Research and development (R&D) (rd)

1.1. Contact organisation

National Documentation Centre (EKT)

1.2. Contact organisation unit

RDI Metrics and Services Department

1.3. Contact name

Restricted from publication

1.4. Contact person function

Restricted from publication

1.5. Contact mail address

56, Zefyrou, GR-17564, P. Faliro

1.6. Contact email address

Restricted from publication

1.7. Contact phone number

Restricted from publication

1.8. Contact fax number

Restricted from publication

29 October 2025

2.1. Metadata last certified

29 October 2025

2.2. Metadata last posted

29 October 2025

2.3. Metadata last update

29 October 2025

3.1. Data description

Statistics on Business enterprise R&D (BERD) measure research and experimental development (R&D) performed in the business enterprise sector, i.e. R&D expenditure and R&D personnel. In line with this objective, the target population for the national R&D survey of the business enterprise sector consists of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. The “enterprise” is defined in Council Regulation (EEC) No 1993/696 of 15 March 1993. The results are related to the population of all R&D performing enterprises classified in Sections A to U of the common statistical classification of economic activities as established by Regulation (EC) No 1893/2006 of the European Parliament and of the Council (NACE Rev.2).

The main concepts and definitions used for the production of R&D statistics are given by OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, 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).

The guiding document to preparing the quality reports is the European Statistical System (ESS)  for Quality and Metadata Reports — re-edition 2021.

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.

3.2. Classification system

• The distribution of principal economic activity and by industry orientation are based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
• The local unit for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
• The distribution by socioeconomic objectives (SEO) are based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
• The fields of research and development are based on Classification and distribution by Fields of Research and Development (FORD).
• The R&D personnel and researchers by educational attainment are classified by the International Standard Classification of Education ISCED 2011
• The BERD by industry orientation is based on the Statistical classification of products by activity (CPA) 

3.3. Coverage - sector

Please see the sub-concepts 3.3.1 to 3.3.5. in the full metadata view.

3.3.1. General coverage

Definition of R&D

R&D comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge.

3.3.2. Sector institutional coverage

Business enterprise sector (BES)	Coverage of BES is in line with Frascati Manual recommendations. The survey covers enterprises known or likely to perform R&D activities in Greece regardless of size or private/public status.
Hospitals and clinics	Private hospitals and clinics are covered.
Inclusion of units that primarily do not belong to BES and the borderline cases.	Not applicable / not included

3.3.3. R&D variable coverage

R&D administration and other support activities	Included, according to FM.
External R&D personnel	Since reference year 2011, the reported total R&D personnel included both internal and external personnel, as required by the FM 2005 and FM 2015. However, no detailed data were available for each category and information on breakdowns (such as gender) was missing. From the reference year 2022 and onwards, EKT has defined five distinct R&D personnel categories based on the most common types of employment in Greek R&D institutional units. Depending on the R&D performance sector, each R&D personnel category can be classified either as internal or as external. Data are separately collected for each category, allowing for an accurate measurement of both the internal and the external personnel, of the R&D performing unit, across various breakdowns (gender, education level, age etc. Detailed guidelines and examples, customized for each R&D performance sector, have been developed and are provided to statistical units to assist them in computing the distribution of their personnel into the different categories.  More specifically, Question B.1 of the BES questionnaire asks respondents to indicate whether they employ individuals (Researchers and/or Other R&D personnel) under the following five employment status categories: B1.1. Internal permanent personnel engaged in R&D activities This category involves all persons with employment contracts of indeterminate duration with the enterprise. B1.2 Internal temporary personnel engaged in R&D activities This category includes individuals who work in R&D activities under the instructions of the enterprise and have a regular interaction with it (regular physical presence or remote work, regular work meetings, etc.). The category refers to fixed-term employment contracts (full-time or part-time) and civil contracts covered by par. 9 of art 39 of Greek law Ν.4387/2016. B1.3 External contributors engaged in R&D activities This category includes individuals who work on R&D under the instructions of the enterprise but without a regular interaction with it. It refers to contracts for the provision of services or the assignment of work to natural persons, experts, etc. This type of contracts mainly concerns independent/self-employed individuals. The social security contributions for their remuneration are paid by the individuals themselves, and not by the institution as in category B1.2. It should be noted that, exclusively in this category, double counting of the Head counts is likely to occur, due to data aggregation across different units (e.g. an expert who works for two or more enterprises).  B1.4. External personnel of Greek HEIs engaged in R&D activities This category includes the (active) Universities’ personnel, such as Professors, Associate Professors, laboratory personnel etc., who work as external experts in R&D activities of the enterprise. It should be noted that, for this category, only FTEs are considered for the calculation of aggregates; HCs are not considered to avoid double counting, since they are reported in HES as Universities’ permanent personnel.  B1.5. Other external personnel engaged in R&D activities This category includes individuals who work on intramural R&D activities under the instructions of the enterprise (with or without a regular interaction with it), and they are: paid by another institution/enterprise, or seconded from another institution, or paid for their R&D activities through external R&D grants
Clinical trials: compliance with the recommendations in FM §2.61.	Clinical trials (phases 1, 2, 3 and occasionally 4) undertaken by pharmaceutical companies are covered.

 

3.3.4. International R&D transactions

Receipts from rest of the world by sector - availability	Funding from abroad is covered by all sectors and is broken down into: European Commission (e.g. Framework and other EU Programmes), Foreign Business enterprises, International Organisations, Other sources. For the BES category ‘foreign business enterprises’ is further broken down into ‘foreign enterprises within the same group’ and ‘other foreign enterprises’.
Payments to rest of the world by sector - availability	Since the 2013 survey, an additional section on extramural expenditure has been added to all questionnaires (BES, GOV, HES, PNP), including information on extramural expenditure to abroad (enterprises and other organisations separately). However, it is to be noted that data are collected only from R&D Performers and do not cover the total national payments to abroad.
Intramural R&D expenditure in foreign-controlled enterprises – coverage	Foreign affiliates in the BE sector that conduct their R&D activities in Greece are covered. The questionnaire includes a question (see more details in 3.4.1, R&D by type of institutions) about whether the reporting unit is member of a group of enterprises as well as the country where the parent company is located and a question about whether the reporting unit is governed by a foreign company.

3.3.5. Extramural R&D expenditures

According to the Frascati Manual, expenditure on extramural R&D (i.e. R&D performed outside the statistical unit enterprise) is not included in intramural R&D performance totals (FM, §4.12).

Data collection on extramural R&D expenditure (Yes/No)	Yes
Method for separating extramural R&D expenditure from intramural R&D expenditure	Since the 2013 survey, an additional section on extramural expenditure has been added to the questionnaire, including information on extramural expenditure to abroad (enterprises and other organisations separately). However, it should be noted that data are collected only from R&D Performers and do not cover the total national payments to abroad.
Difficulties to distinguish intramural from extramural R&D expenditure	No particular difficulties reported.

3.4. Statistical concepts and definitions

Please see the sub-concepts 3.4.1 and 3.4.2 in the full metadata view.

3.4.1. R&D expenditure

Coverage of years	Calendar year.
Source of funds	No divergence from the Frascati Manual recommendations. Since the reference year 2011, in order to address national requirements, government funding has been further categorised to separately indicate R&D funding from European Structural Investment Frameworks, such as the Greek Partnership Agreement ESPA 2014-2020 and ESPA 2021-2027. These subcategories are specified during each survey round.   For the reference year 2023, the BES questionnaire covered the following sources of funding (question C2): Government: Public Investment Budget (National Development Programme, Regions, Municipalities, Special Funds, etc.) Partnership Agreement ESPA 2014-2020 Partnership Agreement ESPA 2021-2027 Recovery and Resilience Fund (RRF) Business enterprises sector: Own funds / Self-financing Greek enterprises within the same group Other private Greek enterprises Other public enterprises Higher Education Sector Private non-profit institutions Rest of the World: European Commission (e.g. Horizon Europe, Horizon 2020, other EU programmes) Foreign enterprises within the same group Other foreign enterprises International Organisations (United Nations, etc.) Other foreign organisations Additional analysis is conducted to offer further breakdowns regarding internal and external funds as well as transfer and exchange funds.  More specifically, the ‘Own funds / Self-financing’ variable is utilized to compute the ‘internal’ component, whereas the remaining source of funds (Government, other statistical units of Business enterprise sector, Higher Education Sector, Private non-profit institutions, and Rest of the World) yield the ‘external component’. In order to determine the breakdown between Exchange and Transfer funds within external R&D funding, survey participants are specifically asked to report whether they received relevant funding for research and development under a contractual agreement which involves providing R&D services or results directly to the funding institution. By identifying these contractual arrangements, it is possible to clearly distinguish Exchange funds from other forms of funding. Once the Exchange funds for each R&D performing unit have been collected, calculating the Transfer component of external funding becomes a straightforward process.
Type of R&D	Since reference year 2011 onwards, breakdowns regarding type of R&D (basic research, applied research and experimental development) are available for the total intramural R&D expenditure.
Type of costs	Since reference year 2011 onwards, the available breakdowns regarding type of costs included: Current expenditure Current - labour cost Current - other expenditure Capital expenditure Capital - land and buildings Capital - instruments and equipment Since reference year 2022 and onwards, additional work has been realised to provide further breakdowns for type of costs according to Eurostat’s guidelines. The following list presents the categories by type of cost: Current costs Labour costs for internal R&D personnel Other current costs Other current costs / External R&D personnel Other current costs / Other costs Capital costs Land and buildings Machinery and equipment Capitalized computer software Other intellectual property products
Economic activity of the unit	R&D resources are allocated to the principal economic activity of the enterprise, according to NACE rev.2.
Economic activity of industry served (for enterprises in ISIC/NACE 72)	R&D resources are allocated to the principal economic activity of the enterprise, according to NACE rev.2
Product field	Covered following the NACE rev.2 classification for R&D products. To calculate the breakdown by product field/ industry served (the CL_NACE2 dimension in the R&D DSD Version 4), respondents are asked to report the main industry served by the outcome of the R&D activities of their enterprise (i.e., the main economic activity where the R&D results of the enterprise will be applied/used).
Defence R&D - method for obtaining data on R&D expenditure	Information about defence R&D is separately available for the GOV sector only (NABS classification). Defence R&D that is covered in other sectors is not separately available.

