National Documentation Centre (EKT)

RDI Metrics and Services Department

56, Zefyrou, GR-17564, P. Faliro

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.

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.

See below.

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).

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.

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.

Not requested.

Not requested.

Not requested. 

Not requested.

a) Calendar year: 2021

b) Fiscal year: 2021

    Start month: January

    End month: December

See below.

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.

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, 28.08.2012)
• Regulation on the Statistical Obligations of the agencies of the Hellenic Statistical System (Government Gazette 4083 Β, 20.12.2016)

All available in Greek only: https://metrics.ekt.gr/about

-          Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development

-          EBS Methodological Manual on R&D Statistics

Not requested.

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.

a)       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 (https://metrics.ekt.gr/sites/metrics-ekt/files/pages-pdf/EKT_Policy_StatisticalConfidentiality_el.pdf ).

b)       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. 

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.

The anticipated release dates for GBARD data are included in the annual release calendar published by EKT during the first week of December each year.

The release calendar is available online (https://metrics.ekt.gr/statistics-announcements)   

EKT provides equal and simultaneous access to its statistical products for all users, as outlined in the Dissemination Policy it adheres to (https://metrics.ekt.gr/sites/metrics-ekt/files/pages-pdf/EKT_Policy_Dissemination_el.pdf). 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 page: http://metrics.ekt.gr/

GBARD data are produced and disseminated on a yearly basis.

See below.

1) Y - Yes, N – No

See below.

1) Y – Yes, N - No 

Aggregate figures.

Data tables: https://metrics.ekt.gr/gbard/datatables. Data are currently shown in Greek only.

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

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 (in Greek) are made available to all users in the dedicated EKT website. https://metrics.ekt.gr/sites/metrics-ekt/files/pages-pdf/EKT_SIMS_GBARDstatistics_el.pdf

Not requested.

See below.

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 https://metrics.ekt.gr/policies .

The certification of RDI statistics produced by EKT is currently under way, in the framework of the Hellenic Statistical System. The process is led by the Hellenic Statistical Authority. 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.

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. 

See below.

1)       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 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.)

To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.

See below.

100%. All mandatory variables are covered and transmitted to Eurostat. 

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.

1)  Criteria: Obligatory data (provisional budget and final budget). Only 'Very Good' = 100% and 'Very Poor' <100% apply.

2)  Criteria: Optional data (final budget). 'Very Good' = 100%; 'Good' = >75%;'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.

See below.

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

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

1) Stage: P - provisional, F - final. 

2) Availability of the data: No, data are not available, Y: Yes, data are available + start year.

3) 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

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:

1. 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.

2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:

a) Coverage errors,

b) Measurement errors,

c) Non response errors and

d) Processing errors.

Model assumption errors should be treated under the heading of the respective error they are trying to reduce.

1)  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 ‘-‘.

2)  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.

1) 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.  

2) If at least one out of the three criteria described above would not be fully met.

3) In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.

4) 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.

5) If all the three criteria described above are not met.

Not requested.

Not requested.

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.

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.

a)       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.  

b)      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 2014-2020 as well as the preceding National Strategic Reference Framework 2007-2013. ESPA is the main component of Public Investment Budget.)

0%

Not requested.

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.

a)       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.

b)      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.  

To further reduce any errors and discontinuity in the data reported, the part of the questionnaire asking for final budget data of year X is pre-filled with the information that was provided by the reporting units with reference to provisional budget data for the same year X.

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.  

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.

a) 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.

b) Measures taken to reduce their effect:

 1) constant telephone follow-up, 2) letter 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.

c) Effect of non-response errors on the produced statistics:

 Not applicable

Not requested.

Not requested.

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.

a)       Data processing and editing processes:

 Data have been collected with Excel questionnaire in pre-specified format. Some processing was required in cases where data have been supplied in different formats.

b)      Description of errors:

No processing errors exist. 

c)       Measures taken to reduce their effect:

Not applicable.

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).

Description/assessment: 

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.

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)

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 2021 were released in December 2022, that is T+12).     

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.

Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)

See below.

Not requested.

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.

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.

See below.

See below.

1)       Breaks years are years for which data are not fully comparable to the previous period.

General differences are those outlined in the FM § 522 and 523.

Not requested.

Not requested.

This part compares GBARD statistics from the provisional and final budget for the reference year.

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. 

1)       The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.

1)        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’)

No revisions are foreseen and/ or applied.

Not requested.

Not requested.

a)       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 2014-2020 as well as the preceding National Strategic Reference Framework 2007-2013. ESPA is the main component of Public Investment Budget.)  

b)      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 2014-2020 as well as the preceding National Strategic Reference Framework 2007-2013. ESPA is the main component of Public Investment Budget.) 

c)       General University Funds (GUF):

Application of R&D coefficients on Universities funding administrative data provided by the Ministry of Education.      

See 12.3.3.

See below.

1) 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.

Not applicable.

EKT has followed specific procedures for the validation of the output data. Validation activities include:

•          Comparison of the 2021 data with previous years of GBARD statistics

•          Performing micro data editing. EKT performed validation for each one questionnaire received by a funding authority based on its answers in previous rounds. Where an inconsistency was identified, EKT communicated with the respective funding authorities and the micro data were edited and corrected.

•          Confronting GBARD statistics against other relevant data (direct RD survey for RD performers with the reference year: 2021)

•          Verifying the GBARD statistics based on the secondary data EKT collects from various sources (e.g. Data from the Monitoring Information System (M.I.S.) of the Hellenic Ministry of Development and Investments)  

See below.

No imputation

See below.

Not requested.

Not requested.