NEWS (10.03.2016): The ETER data collection for 2013/2014 is running and data for 27 countries are already validated. Additionally, you can download
the final report of the first two years of the ETER project in 'Documents'.


ETER (European Tertiary Education Register) is a project promoted by the Directorate General for Education and Culture of the European Commission, in cooperation with the Directorate General for Research and Innovation and EUROSTAT (see poster here and a general presentation of ETER here). The purpose is to build a register of higher education institutions in Europe, providing data on the number of students, graduates, international doctorates, staff, fields of education, income and expenditure as well as descriptive information on their characteristics. You can download some examples of analyses which can be done from ETER here and a guidance on how to use the data here.

The Register builds on the results and experience of the EUMIDA (EUropean MIcroDAta collection) study and has the following goals:

  • Develop a more complete set of indicators and characterize HEIs according to their main activities.
  • Extend the coverage of the EUMIDA dataset to cover all European HEIs (with the exception of some small institutions).
  • Collect data for 2011 and 2012, validate them and make them publicly available.
  • Produce a methodological Handbook, as the basis for a regular data collection on European HEIs.
This website provides access to data collected for the year 2011 (respectively the academic year 2011/2012) and 2012 (academic year 2012/2013). ETER is not a ranking of European Higher Education and thus does not aim directly to compare HEIs. Rather, it provides a register of European Higher Education, as well as a core set of data on their characteristics, resources and outputs.

In case you have any questions or problems, please contact Daniel Wagner-Schuster (+43 316 876 1475, ) or Angelika Sauer (+43 316 876 1483, ).

This application provides access to the established tertiary education register and enables the user to perform the following activities:

  1. Viewing the list of HEIs in ETER by using the tab Higher Education Institutions. By clicking on one HEI, it is possible to see its identifier and to export the data for that individual HEI in XLSX or CSV format (“export results/create reports” tab). It is possible to select all data or only a specific subset of them.

  2. Downloading the ETER micro data through the tab Download ETER Data. This tab opens a search interface where it is possible to search HEIs based on the reference year, their name, IDs and country. Once the list has been generated, it is possible to export the data in XLSX or CSV format (“export results/create reports” tab). To export the full dataset, simply perform the search inserting only the year(s) of interest.

  3. Downloading the full dataset in different versions:
    1. Download the whole dataset for both years (.xlsx) from 03.07.2015 here.
    2. Download the whole dataset for both years (.csv) from 03.07.2015 here.
    3. Download the combined 2011/12-2012/13 dataset (.sav) from 03.07.2015 here. This dataset includes mostly 2012/13 data, except for a few countries for which only 2011/12 data are available. It already includes the variable codes needed for the analysis in SPSS.
  4. Downloading information about demographic events and country level metadata. Demographic events inform about changes in the HEI landscape between the years 2008 (EUMIDA baseline year), 2011 (ETER baseline year) and 2012. Metadata provide important information on methodological issues, data sources and departures from definitions and thus are an important complement to the dataset. It is possible to both download metadata for all countries at once, as well as those for individual countries separately.
Only publicly available data can be accessed from this site. A few additional data (mostly concerning finances) are available only for research purposes under signature of a non-disclosure agreement. In case you would like to have access to restricted data, please contact Daniel Wagner-Schuster (+43 316 876 1475, ) or Angelika Sauer (+43 316 876 1483, ).

All statistical data, metadata, content of web pages or other dissemination tools, official publications and other documents published on this website can be reused without any payment or written license provided that the source is indicated as ETER and when re-use involves modifications to the data or text, this must be stated clearly to the end user of the information.

ETER provides data on the following dimensions of HEI activities:

  1. Institutional descriptors including legal status, institutional category, foundation year, etc.
  2. Geographical descriptors including the region of establishment, the city and the geographical coordinates of the institution.
  3. Educational activities: data on students and graduates by level of education (diploma, bachelor, master; ISCED5-7), field of education, gender, citizenship and mobility.
  4. Research activities: research-active institution, PhD students and graduates (ISCED8), R&D expenditures.
  5. Expenditures, divided between personnel, non-personnel and capital, and revenues, divided between core budget, third-party funding and student fees funding.
  6. Staff: academic staff by gender, citizenship and field of education; non-academic staff; full professors by gender.
  7. A set of characterization indicators concerning gender, citizenship, mobility, composition of staff and composition of HEI revenues.