3.4.2. R&D personnel

See below.

3.4.2.1. R&D personnel – Head Counts (HC)

Coverage of years	Calendar year.
Function	Information about the two occupational categories (researchers and other R&D personnel) is collected. Since 2012 (reference period 2011 onwards) information about all occupations is also available by sex, educational level (and sex) and by region.
Qualification	Qualification is available for the two occupational categories and sex. Data are separately available for ISCED 2011 level 8, ISCED 2011 levels 5, 6 and 7 and ‘other qualification’ in line with the new classification that has been introduced with the Com. Reg. 995/2012.
Age	Since 2012 (reference year 2011 onwards) information about age (and sex) of the researchers has been collected in head counts.
Citizenship	Since 2012 (reference year 2011 onwards) information about citizenship of the researchers has been collected in head counts.

3.4.2.2. R&D personnel – Full Time Equivalent (FTE)

Coverage of years	Calendar year.
Function	Information about the two occupational categories (researchers and other R&D personnel) is collected. Since 2012 (reference period 2011 onwards) information about all occupations is also available by sex, educational level (and sex) and by region (and sex).
Qualification	Qualification is available all qualification categories and sex. Data are separately available for ISCED 2011 level 8, ISCED 2011 levels 5, 6 and 7 and ‘other qualification’ in line with the new classification that has been introduced with the Com. Reg. 995/2012.
Age	Not available / not collected
Citizenship	Not available / not collected

3.4.2.3. FTE calculation

Reporting units made the calculation of FTEs following the questionnaire guidelines that have been drafted in line with FM recommendations (§ 333). Information about how calculations were performed has been provided by respondents in the metadata chapter of the questionnaire. Note that since 2017, FTEs less than 10% are not reported as R&D activities.

The most commonly used approach is that of reports made by the manager(s) of the reporting enterprise, followed by the use of time-sheets. Combination of the two has also been used to some extent. Smaller proportion of enterprises applied different coefficients to different personnel categories (e.g. scientific personnel, technicians, administrations staff, etc.) or used other estimation approaches (e.g. 100% for all staff working in the R&D unit of the enterprise and smaller coefficients for other staff categories).

3.5. Statistical unit

The statistical unit for BERD is the enterprise as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.

 

3.6. Statistical population

Please see the sub-concepts 3.6.1 and 3.6.2 in the full metadata view.

3.6.1. National target population

The objective of the European R&D statistics is to cover all intramural R&D activities. In line with this objective the target population for the national R&D survey of the Business Enterprise Sector should consist of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. In practice however, countries in their R&D surveys might exclude some enterprises for which R&D activities are deemed to be non-existent or negligible, in order to limit the response burden or due to budgetary constraints.

 

	Target population when sample/census survey is used for collection of raw data	Target population when administrative data or pre-compiled statistics are used
Definition of the national target population	No deviations from the FM2015 definition. The national target population consists of all enterprises known or very likely to perform (or fund) R&D on regular or occasional basis. All size classes and all NACE Rev2 classes are covered.	Not Applicable
Estimation of the target population size	EKT has undertaken the responsibility to produce the national R&D statistics in spring 2012. From that point, EKT has established a mechanism for defining and continuously updating the target population based on the relevant sources for assuring high coverage of the business R&D activity. This is a continuous process. The BES R&D directory (which is a subset of the national business register) maintained by EKT is constantly enriched in close collaboration with the National Statistical Authority, which is responsible for the maintenance and constant update of the national business register. In the current phase, the size of the national target population used for the BES R&D 2023 data collection is approximately 4419 enterprises.	Not Applicable
Size cut-off point	No size cut-off point.	Not Applicable
Size classes covered (and if different for some industries/services)	All size classes are covered: 0, 1-9, 10-49, 50-249, 250-499, >=500.	Not Applicable
NACE/ISIC classes covered	All NACE Rev.2 classes covered.	Not Applicable

3.6.2. Frame population – Description

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.

 

Method used to define the frame population	The BES R&D frame population is formed using information from the national statistical business register, maintained by ELSTAT, as well as from other, additional, administrative sources.
Methods and data sources used for identifying a unit as known or supposed R&D performer	The target population includes those enterprises of the national statistical business register that are known to perform or are very likely to perform R&D. To this end, the R&D survey frame for BES is the BES R&D directory (which is a subset of the national statistical business register) maintained by EKT, that includes enterprises having the following characteristics: recorded R&D activity in previous national surveys for R&D, CIS and SBS statistics, participation in European or/and national research projects, recorded R&D expenses in the enterprises’ balance sheets, participation in innovation clusters, tax incentives for R&D activities, beneficiaries of the national development framework programmes (ESPA 2014-2020 & 2021-2027), information from media & other sources about their R&D activities (i.e. advertisements, conferences, websites), etc.
Inclusion of units that primarily do not belong to the frame population	Inclusion of units that primarily do not belong to the frame population is driven by results of the CIS survey that includes a question about R&D performance as well as from updated information for the sources that have been listed above (participation in Horizon Europe and Horizon 2020 - eCORDA database, information from GSRI and MIS (i.e. tax incentives beneficiaries, NSRF beneficiaries), etc.)
Frequency and the methods applied for inclusion R&D performers not known and not supposed to perform R&D	R&D performers not known or supposed to perform R&D are mainly identified through the results of the CIS survey that includes a question about R&D performance as well as from updated information for the sources that have been listed above (participation in Horizon Europe and Horizon 2020 - eCORDA database, information from GSRI and MIS (i.e. tax incentives beneficiaries, NSRF beneficiaries), etc.)
Number of “new”1) R&D enterprises that have been identified and included in the target population	Around 846 ‘new’ enterprises were added in the BES 2023 target population.
Systematic exclusion of units from the process of updating the target population	No systematic exclusions are made.
Estimation of the frame population	The frame population includes all enterprises that are included in the BES R&D directory maintained by EKT, i.e. 4,419 enterprises for reference year 2023 (based on the statistical unit enterprise method).

1)       i.e. enterprises previously not known or not supposed to perform R&D

3.7. Reference area

Not requested. R&D statistics cover national and regional data.

3.8. Coverage - Time

Not requested, see concept 12.3.3. (data availability).

3.9. Base period

The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.

R&D expenditure is published in the following units:  Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).

R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.

• Personnel figures: PS (HC in older DSD versions), FT (FTE in older DSD versions)
• Expenditure figures: XDC (MIO_NAC - Millions of National Currency in older DSD versions)
• Percentage: PC
• Pure number: PN

Reference year 2023 calendar year.

6.1. Institutional Mandate - legal acts and other agreements

See below.

6.1.1. European legislation

Legal acts / agreements:

Since the beginning of 2021, the collection of R&D statistics is based on the 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. Regulation No 2020/1197 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. The transmission of R&D data is mandatory for Member States and EEA countries.

The Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology was in force until the end of 2020.

6.1.2. National legislation

Existence of R&D specific statistical legislation	The production of national R&D statistics is governed by general national statistical legislation.
Are respondents obliged by the national law to provide raw and administrative data:	Yes, the act is covered by Greek Law 3832/2010.

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

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.

