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

1.1. Contact organisation

STATEC - National Institute of Statistics and Economic Studies

1.2. Contact organisation unit

Unit MAC 4 - Government Accounts

1.3. Contact name

Confidential because of GDPR

1.4. Contact person function

Confidential because of GDPR

1.5. Contact mail address

STATEC

Bâtiment Twist
12, boulevard du Jazz
B.P. 10
L-4370 Belvaux

Luxembourg

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

15 October 2025

2.2. Metadata last posted

15 October 2025

2.3. Metadata last update

15 October 2025

3.1. Data description

Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and experimental development (R&D) activities, and thereby provide information about the priority Governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content (FM 2015, Chapter 12).

Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015 (EN), which is the internationally recognised standard methodology for collecting R&D statistics.

Statistics on science, technology and innovation were collected based on Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 1197/2020 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/ of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).

Please note that according to Article 12(4) of Regulation (EU) 1197/2020, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.

3.2. Classification system

Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.

3.2.1. National classification

National nomenclature of SEO used	NABS 2007.
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	Not available

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	All fields of science are covered.
Socioeconomic objective (SEO by NABS)	Yes, 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	Central government as defined by ESA2010.	Included.
Regional (state) government		Not applicable.
Local (municipal) government		Not included.	There is no R&D in Local Government.

3.4. Statistical concepts and definitions

Not requested.

3.5. Statistical unit

Budgetary central government budget appropriations.

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	The data covers budget appropriations of budgetary central government which include R&D.
Estimation of the target population size	Not applicable.

3.7. Reference area

Not requested.

3.8. Coverage - Time

Not requested. See point 5.

3.9. Base period

Not requested.

Not requested.

• Calendar year: 2023
• Fiscal year: Calendar year.
  • Start month: January 2023.
  • End month: December 2023.

6.1. Institutional Mandate - legal acts and other agreements

See below.

6.1.1. European legislation

GBARD statistics are based on the Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. Since the beginning of 2021, 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. Please note that according to Article 12(4) of Regulation (EU) 2020/1197, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.

6.1.2. National legislation

Loi du 10 juillet 2011 portant organisation de l'Institut national de la statistique et des études économiques et modifiant la loi modifiée du 22 juin 1963 fixant le régime des traitements des fonctionnaires de l'Etat 

Loi du 10 juillet 2011 portant organisation de ... - Legilux (public.lu)

6.1.3. Standards and manuals

Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development.

6.2. Institutional Mandate - data sharing

Not requested.

7.1. Confidentiality - policy

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

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

• Confidentiality protection required by law: Not applicable, as the State budget is not confidential.
• Confidentiality commitments of survey staff: Not applicable.

7.2. Confidentiality - data treatment

Not applicable.

8.1. Release calendar

The GBARD data is updated on the STATEC website twice a year, in April and in October.

8.2. Release calendar access

The STATEC release calendar can be found here: Release calendar 2025 - Statistics Portal - Luxembourg. However, the GBARD table is not included in the release calendar.

8.3. Release policy - user access

Data becomes available to everyone in the public at the same time.

Annual.

10.1. Dissemination format - News release

See below.

10.1.1. Availability of the releases

	Availability (Y/N)1	Content, format, links, ...
Regular releases	Y	LUSTAT Data Explorer • Crédits budgétaires publics de R&D par objectif socio-économique (en millions EUR) (statec.lu)
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	LUSTAT Data Explorer • Crédits budgétaires publics de R&D par objectif socio-économique (en millions EUR) (statec.lu)
Specific paper publication (paper, online)	Not applicable.	Not applicable.

1) Y – Yes, N - No 

10.3. Dissemination format - online database

LUSTAT Data Explorer • Crédits budgétaires publics de R&D

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	The data are freely accessible.
Access cost policy	None.
Micro-data anonymisation rules	Not applicable.

10.5. Dissemination format - other

See below.

10.5.1. Metadata - consultations

Not requested.

10.5.2. Availability of other dissemination means

Dissemination means	Availability (Y/N)1	Micro-data / Aggregate figures	Comments
Internet: main results available on the national statistical authority’s website	Y	N	See above.
Data prepared for individual ad hoc requests	N	N
Other	N	N

1) Y – Yes, N - No 

10.6. Documentation on methodology

No dissemination on the STATEC website of documentation on methodology applied for GBARD.

