Government budget allocations for R&D (GBARD) (gba)

1.1. Contact organisation

Statistisches Bundesamt

1.2. Contact organisation unit

Unit H24 - Research, Culture

1.3. Contact name

Confidential because of GDPR

1.4. Contact person function

Confidential because of GDPR

1.5. Contact mail address

Gustav-Stresemann-Ring 11

D-65180 Wiesbaden

Germany

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

13 November 2025

2.2. Metadata last posted

13 November 2025

2.3. Metadata last update

13 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	NABS 2007 from reference year 2007. NABS 1993 for previous years.
Correspondence table with NABS	Not applicable

3.2.2. NABS classification

Deviations from NABS	No deviations.
Problems in identifying / separating NABS chapters and sub chapters	No problems.
Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D	GUF is available by FOS.

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.
Fields of R&D (FORD) covered	NSE+SSH.
Socioeconomic objective (SEO by NABS)

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	As defined in the European System of National accounts, which includes the federal states (Länder)	Included
Regional (state) government		Included
Local (municipal) government		Not  Included

3.4. Statistical concepts and definitions

Not requested.

3.5. Statistical unit

The statistical unit is the single household budget item which is found in the household books for the 16 federal states (Länder) plus the Federal household book.

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	Whole household budget items related to R&D which is found in the household books for the 16 federal states (Länder) plus the Federal household book.
Estimation of the target population size	Full survey of the budget titles

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.

2023 reference year

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

The EU-regulation is the juridical base directly used for computing GBARD. There is no special national law.

6.1.3. Standards and manuals

• Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development.
• EBS Methodological Manual on R&D Statistics.

6.2. Institutional Mandate - data sharing

Not requested.

7.1. Confidentiality - policy

Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.

A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.

 

a)       Confidentiality protection required by law: Federal Statistics Act (BStatG)

 

b)       Confidentiality commitments of survey staff: Is ensured by oath of office       

7.2. Confidentiality - data treatment

The single household items plus R&D-coefficients are treated confidentialy.

8.1. Release calendar

No predefined release calendar. 

8.2. Release calendar access

GBARD is not part of the official release calendar

8.3. Release policy - user access

Ministries and international organisations check and analyse the GBARD-figures regularly.

No dissemination of national data by the official statistics

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

Mean of dissemination	Availability (Y/N)1	Content, format, links, ...
General publication/article (paper, online)	Y	Online-Publication by the Federal Ministry of Education and Research a) Datenportal: Datenportal b) Bundesbericht Forschung und Innovation:  Datenportal Bundesbericht Forschung und Innovation
Specific paper publication (paper, online)	N

1) Y – Yes, N - No 

10.3. Dissemination format - online database

Eurostat-Database and BMBF-Datenportal (Datenportal Eurostat)

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	Public access
Access cost policy	No costs
Micro-data anonymisation rules	Micro-data are not considered to be in need of protection, as they are generally available (household books)

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	N
Data prepared for individual ad hoc requests	N
Other	N

1) Y – Yes, N - No 

10.6. Documentation on methodology

Documentation on GBARD-methodology is done internally in unit H24 of the Federal Statistical Office. 

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.)	Quality report, methodological explanations in each publication.
Request on further clarification	Assistance to users is given by answering questions mostly on the source of the data and on the socio-economic objectives.
Measure to increase clarity	No
Impression of users on the clarity of the accompanying information to the data	Good. No mentionable complaints.

11.1. Quality assurance

Once in a year data are checked in collaboration with the responsible ministries of the federal states (Länder).  

11.2. Quality management - assessment

The overall assessment of the GBARD data is good. Some weaknesses might appear by using R&D coefficients. An assessment through experts from the Ministries of the Länder in 2007 has more or less approved the quality of the analysis. An assessment of the data is done yearly.

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class1	Description of users	Users’ needs
1. European level	Commission (DGs, Secretariat General, EUROSTAT)	Tabulating data; policy analysis.
1. Member States	Ministries of Economy or Finance, other Ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies	Comparing themselves with other countries
1. National level	Federal and Länder Ministries (Science, Finance)	Policy analysis and assessment.
4. Researchers and students		Analysis, ad hoc services.