At the level of the ESS,  the EU regulation 223/2009 on European statistics defines confidential data as data which allows statistical units (respondents) to be identified, either directly - by formal identifiers such as respondents’ names, addresses, identification numbers - or indirectly - by using a combination of variables or characteristics such as age, gender, education - thereby disclosing individual information (see Article 2(1)(e) of regulation 223/2009). 

At national level:

• 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 a National Authority Agency of the ELSS, 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 (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

Data cells have been protected according to the following rules:

• primary protection: cell numbers =<3
• secondary protection:         
  • in case of 2-classes aggregation (e.g. NACE classes) A = B + C, IF cell B is suppressed THEN either cell C is also suppressed and total A is published or A is suppressed and C is published. Decision between A and C is taken upon the importance and/or users’ interest on what each value represents
  • in case of 3-classes aggregation A = B + C + D, IF one of the B, C or D is suppressed THEN the smallest of the other two is also suppressed while the third component and the total A are published
  • in case of 3-classes aggregation A = B + C + D, IF two of B, C or D, are suppressed and the third one represents less than 3 enterprises, THEN the third one is also suppressed and the total A is published. If the third cell represents more than 3 enterprises THEN the third cell and the total A are both published.

Concerning the Procedures to identify confidential cells in data delivered to Eurostat, no confidential suppression/protection was applied on GOV data.

Concerning the Procedures to identify confidential cells in data delivered to Eurostat, no confidential suppression/protection was applied on HES data.

8.1. Release calendar

Before the beginning of each calendar year, as stated in Principle 6 of EKT’s Dissemination Policy, EKT compiles and publishes on its website its Statistical Work Programme, which includes the planned statistical survey/work for the following year (Annual Statistical Programs ). More specifically, EKT’s Statistical Work Programme presents the list of European and national statistics produced by EKT, refers to the key statistical legislation and sets out EKT’s annual objectives.

Data releases are also preannounced on the dedicated website of EKT for RDI indicators in the form of a “Data Release Calendar”, which specifies the scheduled month for each statistical data release.

8.2. Release calendar access

At Eurostat level this is: Release calendar - Eurostat (europa.eu)

The calendar is accessible by all users at the following link: National Release Calendar

8.3. Release policy - user access

The main source of information for all R&D statistics derived by EKT, accessible to all users, is the dedicated page Main Statistical Data.

EKT provides equal and simultaneous access to its statistical products to all users, as mentioned in the Dissemination Policy it applies (National Statsitics Dissemination Policy ). EKT is fully complying with the relevant principles and regulations of the Statistical Confidentiality Policy. 

At Eurostat level the frequency of R&D data dissemination is yearly for provisional and final data.

10.1. Dissemination format - News release

Please see the sub-concepts 10.1 to 10.5 in the full metadata view.

10.1.1. Availability of the releases

	Availability (Y/N)1)	Links
Regular releases	Y	Each R&D data publication is accompanied with press releases, which are sent to all media in Greece as well as social media (Twitter, Facebook and LinkedIn) and are published in EKT’ s website. For example: Key R&D Indicators - Preliminary Data  (provisional R&D results for 2023) Key R&D Indicators - Final Data (final R&D results for 2023)
Ad-hoc releases	Y	At regular intervals, the organization issues ad-hoc publications, such as reports on regional data, on women's participation in R&D etc: EKT Publications

1) 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)	Links
General publication/article	Y	EKT operates a website dedicated to the dissemination and promotion of its statistical data: EKT R&D Publications , recognizable by its “metrics” logo. This portal serves as the primary access point for EKT’s statistical information, providing unrestricted access to all users. The metrics site is also available via EKT’s main website, which reported approximately 170,000 unique users and roughly 420,000 page views in 2023. R&D data from EKT is available in several formats: Publications (R&D Publications ): These documents present key findings from R&D surveys, along with additional publications that offer in-depth analysis of specific topics. Most of these publications are also accessible in English. Data Brief Reports (R&D Data Release): Concise publications that provide focused analyses of results on specific subjects. EKT Biweekly Electronic Newsletter Articles: Sent to over 55,000 recipients, this newsletter includes articles covering current developments. Social Media Releases: Updates are shared via EKT's accounts on X, Facebook, and LinkedIn, with the follower base exceeding 56,000 in 2023. DATAHub@EKT Interactive Platform: EKT has introduced DATAHub@EKT, an integrated digital infrastructure designed to enhance the dissemination and analysis of its statistical data. This platform facilitates ease of access, comprehension, and application of EKT’s statistical resources, catering to policy makers, researchers, businesses, and other stakeholders. DATAHub@EKT supports the simplification, analysis, and effective utilisation of EKT’s statistical data and indicators.
Specific paper publication (e.g. sectoral provided to enterprises)	Y	Final R&D results for 2023: Key R&D Indicators

1) Y – Yes, N - No

10.3. Dissemination format - online database

Data tables R&D Main Indicators Database 

DATAHub@EKT Interactive Platform

(available only in Greek language).

10.3.1. Data tables - consultations

Not requested.

10.4. Dissemination format - microdata access

As Eurostat receives no R&D micro-data from the reporting countries, users should contact directly the respective national statistical institute (NSI) for access to the micro-data.

10.4.1. Provisions affecting the access

Access rights to micro-data	Microdata access is not provided to users outside EKT. Upon users’ requests, more detailed analyses are produced, compared to the analysis of data requested and transmitted to Eurostat. These analyses are still in aggregated form. Data are protected for confidentiality and aggregations are produced in such way as not to reveal the identity of the enterprises/institutions.
Access cost policy	No charges.
Micro-data anonymisation rules	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. This analysis is still in aggregated form. Data are protected for confidentiality and aggregations are produced in such way as not to reveal the identity of the enterprises/institutions.

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	DATAHub@EKT Interactive Platform Key R&D Indicators
Data prepared for individual ad hoc requests	Y	Aggregate figures	Upon request from NSRF and RIS monitoring authorities, policy makers, expert group meetings, etc.
Other	Y	Aggregate figures	Data presented in the form of short articles: EKT Articles on R&D Data Data presented in conferences organised by EKT and targeting various audiences: Businesses, Researchers, academia, public e.tc. Conferences presentations can be accessed here: EKT Events

1) Y – Yes, N - No

10.6. Documentation on methodology

The production of R&D statistics follows the Frascati Manual 2015 concepts, definitions and methodology as well as Eurostat "FM2015 Implementation, Harmonisation EU Guidelines" as updated.

Detailed handbooks on R&D collection processes have been developed (internal) for all sectors and are continuously enriched and improved.

National metadata (SIMS v2.0, in Greek) are made available to all users in the dedicated EKT website:

National R&D Metadata

10.6.1. Metadata completeness - rate

Not requested.

10.7. Quality management - documentation

Please see the sub-concept 10.7.1 in the full metadata view.

10.7.1. Documentation and users’ requests

Type(s) of data accompanying information available (metadata, graphs, quality reports, etc.)

A glossary is available online to explain all the R&D related concepts to users of these statistics: EKT General Glossary Reference material is available online in the main page of the R&D statistics portal (English version: Main R&D Indicators). This page contains information about the aim of the survey, links to reference documents (Commission Regulation, Frascati Manual, etc, all related publications and datatables and the link for the online R&D questionnaire. Access to the online questionnaire requires username and password, which details are sent to respondents along with the (email) survey invitation. An online helpdesk is also available for authorized users (i.e. respondents). However, the FAQ page is open to the public (Online Helpdesk on R&D Data). National metadata (SIMS v2.0, in Greek) are published in the dedicated EKT  National R&D Metadata Publications with graphs, tables, maps, etc. are made available, containing, additionally, methodological notes about the survey. Finally, a detailed handbook on the production of R&D statistics, coupled with methodological annexes, has been developed and is continuously enriched and improved.

Requests on further clarification, most problematic issues

No further requests for clarifications have been received.

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).

EKT is an Agency of the Hellenic Statistical System (ELSS) and a National Authority, and as such it fully complies to 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 EKT Quality Policy

EKT follows the Generic Statistical Business Process Model (GSBPM) for the production of RDI statistics. Accordingly, the workflow of a typical BES R&D 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 BES R&D statistics, coupled with methodological annexes, has been developed and is continuously enriched and improved.

The quality of the data that EKT collects is controlled through a carefully implemented procedure that guarantees the production of meaningful statistics. In particular, the following practices are in place to enhance data quality:

Designing of the statistical process: Before the collection begins, a thorough investigation of the actions needed to ensure the quality of the data is conducted. This includes a) registry updates, b) questionnaire updates, c) preparation of the relevant infrastructure, d) preparation of a calendar program, and e) the employment of external statistical correspondents to assist the collection.