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.)	None.
Request on further clarification	Assistance is offered to the users. In most cases, users have direct contact with the GBARD providers.
Measure to increase clarity	None.
Impression of users on the clarity of the accompanying information to the data	None.

11.1. Quality assurance

Twice a year, data are checked in collaboration with the General Finance Inspection. The quality of the treatment of the data is ensured by the use of best practices, quality reviews and self-assessments.

11.2. Quality management - assessment

Quality is expected to be good as data is provided directly by the General Finance Inspection.

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class1	Description of users	Users’ needs
1 - European level	EU Commission (Eurostat)	EU statistics
1 - National level	Ministry for Higher Education and Research, National Research Fund	International comparison
1 - International level	OECD	International comparison
4 - Researchers and students	Researchers and students	Detailed data for analysis

1)       Users' class codification

1- Institutions:

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

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

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

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

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

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

12.2. Relevance - User Satisfaction

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

12.2.1. National Surveys and feedback

Conduction of a user satisfaction survey or any other type of monitoring user satisfaction	No survey.
User satisfaction survey specific for GBARD statistics	No survey.
Short description of the feedback received

12.3. Completeness

See below.

12.3.1. Data completeness - rate

The data is complete.

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

1)  Criteria: Obligatory data (provisional budget and final budget). Only 'Very Good' = 100% and 'Very Poor' <100% apply.

2)  Criteria: Optional data (final budget). 'Very Good' = 100%; 'Good' = >75%;'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.

12.3.3. Data availability

See below.

12.3.3.1. Data availability – Provisional data

	Availability1	Frequency of data collection	Gap years – years with missing data	Time of compilation (T+x)2	Comments
Total GBARD	Y - 2000	Annual	None	T+3 months
NABS Chapter level	Y - 2000	Annual	None	T+3 months
NABS Sub-chapter level	N
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 - 2000	Annual	None	T+9 months
NABS Chapter level	Y - 2000	Annual	None	T+9 months
NABS Sub-chapter level	N
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
Not applicable		Not available				No special categories

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:

• Coverage errors,
• Measurement errors,
• Non response errors and
• Processing errors.

Model assumption errors should be treated under the heading of the respective error they are trying to reduce.

13.1.1. Accuracy - Overall by 'Types of Error'

Sampling errors	Non-sampling errors1)				Model-assumption Errors1)	Perceived direction of the error2)
	Coverage errors	Measurement errors	Processing errors	Non response errors
Not applicable.	-	-	-	-	Not applicable.	Not applicable.

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

Not applicable.

13.3.1.2. Common units - proportion

Not requested.

13.3.2. Measurement error

Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.

• Description/assessment of measurement errors: No measurement errors are expected.
• Measures taken to reduce their effect: Not applicable.

13.3.3. Non response error

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

• Problems in obtaining data from targeted information providers: Not applicable.
• 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 such processing errors are expected.
• Description of errors:  Not applicable.
• Measures taken to reduce their effect: Not applicable.

13.3.5. Model assumption error

Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).

Description/assessment: Not applicable.

14.1. Timeliness

Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.

14.1.1. Time lag - first result

Date of first release of national data: T+3 months.

14.1.2. Time lag - final result

Date of first release of national data: T+9 months.

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	no delay	no delay

15.1. Comparability - geographical

See below.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. Survey Concepts Issues

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

 

Concept / Issue	Reference to recommendations	Deviation from recommendations	National definition / Treatment / Deviations from recommendations
Research and development	FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4).	No deviation
Coverage of levels of government	FM2015, §12.5 to 12.9	No deviation
Socioeconomic objectives coverage and breakdown	Reg. 2020/1197: Annex 1, Table 20	No deviation
Reference period	Reg. 2020/1197: Annex 1, Table 20	No deviation	In the latest publication, NABS reclassifications are reflected from 2021 onwards. For previous years, these reclassifications will only be reflected in the published data referring to the transmission after a benchmark revision. This revision policy might lead to a lack of comparability between the last for years and back years. The comparability is re-established on a regular basis after benchmark revisions.

