1.1. Contact organisation
Statistical Office of the Republic of Slovenia (SURS)
1.2. Contact organisation unit
Demography and Social Statistics Division, Social Services Statistics Section
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Litostrojska cesta 54, 1000 Ljubljana, Slovenija
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
23 October 2025
2.2. Metadata last posted
7 October 2025
2.3. Metadata last update
7 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 | National classification is not used. |
|---|---|
| Correspondence table with NABS | Not available |
3.2.2. NABS classification
| Deviations from NABS | No deviation from NABS classification. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | The problems in identifying / separating NABS chapters and sub-chapters encounter mainly due to the structure of the budget. NABS reporting is difficult for respondents as the relevant items in the budget are often "hidden" under innapropriate category names (from which the proper meaning is not always clear) and, in addition, some categories are often combined. In some cases it is difficult to determine the proper socio-economic objective(s). |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Yes. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | FM`s definition is used. |
|---|---|
| Coverage of R&D or S&T in general | GBARD statistics cover only R&D. |
| Fields of R&D (FORD) covered | According to the FM 2015 all fields of research and development are covered (Natural sciences, Engineering and technology, Medical and Health sciences, Agriculture sciences, Social sciences and Humanities). |
| Socioeconomic objective (SEO by NABS) | All SEO by NABS are covered. |
3.3.2. Definition and coverage of government
GBARD statistics are assumed to report detailed data on all the government's budget items that may support R&D activities and to measure or estimate their R&D content. For the purposes of GBARD, the Government sector comprises (a) the central (federal) government, (b) regional (state) government and (c) local (municipal) government subsectors (FM2015, Chapter 12).
| Levels of government | Definition | Included / Not included | Comments |
|---|---|---|---|
| Central (federal) government | Government institutions (ministries, government offices and other relevant agencies) involved in the allocation of financial resources earmarked for research and development activities in the Republic of Slovenia. | Included | |
| Regional (state) government | Not applicable. | Not included | In Slovenia there is no regional (provincial) government. |
| Local (municipal) government | Not applicable. | Not included | In Slovenia local government is clearly separated from central government. |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Government budget allocations.
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 unit of observation is the national budget funds allocated for R&D. The survey is based on a full coverage, meaning that all relevant national budget funds allocated for R&D were included in the data collection. Reporting units are government authorities and public sector bodies (including agencies, public funds, and other legal entities under public law) that manage state budget resources earmarked for research and development (R&D). The data sources are the national budget and the official records maintained by the reporting units. |
|---|---|
| Estimation of the target population size | Around 30 reporting units are included in the survey. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested.
Not requested.
a) Calendar year: 2023
b) Fiscal year: 2023
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
- Annual Programme of Statistical Survey (LPSR) (only in Slovene).
- National Statistics Act (OJ RS, No. 45/95 and 9/01) (only in Slovene available at National Statistics Act).
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:
The National Statistics Act (hereinafter the ZDSta) stipulates within fundamental principles of national statistics in Article 2 that “national statistics shall be implemented on the principles of … confidentiality …”.
b) Confidentiality commitments of survey staff:
All employees are obliged to protect the content of personal and individual data and data on reporting units which they learn during their work as official secrecy. All employees sign a statement of data protection and thus confirm that they are informed about the issue. The obligation to protect the official secrecy continues after the termination of employment.
7.2. Confidentiality - data treatment
All GBARD data collected are treated as confidential and are used only for statistical purposes. By following general statistical confidentiality framework used in SURS, statistics can be published only in aggregate form, i.e. in a manner that does not allow recognition of the unit to which data relate. Identifiable information can be published only exceptionally in cases where the unit gives its written consent to publish it. More information on statistical confidentiality is available at Statistical Confidentiality.
8.1. Release calendar
Release calendar is publicly accessible.
8.2. Release calendar access
8.3. Release policy - user access
All data and metadata information are published and are accessible to users through various channels; among them is the most important website. The information on the website is available free of charge and is also available at English, for the widest possible use that is actively promoted.
The release policy deternines the dissemination of statistical data to all users at the same time.
The data are published yearly, namely in September.
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 | Data on GBARD are published in the:
|
| 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 |
|
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
See 10.1.1
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 | More information on microdata access is available at Access Information for researchers |
|---|---|
| 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 | Aggregate figures | |
| Data prepared for individual ad hoc requests | N | Aggregate figures | |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Methodological explanation on SURS’s website are available at Government Budget Allocation for R&D
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.) | Graphs, methodological explanations, quality report |
|---|---|
| Request on further clarification | Most common request for further clarifications is about the difference between GBARD and GERD figures, namely related to R&D performed in the government sector and to funding for intramural R&D received from government. |
| Measure to increase clarity | Yes, key differences between GBARD and GERD figures are summarised in methodological explanations. |
| Impression of users on the clarity of the accompanying information to the data | The clarity is good. |
11.1. Quality assurance
See 11.2.
