1.1. Contact organisation
National Documentation Centre (EKT)
1.2. Contact organisation unit
Production of RDI statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
56, Zefyrou, GR-17564, P. Faliro
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
31 October 2025
2.2. Metadata last posted
31 October 2025
2.3. Metadata last update
31 October 2025
3.1. Data description
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.
Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
3.2. Classification system
Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.
3.2.1. National classification
| National nomenclature of SEO used | National classification is not used. |
|---|---|
| Correspondence table with NABS | Not applicable. |
3.2.2. NABS classification
| Deviations from NABS | Not applicable. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | No problems. Information at sub-chapter level has not been collected. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | “Non-oriented research” and “general university funds (GUF)” are not available by fields of R&D (FORD). |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Frascati Manual definition to identify R&D. |
|---|---|
| Coverage of R&D or S&T in general | GBARD statistics cover R&D. |
| Fields of R&D (FORD) covered | GBARD data cover NSE and SSH. |
| Socioeconomic objective (SEO by NABS) | GBARD data cover SEO by NABS. |
3.3.2. Definition and coverage of government
GBARD statistics are assumed to report detailed data on all the government's budget items that may support R&D activities and to measure or estimate their R&D content. For the purposes of GBARD, the Government sector comprises (a) the central (federal) government, (b) regional (state) government and (c) local (municipal) government subsectors (FM2015, Chapter 12).
| Levels of government | Definition | Included / Not included | Comments |
|---|---|---|---|
| Central (federal) government | Ministries (Central Administrations), General Secretariats | included | Included are: Ministries (Central Administrations) and General Secretariats. General Secretariats are covered as separate reporting units in cases of important R&D Secretariats (e.g. General Secretariat for Research and Innovation) or in cases of complex structures in some Ministries (e.g. Ministry of Environment). |
| Regional (state) government | Self-governed Public Legal Entities | included | Regions are territorially self-governed Public Legal Entities responsible for planning and implementing policies at regional level. |
| Local (municipal) government | Not included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
All Ministries, according to the Register of General Government Entities maintained at the Hellenic Statistical Authority (ELSTAT), and all regional authorities. General Secretariats are covered as separate reporting units in cases of important R&D Secretariats (e.g. General Secretariat for Research and Innovation) or in cases of complex structures in some Ministries (e.g. Ministry of Environment).
3.6. Statistical population
See below.
3.6.1. National target population
The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units, which can be accessed through the frame and the survey data really refer to this population.
| Definition of the national target population | All Ministries and Regional Authorities. |
|---|---|
| Estimation of the target population size | Ministries and Regional Authorities according to the government structure in 2023: 23 Ministries (including some important General Secretariats as separate statistical units) and 13 Regional Authorities. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested.
3.9. Base period
Not requested.
Not requested.
- Calendar year: 2023.
- Fiscal year: 2023.
- Start month: January.
- End month: December.
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
Since the beginning of 2021, GBARD statistics are based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. GBARD statistics were based until the end of 2020 on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
6.1.2. National legislation
GBARD statistics are governed by general national statistical legislation.
More specifically:
- Greek Statistical Law No 3832/2010, as in force
- Regulation on the Operation and Administration of the Hellenic Statistical Authority (ELSTAT), 2012 (Government Gazette 2390 B, 28 August 2012),
- Regulation on the Statistical Obligations of the agencies of the Hellenic Statistical System (Government Gazette 4083 Β, 20 December 2016).
More information available More Information on Indicators and Statistics
6.1.3. Standards and manuals
- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development.
- EBS Methodological Manual on R&D Statistics.
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.
A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.
- Confidentiality protection required by law:
Confidentiality issues are clearly defined in the provisions on statistical confidentiality of the Greek statistical law (Law 3832/2010, as amended and in force), and are further specified in the Regulation on the Statistical Obligations of the Agencies of the Hellenic Statistical System (ELSS).
As an Agency of the ELSS and a National Authority, EKT fully implements the above law and regulation as well as the European Statistics Code of Practice (principle 5 and relevant indicators). To this end, EKT has developed and published its Statistical Confidentiality Policy.
- Confidentiality commitments of survey staff:
The internal personnel employed in the RDI statistics unit at EKT, the external statistical correspondents used for the collection and checking of primary data of its statistical surveys, as well as the external experts providing EKT with technical support or being assigned to carry out statistical works on account of EKT, commit themselves to the observance of statistical confidentiality of the data to which they have access or which they handle and sign a statistical confidentiality declaration.
7.2. Confidentiality - data treatment
Concerning the procedures to identify confidential cells in data delivered to Eurostat, no confidential suppression/protection was applied on GBARD data. Personal data collected through the collection process are strictly confidential, are used by the EKT for statistical purposes only and are not publicized or disseminated to third parties in any way.
8.1. Release calendar
The anticipated release dates for GBARD data are included in the annual release calendar published by EKT.
8.2. Release calendar access
The release calendar is available online.
8.3. Release policy - user access
EKT provides equal and simultaneous access to its statistical products for all users, as outlined in the Dissemination Policy. EKT fully complies with the relevant principles and regulations of the Statistical Confidentiality Policy.
