1.1. Contact organisation
Statistics Austria
1.2. Contact organisation unit
Directorate Social Statistics
Research and Digitalisation Statistics Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Guglgasse 13
1110 Wien
Austria
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
26 November 2025
2.2. Metadata last posted
26 November 2026
2.3. Metadata last update
26 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 | National nomenclature of SEO used. Data are initially distributed according to the national Austrian classification by socio-economic objectives, which is almost identical to NABS. |
|---|---|
| Correspondence table with NABS | Full correspondance with NABS. |
3.2.2. NABS classification
| Deviations from NABS | No deviations. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | No specific problems known. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Non-oriented research and GUF available by FOS broken down by the six major FOS: Natural sciences, engineering, medical sciences, agricultural sciences, social sciences and humanities |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Frascati Manual definition of R&D. |
|---|---|
| Coverage of R&D or S&T in general | R&D only. |
| Fields of R&D (FORD) covered | All fields of R&D covered. |
| Socioeconomic objective (SEO by NABS) | All SEO 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 | Federal government (“Bund”) is regarded as central government, in conformity with SNA rules. | Included. | |
| Regional (state) government | 9 regional governments | Not included. | |
| Local (municipal) government | Not included. |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Budget lines or budget items in the federal budget.
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 lines or budget items in the federal budget that contain an element of R&D. |
|---|---|
| Estimation of the target population size | Does not apply. |
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: Does not apply. Federal budget refers to calendar years.
Start month:
End month:
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
Statistics Austria (national NSI) is obliged by the national statistics law and the national R&D statistics regulation to collect R&D data and report them to international organisations.
There is one national R&D statistics regulation which covers all aspects of EU-relevant R&D statistics:
Verordnung der Bundesministerin für Bildung, Wissenschaft und Kultur, des Bundesministers für Verkehr, Innovation und Technologie und des Bundesministers für Wirtschaft und Arbeit über Statistiken betreffend Forschung und experimentelle Entwicklung (F&E-Statistik-Verordnung) vom 29. August 2003, BGBl. II Nr. 396/2003; Verordnung des Bundesministers für Wissenschaft und Forschung, des Bundesministers für Verkehr, Innovation und Technologie und des Bundesministers für Wirtschaft und Arbeit, mit der die Verordnung über Statistiken betreffend Forschung und experimentelle Entwicklung (F&E-Statistik-Verordnung) geändert wird vom 8. Mai 2008, BGBl. II Nr. 150/2008
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: According to national law, data may only be published in a way that no conclusions on individual units can be drawn. Practically, this does not apply to a statistics based on adminstrative data, as GBARD.
b) Confidentiality commitments of survey staff: Every individual staff member is obliged by internal rules to a strict confidentilal treatment of information.
7.2. Confidentiality - data treatment
GBARD data are data publicly available. No confidentiality precautions need to be made.
However, in Statistics Austria receives the relevant budget data earlier than they are published and is obliged to keep information confidential before they are officially released by the Federal Ministry of Finance.
8.1. Release calendar
Preliminary GBARD on 2023 data were published nationally on 23 January 2023.
Final GBARD 2023 data were published nationally on 2 April 2025.
Data are published when available, and are therefore not listed in the release calendar. This depends also when budgets are approved by parliament.
Usually preliminary data are published on the website 6 months before the end of the calendar year (t-6).
Final data are published T+18 on the website at the latest.
8.2. Release calendar access
Statistik Kalender (German)
Release Calendar (English)
8.3. Release policy - user access
Data releases are announced in the official “release calendar” on Statistics Austria’s website. Data releases can have several forms: press conferences, press releases, tables on the website, written reports or a mix of those means. Usually all users are treated equally and receive information at the same time. In exceptional cases, for highly important statistics, this rule might be suspended when the Federal Chancellary ("Prime Minister´s Office") can be informed shortly beforehand (one day before); in such cases, this is publicly announced.
