1.1. Contact organisation
Ministry for Higher Education, Research and Space (MESRE)
1.2. Contact organisation unit
SIES - Sub-Directorate for Information Systems and Statistical Studies
Department of statistical studies on research
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Ministère de l’enseignement supérieur, de la recherche et de l'espace
DGESIP/DGRI – SIES – Département des études statistiques de la recherche
1 rue Descartes, 75231 Paris Cedex 05
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
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 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 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 (Commission Implementing Regulation (EU) 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 (europa.eu)).
Please note that according to Article 12(4) of Regulation (EU) 1197/2020, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.
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 | The national SEO classification is more detaited than NABS classification. Most of the NABS categories can be rebuilt by aggregating national SEO categories, except for chapters number 12 and 13 for which we use coefficients to share between GUF funds and other sources than GUF. |
|---|---|
| Correspondence table with NABS | We have such a table. |
3.2.2. NABS classification
| Deviations from NABS | We try to stay as close as possible to the NABS. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | For chapters number 12 and 13, we use coefficients to share between GUF funds and other sources than GUF. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | We are able to distribute chapters number 12 and 13 by fields of R&D. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | The definition used for R&D is compliant with the definition in the Frascati Manual. |
|---|---|
| Coverage of R&D or S&T in general | GBARD statistics cover all government bodies allocating R&D. |
| Fields of R&D (FORD) covered | All fields are covered. |
| Socioeconomic objective (SEO by NABS) | All categories of NABS are covered. |
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 Ministry in charge of research and higher education, other central government bodies, public research institutes and several medical research foundations are included in the definition. This is justified by the fact that they are funded from the civilian R&D budget. | Included | |
| Regional (state) government | Not applicable. | Not included | |
| Local (municipal) government | For France, it is : regions, departments, community of municipalities, municipalities. | Not included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Government bodies.
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 | All gouvernment bodies allocating R&D. |
|---|---|
| Estimation of the target population size | 70 |
3.7. Reference area
France.
3.8. Coverage - Time
Calendar year : January to December 2023
3.9. Base period
Not requested.
Thousand of euros.
Reference year 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, GBARD statistics are 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
Not applicable.
6.1.3. Standards and manuals
Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development.
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:
Not applicable.
b) Confidentiality commitments of survey staff:
Not applicable.
7.2. Confidentiality - data treatment
No restriction on broadcasting.
8.1. Release calendar
National results : June N.
8.2. Release calendar access
8.3. Release policy - user access
- Official calendar
- Publications
- Press releases
- Users are treated according to the national statistical system rules, i.e. all users have access to the information at the same time.
Yearly
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 | Regular Release GBARD Data 2023 |
| Ad-hoc releases | Y | Socio-Economic Objectives for GBARD
|
1) Y - Yes, N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
|---|---|---|
| General publication/article (paper, online) |
Y | |
| Specific paper publication (paper, online) |
Y | Socio-Economic Objective Publication n°16 |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Not requested.
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 microdata published. |
|---|---|
| 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 | Agregate figures | Ministry website : Publication Enseignements Recherche Gouv |
| Data prepared for individual ad hoc requests | Y | Micro-data / Aggregate figures | Specific requests from government bodies. |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Survey on the GBARD Indicators
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.) | Guidelines of the questionnaire. |
|---|---|
| Request on further clarification | If necessary, we answer specificals requests from government bodies. |
| Measure to increase clarity | Guidelines are updated every year. |
| Impression of users on the clarity of the accompanying information to the data | Good impression. |
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 | OCDE, Eurostat | Database |
| 1 | Ministries | National data |
| 3 | Media | Disseminated data |
| 6 | Governement bodies (Cour des comptes, inspections générales de l'administration, des finances ou de l'éducation nationale) | Specific questions |
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 survey conducted |
|---|---|
| User satisfaction survey specific for GBARD statistics | No survey conducted |
| Short description of the feedback received | Not available. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
82 %
12.3.2. Completeness - overview
Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.
| 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 |
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 | Yearly | None | T | |
| NABS Chapter level | Y | Yearly | None | T | |
| NABS Sub-chapter level | Y | Yearly | None | T | |
| Special categories - Biotech | Y | Yearly | None | T | |
| Special categories - Nanotech | Y | Yearly | None | T | |
| Special categories - Security | Y | Yearly | None | T |
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 | Yearly | None | T | |
| NABS Chapter level | Y | Yearly | None | T | |
| NABS Sub-chapter level | Y | Yearly | None | T | |
| Special categories - Biotech | Y | Yearly | None | T | |
| Special categories - Nanotech | Y | Yearly | None | T | |
| Special categories - Security | Y | Yearly | None | T |
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 |
|---|---|---|---|---|---|---|
| None |
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:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
13.1.1. Accuracy - Overall by 'Types of Error'
| Sampling errors | Non-sampling errors1) | Model-assumption Errors1) | Perceived direction of the error2) | |||
|---|---|---|---|---|---|---|
| Coverage errors | Measurement errors | Processing errors | Non response errors | |||
| - | 2 | - | 1 | - | - | |
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
| Indicators | 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 |
- 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.