The full list of variables and indicators available in ETER can be downloaded here, additionally you can find a summary of all special codes and flags used in the dataset here. Users are strongly recommended to read carefully the ETER handbook providing full methodological information (here).

Data have been mostly provided by National Statistical Authorities based on their statistical systems and, when applicable, to standardized definitions at the European and international levels. Some data (particularly descriptors) have been retrieved directly by the project partners from public sources. The full dataset can be downloaded as XLSX-version here or as CSV-version here. The combined 2011/12-2012/13 dataset in SPSS format can also be downloaded here.

The user should refer to the annexed metadata in order to ascertain sources and limitations of data. A quality report on the dataset can be consulted here.

Data and information provided on this Website do not in any way engage the responsibility of the European Commission, nor of the national data providers.

Further information on the data, methodology and the project is provided in the Frequently Asked Question section and in the annexed documents. For any specific queries and issues concerning data please contact the ETER consortium at .

In this section, we provide a few results of analyses based on the ETER data. They are based on the combined database 2011/2012, which includes data for 2293 HEIs in 31 countries, accounting for 16,6m undergraduate students and 0,5m PhD students.

It is possible to download the whole set of analyses in pdf format (here) or to download individual analysis, as well as the figures separately in JPEG format. This information can be freely reused under the condition that the source is acknowledged (© ETER project 2015).

  1. How many HEIs and how large? A short analysis of the distribution by size of European Higher Education Institutions, both concerning the number of students and of staff. - pdf
    Figure 1. Number of HEIs, student population and average size by country
    Figure 2. Distribution of HEIs by size and country
    Figure 3. Distribution of academic staff by country and HEI

  2. How important are private HEIs in European higher education? - pdf
    Figure 1. Distribution of HEIs by their size
    Figure 2. Undergraduate students by HEIs legal status by country

  3. Which types of HEIs? Unitary and binary systems in Europe - pdf
    Figure 1. HEIs by type and activity
    Figure 2. Distribution of undergraduate students by type of HEIs

  4. How are European HEIs funded? - pdf
    Figure 1. Composition of revenues of HEIs
    Figure 2. Third party funds per professor in purchasing power parities
    Figure 3. Share of third-party funds and tuition fees over total revenues

  5. Education and research: complementary or segregated? - pdf
    Figure 1. Distribution of HEIs by research activity and country
    Figure 2. Distribution of undergraduate students by HEI level of degree
    Figure 3. PhD intensity by country and HEI

  6. Subject domains: specialized vs. generalist HEIs - pdf
    Figure 1. Frequency distribution of subject specialization
    Figure 2. Distribution of subject specialization by countries
    Figure 3. Frequency distribution of the Herfindahl index by institution category

  7. Mobility of students and academics in the European Research Area - pdf
    Figure 1. Share of foreign students by degree levels
    Figure 2. Share of foreign undergraduate students (above) and foreign PhD students (below)
    Figure 3. Share of foreign academic staff

  8. Gender equality at European Higher Education Institutions - pdf
    Figure 1. Share of full professors among total academic staff at universities in selected countries: 2012
    Figure 2. Share of women among academic staff and full professors at universities in selected countries: 2012

The ETER consortium strongly recommends interested users to read carefully all the documents produced and accompanying the data reported below before using them. The main documents on the ETER dataset, its methodology and results are:

  1. The ETER final report provides a general presentation of the main conceptual and methodological choices of ETER, an overview of the database content and selected analytical results of policy interest. It has been written for a broader audiences and is available here. Additionally, you can access the executive summary and the technical annex.

  2. The Handbook for Data Collection provides an in-depth description of the data collection methodology of the ETER project, including basic definitions, the perimeter for data collection, classification schemes for data, definition of variables and guidelines for data collection and quality control. You can download the handbook here, additionally you can find a summary of all codes and flags used in the data set here.

  3. The ETER technical report provides detailed information on the ETER methodology, data collection process, data management and data quality. It is especially intended for expert users and national statistical authorities (available here).

