1.1. Contact organisation
Statistical Service of Cyprus (CYSTAT)
1.2. Contact organisation unit
Science and Technology Statistics Unit
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
Statistical Service of Cyprus
CY-1444
Nicosia
Cyprus
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
(+357) 22661313
2.1. Metadata last certified
31 October 2025
2.2. Metadata last posted
31 October 2025
2.3. Metadata last update
31 October 2025
3.1. Data description
Statistics on 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
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) |
No deviations in definitions and recommendations of Frascati Manual (§3.51-3.59). |
|---|---|
| Hospitals and clinics | No deviations in definitions and recommendations of Frascati Manual (§3.51-3.59). |
| Inclusion of units that primarily do not belong to BES and the borderline cases. | No |
3.3.3. R&D variable coverage
| R&D administration and other support activities | No deviations from FM §2.122. |
|---|---|
| External R&D personnel | No deviations from FM §5.20-5.24, Table 5.2. External personnel is calculated only in R&D expenditure. R&D personnel is only the internal R&D personnel. |
| Clinical trials: compliance with the recommendations in FM §2.61. | Information for clinical trials is included (FM §2.61) and is calculated/distributed in the sector performing them. If R&D can not been separated, the R&D is distributed to the NACE of the enterprise performing the clinical trial. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Yes. Receipts from Rest of the world by sector (FM §4.108, Table 4.3) |
|---|---|
| Payments to rest of the world by sector - availability | Not applicable. No Payments to Rest of the world by sector (FM §4.133). No extramural R&D is collected. |
| Intramural R&D expenditure in foreign-controlled enterprises – coverage | No |
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) | No |
|---|---|
| Method for separating extramural R&D expenditure from intramural R&D expenditure | Not applicable |
| Difficulties to distinguish intramural from extramural R&D expenditure | Not applicable |
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 FM (FM §4.104-4.108, Table 4.3.) |
| Type of R&D | No divergence from FM (FM section 2.5) |
| Type of costs | No deviations from FM (section 4.2). No more detailed breakdown of costs than in the FM exist. |
| Economic activity of the unit | Statistics by principal economic activity |
| Economic activity of industry served (for enterprises in ISIC/NACE 72) | R&D survey |
| Product field | Not collecting data by product field. |
| Defence R&D - method for obtaining data on R&D expenditure | R&D survey |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | Total number of persons employed during the calendar year. |
|---|---|
| Function | No difficulties encountered with classifying personnel by Occupation (researcher, technicians, other support staff). |
| Qualification | No difficulties encountered with classifying personnel by qualification. |
| Age | Not applicable. No data for age is collected in Bussiness sector. |
| Citizenship | Not applicable. No data for citizenship is collected in Bussiness sector. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | Total number of persons employed during the calendar year. |
|---|---|
| Function | No difficulties encountered with classifying personnel by Occupation (researcher, technicians, other support staff). |
| Qualification | No difficulties encountered with classifying personnel by qualification. |
| Age | Not applicable. No data for age is collected in Bussiness sector. |
| Citizenship | Not applicable. No data for citizenship is collected in Bussiness sector. |
3.4.2.3. FTE calculation
The Full-time Equivalent (F.T.E.) expresses the total time devoted to research by a person during one year. One F.T.E. may be thought of as one person-year which corresponds to one person working full-time on R&D during one year. Thus, a person who normally spends 30% of his time on R&D and the remaining 70% on other activities should be considered as 30/100 = 0,3 person-years. Three persons who spend 30%, 50% and 80% of their time on R&D activities correspond to 0,3 + 0,5 + 0,8 = 1,6 person-years.
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, if there are deviations please explain.
For Cyprys, the statistical unit and the reporting unit are the same and is the enterprise.
No deviation from the mandatory use of the 'enterprise' as statistical unit for business R&D statistics exist.
