1.1. Contact organisation
Swiss Federal Statistical Office (FSO)
1.2. Contact organisation unit
Division WI (Economy),
Section WSA (Economic structure and analysis)
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
Office fédéral de la Statistique (OFS)
Espace de l'Europe 10
2010 Neuchâtel
SWITZERLAND
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Not requested
31 October 2025
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 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)..
The guiding document to preparing the quality reports is the European Statistical System (ESS) Handbook 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 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);
- The R&D personnel and researchers by educational attainment are classified by the International Standard Classification of Education ISCED 2011
3.3. Coverage - sector
See below.
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.
The definition of R&D complies with the Frascati Manual.
3.3.2. Sector institutional coverage
| Private non-profit sector | Ad hoc estimation with other sector R&D survey |
|---|---|
| Inclusion of units that primarily do not belong to PNP and the borderline cases | No |
3.3.3. R&D variable coverage
| R&D administration and other support activities | No data for R&D personnel in the PNP sector |
|---|---|
| External R&D personnel | No data for R&D personnel in the PNP sector |
| Clinical trials: compliance with the recommendations in Frascati Manual §2.61. | Not applicable |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Not available |
|---|---|
| Payments to rest of the world by sector - availability | Not available |
3.3.5. Extramural R&D expenditures
According to the Frascati Manual (FM), 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 | Not applicable |
| Difficulties to distinguish intramural from extramural R&D expenditure | Not applicable |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | Biennial (odd years) |
|---|---|
| Source of funds | Ad hoc Estimation, in accordance with FM (2015) We only estimates for the 5 principal source of funds |
| Type of R&D | Ad hoc Estimation, in accordance with FM (2015) |
| Type of costs | Ad hoc Estimation, in accordance with FM (2015) |
| Defence R&D - method for obtaining data on R&D expenditure | We do not collect information on Defence R&D for the PNP sector |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | No data for R&D personnel in the PNP sector. |
|---|---|
| Function | No data for R&D personnel in the PNP sector. |
| Qualification | No data for R&D personnel in the PNP sector. |
| Age | No data for R&D personnel in the PNP sector. |
| Citizenship | No data for R&D personnel in the PNP sector. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | No data for R&D personnel in the PNP sector. |
|---|---|
| Function | No data for R&D personnel in the PNP sector. |
| Qualification | No data for R&D personnel in the PNP sector. |
| Age | No data for R&D personnel in the PNP sector. |
| Citizenship | No data for R&D personnel in the PNP sector. |
3.4.2.3. FTE calculation
No data for R&D personnel in the PNP sector.
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 | No target population; Ad hoc estimation are made with financial data from the other sectors | |
| Estimation of the target population size | No estimation, see above |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested.
3.9. Base period
The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
R&D expenditure is published in the following units: Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).
R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.
2023
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
Legal acts / agreements:
Since the beginning of 2021, the collection of R&D statistics is based on the Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. 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. The transmission of R&D data is mandatory for Member States and EEA countries.
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.
Switzerland delivers R&D data on a volountary basis
6.1.2. National legislation
| Existence of R&D specific statistical legislation | Yes
|
|---|---|
| Are respondents obliged by the national law to provide raw and administrative data: | No |
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
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:
a) Confidentiality protection required by law:
Federal Statistics Act (FStatA) of 9 October 1992 (RS 431.01)
b) Confidentiality commitments of survey staff:
Federal Statistics Ordinance of 30 April 2025 (OFS)
7.2. Confidentiality - data treatment
No micro data
8.1. Release calendar
The calendars of statistical publications are publicly available.
The data are available in June (odd years)
8.2. Release calendar access
For Eurostat this is: Release calendar - Eurostat (europa.eu)
For Switzerland this is: Agenda | Federal Statistical Office - FSO
8.3. Release policy - user access
Statistical information shall be disseminated in such a way that all users can access it simultaneously. All users have access to statistical publications at the same time and under the same conditions, and any privileged pre-release access granted to an external user is limited, controlled and made public. Some authorities may receive advance information under embargo in order to prepare for possible questions. The policy on consultations and advance information regulates the modalities.
