1.1. Contact organisation
Statistical Office of the Slovak Republic
1.2. Contact organisation unit
Cross-sectional Statistics Department
1.3. Contact name
Restricted from publication1.4. Contact person function
Restricted from publication1.5. Contact mail address
Statistical Office of the Slovak Republic
Lamacska cesta 3/C
840 05 Bratislava 45
Slovakia
1.6. Contact email address
Restricted from publication1.7. Contact phone number
Restricted from publication1.8. Contact fax number
Restricted from publication2.1. Metadata last certified
30 October 20232.2. Metadata last posted
30 October 20232.3. Metadata last update
30 October 20233.1. Data description
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit 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 private non-profit sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
The main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
3.2. Classification system
- The distribution of principal economic activity and by product field is based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
- The local units for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
- The distribution by socioeconomic objectives (SEO) is based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
- The fields of research and development based on Classification and distribution by Fields of Research and Development (FORD).
3.2.1. Additional classifications
| Additional classification used | Description |
| ISCO-08 | International Standard Classification of Occupations. |
| ISCED-2011 | International Standard Classification of Education. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Frascati manual methodology is used for identifying R&D. R&D covers three activities: basic research, applied research and experimental development. |
| Fields of Research and Development (FORD) | NSE and SSH are covered and separately available at the 1-digit level (6 main fields of science). From 2013 onwards, indicators (R&D personnel (HC), R&D expenditure) are available at 2-digit level of FOS. |
| Socioeconomic objective (SEO) | SEO are covered and available at chapter level of NABS. |
3.3.2. Sector institutional coverage
| Private non-profit sector | Corresponds to Frascati manual. The FM methodology was implemented in the 1994 R&D questionnaire. From 2011 onwards, the classification of R&D organisations by sectors is based on the ESA2010 classification. The frame population comprises all institutional units of the PNP sector active in the reference period. It is derived from the Statistical business register by extraction of units classified by the national accounts (ESA 2010) to S.15 (Non-profit institutions serving households) with the exclusion of those units included in the HES sector. |
| Inclusion of units that primarily do not belong to PNP | No |
3.3.3. R&D variable coverage
| R&D administration and other support activities | Treatment in line with the Frascati Manual §2.122. |
| External R&D personnel | Treatment in line with the Frascati Manual §5.20-5.24. |
| Clinical trials | Not applicable. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Available. |
| Payments to rest of the world by sector - availability | Not available. |
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) 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 | |
| Difficulties to distinguish intramural from extramural R&D expenditure |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | Calendar year. |
| Source of funds | Source of funds follows the Frascati Manual methodology. From 2006 onwards, full breakdown according to FM. Since 2016, data on internal/external funds and transfer/exchange funds are collected. |
| Type of R&D | All 3 types of R&D available, basic research, applied research and experimental development. |
| Type of costs | From 1996 onwards, the breakdown by type of costs is available. Since 2018, more detailed breakdown of capital and current expenditure according to FM2015 is available. |
| Defence R&D - method for obtaining data on R&D expenditure | Only defence related R&D expenditure performed by the civil sector is surveyed. |
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 during the calendar year. |
| Function | The classification into the three categories of personnel is by ISCO-08 classification. |
| Qualification | Questions on personnel by qualification were introduced in the 1994 questionnaire. Qualification at level ISCED-5B (First-stage tertiary education - practical) was included in the secondary education. From 2006 onwards, qualification at level ISCED 5B (ISCED 2011 554) is separately available. From 2016, qualification structure available for employees only. |
| Age | Available for researchers, for researchers employees in 2003-2015, for internal researchers from 2016 onwards. |
| Citizenship | Available for researchers, for researchers employees in 2003-2015, for internal researchers from 2016 onwards. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | Calendar year. |
| Function | The classification into the three categories of personnel is by ISCO-08 classification. |
| Qualification | Questions on personnel by qualification were introduced in the 1994 questionnaire. Qualification at level ISCED-5B (First-stage tertiary education - practical) was included in the secondary education. From 2006 onwards, qualification at level ISCED 5B (ISCED 2011 554) is separately available. From 2016, qualification structure available for employees only. |
| Age | Not surveyed. |
| Citizenship | Not surveyed. |
3.4.2.3. FTE calculation
FTE is provided by units in the R&D questionnaire, it is calculated according to the formula:
Sum of work-hours in R&D activities over the current year divided by 2000
3.4.2.4. R&D personnel - Cross-classification by function and qualification
| Cross-classification | Unit | Frequency |
| Cross-classification of R&D personnel and researchers by occupation and qualification is available for employees. | HC, FTE | annually |
3.5. Statistical unit
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
3.6. Statistical population
See below.