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 | The FM2015 definition of target population is (§7.70): "all businesses located in a given territory known or very likely to perform (or fund) R&D with reference to a single period of time." No deviations exist. | The FM2015 definition of target population is (§7.70): "all businesses located in a given territory known or very likely to perform (or fund) R&D with reference to a single period of time." No deviations exist. |
| Estimation of the target population size | Not available | Not available |
| Size cut-off point | No deviation from the mandatory size cut-off point given in the Regulation. | No deviation from the mandatory size cut-off point given in the Regulation. |
| Size classes covered (and if different for some industries/services) | No deviation from the mandatory size-classes break-down given in the Regulation. | No deviation from the mandatory size-classes break-down given in the Regulation |
| NACE/ISIC classes covered | No deviation from the mandatory NACE break-down given in the Regulation. | No deviation from the mandatory NACE break-down given in the Regulation. |
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 | There is full coverage of all enterprises which are known or potential R&D performers, based on a register of all possible R&D performing enterprises, following the Frascati Manual recommendations. This register is regularly updated. |
|---|---|
| Methods and data sources used for identifying a unit as known or supposed R&D performer | The recommendations of the Frascati Manual 2015 are followed in order to identify a unit as an established or a potential R&D performer. Information on enterprises active in areas which, on the basis of the findings of the previous corresponding surveys, the nature of their work and the experience of other countries, are the most probable to involve an element of research, is taken into account. An important source of information is the Research & Innovation Foundation for persons/bodies/enterprises applying for funding from the Programmes for the Financing of Research Projects. Reports in the press and articles in industrial journals and research compendia are additional sources used to identify potential R&D performing enterprises . The CORDIS database, as well as the web sites of various funding agencies and programmes, is also frequently consulted in order to identify any possible research activities. |
| Inclusion of units that primarily do not belong to the frame population | No inclusion. |
| Frequency and the methods applied for inclusion R&D performers not known and not supposed to perform R&D | No (cost reasons) |
| Number of “new”1) R&D enterprises that have been identified and included in the target population | No such estimation can be made. |
| Systematic exclusion of units from the process of updating the target population | No |
| Estimation of the frame population | The register of all possible R&D performers included 300 entries. |
1) i.e. enterprises previously not known or not supposed to perform R&D
3.7. Reference area
Not requested.
Government controlled areas of the Republic of Cyprus.
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.
The units of measures used for the data set disseminated are Euro, %, number of persons.
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.
Calendar year 2023
6.1. Institutional Mandate - legal acts and other agreements
See below.
Article 3 of the national Official Statistics Law, No. 25(I) of 2021 defines the functions of the Statistical Service of Cyprus regarding the production and dissemination of official statistics. Moreover, Article 13, explicitly stipulates the mandate for data collection and introduces a mandatory response to statistical enquiries by stipulating the obligation of respondents to reply to surveys and provide the data required. This relates not only to national but also to European statistics which, by virtue of Article 8 of the said Law, are incorporated in the annual and multiannual programmes of work without any further procedure.
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 | Official Statistics Law No. 25(I) of 2021: Official Statistics Law |
|---|---|
| Are respondents obliged by the national law to provide raw and administrative data: | Yes and according by the provitions of the above Law. |
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: Yes under the provisions of the Official Statistics Law No. 25(I) of 2021.
- Confidentiality commitments of survey staff: Yes under the provisions of the Official Statistics Law No. 25(I) of 2021.
Official statistics are released in accordance to all confidentiality provisions of the following:
- National Official Statistics Law No. 25(I) of 2021 (especially Article 16 on statistical confidentiality).
- Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality).
- European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
- Guidelines for the Protection of Confidential Data.
- Official Statistics Law No. 25(I) of 2021: Official Statistics Law
- Regulation (EC) No 223/2009 on European statistics (consolidated text)
- European Statistics Code of Practice
- Guidelines for the Protection of Confidential Data
7.2. Confidentiality - data treatment
The survey is carried out in accordance to the Official Statistics Law No. 25(I) of 2021. The Statistical Service is bound, under the provisions of the Statistics Law, to treat all information collected as confidential. All collected information and data are used solely for statistical purposes. Data on individual enterprise cannot be published or disclosed to either public bodies or private individuals.
The treatment of confidential data is regulated by Guidelines for the Protection of Confidential Data.
