1.1. Contact organisation
Statistical Office in Szczecin
1.2. Contact organisation unit
Statistics Centre for Science, Technology, Innovation and Information Society.
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Jana Matejki Street 22
70-530 Szczecin
Poland
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
23 October 2023
2.2. Metadata last posted
23 October 2023
2.3. Metadata last update
23 October 2023
3.1. Data description
Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.
Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.
The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).
Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
3.2. Classification system
Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.
3.2.1. National classification
| National nomenclature of SEO used | National nomenclature of SEO used in Poland is in accordane with Frascati Manual 2015. |
| Correspondence table with NABS | NABS Chapters |
3.2.2. NABS classification
| Deviations from NABS | Data not compiled at sub-chapters level. |
| Problems in identifying / separating NABS chapters and sub chapters | Provisional and final data could considerably differ. Data not compiled at sub-chapters level. |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | Data are compiled at NABS chapters level. |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Frascati Manual 2015 |
| Coverage of R&D or S&T in general | GBARD statistics cover R&D. |
| Fields of R&D (FORD) covered | GBARD statisctics coved all fields of R&D (FORD). |
| Socioeconomic objective (SEO by NABS) | GBARD statisctics coved all socioeconomic objective (SEO by NABS). |
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 | Central government covers Ministries and government agencies. | included | |
| Regional (state) government | Not applicable | not included | In Poland units from General government (S.13) is classified by SNA only to central government or local government. |
| Local (municipal) government | Voivodship Offices and Marshal Offices | included |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Institutions allocating budgetary funds for R&D.
3.6. Statistical population
See below.
3.6.1. National target population
Restricted from publication
3.7. Reference area
GBARD data are presented only at the country level.
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.
The units of measures used in the survey are thousand units of national currency.
Calendar year.
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
Law issued on 29 VI 1995 on Official Statistics and Regulation of the Council of Ministers on Statistical Surveys Program of Public 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:
Law issued on 29 VI 1995 on Official Statistics.
b) Confidentiality commitments of survey staff:
Law issued on 29 VI 1995 on Official Statistics.
7.2. Confidentiality - data treatment
Microdata for GBARD are subject to statistical confidentiality.
8.1. Release calendar
In Poland there is release calendar.
8.2. Release calendar access
The release calendar is accessible on the Statistics Poland website.
8.3. Release policy - user access
The data is published for the first time in a singature study that is published on the Statistics Poland website, but GBARD data is published only in the Eurostat and OECD database.
Frequency of data collection is annually and the published data refer to the year.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
| Regular releases | Y | Eurostat and OECD database |
| 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
https://ec.europa.eu/eurostat/data/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 | Microdata are not available. |
| Access cost policy | Microdata are not available. |
| Micro-data anonymisation rules | Microdata are not available. |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
| Internet: main results available on the national statistical authority’s website | Y | Aggregate figures | Eurostat and OECD database |
| Data prepared for individual ad hoc requests | N | ||
| Other | N |
N1) Y – Yes, N - No
10.6. Documentation on methodology
The national reference metadata files are not available because polish GBARD survey is based on the metodology included in the FM 2015.
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.) | Analytical notes included in annual raport. Additional explanations for the users (assistance) are also provided if required, by the Statistical Information Centre as well as by the authors of the survey. |
| Request on further clarification | No |
| Measure to increase clarity | Preparations of the GBARD methodology. |
| Impression of users on the clarity of the accompanying information to the data | Explanations were comprehensive. |
11.1. Quality assurance
Quality assurance framework is based on quality guidelines, training courses for all persons engaged in the R&D survey, the use of best practices, quality reviews, self-assessments, compliance monitoring.
11.2. Quality management - assessment
Source of GBARD data in Poland are final country budget and report on research and development (R&D) - PNT-01. Use two sources of data allows to collect all necessary data and improves their quality. Data are comparable with data from foreign countries.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
| 1- International | Eurostat, OECD | Data used for the European Scoreboard and its further development |
| 1- National | Ministry of Education and Science | Data for analysis, publishing, etc. |
| 4 - Researchers and students | Researchers and students | Data for analysis, publishing, study, etc. |
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
User satisfaction surveys is not used.