- If at least one out of the three criteria described above would not be fully met.
- In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.
- 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.
- If all the three criteria described above 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:
Very high rate of coverage.
b) Measures taken to reduce their effect:
Not applicable
13.3.1.1. Over-coverage - rate
Magnitude of error (%) = (Observed Value-True Value)/ True Value (%)
Near 0% of coverage error.
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:
Some government bodies have difficulties to assess budget credits by SEO.
b) Measures taken to reduce their effect:
Exchanges with government bodies to help them.
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:
A few public bodies don't answer the questionary.
b) Measures taken to reduce their effect:
Follow-up, calls and explanations about the importance of the survey and the results.
c) Effect of non-response errors on the produced statistics:
If non response for a governement body unit, its total credit budget is imputed with budgetary documents and the breakdown by SEO is estmated with the structure of the previous year response.
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:
Not applicable
c) Measures taken to reduce their effect:
Not applicable
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:
Not applicable
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 : September 2023.
14.1.2. Time lag - final result
Date of first release of national data: September 2023.
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 |
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 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics 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 | No local data |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No deviation | Since 2010, the Defense objective has been subdivided between Defense and Global Security: 1) Defense and defense strategies, science, technology and arms economies 2) Internal security, civil security, economic security |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | 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 | No deviation | GBARD covers the civilian R&D budget (with a few adjustments), appropriations for higher education research and for the R&D appropriations of the Defense's Ministry. |
| Stages of data collection | FM2015 §12.41 | No deviation | Budget appropriations before Parliament vote. There is no new investigation at the end of the budget year |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation | Resources from other sectors are not included. |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No deviation | EU funds are not included. Similarly, France’s participation in funding the R&D Framework Programme is not included in these budget appropriations, although it is included in calculating national R&D expenditure. |
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation | |
| Current and capital expenditure | FM §12.15 | No deviation | Both current and capital expenditure are included in GBARD. |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | No deviation | Extra budgetary funds are not included. Only resources included in the State budget are taken into account. |
| Loans | FM §12.31, 12.32, 12.34 | No deviation | No distinction is made in the treatment of non-repayable and repayable subsidies. |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation | Tax credits are not included. |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | No deviation | GBARD includes government-financed R&D performed abroad. |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | No deviation | |
| Method of identification of primary objective | Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6 | No deviation |
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 | 7 years | 2001 and 1997, 1992 and 1991, 1983, 2006, 2016 | 2001 and 1997: there were breaks in the series due to changes in the method of evaluating defence appropriations, which are included entirely in the objective “Defence”. 1992 and 1991: firstly, there was a change in methodology. The data are now based on a survey on socio-economic objectives sent to the agencies and ministries administering the civilian R&D budget, but also to subsidiary agencies. Secondly, the legal status of France Télécom and GIAT industries has changed, since they have left the government sector for the private sector. 1983: following adoption of the NABS 1983, there was a break in the Defence objective. 2006: implementation of the Constitutional Bylaw on Budget Acts: applied to the central government budget with a new framework of presentation for expenditures by public policies. These policies are translated into missions and programmes. 2016 : new classification The budget appropriations for R & D gathered in the "Mission Research and Higher Education" (MIRES). From that date, the remuneration of teachers and researchers for their research activity is now integrated in the R & D budget appropriations. |
| Final data | 7 years | 2001 and 1997, 1992 and 1991, 1983, 2006, 2016 | 2001 and 1997: there were breaks in the series due to changes in the method of evaluating defence appropriations, which are included entirely in the objective “Defence”. 1992 and 1991: firstly, there was a change in methodology. The data are now based on a survey on socio-economic objectives sent to the agencies and ministries administering the civilian R&D budget, but also to subsidiary agencies. Secondly, the legal status of France Télécom and GIAT industries has changed, since they have left the government sector for the private sector. 1983: following adoption of the NABS 1983, there was a break in the Defence objective. 2006: implementation of the Constitutional Bylaw on Budget Acts: applied to the central government budget with a new framework of presentation for expenditures by public policies. These policies are translated into missions and programmes. 2016 : new classification The budget appropriations for R & D gathered in the "Mission Research and Higher Education" (MIRES). From that date, the remuneration of teachers and researchers for their research activity is now integrated in the R & D budget appropriations. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
This part deals with any national coherence assessments which may have been undertaken.
