, DK6). DK1, DK2, DK3, DK4, 
DK7 are based on administrative data, DK5 and DK6 on a combination of survey and 
administrative data. Drop-outs are covered but not people who migrate to another 
country after graduation. Longitudinal data on graduates are available; cohorts are 
followed in DK1, DK2, DK3, DK4. Recommendation indicators for satisfaction and the 
level, field of study and education provider are not covered in the measures.  

In Ireland six measures are reported, of which three cover initial vocational education 
and training and continuing vocational education and training (IE1, IE4, IE5), one covers 
initial vocational education and training (IE2), and two covering higher education (IE3, 
IE6). IE1, IE2 are based on a survey, IE4, IE5, IE6 on administrative data, IE3 is based 
on both. People who migrate to another country after graduation are not covered. 
Longitudinal data on graduates are available - cohorts are followed in IE5, IE6. All 
Recommendation indicators are covered in the measures. 

In Sweden two measures cover initial vocational education and training (SE1, SE2), two 
cover continuing vocational education and training (SE5, SE6), and two cover higher 
education (SE3, SE4). One covers initial vocational education and training as well as 
continuing vocational education and training (SE7). SE5 is based on a survey, SE2, SE4, 
SE6 on administrative data, SE1 and SE3 on a combination of both. People who migrate 
to another country after graduation are not covered. Longitudinal data on graduates are 
available; cohorts are followed in SE2. All Recommendation indicators are covered in the 
measures. 

In the United Kingdom, measure UK2 covers all sectors (initial vocational education and 
training, continuing vocational education and training, higher education) across the UK. 
The focus of UK3 is on initial vocational education and training (Northern Ireland), UK4 
covers initial vocational education and training and continuing vocational education and 
training (Scotland), and UK1 covers higher education (whole UK). UK1 and UK3 are 
based on survey data, UK2 on administrative data and UK4 is based on both. People who 
migrate to another country after graduation are not covered in the data measures. 
However, longitudinal data on graduates are available as cohorts are followed in UK2. All 
Recommendation indicators are covered in the measures. 

4.1.4  Countries with good coverage 

The three measures reported for Belgium (NL) cover initial vocational education and 
training and higher education (BE-NL1), continuing vocational education and training 
(BE-NL2) or all three sectors (BE-NL3). All measures are based on administrative data; 
surveys are not applied which reduces the indicators which are collected. People who 
migrate to another country after graduation are not covered. Longitudinal data on 
graduates are available; cohorts are followed in BE-NL1 (covering initial vocational 
education and training and higher education), but only once, and in BE-NL2 (covering 
continuing vocational education and training). Recommendation indicators for further 
education and training pathways, satisfaction and relevance of acquired skills at the 
workplace are not covered in the measures.  

March, 2020 

50 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

In the Czech Republic, from the five measures identified, three focus on higher 
education (CZ1, CZ2, CZ3), one on initial vocational education and training and higher 
education (CZ4), and one on initial vocational education and training (CZ5). CZ4 is based 
on administrative data, the other measures are based on surveys. People who migrate to 
another country after graduation are not covered. Longitudinal data on initial vocational 
education and training graduates are available; cohorts are followed in CZ5. All 
Recommendation indicators are covered in the measures. 

In Estonia the initial vocational education and training sector is covered by measures 
EE1 and EE2, continuing vocational education and training by EE2 and higher education 
by measure EE3. EE1 is based on administrative data, EE2 and EE3 on surveys. People 
who migrate to another country after graduation are not covered. Longitudinal data on 
graduates are not available. All Recommendation indicators are covered in the measures. 

For France five measures are reported, two of them with a focus on initial vocational 
education and training (FR2, FR3), two of them with a focus on higher education (FR4, 
FR5) and one covering all sectors (FR1). All measures are based on surveys; 
administrative data are not used. People who migrate to another country after graduation 
are not covered. Longitudinal data on graduates are available; cohorts are followed in 
FR1, FR4, FR5. All Recommendation indicators are covered in the measures. 

The measures identified in Hungary focus on initial vocational education and training 
(HU3) and higher education (HU1). A new, planned measure will focus on initial 
vocational education and training and continuing vocational education and training 
(HU2). HU1 is based on a combination of survey and administrative data, HU3 on survey 
data. People who migrate to another country after graduation and drop-outs are covered. 
Longitudinal data on graduates are available; cohorts are followed in HU1 and HU3. All 
Recommendation indicators are covered in the measures. 

In Italy, from the ten measures identified, five focus on initial vocational education and 
training (including four national and one regional measure), four on higher education, 
and one measure addresses initial vocational education and training as well as higher 
education. Continuing vocational education and training is not covered. IT3 and IT8 are 
based on administrative data, whereas all other measures use a combination of survey 
and administrative data. Drop-outs and people who migrate to another country after 
graduation are not covered. Longitudinal data on graduates are available; cohorts are 
followed in IT1, IT2, IT6, IT7. All Recommendation indicators are covered in the 
measures. 

In Lithuania LT1 covers initial vocational education and training and LT1 and LT2 cover 
higher education. Continuing vocational education and training is not covered. LT1 is 
based on administrative data, LT2 on a combination of survey and administrative data. 
Drop-outs and people who migrate to another country after graduation are not covered. 
Longitudinal data on graduates are available; cohorts are followed in LT2. All 
Recommendation indicators are covered in the measures. 

Most of the six measures reported for the Netherlands cover the higher education 
sector (NL1, NL2, NL4, NL5, NL6); NL3 focuses on initial vocational education and 
training and continuing vocational education and training. NL1, NL3 and NL5 are based 
on a combination of surveys and administrative data, whereas the other measures focus 
on surveys (NL2) or administrative data (NL4, NL6). Drop-outs are not covered as target 
group of the measures. Longitudinal data on graduates are not available. All 
Recommendation indicators are covered in the measures. 

In Norway all sectors are covered through five measures. NO1 covers initial vocational 
education and training, continuing vocational education and training, and higher 
education; NO2 and NO3 focus on higher education; NO4 on initial vocational education 
and training; and NO5 on continuing vocational education and training. NO1 is based on 
administrative data, NO3, NO4 and NO5 on surveys, and NO2 is based on a combination 
of both methods. Dropouts and people who migrate to another country after graduation 

March, 2020 

51 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

are not covered. Longitudinal data on graduates are not available. All Recommendation 
indicators are covered in the measures. 

In Poland, PL1 focuses on initial vocational education and training and continuing 
vocational education and training (but it is still in a testing phase) and PL2 covers higher 
education. PL1 is based on the combination of a survey and administrative data, PL2 on 
administrative data. People who migrate to another country after graduation are not 
covered. Longitudinal data on graduates are available, cohorts are followed longitudinally 
in PL2. All Recommendation indicators are covered in the measures. 

Three measures are reported for Portugal: PT2 focuses on initial vocational education 
and training and PT3 on ESF-funded initial vocational education and training and 
continuing vocational education and training. PT1 covers higher education but it is not 
strictly a tracking measure - the public employment service interviews unemployed 
people and collects data on their previous studies (programme and provider). PT1 and 
PT2 use combined approaches of surveys and administrative data, PT3 is based on 
administrative data. All groups of graduates, including people who migrate to another 
country after graduation, and drop-outs are covered. Longitudinal data on graduates are 
available, cohorts are followed in PT2. Recommendation indicators such as the level, field 
of study and provider are not covered in some of the measures. 

In Spain initial vocational education and training is covered in five of seven measures 
(ES1, ES2, ES3, ES4, ES5), continuing vocational education and training in one measure 
(ES1), higher education in four measures (ES1, ES2, ES6, ES7). ES1 addresses all 
sectors (initial vocational education and training, continuing vocational education and 
training, higher education). ES3 is based on survey data, ES1, ES2 and ES6 on 
administrative data, ES4, ES5 and ES7 use both methods. All groups of graduates, 
including dropouts and people who migrate to another country after graduation, are 
covered. Longitudinal data on graduates are available, cohorts are followed in ES5, ES6. 
All Recommendation indicators are covered in the measures. 

4.1.5  Countries with limited coverage 

In Belgium (FR) one measure covers continuing vocational education and training (BE-
FR1).  A new measure covering all three sectors (BE-FR2) has been announced but has 
not yet been launched. BE-FR1 is based on a combination of survey and administrative 
data. People who migrate to another country after graduation are not covered. 
Longitudinal data on graduates are currently not available. Indicators such as the level, 
field of study and education provider are not covered in the measure. 

The measures reported for Bulgaria focus on initial vocational education and training 
(BG1, pilot) and higher education level (BG2), continuing vocational education and 
training is not covered. BG1 is based on a combination of survey and administrative data, 
BG2 on administrative data. Drop-outs and people who migrate to another country after 
graduation are not covered. Longitudinal data on graduates are not available. Indicators 
for socio-biographical and socioeconomic information, relevance of acquired skills at the 
workplace and the link to level, field of study and provider are not covered in the 
measures.  

For Croatia one measure was reported (HR1), focusing on higher education. Initial 
vocational education and training and continuing vocational education and training are 
not covered at system level. HR1 is based on a survey, administrative data are not used. 
Drop-outs and migrant graduates are covered by the measure. Longitudinal data on 
graduates are not available. Indicators on further education and training pathways and 
the level, field of study and provider are not covered in the measure.  

There are currently two measures in Latvia that cover higher education (LV1 and LV2), 
the second one focusing on doctorate holders. A new measure, covering initial vocational 
education and training and continuing vocational education and training (LV3), is 
currently in an early planning phase. LV2 is based on administrative data, LV1 combines 
survey and administrative data. Drop-outs and people who migrate to another country 

March, 2020 

52 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

after graduation are not covered. Longitudinal data on graduates are available; cohorts 
are followed in LV2. All indicators are covered in the measures. 

For Liechtenstein only a one-off study (LI1) was reported as a relevant measure, 
covering higher education. There are no measures for initial vocational education and 
training and continuing vocational education and training. LI1 is based on a survey, 
administrative data are not used. It covers completers and drop-outs, but not migrant 
graduates. Longitudinal data on graduates are not available. Indicators on further 
education and training pathways and the relevance of acquired skills at the workplace are 
not covered in the measure.  

In Luxembourg one measure is reported with a focus on initial vocational education and 
training. Continuing vocational education and training and higher education are not 
covered. The measure is based on administrative data. People who migrate to another 
country after graduation are not covered. Longitudinal data on graduates are available in 
LU1. Indicators for satisfaction, relevance of acquired skills at the workplace and link to 
level, field of study and provider are not covered in the measure. 

In Malta tracking is not conducted on a regular basis. There have been two one-off 
measures: a pilot conducted in 2015, covering all education sectors (MT1); and the 
country’s current participation in the Eurograduate survey which covers the higher 
education sector (MT2). The two measures are based on a survey; administrative data 
are not used. Drop-outs are not covered. Longitudinal data on graduates are not 
available. All indicators are covered in the measures. 

In Romania RO1 covers initial vocational education and training and continuing 
vocational education and training; however, this measure has not been applied 
systematically. RO2 focused on higher education but it was a pilot project which ended in 
2012. Both measures are based on survey data. Drop-outs and people who migrate to 
another country after graduation are not covered. Longitudinal data on graduates are 
available; cohorts are followed in RO1 and RO2. Indicators on further education and 
training pathways are not covered in the measures. 

The two measures reported for Slovakia cover initial vocational education and training 
and higher education (SK1) and higher education sector (SK2); there is no measure 
focusing on continuing vocational education and training. SK1 is based on administrative 
data, SK2 on a survey. Drop-outs and migrant graduates are not covered by the 
measures. Longitudinal data on graduates are not available. Indicators on satisfaction are 
not covered in the measures. 

The two measures reported for Slovenia focus on initial vocational education and 
training (SI1) and higher education (SI2); continuing vocational education and training is 
not covered. SI1 is based on survey data with a low response, SI2 on administrative 
data. People who migrate to another country after graduation are not covered. 
Longitudinal data on graduates are not available. All indicators are covered in the 
measures. 

4.1.6  Countries with (nearly) no coverage 

In Cyprus, the only tracking system identified concerns ESF-funded training with no 
further information available on the methodologies used. There are no other graduate 
tracking measures at system level. The situation in Greece is similar. Except for tracking 
of completers of ESF-funded training, there are no other system-level measures 
available. In Iceland graduate tracking takes place at provider level, but not at system 
level.  

4.2  Coverage of benchmarking criteria 

This section examines the overall coverage of the benchmarking criteria in the analysed 
measures as well as the coverage in each education sector: initial vocational education 
and training, continuing vocational education and training, higher education. The 

March, 2020 

53 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

following table presents the results. Complete coverage is indicated in dark green, nearly 
complete coverage in light green, good coverage in yellow, limited coverage in orange, 
and no coverage in red. The basis for this assessment is the number of countries to 
which the respective criteria apply (see detailed table in Annex 4). 

The table shows: 

  Continuing vocational education and training is much less frequently covered than 

higher education and initial vocational education and training. 

  Surveys are applied in more countries (28 countries) than data administrative 

collection (24 countries). 

  A high number of countries (26) conducts graduate tracking measures regularly. 
  Representative data is obtained in 24 countries, sufficient response rates in 19 
countries (from 28 countries which use surveys) but this is not consistent across 
initial vocational education and training, continuing vocational education and 
training and higher education. 

  There is a high grade of data availability: In 29 countries some data from 

tracking measures are available in public or in limited form.  

  While programme completers are generally included in the graduate population, 
others such as emigrants are often not, even when the latter could be included in 
surveys. Drop-outs are covered in measures in 19 countries. 

  Cohorts are followed up in 20 countries’ measures – 17 countries follow 

graduates in the initial vocational education and training sector, 12 countries in 
continuing vocational education and training and 15 in higher education.  
  Main indicators with high levels of coverage include socio-biographical and 
socioeconomic information (in 28 countries – 25 countries in initial vocational 
education and training, 15 in continuing vocational education and training, 25 in 
higher education) as well as the employment status of graduates (in 29 countries 
– 27 in initial vocational education and training, 19 in continuing vocational 
education and training, 26 in higher education).  

  Indicators of ‘satisfaction’ and ‘relevance/utilisation of acquired skills at 

the workplace’ from surveys have high levels of coverage. Satisfaction in 25 of 
28 countries (18 in initial vocational education and training, 12 in continuing 
vocational education and training, 19 in higher education). The relevance of 
acquired skills is covered in 25 countries (21 countries in initial vocational 
education and training, 12 countries in continuing vocational education and 
training, 21 countries in higher education). 

  Other indicators, such as information about further education and training 

pathways, level, field of study and provider and the place of residence / migration 
to other countries are covered in 24 countries, with better coverage in higher 
education (22 countries) than in initial vocational education and training (16 
countries) and continuing vocational education and training (10 countries).  
  In many countries the measures cover up to three forms of use. 15 countries 

cover 4 or 5 forms of use, only in 7 countries are all forms of use of data found.  
  Country coverage of benchmarking criteria overall and by education sector (initial 
vocational education and training, continuing vocational education and training, 
higher education).  

March, 2020 

54 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 28.  Country coverage of benchmarking criteria overall and by education sector 

(initial vocational education and training, continuing vocational education and 
training, higher education)  

Overall 
coverag
e (of 31 
cases) 

Initial 
vocation
al 
educatio
n and 
training 
coverag
e  

higher 
educatio
n 
coverag
e 

Continui
ng 
vocation
al 
educatio
n and 
training 
coverage   

Benchmarki
ng criteria* 

Inclusion of 
graduate 
programmes 

Graduate 
population 
included 

Surveys  

Administrative data 
collection 

Periodicity of 
measures 

Representativeness 
of data 

Sufficient response 
rate* 

Data availability 

Completers 

People who have 
left without 
completing 

Students (before 
completion) 

Residents in 
country 

Migrants to another 
country after 
graduation 

Longitudinalit
y / Follow-up 

Is the cohort 
followed-up? 

Quality of 
data / main 
indicators 
covered 

Socio-biographical 
and socioeconomic 
information 

Employment status 

March, 2020 

55 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Benchmarki
ng criteria* 

Overall 
coverag
e (of 31 
cases) 

Initial 
vocation
al 
educatio
n and 
training 
coverag
e  

higher 
educatio
n 
coverag
e 

Continui
ng 
vocation
al 
educatio
n and 
training 
coverage   

Further education 
and training 
pathways 

Satisfaction* 

Relevance/utilisatio
n of acquired skills 
at the workplace* 

Link to level, field 
of study and 
provider 

Place of residence / 
migration to other 
countries 

All forms of use (6-
7 options) 

Good coverage of 
forms of use (4-5 
options) 

Limited forms of 
use (2-3 options) 

(Nearly) no forms 
of use (0-1 options) 

Dissemination 
and use of 
data /  
Missing forms 
of use 

Source: Mapping research conducted by ICF, 3s and CHEPS. * Evaluated only for 
countries with survey-based measures (n=28), as these indicators usually are not 
collected via administrative data instruments. 

This also indicates that there are many criteria which are not met by at least around 10 
countries. There are more criteria relating to continuing vocational education and training 
that need to be addressed by countries than relate to higher education and initial 
vocational education and training. Specific criteria which require most attention include: 
response rates to surveys, the inclusion of migrant students in surveys and coverage of 
all the recommended areas of data collection. 

4.3  Key summary points 

The assessment of countries’ progress towards achieving in full the Council’s 
Recommendation on graduate tracking summarised in Table 25 above shows: 

March, 2020 

56 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Virtually complete coverage of the benchmarking criteria for Germany and Finland 
and nearly complete coverage for Austria, Denmark, Ireland, Sweden and United 
Kingdom.  

  Countries with (nearly) no coverage are Cyprus, Greece and Iceland. Belgium (fr), 
Bulgaria, Croatia, Latvia, Liechtenstein, Luxembourg, Malta, Romania, Slovakia 
and Slovenia have limited coverage, the other countries provide good coverage of 
the assessment against the criteria. 

There are improvements to be made against all of the criteria of the Recommendation by 
the majority of countries. 

  The most significant areas for improvement for at least ten countries (those with 

orange and red ratings in Table 26 above) are coverage of all the graduate 
population in initial vocational education and training, continuing vocational 
education and training and higher education; the inclusion of all graduates; and 
having a longitudinal approach to tracking.   

  A more detailed analysis of this shows that there is considerable room for 
improvement, particularly in the following aspects of graduate tracking: 

-  The coverage of continuing vocational education and training across nearly all 

benchmarking criteria; 

-  The inclusion of drop-outs and migrants in surveys; 
-  The follow-up of cohorts of learners at least twice within five years; 
-  The coverage of the main indicators across all sectors; and 
-  The quality of surveys to provide sufficient representative achieved samples in 

all case.  

March, 2020 

57 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

5 

Compatibility of practices and comparability of graduate 
outcomes data among countries 

This chapter analyses the potential for comparing national data from graduate tracking 
cross-nationally. This involved an analysis of the similarities and differences in the data 
collected, the methods used and the coverage of existing measures. It only includes 
analysis of system-level graduate tracking measures. 

5.1  Methodology for the analysis of comparability and compatibility of 

practices and graduate outcomes data 

This study has applied a four-step methodology to identify the measures with a higher 
potential for comparability based on the following criteria: type of data/indicators 
covered, use of international classifications and representativeness of data. See Annex 
5). The steps were as follows:  

  Step 1: Identification of graduate outcome indicators that are commonly produced 

from tracking surveys. 

  Step 2: For each of the indicators, identification of the measures by which they 
can be derived and their coverage (initial vocational education and training, 
continuing vocational education and training or higher education sector).  

  Step 3: For each of the indicators, identification of the feasibility with which they 

can be compared based on:  

-  Graduate population included (whether its completers, drop-outs, migrated 

graduates etc.) 
- 
Indicator classification (whether they are using international standards) 
-  Representativeness of graduate population included (whether they have the 

same level of robustness) 

-  Periodicity of data collection (whether it is conducted regularly or not) 

-  Similarity of graduate group 

  Step 4: Analysis of supporting and limiting factors for comparability 

5.1.1  Step 1: Identification of the most common outcome indicators 

The main indicators covered by the measures generally match those in the Council 
Recommendation on tracking graduates (see also chapter 3.2.2). In 110 of 123 
measures the employment status is covered, followed by socio-biographical and socio-
economic information (94), further education and training pathways (84) and 
relevance/utilisation of acquired skills at the workplace (60). Social and civic activities 
and participation in these are only covered in 13 measures (see box below). 
Nevertheless, they are a relevant indicator in surveys for social and civic engagement 
and skills of graduates (see chapter 3.2.2 for examples). 

Regular outcome indicators in graduate tracking measures  

  Employment status (110)  
Sustainability of employment (65) 
Salary (49) 

  Further education and training pathways (84)  

  Satisfaction (in general) (61) 

Satisfaction with study programme/training (47) 
Satisfaction with current job (25) 

  Relevance/utilisation of acquired skills at the workplace (60) 

  Social and civic activities and participation in these (13) 

March, 2020 

58 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

There are also other indicators that are collected frequently in graduate tracking 
measures and therefore could be used from cross-national comparison. These are shown 
in the box below and include socio-biographical and socioeconomic indicators (94) as well 
as the level, field and provider of the study programme (covered in 68 measures). The 
place of residence and/or information about migration of graduates to other countries is 
collected in 54 measures. 

Other relevant indicators for comparability in graduate tracking 
measures  

  Socio-biographical and socioeconomic information (94):  

-  Age (59) 
-  Gender (65) 
-  Nationality (43) 
-  Social background (highest educational attainment of parents, 

occupation of parents) (27) 

  Link to level, field of study and provider (68)  

  Place of residence / migration to other countries (54) 

5.1.2  Step 2: Identification of the measures from which indicators can be 

derived 

In Step 2 the indicators were then compared to examine the extent to which they were 
available for initial vocational education and training, continuing vocational education and 
training and higher education. The regular outcome indicators in graduate tracking 
measures are presented in table 27 below. This mapping found: 

  Indicators such as employment status and further education and training 

pathways have good coverage. They are covered in at least 42 measures and 24 
countries for initial vocational education and training, in at least 55 measures and 
22 countries for higher education and in at least 27 measures and 15 countries for 
continuing vocational education and training. 

  There is reasonable coverage of indicators relevant to acquired skills at the 

workplace, salary, general satisfaction and sustainability of employment. 
These are covered in at least 22 measures and 15 countries for initial vocational 
education and training, in at least 36 measures in 20 countries for higher 
education and in at least 12 measures (covering at least 11 countries) for 
continuing vocational education and training. 

  Overall, comparability is more feasible for higher education and initial vocational 
education and training. Six of the indicators are covered in at least 22 measures 
for initial vocational education and training (covering at least 15 countries) and in 
at least 36 measures for higher education (covering at least 15 countries. In 
contrast, for continuing vocational education and training only three indicators are 
contained in 17 or more measures and cover 14 or more countries. 

A detailed analysis of the specific measures that contain these indicators is presented in 
Annex 5.  

March, 2020 

59 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 29.  Coverage of regular outcome indicators by measures and countries for initial 

vocational education and training, continuing vocational education and training 
and higher education 

Indicator 

Initial vocational 
education and 
training 

Continuing 
vocational 
education and 
training 

higher education 

Others 

Employment 
status 

57 measures, 
covering 27 
countries 

30 measures, 
covering 19 
countries  

69 measures, 
covering 26 
countries 

15 measures, 
covering, 11 
countries 

Sustainability of 
employment 

35 measures, 
covering 20 
countries 

17 measures, 
covering 14 
countries 

37 measures, 
covering 15 
countries 

Salary 

22 measures, 
covering 15 
countries  

12 measures, 
covering 11 
countries 

36 measures, 
covering 20 
countries  

10 measures 
covering, 8 
countries 

6 measures, 
covering 6 
countries 

42 measures, 
covering 24 
countries 

27 measures, 
covering 15 
countries 

55 measures, 
covering 22 
countries 

12 measures, 
covering 9 
countries 

Further 
education and 
training 
pathways 

Satisfaction (in 
general) 

Satisfaction 
with study 
program/trainin
g 

24 measures, 
covering 18 
countries 

13 measures, 
covering 13 
countries 

40 measures, 
covering 19 
countries 

18 measures, 
covering 14 
countries 

10 measures, 
covering 11 
countries 

29 measures, 
covering 16 
countries 

Satisfaction 
with current job 

12 measures, 
covering 10 
countries 

7 measures, 
covering 6 
countries 

18 measures, 
covering 11 
countries 

Relevance of 
acquired skills 
at the 
workplace 

Social and civic 
activities and 
participation in 
these 

26 measures, 
covering 21 
countries 

13 measures, 
covering 13 
countries 

37 measures, 
covering 21 
countries  

5 measures, 
covering 5 
countries 

5 measures, 
covering 5 
countries 

10 measures, 
covering 8 
countries 

5 measures, 
covering 4 
countries 

2 measures, 
covering, 2 
countries 

3 measures, 
covering 3 
countries 

5 measures, 
covering 5 
countries 

no measures 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

Other relevant indicators for comparability in graduate tracking measures with a focus on 
socio-biographical and socioeconomic variables about graduates are presented in the 
table below. It shows that:  

  Socio-biographical and socioeconomic information has good coverage – in 

45 measures covering 25 countries in initial vocational education and training and 
60 measures covering 25 countries in higher education. In continuing vocational 
education and training the coverage is lower with 24 measures in 15 countries. 

March, 2020 

60 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  More specifically, there is reasonable coverage of age and gender with at least 27 
measures in 18 countries in initial vocational education and training and with at 
least 39 measures covering at least 17 countries in higher education. In continuing 
vocational education and training the coverage is lower with 13 measures covering 
at least 9 countries. 

  Information about the level, field of study and provider shows good coverage 
in initial vocational education and training and higher education with at least 30 
measures covering at least 19 countries. In continuing vocational education and 
training 20 measures in 14 countries are covered. 

  Overall, as in the results for regular outcome indicators above, comparability is 
better for initial vocational education and training (five of the indicators are 
covered in at least 18 measures covering at least 16 countries) and for higher 
education (five of the indicators are covered in at least 39 measures covering at 
least 17 countries). 

Table 30.  Coverage of other indicators by measures and countries for initial vocational 

education and training, continuing vocational education and training and 
higher education 

Indicator 

Initial 
vocational 
education and 
training 

Continuing 
vocational 
education and 
training 

higher 
education 

Others 

Socio-
biographical and 
socioeconomic 
information 

Age 

Gender 

45 measures, 
covering 25 
countries 

24 measures, 
covering 15 
countries 

60 measures, 
covering 25 
countries 

11 measures, 
covering 8 
countries 

27 measures, 
covering 18 
countries 

13 measures, 
covering 10 
countries 

39 measures, 
covering 18 
countries 

9 measures, 
covering 8 
countries 

31 measures, 
covering 18 
countries 

13 measures, 
covering 9 
countries 

41 measures, 
covering 17 
countries 

9 measures, 
covering 8 
countries 

Nationality 

19 measures, 
covering 13 
countries 

10 measures, 
covering 8 
countries 

28 measures, 
covering 14 
countries 

7 measures, 
covering 6 
countries 

Social 
background 

12 measures, 
covering 10 
countries 

3 measures, 
covering 3 
countries 

20 measures, 
covering 9 
countries 

3 measures, 
covering 3 
countries 

Link to level, 
field of study 
and provider 

30 measures, 
covering 19 
countries 

20 measures, 
covering 14 
countries 

46 measures, 
covering 22 
countries 

8 measures, 
covering 6 
countries 

Place of 
residence / 
migration to 
other countries 

18 measures, 
covering 16 
countries 

11 measures, 
covering 10 
countries 

44 measures, 
covering 22 
countries 

5 measures, 
covering 5 
countries 

Source: research ICF, 3s and CHEPS. 

March, 2020 

61 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

A detailed analysis of the specific measures that contain these indicators are presented in 
Annex 5.  

5.1.3  Step 3: Assessment of comparability of measures 

For an assessment of the comparability of measures the following characteristics of 
graduate tracking measures were taken into account:  

  Graduate population included (completers, drop-outs, students, residents in 

country, graduates who migrate to another country after graduation) 
  Use of international standards and classifications such as ISCED, ILOSTAT, 

ESCO/ISCO or NACE 

  Representativeness of the population in the achieved sample and/or sufficient 

response rate 

  Rhythm/periodicity of data collection (whether it is conducted regularly or not, e.g. 

in case of one-off measures or measures which are not continued any more) 

  Follow up of cohorts 
  Similarity of graduate groups, using the ISCED levels covered by the respective 

survey as indicator for comparability 

  Data availability (data are public available or available with limitations, e.g. for 

specific target groups such as researcher) 

  Education sector (initial vocational education and training, continuing vocational 

education and training, higher education) 

The detailed findings of the analysis are presented (separately for initial vocational 
education and training, continuing vocational education and training, higher education) in 
Annex 5. 

It is evident that not all the tracking measures can be used for comparability. Taking 
each of the characteristics above, the analysis finds that:  

  Graduate populations are differently defined which may mean that in some cases, 

say where many graduates migrate are not captured, that they may not be 
comparable. For example, the graduate population includes completers in 114 
measures while only 36 measures cover drop-outs and migrants to another 
country are covered in 13 measures (see chapter 3.2.1). 

  International classifications are commonly but not universally used. The 

international classification most often used across measures to allocate the level 
of educational attainment and orientation is ISCED. 76% of the measures (93) 
are based on ISCED or ISCED-F (46 of 64 measures in initial vocational education 
and training, 24 of 34 measures in continuing vocational education and training, 
63 of 76 measures in higher education). 

  Overall, 55% of the measures use a classification of occupations and/or skills 

on the basis of ILOSTAT, ESCO/ISCO and/or NACE (32 in initial vocational 
education and training, 16 in continuing vocational education and training, 47 in 
higher education). 

  Many but by no means all have representative samples which enable any 

comparison. Sixty-one measures have very large samples (29 in initial vocational 
education and training, 20 in continuing vocational education and training, 41 in 
higher education). The survey response rate is also sufficient in 40 survey 
measures (16 in initial vocational education and training, 11 in continuing 
vocational education and training, 28 in higher education).  

  The periodicity of data collection may make comparison difficult if measures 
are at dissimilar times post-graduation. In 91 measures the data are collected 
regularly and can be compared on this basis (46 measures in initial vocational 
education and training, 23 in continuing vocational education and training, 60 in 
higher education). The other measures are either one-off measures, measures 
with several measurement points which are not continued any more or measures 
which data are not available yet.  

March, 2020 

62 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  45 measures are longitudinal measures with a follow up of cohorts (25 in initial 
vocational education and training, 14 in continuing vocational education and 
training, 28 in higher education). In many cases the follow-up takes place twice 
(13 measures), followed by three times (9 measures), yearly follow-ups (7 
measures) and other rhythms (e.g. continuously over 36 months after completing 
vocational education and training studies such as in LU1). Comparability of around 
one, three and five years should be possible between most of these measures. 

  Data are available in 98 of 123 measures (51 times in initial vocational 

education and training, 26 times in continuing vocational education and training, 
65 times in higher education) – in 40 measures they are publicly available, in 58 
measures with limitations (see chapter 3.2.7).   

Applying the comparability criteria of the use of ISCED classification, 
representativeness of the sample and/or sufficient response rate, periodicity of data 
collection as well as (limited) availability of data to the 123 measures, this reduces the 
number to 51 potentially comparable measures.  

These are analysed further to understand to what extent the different graduate groups 
and indicators are covered by these 51 measures and for how many countries. The 
detailed findings of this analysis are presented in Tables 75 to 82 (separately for initial 
vocational education and training, continuing vocational education and training, higher 
education) in Annex 5. A summary of the results is provided here: 

  There are 25 measures in initial vocational education and training, 14 measures in 
continuing vocational education and training and 37 measures in higher education 
which show high potential for comparability.  

  There is good country coverage of completers, followed by drop-outs and residents 
in country. Low coverage for comparative analysis of students (before completion) 
and graduate populations including migrants. 

  Of all the indicators, ‘employment status’ is covered best of all – with 19 countries 
in initial vocational education and training, 9 countries in continuing vocational 
education and training and 21 countries in higher education. 

  Other indicators in initial vocational education and training covering at least 10 
countries and a maximum of 13 countries are sustainable employment, further 
education and training, socio-biographical information, age, gender. Indicators 
with lowest coverage are social/civic activities (one country) and social 
background (5 countries). 

  In continuing vocational education and training none of the indicators has a 

coverage of more than 9 countries. Indicators with highest coverage are – besides 
employment status – further education and training (9 countries), socio-
biographical information as well as level, field of study and provider (8 countries 
each). Indicators with lowest coverage are social/civic activities (1 country) and 
social background (2 countries). 

  In higher education other indicators with higher country coverage are socio-

biographical information (17 countries) and further education and training (15 
countries). Indicators like social/civic activities (3 countries), social background (4 
countries), nationality (6 countries), satisfaction (8 countries) and sustainable 
employment (9 countries) show lowest coverage, all other indicators are covered 
in 10 or more countries. 

Many measures were considered not to be comparable because either they were not 
representative or information was missing about the achieved sample size and 
population. For example, there was no information available about the 
representativeness of 31 measures. If comparability criteria are reduced to a 
minimum threshold of at least the use of ISCED classification and periodicity of data 
collection, the number of comparable measures increases to 75 measures with 
corresponding increases in the number of countries where measures can potentially 
provide comparable indicators: 

March, 2020 

63 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  39 measures in initial vocational education and training, 19 measures in 

continuing vocational education and training and 51 measures in higher education 
show high potential for comparability.  

  In initial vocational education and training indicators on employment status (21 

countries), socio-biographical information (18 countries) and further education and 
training (15 countries) show the highest coverage, similar to continuing vocational 
education and training where these indicators are each covered by 9 to 10 
countries.  

  In higher education these three indicators are covered by 18 to 21 countries with 
salary, level, field of study, provider and the place of residence/migration covered 
in 16 countries each.  