Data collection – start of the collection period: At the beginning of the collection period, a request to complete the questionnaire is forwarded electronically to all respondents, through an online questionnaire completion tool (LimeSurvey). The request is accompanied by an official letter by EKT’s Director, detailed instructions on how to complete the questionnaire, as well as instructions on how to request guidance regarding the completion process. For this purpose, EKT operates an electronic Help Desk which provides definitions, glossaries, and completion instructions with representative examples for each questionnaire. In addition, respondents can electronically submit questions and comments in the system which are, in turn, monitored by EKT members who are responsible for providing the relevant feedback. It is important to note that LimeSurvey provides statistics that assist the monitoring of the collection process. For administrative data, separate requests are sent via emails to the corresponding government entities.

Data Processing: After the end of the collection period, the micro-data are passed through several, and more sophisticated, validation layers. For the analysis process for R&D statistics, a Data Management System (DMS) is in place, along with peripheral analytics tools such as Python and R libraries. The validation process includes tests with respect to: a) logical rules not provided in the online questionnaire, b) the time-series component, c) ratios (e.g., expenditure over the number of FTEs, etc.), d) cross-testing with data reported from other countries cross-testing with administrative data from external (to EKT) sources, and e) statistical tests (e.g., identification of outliers).

The indicators’ production is automatically implemented via a combination of the EKT’s DMS (Data Management System) and R/Python libraries. Indicators are monitored for their validity through a second layer of tests based on the aggregated data. The validation process includes basic logical tests, time series tests as well as distribution tests (e.g., R&D activities by region). Further, depending on their economic content, statistical outputs are additionally evaluated by EKT members with expertise on the field from other departments. The final SDMX file is tested and automatically corrected for rounding errors, through specific Python libraries.

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.

11.2. Quality management - assessment

The overall quality of the R&D statistical outputs is very good. 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 were met (such as the Hellenic Statistical Authority, the central /regional Monitoring Committees of the national development projects (ESPA projects) etc.).

In  2015, EKT realised detailed case studies in 9 enterprises of various sectors and size classes. 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 enterprises, 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. This procedure was also repeated in 2017, with more interviews with respondents (16 enterprises from various sectors and size classes). Due to the restructuring of the questionnaire in 2017, similar (as in 2015) topics were investigated. Based on the results of the case studies, the structure of the online questionnaires was improved and the guidelines available to respondents through the RDI e-helpdesk operating at EKT were enriched. In addition to the feedback received from the case studies, any comments made by the respondents in the relevant section of the R&D questionnaire, regarding the questionnaire’s structure or the clarity of the guidelines provided and their proposals for improvements thereon, were also taken into consideration.

Overall, the respondents in BES 2023 survey declared a satisfaction rate above 96%.

EKT’s R&D Information System is based on relevant international standards, such as CERIF and SDMX, robust technologies and best practices. The R&D Statistics Information System serves the objectives of: a) R&D micro-data collection, b) Workflow-based statistical analysis, c) Validation of data, d) R&D indicators production, e) Benchmarking analysis with third party datasets, f) Dissemination of R&D statistics.

The desired functionality is achieved by four subsystems, namely the Organisation Registry (OR), the Online Data Collection System (ODCS), the DMS and the SDMX Reference Implementation.

It is important to note that several peripheral Python packages were, additionally, developed to support the DMS, for certain data processing and statistical needs:

• Monitoring: libraries and visualization tools to track the survey response process, monitoring both daily submission rates and the evolution of key R&D indicators.
• Additional layers of data validation:
  • Microdata level: a) cross-validation tests with respect to other sources (administrative data), b) time-series analyses using historical data from the R&D Survey, c) statistical tests (e.g., outlier detection and correlations between variables), d) logical and correctness tests.
  • Aggregate level: a) cross-validation tests with other countries’ data, b) logical and correctness tests (e.g., the total is equal to the sum of the components for each breakdown).
• Imputation and estimation tools: a) outlier corrections, b) strata imputation, c) variable estimation based on historical rates and strata rates (using linear programming techniques).   
• Calculation of statistical indicators: libraries to calculate all statistical indicators, including automated tools that correct for rounding errors (based on linear programming techniques).
• Interactive dashboard reporting: interactive visualization (e.g., bar charts) of the indicators (and their breakdowns) in absolute values and percentages and interactive comparison with data provided by other countries.

Relevance is the degree to which statistics meet current and potential users’ needs. It includes the production of all needed statistics and the extent to which concepts used (definitions, classifications etc.) reflect user needs. The aim is to describe the extent to which the statistics are useful to, and used by, the broadest array of users. For this purpose, statisticians need to compile information, firstly about their users (who they are, how many they are, how important is each one of them), secondly on their needs, and finally to assess how far these needs are met.

12.1. Relevance - User Needs

Please see the sub-concept 12.1.1 in the full metadata view.

12.1.1. Needs at national level

Users’ class1)	Description of users	Users’ needs
1	Eurostat	Production of European statistics / Data dissemination in Eurobase (R&D Main Indicators in Eurostat's Online Database) and in various publications (R&D Eurostat's  Publications).
1	European Commission, other European agencies	Policy making for R&D and Innovation. Especially the R&D intensity indicator is one of the longstanding indicators for R&D in Europe as well as one of the auxiliary indicators of the MIP Scoreboard. Moreover, SDG 9 goal includes RD intensity and RD personnel among its target indicators. EKT provides the national indicators on gender equality.
1	OECD	Policy making for R&D and Innovation Publications and studies (Science, Technology and Industry Scoreboard, STI Outlook, etc.) with country comparisons and presentation of country profiles.
1	Hellenic Statistical Authority	Compilation of National Accounts in line with the revised European System of National and Regional Accounts (ESA 2010) (Commission Reg. 549/2013).
1	Greek Government	R&D Intensity is one of the indicators of the National Reform Programme.
1	General Secretariat for Research and Innovation, Ministry of Education and Religious Affairs, Ministry of Development and Investment, Regional Authorities, Central /regional monitoring Committees of the ESPA national development projects etc.	Policy making and national strategic planning for R&D and Innovation, Monitoring of EU strategic targets (e.g. EU2020), Monitoring and evaluation of ESPA National Development Frameworks (the current “Partnership Agreement for the Development Framework 2021-2027”)
1	National Council for Research and Innovation (N.C.R.I.)	Benchmarking, monitoring country's performance in Science and Technology, monitoring BES/ GOV/HES performance in Research and Technology, evaluation and assessment of research outputs.
2	Business associations, Innovation clusters	Evaluation of the R&D outcome in relation to R&D investments, benchmarking purposes - performance of enterprises in specific NACE sectors, comparison with other countries R&D performance, etc.
3	Media	Country performance in relation to other European countries, publication of main policy R&D indicators.
4	Researchers, students	Analysis, subject-specific studies and/or regional studies, etc.
5	Enterprises	Benchmarking with other enterprises belonging to the same NACE group/class and/or size class.

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. )

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 organised 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 twice a year. Feedback is taken into consideration in the R&D survey design. Moreover, in the dedicated website of metrics.ekt.gr users can also add their feedback and ask questions (Feedback Form on EKT Data). Also this feedback is taken into consideration for future improvements and proposal of additional indicators. 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).  An additional real time source of information used by EKT is social media platforms. EKT monitors regularly comments across platforms like Facebook, Twitter, 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 R&D statistics	The users’ workshops are focused on R&D statistics: the main results are presented and explained with additional information and breakdowns relevant to the national environment. 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	Users are overall very satisfied with the quality of the statistics produced. As a result of the workshops, some additional breakdowns have been added to the R&D questionnaires (for example data collection on HCs / FTEs of R&D personnel working in projects financed by the National Development Framework). At a wider audience, user survey results showed that R&D indicators are used at least once every three months and they are considered very important.

12.3. Completeness

Please see the sub-concept 12.3.2 in the full metadata view.

12.3.1. Data completeness - rate

Mandatory variables: 100%

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.

 

	Reasons for missing cells
Preliminary variables	Very Good
Obligatory data on R&D expenditure	Very Good
Optional data on R&D expenditure	Very Good
Obligatory data on R&D personnel	Very Good
Optional data on R&D personnel	Good - We did not collect these values as it was not possible.
Regional data on R&D expenditure and R&D personnel	Very Good

12.3.3. Data availability

See below.

