1.1. Contact organisation
Statistics Estonia
1.2. Contact organisation unit
Economic and Environmental Statistics Department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
51 Tatari Str, 10134 Tallinn, Estonia
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
22 October 2025
2.2. Metadata last posted
22 October 2025
2.3. Metadata last update
22 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 | The main classification NABS 2007 is used to compile GBARD data. |
|---|---|
| Correspondence table with NABS | Not applicable. |
3.2.2. NABS classification
| Deviations from NABS | No deviation. |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | Sub-chapters are not used as it is impossible to obtain GBARD data at national level in this detailed level. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Not available. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Consistent with the Frascati Manual (FM15) definition. |
|---|---|
| Coverage of R&D or S&T in general | R&D |
| Fields of R&D (FORD) covered | All |
| Socioeconomic objective (SEO by NABS) | Not applicable. |
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 | R&D performers financed by central government. | Included | |
| Regional (state) government | Not included | ||
| Local (municipal) government | R&D performers financed by local government. | Included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
State budget allocations for research and development
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 | Not applicable. |
|---|---|
| Estimation of the target population size | Not applicable. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See point 5.
3.9. Base period
Not requested.
Not requested.
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 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: not applicable
b) Confidentiality commitments of survey staff: not applicable
7.2. Confidentiality - data treatment
Confidentiality is not used for GBARD data.
8.1. Release calendar
Release calendar
Annexes:
Release calendar
8.2. Release calendar access
Release calendar.
Annexes:
Release calendar
8.3. Release policy - user access
All users have been granted equal access to official statistics: dissemination dates of official statistics are announced in advance and no user category (incl. Eurostat, state authorities and mass media) is provided access to official statistics before other users. Official statistics are first published in the statistical database. If there is also a news release, it is published simultaneously with data in the statistical database. Official statistics are available on the website at 8:00 a.m. on the date announced in the release calendar.
Preliminary GBARD data T+6
Final GBARD data T+12
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 | There is no separate press release for GBARD data, but the press release for RD includes the information about the GBARD data. Press is released in beginning of december (T+12) |
| 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 | GBARD data are published since 2016 in SE database together with other RD data |
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Database.
Annexes:
Database
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 |
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
There are guidelines for submitting GBARD data, which are attached to the questionnaire to be filled in by the ministries. The quidelines are based on the FM methodolgy.
There is no separate methodology document that is described in national publications or in on-line methodological repositories.
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.) | Statistics in online database is accompanied with adequate metadata. |
|---|---|
| Request on further clarification | Net approach in case of EU fund |
| Measure to increase clarity | No need |
| Impression of users on the clarity of the accompanying information to the data | The users’ phone interview survey showed they are satisfied with available data. |
11.1. Quality assurance
To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, the European Statistics Code of Practice and the Quality Assurance Framework of the European Statistical System (ESS QAF). Statistics Estonia is also guided by the requirements in § 7. “Principles and quality criteria of producing official statistics” of the Official Statistics Act.
11.2. Quality management - assessment
Statistics Estonia performs all statistical activities according to an international model (Generic Statistical Business Process Model – GSBPM). According to the GSBPM, the final phase of statistical activities is overall evaluation using information gathered in each phase or sub-process; this information can take many forms, including feedback from users, process metadata, system metrics and suggestions from employees. This information is used to prepare the evaluation report which outlines all the quality problems related to the specific statistical activity and serves as input for improvement actions.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 | President, Parliament, Ministries, political parties, governmental agencies and funds | Data on capacity and trends of Estonian R&D performance by socio-economic objectives for R&D and innovation and education policy decisions and strategy planning |
| 2 | Media for general public | Analysis of changes in Estonian R&D performance together with international comparisons |
| 3 | Researches and students | Statistics and analysis |
1) Users' class codification
1- Institutions:
- European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
- in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
- International organisations: OECD, UN, IMF, ILO, etc.
2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.
3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.
4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)
5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)
6- Other (User class defined for national purposes, different from the previous classes.)
12.2. Relevance - User Satisfaction
To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.
12.2.1. National Surveys and feedback
| Conduction of a user satisfaction survey or any other type of monitoring user satisfaction | Not available |
|---|---|
| User satisfaction survey specific for GBARD statistics | Not available |
| Short description of the feedback received | Not available |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not available
12.3.2. Completeness - overview
Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.
| 5 (Very Good) |
4 (Good) |
3 (Satisfactory) |
2 (Poor) |
1 (Very poor) |
Reasons for missing cells | |
|---|---|---|---|---|---|---|
| Provisional budget statistics1 | x | |||||
| Obligatory final budget statistics1 | x | |||||
| Optional final budget statistics2 | x | For NABS 12 and 13 subsectors information is incomplete as ministries do not have such detailed information. |
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 | Since 1999 | yearly | T+6 | ||
| NABS Chapter level | Since 1999 | yearly | T+6 | ||
| NABS Sub-chapter level | Not available | ||||
| Special categories - Biotech | Not available | ||||
| Special categories - Nanotech | Not available | ||||
| Special categories - Security | 1999 | yearly | T+6 |
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 | Since 1999 | yearly | T+12 | ||
| NABS Chapter level | Since 1999 | yearly | T+12 | ||
| NABS Sub-chapter level | Not available | ||||
| Special categories - Biotech | Not available | ||||
| Special categories - Nanotech | Not available | ||||
| Special categories - Security | Since 1999 | yearly | T+12 |
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:
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) | |||
|---|---|---|---|---|---|---|
| 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: 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: There are guidelines for respondents and trainings have been conducted.