  There continues to be very low coverage of indicators such as social/civic activities 

and social background of graduates in all three education sectors.  

5.1.4  Step 4: Analysis of supporting and limiting factors for comparability 

For the comparability and compatibility of measures across countries some aspects were 
identified as helpful. 

First, the use of international classifications such as ISCED or ESCO/ISCO. The level 
of highest educational attainment and orientation (ISCED) is included in most of the 
countries. Only BE-FR, BG, LE, RO so far do not have any measures with ISCED-related 
data, neither on level of ISCED nor on level of ISCED-F. It will be helpful too if similar or 
the same ISCED levels are covered by measures which are compared with each other. 

ILOSTAT, ESCO/ISCO or NACE criteria are provided by at least one measure in most 
of the countries using international classifications, but this is not the case for BE-FR, HR, 
LE, MT, PT, RO, and SI. This makes it more difficult to compare these countries’ 
measures in relation to occupations and skills of graduates.  

Second, the use of similar intervals of data collection and follow up of cohorts 
post-graduation. Measures that have cohort follow-up and are carried out annually 
potentially provide comparable indicators. One-off measures do not enable this.  

Third, having a representative achieved sample which in the case of surveys means a 
sufficient response rate. If this cannot be provided results cannot be used for any 
comparative analysis. 

Fourth, data must be available to be shared with other parties for comparative 
research. This is no always the case for measures which do have data which can be 
compared. 

A major limitation for comparability is the form in which many indicators, such as 
employment status, socio-biographical information, relevance of acquired skills, are 
operationalized. The analysis of information collected from graduate tracking measures in 
chapter 3.2.2 already show differences in how information about these indicators is 
collected. See the examples in the box below.   

Examples for differences of indicators in surveys 

27 measures collect information on the social background of respondents, but 
this is done in very different forms for: 

  Background of parents (which can contain. profession/occupation, level of 

education, income of parents),  

  Economic situation of the individual (which can include income/financial 
barriers or the household situation of the respondent (e.g. household 
income).  

March, 2020 

64 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

In 68 measures the indicator link to level, field of study and provider is 
covered. The specification information shows that not in all cases is the same 
kind of detail information collected, although most at least collect the field and 
level of study.  The provider is covered via its name or due to anonymity via its 
province, its type (higher education provider, vocational education and training 
provider etc., public/private), and/or its subject focus. 

Another key limitation is the representativeness of data because of too small samples 
being drawn or too small or biased survey responses.  

Limitations to the representativeness of data might hinder comparability of data from 
HR, HU, LI and MT. This, as shown above, significantly reduces the number of 
comparable measures. 

A too small or biased survey response rate which hinders sub analysis (inference from 
sample or coverage population to target population when using survey data) was 
indicated for 12 measures (CZ2, CZ5, EE2, EE3, FI4, FR5, IE1, LT2, NO2, NO4, NO5, and 
SK2) in eight countries.  

5.1.5  Comparison of selected measures in higher education 

For a better illustration of the possibilities and limits of comparability, an exemplary 
comparison of three selected measures from the higher education area is presented here.  

Comparison of selected measures in the higher education area 

For the selection the following criteria were applied: 

  The measures focus on higher education level.  
  Their data are comparable on ISCED level.  
  ISCED levels which are covered are similar or at least overlap.  
  Cohorts are followed up three times (1, 3, 5 years after graduation). 
  The measures are based on administrative data collection as method.  
  There are no limitations because of representativeness of the sample. 

On the basis of these criteria the following measures were selected:  

  FI8: Placement after graduation 
  IE6: higher education outcomes 
  LV2: higher education graduate monitoring 

An analysis of main indicators covered via the three measures shows 
comparability in the following areas which are covered by all three 
instruments: 

  Socio-biographical and socioeconomic information 

-  Age (not specified for FI8, but probably covered) 
-  Gender (not specified for FI8, but probably covered) 
-  Nationality 

  Employment status, including occupation, type of employment, salary 

level, career progression 

-  Employment status (employed, not employed) 
-  Salary (not specified for FI8, but probably covered) 

  Further education and training pathways 

-  Further education/training 

  Link to level, field of study and provider 

March, 2020 

65 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

-  Field of study 

Other indicators are not covered by all three measures: satisfaction and 
relevance/ utilisation of acquired skills at the workplace are covered in LV2. The 
indicator place of residence / migration to other countries is covered in FI8 and 
LV2, but not in IE6 which hinders comparability. 

5.2  Key summary points 

There is potential for comparison of the results of graduate tracking measures: 

  Fifty-one measures meet a minimum threshold in relation to employment 

classification, representativeness and cohort /periodicity though there were more 
countries which could be compared for initial vocational education and training and 
higher education graduate indicators than for continuing vocational education and 
training; 

  Many indicators are commonly collected so are potentially comparable. Indicators 
with the highest country coverage across initial vocational education and training, 
continuing vocational education and training and higher education are employment 
status, socio-biographical information and further education and training of 
graduates.  

  For the 51 potentially comparable measures, ‘employment status’ is covered best 
of all – with 19 countries in initial vocational education and training, 9 countries in 
continuing vocational education and training and 21 countries in higher education. 

  Other indicators in initial vocational education and training covering at least 10 
countries and a maximum of 13 countries are sustainable employment, further 
education and training, socio-biographical information, age, gender. Indicators 
with lowest coverage are social/civic activities (one country) and social 
background (5 countries). 

  In continuing vocational education and training none of the indicators has a 

coverage of more than 9 countries. Indicators with highest coverage are – besides 
employment status – further education and training (9 countries), socio-
biographical information as well as level, field of study and provider (8 countries 
each). Indicators with lowest coverage are social/civic activities (1 country) and 
social background (2 countries). 

  In higher education other indicators with higher country coverage are socio-

biographical information (17 countries) and further education and training (15 
countries). Indicators like social/civic activities (3 countries), social background (4 
countries), nationality (6 countries), satisfaction (8 countries) and sustainable 
employment (9 countries) show lowest coverage, all other indicators are covered 
in 10 or more countries. 

  Comparability is enabled by the use of standard international classifications such 

as ISCED and NACE; standard definitions for socioeconomic/biographical data and 
satisfaction questions; similar periodicities for data collection; representativeness 
of the achieved sample or, in case of surveys, sufficient response rate; and data 
availability for comparative research. Many measures do not currently match these 
requirements. 

March, 2020 

66 

 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

6 

Institutional graduate tracking in higher education 

This chapter presents analysis of institution-specific graduate tracking undertaken by 
individual higher education institutions. It presents information on the types of approach 
that higher education institutions have adopted, the quality and coverage of these 
tracking measures and what information is collected. 

The chapter draws on analysis of a survey of higher education institutions across the EU-
28 and EEA countries that received 714 responses75. However, after cleaning the data to 
remove out-of-scope institutions and duplicate entries the final number of responses 
used in the analysis is 615 higher education institutions. Further details on the 
characteristics of respondents by country can be found in the annex for chapter six.   

6.1  Prevalence and type of graduate tracking undertaken by higher 

education institutions 

6.1.1  Prevalence of graduate tracking 

Nearly all (93%) survey respondents stated that they undertook some form of graduate 
tracking. However, this is not necessarily wholly representative of the wider population of 
higher education institutions since those that do not conduct graduate tracking at 
institutional level may have been less likely to complete the survey (i.e. this particular 
finding may be affected by non-response bias). In some of the countries with slightly 
lower response rates,76 the research team detected reluctance from higher education 
institutions to invest time in completing the survey because they do not have their own 
tracking measures and, instead, participate in tracking measures at national level (DE, 
NO, UK).  

higher education institutions in countries with well-established system-level graduate 
tracking measures are less likely to undertake their own graduate tracking. The countries 
with the highest proportion of higher education institutions with no tracking measures 
were the UK (19% of non-tracking respondents; 8 higher education institutions), and 
Sweden (17%; 7 higher education institutions). The number of Swedish higher education 
institutions that do not conduct any graduate tracking can be explained by their 
participation in national graduate tracking systems (by Statistics Sweden and the higher 
education national agency).77 In the UK, higher education institutions collectively fund 
the higher education Statistics Agency to undertake graduate tracking which explains 
why fewer higher education institutions have in-house tracking measures. 

6.1.2  Approaches to undertaking graduate tracking 

Quantitative surveys are the most common tool used by individual higher education 
institutions to undertake graduate tracking, as indicated by the survey results in the 
figure below. About four fifths of higher education institutions that responded to the 
survey use this approach to track their graduates, while only about one in eight use 
qualitative surveys or data mining (either instead of a quantitative survey or 
administrative data matching or more often to supplement them).  

75 Number of responses received by 20 January 2020. 
76 For response rates, please go to Error! Reference source not found.. 
77 Sub-samples of higher education institutions with no tracking measures in the remaining countries are too small 
to draw any conclusions on the reasons for non-tracking.  

March, 2020 

67 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 6.  Types of graduate tracking measures used by higher education institution 

survey respondents 

82%

21%

13%

13%

9%

7%

100%

80%

60%

40%

20%

0%

Quantitative
survey

Matching
administrative
data

Data mining

Qualitative
survey

 Other

 None

Source: ICF graduate tracking higher education institution survey (N= 615). Multiple 
choice question.  

Some survey respondents reported that administrative data matching and qualitative 
surveys were used to address gaps and supplement a quantitative survey which served 
as their primary graduate tracking tool. However, in other cases different departments in 
a few higher education institutions have adopted other approaches to tracking their 
respective graduates.   

Around a tenth of survey respondents also reported using other methods for gathering 
intelligence on the destinations and views of their graduates, often in more informal and 
less rigorous ways. These included obtaining insights from:  

  Alumni events and “meet and greets;” 
  Institutional online alumni portals; and 
  Aggregated higher education databases. 

Of the higher education institutions that only conduct one tracking measure, over four-
fifths used quantitative surveys. Relatively few conducting only qualitative surveys, data 
matching, or data mining. 

Table 31.  Type of tracking measure used amongst higher education institutions only 

using one method 

% of higher education 
institutions only using 
one tracking method 

Number of higher 
education institutions 

Quantitative surveys 

85% 

Qualitative surveys 

Data matching 

Data mining 

Other 

2% 

6% 

2% 

6% 

318 

6 

22 

7 

22 

Source: ICF graduate tracking higher education institution survey (N= 375) 

The proportion of higher education institutions using quantitative surveys was generally 
consistent across all countries78. Qualitative surveys were also used across most 
countries, with the exception of: IS, IE, LI, LT, LU NO, CY, ES. Over a quarter of the 
higher education institutions conducting data mining were situated in France. However, 

78 The annex for chapter six contains a detailed breakdown of the types of tracking measures used by country.  

March, 2020 

68 

 
 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

across the rest of the countries there was also a relatively even spread of higher 
education institutions that have conducted data mining. The countries where data mining 
was not used were: BE, HU, IS, IE, LI, LT, LU, MT, NO, SI. In contrast, administrative 
data matching is more prevalent in Austria (AT), Italy (IT), and Spain (ES) but not widely 
used by higher education institutions from other countries. The countries where data 
matching is not used at all are: BE, CY, EE, IS, LI, LU, MT, NO, SI. 

The type of tracking measures used varies slightly by the size of the higher education 
institution, as shown in the figure below. Most notably, while larger universities more 
commonly use quantitative surveys, other methods are used more commonly by smaller 
universities. Smaller higher education institutions with 5,000 or less enrolled students 
more commonly have used qualitative surveys or data mining than larger higher 
education institutions. These approaches can be undertaken at a small scale with limited 
resources or technical expertise which may explain this difference. A very small 
proportion of large higher education institutions with more than 25,000 enrolled students 
used either of these approaches.   

Figure 7.  Type of tracking measure(s) used by size of higher education institution 

%
6
8

%
2
8

%
2
8

%
8
7

100%

80%

60%

40%

20%

0%

%
1
2

%
1
1

%
8

%
5

%
3
2

%
2
2

%
8
1

%
9
1

%
4
2

%
0
1

%
7

%
7

%
0
1

%
0
1

%
9

%
9

%
7

%
6

%
9

%
7

Quantiative
survey

Qualitative
survey

Data matching

Data mining

 Other

 None

HEIs with 5,000 or less students

HEIs with 5,001-15,000 students

HEIs with 15,001-25,000 students

HEIs with more than 25,000 students

Source: ICF graduate tracking higher education institution survey (5,000 or less: N=199, 
5,001-15,000: N=209, 15,001-25,000: N=96, More than 25,000: N=111). Multiple 
choice question.  

Over three quarters of each of private, private government dependent, and public higher 
education institutions use quantitative surveys, as shown in the table below. A marginally 
higher proportion of private institutions use qualitative surveys and data mining while a 
higher share of public institutions has used data matching.  

March, 2020 

69 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 32.  Tracking measures used by public and private higher education institutions79 

Type of tracking 
measure 

Private higher 
education 
institutions 

Private 
government 
dependent 
higher education 
institutions 

Public higher 
education 
institutions 

% 

No. 

% 

No. 

% 

No. 

Quantitative 
survey 

85% 

52 

78% 

64 

80% 

328 

Qualitative survey  21% 

13 

9% 

Data matching 

15% 

9 

16% 

Data mining  

20% 

12 

12% 

7 

13 

10 

7 

11% 

46 

24% 

100 

10% 

10% 

40 

41 

27 

Other 

None 

11% 

5% 

7 

3 

9% 

12% 

10 

7% 

Source: ICF graduate tracking higher education institution survey (Private: N=61, Private 
government dependent: N=82, Public: N=409). Multiple choice question.  

Around four-fifths of universities, universities of applied sciences, and other types of 
higher education institution conduct quantitative surveys. Other institutions are more 
likely to conduct qualitative surveys and data mining, which is to be expected given that 
these are often smaller institutions with more limited resources and capabilities.  

Table 33.  Tracking measures used by type of higher education institution 80 

Type of tracking 
measure 

University 

University of 
applied sciences 

Other81 higher 
education 
institution 

% 

No. 

% 

No. 

% 

No. 

Quantitative 
survey 

81% 

344 

79% 

60 

80% 

40 

Qualitative survey  11% 

Data matching 

23% 

Data mining  

11% 

Other 

11% 

45 

98 

45 

45 

13%  

21% 

9% 

7% 

10 

16 

7 

5 

22% 

11 

16% 

8 

20% 

10 

10% 

5 

79 The type of the higher education institution was obtained using the ETER database. 552 of the 615 
respondents to our survey were matched with this data and did not contain missing information. The table 
therefore excludes the remaining 63 survey responses from the analysis.  
80 The legal status of the higher education institution was obtained using the ETER database. 552 of the 615 
respondents to our survey were matched with this data and did not contain missing information. The table 
therefore excludes the remaining 63 survey responses from the analysis.  
81 Examples of the type of institutions in this category include engineering schools, university colleges, and art 
academies. 

March, 2020 

70 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Type of tracking 
measure 

University 

University of 
applied sciences 

Other81 higher 
education 
institution 

None 

% 

8% 

No. 

% 

No. 

% 

No. 

32 

5% 

4 

8% 

4 

Source: ICF graduate tracking higher education institution survey (University: N=426, 
University of applied sciences: N=76, Other: N=50). Multiple choice question.  

Around three fifths of higher education institutions responding to the survey have used 
only one type of tracking measure (61%, or 374 out of 615) as shown in the table below. 
Of these 374 higher education institutions, 85% chose to conduct a quantitative survey. 
Of those who have carried out more than one type of measure (39%), it was relatively 
uncommon for higher education institutions to conduct more than two, with only 10% 
doing so. 

Table 34.  Number of tracking measures used by higher education institutions 

Number of tracking measures 

All higher education 
institutions 

No tracking measures 

One tracking measure 

Two tracking measures 

Three tracking measures 

Four tracking measures 

% 

7% 

61% 

22% 

8% 

2% 

No.   

41 

375 

136  

50 

13 

Total 

100% 

615 

Source: ICF graduate tracking higher education institution survey (N= 615).  

Where higher education institutions used qualitative methods they were typically used in 
conjunction with quantitative surveys (63 out of 78 higher education institutions using 
qualitative surveys, 81%) presumably to provide supplementary richer data. A similar 
proportion of higher education institutions that match administrative data to track 
graduates also use quantitative surveys. Again, these two methods typically provide 
quite different types of intelligence for higher education institutions.  

There were no significant country level differences between the number of tracking 
measures used by higher education institutions82.  

The number of tracking measures used varies by the size of higher education institution, 
as shown in the figure below. The largest higher education institutions typically focus on 
one tracking measure (70%), usually a quantitative survey, while a higher share of the 
smallest higher education institutions (45%) use two or more different types of tracking 
measure.  

82 The annex for chapter six contains a detailed breakdown of the number of tracking measures used by country.  

March, 2020 

71 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 8.  Number of tracking measures used by size of higher education institution 

HEIs with more than 25,000 students

6%

HEIs with 15,001-25,000 students

9%

HEIs with 5,001-15,000 students

6%

70%

61%

67%

16%

5%

2%

23%

6%

0%

19%

7%

2%

HEIs with 5,000 or less students

7%

50%

29%

12%

4%

0%

20%

40%

60%

80%

100%

No tracking measures

One tracking measure

Two tracking measures

Three tracking measures

Four tracking measures

Source: ICF graduate tracking higher education institution survey (5,000 or less: N=199, 
5,001-15,000: N=209, 15,001-25,000: N=96, More than 25,000: N=111).  

Over half of private, private government dependent, and public higher education 
institutions all used only one tracking measure. Private government dependent higher 
education institutions were twice as likely (12%) to have no tracking measures than 
private and public higher education institutions.  

For all types of higher education institution, over half only used one tracking measure, 
and over a fifth used two tracking measures. The proportion using no tracking measures, 
three tracking measures, and four tracking measures were below 10% for all types of 
higher education institution. No universities of applied sciences used four tracking 
measures.  

6.2  Use of quantitative and qualitative surveys 

6.2.1  Methods used to administer the surveys 

About nine out of ten (89%) respondents using a quantitative survey to track their 
graduates reported that it was administered online. Telephone surveys were used by 
39% and paper surveys by 14% of higher education institutions, sometimes in 
conjunction with an online method to increase response rates.  In a few (3%) higher 
education institutions several different surveys were administered and the methods 
varied depending on the curriculum area, study level or qualification type. Only 3% of 
institutions used other methods, which included administering surveys using social media 
(e.g. through platform-specific tools on LinkedIn and Facebook). 

Qualitative surveys were most often administered through face-to-face interviews (45%), 
followed by focus groups (40%) and telephone interviews (37%). Workshops, online wiki 
chat rooms, and other methods were not used frequently. Examples of other informal 
methods included discussions through the alumni network. No respondents reported 
using webinars.   

6.2.2  Graduate population coverage 

Most higher education institutions only survey graduates that have completed their 
studies and were working in the country in which they studied. One in ten respondents 
undertaking quantitative surveys and 17% of respondents using qualitative surveys 
reported that they surveyed former students who left without graduating. Graduates and 
former students who migrated to another country after leaving their institution were only 
included in 33% of quantitative surveys and 27% of qualitative surveys.  

More than four out of five higher education institutions using both quantitative and 
qualitative surveys focus on surveying graduates that studied at ISCED level 6 and 7. 

March, 2020 

72 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

ISCED level 8 graduates are covered in around a half of quantitative surveys and around 
a third of qualitative surveys. Few surveys include tracking of ISCED level 5 graduates. 
These results are in line with the scope of the study and dissemination efforts which 
targeted higher education institutions providing programmes at ISCED level 6 and above, 
as well as the additional measure of excluding higher education institutions with 50% or 
more of their students studying at ISCED level 5 from the survey analysis. 

Table 35.  ISCED levels included in quantitative and qualitative survey 

ISCED level(s) covered in tracking 
measure 

 ISCED level 5 (Short-cycle tertiary 
education) 

 ISCED level 6 (Bachelor degree or 
equivalent) 

 ISCED level 7 (Master degree or 
equivalent) 

 ISCED level 8 (Doctoral degree or 
equivalent) 

Higher 
education 
institutions 
that conduct 
quantitative 
surveys 

Higher 
education 
institutions 
that conduct 
qualitative 
surveys 

% 

No.  % 

No. 

13% 

65 

9% 

7 

84% 

415 

86% 

66 

94% 

464 

92% 

71 

48% 

234 

32% 

25 

Source: ICF graduate tracking higher education institution survey (quantitative survey N=492; 
qualitative survey N=77). Multiple choice question.  

6.2.3  Frequency of graduate tracking 

Three quarters of higher education institutions conducting quantitative surveys (75%) 
and around half (47%) of higher education institutions conducting qualitative surveys run 
the survey every year. A relatively high proportion of qualitative surveys in particular are 
undertaken as and when required (33%). These results may suggest that qualitative 
surveys are not the primary source of data but are used to answer more specific ad hoc 
research questions about graduates where quantitative survey results do not provide 
sufficient insights.  

Table 36.   Frequency of graduate tracking using surveys 

Frequency of data 
collection 

Higher education 
institutions that 
conduct quantitative 
surveys 

Higher education 
institutions that 
conduct qualitative 
surveys 

Every year 

Every two years 

Every three years 

Every four years 

% 

75% 

9% 

6% 

1% 

No. 

368 

43 

31 

3 

% 

47% 

9% 

8% 

1% 

No. 

36 

7 

6 

1 

March, 2020 

73 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Frequency of data 
collection 

Higher education 
institutions that 
conduct quantitative 
surveys 

Higher education 
institutions that 
conduct qualitative 
surveys 

Every five years 

% 

1% 

As and when required 

8% 

No. 

6 

38 

% 

1% 

33% 

Total 

100% 

489 

100% 

No. 

1 

25 

76 

Source: ICF graduate tracking higher education institution survey (quantitative survey 
N=489; qualitative survey N=76).  

6.2.4  Stage at which data is collected and the use of follow-up tracking 

The most common stage at which higher education institutions start undertaking tracking 
is 12-18 months after study completion for quantitative surveys and immediately after 
study completion for qualitative surveys. These results suggest that qualitative surveys 
are typically used to gather insights on graduate perceptions of their course and plans for 
the future, while quantitative surveys are initially used to capture the destinations and 
early outcomes of a cohort of graduates.  

Table 37.   Stage at which graduate tracking is first collected 

Period after completion when 
tracking information is 
collected 

Higher education 
institutions that 
conduct 
quantitative 
surveys 

Higher education 
institutions that 
conduct qualitative 
surveys 

% 

No. 

% 

No. 

Immediately after completion  

11% 

Within three months  

After 3-6 months 

After 6-12 months 

7% 

11% 

17% 

56 

32 

54 

82 

After 12-18 months 

21% 

102 

After 18 – 24 months  

After 2-3 years 

After 3-5 years 

After 5+ years  

Other83 

Total 

8% 

10% 

7% 

1% 

7% 

39 

49 

36 

5 

33 

18% 

5% 

14% 

16% 

12% 

8% 

5% 

5% 

3% 

14%  

13 

4 

10 

12 

9 

6 

4 

4 

2 

10 

74 

100% 

488 

100% 

83 Reponses under “other” included: survey sent out to all graduates every three years and therefore initial time 
after graduating varies, five years after graduation, and on an ad hoc basis 

March, 2020 

74 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Source: ICF graduate tracking higher education institution survey (quantitative survey 
N=488; qualitative survey N=74).  

Overall, follow-up tracking of graduate cohorts is done by around one third of the higher 
education institutions using surveys. About two fifths of respondents who conduct 
quantitative surveys and 35% of those that conduct qualitative surveys track their 
graduates over time. 

Among higher education institutions that do collect longitudinal data, most of the follow 
up data is collected either 1, 3, or 5 years after the initial stage of tracking.  For higher 
education institutions conducting quantitative surveys, 100 out of the 195 institutions 
stated that they follow up on their graduates more than once. For qualitative surveys this 
was 8 out of 26.  

Figure 9.  Frequency of follow-ups for quantitative and quantitative surveys 

46%

38%

41%

42%

33%

29%

39%

25%

13%

13%

50%

40%

30%

20%

10%

0%

3%

0%

2%

0%

2%

0%

2%

0%

4%

3%

Quantitative surveys

Qualitative surveys

Source: ICF graduate tracking higher education institution survey (quantitative survey 
N=195; qualitative survey N=24).  

6.2.5  Sampling and response rates 

More than four out of five survey respondents (83%) stated that their quantitative 
survey target the total graduate population instead of a sample. About 7% stated they 
targeted a total graduate population with a more specific definition (e.g. excluding those 
living abroad). Only 10% employ a formal sampling technique or use a convenience 
sample.  

Where a higher education institution’s survey has used a sample, there is a reasonably 
equal mix of sampling approaches used in both quantitative and qualitative surveys, as 
shown in the table below. For quantitative surveys, stratified sampling was the most 
popular technique (used by 40% of higher education institutions), which is often the 
most rigorous approach to collecting high quality and representative survey data from a 
sample.  

higher education institutions most commonly did not use a formal sampling approach 
when using qualitative surveys (i.e. they achieved a convenience sample of graduates 
that were easy to reach) or used purposive sampling with criteria determined by the 
researcher(s).  

March, 2020 

75 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 38.   Sampling techniques employed by higher education institutions 

Sampling approach 

Higher education 
institutions that 
conduct quantitative 
surveys 

Higher education 
institutions that 
conduct qualitative 
surveys 

% 

No. 

% 

No. 

Stratified random sampling  40% 

Random sampling 

Purposeful sampling 

28% 

N/A 

19 

13 

N/A 

14% 

24% 

27% 

9 

15 

17 

No formal sampling 
approach (convenience 
sample) 

32% 

15 

35% 

22 

Total 

100% 

47 

100% 

63 

Source: ICF graduate tracking higher education institution survey (quantitative survey 
N=47; qualitative survey N=63) 

There is considerable variation in the response rates that higher education institutions 
reported that they received to their quantitative surveys. Around one third of higher 
education institutions (31% of 468 higher education institutions that responded to this 
question) received a response rate to their graduate survey that was lower than 30% of 
their student population, which can be problematic when generalising findings if the 
overall size of the graduate population is relatively small. Nearly half (48%) of higher 
education institutions obtained more favourable response rates to their graduate surveys 
of above 50%, and around a quarter (27%) achieved a response rate of above 70%, 
which would provide data for robust statistical analysis.  

The figure below shows that higher education institutions that only distributed their 
graduate tracking survey online often achieved a lower response rate compared to higher 
education institutions that used more than one survey method, particularly where the 
survey was administered via telephone too. Some of the counts for this breakdown are 
low so results should be treated with caution but whereas 75% of higher education 
institutions using only online methods have failed to achieve a 50% response rate, only 
around 28% of those using online and telephone failed to achieve 50%.  

March, 2020 

76 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 10. Quantitative survey response rates by method(s) used 

29

31

80

96

s
n
o
i
t
u
t
i
t
s
n

i

n
o
i
t
a
c
u
d
e
r
e
h
g
h
f
o
r
e
b
m
u
N

i

6

4

20

4

1

3

2

34

58

27

8

10

13

4

1

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

10

6

2

Online survey
only (n=236)

Online and
paper-based
survey (n=34)

Paper-based
survey only
(n=6)

Online and
telephone
survey (n=127)

Telephone
survey only
(n=28)

Online,
telephone and
paper-based
survey (n=18)

Response rate of 25% or less

Response rate of 26%-50%

Response rate of 51%-75%

Response rate of 76% or more

Source: ICF graduate tracking higher education institution survey (N=number of respondents 
shown above). ‘Don’t know’ responses and item non-responses removed from the analysis.  

Further analysis of the graduate survey response rates achieved by size of higher 
education institution is presented in the figure below. It shows that about a third (32%) 
of small higher education institutions with 5,000 or less enrolled students achieved 
response rates to their surveys of more than 75% from their intended population of 
graduates. It is possible that smaller institutions are able to reach their overall target 
graduate population more easily. However, about one in five (22%) of the larger higher 
education institutions with more than 25,000 enrolled students also achieved a response 
rate above 75%, while medium sized higher education institutions typically had lower 
response rates to their graduate tracking surveys. It is possible that the largest 
institutions often have more resources and capability to invest in achieving high response 
rates to surveys than medium sized institutions.   

Figure 11. Quantitative survey response rates by size of higher education institution 

HEIs with more than 25,000 students

20%

29%

30%

15%

7%

HEIs with 15,001-25,000 students

32%

34%

21%

13%

0%

HEIs with 5,001-15,000 students

29%

31%

29%

6%

5%

HEIs with 5,000 or less students

19%

26%

22%

21%

11%

0%

20%

40%

60%

80%

100%

Response rate of 25% or less
Response rate of 51-75%
Response rate of 91% or more

Response rate of 26-50%
Response rate of 76-90%

Source: ICF graduate tracking higher education institution survey (5,000 or less: N=140, 
5,001-15,000: N=157, 15,001-25,000: N=71, More than 25,000: N=91).   

March, 2020 

77 

 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

6.2.6  The organisation, administration and management of the surveys 

Both quantitative and qualitative surveys were predominantly organised and delivered by 
in-house staff as opposed to an external organisation. A lower proportion of responding 
higher education institutions using quantitative surveys said their institution’s survey was 
conducted by in-house staff (73%) than for qualitative surveys (87%). This is not 
surprising given that quantitative surveys typically require more resources and technical 
expertise that some universities may not have.  

Graduate tracking surveys in a large proportion of higher education institutions are 
administered by quality assurance staff. Overall, 26% of higher education institutions 
using quantitative surveys said they were administered by quality assurance staff, and a 
similar proportion were administered by quality assurance staff for higher education 
institutions using qualitative surveys (25%). Alumni liaison services also played a 
prominent role, with 14% of respondents using quantitative surveys and 21% using 
qualitative surveys reporting their responsibility for administering tracking measures. 75 
higher education institutions reported using the careers service to administer their 
surveys.  

Quality assurance staff also often manage graduate tracking surveys in addition to 
administering them (this was the case for 30% of respondents using quantitative 
surveys, and 25% using qualitative surveys). Alumni Liaison teams also manage 
graduate tracking surveys relatively commonly (13% for quantitative surveys and 21% 
for qualitative surveys). 82 higher education institutions reported using the careers 
service to manage their surveys.  

Table 39.  Administering and managing of surveys 

Organisation 
responsible  

Administering tracking 
measure 

Managing tracking 
measure 

Quantitative 
surveys 

Qualitative 
surveys 

Quantitative 
surveys 

Qualitative 
surveys 

No.  % 

No.  % 

No.  % 

No.  % 

Quality assurance 
staff 

91 

26%  17 

26%  142 

30%  19 

25% 

Alumni liaison team  50 

14%  14 

21%  62 

13%  16 

21% 

Registrar's office 
team 

Head(s) of 
department 

30 

9% 

7 

11%  31 

7% 

8 

11% 

6 

2% 

4 

6% 

15 

3% 

5 

7% 

Head(s) of faculty 

6 

2% 

6 

9% 

9 

2% 

5 

7% 

Senior leadership 
team 

Course tutors 

5 

3 

1% 

2 

3% 

20 

4% 

6 

8% 

1% 

2 

3% 

3 

1% 

2 

3% 

March, 2020 

78 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Organisation 
responsible  

Administering tracking 
measure 

Managing tracking 
measure 

Quantitative 
surveys 

Qualitative 
surveys 

Quantitative 
surveys 

Qualitative 
surveys 

No.  % 

No.  % 

No.  % 

No.  % 

Other 

15784  45%  1485 

21%  19386  41%  1587 

20% 

Source: ICF graduate tracking higher education institution survey  

6.3  Use of administrative data 

6.3.1  Graduate population coverage in data matching  

At least nine out of ten higher education institutions responding to the survey that used 
administrative data matching as a tool tracked graduates at ISCED level 6 and level 7. 
This is similar to the coverage of quantitative and qualitative surveys. Almost half of the 
responses included ISCED level 8 but few covered ISCED level 5. 

Table 40.  ISCED levels included in data matching 

Higher education institutions 
that conduct data matching 

ISCED level covered in tracking 
measure 

 ISCED level 5 (Short-cycle tertiary 
education) 

 ISCED level 6 (Bachelor degree or 
equivalent) 

% 

15% 

95% 

 ISCED level 7 (Master degree or equivalent)  90% 

 ISCED level 8 (Doctoral degree or 
equivalent) 

48% 

No. 

16 

103 

97 

52 

Source: ICF graduate tracking higher education institution survey (N= 106). Multiple 
choice question.  

Most of the higher education institutions tracking their graduates through data matching 
only cover graduates that have completed their course and live in the country where they 
have studied. Only 10% of respondents to this question stated that they used data 
matching for students that left without graduating, and only 16% reported that it 
covered students living abroad. 

6.3.2  Frequency of tracking 

Most (69%) institutions that conduct data matching do so every year. It is very 
uncommon for institutions to only follow up every four or five years, and only 13% do it 
as and when required. 

84 75 out of 157 using “other” reported using the careers service 
85 8 out of 14 using “other” reported using the careers service 
86 82 out of 193 using “other” reported using the careers service 
87 8 out of 15 using “other” reported using the careers service 

March, 2020 

79 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 41.   Frequency of graduate tracking using data matching 

Frequency of data collection 

Higher education institutions 
that conduct data matching 

Every year 

Every two years 

Every three years 

Every four years 

Every five years 

As and when required 

Total 

% 

69% 

8% 

8% 

1% 

1% 

13% 

100% 

No. 

73 

8 

9 

1 

1 

14 

106 

Source: ICF graduate tracking higher education institution survey (N = 106).   

6.3.3  Stage at which tracking is collected and the use of follow-up tracking 

Overall, most higher education institutions (71%) start collecting information about 
graduates through data matching within 18 months of their graduation, and almost a 
quarter (23%) collect information between 12 and 18 months after completion.  

