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

1.1. Contact organisation

Hungarian Central Statistical Office

1.2. Contact organisation unit

Services Statistics Department

Research-Development and Information Statistics Section

1.3. Contact name

Confidential because of GDPR

1.4. Contact person function

Confidential because of GDPR

1.5. Contact mail address

1024 Budapest, Keleti Károly utca 5-7, Hungary

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

30 October 2025

2.2. Metadata last posted

30 October 2025

2.3. Metadata last update

30 October 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	Not applicable.
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 problem identified.
Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D	GUF data distributed by fields of R&D is available. Chapter 12: Contains only those financial resources that are transferred from a public institution to HE institution for R&D purposes where the research activity is not specified. Chapter 13: Contains only those financial resources that are transferred from a public institution to a public or private research institution (in NACE Rev.2 Division 72) for R&D purposes where the research activity is not specified.

3.3. Coverage - sector

See below.

3.3.1. General coverage

Definition of R&D	No deviation from FM2015.
Coverage of R&D or S&T in general	GBARD statistics cover only R&D
Fields of R&D (FORD) covered	GBARD statistics cover all fields of FORD. No deviation.
Socioeconomic objective (SEO by NABS)	GBARD statistics cover all fields of NABS. No deviation.

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	Includes ministries and other central bodies.	Included
Regional (state) government		Not included	Regional government either has no R&D funding activities or the source is located in the central government budget.
Local (municipal) government		Not included	Local government either has no R&D funding activities or the source is located in the central government budget.

3.4. Statistical concepts and definitions

Not requested.

3.5. Statistical unit

Government entities with individual budgets.

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 government entities that fund R&D performance.
Estimation of the target population size	19

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:

 1 January  - 31 December 2023

b) Fiscal year: Same as calendar year.

    Start month: January 

    End month: December 

6.1. Institutional Mandate - legal acts and other agreements

See below.

6.1.1. European legislation

Since the beginning of 2021, GBARD statistics are based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail.  GBARD statistics were based until the end of 2020 on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.

6.1.2. National legislation

Data collection was carried out according to the national Government Decree on The National Statistical Data Collection Programme enacting the surveys of the reference period.

The national legal act: Hungarian Act CLV. of 2016. on Statistics

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:

 Legislation and policy at national level:

• The Act CLV of 2016 on Official Statistics (the Hungarian Statistical Law);
• Act CXII of 2011 on Informational self-administration and freedom of information.
• The confidentiality policy of HCSO is available at the following website address: Confidentiality Policy
• Additional information in English is available on the following website: Statistical Legislation

HCSO ensures confidentiality for all the data reported by data providers and the exclusive use of the data for statistical purposes. We disseminate only aggregated data in full compliance with the rules of confidentiality. Individual data, as well as aggregated data consisting of fewer than 3 enterprises are regarded as confidential. Researchers have access to de-identified data sets and to anonymised micro data for scientific purposes with appropriate legal and methodological guaranties in place.

b)       Confidentiality commitments of survey staff:

 Employees can work with datasets in their competence with registered and controlled access rights, and need to work in line with the confidentiality policies and protocols.

7.2. Confidentiality - data treatment

Budgetary data are not confidential.

HCSO ensures confidentiality for all the data reported by data providers and the exclusive use of the data for statistical purposes. We disseminate only aggregated data in full compliance with the rules of confidentiality. Individual data, as well as aggregated data consisting of fewer than 3 data suppliers are regarded as confidential and therefore not published. Researchers have access to de-identified data sets and to anonymised micro data for scientific purposes with appropriate legal and methodological guaranties in place. As for the employees, they can work with datasets in their competence with registered and controlled access rights.

8.1. Release calendar

There is a release policy in place for the GBARD data set. The release calendar is publicly available on the website.

8.2. Release calendar access

HCSO's publication and revision calendar is publicly available on the website: 

Publication Calendar in English

Pubilcation Calendar in Hungarian

8.3. Release policy - user access

Data is disseminated to the public according to the release policy and release calendar. At t+M8, the final data of GBARD were published in the national online summary tables.