12.2.1. National Surveys and feedback
| Conduction of a user satisfaction survey or any other type of monitoring user satisfaction | Users' satisfaction survey is not carried out but the statistical program is announced every year and is given for consultation to ministries, universities and scientists, voivodships’authorities, who can put forward any suggestions which are taken into consideration and statistical plan may be changed. |
| User satisfaction survey specific for GBARD statistics | No |
| Short description of the feedback received | Not applicable. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Data completeness - rate = 100%
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 | 5 |
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-1991 | Annual | 2002, 2003 | T+6 months | |
| NABS Chapter level | Y-2004 | Annual | 2009, 2010, 2011 | T+6 months | |
| NABS Sub-chapter level | Not applicable. | ||||
| Special categories - Biotech | Not applicable. | ||||
| Special categories - Nanotech | Not applicable. | ||||
| Special categories - Security | Not applicable. |
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-1991 | Annual | 2002, 2003 | T+12 | |
| NABS Chapter level | Y-2004 | Annual | 2009, 2010, 2011 | T+12 | |
| NABS Sub-chapter level | Not applicable | Not applicable | Not applicable | Not applicable | |
| Special categories - Biotech | Not applicable | Not applicable | Not applicable | Not applicable | |
| Special categories - Nanotech | Not applicable | Not applicable | Not applicable | Not applicable | |
| Special categories - Security | Not applicable | Not applicable | Not applicable | Not applicable |
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 |
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 | |||
| Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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 | 5 | ||||
| National public funding to transnationally coordinated R & D | 5 |
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:
Measurement errors included errors with data collection and respondent mistakes.
b) Measures taken to reduce their effect:
To reduce measurement errors we train persons responsible for R&D survey, before the survey starts we do questionnaire testing and prepare guidelines for responsents.
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
a) Problems in obtaining data from targeted information providers:
There is a problem with defence data because of the state secret.
b) Measures taken to reduce their effect:
The missing data is obtained from the budget impementation report.
c) Effect of non-response errors on the produced statistics:
Obtaining data from a different source allows to minimize the effect of the lack of data from the survey.
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: Model assumption errors do not occur.
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: 22.06.2022
14.1.2. Time lag - final result
Date of first release of national data: 30.12.2022
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) = 0
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 | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | No | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | No |
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 | All definitions included in GBARD statistics are accordance with FM. |
| Stages of data collection | FM2015 §12.41 | No | |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | No | Net principle |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No | EU funds are excluded. |
| Types of expenditure | FM2015 §12.15 to 12.18 | No | |
| Current and capital expenditure | FM §12.15 | No | Both included |
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | No | Reporting units should included all budgetary funds in the report. |
| Loans | FM §12.31, 12.32, 12.34 | No | Loans to be repaid are not included. |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No | Indirect funding, tax rebates, etc. are excluded. |
| Treatment of multi-annual projects | FM2015 §12.44 | No | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | No | GBARD cover government financed R&D performed abroad. Example organisations names: |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | No | |
| Method of identification of primary objective | Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6 | No |
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 | 10 | 2012 | Since 2012 GBARD data not include European Comission funds. |
| Final data | 10 | 2012 | Since 2012 GBARD data not include European Comission funds. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD data cover funds that have been assigned but did not have to be spend by the R&D performer yet. GERD cover funds that have been already spent on R&D therfore GBARD and GERD data cannot be directly compared.