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		Outlays are to be met only from taxation or other government revenue within the budget.
Stages of data collection	FM2015 §12.41		No deviations.
Gross / net approach, net principle	FM2015 §12.20 and 12.21		Corresponding revenue is excluded from budget appropriations according to the net principle.
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		No deviations.
Current and capital expenditure	FM §12.15		Both current and capital expenditure are included in GBARD.
Extra budgetary funds	FM §12.8, 12.20, 12.38		Extra-budgetary central government entities as defined by ESA2010 are included.
Loans	FM §12.31, 12.32, 12.34		No deviations.
Indirect funding, tax rebates, etc.	FM §12.31 - 12.38		No deviations.
Treatment of multi-annual projects	FM2015 §12.44		No deviations.  In the latest publication, NABS reclassifications are reflected from 2021 onwards. For back years, these reclassifications will only be reflected in the published data referring to the transmission after a benchmark revision.
Treatment of GBARD going to R&D abroad	FM2015 §12.19		GBARD includes government-financed R&D performed abroad.
Criterion for distribution by socioeconomic objective	FM2015 §12.50 to 12.71		No deviations.
Method of identification of primary objective	Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6		The primary objective is mainly identified with the COFOG code. Therefore, COFOG reclassifications will in general lead to NABS reclassifications. These reclassifications are only reflected in the last 4 years published, until the whole series is revised after a benchmark revision.

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	2004	2017-2018 and 2020-2021	Revisions for the improvement of the data quality which are not included in the data before 2021.
Final data	2004, 2021	2017-2018 and 2020-2021	Revisions for the improvement of the data quality which are not included in the data before 2021. From 2021 reference year, the revision of the data is due to the change of COFOG codification of one budget appropriation in the context of the revision of government expenditure on defense. A COFOG reclassification of budget appropriations and expenditure of special funds took place from 2021 onwards hence some variations of data.

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

15.3. Coherence - cross domain

No systematic comparisons between the GERD and the GBARD series are made.

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	0	0	0
Environment	11	8	-3
Exploration and exploitation of space	0	67	66
Transport, telecommunication and other infrastructures	3	6	3
Energy	0	0	0
Industrial production and technology	42	106	64
Health	84	82	-2
Agriculture	1	1	0
Education	11	0	-11
Culture, recreation, religion and mass media	0	1	1
Political and social systems, structures and processes	21	21	0
General advancement of knowledge: R&D financed from General University Funds (GUF)	130	132	2
General advancement of knowledge: R&D financed from other sources than GUF	124	82	-43
Defence	0	2	2
TOTAL GBARD	427	506	78

in millions of euros

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 available separately	No subcontracting
Data collection costs	Not available separately	No subcontracting
Other costs	Not available separately	No subcontracting
Total costs	Not available separately	No subcontracting
Comments on costs
Costs are not separately available. Not applicable as there is no sub-contracting.

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)	Not relevant.	Not relevant.
Average Time required to complete the questionnaire in hours (T)1	Not relevant.	Not relevant.
Average hourly cost (in national currency) of a respondent (C)	Not relevant.	Not relevant.
Total cost	Not relevant.	Not relevant.

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

The coding of budget appropriations, special funds and extra-budgetary central government units is constantly monitored and, if necessary, revised. The revisions are included in the published data for the last 4 years. Back data is updated after benchmark revisions.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

a)       Provisional data: Budget appropriations provided by the General Finance Inspection.

b)      Final data: Final account provided by the General Finance Inspection.

c)       General University Funds (GUF): Budget appropriations and final accounts provided by the General Finance Inspection, completed by an annual survey.

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	The General Finance Inspection, which is an administration of the Ministry of Finance, collects the data, brings it into form and provides the data to STATEC.	The General Finance Inspection, which is an administration of the Ministry of Finance, collects the data, brings it into form and provides the data to STATEC.
Stage of data collection	Initial budget appropriations (figures as voted by the parliament for the coming year) are used for provisional GBARD.	Final accounts, i.e. actual outlays (money paid out during the year, including the complementary months of year T+1 referring to year T) are used for final GBARD.
Reporting units	General Finance Inspection.	General Finance Inspection.
Basic variable	Initial budget appropriations.	Final accounts.
Time of data collection (T+x)1)	Initial budget appropriations for the year T are usually available in December T-1, but at the latest in the first months of the year T.	T+8: the final accounts become available at the end of the summer of year T.
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 data is collected through a survey.

