1.1. Contact organisation
Statistics Norway
1.2. Contact organisation unit
Statistics Norway, Division for R&D, technology and business dynamics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
P.O. Box 2633 St. Hanshaugen, NO-0131 Oslo, Norway
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
7 November 2025
2.2. Metadata last posted
7 November 2025
2.3. Metadata last update
7 November 2025
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 | They are distributed according to NORDFORSK classification. |
|---|---|
| Correspondence table with NABS | They are converted to NABS using OECD key. |
3.2.2. NABS classification
| Deviations from NABS | No deviations. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | None |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | “Non oriented research” is not available by fields of research and development (FORD). "General university funds (GUF)” are distributed by FORD from 2021 onwards using coefficients from the latest R&D statistics for Higher Education Sector. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Frascati Manual definition to identify R&D. |
|---|---|
| Coverage of R&D or S&T in general | Only R&D is measured. |
| Fields of R&D (FORD) covered | GBARD data cover all fields of research and development. |
| Socioeconomic objective (SEO by NABS) | Frascati Manual definition is used. |
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 | Ministries, main R&D funding organisations, universities, university hospitals, research centres and institutes and state central agencies. | Included | |
| Regional (state) government | Partly included | Provincial government is included where the contribution is significant. Provincial government is partly included where appropriations are earmarked for provincial institutions performing R&D (hospitals, museums). | |
| Local (municipal) government | Not included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Budget chapter
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 budget items that contain an element of R&D are included. |
|---|---|
| Estimation of the target population size | About 140 budget items. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested. The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
Not requested.
a) Calendar year: 2023
b) Fiscal year: 2023
Start month: January
End month: December
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.
a) Confidentiality protection required by law: Yes
b) Confidentiality commitments of survey staff: Yes
7.2. Confidentiality - data treatment
Not applicable
8.1. Release calendar
Release calendar is available on website
8.2. Release calendar access
Calendar of Release in English
8.3. Release policy - user access
Data available at the same time for all users.
Annual
Frequency of Dissemination
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 release of the data is made public through the online databank at Statistics Norway |
| Ad-hoc releases | N |
1) Y - Yes, N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
|---|---|---|
| General publication/article (paper, online) |
Y | Figures are used in an annual publication published by NIFU Nordic Institute for Studies of innovation, research and education. Figures are also made available in the publication “Report on Science & Technology Indicators for Norway”, published annually by the Research Council of Norway. |
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
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 | Not applicable |
|---|---|
| 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 | Aggregated data | |
| Data prepared for individual ad hoc requests | Y | Aggregated data/micro-data | Delivery of data every year to the Ministry of Education and Research and other ministries. |
| Other | Y | Aggregated data | “Report on Science & Technology Indicators for Norway” including detailed tables, are published on the web pages of the Research Council of Norway. |
1) Y – Yes, N - No
10.6. Documentation on methodology
Not available
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.) | The online data bank on R&D statistics includes some metadata. Clarity is further ensured by including contact persons' names, phone numbers and e-mail addresses at our web pages. |
|---|---|
| Request on further clarification | No |
| Measure to increase clarity | Further update with metadata in the online bank on R&D statistics. |
| Impression of users on the clarity of the accompanying information to the data | No comments on this from users. |
11.1. Quality assurance
Statistics Norway's requirements for official statistics is based on the Statistics Act, which lays down the formal framework for all Norwegian official statistics, and those requirements developed in international collaborations
11.2. Quality management - assessment
The GBARD data is considered to be of good quality.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 - National level | Ministry of Education and Research, Ministry of Finance, Other ministries | Data used for policy assessment and policy creation. |
| 1 - National level | The Research Council of Norway | Data used for benchmarking and research policy issues. |
| 3 - Media | National media and trade specific journals | National media are interested in the benchmarking aspects, specifically comparisons to other countries |
| 4- Researchers and students | Researchers | Data used for analyses and research purposes. |
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 | We have not conducted user satisfaction surveys for GBARD. Instead, meetings are held with key users. At these meetings the users are encouraged to evaluate and suggest changes or amendments to the production of GBARD. |
|---|---|
| User satisfaction survey specific for GBARD statistics | Key users are generally satisfied. |
| Short description of the feedback received | The timeliness is appricated. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not available
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-1977 | Annual | T-6 | ||
| NABS Chapter level | Y-1977 | Annual | T-6 | ||
| NABS Sub-chapter level | Y-2021 | Annual | T-6 | GUF by FORD | |
| 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-1977 | Annual | T+6 | ||
| NABS Chapter level | Y-1977 | Annual | T+6 | ||
| NABS Sub-chapter level | Y-2021 | Annual | T+6 | GUF by FORD | |
| 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 |
|---|---|---|---|---|---|---|
| National public funding to transnationally coordinated R&D | P | Y-2005 | Annual | T-6 | ||
| GBARD by mode of funding | P | Y-2007 | Annual | T-6 | ||
| National public funding to transnatiionally coordinated R&D | F | Y-2005 | Annual | T+6 | ||
| GBARD by mode of funding | F | Y-2007 | Annual | T+6 |
- Stage: P - provisional, F - final.
