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

1.1. Contact organisation

Federal Public Planning Service Science Policy

1.2. Contact organisation unit

MERI - Monitoring & Evaluation of Research & Innovation

1.3. Contact name

Restricted from publication

1.4. Contact person function

Restricted from publication

1.5. Contact mail address

Simon Bolivarlaan 30 Bd Simon Bolivar / 1000 Brussel - Bruxelles

1.6. Contact email address

Restricted from publication

1.7. Contact phone number

Restricted from publication

1.8. Contact fax number

Restricted from publication

2.1. Metadata last certified

27 October 2023

2.2. Metadata last posted

27 October 2023

2.3. Metadata last update

27 October 2023

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

Besides and parallel to the NABS nomenclature, a national "CFS/STAT nomenclature" is used.
This nomenclature is provided as annex "CFS-STAT_f.pdf""("Belgian CFS-STAT nomenclature"; version in French) and as annex "CFS-STAT_n.pdf" ("Belgian CFS-STAT nomenclature"; version in Dutch).
The CFS/STAT nomenclature= the Belgian Nomenclature for the Analysis and Comparison of the Estimated R&D Appropriations of the Belgian Governments. This standardised nomenclature was developed to classify all appropriations uniformly according to their destination, whatever the budget. This provides a better idea of the institutional or functional destination of these appropriations, as well as a reference baseline making it possible accurately to analyse and compare the following:
- budget appropriations selected as basic data used for the estimate;
- keys used to determine the share of R&D in these budget appropriations;
- keys used for the functional distribution of these amounts by NABS objectives.

Correspondence table with NABS

N/A

3.2.2. NABS classification

Deviations from NABS	No deviations.
Problems in identifying / separating NABS chapters and sub chapters	No problems for NABS chapters (no data for sub-chapters).
Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D	No data available for distribution by field of science (for the two mentioned NABS chapters).

3.3. Coverage - sector

See below.

3.3.1. General coverage

Definition of R&D	Frascati Manual definition is used to identify R&D.
Coverage of R&D or S&Tin general	GBARD statistics cover R&D.
Fields of R&D (FORD) covered	GBARD data cover NSE and SSH.
Socioeconomic objective (SEO by NABS)	GBARD data cover SEO's.

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	Since 1989, Government includes regional and community authorities.	Y
Regional (state) government		Y	Contributions of provincial government are not significant.
Local (municipal) government		N	Contributions of local government are not significant.

3.4. Statistical concepts and definitions

Not requested.

3.5. Statistical unit

N/A

3.6. Statistical population

See below.

3.6.1. National target population

The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units, which can be accessed through the frame and the survey data really refer to this population.

Definition of the national target population	All budget lines of the different Belgian authorities that contain an element of R&D.
Estimation of the target population size	427 budget lines in 2021.

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:

2021

b) Fiscal year:

Start month:

End month:

6.1. Institutional Mandate - legal acts and other agreements

See below.

6.1.1. European legislation

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

6.1.2. National legislation

Not applicable

6.1.3. Standards and manuals

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

- EBS Methodological Manual on R&D Statistics

6.2. Institutional Mandate - data sharing

Not requested.

7.1. Confidentiality - policy

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

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

a) Confidentiality protection required by law:

b) Confidentiality commitments of survey staff:

7.2. Confidentiality - data treatment

N/A

8.1. Release calendar

Data are released to the public on BELSPO/MERI website after approval by all competent regions and communities in Belgium, usually in April/May.

8.2. Release calendar access

Not applicable

8.3. Release policy - user access

Not applicable

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	Y	In principle, every year a brief electronic publication is produced. It contains an update of the GBARD data. This e-publication is (usually) announced in a short press review, informing as well that more updated and detailed figures are available on the website.
Ad-hoc releases

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)	N	GBARD data are made available on the website of the Federal Science Policy Office (https://meri.belspo.be/site/gbard_en.stm). An electronic publication with a selection of GBARD tables with some commentary is made available, once a year, on the same website a short time after approval of the data.
Specific paper publication (paper, online)

1) Y – Yes, N - No

10.3. Dissemination format - online database

Tables with aggregate figures

https://meri.belspo.be/site/gbard_en.stm

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	N/A
Access cost policy	N/A
Micro-data anonymisation rules	N/A

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		GBARD data are made available on the MERI website of the Federal Science Policy Office (https://meri.belspo.be/site/gbard_en.stm). An electronic publication with a selection of GBARD tables with some commentary is made available, once a year, on the same website a short time after approval of the data.
Data prepared for individual ad hoc requests	N
Other	N

1) Y – Yes, N - No

10.6. Documentation on methodology

See below.

10.6.1. Metadata completeness - rate

Not requested.

10.7. Quality management - documentation

See below.