The primary source of information for all R&D statistics produced by EKT, accessible to all users, is available on the following Metriks and Indicators. Additonally, EKT has launched a new interactive platform, DATAHub@EKT , specifically designed to enhance the dissemination of its statistical data.
GBARD data are produced and disseminated on a yearly basis.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
|---|---|---|
| Regular releases | Y | Each GBARD data is published on EKT's website, within one month of its transmission to Eurostat. Publication may be accompanied by press releases, which are distributed to all media outlets in Greece, as well as shared on social media platforms such as X, Facebook, and LinkedIn. |
| Ad-hoc releases |
- Y - Yes,
- N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
|---|---|---|
| General publication/article (paper, online) |
Y | Dedicated webpage for GBARD statistics has been created by EKT (also available in english Means of Dissemination). The GBARD data dissemination is made through different formats: 1) Publications: Publications that present the main findings of the GBARD survey and in addition publications which analyze specific issues more in depth. Some of the publications are also available in English. 2) Data briefs (Articles): Brief analysis of the results for specific topics. These reports are in Greek. 3) Data tables : This is a dissemination tree where we publish data in the form of data tables. This data tree is in Greek only. 4) EKT has launched a new interactive platform, DATAHub@EKT , specifically designed to enhance the dissemination of its statistical data. DATAHub@EKT is a new integrated digital infrastructure that offers a range of capabilities facilitating access to, understanding and use of EKT's statistical data, targeting a wide audience including policy makers, researchers and businesses. DATAHub@EKT enhances the simplification, analysis and utilization of EKT's produced statistical data |
| Specific paper publication (paper, online) |
Y | Paper publications are presented at GBARD statistics section and DATAHub@EKT. Online publication with the overall GBARD results during the reference time 2008-2018. |
- Y – Yes,
- N - No
10.3. Dissemination format - online database
Aggregate figures.
(Data are currently shown in Greek only).
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Microdata access is not provided to users outside EKT. Upon user requests, we produce more detailed analysis compared to the analysis of data requested and transmitted to Eurostat. |
|---|---|
| Access cost policy | No charges. |
| Micro-data anonymisation rules | Not applicable. |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
|---|---|---|---|
| Internet: main results available on the national statistical authority’s website | Y | Aggregate figures | |
| Data prepared for individual ad hoc requests | Y | Aggregate figures | Upon request from policy makers, expert group meetings, etc. |
| Other | Y | Aggregate figures | Data presented in the form of short articles |
- Y – Yes,
- N - No
10.6. Documentation on methodology
The production of GBARD statistics follows the Frascati Manual 2015 concepts, definitions and methodology as well as Eurostat "FM2015 Implementation, Harmonisation EU Guidelines" as updated. A detailed handbook on GBARD collection processes has been developed (internal) and is continuously enriched and improved. National metadata ((SIMS v2.0, in Greek) are made available to all users in the dedicated EKT website.
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
See below.
10.7.1. Documentation and users’ requests
| Type(s) of data accompanying information available (metadata, graphs, etc.) | National metadata (SIMS v2.0, in Greek) are made available to all users in the dedicated EKT Website. Moreover, a Glossary on GBARD Indicators is available online to explain all the R&D related concepts, NABS classification etc... Publications with graphs, tables, maps, etc. specific to each authority (ministry, general secretariate, regional authority) were been prepared during the first round of GBARD collection in 2012, containing also some methodological notes about the survey. Publications with extensive presentation of the GBARD methodology and with detailed presentation of all results have also been prepared and presented to key stakeholders during conferences. |
|---|---|
| Request on further clarification | No further clarifications have been received. |
| Measure to increase clarity | Continuous update of lexicon, regular release of publications and use of social media to raise the awareness on GBARD data and concepts. |
| Impression of users on the clarity of the accompanying information to the data | Users of GBARD statistics that participated in the user satisfaction survey, reported that they are aware of the accompanying information that is available on the website. They report to have used it and they perceive that the quality of this information is high. |
11.1. Quality assurance
At Eurostat level, the common quality framework of the European Statistical System (ESS) is composed of the European Statistics Code of Practice, the Quality Assurance Framework of the ESS, and the general quality management principles (such as continuous interaction with users, continuous improvement, integration, and harmonisation). The Code of Practice available at The ESS Code of Practice
EKT is an Agency of the Hellenic Statistical System (ELSS) and a National Authority, and as such it fully complies with the European and international standards concerning statistical methodologies, organizational procedures and IT infrastructure. EKT also complies strictly with the national and European legislative framework about statistics. EKT;s quality policy is publicly available in Greek (The Policies of the EKT).and in English ((PoliciesOf the EKT)
The 3rd round of Peer Review on the Hellenic Statistical System, conducted and published by Eurostat , has confirmed the high standards maintained by the National Documentation Centre (EKT) in its statistical operations. The review specifically highlighted EKT’s strict adherence to the principles established in the European Statistics Code of Practice. As a National Authority responsible for Research, Development, and Innovation (RDI) European statistics, EKT actively participated in the peer review process. The assessment recognized EKT’s exemplary performance and its overall excellence in fulfilling its statistical responsibilities within the European framework. EKT follows the GSBPM model (Generic Statistical Business Process Model) for the production of RDI statistics. Accordingly, the workflow of a typical GBARD collection follows all level 1 phases of the GSBPM model and level 2 sub processes, modified to meet the specific sector and data collection requirements. A detailed handbook on the production of GBARD statistics has been developed and is continuously enriched and improved.