- Availability of the data: No, data are not available, Y: Yes, data are available + start year.
- 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 | 3 | - | 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 ‘-‘.
- 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:
Not applicable
b) Measures taken to reduce their effect:
Not applicable
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:
Not applicable
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
b) Measures taken to reduce their effect:
Not applicable
c) Effect of non-response errors on the produced statistics:
Not applicable
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: 30 June 2023
14.1.2. Time lag - final result
Date of first release of national data: 17 June 2024
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) | T+6 | T+12 |
| Actual date of transmission of the data (T+x months) | T-6 | T+6 |
| 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 | |
| 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 | GBARD includes only appropriations included in budget. |
| Stages of data collection | FM2015 §12.41 | No deviation | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation | Net approach |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No deviation | Fees for participating in EU programs are excluded when data is reported internationally. |
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation | |
| Current and capital expenditure | FM §12.15 | No deviation | GBARD include both current and capital expenditure. |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | No deviation | Extra budgetary funds are not included. |
| Loans | FM §12.31, 12.32, 12.34 | No deviation | A share of loans that are expected not to be repaid is included. |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation | Indirect funding is excluded: the Norwegian budget does not include appropriations on tax rebates, etc. |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | No deviation | GBARD cover government financed R&D performed abroad. Fees for participation in the EU framework programs and in international institutions such as CERN. (Fee for EU framework programs is excluded in international reports). |
| 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 | 1977- | 1996 | The method for compiling GBARD data changed in 1996; series were revised historically to exclude contract research (net approach), state enterprises and payments to the European Commission. |
| Final data | 1977- | 1996 | The method for compiling GBARD data changed in 1996; series were revised historically to exclude contract research (net approach), state enterprises and payments to the European Commission. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD is based upon the purpose of the appropriations. GERD accounts for how the appropriations were spent.
GBARD includes appropriations to some international institutions while GERD only accounts for R&D performed in Norway. (Although fees for participation in EU framework programs are excluded in international GBARD reports).
GERD includes R&D financed by regional and local government while GBARD for the most only accounts for appropriations by central government.
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 | 503592 | 514424 | 10832 |
| Environment | 1125827 | 1141163 | 15336 |
| Exploration and exploitation of space | 1014252 | 1125661 | 111409 |
| Transport, telecommunication and other infrastructures | 630894 | 652262 | 21368 |
| Energy | 804658 | 810377 | 5719 |
| Industrial production and technology | 2892766 | 2940834 | 48068 |
| Health | 6629953 | 6826714 | 196761 |
| Agriculture | 2704961 | 2830159 | 125198 |
| Education | 563880 | 576518 | 12638 |
| Culture, recreation, religion and mass media | 478993 | 487200 | 8207 |
| Political and social systems, structures and processes | 1991271 | 2077042 | 85771 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 14727843 | 14833465 | 105622 |
| General advancement of knowledge: R&D financed from other sources than GUF | 5685977 | 5991629 | 305652 |
| Defence | 1300000 | 1385070 | 85070 |
| TOTAL GBARD | 41054867 | 42192518 | 1137651 |
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 | 200000 NOK | |
| Data collection costs | None | |
| Other costs | None | |
| Total costs | 200000 NOK | |
| Comments on costs | ||
| It is not easy to calculate the exact costs for producing GBARD statistics. Here the activity is calculated based upon the costs of 1 month's work per year. | ||
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 survey is conducted | Not applicable |
| Average Time required to complete the questionnaire in hours (T)1 | Not applicable | Not applicable |
| Average hourly cost (in national currency) of a respondent (C) | Not applicable | Not applicable |
| Total cost | Not applicable | 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
When new information arise, figures are revised three years back in time for comparison reasons.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: Basic data are derived from the general state budget.