Table 42.  Stage at which gradate tracking is first conducted using data matching 

Period after completion when tracking 
information is collected 

Higher education institutions 
that conduct data matching 

Immediately after completion 

Within three months 

After 3-6 months 

After 6-12 months  

After 12-18 months 

After 18 – 24 months 

After 2-3 years 

After 3-5 years 

After 5+ years  

Other88 

Total 

% 

13% 

4% 

10% 

20% 

24% 

6% 

5% 

5% 

3% 

11% 

100% 

No. 

14 

4 

10 

21 

25 

6 

5 

5 

3 

11 

104 

88 Responses under “other” included: initial time of tracking is dependent on department, tracking is conducted 
continuously 

March, 2020 

80 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Source: ICF graduate tracking higher education institution survey (N = 104). Percentages 
may not sum to 100% due to rounding.  

Less than half of higher education institutions responding to the survey who use data 
matching to track their graduates repeated the exercise to track the same graduates 
over time (43 out of the 104 higher education institutions that responded to this 
question). Where follow-up data is collected, over half follow-up over multiple time 
periods and most do so again within the first five years after graduation. The figure 
below shows the time points at which higher education institutions typically collect data.  

Figure 12. Frequency of follow ups for data matching 

50%

50%

45%

45%

24%

60%

50%

40%

30%

20%

10%

0%

5%

2%

5%

5%

7%

Source: ICF graduate tracking higher education institution survey (N = 42). Multiple 
choice question.  

6.3.4  Sampling  

Almost four-fifths (78%) of higher education institutions use data for their total graduate 
population in a given cohort to conduct data matching. About 14% used a narrower 
definition of their total graduate population with some graduates removed such as those 
living abroad). Only 8% conducted data matching on a sample of graduates.  

6.3.5  The organisation, administration and management of data matching 

The organisation and delivery of data matching was usually done by in-house staff (66%) 
as opposed to external organisations (33% of higher education institutions).  

Over a quarter of higher education institutions responding to this question use quality 
assurance staff to administer data matching (28%). A relatively high proportion of data 
matching measures are also managed by the Registrar’s office team (21%). The use of 
other institutions to administer data matching was reported by 25% of respondents, with 
8 out of the total 18 of these responses referring to the use of the higher education 
institution’s careers service. These departments are also most commonly responsible for 
managing data matching tracking exercises. 

6.3.6  External data sources used 

Most higher education institutions conducting administrative data matching use 
government employment data to match their institution data on graduates (71%). 
Relatively few (17%) use government tax data and only 12% use data collected by 
commercial organisations. Over a fifth (23%) of survey respondents said their higher 
education institution used other external data sources, which included data collected 
from employers and social media such as LinkedIn. 

March, 2020 

81 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 43.   External data sources used to match institution data on graduates 

Data source 

Higher education institutions 
that conduct data matching 

Government employment data 

Government tax data 

Data collected by commercial organisations  

(e.g. recruitment companies) 

Other 

None 

% 

71% 

17% 

12% 

23% 

13% 

No. 

79 

19 

13 

25 

15 

Source: ICF graduate tracking higher education institution survey (N= 112). Multiple choice 
question.  

6.4  Use of data mining 

6.4.1  Graduate population coverage in data mining 

At least three quarters of higher education institutions using data mining to track their 
graduates target graduates who studied at ISCED levels 6 and 7. Just under half of them 
include ISCED level 8 with much fewer including ISCED level 5 graduates. This is similar 
to the approach to undertaking surveys and data matching.  

Table 44.  ISCED levels covered in data mining 

ISCED level covered in tracking measure 

Higher education 
institutions that conduct 
data mining 

% 

No. 

 ISCED level 5 (Short-cycle tertiary education)  11% 

 ISCED level 6 (Bachelor degree or 
equivalent) 

76% 

 ISCED level 7 (Master degree or equivalent)  92% 

 ISCED level 8 (Doctoral degree or equivalent)  45% 

8 

56 

68 

33 

Source: ICF graduate tracking higher education institution survey (N = 74). Multiple 
choice question.  

Over half (53%) of the higher education institutions that conduct graduate tracking 
through data mining aimed to capture information on both graduates and former 
students who have migrated to another country after leaving the institution. However, 
less than a quarter include former students who left without graduating. This is not 
surprising given that this group are likely to be harder to capture through data mining 
techniques, such as social media data web scraping, if these former students do not 
mention the institution or course they dropped out of.  

March, 2020 

82 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

6.4.2  Frequency of tracking 

Over two-thirds (70%) of higher education institutions conducting data mining to track 
their graduates do so every year. However, a fifth of survey respondents stated that they 
conduct it as and when it is required.  

Table 45.  Frequency of graduate tracking using data mining 

Frequency of data collection 

Higher education institutions 
that conduct data mining 

Every year 

Every two years 

Every three years 

Every four years 

Every five years 

As and when required 

Total 

% 

70% 

3% 

5% 

0% 

1% 

20% 

100% 

No. 

52 

2 

4 

0 

1 

15 

74 

Source: ICF graduate tracking higher education institution survey (N= 74).  

6.4.3  Stage at which tracking is first collected and follow-ups 

Over three-quarters (76%) of survey respondents said their higher education institutions 
start collecting information about graduates through data mining within 18 months of 
graduation, and more than a quarter (28%) conduct it immediately after graduates 
complete their study. Only 2% of institutions start to collect tracking more than three 
years after study completion.  

Table 46.  Stage at which graduate information is first collected using data mining 

Period after completion when tracking 
information is collected 

Higher education institutions 
that conduct data mining 

Immediately after completion 

Within three months 

After 3-6 months 

After 6-12 months  

After 12-18 months 

After 18 – 24 months 

After 2-3 years 

After 3-5 years 

After 5+ years 

% 

28% 

10% 

14% 

17% 

7% 

4% 

3% 

1% 

1% 

No. 

20 

7 

10 

12 

5 

3 

2 

1 

1 

March, 2020 

83 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Period after completion when tracking 
information is collected 

Higher education institutions 
that conduct data mining 

Other89 

Total 

% 

14% 

100% 

No. 

10 

71 

Source: ICF graduate tracking higher education institution survey (N = 71). Percentages 
may not sum to 100% due to rounding.  

Just under half (49%) of higher education institutions conducting data mining collect 
follow up information on the same graduates over time. When they do follow-up with 
graduates, most collect data one year after the initial stage of tracking. Fourteen out of 
the 21 higher education institutions that conduct follow up tracking using data mining 
follow up over more than one time period.  

Figure 13. Frequency of follow ups for data mining 

63%

70%

60%

50%

40%

30%

20%

10%

0%

33%

30%

30%

17%

17%

7%

3%

3%

3%

Source: ICF graduate tracking higher education institution survey (N=30). Multiple choice 
question.   

6.4.4  The organisation, administration and management of data mining 

The organisation and delivery of data mining is typically undertaken by in-house staff 
(reported by 92% of respondents). Only six respondents reported that they use an 
external organisation.  

Similar to other institutional graduate tracking measures, data mining is commonly 
administered by alumni liaison teams (36%). About a third (29%) indicated that they use 
other institutions to manage it. 8 out of the 21 higher education institutions using other 
institutions stated that they used the careers service to administer surveys. 

89 Examples of responses in “other” include: as and when required, during their studies 

March, 2020 

84 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

6.5  Information collected in higher education institution graduate 

tracking measures 

6.5.1  Data collected in surveys 

Employment outcomes are most commonly collected in quantitative and qualitative 
surveys. This includes data on employment status, type of employment and matching 
between job and qualification. These variables are collected in over 80% of quantitative 
surveys and over 70% of qualitative surveys. 

For quantitative surveys, other variables commonly collected include duration of 
employment, salary level, length of job search and satisfaction with job and higher 
education institution. Data on these variables is collected in around 65-75% of surveys.  
For qualitative surveys over half collect information on graduates’ satisfaction with their 
job, the higher education institution (including the teaching in the institution), and 
duration of their employment. 

Relatively few quantitative and qualitative graduate tracking surveys collect information 
on participation in volunteering or civic/community activities and reasons for pursuing 
further education.  

Table 47.  Data collected in surveys 

Information collected 

Higher 
education 
institutions 
that conduct 
quantitative 
surveys 

Higher 
education 
institutions 
that conduct 
qualitative 
surveys 

% 

No.  % 

No. 

Employment status (employed/not 
employed) 

99% 

481 

86% 

64 

Type of employment (permanent/temporary; 
part-time/full time; employment 
contract/self-employed, other) 

Matching between job and qualification (job 
fits obtained qualification / job requires 
another qualification / job below 
qualification/skill set) 

89% 

433 

74% 

55 

83% 

404 

73% 

54 

Salary level 

77% 

374 

53% 

39 

Length of job search after graduation (first 
job/good job) 

73% 

358 

39% 

29 

Duration of employment/unemployment 
(employed/unemployed since ...) 

72% 

352 

58% 

43 

Satisfaction of graduates with current job 

70% 

341 

59% 

44 

Satisfaction of individuals with the 
educational institution 

64% 

314 

54% 

40 

Matching between position and level of 
education 

64% 

313 

59% 

44 

March, 2020 

85 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Information collected 

Higher 
education 
institutions 
that conduct 
quantitative 
surveys 

Higher 
education 
institutions 
that conduct 
qualitative 
surveys 

% 

No.  % 

No. 

Participation in further education or training 
pathways 

59% 

289 

35% 

26 

Satisfaction rate of individuals with 
instruction received (acquired 
skills/competences) 

58% 

285 

53% 

39 

Further qualifications achieved 

46% 

225 

41% 

30 

Satisfaction with income / salary level 

41% 

202 

31% 

23 

Satisfaction of individuals with the form of 
delivery of curriculum 

41% 

200 

39% 

29 

Other 

40% 

194 

34% 

25 

Reasons for pursuing further education 

36% 

175 

36% 

27 

Participation in volunteering or 
civic/community activities 

23% 

113 

19% 

14 

Source: ICF graduate tracking higher education institution survey (quantitative survey 
N=488; qualitative survey N=74). Multiple choice question.  

6.5.2  Data collected through administrative data matching 

The most common indicators collected through data matching are employment status 
(reported by 93% of respondents) followed by type of employment and salary level. As 
might be expected, few higher education institution’s matching datasets on their 
graduates  capture data to assess  satisfaction of employers with skills/competences, 
satisfaction of individuals with the form of delivery of curriculum (unless they match 
survey responses), participation in volunteering or civic/community activities, and 
reasons for pursuing further education. 

It is more common for survey methods across different higher education institutions to 
collect similar types of data than matching methods. The majority of surveys collect data 
on most of the indicators included in the above tables, whereas there is a wider 
discrepancy in the data collected in data matching. This could be due to variations in 
quality of the administrative data used to match graduate outcomes across countries and 
higher education institutions. It would also be more difficult to collect more subjective 
data on satisfaction rates using matching than with surveys.  

March, 2020 

86 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Table 48.  Data collected through data matching 

What information is collected? 

Higher education 
institutions that 
conduct data 
matching 

% 

No. 

Employment status (employed/not employed) 

93% 

100 

Type of employment (permanent/temporary; part-time/full 
time; employment contract/self-employed, other) 

72% 

77 

Salary level 

Duration of employment/unemployment 
(employed/unemployed since ...) 

58% 

61 

55% 

58 

Matching between job and qualification (job fits obtained 
qualification / job requires another qualification / job below 
qualification/skill set) 

48% 

51 

Length of job search after graduation (first job/good job) 

41% 

Matching between position and level of education 

32% 

Participation in further education or training pathways 

30% 

Satisfaction of individuals with the educational institution 

26% 

Further qualifications achieved 

Satisfaction of graduates with current job 

Satisfaction with income / salary level 

26% 

25% 

23% 

43 

34 

32 

28 

28 

27 

24 

Satisfaction rate of individuals with instruction received 
(acquired skills/competences) 

Other 

Reasons for pursuing further education 

Satisfaction of individuals with the form of delivery of 
curriculum 

22% 

23 

21% 

12% 

22 

13 

11% 

12 

Participation in volunteering or civic/community activities 

9% 

10 

Source: ICF graduate tracking higher education institution survey (N = 106). Multiple 
choice question.  

6.5.3  Data collected through data mining 

Data mining is mostly used to collect information on employment status (reported by 
86% of respondents). Over a third of respondents said they collect information on 
graduates’ type of employment and matching the fit between graduates’ job and 
qualification. Less than a quarter of institutions collect any data on satisfaction with 
income/salary level, length of job search, and satisfaction rate of employers with 
acquired skills/competences. This information is collected far more frequently in the 

March, 2020 

87 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

surveys, which is to be expected given that those research methods are better suited to 
collecting these kinds of variables.  

Table 49.  Data collected through data mining 

What information is collected? 

Higher 
education 
institutions 
that conduct 
data mining 

% 

No. 

 Employment status (employed/not employed) 

86% 

59 

 Type of employment (permanent/temporary; part-time/full 
time; employment contract/self-employed, other) 

54% 

37 

 Matching between job and qualification (job fits obtained 
qualification / job requires another qualification / job below 
qualification/skill set) 

 Duration of employment/unemployment 
(employed/unemployed since ...) 

 Salary level 

43% 

30 

41% 

28 

41% 

28 

 Satisfaction of individuals with the educational institution 

41% 

28 

 Other 

 Satisfaction of graduates with current job 

 Further qualifications achieved 

38% 

26 

36% 

25 

36% 

25 

 Length of job search after graduation (first job/good job) 

30% 

21 

 Participation in further education or training pathways 

30% 

21 

 Matching between position and level of education 

26% 

18 

 Satisfaction rate of individuals with instruction received 
(acquired skills/competences) 

 Satisfaction with income / salary level 

 Satisfaction of individuals with the form of delivery of 
curriculum 

26% 

18 

25% 

17 

25% 

17 

 Participation in volunteering or civic/community activities 

25% 

17 

 Reasons for pursuing further education 

19% 

13 

Source: ICF graduate tracking higher education institution survey (N = 69). Multiple 
choice question.  

6.6  Main differences and commonalities between methods 

Some key differences and commonalities between different methods higher education 
institutions use to track their graduates are summarised below.  

March, 2020 

88 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Graduate population coverage of tracking measures: All methods focus on collecting 
data from ISCED levels 6 and 7. Across all methods, data mining is most likely to include 
graduates/former students who have migrated to another country after leaving their 
studies (53%).  

Timing and frequency of graduate tracking measures: For all methods, tracking is 
most commonly conducted every year for a new cohort of graduates. For quantitative 
surveys and data matching, it is most likely for higher education institutions to initially 
collect graduate tracking information 12-18 months after completing their study. Data 
mining is mostly undertaken immediately after graduates complete their studies. For 
qualitative surveys, there is a relatively even distribution across the different time points 
for initially contacting graduates. 

Organisation, administration and management of tracking measures: For all 
tracking methods, the majority of higher education institutions manage and deliver them 
in house. Across higher education institutions conducting quantitative surveys, qualitative 
surveys, and data matching, tracking methods are most commonly administered and 
managed in-house.  While there is some variation by method, in-house staff responsible 
for managing and administering graduate tracking measures are often either quality 
assurance staff, alumni liaison staff or careers service staff. 

Content of data collected: Quantitative and qualitative surveys are almost twice as 
likely to collect information on the satisfaction of graduates with their current job than 
data mining or data matching, which are less well suited to capturing such data unless 
surveys are part of the data matching. Quantitative surveys are also more likely to 
collect information on salary level and the length of job search after graduation than any 
other tracking method. Where tracking measures are conducted nationally at system 
level, matching administrative data may be a more reliable method to capture graduate 
salary data than self-reported survey results, but this analysis is typically not possible for 
individual higher education institutions to undertake. For all tracking methods, it is 
relatively uncommon for higher education institutions to collect data relating to graduate 
participation in volunteering or civic/community activities. This is surprising given the 
wider expectation of higher education institutions’ education and graduate outcomes. 

6.7  Availability and types of contact information held by higher 

education institutions 

Private email addresses are the most common type of contact information held by higher 
education institutions, with four out of five higher education institutions who responded 
having these details available to contact graduates, as shown in the table below. Three 
quarters (74%) of respondents said their higher education institution store more than 
one type of contact detail.  

Table 50.  Contact details stored on graduates 

Type of contact details 

 Private e-mail addresses 

 Telephone numbers 

 Institutional e-mail addresses 

 Home addresses 

All higher education 
institutions 

% 

80% 

61% 

54% 

50% 

No. 

493 

378 

330 

309 

Source: ICF graduate tracking higher education institution survey (N = 615). Multiple 
choice question.  

March, 2020 

89 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Graduate contact details are most often collected/updated when students enrol in their 
higher education institution. Almost three quarters (72%) of respondents said their 
higher education institution collects contact information at this point, dropping to 50% of 
higher education institutions that collect information when students are about to 
graduate, and 38% that collect information after students graduate. Nearly half 
collect/update details at multiple time points.   

6.8  How higher education institutions use graduate tracking data 

More than four out of five (85%) higher education institutions use the results from their 
graduate tracking measures for internal quality assurance purposes, as shown in the 
table below. This is perhaps unsurprising given that quality assurance teams most 
commonly manage and administer the tracking measure. Over half of survey 
respondents also reported that the results are used to support strategic planning, in 
external inspections, for marketing purposes, and/or to inform curriculum planning.   

Table 51.  How results are used across institutions 

How higher education institutions use graduate 
tracking data 

 For internal quality assurance 

 To support strategic planning 

 In external inspections, (re-)accreditation 

All higher education 
institutions that 
conduct graduate 
tracking 

% 

85% 

74% 

74% 

No. 

464 

409 

407 

 For marketing the institution to new students (e.g. 
promoting information on positive graduate outcomes 
and destinations) 

73% 

402 

 To inform curriculum planning 

 To inform departmental reviews 

 To inform staff performance reviews 

 Other 

66% 

38% 

17% 

7% 

364 

207 

93 

39 

Source: ICF graduate tracking higher education institution survey (N =549). Multiple 
choice question.  

Higher education institutions were asked to rate the impact the results of their graduate 
tracking had on different areas of their institution between 1 (no impact) and 5 (major 
impact), as shown in the figure below. This found that graduate tracking has the greatest 
impact on careers advice higher education institutions offer their students, where 47% of 
respondents thought it had a large impact (grade 4 or 5). Around a third (35%) reported 
it had a large impact on the range and scope of the courses their institution offers and 
30% reported it had a large impact on alumni contributions (e.g. financial donations to 
higher education institutions from former students).  

March, 2020 

90 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Figure 14. Impact of graduate tracking on different areas of higher education institutions  

Careers advice (n=487)

19%

28%

30%

14%

10%

The range and scope of the courses your
institution offers (n=478)

10%

25%

35%

19%

13%

Alumni contributions (n=474)

10%

20%

33%

19%

18%

0%

20%

40%

60%

80%

100%

5 - major impact

4

3

2

1 - no impact

Source: ICF graduate tracking higher education institution survey. N=number of 
respondents answering each question.  

Higher education institutions were also asked about the methods they employed to 
benchmark the results of their graduate tracking measures. Three quarters of higher 
education institutions compare performance with previous years (77% of respondents) 
and half (52%) also compare the results of institutional tracking with national tracking 
survey data, while over a third (37%) compare their results with other higher education 
institutions or across different departments (44%).  

Table 52.  Benchmarking the results of graduate tracking measure 

Benchmarking approach 

All higher 
education 
institutions that 
conduct graduate 
tracking 

% 

No. 

 Compare performance with previous years 

77% 

392 

 Compare results with national tracking survey data 

52% 

263 

 Compare graduates in different departments 

44% 

224 

 Compare results with other individual higher education 
institutions 

37% 

189 

 Compare particular groups of programmes 

35% 

179 

 Other 

 No comparison done 

11% 

11% 

57 

57 

Source: ICF graduate tracking higher education institution survey (N = 510). Multiple 
choice question.  

6.9  Reasons for not undertaking graduate tracking 

The most common reason why respondents reported that their higher education 
institutions does not conduct graduate tracking is a lack of available resources. In the 
survey, 14 of the 34 respondents for higher education institutions that do not conduct 
graduate tracking stated this was a high influence (rated 5 on a scale of 1-5). A further 

March, 2020 

91 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

10 stated a major reason why their institution does not do graduate tracking is because 
they could access relevant data from national organisations running national graduate 
tracking initiatives instead. Only three respondents stated that they do not conduct any 
institutional graduate tracking because they did not feel it would bring any value.  

Table 53.  Influence of factors in choosing to not conduct tracking 

Factor 

Can get the information from 
national organisations running 
national initiatives* 

Higher education institutions that do 
not conduct graduate tracking 

1 – no 
influen
ce 

2 

3 

4 

5 – high 
influenc
e 

12 

3 

4 

5 

10 

Do not believe there is a value in 
it** 

26 

We do not have the resources to do 
it*** 

5 

We do not believe it provides good 
quality data**** 

Tutors are disinclined to 
participate***** 

25 

24 

0 

2 

1 

1 

2 

4 

4 

3 

1 

8 

0 

0 

2 

14 

2 

1 

Source: ICF graduate tracking higher education institution survey (*N=34, **N=31, 
***N=33, ****N=32, *****N=29) 

6.10  Key summary points 

The survey has identified that graduate tracking is generally well-embedded in 
higher education institutions across EU and EEA countries: 

  Four out of five survey respondents said their higher education institution hold 

private email addresses for their graduates, while only half said they store home 
address contact details.  

  More than nine out of ten survey respondents said their higher education 

institution undertakes some form of graduate tracking. The existence of good 
measures at national level appears to save resources for higher education 
institutions in some countries that are less likely to undertake institutional 
graduate tracking. Examples include the UK and Norway. 

Most higher education institutions reported that they undertook a questionnaire 
survey to which they invited cohorts of graduates for whom they had contact 
details to complete online.   

  Quantitative surveys are the most common form of graduate tracking and are 
used by more than four out of five higher education institutions, typically 
administered online. Smaller higher education institutions are more likely to 
conduct qualitative surveys such as interviews and focus groups.  

  About three fifths of higher education institutions only use one tracking measure. 

Where higher education institutions use qualitative surveys or match 
administrative data this is often in addition to a quantitative survey of their 
graduates.  

March, 2020 

92 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Higher education institutions typically limit their tracking to former students who 

complete their studies and remain in the same country. Graduates from 
programmes at ISCED levels 6 and 7 are most commonly included.  

The quality of institutional tracking varies considerably.  

  For quantitative graduate tracking surveys, around two thirds of higher education 
institutions said they use some form of random sampling and nearly half said they 
achieve a response rate of 50% or more. However, around a third of those 
sampling use a convenience sample. 

  Sampling may account for some of the poor level of response higher education 

institutions receive to their quantitative surveys. For around a third it is reported 
to be lower than 30%. Under half (43%) of higher education institutions graduate 
surveys obtain more favourable response rates above 50%. Around a quarter 
(25%) achieve a response rate of above 70%, which would provide sufficient data 
for detailed sub-group analysis (by programme and graduate characteristics).  

  Higher education institutions that only distribute their graduate tracking survey 
online more often achieve a lower response rate compared to higher education 
institutions that use more than one survey method, particularly where the survey 
is administered via telephone too. Three quarters of higher education institutions 
using only online methods failed to achieve a 50% response rate compared to just 
under a third (28%) of those using online and telephone. 

  A little over two thirds of higher education institutions implement their tracking 
measure within 18 months of graduation. The majority of higher education 
institutions do not track their graduates over more than one time period to collect 
longitudinal data.  

Tracking measures most commonly capture data on graduates’ employment 
status, job level and salary.  

  Less than a quarter of higher education institutions using each type of tracking 
measure capture data on participation in volunteering or civic/community 
activities, and similarly reasons for pursuing further education was a measure 
much less commonly collected by individual higher education institutions.  

  Overall, collected data typically has a larger impact on the careers’ advice higher 
education institutions give their students than other areas, such as the range and 
scope of courses they offer or financial contributions from alumni.  

  About three quarters of higher education institutions said they use their 

institutional graduate tracking data to inform strategic planning, internal quality 
assurance and/or external inspection.  

March, 2020 

93 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

7 

Conclusions 

In this final chapter, the first section considers what the findings of the study set out in 
chapters 2-6 indicate for each of the research questions. The second section draws out 
the implications for the work of the Expert Network and the Commission. This is followed 
by some potential recommendations for their consideration. 

7.1  Addressing the research questions 

7.1.1  What is the general coverage of graduate tracking at system level, both of 
higher education and vocational education and training graduates? 

There is a strong policy driver and impetus in most but not all countries to 
implement graduate tracking. This has resulted in a range of recent and planned 
developments in many countries to improve their graduate tracking, although 
some are not at an advanced stage of implementation. 

Graduate tracking is a policy objective in 24 countries and a legal obligation in 16 
countries, out of the 32 EU Member States and EEA countries. Countries where graduate 
tracking is a legal obligation, tend to have system-level tracking. For vocational 
education and training, this is the case in DK, EE, ES, FI, FR, HU, IT, NL, PT and SE. For 
higher education, this is the case in AT, DE, DK, EE, FI, FR, HU, IT, PL, SE and UK. In LV, 
there is a legal obligation covering both vocational education and training and higher 
education and graduate tracking measures are currently being developed for the two 
sectors. This is summarised in the tables below. 

However, a legal background is not a necessary condition for regular graduate tracking. 
Countries where graduate tracking is among policy objectives, tend to have system-level 
tracking, even in the absence of a legal obligation to track. For vocational education and 
training, this is the case in AT, BE-FR, IE, LT, SK and UK. For higher education, this is the 
case in CZ, ES, IE, LT, NL, and SK. In BG graduate tracking is among policy objectives in 
vocational education and training, and a system-level measure covering vocational 
education and training graduates is currently being piloted. In BE-FR and SI graduate 
tracking is among policy priorities in higher education and system-level measures to 
track higher education graduates are under development. HR, MT and RO also refer to 
graduate tracking in their policy objectives but these countries have only conducted pilot 
studies or one-off initiatives.  

In a few countries, system-level graduate tracking is an established practice even if not a 
legal obligation or policy priority. In vocational education and training, this is the case in 
BE-NL, CZ, DE, LU, and NO. In higher education, this is the case in BE-NL and NO. 

Table 54.  Graduate tracking as policy objective and legal requirement. Vocational 
education and training (initial vocational education and training and/or 
continuing vocational education and training) 

System level tracking  Policy objective 

Legal obligation 

AT 

BE-FR 

BE-NL 

BG 

CY 

Yes 

Yes 

Yes 

No – ongoing pilot   

No 

Yes 

Yes 

No 

Yes 

No 

No 

No 

No 

No 

No 

March, 2020 

94 

 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

System level tracking  Policy objective 

Legal obligation 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

Yes 

Yes 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

No 

Yes 

Yes 

No 

Yes 

No 

Yes 

Yes 

No 

No 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

Yes 

No 

Yes 

No 

Yes 

No 

No - under development 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

No 

No – under development  No 

Yes 

No – recent pilots 

Yes 

No 

Yes 

Yes 

No 

Yes 

Yes 

No 

Yes 

Yes 

No 

No 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

No 

No 

No 

No 

Yes 

No 

No 

No 

Yes 

No 

Yes 

No 

No 

Yes 

No 

Yes 

No 

No 

No 

Source: mapping research conducted by ICF, 3s and CHEPS 

Table 55.  Graduate tracking as policy objective and legal requirement. Higher education 

System level tracking  Policy objective 

Legal obligation 

AT 

BE-FR 

BE-NL 

BG 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

No 

Yes 

Yes 

No 

No 

No 

March, 2020 

95 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

System level tracking  Policy objective 

Legal obligation 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

No 

Yes 

Yes 

Yes 

Yes 

No – participated in 
Eurograduate survey 

Yes 

Yes 

Yes 

No – participated in 
Eurograduate survey 

Yes 

Yes 

No 

Yes 

No 

Yes 

No90 

No – under 
development 

No – participated in 
Eurograduate survey 

Yes 

Yes 

Yes 

No 

No 

Yes 

No 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

Yes 

No 

No 

No 

Yes 

No 

Yes 

Yes 

Yes 

No 

Yes 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

No 

No 

Yes 

Yes 

Yes 

No 

No 

Yes 

Yes 

No 

Yes 

No 

No 

Yes 

No 

No 

No 

Yes 

No 

No 

No 

Yes 

No 

No 

Yes 

No 

No 

Yes 

Source: mapping research conducted by ICF, 3s and CHEPS 

90 Note: In Luxembourg no evidence has been found of higher education graduate tracking at system level. 
However, the only Luxembourgish higher education institution that falls within the scope of this study -the 
University of Luxembourg- conducts an annual survey to track its graduates. Therefore, it can be considered that 
the country does in fact track its graduates and has an established graduate tracking practice. 

March, 2020 

96 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

At present, system-level graduate tracking is in place for vocational education and 
training in 20 countries: AT, BE-FR, BE-NL, CZ, DE, DK, EE, ES, FI, FR,  IE, IT, LT, LU, 
NL, NO, PT, SE, SK and UK. For higher education, it is in place in 20 countries: AT, BE-
NL, BG, CZ, DE, DK, EE, ES, FI, FR, HU, IE, IT, LT, NL, NO, PL, SE, SK and UK. 

Three countries are taking clear steps towards the implementation of systematic 
graduate tracking in vocational education and training (BG, LV) or higher education (LV, 
SI). In BE-FR a new measure to track higher education graduates was announced in 
2014 but has not yet been launched. In LI and PL (vocational education and training) 
new measures have been announced or are currently under discussion but there it is little 
evidence of concrete developments so far. 

In HR, MT, RO, there have been pilot studies or one-off graduate tracking initiatives, but 
systematic tracking is not likely to be in place in the near future. In the remaining 
countries, there have been no recent efforts towards the development of system-level 
graduate tracking where it is unavailable: in higher education and vocational education 
and training (CY, EL, IS) or in higher education (PT).  

The abundance of tracking measures contrasts with their considerable 
differentiation and limited coordination 

Most countries have a variety and range of tracking measures which broadly divide 
between using either surveys or administrative data. There are as many as nine national 
measures at system-level in one country, covering different sectors and different 
graduate populations, and using different data collection approaches to cover the same 
sector or graduate population. In addition, several countries have measures at the 
regional level, and all countries have a multitude of measures at institutional level in both 
higher education and vocational education and training. However, there are often weak 
or no links between the design of tracking measures by different organisations. 
Mechanisms to ensure the complementarity of tracking measures have only been 
identified in ten countries.91  

Having convergence of the different measures in a country is a precondition to enabling 
comparability. This can be done, for instance, by formulating key survey questions in the 
same way for higher education and vocational education and training graduates, or 
graduates in different programmes, higher education institutions or regions.  

Complementary measures can also increase the efficiency of graduate tracking by 
avoiding the collection of similar information from the same individuals more than once 
e.g. through administrative data and surveys; or through surveys implemented at 
system and institutional level. In the case of surveys, redundant data collection 
contributes to ‘survey fatigue’ and lower response rates for repeated cycles of surveys 
which are widely reported.  

Some countries have implemented mechanisms to enhance the complementarity of 
system-level measures, and the synergies of these measures with those undertaken at 
institutional or other levels. For instance, in the Netherlands, there is mutual consultation 
on the design of the main graduate surveys, resulting in a convergence of questions at 
national level. Several countries offer higher education institutions or other entities 
(trade unions, regional authorities) the opportunity to include their own questions in 
tracking surveys.92 Such initiatives could be used as inspiration for other countries to 
increase coherence and efficiency in graduate tracking.  

A specific case is that of the tracking measures of ESF-funded education and training, 
further discussed below.  

The quality of graduate tracking measures is variable 

91 DK, FI, FR, HU, IE, IT, LV, NL, RO and UK. 
92 DK, FI, HU, IT, NL, RO, UK. 

March, 2020 

97 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

There are different elements to the quality of tracking measures. The main key 
limitations include the lack of representativeness of the achieved sample due to low 
response rates and the use of convenience sampling with e-surveys;93 a limited coverage 
of graduate groups; and a limited coverage of the data collected.  

Low response rates are the most common difficulty faced in the implementation of 
graduate surveys and was identified in 18 system-level measures. Non-respondents may 
well be reluctant to participate if they have not obtained suitable employment or started 
an intended career. If they differ from those who participate in the survey, this has 
implications for the extent that they can infer from the sample to the target population. 
Also, low response rates hinder the analysis of disaggregated data for particular graduate 
subgroups (e.g. graduates from different programmes or with different socio-economic 
backgrounds). 

The use of convenience sampling is relatively common in graduate tracking: it was used 
in 12 of the system-level measures identified. This approach can leave out harder-to-
reach individuals and also limits the extrapolation of findings from the collected data to 
the full graduate population. 

Many countries are using more robust sampling techniques and have developed 
strategies and devoted resources to ensure high response rates from samples and whole 
populations. Often, high response rates are linked to the use of short survey 
questionnaires. Combining surveys and administrative data by matching individuals can 
help keep questionnaires short without losing relevant information on individuals’ 
trajectories after graduating. More factual data can be collected from administrative 
databases (e.g. on employment status, salary, etc.), and surveys can focus on the 
reasons behind career pathways and thus be kept shorter. 

Regarding the coverage of different graduate groups, continuing vocational education 
and training graduates are less often covered by tracking measures than higher 
education and initial vocational education and training graduates. Also, measures may 
not comprehensively cover all continuing vocational education and training programmes 
and providers (e.g. only those receiving ESF-funded training).94 Graduate tracking can 
however provide valuable data on continuing vocational education and training’s 
contribution to upskilling adults, and the resulting individual benefits and social and 
economic impact. One of the key features of the Cedefop analytical framework for 
developing upskilling pathways, is the establishment of overarching monitoring and 
evaluation systems;95 tracking data of continuing vocational education and training 
graduates could be a centrepiece of such systems.    

