1.1. Contact organisation
Rathenau Instituut
1.2. Contact organisation unit
Onderzoek en Dialoog, Programma Werking van de wetenschap in Nederland
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Rathenau Instituut
Postbus 95366
2509 CJ Den Haag
The Netherlands
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
12 January 2026
3.1. Data description
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and 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.
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 (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (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)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
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 | Not applicable |
|---|---|
| Correspondence table with NABS | NABS is used to classify socio-economic objectives for GBARD |
3.2.2. NABS classification
| Deviations from NABS | Not applicable |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | All expenditure is classified by NABS chapters and sub-chapters. Repondents at the departments are asked to indicate how the expenditure in the programmes and projects is divided over NABS categories. In some cases, estimates have been used in order to classify the expenditure. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Research organisations providing none-oriented research are asked to indicate how their funding is divided over NABS 13 sub categories. A small part of the research cannot be divided over the NABS 13 sub categories. This part is ultimately divided, based on the available division within NABS 13. GUF is divided by NABS 12 sub categories, using the percentage-division of funds in the aggregate talent programme's of the National scientific research funding agency. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Research and development (R&D) includes systematically performed, creative activities, based on scientific methods and aims to increase knowledge, including knowledge of humans, culture and society, and on developing new applications based on available knowledge or improving existing applications. Characteristic of R&D is the element of originality or innovation in the research. R&D activities must therefore meet five criteria: novelty, creativity, uncertainty, systematic and repeatable. |
|---|---|
| Coverage of R&D or S&T in general | Good |
| Fields of R&D (FORD) covered | All |
| Socioeconomic objective (SEO by NABS) | 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 | Rijksoverheid: National government | Included | National ministries / departments |
| Regional (state) government | Provinces | Not included | Contribution to R&D funding is less than 3% |
| Local (municipal) government | Municipalities | Not included | Contribution to R&D funding expected to be marginal |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
National government departments
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 | National government departments |
|---|---|
| Estimation of the target population size |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested. All calculations of non-basic unit (national currencies) are done by Eurostat.
Not requested.
Calendar year: 2023 (final expenditure).
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
Since the beginning of 2021, GBARD statistics are based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. GBARD statistics were based until the end of 2020 on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
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.
- 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.
- Confidentiality protection required by law: not applicable.
- Confidentiality commitments of survey staff: not applicable.
7.2. Confidentiality - data treatment
Not applicable.
8.1. Release calendar
Data are provided to Eurostat by 31 December every year: final expenditure for year t-1 and provisional expenditure for year t. As well as multi-annual forecast for the years t+1, t+2, t+3 and t+4
Publication of the data and a report is offered to the National Parliament in April every year.
8.2. Release calendar access
Not publicly available.
8.3. Release policy - user access
The data are published open access on www.rathenau.nl and by a mailing to inform users about the release is sent out to all known potential users of the data as well as national parliament.
Annual dissemination and publication, in Dutch only.
TWIN 2023-2029 | Rathenau Instituut
An English version of the report and the data file can be made accessible if requested.
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 | Totale investeringen in wetenschap en innovatie (TWIN) 2021-2027 - Revisie | Rathenau Instituut |
| Ad-hoc releases | Y | in case of updates or specific factsheets |
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 | Total Expenditure in R&D Data by the Rathenau Institut |
| Specific paper publication (paper, online) |
Y | Total Expenditure in R&D Data by the Rathenau Instituut |
1) Y – Yes, N - No
10.3. Dissemination format - online database
See below.
10.3.1. Data tables - consultations
Not requested.
Total Expenditure in R&D Data by the Rathenau Instituut
Totaaloverzicht (XLSX file)
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | The data are open access available in XLSX format |
|---|---|
| Access cost policy | no costs involved |
| Micro-data anonymisation rules | Micro-data per department are presented at programme level |
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 | Micro-data and aggregate figures | GBARD data |
| Data prepared for individual ad hoc requests | Y | Micro-data and aggregate figures | On request. Prepared data and results are thereafter published open access. |
| Other | Y | Data are used in graphs and figures in various other publications of the Rathenau Institute | See also: Science in figures by the Rathenau Institut |
1) Y – Yes, N - No
10.6. Documentation on methodology
See below.