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 available
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: data entry is checked for NABS codes as well as units of measurement. The processing also compares with previous years. In case of discrepancies, the Ministry of Education and Research will be contacted, which will provide data and specify the discrepancies.
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: Not applicable.
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Date of first release of national data: T+6
14.1.2. Time lag - final result
Date of first release of national data: T+12
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)
14.2.1.1. Deadline and date of data transmission
| Transmission of provisional data | Transmission of final data | |
|---|---|---|
| Legally defined deadline of data transmission (T+_ months) | 6 | 12 |
| Actual date of transmission of the data (T+x months) | 6 | 12 |
| Delay (days) | 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. | Information on sub-sectors is incomplete |
| 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 | Funds from budget, from governmental foundations and agencies |
| Stages of data collection | FM2015 §12.41 | No deviation. | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation. | |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No deviation. | |
| Types of expenditure | FM2015 §12.15 to 12.18 | No deviation. | |
| Current and capital expenditure | FM §12.15 | No deviation. | |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | No deviation. | |
| Loans | FM §12.31, 12.32, 12.34 | No deviation. | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation. | |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation. | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | Yes | Not included, partly available |
| 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 | 2016, 2015 | The Ministry of Education and Research (MER) collects and assembles the GBARD data at the national level based on the RD&I strategy and implementation plan “Knowledge based Estonia” (2014-2020). Data are collected through a questionnaire based on
|
|
| Final data | Since 2015 | In 2020, a correction was made, so that NABS 12 was separated from NABS 13, and the correction was introduced retroactively from 2015. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
There are some differences as GBARD data is a state allocation for research and development, GERD is the R&D expenditure in the reference year. Differences may arise from the interpretation of the concept of R&D definition and the time shift between the allocation and use of money also plays a role. In generally the GBARD and GERD data are comparable
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 | 2220,3 | 2220,3 | |
| Environment | 5123,5 | 5123,3 | -0,2 |
| Exploration and exploitation of space | 0 | 0 | |
| Transport, telecommunication and other infrastructures | 472,4 | 510,2 | +37,8 |
| Energy | 0 | 0 | |
| Industrial production and technology | 90881,8 | 91306,5 | +424,7 |
| Health | 2287,4 | 5285,2 | +2997,8 |
| Agriculture | 13832,4 | 13930,4 | +98 |
| Education | 183,8 | 183,8 | |
| Culture, recreation, religion and mass media | 9260,9 | 9260,9 | |
| Political and social systems, structures and processes | 2569,7 | 2156,9 | -412,8 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 44670,7 | 44670,7 | |
| General advancement of knowledge: R&D financed from other sources than GUF | 152170,3 | 153467,4 | +1297,1 |
| Defence | 9181,8 | 9181,8 | |
| TOTAL GBARD | 332855,0 | 337297,4 | +4442,4 |
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 | ||
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) | ||
| 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. | The data is provided by the Ministry of Education and Research and there is no information on time and 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
The data revision policy and notification of corrections are described in the section Principles of dissemination of official statistics of the website of Statistics Estonia.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: Data received by classification of socioeconomic objectives for GBARD.
b) Final data: Data received by classification of socioeconomic objectives for GBARD.
c) General University Funds (GUF): Data received by classification of socioeconomic objectives for GBARD without recommended subcategories.
18.2. Frequency of data collection
See 12.3.3.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | The Ministry of Education and Research (MER) collects and assembles the GBARD data at the national level based on the RD&I strategy and implementation plan “Knowledge based Estonia” (2014-2020). |
The Ministry of Education and Research (MER) collects and assembles the GBARD data at the national level based on the RD&I strategy and implementation plan “Knowledge based Estonia” (2014-2020). |
|
| Stage of data collection | Obligations. | Obligations. | |
| Reporting units | The Ministry of Education and Research (MER). | The Ministry of Education and Research (MER). | |
| Basic variable | Appropriations. | Appropriations. | |
| Time of data collection (T+x)1) | T+6 preliminar data, T+12 revised data if there are changes. | ||
| Problems in the translation of budget items | Not applicable. | ||
1) Time of data collection (T+x): T is assumed to represent the end of reference period. x expresses the number of months after (positive) or before (negative) T when data is collected.
18.3.2. General University Funds (GUF)
Survey questionnaire.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Institution or programme/project: programme/project. |
|---|---|
| Criterion of distribution – purpose or content | Purpose. |
| Method of identification of primary objectives | Purpose of the programme/project funding. |
| Difficulties of distribution | No diffciulties |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Not available. |
| GBARD national questionnaire and explanatory notes in the national language: | Not available. |
| Other relevant documentation of national methodology in English: | Not available. |
| Other relevant documentation of national methodology in the national language: | Not available. |
18.4. Data validation
The initial verification of the data at the micro-data level is carried out by the Ministry of Science and Education, which compiles the data. The SE checks the comparison of the data with the previous period, the units of measurement as well as the NABS categories
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 | The distinction following the explanations in the Frascati Manual FM15. |
|---|---|
| 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 | The distinction following the explanations in the Frascati Manual FM15. |
|---|---|
| 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 | Budgeted year |
|---|---|
| Possibility to classify budgetary items by COFOG functions | Not applicable |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Not applicable |
| Method of estimation of future budgets | Growth rates |
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.
22 October 2025
Not requested.
State budget allocations for research and development
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:
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: Data received by classification of socioeconomic objectives for GBARD.
b) Final data: Data received by classification of socioeconomic objectives for GBARD.
c) General University Funds (GUF): Data received by classification of socioeconomic objectives for GBARD without recommended subcategories.
Preliminary GBARD data T+6
Final GBARD data T+12
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.