Yearly.

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	Aggregate figures of Government budget allocations for R&D by socioeconomic obejctives are published in the Annual R&D Report, 2023 (in Hungarian only) and Summary tables (STADAT). Kiadványtár - Központi Statisztikai Hivatal (ksh.hu) Total GBARD by NABS SEO
Specific paper publication (paper, online)	N

1) Y – Yes, N - No 

10.3. Dissemination format - online database

Not applicable.

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	No micro-data is disseminated, only aggregate figures.
Access cost policy	Not applicable.
Micro-data anonymisation rules	Not applicable.

10.5. Dissemination format - other

See below.

10.5.1. Metadata - consultations

Not requested.

10.5.2. Availability of other dissemination means

Dissemination means	Availability (Y/N)1	Micro-data / Aggregate figures	Comments
Internet: main results available on the national statistical authority’s website	Y	Aggregate figures	Database access via website is free of charge for the public. No registration is needed to access the public database.
Data prepared for individual ad hoc requests	N
Other	N

1) Y – Yes, N - No 

10.6. Documentation on methodology

Each publication with R&D data contains the main definitions, concepts and a section on brief methodological summary of the R&D/ GBARD data collection.

E.g.: Summary Tables - Methodology Summary:

Methodology Summary for R&D data

 

Detailed R&D metadata are available on the website of Hungarian Central Statistical Office, both in English and Hungarian:

Metadata information on R&D domain

10.6.1. Metadata completeness - rate

Not requested.

10.7. Quality management - documentation

See below.

10.7.1. Documentation and users’ requests

Type(s) of data accompanying information available (metadata, graphs, etc.)	Metadata is avaiable: Methodology Summary for R&D data
Request on further clarification	No further request
Measure to increase clarity	No
Impression of users on the clarity of the accompanying information to the data	Data users are mostly satisfied.

11.1. Quality assurance

The HCSO Quality Policy lays out the principles and commitments related to the quality of statistics. The document is consistent with the goals set out in the Mission and Vision statements and with the principles of the European Statistics Code of Practice and is publicly available on the HCSO website.

The European Statistics Code of Practice is available on the website of the HCSO. Also, HCSO together with the member-organisations of the Hungarian Official Statistical Service created a National Statistics Code of Practice based on the European Statistics Code of Practice.

Quality Guidelines are meant to ensure the quality of the statistical processes. The document has been in place since 2007 (1st revision in 2009, 2nd revision in 2014 and 3rd revision is currently ongoing). The latest version (2014) is available on the HCSO website.

At HCSO, special attention is given to quality measurement, monitoring and documentation. Procedures are in place in order to ensure updated documentation on product quality. Apart from the internal reports, quality reports are regularly provided to Eurostat as well.

All statistical processes of the national GBARD survey were carried out in accordance with HCSO’s Quality Policy, Quality Guidelines and in line with the National Statistics Code of Practice that is consistent with the principles of the European Statistics Code of Practice.

In the GBARD data collection, principles relevant for the institutional environment, the statistical procedures and statistical output were observed.

11.2. Quality management - assessment

The GBARD data collection is carried out according to HCSO's quality management standards and guidelines, which ensures high quality data. Main strength of the data collection: GBARD data collection is based on a dedicated GBARD survey for government entities funding R&D activities. Response rate is 100%.

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class1	Description of users	Users’ needs
1 - International level	Eurostat The European Commission OECD	According to Commission Regulation No. 2019/2152/EU (No. 995/2012 until 2020)
1 - National level	Ministry of Interior, Ministry for National Economy, Ministry of Culture and Innovation, Prime Minister's Office	Provisional and final GBARD data
1 - National level	National Research, Development and Innovation Office	Provisional and final GBARD data

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	In general, HCSO registers data user’s opinion/feedback.
User satisfaction survey specific for GBARD statistics	No GBARD specific user satisfaction survey is carried out.
Short description of the feedback received	Not applicable.