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.) | Metadata, methodological explanation, graphs etc. all in report |
|---|---|
| Request on further clarification | Sometimes we receive requests for further clarification, for example on how to work with the data and what are similarities and differences between R&D expenditure data and GBARD data |
| Measure to increase clarity | We provide additional explanatory texts in report whenever we receive request for clarification. |
| Impression of users on the clarity of the accompanying information to the data | The feedback that we receive is that the data and the report are highly valued by users |
11.1. Quality assurance
Researchers working in the unit on GBARD statistics are specialised in quantitative data management and analysis, at minimum MA / MSc level.
Researchers working with the GBARD data receive training and support by the programma coordinator as required.
Researchers always work in couples on the GBARD project.
We have recently introduced extra attention to the 'four eyes' principle at the departments delivering the data.
11.2. Quality management - assessment
We make use of a guideline (TWIN-Handleiding) for data collection, checks and analyses.
We do several checks on the data: historical and internal consistency, checks with new policy announcements, coalition agreements, etc.
We compare with matching government R&D expenditure based on data from R&D performers perspective, from the national statistics bureau.
If in doubt, we contact the delivering departments to double check and provide clarification.
We send out reminders to ensure full coverage and response rates from all participating departments and if needed, we do a follow up with telephone calls and additional reminders.
During and after data processing, we do cross-checks of aggregates and sub-totals, and spotchecks to validate the data.
The data and report are checked by supervisor before publication. The report and data within are checked by two collegues and the chief scientist of the institute, as well as by three external peers from three different relevant government departments.
Compliance is monitored by the unit supervisor (coordinator), who has over 10 years working experience on the GBARD project in the Netherlands.
Every year after publication of the data en the report, the GBARD project subject to an internal evaluation in order to improve the process and quality if and where possible. Enhanced political interest in the data and report increasinly ensure that we and the officials at the data delivering departments are aware of the importance of correctness of the data.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| Institutions | European Commission and Parliament. OECD | Overview of realised and planned R&D investments by government, in time series by department and NABS and in relation to gdp. OECD, UNESCO: data delivery |
| Institutions | National and regional and National Statistics bureau (CBS) | Realised and planned R&D investments by government, in time series by department and NABS and in relation to gdp. CBS: cross check on GUF and government R&D expenditure for HE sector. |
| Social actors | Unions of the universities (UNL), university medical centres (UMCNL) and universities of applied sciences (VH), TO2-institutes and 4-TU federation, Platform Beta Techniek, RKI-Netwerk, CAOP. Also individual institutes (eg. WUR, TNO). | Overview of realised and planned R&D investments by government, in time series by department and NABS and in relation to gdp, but also government R&D expenditure by type of research performing institute. Monitoring progress towards ambition 3% R&D as percentage of GDP. Also: use of microdata. |
| Media, researchers and students | Various requests | Press release, interviews, presentations and workshops about the findings, results and implications, micro-data and guidance on appropriate use. |
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 | Every 5 years, an evaluation of the institute is being done, where stakeholders are specifically asked what units and types of work of the institute they are familiar with and how they would assess the quality of the work. |
|---|---|
| User satisfaction survey specific for GBARD statistics | We present the GBARD data and main findings of the report to users at government departments, parliamentarians and other users and get immediate feedback about user satisfaction and potential to improve the data and reporting. |
| Short description of the feedback received | The feedback received from users is generally very positive and they seem to be satisfied. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Data are as complete as possible.