3.6.1. National target population
The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units which can be accessed through the frame and the survey data really refer to this population of institutional units.
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 PNP Sector should consist of all R&D performing units (including known R&D performers or assumed to perform R&D). In practise however, countries in their R&D surveys might have difficulty in identifying R&D activities at the municipality level.
| 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 target population is in line with the Frascati Manual recommendations. It includes: ESA 2010 S.15 Non-profit institutions serving households | |
| Estimation of the target population size | 22 |
3.7. Reference area
Not requested. R&D statistics cover national and regional data.
3.8. Coverage - Time
Not requested. See point 3.4.
3.9. Base period
Not requested. 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 indicators are available according to 3 units of measure:
R&D expenditure in thousand €
Number of R&D personnel in HC as total number of persons engaged in R&D during the calendar year
Number of R&D personnel in FTE as sum of work-hours in R&D activities over the current year divided by 2000.
Reference period is calendar year 2021.
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 Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. 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. |
| Nature of the “obligations” of responsible national organisations to produce statistics and report to international organisations | Yes, derived from the legal act. |
6.1.2. National legislation
| Existence of R&D specific statistical legislation | Production of R&D statistics is governed by the general national statistical legislation. |
| Legal acts | Act No. 540/2001 Coll. on State Statistics, as amended; https://www.slov-lex.sk/pravne-predpisy/SK/ZZ/2001/540/ Program of State Statistical Surveys, published for three years in the Collection of Laws of the SR; https://www.slov-lex.sk/pravne-predpisy/SK/ZZ/2020/292/20230101 |
| Obligation of responsible organisations to produce statistics (as derived from the legal acts) | Yes |
| Right of responsible organisations to collect data – obligation of (natural / legal) persons to provide raw and administrative data (as derived from the legal acts) | Yes, derived from the legal act. |
| Obligation of responsible organisations to protect confidential information from disclosure (as derived from the legal acts) | Laid down in the Act No. 540/2001 Coll. on state statistics as amended. |
| Rights of access of third organisations / persons to data and statistics (as derived from the legal acts) | No access of third organisations to confidential data. |
| Planned changes of legislation | - |
6.1.3. Standards and manuals
- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development
- European Business Statistics Methodological Manual on R&D
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.
A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.
a) Confidentiality protection required by law:
Act No. 540/2001 Coll. on state statistics as amended.
Internal Directive on the Protection of Confidential Statistical Data (regulates the method of management and implementation of activities related to ensuring the protection of confidential statistical data in the Statistical Office of the Slovak Republic).
b) Confidentiality commitments of survey staff:
The survey staff signed the confidentiality commitment.
7.2. Confidentiality - data treatment
Confidential data are protected according to the CR (EC) No 322/97 and according to the national Act No 540/2001 on State Statistics as amended.
Internal methodological instruction of the Statistical Office of the Slovak Republic regulates specific methods and values of parameters used in the protection of confidential statistical data of surveys and data sets specified in the Directive on the protection of confidential statistical data.
Identifying confidential cells in aggregated data: minimum frequency rule (n=3) together with the k % dominance rule.
8.1. Release calendar
The Catalog of Publications is publicly available on the website of the Statistical Office of the Slovak Republic and it contains basic information on the issued titles, issue dates, periodicity and language version.
8.2. Release calendar access
https://slovak.statistics.sk/wps/portal/ext/products/publikacie/Kalendár zverejňovania publikácií/
8.3. Release policy - user access
Information on all new released publications is available on the website of the Statistical Office of the Slovak Republic. The release policy determines the availability of statistical data to all users at the same time.