Only a minority of the system-level measures identified include graduates who move to 
another country after graduation. Tracking migrant graduates may be particularly 
relevant for countries and regions with high levels of graduates moving abroad. A recent 
study identified as the main ‘senders’ of skilled workers among EU countries BG, EE, HR, 
LV, LT, PL, PT, RO and SK, and as both strong ‘receivers’ and ‘senders’ IE and LU.96 
Particularly relevant would be to understand the trajectories of migrant graduates from 
science, technology, engineering, and mathematics (STEM) or other disciplines in 
high demand in the graduates’ country -or region- of origin. Such data could help 

93 This topic is also discussed in European Commission (2017). Mapping of vocational education and training 
graduate tracking measures in EU Member States. 
94 See also European Commission (2017). Mapping of vocational education and training graduate tracking 
measures in EU Member States. 
95 See Cedefop. Analytical framework for developing upskilling pathways for adults (Key Area 4). Available at: 
https://www.cedefop.europa.eu/files/cedefop_af_upskilling_pathways_20-21.05.2019.pdf (accessed on 
30/01/2020). 
96 European Commission (2018). Study on the movement of skilled labour. Available at 
https://ec.europa.eu/social/main.jsp?catId=738&langId=en&pubId=8156&furtherPubs=yes (accessed 
28/01/2020). 

March, 2020 

98 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

further understand what drives graduates to move and inform policy responses to 
brain flow.  

Regarding topic coverage, most of the measures identified collected data on employment 
status, further education and training pathways, and socio-biographical and 
socioeconomic information. However, only around half of the measures collected 
information on the relevance of acquired skills at the workplace and graduates’ 
satisfaction with the education received or the employment acquired. Such data is key to 
understand the match between graduates’ skills and the needs of the labour market. 

Also, only 13 out of 123 measures collected data on the participation of graduates in 
social and civic activities, including the Eurograduate survey and national measures from 
DE, FI and the UK.97 Social and civic activities are not only learning experiences -thus 
contributing to the update and further development of graduates’ skills- but also 
evidence the impact of education in society. Education at all levels has been considered 
key to the promotion of common values and social cohesion and the European Council 
has called Member States to improve ‘evidence-informed policy making on the social and 
civic dimensions of education and training’.98  Graduate tracking data can provide 
valuable insights into this dimension in vocational education and training and higher 
education but it seems this opportunity is rarely exploited. The module on social 
outcomes of the Eurograduate survey and the identified national examples could serve as 
inspiration to improve the measurement of the social impact of vocational education and 
training and higher education across the EU. 

Graduate tracking data is used to improve programmes’ alignment with labour 
market needs through a variety of mechanisms. However, tracking data needs 
to be contextualised and used with other data.  

Graduate tracking information can bring valuable insights to the labour market relevance 
of different programmes. Programmes consistently linked to high employment over 
several years, are likely to be better aligned with labour market needs. Other 
programmes may need to be adapted to increase their quality and the employability of 
their graduates. 

Over a third of the tracking measures identified in this study have been used to support 
curriculum design and improvement -including to ensure it is up to date- to improve 
graduate skills and employability (53 out of 123 measures). Education providers may 
receive support in this endeavour through external quality assurance. Graduate tracking 
results were part of external quality assurance in 26 measures. In this context, tracking 
results can also be used to prove that education programmes meet labour market needs 
for instance as part of (re)accreditation mechanisms. 

Graduate tracking results can also be linked to guidance tools or incentive mechanisms, 
such as performance-based funding (including as part of funding formulae) or 
performance or development agreements, linked or not to funding.99 Such mechanisms 
are used by governments to influence the policies of higher education institutions or 
vocational education and training providers and increase their performance in different 
areas, for instance, the labour market relevance of their programmes. Graduate tacking 
is used in these ways in 24 of the measures identified here. 

Tracking data is also currently used by 15 countries as part of their planning of course 
offers. This typically involves limiting student intake in programmes or fields whose 

97 DE (National Educational Panel Study NEPS, covering INITIAL vocational education and training and higher 
education), FI (Career monitoring for master's level graduates) and UK (Graduate Outcomes survey and College 
Leaver Destinations). Other examples include one-off measures or measures still under development. 
98 Council Recommendation of 22 May 2018 on promoting common values, inclusive education, and the 
European dimension of teaching (Official Journal of the European Union 7/6/2018, C 195/1). 
99 See discussion on the types of performance-based funding mechanisms in Claeys-Kulik & Estermann (2015). 
Define thematic report: Performance-based funding of universities in Europe. 

March, 2020 

99 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

graduates have historically and systematically experienced lower employment rates than 
those of graduates in general. Governments can put caps on the overall number of places 
offered in certain programmes or fields or the number of places that receive public 
funding. Public policies can also establish floors to encourage more graduates in certain 
areas.100 

The analysis of graduates’ employability needs to be contextualised, first and foremost by 
considering regional and local labour markets and the socio-economic background of 
student populations. For instance, benchmarking results of specific programmes and 
providers against local or regional averages can help contextualise and better understand 
results. However, from the 53 system-level measures examined that provided 
performance feedback to specific vocational education and training providers or higher 
education institutions, less than a third included other locally relevant benchmarking 
data. More information on how countries analyse and contextualise tracking results could 
help improve the use of tracking data across European countries. 

The EU is contributing to the development of graduate tracking at national level; 
strengthening synergies with national initiatives could increase the EU impact in 
this area. 

The European Structural and Investment Funds and Erasmus+ are co-funding some 
national graduate tracking measures, as well as pilots and one-off studies.101 Erasmus+ 
is also funding the Eurograduate pilot survey which covers eight European countries.102 
The participation in the Eurograduate study of countries where tracking is currently 
poorly developed (HR, EL, MT), is a sign that some attention is being given to the topic at 
national level and should be expected to lead to the creation of a regular tracking 
measure of higher education graduates in these countries.103 

Additionally, the ESF requires countries to follow up completers of ESF-funded education 
and training, to collect data on, at least, the employment status of participants six 
months after leaving the ESF-funded measure. Although there is some evidence that 
countries have started collecting this data, as required, in 2018, data collection seems to 
have run in parallel to other national-level tracking systems. The fact that it covers only 
the programmes and individuals who benefitted from ESF funds, may make its results of 
little relevance to national decision makers and it risks becoming a measure for the sole 
purpose of compliance with ESF requirements. Instead, having comparable data -based 
on linked tracking measures- on the employability of ESF-funded and other programmes, 
could provide valuable information on the impact of the programme. Furthermore, an 
ESF tracking system could potentially be used as a point of departure for more 
comprehensive tracking systems where these do not exist (CY and EL104).  

7.1.2  To what extent do national graduate tracking systems meet the 

requirements of the Council Recommendation on tracking graduates?  

Two thirds of countries have a relatively high level of compliance with the 
Recommendation to build on. Although only one country fully complies with it, 

100 See: OECD (2017), In-Depth Analysis of the Labour Market Relevance and Outcomes of Higher Education 
Systems: Analytical Framework and Country Practices Report, Enhancing Higher Education System 
Performance, OECD, Paris. 
101 The European Structural and Investment Funds are co-funding measure sin several countries (FI4, HR1, HU1, 
LT1, LT2, LV1). Erasmus+ is funding one pilot project in BG (BG1) and funded a one-off study in Malta (MT1).  
102 Eurograduate pilot study is being implemented in AT, HR, CZ, DE, EL, LT, MT and NO. 
103 Erasmus+ is also currently funding the project “OnTrack”, started in 2018, that seeks to develop a tracking 
system for graduates of vocational education and training and higher education institutions with applied study 
programmes. It focuses on countries where administrative data is mostly not available to follow graduates in their 
development in employment or further education and will provide feedback for educational institutions. See 
http://www.ontrack-project.eu, 10.01.2020 
104 Note that only EU-28 countries are beneficiaries of the ESF. 

March, 2020 

100 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

there is a vanguard of countries that have well established and robust systems 
and would be likely to be able to comply with limited fine-tuning.  

The assessment of countries’ progress against the Council Recommendation on tracking 
graduates shows that: 

  Only two countries (DE, FI) meet all the criteria set out by the Recommendation: 
graduate tracking measures cover all the sectors -initial vocational education and 
training, continuing vocational education and training and higher education- with 
the use of surveys and matching of administrative data. All groups of graduates 
are covered in the tracking measures, including people who move to another 
country after graduation and drop-outs. Longitudinal data on graduates are 
collected and all the types of data indicated in the Recommendation are 
covered.105  

  Five countries (AT, DK, IE, SE and the UK) are very close to meeting the criteria in 
the Recommendation. In these countries, either tracking in some of the sectors is 
only done through one data collection approach (survey or administrative data 
matching) (AT), or the people who have moved to another country after 
graduation (DK, FI, IE, SE, UK) or drop-outs (FI) are not covered. 

  Twelve countries have a good coverage of criteria in the Recommendation but 
there is scope for development (BE-NL, CZ, EE, FR, HU, IT, LT, NL, NO, PL, PT, 
ES). In these countries, it might be the case that one of the data collection 
approaches (survey/administrative data) is not used in any sector (BE-NL, FR), 
one sector is not (fully) covered (IT, PT) or is covered by a measure still in testing 
(PL). In some cases, there are several criteria that are not fully met (e.g. 
graduates who move to another country or drop-outs are not covered and/or 
longitudinal data is not available and/or data collected is not comprehensive).    

  Ten countries have a lower level of compliance with the criteria in the 

Recommendation (BE-FR, BG, HR, LI, LV, LU, MT, RO, SK and SI) and three 
countries have no/hardly any coverage of the criteria (CY, EL and IS). These 
require more substantial development of their graduate tracking, for instance, to 
increase the regularity of tracking, to widen its coverage to all the education 
sectors, to collect longitudinal data on graduates or to include a wider range of 
indicators in existing measures. 

Graduate tracking generally has shortcomings in relation to the 
Recommendation than go beyond it 

There is room for improvement in all the criteria of the Recommendation. The main 
shortcomings include:   

  Continuing vocational education and training is much less frequently covered than 
higher education and initial vocational education and training. The quality of the 
methodologies and data coverage is also lower in continuing vocational education 
and training.  

  Administrative data is not used for tracking purposes in all the countries (it is 

missing in eight countries);  

  Issues with the representativeness of the tracking data collected with achieved 
sample that are too small and biased, mainly in initial vocational education and 
training and continuing vocational education and training. 

  The population covered by tracking measures often excludes graduates who 

moved to another country after graduating. This is critical in the case of initial 
vocational education and training and continuing vocational education and training 

105 Socio-biographical and socioeconomic information, information on education and training, information on 
employment or further education and training, relevance of education and training to employment or life-long 
learning and career progression. 

March, 2020 

101 

 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

where migrant graduates are never covered. People who have left their studies 
without completing are also seldom covered by tracking measures. 

  Longitudinal tracking is not commonplace: 17 countries follow graduates in the 
initial vocational education and training sector, 12 countries in continuing 
vocational education and training and 15 in higher education. 

7.1.3  Are data collection practices based on administrative data, survey data or 

both? 

There is a balance in the use of surveys and administrative data collection 
instruments at system-level. Over a quarter of the measures identified combine 
the two data collection approaches. There is only an incipient use of other 
techniques such as data mining.  

Robust graduate tracking benefits from the combination of surveys and administrative 
data matching so that qualitative data can be linked to quantitative data about individual 
graduates. From the 123 measures identified, 37 combine the two data collection 
approaches. This approach is used in 18 countries (AT, BE-FR, BG, DE, DK, ES, FI, HU, 
IE, IT, LT, LV, NL, NO, PL, PT, SE and UK) and it is more common in higher education (21 
measures) followed by initial vocational education and training (17) and continuing 
vocational education and training (8).  

Where combined approaches do not exist, quality of graduate tracking could be enhanced 
by ensuring that countries use both surveys and administrative data to track similar 
graduate populations and that the two approaches collect complementary, as opposed to 
redundant data. As discussed above, mechanisms to ensure the complementarity of 
tracking measures are currently not common.  

Data collection for graduate tracking goes beyond surveys and administrative data 
matching. The Netherlands has gathered data directly from LinkedIn for tracking 
purposes in a recent pilot study.106 Data mining is used by some higher education 
institutions across several countries.107 New avenues in graduate tracking may involve 
further use of such data which can facilitate the coverage of graduates or former 
students who  move to another country after leaving their studies, thus helping to 
overcome a common limitation in existing graduate tracking measures. 

7.1.4  Where there are large discrepancies in graduate tracking practices 

notable between the countries and between the sectors, how could they 
pose a problem for comparability of data at EU level? 

There is significant distance to travel before country graduate tracking 
information will be comparable.  

Most tracking measures across countries collect key indicators reflecting the areas which 
should be covered in graduate tracking stated in the Council Recommendation. However, 
there is considerable variability in the coverage of these and in the definitions used for 
each indicator which poses considerable difficulties for comparing results and for 
contextualising them. If tracking indicators are to be comparable and useful for 
benchmarking, there would need to be more convergence in the questions asked, the 
definition of indicators and their classification.  

For instance, standard definitions for socioeconomic or biographical data and satisfaction 
questions could significantly enhance comparability. As an example of current 
differences, information on the satisfaction with the quality of education is covered by 27 
measures but the way it is operationalised varies substantially (e.g. quality of university, 

106 Insights into career outcomes and skills of Dutch graduates with LinkedIn data, https://www.cbs.nl/-
/media/_pdf/2019/12/sessie%201%20arbeidsmarkt.pdf?la=nl-nl 
107 Data mining is not used in BE, HU, IS, IE, LI, LT, LU, MT, NO and SI. 

March, 2020 

102 

 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

perception of quality/relevance of education and training for finding employment and for 
current job, quality of teachers, quality of exams).  

It is evident that the details collected on the level, field of study and provider make it 
difficult to compare because of the variation in approach across countries. It is 
reasonable to expect that the considerable differences in qualification spectrums in 
different countries -particularly in vocational education and training- will make it difficult 
to enable comparisons. The use of an international classification to code information on 
the level and fields of education can help overcome this difficulty. ISCED is in fact used 
by most of the measures identified to code information on the ‘level of highest 
educational attainment and orientation’ Also, ISCED classifications should be relatively 
easy to apply to any database as all the countries should have a mapping of their own 
classifications of education levels and fields of study against ISCED and ISCED-F. 

Extending the use of international classifications (e.g. by using ESCO/ISCO and NACE) 
and standard definitions of indicators to all system measures would support convergence. 
Comparability is also enabled by similar periodicities for data collection; 
representativeness of the achieved sample or, in case of surveys, sufficient response 
rate; and data availability for comparative research. 

Comparability is only possible if all tracking measures have robust approaches for their 
administration and sampling. For example, they need to have samples that are deemed 
to be representative and a suitable size for statistical analysis. Thirty of the 123 
measures identified have limitations related to the representativeness of the sample due 
mainly to small response rates to surveys and to the use of convenience sampling. Some 
measures only cover part of the programmes or graduates (e.g. beneficiaries of ESF 
funds) and hence their results cannot be generalised to wider graduate populations.   

The Commission could consider setting minimum standards for measures to be included 
in any comparisons and defining a standard set of indicators for comparison. 

7.1.5  To what extent are higher education institutions undertaking their own 

graduate tracking and how are they doing it? 

The survey of higher education institutions undertaken for this study has found 
that they generally undertake graduate tracking of all cohorts although there is 
a considerable variety of practices some of which may devalue the results  

Before this study, it was generally reported that there was graduate tracking in higher 
education institutions in all countries but there was little information on its extensiveness 
within each country. The survey results show that it is a common practice across EU and 
EEA countries. In countries with well-established system-level graduate tracking 
measures, there is a tendency for fewer higher education institutions to do their own 
tracking (NO, UK), and this appears to save resources for higher education institutions.  

At institutional level, over three-quarters of higher education institutions surveyed used 
the results from graduate tracking for internal quality assurance. Other common uses 
include support to strategic planning, marketing, and/or informing external inspections 
and curriculum planning. Graduate tracking data was considered to have the greatest 
impact on careers advice higher education institutions offer their students when 
compared to other areas such as the range and scope of courses they offer or financial 
contributions from alumni.  

There are significant variations in the quality of institutional graduate tracking. Random 
sampling was used in around two thirds of higher education institutions using 
quantitative surveys and more than half failed to achieve a suitable response rate of 50% 
or more. For around a third it was under 30%. Around a third of higher education 
institutions who used sampling drew on a convenience sample which is likely to provide 
poorer response rates.  

March, 2020 

103 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Higher education institutions in some countries work with national authorities 
who manage system level graduate tracking to coordinate their activities, but 
this is not commonplace  

There is little evidence of coordination mechanisms between higher education institutions 
and system-level tracking. According to mapping data, only four countries offer higher 
education institutions the opportunity to include their own questions in system-level 
graduate tracking surveys (FI, HU, IT, UK) and other coordination mechanisms were 
generally not reported.  

Finland is an exception as the government and higher education institutions share the 
responsibility for graduate tracking. Tracking based on administrative data is conducted 
by Education Statistics Finland (Vipunen). Universities - through the Aarresaari network 
of university career services – are responsible for the development and management of 
tracking surveys. Survey results are collated and aggregated at the national level. The 
universities of applied sciences are developing a similar approach. 

At institutional level, higher education institutions most often compare their results with 
their performance in previous years and, secondly, with results at national level. Around 
one third of higher education institutions compared their results with other individual 
higher education institutions. However, comparability of institutional measures -
developed independently and often without coordinating with other measures in the 
country- is likely to be low. 

A way of overcoming this difficulty is by creating networks of higher education 
institutions with common approaches to graduate tracking. In Germany, 60 higher 
education institutions cooperate under the KOAB project, coordinated by the research 
institute of the University of Kassel, and currently apply a common tracking methodology 
and survey. In Iceland, public higher education institutions have also coordinated to use 
the same survey questionnaire and same approach data analysis. 

7.2  Implications  

The study’s findings should give rise to further action to improve graduate 
tracking measures in all countries 

The results of the mapping should provide both the Commission and the Expert Group 
with up to date information about the state of play of graduate tracking. Most 
immediately, this should provide data for the report which the Expert Group is to draft 
this year on the progress against the Recommendation. Beyond this, it should show what 
gaps there are in graduate tracking, what differences exist which prevent comparison, 
and what coordination is needed to improve their effectiveness.   

The analysis of measures to understand the extent they can be compared should provide 
data to the Commission and the Expert Network about the indicators that could be 
benchmarked among ten or so countries, the changes to measures that would be needed 
to enable this on a greater scale, and the extent of standardisation required. Increasing 
convergence could be challenging as it consists of improving different aspects of 
measures (sampling, data collected, and the classification of data).  

The results of the higher education institution survey should provide the Commission and 
other bodies with up to date information on the state of play of graduate tracking within 
the higher education sector across the EU and EEA. This should provide data to consider 
how the sector might be better supported to undertake effective tracking and use the 
results for benchmarking.  

Countries some distance from meeting the Recommendation’s requirements 
might benefit from support and guidance 

Other European initiatives in the field of education have benefited from opportunities for 
mutual learning and access to experts through meetings, training and guidance 

March, 2020 

104 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

publications. These have enabled national initiatives to progress and for greater 
convergence to be built into systems and approaches.  

This could be through peer learning, expert support, self-organised consultancy/problem 
sharing between countries close to each other or with the same problems. A group of 
countries in Mid-Eastern Europe have similar problems (BG, CY, EL, HR, RO, SI, SK), for 
example, as do a group of small countries (CY, LU, LV, MT, SI, SK). Countries which have 
progressed furthest towards the Recommendation may have experience they can share.  

7.3  Some recommendations 

The Commission should:  

  Encourage Member States to increase the coverage of graduate tracking: 

introduce it where absent, particularly for continuing vocational education and 
training graduates, with all graduate cohorts tracked; 

  Encourage Member States to work towards convergence: particularly in relation to 
survey questions, data collected, representative data, and longitudinal data;  

  Consider providing additional capacity building support in the form of drawing 
together and spreading good practice in establishing and maintaining graduate 
tracking systems to overcome some of the gaps and deficiencies in 
implementation. This could be in the form of: peer learning opportunities, mutual 
learning country groups, task forces to support a specific country;   

  Consider raising the bar by adding to/adjusting the Recommendation. This might 

include adding social and civic outcomes to the data collected, expecting 
coordination between measures and specifying minimum percentages of graduates 
in achieved samples; 

  Encourage European bodies representing higher education institutions to increase 
the advice and guidance they provide on graduate tracking and reflect on the 
findings of this study’s survey results about the quality/scope of surveys.  

The Expert Network Group should: 

  Continue its work on indicators for the Commission to take forward; 

  Note the progress made and the state of play (at October 2019) in graduate 

tracking in its report on progress towards achieving the Council Recommendation 
in 2020. 

Countries should, where this is not the case, in their work towards achieving the Council 
Recommendation: 

  Include coverage of all the graduate population across higher education and 

vocational education and training in graduate tracking measures; 

  Work towards greater convergence of measures in relation to survey questions, 

data collected, representative data and longitudinal data; 

  Establish coordination between national and provider level graduate tracking 

activities to increase synergies and convergence; 

  Establish national level coordination of system level measures including those for 

ESF completers. 

March, 2020 

105 

 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Annex 1.  List of interviewees 

Table 56.  List of interviewees (anonymised) 

Country  Nbr. 

Institution 

Function of interviewee 

AT 

BE (fr) 

1 

3 

University of Vienna. 

Head of Quality Assurance. 

Académie de recherche et 
d'enseignement supérieur 
(ARES). 

Project manager. 

Federation Wallonie-
Brussels. 

Project manager; statistical 
coordination and research. 

Brussels Formation. 

Analyst, Service for Studies and 
Statistics. 

BE (nl) 

4 

Flemish Department of 
Education and Training. 

Data analyst. 

Ibid. 

Researcher. 

SYNTRA Vlaanderen.* 

Sociologist.* 

ESF-Agency Flanders.*  

General Director.* 

BG 

3 

Ministry of Education and 
Science. 

Chief expert. 

CY 

CZ 

DE 

DK 

2 

1 

1 

3 

National Agency for VET. 

Secretary-General. 

Ministry of Education and 
Science.  

Expert. 

Higher Education 
Department – MOEC. 

Senior official. 

Secondary Technical 
Education Department – 
MOEC. 

MIEEK (Public School of Higher 
Education and Training) 
Coordinator. 

Centre for Higher Education 
Studies. 

Director. 

Federal Institute for 
Vocational Education and 
Training (BIBB). 

Population and Education, 
Social Statistics, Statistics 
Denmark. 

Researcher. 

Chief consultant. 

Statistics Denmark.* 

Chief consultant.* 

March, 2020 

106 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Nbr. 

Institution 

Function of interviewee 

The Danish Business 
Authority. 

Special consultant. 

Ministry of Higher Education 
and Science. 

Head of section. 

National Agency for IT and 
Learning, Ministry of 
Children and Education. 

Senior consultant. 

Ministry of Children and 
Education. 

Senior consultant. 

Ministry of Education and 
Research 

Leading Analyst. Analysis 
Department. 

3 

4 

Ministry of Education and 
Research 

Head of Department. Analysis 
Department. 

The Panteion University of 
Social and Political 
Sciences. 

Sociologist and senior 
researcher. 

Demokritean University of 
Thrace. 

Career officer. 

Ministry of Education and 
Religious Affairs. 

General Secretary of 
Professional Training and Life-
long learning. 

National Qualifications - 
Institute. General 
Directorate for VET. 

Director. 

Secretariat General of 
Universities of the Ministry 
of Science, Innovation and 
Universities. 

Ministerial adviser. 

Ibid. 

Statistical officer. 

EE 

EL 

ES 

European Social Fund. 

Head of service, Administration 
Unit. 

FI 

10 

Ministry of Education and 
Culture. 

Counsellor.  

Ibid. 

Senior Officer. 

University of Helsinki. 

Chair of the Aarresaari 
Network’s career monitoring 
group. 

March, 2020 

107 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Nbr. 

Institution 

Function of interviewee 

University of Turku, Career 
Services. 

Researcher. 

Turku University of Applied 
Sciences. 

Quality specialist, Project 
manager. 

Ministry of Employment and 
the Economy. 

Specialist, Regions and Growth 
Services, Cohesion Policy and 
Structural Funds. 

Ibid. 

Ibid. 

Ministerial Adviser.  

Conciliation Officer, Regions and 
Growth Services, Cohesion Policy 
and Structural Funds. 

Ministry of Education and 
Culture. 

Senior ministerial adviser. 

Hämeen ELY-keskus. 

Finance Manager. 

Ministry of National 
Education and Youth / 
Ministry of Higher Education 
and Research* 

Head of the European and 
International Relations Unit, 
Directorate of Evaluation, 
Forward-Planning and 
Performance.* 

Institute for Social 
Research. 

Junior lecturer, research 
assistant. 

University of Zagreb, 
Faculty of Law. 

Professor. 

Educational Office. 

Head of Department. 

SOLAS – Further Education 
and Training Authority 

Manager. Active Inclusion. 

Manager. Operational Data 
Analytics Unit. 

Higher Education Authority  Head of Performance Valuation. 

Senior Manager, Performance 
Evaluation and Statistics. 

Senior Statistics Manager. 

1 

2 

1 

7 

Central Statistics Office 
(CSO) 

Statistician.  

Senior statistician. 

8 

Ministry of Education, 
Science and Culture* 

Senior advisor. Department of 
Finance and Administration. 

Senior advisor. Department of 
Higher Education and Science. 

FR 

HR 

HU 

IE 

IS 

March, 2020 

108 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Nbr. 

Institution 

Function of interviewee 

Tækniskolinn (VET 
provider)*  

Several HEI.  

Principal. 

Director of Social Science 
Research Institute*.  

Director of Academic Affairs 
from the Icelandic Academy of 
Arts. 

Marketing manager at Reykjavik 
University.  

Director of UNAK Research 
Center at University of Akureyri.  

Assistant Professor at Bifrost 
University*. 

IT 

4 

Service for education, 
training and work, ISTAT. 

Researcher. 

Ibid. 

Researcher. 

AlmaLaurea. 

Responsible for the Unit surveys 
and statistics. 

National Agency for Active 
Labour Market Policies. 

Responsible for the research 
structure ‘monitoring and 
evaluation of employment 
services and employment 
policies’. 

National Office of Statistics.  Responsible for administrative 

data and surveys. 

Centre for Development of 
Qualifications and 
Vocational Education and 
Training. 

Head of Qualifications Formation 
Unit. 

Government Strategic 
Analysis Centre. 

Head of the Higher Education 
Policy and Career Analysis Unit. 

Ministère de l'Éducation 
nationale, de l'Enfance et de 
la Jeunesse 

Statistician.  

National Institute for the 
Development of Continuing 
vocational training 

Responsible Training 
Observatory. 

Research Analyst at the Training 
Observatory. 

LI 

LT 

LU 

1 

2 

3 

LV 

3 

Ministry of Education and 
Science. 

Senior expert. 

March, 2020 

109 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Nbr. 

Institution 

Function of interviewee 

MT 

NO 

NL 

PL 

PT 

0 

3 

6 

Ibid. 

Ibid. 

N/A 

Ministry of Education and 
Research, Department for 
Higher Education, Research 
and International Affairs. 

Deputy Director of Vocational 
Education and Lifelong Learning 
Development. 

(on the VET graduate tracking 
system is still in the planning 
phase).  

N/A 

Technical Director. 

NIFU. 

Ibid. 

Project leader Graduate Surveys 
in HE. 

Project leader VET surveys. 

ROA (Research Centre 
Education and Labour 
Market). 

Project leader. 

Ibid. 

Project leader. 

Association of Dutch 
Universities (VSNU). 

Policy Advisor Institutional 
Research. 

Maastricht University. 

Head BI organisation. 

Delft University of 
Technology. 

Education & Student Affairs.  

Statistics Netherlands. 

Senior researcher. 

2 

University of Warsaw  

Head of Unit, Laboratory for the 
Evaluation of Quality of 
Education at the University of 
Warsaw (UoW), involved in 
creating the ELA system. 

Ministry of Science and 
Higher Education (MoSHE). 

Deputy Director, Department of 
Innovation and Development.  

3 

DG Statistics of Education 
and Science (information on 
HE) 

Sub-director General. 

DG Statistics of Education 
and Science (information on 
VET) 

Officer at the division of studies 
and management of access to 
research data. 

Operational Programme 
Social Inclusion and 
Employment.  

President of the Executive 
Committee. 

March, 2020 

110 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Nbr. 

Institution 

Function of interviewee 

RO 

SE 

SK 

SL 

2 

4 

2 

3 

National Center for the 
Development of Vocational 
and Technical Education 
(CNDIPT). 

Specialised inspector, regional 
coordinator. 

Ministry of National 
Education. 

Counsellor, General Directorate 
for HE. 

Swedish National Agency 
for Education. 

Head of unit. Statistics. 

Ministry of Education and 
Research. 

Desk Officer. 

Statistics Swede. 

Analyst/Statistician. 

Svenska ESF-rådet/Swedish 
ESF-Council. 

Deputy Director General. 

Ministry of Education, 
Research and Sport. 

Economic Analyst. 

Slovak Centre of Scientific 
and Technical Information. 

Analyst, Head of Department. 

University of Ljubljana, 
Faculty of Arts. 

National expert of QA in HE, 
associate professor. 

Institute of the Republic of 
Slovenia for Vocational 
Education and Training. 

Senior adviser. 

Ibid. 

Senior adviser. 

UK 

0 

TOTAL  

92 

Source: research ICF, 3s and CHEPS. 
* Input received by e-mail. 

Annex 2.  Annexes to chapter 2 

Table 57.  Strategy/policy documents that refer to graduate tracking 

Country  Policy 
focus 

Sector  Strategy/policy document 

AT 

Yes 

both 

March, 2020 

111 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Policy 
focus 

Sector  Strategy/policy document 

both 

Decree of 11 April 2014 on the development of a register 
of post-educational educational trajectories.108 

BE-FR 

BE-NL 

Yes 

No 

VET: Strategy for the development of vocational 
education and training in the Republic of Bulgaria 2015-
2020'. 

HE: Strategy for higher education development in the 
Republic of Bulgaria (2014-2020). Bulgarian University 
Ranking System. 

both 

Yes 

No 

Yes 

HE 

Strategic plan for higher education development (2016-
2020).  

BG 

CY 

CZ 

HE: Resolution of the Standing Conference of the 
Ministers of Education and Cultural Affairs of the Länder 
in the Federal Republic of Germany, 2005, Quality 
Assurance in Higher Education.109 Law on Higher 
Education Statistics: since 2016 including statistics on the 
course of studies. 

VET: A reform of the Danish VET system from 2014 
established four goals, one of which linked to an 
indicator on the employment rates of VET graduates. 

HE: dimensioning model in HE which limits the intake of 
students in HE programmes with systematic high 
unemployment rates amongst graduates. In 2017 
funding to HE became dependent on graduates' 
employment rates. 

Estonian Lifelong Learning Strategy 2020 

VET: 2018 VET reform, policy recommendations to the 
VET providers, performance-based funding for VET.   

DE 

Yes 

HE 

DK 

EE 

EL 

ES 

Yes 

Yes 

No 

Yes 

both 

both 

FI 

Yes 

both 

108 https://www.gallilex.cfwb.be/document/pdf/40250_000.pdf 
109 https://www.kmk.org/fileadmin/veroeffentlichungen_beschluesse/2005/2005_09_22-
Qualitaetssicherung-Lehre.pdf 

March, 2020 

112 

 
 
 
 
 
 
 
  
 
 
  
  
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Policy 
focus 

Sector  Strategy/policy document 

HE: ‘Vision for higher education and science 2030’ 
strategy: new funding allocation models for universities 
and UAS.  

VET: Order of 24 January 2013 creating an automated 
processing of data from two surveys: the Survey on 
active life insertion (IVA) and the Professional Insertion 
of Apprentices Survey (IPA) 

FR 

Yes 

both 

HR 

Yes 

both 

The National Programme for VET System Development 
2016-2020. 

HU 

Yes 

both 

VET: Government Act 319/2014. Vocational Education 
and Training 4.0 policy strategy document, approved by 
Government decree 1168/2019.110 

VET 

Ireland 2014-2019 Further Education and Training 
strategy. 

IE 

IS 

Yes 

No 

VET:  

1) Art. 14 of D.P.C.M. (25 January 2008) of the 
'Guidelines for the reorganisation of the education and 
training system and the constitution of higher technical 
institutes'111 foresees a general monitoring of the system 
and of the employment outcomes. 

2) The Agreement between the State and the Regions 
(24 September 2015)112 establishes that regions and 
provinces should gather the data related to VET and link 
them to the compulsory communications that employers 
have to send to employment offices whenever a labour 
contract is started or discontinued in order to track the 
employment outcomes. 

3) As regards the ITS pathways, the Agreement between 
Government, Regions ed Local authorities (5 August 
2014) includes a reference to a monitoring and 
evaluation system of ITS pathways. 

IT 

LI 

VET 

Yes 

No 

110 https://www.nive.hu/index.php?option=com_content&view=article&id=1024:szakkepzes-40-
strategia&catid=10:hirek&Itemid=166 
111 https://www.cliclavoro.gov.it/normative/d.p.c.m_25_gennaio_2008.pdf 
112http://www.sistemaduale.anpal.gov.it/documentazione/Documents/accordo_stato_regioni_24_se
ttembre_2015.pdf; 

March, 2020 

113 

 
 
 
 
 
 
  
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Policy 
focus 

LT 

LU 

Yes 

No 

Sector  Strategy/policy document 

both 

 Government programme 2012-2016 

LV 

Yes 

both 

‘Guidelines for the Development of Education for 2014-
2020’.113 HE and VET monitoring will be part of the next 
education planning document (2021-2027). 

MT 

Yes 

both 

The National Vocational Education and Training Policy 
(2015).114 

both 

Macro Efficiency policy. 2015 strategy for Higher 
Education.  

both 

NL 

NO 

PL 

PT 

Yes 

No 

Yes 

No 

RO 

Yes 

both 

SE 

Yes 

both 

SI 

Yes 

HE 

SK 

Yes 

both 

VET: Education and Training Strategy of Romania for the 
period 2016-2020115 
HE: National Strategy for Tertiary Education 2015 - 
2020116  

Regulations tasking several agencies with graduate 
tracking: National Agency for Education (Skolverket); 
Swedish Higher Education Authority 
(Universitetskanslersämbetet (UKÄ); and Swedish 
National Agency for Higher Vocational Education 
(Myndigheten för yrkeshögskolan). 