11.2. Quality management - assessment
The overall quality of the GBARD statistical outputs is very good and captures precisely the funding flows of the government budget that are oriented for R&D purposes. The methodology has been designed in line with the FM recommendations, the relevant Commission Regulation and Eurostat guidelines. The continuous improvement is a key goal set by EKT and is implemented alongside the phases of GSBPM model.
Firstly, requirements of national users are met (such as the Hellenic Statistical Authority, the central /regional Monitoring Committees of the national development projects (ESPA projects) etc.). Moreover, in 2015, EKT realized detailed case studies in 6 central (ministries) as well as regional funding authorities. The case studies were performed through on site visits and interviews with respondents. The following topics were investigated: the data collection methodology and the systems used by the responding authorities, the problems faced as well as probable measurement errors, best practices in data collection as well as motives for respondents to participate in the survey.
In each GBARD collection round, thorough validation is carried out to check the quality as well the coherence of the outputs produced. To this end, in addition to the extensive statistical checking, multiple official sources as well as text analysis are used to check the collected data against relevant data. The final outputs are interpreted using both tangible and tacit knowledge accumulated at EKT.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 | EUROSTAT | Production of European statistics Data dissemination in Eurobase. |
| 1 | European Commission, other European agencies | Policy making for R&D and Innovation. |
| 1 | OECD, Ministries, Regional Authorities, Central /regional Monitoring Committees of the ESPA national development projects etc. | Data analysis and international comparability, dissemination of national data, drafting of publications |
| 3 | Media | Country performance in relation to other European countries. |
| 4 | Researchers, students | Analyses of public sector R&D funding (main public funders, funding streams and instruments), data analysis for the needs of MSc programmes or PhD thesis. |
Users' class codification:
1- Institutions:
- European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
- In Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
- International organisations: OECD, UN, IMF, ILO, etc.
2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.
3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of dissemination of statistics to the general public.
4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)
5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)
6- Other (User class defined for national purposes, different from the previous classes.)
12.2. Relevance - User Satisfaction
To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.
12.2.1. National Surveys and feedback
| Conduction of a user satisfaction survey or any other type of monitoring user satisfaction | Users workshops / meetings are organized with key stakeholders and policy makers (General Secretariat for Research and Innovation, Ministry of Education and Religious Affairs, Ministry of Development and Investment, central /regional Monitoring Committees of the ESPA national development projects e.tc.) on a systematic base, at least once a year. Feedback is taken into consideration in the GBARD survey design. A wide user satisfaction survey was conducted in 2015. The survey consisted of two parts: a) electronic questionnaire and b) interviews with most important/ key users (e.g. officials from the General Secretariat for Research and Innovation, key researchers). In addition, the following webiste Metrics is available with the aim to get users’ feedback and capture their satisfaction regarding the quality of the statistics produced. Each user can add any comments on this link and respective form. In addition, the user can evaluate the usefulness of the statistics produced and utilised based on a dropdown likert scale list (from not at all to very much useful). The user can also add any propositions for improvements in a specific cell in the form mentioned above. An additional -to the above- real time source of information used by EKT is social media platforms. EKT monitors regularly comments across platforms like Facebook, X, or Instagram to gather user feedback and measure satisfaction through direct user engagement. For instance, EKT identifies recurring themes in user comments, such as requests for new data requirements or additional clarifications. |
|---|---|
| User satisfaction survey specific for GBARD statistics | As regards the user survey, the questionnaire provided separate questions for each set of RDI statistics: R&D, GBARD and Innovation statistics. |
| Short description of the feedback received | Following the analysis of the feedback received by the form and link mentioned above, users are overall very satisfied with the quality of the statistics produced. At a wider audience, user survey results showed that GBARD indicators are used at least once every three months and they are considered very important. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
100%. All mandatory variables are covered and transmitted to Eurostat.
12.3.2. Completeness - overview
Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.
| 5 (Very Good) |
4 (Good) |
3 (Satisfactory) |
2 (Poor) |
1 (Very poor) |
Reasons for missing cells | |
|---|---|---|---|---|---|---|
| Provisional budget statistics1 | X | |||||
| Obligatory final budget statistics1 | X | |||||
| Optional final budget statistics2 | X |
- Criteria: Obligatory data (provisional budget and final budget). Only 'Very Good' = 100% and 'Very Poor' <100% apply.
- Criteria: Optional data (final budget). 'Very Good' = 100%; 'Good' = >75%;'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.
12.3.3. Data availability
See below.
12.3.3.1. Data availability – Provisional data
| Availability1 | Frequency of data collection | Gap years – years with missing data | Time of compilation (T+x)2 | Comments | |
|---|---|---|---|---|---|
| Total GBARD | Y (- before 1983) | Annual | 2009, 2010 | ||
| NABS Chapter level | Y | Annual | |||
| NABS Sub-chapter level | Y-2001 | Annual until 2008 | |||
| Special categories - Biotech | Y-2001 | Annual until 2008 | |||
| Special categories - Nanotech | |||||
| Special categories - Security |
- Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
- Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled.
