1.1. Contact organisation
State Data Agency (Statistics Lithuania)
1.2. Contact organisation unit
Knowledge Economy and Special Survey Statistics Division
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
29 Gedimino Ave., LT-01500 Vilnius, Lithuania
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
28 October 2025
2.2. Metadata last posted
28 October 2025
2.3. Metadata last update
28 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 | State budget is structured according to the COFOG classification. |
|---|---|
| Correspondence table with NABS | Part of SEO between NABS and COFOG correspond directly. Education function in COFOG are analysed and restructured by objectives of institutions. |
3.2.2. NABS classification
| Deviations from NABS | No deviations but possibilities of SEO misunderstanding |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | Problems in identifying NABS sub-chapters. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Non-oriented research and GUF are not available by field of science (FOS). |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | The Frascati Manual definition is used. |
|---|---|
| Coverage of R&D or S&T in general | GBARD statistics cover R&D |
| Fields of R&D (FORD) covered | All field of science are covered. NSE+SSH. |
| Socioeconomic objective (SEO by NABS) | 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 | Includes ministries and other central bodies, universities, research institutes, research centres | included | |
| Regional (state) government | not included | ||
| Local (municipal) government | not included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Institutions funding R&D or administering R&D funds
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 | These are administrative, budgetary data and information from the survey data on the higher education sector |
|---|---|
| Estimation of the target population size | Not applicable |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested. 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: 2023
b) Fiscal year:
Start month: 1 January 2023
End month: 31 December 2023
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
Official statistics programme Part I is regulated by the Law on Official 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:
In the process of statistical data collection, processing and analysis and dissemination of statistical information, the State Data Agency fully guarantees confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality policy guidelines of the State Data Agency.
b) Confidentiality commitments of survey staff: not applicable
7.2. Confidentiality - data treatment
Statistical Disclosure Control Manual, approved by Order No DĮ-26 of 19 January 2024 of the Director General of the State Data Agency;
The State Data Governance Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the State Data Governance Information System, approved by Order No DĮ-163 of 20 August 2024 of the Director General of the State Data Agency.
8.1. Release calendar
No press release. Statistical information is published on the Official Statistics Portal according to the Official Statistics Calendar.
8.2. Release calendar access
8.3. Release policy - user access
Statistical information is prepared and disseminated under the principle of impartiality and objectivity, i.e. in a systematic, reliable and unbiased manner, following professional and ethical standards (the European Statistics Code of Practice), and the policies and practices followed are transparent to users and survey respondents.
All users have equal access to statistical information. All statistical information is published at the same time – at 9 a.m. on the day of publication of statistical information as indicated in the calendar on the Official Statistics Portal. Relevant statistical information is sent automatically to news subscribers.
The President and Prime Minister of the Republic of Lithuania, their advisers, the Ministers of Finance, Economy and Innovation, as well as Social Security and Labour of the Republic of Lithuania or their authorized persons, as well as, in exceptional cases, external experts and researchers have the right to receive early statistical information. The specified persons are entitled to receive statistical reports on GDP, inflation, employment and unemployment and other particularly relevant statistical reports one day prior to the publication of this statistical information on the Official Statistics Portal. Before exercising the right of early receipt of statistical information, a person shall sign an undertaking not to disseminate the statistical information received before it has been officially published.
Statistical information is published following the Official Statistics Dissemination Policy Guidelines and the Rules for Information Dissemination and Communication of the State Data Agency, approved by Order No DĮ-208 of 8 October 2024 of the Director General of the State Data Agency.
Annual
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
|---|---|---|
| Regular releases | 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) |
N | |
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Statistical indicators are published in Database of Indicators (Science and technology -> Research and development (R&D)).
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Not applicable |
|---|---|
| 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 | ||
| Data prepared for individual ad hoc requests | N | ||
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Methodological documents are published in the Official Statistics Portal section Research and development (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.) | R&D expenditure data table by function. |
|---|---|
| Request on further clarification | No requests |
| Measure to increase clarity | No |
| Impression of users on the clarity of the accompanying information to the data | Positive |
11.1. Quality assurance
Quality of statistical information and its production process is ensured by the provisions of the European Statistics Code of Practice and ESS Quality Assurance Framework.
In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at the State Data Agency. Main trends in activity of the State Data Agency aimed at quality management and continuous development in the institution are established in the Quality Policy.
Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify areas which need improvement and to promptly eliminate shortcomings.