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 allocations in the provisional budget delivered at T+6 | R&D allocations in the final budget delivered at T+12 | Difference (of final data) | |
|---|---|---|---|
| Exploration and exploitation of the Earth | 211280 | 211280 | 0 |
| Environment | 316033 | 316033 | 0 |
| Exploration and exploitation of space | 2284326 | 2284326 | 0 |
| Transport, telecommunication and other infrastructures | 829133 | 829133 | 0 |
| Energy | 2017222 | 2017222 | 0 |
| Industrial production and technology | 161523 | 161523 | 0 |
| Health | 900111 | 900111 | 0 |
| Agriculture | 492499 | 492499 | 0 |
| Education | 31407 | 31407 | 0 |
| Culture, recreation, religion and mass media | 187012 | 187012 | 0 |
| Political and social systems, structures and processes | 29293 | 29293 | 0 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 4790160 | 4790160 | 0 |
| General advancement of knowledge: R&D financed from other sources than GUF | 4459217 | 4459217 | 0 |
| Defence | 1556523 | 1556523 | 0 |
| TOTAL GBARD | 18265740 | 18265740 | 0 |
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 | 83160 | 0% |
| Data collection costs | 0% | |
| Other costs | 14041 | 0% |
| Total costs | 97201 | 0% |
| Comments on costs | ||
| There is no cost calculation. | ||
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) | 70 | |
| Average Time required to complete the questionnaire in hours (T)1 | Not available. | |
| Average hourly cost (in national currency) of a respondent (C) | Not available. | |
| Total cost |
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
- Provisional data: Budgetary documents analysis and census survey (Mires survey).
- Final data: Budgetary documents analysis and census survey (Mires survey).
- General University Funds (GUF): Budgetary documents analysis and census survey (Mires survey).
18.2. Frequency of data collection
Yearly
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | Budgetary documents analysis and census survey through questionnaires | Budgetary documents analysis and census survey through questionnaires | |
| Stage of data collection | Initial budget allocations (figures as voted by the parliament for the coming year, including changes introduced in the parliamentary debate) : stage 4 of Frascati manual 12.41 | Initial budget allocations (figures as voted by the parliament for the coming year, including changes introduced in the parliamentary debate) : stage 4 of Frascati manual 12.41 | |
| Reporting units | The organization that implements the budget and the institution funding | The organization that implements the budget and the institution funding | |
| Basic variable | Budget allocation | Budget allocation | |
| Time of data collection (T+x)1) | In year n, we work on the budget of year n, 6 months after the beginning of its implementation.
|
In year n, we work on the budget of year n, 6 months after the beginning of its implementation.
|
|
| Problems in the translation of budget items | No specific problem identified | ||
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)
For chapters number 12 and 13, we use coefficients to share between GUF funds and other sources than GUF.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Both methods are used (SEO distribution obtained by institution or by programme/project), the choice is left to the reporting organization. |
|---|---|
| Criterion of distribution – purpose or content | It is difficult to know the method used by respondents. This is the reason why the beakdown by funding mode cannot be provided. |
| Method of identification of primary objectives | Guidelines are given to the respondents. |
| Difficulties of distribution | Yes for a few bodies. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | N |
| GBARD national questionnaire and explanatory notes in the national language: | GBARD National Survey |
| Other relevant documentation of national methodology in English: | N |
| Other relevant documentation of national methodology in the national language: | N |
18.4. Data validation
Controling with the finance bill.
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.
Credit budget are imputed with budgetary documents.
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 accuracy of our national CEO classification is sufficient to separate R&D from non R&D in most cases. |
|---|---|
| Description of the use of the coefficient (if applicable) | Not available |
| Coefficient estimation method | Not available |
| Frequency of updating of coefficients | Not available |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | The accuracy of our national CEO classification is sufficient to separate R&D from non R&D in most cases. |
|---|---|
| Description of the use of the coefficient (if applicable) | Not available |
| Coefficient estimation method | Not available |
| Frequency of updating of coefficients | Not available |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | Not available |
|---|---|
| Possibility to classify budgetary items by COFOG functions | No, as far as we know, this work has never been undertaken. |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Not available |
| Method of estimation of future budgets | We work only on the current year. |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comment.
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 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 (Commission Implementing Regulation (EU) 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 (europa.eu)).
Please note that according to Article 12(4) of Regulation (EU) 1197/2020, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.
31 October 2025
Not requested.
Government bodies.
See below.
France.
Reference year 2023.
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
- Coverage errors,
- Measurement errors,
- Non response errors and
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
Thousand of euros.
See below.
- Provisional data: Budgetary documents analysis and census survey (Mires survey).
- Final data: Budgetary documents analysis and census survey (Mires survey).
- General University Funds (GUF): Budgetary documents analysis and census survey (Mires survey).
Yearly
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.