12.3.3.1. Data availability - R&D Expenditure

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Source of funds	Y	Annual		Additional voluntary break downs (internal / external, transfer exchange)	2020	2020_EL_RDI project Module 2.2
Type of R&D	Y-2003	Biennial	2009	Annual frequency	2020
Type of costs	Y	Biennial	2009	Annual frequency Additional break downs (Other current costs / External R&D personnel, Other current costs / Other costs, Capitalized computer software, Other intellectual property products.		2020_EL_RDI project Module 2.2
Socioeconomic objective	N
Region	Y-2007	Biennial	2009	Annual frequency	2020
FORD	Y-2011, N - 2013, Y-2017	Biennial		Annual frequency	2017, 2020	The FORD breakdown is again included from 2017 onwards.   The FORD breakdown frequency changes to annual after 2020.
Type of institution	Y-2011	Annual		Additional break downs (Independent enterprises and enterprises within the domestic group, Multi-national enterprises, Multi-national enterprises domestically controlled, Multi-national enterprises foreign controlled)	2020	2020_EL_RDI project Module 2.2

1) Y-start year, N – data not available

12.3.3.2. Data availability - R&D Personnel (HC)

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Sex	Y-1999	Biennial	2009	Annual frequency	2011
Function	Y-1993	Biennial	2009	Annual frequency	2011
Qualification	Y-1993	Biennial	2009	Annual frequency	2020
Age	Y-2011	Biennial		Available for researchers only  Annual frequency after 2020	2011, 2020
Citizenship	Y-2011	Biennial		Available for researchers only  Annual frequency after 2020	2011, 2020
Region	Y-2011	Biennial		Annual frequency	2020
FORD	Y-2011, N - 2013, Y-2017, N-2019	Biennial	2019	The FORD breakdown is again included from 2017 onwards.  Annual frequency after 2020	2017, 2020
Type of institution	Y-2011	Biennial		Annual frequency	2020
Economic activity	Y-2011	Biennial		Annual frequency	2020
Product field	N
Employment size class	Y-2011	Biennial		Annual frequency	2020

1) Y-start year, N – data not available

12.3.3.3. Data availability - R&D Personnel (FTE)

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Sex	Y-1999	Biennial	2009	Annual frequency	2011
Function	Y-1993	Biennial	2009	Annual frequency	2011
Qualification	Y-1993	Biennial	2009	Annual frequency	2020
Age	N
Citizenship	N
Region	Y-2011	Biennial		Annual frequency	2020
FORD	Y-2011, N - 2013, Y-2017, N- 2019	Biennial	2019	The FORD breakdown is again included from 2017 onwards.   Annual frequency after 2020	2017, 2020	The FORD breakdown is again included from 2017 onwards.
Type of institution	Y-2011	Biennial		Annual frequency	2020
Economic activity	Y-2011	Biennial		Annual frequency	2020
Product field	N
Employment size class	Y-2003	Biennial		Annual frequency	2020

1) Y-start year, N – data not available

12.3.3.4. Data availability - other

Additional dimension/variable available at national level1)	Availability2)	Frequency of data collection	Breakdown variables	Combinations of breakdown variables	Level of detail
Further breakdown for R&D Expenditure funded by GOV	Y-2011	Annual	a) Funds from the ESPA National Development Framework, b) Public Investment Programme (PIP) other than ESPA, c) Other (Regional Authorities, Municipalities,  etc.)
Further breakdown for R&D Expenditure funded by BES	Y-2011	Annual	a) Own funds, b) Private Greek enterprises, c) State owned enterprises (e.g. Government owned corporations)
R&D expenditure in specific fields of interest	Y-2017	Biennial	Fields of Research and Innovation Strategy for Smart Specialisation (RIS 3) in the following eight fields: Agri-food, Health – medicines, ICT, Energy, Environment and sustainable development, Transport, Materials – construction, Tourism – Culture – Creative industries.
Extramural R&D expenditure outsourced to third parties	Y-2013	Biennial	Type of organization undertaken the R&D activity (private /public, national / abroad): a) Domestic enterprises (excl. banks and state-owned enterprises), b) Domestic banks, c) Domestic enterprises of the public sector, d) Domestic non-profit Institutions, e) Domestic other institutions of the public sector, f) Foreign enterprises, g) Other foreign institutions.

1) This question is optional. It refers to variables and breakdowns NOT asked by the Commission Implementing Regulation (EU) No 2020/1197 (neither as 'optional'), if R&D data for BES are collected for additional breakdowns or/and at more detailed level than requested.

2) Y-start year

12.3.3.5. R&D personnel - Cross-classification by function and qualification (if available in FTE and HC)

Cross-classification	Unit	Frequency
Yes	Both	Every Year

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:

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:

• • 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 errors1)	Non-sampling errors1)				Model-assumption Errors1)	Perceived direction of the error2)
		Coverage errors	Measurement errors	Processing errors	Non- response errors
Total intramural R&D expenditure	4	3	1	-	2		+/-
Total R&D personnel in FTE	4	3	1	-	2		+/-
Researchers in FTE	4	3	1	-	2		+/-

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 (6). If errors of a particular type do not exist, the sign ‘:‘ is used.

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 R&D.

13.1.2. Assessment of the accuracy with regard to the main indicators

Indicators	5 (Very Good)1)	4 (Good)2)	3 (Satisfactory)3)	2 (Poor)4)	1 (Very poor)5)
Total intramural R&D expenditure		X
Total R&D personnel in FTE		X
Researchers in FTE		X

1) 'Very Good' = High level of coverage (annual rate of substitution in the target population lower than 5%). High average rates of response (>80%) in census and sample surveys (BES R&D). Full data consistency with reference to totals and relationships between variables in the dataset sent to Eurostat.  

2) 'Good' = If at least one out of the three criteria described above is not fully met.

3) 'Satisfactory' = If the average rate of response is lower than 60% even by meeting the two remaining criteria.

4) 'Poor' = If the average rate of response is lower than 60% and at least one of the two remaining criteria is not met.

5) 'Very Poor' = If all the three criteria are not met.

13.2. Sampling error

That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.

13.2.1. Sampling error - indicators

See below. 

13.2.1.1. Variance Estimation Method

The standard variance estimator for stratified random sampling was used.

Confidence Intervals for the CVs were based on the bootstrap method at a significance level of 95%.

13.2.1.2. Confidence interval for key variables by NACE

	Industry sector1)	Services sector2)	TOTAL
R&D expenditure	(0.0827, 0.6502)	(0.0874, 0.6651)	(0.0883, 0.5652)
R&D personnel (FTE)	(0.0840, 0.2828)	(0.0736, 0.4983)	(0.0711, 0.4191)

1)        Industry sector (NACE Rev. 2: 01-03, 05-09, 10-33, 35, 36-39, 41-43)

2)        Services sector (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66, 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

13.2.1.3. Confidence interval for key variables by Size Class

	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250- and more employees and self-employed persons	TOTAL
R&D expenditure	(0.0964, 0.1550)	(0.0770, 0.1288)	(0.0984, 0.2037)	(0.1428, 0.7282)	(0.0883, 0.5652)
R&D personnel (FTE)	(0.0786, 0.1706)	(0.0539, 0.1297)	(0.0846, 0.1689)	(0.1141, 0.6659)	(0.0711, 0.4191)

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 (or frame 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: There are only minor divergences between target and frame population, therefore coverage errors are considered negligible.
• Measures taken to reduce their effect: Not applicable

13.3.1.1. Over-coverage - rate

Not requested.

13.3.1.2. Common units - proportion

Not requested.

13.3.1.3. Frame misclassification rate

Misclassification rate measures the percentage of enterprises that changed stratum between the time the frame was last updated and the time the survey was carried out. It is defined as the number of enterprises that changed stratum divided by the number of enterprises which belong to the stratum, according to the frame. The rate can be estimated based on the characteristics of the surveyed enterprises.

 

By size class for the Industry Sector (NACE Rev. 2: 01-03, 05-09, 10-33, 35, 36-39, 41-43)	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number or surveyed enterprises in the stratum (according to frame)	224	869	470	147	1710
Number of surveyed enterprises that have changed stratum (after inspection of their characteristics)	2	5	3	0	10
Misclassification rate	0.89%	0.58%	0.64%	0%	0.58%
By size class for the Services Sector (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number or surveyed enterprises in the stratum (according to frame)	912	1247	395	135	2709
Number of surveyed enterprises that have changed stratum (after inspection of their characteristics)	11	14	4	1	30
Misclassification rate	1.21%	1.12%	1.01%	0.74%	1.11%

13.3.2. Measurement error

Measurement errors occur during data collection and generate bias by recording values different than the true ones (e.g. difficulty to distinguish intramural from extramural R&D Expenditure). The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.

• Description/assessment of measurement errors: The main difficulties that have been reported by respondents concerned a) the separation of R&D from other activities, b) the separation of in-house R&D performance from outsourcing activities, c) the breakdown of labour cost in all types of personnel.
• Measures taken to reduce their effect: The survey questionnaire is accompanied by detailed guidelines on all requested variables and breakdowns. The electronic form includes also a set of validation rules to help respondents in the completion of the questionnaire. In addition, the collection is supported by experienced interviewers and the electronic and telephone helpdesk to respond to enquiries made by respondents.