12.3.3.2. Data availability – Final data
| Availability1 | Frequency of data collection | Gap years – years with missing data | Time of compilation (T+x)2 | Comments | |
|---|---|---|---|---|---|
| Total GBARD | Y-1978 | Annual | |||
| NABS Chapter level | Y-1978 | Annual | |||
| NABS Sub-chapter level | Y-1986 | Annual until 2008 | |||
| Special categories - Biotech | Y-1984 | Annual until 2008 | |||
| Special categories - Nanotech | |||||
| Special categories - Security |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.3. Data availability – Other special categories
| Special categories | Stage1 | Availability1 | Frequency of data colletion | Gap years – years with missing data | Time of compilation (T+x)3 | Comments |
|---|---|---|---|---|---|---|
| GBARD by Project/Institutional funding | P/F | Y-2008 | Annually | |||
| GBARD by Ordinary / Investment budget | P/F | Y-2008 | Annually | GBARD covers the two main flows of government budget: Ordinary budget and Investment budget. Ordinary budget provides mainly the institutional funding which is allocated to institutes of the public sector (including universities as well as institutions located abroad e.g. CERN). Investment budget provides funding in the form of projects/programmes allocated to both public and private institutes (project funding). | ||
| GBARD by Ministry / Region | P/F | Y-2008 | Annually | |||
- Stage: P - provisional, F - final.
- Availability of the data: No, data are not available, Y: Yes, data are available + start year.
- Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled.
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
13.1.1. Accuracy - Overall by 'Types of Error'
| Sampling errors | Non-sampling errors1) | Model-assumption Errors1) | Perceived direction of the error2) | |||
|---|---|---|---|---|---|---|
| Coverage errors | Measurement errors | Processing errors | Non response errors | |||
| 2 | 1 | 4 | 3 | - | +/- | |
- Ranking of the type(s) of errors that result in over/under-estimation, from the most important source of error (1) to the least important source of error (5) In the event that errors of a particular type do not exist, is used the sign ‘-‘.
- The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for GBARD.
13.1.2. Assessment of the accuracy
| Indicators | 5 (Very Good)1 | 4 (Good)2 | 3 (Satisfactory)3 | 2 (Poor)4 | 1 (Very poor)5 |
|---|---|---|---|---|---|
| GBARD | X | ||||
| National public funding to transnationally coordinated R & D | X |
High level of coverage (At least all national or federal ministries and the ministries and agencies responsible for R&D funding at state or regional level). High rate of response (>90%) in data collection. All figures broken down by NABS.
- If at least one out of the three criteria described above would not be fully met.
- In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.
- In the event that the average rate of response would be lower than 70% and at least one of the two remaining criteria would not be met.
- If all the three criteria described above are not met.
13.2. Sampling error
Not requested.
13.2.1. Sampling error - indicators
Not requested.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
- Description/assessment of coverage errors:
Coverage errors are considered to be insignificant. GBARD survey covers all the government organizations, at both central and regional level, that may fund R&D through state budget, e.g. all Ministries and all Regional Authorities.
- Measures taken to reduce their effect:
The exact list of responding units is continuously updated, following any changes in the structure of government bodies, and is aligned with the Register of General Government Entities of the Hellenic Statistical Authority (ELSTAT).
Funding authorities are asked to report detailed information on funding flows that are oriented to each R&D performer separately through each stream of the government budget. Moreover, updated administrative data retrieved from the central Special Service for the Monitoring Information System (M.I.S.) is provided to the respondents to support them in the identification of R&D projects. (MIS is the central monitoring system of ESPA e.g. all Operational and Regional Programs of the current Partnership Agreement for the Development Framework 2021-2027 as well as the preceding National Strategic Reference Frameworks (2014-2020, 2007-2013). ESPA is the main component of Public Investment Budget.)
13.3.1.1. Over-coverage - rate
0%.
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.
- Description/assessment of measurement errors:
The main difficulties that have been reported by respondents are a) the identification of the R&D part of funds that are not fully dedicated for R&D purposes b) the distribution of funds into the NABS socio-economic objectives, which is not always straightforward since central and regional Government authorities do not use the NABS classification in their budget functions. Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.
- Measures taken to reduce their effect:
Measurement errors are reduced through the questionnaire that decomposes total GBARD into the different budget streams by beneficiary organisation (R&D performers) or R&D project. In some cases, mostly reported when distributing the ordinary budget for R&D (institutional R&D funding), reporting units are consulting the performing institutions about the content of R&D in their activities and the distribution of R&D to NABS objectives.
EKT, by utilizing its expertise on issues concerning R&D, provides specific guidelines and support to respondents as to ensure that the identification, quantification and distribution (NABS) of R&D funds is made according to Eurostat definitions. Constant telephone follow-up for guidance and clarifications as well face-to-face meetings with the staff involved in the compilation of the data were also realized. Finally, cross-checking was performed with other relevant administrative sources publicly available e.g. budget execution bulletins, ESPA monitoring portals, etc.
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
- Problems in obtaining data from targeted information providers:
Data have been collected by all (100%) R&D Funders including ministries, general secretariats and regional authorities.
- Measures taken to reduce their effect:
- Constant telephone follow-up,
- email reminders that were addressed to the heads of the agencies (mainly to the relevant General Secretary), to the directors of the responding financial departments and to the people responsible for providing the requested data.