  4. Summary PowerPoint-presentations of ETER:
    1. An overall presentation of the database and its coverage. You can download the presentation in pdf format here.
    2. A presentation of the data quality process in ETER can be downloaded in pdf format here.
    3. A presentation of the indicators for characterizing HEIs provided in ETER can be downloaded in pdf format here.
    4. A presentation of the on-line tool and a guidance on how to use the data can be downloaded in pdf format here.
    5. A few highlights of potentially interesting results from a preliminary analysis of the data can be downloaded here.



Publication Author Year Publisher Short description Link Download
Hoe komen hogeronderwijsinstellingen aan hun geld?
(What are the revenue sources of higher education institutions?)
Ben Jongbloed 2015 THEMA Hoger Onderwijs, Vol. 21 No. 5, pp. 44-48 Short description http://doc.utwente.nl/93470/
Analyzing subject mix of European Higher Education Institutions. An Exploratory analysis using the European Tertiary Education Register data
Daniel Wagner-Schuster and Benedetto Lepori 2015 20th Conference on Science and technology Indicators, Lugano, 2-4 September 2015 Short description http://www.sti2015.usi.ch/characterizing-higher-education-institutions
Characterizing European Research Universities
Benedetto Lepori, Valerio Veglio and Aldo Geuna 2015 20th Conference on Science and technology Indicators, Lugano, 2-4 September 2015 Short description http://www.sti2015.usi.ch/characterizing-higher-education-institutions
Gender equality in higher education institutions in Europe. An analysis based on ETER data.
Hebe Gunnes and Elisabeth Hovdhaugen 2015 20th Conference on Science and technology Indicators, Lugano, 2-4 September 2015 Short description http://www.sti2015.usi.ch/characterizing-higher-education-institutions
The funding of research in higher education: mixed models and mixed results.
Ben Jongbloed and Benedetto Lepori 2015 Handbook of Higher Education Policy and Governance. Palgrave. Short description

This section provides short answers to key questions about the ETER project and the data.

  1. The ETER project

    1. What is the ETER project?
      The European Tertiary Education Register (ETER) is a project funded by the European Commission, Directorate general Education and Culture (contract EAC-2013-0308), which aims at constituting a register of European Higher Education Institutions (HEI) and collecting a comparable set of data for the HEIs in the perimeter. It started in August 2013 and will terminate in summer 2015.

    2. Who are the project partners?
      ETER is a joint undertaking of four partners:
      1. USI – Università della Svizzera Italiana, Center for Organizational Research, Lugano
      2. JOANNEUM RESEARCH, POLICIES – Centre for Economic and Innovation Research, Graz
      3. NIFU – Nordic Institute for Studies in Innovation, Research and Education, Oslo
      4. University of Rome La Sapienza, Department of Computer, Control and Management Engineering Antonio Ruberti, Rome
      They are supported by Andrea Bonaccorsi, former EUMIDA coordinator, as individual expert, as well as by a network of experts in the concerned countries. It is supervised by the Directorate General for Education and Culture of the European Commission, in cooperation with DG Research and Innovation and EUROSTAT.


    3. What are the relationships between ETER and EUMIDA?
      EUMIDA (EUropean MIcroDAta) was a feasibility study for undertaking a data collection on European higher education supported by the European Commission in 2010. It collected data on higher education institutions for the year 2008 for the EU member states plus Norway and Switzerland. EUMIDA was the predecessor of ETER. ETER adopts a very similar set of definitions and methodologies as EUMIDA, but builds to a larger extent on the cooperation with National Statistical Authorities.

    4. Which is the role of National Statistical Authorities in ETER?
      National Statistical Authorities are actively involved in ETER through a project task force, where methodological choices are discussed between the consortium and NSAs. Moreover, NSAs provide most of the statistical data contained in the ETER database.


  2. Coverage

    1. Which countries are covered?
      ETER covers all 28 European Union member states, EEA-EFTA countries (Iceland, Liechtenstein, Norway and Switzerland), as well as candidate countries (the Former Yugoslav Republic of Macedonia, Montenegro, Serbia and Turkey), for a total of 36 countries.
      For the moment, the following countries have not provided data beyond the list of HEIs: Montenegro, Romania, Serbia, Slovenia and Turkey. Belgium provided data only for the Flemish speaking region of the country.