12.3. Completeness

See below.

12.3.1. Data completeness - rate

not available

12.3.2. Completeness - overview

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.

	5 (Very Good)	4 (Good)	3 (Satisfactory)	2  (Poor)	1 (Very poor)	Reasons for missing cells
Provisional budget statistics1	X
Obligatory final budget statistics1	X
Optional final budget statistics2	X

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

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

12.3.3. Data availability

See below.

12.3.3.1. Data availability – Provisional data

	Availability1	Frequency of data collection	Gap years – years with missing data	Time of compilation (T+x)2	Comments
Total GBARD	Y-2005	annually
NABS Chapter level	Y-2005	annually
NABS Sub-chapter level	Y-2020	annually
Special categories - Biotech
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

12.3.3.2. 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-2005	annually
NABS Chapter level	Y-2005	annually
NABS Sub-chapter level	Y-2019	annually
Special categories - Biotech
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
Funding mode (institutional or project funding)	P, F	Y-2020	annually

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
-	-	-	-	-	-	-

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:

Local and regional government institutions are not covered in the data collection, because the funding source of R&D projects is located in the central government budget or when funded from own resources it is negligble.

 

b)      Measures taken to reduce their effect:

 Continuous monitoring of local and regional government R&D projects.

13.3.1.1. Over-coverage - rate

No deviation from FM2015.

13.3.1.2. Common units - proportion

Not requested.

13.3.2. Measurement error

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

a)       Description/assessment of measurement errors:

  No errors.

b)      Measures taken to reduce their effect:

Guidelines are provided in the filling instructions to help data providers. During data collection, the GBARD data is monitored to prevent double-counting of funds. All interrelated data being provided is checked for logical consistency, and when problematic data is found, data providers are requested for correction.

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: No non-reponse error.
• 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.

a)       Data processing and editing processes: No processing error.

b)      Description of errors: Not applicable.

c)       Measures taken to reduce their effect: Not applicable.

13.3.5. Model assumption error

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

Description/assessment: 

Not applicable.

14.1. Timeliness

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

14.1.1. Time lag - first result

Date of first release of national data: T+6

14.1.2. Time lag - final result

Date of first release of national data: T+12

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)	-23	-13
Reasoning for delay	Not available.	Not available.

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: in accordance with FM2015 recommendations, due to the insignificant role of local and regional government budget funds, it was excluded from the data collection.
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	Net principle is applied.
EU/other funds	Eurostat's EBS Methodological Manual on R&D Statistics	No deviation	EU funds are not included, only the national co-financing part.
Types of expenditure	FM2015 §12.15 to 12.18	No deviation
Current and capital expenditure	FM §12.15	No deviation	Both are included.
Extra budgetary funds	FM §12.8, 12.20, 12.38		Others funds are excluded.
Loans	FM §12.31, 12.32, 12.34		Forgiven loans are included but loans to be repaid are excluded.
Indirect funding, tax rebates, etc.	FM §12.31 - 12.38		Indirect funding is excluded.
Treatment of multi-annual projects	FM2015 §12.44	No deviation
Treatment of GBARD going to R&D abroad	FM2015 §12.19	No deviation	GBARD includes government-financed R&D performed abroad (CERN, COST, EUREKA etc.).
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	not applicable
Final data	8	2013	First data collection was for 2005. For 2007, data were estimated. There was a break in series for reference year 2013 - data of that year is not comparable with other years-, because of different treatment of multi-annual projects.

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

15.3. Coherence - cross domain

Hungarian GBARD and GERD data are not comparable (E.g. GBARD data is based on the funding of R&D that is paid to units in the reference period, but this is not necessarily used by the units for R&D activities in the same reference period.)