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 2000 - 2024 | Annual | none | T+6 | |
| NABS Chapter level | Y 2000 - 2024 | Annual | none | T+6 | |
| NABS Sub-chapter level | Y 2000 - 2024 | Annual | none | T+6 | |
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | N |
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 1999 - 2023 | Annual | none | T+18 | |
| NABS Chapter level | Y 1999 - 2023 | Annual | none | T+18 | |
| NABS Sub-chapter level | Y 1999 - 2023 | Annual | none | T+18 | |
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | N |
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 |
|---|---|---|---|---|---|---|
| Budget | P | Y 2001 - 2025 | Annual | none | T | |
| Multi-annual budget forecast | P | Y 2002 - 2026 | Annual | none | T-12 | |
| Multi-annual budget forecast | P | Y 2003 - 2027 | Annual | none | T-24 | |
| Multi-annual budget forecast | P | Y 2004 - 2028 | Annual | none | T-36 | |
| Multi-annual budget forecast | P | Y 2005 - 2029 | Annual | none | T-48 | |
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 | |||
| - | - | - | x | - | Underestimation | |
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 |
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 described above 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 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:
The total target population is included in the sample.
Only exception is the ministry of finance.
b) Measures taken to reduce their effect:
The ministry has been approached to discuss their potential participation. The ministry does not participate as they expect the contribution of the ministry to R&D expenditure is marginal. We will contact the ministry again in the near future to discuss if the situation may have changed.
13.3.1.1. Over-coverage - rate
There is no over-coverage
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:
It is not always easy for the officials at the ministries to estimate the expected expenditure on R&D in programmes with mixed activitities (e.g. where R&D is not the only activity taking place within the programme, and is combined with other activities, such as innovation activities without an R&D component or government service delivery activities, etc. The same applies to the allocation of programmes or expenditure within programmes to specific NABS codes, especially where multiple socio-economic objectives are pursued with or within a programme.
b) Measures taken to reduce their effect:
Together with the GBARD questionnaire, a Guideline (Handleiding) is sent to the respondents at the ministries who are supposed to collect the data. In addition, we offer guidance and support whenever officials feel they want to ask or discuss issues related to the data collection or allocation with the coordinator, who has over 10 years of experience with GBARD data. We contact and/or organise meetings with departments where a shortcoming or mistake in the data is suspected in order to correct and/or prevent errors and to be able to provide proper explanations.
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.
- Problems in obtaining data from targeted information providers: Data are sometimes delivered after our deadline, but generally, we still manage to get all the data from all the population units just in time to complete our analysis and data delivery to Eurostat in time.
- Measures taken to reduce their effect: We mail and call to follow-up our data request.
- Effect of non-response errors on the produced statistics: One ministry has indicated not to participate in the data delivery as they expect their contribution to R&D to be negligible. All other ministries participate and generally do deliver the requested data.
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.
- Data processing and editing processes:
Data entry by the contactpersons at the departments is done in the same format as the analysis, which limits errors. Imputation is kept to a minimum as the departments are requested to fill in the R&D expenditure for all the years (t-1, t, t+1, t+2...upto t+5) that programmes are running.
The coefficient for GUF is ideally based on the (year closest to the) final expenditure year (t-1). This coefficient is then also applied to the preliminary expenditure in (t) and the budget year (t+1).
This may also apply to the percentage of programmes which is expected to be spent on R&D.
- Description of errors:
It may occur that the coefficient based on year (t) leads to a small over- or under-estimation in the preliminary data (t), budget data (t+1) and multi-annual forecasts.
The R&D-expenditure in a number of programmes is based on a judgement by the departmental respondents about the expected expenditure on R&D within the programme in the final year (t-1). This perentage is then mostly also applied to the consequetive years.
- Measures taken to reduce their effect:
Mostly, the change in the coefficient between two consequetive years is rather small. Over the period between 1999 and 2023, the difference in the coeffcient between two consequetive years has on average been less than 3%. By using the coefficient closest to the final realisation year, the data for the final expenditure are as close to realisation as possible.
The data for t, t+1 and later years are corrected before they become final, based on the coefficient that has been calculated for that specific year. This also applies to the percentage of the programme funding which is spent on R&D.
The National statistics bureau and the bodies representing the universities, umc's and universities of applied sciences are currently working on improving the research coefficients.
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: T+6 (June 2025).