10.7.1. Information and clarity

Type(s) of data accompanying information available (metadata, graphs, etc.)	The Flemish GBARD data, together with explanatory notes and a brief analysis are yearly published (EWI-Budget Browser; EWI-Speurgids). Additional information can be consulted online on 'www.ewi-vlaanderen.be/speurgids'. These GBARD data, together with the explanatory notes, give an overview of the science and R&D policy and is of use to many people.
Request on further clarification	The users’ feedback is minimal.
Measure to increase clarity	We publish a GBARD Dashboard with dynamic aggregates.
Impression of users on the clarity of the accompanying information to the data	N/A

11.1. Quality assurance

Not applicable

11.2. Quality management - assessment

Weakness: unchanging R&D coefficients from GUF-dates and scientific institutes (R&D coefficients from other budget items may change from one year to another as a result of policy decisions).

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class¹	Description of users	Users’ needs
1- European level	Eurostat: Commission Regulation No. 995/2012
1- International level	OECD
1- National level	National and regional level
4- Researchers and students	Researchers and students

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	A user satisfaction survey is not undertaken.
User satisfaction survey specific for GBARD statistics	Not applicable
Short description of the feedback received	Not applicable

12.3. Completeness

See below.

12.3.1. Data completeness - rate

Not applicable

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 (1989)	Annual		T (+6)
NABS Chapter level	Y (1989)	Annual		T (+6)
NABS Sub-chapter level
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 (1965)	Annual	1970-1971-1972-1973	T (+12)
NABS Chapter level	Y (1989)	Annual		T (+12)
NABS Sub-chapter level	Y (only for the year 1983)
Special categories - Biotech	Y (only for the year 1984)
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
Does not apply.

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⁾
Sampling errors	Coverage errors	Measurement errors	Processing errors	Non response errors	Model-assumption Errors¹⁾	Perceived direction of the error²⁾
	2	1	3	-	4	+/-

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:

b) Measures taken to reduce their effect:

13.3.1.1. Over-coverage - rate

Not requested

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:

b) Measures taken to reduce their effect:

13.3.3. Non response error

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

a) Problems in obtaining data from targeted information providers:

b) Measures taken to reduce their effect:

c) Effect of non-response errors on the produced statistics:

13.3.3.1. Unit non-response - rate

Not requested.

13.3.3.2. Item non-response - rate

Not requested.

13.3.4. Processing error

Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.

a) Data processing and editing processes:

b) Description of errors:

c) Measures taken to reduce their effect:

13.3.5. Model assumption error

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

Description/assessment:

14.1. Timeliness

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

14.1.1. Time lag - first result

Date of first release of national data:

14.1.2. Time lag - final result

Date of first release of national data:

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)
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	The GBARD data are derived from the general budget of State expenditures totally financed by revenues (tax and other). Principle of universality is applied, which excludes R&D financed by other sources. Other funds are excluded.
Stages of data collection	FM2015 §12.41	No deviation
Gross / net approach, net principle	FM2015 §12.20 and 12.21	Corresponding revenue is excluded from 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 deviation
Current and capital expenditure	FM §12.15	GBARD include both current and capital expenditure
Extra budgetary funds	FM §12.8, 12.20, 12.38	Other funds are excluded.
Loans	FM §12.31, 12.32, 12.34	There is no distinction for loans (both types of loans (forgiven and to be repaid) are included).
Indirect funding, tax rebates, etc.	FM §12.31 - 12.38	No deviation
Treatment of multi-annual projects	FM2015 §12.44
Treatment of GBARD going to R&D abroad	FM2015 §12.19	Minor deviation possible concerning GBARD going to abroad.	GBARD include government-financed R&D performed abroad. A) R&D programmes (contracts, initiatives and contributions), not limitative: ESA space programmes, grants, bilateral projects, UNESCO projects, Eureka initiatives, IVVV, NDSC networks, ESO national committee, GARS (UNESCO), BCCM (Bio), EMB Net, Eurotrac, COST, ETSAP, etc. B) International organizations: European University Institute (Florence), Belgian American Education Foundation, Institute Von Karman (=International organisation in Belgium): NATO (share in the internal budget of the civilian bodies of NATO), IHO/OHI (share in the budget of the International Hydro graphic Organisation, Monaco), NEA and OECD database, IAEA/AIEA, UNEP/PNUE (contribution to the environment fund), Eumetsat, ESO, ECMWF, WMO, IUCN, EMBC, EMBL, ESRF, 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		1989	Government budget appropriations or outlays for R&D (GBARD) include the resources of the Communities (x2) and the Regions (x3). This was not the case in the years before 1989.
Final data		1) 1970-1971-1972-1973 2) 1989	1) Total GBARD figures for these four years were "estimated" to avoid gaps for these years. 2) Government budget appropriations or outlays for R&D (GBARD) include the resources of the Communities (x2) and the Regions (x3). This was not the case in the years before 1989.

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

15.3. Coherence - cross domain

No differences with those explained in the chapter 8.8 of the Frascati Manual.

