1.1. Contact organisation
Central Statistical Bureau Republic of Latvia
1.2. Contact organisation unit
Business Statistics Methodology Section (BES);
Social Statistics Methodology Section (HES, GOV)
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Central Statistical Bureau of Latvia
Lāčplēša street 1, Rīga, LV 1010
Latvia
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
30 October 2025
2.2. Metadata last posted
30 October 2025
2.3. Metadata last update
30 October 2025
3.1. Data description
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.
Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
3.2. Classification system
Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.
3.2.1. National classification
| National nomenclature of SEO used | NABS used in chapter and sub-chapter level |
|---|---|
| Correspondence table with NABS | Not applicable |
3.2.2. NABS classification
| Deviations from NABS | No |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | No problems with NABS chapters and sub-chapters |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Not applicable |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | No difference from Frascati Manual |
|---|---|
| Coverage of R&D or S&T in general | GBARD statistics cover R&D |
| Fields of R&D (FORD) covered | No difference from Frascati Manual |
| Socioeconomic objective (SEO by NABS) | No difference from Frascati Manual |
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 | Ministries, Universities, Research institutions | Included | |
| Regional (state) government | Not applicable | Not applicable | |
| Local (municipal) government | Municipalities | Included |
3.4. Statistical concepts and definitions
The main variables collected in the framework of GBARD statistics are:
Government budget allocations for R&D (GBARD) are all allocations distributed to R&D in central (federal) government, regional (state) and local (municipal) government. They therefore refer to budget provisions, not to actual expenditure. Local government budget funds may not be included if their contribution is not significant or if the data cannot be collected.
3.5. Statistical unit
BES - enterprise, HES and GOV - institutions
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 | Budget items that contain an element of R&D |
|---|---|
| Estimation of the target population size | Not applicable |
3.7. Reference area
Latvia
3.8. Coverage - Time
See point 12.3.
3.9. Base period
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.
GBARD data are available in:
XDC: Thousands of national currency. All financial variables are provided in thousands of euros.
a) Calendar year: 2023
b) Fiscal year: Not applicable
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
Statistics Law
Cabinet regulation Nr. 741 "Official Statistics Programme for 2023–2025" (only in Latvian)
Annexes:
Statistics Law
Cabinet regulation Nr. 741 "Official Statistics Programme for 2023–2025" (only in Latvian)
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 available
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:
- Regulation (EC) No 223/2009 of the European Parliament and of the Council on European statistics
- Regulation (EU) 2016/679 of the European Parliament and of the Council
- Statistics Law.
b) Confidentiality commitments of survey staff:
- Code of Ethics
- Privacy Statement
7.2. Confidentiality - data treatment
Confidentiality is not used for GBARD data.
8.1. Release calendar
The release policy and release calendar exists and they are publicly accessible. All official statistics are published according to the data release calendar, at 13.00.
8.2. Release calendar access
Release calendar is available.
Annexes:
Release calendar
8.3. Release policy - user access
Users are informed that the data is being released by release calendar. Before the official time of publication, some officials are granted access to statistical data to ensure them time needed for data analysis, understanding and preparation of the point of view. Before provision of such information, the CSB assesses the need and benefits to the society, as well as concludes an agreement on compliance with data confidentiality. Information on the privileged access to statistical data is published on the CSB website.
Preliminary GBARD data: T+7
Final GBARD data: T+13
See 10.3.
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
10.3.1. Data tables - consultations
Not available
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Microdata are available under some conditions. |
|---|---|
| Access cost policy | Microdata are available under some conditions. |
| Micro-data anonymisation rules |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not available
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
Not available
10.6.1. Metadata completeness - rate
Not applicable
10.7. Quality management - documentation
See below.
10.7.1. Documentation and users’ requests
| Type(s) of data accompanying information available (metadata, graphs, etc.) | Definitions and explanations in online survey are available. |
|---|---|
| Request on further clarification | No |
| Measure to increase clarity | No |
| Impression of users on the clarity of the accompanying information to the data | No complains |
11.1. Quality assurance
CSB has introduced Quality Management System (QMS). The system is directed towards providing high user satisfaction and ensuring compliance with regulatory enactments. Based on the structure of Generic Statistical Business Process Model (GSBPM), QMS defines and at the level of procedures describes processes of statistical production as well as sets the persons responsible for the monitoring of processes at all stages of the statistical production. QMS defines the sequence how processes are implemented (i.e., activities to be performed (incl. verifications of processes and statistics, sequence and implementation requirements thereof, as well as persons responsible for the implementation)), procedures used in the evaluation of processes and statistics, as well as any improvements needed.