Annually.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
|---|---|---|
| Regular releases | N | |
| 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 | Tables with GBARD data can be found: Website of Statistics Austria: Statistik Forschung und Innovation Digitalisierung (German) Funding in Public Budgets (English) Statistical database STATCUBE: Statistical Database Statistical Yearbook: Statistical Yearbook of Austria 2025 Annual Austrian Research and Technology Report of the Federal Ministry of Ecudation, Science and Research: Annual Austrian Research and Technology Report
|
| Specific paper publication (paper, online) |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Statistical database STATCUBE: Statistical 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 | Does not apply. Relevant budget tables are freely available to everyone. |
|---|---|
| Access cost policy | |
| Micro-data anonymisation rules |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
|---|---|---|---|
| Internet: main results available on the national statistical authority’s website | Y | Aggregate figures | German: Statistik Forschung und Innovation Digitalisierung English: Funding in Public Budgets |
| Data prepared for individual ad hoc requests | N | Further detailed data not requested by users. | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Detailed metadata description available in the national "Standard documentation":
German:
English (only Executive summary in English available):
Standard Documentation on Metadata
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.) | No further information available. Published data contain a number of footnotes and explanations. |
|---|---|
| Request on further clarification | Questions on the different concepts of GBARD and "direct funding by the government sector" and "expenditures of the government sector" are sometimes asked. |
| Measure to increase clarity | Not planned. |
| Impression of users on the clarity of the accompanying information to the data |
11.1. Quality assurance
Statistics Austria as an organisation is committed to a series of quality guidelines which are summed up on the website:
11.2. Quality management - assessment
- Close cooperation with the responsible ministries which fund R&D during the compilation of the "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes") of the federal budget, which is the main source for GBARD statistics. This includes the role of Statistics Austria to add missing budget items or delete budget lines without R&D content and the compilation and checking of the used coefficients.
- A direct feedback to the Ministry of Finance from the results of the biennial R&D surveys increases coherence with the R&D survey data.
- Regular revisions of data improve data quality as the most recent information available is used, especially to derive the R&D coefficients used.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 | European Commission | Data needs for European research policy. |
| 1 | Federal Ministries that fund R&D (applies to practically all ministries) | Data needs for national research policies. |
| 1 | Federal Ministry of Finance | Interest to reflect total federal R&D funding in the budgetary documents as responsible ministry for the federal budget |
| 1 | FORWIT - Austrian Council for Sciemces, Technologies and Innovation (“Österreichischer Rat für Forschung, Wissenschaft, Innovation und Technologieentwicklung”) | Advisory Board for the Federal Government, the ministers and the provinces (“Laender”) in all matters of research, technology and innovation. Various detailed data needs for strategy development. |
| 1 | National Court of Audit ("Rechnungshof") | Detailed data on public R&D funding in order to assess the efficiency of the public R&D funding system in the course of specific audits |
| 4 | Various research institutes | Specific data for further in-depth analyses of the national situation of R&D |
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 com
- parisons), 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 specific user satisfaction survey on GBARD data was carried out. |
|---|---|
| User satisfaction survey specific for GBARD statistics | |
| Short description of the feedback received |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
100%
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-1975 | Annual | T - 6 months | ||
| NABS Chapter level | Y-1998 | Annual | T - 6 months | ||
| NABS Sub-chapter level | Y-1998 | Annual | T - 6 months | ||
| 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-1975 | Annual | T + 12 months | ||
| NABS Chapter level | Y-1998 | Annual | T + 12 months | ||
| NABS Sub-chapter level | Y-1998 | Annual | T + 12 months | ||
| 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 |
|---|---|---|---|---|---|---|
| GBARD by type of funding ministry | P, F | Y-1998 | Annual | provisional: t-6 final: t+12 |
||
| GBARD by domestic funding / funding to abroad | P, F | Y-1998 | Annual | provisional: t-6 final: t+12 |
||
| GBARD by institutional / project funding | F | Y-2011 | Annual | only final: t+12 | ||
| Trans-nationally coordinated R&D | F | Y-2010 | Annual | only final: t+12 |
1) Stage: P - provisional, F - final.
2) Availability of the data: No, data are not available, Y: Yes, data are available + start year.
3) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
13.1.1. Accuracy - Overall by 'Types of Error'
| Sampling errors | Non-sampling errors1) | Model-assumption Errors1) | Perceived direction of the error2) | |||
|---|---|---|---|---|---|---|
| Coverage errors | Measurement errors | Processing errors | Non response errors | |||
| Does not apply. Budget analysis. | ||||||
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: Funding from regional government is not included.
b) Measures taken to reduce their effect:
13.3.1.1. Over-coverage - rate
Does not apply.
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.
- Description/assessment of measurement errors: No such errors known.
- Measures taken to reduce their effect:
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
a) Problems in obtaining data from targeted information providers: Does not apply.
b) Measures taken to reduce their effect:
c) Effect of non-response errors on the produced statistics:
13.3.3.1. Unit non-response - rate
Not requested.
13.3.3.2. Item non-response - rate
Not requested.
13.3.4. Processing error
Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.
a) Data processing and editing processes: Does not apply. Budget analysis.
b) Description of errors: Does not apply
c) Measures taken to reduce their effect: Does not apply
13.3.5. Model assumption error
Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).
Description/assessment:
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Date of first release of national data:
Provisional data on 2023 were published nationally on 23 January 2023
14.1.2. Time lag - final result
Date of first release of national data: Final data on 2023 were published nationally on 2 April 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)
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 |
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 | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | Only federal government. | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | No |
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 | GBARD includes all outlays to be met from taxation (in conformity with the FM). |
| Stages of data collection | FM2015 §12.41 | stage iv) | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | Net approach. | |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | EU funds are not included. | |
| Types of expenditure | FM2015 §12.15 to 12.18 | All types of expenditures included. | |
| Current and capital expenditure | FM §12.15 | All types of expenditures included. | |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | Other government funds are not included | |
| Loans | FM §12.31, 12.32, 12.34 | Not included | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | Not included | |
| Treatment of multi-annual projects | FM2015 §12.44 | ||
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | Included and separately available. | GBARD includes government-financed R&D performed abroad, but only contributions to international R&D programmes or organisations (e.g. , CERN, ESA, ESO, WHO, OECD, IIASA, IAEO, UNESCO, FAO, ITA, IIF etc). The Federal budget appropriations and actual outlays devoted to R&D programmes performed abroad and to international organisations engaged in R&D activities are listed and summed up in Part A of the so-called “Federal R&D Budget”. Only for dedicated research organisations (e.g. CERN, ESO) 100% of the contributions are considered are R&D-relevant. For international organisations for which R&D is not the main activity, only a (smaller) share of these contributions is considered an allocation for R&D |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | ||
| Method of identification of primary objective | Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6 |
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 | Y-1975 | 1981, 1985 | |
| Final data | Y-1975 | 1981, 1985 |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD includes only Federal government ("Bund") and excludes R&D financed by provincial governments and by other public sector sources. It is possible to compare GBARD with “intramural R&D expenditures funded by the federal government” of the same calendar year. For 2023 (the latest year available), this comparison looks as follows: According to the R&D survey 2023, 3.857 billion € of total GERD were funded by the federal government (3.244 bn € by the "core" federal government, 614 mn by the FFG and FWF and other federal funding institutions). GBARD for 2023 amounted to 4.095 billion €; 125 million € of these went abroad and were not spent domestically, and are therefore not part of GERD. GERD funded by the federal government 2023 (3.857 billion €) therefore amounted to approximately 97% of domestic GBARD (4.095 bn € minus 125 mn € = 3.970 billion €). This high correspondence is also due to the use of coefficients for GBARD, i.e. for determining the R&D-relevant share of budget items directly from the results of the R&D survey. E.g., when the most recent R&D survey reveals the amount of federal R&D funding for a specific R&D performer, this information is proposed to the Ministry of Finance to be used to determine the coefficient in the budget line which shows the total amount of funding for this specific institution. The coefficient is set that the R&D share of total funding equals the results from the most recent R&D survey. This is mostly used for future budget appropriations until new, more updated data is available from the next R&D survey. This coefficent is especially important for determining the R&D part of overall GUF, which currently amounts to 51%.