1)       Users' class codification

1- Institutions:

• European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
• in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
• International organisations: OECD, UN, IMF, ILO, etc.

2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.

3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.

4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)

5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)

6- Other (User class defined for national purposes, different from the previous classes.)

12.2. Relevance - User Satisfaction

To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.

12.2.1. National Surveys and feedback

Conduction of a user satisfaction survey or any other type of monitoring user satisfaction	No user satisfaction survey has been carried out.
User satisfaction survey specific for GBARD statistics	No user satisfaction survey has been carried out.
Short description of the feedback received	Not applicable

12.3. Completeness

See below.

12.3.1. Data completeness - rate

Data completeness is secured as this exercise is based on a full inventory. 

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%.

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 995/2012.

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- 1983	Yearly.
NABS Chapter level	Y- 1983	Yearly.
NABS Sub-chapter level	Y- 1983	Yearly.
Special categories - Biotech	Y- 1983	Yearly.			1983 to 1992 only NABS 99.
Special categories - Nanotech
Special categories - Security	Y- 1983	Yearly.

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-1983	Yearly
NABS Chapter level	Y-1983	Yearly
NABS Sub-chapter level	Y-1983	Yearly
Special categories - Biotech	Y-1983	Yearly			1983 to 1992 only NABS 99.
Special categories - Nanotech
Special categories - Security

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
No other special categories are available

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
	-	1	-	2	-	+/-

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.

• Description/assessment of coverage errors: Not applicable.
• Measures taken to reduce their effect: Not applicable.

13.3.1.1. Over-coverage - rate

In case one item occurs by mistake twice in the list the doubled item is immediately deleted from the list. 

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: Description/assessment of measurement errors: Measurement errors can occur while using R&D coefficients.
• Measures taken to reduce their effect: Measures taken to reduce their effect: The R&D coefficients are checked with information from other sources. Close exchange with ministries and respondents. The questionnaire and the validity checks are improved continuously.

13.3.3. Non response error

Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

• Problems in obtaining data from targeted information providers: Problems in obtaining data from targeted information providers: sometimes problems of respondents to report R&D coefficients.
• Measures taken to reduce their effect: The R&D coefficients are checked with information from other sources and over time. Close exchange with ministries and respondents.
• Effect of non-response errors on the produced statistics: small effect

 Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

• Problems in obtaining data from targeted information providers: no problems.
• Measures taken to reduce their effect: Not applicable.
• 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.

• Data processing and editing processes: no noticeable errors.
• Description of errors: no noticeable errors.
• 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: we do not use an estimation model

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: No dissemination of national data by the official statistics

14.1.2. Time lag - final result

Date of first release of national data: No dissemination of national data by the official statistics

14.2. Punctuality

Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.

14.2.1. Punctuality - delivery and publication

Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)

14.2.1.1. Deadline and date of data transmission

	Transmission of provisional data	Transmission of final data
Legally defined deadline of data transmission (T+_ months)	6	12
Actual date of transmission of the data (T+x months)	6	12
Delay (days)	0	0
Reasoning for delay

15.1. Comparability - geographical

See below.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. Survey Concepts Issues

The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.

 

Concept / Issue	Reference to recommendations	Deviation from recommendations	National definition / Treatment / Deviations from recommendations
Research and development	FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4).	No deviation
Coverage of levels of government	FM2015, §12.5 to 12.9	No deviation
Socioeconomic objectives coverage and breakdown	Reg. 2020/1197: Annex 1, Table 20	No deviation
Reference period	Reg. 2020/1197: Annex 1, Table 20	No deviation

 

15.1.3. Deviations from recommendations

GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.