Resolution on the National Higher Education Programme 
2011-2020 (Ministry of Education, Science and Sport of 
the Republic of Slovenia, 2011).  

VET: VET Law from 2015,117 Decree of the Ministry of 
Education, Science, Research and Sport from 2019 on 
determining the number of pupils.118 

113 http://www.lsa.lv/wp-content/uploads/2013/03/Izglitibasattistibaspamatnostadnes.pdf  
114 
https://ncfhe.gov.mt/en/resources/Documents/Strategy%20Documents/National%20Vocational%20
Education%20and%20Training%20Policy.pdf 
115 
https://www.edu.ro/sites/default/files/_fi%C8%99iere/Minister/2016/strategii/Strategia_VET%2027%2004%20201
6.pdf 
116 https://www.edu.ro/sites/default/files/fisiere%20articole/Strategie_inv_tertiar_2015_2020.pdf 
117 https://www.slov-lex.sk/pravne-predpisy/SK/ZZ/2015/61/ 
118 https://www.slov-lex.sk/pravne-predpisy/SK/ZZ/2019/292/20191001 

March, 2020 

114 

 
 
 
 
  
 
  
 
 
  
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Policy 
focus 

Sector  Strategy/policy document 

HE:  Higher Education Act.119 

UK 

Yes 

both 

HE: Teaching Excellence and Student Outcomes 
Framework (TEF) (2017) (England and some universities 
from Scotland and Wales).120 

Table 58.  Purpose of graduate tracking: VET 

Country  Purposes   

Quality 
assurance 

Access to 
funding 

Monitorin
g of 
education 
policies 

Other 

Provision 
of 
informatio
n and 
guidance 

Strategic 
planning 
of course 
offer 

x 

x 

x 

x 

x 

x 

x 

x 

x 

AT 

BE-NL 

BE-FR 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

X 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

119 zakonypreludi.sk/zz/2002-131 
120 
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/658490/Teachi
ng_Excellence_and_Student_Outcomes_Framework_Specification.pdf and 
https://www.officeforstudents.org.uk/media/4013afd5-0943-4350-8d77-ee46a59af38b/ofs2018_45a.pdf 

March, 2020 

115 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                           
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Purposes   

Quality 
assurance 

Access to 
funding 

Monitorin
g of 
education 
policies 

Other 

Provision 
of 
informatio
n and 
guidance 

Strategic 
planning 
of course 
offer 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

20 

20 

Source: research ICF and 3s 

x 

x 

x 

x 

x 

x 

7 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

15 

20 

11 

Table 59.  Purpose of graduate tracking: HE 

Country  Purposes   

Quality 
assurance 

Access to 
funding 

Monitorin
g of 
education 
policies 

Other 

Provision 
of 
informatio
n and 
guidance 

Strategic 
planning 
of course 
offer 

AT 

x 

x 

x 

x 

March, 2020 

116 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Purposes   

Quality 
assurance 

Access to 
funding 

Monitorin
g of 
education 
policies 

Other 

Provision 
of 
informatio
n and 
guidance 

Strategic 
planning 
of course 
offer 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

BE-NL 

BE-FR 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

March, 2020 

117 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Purposes   

Quality 
assurance 

Access to 
funding 

Monitorin
g of 
education 
policies 

Other 

Provision 
of 
informatio
n and 
guidance 

Strategic 
planning 
of course 
offer 

RO 

SE 

SI 

SK 

UK 

x 

x 

x 

x 

x 

x 

18 

22 

x 

x 

9 

Source: research ICF, 3s and CHEPS 

x 

x 

x 

x 

23 

x 

x 

16 

x 

12 

Table 60.  Main users of graduate tracking: VET 

Country  Users 

Governme
nt 

VET 
providers 

Students 
and 
graduates 

Employers  Researche

Other 

rs 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

AT 

BE-NL 

BE-FR 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

March, 2020 

118 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Users 

Governme
nt 

VET 
providers 

Students 
and 
graduates 

Employers  Researche

Other 

rs 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

26 

19 

13 

7 

15 

8 

Source: research ICF, 3s and CHEPS. 

Table 61.  Main users of graduate tracking: HE 

Country  Users 

Governme
nt 

HEIs 

Students 
and 
graduates 

Employers  Researchers  Other 

AT 

BE-NL 

x 

x 

x 

x 

x 

x 

x 

x 

March, 2020 

119 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Users 

Governme
nt 

HEIs 

Students 
and 
graduates 

Employers  Researchers  Other 

BE-FR 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IS 

IT 

LI 

LT 

LU 

LV 

MT 

NL 

NO 

PL 

PT 

RO 

SE 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

x 

March, 2020 

120 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country  Users 

Governme
nt 

HEIs 

Students 
and 
graduates 

Employers  Researchers  Other 

SI 

SK 

UK 

x 

x 

x 

27 

x 

x 

25 

x 

x 

x 

x 

x 

x 

17 

8 

21 

7 

Source: research ICF, 3s and CHEPS

March, 2020 

121 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Annex 3.  Annexes to chapter 3 

Table 62.  Graduate tracking measures identified in EU Member States 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

IVET, CVET, 
HE 

  Administrative data 

collection instrument 

national 

IVET, 
Others 

  Survey, Administrative data 

national 

sample 

collection instrument 

Basis 
(reference 
population)4 

total reference 
population 

1 

AT1 

Education-related employment 
career monitoring (BibEr) 

2 

AT2 

After graduation of dual VET: 
Training and professional 
success of graduates of dual 
VET in Austria. An empirical 
study on the basis of 
administrative individual- and 
registry-based data and a 
graduate survey 

Bildungsbezogenes 
Erwerbskarrieremonitoring 
(BibEr) 

Nach der Lehre: Ausbildungs- 
und Berufserfolg von 
Lehrabsolventen und 
LehrabsolventInnen in 
Österreich. Eine empirische 
Untersuchung auf Basis von 
amtlichen Individual- / 
Regiserdaten und persönlicher 
Befragung 

3 

4 

5 

AT3 

HRSM project: Graduate 
tracking 

HRSM Projekt 
AbsolventInnentracking 

HE 

  Administrative data 

collection instrument 

national 

AT4 

Student Social Survey  

Studierenden-Sozialerhebung   HE 

  Survey 

national 

total reference 
population 

total reference 
population 

AT5 

Eurograduate Pilot Survey: This 
measure is a one-off pilot 
survey of recent graduates in 8 
European countries 

Eurograduate Pilot Survey 

HE 

  Survey 

national 

sample 

6 

BE-FR1 

Ulysse Survey. To be renamed 
in 2019: Survey on labour 
market insertion after 
professional training 

Enquete Ulysse. A partir de 
2019: ENQUÊTE INSERTION 
SUR LE MARCHÉ DU TRAVAIL À 
L’ISSUE DE LA FORMATION 
PROFESSIONNELLE 

CVET 

  Survey, Administrative data 

federal/regional  sample 

collection instrument 

March, 2020 

122 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

7 

8 

9 

BE-FR2 

Register of educational 
trajectories 

Cadastre des parcours 
educatifs 

IVET, CVET, 
HE, Others 

  Administrative data 

collection instrument 

federal/regional  total reference 

population 

BE-NL1 

School leavers study 

Schoolverlatersstudie 

IVET, HE 

  Administrative data 

federal/regional  total reference 

BE-NL2 

SYNTRA graduate tracking 

SYNTRA graduate tracking 

CVET 

collection instrument 

population 

  Administrative data 

collection instrument 

federal/regional  total reference 

population 

10 

BE-NL3 

European Social Fund (ESF) 
tracking in Flanders - no official 
name 

Europees Social Fonds (ESF) in 
Vlaanderen 

IVET, CVET, 
HE 

  Administrative data 

collection instrument 

federal/regional   

11 

BG1 

Erasmus+ Project № 609397-
EPP-1-2019-1-BG-EPPKA3-
EQAVET-NRP 'Piloting Tracking' 
(2019-20021), Agreement № 
2019-0485/001-001 (EACEA-
MES) 

Еразъм + проект, който 
пилотира механизъм за 
проследяване на 
завършилите ПОО (2019– 
2021)  

12 

BG2 

Bulgarian University Ranking 
System 

РЕЙТИНГОВА СИСТЕМА НА 
ВИСШИТЕ УЧИЛИЩА В 
БЪЛГАРИЯ 

13 

CY1 

ESF-funded measures 

14 

CZ1 

Graduate 2018 

Absolvent 2018 

15 

CZ2 

Reflex 2006, 2010, 2013 

Reflex 2006, 2010, 2013 

16 

CZ3 

Eurograduate 

Eurograduate 

IVET 

  Survey, Administrative data 

Federal/regional  sample 

collection instrument 

HE 

HE 

HE 

HE 

  Administrative data 

collection instrument 

national 

total reference 
population 

  Survey 

  Survey 

  Survey 

national 

sample 

national 

sample 

national 

sample 

17 

CZ4 

Tracking of VET and HE 
graduates' unemployment 
through administrative data    

Sledovani nezamestanosti 
absolventu skol a vysokych 
skol 

IVET, HE 

  Administrative data 

national 

collection instrument 

total reference 
population 

March, 2020 

123 

 
 
 
 
 
   
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

18 

CZ5 

Survey of school graduates 
regarding their transition from 
education into labour market 
(2009, 2015, 2017, 2018) 

Dotazníkové šetření žáků 
posledních ročníků středních 
odborných škol (2009, 2015, 
2017, 2018)  

IVET 

  Survey 

national 

sample 

19 

DE1 

National Educational Panel 
Study - NEPS 

Nationales Bildungspanel - 
NEPS 

IVET, CVET, 
HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

20 

DE2 

BIBB Transition Surveys 2006 
and 2011 

BIBB Übergangsstudien 2006 
und 2011  

IVET, HE, 
Others 

  Survey 

national 

sample 

21 

DE3 

Integrated Employment 
Biographies Sample (SIAB) 

Stichprobe der Integrierten 
Arbeitsmarktbiografien (SIAB) 

IVET, CVET, 
HE 

  Administrative data 

collection instrument 

national 

sample 

22 

DE4 

BIBB/BAuA Labour Force Survey 
- Changing labour and 
employment, attainment and 
utilisation of professional 
qualifications. 

BIBB/BAuA 
Erwerbstätigenbefragung - 
Arbeit und Beruf im Wandel, 
Erwerb und Verwertung 
beruflicher Qualifikationen 

IVET, CVET, 
HE 

  Survey 

national 

sample 

23 

DE5 

Educational Panel Saarland  

Das Aubildungspanel Saarland   IVET 

  Administrative data 

collection instrument 

federal/regional  total reference 

population 

DZHW Absolventenpanel 

HE 

  Survey 

national 

sample 

24 

DE6 

DZHW Graduate Panel - The 
DZHW conducts graduate 
surveys since 1989, since then 
every fourth examination cohort 
is surveyed several times. The 
newest graduate cohort from 
2017 (AP2017) is the first 
nationwide project in graduate 
research in Germany to be 
carried out by a supra-regional 
group of research institutes 
(DZHW, INCHER, ISTAT). In the 

March, 2020 

124 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

25 

DE7 

following description the focus 
lies on the study of 2017.  

The cooperation project 
graduate studies (KOAB): This 
measures was first carried out 
between 2007 and 2017, since 
2018, the research institute 
ISTAT is undertaking the 
survey. 

Das Kooperationsprojekt 
Absolventenstudien (KOAB) 

HE 

  Survey 

national 

sample 

26 

DE8 

Bavarian Graduate Panel (BAP) 

 Das Bayerische 
Absolventenpanel (BAP) 

HE 

  Survey 

federal/regional  sample 

27 

DE9 

DZHW Panel Study of School 
Leavers with a Higher Education 
Entrance Qualification 

DZHW-
Studienberechtigtenpanel 

IVET, HE, 
Others 

  Survey 

national 

sample 

28 

DE10 

Eurograduate Pilot Survey: This 
measure is a one-off pilot 
survey of recent graduates in 8 
European countries 

Eurograduate Pilot Survey 

HE 

  Survey 

national 

sample 

29 

DE11 

Saxon Alumni Study* 

Sächsische Absolventenstudie   HE 

  Survey 

federal/regional  sample 

30 

DK1 

Statistics Denmark student 
register 

Danmarks Statistiks 
elevregister 

IVET, HE, 
Others 

  Administrative data 

collection instrument 

31 

DK2 

The cross-sectional course 
register 

Det tværgående kursistregister  CVET 

  Administrative data 

collection instrument 

national 

national 

32 

DK3 

From education to the labour 
market 

Fra uddannelse til 
arbejdsmarked 

IVET, HE 

  Administrative data 

national 

collection instrument 

March, 2020 

total reference 
population 

total reference 
population 

total reference 
population 

125 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

33 

DK4 

Labour Market Account (LMA) 

Arbejdsmarkedsregnskabet 

Others 

  Administrative data 

national 

collection instrument 

34 

DK5 

Implementation report 

Årsrapport 

IVET, CVET 

  Survey, Administrative data 

national 

collection instrument 

Basis 
(reference 
population)4 

total reference 
population 

35 

DK6 

EducationZOOM 

UddannelsesZOOM 

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

36 

DK7 

Employment rates of VET 
graduates 

Beskæftigelsesfrekvenser for 
EUD-dimittender 

IVET 

  Administrative data 

collection instrument 

national 

37 

EE1 

Labour Market Success of 
Vocational and Higher Education 
Graduates (2016, 2017, 2018) 

Kutse- ja kõrghariduse 
omandanute edukus tööturul 
(2016, 2017, 2018)  

IVET, HE 

  Administrative data 

national 

collection instrument 

38 

EE2 

Estonian VET graduates` 2015-
2016 research (2017) 

Eesti kutseõppe 2015.-2016. 
aasta vilistlaste uuring (2017) 

IVET, CVET 

  Survey 

national 

39 

EE3 

Estonian HE graduates´ 2015 
research (2017) 

Eesti kõrgkoolide 2015. aasta 
vilistlaste uuring (2017) 

HE 

  Survey 

national 

total reference 
population 

total reference 
population 

total reference 
population 

40 

EL1 

ESF-funded training 

  Survey 

41 

ES1 

Continuous sample of working 
lives 

Muestra continua de vidas 
laborales 

IVET, CVET, 
HE, Others 

  Administrative data 

collection instrument 

national 

sample 

42 

ES2 

Monthly/annual information of 
the labour market of graduates 

Informacion mensual/annual 
de mercado de trabajo de 
personas tituladas 

IVET, HE 

  Administrative data 

national 

collection instrument 

total reference 
population 

43 

ES3 

Survey on education-training 
transitions and labour insertion 

Encuesta de Transicion 
Educativo-Formativa e 
Insercion Laboral (ETEFIL) 

IVET, 
Others 

  Survey 

national 

sample 

March, 2020 

126 

 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

44 

ES4 

Report on the labour market 
insertion. VET graduates from 
the education system (under 
development) 

Informe de insercion en el 
mercado laboral. Titulados the 
FP del sistema educativo. 

IVET 

  Survey, Administrative data 

national 

sample 

collection instrument 

45 

ES5 

Long-term common output and 
result indicators for ESF 
investments  

Indicadores Comunes 
Comunitarios de resultado a 
largo plazo 

IVET, 
Others 

  Survey, Administrative data 

federal/regional  sample 

collection instrument 

46 

ES6 

Labour insertion of university 
graduates 

Inserción laboral de los 
agresados universitarios 

47 

ES7 

Survey of the labour insertion of 
university graduates (EILU) 

Encuesta de Inserción Laboral 
de los Titulados Universitarios 
(EILU) 

HE 

HE 

  Administrative data 

collection instrument 

national 

total reference 
population 

  Survey, Administrative data 

national 

sample 

collection instrument 

48 

FI1 

Transition from school to further 
education and work"   

Sijoittuminen koulutuksen 
jalkeen  

IVET, CVET, 
HE, Others 

  Administrative data 

collection instrument 

national 

49 

FI2 

Career monitoring for master's 
level graduates (in universities) 

Maistereiden uraseuranta 
(yliopistot) 

HE 

  Survey, Administrative data 

national 

collection instrument 

50 

FI3 

Career Monitoring for Doctor's 
Level Graduates 

Tohtoreiden uraseuranta 

HE 

  Survey, Administrative data 

national 

collection instrument 

51 

FI4 

 Career Monitoring in 
Universities of Applied Sciences 

Ammattikorkeakoulujen 
uraseuranta 

Kandipalaute - the Finnish 
Bachelor Graduate Survey 
(university students) 

Kandipalaute 

HE 

HE 

  Administrative data 

collection instrument 

national 

  Survey, Administrative data 

national 

collection instrument 

AVOP Graduate feedback 
questionnaire for UAS 
(graduating students) 

Ammattikorkeakoulujen 
valmistumisvaiheen 
opiskelijapalaute AVOP 

HE 

  Survey, Administrative data 

national 

collection instrument 

52 

FI5 

53 

FI6 

March, 2020 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

127 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

54 

FI7 

Amis feedback from graduating 
VET students 

Amispalaute valmistuville 
opiskelijoille 

IVET, CVET 

  Survey, Administrative data 

national 

collection instrument 

55 

FI8 

Placement after graduation 

Tutkinnon suorittaneiden 
sijoittuminen 

IVET, CVET, 
HE 

  Administrative data 

collection instrument 

national 

Basis 
(reference 
population)4 

total reference 
population 

total reference 
population 

56 

FI9 

Operational programme 
Sustainable Growth and Jobs 
2014-2020: tracking of 
participants 

Operationaalinen ohjelma 
Kestavaa kasvua ja tyota 

IVET, CVET, 
HE, Others 

  Survey, Administrative data 

national 

sample 

collection instrument 

57 

FR1 

Generation Survey (Cereq) 

L'enquête Génération (Céreq) 

IVET, CVET, 
HE, Others 

  Survey 

national 

sample 

58 

FR2 

Survey on active life insertion 

59 

FR3 

Professional Insertion of 
Apprentices Survey  

Enquête Insertion dans la vie 
active (IVA) 

Enquete sur l'insertion 
professionnelle des apprentis 
(Enquete IPA)  

60 

FR4 

Employability survey for higher 
education degrees 

Insertion professionnelle des 
diplômés de l'université 

61 

FR5 

professional instertion of 
doctorate holders 

"Insertion professionnelle des 
docteurs" 

62 

HR1 

The Results of the Research of 
the Employability of Students 
Who Graduated in Academic 
Year 2015/2016 

Rezultati istraživanja o 
zapošljivosti studenata koji su 
diplomirali akademske godine 
2015./2016. 

IVET 

  Survey 

national 

IVET 

  Survey 

national 

HE 

HE 

HE 

  Survey 

national 

  Survey 

national 

  Survey 

national 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

63 

HU1 

Graduate Tracking System 

Diplomás Pályakövetés 
Rendszere 

HE 

  Survey, Administrative data 

national 

collection instrument 

total reference 
population 

March, 2020 

128 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

64 

HU2 

Graduate Tracking Scheme in 
VET 

Not yet available. 

IVET, CVET 

national 

Basis 
(reference 
population)4 

total reference 
population 

65 

HU3 

Labor market situation of freshly 
graduated skilled workers 

A pályakezdő szakmunkások 
munkaerő-piaci helyzete 

IVET 

  Survey 

national 

sample 

66 

IE1 

2016 Follow Up Surveys of FET 
Programme Participants 

2016 Follow Up Surveys of FET 
Programme Participants 

IVET, CVET 

  Survey 

national 

total reference 
population 

67 

IE2 

School Leavers Survey 

School Leavers Survey 

IVET 

  Survey 

national 

sample 

68 

IE3 

Graduate Outcomes Survey 

Graduate Outcomes Survey 

HE 

  Survey, Administrative data 

national 

69 

IE4 

Programme and Learner 
Support System 

Programme and Learner 
Support System 

collection instrument 

IVET, CVET 

  Administrative data 

national 

collection instrument, Other 
Source of discrete mass-
data 

70 

IE5 

Further Education Outcomes 

Further Education Outcomes 

IVET, CVET 

  Administrative data 

national 

71 

IE6 

Higher Education Outcomes 

Higher Education Outcomes 

HE 

collection instrument 

  Administrative data 

collection instrument 

national 

total reference 
population 

total reference 
population 

total reference 
population 

total reference 
population 

72 

IT1 

ISTAT Inquiry into the study and 
work paths of diploma holders 

Indagine sui percorsi di studio 
e di lavoro dei diplomati 

IVET 

  Survey, Administrative data 

national 

sample 

collection instrument 

73 

IT2 

AlmaDiploma - Choices of 
diploma holders: employment 
and education one year and 
three years after 

Analisi delle Scelte dei 
diplomati ad uno e tre anni dal 
conseguimento del diploma.  

IVET 

  Survey, Administrative data 

national 

sample 

collection instrument 

74 

IT3 

National Registry of students 

Anagrafe Nazionale Studenti 

IVET, HE 

  Administrative data 

national 

collection instrument 

March, 2020 

total reference 
population 

129 

 
 
 
   
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

75 

IT4 

ISTAT Inquiry on the 
professional integration of 
graduates 

L’indagine campionaria 
sull’inserimento professionale 
dei laureati  

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

76 

IT5 

Graduates' Profile Survey (Alma 
Laurea Consortium) 

Indagine - Profilo dei Laureati  HE 

  Survey, Administrative data 

national 

collection instrument 

Graduates' employment 
condition (AlmaLaurea 
Consortium) 

Condizione occupazionale dei 
Laureati 

HE 

  Survey, Administrative data 

national 

collection instrument, 
Census 

total reference 
population 

total reference 
population 

Inquiry on the professional 
integration of Phd holders after 
4 and 6 years from the 
completion of their Phd 

Inserimento professionale dei 
dottori di ricerca a 4 e 6 anni di 
distanza dal conseguimento del 
titolo. 

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

National Monitoring of the 
pathways ITS (Istituti Tecnici 
Superiori - Higher Technical 
Institutes ) 

Monitoraggio nazionale dei 
percorsi ITS 

IVET 

  Administrative data 

collection instrument 

national 

total reference 
population 

Youth Guarantee: Sample 
iniquiry on the employment 
results of the participants 
(second report, 2019) 

Garanzia Giovani: Indagine 
campionaria sugli esiti 
occupazionali dei giovani iscritti 
(second report, 2019) 

Thematic assessment report - 
the results of PIPOL (Integrated 
Plan for the policies for 
occupation and work) 

Rapporto tematico di 
valutazione – I risultati di 
PIPOL (Piano Integrato di 
Politiche per l'Occupazione ed il 
Lavoro) 

IVET 

  Survey, Administrative data 

national 

sample 

collection instrument 

IVET 

  Survey, Administrative data 

federal/regional  sample 

collection instrument 

77 

IT6 

78 

IT7 

79 

IT8 

80 

IT9 

81 

IT10 

82 

LI1 

Youth Study 2017 

Jugendstudie 2017 

HE 

  Survey 

national 

sample 

March, 2020 

130 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

83 

LT1 

Human resource demand 
forecasting system 

Žmogiškųjų išteklių paklausos 
prognozavimo sistema 

IVET, HE 

  Administrative data 

national 

collection instrument 

Basis 
(reference 
population)4 

total reference 
population 

84 

LT2 

National survey of higher 
education graduates in Lithuania 
executed in 2014 

Lietuvos aukštųjų mokyklų 
absolventų apklausa, atlikta 
2014 m.  

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

85 

LU1 

Transition School-Active Life 
(TEVA) 

Transition École-Vie Active 
(TEVA) 

IVET 

  Administrative data 

collection instrument 

national 

total reference 
population 

86 

LV1 

Careers and Mobility of 
Doctorate Holders 

Latvijas Zinātņu doktoru 
tālākās karjeras apsekojums 

87 

LV2 

“Higher education graduate 
monitoring”  (This section is 
embedded in “Higher education 
quality monitoring system” 

“Augstākās izglītības 
absolventu monitorings” (šī  
sadaļa ir integrēta augstākās 
kvalitātes monitoringa sistēmā) 

HE 

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

  Administrative data 

collection instrument 

national 

total reference 
population 

88 

LV3 

VET graduate tracking system 

Profesionālās izglītības 
absolventu reģistrs. 

IVET, CVET 

  Administrative data 

national 

collection instrument 

89 

MT1 

Graduate Tracer Study 

Graduate Tracer Study 

IVET, CVET, 
HE 

  Survey 

national 

sample 

90 

MT2 

EUROGRADUATE Pilot Survey 

EUROGRADUATE Pilot Survey 

HE 

  Survey 

national 

sample 

91 

NL1 

HBO-Monitor (HBO = Dutch 
Universities of Applied Sciences 
(in Dutch: hogescholen)) 

HBO-Monitor 

HE 

  Survey, Administrative data 

national 

collection instrument 

92 

NL2 

National Alumni Survey 

Nationale Alumni Enquête 

HE 

  Survey 

national 

total reference 
population 

total reference 
population 

March, 2020 

131 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

93 

NL3 

Vocational Education and Adult 
Education Monitor / BVE-
monitor / School Leavers Survey 

Beroepsonderwijs en 
volwasseneneducatie Monitor /  
BVE-Monitor / 
Schoolverlatersonderonderzoek 

IVET, CVET 

  Survey, Administrative data 

national 

collection instrument 

Basis 
(reference 
population)4 

total reference 
population 

94 

NL4 

SEO Study & Work (SEO = SEO 
Amsterdam Economics, 
economic research agency) 

SEO Studie & Werk 

HE 

  Administrative data 

collection instrument 

national 

total reference 
population 

95 

NL5 

Fine Art Monitor 

Kunsten-Monitor (KUO-
Monitor) 

HE, Others 

  Survey, Administrative data 

national 

collection instrument 

total reference 
population 

96 

NL6 

Insights into career outcomes 
and skills of Dutch graduates 
with LinkedIn data 

Inzicht in carrières en skills 
met LinkedIn data 

HE 

  Administrative data 

national 

sample 

collection instrument, Other 
Source of discrete mass-
data 

97 

NO1 

National Education Data Base 
(part of Statistics Norway) 

Arbeidskraftsundersøkelsen  

IVET, CVET, 
HE, Others 

  Administrative data 

collection instrument 

national 

sample 

98 

NO2 

Graduate Survey (Master's) 

Kandidatundersøkelsen 

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

99 

NO3 

Special Graduate Survey 
(Master's) 

100 

NO4 

Upper-secondary vocational 
education (IVET) graduate 
survey 

101 

NO5 

Survey of graduates from Post-
secondary vocational schools 

Spesialkandidatundersøkelsen  HE 

  Survey 

national 

sample 

Fagarbeiderundersøkelsen 

IVET 

  Survey 

national 

Fagskolekandidatundersøkelsen  CVET 

  Survey 

national 

total reference 
population 

total reference 
population 

102 

PL1 

Vocational school graduate 
tracking system (Polish 

Monitorowanie losów 
absolwentów szkół 

IVET, CVET 

  Survey, Administrative data 

national 

sample 

collection instrument 

March, 2020 

132 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

Basis 
(reference 
population)4 

acronym: MLASZ) - the first 
round (graduates of vocational 
schools from the 2016/2017 
school year: monitoring of 
vocational school graduates - 
the first round) 

zawodowych - pierwsza 
runda (MLASZ) / Absolwenci 
szkół zawodowych z roku 
szkolnego 2016/2017: 
monitoring losów 
edukacyjnozawodowych 
absolwentów szkół 
zawodowych - pierwsza runda 

103 

PL2 

104 

PT1 

105 

PT2 

106 

PT3 

107 

RO1 

The Polish Graduate Tracking 
System (Polish acronym: ELA); 
hereafter referred to as ELA 
system.  

Ekonomiczne Losy 
Absolwentów (ELA) 

HE 

  Administrative data 

collection instrument 

national 

total reference 
population 

Data and statistics on Higher 
Education courses: indicator on 
the percentage of recent 
graduates registered in the 
public employment service as 
unemployed 

Dados e estadisticas de cursos 
superiores: indicador 
percentagem de recém-
diplomados do curso que estão 
registados no IEFP como 
desempregados 

Observatory of secondary 
students’ trajectories. Youth in 
post-secondary survey. 

Observatório dos Trajectos dos 
Estudantes do Ensino 
Secundário. Jovens no pós-
secundário. 

HE 

  Survey, Administrative data 

national 

collection instrument 

total reference 
population 

IVET 

  Survey, Administrative data 

national 

collection instrument 

total reference 
population 

Long-term common output and 
result indicators for ESF 
investments  

Indicadores Comuns 
Comunitários de resultado de 
longo prazo 

IVET, CVET 

  Administrative data 

national 

collection instrument 

total reference 
population 

Monitoring the socio-
professional insertion of VET 
graduates at 6 and 12 months 
after graduation 

Monitorizarea insertiei socio-
profesionale a absolventilor IPT 
la 6 si la 12 luni de la absolvire 

IVET, CVET 

  Survey 

federal/regional  total reference 

population 

March, 2020 

133 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

108 

RO2 

National study of monitoring the 
labour market insertion of 
higher education graduates  

Studiul naţional de 
monitorizare a inserţiei pe 
piaţa muncii a absolvenţilor din 
învăţământul superior 

HE 

  Survey 

national 

Basis 
(reference 
population)4 

total reference 
population 

109 

SE1 

Entrance on the labour market 
after upper secondary school 

Inträdet på arbetsmarknaden 
bland gymnasieavgångna 

IVET, 
Others 

  Survey, Administrative data 

national 

sample 

collection instrument 

110 

SE2 

Establishment on the labour 
market - What young people do 
after upper secondary education 

Vad ungdomar gör efter 
gymnasieskolan 

IVET, 
Others 

  Administrative data 

collection instrument 

national 

total reference 
population 

111 

SE3 

Entrance on the Labour Market 
after higher education 

Inträdet på arbetsmarknaden 
efter högskolestudier 

HE 

  Survey, Administrative data 

national 

sample 

collection instrument 

112 

SE4 

Establishment on the labour 
market after higher education 

Etablering på arbetsmarknaden 
efter hogskolestudier 

HE 

  Administrative data 

collection instrument 

national 

CVET 

  Survey 

national 

total reference 
population 

total reference 
population 

113 

SE5 

114 

SE6 

Entrance on the labour market 
after higher vocational 
education 

Studerandes sysselsättning 
2018 - Examinerade från 
yrkeshögskolan 2017 

Establishment on the labour 
market after higher vocational 
education 

Etablering på arbetsmarknaden 
efter kvalificerade 
yrkesutbildningar och 
yrkeshögskoleutbildningar 

CVET 

  Administrative data 

collection instrument 

national 

total reference 
population 

115 

SE7 

Operational programme for 
investing in growth and 
employment 2012-2020 

Operativt Program:  Nationellt 
socialfondsprogram för 
investering för tillväxt och 
sysselsättning 2014-2020 

IVET, CVET, 
Others 

national 

116 

SI1 

Monitoring of employability of 
graduates of upper-secondary 
vocational and technical schools 

Spremljanje zaposljivosti 
diplomantov srednjih poklicnih 
in strokovnih šol  

IVET 

  Survey 

national 

sample 

March, 2020 

134 

 
 
 
   
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Nbr.  Country  Title of measure in English 

Titel of measure in original 
language 

System 
coverage1 

  General type/ Source2 

Area/ level3 

117 

SI2 

Records and analytical 
information system for higher 
education in the Republic of 
Slovenia (eVŠ) 

Evidenčni in analitski 
informacijski sistem visokega 
šolstva v Republiki Sloveniji 
(eVŠ) 

HE 

  Administrative data 

collection instrument 

national 

Basis 
(reference 
population)4 

total reference 
population 

118 

SK1 

Tracking of school and HE 
graduates' unemployment 
through administrative data    

Uplatnenie absolventov 
strednych a vysokych skol v 
praxi 

IVET, HE 

  Administrative data 

national 

collection instrument 

total reference 
population 

119 

SK2 

Employment of university 
graduates 

Uplatnenie absolventov 
vysokých škôl 

HE 

  Survey 

national 

sample 

120 

UK1 

Graduate Outcomes survey 

Graduate Outcomes survey 

HE 

  Survey 

national 

121 

UK2 

Longitudinal Education 
Outcomes (LEO) study 

Longitudinal Education 
Outcomes (LEO) study 

IVET, CVET, 
HE 

  Administrative data 

collection instrument 

national 

total reference 
population 

total reference 
population 

122 

UK3 

Survey of Further Education 
College Leavers 

Survey of Further Education 
College Leavers 

IVET 

  Survey 

federal/regional  sample 

123 

UK4 

College Leaver Destinations 
(CLD) 

College Leaver Destinations 
(CLD) 

IVET, CVET 

  Survey, Administrative data 

federal/regional  total reference 

collection instrument 

population 

Source: ICF/3s.  

1 System coverage: initial VET (IVET), continuing VET (CVET), higher education (HE), Others; 

2 General type/source: Survey, Administrative data collection instrument, Census, Other Source of discrete mass-data; 

3 Area/level of intervention: national, federal/regional; 

4 Basis: total reference population, sample; 

5 Reasons for tracking: policy, institutional, other. 

*Note: these measures are not strictly graduate tracking as data is collected at one point in time only. 

March, 2020 

135 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Annex 4.  Annexes to chapter 4 

In the following the methodology for the assessment of each country’s progress towards 
meeting the Recommendation of the Council of the European Union is described in detail. 
The following considerations affected the analysis: 

  Broad features of tracking systems enable the specific requirements in the 
Recommendation to be grouped and to remove some double counting; for 
example, not scoring aspects of coverage twice with separate assessments for 
groups covered and the approaches available. 