In cases where measurement errors are detected during the validation phase (e.g. very small R&D performance in relation to the enterprises turnover, inconsistencies between the personnel and expenditure data), enterprises are contacted by experienced staff to clarify misunderstandings, etc.

With reference to the reporting of all possible types of personnel, the questionnaire includes separate tables for all types (internal, full-time, part-time, external, etc.) in order to facilitate the understanding and the reporting of figures. This separate breakdown is also applied in the reporting of the personnel’s labour cost in order to assure the consistency between personnel (FTE) and expenditure figures.

Finally, the introduction of the questionnaire includes a question relevant to R&D activities that can help respondents understand the concept of R&D and may also lead to the identification of R&D activities in their enterprise.

13.3.3. Non response error

Non-response occurs 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.

There are two elements of non-response:

• Unit non-response, which occurs when no data (or so little as to be unusable) are collected on a designated population unit.
• Item non-response, which occurs when data only on some, but not all survey variables are collected on a designated population unit.

The extent of response (and accordingly of non response) is also measured with response rates.

13.3.3.1. Unit non-response - rate

The main interest is to judge if the response from the target population was satisfying by computing the weighted and un-weighted response rate.

Definition:

Eligible are the sample units which indeed belong to the target population. Frame imperfections always leave the possibility that some sampled units may not belong to the target population. Moreover, when there is no contact with sample units and no other way to establish their eligibility they are characterised as ‘unknown eligibility units’

Definition:

• Un-weighted Unit Non- Response Rate = [1 - (Number of units with a response) / (Total number of eligible and unknown eligibility units in the survey)] * 100 
• Weighted Unit Non- Response Rate = [1 - (Total weighted responding units) / (Total weighted number of eligible / unknown eligibility units in the sample)] * 100

13.3.3.1.1. Unit non-response rates by Size Class

	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number of units with a response in the realised sample	130	351	226	152	859
Total number of units in the sample	243	529	281	160	1213
Unit Non-response rate (un-weighted)	46.5 %	33.65 %	19.57 %	5 %	29.18 %
Unit Non-response rate (weighted)	49.01 %	39.31 %	25.99 %	10.86 %	38.9 %

13.3.3.1.2. Unit non-response rates by NACE

	Industry1)	Services2)	TOTAL
Number of units with a response in the realised sample	325	534	859
Total number of units in the sample	448	765	1213
Unit Non-response rate (un-weighted)	27.46 %	30.2 %	29.18%
Unit Non-response rate (weighted)	36.87 %	40.07 %	38.9 %

1)        Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2)        Services (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

13.3.3.1.3. Recalls/Reminders description

• E-mail invitations, accompanied with an official letter, signed by the Director of EKT, were sent to launch the survey. The e-mail invitations explained the purpose and mandatory nature of the survey
• The appropriate links to the online publications of EKT were also provided in the invitations to help respondents to better understand the use of the data they provide. Hard copies of the publications were also sent via post.
• Statistical units were urged to respond via email reminders as well as systematic follow-up by phone and personal emails.

13.3.3.1.4. Unit non-response survey

Conduction of a non-response survey	Non-response analysis is not carried out. For BES, weighting for the sampling part and imputation using previous survey data for known R&D performers were used to impute unit non-response for R&D performers.
Selection of the sample of non-respondents	Not applicable.
Data collection method employed	Not applicable.
Response rate of this type of survey	Not applicable.
The main reasons of non-response identified	large amount of information requested, detail of data requested, length of the questionnaire, difficulty to separate R&D from other non-R&D activities, difficulty to understand which personnel categories to cover

13.3.3.2. Item non-response - rate

Definition:
Un-weighted Item non-Response Rate (%) = [1-(Number of units with a response for the item) / (Total number of eligible , for the item, units in the sample)] * 100

13.3.3.2.1. Un-weighted item non-response rate

	R&D Expenditure	R&D Personnel (FTE)	Researchers (FTE)
Item non-response rate (un-weighted) (%)	0%	0%	0%
Imputation (Y/N)	N	N	N
If imputed, describe method used, mentioning which auxiliary information or stratification is used	Not applicable	Not applicable	Not applicable

13.3.3.3. Magnitude of errors due to non-response

	Magnitude of error (%) due to non-response
Total intramural R&D expenditure	Not available.
Total R&D personnel in FTE	Not available.
Researchers in FTE	Not available.

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.

13.3.4.1. Identification of the main processing errors

Data entry method applied	No data entry errors since the online questionnaire has been used by all respondents.
Estimates of data entry errors	Not applicable.
Variables for which coding was performed	Not applicable.
Estimates of coding errors	Not applicable.
Editing process and method	Validation checks were embedded into the online questionnaire to inform users, in real time, about the occurrence of errors (check totals, sub-totals, totals between questions, values of FTEs vs values of HCs). In addition, extra controls were applied on the submitted data using statistical software to cover other types of errors. Identified errors have been corrected as described below.
Procedure used to correct errors	In cases of errors respondents have been contacted by phone for correction / verification.

13.3.5. Model assumption error

Not requested.

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

Time lag between the end of reference period and the release date of the results:
Indicator: (Release date of provisional/ first results) - (Date of reference for the data)

• End of reference period: December 2023 (T)
• Date of first release of national data: October 2024 (T+10)
• Lag (days): 10 months (300 days)

14.1.2. Time lag - final result

• End of reference period: December 2023 (T).
• Date of first release of national data: June 2025 (T+18).
• Lag (days): 18 months (540 days).

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)	10	18
Actual date of transmission of the data (T+x months)	10	18
Delay (days)	0 – no delay	0 – no delay
Reasoning for delay

15.1. Comparability - geographical

This sub-concept refers to the geographical comparability of data among the 27 Member States and the EFTA and Candidate Countries.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. General issues of comparability

No deviations from FM recommendations and classifications. Therefore, R&D data for Greece are considered to be comparable with international R&D data.

15.1.3. Survey Concepts Issues

The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Implementing Regulation (EU) No 2020/1197 or Frascati manual (FM) and EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.

 

Concept / Issues	Reference to recommendations	Deviation from recommendations	Comments on national definition / Treatment – deviations from recommendations
R&D personnel	FM2015 Chapter 5 (mainly sub-chapter 5.2).	No deviation.
Researcher	FM2015, §5.35-5.39.	No deviation.
Approach to obtaining Headcount (HC) data	FM2015, §5.58-5.61 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Approach to obtaining Full-time equivalence (FTE) data	FM2015, §5.49-5.57 (in combination with Eurostat’s EBS Methodological Manual on R&D Statistics).	No deviation.	Starting from the 2017 survey, we provide detailed guidelines to R&D performing units to exclude personnel with less than 0.1 FTE of R&D activities. We also implement additional validation rules in the online questionnaire to ensure that these persons are not recorded.
Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel	FM2015, §5.25	No deviation.	Total R&D personnel is divided into internal and external personnel. In the questionnaire we implement a more detailed division of R&D personnel into five groups, of which the first two groups (a and b) represent the internal personnel (except for HES, where group d is also considered as internal personnel): a) regular personnel, b) temporary personnel, c) external associates, d) Greek University personnel and e) external associates who are paid by another organisation/enterprise. This detailed breakdown also improves the understanding of respondents.
Intramural R&D expenditure	FM2015 Chapter 4 (mainly sub-chapter 4.2).	No deviation.
Special treatment for NACE 72 enterprises	FM2015, § 7.59.	No deviation.
Statistical unit	FM2015 Chapter 7 (mainly paragraphs 7.3 and 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Target population	FM2015 Chapter 7 (mainly sub-chapter 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Identification of not known R&D performing or supposed to perform R&D enterprises	FM2015 Chapter 7 (mainly sub-chapter 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Sector coverage	FM2015 Chapter 3 (mainly sub-chapter 3.5) in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
NACE coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Enterprise size coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Reference period for the main data	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Reference period for all data	Reg. 2020/1197 : Annex 1, Table 18	No deviation.

15.1.4. Deviations from recommendations

The following table lists a number of key methodological issues, which may affect the international comparability of national R&D statistics. The table gives the references in the Frascati manual (FM), where related recommendations are made. Countries are asked to report on the existence of any deviations from existing recommendations and comment upon.

 

Methodological issues	Reference to recommendations	Deviation from recommendations	Comments on national treatment / treatment deviations from recommendations
Data collection preparation activities	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation.
Data collection method	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation.
Cooperation with respondents	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation.
Follow-up of non-respondents	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation.
Data processing methods	FM2015 Chapter 6 (mainly sub-chapter 6.7).
Treatment of non-response	FM2015 Chapter 6 (mainly sub-chapter 6.7).
Data weighting	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation.
Variance estimation	FM2015 Chapter 6 (mainly sub-chapter 6.9).	Not applicable
Data compilation of final and preliminary data	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Survey type	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation.
Sample design	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation.
Survey questionnaire	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation.