Since 2018, QMS of the CSB has been certified by the standard ISO 9001:2015 “Quality Management Systems. Requirements” (certified scope: Production of official statistics – planning, development, data acquisition, processing, analysis and dissemination).
11.2. Quality management - assessment
Quality of statistics is assessed in accordance with the existing requirements of external and internal regulatory enactments and in accordance with the established quality criteria.
Regulation (EC) no 223/2009 of the European Parliament and of the Council on European statistics states that European Statistics European statistics shall be developed, produced and disseminated on the basis of uniform standards and of harmonised methods. In this respect, the following quality criteria shall apply: relevance, accuracy, timeliness, punctuality, accessibility, clarity, comparability and coherence.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 - European level | The European Commission | Data according to Commission Regulation 2020/1197 |
| 1 - International organisations | OECD | Data according to Commission Regulation 2020/1197 |
| 1 - National level | Ministries of Economy, Finance, Education and Science | Summary table |
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 | No user satisfaction survey has been conducted. |
|---|---|
| User satisfaction survey specific for GBARD statistics | Not conducted |
| 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 | 5 | |||||
| Obligatory final budget statistics1 | 5 | |||||
| Optional final budget statistics2 | 4 |
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 | No | T+6 | |
| NABS Chapter level | Y - 2007 | Yearly | No | T+6 | |
| NABS Sub-chapter level | Y - 2016 | Yearly | No | T+6 | |
| 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 - 2006 | Yearly | No | T+12 | |
| NABS Chapter level | Y - 2006 | Yearly | No | T+12 | |
| NABS Sub-chapter level | Y - 2016 | Yearly | No | T+12 | |
| 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 special categories |
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 applicable
13.2.1. Sampling error - indicators
Not applicable
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 applicable
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 applicable
13.3.3.2. Item non-response - rate
Not applicable
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: Respondents responds through electronic online questionnaires (CAWI). The programme for data input does not allow inputting erroneous for it has logical and mathematical data controls.
b) Description of errors: Not applicable
c) Measures taken to reduce their effect: Not applicable
13.3.5. Model assumption error
Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).
Description/assessment: Not applicable
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Date of first release of national data: T+7
14.1.2. Time lag - final result
Date of first release of national data: T+13
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 available
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 | Calendar year |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Definition of GBARD | FM § 12.9 | No deviation | |
| Stages of data collection | FM2015 §12.41 | No deviation | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No deviation | |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | Cofinancing is included | |
| 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 | 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 | GBARD does not cover 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 point 12.3.
15.2.2. Breaks in time series
| Length of comparable time series | Break years1 | Nature of the breaks | |
|---|---|---|---|
| Provisional data | No break years | ||
| Final data | No break years |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
Not available
15.3.1. Coherence - sub annual and annual statistics
Not available
15.3.2. Coherence - National Accounts
Not available
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 | 655.577 | 655.577 | 0 |
| Environment | 10152.408 | 10152.408 | 0 |
| Exploration and exploitation of space | 1804.405 | 1804.404 | -0.001 |
| Transport, telecommunication and other infrastructures | 2571.914 | 2571.914 | 0 |
| Energy | 6299.455 | 6299.455 | 0 |
| Industrial production and technology | 7193.596 | 7192.978 | -0.618 |
| Health | 14540.177 | 14540.177 | 0 |
| Agriculture | 15816.224 | 15815.576 | -0.648 |
| Education | 3727.068 | 3727.068 | 0 |
| Culture, recreation, religion and mass media | 3216.581 | 3216.581 | 0 |
| Political and social systems, structures and processes | 2464.441 | 2464.441 | 0 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 10840.088 | 10840.088 | 0 |
| General advancement of knowledge: R&D financed from other sources than GUF | 34347.104 | 34383.579 | 36.475 |
| Defence | 4333.429 | 4333.039 | -0.39 |
| TOTAL GBARD | 117962.467 | 117997.285 | 34.818 |
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 | Confidential | No sub-contracting |
| Data collection costs | Confidential | No sub-contracting |
| Other costs | Confidential | No sub-contracting |
| Total costs | Confidential | No sub-contracting |
| Comments on costs | ||
| Confidential | ||
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
Revision Policy is an important component of good governance practice addressed more and more often in the international statistical society. The objective of the Revision Policy is to lay down the order of review or revision of the prepared and published data. The first chapter of the present document explains the terms applied in the Revision Policy, the second chapter shortly characterises the CSB Revision Policy, whereas the third chapter stipulates the revision cycle of the statistical data produced by the CSB.