Yearly data dissemination.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
| Regular releases | N | |
| 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 | Content, format, links, ... |
| General publication/article (paper, online) |
Y | Yearbook of Science and Technology of the SR 2022 Statistical Yearbook of the SR 2022 – chapter on S&T&I Slovak Republic in figures 2022 – chapter on R&D |
| Specific paper publication (e.g. sectoral provided to enterprises) (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
On-line database of the Statistical Office of the Slovak Republic, https://slovak.statistics.sk/wps/portal/ext/Databases
The way to R&D data on this address: DATAcube. - Access to database DATAcube. - Multi-domain statistics - Science, technology and innovation - Research and Development
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Micro-data are provided only for scientific purposes according to the stated rules. Conditions for granting access to confidential statistical data for scientific purposes are provided on the website of the Statistical Office of the Slovak Republic. |
| Access cost policy | Payment required. |
| Micro-data anonymisation rules | Anonymized micro-data are provided to outside users for scientific purposes. Users (researchers) have to sign an agreement with the Statistical Office of the Slovak Republic that includes also data protection items. |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
| Internet: main results available on the national statistical authority’s website | Y | Aggregate figures | |
| Data prepared for individual ad hoc requests | Y | Aggregate figures | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Meta-information is available in on-line publication and on-line database, which includes description of indicators, definitions, survey methodology etc.
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
See below.
10.7.1. Information and clarity
| Type(s) of data accompanying information available (metadata, graphs, quality reports, etc.) | Metadata on the statistical web-site and in publications, methodological explanation in the questionnaire. |
| Request on further clarification, most problematic issues | We have a few requests from data users for further clarification. They are mainly about data breakdowns. |
| Measure to increase clarity | We permanently improve the methodological explanations in the survey questionnaire. |
| Impression of users on the clarity of the accompanying information to the data | According to the information from requests on the R&D data from users by phone or e-mail, we assume that accompanying methodological explanations to data is understandable for users on overall. |
11.1. Quality assurance
Statistical Office of the SR has established the system of quality management. Quality manual contains description of system of quality management and fulfillment of requirements of standard ISO 9001.
The application of the Quality manual in practice ensures that all activities with impact on the quality of statistical products are planned, managed, examined, evaluated and meet the requirements accepted in the customer order. Quality manual is available at: https://slovak.statistics.sk/wps/wcm/connect/b28fd6cb-76cf-4477-9a97-d9789b1fa429/Prirucka_kvality_2021.pdf?MOD=AJPERES&CVID=nTynTCM&CVID=nTynTCM
The basis of the whole system of quality management is the European Statistics Code of Practice.
11.2. Quality management - assessment
The overall quality of the PNP R&D statistical outputs is very good. The survey methodology follows the Frascati manual recommendations and the national and international requirements. The R&D statistics complies with 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.
The R&D survey coverage, reference period, data collection, checking and data processing follow the Eurostat methodology and recommendations for production of the common R&D statistics of the EU member states. Results of the survey for the country total and by regions as well were transmitted to Eurostat. Transmission of R&D data to Eurostat was realised in the SDMX format via eDAMIS - the safe, secure procedure.
Main strengths of the survey:
- R&D survey is an annual exhaustive survey
- The survey methodology complies with the Frascati Manual methodology and the Eurostat/OECD harmonised R&D data collection
- All mandatory and most of optional indicators were introduced to the R&D survey
- Enterprises are contacted to consult errors and missing variables in all necessary cases
- The item-non response is equal to zero
Main activities undertaken to assure high quality of PNP R&D statistics:
- Increase the response rate by several reminders
- Communications with respondents
- Use of best practices, quality guidelines, quality management activities used in the Statistical Office of the Slovak Republic according to ISO 9001.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
| 1 | The European Commission (DG RTD, DG ENTR); Eurostat |
Data used in publications and further development; Data used for dissemination in Eurostat on-line database and publications, preparation of EP and Council report etc. |
| 1 | OECD, UN | Data used in databases, publications and international comparisons |
| 1 | Ministry of Economy; Ministry of Finance; Ministry of Education, Science, Research and Sport; Other Ministries; Government Office of the Slovak Republic; National Bank of Slovakia; Statistical Office of the Slovak Republic | Data used for policy making in the field of Science, Technology and Innovation, further for sectoral comparisons and international comparisons; Data used for storing in the database and published in national publications and on the web site |
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 | The Statistical Office of the Slovak Republic carried out the user satisfaction survey in 2022, where also R&D statistics was included; https://slovak.statistics.sk/wps/portal/ext/aboutus/marketing/survey.of.satisfaction |
| User satisfaction survey specific for R&D statistics | No, the survey covered several statistical areas, where products of R&D statistics were included together with innovation, energy and environment statistics in one category. |
| Short description of the feedback received | Average rate of user satisfaction with products of these statistics was 68,9 %. No specific feedback for these statistics was in 2022. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not available.
