1.1. Contact organisation
Swiss Federal Statistical Office (FSO)
1.2. Contact organisation unit
Division WI/ section WSA
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Office Fédéral de la Statistique (OFS)
Espace de l'Europe 10
2010 Neuchâtel
SWITZERLAND
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
25 September 2025
2.2. Metadata last posted
25 September 2025
2.3. Metadata last update
11 September 2025
3.1. Data description
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and experimental development (R&D) activities, and thereby provide information about the priority Governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content (FM 2015, Chapter 12).
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.
Statistics on science, technology and innovation were collected based on Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 1197/2020 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
Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.
3.2.1. National classification
| National nomenclature of SEO used | Federal data providers distribute their data, i.e. intramural R&D expenditure and extramural R&D expenditure (R&D contracts, R&D contributions (subsidies)) according to NABS chapters, 2007. As for indirect cantonal and federal funds, they are included in the category (NABS 12) “General advancement of knowledge: R&D financed from General University Funds (GUF)”. |
|---|---|
| Correspondence table with NABS | The NABS classification is used for the collection at level 1 (chapters) (13 categories). |
3.2.2. NABS classification
| Deviations from NABS | The break down is at the level of NABS chapters only. No break down possible by NABS sub-chapters |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | The break down is at the level of NABS chapters only. No break down possible by NABS sub-chapters |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Neither non-oriented research nor GUF can be broken down by FORD. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | We use Frascati Manual definition of R&D. The definition is sent with the questionnaire |
|---|---|
| Coverage of R&D or S&T1 in general | R&D only |
| Fields of R&D (FORD) covered | Natural Sciences and Engeneering (NSE) + Social Sciences and Humanities (SSH) |
1) Science & Technology
3.3.2. Definition and coverage of government
GBARD statistics are assumed to report detailed data on all the government's budget items that may support R&D activities and to measure or estimate their R&D content. For the purposes of GBARD, the Government sector comprises (a) the central (federal) government, (b) regional (state) government and (c) local (municipal) government subsectors (FM2015, Chapter 12).
| Levels of government | Definition | Included / Not included | Comments |
|---|---|---|---|
| Central (federal) government | The definition of “Federal State” comprises the general services of the Federal Government and legally independent federal institutions. | Included | |
| Regional (state) government | For the provincial level (cantons), R&D indirect cantonal funds (governed by the Act on higher education) are included in GBARD. It corresponds to the GUF. Only a small part of other R&D cantonal funds are included in GBARD. This information on R&D direct cantonal funds comes from the administrative data of the Higher Education Sector. | Included partially (Only R&D indirect cantonal funds, included in the GUF and partial R&D direct cantonal funds from the Higher Education Sector). | There are no survey at the provincial (cantonal) level. |
| Local (municipal) government | There are no R&D data on communal level. | Not included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Budget of federal offices financing or executing R&D
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.
| Definition of the national target population | Federal offices funding or executing R&D |
|---|---|
| Estimation of the target population size | Not applicable |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested.
Not requested.
a) Calendar year: Reference year
b) Fiscal year: -
Start month: 1 January 2023
End month: 31 December 2023
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
GBARD statistics are based on the Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. 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. Please note that according to Article 12(4) of Regulation (EU) 2020/1197, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.
6.1.2. National legislation
There is no special national law.
6.1.3. Standards and manuals
- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development.
- EBS Methodological Manual on R&D Statistics.
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
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: Ordonnance concernant l'exécution des relevés statistiques du 30 juin 1993
b) Confidentiality commitments of survey staff:
7.2. Confidentiality - data treatment
GBARD data are publicly available. No confidentiality precautions needs to be made.
8.1. Release calendar
The release calendar is publicly available at the Swiss federal offices website.
Preliminary GBARD are published in February of the year following the reference year (Y+1). The final GBARD data are published at national level in July of the year following the reference year (Y+1).
8.2. Release calendar access
8.3. Release policy - user access
GBARD data is available to all users on the FSO website.