Source: LSF 18.1, Charte Principes fondamentaux 9 et 10, CoP 10 ind. 6
The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.
The frequency of R&D data dissemination in Switzerland for the PNP sector is every two years (odd years). Switzerland do not produce provisional data
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1) | Links | |
|---|---|---|
| Regular releases | Y | Almost CHF 26 billion invested in R&D in Switzerland in 2023 - Research and development in Switzerland in 2023 | Medienmitteilung |
| 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 | Y | Recherche et développement en Suisse 2023 - Finances et personnel | Publication |
| Specific paper publication (e.g. sectoral provided to enterprises) | N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
No online database but a system of S&T indicators: Système d'indicateurs Science et Technologie | Office fédéral de la statistique - OFS
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 the micro-data | No micro data available |
|---|---|
| Access cost policy | Not applicable |
| Micro-data anonymisation rules | Not applicable |
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 | Science and Technologie indicator |
| Data prepared for individual ad hoc requests | Y | Aggregate figures | Data prepared for individual ad hoc request |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
No methodological documents available for the PNP sector
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
See below.
10.7.1. Documentation and users’ requests
| Type(s) of data accompanying information available (metadata, graphs, quality reports, etc.) | Graphs and analytical comments |
|---|---|
| Requests on further clarification, most problematic issues | Explanation on methodology |
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).
11.2. Quality management - assessment
Not applicable
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1) | Description of users | Users’ needs |
|---|---|---|
| 1- Institutions | OECD and ESTAT | All R-D statistics |
| 1- Institutions | State Secretariat for Education, Research and Innovation (SERI). The SERI within the Federal Department of Home Affairs is the federal government's specialised agency for national and international matters concerning general and university education, research and space. | All the R-D and STI statistics needed for the redaction of the “Message relating to the encouragement of the formation, research and innovation” and for the strategic controlling of the formation, research and the technology objectives. |
| 1- Institutions | State Secretariat for Economic Affairs (SECO).The SECO is the Confederation's competence centre for all core issues relating to economic policy. | All kind of R-D and STI statistics |
| 2- Social actors | Economiesuisse: federation of the swiss companies | All the R-D statistics |
| 3 -Media | Media in general and in particular: “economic life, the review of economic policy”. Published under the auspices of the Secretariat for Economic Affairs SECO, this review: “economic life, the review of economic policy” analyzes every month the economic evolution of the country. Moreover, it regularly publishes statistical data of which R-D statistics. | All R-D statistics |
| 4- Researchers and students | Universities in general and in particular: the Swiss Institute for Business Cycle Research (KOF) within the Swiss Federal Institute of Technology of Zurich, (ETHZ). The KOF within the Swiss Federal Institute of Technology of Zurich supplies information in the range of the economic and market research. |
R-D statistics for the validation of the Innovation survey. |
| 4- Researchers and students | Researchers and students. | All kind of R-D and STI statistics. |
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 FSO conducts non-regular surveys on user satisfaction. |
|---|---|
| User satisfaction survey specific for R&D statistics | We do not conduct a user satisfaction survey specific for R&D statistics |
| Short description of the feedback received | We do not receive feedback for the PNP sector |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not applicable
12.3.2. Data availability
Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 1%
12.3.2.1. Incorporation of PNP sector in another sector
| Incorporation of PNP in another sector | No |
|---|---|
| Reasons for not producing separate R&D statistics for the PNP sector | Not applicable |
| Share of PNP expenditure in the total expenditure of the other sector | 1% |
| Share of PNP R&D Personnel in the respective figure of the other sector | Not applicable. No estimations are made for the R&D personnel in the PNP 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 | Not applicable |
|---|---|
| PNP R&D expenditure/ GERD*100) | The share of R-D expenditures of the PNP sector in total R&D expenditure is estimated at 1%. |
| Share of PNP R&D Personnel in the respective figure of the total national economy | Not applicable |
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 |
|---|---|---|---|---|---|
| No other additional dimension /variable are available |
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
12.3.2.4. R&D personnel - Cross-classification by function and qualification (if available in FTE and HC)
| Cross-classification | Unit | Frequency |
|---|---|---|
| No |
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
Confidence interval for Total R&D expenditure: Not applicable (ad hoc estimations)
Confidence interval for Total R&D personnel (FTE): No data for R&D personnel in the PNP sector.