8.1. Release calendar
Notifications about the dissemination of statistics are published in the release calendar, which is available on CYSTAT’s web portal. The annual release calendar, announced during the 4th quarter of the year, includes provisional dates of publication for the following year, which are finalized the week before publication.
8.2. Release calendar access
- Link to CYSTAT’s release calendar: National Release Calendar
- At Eurostat level this is: Release calendar - Eurostat (europa.eu)
8.3. Release policy - user access
According to the Dissemination and Pricing Policy of the Statistical Service of Cyprus (section 2.3) CYSTAT΄s main channel for dissemination of statistics is the web portal, which offers the same conditions to everyone and is updated at the same time every working day (12:00 noon). No privileged pre-released access is granted.
In addition to the annual release calendar, users are informed of the various statistical releases through the “Alert” service provided by CYSTAT.
Dissemination and Pricing Policy of the Statistical Service of Cyprus: National Dissemination 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 | A press release is issued. |
| Ad-hoc releases | N |
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 (paper, online) |
Y | The results of the national R&D surveys are published in the annual report “Research and Development Statistics”. The key results are also published in our statistical yearbook entitled “Statistical Abstract”. Both publications can be purchased in paper form or can be downloaded for free from our website. |
| Specific paper publication (e.g. sectoral provided to enterprises) | N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Not available.
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 | There is no Micro-data access to outside users.
Statistical micro-data from CYSTAT’s surveys are accessible for research purposes only and under strict provisions as described below:
Under the provisions of the Official Statistics Law, CYSTAT may release microdata for the sole use of scientific research. Applicants have to submit the request form "APPLICATION FOR DATA FOR RESEARCH PURPOSES" giving thorough information on the project for which micro-data are needed.
The application is evaluated by CYSTAT’s Confidentiality Committee and if the application is approved, a charge is fixed according to the volume and time consumed for preparation of the data. Micro-data may then be released after an anonymization process which ensures no direct identification of the statistical units but, at the same time, ensures usability of the data. The link for the application is attached below.
Link to the application for access to microdata on CYSTAT's website: |
|---|---|
| Access cost policy | See above |
| Micro-data anonymisation rules | See above |
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 | The results of the national R&D surveys are published in the annual report “Research and Development Statistics”. The publication can be downloaded free of charge from the web site of the Statistical Service of Cyprus (Statistical Service of Cyprus) in PDF format. The main R&D indicators are also included, as MS Excel files, in the “Key Figures” section of the web site, under the statistical theme “Science and Technology”. Finally, the key results are also published in our statistical yearbook entitled “Statistical Abstract” which can be downloaded from the web site. | |
| Data prepared for individual ad hoc requests | Y | Further information to interested users is given upon request. | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
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.) | Users can download free of charge from the web site of the Statistical Service of Cyprus the annual publication “Research and Development Statistics”. This contains a textual description of latest developments in R&D activities, a number of graphical displays and numerous tables, including a comparison with corresponding international statistics. It also contains a comprehensive methodological note, giving information on the national R&D survey and its scope, concepts and definitions, as well as a copy of the questionnaire used. Every time that new data is disseminated at the national level, a press release is issued. |
|---|---|
| Requests on further clarification, most problematic issues | For any further information, users can make a request to the Statistical Service (by phone, mail, e-mail or via the enquiries facility on the web site). |
11.1. Quality assurance
At Eurostat level, the common quality framework of the European Statistical System (ESS) is composed of the European Statistics Code of Practice, the Quality Assurance Framework of the ESS, and the general quality management principles (such as continuous interaction with users, continuous improvement, integration, and harmonisation).
The quality of statistics in CYSTAT is managed in the framework of the European Statistics Code of Practice which sets the standards for developing, producing and disseminating European Statistics as well as the ESS Quality Assurance Framework (QAF). CYSTAT endorses the Quality Declaration of the European Statistical System. In addition, CYSTAT is guided by the requirements provided for in Article 11 of the Official Statistics Law No. 25(I) of 2021 as well as Article 12 of Regulation (EC) No 223/2009 on European statistics, which sets out the quality criteria to be applied in the development, production and dissemination of European statistics.