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	50730	53287	5.0%
Environment	22229	20858	-6.2%
Exploration and exploitation of space	283825	283558	-0.1%
Transport, telecommunication and other infrastructures	16355	19625	20.0%
Energy	65307	63893	-2.2%
Industrial production and technology	1149999	1211456	5.3%
Health	60272	59298	-1.6%
Agriculture	60443	78685	30.2%
Education	9950	9954	0.03%
Culture, recreation, religion and mass media	49760	48873	-1.8%
Political and social systems, structures and processes	133055	97683	-26.6%
General advancement of knowledge: R&D financed from General University Funds (GUF)	590961	601970	1.9%
General advancement of knowledge: R&D financed from other sources than GUF	920731	1087522	18.1%
Defence	28329	27802	-1.9%
TOTAL GBARD	3441944	3664464	6.5%

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	70.000 euro (0.8 FTE)
Data collection costs
Other costs	5.000 euro
Total costs	75.000 euro	No payments to other Government agencies. Estimated costs other Government agencies: 20.000 euros.
Comments on costs
Not applicable

1) The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.

16.2. Components of burden and description of how these estimates were reached

	Value	Computation method
Number of Respondents (R)	No survey done	No survey done
Average Time required to complete the questionnaire in hours (T)¹	No survey done	No survey done
Average hourly cost (in national currency) of a respondent (C)	No survey done	No survey done
Total cost	Not applicable	Not applicable

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

17.1. Data revision - policy

Not requested.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

a) Provisional data: All budget lines of the different Belgian authorities that contain an element of R&D

b) Final data: All budget lines of the different Belgian authorities that contain an element of R&D

c) General University Funds (GUF): see 18.3.2.

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; Systematic "Screening" of allocations on basis of the Frascati manual and the NABS (with concerned department by phone, e-mail,…)	Budget text analysis; Systematic "Screening" of allocations on basis of the Frascati manual and the NABS (with concerned department by phone, e-mail,…)	Systematic "screening" of the allocations on basis of the Frascati Manual and the NABS (with feedback (if necessary) from the concerned ministerial departments (by phone, e-mail, …)
Stage of data collection	Stage ii) {Flemish community : stage iv)}	Stage v) {Flemish community : stage vi)}
Reporting units
Basic variable	French: Crédits d’ordonnancement Flemish: ordonnanceringskredieten.	French: Crédits d’ordonnancement Flemish: ordonnanceringskredieten.
Time of data collection (T+x)¹⁾	T - 1 month	T - 1 month
Problems in the translation of budget items	The accompanying descriptions of the budget items are written in Dutch or French.

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)

Data procured by the Authorities of the 2 Communities (25% key is applied).

18.3.3. Distribution by socioeconomic objectives (SEO)

Level of distribution of budgetary items – institution or programme/project	Project or institution.
Criterion of distribution – purpose or content	Distribution is made according to: 1. The main content of the project or programme. 2. The purpose.
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:	No guestionnaire is used to collect the data. All Belgian authorities collect their budget lines that contain an element of R&D and transfer them to the responsable person for the Federal Authority. In addition, the official documents of the Chamber are used to verify and/or correct the data.
GBARD national questionnaire and explanatory notes in the national language:
Other relevant documentation of national methodology in English:
Other relevant documentation of national methodology in the national language:

18.4. Data validation

Data is validated by all competent authorities.

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	25% of general university funds (GUF) is considered as R&D; 55% of governmental budget to scientific institutions (SI) is considered as R&D.
Description of the use of the coefficient (if applicable)
Coefficient estimation method	The estimation of R&D is made (for the different authorities) by listing credits by activity (R&D activities and other S&T activities). When credits have the same destination, they are totalised. This total is classified according to activity. When the destination cannot be classified, fixed key of distribution is used (representative of the last situation).
Frequency of updating of coefficients	Coefficients have not been reviewed.

18.5.2.2. General University Funds (GUF)

Method(s) of separating R&D from non-R&D	N/A
Description of the use of the coefficient (if applicable)	N/A
Coefficient estimation method	N/A
Frequency of updating of coefficients	N/A

18.5.2.3. Other issues

Treatment of multi-annual programmes	Multi annual programmes are reported in the years in which the budget is authorised.
Possibility to classify budgetary items by COFOG functions	N/A
Possibility to classify budgetary items by other nomenclatures e.g. NACE	Besides and parallel to the NABS nomenclature, a national "CFS/STAT nomenclature" is used.
Method of estimation of future budgets	Future GBARD data are estimated occasionally (linear progression).

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

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.

27 October 2023

Not requested.

N/A

See below.

Not requested.

a) Calendar year:

2021

b) Fiscal year:

Start month:

End month:

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

1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.

2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:

a) Coverage errors,

b) Measurement errors,

c) Non response errors and

d) Processing errors.

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

Not requested.

See below.

a) Provisional data: All budget lines of the different Belgian authorities that contain an element of R&D

b) Final data: All budget lines of the different Belgian authorities that contain an element of R&D

c) General University Funds (GUF): see 18.3.2.

Yearly

See below.