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.
- Extent of non-sampling errors: Not applicable (ad hoc estimations).
- Measures taken to reduce the extent of non-sampling errors: Not applicable.
- Methods used in order to correct/adjust for such errors: Not applicable.
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: Decembre 31st of the reference year
b) Date of first release of national data: June (Y+2)
c) Lag (days): 18 month
NB: we have only final results (no provisional results)
14.1.2. Time lag - final result
a) End of reference period: Decembre 31st of the reference year
b) Date of first release of national data: June (Y+2)
c) Lag (days): 18 month
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) | We do not have provisional data | 18 |
| Delay (days) | Not applicable | 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
Not applicable
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) 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 sub-chapter 5.2). | Not applicable | No data available for R&D personnel in the PNP sector |
| Researcher | FM2015, § 5.35-5.39. | Not applicable | No data available for R&D personnel in the PNP sector |
| Approach to obtaining Headcount (HC) data | FM2015, § 5.58-5.61 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | Not applicable | No data available for R&D personnel in the PNP sector |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | Not applicable | No data available for R&D personnel in the PNP sector |
| Approach to obtaining FTE data | FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | Not applicable | No data available for R&D personnel in the PNP sector |
| Intramural R&D expenditure | FM2015,Chapter 4 (mainly sub-chapter 4.2). | No | Ad hoc estimation |
| Statistical unit | FM2015, § 10.40-10.42 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | Ad hoc estimation |
| Target population | FM2015, § 10.40-10.42 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | Ad hoc estimation |
| Sector coverage | FM2015, § 10.2-10.8 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No | Ad hoc estimation |
| Reference period for the main data | Reg. 2020/1197: Annex 1, Table 18 | No | Ad hoc estimation |
| Reference period for all data | Reg. 2020/1197: Annex 1, Table 18 | No | Ad hoc estimation |
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 | Reference to recommendations | Deviation from recommendations | Comments on national treatment / treatment deviations from recommendations |
|---|---|---|---|
| Data collection method | FM2015 Chapter 10 (mainly sub-chapter 10.6). | No | Ad hoc estimation |
| Survey questionnaire / data collection form | FM2015 Chapter 10 (mainly sub-chapter 10.6). | Not applicable | Ad hoc estimation |
| Cooperation with respondents | FM2015 Chapter 10 (mainly sub-chapter 10.6). | Not applicable | Ad hoc estimation |
| Data processing methods | FM2015 Chapter 10 (mainly sub-chapter 10.6). | Not applicable | Ad hoc estimation |
| Treatment of non-response | FM2015 Chapter 10 (mainly sub-chapter 10.6). | Not applicable | Ad hoc estimation |
| Data compilation of final and preliminary data | Reg. 2020/1197: Annex 1, Table 18 | Not applicable | No preliminary data |
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) | No data available for R&D personnel in the PNP sector | ||
| Function | No data available for R&D personnel in the PNP sector | ||
| Qualification | No data available for R&D personnel in the PNP sector | ||
| R&D personnel (FTE) | No data available for R&D personnel in the PNP sector | ||
| Function | No data available for R&D personnel in the PNP sector | ||
| Qualification | No data available for R&D personnel in the PNP sector | ||
| R&D expenditure | Y - 2000 |
2012 | Adaptation of the method for estimating PNP sector amounts based on higher education financial data |
| Source of funds | Y - 2000 |
2012 | Adaptation of the method for estimating PNP sector amounts based on higher education financial data |
| Type of costs | Y - 2000 |
2012 | Adaptation of the method for estimating PNP sector amounts based on higher education financial data |
| Type of R&D | Y - 2000 |
2012 | Adaptation of the method for estimating PNP sector amounts based on higher education financial data |
| Other |
|
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
We do not make an ad-hoc estimation in the even years for PNP sector
15.3. Coherence - cross domain
See below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Coherence with the national accounts sectorisation is insured.