Additionally, CYSTAT has issued "Quality Guidelines for Statistical Processes", aiming to provide guidance on statistical production processes. The two pillars on which the guidelines are based, are the European Statistics Code of Practice which provides the basic principles for the production of high-quality European statistics and the GSBPM which defines and describes the main phases of the statistical production process. This document provides a description of CYSTAT’s Quality Policy, of the phases of statistical production and specific guidelines to be followed in every phase of statistical production. It is available internally to CYSTAT staff and Other National Authorities (ONAs).
- European Statistics Code of Practice
- ESS Quality Assurance Framework (QAF)
- Quality Declaration of the European Statistical System
- Official Statistics Law No. 25(I) of 2021
- Regulation (EC) No 223/2009 on European statistics (consolidated text)
11.2. Quality management - assessment
The R&D data on the BES sector in Cyprus are assessed as being of high quality. The definitions, concepts and methodology used are in compliance with the requirements of Eurostat and follow the guidelines of the Frascati Manual 2015. The national R&D survey is a well established survey which yields the maximum of the information required on an annual basis and with a comparatively short time lag from the end of the reference period. Although the register of all possible R&D performing enterprises is regularly updated, it is likely that there is an under coverage of R&D in small enterprises or in the services sectors. However, the effect on total business enterprise R&D is not significant, as all the important R&D performers are included in any case.
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 | European institutions: Council, Commission (Eurostat, DG Research), European Parliament. | Formulating the needs and assessing the implementation of Community research policies, especially with regard to the EU goals in R&D, as set by the Lisbon summit strategy. |
| 1 | International organisations: OECD, UNESCO etc. | Economic analysis and monitoring. |
| 1 | National: Ministry of Finance, Ministry of Energy, Commerce and Industry, Deputy Ministry of Research, Innovation and Digital Strategy, Directorate General for European Programmes, Coordination and Development, Research & Innovation Foundation. | Assessing the implementation of the national reform programme for the Lisbon strategy, strategic programming, economic analysis and monitoring. |
| 2 | Social actors: various employers’ associations, trade unions and lobby groups. | Economic analysis and monitoring, interested both in figures and comments. |
| 3 | Media: Economic newspapers, TV channels. | Interested in figures, comments and analyses. |
| 4 | Researchers and students: Higher education institutions, researchers, students and private individuals. | Interested in figures, comments and analyses. |
| 5 | Enterprises or businesses: Business enterprises, consultancy offices. | Market analysis, marketing strategy, offering consultancy services. |
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 | Since 2008 (with the exception of 2010, 2013 and 2020) CYSTAT carries out an annual online “Users Satisfaction Survey”. The results of the surveys are available on CYSTAT’s web portal at the link attached below. Overall, there is a high level of satisfaction of the users of statistical data published by CYSTAT. Results of CYSTAT’s User Satisfaction Surveys: Cystat User Satisfaction Survey |
|---|---|
| User satisfaction survey specific for R&D statistics | In the latest national user satisfaction survey, R&D statistics were listed down explicitly as one of the main statistical fields to be commented on. |
| Short description of the feedback received | However, the number of questionnaires with relevant comments was too low to allow for any concrete conclusions to be drawn. No specific problems were reported. There were no findings specific to the BES sector. |
12.3. Completeness
Please see the sub-concept 12.3.2 in the full metadata view.
12.3.1. Data completeness - rate
See below.