The collection of GBARD data is conducted and disseminated on an yearly basis
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
|---|---|---|
| Regular releases | Y | The data is updated annually in an indicator (xlsx tables and diagramms) on the FSO website. A newsmail is also produced annually for the release of GBARD data. |
| Ad-hoc releases | N |
1) Y - Yes, N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Mean of dissemination | Availability (Y/N)1 | Content, format, links, ... |
|---|---|---|
| General publication/article (paper, online) |
Y | S&T Indicators: In the indicator, GBARD. indicator in French and in German. |
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Free online database (S-T Indicators) accessible on our website
S&T Indicators: In the indicator, GBARD.
indicator in French and in German.
Crédits budgétaires publics de recherche et développement
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 | No access rights - it is public |
|---|---|
| Access cost policy | Free access |
| Micro-data anonymisation rules | Not applicable; In GBARD only public institutions are covered, there is no need of anonymisation |
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 | |
| CD-ROMs | N | ||
| Data prepared for individual ad hoc requests | Y | aggregate figures | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
In 2021, the FSO introduced a methodological revision of the calculation of GBARD, based on administrative data. The new methodology was applied retrospectively to the series of all national GBARD data from 2017 onwards. The GBARD methodology is described in a FSO publication (only in french and german)
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, etc.) | To increase clarity we add definitions and comments to the Indicators on Internet and to the publications |
|---|---|
| Request on further clarification | No requests |
| Measure to increase clarity | No |
| Impression of users on the clarity of the accompanying information to the data |
11.1. Quality assurance
Not applicable
11.2. Quality management - assessment
The overall assessment of the GBARD data is good. Some weaknesses might appear by using R&D coefficients
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 - International institutions. | OECD and Eurostat | Data used for international comparison |
| 1 - National level | 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 innovation. |
GBARD statistics needed for the drafting of the message on the promotion of education, research and innovation” and for the strategic controlling of education, research and innovation |
| 1 - National level | State Secretariat for Economic Affairs (SECO). The SECO is the Confederation's competence centre for all core issues relating to economic policy. |
|
| 3 -Media | Media in general | All kind of R-D and STI statistics. |
| 4- Researchers and strudents | Universities in general, 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 | No national user satisfaction survey has been undertaken |
|---|---|
| User satisfaction survey specific for GBARD statistics | - |
| Short description of the feedback received | - |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
No data for the NABS sub-chapter
12.3.2. Completeness - overview
Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 995/2012.
| 5 (Very Good) |
4 (Good) |
3 (Satisfactory) |
2 (Poor) |
1 (Very poor) |
Reasons for missing cells | |
|---|---|---|---|---|---|---|
| Provisional budget statistics1 | X | |||||
| Obligatory final budget statistics1 | X | |||||
| Optional final budget statistics2 | X | The only optional data that are not delivered are the breakdown by FORD. |
1) Criteria: Obligatory data (provisional budget and final budget). Only 'Very Good' = 100% and 'Very Poor' <100% apply.
2) Criteria: Optional data (final budget). 'Very Good' = 100%; 'Good' = >75%;'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.
12.3.3. Data availability
See below.
12.3.3.1. Data availability – Provisional data
| Availability1 | Frequency of data collection | Gap years – years with missing data | Time of compilation (T+x)2 | Comments | |
|---|---|---|---|---|---|
| Total GBARD | Y | Annual | T+2 | Provisional data are available since 2021 | |
| NABS Chapter level | Y | Annual | T+6 | Provisional data are available since 2021 | |
| NABS Sub-chapter level | N | ||||
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | Y | Annual | T+2 | Provisional data are available since 2021 |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.2. Data availability – Final data
| Availability1 | Frequency of data collection | Gap years – years with missing data | Time of compilation (T+x)2 | Comments | |
|---|---|---|---|---|---|
| Total GBARD | Y-2000 | Annual | odd years and 2016 before Reference year 2017 | T+6 | Before 2017: Every 2 years |
| NABS Chapter level | Y-2000 | Annual | odd years and 2016 before Reference year 2017 | T+12 | Before 2017: Every 2 years |
| NABS Sub-chapter level | N | ||||
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | Y-2000 | Annual | odd years and 2016 before Reference year 2017 | T+6 | Before 2017: Every 2 years |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.3. Data availability – Other special categories
| Special categories | Stage1 | Availability1 | Frequency of data colletion | Gap years – years with missing data | Time of compilation (T+x)3 | Comments |
|---|---|---|---|---|---|---|
| Not applicable |
1) Stage: P - provisional, F - final.