14.1.2. Time lag - final result
Date of first release of national data: T+12 (June 2025).
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)
The actual data release has been punctual.
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) | 0 | 12 |
| Delay (days) | 0 | 0 |
| Reasoning for delay | no delay | no 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 | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | no deviation | |
| 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 | |
| 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 EBS Methodological Manual on R&D Statistics | no deviation | |
| Types of expenditure | FM2015 §12.15 to 12.18 | no deviation | |
| Current and capital expenditure | FM §12.15 | no deviation | |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | no deviation | |
| Loans | FM §12.31, 12.32, 12.34 | no deviation | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | no deviation | |
| 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 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 | 2000 - 2022 | none | |
| Final data | 1999 - 2021 | none |
1) Break years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
See below.
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.
The differences beteen de provisional en final 2023 GBARD data (table 15.4.1) are larger than the differences in previous years. This is mainly due to shifts in cash flows, including for projects from the large National Growth Fund (Nationaal Groeifonds) and for instruments within the Future Fund (Toekomstfonds). As a result, some of the funds designated for 2023 were not spent in that year. These have been carried over to 2024 and later years, increasing the figures for those years.
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 | 94.774,841 | 91.669,313 | -3.105,528 |
| Environment | 160.108,157 | 128.764,729 | -31.343,428 |
| Exploration and exploitation of space | 172.269,122 | 173.005,640 | 736,518 |
| Transport, telecommunication and other infrastructures | 246.933,717 | 129.888,966 | -117.044,751 |
| Energy | 378.936,768 | 224.484,357 | -154.452,411 |
| Industrial production and technology | 767.608,248 | 431.550,367 | -336.057,881 |
| Health | 649.670,935 | 682.844,193 | 33.173,258 |
| Agriculture | 439.321,888 | 420.738,905 | -18.582,983 |
| Education | 58.232,771 | 74.610,922 | 16.378,151 |
| Culture, recreation, religion and mass media | 15.505,639 | 23.350,173 | 7.844,534 |
| Political and social systems, structures and processes | 96.670,887 | 107.882,721 | 11.211,834 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 4.225.434,522 | 4.323.170,618 | 97.736,096 |
| General advancement of knowledge: R&D financed from other sources than GUF | 1.526.052,387 | 1.475.490,820 | -50.561,567 |
| Defence | 261.132,024 | 244.574,941 | -16.557,083 |
| TOTAL GBARD | 9.092.651,906 | 8.532.026,665 | -560.625,241 |
The assessment of costs associated with a statistical product is a rather complicated task since there must exist a mechanism for appointing portions of shared costs (for instance shared IT resources and dissemination channels) and overheads (office space, utility bills etc). The assessment must become detailed and clear enough so that international comparisons among agencies of different structures are feasible.
16.1. Costs summary
| Costs for the statistical authority (in national currency) | % sub-contracted1) | |
|---|---|---|
| Staff costs | not specified | None |
| Data collection costs | not specified | None |
| Other costs | not specified | None |
| Total costs | not specified | None |
| Comments on costs | ||
| Costs on producing GBARD are not separately 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) | 13 National government department contact points | |
| Average Time required to complete the questionnaire in hours (T)1 | not available | |
| Average hourly cost (in national currency) of a respondent (C) | EUR 117 | Average (Senior) Policy Advisor level, excl. VAT Handleiding Overheidstarieven 2025 | Kennisbank Openbaar Bestuur |
| Total cost | not available |
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
Data are revised only in case we are informed of substantial changes in the realised expenditure data due to changes in one of the coefficients, which affect the amount or distribution of the funding.
17.2. Data revision - practice
Currently the National statistics bureau and the representing bodies for the universities, universities of applied sciences and university medical centres are working on improvements to the research coefficients used to determine the research expenditure in these higher education institutions. The resulting new coefficients will be applied to the data, starting from the 2024 final GBARD data onwards.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
- Provisional data: Survey amongst officials at the ministries, based on the provisional expenditure figures in the latest National budget presented to parliament.