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 | 54.312 | 57.287 | 2.975 |
| Environment | 57.119 | 42.703 | -14.416 |
| Exploration and exploitation of space | 28.385 | 26.295 | -2.09 |
| Transport, telecommunication and other infrastructures | 96.018 | 45.196 | -50.822 |
| Energy | 149.833 | 110.292 | -39.541 |
| Industrial production and technology | 664.063 | 529.301 | -134.762 |
| Health | 190.129 | 206.089 | 15.96 |
| Agriculture | 55.868 | 94.636 | 38.768 |
| Education | 32.224 | 30.047 | -2.177 |
| Culture, recreation, religion and mass media | 15.806 | 13.448 | -2.358 |
| Political and social systems, structures and processes | 37.592 | 37.735 | 0.143 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 2,250.984 | 2,337.556 | 86.572 |
| General advancement of knowledge: R&D financed from other sources than GUF | 535.385 | 557.941 | 22.556 |
| Defence | 6.673 | 6.966 | 0.239 |
| TOTAL GBARD | 4,174.391 | 4,095.492 | -78.899 |
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 separately available. | No work sub-contracted to third parties. |
| Data collection costs | Not separately available. | No work sub-contracted to third parties. |
| Other costs | Not separately available. | No work sub-contracted to third parties. |
| Total costs | Not separately available. | No work sub-contracted to third parties. |
| Comments on costs | ||
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) | 0 | Not a statistical survey. |
| Average Time required to complete the questionnaire in hours (T)1 | 0 | |
| Average hourly cost (in national currency) of a respondent (C) | Does not apply. | |
| Total cost | 0 |
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
Final data are subject to revision even after t+12, when detailed funding information for certain institutions from the two-yearly R&D surveys are taken into account to determine the final coefficients for those budget lines describing the public funding for those institutions. The coefficients used previously for determining the "R&D content" of these budget lines are then revised. The consequence can be very slight changes in total GBARD even later than 12 months after the end of the calendar year
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: "Detailed table Allocation of R&D-relevant funds of the federal government" - Appropriation ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes" - Finanzierungsvoranschlag)
b) Final data: "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes" - Erfolg)
c) General University Funds (GUF): "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes"): The respective lines for total GUF are identified. A coefficient derived from the R&D survey, which is revised annually, is used to determine "GUF used for R&D". Currently this coefficient is 51 (51% of total GUF are considered R&D-relevant).
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 federal budget appropriations. The "Detailed table Allocation of R&D-relevant funds of the federal government" of the Federal Fiscal Act (Federal Research Budget) lists all expenditures of the federal ministries with R&D relevance. Normally, this information is available every year in December containing the budget appropriations for the next calendar year. The final fiscal balance sheet should at this time be available for the previous year (i.e., in December 2022, budget data for 2023 and final fiscal data for 2021 were available). Overall expenditure for specific programmes/institutions is published, including an “R&D coefficient” for each estimate of expenditure. According to these data, Statistics Austria is calculating GBARD. The “R&D coefficient” for large R&D performing institutions with considerable public R&D funding is, however, derived from the R&D surveys of Statistics Austria, transmitted to the Federal Ministry of Finance and proposed to be used for next year's document. Each budget item (=statistical unit for the GBARD “survey”) receives an individual R&D coefficient. Classification according to socio-economic objective is then made individually for each budget item. The timeline can be delayed in case parliament does not vote on a budget appropriation, often due to an election year when a new federal government is not yet appointed, or in times of an interim government. |
Same procedure as for provisional data. Final data of previous years are usually collected at the same time with provisional figures for forthcoming years. Text analysis of the federal budget appropriations. The "Detailed table Allocation of R&D-relevant funds of the federal government" of the Federal Fiscal Act (Federal Research Budget) lists all expenditures of the federal ministries with R&D relevance. Normally, this information is available every year in December containing the budget appropriations for the next calendar year. The final fiscal balance sheet should at this time be available for the previous year (i.e., in December 2022, budget data for 2023 and final fiscal data for 2021 were available). Overall expenditure for specific programmes/institutions is published, including an “R&D coefficient” for each estimate of expenditure. According to these data, Statistics Austria is calculating GBARD. The “R&D coefficient” for large R&D performing institutions with considerable public R&D funding is, however, derived from the R&D surveys of Statistics Austria, transmitted to the Federal Ministry of Finance and proposed to be used for next year's document. Each budget item (=statistical unit for the GBARD “survey”) receives an individual R&D coefficient. Classification according to socio-economic objective is then made individually for each budget item. The timeline can be delayed in case parliament does not vote on a budget appropriation, often due to an election year when a new federal government is not yet appointed, or in times of an interim government. |