15.2. Comparability - over time

For more information related to the break years and the nature of the breaks, see the following sub-concepts in the full metadata view.

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
R&D personnel (HC)	13 consequent years, starting from 2011.	2011, 1983	2011: A new frame population has been created to cover exhaustively all enterprises that possibly had R&D activities in recent years. Moreover, better measurement has been achieved as a result of the actions taken for adequate comprehension of the R&D concept by the respondents.  1983: The methodology for identifying R&D personnel was brought into line with the recommendations of the Frascati Manual, resulting in changes to personnel cost.
Function			Not available
Qualification			Not available
R&D personnel (FTE)	13 consequent years, starting from 2011.	2011, 1983	2011: A new frame population has been created to cover exhaustively all enterprises that possibly had R&D activities in recent years. Moreover, better measurement has been achieved as a result of the actions taken for adequate comprehension of the R&D concept by the respondents.  1983: The methodology for identifying R&D personnel was brought into line with the recommendations of the Frascati Manual, resulting in changes to personnel cost.
Function			Not available
Qualification			Not available
R&D expenditure	13 consequent years, starting from 2011.	2011	2011: A new frame population has been created to cover exhaustively all enterprises that possibly had R&D activities in recent years. Moreover, better measurement has been achieved as a result of the actions taken for adequate comprehension of the R&D concept by the respondents.
Source of funds			Not available
Type of costs			Not available
Type of R&D			Not available
Other		1991	Some activities included previously under "office machinery and computers" (and hence in the corresponding subtotal "Machinery equipment, instruments and transport equipment") in manufacturing were reclassified in services under "computer and related activities" (and hence in the corresponding subtotal "real estate, renting and business activities") in services.

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

15.2.3. Collection of data in the even years

All data for R&D personnel (HC, FTE) and Expenditure variables are annually collected.

15.3. Coherence - cross domain

This part deals with any national coherence assessments which may have been undertaken. It reports results for variables which are the same or relevant to R&D statistics, from other national surveys and / or administrative sources and explains and comments on their degree of agreement with R&D statistics.  Intramural R & D expenditure (code 230101 in the Commission Implementing Regulation (EU) 2020/1197) and R & D personnel (code 230201) are surveyed also in foreign-controlled EU enterprises statistics (inward FATS).

The Community innovation survey also collects the R&D expenditure of enterprises that form the coverage of the CIS survey.

15.3.1. Coherence - sub annual and annual statistics

Not requested.

15.3.2. Coherence - National Accounts

Based on the MOU between ELSTAT and EKT, R&D microdata are sent annually to ELSTAT for inclusion in the National Accounts.

15.3.3. National Coherence Assessments

Variable name	R&D Statistics - Variable Value	Other national statistics - Variable value	Other national statistics - Source	Difference in values (of R&D statistics)	Explanation of / comments on difference
R&D Expenditure	1,181,776,942.34 euro * Total BES R&D expenditure for common enterprises with CIS	1,298,533,751.05 euro	CIS 2020-2022	116,756,808.71 euro	Differences are due to differences in the reference year, coverage of target population, formulation of the question on R&D expenditure in the CIS questionnaire

15.4. Coherence - internal

Please see the sub-concepts 15.4.1 and 15.4.2 in the full metadata view.

15.4.1. Comparison between preliminary and final data

This part compares key R&D variables as preliminary and final data.

	Total R&D expenditure (in 1000 of national currency)	Total R&D personnel (in FTEs)	Total number of researchers (in FTEs)
Preliminary data (delivered at T+10)	1657949.066	22627.826	17020.388
Final data (delivered T+18)	1657942.066	22627.84	17001.3
Difference (of final data)	7	-0.014	19.088

Comments : No comments.

15.4.2. Consistency between R&D personnel and expenditure

	Average remuneration per year (cost in national currency)	Explanation of consistency issues if any
Consistency between FTEs of internal R&D personnel and R&D labour costs (1)	42197.26	Not applicable
Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2)	58560.37	Not applicable

(1)    Calculate the average remuneration (cost) of individuals belonging to the internal R&D personnel, excluding those who are only formally ‘employees’ (university students, grant holders, etc.).

(2)    Calculate the average remuneration (cost) of individuals belonging to the external R&D personnel (FTEs/other current R&D costs for external R&D personnel).

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)	Cost for the NSI in time use / person / day
Staff costs	Not available	Not available
Data collection costs	Not available	Not available
Other costs	Not available	Not available
Total costs	Not available	Not available

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

Comments on costs :

 

16.2. Components of burden and description of how these estimates were reached

	Value	Computation method
Number of Respondents (R)	2	Information has been retrieved from a relevant question that is included in the questionnaire. Number of Respondents is calculated as the average persons per unit: number of total persons answering divided by total number of units (BES Enterprises).
Average Time required to complete the questionnaire in hours (T)1	8.82	Information has been retrieved from a relevant question that is included in the questionnaire. Average time is calculated as the average amount of hours per enterprise needed to complete the survey, as reported by all responding units.
Average hourly cost (in national currency) of a respondent (C)	Not Available
Total cost	Not Available

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’)

17.1. Data revision - policy

Not requested.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.

18.1.1. Data source – general information

Survey name	BES R&D survey- Personnel engaged and Expenditure spent on R&D Activities.
Type of survey	Combination of census and sample survey to all enterprises known or supposed to perform R&D activities.
Combination of sample survey and census data	Enterprises with high R&D expenditure (more than 500,000 €) are covered by census. All other enterprises in the national target population are covered by random sampling stratified by NACE Rev.2 division (2-digit) and size class.
Combination of dedicated R&D and other survey(s)	Not applicable
Sub-population A (covered by sampling)	4149
Sub-population B (covered by census)	270
Variables the survey contributes to	All R&D variables requested by the Commission Regulation No 2020/1197 and additional variable-dimension combinations.
Survey timetable-most recent implementation	2011 survey: EKT took over the collection and production of R&D and GBAORD statistics in spring 2012. The GBAORD collection preceded the R&D survey. Within this limited time frame, the BES survey started in the beginning of 2013 and ended end of July 2013. 2013 survey: The BES survey started end of April 2014 and finished end of October 2014. During 2015, additional information has been collected, via personalised communication, to verify data for 2014 reference year, when needed. 2015 survey: The BES survey started end of March 2016 and finished in September 2016. 2017 survey: The BES survey started end of May 2018 and finished in September 2018. 2019 survey: The BES survey started mid of June 2020 and ended in September 2020. 2020 survey: The BES survey started in March 2021 and ended in September 2021. 2021 survey: The BES survey started in March 2022 and ended in September 2022. 2023 survey: The BES survey started in April 2024 and ended in September 2024.

18.1.2. Sample/census survey information

Sampling unit	Enterprise
Stratification variables (if any - for sample surveys only)	Combination of census and sample survey to all enterprises known or supposed to perform R&D activities. Stratification variables used were NACE and size.
Stratification variable classes	For the NACE variable the classes were based on the high level Nace rev. 2 of the enterprises. That is, A,B,C,D35, E, F, G, H, I, J, K, L68, M, N,  O84, P85, Q. R. S, T, U99. For the size variable, the classes were the 0-9, 10-49, 50-249, >=250 classes which were constructed based upon the number of employees in the company.
Population size	4419
Planned sample size	1213
Sample selection mechanism (for sample surveys only)	Stratified random sampling
Survey frame	Starting from 2011 survey, EKT has developed a directory of enterprises which are included in the National Business Register maintained by ELSTAT (the Hellenic Statistical Authority) and which additionally, are known or potential R&D performers. The directory is regularly updated. The enterprises included in the BES R&D directory have one or more of the following characteristics: R&D in previous R&D surveys, R&D in CIS surveys, participation in European or/and national research projects, records for R&D expenses in their balance sheet, R&D in the SBS conducted by ELSTAT, participation in innovation clusters, tax incentives for the R&D activities, etc.
Sample design	Stratified random sampling Stratification variables: NACE Rev.2 divisions (High Level Nace) and size classes 0-9, 10-49, 50-249, >=250
Sample size	1213 enterprises = 943 enterprises covered by sample + 270 enterprises covered by census
Survey frame quality	Overall assessment is good and essentially improved compared to previous rounds.
Variables the survey contributes to	All R&D variables requested by the Commission Regulation No 2020/1197

18.1.3. Information on collection of administrative data or of pre-compiled statistics

Source	EKT collects data from the General Secretarial Research and Innovation bureau regarding tax incentives.
Description of collected data / statistics	The data EKT receives are tax incentives on enterprises’ R&D expenditure.
Reference period, in relation to the variables the administrative source contributes to	2023
Variables the administrative source contributes to	R&D expenditure

18.2. Frequency of data collection

See 12.3.3.