  Weighting the criteria to reflect their importance in the achievement of the 

Recommendation. 'Inclusion’ is critical so has over a third of the score to guide an 
overall assessment of data quality; longitudinality, quality of data and 
dissemination and use are given 20% each. 

  As the Recommendation focuses on surveys and administrative data collection 

instruments, this focus is also reflected in this analysis. Surveys and 
administrative data are the most common methods used anyhow: 98% of the data 
collection approaches are either surveys (50%) or administrative data collection 
instruments (48%). Census is only used in one measure, other sources of discrete 
mass data are used in two measures. 

The following table provides an overview about the benchmarking criteria which were 
defined on basis of the Recommendation, relevant elements of country system level 
graduate tracking measures which were taken into account for the analysis, the rating 
score and scale as basis for the qualitative assessment.   

Table 63.  Assessment of countries’ progress towards meeting the Council 

Recommendation 

Benchmarking 
criteria 

Elements of 
country system 
level graduate 
tracking   

Rating score out 
of 100 

Out of 25 

Inclusion of 
graduate 
programmes:  

coverage of the 
relevant graduate 
programmes in 
HE, IVET and CVET 
by regular survey 
and administrative 
data analysis 

Inclusion of 
graduates from 
IVET (upper sec 
and work 
based/apprentices, 
CVET (work-based 
and provider 
based), HE 
(graduate and post 
grad)  

Qualitative 
assessment 
(broad five-point 
scale) 

Complete coverage 
(25) 

Nearly complete 
coverage (missing 
one group per 
method) (20) 

Good coverage (all 
groups covered by 
at least one 
method) (15) 

Limited coverage 
(missing groups by 
any method and 
other gaps) (10) 

(Nearly) no 
coverage apart 
from occasional 
one-off measures 
(5) 

March, 2020 

136 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Rating score out 
of 100 

Out of 15 

Benchmarking 
criteria 

Inclusion of 
graduates:  

coverage of the 
graduate 
population  

Elements of 
country system 
level graduate 
tracking   

Inclusion of all 
graduates in each 
cohort in surveys 
and administrative 
data analysis - so 
capturing 
graduates who 
have migrated (in 
surveys) and those 
who have dropped 
out (in surveys 
and admin data) 
and achieving 
responses to 
surveys from 
sufficient 
graduates 
representative of 
the total 
population to 
enable sub-
analysis  

Longitudinality:  

tracks graduates 
at different points 
after they have 
graduated   

All graduates are 
tracked at regular 
specified intervals 
in both surveys 
and administrative 
data analysis 

Out of 20 

Qualitative 
assessment 
(broad five-point 
scale) 

Complete coverage 
(15) 

Nearly complete 
coverage (missing 
one group) (12) 

Good coverage 
(missing two 
groups) (10) 

Limited coverage 
(missing cohorts 
and sub-groups, 
convenience 
samples, 
insufficient sample 
sizes) (8) 

(Nearly) no 
coverage except 
occasional one-off 
measures (5) 

Completely 
achieved (20) 

Nearly achieved 
(tracking at two or 
more points after 
graduation by at 
least one measure 
covering two 
sectors only) (16) 

Partially achieved 
(tracking at two or 
more points after 
graduation by at 
least one measure 
covering one 
sector only) (12) 

Limited 
achievement (only 
one/some sub-
group/s tracked) 
(8) 

(Nearly) no 
evidence of 
longitudinal 
tracking (4) 

March, 2020 

137 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Rating score out 
of 100 

Out of 20 

Out of 20 

Benchmarking 
criteria 

Quality of data:  

provides 
quantitative and 
qualitative data 
which meets a 
wide variety of 
needs 

Dissemination and 
use of data: 

different users and 
forms of use of the 
data  

Elements of 
country system 
level graduate 
tracking   

Administrative 
data includes 
information on 
graduates’ pay, 
employment, 
unemployment 
linked to 
educational 
achievement. 
Survey data 
includes 
information on 
further education 
and training, 
employment and 
career progression 
and relevance of 
education linked to 
educational 
achievement and 
socio-biographical 
information.    

Data is available in 
suitable formats 
for use by policy 
makers, providers 
and researchers to 
inform career 
guidance, 
curriculum 
development, skills 
needs 
assessments, 
employment and 
education planning 
at national as well 
as provider levels 

 Source: research ICF, 3s and CHEPS. 

Qualitative 
assessment 
(broad five-point 
scale) 

Completely 
achieved (20) 

Nearly achieved 
(one information 
area missing for 
one group) (16) 

Partially achieved 
(several 
information areas 
missing for more 
than one group) 
(12) 

Limited 
achievement (all 
groups have only 
some areas of 
information 
collected) (8) 

(Nearly) no 
evidence of 
collecting relevant 
data (4) 

Complete coverage 
(20) 

Nearly complete 
coverage (missing 
one user group 
and one use) (16) 

Good coverage 
(evidence of policy 
or provider level 
use in several 
types of use) (12) 

Limited coverage 
(few users/uses, 
little availability of 
data) (8) 

(Nearly) no 
coverage except 
occasional use of 
one-off measures  

(4) 

March, 2020 

138 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Each criterion is be analysed in a separate section below. This is followed by a 
summarizing discussion of the results at the end.    

Benchmarking criterion ‘Inclusion of graduate programmes’ 

The criterion ‘Inclusion of graduate programmes’ focuses on the coverage of the relevant 
graduate programmes in HE, IVET and CVET by regular survey and administrative data 
analysis. The following items were taken into account for the analysis of the coverage of 
the inclusion: 

  Which education sectors are covered by the graduate tracking measures in a 

country? (IVET, CVET, HE) 

  Which data collection approach and research design is applied? (Survey, 

Administrative data collection) 

The results for these items were analysed for each individual measure and in summary 
per country. The qualitative assessment of the coverage of the inclusion of graduate 
programmes per country was based on the following criteria:  

  Complete coverage (25 points): all parts of the education system are covered by 

all methods 

  Nearly complete coverage (20 points): one education sector per method is missing 
  Good coverage (15 points): all education sectors are covered by at least one 

method 

  Limited coverage (10 points): more than one education sector is missing and/or 

one method is missing across all parts 

  (Nearly) no coverage (5 points): (apart from occasional one-off measures) there is 

no coverage of the education sectors and methods  

The results of the assessment can be found in the table below. Besides the assessment of 
the coverage, the table contains information on what education sectors are not covered 
via any of the graduate tracking measures, what tracking methods are not applied or 
what combinations of education sectors and methods are missing, in each country, as 
relevant. 

Table 64.  Inclusion of graduate programmes: Coverage of relevant graduate 

programmes in IVET, CVET and HE by survey and administrative data analyses 

Country 

Complete 
coverage 
(25 points) 

Nearly 
complete 
coverage  

(20 points) 

20 

Austria 

Belgium (Flanders) 

Belgium (France)  

Bulgaria  

Croatia 

March, 2020 

Good 
coverage 

Limited 
coverage 

(15 
points) 

(10 
points) 

(Nearly) 
no 
coverage 

Missing 
education 
sectors 

Missing 
methods 

Missing combination 
of education sectors 
and methods 

(5 points) 

15 

 - 

 - 

 - 

CVET survey 

survey 

 - 

 10* 

 HE 

 - 

IVET survey,  

10 

10 

HE admin data,  

HE survey 

CVET 

 - 

CVET survey,  

IVET, 
CVET 

admin 
data 

CVET admin data,  
HE survey 

IVET survey, 

IVET admin data,  
CVET survey,  

139 

 
 
 
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

Complete 
coverage 
(25 points) 

Nearly 
complete 
coverage  

(20 points) 

Good 
coverage 

Limited 
coverage 

(15 
points) 

(10 
points) 

(Nearly) 
no 
coverage 

Missing 
education 
sectors 

Missing 
methods 

Missing combination 
of education sectors 
and methods 

(5 points) 

15 

15 

Cyprus 

Czech Republic 

Denmark 

Estonia 

Finland 

France 

25 

25 

20 

Germany 

25 

25 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

Luxembourg 

March, 2020 

5 

all 

10 

CVET 

 - 

 - 

 - 

 - 

 - 

5 

all 

10 

CVET 

5 

all 

 - 

CVET 

 - 

all 

 - 

 - 

 - 

 - 

admin 
data 

 - 

all 

 - 

all 

 - 

 - 

 - 

IVET, 
CVET 

admin 
data 

CVET 

 - 

CVET, HE 

survey 

10 

10 

10 

10 

CVET admin data, 
HE admin data 

all 

CVET survey,  

CVET admin data 

 - 

CVET admin data 

 - 

 - 

 - 

all 

IVET admin data,  
CVET survey,  

CVET admin data 

 all 

 - 

CVET survey,  

CVET admin data 

IVET survey,  
CVET survey 

IVET survey,   

IVET admin data,  
CVET survey,  

CVET admin data, 
HE survey 

IVET survey,  
CVET survey,  

CVET admin data 

IVET survey,  
CVET survey,  

CVET admin data,  
HE survey,  

HE admin data 

140 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

Complete 
coverage 
(25 points) 

Nearly 
complete 
coverage  

(20 points) 

Good 
coverage 

Limited 
coverage 

(15 
points) 

(10 
points) 

(Nearly) 
no 
coverage 

Missing 
education 
sectors 

Missing 
methods 

Missing combination 
of education sectors 
and methods 

(5 points) 

Malta 

15 

Netherlands 

Norway 

Poland 

Portugal 

25 

25 

20 

 - 

 - 

 - 

 - 

admin 
data 

IVET admin data,  
CVET admin data, 
HE admin data 

 - 

 - 

 - 

 - 

 - 

HE survey 

 10** 

 HE 

admin 
data 

IVET admin data, 

CVET admin data, 

15 

 - 

CVET survey,  

HE admin data,  

HE survey 

admin 
data 

IVET survey,  
CVET survey, 
HE survey 

10 

10 

CVET 

 - 

CVET 

 - 

 - 

 - 

 - 

-  

 - 

 - 

IVET survey,  
CVET survey,  

CVET admin data 

IVET admin, 
CVET survey,  

CVET admin data, 
HE survey 

CVET survey 

 - 

 - 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United Kingdom 

25 

25 

20 

Source: research ICF, 3s and CHEPS. 

*) A new measure covering HE in Belgium (France) is expected for 2020 (‘Cadastre des 
parcours educatifs’ / ‘Register of educational trajectories’). 

**) In Portugal, the government has developed an ‘indicator on the percentage of recent 
graduates registered in the public employment service’ covering HE graduates, but has 
not developed tracking as such for this level. VET graduates are, however, tracked 
through a survey covering all upper secondary graduates which has been conducted 
systematically since 2010. 

Graduate tracking covers all the education sectors and methods in Germany, Denmark, 
Finland, Ireland, Netherlands, Norway, Sweden and UK. Coverage is nearly complete in 
Austria, Estonia, Spain, and Poland. In Cyprus, Greece, and Iceland there is no coverage 
on systemic level.   

March, 2020 

141 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Benchmarking criterion ‘Inclusion of graduates’ 

The criterion ‘Inclusion of graduates’ relates to the coverage of the graduate population 
within each country, i.e. the inclusion of all graduates in each cohort in surveys and 
administrative data collection.   

The following items were taken into account for the analysis of the coverage of the 
inclusion of graduates: 

  Which graduate population is included by the graduate tracking measures in a 

country? (completers, people who have left without completing/drop-outs, people 
who migrate to another country after graduation) 

  Are there limitations because of representativeness of the sample? (applies to 

administrative data collection instruments and surveys) 

  Is a survey response rate too small or biased for sub analysis? (applies to surveys) 

The qualitative assessment of the criterion ‘Inclusion of graduates’ was based on the 
following criteria:  

  Complete coverage (15 points): all relevant population groups and 

representativeness of data 

  Nearly complete coverage (12 points): one group of graduate population missing 

(migrants or drop-outs), representativeness of data  

  Good coverage (10 points): two groups of graduate population missing, 

representativeness of data  

  Limited coverage (8 points): missing cohorts and sub-groups, convenience 

samples, insufficient sample sizes 

  (Nearly) no coverage (5 points): (apart from occasional one-off measures) there is 

no coverage of the different graduate population groups and no 
representativeness of data 

Two measures have been excluded from this analysis, as they currently are not used for 
tracking graduates: AT4 refers to a student social survey which tracks students, not 
graduates. ES2 focuses on people registered at Public Employment Services; this 
measure includes also graduates, but does not focus on this population. For further 
information see the country factsheets.  

The results of the assessment can be found in the table below. For each country, the 
assessment checks if there is at least one measure that covers all relevant population 
groups and provides representative data. Besides the assessment of the coverage the 
table contains information on which groups of graduate population are missing and what 
is the measure/s coverage in term of education sector/s. 

Table 65.  Inclusion of graduates: population covered and representativeness 

Country 

Complete 
coverage 

(15 points) 

Nearly 
complete 
coverage 
(12 points) 

Good 
coverage 
(10 points)  

Limited 
coverage  

(Nearly) no 
coverage 

(8 points)  

 (5 points)  

Relevant 
measure/s  
(highest 
coverage) 

Missing group/s 

Austria 

15 

Belgium (Flanders) 

Belgium (France)  

Bulgaria  

12 

12 

AT1, AT2, 
AT3, AT5 

- 

BE-NL1 

Migrated graduates 

BE-FR2 

Migrated graduates 

8 

- 

Drop-outs, migrated 
graduates 

March, 2020 

142 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Complete 
coverage 

(15 points) 

Nearly 
complete 
coverage 
(12 points) 

Good 
coverage 
(10 points)  

Limited 
coverage  

(Nearly) no 
coverage 

(8 points)  

 (5 points)  

Relevant 
measure/s  
(highest 
coverage) 

Missing group/s 

Country 

Croatia 

Cyprus 

5 

5 

5 

5 

- 

- 

Completers,  

drop-outs, migrated 
graduates 

Completers,  

drop-outs, migrated 
graduates 

CZ4 

Migrated graduates 

DK1, DK2 

Migrated graduates 

EE1 

Migrated graduates 

- 

FR1 

Migrated graduates 

DE3, DE4, 
DE5 

- 

- 

- 

- 

Completers,  

drop-outs, migrated 
graduates 

- 

Completers,  

drop-outs, migrated 
graduates 

IE4 

Migrated graduates 

- 

- 

- 

- 

- 

- 

NL4 

- 

Drop-outs, migrated 
graduates 

Drop-outs, migrated 
graduates 

Migrated graduates 

Drop-outs, migrated 
graduates 

Migrated graduates 

Drop-outs 

Drop-outs 

Drop-outs, migrated 
graduates 

143 

12 

12 

12 

12 

12 

Czech Republic 

Denmark 

Estonia 

Finland 

France 

15 

Germany 

15 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

Luxembourg 

Malta 

Netherlands 

Norway 

March, 2020 

10 

10 

10 

10 

8 

8 

8 

8 

8 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Country 

Complete 
coverage 

(15 points) 

Nearly 
complete 
coverage 
(12 points) 

Good 
coverage 
(10 points)  

Limited 
coverage  

(Nearly) no 
coverage 

(8 points)  

 (5 points)  

Relevant 
measure/s  
(highest 
coverage) 

Missing group/s 

Poland 

12 

PL1, PL2 

Migrated graduates 

Portugal 

15 

PT2 

- 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United Kingdom 

8 

10 

10 

10 

12 

12 

- 

- 

Drop-outs, migrated 
graduates 

Drop-outs, migrated 
graduates 

SI2 

Migrated graduates 

ES3, ES7 

- 

SE2, SE4 

Migrated graduates 

UK2 

Migrated graduates 

Source: research ICF, 3s and CHEPS. 

The main results of the assessment are described in the following: 

  Only four measures (AT2, DE3, HU3, PT2) provide data for all relevant population 

groups and do provide representative data.  

  The target group of persons who have left their studies without completing is 

included in 36 measures in Austria (AT1, AT2, AT3), Belgium (BE-FR2, BE-NL1), 
Czech Republic (CZ4), Germany (DE1, DE3, DE4, DE5), Denmark (DK1, DK2), 
Estonia (EE1), Spain (ES1, ES3, ES5), Finland (FI1), France (FR1, FR2, FR3), 
Hungary (HU3), Ireland (IE2, IE4), Liechtenstein (LI1), Luxembourg (LU1), Poland 
(PL1, PL2), Portugal (PT2, PT3), Sweden (SE1, SE2, SE3, SE4), Slovenia (SI1, 
SI2), and United Kingdom (UK2). 

  The target group of persons who migrated to another country after graduation is 
only part of 13 measures within 8 countries: AT2 and AT 5 in Austria, DE3 and 
DE10 in Germany, ES7 in Spain, FI2 and FI3 in Finland, HU3 in Hungary, LV3 in 
Latvia, MT2 in Malta, NL4 and NL6 in the Netherlands as well as PT2 in Portugal.  

  No limitations because of representativeness of the sample are reported for 63 

measures. This information was not available for 29 measures.  

  Survey response rates were considered adequate in 69 measures; in 20 measures 
the survey response rate was too small or biased for further sub analysis. This 
information was not available in 34 cases. 

Benchmarking criterion for ‘Longitudinality’ 

The criterion ‘Longitudinality’ aims to determine if a country has longitudinal data on its 
graduates – that is if graduates are tracked at regular specified intervals through surveys 
and/or administrative-data based tools.  

The following item was taken into account for the analysis: 

  Is the cohort followed up (longitudinal study – i.e. the same individual is followed 

twice or more times)? 

The qualitative assessment of the criterion ‘Longitudinality’ was based on the following 
criteria:  

March, 2020 

144 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

  Completely achieved (20 points): tracking at two points after graduation – or more 
– by at least one measure covering all the sectors: IVET, HE and CVET and using 
survey and administrative data matching 

  Nearly achieved (16 points): tracking at two points after graduation – or more – 
by at least one measure in the country covering all the sectors (IVET, HE, CVET) 
and using either survey or admin data 

  Partially achieved (12 points): tracking at two points after graduation – or more – 

by at least one measure in the country covering two sectors only 

  Limited achieved (8 points): tracking at two points after graduation – or more – by 

at least one measure in the country covering one sector only 

  Little or no evidence of longitudinal tracking (4 points) 

The results of the assessment can be found in the table below. For each country, relevant 
measure/s with highest coverage are listed as well as missing sectors and/or other 
limitations 

Table 66.  Longitudinality of tracking 

Nearly 
achieved  

Partially 
achieved 

Limited 
achieved 

(Nearly) not 
achieved  

(12 points) 

(8 points) 

(4 points) 

Relevant 
measure/s  
(highest 
coverage) 

Missing 
sectors, 
methods 
and other 
limitations 

AT1 

- 

(16 
points) 

16 

16 

Country 

Completely 
achieved 
(20 points) 

Austria 

Belgium (Flanders) 

Belgium (France)  

Bulgaria  

Croatia 

Cyprus 

8 

BE-NL2 

Survey 

BE-FR2 

- 

4 

4 

4 

- 

- 

- 

CVET 

IVET, CVET;  

admin data 

IVET, CVET, 
HE;  

survey, 
admin data 

Czech Republic 

8 

CZ5 

CVET 

Denmark 

Estonia 

Finland 

France 

Germany 

20 

Greece 

16 

16 

12 

DK1, DK3 

4 

- 

- 

- 

FI1, FI7, FI8 

- 

FR1 

DE1 

- 

admin data 

- 

IVET, CVET, 
HE;  

admin data 

4 

Hungary 

12 

HU1 

- 

March, 2020 

145 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Completely 
achieved 
(20 points) 

Nearly 
achieved  

Partially 
achieved 

Limited 
achieved 

(Nearly) not 
achieved  

(16 
points) 

(12 points) 

(8 points) 

(4 points) 

Relevant 
measure/s  
(highest 
coverage) 

Missing 
sectors, 
methods 
and other 
limitations 

Country 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

Luxembourg 

Malta 

Netherlands 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

12 

12 

12 

12 

12 

12 

8 

8 

8 

8 

4 

4 

4 

4 

4 

4 

- 

IE5 

- 

- 

IT1, IT2, 
IT6, IT7 

CVET 

LV2 

- 

4 

- 

LT2 

LU1 

- 

- 

- 

PL2 

IVET, CVET;  

admin data 

CVET 

CVET, HE;  

survey 

admin data 

- 

- 

PL1: system 
at 
development 
stage 

PT2, PT3 

- 

RO1 

admin data 

- 

- 

ES5 

SE2 

UK2 

CVET 

CVET 

- 

- 

- 

United Kingdom 

16 

Source: research ICF, 3s and CHEPS. 

The only with complete coverage of longitudinal data, all sectors and methods is 
Germany. Countries which have nearly achieved full coverage are Austria, Belgium 
(France), Finland, France and UK. Countries with no coverage are Bulgaria, Cyprus, 
Estonia, Greece, Croatia, Iceland, Liechtenstein, Malta, Netherlands, Norway, Slovenia 
and Slovakia. 

March, 2020 

146 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Benchmarking criterion on the ‘Quality of data’ 

The criterion ‘Quality of data’ aims to determine if quantitative and qualitative data which 
are collected in the graduate tracking measures within each country provide a variety of 
information (e.g. information on graduates’ pay, employment, unemployment,  
information on further education and training, employment and career progression, etc.).  

The following items were taken into account for the analysis: 

  What are the main indicators covered by the instrument? (Focus on the following 
options: socio-biographical and socioeconomic information, employment status, 
further education and training pathways, satisfaction, relevance/utilisation of 
acquired skills at the workplace, link to level, field of study and provider) 

The qualitative assessment of the criterion ‘Quality of data’ was based on the following 
criteria:  

  Completely achieved (20 points): all relevant data are collected for all education 

sectors (IVET, HE and CVET) 

  Nearly achieved (16 points): one data area missing for more than one education 

sector (IVET, HE or CVET) 

  Partially achieved (12 points): several data areas missing for more than one 

education sector 

  Limited achieved (8 points): all groups have only some areas of information 

collected 

  (Nearly) not achieved (4 points): little or no evidence of collecting relevant data 

The following table contains the results of the assessment and information about relevant 
measure/s within highest coverage within each country. Complete coverage of all data 
and education sectors within one measure is only given for Germany (DE1) and Malta 
(MT1). 

Table 67.  Quality of data of tracking 

Country 

Completely 
achieved 
(20 points) 

Nearly 
achieved  

Partially 
achieved 

Limited 
achieved 

(16 points) 

(12 points) 

(8 points) 

(Nearly) 
not 
achieved  

(4 points) 

Relevant 
measure/s  
(highest 
coverage) 

Education 
sector covered: 

IVET/CVET/HE 

Austria 

16 

Belgium (Flanders) 

Belgium (France)  

Bulgaria  

Croatia 

Cyprus 

Czech Republic 

Denmark 

Estonia 

12 

12 

12 

12 

AT5 

IVET, CVET, HE 

BE-NL1 

IVET, CVET, HE 

BE-FR1 

IVET, CVET, HE 

HR1 

- 

4 

IVET, HE 

HE 

- 

16 

16 

8 

CZ1, CZ2, 
CZ3, CZ5 

IVET, HE 

 DK6 

EE2 

IVET, CVET, HE 

IVET, CVET, HE 

March, 2020 

147 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Completely 
achieved 
(20 points) 

Nearly 
achieved  

Partially 
achieved 

Limited 
achieved 

(16 points) 

(12 points) 

(8 points) 

(Nearly) 
not 
achieved  

(4 points) 

Relevant 
measure/s  
(highest 
coverage) 

Education 
sector covered: 

IVET/CVET/HE 

Country 

Finland 

France 

Germany 

20 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

Liechtenstein 

Lithuania 

Luxembourg 

Malta 

20 

Netherlands 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United Kingdom 

16 

16 

16 

16 

16 

16 

16 

16 

16 

16 

12 

12 

12 

12 

12 

12 

12 

12 

12 

4 

4 

FI2, FI3, FI4, 
FI7 

IVET, CVET, HE 

FR1 

IVET, CVET, HE 

DE1, DE4, 
DE10 

IVET, CVET, HE 

- 

- 

HU1 

IVET, HE 

- 

IE1 

- 

IVET, CVET, HE 

IT2, IT3, IT6 

IVET, HE 

LV2 

LI1 

IVET, CVET, HE 

HE 

LT1, LT2 

IVET, HE 

LU1 

IVET 

MT1, MT2 

IVET, CVET, HE 

NL1, NL3, 
NL5 

NO2, NO3, 
NO4, NO5 

IVET, CVET, HE 

IVET, CVET, HE 

PL1 

PT2 

IVET, CVET, HE 

IVET, CVET, HE 

RO1, RO2 

IVET, CVET, HE 

SK2 

SI1 

IVET, HE 

IVET, HE 

ES3, ES4 

IVET, CVET, HE 

SE1, SE5 

IVET, CVET, HE 

UK1, UK2 

IVET, CVET, HE 

Source: research ICF, 3s and CHEPS. 

March, 2020 

148 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Benchmarking criterion on ‘Dissemination and use of data’ 

The criterion ‘Dissemination and use of data’ contains analyses if data of graduate 
tracking measures are available in suitable formats for different user groups (policy 
makers, providers, researchers) and for different forms of usage (e.g. to inform career 
guidance, curriculum development, skills needs assessments, employment and education 
planning).  

The following items were taken into account for the analysis: 

  Who uses the results? (including an analysis of open answers) 
  Please indicate for what data are used (strengthen career guidance, support the 
design and current curriculum, improve skills matching, plan for employment, 
education and social needs, monitor and evaluate education policies, contribute to 
policy development at national level) 

The qualitative assessment was based on the following criteria:  

  Complete coverage (20 points): all user groups and forms of use covered, all 

sectors (IVET, CVET, HE) covered 

  Nearly complete coverage (16 points): one user group and/or one use are missing, 

two or more sectors covered 

  Good coverage (12 points): evidence of policy or provider level use in several 

types of use, two or more sectors covered 

  Limited coverage (8 points): few user groups and/or forms of use, little availability 

of data, one or two sectors covered 

  No coverage (4 points): apart from occasional one-off measures there is no 

coverage of the different user groups and user forms 

The results of the assessment can be found in the table below. Besides the assessment of 
the coverage the table contains the information, which user groups and/or forms of 
usage are missing per country. 

March, 2020 

149 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 68.  Coverage of the dissemination and use of data in graduate tracking measures per country 

Country  

Coverage 

Complete 
coverage 
(20 
points) 

Nearly 
complete 
coverage 
(16 
points) 

Good 
coverage 
(12 
points) 

Limited 
coverage 
(8 
points) 

(Nearly) 
no 
coverage 
(4 
points) 

Austria 

16 

12 

12 

12 

8 

4 

4 

Belgium 
(Flanders) 

Belgium 
(France)  

Bulgaria  

Croatia 

Cyprus 

Czech 
Republic 

Denmark 

20 

Estonia 

20 

Finland 

20 

France 

12 

Education 
sector 
covered: 

IVET, 
CVET,  

HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET 

HE 

- 

IVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

Missing 
users 

Missing forms of use 

* 

- 

 - 

 - 

- 

- 

n.i. 

- 

- 

- 

- 

- 

Strengthen 
career 
guidance 

Support 
design 
and 
current 
curriculum 

Improve 
skills 
matching 

Plan for 
employment, 
education 
and social 
needs 

Monitor 
and 
evaluate 
education 
policies 

Contribute 
to policy 
development 
at a national 
level 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

150 

 
 
 
  
 
  
  
 
 
 
 
 
  
  
  
  
 
 
 
  
  
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Country  

Coverage 

Complete 
coverage 
(20 
points) 

Nearly 
complete 
coverage 
(16 
points) 

Good 
coverage 
(12 
points) 

Limited 
coverage 
(8 
points) 

(Nearly) 
no 
coverage 
(4 
points) 

4 

4 

4 

4 

16 

16 

Germany 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

16 

Latvia 

20 

Liechtenstein 

Lithuania 

16 

Luxembourg 

Malta 

Netherlands 

March, 2020 

12 

12 

12 

Education 
sector 
covered: 

Missing 
users 

* 

IVET, 
CVET,  

HE 

IVET, 
CVET, HE 

- 

- 

n.i. 

IVET, HE 

- 

- 

n.i. 

IVET, 
CVET, HE 

IVET, HE 

IVET, 
CVET, HE 

HE 

IVET, HE 

IVET 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

- 

- 

- 

- 

- 

- 

- 

- 

Missing forms of use 

Strengthen 
career 
guidance 

Support 
design 
and 
current 
curriculum 

Improve 
skills 
matching 

Plan for 
employment, 
education 
and social 
needs 

Monitor 
and 
evaluate 
education 
policies 

Contribute 
to policy 
development 
at a national 
level 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

151 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Country  

Coverage 

Complete 
coverage 
(20 
points) 

Nearly 
complete 
coverage 
(16 
points) 

Good 
coverage 
(12 
points) 

Limited 
coverage 
(8 
points) 

(Nearly) 
no 
coverage 
(4 
points) 

Norway 

20 

Poland 

Portugal 

Romania 

16 

Slovakia 

Slovenia  

Spain 

Sweden 

20 

United 
Kingdom 

8 

12 

12 

12 

12 

12 

Source: research ICF, 3s and CHEPS. 

* n.i. = no information available. 

Education 
sector 
covered: 

Missing 
users 

* 

IVET, 
CVET,  

HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, HE 

IVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

IVET, 
CVET, HE 

- 

- 

- 

- 

- 

- 

- 

- 

- 

Missing forms of use 

Strengthen 
career 
guidance 

Support 
design 
and 
current 
curriculum 

Improve 
skills 
matching 

Plan for 
employment, 
education 
and social 
needs 

Monitor 
and 
evaluate 
education 
policies 

Contribute 
to policy 
development 
at a national 
level 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

Complete coverage (all user groups and forms of use) is given in Denmark, Estonia, Finland, Latvia, Norway and Sweden.  

March, 2020 

152 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Overview on results 

The following table provides an overview about the assessment per benchmarking 
criterion and country as well as an average across the five benchmarking areas for each 
country. 

Table 69.  Inclusion of graduate programmes: Coverage of relevant graduate 

programmes in IVET, CVET and HE by survey and administrative data analyses 

Inclusion of 
graduate 
programmes 

(max. 25 
points) 

Inclusion of 
graduates 

(max. 15 
points) 

Longitudinality 

Quality of data 

(max. 20 
points) 

(max. 20 
points) 

Dissemination 
and use of data 

(max. 20 
points) 

Average across 
the benchmark 
areas 

Austria 

Belgium 
(Flanders) 

Belgium 
(France)  

Bulgaria  

Croatia 

Cyprus 

20 

15 

10 

10 

10 

5 

Czech Republic  10 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Iceland 

Ireland 

Italy 

Latvia 

25 

20 

25 

15 

25 

5 

10 

5 

25 

10 

15 

Liechtenstein 

10 

Lithuania 

10 

Luxembourg 

10 

15 

12 

12 

8 

5 

5 

12 

12 

12 

10 

12 

15 

5 

12 

5 

10 

10 

8 

8 

8 

8 

16 

8 

16 

4 

4 

4 

8 

12 

4 

16 

16 

20 

4 

12 

4 

12 

12 

8 

4 

12 

8 

16 

12 

12 

12 

12 

4 

16 

8 

16 

16 

16 

20 

4 

16 

4 

16 

12 

16 

12 

12 

12 

 16 

 12 

 8 

 12 

4 

4 

12 

20 

20 

20 

12 

16 

4 

16 

4 

12 

16 

 20 

 4 

 16 

 4 

17 

12 

13 

9 

7 

4 

12 

15 

14 

17 

14 

19 

4 

13 

4 

15 

12 

12 

9 

11 

10 

March, 2020 

153 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Inclusion of 
graduate 
programmes 

(max. 25 
points) 

Inclusion of 
graduates 

(max. 15 
points) 

Longitudinality 

Quality of data 

(max. 20 
points) 

(max. 20 
points) 

Dissemination 
and use of data 

(max. 20 
points) 

Average across 
the benchmark 
areas 

Malta 

15 

Netherlands 

25 

Norway 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia  

Spain 

Sweden 

United 
Kingdom 

25 

20 

10 

15 

10 

10 

20 

25 

25 

8 

10 

10 

12 

15 

10 

8 

10 

12 

12 

10 

4 

4 

4 

8 

12 

12 

4 

4 

12 

8 

16 

20 

16 

16 

16 

12 

12 

12 

16 

12 

16 

12 

 12 

 12 

 20 

 12 

 8 

 16 

 12 

 12 

12 

 20 

 12 

12 

13 

14 

14 

12 

12 

9 

10 

14 

15 

16 

Source: research ICF, 3s and CHEPS. 

The average is assessed as follows:   

  4–5 points: (nearly) no coverage (apart from occasional one-off measures) 
  6–10 points: limited coverage 
  11–14 points: good coverage 
  15–18 points: nearly complete coverage 
  19–20 points: complete coverage 

Methodology for assessing coverage of benchmarking criteria 

The following table provides an overview about the coverage of the benchmarking criteria 
in the analysed measures as well as the coverage within each education sector: initial 
VET (IVET), continuing VET (CVET), higher education (HE). In each case, the countries to 
which the respective criterion and the respective education sector applies is listed. 