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 | 8012.3 | 8012.3 | 0 |
| Environment | 64265.6 | 64265.6 | 0 |
| Exploration and exploitation of space | 40856.1 | 40856.1 | 0 |
| Transport, telecommunication and other infrastructures | 26168.9 | 26168.9 | 0 |
| Energy | 38984.3 | 38984.3 | 0 |
| Industrial production and technology | 104014.3 | 104014.3 | 0 |
| Health | 333675.2 | 333675.2 | 0 |
| Agriculture | 19795.4 | 19795.4 | 0 |
| Education | 204.5 | 204.5 | 0 |
| Culture, recreation, religion and mass media | 914.7 | 914.7 | 0 |
| Political and social systems, structures and processes | 12542.2 | 12542.2 | 0 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 6055607.8 | 6057484.5 | 1876.7 |
| General advancement of knowledge: R&D financed from other sources than GUF | 3431394.9 | 4778023.2 | 1346628.3 |
| Defence | 533092.2 | 533092.2 | 0 |
| TOTAL GBARD | 10669528.4 |
12018033.4 | 1348505 |
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 applicable | Not applicable |
| Data collection costs | Not applicable | Not applicable |
| Other costs | Not applicable | Not applicable |
| Total costs | Not applicable | Not applicable |
| Comments on costs | ||
| Details of costs by requested structure are not available | ||
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) | 22 | data from questionarie |
| Average Time required to complete the questionnaire in hours (T)1 | 4.4 | |
| Average hourly cost (in national currency) of a respondent (C) | Not applicable | |
| Total cost | Not applicable |
1) T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)
17.1. Data revision - policy
In order to prepare final data, information from final country budget and report on research and development (R&D) are additionally compared with information provided by R&D performers. Used these sources of data allows to improves quality of data. No other data revisions are carried out.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data:
Preliminary data from the report on research and development (R&D) and data from the final country budget
b) Final data:
Final data from the report on research and development (R&D) and data from the final country budget
c) General University Funds (GUF):
Final data from the report on research and development (R&D)
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 | administration data and data from survey | administration data and data from survey | |
| Stage of data collection | the administrative data comes from the report on the implementation of the state budget date from survey are collected by electronic questionnaire portal |
the administrative data comes from the report on the implementation of the state budget date from survey are collected by electronic questionnaire portal |
|
| Reporting units | Funding/administering institutions | Funding/administering institutions | |
| Basic variable | Government budget allocations for R&D | Government budget allocations for R&D | |
| Time of data collection (T+x)1) | T+6 | T+12 | |
| 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)
Cooperation with Ministry of Education and Science and additionally data from the report on research and experimental development (R&D) in higher education sector.
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Level of distribution of budgetary items – institution or programme/project included in GBARD survey |
| Criterion of distribution – purpose or content | Purpose |
| Method of identification of primary objectives | Direct derivation |
| Difficulties of distribution | Not applicable |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
| GBARD national questionnaire and explanatory notes in English: | PNT-01_2021_ENG |
| GBARD national questionnaire and explanatory notes in the national language: | PNT-01_2021 |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: |
Annexes:
Report on R&D for 2021 - in English
Report on R&D for 2021 - in the national language
18.4. Data validation
Procedures for checking and validating data include:
- checking response rates are as required;
- comparing the statistics with previous cycles (if applicable);
- confronting the statistics data from survey against administrative data;
- investigating inconsistencies in the statistics.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Restricted from publication
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 | Comparison of data from financing institutions with data from R&D performens |
| 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 | Use in survey data from the report on research and experimental development (R&D) in higher education sector |
| 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 | Multi-annual projects are allocated to the GBARD of the year(s) in which they are budgeted, not in the years of performance. |
| 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 | 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.
23 October 2023
Not requested.
Institutions allocating budgetary funds for R&D.
See below.
GBARD data are presented only at the country level.
Calendar year.
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.
The units of measures used in the survey are thousand units of national currency.
See below.
a) Provisional data:
Preliminary data from the report on research and development (R&D) and data from the final country budget
b) Final data:
Final data from the report on research and development (R&D) and data from the final country budget
c) General University Funds (GUF):
Final data from the report on research and development (R&D)
Frequency of data collection is annually and the published data refer to the year.
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.