12.3.2. Data availability
Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 0,05%
12.3.2.1. Incorporation PNP sector in another sector
| Incorporation of PNP in another sector | No |
| Reasons for not producing separate R&D statistics for the PNP sector | |
| Share of PNP expenditure in the total expenditure of the other sector | |
| Share of PNP R&D Personnel in the respective figure of the other sector |
12.3.2.2. Non-collection of R&D data for the PNP sector
| Reasons for not compiling R&D statistics for the PNP sector | |
| PNP R&D expenditure/ GERD*100) | |
| Share of PNP R&D Personnel in the respective figure of the total national economy |
12.3.2.3. Data availability on more detail level
| Additional dimension/variable available at national level1) | Availability2 | Frequency of data collection | Breakdown variables |
Combinations of breakdown variables | Level of detail |
| Total R&D Expenditure and R&D Expenditure from government sources in selected areas of R&D: information and communication technologies, of which software; biotechnology; nanotechnologies and nanomaterials | Y-2006 | Annual | |||
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').
2) Y-start 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:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
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
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)
Coefficient of variation for Total R&D expenditure :
Coefficient of variation for Total R&D personnel (FTE) :
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.
a) Extent of non-sampling errors:
b) Measures taken to reduce the extent of non-sampling errors:
c) Methods used in order to correct / adjust for such errors:
13.3.1. Coverage error
Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Not requested.
13.3.3. Non response error
Not requested.
13.3.3.1. Unit non-response - rate
Not requested.
13.3.3.2. Item non-response - rate
Not requested.
13.3.4. Processing error
Not requested.
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)
a) End of reference period: 31/12/2021
b) Date of first release of national data: 12/10/2022
c) Lag (months): 10
14.1.2. Time lag - final result
a) End of reference period: 31/12/2021
b) Date of first release of national data: 28/06/2023
c) Lag (months): 18
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 | 0 |
| Reasoning for delay |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. General issues of comparability
No divergences from FM, from international classification, no divergence in survey coverage.
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 paragraphs and the EBS Methodological Manual on R&D Statistics 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 paragraph 5.2). | No | |
| Researcher | FM2015, § 5.35-5.39. | No | |
| Approach to obtaining Headcount (HC) data | FM2015, § 5.58-5.61 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | No | |
| Approach to obtaining FTE data | FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | |
| Intramural R&D expenditure | FM2015,Chapter 4 (mainly paragraph 4.2). | No | |
| Statistical unit | FM2015, § 10.40-10.42 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | |
| Target population | FM2015, § 10.40-10.42 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | |
| Sector coverage | FM2015, § 10.2-10.8 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | |
| Reference period for the main data | Reg. 2020/1197: Annex 1, Table 18 | No | |
| Reference period for all data | Reg. 2020/1197: Annex 1, Table 18 | No |
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, where related recommendations are made. Countries are asked to report on the existence of any deviations from existing recommendations and comment upon.
| Methodological issues | Deviation from recommendations | Comments on national treatment / treatment deviations from recommendations |
| Data collection method | No | |
| Survey questionnaire / data collection form | No | |
| Cooperation with respondents | No | |
| Data processing methods | No | |
| Treatment of non-response | No | |
| Data compilation of final and preliminary data | No |
15.2. Comparability - over time
See below.
15.2.1. Length of comparable time series
See below.