March, 2020 

154 

 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 70.  Country coverage of benchmarking criteria across IVET, CVET, HE sectors 

Benchmarking 
criteria* 

Overall coverage (from 32) 

IVET coverage  

CVET coverage   

HE coverage 

Inclusion of graduate 
programmes 

Survey collection 

AT, BE-FR, BG, CZ, DE, DK, EE, 
EL, ES, FI, FR, HR, HU, IE, IT, LI, 
LT, LV, MT, NL, NO, PL, PT, RO, 
SE, SI, SK, UK (28) 

AT, BG, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, MT, NL, NO, 
PL, PT, RO, SE, SI, UK (21) 

BE-FR, DE, DK, EE, FI, FR, 
IE, MT, NL, NO, PL, RO, SE, 
UK (14) 

AT, CZ, DE, DK, EE, ES, FI, FR, 
HR, HU, IE, IT, LI, LT, LV, MT, 
NL, NO, PT, RO, SE, SK, UK (23) 

Data administration  AT, BE-FR, BE-NL, BG, CZ, DE, 

Periodicity of 
measures 

DK, EE, ES, FI, HU, IE, IT, LT, LU, 
LV, NL, NO, PL, PT, SE, SI, SK, 
UK (24) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HU, IE, IT, LT, 
LU, LV, NL, NO, PL, PT, RO, SE, 
SI, SK, UK (26) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, IE, IT, LT, LU, 
LV, NL, NO, PL, PT, SE, SK, UK 
(22) 

AT, BE-FR, BE-NL, DE, DK, 
ES, FI, IE, LV, NL, NO, PL, 
PT, SE, UK (15) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, HU, IE, IT, LT, LV, 
NL, NO, PL, PT, SE, SI, SK, UK 
(23) 

AT, BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, LT, LU, NL, 
NO, PT, SE, SK, UK (20) 

AT, BE-FR, BE-NL, DE, DK, 
ES, FI, FR, IE, NL, NO, PT, 
SE, UK (14) 

AT, BE-NL, BG, CZ, DE, DK, EE, 
ES, FI, FR, HU, IE, IT, LT, LV, NL, 
NO, PL, PT, RO, SE, SI, SK, UK 
(24) 

Representativeness 
of data 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, IE, IT, LT, LU, LV, 
NL, NO, PL, PT, RO, SE, SI, SK, 
UK (24) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, IE, IT, LT, LU, 
NL, NO, PL, PT, RO, SE, SK, UK 
(22) 

BE-FR, BE-NL, DE, DK, EE, 
FI, FR, IE, NL, NO, PL, PT, 
RO, SE, UK (15) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, IE, IT, LT, LV, NL, 
NO, PL, RO, SE, SI, SK, UK (22) 

Sufficient response 
rate* 

AT, BE-FR, CZ, DE, ES, FI, FR, 
HR, HU, IT, LV, MT, NL, NO, PL, 
PT, RO, SE, UK (19) 

DE, ES, FI, FR, HU, IT, MT, NL, 
PL, RO, SE, UK (12) 

BE-FR, DE, FI, FR, MT, NL, 
PL, RO, SE, UK (10) 

AT, CZ, DE, ES, FI, FR, HR, HU, 
IT, LV, MT, NL, NO, PT, RO, SE, 
UK (17) 

Data availability 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HR, HU, IE, 
IT, LI, LT, LU, LV, MT, NL, NO, 
PL, PT, RO, SE, SI, SK, UK (29) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HU, IE, IT, LT, 
LU, LV, MT, NL, NO, PL, PT, 
RO, SE, SI, SK, UK (26) 

AT, BE-FR, DE, DK, EE, ES, 
FI, FR, IE, LV, MT, NL, NO, 
PL, PT, RO, SE, UK (18) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HR, HU, IE, 
IT, LI, LT, LV, MT, NL, NO, PL, 
PT, RO, SE, SI, SK, UK (28) 

Graduate population 
included 

Completers 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HR, HU, IE, 
IT, LI, LT, LU, LV, MT, NL, NO, 
PL, PT, RO, SE, SI, SK, UK (29) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HU, IE, IT, 
LT, LU, MT, NL, NO, PL, PT, 
RO, SE, SI, SK, UK (26) 

AT, BE-FR, BE-NL, DE, DK, 
EE, ES, FI, FR, HU, IE, MT, 
NL, NO, PL, PT, RO, SE, UK 
(19) 

AT, BE-FR, BG, CZ, DE, DK, EE, 
ES, FI, FR, HR, HU, IE, IT, LI, LT, 
LV, MT, NL, NO, PL, PT, RO, SE, 
SI, SK, UK (27) 

People who have left 
without completing 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HU, IE, LI, LU, PL, 
PT, SE, SI, UK (19) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HU, IE, LU, PL, 
PT, SE, SI, UK (18) 

AT, BE-FR, DE, DK, ES, FI, 
FR, IE, PL, PT (10) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, LI, PL, SE, SI, UK 
(15) 

March, 2020 

155 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Benchmarking 
criteria* 

Overall coverage (from 32) 

IVET coverage  

CVET coverage   

HE coverage 

Students (before 
completion) 

AT, CZ, DE, DK, EE, FI, HU, IE, 
IT, LI, PL, PT, SI (13) 

CZ, DE, DK, HU, IE, IT, FI, PL, 
PT (9) 

DE, DK, IE, FI, PL (5) 

AT, DE, DK, EE, FI, HU, IT, LI, SI 
(9) 

Residents in country  AT, BG, DE, ES, FI, FR, LI, LT, 

LV, MT, NL, NO, PT, SE, UK (15) 

AT, BG, DE, ES, FR, LT, LV, 
NO, PT, SE, UK (11) 

AT, DE, ES, FR, LV, NO, SE, 
UK (8) 

AT, BG, DE, ES, FI, FR, LI, LT, 
MT, NL, NO, SE, UK (13) 

Migrants to another 
country after 
graduation 

AT, DE, ES, FI, HU, LV, MT, NL, 
PT (9) 

AT, DE, HU, LV, PT (5) 

DE, LV (2) 

AT, DE, ES, FI, MT, NL (6) 

Longitudinality / 
Follow-up 

Is the cohort 
followed-up? 

AT, BE-FR, BE-NL, CZ, DE, DK, 
ES, FI, FR, HU, IE, IT, LT, LU, LV, 
PL, PT, RO, SE, UK (20) 

AT, BE-FR, CZ, DE, DK, ES, FI, 
FR, HU, IE, IT, LU, PL, PT, RO, 
SE, UK (17) 

AT, BE-FR, BE-NL, DE, DK, 
FI, FR, IE, PL, PT, RO, UK 
(12) 

AT, BE-FR, DE, DK, ES, FI, FR, 
HU, IE, IT, LT, LV, PL, RO, UK 
(15) 

Quality of data / 
main indicators 
covered 

Socio-biographical 
and socioeconomic 
information 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HR, HU, IE, IT, LI, 
LT, LU, LV, MT, NL, NO, PL, PT, 
RO, SE, SI, SK, UK (28) 

AT, BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, LT, LU, LV, 
MT, NL, NO, PL, PT, RO, SE, 
SI, SK, UK (25) 

AT, BE-FR, DE, DK, EE, FI, 
IE, LV, MT, NL, NO, PL, RO, 
SE, UK (15) 

AT, BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, HR, HU, IE, IT, LI, LT, LV, 
MT, NL, NO, PL, RO, SE, SI, SK, 
UK (25) 

Employment status 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HR, HU, IE, 
IT, LI, LT, LU, LV, MT, NL, NO, 
PL, PT, RO, SE, SI, SK, UK (29) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HU, IE, IT, 
LT, LU, LV, MT, NL, NO, PL, PT, 
RO, SE, SI, SK, UK (27) 

AT, BE-FR, BE-NL, DE, DK, 
EE, ES, FI, FR, IE, LV, MT, 
NL, NO, PL, PT, RO, SE, UK 
(19) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HR, HU, IE, IT, LI, 
LT, LV, MT, NL, NO, PL, PT, RO, 
SE, SK, UK (26) 

Further education 
and training 
pathways 

AT, BE-FR, BG, CZ, DE, DK, EE, 
ES, FI, FR, HU, IE, IT, LT, LU, LV, 
MT, NL, NO, PL, SE, SI, SK, UK 
(24) 

AT, BE-FR, BG, CZ, DE, DK, 
EE, ES, FI, FR, HU, IE, IT, LU, 
LV, MT, NL, NO, PL, PT, SE, SI, 
UK (23) 

AT, BE-FR, DE, DK, EE, FI, 
FR, IE, LV, MT, NL, NO, PL, 
SE, UK (15) 

AT, BE-FR, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, LT, LV, MT, NL, 
NO, PL, SE, SI, SK, UK (22) 

Satisfaction* 

AT, BE-FR, BG, CZ, DE, EE, ES, 
FI, FR, HR, HU, IE, IT, LI, LT, LV, 
MT, NL, NO, PL, PT, RO, SE, SI, 
UK (25) 

Relevance/utilisation 
of acquired skills at 
the workplace* 

AT, BE-FR, CZ, DE, DK, EE, ES, 
FI, FR, HR, HU, IE, IT, LT, LV, 
MT, NL, NO, PL, PT, RO, SE, SI, 
SK, UK (25) 

AT, BG, CZ, DE, EE, FI, FR, 
HU, IE, IT, MT, NL, NO, PL, PT, 
RO, SI, UK (18) 

BE-FR, DE, EE, FI, FR, IE, 
MT, NL, NO, PL, RO, SE (12) 

AT, CZ, DE, EE, ES, FI, FR, HR, 
HU, IE, IT, LI, LT, LV, MT, NL, 
NO, RO, UK (19) 

AT, CZ, DE, DK, EE, ES, FI, FR, 
HU, IE, IT, LT, MT, NL, NO, PL, 
PT, RO, SE, SI, UK (21) 

BE-FR, DE, EE, FI, FR, IE, 
MT, NL, NO, PL, RO, SE (12) 

AT, CZ, DE, DK, EE, ES, FI, FR, 
HR, HU, IE, IT, LT, LV, MT, NL, 
NO, RO, SE, SK, UK (21) 

March, 2020 

156 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Benchmarking 
criteria* 

Overall coverage (from 32) 

IVET coverage  

CVET coverage   

HE coverage 

Link to level, field of 
study and provider 

AT, BE-NL, BG, CZ, DE, EE, ES, 
FI, FR, HU, IE, IT, LI, LT, LV, MT, 
NL, NO, PL, RO, SE, SI, SK, UK 
(24) 

Place of residence / 
migration to other 
countries 

AT, BE-FR, BE-NL, CZ, DE, DK, 
EE, ES, FI, FR, HU, IE, IT, LI, LT, 
LV, MT, NL, NO, RO, SE, SI, SK, 
UK (24) 

AT, BE-NL, BG, CZ, DE, EE, ES, 
FI, FR, IE, IT, LT, LV, MT, NL, 
NO, PL, SE, SI, UK (20) 

AT, BE-NL, DE, EE, FI, FR, 
IE, LV, MT, NL, NO, PL, SE, 
UK (14) 

AT, BE-NL, CZ, DE, EE, ES, FI, 
FR, HU, IE, IT, LI, LT, LV, MT, NL, 
NO, RO, SE, SI, SK, UK (22) 

AT, BE-NL, DE, DK, ES, FI, FR, 
HU, IE, IT, LT, MT, NL, NO, SE, 
SI (16) 

AT, BE-FR, DE, FI, FR, IE, 
MT, NL, NO, SE (10) 

AT, BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, LI, LT, LV, MT, 
NL, NO, RO, SI, SK, UK (22) 

Dissemination and 
use of data /  
Missing forms of use 

All forms of use (6-7 
options) 

Good coverage of 
forms of use (4-5 
options) 

EE, FI, HU, LT, LV, NO, SE (7) 

EE, FI, LT, LV, NO, SE (6) 

FI, LV, NO, SE (4) 

EE, FI, HU, LT, LV, NO (6) 

AT, DE, DK, FI, HU, IT, LT, MT, 
NL, PL, RO, SE, SI, SK, UK (15) 

AT, DE, DK, FI, HU, IT, MT, NL, 
PL, SE, SK (11) 

AT, DE, DK, FI, MT, NL, PL, 
SE (8) 

AT, DE, DK, FI, IT, LT, MT, NL, 
RO, SE, SI, SK, UK (13) 

Limited forms of use 
(2-3 options) 

AT, BE-FR, BE-NL, BG, CZ, DE, 
DK, EE, ES, FI, FR, HR, IE, IT, LV, 
NO, PL, PT, RO, SI, SK, UK (22) 

BE-NL, CZ, DE, DK, EE, ES, FR, 
IE, IT, NO, PT, RO, SI, UK (14) 

BE-FR, BE-NL, EE, FR, IE, 
NO, PT, RO, UK (9) 

AT, BE-NL, BG, CZ, DE, DK, EE, 
ES, FI, FR, HR, IE, IT, LV, PL, PT, 
SK, UK (18) 

(Nearly) no forms of 
use (0-1 options) 

AT, BE-FR, BE-NL, BG, CY, CZ, 
DE, DK, EL, ES, FI, FR, HU, LI, 
LU, MT, NL, SE (18) 

AT, BE-FR, BE-NL, BG, DE, DK, 
ES, FI, FR, HU, LU, SE (12) 

BE-FR, BE-NL, DE, DK, ES, 
FI, HU, SE (8) 

AT, BE-FR, BE-NL, CZ, DE, DK, 
ES, FI, FR, LI, MT, NL (12) 

Source: Mapping research conducted by ICF, 3s and CHEPS. * Evaluated only for countries with survey-based measures (n=28), as these 
indicators usually are not collected via administrative data instruments. 

March, 2020 

157 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

The coverage is assessed as follows for 31 countries:   

  0–4 countries:  
  5–16 countries:  
  17–27 countries:  
  28–30 countries:  
  31–32 countries:  

(nearly) no coverage  
limited coverage 
good coverage 
nearly complete coverage 
complete coverage 

The coverage for indicators only relevant for countries with survey measures was 
assessed as follows for 28 countries:   

  0–4 countries:  
  5–14 countries:  
  15–23 countries:  
  24–26 countries:  
  27–28 countries:  

(nearly) no coverage  
limited coverage 
good coverage 
nearly complete coverage 
complete coverage 

March, 2020 

158 

 
 
 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Methodology for assessing the timeline for countries to meet the Council 
Recommendation 

Table 71.  Assessment of timeline for countries to meet the Council Recommendation** 

Average 
assessment 
against 
Recommendati
on 

Timelin
e in 
months, 
based 
on 
coverag
e 

Country 

Country 

Population
* 

Populatio
n in 
clusters 

Factor 
for 
countr
y size 

Timelin
e in 
years 
(rounde
d up) 

nearly complete 
coverage 

24 

Austria 

8858775 

6-15 mio.  1,25 

3 

good coverage 

36 

Belgium 
(Flanders) 

11467923 
(Belgium) 

6-15 mio.  1,25 

4 

limited coverage  48 

Belgium 
(French-
speaking) 

11467923 
(Belgium) 

6-15 mio.  1,25 

5 

limited coverage  48 

Bulgaria 

7000039 

6-15 mio.  1,25 

limited coverage  48 

Croatia 

4076246 

1-5 mio. 

1 

(nearly) no 
coverage 

60 

Cyprus 

875898 

up to 1 
mio. 

0,75 

good coverage 

36 

Czechia 

10649800 

6-15 mio.  1,25 

nearly complete 
coverage 

24 

Denmark 

5806081 

6-15 mio.  1,25 

good coverage 

36 

Estonia 

1324820 

1-5 mio. 

1 

nearly complete 
coverage 

24 

Finland 

5517919 

6-15 mio.  1,25 

5 

4 

4 

4 

3 

3 

3 

good coverage 

36 

France 

67028048 

12 

Germany 

83019213 

above 50 
mio. 

above 50 
mio. 

1,75 

5 

1,75 

2 

60 

Greece 

10722287 

6-15 mio.  1,25 

6 

complete 
coverage 

(nearly) no 
coverage 

good coverage 

36 

Hungary 

9772756 

6-15 mio.  1,25 

nearly complete 
coverage 

nearly complete 
coverage 

24 

Iceland 

356991 

up to 1 
mio. 

0,75 

24 

Ireland 

4904226 

1-5 mio. 

1 

4 

2 

2 

March, 2020 

159 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Average 
assessment 
against 
Recommendati
on 

Timelin
e in 
months, 
based 
on 
coverag
e 

Country 

Country 

Population
* 

Populatio
n in 
clusters 

Factor 
for 
countr
y size 

Timelin
e in 
years 
(rounde
d up) 

good coverage 

36 

Italy 

60359546 

above 50 
mio. 

1,75 

5 

limited coverage  48 

Latvia 

1919968 

1-5 mio. 

1 

limited coverage  48 

Liechtenste
in 

38378 

up to 1 
mio. 

0,75 

good coverage 

36 

Lithuania 

2794184 

1-5 mio. 

1 

limited coverage  48 

Luxembour
g 

613894 

limited coverage  48 

Malta 

493559 

nearly complete 
coverage 

24 

Netherland
s 

17282163 

up to 1 
mio. 

up to 1 
mio. 

16-50 
mio. 

0,75 

0,75 

3 

1,5 

3 

4 

3 

3 

3 

good coverage 

36 

Norway 

5328212 

1-5 mio. 

1 

good coverage 

36 

Poland 

37972812 

16-50 
mio. 

1,5 

good coverage 

36 

Portugal 

10276617 

6-15 mio.  1,25 

limited coverage  48 

Romania 

19401658 

16-50 
mio. 

limited coverage  48 

Slovakia 

5450421 

1-5 mio. 

limited coverage  48 

Slovenia 

2080908 

1-5 mio. 

good coverage 

36 

Spain 

46934632 

16-50 
mio. 

1,5 

1 

1 

1,5 

3 

5 

4 

6 

4 

4 

5 

nearly complete 
coverage 

24 

Sweden 

10230185 

6-15 mio.  1,25 

3 

nearly complete 
coverage 

24 

United 
Kingdom 

66647112 

above 50 
mio. 

1,75 

4 

Source: Mapping research conducted by ICF, 3s and CHEPS.  

* Population in EU and EEA Member States on 1 January 2020, 
https://europa.eu/webtools/rest/charts/export/html/ and 
https://countryeconomy.com/countries/groups/european-economic-area 

March, 2020 

160 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

** The timeline is estimated on basis of the average assessment of each country against 
the Council Recommendation (see chapter 4.1.1), set in relation to each country’s size, 
operationalized by a size factor.   

Annex 5.  Annexes to chapter 5 

Table 72.  Collection of different outcome indicators by graduate tracking measures for 

initial VET (IVET), continuing VET (CVET) and higher education (HE) 

Indicator 

IVET 

CVET 

HE 

Others 

Employment 
status 

Sustainabilit
y of 
employment 

Salary 

AT1, AT2, BE-FR2, 
BE-NL1, BG1, CZ4, 
CZ5, DE1, DE2, DE3, 
DE4, DE5, DK3, DK5, 
DK6, DK7, EE1, EE2, 
ES1, ES2, ES3, ES4, 
ES5, FI1, FI7, FI8, 
FI9, FR1, FR2, FR3, 
HU3, IE1, IE5, IT1, 
IT2, IT8, IT9, IT10, 
LT1, LU1, LV3, MT1, 
NL3, NO1, NO4, PL1, 
PT2, PT3, RO1, SE1, 
SE2, SE7, SI1, SK1, 
UK2, UK3, UK4  

(57) 

AT1, AT2, CZ5, DE1, 
DE2, DE4, DE5, DE9, 
ES3, ES4, FI1, FI7, 
FI8, FR1, FR2, FR3, 
HU3, IE1, IE2, IT1, 
IT2, IT8, LT1, LU1, 
LV3, MT1, NL3, NO1, 
NO4, PT2, RO1, SE1, 
SE2, SI1, UK3  

(35) 

AT1, AT2, DE1, DE4, 
DE5, DE9, DK6, EE1, 
EE2, ES3, FR1, IE1, 
IT1, IT2, LT1, LV3, 
MT1, NL3, RO1, SE2, 
UK2, UK3 

(22)  

AT1, BE-FR1, BE-
FR2, BE-NL2, DE1, 
DE3, DE4, DK5, 
EE2, ES1, FI1, FI7, 
FI8, FI9, FR1, IE1, 
IE5, LV3, MT1, NL3, 
NO1, NO5, PL1, PT3, 
RO1, SE5, SE6, SE7, 
UK2, UK4  

(30) 

AT1, BE-FR1, BE-
NL2, DE1, DE4, FI1, 
FI7, FI8, FR1, IE1, 
LV3, MT1, NL3, 
NO1, NO5, RO1, SE6 

(17) 

AT1, DE1, DE4, EE2, 
FR1, IE1, LV3, MT1, 
NL3, RO1, SE6, UK2 

(12) 

AT1, AT3, AT4, AT5, 
BE-FR2, BE-NL1, CZ1, 
CZ2, CZ3, CZ4, DE1, 
DE2, DE3, DE4, DE6, 
DE7, DE8, DE10, 
DE11, DK3, DK6, EE1, 
EE3, ES1, ES2, ES6, 
ES7, FI1, FI2, FI3, FI4, 
FI5, FI8, FI9, FR1, 
FR4, FR5, HR1, HU1, 
IE3, IE6, IT4, IT5, IT6, 
IT7, LI1, LT1, LT2, 
LV1, LV2, MT1, MT2, 
NL1, NL2, NL4, NL5, 
NL6, NO1, NO2, NO3, 
PL2, PT1, RO2, SE3, 
SE4, SK1, SK2, UK1, 
UK2 (69) 

AT1, AT3, AT4, AT5, 
CZ3, DE1, DE2, DE4, 
DE6, DE8, DE9, ES6, 
ES7, FI1, FI2, FI3, FI8, 
FR1, FR4, IT4, IT5, 
IT6, IT7, LT1, LV1, 
MT1, MT2, NL1, NL2, 
NL4, NL5, NO1, NO2, 
RO2, SE3, SE4, UK1 

(37) 

AT1, AT3, AT4, CZ1, 
CZ2, DE1, DE4, DE8, 
DE9, DK6, EE1, EE3, 
FI4, FR1, FR4, HR1, 
HU1, IE3, IE6, IT4, 
IT6, LT1, LT2, LV2, 
MT1, MT2, NL1, NL2, 
NL4, NL5, NO2, RO2, 
SE4, SK2, UK1, UK2 

(36)  

Number 
of 
measure
s 

110 

AT2, BE-
FR2, DE2, 
DK4, ES1, 
ES3, ES5, 
FI1, FI9, 
FR1, NL5, 
NO1, SE1, 
SE2, SE7  

(15) 

65 

AT2, DE2, 
DE9, ES3, 
FI1, FR1, 
NL5, NO1, 
SE1, SE2 

(10) 

49 

AT2, DE9, 
ES3, FR1, 
NL5, SE2 

(6) 

Further 
education 
and training 
pathways 

AT1, BE-FR2, BG1, 
CZ5, DE1, DE2, DE3, 
DE4, DE5, DE9, DK1, 
DK3, DK5, EE1, EE2, 
ES3, FI1, FI7, FI8, 
FI9, FR1, HU3, IE1, 
IE5, IT1, IT2, IT3, 
LU1, LV3, MT1, NL3, 
NO1, NO4, PL1, PT2, 
SE1, SE2, SE7, SI1, 
UK2, UK3, UK4  

AT1, BE-FR1, BE-
FR2, DE1, DE3, DE4, 
DK2, DK5, EE2, FI1, 
FI7, FI8, FI9, FR1, 
IE1, IE5, LV3, MT1, 
NL3, NO1, NO5, 
PL1, SE5, SE6, SE7, 
UK2, UK4  

(27) 

AT1, AT3, AT5, BE-
FR2, CZ1, CZ2, CZ3, 
DE1, DE2, DE3, DE4, 
DE6, DE7, DE8, DE9, 
DE10, DE11, DK1, 
DK3, EE1, ES7, FI1, 
FI2, FI3, FI4, FI8, FI9, 
FR1, FR5, HU1, IE3, 
IE6, IT3, IT4, IT5, IT6, 
LT2, LV2, MT1, MT2, 
NL1, NL2, NL4, NL5, 
NL6, NO1, NO2, NO3, 

BE-FR2, 
DE2, DE9, 
ES3, FI1, 
FI9, FR1, 
NL5, NO1, 
SE1, SE2, 
SE7  

(12) 

84 

March, 2020 

161 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Indicator 

IVET 

CVET 

HE 

Others 

Number 
of 
measure
s 

(42) 

Satisfaction 
(in general) 

AT2, BG1, CZ5, DE1, 
DE2, DE4, DE9, EE2, 
FI7, FR1, HU3, IE1, 
IT1, IT2, IT9, IT10, 
MT1, NL3, NO4, PL1, 
PT2, RO1, SI1, UK3  

BE-FR1, DE1, DE4, 
EE2, FI7, FR1, IE1, 
MT1, NL3, NO5, PL1, 
RO1, SE5  

(13) 

(24) 

Satisfaction 
with study 
program/tra
ining 

CZ5, DE4, DE9, EE2, 
FI7, HU3, IE1, IT1, 
IT2, IT9, IT10, MT1, 
NL3, NO4, PT2, RO1, 
SI1, UK3 

BE-FR1, DE4, EE2, 
FI7, IE1, MT1, NL3, 
NO5, RO1, SE5 

(10) 

(18) 

Satisfaction 
with current 
job 

AT2, CZ5, DE1, DE2, 
DE4, EE2, FR1, HU3, 
IE2, MT1, NL3, RO1  

DE1, DE4, EE2, FR1, 
MT1, NL3, RO1 

(7) 

(12) 

Relevance 
of acquired 
skills at the 
workplace 

AT2, CZ5, DE1, DE4, 
DK6, EE2, ES3, ES4, 
FI7, FR1, FR2, FR3, 
HU3, IE1, IT2, IT10, 
LT1, MT1, NL3, NO4, 
PL1, PT2, RO1, SE1, 
SI1, UK3  

(26) 

BE-FR1, DE1, DE4, 
EE2, FI7, FR1, IE1, 
MT1, NL3, NO5, PL1, 
RO1, SE5  

(13) 

PL2, SE3, SE4, SI2, 
SK2, UK1, UK2  

(55) 

AT4, AT5, CZ1, CZ2, 
CZ3, DE1, DE2, DE4, 
DE7, DE8, DE9, DE10, 
DE11, EE3, ES7, FI2, 
FI3, FI4, FI5, FI6, FR1, 
HR1, HU1, IE3, IT5, 
IT6, IT7, LI1, LT2, 
LV1, LV2, MT1, MT2, 
NL1, NL2, NL5, NO2, 
NO3, RO2, UK1 (40) 

AT4, AT5, CZ1, CZ2, 
CZ3, DE4, DE7, DE8, 
DE9, EE3, ES7, FI2, 
FI4, FI5, FI6, HU1, 
IE3, IT5, IT6, IT7, LT2, 
LV2, MT1, NL1, NL2, 
NL5, NO2, RO2, UK1 

(29) 

CZ1, CZ2, DE1, DE2, 
DE4, EE3, FI2, FI3, 
FI4, FR1, HR1, LI1, 
LV1, MT1, MT2, NL1, 
NL2, UK1 

(18) 

AT5, CZ1, CZ2, CZ3, 
DE1, DE4, DE10, DK6, 
EE3, ES7, FI2, FI3, 
FI4, FI5, FI6, FR1, 
HR1, HU1, IE3, IT6, 
LT1, LT2, LV1, LV2, 
MT1, MT2, NL1, NL2, 
NL4, NL5, NL6, NO2, 
NO3, RO2, SE3, SK2, 
UK1 (37)  

61 

AT2, DE2, 
DE9, FR1, 
NL5  

(5) 

DE9, NL5 

47 

(2) 

AT2, DE2, 
FR1 

25 

(3) 

60 

AT2, ES3, 
FR1, NL5, 
SE1  

(5) 

Social and 
civic 
activities 
and 
participation 
in these 

DE1, EE2, MT1, PL1, 
UK4 

DE1, EE2, MT1, PL1, 
UK4 

(5) 

(5) 

AT5, CZ3, DE1, DE10, 
FI2, LI1, LV2, MT1, 
MT2, UK1 

- 

(10) 

13 

Source: research ICF, 3s and CHEPS. 

Table 73.  Collection of other indicators for comparability in graduate tracking measures 

for IVET, CVET and HE 

Indicator 

IVET 

CVET 

HE 

Others 

Sum 

Socio-
biographical 
and 

AT1, AT2, BE-NL1, 
CZ4, CZ5, DE1, DE4, 
DE5, DE9, DK6, EE1, 

AT1, BE-FR1, DE1, 
DE4, DK2, EE2, FI1, 
FI7, FI8, FI9, IE1, 

AT1, AT3, AT4, AT5, 
BE-NL1, CZ1, CZ2, 
CZ3, CZ4, DE1, DE4, 

AT2, DE9, 
DK4, ES3, 
FI1, FI9, 

94 

March, 2020 

162 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Indicator 

IVET 

CVET 

HE 

Others 

Sum 

socioecono
mic 
information 

Age 

Gender 

EE2, ES3, ES4, FI1, 
FI7, FI8, FI9, FR2, 
FR3, HU3, IE1, IE5, 
IT1, IT2, IT3, IT8, 
IT10, LT1, LU1, LV3, 
MT1, NL3, NO1, 
NO4, PL1, PT2, RO1, 
SE1, SE2, SE7, SI1, 
SK1, UK2, UK4  

(45) 

AT1, AT2, DE4, DE5, 
DE9, EE1, ES3, ES4, 
FI7, FI9, IE1, IE5, 
IT2, IT8, LT1, LU1, 
MT1, NL3, NO1, 
NO4, PT2, RO1, SE1, 
SE2, SI1, SK1, UK2  

(27) 

AT1, AT2, BE-NL1, 
CZ4, DE4, DE5, DE9, 
EE1, ES3, ES4, FI7, 
FI9, FR2, FR3, IE1, 
IE2, IE5, IT2, IT3, 
IT8, IT10, LT1, LU1, 
MT1, NL3, NO1, 
NO4, PT2, RO1, SE1, 
SE2  

(31) 

IE5, LV3, MT1, NL3, 
NO1, NO5, PL1, 
RO1, SE5, SE6, SE7, 
UK2, UK4 (24) 

AT1, DE4, FI7, FI9, 
IE1, IE5, MT1, NL3, 
NO1, NO5, RO1, 
SE5, UK2  

(13) 

AT1, DE4, FI7, FI9, 
IE1, IE5, MT1, NL3, 
NO1, NO5, RO1, 
SE5, SE6  

(13) 

Nationality 

AT1, AT2, DE4, DE5, 
DE9, ES3, ES4, FI8, 
IE1, IE5, IT8, LU1, 
MT1, NO1, PT2, RO1, 
SE1, SE2, SI1  

AT1, DE4, FI8, IE1, 
IE5, MT1, NO1, RO1, 
SE5, SE6  

(10) 

(19) 

NL5, NO1, 
SE1, SE2, 
SE7 

(11) 

AT2, DE9, 
DK4, ES3, 
FI9, NL5, 
NO1, SE1, 
SE2 

(9) 

AT2, DE9, 
DK4, ES3, 
FI9, NL5, 
NO1, SE1, 
SE2 

(9) 

DE6, DE8, DE9, DE10, 
DE11, DK6, EE1, EE3, 
ES7, FI1, FI2, FI3, FI4, 
FI5, FI6, FI8, FI9, FR4, 
FR5, HR1, HU1, IE3, 
IE6, IT3, IT4, IT5, IT6, 
IT7, LI1, LT1, LT2, 
LV1, LV2, MT1, MT2, 
NL1, NL4, NL5, NO1, 
NO2, NO3, PL2, RO2, 
SE3, SE4, SI2, SK1, 
UK1, UK2 (60) 

AT1, AT4, AT5, CZ1, 
CZ2, CZ3, DE4, DE8, 
DE9, EE1, EE3, FI2, 
FI3, FI4, FI5, FI6, FI9, 
HR1, IE3, IE6, IT4, 
IT5, IT7, LT1, LT2, 
LV1, LV2, MT1, MT2, 
NL1, NL4, NL5, NO1, 
NO2, RO2, SE3, SI2, 
SK1, UK2  

(39) 

AT1, AT3, AT4, AT5, 
BE-NL1, CZ1, CZ2, 
CZ3, CZ4, DE4, DE6, 
DE8, DE9, EE1, FI2, 
FI3, FI4, FI5, FI6, FI9, 
FR4, HR1, IE3, IE6, 
IT3, IT4, IT5, IT7, 
LT1, LT2, LV1, LV2, 
MT1, MT2, NL1, NL4, 
NL5, NO1, NO2, RO2, 
SE4  

(41) 

AT1, AT3, AT4, AT5, 
CZ1, CZ2, CZ3, DE4, 
DE6, DE8, DE9, FI2, 
FI3, FI8, IE6, IT6, IT7, 
LI1, MT1, NL1, NL4, 
NL5, NO1, NO2, RO2, 
SE3, SI2, UK1  

AT2, DE9, 
ES3, NL5, 
NO1, SE1, 
SE2 

(7) 

(28) 

59 

65 

43 

Social 
background 

DE4, DE9, ES3, FI9, 
HU3, IE2, IT1, IT3, 
LU1, PT2, SI1, UK2  

DE4, FI9, UK2  

(3) 

(12) 

AT3, AT4, AT5, CZ1, 
CZ2, CZ3, DE4, DE6, 
DE8, DE9, FI9, IE3, 
IT3, IT4, IT5, IT6, IT7, 
LI1, LV1, UK2  

DE9, ES3, 
FI9 

27 

(3) 

Link to 
level, field 
of study and 
provider 

AT1, BE-NL1, BG1, 
CZ5, DE1, DE2, DE5, 
EE2, ES3, ES4, FI1, 
FI7, FI8, FI9, FR1, 
FR2, FR3, IE1, IE5, 
IT3, LT1, LV3, MT1, 
NL3, NO4, PL1, SE1, 
SE7, SI1, UK2  

AT1, BE-NL2, DE1, 
EE2, FI1, FI7, FI8, 
FI9, FR1, IE1, IE5, 
LV3, MT1, NL3, NO5, 
PL1, SE5, SE6, SE7, 
UK2  

(20) 

(30) 

(20) 

AT1, AT3, AT4, AT5, 
BE-NL1, CZ1, CZ2, 
CZ3, DE1, DE2, DE8, 
DE10, EE3, ES7, FI1, 
FI2, FI3, FI4, FI5, FI6, 
FI8, FI9, FR1, FR4, 
HU1, IE6, IT3, LI1, 
LT1, LV1, LV2, MT1, 
MT2, NL1, NL2, NL4, 
NL5, NL6, NO2, NO3, 

68 

DE2, ES3, 
FI1, FI9, 
FR1, NL5, 
SE1, SE7 

(8) 

March, 2020 

163 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States 
and EEA countries 

Indicator 

IVET 

CVET 

HE 

Others 

Sum 

Place of 
residence / 
migration to 
other 
countries 

AT1, BE-NL1, DE1, 
DK6, ES3, FI1, FI8, 
FR1, HU3, IE1, IT2, 
IT3, LT1, MT1, NL3, 
NO4, SE7, SI1 

AT1, BE-FR1, DE1, 
FI1, FI8, FR1, IE1, 
MT1, NL3, NO5, SE7 

(11) 

(18) 

Source: research ICF, 3s and CHEPS. 