11.2. Quality management - assessment
Overall quality of GBARD statistics is good.
The coverage of reporting units is full. GBARD statistics domain follow general quality management activities used in SURS (including the European Statistics Code of Practice and the Fundamental Principles of Official Statistics). Detailed methodological instructions for completing questionnaite are available. Data validation is performed in collaboration with reporting units if necessary. Discussion of results, substantive matters and key issues are points on the agenda or the subjects under discussion of the Research and Development, and Technology Statistics Advisory Committee.
However, there are still some aspects to be improved at GBARD statistics. Despite the available methodological guidelines and instructions reporting units still have some problems with understanding the content/definitions of R&D, especially with identifying or estimating the real/proper content of the budget items (i.e. capturing R&D from the budget items) as their records are not principally intended for GBARD reporting.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
| 1 - Institution | European level: European Commission (EC) | Data needs for determining European research policy and international benchmarking. |
|---|---|---|
| National level: prime minister, parliament, ministries, political parties, government offices, etc. | Detailed data on capacity and trends of Slovenian R&D performance for R&D and innovation and education policy decisions and strategy planning. | |
| International level: Organization for Economic Cooperation and Development (OECD) | International benchmarking. | |
| 2 - Social actors | Tertiary education institutions | Data for self-estimates and planning. |
| 3 - Media | Different media | General interest in R&D data for monitoring the policymaker`s political goals. |
| 4 - Researchers and student | Reseachers and students | Data for statistics, in-depth analyses. |
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 | SURS measured general user satisfaction in 2024 with the average score of 8.4 (on a scale from 1 – disagree completely to 10 – agree completely). |
|---|---|
| User satisfaction survey specific for GBARD statistics | It is not specific for GBARD statistics. |
| Short description of the feedback received | GBARD statistics falls within the scope of the Statistical Advisory Committee on Research and Development Activities and Technologies. The last meeting of the Committee was held on 4 April 2023. More information on the operation of the Committe is available on the following website Statistical Advisory Committee (in Slovenian only). Data users frequently request for GBARD figures expressed as a percentage of gross domestic product (GDP). |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
All data required were provided.
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 | Annual | T+9 | ||
|---|---|---|---|---|---|
| NABS Chapter level | Y | Annual | T+9 | ||
| NABS Sub-chapter level | Y | Annual | T+9 | ||
| 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 - 1996 | Annual | T+9 | ||
|---|---|---|---|---|---|
| NABS Chapter level | Y | Annual | T+9 | ||
| NABS Sub-chapter level | Y | Annual | T+9 | ||
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | N |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.3. Data availability – Other special categories
| Special categories | Stage1 | Availability1 | Frequency of data colletion | Gap years – years with missing data | Time of compilation (T+x)3 | Comments |
| GBARD by fields of research and development | Final | Y | Annual | T+9 | ||
|---|---|---|---|---|---|---|
| GBARD by sector of performance | Final | Y | Annual | T+9 | ||
| GBARD by type of transfer | Final | Y | Annual | T+9 | ||
| Transnationally coordinated R&D | Final | Y | Annual | T+9 |
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:
The coverage errors were not identified.
b) Measures taken to reduce their effect: Not applicable
13.3.1.1. Over-coverage - rate
There are no over-coverage errors in the survey.
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:
Data error detection controls are focused on the consistency of the totals derived from different breakdowns (sector of performance, type of support, socio-economic objective, field of research and development). In case an important intra-annual change in GBARD figures is identified, one or more contacts with the reporting unit are made in order to obtain additional explanatory notes on data deviation or to arrange data retransmission. Data are collected with web survey. To reduce the phase of cleaning data some additional controls were included in the questionnaire.
The main reasons that cause measurement errors are: the questionnaire is filled in by several persons or organisational units, non-compliance with the methodological instructions, subjective and often unreliable and inconsistent assessment of funds as data can not be derived directly from reporting unit's records.
b) Measures taken to reduce their effect:
If some errors are detected by the person responsible at SURS for data editing, it is first determined whether an error is remedied without contacting the reporting units, or the error is unclear and requires additional explanations form the reporting units. The reporting unit is always contacted when it is not clear from the reported data whether they are correct or not. Is also applies to the reporting unit when the reported data are very different form the data reported by the same reporting units for previous years.