Text analysis of the Federal R&D budget + annual up-dating and checking procedure covering the Federal Ministry of Finance and other Ministries financing R&D activities by direct contacts. After every full national performer-based R&D survey a complete up-dating survey (“Grosse Revision”) is conducted covering all Federal Ministries. The systematic analysis of the Federal budget leads to the identification of all budget chapters, budget items, budget sub-items and budget posts which are of relevance for financing of R&D activities. The R&D coefficients applied to the individual budget items originate often from the most recent results of the national performer-based R&D surveys or, if such information is not available, the R&D percentages applied are obtained directly from the institutional units within the Federal Ministries responsible for funding and/or administering the respective R&D activities. All the R&D coefficients in the Federal R&D Budget are checked and up-dated annually under the auspices of Statistics Austria and, after every full R&D survey, a complete exhaustive up-dating survey is conducted by Statistics Austria covering all Federal Ministries. |
| Stage of data collection | Initial budget appropriations (figures as voted by the parliament for the coming year, including changes introduced in the parliamentary debate) are used for provisional GBARD (stage iv). | Actual outlays (money paid out during the year) are used for final GBARD (stage vii). | |
| Reporting units | the institutional units funding and/or administering R&D activities within the Federal Ministries | the institutional units funding and/or administering R&D activities within the Federal Ministries | The final sources of information (“reporting units”) are the institutional units funding and/or administering R&D activities within the Federal Ministries. This information is reported – usually after consultations with Statistics Austria – to the Federal Ministry of Finance. Statistics Austria is involved in this process to guarantee the Frascati Manual conformity. The statistical unit for the budgetary analysis performed is the budget chapter or budget item or budget sub-item or budget post, which depends on the individual data situation |
| Basic variable | Initial budget appropriations for the current and the last year (reported at the beginning of the second quarter of the current year): “Bundesvoranschlag” | Actual or final outlays for the previous years: “Erfolg”/”Rechnungsabschluss des Bundes”. | |
| Time of data collection (T+x)1) | t-9: Initial budget appropriations for the coming year are usually available in December of the preceding year and can (usually) be reported to Eurostat, after detailed analysis by Statistics Austria, at the beginning of the second quarter. Deviations can occur when due to the political situation no provisional budget altogether (not just for R&D) is available due to delays in the political process (after general elections when a federal budget is often adopted later than usual) | t+12: Final outlays for the calendar year x are usually available at the same time as initial budget appropriations for calendar year x + 2 years.Deviations can occur when due to the political situation no provisional budget altogether (not just for R&D) is available due to delays in the political process (after general elections when a federal budget is often adopted later than usual) | |
| Problems in the translation of budget items | No major problems. | ||
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)
Same as for GBARD data: "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes")
The R&D-relevant share of GUF is estimated by using a coefficent derived from the most recent R&D survey.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | The classification or distribution by socio-economic objectives is done on the basis of the statistical units selected, which are – within the framework of the GBARD budgetary analysis – budget chapters, budget items, budget sub-items or budget posts. These units represent either institutional units or programmes or an aggregation of projects and are not uniform. |
|---|---|
| Criterion of distribution – purpose or content | Purpose |
| Method of identification of primary objectives | |
| Difficulties of distribution | For the distribution to NABS of budget items which are contributions to large R&D performers, information from the latest R&D survey is used. For the funding of the research agencies (FWF and FFG), information directly from these institutions is used (e.g. annual reports and more detailed funding data). For other budget lines information on the purpose and orientation of these programmes or projects is used. No specific problems accrued. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | |
| GBARD national questionnaire and explanatory notes in the national language: | Provisional GBARD 2023; Final GBARD 2023. |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: | National classification of socio-economic objectives (in German); FTB_2023_EN_bf.pdf |
18.4. Data validation
Statistics Austria receives a provisional version of the R&D-relevant annex of the budget, namely the"Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes").