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 | No missing cells |
| Obligatory data on R&D expenditure | No missing cells |
| Optional data on R&D expenditure | No missing cells |
| Obligatory data on R&D personnel | No missing cells |
| Optional data on R&D personnel | No missing cells |
| Regional data on R&D expenditure and R&D personnel | No missing cells |
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-1998 | Annual | No gap years | No changes | ||
| Type of R&D | Y-1998 | Annual | No gap years | No changes | ||
| Type of costs | Y-1998 | Annual | No gap years | No changes | ||
| Socioeconomic objective | N – data not available | |||||
| Region | Not apllicable. Cyprus is one region | |||||
| FORD | Y-1998 | Annual | No gap years | No changes | ||
| Type of institution | Y-1998 | Annual | No gap years | No changes |
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-1998 | Annual | No gap years | No changes | ||
| Function | Y-1998 | Annual | No gap years | No changes | ||
| Qualification | Y-1998 | Annual | No gap years | No changes | ||
| Age | N – data not available | |||||
| Citizenship | N – data not available | |||||
| Region | Not apllicable. Cyprus is one region | |||||
| FORD | Y-1998 | Annual | No gap years | No changes | ||
| Type of institution | Y-1998 | Annual | No gap years | No changes | ||
| Economic activity | Y-1998 | Annual | No gap years | No changes | ||
| Product field | N – data not available | |||||
| Employment size class | Y-1998 | Annual | No gap years | No changes |
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-2001 | Annual | No gap years | No changes | ||
| Function | Y-1998 | Annual | No gap years | No changes | ||
| Qualification | Y-1998 | Annual | No gap years | No changes | ||
| Age | N – data not available | |||||
| Citizenship | N – data not available | |||||
| Region | Not apllicable. Cyprus is one region | |||||
| FORD | Y-1998 | Annual | No gap years | No changes | ||
| Type of institution | Y-1998 | Annual | No gap years | No changes | ||
| Economic activity | Y-1998 | Annual | No gap years | No changes | ||
| Product field | N – data not available | |||||
| Employment size class | Y-1998 | Annual | No gap years | No changes |
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 |
|---|---|---|---|---|---|
| Not applicable. | Not applicable. | Not applicable. | Not applicable. | Not applicable. | Not applicable. |
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 |
|---|---|---|
| Not applicable. | Not applicable. | Not applicable. |
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
13.1.1. Accuracy - Overall by 'Types of Error'
| Sampling 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 | - | - | - | - | - | - | |
| Total R&D personnel in FTE | - | - | - | - | - | - | |
| Researchers in FTE | - | - | - | - | - | - | |
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.
The main indicator used to measure sampling errors is the coefficient of variation (CV).
Definition of coefficient of variation:
CV= (Square root of the estimate of the sampling variance) / (Estimated value)
Not applicable. No sampling is used.
13.2.1.1. Variance Estimation Method
Not applicable.
13.2.1.2. Confidence interval for key variables by NACE
| Industry sector1) | Services sector2) | TOTAL | |
|---|---|---|---|
| R&D expenditure | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. |
| R&D personnel (FTE) | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. |
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 | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. |
| R&D personnel (FTE) | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. | Not applicable, since no sample survey is conducted. |
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: Not applicable.
- 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) | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Number of surveyed enterprises that have changed stratum (after inspection of their characteristics) | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Misclassification rate | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| 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) | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Number of surveyed enterprises that have changed stratum (after inspection of their characteristics) | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Misclassification rate | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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: No measurement errors exist.
- Measures taken to reduce their effect: The data collection and processing phase is managed by a highly skilled person who is working in the field for more than 24 years. Information providers, in most cases, stay the same for years and, consequently, are very well aware of the questionnaire and the relevant concepts and definitions. Regular contacts by telephone or e-mail and, in some cases, personal interviews, are also made to provide clarifications and assistance and to check and correct possible inconsistencies and oversights in the questionnaires received. The data reported are also checked against administrative records kept by the Research & Innovation Foundation, which is the national institute for the promotion of scientific and technological research in Cyprus. The CORDIS database, as well as the web sites of various funding agencies and programmes, is also frequently consulted in order to identify any possible research activities that the information providers may have failed to report.
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 | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Total number of units in the sample | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
| Unit Non-response rate (un-weighted) | 0% | 0% | 0% | 0% | 0% |
| Unit Non-response rate (weighted) | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
13.3.3.1.2. Unit non-response rates by NACE
| Industry1) | Services2) | TOTAL | |
|---|---|---|---|
| Number of units with a response in the realised sample | Not applicable | Not applicable | Not applicable |
| Total number of units in the sample | Not applicable | Not applicable | Not applicable |
| Unit Non-response rate (un-weighted) | 0% | 0% | 0% |
| Unit Non-response rate (weighted) | Not applicable | Not applicable | Not applicable |
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
There is no unit non-response.