More information on assurance of quality of statistical information and its preparation is published in the Quality Management section on the State Data Agency website.
11.2. Quality management - assessment
The quality of the statistical results meets the requirements of accuracy, timeliness and punctuality, comparability and consistency. The results are compared with the previous year. Outliers are identified and analysed. If inaccuracies are detected, statistical data are corrected.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1- European level | European Commission (DGs, Secretariat General), European Council, European Parliament, ECB, other European agencies etc. | To formulate science and technology policy. |
| 1- the national or regional level | Ministry of the Economy and Innovation, Ministry of Education, Science and Sport, Government Strategic Analysis Center (STRATA) | For the own market analysis and formulate R&D statistics policy |
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 | Yes, overall satisfaction survey |
|---|---|
| User satisfaction survey specific for GBARD statistics | No |
| Short description of the feedback received | The State Data Agency attaches great importance to strengthening relations with users. Users are given the opportunity to test questionnaires, submit their suggestions and requests via email and online, and regular meetings and training sessions with users are organized. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
All indicators established by the legislation are published.
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 | Not applicable. | ||||
| Obligatory final budget statistics1 | x | Not applicable. | ||||
| Optional final budget statistics2 | GBARD data are not compiled at NABS sub-chapter level. |
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-2007 | Yearly | T+6 | ||
| NABS Chapter level | Y-2007 | Yearly | T+6 | ||
| NABS Sub-chapter level | N | ||||
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | N |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.2. Data availability – Final data
| Availability1 | Frequency of data collection | Gap years – years with missing data | Time of compilation (T+x)2 | Comments | |
|---|---|---|---|---|---|
| Total GBARD | Y-2007 | Yearly | N | T+6 | |
| NABS Chapter level | Y-2007 | Yearly | N | T+6 | |
| NABS Sub-chapter level | N | ||||
| Special categories - Biotech | N | ||||
| Special categories - Nanotech | N | ||||
| Special categories - Security | N |
1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.
2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
12.3.3.3. Data availability – Other special categories
| Special categories | Stage1 | Availability1 | Frequency of data colletion | Gap years – years with missing data | Time of compilation (T+x)3 | Comments |
|---|---|---|---|---|---|---|
| No other special categories data are available |
1) Stage: P - provisional, F - final.
2) Availability of the data: No, data are not available, Y: Yes, data are available + start year.
3) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- 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.
- 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 |
- 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.
- If at least one out of the three criteria described above would not be fully met.
- In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.
- 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.
- 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: Not applicable.
b) Measures taken to reduce their effect: Not applicable.
13.3.1.1. Over-coverage - rate
Not applicable.
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.
a) Description/assessment of measurement errors: Not applicable.
b) Measures taken to reduce their effect: Not applicable.
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
a) Problems in obtaining data from targeted information providers:
Not applicable.
b) Measures taken to reduce their effect:
Not applicable.
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:
Not applicable.
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:
Statistical information is published in the 6 month after the end of the reference period.
14.1.2. Time lag - final result
Date of first release of national data:
Statistical information is published in the 6 month after the end of the reference period.
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)
14.2.1.1. Deadline and date of data transmission
| Transmission of provisional data | Transmission of final data | |
|---|---|---|
| Legally defined deadline of data transmission (T+_ months) | 6 | 12 |
| Actual date of transmission of the data (T+x months) | 6 | 12 |
| Delay (days) | 0 | 0 |
| Reasoning for delay |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.
| Concept / Issue | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Research and development | FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4). | No deviation | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | No deviation | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No deviation | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | No deviation |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Definition of GBARD | FM § 12.9 | GBARD includes outlays to R&D from the budget | |
| Stages of data collection | FM2015 §12.41 | No deviation | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | Net principle is applied. | |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | EU structural funds are not included. Direct EU funds are external funding not budgetary item. | |
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation | |
| Current and capital expenditure | FM §12.15 | Both current and capital expenditure are included in GBARD. | |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | Budgetary organisations take away income from contracts into the state budget and revenue of activity of these organisations is included in the state budget. | |
| Loans | FM §12.31, 12.32, 12.34 | Loans to be repaid are not included. | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | Indirect funding (tax rebates) 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 | Includes government-financed R&D performed abroad. |
| 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 | Not applicable | |
| Final data | 2007 | until 2007 no GUF. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD are based on report by funder. Government-financed GERD are based on reports by R&D performers. Differences are because the money is finally spent by the performer in a later year than the one in which it was committed by the funder.