- Final data: Survey amongst officials at the ministries, based on the final expenditure figures in the latest National budget presented to parliament.
- General University Funds (GUF): Survey amongst officials at the ministries, based on the final expenditure figures in the latest National budget presented to parliament combined with research coefficient. The research coefficient is annually calculated by the National Statistics Bureau (CBS), which is based on the number of research fte divided by the total academic personnel fte (most recent realisation year). The research coefficient is currently under revision for improvement, see under 17.
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 | Survey and coefficients | Survey and coefficients | |
| Stage of data collection | Initial budget appropriations | Final budget appropriations | |
| Reporting units | Ministries | Ministries | |
| Basic variable | Allocations | Allocations | The difference between these variables is difficult to translate |
| Time of data collection (T+x)1) | T | T+8 | |
| Problems in the translation of budget items | |||
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)
A research coefficient is used to determine the share of the national government contribition to the universities that is spent on research. This coefficient is calculated every year for the final year based on research fte divided by total academic fte, by our National Statistics Bureau (CBS).
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Programme |
|---|---|
| Criterion of distribution – purpose or content | Mainly purpose (objective) |
| Method of identification of primary objectives | Annual survey amongst government officials |
| Difficulties of distribution | Sometimes, programmes contribute to multiple objectives. In such cases, the R&D expenditure of the programme s divided over the respective SEO's / NABS codes |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | not available |
| GBARD national questionnaire and explanatory notes in the national language: | URL below: TWIN Questionnaire format |
| Other relevant documentation of national methodology in English: | not available |
| Other relevant documentation of national methodology in the national language: | URL below: TWIN Handleiding |
Annexes:
TWIN Questionnaire 2023-2029
TWIN Manual aug. 2024
Letter accompanying request for GBARD data based on 2025 Budget
18.4. Data validation
Annually, the programme coordinator checks that 100% of the ministries that are expected to deliver the data, are mailed with the data request, together with a letter, the questionnaire format and the manual for data collection (Handleiding). The ministries are being e-mailed with reminders and if necessary this is followed up by telephone calls, to ensure data delivery as requested. We do macro edits as well as mirco edits and always compare the statistics with the previous year's data collected for all the years for which such comparative data are available. In case of large or unexpected deviations from data for previous years, we contact the relevant ministries for eplanations. Where possible, we compare the resulting GBARD data against data from our National Statistics Bureau based on the survey of R&D-performers. We also look at external policy documents and coalition agreement documents. Any apparent inconsistencies in the statistics are further investigated and we may request the officials in the department to look into apparent inconsistencies as well. We are also offering guidance and support in case officials reponsible for the data collection have questions or ask for our advise.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
No imputation is done.
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 | We use a coefficient to distinguish R&D expenditure within GUF from other expenditure. |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | The coefficient is based on research fte divided by total academic fte. |
| Frequency of updating of coefficients | Annually |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | See 18.5.2.1 |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | |
| Frequency of updating of coefficients |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | n/a |
|---|---|
| Possibility to classify budgetary items by COFOG functions | n/a |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | n/a |
| Method of estimation of future budgets | n/a |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comments.
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and 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.
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 (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (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)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
12 January 2026
Not requested.
National government departments
See below.
Not requested.
Calendar year: 2023 (final expenditure).
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.
Not requested.
See below.
- Provisional data: Survey amongst officials at the ministries, based on the provisional expenditure figures in the latest National budget presented to parliament.
- Final data: Survey amongst officials at the ministries, based on the final expenditure figures in the latest National budget presented to parliament.
- General University Funds (GUF): Survey amongst officials at the ministries, based on the final expenditure figures in the latest National budget presented to parliament combined with research coefficient. The research coefficient is annually calculated by the National Statistics Bureau (CBS), which is based on the number of research fte divided by the total academic personnel fte (most recent realisation year). The research coefficient is currently under revision for improvement, see under 17.
Annual dissemination and publication, in Dutch only.
TWIN 2023-2029 | Rathenau Instituut
An English version of the report and the data file can be made accessible if requested.
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.