- Effect of non-response errors on the produced statistics:
Not applicable.
13.3.3.1. Unit non-response - rate
Not requested.
13.3.3.2. Item non-response - rate
Not requested.
13.3.4. Processing error
Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.
- Data processing and editing processes:
Data has been collected with Excel questionnaire in pre-specified format. Some processing was required in cases where data has been supplied in different formats.
- Description of errors:
No processing errors exist.
- Measures taken to reduce their effect:
Not applicable.
13.3.5. Model assumption error
Description/assessment:
Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Date of first release of national data:
- Provisional budget data released and transmitted to Eurostat: T+6 months (i.e., June).
- Final budget data released and transmitted to Eurostat: T+12 months (i.e., December).
14.1.2. Time lag - final result
Date of first release of national data:
Final budget data are released twelve months after the end of reference year (e.g. final budget data for year 2023 were released in December 2024, that is T+12).
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release).
14.2.1.1. Deadline and date of data transmission
| Transmission of provisional data | Transmission of final data | |
|---|---|---|
| Legally defined deadline of data transmission (T+_ months) | 6 | 12 |
| Actual date of transmission of the data (T+x months) | 6 | 12 |
| Delay (days) | 0 - no delay | 0 - no delay |
| Reasoning for delay | not applicable | not applicable |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.
| Concept / Issue | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Research and development | FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4). | NO | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | NO | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | NO | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | NO |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Definition of GBARD | FM § 12.9 | GBARD covers the two flows/chapters of the Greek government budget: • Ordinary budget, • Investment budget Ordinary budget provides mainly the institutional funding which is allocated to institutes of the public sector (including universities as well as institutions located abroad e.g. CERN). Investment budget provides funding in the form of projects/programmes allocated to both public and private institutes (project funding). |
|
| Stages of data collection | FM2015 §12.41 | NO | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | Gross approach – inclusion of the EU support funds. | |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | The EU contribution in European Structural and Investment Funds (ESIF) projects was allocated for the period 1995-2022. The reasons can be summarized as follows: 1. Greece is a major net-beneficiary of the European Structural and Investment Funds (ESIF), receiving support for its national strategic plans for growth. 2. The Greek government plays an essential and decisive role in setting the national strategic priorities that ESIF serves and in allocating funds directed towards R&D over other projects (e.g., social, infrastructures, etc.). 3. Within the Investment budget, programs cofinanced by ESIF are reported as aggregates, comprising both the ESIF and the national contributions. 4. ESIF programs undergo the same budgetary procedures for approval (e.g. budget proposals, voting by the parliament etc.). 5. From a technical point of view, up to 2022 it was quite difficult to exclude EU funding from the GBARD data, with respect to totals or NABS breakdowns. From 2023 and onwards, following consultation with Eurostat as well as new data availability for Investment Budget, EKT has developed a process for defining EU contribution at a project level and no EU funds are reported in GBARD data. |
|
| Types of expenditure | FM2015 §12.15 to 12.18 | Both current costs and capital expenditure are covered. | |
| Current and capital expenditure | FM §12.15 | GBARD include both current and capital expenditure. | |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | Extra budgetary funds are excluded. | |
| Loans | FM §12.31, 12.32, 12.34 | Until now we have not dealt with such a case. | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | NO | Indirect funding (tax rebates, …) is excluded. |
| Treatment of multi-annual projects | FM2015 §12.44 | NO | Multi-annual projects are allocated to the GBARD of the year(s) in which they are budgeted |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | NO | GBARD covers the national contribution (part of the Ordinary Budget) to R&D performed abroad: European Organizations (European Molecular Biology Laboratory (EMBL), European Molecular Biology Conference (EMBC), CERN, European Space Foundation (ESF), European Space Agency (ESA) |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | NO | Purpose in both cases of institutional and project level distribution |
| Method of identification of primary objective | Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6 | NO | Both direct derivation and indirect spin-off approach. |
15.2. Comparability - over time
See below.
15.2.1. Length of comparable time series
See below.