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 (in thousand HUF)	R&D allocations in the final budget delivered at T+12 (in thousand HUF)	Difference (of final data) (in thousand HUF)
Exploration and exploitation of the Earth	2363202	2108725	-254477
Environment	4406940	4611396	204456
Exploration and exploitation of space	14583412	26045834	11462422
Transport, telecommunication and other infrastructures	20276456	24407825	4131369
Energy	4869377	17899230	13029853
Industrial production and technology	19966635	24174075	4207440
Health	18759492	25709869	6950377
Agriculture	7052405	6764026	-288379
Education	4485994	20768271	16282277
Culture, recreation, religion and mass media	2324596	6631756	4307160
Political and social systems, structures and processes	2480273	7255162	4774889
General advancement of knowledge: R&D financed from General University Funds (GUF)	6404548	482418	-5922130
General advancement of knowledge: R&D financed from other sources than GUF	56580785	58918966	2338181
Defence	11585400	9301883	-2283517
TOTAL GBARD	176139515	235079437	58939922

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 work sub-contracted.
Data collection costs	Not available separately
Other costs	Not available separately
Total costs	Not available separately
Comments on costs
Not available separately. No work sub-contracted.

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)	19
Average Time required to complete the questionnaire in hours (T)1	2-3 hours
Average hourly cost (in national currency) of a respondent (C)	Not available.
Total cost	Not available.

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

17.1. Data revision - policy

Not applicable (GBARD data is based on direct data collection and is carried out annually. No revision of GBARD data after t+12 is needed.)

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

a)       Provisional data:

 Heads of budget units (ministries or other government units financing R&D activities)

b)      Final data:

 Heads of budget units (ministries or other government units financing R&D activities)

c)       General University Funds (GUF):

 Heads of budget units (ministries or other government units financing R&D activities)

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	direct survey	direct survey
Stage of data collection	Stage 5	Stage 7
Reporting units	heads of budget	heads of budget
Basic variable	Final budget appropriations	Expenditures
Time of data collection (T+x)1)	T-9	T+3
Problems in the translation of budget items	Not applicable.

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)

direct survey

18.3.3. Distribution by socioeconomic objectives (SEO)

Level of distribution of budgetary items – institution or programme/project	Not available.
Criterion of distribution – purpose or content	Purpose
Method of identification of primary objectives	The funding unit (data provider) identifies the primary obejctives.
Difficulties of distribution	Not applicable.

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:	GBARD_2023F_questionnaire_HU
Other relevant documentation of national methodology in English:
Other relevant documentation of national methodology in the national language:

Annexes:
GBARD_2023F_questionnaire_HU

18.4. Data validation

Data validation activities included: continous monitoring of the response rate, comparison of data with that of the previous cycle, verifying the statistics against expectations, and outlier detection.

18.5. Data compilation

See below.

18.5.1. Imputation - rate

No imputation.

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	Not applicable.
Description of the use of the coefficient (if applicable)	Not applicable.
Coefficient estimation method	Not applicable.
Frequency of updating of coefficients	Not applicable.

18.5.2.2. General University Funds (GUF)

Method(s) of separating R&D from non-R&D	Not applicable.
Description of the use of the coefficient (if applicable)	Not applicable.
Coefficient estimation method	Not applicable.
Frequency of updating of coefficients	Not applicable.

18.5.2.3. Other issues

Treatment of multi-annual programmes	Multi annual programmes are broken down and allocated to budgeted years.
Possibility to classify budgetary items by COFOG functions	Not applicable.
Possibility to classify budgetary items by other nomenclatures e.g. NACE	Not applicable.
Method of estimation of future budgets	Not applicable.

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.

30 October 2025

Not requested.

Government entities with individual budgets.

See below.

Not requested.

a) Calendar year:

 1 January  - 31 December 2023

b) Fiscal year: Same as calendar year.

    Start month: January 

    End month: December 

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

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

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:

 Heads of budget units (ministries or other government units financing R&D activities)

b)      Final data:

 Heads of budget units (ministries or other government units financing R&D activities)

c)       General University Funds (GUF):

 Heads of budget units (ministries or other government units financing R&D activities)

Yearly.

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.