2) Availability of the data: No, data are not available, Y: Yes, data are available + start year.
3) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
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.
13.1.1. Accuracy - Overall by 'Types of Error'
| Sampling errors | Non-sampling errors1) | Model-assumption Errors1) | Perceived direction of the error2) | |||
|---|---|---|---|---|---|---|
| Coverage errors | Measurement errors | Processing errors | Non response errors | |||
| non applicable | non applicable | non applicable | non applicable | non applicable | non applicable | |
1) Ranking of the type(s) of errors that result in over/under-estimation, from the most important source of error (1) to the least important source of error (5) In the event that errors of a particular type do not exist, is used the sign ‘-‘.
2) The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for GBARD.
13.1.2. Assessment of the accuracy
| Indicator | 5 (Very Good)1 | 4 (Good)2 | 3 (Satisfactory)3 | 2 (Poor)4 | 1 (Very poor)5 |
|---|---|---|---|---|---|
| GBARD | X | ||||
| National public funding to transnationally coordinated R&D | X |
1) High level of coverage (At least all national or federal ministries and the ministries and agencies responsible for R&D funding at state or regional level). High rate of response (>90%) in data collection. All figures broken down by NABS.
2) If at least one out of the three criteria above described would not be fully met.
3) In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.
4) In the event that the average rate of response would be lower than 70% and at least one of the two remaining criteria would not be met.
5) If all the three criteria above described are not met.
13.2. Sampling error
Not requested.
13.2.1. Sampling error - indicators
Not requested.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors 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.
a) Description/assessment of coverage errors:
Not applicable (census)
b) Measures taken to reduce their effect:
13.3.1.1. Over-coverage - rate
not applicable
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.
a) Description/assessment of measurement errors:
Not applicable
b) Measures taken to reduce their effect:
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
a) Problems in obtaining data from targeted information providers:
Not applicable (census)
b) Measures taken to reduce their effect:
c) Effect of non-response errors on the produced statistics:
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
Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.
a) Data processing and editing processes:
Not applicable
b) Description of errors:
c) Measures taken to reduce their effect:
13.3.5. Model assumption error
Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).
Description/assessment:
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
Date of first release of national data: T+2
14.1.2. Time lag - final result
Date of first release of national data: T+6
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) | 6 | 12 |
| Actual date of transmission of the data (T+x months) | 6 |
12 |
| Delay (days) | 0 | 0 |
| Reasoning for delay | NA | NA |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 995/2012 or Frascati manual paragraphs with recommendations about these concepts / issues.