15.2.2. Breaks in time series
| Length of comparable time series | Break years1 | Nature of the breaks | |
|---|---|---|---|
| Provisional data | 12 consequent years, starting from 2008 | 2023, 2008, 2004, 1995, 1989, 1984, 1983 | 2023: From 2023 onwards, the EU contribution regarding projects financed by European Structural and Investment Funds (ESIF) is no longer included in GBARD data. 2008: Revision in methodology. GBARD data (appropriations) are collected exclusively from funders. One more element to consider when analysing the Greek GBARD time series is the backloading of multiannual projects financed from Structural Funds (largest part of the Investment Budget which is approximated by the project funding breakdown of GBARD). For example, during the implementation phase of the 3rd Community Support Framework (CSF), the largest amount of available funds was distributed towards the end period of the Framework. Therefore the peak in the overall GBARD figures for 2008 which is also reflected in the project funding breakdown. Moreover, years 2007 – 2008 were overlapping years of the 3rd CSF with the National Strategic Reference Framework (NSFR). The same pattern can be seen from 2013 and onwards. In 2013, GBARD figures and in particular the project funding part start to peak again, due to the contribution of NSRF, despite the significant Ordinary Budget cuts which are reflected in the institutional funding part of the GBARD series. Moreover, the NABS 10 chapter break in 2008 can be explained by the fact that archaeological and cultural R&D activities, which is the lion’s share of GBARD NABS 10 chapter, were previously undercovered and therefore underestimated. The adoption of the new NABS 2007 classification, which included as a separate chapter “Culture”, resulted in a better identification of R&D activities in this domain. Before 2007, NABS 1992 cultural activities were included under the heading Social structures and relations (Chapter 8.), and were therefore undercovered. 2004:Research coefficients were revised for higher education, including GUF.1995:In 1995, the whole budget of the structural funds coming from the EU (under the Community Support Framework and other community initiatives), the contribution of the EU included, has been added to GBARD. Research coefficients were revised for higher education, including GUF. 1989:research coefficients were revised for higher education, including GUF. 1984: In 1984 there was a break in series 1983:methodology for GBARD data was modified in order to improve international comparability. - Public enterprises are excluded (break in series); - Establishment of the "research coefficients” to evaluate the amounts in HE. General university funds are calculated from the "research coefficients" established on the basis of a survey of higher education institutions. The first survey for the estimation of these coefficients was done in 1983 |
| Final data | 12 consequent years, starting from 2008 | 2023, 2008, 2004, 1995, 1989, 1984, 1983 | 2023: From 2023 onwards, the EU contribution regarding projects financed by European Structural and Investment Funds(ESIF) is no longer included in GBARD data. 2008: Revision in methodology. GBARD data (appropriations) are collected exclusively from funders. One more element to consider when analysing the Greek GBARD time series is the backloading of multiannual projects financed from Structural Funds (largest part of the Investment Budget which is approximated by the project funding breakdown of GBARD). For example, during the implementation phase of the 3rd Community Support Framework (CSF), the largest amount of available funds was distributed towards the end period of the Framework. Therefore the peak in the overall GBARD figures for 2008 which is also reflected in the project funding breakdown. Moreover, years 2007 – 2008 were overlapping years of the 3rd CSF with the National Strategic Reference Framework (NSFR). In 2013, GBARD figures and in particular the project funding part start to peak again, due to the contribution of NSRF, despite the significant Ordinary Budget cuts which are reflected in the institutional funding part of the GBARD series. Moreover, the NABS 10 chapter break in 2008 can be explained by the fact that archaeological and cultural R&D activities, which is the lion’s share of GBARD NABS 10 chapter, were previously undercovered and therefore underestimated. The adoption of the new NABS 2007 classification, which included as a separate chapter “Culture”, resulted in a better identification of R&D activities in this domain. Before 2007, NABS 1992 cultural activities were included under the heading Social structures and relations (Chapter 8.), and were therefore undercovered.2004:Research coefficients were revised for higher education, including GUF. 1995:In 1995, the whole budget of the structural funds coming from the EU (under the Community Support Framework and other community initiatives), the contribution of the EU included, has been added to GBARD. Research coefficients were revised for higher education, including GUF. 1989:research coefficients were revised for higher education, including GUF. 1984: In 1984 there was a break in series 1983:methodology for GBARD data was modified in order to improve international comparability. - Public enterprises are excluded (break in series); - Establishment of the "research coefficients” to evaluate the amounts in HE. General university funds are calculated from the "research coefficients" established on the basis of a survey of higher education institutions. The first survey for the estimation of these coefficients was done in 1983. |
- Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
General differences are those outlined in the FM § 522 and 523.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Not requested.
15.4. Coherence - internal
This part compares GBARD statistics from the provisional and final budget for the reference year.
15.4.1. Comparison between provisional and final data according to NABS 2007
| R&D allocations in the provisional budget delivered at T+6 | R&D allocations in the final budget delivered at T+12 | Difference (of final data) | |
|---|---|---|---|
| Exploration and exploitation of the Earth | 19036.254 (thousand euro) | 18970.161 (thousand euro) | -66.089 (thousand euro) |
| Environment |
20327.216 (thousand euro) |
21275.861 (thousand euro) |
948.645 (thousand euro) |
| Exploration and exploitation of space | 23885.799 (thousand euro) | 23607.164 (thousand euro) | -278.635 (thousand euro) |
| Transport, telecommunication and other infrastructures | 48581.232 (thousand euro) | 137473.616 (thousand euro) | 589.617 (thousand euro) |
| Energy | 8206.303 (thousand euro) | 8780.477 (thousand euro) | 574.174 (thousand euro) |
| Industrial production and technology | 210755.631 (thousand euro) | 212665.507 (thousand euro) | 1909.876 (thousand euro) |
| Health | 141147.303 (thousand euro) | 149587.568 (thousand euro) | 8440.265 (thousand euro) |
| Agriculture | 44759.835 (thousand euro) | 45033.733 (thousand euro) | -5250.644;(thousand euro) |
| Education | 7269.28 (thousand euro) | 7572.401 (thousand euro) | 303.121 (thousand euro) |
| Culture, recreation, religion and mass media | 102636.122 ;(thousand euro) | 97427.247 (thousand euro) | -5208.875 ;(thousand euro) |
| Political and social systems, structures and processes | 30460.208 ;(thousand euro) | 30486.892 (thousand euro) | 26.684 ;(thousand euro) |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 537320.226 (thousand euro) | 554234.247 (thousand euro) | 16913.981 (thousand euro) |
| General advancement of knowledge: R&D financed from other sources than GUF | 54676.551 (thousand euro) | 39900.617 (thousand euro) | -14775.934 ;(thousand euro) |
| Defence | 25816.68 (thousand euro) | 22181.560 (thousand euro) | -3635.12 (thousand euro) |
| TOTAL GBARD | 1274878.64 (thousand euro) | 1280894.284 (thousand euro) | 6015.644 ;(thousand euro) |
The assessment of costs associated with a statistical product is a rather complicated task since there must exist a mechanism for appointing portions of shared costs (for instance shared IT resources and dissemination channels) and overheads (office space, utility bills etc). The assessment must become detailed and clear enough so that international comparisons among agencies of different structures are feasible.