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 | 8,486 | 8,486 | 0 |
| Environment | 1,484 |
1,484 |
0 |
| Exploration and exploitation of space | 1,071 |
1,071 |
0 |
| Transport, telecommunication and other infrastructures | 8,219 | 8,219 | 0 |
| Energy | 8,073 | 8,073 | 0 |
| Industrial production and technology | 24,326 | 24,326 | 0 |
| Health | 3,832 | 3,832 | 0 |
| Agriculture | 8,493 | 8,493 | 0 |
| Education | 1,486 | 1,486 | 0 |
| Culture, recreation, religion and mass media | 8,583 | 8,583 | 0 |
| Political and social systems, structures and processes | 8,044 | 8,044 | 0 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 156,158 | 156,158 | 0 |
| General advancement of knowledge: R&D financed from other sources than GUF | 39,440 | 39,440 | 0 |
| Defence | 0,763 | 0,763 | 0 |
| TOTAL GBARD | 178,925 | 178,925 | 0 |
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. | No subcontracting |
| Data collection costs | Not available. | |
| Other costs | Not available. | |
| Total costs | Not available. | |
| Comments on costs | ||
| Government budget allocation for expenditures for research and experimental development amounted to EUR 3.9 thousand. Administrative data are used. In this case there is no statistical reporting burden on respondents. | ||
1) The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | not available | |
| Average Time required to complete the questionnaire in hours (T)1 | not available | |
| 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
The revision policy applied by the State Data Agency is described in the Description of Procedure for Performance, Analysis and Publication of Revisions of Statistical Information.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data:
Administrative source, national budget account, compiled by the Ministry of Finance; data from a statistical survey on R&D in higher education.
b) Final data:
Administrative source, national budget account, compiled by the Ministry of Finance; data from a statistical survey on R&D in higher education.
c) General University Funds (GUF): data from a statistical survey on R&D in higher education.
18.2. Frequency of data collection
See 12.3.3.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | Budget text analysis and data from institutions and census R&D survey in HES | Budget text analysis and data from institutions and census R&D survey in HES | |
| Stage of data collection | Data collected by final budget data via actual outlays (money paid out during the year) | Data collected by final budget data via actual outlays (money paid out during the year) | |
| Reporting units | The institution funding/administering is the reporting units. In HES performing units | The institution funding/administering is the reporting units. In HES performing units | |
| Basic variable | Appropriations | Appropriations | |
| Time of data collection (T+x)1) | T+6 | T+6 | |
| Problems in the translation of budget items | No directly relation between COFOG and NABS | ||
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)
Census R&D survey in HES.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Institution |
|---|---|
| Criterion of distribution – purpose or content | purpose |
| Method of identification of primary objectives | By core activity of the institution. |
| Difficulties of distribution | Institution may use of the funding for several SEO and problem is to identify proportions. |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Not applicable |
| GBARD national questionnaire and explanatory notes in the national language: | Not applicable |
| Other relevant documentation of national methodology in English: | Methodological documents are published on the Official Statistics Portal in the section Research and Development (R&D). |
| Other relevant documentation of national methodology in the national language: | Methodological documents are published on the Official Statistics Portal in the section Research and Development (R&D). |
18.4. Data validation
In order to ensure statistical data quality, the data is checked (statistical data validation, comparison with the previous year of statistical data).
The eligibility of statistical data is determined on the basis of the quality of the information received. Statistical information is adjusted if adjusted administrative data had been received.
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 | R&D activities are separated according to the COFOG classification and Frascati manual methodology. |
|---|---|
| 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 | R&D questionnaire has questions about direct appropriations for R&D. |
|---|---|
| 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 | They are reported in each of budgetary years, but only that part which corresponds to the given year. |
|---|---|
| Possibility to classify budgetary items by COFOG functions | Yes |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | No |
| 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.
28 October 2025
Not requested.
Institutions funding R&D or administering R&D funds
See below.
Not requested.
a) Calendar year: 2023
b) Fiscal year:
Start month: 1 January 2023
End month: 31 December 2023
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:
- 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.
- 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:
Administrative source, national budget account, compiled by the Ministry of Finance; data from a statistical survey on R&D in higher education.
b) Final data:
Administrative source, national budget account, compiled by the Ministry of Finance; data from a statistical survey on R&D in higher education.
c) General University Funds (GUF): data from a statistical survey on R&D in higher education.
Annual
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.