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) | Not applicable | Not applicable | Not applicable |
| Final data (delivered T+18) | Not applicable | Not applicable | Not applicable |
| Difference (of final data) | Not applicable | Not applicable | Not applicable |
Comments:
We do not have preliminary data
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) | No data for R&D personnel in the PNP sector | |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | No data for R&D personnel in the PNP sector |
(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 |
1) 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:
We do not evaluate the costs for the R&D statistics
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | No respondents (ad hoc estimations) | |
| Average Time required to complete the questionnaire in hours (T)1) | No questionnaire (ad hoc estimations) | |
| Average hourly cost (in national currency) of a respondent (C) | Not applicable | |
| Total cost | Not applicable |
1) T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.
18.1.1. Data source – general information
No survey (ad hoc estimations on fionancial data from other R&D sectors)
18.1.2. Sample/census survey information
| Sampling unit | Not applicable (ad hoc estimations) |
|---|---|
| Stratification variables (if any - for sample surveys only) | Not applicable (ad hoc estimations) |
| Stratification variable classes | Not applicable (ad hoc estimations) |
| Population size | Not applicable (ad hoc estimations) |
| Planned sample size | Not applicable (ad hoc estimations) |
| Sample selection mechanism (for sample surveys only) | Not applicable (ad hoc estimations) |
| Survey frame | Not applicable (ad hoc estimations) |
| Sample design | Not applicable (ad hoc estimations) |
| Sample size | Not applicable (ad hoc estimations) |
| Survey frame quality | Not applicable (ad hoc estimations) |
| Variables the survey contributes to | Not applicable (ad hoc estimations) |
Not applicable (ad hoc estimations)
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | HERD; GOVRD; BERD; GBARD |
|---|---|
| Description of collected data / statistics | Harmonisation of financial flows between sectors |
| Reference period, in relation to the variables the administrative source contributes to | Reference year |
| Variables the administrative source contributes to | Not applicable |
18.2. Frequency of data collection
See 12.3.2.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | FSO Switzerland |
|---|---|
| Description of collected information | Financial data |
| Data collection method | Ad hoc estimations |
| Time-use surveys for the calculation of R&D coefficients | No survey |
| Realised sample size (per stratum) | Not applicable |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | Not applicable |
| Incentives used for increasing response | Not applicable |
| Follow-up of non-respondents | Not applicable |
| Replacement of non-respondents (e.g. if proxy interviewing is employed) | Not applicable |
| Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility) | Not applicable |
| Non-response analysis (if applicable -- also see section 18.5. Data compilation - Weighting and Estimation methods) | Not applicable |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| R&D national questionnaire and explanatory notes in English: | No questionnaire |
| R&D national questionnaire and explanatory notes in the national language: | No questionnaire |
| Other relevant documentation of national methodology in English: | No documentation of national methodology available |
| Other relevant documentation of national methodology in the national language: | No documentation of national methodology available |
18.4. Data validation
Not available
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition:
Imputation rate (for the variable x) % = (Number of imputed records for the variable x) * 100/ (Total number of possible records for x)
18.5.2. Data compilation methods
| Data compilation method - Final data | Ad hoc estimation |
|---|---|
| Data compilation method - Preliminary data | No preliminary data |
18.5.3. Measurement issues
| Method of derivation of regional data | Not applicable |
|---|---|
| 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 | Not applicable |
18.5.4. Weighting and estimation methods
| Description of weighting method | Not applicable |
|---|---|
| Description of the estimation method | Ad hoc estimation based on the financial data of the other R&D sector |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comments.
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)..
The guiding document to preparing the quality reports is the European Statistical System (ESS) Handbook 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
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.
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:
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 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.
The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.
The frequency of R&D data dissemination in Switzerland for the PNP sector is every two years (odd years). Switzerland do not produce provisional 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.
See below.
See below.