16.1. Costs summary
| Costs for the statistical authority (in national currency) | % sub-contracted1) | |
|---|---|---|
| Staff costs | not separately available | no sub-contracting |
| Data collection costs | not separately available | no sub-contracting |
| Other costs | not separately available | no sub-contracting |
| Total costs | not separately available | no sub-contracting |
| Comments on costs | ||
- The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | 2.15 HC | Average across responding units (data are collected via the questionnaire) |
| Average Time required to complete the questionnaire in hours (T)1 | 7.75 hours (in total for 2.15 HC on average) | Average across responding units (data are collected via the questionnaire) |
| Average hourly cost (in national currency) of a respondent (C) | not available | not available |
| Total cost | not available | not available |
- T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’).
17.1. Data revision - policy
No revisions are foreseen and/ or applied.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
- Provisional data:
Survey to all funding authorities, at both central and regional level. In addition, text analysis is performed by EKT on administrative data retrieved from the central Special Service for the Monitoring Information System (M.I.S.) to identify any additional R&D projects not reported by the responding authorities. (MIS monitors ESPA e.g. all Operational and Regional Programs of the current Partnership Agreement for the Development Framework 2021-2027 as well as the preceding National Strategic Reference Frameworks 2014-2020 &2007-2013. ESPA is the main component of Public Investment Budget.
- Final data:
Survey to all funding authorities, at both central and regional level. In addition, text analysis is performed by EKT on administrative data retrieved from the central Special Service for the Monitoring Information System (M.I.S.) to identify any additional R&D projects not reported by the responding authorities. (MIS monitors ESPA e.g. all Operational and Regional Programs of the current Partnership Agreement for the Development Framework 2021-2027 as well as the preceding National Strategic Reference Frameworks 2014-2020 & 2007-2013. ESPA is the main component of Public Investment Budget.
- General University Funds (GUF):
Application of R&D coefficients on administrative data provided by the Ministry of Education for Universities funding.
Annexes:
GBARD questionnaire for reference year 2023
18.2. Frequency of data collection
See 12.3.3.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | Direct data collection through:
|
Direct data collection through:
|
|
| Stage of data collection | Initial budget appropriations (figures as voted by the legislature for the coming year, including changes introduced in the parliamentary debate) |
Final budget appropriations (figures as voted by the parliament for the coming year, including additional votes during the year). In some exclusive cases (investment budget for the General Secretariat for Research and Innovation), actual expenditures (money paid out during the year) have been taken into consideration and reported. |
|
| Reporting units | Funding/administering institutions(ministries, general secretariats, regions) | Funding/administering institutions(ministries, general secretariats, regions) | |
| Basic variable | Initial budget allocations have been collected for year 2023 | Final budget allocations have been collected for year 2023 | Regarding Final data some of the reporting units had difficulties to retrieve appropriations from their archives and therefore provided outlays. |
| Time of data collection (T+x)1) | Before 2008 it was T+12 2008:T+46 2009: T+34 2010: T+22 2011 onwards: T+10 |
||
| Problems in the translation of budget items | |||
- Time of data collection (T+x): T is assumed to represent the end of reference period. x expresses the number of months after (positive) or before (negative) T when data is collected.
18.3.2. General University Funds (GUF)
Not applicable.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Budgetary items of the Ordinary budget are distributed at institutional level. Budgetary items of the Investment budget are distributed at project level. |
|---|---|
| Criterion of distribution – purpose or content | Purpose in both cases of institutional and project level distribution. |
| Method of identification of primary objectives | Both direct derivation and indirect spin-off approach. |
| Difficulties of distribution | Central Government authorities do not use the NABS classification in their budget’ functions. Therefore, the distribution of GBARD into NABS objectives is not always straightforward. In such cases, mostly reported when distributing the ordinary (institutional) R&D, reporting units are consulting the performing institutions about splitting their R&D budgets into objectives. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Not available. |
| GBARD national questionnaire and explanatory notes in the national language: | EL_Questionnaire_GBARD_2023.xlsx (available in Greek). |
| Other relevant documentation of national methodology in English: | Not available. |
| Other relevant documentation of national methodology in the national language: | The production of GBARD statistics follows the Frascati Manual 2015 concepts, definitions and methodology as well as Eurostat "FM2015 Implementation, Harmonisation EU Guidelines" as updated. A detailed handbook on GBARD collection processes has been developed (internal) and is continuously enriched and improved. National metadata (SIMS v2.0, in Greek) are made available to all users in the dedicated EKT website. |
18.4. Data validation
EKT has followed specific procedures for the validation of the output data:
- A critical aspect of the data validation process involves a detailed comparison of the 2023 GBARD statistics with data from previous years. This comparison is conducted to identify trends, ensure continuity, and detect any significant deviations or anomalies in the reported figures..