    2. Which educational institutions are included?
      ETER includes educational institutions for which a major activity is graduating at least at level 5 of the ISCED-2011 classification of education degrees, possibly alongside research. As a general rule, institutions delivering tertiary education as a side activity (for example professional associations) and HEIs with less than 200 students and 30 full-time equivalents of staff are excluded.
      In terms of coverage of tertiary education, ETER includes almost all educational institutions graduating at ISCED level 6 (bachelor), 7 (master) or 8 (doctorate), while institutions delivering only professional diplomas (level ISCED 5) are mostly excluded.


    3. How many HEIs are covered by ETER?
      ETER currently includes 2673 HEIs the 36 considered countries; for 2293 HEIs data are available. The largest number of HEIs is in Germany (386), followed by Poland (272), France (286), Turkey (182) Italy (176) and UK (151).


  3. Variables

    1. To which year do data refer to?
      In the current release of ETER, two waves of data collection are provided. Data refer to the academic years 2011/12 respectively 2012/13.

    2. Which kinds of variables are included in the dataset?
      The dataset includes following main groups of variables:
      1. Institutional descriptors, e.g. the name of the institution and the foundation year.
      2. Geographical descriptors like the NUTS region, the city of the main seat and its postcode.
      3. Data on numbers of students and graduates divided by ISCED-2011 level, by gender, fields of education, nationality and mobility.
      4. Data on HEI expenditures and revenues.
      5. Data on the number of staff, divided between academic and non-academic, as well as on the number of professors.
      6. Data on research activities (PhD students and graduates, R&D expenditure).
      A full list of variables is included in the ETER handbook.


    3. Why does ETER also provides indicators?
      The ETER database includes also a set of indicators computed from the variables in ETER, concerning gender, citizenship, mobility, composition of staff and of HEI revenues. These indicators have been selected based on their analytical and policy interest, but also based on consideration of methodological robustness and availability of data.

    4. How are variables defined?
      To the extent possible, ETER builds on available definitions and standards from official statistics and, especially from the Unesco – OECD – EUROSTAT handbook on educational data collection (for students and graduates), as well as on the Frascati manual for R&D expenditures. In some areas which are not fully covered by official statistics, like descriptors, ETER has built its own definitions. Users are requested to consult the ETER handbook for definitions and methodological instructions before starting to use the data.

    5. What do special codes in the dataset mean?
      Following special codes are used in the dataset:
      1. Code “a” refers to the fact that the variable is not applicable to the unit of observation (e.g. number of PhD students for a HEI which does not have the right to award doctorates).
      2. Code “m” refers to the fact that the data in question is missing.
      3. Code “x” is used when a specific breakdown is not available, but the data are included in the total.
      4. Code “xc” is used when the value is included in another subcategory (e.g. private funding, when it is included in third party funding but cannot be singled out).
      5. Code “xr” is used when the value is included in another row (e.g. value for an HEI included in a parent HEI).
      6. Code “c” is used when the data are available, but under restricted access.
      7. Code “s” is used when a value is larger than “0” and below or equal to “3” and thus cannot be disclosed for data protection reasons.
      8. Code “nc”: The second round of data collection included new variables, which were not collected for the academic year 2011/2012. The special code “nc” refers to “not collected for reference year”).
    6. Is the dataset complete? Why are some variables missing?
      ETER undertook all efforts in order to collect as many data as possible. However, coverage is somewhat unequal across countries and variables due to the lack of reliable data sources. More specifically, the situation concerning groups of variables is as follows:
      1. Descriptors are generally available for all countries, with the exception of a few cases where information on foundation years was not available.
      2. Financial data (revenues, expenditures, R&D expenditures) are available for only about half of the countries.
      3. Staff data are generally available in most countries, the main exceptions being countries, which provided for the time being only the descriptors, but no statistical information. However, the breakdown of academic staff between national and foreigners is available for a much smaller number of countries.
      4. Students and graduates data are available for most countries, including the breakdown by gender, nationality, and fields of education. The breakdown by mobile students is less widely available.
      5. The situation is similar for PhD students, except that data are missing for a few countries.
    7. Will the set of variables be extended in the future?
      In case of future data collections, the ETER Task Force will carefully consider the possibility of including additional variables, taking into account also practical considerations concerning the resources required for collecting data.