 

Methodological issues	Reference to recommendations	Deviation from recommendations	National definition / Treatment / Deviations from recommendations
Definition of GBARD	FM § 12.9	No deviation
Stages of data collection	FM2015 §12.41	No deviation
Gross / net approach, net principle	FM2015 §12.20 and 12.21	No deviation
EU/other funds	Eurostat's EBS Methodological Manual on R&D Statistics	No deviation
Types of expenditure	FM2015 §12.15 to 12.18	No deviation
Current and capital expenditure	FM §12.15	No deviation
Extra budgetary funds	FM §12.8, 12.20, 12.38		Resources for the economic stimulus package in the course of the economic and financial crisis (extra-budgetary) are included (if used for R&D).
Loans	FM §12.31, 12.32, 12.34		Loans that are to be repaid are excluded in general (extra-budgetary if existing).
Indirect funding, tax rebates, etc.	FM §12.31 - 12.38	No deviation
Treatment of multi-annual projects	FM2015 §12.44	No deviation
Treatment of GBARD going to R&D abroad	FM2015 §12.19	No deviation
Criterion for distribution by socioeconomic objective	FM2015 §12.50 to 12.71	No deviation
Method of identification of primary objective	Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6	No deviation

 

15.2. Comparability - over time

See below.

15.2.1. Length of comparable time series

See below.

15.2.2. Breaks in time series

	Length  of comparable time series	Break years1	Nature of the breaks
Provisional data		2007, 2003-2001, 1997, 1997-1996, 1991, 1991, 1990	2007: using NABS 2007 classification. 2001-2003 and 1997:The total budget figure of the Federal Ministry of Education, Science, Research and Technology was reduced, but the global reduction was not available by socio-economic objective. Therefore, total GBAORD reflects the adjusted budget figure, and the sum of the breakdown for those years does not add to the total. 1997:The methodology of assessing GBAORD by socio-economic objective changed. 1997-1996:Break in series due to a change in methodology for breakdown into SEO (NABS10, NABS12). 1991:on the data are for unified Germany. 1990:Until 1990 the data covered western Germany only.
Final data		2007, 2003-2001, 1997, 1997-1996, 1991, 1991, 1990.	2007: using NABS 2007 classification. 2001-2003 and 1997:The total budget figure of the Federal Ministry of Education, Science, Research and Technology was reduced, but the global reduction was not available by socio-economic objective. Therefore, total GBAORD reflects the adjusted budget figure, and the sum of the breakdown for those years does not add to the total. 1997:The methodology of assessing GBAORD by socio-economic objective changed. 1997-1996:Break in series due to a change in methodology for breakdown into SEO (NABS10, NABS12). 1991:on the data are for unified Germany. 1990:Until 1990 the data covered western Germany only.

1)       Breaks years are years for which data are not fully comparable to the previous period.

15.3. Coherence - cross domain

is fullfiled

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	594746	588965	5781
Environment	1250627	1271130	-20503
Exploration and exploitation of space	1792421	1793810	-1389
Transport, telecommunication and other infrastructures	1314710	1197005	117705
Energy	2643034	2711705	-68671
Industrial production and technology	7073445	7216039	-142594
Health	2492305	2513169	-20864
Agriculture	1075779	1092720	-16941
Education	1233296	864918	368378
Culture, recreation, religion and mass media	347920	462859	-114939
Political and social systems, structures and processes	833101	814268	18833
General advancement of knowledge: R&D financed from General University Funds (GUF)	15651887	15112548	539339
General advancement of knowledge: R&D financed from other sources than GUF	6463613	6498020	-34407
Defence	1883818	1952900	-69082
TOTAL GBARD	44650705	44090055	560650

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	No costs has been determined so far	No share has been determined so far
Data collection costs	No costs has been determined so far	No share has been determined so far
Other costs	No costs has been determined so far	No share has been determined so far
Total costs	No costs has been determined so far	No share has been determined so far
Comments on costs
A national standardised method of calculating costs and burden of all administrative actions (including statistics) is currently being developed. No assessment of costs and burden can be done in advance.

