Statistical Office of the Slovak Republic

Cross-sectional Statistics Department

Statistical Office of the Slovak Republic

Lamacska cesta 3/C

840 05 Bratislava 45

Slovakia

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.  

• 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).

See below.

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).

See below.

See below.

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

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

See below.

The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units which can be accessed through the frame and the survey data really refer to this population 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. 

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

Not requested. See point 3.4.

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.

See below.

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

- European Business Statistics Methodological Manual on R&D

Not requested.

Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.

A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.

a)       Confidentiality protection required by law:

 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.

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.

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.

https://slovak.statistics.sk/wps/portal/ext/products/publikacie/Kalendár zverejňovania publikácií/

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.

See below.

1) Y - Yes, N – No

See below.

1) Y – Yes, N - No 

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

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

Meta-information is available in on-line publication and on-line database, which includes description of indicators, definitions, survey methodology etc.

Not requested.

See below.

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.

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.

See below.

1)       Users' class codification

1- Institutions:
• European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
• in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
• International organisations: OECD, UN, IMF, ILO, etc.

2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.

3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.

4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)

5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)

6- Other (User class defined for national purposes, different from the previous classes.)

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

See below.

Not available.

Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 0,05%

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

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.

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.

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) : 

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:

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.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

Not requested.

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.

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

a) End of reference period: 31/12/2021

b) Date of first release of national data: 28/06/2023

c) Lag (months): 18

Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.

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

See below.

Not requested.

No divergences from FM, from international classification, no divergence in survey coverage.

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.

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.

See below.

See below.

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

The data are produced in the same way in the odd and even years.

See below.

Not requested.

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.

See below.

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

(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. 

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

1)        T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)

Not requested.

Not requested.

Not requested.

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.

Annual data collection.

See below.

Data validation is embedded in the integrated statistical information system (ISIS) of the Statistical Office of the Slovak Republic (SO SR). 

See below.

Not applicable.

Not requested.

Not requested.