RO2, SE3, SE4, SI2, 
SK2, UK2  

(46) 

AT1, AT3, AT4, AT5, 
BE-NL1, CZ1, CZ2, 
CZ3, DE1, DE10, DK6, 
EE3, ES7, FI1, FI2, 
FI3, FI4, FI5, FI6, FI8, 
FR1, FR4, HU1, IE3, 
IT3, IT5, IT7, LI1, LT1, 
LV1, LV2, MT1, MT2, 
NL1, NL2, NL4, NL5, 
NL6, NO2, NO3, RO2, 
SI2, SK2, UK1 

(44) 

54 

ES3, FI1, 
FR1, NL5, 
SE7 

(5) 

March, 2020 

164 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 74.  Assessment of the measures – Initial VET  

Code 

AT1 

AT2 

BE-
FR2 

BE-
NL1 

BE-
NL3 

BG1 

CZ4 

CZ5 

DE1 

DE2 

DE3 

DE4 

DE5 

Completers  Drop-outs  Students 

Residents 
in country 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X  

X 

X 

X 

X 

X  

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

3-8 

4 

2-8 

3 

n.a. 

2-4 

3, 6-8 

3 

0-8 

3-4, 6-8 

1-8 

1-8 

3 

X* 

X* 

X 

X* 

X 

X* 

X* 

X* 

X* 

X* 

X* 

165 

 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

Code 

DE9 

DK1 

DK3 

DK5 

DK6 

DK7 

EE1 

EE2 

ES1 

ES2 

ES3 

ES4 

ES5 

FI1 

FI7 

X 

X 

X  

X 

X 

X 

X 

X 

 X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

X 

 X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

3-8 

0-8 

n.a. 

n.a. 

n.a. 

n.a. 

0-8 

0-5 

0-8 

3, 5-8 

2-3, 5 

3, 5 

2-3, 5 

3-8 

3-5 

X 

X 

X 

X* 

X* 

X* 

X 

X* 

X* 

X* 

X 

X 

X 

X* 

X* 

166 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

 X 

X 

 X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

Code 

FI8 

FI9 

FR1 

FR2 

FR3 

HU2 

HU3 

IE1 

IE2 

IE4 

IE5 

IT1 

IT2 

IT3 

IT8 

March, 2020 

X 

3-8 

X 

X 

X 

X 

X 

X 

1-8 

3-8 

3, 5 

3-5 

n.a. 

3-4 

1-4 

3 

1-4 

1-4 

3 

3 

3-6 

4 

X* 

X 

X 

X 

X 

X* 

X* 

X 

X* 

167 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

Code 

IT9 

IT10 

LT1 

LU1 

LV3 

MT1 

NL3 

NO1 

NO4 

PL1 

PT2 

PT3 

RO1 

SE1 

SE2 

SE7 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

3 

3 

2-4, 6-8 

X 

0-4 

2-4 

1-7 

2-4 

0-8 

3 

3 

3 

n.a. 

n.a. 

3 

X 

X 

X 

X 

X 

2-3 

n.a. 

X* 

X 

X* 

X* 

X* 

X* 

X 

X 

X 

X 

X 

X* 

X 

X 

168 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

Residents 
in country 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

Code 

SI1 

SK1 

UK2 

UK3 

UK4 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

X 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X 

X 

X 

X 

X 

X 

X 

X* 

X* 

X 

3 

6-9 

X 

3-4, 6 

1-3 

2-5 

Source: research ICF, 3s and CHEPS. * Regular measure, in contrast to one-off measures, measures which were conducted two or three times, 
but were then no longer carried out, or measures which were not conducted yet. 

Table 75.  Assessment of the measures – Continuing VET  

Code 

Completers  Drop-outs  Students 

X 

X 

AT1 

X 

BE-
FR1 

BE-
FR2 

X 

X 

March, 2020 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

X 

X 

Residents 
in country 

X 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X 

X 

X  

X  

X 

X 

3-8 

0-4 

X 

2-8 

X* 

X* 

X 

169 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Code 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

BE-
NL2 

BE-
NL3 

DE1 

X 

DE3 

DE4 

DK2 

DK5 

EE2 

ES1 

FI1 

FI7 

FI8 

FI9 

FR1 

HU2 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

X 

X 

X 

X 

X 

 X  

X 

X 

X 

X 

 X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

4 

X 

n.a. 

0-8 

1-8 

1-8 

X 

n.a. 

n.a. 

0-5 

0-8 

3-8 

3-5 

3-8 

1-8 

3-8 

n.a. 

X 

X 

X 

X 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X 

X* 

170 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

Code 

IE1 

IE4 

IE5 

LV3 

MT1 

NL3 

NO1 

NO5 

PL1 

PT3 

RO1 

SE5 

SE6 

SE7 

UK2 

UK4 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

1-4 

1-4 

X 

1-4 

2-4 

1-7 

2-4 

0-8 

4-5 

3 

n.a. 

n.a. 

4-6 

4-6 

n.a. 

X 

X 

X 

X 

3-4, 6 

2-5 

X 

X 

X* 

X* 

X* 

X 

X 

X 

X 

X* 

X 

X 

X 

171 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Source: research ICF, 3s and CHEPS. * Regular measure, in contrast to one-off measures, measures which were conducted two or three times, 
but were then no longer carried out, or measures which were not conducted yet. 

Table 76.  Assessment of the measures – HE  

Code 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

AT1 

AT3 

AT4 

AT5 

X 

BE-
FR2 

BE-
NL1 

BE-
NL3 

BG2 

CZ1 

CZ2 

CZ3 

CZ4 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X  

X 

X 

X 

X 

X 

X* 

X* 

X* 

X* 

X 

X* 

X 

X 

X 

3-8 

6-8 

6-7 

5-7 

X 

2-8 

3 

n.a. 

6-8 

6-8 

6-8 

6-7 

3, 6-8 

X 

172 

 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

 X 

 X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

Code 

DE1 

DE2 

DE3 

DE4 

DE6 

DE7 

DE8 

DE9 

DE10 

DE11 

DK1 

DK3 

DK6 

EE1 

EE3 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

0-8 

3-4, 6-8 

1-8 

1-8 

6-8 

6-8 

6-8 

3-8 

5-7 

6-8 

0-8 

n.a. 

n.a. 

0-8 

5-8 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X* 

X 

X* 

X* 

173 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Code 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

ES1 

X 

X 

X  

X  

X 

X 

X 

 X 

 X 

X 

X  

X 

X 

X 

ES2 

ES6 

ES7 

FI1 

FI2 

FI3 

FI4 

FI5 

FI6 

FI8 

FI9 

FR1 

FR4 

FR5 

HR1 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

0-8 

X* 

3, 5-8 

X 

6 

X 

X 

X 

X 

X 

X 

6-7 

3-8 

6-7 

8 

6-7 

6 

6-7 

3-8 

1-8 

3-8 

5-7 

8 

6-7 

X 

X 

X 

X* 

X* 

X* 

X* 

X* 

X* 

X 

X* 

X 

X 

174 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Code 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

X 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

HU1 

X 

IE3 

IE6 

IT3 

IT4 

IT5 

IT6 

IT7 

LI1 

LT1 

LT2 

LV1 

LV2 

MT1 

MT2 

NL1 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X  

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

6-8 

5-8 

X 

6-8 

X 

X 

X 

X 

3-6 

5 

5 

5 

6 

n.a. 

2-4, 6-8 

6 

8 

5-8 

1-7 

5-7 

5-7 

X* 

X* 

X 

X 

X* 

X* 

X* 

X* 

X 

X 

X 

X* 

X* 

X* 

X 

175 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

Code 

NL2 

NL4 

NL5 

NL6 

NO1 

NO2 

NO3 

PL2 

PT1 

RO2 

SE3 

SE4 

SI2 

SK1 

SK2 

UK1 

March, 2020 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

7-8 

6-7 

6-7 

7 

0-8 

7 

6-7 

6-8 

6-7 

X 

X 

6 

5-7 

5-7 

6-8 

6-9 

7-9 

5-8 

X* 

X 

X 

X 

X 

X 

X* 

X 

X 

X* 

X* 

X* 

176 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Code 

Completers  Drop-outs  Students 

Residents 
in country 

Migrants to 
another 
country 
after 
graduation 

ISCED 
or 
ISCED-
F 

ILO- 
STAT, 
ESCO, 
ISCO 
or 
NACE 

Represen- 
tative 

Sufficient 
survey 
response 
rate 

Periodicity  

Follow 
up of 
cohort 

ISCED levels 
covered 

Data 
availability 

UK2 

X 

X 

X 

X 

X 

X 

X 

3-4, 6 

X 

Source: research ICF, 3s and CHEPS. * Regular measure, in contrast to one-off measures, measures which were conducted two or three times, 
but were then no longer carried out, or measures which were not conducted yet.

March, 2020 

177 

 
 
 
  
  
  
  
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 77.  Country coverage of graduate groups with potential for comparability (in measures using ISCED/ISCED-F classification, 

representativeness and/or sufficient response rate, periodicity of measure, data availability) in IVET (25 measures) 

Indicator 

Completers 

People who have left 
without completing 

Employment 
status 

BE-NL, CZ, DE, DK, EE, ES, 
FI, FR, HU, IE, IT, LT, LU, 
NL, PT, SE, SK, UK (18) 

BE-NL, CZ, DE, EE, ES, 
FI, FR, HU, LU, PT, SE, 
UK (12) 

Students 
(before 
completion) 

DE, FI, HU (3) 

Residents in country  Migrants to 

another country 
after graduation 

DE, FR, LT, NO, SE, UK 
(6) 

HU (1) 

Sustainable 
employment 

DE, FI, FR, HU, IE, IT, LT, 
LU, NL, SE (10) 

DE, FI, FR, HU, LU, SE 
(6) 

DE, FI, HU (3) 

DE, FR, LT, NO, SE (5)  HU (1) 

Salary 

DE, EE, FR, IE, IT, LT, NL, 
SE, UK (9) 

DE, EE, FI, FR, HU, SE, 
UK (7) 

DE, FI (2) 

DE, FR, LT, SE, UK (5)  HU (1) 

Further education  DE, DK, EE, FI, FR, HU, IE, 

IT, LU, NL, SE, UK (12) 

DE, DK, EE, FI, FR, LU, 
SE, UK (8) 

DE, DK, FI, HU (4)  DE, FR, NO, SE, UK (5)  - 

Satisfaction 
(general) 

DE, FI, FR, IE, IT, NL (6) 

DE, FR, HU (3) 

DE (1) 

DE, FR (2) 

HU (1) 

Relevance of 
acquired skills 

DE, FI, FR, HU, IE, LT, NL, 
SE (8) 

DE, FR, HU, SE (4) 

DE, HU (2) 

DE, FR, LT, SE (4) 

HU (1) 

DE (1) 

DE (1) 

DE (1) 

DE (1) 

- 

BE-NL1, CZ4, DE, EE, FI, 
IE, IT, LT, LU, NL, SE, SK, 
UK (13) 

BE-NL, CZ, DE, EE, FI, 
HU, LU, SE, UK (9) 

DE, FI (2) 

DE, LT, NO, SE, UK (5)  HU (1) 

DE, EE, ES, FI, IE, LT, LU, 
NL, SE, SK, UK (11) 

DE, EE, ES, FI, LU, SE, 
UK (7) 

DE, FI (2) 

DE, LT, NO, SE, UK (5)  - 

Social/civic 
activities 

Socio-
biographical 
information 

Age 

March, 2020 

178 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in country  Migrants to 

another country 
after graduation 

Gender 

BE-NL, CZ, DE, EE, ES, FI, 
IE, LT, LU, NL, SE (11) 

BE-NL, CZ, DE, EE, ES, 
FI, LU, SE (8) 

DE, FI (2) 

DE, LT, NO, SE (4) 

Nationality 

DE, ES, FI, IE, LU, SE (6) 

DE, ES, FI, LU, SE (5) 

DE, FI (2) 

DE, NO, SE (3) 

- 

- 

Social background  DE, IT, LU, UK (4) 

DE, FI, HU, LU, UK (5) 

DE, FI (2) 

DE, UK (2) 

HU (1) 

Level, field of 
study, provider 

BE-NL, DE, FI, FR, IE, LT, 
NL, SE, UK (9) 

BE-NL, DE, FI, FR, SE, 
UK (6) 

DE, FI (2) 

DE, FR, LT, SE, UK (5)  - 

Place of 
residence/migrati
on 

BE-NL, DE, FI, FR, HU, IE, 
LT, NL (8) 

BE-NL, DE, FI, FR, HU 
(5) 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

DE, FI, HU (3) 

DE, FR, LT (3) 

HU (1) 

March, 2020 

179 

 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 78.  Country coverage of graduate groups with potential for comparability (in measures using ISCED/ISCED-F classification, 

representativeness and/or sufficient response rate, periodicity of measure, data availability) in CVET (14 measures) 

Indicator 

Completers 

People who have left 
without completing 

Students (before 
completion) 

Residents in country  Migrants to another 

country after 
graduation 

Employment 
status 

DE, FI, FR, IE, NL, 
NO, PT, SE, UK (9) 

DE, FI, FR, PT, UK (5) 

DE, FI (2) 

DE, FR, NO, SE, UK (5)  - 

Sustainable 
employment 

DE, FI, FR, IE, NL, 
NO (6) 

Salary 

DE, FR, IE, NL, UK 
(5) 

Further education  DE, DK, FI, FR, IE, 
NL, NO, SE, UK (9) 

Satisfaction 
(general) 

DE, FI, FR, IE, NL, 
NO, SE (7) 

Relevance of 
acquired skills 

DE, FI, FR, IE, NL, 
NO, SE (7) 

DE, FI, FR (3) 

DE, FI (2) 

DE, FR, NO (3) 

DE, FI, FR, UK (4) 

DE, DK, FI (3) 

DE, FR, UK (3) 

- 

- 

DE, DK, FI, FR, UK (5) 

DE, FI (2) 

DE, FR, NO, SE, UK (5)  - 

DE, FR (2) 

DE (1) 

DE, FR, SE (3) 

DE, FR (2) 

DE (1) 

DE, FR, SE (3) 

DE (1) 

DE (1) 

DE (1) 

DE (1) 

DE, DK, FI, UK (4) 

DE, DK, FI (3) 

DE, NO, SE, UK (4) 

- 

- 

- 

- 

Social/civic 
activities 

Socio-
biographical 
information 

Age 

March, 2020 

DE, DK, FI, IE, NL, 
NO, SE, UK (8) 

DE, FI, IE, NL, NO, 
SE, UK (7) 

DE, FI, UK (3) 

DE, FI (2) 

DE, NO, SE, UK (4) 

- 

180 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students (before 
completion) 

Residents in country  Migrants to another 

country after 
graduation 

Gender 

DE, FI, IE, NL, NO, 
SE (6) 

DE, FI (2) 

DE, FI (2) 

DE, NO, SE (3) 

Nationality 

DE, FI, IE, SE (4) 

DE, FI(2) 

DE, FI (2) 

DE, NO, SE (3) 

Social background  DE, UK (2) 

DE, FI, UK (3) 

DE, FI (2) 

DE, UK (2) 

Level, field of 
study, provider 

DE, FI, FR, IE, NL, 
NO, SE, UK (8) 

Place of 
residence/migrati
on 

DE, FI, FR, IE, NL, 
NO (6) 

DE, FI, FR, UK (4) 

DE, FI (2) 

DE, FR, SE, UK (4) 

DE, FI, FR (3) 

DE, FI (2) 

DE, FR (2) 

- 

- 

- 

- 

- 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

181 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 80.  Country coverage of graduate groups with potential for comparability (in measures using ISCED/ISCED-F classification, representativeness 

and/or sufficient response rate, periodicity of measure, data availability) in HE (37 measures) 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Employment 
status 

BE-NL, CZ, DE, DK, EE, ES, FI, 
FR, HU, IE, IT, LT, LV, NL, PL, 
PT, SE, SK, UK (19) 

BE-NL, CZ, DE, EE, FI, FR, PL, 
SE, UK (9) 

AT, DE, FI, HU (4)  DE, ES, FI, FR, LT, 

ES, FI (2) 

NO, SE, UK (8) 

Sustainable 
employment 

DE, ES, FI, FR, IT, LT, LV, NL, SE 
(9) 

DE, FI, FR, SE (4) 

AT, DE, FI (3) 

DE, ES, FI, FR, LT, 
NO, SE (7) 

ES, FI (2) 

Salary 

DE, EE, FI, FR, HU, IE, IT, LT, 
LV, NL, SE, UK (12) 

DE, EE, FI, FR, SE, UK (6) 

AT, DE, FI, HU (4)  DE, FI, FR, LT, SE, 

FI (1) 

UK (6) 

Further 
education 

DE, DK, EE, ES, FI, FR, HU, IE, 
IT, LV, NL, PL, SE, SI, UK (15) 

DE, DK, EE, FI, FR, PL, SE, SI, 
UK (9) 

DE, DK, FI, HU, SI 
(5) 

DE, ES, FI, FR, NO, 
SE, UK (7) 

ES, FI (2) 

Satisfaction 
(general) 

DE, ES, FI, FR, HU, IT, LV, NL 
(8) 

DE, FR (2) 

AT, DE, HU (3) 

DE, ES, FI, FR (4) 

ES, FI (2) 

Relevance of 
acquired skills 

DE, ES, FI, FR, HU, IT, LT, LV, 
NL, SE (10) 

DE, FR, SE (3) 

DE, HU (2) 

DE, ES, FI, FR, LT, SE 
(6) 

ES, FI (2) 

DE, FI, LV (3) 

DE (1) 

DE (1) 

DE, FI (2) 

FI (1) 

BE-NL, CZ, DE, EE, ES, FI, FR, 
HU, IE, IT, LT, LV, PL, SE, SI, 
SK, UK (17) 

DE, EE, FI, IE, IT, LT, LV, SE, SI, 
SK, UK (11) 

BE-NL, CZ, DE, EE, FI, PL, SE, 
SI, UK (9) 

AT, DE, FI, HU, SI 
(5) 

DE, ES, FI, LT, NO, 
SE, UK (7) 

ES, FI (2) 

DE, EE, FI, SE, SI, UK (6) 

AT, DE, FI, SI (4)  DE, FI, LT, NO, SE, 

FI (1) 

UK (6) 

Social/civic 
activities 

Socio-
biographical 
information 

Age 

March, 2020 

182 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Gender 

BE-NL, CZ, DE, EE, FI, FR, IE, IT, 
LT, LV, SE (11) 

BE-NL, CZ, DE, EE, FI, SE (6)  AT, DE, FI (3) 

DE, FI, LT, NO, SE 
(5) 

FI (1) 

Nationality 

DE, FI, IE, IT, SE, SI (6) 

DE, FI, SE, SI (4) 

AT, DE, FI, SI (4)  DE, FI, NO, SE (4) 

FI (1) 

Social 
background 

DE, IT, LV, UK (4) 

DE, FI, UK (3) 

AT, DE, FI (3) 

DE, FI, UK (3) 

FI (1) 

Level, field of 
study, provider 

BE-NL, DE, ES, FI, FR, HU, IE, 
LT, LV, NL, SE, SI, UK (13) 

BE-NL, DE, FI, FR, SE, SI, UK 
(7) 

AT, DE, FI, HU, SI 
(5) 

DE, ES, FI, FR, LT, 
SE, UK (7) 

ES, FI (2) 

Place of 
residence/migrati
on 

BE-NL, DE, ES, FI, FR, HU, IT, 
LT, LV, NL, SI (11) 

BE-NL, DE, FI, FR, SI (5) 

AT, DE, FI, HU, SI 
(5) 

DE, ES, FI, FR, LT (5)  ES, FI (2) 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

183 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 81.  Country coverage of graduate groups with potential for comparability (in measures with ISCED/ISCED-F classification, periodicity) in IVET (39 

measures) 

Indicator 

Completers 

People who have left 
without completing 

Students (before 
completion) 

Residents in 
country 

Migrants to another 
country after 
graduation 

Employment 
status 

AT, BE-NL, CZ, DE, DK, EE, ES, FI, 
FR, HU, IE, IT, LT, LU, NL, NO, PT, 
SE, SK, UK (20) 

AT, BE-NL, CZ, DE, EE, 
ES, FI, FR, HU, LU, PT, 
SE, UK (13) 

CZ, DE, FI, HU (4) 

AT, DE, FR, LT, 
NO, SE, UK (7) 

HU (1) 

Sustainable 
employment 

AT, CZ, DE, FI, FR, HU, IE, IT, LT, 
LU, NL, NO, SE (13) 

AT, DE, FI, FR, HU, LU, 
SE (7) 

CZ, DE,FI, HU (4) 

AT, DE, FR, LT, 
NO, SE (6) 

HU (1) 

Salary 

AT, DE, DK, EE, FR, IE, IT, LT, NL, 
SE, UK (11) 

AT, DE, EE, FI, FR, HU, 
SE, UK (8) 

DE, FI (2) 

AT, DE, FR, LT, 
SE, UK (6) 

HU (1) 

Further 
education 

AT, CZ, DE, DK, EE, FI, FR, HU, IE, 
IT, LU, NL, NO, SE, UK (15) 

AT, DE, DK, EE, FI, FR, 
LU, SE, UK (9) 

CZ, DE, DK, FI, HU 
(5) 

AT, DE, FR, NO, 
SE, UK (6) 

- 

Satisfaction 
(general) 

CZ, DE, FI, FR, IE, IT, NL, NO (8) 

DE, FR, HU (3) 

CZ, DE (2) 

DE, FR (2) 

HU (1) 

Relevance of 
acquired skills 

CZ, DE, DK, FI, FR, HU, IE, IT, LT, 
NL, NO, SE (12) 

DE, FR, HU, SE (4) 

CZ, DE, HU (3) 

DE, FR, LT, SE (4)  HU (1) 

Social/civic 
activities 

DE (1) 

DE (1) 

DE (1) 

DE (1) 

- 

Socio-
biographical 
information 

AT, BE-NL1, CZ4, DE, DK, EE, FI, 
FR, IE, IT, LT, LU, NL, NO, SE, SK, 
UK (17) 

AT, BE-NL, CZ, DE, EE, 
FI, FR, HU, LU, SE, UK 
(11) 

CZ, DE, FI (3) 

AT, DE, LT, NO, 
SE, UK (6) 

HU (1) 

Age 

AT, DE, EE, ES, FI, IE, LT, LU, NL, 
NO, SE, SK, UK (13) 

AT, DE, EE, ES, FI, LU, 
SE, UK (8) 

DE, FI (2) 

AT, DE, LT, NO, 
SE, UK (6) 

- 

March, 2020 

184 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students (before 
completion) 

Residents in 
country 

Migrants to another 
country after 
graduation 

Gender 

AT, BE-NL, CZ, DE, EE, ES, FI, FR, 
IE, LT, LU, NL, NO, SE (14) 

AT, BE-NL, CZ, DE, EE, 
ES, FI, FR, LU, SE (10) 

DE, FI (2) 

Nationality 

AT, DE, ES, FI, IE, IT, LU, SE (8) 

AT, DE, ES, FI, LU, SE 
(6) 

DE, FI (2) 

AT, DE, LT, NO, 
SE (5) 

AT, DE, NO, SE 
(4) 

- 

- 

Social 
background 

DE, FI, IT, LU, UK (5) 

DE, FI, HU, LU, UK (5) 

DE, FI (2) 

DE, UK (2) 

HU (1) 

Level, field of 
study, provider 

AT, BE-NL, CZ, DE, FI, FR, IE, LT, 
NL, NO, SE, UK (12) 

AT, BE-NL, DE, FI, FR, 
SE, UK (7) 

CZ, DE, FI (3) 

AT, DE, FR, LT, 
SE, UK (6) 

- 

Place of 
residence/migra
tion 

AT, BE-NL, DE, DK, FI, FR, HU, IE, 
IT, LT, NL, NO (12) 

AT, BE-NL, DE, FI, FR, 
HU (6) 

DE, FI, HU (3) 

AT, DE, FR, LT (4)  HU (1) 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

185 

 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 82.  Country coverage of graduate groups with potential for comparability (in measures with ISCED/ISCED-F classification, periodicity) in CVET (19 

measures) 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Employment status 

AT, DE, FI, FR, IE, NL, NO, 
PT, SE, UK (10) 

AT, DE, FI, FR, PT, UK (6)  DE, FI(2) 

Sustainable 
employment 

AT, DE, FI, FR, IE, NL, NO 
(7) 

AT, DE, FI, FR (4) 

DE, FI (2) 

AT, DE, FR, NO, 
SE, UK (6) 

AT, DE, FR, NO 
(4) 

- 

- 

Salary 

AT, DE, FR, IE, NL, UK (6) 

AT, DE, FI, FR, UK (5) 

DE, DK, FI(3) 

AT, DE, FR, UK (4)  - 

Further education 

AT, DE, DK, FI, FR, IE, NL, 
NO, SE, UK (10) 

AT, DE, DK, FI, FR, UK (6)  DE, FI (2) 

AT, DE, FR, NO, 
SE, UK (6) 

Satisfaction (general)  DE, FI, FR, IE, NL, NO, SE 
(7) 

Relevance of acquired 
skills 

DE, FI, FR, IE, NL, NO, SE 
(7) 

DE, FR (2) 

DE (1) 

DE, FR, SE (3) 

DE, FR (2) 

DE (1) 

DE, FR, SE (3) 

Social/civic activities  DE (1) 

DE (1) 

DE (1) 

DE (1) 

Socio-biographical 
information 

AT, DE, DK, FI, IE, NL, NO, 
SE, UK (9) 

AT, DE, DK, FI, UK (5) 

DE, DK, FI (3)  AT, DE, NO, SE, 

AT, DE, FI, IE, NL, NO, SE, 
UK (8) 

AT, DE, FI, IE, NL, NO, SE 
(7) 

AT, DE, FI, UK (4) 

DE, FI (2) 

AT, DE, FI (3) 

DE, FI (2) 

Age 

Gender 

March, 2020 

UK (5) 

AT, DE, NO, SE, 
UK (5) 

AT, DE, NO, SE 
(4) 

- 

- 

- 

- 

- 

- 

- 

186 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Nationality 

AT, DE, FI, IE, SE (5) 

AT, DE, FI(3) 

DE, FI (2) 

AT, DE, NO, SE 
(4) 

Social background 

DE, FI, UK (3) 

DE, FI, UK (3) 

DE, FI (2) 

DE, UK (2) 

Level, field of study, 
provider 

AT, DE, FI, FR, IE, NL, NO, 
SE, UK (9) 

AT, DE, FI, FR, UK (5) 

DE, FI (2) 

AT, DE, FR, SE, 
UK (5) 

Place of 
residence/migration 

AT, DE, FI, FR, IE, NL, NO 
(7) 

AT, DE, FI, FR (4) 

DE, FI (2) 

AT, DE, FR (3) 

- 

- 

- 

- 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

187 

 
 
 
 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Table 84.  Country coverage of graduate groups with potential for comparability (in measures with ISCED/ISCED-F classification, periodicity) in HE (51 

measures) 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Employment 
status 

AT, BE-NL, CZ, DE, DK, EE, ES, FI, 
FR, HU, IE, IT, LT, LV, NL, NO, PL, 
PT, SE, SK, UK (21) 

AT, BE-NL, CZ, DE, EE, FI, 
FR, PL, SE, UK (10) 

AT, DE, FI, HU 
(4) 

AT, DE, ES, FI, FR, 
LT, NO, SE, UK (9) 

ES, FI (2) 

Sustainable 
employment 

AT, DE, ES, FI, FR, IT, LT, LV, NL, 
NO, SE (11) 

AT, DE, FI, FR, SE (5) 

AT, DE, FI (3) 

AT, DE, ES, FI, FR, 
LT, NO, SE (8) 

ES, FI (2) 

Salary 

AT, DE, DK, EE, FI, FR, HU, IE, IT, 
LT, LV, NL, NO, SE, SK, UK (16) 

AT, DE, EE, FI, FR, SE, UK 
(7) 

AT, DE, FI, HU 
(4) 

AT, DE, FI, FR, LT, 
SE, UK (7) 

FI (1) 

Further 
education 

AT, DE, DK, EE, ES, FI, FR, HU, IE, 
IT, LV, NL, NO,  PL, SE, SI, SK, UK 
(18) 

Satisfaction 
(general) 

DE, ES, FI, FR, HU, IE, IT, LV, NL, 
NO (10) 

AT, DE, DK, EE, FI, FR, PL, 
SE, SI, UK (10) 

DE, DK, FI, HU, 
SI (5) 

AT, DE, ES, FI, FR, 
NO, SE, UK (8) 

ES, FI (2) 

DE, FR (2) 

AT, DE, HU (3) 

DE, ES, FI, FR (4) 

ES, FI (2) 

Relevance of 
acquired skills 

DE, DK, ES, FI, FR, HU, IE, IT, LT, 
LV, NL, NO, SE, SK (14) 

DE, FR, SE (3) 

DE, HU (2) 

DE, ES, FI, FR, LT, 
SE (6) 

ES, FI (2) 

Social/civic 
activities 

DE, FI, LV (3) 

DE (1) 

DE (1) 

DE, FI (2) 

FI (1) 

Socio-
biographical 
information 

AT, BE-NL, CZ, DE, DK, EE, ES, FI, 
FR, HU, IE, IT, LT, LV, NO, PL, SE, 
SI, SK, UK (20) 

AT, BE-NL, CZ, DE, EE, FI, 
PL, SE, SI, UK (10) 

AT, DE, FI, HU, SI 
(5) 

AT, DE, ES, LT, NO, 
SE, UK (7) 

ES, FI (2) 

Age 

AT, DE, EE, FI, IE, IT, LT, LV, NO, 
SE, SI, SK, UK (13) 

AT, DE, EE, FI, SE, SI, UK 
(7) 

AT, DE, FI, SI (4)  AT, DE, FI, LT, NO, 

FI (1) 

SE, UK (7) 

March, 2020 

188 

 
 
 
Mapping the state of graduate tracking policies and practices in the EU Member States and EEA countries 

Indicator 

Completers 

People who have left 
without completing 

Students 
(before 
completion) 

Residents in 
country 

Migrants to 
another country 
after graduation 

Gender 

AT, BE-NL, CZ, DE, EE, FI, FR, IE, 
IT, NO, LT, LV, SE (13) 

AT, BE-NL, CZ, DE, EE, FI, 
SE (7) 

AT, DE, FI (3) 

AT, DE, FI, LT, NO, 
SE (6) 

FI (1) 

Nationality 

AT, DE, FI, IE, IT, NO, SE, SI (8) 

AT, DE, FI, SE, SI (5) 

AT, DE, FI, SI (4)  AT, DE, FI, NO, SE 

FI (1) 

(5) 

Social 
background 

AT, DE, IE, IT, LV, UK (6) 

AT, DE, FI, UK (4) 

AT, DE, FI (3) 

AT, DE, FI, UK (4) 

FI (1) 

Level, field of 
study, provider 

AT, BE-NL, DE, ES, FI, FR, HU, IE, 
LT, LV, NL, NO, SE, SI, SK, UK (16) 

AT, BE-NL, DE, FI, FR, SE, 
SI, UK (8) 

AT, DE, FI, HU, SI 
(5) 

AT, DE, ES, FI, FR, 
LT, SE, UK (8) 

ES, FI (2) 

Place of 
residence/migr
ation 

AT, BE-NL, DE, DK, ES, FI, FR, HU, 
IE, IT, LT, LV, NL, NO, SI, SK (16) 

AT, BE-NL, DE, FI, FR, SI 
(6) 

AT, DE, FI, HU, SI 
(5) 

AT, DE, ES, FI, FR, 
LT (6) 

ES, FI (2) 

Source: Mapping research conducted by ICF, 3s and CHEPS. 

March, 2020 

189 

 
 
 
GETTING IN TOUCH WITH THE EU 

In person 

All over the European Union there are hundreds of Europe Direct information centres. 
You can find the address of the centre nearest you at: https://europa.eu/european-
union/contact_en 

On the phone or by email 

Europe Direct is a service that answers your questions about the European Union. You 
can contact this service: 

– by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls), 

– at the following standard number: +32 22999696 or  

– by email via: https://europa.eu/european-union/contact_en 

FINDING INFORMATION ABOUT THE EU 

Online 

Information about the European Union in all the official languages of the EU is available 
on the Europa website at: https://europa.eu/european-union/index_en 

EU publications 

You can download or order free and priced EU publications at: 
https://op.europa.eu/en/publications. Multiple copies of free publications may be 
obtained by contacting Europe Direct or your local information centre (see 
https://europa.eu/european-union/contact_en). 

EU law and related documents 

For access to legal information from the EU, including all EU law since 1952 in all the 
official language versions, go to EUR-Lex at: http://eur-lex.europa.eu 

Open data from the EU 

The EU Open Data Portal (http://data.europa.eu/euodp/en) provides access to datasets 
from the EU. Data can be downloaded and reused for free, for both commercial and non-
commercial purposes.