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)	We evaluate budget books, so there are no respondents	manually
Average Time required to complete the questionnaire in hours (T)1	see above
Average hourly cost (in national currency) of a respondent (C)	see above
Total cost	see above

1)        T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)

17.1. Data revision - policy

Data revision is done throughout the year.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

• Provisional data: household books for the 16 federal states (Länder) plus the Federal household book.
• Final data: household books for the 16 federal states (Länder) plus the Federal household book.
• General University Funds (GUF): household books for the 16 federal states (Länder) plus the Federal household book.

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	Budget text analysis and other. Text analysis of (provisional) budgets; no link to survey of R&D performers.	Budget text analysis and other.	Text analysis of (provisional) budgets; no link to survey of R&D performers.
Stage of data collection	Budget data are based on figures from stage iv and v, in some cases from stage iii	Budget data are based on figures from stage iv and v, in some cases from stage iii
Reporting units	Reporting unit is: -Ministries of Finance (Länder) for budgets; -Other Ministries for R&D coefficients and additional information on NABS-categories in case of project funding.	Reporting unit is: -Ministries of Finance (Länder) for budgets; -Other Ministries for R&D coefficients and additional information on NABS-categories in case of project funding.
Basic variable	Appropriation - Fördermittel.	Appropriation - Fördermittel.
Time of data collection (T+x)1)	T+3	T+15
Problems in the translation of budget items	No 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)

The basis for the calculation of R&D statistics in the HES is an annual survey in the HES for expenditure.

18.3.3. Distribution by socioeconomic objectives (SEO)

Level of distribution of budgetary items – institution or programme/project	Objectives distributed at project level.
Criterion of distribution – purpose or content	Content - predominantly according to the main content of R&D programmes.
Method of identification of primary objectives
Difficulties of distribution

18.3.4. Questionnaire and other documents

Annex	Name of the file
GBARD national questionnaire and explanatory notes in English:	We evaluate budget books, so there is no questionaire.
GBARD national questionnaire and explanatory notes in the national language:	see above
Other relevant documentation of national methodology in English:	not available
Other relevant documentation of national methodology in the national language:	not available at present

18.4. Data validation

Data validation is done throughout the year.

18.5. Data compilation

See below.

18.5.1. Imputation - rate

The GBARD-compilation is based on a full inventory.

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 is separated from non-R&D by using R&D coefficients in every single budget item (Haushaltstitel).
Description of the use of the coefficient (if applicable)
Coefficient estimation method	R&D coefficients are not derived but based on various information sources (Ministries, surveys, publications etc.).
Frequency of updating of coefficients	Updated annually.

18.5.2.2. General University Funds (GUF)

Method(s) of separating R&D from non-R&D	Distinction is made by R&D coefficients
Description of the use of the coefficient (if applicable)
Coefficient estimation method	R&D coefficients are calculated by estimating the time spent for R&D activities (eliminating time spent for non-R&D activities). Coefficients are calculated for each type of institution (universities, specialised colleges of higher education etc.) and in addition on the level of (major) fields of science for the universities.
Frequency of updating of coefficients	The R&D coefficients are computed every fourth year.

18.5.2.3. Other issues

Treatment of multi-annual programmes	Multi-annual programmes are not reported in a single year -- they are allocated to the years they are budgeted.
Possibility to classify budgetary items by COFOG functions	No, because for GBARD no distinction is made between fundamental and applied research.
Possibility to classify budgetary items by other nomenclatures e.g. NACE	no possibility
Method of estimation of future budgets	Growth rates of certain areas of budget (e.g. expenditure for Higher education, Science, etc.).

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

No comment.

Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and 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.

13 November 2025

Not requested.

The statistical unit is the single household budget item which is found in the household books for the 16 federal states (Länder) plus the Federal household book.

See below.

Not requested.

2023 reference year

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.

• Provisional data: household books for the 16 federal states (Länder) plus the Federal household book.
• Final data: household books for the 16 federal states (Länder) plus the Federal household book.
• General University Funds (GUF): household books for the 16 federal states (Länder) plus the Federal household book.

No dissemination of national data by the official statistics

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.