b) Final data: Basic data are derived from the general state budget.
c) General University Funds (GUF): Chapter 260 in the state budget. R&D coefficients derive from the latest R&D statistics.
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 | Text analysis of the state budget and other government documents. Direct contact with ministries or agencies |
Text analysis of the state budget and other government documents. Direct contact with ministries or agencies |
No survey is conducted |
| Stage of data collection | As from 2002: iv) Initial budget appropriations (figures as voted by the parliament for the coming year, including changes introduced in the parliamentary debate). | As from 2002: v) Final budget appropriations (figures as voted by the parliament for the coming year, including additional votes during the year). |
|
| Reporting units | The funding ministry is the unique reporting unit for all years. | The funding ministry is the unique reporting unit for all years. | |
| Basic variable | Central Government R&D appropriations (In Norwegian: "Anslåtte bevilgninger til FoU") | Central Government R&D appropriations (In Norwegian: "Anslåtte bevilgninger til FoU") | |
| Time of data collection (T+x)1) | Data will be analysed by June in the budget year (T-6 months). | Data will be available by June the year after the budget year (T + 6 months). | |
| Problems in the translation of budget items | No problem with translation | ||
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)
Total appropriations per institution are found in the budget. R&D coeffisients are taken from the latest available R&D survey.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Data are broken down according to objectives at the institution level. |
|---|---|
| Criterion of distribution – purpose or content | According to the purpose. |
| Method of identification of primary objectives | Objectives are partly based on the regular R&D survey for Government sector. Some text analysis in the budget proposal is also used. |
| Difficulties of distribution | The purpose of R&D activities often have more than one objective. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Questionnaire is not in use |
| GBARD national questionnaire and explanatory notes in the national language: | Questionnaire is not in use |
| Other relevant documentation of national methodology in English: | Not available |
| Other relevant documentation of national methodology in the national language: | Not available |
18.4. Data validation
Comparing GBARD with previous cycles.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Not applicable
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 | R&D and non-R&D are separated by R&D coefficients. |
|---|---|
| Description of the use of the coefficient (if applicable) | Coefficients are used for most of the budget items. |
| Coefficient estimation method | The R&D coefficients derive from the latest R&D statistics. |
| Frequency of updating of coefficients | R&D coefficients are normally updated every second year. |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | R&D and non-R&D are separated by R&D coefficients. |
|---|---|
| Description of the use of the coefficient (if applicable) | Coefficients are used for all budget items relatred to GUF. |
| Coefficient estimation method | The R&D coefficients derive from the latest national R&D statistics. |
| Frequency of updating of coefficients | R&D coefficients are normally updated every second year. |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | Multi-annual programs 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 | Data cannot be allocated to COFOG functions. |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Not available |
| Method of estimation of future budgets | Future budgets are not estimated. |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
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.
7 November 2025
Not requested.
Budget chapter
See below.
Not requested.
a) Calendar year: 2023
b) Fiscal year: 2023
Start month: January
End month: December
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.
a) Provisional data: Basic data are derived from the general state budget.
b) Final data: Basic data are derived from the general state budget.
c) General University Funds (GUF): Chapter 260 in the state budget. R&D coefficients derive from the latest R&D statistics.
Annual
Frequency of Dissemination
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.