- EKT conducted thorough micro data editing for each one questionnaire submitted by a funding authority. This involved reviewing the responses in the current round and comparing them with answers provided in previous rounds. In cases where inconsistencies or discrepancies were detected, EKT established direct communication with the respective funding authorities to address these issues. The micro data were subsequently edited and corrected based on the clarifications and additional information received.
- As part of the data validation process, the GBARD statistics for the reference year 2023 are systematically compared with data obtained from the direct Research and Development (R&D) survey conducted among R&D performers.
- An essential component of the data validation process involves verifying the GBARD statistics through secondary data collected by EKT from a range of external sources. One key source is the Monitoring Information System (M.I.S.) of the Hellenic Ministry of Development and Investments that provides detailed information on ESIF programmes .
18.5. Data compilation
See below.
18.5.1. Imputation - rate
No imputation.
18.5.2. Data compilation methods
See below.
18.5.2.1. Identifying R&D
| Method(s) of separating R&D from non-R&D | Separation of R&D from non-R&D is done by the reporting units following the recommendations of EKT in line with the Frascati Manual recommendations. Regarding the Ordinary budget, which covers mainly institutional funding, a distinction was recommended to be made between the ‘core R&D institutions’ having R&D as their main activity (100% R&D) and the ‘other institutions’ where R&D is part of their activities. Ministries have applied their own coefficients for the ‘other institutions’ mostly after consultation with EKT and with the institutions. EKT has applied coefficients to derive GUF (see 20.5.2) based on the results of time-use survey performed by EKT on HES personnel in 2020 with reference year 2019. In what regards the Investment budget, which covers exclusively programme funding, the identification of R&D projects are made by the reporting units based on the purpose of the funded projects. |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | Coefficients, when applied to distinguish ‘R&D’ from ‘other’ institutes, are applied by the reporting unit mostly after consultation with EKT and institutions. |
| Frequency of updating of coefficients | The coefficients applied by the reporting units can be revised every year if the unit considers this is a necessity. |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | GUF are produced by the application of R&D coefficients on administrative data regarding the funding of higher education institutions as provided by the Ministry of Education. The coefficients used for the distinction between R&D and non-R&D activities based on the results of time-use survey performed by EKT on HES personnel in 2020 with reference year 2019 according to Frascati manual instructions. |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | The coefficients used are based on the results of the time-use survey performed by EKT on HES personnel in 2020 with reference year 2019 according to Frascati manual instructions. |
| Frequency of updating of coefficients | The coefficients are being updated every five years. |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | In line with the Frascati recommendation (FM§ 495), multi-annual projects are allocated to the GBARD of the year(s) in which they are budgeted. Neither in the year(s) of performance nor in the year of authorization. |
|---|---|
| Possibility to classify budgetary items by COFOG functions | This allocation has never been made before. We could possibly consider classifying budgetary items by COFOG (top level) since the reporting units are mainly ministries that reflect government structure and functions. |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Classification into institutional and project funding as proposed by the new Regulation. |
| Method of estimation of future budgets | Not applicable |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comment.
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.
Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
31 October 2025
Not requested.
All Ministries, according to the Register of General Government Entities maintained at the Hellenic Statistical Authority (ELSTAT), and all regional authorities. General Secretariats are covered as separate reporting units in cases of important R&D Secretariats (e.g. General Secretariat for Research and Innovation) or in cases of complex structures in some Ministries (e.g. Ministry of Environment).
See below.
Not requested.
- Calendar year: 2023.
- Fiscal year: 2023.
- Start month: January.
- End month: December.
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
Not requested.
See below.
- Provisional data:
Survey to all funding authorities, at both central and regional level. In addition, text analysis is performed by EKT on administrative data retrieved from the central Special Service for the Monitoring Information System (M.I.S.) to identify any additional R&D projects not reported by the responding authorities. (MIS monitors ESPA e.g. all Operational and Regional Programs of the current Partnership Agreement for the Development Framework 2021-2027 as well as the preceding National Strategic Reference Frameworks 2014-2020 &2007-2013. ESPA is the main component of Public Investment Budget.
- Final data:
Survey to all funding authorities, at both central and regional level. In addition, text analysis is performed by EKT on administrative data retrieved from the central Special Service for the Monitoring Information System (M.I.S.) to identify any additional R&D projects not reported by the responding authorities. (MIS monitors ESPA e.g. all Operational and Regional Programs of the current Partnership Agreement for the Development Framework 2021-2027 as well as the preceding National Strategic Reference Frameworks 2014-2020 & 2007-2013. ESPA is the main component of Public Investment Budget.
- General University Funds (GUF):
Application of R&D coefficients on administrative data provided by the Ministry of Education for Universities funding.
GBARD data are produced and disseminated on a yearly basis.
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.