18.3. Data collection

Please see the sub-concepts 18.3.1 and 18.3.2 in the full metadata view.

18.3.1. Data collection overview

Realised sample size (per stratum)	859 enterprises responded to the BES R&D 2023 survey.
Mode of data collection	Since 2012 (reference year 2011 onwards), this is an online survey. Every enterprise receives via e-mail its personal log-in details to access the online questionnaire. Enterprises have the possibility to preview the questionnaire before completion. Frequently, EKT assists the enterprises for the completion of the questionnaire via telephone interview. Moreover, face to face meetings are realized to further explain R&D concepts and variables in the questionnaire. Finally, starting from 2017 the collection is supported by well-trained interviewers responsible for the follow up and the assistance to enterprises during completion of the questionnaire.
Incentives used for increasing response	The launch of the survey is realized with an official letter signed by the Director of EKT, which is attached to the e-mail invitations so as to explain the purpose and mandatory nature of the survey. The appropriate links to the online publications are also provided in the invitations to help respondents to better understand the use of the data they provide. Letters informing the enterprises about the survey are also forwarded to the main Greek business associations. The survey is also promoted through specific publications in the website of the National Documentation Centre (EKT Online), in EKT’s electronic newsletter (e-newsletter) that is produced monthly, is circulated to more than 50,000 recipients and is linked to EKT’s social media accounts (Twitter, Facebook and LinkedIn). Also the involvement of experienced interviewers to data collection improved the length of the fieldwork period and the response rate of the survey.
Follow-up of non-respondents	Several email reminders. Intensive follow-up by phone and personal emails, especially to those enterprises that are known to be important R&D performers. Personal assistance by the experienced interviewers.
Replacement of non-respondents (e.g. if proxy interviewing is employed)	No replacement applied.
Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility)	70.82 % (unweighted)
Non-response analysis (if applicable -- also see section 18.5.4 Data compilation - Weighting and Estimation methods)	Non response analysis is not carried out. Weighting for the sampling part. Only in a few cases, imputation using previous data for known R&D performers were used to impute unit non-response for R&D performers.

18.3.2. Questionnaire and other documents

Annex	Name of the file
R&D national questionnaire and explanatory notes in English:	Not available
R&D national questionnaire and explanatory notes in the national language:	BES_questionnaire_2023_EL.pdf
Other relevant documentation of national methodology in English:	Not available
Other relevant documentation of national methodology in the national language:

18.4. Data validation

For the BES, data validation is performed in various phases of the data production process. At first, data are validated in the collection phase during completion of the questionnaire (real-time validation). The online questionnaire used for the BES R&D survey has incorporated numerous validation rules for checking the completeness and the correctness of the values inserted by respondents (e.g. check totals, sub-totals, totals between questions, FTEs larger than respective HCs e.tc.). For any error detected, respondents see a warning message that provides explanation on the correct completion of that question. The validation performed in this phase has significantly improved the quality of the data collected as it reduces measurement errors and facilitates the understanding of the questions and their completion by respondents.

Concerning the response rate, this is constantly monitored during data collection to ensure that all strata of the sample has a satisfactory response rate that would allow high representativeness of all strata in the population and would also minimise the effect of non-response in the weighting process.

After the collection of responses, data are further validated at micro-level for any vague or extreme/outlier values, making also comparisons with previous R&D data for the common enterprises. At this phase, the collected data are also compared with other relevant data sources, such as the most recent CIS data, databases with information on research programmes, enterprises balance sheets etc. This comparison is either made at micro or macro level depending of the level of information provided in the external data source. For any question occurred, respondents are then re-contacted for the needed clarifications or corrections.

18.5. Data compilation

See below.

18.5.1. Imputation - rate

Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition:
Imputation rate (for the variable x) % = (Number of imputed records for the variable x) * 100 / (Total number of possible records for x)

18.5.1.1. Imputation rate by Size class

Size class	R&D Expenditure		R&D personnel (FTE)
	Unweighted	Weighted	Unweighted	Weighted
0-9 employees and self-employed persons (optional)	1.65%	2.69%	1.65%	2.69%
10-49 employees and self-employed persons	2.95%	0.63%	2.65%	0.63%
50-249 employees and self-employed persons	3.97%	1.98%	4.98%	2.23%
250-and more employees and self-employed persons	10.19%	8.94%	11.87%	9.80%
TOTAL	3.73%	1.84%	4.2%	1.92%

18.5.1.2. Imputation rate by NACE

NACE	R&D Expenditure		R&D personnel (FTE)
	Unweighted	Weighted	Unweighted	Weighted
Industry1)	3.6%	1.02%	4.46%	1.17%
Services2)	3.81%	2.31%	4.05%	2.35%
TOTAL	3.73%	1.84%	4.2%	1.92%

 

1)       Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2)       Services (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

18.5.2. Data compilation methods

Data compilation method - Final data	Not applicable – the R&D survey is conducted every year
Data compilation method - Preliminary data	Not applicable – the R&D survey is conducted every year

18.5.3. Measurement issues

Method of derivation of regional data	Questionnaires for all sectors included separate questions for the regional element of R&D Personnel and R&D expenditure. Respondents are asked to distribute total R&D personnel (headcounts and FTE by sex), Researchers (headcounts and FTE by sex) and total intramural expenditure into the 13 Greek regions (NUTS-2 level).
Coefficients used for estimation of the R&D share of more general expenditure items	Not applicable.
Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures	In line with the FM, respondents were asked to exclude VAT and depreciation from R&D expenditures.

18.5.4. Weighting and estimation methods

Weight calculation method	For the sampling part of the survey, enterprises are distributed in strata based on their primary economic activity (NACE Rev.2 division (2-digit)) and their size class. Sampling is performed randomly at each stratum of the sample. The design weight of each stratum is calculated as the inverse of the sampling fraction, i.e. the ratio of total number of enterprises (Nh) in the population divided by the total number of enterprises in the sample (nh) in stratum h. After data collection, these weights are adjusted for non-response by taking into consideration the realised sample in each stratum (i.e. the number of responses). The weights adjusted for non-response are the final weights used for the production of indicators in the sampling part of the survey.
Data source used for deriving population totals (universe description)	The national business register, as maintained and updated by the National Statistical Authority, is used for the derivation of the population totals.
Variables used for weighting	Weighting is applied on the basis of the number of enterprises in each stratum of the sampling population, stratified by NACE Rev.2 division and size class.
Calibration method and the software used	No calibration method is used.
Estimation	The formula applied for the stratified random sampling has been used to calculate estimates and their errors. The assumption has therefore been made that the probability an enterprise performs R&D is equal between responding and non-responding enterprises of the same stratum. For the census part of the BES survey, we have imputed unit non-responses using previous data (where available).

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

No comments.

BES_questionnaire_2023_EL

Statistics on Business enterprise R&D (BERD) measure research and experimental development (R&D) performed in the business enterprise sector, i.e. R&D expenditure and R&D personnel. In line with this objective, the target population for the national R&D survey of the business enterprise sector consists of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. The “enterprise” is defined in Council Regulation (EEC) No 1993/696 of 15 March 1993. The results are related to the population of all R&D performing enterprises classified in Sections A to U of the common statistical classification of economic activities as established by Regulation (EC) No 1893/2006 of the European Parliament and of the Council (NACE Rev.2).

The main concepts and definitions used for the production of R&D statistics are given by OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, 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).

The guiding document to preparing the quality reports is the European Statistical System (ESS)  for Quality and Metadata Reports — re-edition 2021.

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.

29 October 2025

Please see the sub-concepts 3.4.1 and 3.4.2 in the full metadata view.

The statistical unit for BERD is the enterprise as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.

 

Please see the sub-concepts 3.6.1 and 3.6.2 in the full metadata view.

Not requested. R&D statistics cover national and regional data.

Reference year 2023 calendar year.

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:

• • 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.

R&D expenditure is published in the following units:  Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).

R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.

• Personnel figures: PS (HC in older DSD versions), FT (FTE in older DSD versions)
• Expenditure figures: XDC (MIO_NAC - Millions of National Currency in older DSD versions)
• Percentage: PC
• Pure number: PN

See below.

Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.

At Eurostat level the frequency of R&D data dissemination is yearly for provisional and final data.

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.

This sub-concept refers to the geographical comparability of data among the 27 Member States and the EFTA and Candidate Countries.

For more information related to the break years and the nature of the breaks, see the following sub-concepts in the full metadata view.