15.2.2. Breaks in time series
| Length of comparable time series | Break years1 | Nature of the breaks | |
| R&D personnel (HC) | From 1994 | 1994, 1997, 2016, 2018 | In 1994 Frascati definitions were adopted for the national R&D surveys. In 1997 change in the methodology of institutional classification by sectors resulted in the reclassification of some institutions from the Government sector to the business enterprise sector. 2016: Inclusion of external personnel. 2018: Methodological change in content of the indicator R&D employees in head counts; it includes total number of R&D employees during the reference year, before number of R&D employees at the end of the reference year (as of December 31). |
| Function | From 1994 | ||
| Qualification | From 1994 | 2006, 2016 | Qualification at level ISCED 5B separately available, before 2006 included in the secondary education. 2016: for employees only |
| R&D personnel (FTE) | From 1994 | 1994, 1997, 2016 | In 1994 Frascati definitions were adopted for the national R&D surveys. In 1997 change in the methodology of institutional classification by sectors resulted in the reclassification of some institutions from the Government sector to the business enterprise sector. 2016: Inclusion of external personnel. |
| Function | From 1994 | ||
| Qualification | From 1994 | 2006, 2016 | Qualification at level ISCED 5B separately available, before 2006 included in the secondary education. 2016: for employees only |
| R&D expenditure | From 1994 | 1994, 1997 | In 1994 Frascati definitions were adopted for the national R&D surveys. In 1997 change in the methodology of institutional classification by sectors resulted in the reclassification of some institutions from the Government sector to the business enterprise sector. |
| Source of funds | From 1994 | 2006 | Introduction of detailed breakdown of R&D expenditure from source abroad according to the FM. |
| Type of costs | From 1994 | ||
| Type of R&D | From 1994 | ||
| Other | From 1994 | 2013 | Regional breakdown by NUTS2 is according to local units. |
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
The data are produced in the same way in the odd and even years.
15.3. Coherence - cross domain
See below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Classification ESA2010 is used in R&D statistics for definition of sectors. PNP sector includes institutional units classified in S.15 with exclusion of those units included in the HES.
R&D survey data are regularly used in SNA calculations.
15.4. Coherence - internal
See below.
15.4.1. Comparison between preliminary and final data
This part compares key R&D variables as preliminary and final data.
| Total PNP R&D expenditure (in 1000 of national currency) | Total PNP R&D personnel (in FTEs) | Total number of PNP researchers (in FTEs) | |
| Preliminary data (delivered at T+10) | 415,213 | 9,8675 | 8,1925 |
| Final data (delivered T+18) | 415,213 | 9,8675 | 8,1925 |
| Difference (of final data) | 0 | 0 | 0 |
15.4.2. Consistency between R&D personnel and expenditure
| Average remuneration (cost in national currency) | |
| Consistency between FTEs of internal R&D personnel and R&D labour costs (1) | R&D labour costs / FTEs of internal personnel = 27897,9 |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | Other current costs for external R&D personnel / FTEs of external personnel = 4620,5 |
(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) | % sub-contracted1) | |
| Staff costs | Not separately available. | No work sub-contracted to third parties. |
| Data collection costs | Not separately available. | No work sub-contracted to third parties. |
| Other costs | Not separately available. | No work sub-contracted to third parties. |
| Total costs | Not separately available. | No work sub-contracted to third parties. |
| Comments on costs | ||
1) The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
| Number of Respondents (R) | 6 | number of respondents only |
| Average Time required to complete the questionnaire in hours (T)1 | 4,76 | based on the response to a direct question |
| Average hourly cost (in national currency) of a respondent (C) | 10,28 | based on average labour costs in whole economy |
| Total cost | 293,60 | R x T x C |
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. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
18.1.1. Data source – general information
| Survey name | Annual survey on research and development (In Slovak: Ročný výkaz o výskume a vývoji) |
| Type of survey | Census |
| Combination of sample survey and census data | - |
| Combination of dedicated R&D and other survey(s) | - |
| Sub-population A (covered by sampling) | - |
| Sub-population B (covered by census) | - |
| Variables the survey contributes to | All R&D variables requested by the European regulation. |
| Survey timetable-most recent implementation | Sending out of the questionnaire: middle of February, data collection date: middle of March, final data: end of July. |
18.1.2. Sample/census survey information
| Stage 1 | Stage 2 | Stage 3 | |
| Sampling unit | Non-profit institutions serving households | ||
| Stratification variables (if any - for sample surveys only) | |||
| Stratification variable classes | |||
| Population size | |||
| Planned sample size | |||
| Sample selection mechanism (for sample surveys only) | |||