In order to reduce the number of errors, it is very important that we regularly get feedback from reporting units by recontacting them. It is important to "educate" persons responsible for reporting, provide them methodological support, the reporting units in order to correctly and accurately fill in the questionnaire. The number of measurement errors were reduced by using web questionnaire.
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:
There is no problems.
b) Measures taken to reduce their effect:
No non-response errors.
c) 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:
To reduce the phase of cleaning data additional controls were included in the questionnaire.
b) Description of errors:
So far no processing errors have been identified.
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: 21 September (T +9)
14.1.2. Time lag - final result
Date of first release of national data: 21 September (T +9);
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) | T+6 | T+12 |
|---|---|---|
| Actual date of transmission of the data (T+x months) | T+6 | T+ 12 |
| Delay (days) | 0 |
0 |
| Reasoning for delay |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.
| Concept / Issue | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
| Research and development | FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4). | No deviation | |
|---|---|---|---|
| Coverage of levels of government | FM2015, §12.5 to 12.9 | No deviation | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No deviation | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | No deviation |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
| Definition of GBARD | FM § 12.9 | No deviation | No national deviations. According to the FM 2015, GBARD statistics includes all outlays to be met from taxation or other government revenue within the budget. |
|---|---|---|---|
| Stages of data collection | FM2015 §12.41 | No deviation | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation | Net principle followed. |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No deviation | EU funds for R&D are not included. |
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation | |
| Current and capital expenditure | FM §12.15 | No deviation | GBARD includes both current and capital expenditure. |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | No deviation | No other extra budgetary funds are not included. |
| Loans | FM §12.31, 12.32, 12.34 | No deviation | Loans to be repaid are not included. |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation | Indirect funding, tax rebates, etc. are excluded from GBARD. |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | No deviation | GBARD covers government financed R&D performed abroad (R&D programmes, international organisations listed in the FM, bilateral co-operation). |
| 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 | VAT is not directly included in the GBARD data. |
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 | 2024 | The data since 2024 also include the part of the budget allocated to higher education study activities carried out in public higher education institutions (supevision of doctoral and master's students (ISCET 7 and INSCET 8) to prove their competence by undertaking relatively indipendent study with the elemnts of novelty, supervision of students by university staff in their research projects and personal education (own readind) carried out specifically for a reserch project). | |
| Final data | 2023 | The data since 2023 also include the part of the budget allocated to higher education study activities carried out in public higher education institutions (supevision of doctoral and master's students (ISCET 7 and INSCET 8) to prove their competence by undertaking relatively indipendent study with the elemnts of novelty, supervision of students by university staff in their research projects and personal education (own readind) carried out specifically for a reserch project). |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD data include only R&D financed by central government, while Government-financed GERD data include also R&D financed by local government.
GBARD data also include government funds which are allocated to R&D abroad, while Government-financed GERD covers only R&D performed on national teritory.
GBARD data does not include funds for R&D coming into the country from foreign public sources. Therefore, EU Structural Funds are not included. On the other hand, part of the Government-financed GERD includes also EU Structural Funds.
GBARD and Government-financed GERD are related to the calendar year. However, funds for R&D can be spent by the R&D performer in later years following the year in which it was committed by the funder, while Government-financed GERD shows the actual spending.
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 | 11271 | 9771 | -1500 |
|---|---|---|---|
| Environment | 24327 | 18768 | -5559 |
| Exploration and exploitation of space | 2217 | 1585 | -632 |
| Transport, telecommunication and other infrastructures | 9888 | 7773 | -2115 |
| Energy | 21260 | 18622 | -2637 |
| Industrial production and technology | 42483 | 36993 | -5490 |
| Health | 56619 | 45014 | -11605 |
| Agriculture | 27249 | 22766 | -4483 |
| Education | 7376 | 6207 | -1169 |
| Culture, recreation, religion and mass media | 9918 | 7745 | -2174 |
| Political and social systems, structures and processes | 15871 | 13628 | -2243 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 1305 | 144184 | +142879 |
| General advancement of knowledge: R&D financed from other sources than GUF | 157275 | 172874 | +15599 |
| Defence | 13290 | 12294 | -996 |
| TOTAL GBARD | 400349 | 518223 | +117874 |
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 | 21529 EUR | No sub-contracting |
|---|---|---|
| Data collection costs | 60 EUR | No sub-contracting |
| Other costs | No sub-contracting | |
| Total costs | 21589 EUR | No sub-contracting |
| Comments on costs | ||
| n | ||
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) | 31 |
|
| Average Time required to complete the questionnaire in hours (T)1 | 7,3 hours or 437 min | |
| Average hourly cost (in national currency) of a respondent (C) | ||
| Total cost |
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