In a first step, it is checked if there are budget items missing, if known. In a second step, coefficients are checked by Statistics Austria and potential changes in the value of the coefficient to derive the R&D content are proposed to the Ministry of Finance for the final version. Results of the most recent R&D surveys is taken into account.
Budget lines in a specific year are also compared with the previous years, as well as the coefficients.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Does not apply. Budget analysis, no survey.
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 | "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes") lists all expenditures of the Federal Ministries with R&D relevance. Coefficients are used to estimate the percentage of "R&D content" of the item. Coefficients are determined by the Ministry of Finance or the responsible ministry for the respective budget item, Statistics Austria gives proposals for the coefficients based on micro-data from the most recent R&D survey, |
|---|---|
| Description of the use of the coefficient (if applicable) | An “R&D coefficient” is used for each budget item, which can be between 1% and 100%. According to this coefficient, R&D outlays of the various institutions/programmes are calculated. |
| Coefficient estimation method | An “R&D coefficient” is used for each budget item, which can be between 1% and 100%. According to this coefficient, R&D outlays of the various institutions/programmes are calculated as a percentage of total expenditure for the respective budget item. In case institutions are statistical units in R&D surveys, these coefficients are derived from the most recent R&D survey, indicating the percentage of all federal expenditure for this institution that are funded by the (federal) government and which are used for R&D. Coefficients are calculated on an individual base so that each budget item receives a different coefficient. For other coefficients information from the ministries responsible for the budget line is used. |
| Frequency of updating of coefficients | Every two years for those institutions that are statistical units in the biennial performer-based R&D survey. |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | An “R&D coefficient” is used for each GUF-relevant budget item. According to this coefficient, the R&D share of the entire basic funding for public universities is calculated. According to the latest R&D survey, currently 51% of total GUF is considered as the "R&D GUF" relevant for R&D statistics. This coefficient is derived from the most recent R&D survey, indicating the percentage of "total GUF" which falls upon R&D in public universities. |
|---|---|
| Description of the use of the coefficient (if applicable) | See above. |
| Coefficient estimation method | See above. |
| Frequency of updating of coefficients | Coefficent is updated every two years, after each R&D survey. |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | In these rare occurrences, the annual portions of the multi-annual programmes were allocated to the years for which the expenditure was planned |
|---|---|
| Possibility to classify budgetary items by COFOG functions | Not possible. |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Budget items are also classified by project and institutional funding, based on further detailed information on the various budget items. A distribution of GBARD by sector or performance receiving the funds is available. Otherwise no further analysis is made (e.g NACE). |
| Method of estimation of future budgets | No future budgets are estimated. However, current coefficients are used to estimate the R&D share in preliminary budgets for future years. |
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.
26 November 2025
Not requested.
Budget lines or budget items in the federal budget.
See below.
Not requested.
a) Calendar year: 2023
b) Fiscal year: Does not apply. Federal budget refers to calendar years.
Start month:
End month:
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.
2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
a) Coverage errors,
b) Measurement errors,
c) Non response errors and
d) Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
Not requested.
See below.
a) Provisional data: "Detailed table Allocation of R&D-relevant funds of the federal government" - Appropriation ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes" - Finanzierungsvoranschlag)
b) Final data: "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes" - Erfolg)
c) General University Funds (GUF): "Detailed table Allocation of R&D-relevant funds of the federal government" ("Detailübersicht Forschungswirksame Mittelverwendungen des Bundes"): The respective lines for total GUF are identified. A coefficient derived from the R&D survey, which is revised annually, is used to determine "GUF used for R&D". Currently this coefficient is 51 (51% of total GUF are considered R&D-relevant).
Annually.
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.