| Survey frame | |||
| Sample design | |||
| Sample size | |||
| Survey frame quality |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | No administrative data collection is carried out. |
| Description of collected data / statistics | |
| Reference period, in relation to the variables the survey contributes to |
18.2. Frequency of data collection
Annual data collection.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | The only source for compilation of data transmitted to Eurostat is the R&D survey of the Statistical Office of the Slovak Republic (SO SR). |
| Description of collected information | Information filled in the questionnaire by individual R&D units include number of R&D personnel (researchers, technicians and equivalent staff, supporting staff) by qualification and sex in HC and FTE. Researchers in HC also by age and citizenship. Information from individual units concern also intramural expenditure on R&D, by type of R&D, source of funds, fields of science, socio-economic objectives of R&D performed. |
| Data collection method | The R&D survey of the SO SR is an on-line survey. The statistical system of the Slovak Republic is decentralised, the Regional Department is charged to collect the questionnaires. The Cross-sectional Statistics Department, responsible for R&D statistics of the Statistical Office of the Slovak Republic (SO SR) provides the methodology and organises seminars for training of the regional staff. Monitoring of non-response is made by the regional staff during the collection period. The integrated statistical information system used for data collection contains also fuction for generation of reminders for statistical units. Reminders are sent twice to alert them to meet the survey deadline. Collection and checking of data is made by the regional staff, all further treatments are taken over by the R&D statistics staff of the SO SR. Administrative data sources are not used. |
| Time-use surveys for the calculation of R&D coefficients | |
| Realised sample size (per stratum) | |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | on-line survey |
| Incentives used for increasing response | |
| Follow-up of non-respondents | |
| Replacement of non-respondents (e.g. if proxy interviewing is employed) | |
| Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility) | 0,67 |
| Non-response analysis (if applicable -- also see section 18.5. Data compilation - Weighting and Estimation methods) |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
| R&D national questionnaire and explanatory notes in English: | 2021_SK_RD_questionnaire_VV6-01_EN.pdf |
| R&D national questionnaire and explanatory notes in the national language: | 2021_SK_RD_questionnaire_VV6-01_SK.pdf |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: |
Annexes:
2021_SK_RD questionnaire_VV 6-01 in English
2021_SK_RD questionnaire_VV 6-01 in Slovak language
18.4. Data validation
Data validation is embedded in the integrated statistical information system (ISIS) of the Statistical Office of the Slovak Republic (SO SR).
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Not applicable.
18.5.2. Data compilation methods
| Data compilation method - Final data (between the survey years) | R&D surevey is an annual survey. Data are produced in the same way in the odd and even years. |
| Data compilation method - Preliminary data | R&D surevey is an annual survey. Data are produced in the same way in the odd and even years. |
18.5.3. Measurement issues
| Method of derivation of regional data | Until 2012 in all sectors, units are classified to regions according to their main location (by residence of the company or institutions). From 2013 onwards regional breakdown realised by local units. The new method did not cause significant change in data. |
| Coefficients used for estimation of the R&D share of more general expenditure items | Coefficients are not used. |
| Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures | Depreciation and VAT are excluded from R&D expenditure. |
| Differences between national and Frascati Manual classifications not mentioned above and impact on national statistics | No known differences. |
18.5.4. Weighting and estimation methods
| Description of weighting method | Weighting and estimation methods not used. Information collected by the statistical R&D survey from R&D performing units treated as final. |
| Description of the estimation method | Not applicable. |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit 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 private non-profit sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
The main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
See below.
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
See below.
Not requested. R&D statistics cover national and regional data.
Reference period is calendar year 2021.
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
R&D indicators are available according to 3 units of measure:
R&D expenditure in thousand €
Number of R&D personnel in HC as total number of persons engaged in R&D during the calendar year
Number of R&D personnel in FTE as sum of work-hours in R&D activities over the current year divided by 2000.
See below.
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
Yearly data dissemination.
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.