13.3.3.1.4. Unit non-response survey
| Conduction of a non-response survey | There was no need to carry out a non-response survey. |
|---|---|
| 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 | Not applicable |
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 |
13.3.3.3. Magnitude of errors due to non-response
| Magnitude of error (%) due to non-response | |
|---|---|
| Total intramural R&D expenditure | Not applicable |
| Total R&D personnel in FTE | Not applicable |
| Researchers in FTE | Not applicable |
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 | Data entry is done in MS Excel spreadsheets. |
|---|---|
| Estimates of data entry errors | No processing errors exist. |
| Variables for which coding was performed | All variables included on the questionnaire are being coded. |
| Estimates of coding errors | No coding errors exist. |
| Editing process and method | The MS Excel files used incorporate various cross-checking and validation capabilities. Controls and checks for logical inconsistencies are used to eliminate any remaining errors. Comparisons are also made with the responses provided by the same unit in the previous years’ surveys. Errors detected are corrected by further contacting the information providers. |
| Procedure used to correct errors | Errors detected are corrected by further contacting the information providers. |
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: No release of provisional national data.
- Date of first release of national data: No release of provisional national data.
- Lag (days): No release of provisional national data.
14.1.2. Time lag - final result
- End of reference period: 2023 (T)
- Date of first release of national data: T+22 months
- Lag (days): 660 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 | 19 |
| Delay (days) | 0 | 14 |
| Reasoning for delay | Other urgent national needs |
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 comments.
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 | Total number of persons engaged in R&D during the (calendar) year. |
| 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 | Measurement in personyears is adopted. |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | No deviation | |
| 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 | There are no enterprises in NACE 72. |
| 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 | Production of annual data for all variables. |
| Enterprise size coverage and breakdown | Reg. 2020/1197 : Annex 1, Table 18 | No deviation | Production of annual data for all variables. |
| Reference period for the main data | Reg. 2020/1197 : Annex 1, Table 18 | No deviation | Production of annual data for all variables. |
| Reference period for all data | Reg. 2020/1197 : Annex 1, Table 18 | No deviation | Production of annual data for all variables. |
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 | See present report |
| Data collection method | FM2015 Chapter 7 (mainly sub-chapter 7.7). | No deviation | See present report |
| Cooperation with respondents | FM2015 Chapter 7 (mainly sub-chapter 7.7). | No deviation | See present report |
| Follow-up of non-respondents | FM2015 Chapter 7 (mainly sub-chapter 7.7). | There is no unit non-response | |
| Data processing methods | FM2015 Chapter 6 (mainly sub-chapter 6.7). | No deviation | See present report |
| Treatment of non-response | FM2015 Chapter 6 (mainly sub-chapter 6.7). | There is no unit non-response | |
| Data weighting | FM2015 Chapter 7 (mainly sub-chapter 7.7). | No weighting is used | |
| Variance estimation | FM2015 Chapter 6 (mainly sub-chapter 6.9). | Not applicable. No sampling is used. | |
| Data compilation of final and preliminary data | Reg. 2020/1197 : Annex 1, Table 18 | No deviation | See present report |
| Survey type | FM2015 Chapter 6 (mainly sub-chapter 6.4). | No deviation | See present report |
| Sample design | FM2015 Chapter 6 (mainly sub-chapter 6.4). | Not applicable. No sampling is used. | |
| Survey questionnaire | FM2015 Chapter 6 (mainly sub-chapter 6.4). | No deviation | See present report |
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) | 1998-2023 | No break years | |
| Function | 1998-2023 | No break years | |
| Qualification | 1998-2023 | No break years | |
| R&D personnel (FTE) | 1998-2023 | No break years | |
| Function | 1998-2023 | No break years | |
| Qualification | 1998-2023 | No break years | |
| R&D expenditure | 1998-2023 | No break years | |
| Source of funds | 1998-2023 | No break years | |
| Type of costs | 1998-2023 | No break years | |
| Type of R&D | 1998-2023 | No break years | |
| Other | 1998-2023 | No break years |
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 are produced in the same way in the odd and even years.