Annexes:
Revision policy guidelines
17.2. Data revision - practice
Not available
17.2.1. Data revision - average size
Not available
18.1. Source data
a) Provisional data: Data sources are CSB annual "Survey of the performance of research activities in the business sector" (statistical report form 2-research), "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research) and "Report of scientific work by the public sector scientific institution" (3-research).
b) Final data: Data sources are CSB annual "Survey of the performance of research activities in the business sector" (statistical report form 2-research), "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research) and "Report of scientific work by the public sector scientific institution" (3-research).
c) General University Funds (GUF): Data source is CSB annual "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research)
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 | BES - Survey; The Ministry of Finance provides both provisional budget and final budget for research. Budget funding for research institutions is broken down by two organizations: the Council of Sciences un the Ministry of Education and Science. The CSB receives summarized information from the both above-mentioned organizations on the breakdown of the state budget that is compared with questionnaires submitted by research institutions on the research work in the institution. If relevant distinctions are found, the CBS contacts the research institution |
BES - Survey; The Ministry of Finance provides both provisional budget and final budget for research. Budget |
|
| Stage of data collection | 1. The Ministry of Finance prepares a scenario of the macroeconomic development of the country and tax income forecasts that are approved by the Cabinet of Ministers. 2. Respective ministries prepare requests regarding the budget of their branch, requests for additional financing of prior activities. The Ministry of Finance sums up these requests and submits to the Cabinet of Ministries. 3. The Cabinet of Ministries accepts the scenario of the macroeconomic development, tax income forecasts, |
||
| Reporting units | BES - enterprise; HES,GOV - institutions | BES - enterprise; HES,GOV - institutions | |
| Basic variable | Outlays | Outlays | |
| Time of data collection (T+x)1) | T+6 | T+12 | |
| Problems in the translation of budget items | No | ||
1) Time of data collection (T+x): T is assumed to represent the end of reference period. x expresses the number of months after (positive) or before (negative) T when data is collected.
18.3.2. General University Funds (GUF)
Data source is CSB annual "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research).
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 | No |
| Difficulties of distribution | No |
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: | Data sources are CSB annual R&D surveys:
|
| Other relevant documentation of national methodology in English: | Not available |
| Other relevant documentation of national methodology in the national language: | Not available |
Annexes:
Augstākās mācību iestādes, tās pārraudzībā esošās zinātniskās iestādes pārskats par zinātnisko darbu izpildi 2023. gadā
Pārskats par pētniecības un attīstības darbu izpildi uzņēmējdarbības sektorā 2023. gadā
Valsts sektora zinātniskās iestādes pārskats par zinātnisko darbu izpildi 2023. gadā
18.4. Data validation
Collected data has been compared with previous years.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
No imputated data.
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 and Frascati manual methodology |
|---|---|
| Description of the use of the coefficient (if applicable) | Not applicable |
| Coefficient estimation method | Not used |
| Frequency of updating of coefficients | Not applicable |
18.5.2.2. General University Funds (GUF)
| Method(s) of separating R&D from non-R&D | Not applicable |
|---|---|
| Description of the use of the coefficient (if applicable) | Not applicable |
| Coefficient estimation method | Not applicable |
| Frequency of updating of coefficients | Not applicable |
18.5.2.3. Other issues
| Treatment of multi-annual programmes | Reported in each 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 applicable
18.6.1. Seasonal adjustment
Not applicable
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.
Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
30 October 2025
The main variables collected in the framework of GBARD statistics are:
Government budget allocations for R&D (GBARD) are all allocations distributed to R&D in central (federal) government, regional (state) and local (municipal) government. They therefore refer to budget provisions, not to actual expenditure. Local government budget funds may not be included if their contribution is not significant or if the data cannot be collected.
BES - enterprise, HES and GOV - institutions
See below.
Latvia
a) Calendar year: 2023
b) Fiscal year: Not applicable
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:
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.
GBARD data are available in:
XDC: Thousands of national currency. All financial variables are provided in thousands of euros.
See below.
a) Provisional data: Data sources are CSB annual "Survey of the performance of research activities in the business sector" (statistical report form 2-research), "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research) and "Report of scientific work by the public sector scientific institution" (3-research).
b) Final data: Data sources are CSB annual "Survey of the performance of research activities in the business sector" (statistical report form 2-research), "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research) and "Report of scientific work by the public sector scientific institution" (3-research).
c) General University Funds (GUF): Data source is CSB annual "Report of the performance of scientific work by the higher education institution, the scientific institution under its supervision" (1-research)
Preliminary GBARD data: T+7
Final GBARD data: T+13
See 10.3.
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.