| Concept / Issue | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Research and development | FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4). | No deviation | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | No deviation | |
| Socioeconomic objectives coverage and breakdown | Reg. 753/2004: Annex 1, section 2, §4 Reg. 995/2012: Annex 1, section 2, § 5.2. | No deviation | |
| Reference period | Reg. 995/2012: Annex 1, section 2, § 4. | No deviation |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Definition of GBARD | FM § 12.9 | GBARD includes all the budget appropriations for R&D of the federal government and indirect cantonal funds (GUF). It includes part of the direct cantonal funds (from the Higher Education Sector only) as well. The GBARD data comes from a R&D survey in the federal administration and from universities administrative data (GUF). |
|
| Stages of data collection | FM2015 §12.41 | No deviation | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation | |
| EU/other funds | Eurostat's Methodological Guidelines | ||
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation | |
| Current and capital expenditure | FM §12.15 | Since 1983, GBARD has included current and capital expenditure. Between 1977 and 1981, capital expenditure was excluded from the GBARD data. |
|
| Extra budgetary funds | FM §12.8, 12.20, 12.38 |
|
|
| Loans | FM §12.31, 12.32, 12.34 | Loans are not included in GBARD data. | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation | Indirect funding (federal and cantonal) is included. It is GUF. There are no tax rebates. Both indirect and direct federal funds are included in calculating GBARD. Indirect cantonal funds are included in calculating GBARD. Part only of direct cantonal funds are included in calculating GBARD. Data from 1977 to 1981 are not comparable with current data. They only concern direct federal funds (intramural, contracts and contributions) without the indirect funds allocated to higher education institutions (“hautes écoles”) under the law and without indirect cantonal funds. |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | No deviation | |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | No deviation | |
| Method of identification of primary objective | Eurostat's Methodological Guidelines, topic 2, statement B.6 | No deviation | |
| Inclusion/exclusion of VAT |
FM2015 does not provide with recommendations on this issue. | No deviation | VAT is not collected separately. |
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 | |
|---|---|---|---|
| Provisional data | Provisional data are only available since 2021 | ||
| Final data | 2017; 2014; 2012; 2000; 1998, 1992, 1989, 1986, 1983, 1981, 1977, | 2017: change in the methodology 2014: Little changes in methodology. 1998:- The Federal Office of Agriculture and its research institutes no longer classify their R&D 2000:Data are based on the ARAMIS information system (databank) and on electronic and paper questionnaires. 2012: Change in the method of estimation of R&D data in the Higher education Sector. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD data are higher than GOVERD, for GBARD also includes:
• GUF
• funds allocated for R&D that the performer does not necessarily spend that year or uses for something else (appropriations allocated to universities by the National Science Foundation that are not always spent in their entirety).
• extramural expenditures (mandates and contributions in Switzerland and abroad).
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Not requested.
15.4. Coherence - internal
This part compares GBARD statistics from the provisional and final budget for the reference year.
15.4.1. Comparison between provisional and final data according to NABS 2007
| R&D appropriations in the provisional budget delivered at T+6 | R&D appropriations in the final budget delivered at T+12 | Difference (of final data) | |
|---|---|---|---|
| Exploration and exploitation of the Earth | 22.95 | 23.03 | 0.08 |
| Environment | 26.16 | 26.25 | 0.09 |
| Exploration and exploitation of space | 233.04 | 233.84 | 0.80 |
| Transport, telecommunication and other infrastructures | 16.83 | 16.88 | 0.06 |
| Energy | 61.23 | 61.44 | 0.21 |
| Industrial production and technology | 413.42 | 414.84 | 1.43 |
| Health | 18.34 | 18.40 | 0.06 |
| Agriculture | 198.21 | 198.89 | 0.68 |
| Education | 17.21 | 17.26 | 0.06 |
| Culture, recreation, religion and mass media | 2.64 | 2.65 | 0.01 |
| Political and social systems, structures and processes | 396.70 | 398.07 | 1.37 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 4680.38 | 4680.38 | 0.00 |
| General advancement of knowledge: R&D financed from other sources than GUF | 1715.04 | 1710.07 | -4.97 |
| Defence | 35.27 | 35.39 | 0.12 |
| TOTAL GBARD | 7837.41 | 7837.41 | 0.00 |
In million national currency
| 23 |
| 26 |
| 233 |
| 17 |
| 61 |
| 413 |
| 18 |
| 198 |
| 17 |
| 3 |
| 397 |
| 4 680 |
| 1 715 |
| 35 |
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 | non-available | |
| Data collection costs | non-available | |
| Other costs | non-available | |
| Total costs | non-available | |
| Comments on costs | ||
| non-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.