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
R&D statistics are fully reconcilable with 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 |
|---|---|---|---|---|---|
| Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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) | 88500 | 810.0 | 540.0 |
| Final data (delivered T+18) | 89601 | 822.9 | 557.6 |
| Difference (of final data) | 1101 | 12.9 | 17.6 |
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) | Not available | |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | Not available |
(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: No comments
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | 300 | Count the number of enterprises from which request R&D data. |
| Average Time required to complete the questionnaire in hours (T)1 | Not available | Not available |
| Average hourly cost (in national currency) of a respondent (C) | Not available | Not available |
| Total cost | Not available | 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.
A data revision policy is in place at CYSTAT. It is published on CYSTAT’s web portal, at the following link: Cystat Revision Policy
CYSTAT also publishes a list of scheduled revisions (regular or major revisions), also published on its web portal, at the following link: Cystat List of Sheduled Revisions
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: Survey on Scientific research and experimental development.
- Type of survey: No sampling is used. There is full coverage of all enterprises known or supposed to perform R&D, based on a register of all possible R&D performing enterprises.The national R&D survey is incorporated in the regular programme of work of the Statistical Service of Cyprus and it can be considered as a census.
- Combination of sample survey and census data: Not applicable. No sampling is used.
- Sub-population A (covered by sampling): Not applicable.
- Sub-population B (covered by census): Not applicable.
- Variables the survey contributes to: Not applicable.
18.1.2. Sample/census survey information
| Sampling unit | Not applicable. No sampling is used. |
|---|---|
| Stratification variables (if any - for sample surveys only) | Not applicable. No sampling is used. |
| Stratification variable classes | Not applicable. No sampling is used. |
| Population size | Not applicable. No sampling is used. |
| Planned sample size | Not applicable. No sampling is used. |
| Sample selection mechanism (for sample surveys only) | Not applicable. No sampling is used. |
| Survey frame | Not applicable. No sampling is used. |
| Sample design | Not applicable. No sampling is used. |
| Sample size | Not applicable. No sampling is used. |
| Survey frame quality | Not applicable. No sampling is used. |
| Variables the survey contributes to | Not applicable. No sampling is used. |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | Legal entities and entrerprises in Business sector according to FM definitions. |
|---|---|
| Description of collected data / statistics | Collected information: (a) R&D personnel, both in head counts and full-time equivalent, broken down by occupation, sex, level of formal qualification, field of science and technology, and (b) R&D expenditure, broken down by type of costs, field of science and technology, type of research and source of funds. Collection method: A questionnaire is sent out to all potential information providers, asking them to complete it and return it by mail. A letter indicating that no R&D activity was performed during the year under review is expected from the non-R&D performers as well. Regular contacts by telephone or e-mail and, in some cases, personal interviews, are also used to provide clarifications and assistance and to check and correct possible inconsistencies and oversights in the questionnaires received. The data reported are also checked against administrative records kept by the Research & Innovation Foundation, which is the national institute for the promotion of scientific and technological research in Cyprus. The CORDIS database, as well as the web sites of various funding agencies and programmes, are also frequently consulted in order to identify any possible research activities that the information providers may have failed to report. |
| Reference period, in relation to the variables the administrative source contributes to | All parameters collected are reported on an annual basis. |
| Variables the administrative source contributes to | All collected parameters. |
18.2. Frequency of data collection
See 12.3.3.
In accordance to Commission Implementing Regulation (EU) No 2020/1197, the reference periods to be covered are uneven years, starting with 2021 reference year. For a number of variables and for preliminary data the reference periods to be respected are annual.