18.3.3. Distribution by socioeconomic objectives (SEO)

Level of distribution of budgetary items – institution or programme/project	Objectives distributed at the level of budget appropriations, which may then be split into more SEO’s.
Criterion of distribution – purpose or content	Purpose.
Method of identification of primary objectives	COFOG for the budgetary articles and NABS for the information collected through a survey.
Difficulties of distribution	No problems.

18.3.4. Questionnaire and other documents

Annex	Name of the file
GBARD national questionnaire and explanatory notes in English:	Not applicable.
GBARD national questionnaire and explanatory notes in the national language:	Not applicable.
Other relevant documentation of national methodology in English:	Not applicable.
Other relevant documentation of national methodology in the national language:	Not applicable.

18.4. Data validation

Not applicable.

18.5. Data compilation

See below.

18.5.1. Imputation - rate

Not applicable.

18.5.2. Data compilation methods

See below.

18.5.2.1. Identifying R&D

Method(s) of separating R&D from non-R&D	Almost all budget appropriations can be identified as R&D or as non-R&D. For instance, budget appropriations to public research centers are completely taken into account, whereas appropriations to other extra-budgetary entities without R&D activities are completely left out. For some entities performing R&D and, at the same time, other activities, for instance budget expenditure to university, this is not possible. In that case, the budgetary article is replaced by the results of a survey.
Description of the use of the coefficient (if applicable)
Coefficient estimation method	For public research institutions performing in different fields of R&D, the results of an annual survey are used to calculate coefficients that are applied to the budget appropriations to attribute NABS codes.
Frequency of updating of coefficients	Annual.

18.5.2.2. General University Funds (GUF)

Method(s) of separating R&D from non-R&D	The amounts are separated with an annual survey.
Description of the use of the coefficient (if applicable)	No coefficient is used. For those budget appropriations which include R&D data as well as non-R&D data, the budget appropriations are not taken into account but are replaced by the amounts of the survey.
Coefficient estimation method	Not applicable.
Frequency of updating of coefficients	Annual.

18.5.2.3. Other issues

Treatment of multi-annual programmes	Multi-annual programs are allocated to the years in which the programs are budgeted.
Possibility to classify budgetary items by COFOG functions	Yes.
Possibility to classify budgetary items by other nomenclatures e.g. NACE	Yes, by NACE.
Method of estimation of future budgets	Budgets for future years are established by the government and provided to STATEC via the General Finance Inspection.

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

No comments.

Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and experimental development (R&D) activities, and thereby provide information about the priority Governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content (FM 2015, Chapter 12).

Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015 (EN), which is the internationally recognised standard methodology for collecting R&D statistics.

Statistics on science, technology and innovation were collected based on Commission Implementing Regulation (EU) Regulation (EU) No 995/2012 concerning the production and development of Community statistics on science and technology until the end of 2020. Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 1197/2020 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/ of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).

Please note that according to Article 12(4) of Regulation (EU) 1197/2020, the provisions of Regulation (EU) 995/2012 continue to apply for the reference years that fall before 1 January 2021.

15 October 2025

Not requested.

Budgetary central government budget appropriations.

See below.

Not requested.

• Calendar year: 2023
• Fiscal year: Calendar year.
  • Start month: January 2023.
  • End month: December 2023.

Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).

 

Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:

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:

• Coverage errors,
• Measurement errors,
• Non response errors and
• Processing errors.

Model assumption errors should be treated under the heading of the respective error they are trying to reduce.

Not requested.

See below.

a)       Provisional data: Budget appropriations provided by the General Finance Inspection.

b)      Final data: Final account provided by the General Finance Inspection.

c)       General University Funds (GUF): Budget appropriations and final accounts provided by the General Finance Inspection, completed by an annual survey.

Annual.

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.