    8. Why are variables concerning research output not included in ETER?
      The function of ETER is to provide a statistical dataset with basic data on higher education institutions, which are not available at the international level, like data on students, graduates, staff and finances. Most of data are provided by official statistical sources.
      Data on research output, like publications and patents, can be retrieved for different sources at the international level and, therefore, the user is left free to select the source which best suits its needs and to combine them with ETER data.


  4. Quality and comparability

    1. Which are the main data sources for ETER?
      Almost all ETER data have been provided by national statistical sources, mostly National Statistical Authorities and Research and Higher Education ministries. In a few cases, data have been elaborated by the ETER consortium from publicly available statistical information.
      Descriptive information and geographical information have been retrieved by the consortium from public sources, like the websites of the considered HEIs.


    2. To which extent are data reliable?
      The ETER consortium has developed a systematic data validation and quality control approach described in the methodological handbook and in the documentation of the project. The current overall status of quality of the data is reported in the technical quality report available here.

    3. What are data flags?
      Data flags are special codes appended to the data in order to warn the users of specific problems which impair comparability and affect analytical results. Flags are accompanied by a short explanation in the remarks, while full details are provided in the metadata. It is left to the user to decide whether data can nevertheless be used for their specific purpose.
      Following flags are currently employed in ETER:
      1. b: break in time series
      2. d: definition differs
      3. i: see metadata
      4. ic: inconsistent
      5. rd: rounded
      6. ms: missing subcategory
      7. c: confidential
      For full explanation please refer to the ETER handbook.


    4. How can I check for comparability problems?
      Alongside the data, ETER provides extensive metadata by each country, which explain how data were collected, comparability issues and departures of definitions. It is very important that users carefully analyze the provided metadata before starting their analyses. A short quality report on the data can be downloaded here


  5. Data usage

    1. Under which conditions can I use the ETER data?
      This website has been developed by the ETER consortium, under a contract with the European Commission, to enhance public access to information about higher education in Europe. The website and the information are the property of the European Union. The European Commission's goal is to keep this information accurate and up to date. If errors are brought to its attention, the Commission will endeavour to correct them. However, the Commission accepts no responsibility or liability whatsoever with regard to the information on this site.

      The data available on this platform are publicly available and, accordingly, can be used to make analyses of European higher education and for descriptive and policy purposes. This includes both the data and accompanying information like flags and metadata. The ETER consortium, on behalf of the European Commission, has acquired permission from National Statistical Authorities to disseminate these data.

      Use is permitted on the following conditions:
      1. Reference to the ETER project has to be made as follows: “Data source: ETER project. Download date XXX”.
      2. In scientific publications and reports, the following acknowledgment should be included: “Data have been provided by the European Tertiary Education Register (ETER), funded by the European Commission under the contract EAC-2013-0308”.
      3. The user is invited to provide to the ETER consortium a copy of reports and scientific publications issued from these data.
      4. When re-use involves modifications to the data, this must be stated clearly to the end user.
      5. While users can download the entire dataset or parts of it for analytical purposes, they are not allowed to make available the dataset (or parts of it) on an on-line support.
      6. The European Commission, the ETER consortium or the original data providers assume no liability for any interpretation of the data provided, nor for uses which do not take into account any or all of the underlying methodological issues.

      All statistical data, metadata, content of web pages or other dissemination tools, official publications and other documents published on this website can be reused without any payment or written license provided that the source is indicated as ETER and when re-use involves modifications to the data or text, this must be stated clearly to the end user of the information.


    2. Should I inform the ETER consortium of the use of the data?
      Yes. Users should provide to the ETER consortium a copy of reports and scientific publications issued from these data. Additionally, users may provide feedback on the value of ETER and advice on how the value of the database could be enhanced. Comments and suggestions could be sent to .

    3. How can I get access to restricted data?
      Due to national confidentiality requirements, some ETER data are available only for research purposes on the condition that individual data points are not disclosed publicly. This concerns mostly financial data for a small number of countries, as well as data for some private HEIs. These data are coded with “c” on the database available on this platform.
      Access to the restricted data will be provided upon signature of a non-disclosure agreement. To get access to restricted data, please contact the ETER project team.


This project is funded by the European Commission. This publication content reflects the views only of the authors. The European Commission cannot be held responsible for any use which may be made of the information contained therein.