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) | Not applicable. No sampling is used. |
|---|---|
| Mode of data collection | A questionnaire is sent out to all possible R&D performing enterprises, asking them to complete it and return it by mail. A letter indicating that no R&D activity was performed during the year under review is expected from the non-R&D performers as well. Regular contacts by telephone or email and, in some cases, personal interviews, are also used to provide clarifications and assistance and to check and correct possible inconsistencies and oversights in the questionnaires received. The data reported are also checked against administrative records kept by the Research & Innovation Foundation, which is the national institute for the promotion of scientific and technological research in Cyprus. The CORDIS database, as well as the web sites of various funding agencies and programmes, are also frequently consulted in order to identify any possible research activities that the information providers may have failed to report. |
| Incentives used for increasing response | No incentives used for increasing response. |
| Follow-up of non-respondents | Regular contacts by telephone or email and, in some cases, personal interviews, are also used. |
| Replacement of non-respondents (e.g. if proxy interviewing is employed) | No replacement of non-respondents. |
| Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility) | 100% |
| Non-response analysis (if applicable -- also see section 18.5.4 Data compilation - Weighting and Estimation methods) | There was no need to carry out a non-response survey. |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| R&D national questionnaire and explanatory notes in English: | Quest_2023_BUS_EN.pdf -(R&D Questionnaire 2023 - Business Sector (English)) |
| R&D national questionnaire and explanatory notes in the national language: | Quest_2023_BUS_GR.pdf -(R&D Questionnaire 2023 - Business Sector (Greek)) |
| Other relevant documentation of national methodology in English: | Not applicable |
| Other relevant documentation of national methodology in the national language: | Not applicable |
18.4. Data validation
Validation activities include: checking that the population coverage and response rates are as required; comparing the statistics with previous cycles; confronting the statistics against other relevant data (both internal and external); investigating inconsistencies in the statistics; verifying the statistics against expectations and domain intelligence, outlier detection.
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)
Comment: Not applicable.
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) | Not applicable | Not applicable | Not applicable | Not applicable |
| 10-49 employees and self-employed persons | Not applicable | Not applicable | Not applicable | Not applicable |
| 50-249 employees and self-employed persons | Not applicable | Not applicable | Not applicable | Not applicable |
| 250-and more employees and self-employed persons | Not applicable | Not applicable | Not applicable | Not applicable |
| TOTAL | Not applicable | Not applicable | Not applicable | Not applicable |
18.5.1.2. Imputation rate by NACE
| NACE | R&D Expenditure | R&D personnel (FTE) | ||
|---|---|---|---|---|
| Unweighted | Weighted | Unweighted | Weighted | |
| Industry1) | Not applicable | Not applicable | Not applicable | Not applicable |
| Services2) | Not applicable | Not applicable | Not applicable | Not applicable |
| TOTAL | Not applicable | Not applicable | Not applicable | Not applicable |
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 (between the survey years) |
The national R&D survey is carried out on an annual basis. |
|---|---|
| Data compilation method - Preliminary data | For a significant number of information providers, final data are already available within 10 months after the end of the calendar year of the reference period. For the rest of the providers, an estimate is made on the basis of the previous year’s figures and data derived from administrative records. No use of coefficients is made. |
18.5.3. Measurement issues
| Method of derivation of regional data | Not applicable. Cyprus is one region. |
|---|---|
| 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 | No deviations from FM §4.40-4.43 (VAT), and FM §4.38-4.39 (depreciation) recomendations. |
18.5.4. Weighting and estimation methods
| Weight calculation method | Not applicable. No sampling is used. |
|---|---|
| Data source used for deriving population totals (universe description) | Not applicable. No sampling is used. |
| Variables used for weighting | Not applicable. No sampling is used. |
| Calibration method and the software used | Not applicable. No sampling is used. |
| Estimation | Not applicable. No sampling is used. |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comments.
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.
31 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, if there are deviations please explain.
For Cyprys, the statistical unit and the reporting unit are the same and is the enterprise.
No deviation from the mandatory use of the 'enterprise' as statistical unit for business R&D statistics exist.
Please see the sub-concepts 3.6.1 and 3.6.2 in the full metadata view.
Not requested.
Government controlled areas of the Republic of Cyprus.
R&D statistics cover national and regional data.
Calendar year 2023
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
The units of measures used for the data set disseminated are Euro, %, number of persons.
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.
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.