Provisional data are not disseminated. Only final data are published.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data:
Government budget allocations
b) Final data:
Government budget allocations
c) General University Funds (GUF):
Government budget allocations
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 | Data are collected by web questionnaire | Data are collected by web questionnaire | |
|---|---|---|---|
| Stage of data collection | According to the FM2015 provisional budget data are based on figures of government R&D appropriations indicated in the provisional budget (as approved by the Parliament at the beginning of the budget year). | Final budget appropriations for R&D are reported on the basis of (revised) final budget approved during the budget year. | |
| Reporting units | Reporting units are government authorities and public sector bodies (including agencies, public funds, and other legal entities under public law) that manage state budget resources earmarked for research and development (R&D). | Reporting units are government authorities and public sector bodies (including agencies, public funds, and other legal entities under public law) that manage state budget resources earmarked for research and development (R&D). | |
| Basic variable | Both appropriations and outlays are included. | Both appropriations and outlays are included. | |
| Time of data collection (T+x)1) | The initial budget appropriations and final outlays are collected by the same questionnaire. Reporting units (ministries and governmental agencies) have to fill in the questionnaire by the end of July. Initial budget appropriations data are available in September. | The initial budget appropriations and final outlays are collected by the same questionnaire. Reporting units (ministries and governmental agencies) have to fill in the questionnaire by the end of July (T+7). Initial budget appropriations data are available in September (T+9). | |
| Problems in the translation of budget items | The problems encountered are mainly related to the structure of the budget. Reporting is difficult as some of the items in the budget are sometimes "hidden" unde inappropriate names (from which the true meaning is not always straightforward) and some categories are ofted combined. | ||
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)
Web questionnaire.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | According to the programme or project level for all year. |
|---|---|
| Criterion of distribution – purpose or content | According to the purpose of the R&D programme or project, sometimes also according to the general content of the R&D programme or project. |
| Method of identification of primary objectives | |
| Difficulties of distribution | The problems usually encounter due to the structure of the budget as some of the relevant items in the budget are "hidden" under inappropriate names (from which the proper meaning is not always clear) and some categories are combined. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Questionnaires (only in Slovenian) on SURS's website are available at Questionnaires Methodological Explanations Quality Reports; Theme: Development and Technology, Subtheme: Research and Development Methodological explanations and Quality reports on SURS's website are available at Questionnaires Methodological Explanations Quality Reports; Theme: Development and Technology, Subtheme: Research, development and inovation.
|
| GBARD national questionnaire and explanatory notes in the national language: | Questionnaires on SURS's website are available at Methods Questionnaires Methodological Explanations Quality Reports; Theme: Development and Technology, Subtheme: Research and Development Methodological explanations and quality reports on SURS's website are available at Methods Questionnaires Methodological Explanations Quality Reports; Theme: Development and Technology, Subtheme: Research, development and inovation. |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: |
18.4. Data validation
Validation activities are: comparing the statistics with previous cycles, investigating inconsistencies in the statistics.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
The imputations were not made.
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 | Reporting units often estimate the "percentage" of R&D of certain budget item (i.e. research infrastructure, etc.). Estimation is done on an individual basis so that each relevant budget item receives a different percentage of R&D. |
|---|---|
| Description of the use of the coefficient (if applicable) | |
| Coefficient estimation method | Reporting units often estimate the "percentage" of R&D of certain budget item (i.e. research infrastructure, etc.). Estimation is done on an individual basis so that each relevant budget item receives a different percentage of R&D. |
| Frequency of updating of coefficients | Estimation of the percentage of R&D in the individual budget item is recalculated each year. |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | Not available |
|---|---|
| Description of the use of the coefficient (if applicable) | Not available |
| Coefficient estimation method | Not available |
| Frequency of updating of coefficients | Not available |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | Multi-annual programmes are reported according to the actual expenses in the current year. Multi-annual projects are allocated to the GBARD for the year(s) in which they are budgeted. |
|---|---|
| Possibility to classify budgetary items by COFOG functions | Until now data have not been allocated to COFOG functions. |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Classify by NACE is not possible. |
| Method of estimation of future budgets | Key assumptions are made on information on expected/predicted inflation rate, annual growth of GDP and expected/predicted government revenues. |
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.
7 October 2025
Not requested.
Government budget allocations.
See below.
Not requested.
a) Calendar year: 2023
b) Fiscal year: 2023
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:
Government budget allocations
b) Final data:
Government budget allocations
c) General University Funds (GUF):
Government budget allocations
The data are published yearly, namely in September.
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.