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | No direct burden on respondent | |
| Average Time required to complete the questionnaire in hours (T)1 | Not applicable | |
| 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
There is no data revision policy for GBARD
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: State Budget (estimated initial budget from offices)
b) Final data: Provisional data + Administrative data of public institution budget (higher education)
c) General University Funds (GUF): State Budget + Administrative data of public institution budget (higher education)
18.2. Frequency of data collection
See 12.3.3.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | Federal budget analyses since 2017 | Federal budget analyses since 2017 | All federal departments and offices. |
| Stage of data collection | |||
| Reporting units | The institution responsible for administering the budget -- each federal department, office and institution. | The institution responsible for administering the budget -- each federal department, office and institution. | |
| Basic variable | |||
| Time of data collection (T+x)1) | T+6 | T+12 | |
| Problems in the translation of budget items | N/A | ||
1) Time of data collection (T+x): T is assumed to represent the end of reference period. x expresses the number of months after (positive) or before (negative) T when data is collected.
18.3.2. General University Funds (GUF)
The data comes from administrative data of the Higher Education Sector.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | The unit is the project. Since 2000, data have been compiled via the ARAMIS system (electronic information system on R&D research projects of the federal government). The reporting units (institutions) are the Federal offices and departments. The institutions report their R&D projects in ARAMIS and in a R&D questionnaire. |
|---|---|
| Criterion of distribution – purpose or content | Distribution into objectives is made according to the purpose of the programmes or projects. |
| Method of identification of primary objectives | Not applicable |
| Difficulties of distribution | No special difficulties. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | |
| GBARD national questionnaire and explanatory notes in the national language: | No questionnaire for the GBARD |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: | FR: Crédits budgétaires publics de R-D - Mesurer le financement public de la R-D à partir des données tirées des budgets | Publication |
18.4. Data validation
- Outlier detection (early in the process)
- Checking the population coverage
- Investigating inconsistencies in the statistics.
- Benchmark the responses with the responses of the previous year;
18.5. Data compilation
See below.
18.5.1. Imputation - rate
No imputation was performed, Budget analysis
18.5.2. Data compilation methods
See below.
18.5.2.1. Identifying R&D
| Method(s) of separating R&D from non-R&D | The reporting unit is provided with the Frascati Manual definition of R&D and is separating itself R&D from non R&D in the projects. |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | Not applicable |
| Frequency of updating of coefficients | Not applicable |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | Not applicable |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | Not applicable |
| Frequency of updating of coefficients | Not applicable |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | Multi-annual programmes are not reported in a single year -- they are allocated to the years in which they are budgeted. |
|---|---|
| Possibility to classify budgetary items by COFOG functions | Not applicable |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Not applicable |
| Method of estimation of future budgets | Not applicable |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
Explanation on the large fluctuations of the transnationally coordinated programs
Switzerland was an associated country with the EU for the frameworkprogramms until 2020. After that date Switzerland became non-associated and is considered as a ‘third country’. Compensatory measures have been taken by Switzerland to replace the funds for the EU. These transitional measures enable direct funding of Swiss researchers taking part in transnational projects under the European Framework Programme.
The major fluctuations for Switzerland in programmes coordinated at transnational level are due to the structure of funding during this transitional period.
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and experimental development (R&D) activities, and thereby provide information about the priority Governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content (FM 2015, Chapter 12).
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.
Statistics on science, technology and innovation were collected based on Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 1197/2020 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.
11 September 2025
Not requested.
Budget of federal offices financing or executing R&D
See below.
Not requested.
a) Calendar year: Reference year
b) Fiscal year: -
Start month: 1 January 2023
End month: 31 December 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.
Not requested.
See below.
a) Provisional data: State Budget (estimated initial budget from offices)
b) Final data: Provisional data + Administrative data of public institution budget (higher education)
c) General University Funds (GUF): State Budget + Administrative data of public institution budget (higher education)
The collection of GBARD data is conducted and disseminated on an yearly basis
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.
