1.1. Contact organisation
Institute of Statistics (INSTAT) (Albania)
1.2. Contact organisation unit
Unit for R&D, Innovation, Information Technology Statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
info@instat.gov.al
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
3 October 2025
2.2. Metadata last posted
13 October 2025
2.3. Metadata last update
3 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 | 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. |
|---|---|
| Correspondence table with NABS | Data are presented in accordance with the Nomenclature for the Analysis and Comparison of Scientific Programme's and Budgets 2007 (NABS 2007). |
3.2.2. NABS classification
| Deviations from NABS | No deviation |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | The Nomenclature for the Analysis and Comparison of Scientific Programmes and Budgets – NABS 2007 was used in monitoring of the allocation of the Government Budget appropriations or outlays according to the socio-economic objectives, which is correlated with the Frascati Manual. This Nomenclature explains the socio-economic objectives, that is, the purpose of the spent appropriations or outlays for the R&D in 14 categories. |
| 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 | INSTATuses Frascati Manual definition of R&D. The definition is sent with the questionnaire |
|---|---|
| Coverage of R&D or S&T in general | RD only |
| Fields of R&D (FORD) covered | Not applicable |
| Socioeconomic objective (SEO by NABS) | Covers government-financed R&D performed in government establishments but also government-financed R&D in higher education institutions (HEI-S) |
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 | Included | |
| Regional (state) government | Partially | ||
| Local (municipal) government | Only main municipal of Tirana is included | Partially |
3.4. Statistical concepts and definitions
Not requested.
3.5. Statistical unit
Bugdet Alocation for RD activity from the Government.
Government Institutions and Higher education institutions (HEI-S).
- Unit responded for GBARD 2023 = 60;
- Unit having GBARD data on GBARD 2023= 46.
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 | All R&D projects and institutional support in the given reference year |
|---|---|
| Estimation of the target population size | Does not apply. |
3.7. Reference area
Government Institutions and HEI-s in Albanian territory.
3.8. Coverage - Time
Not requested. See point 5.
Annually produced from 2020
3.9. Base period
Not requested.
National currency (ALL- Albanian Lek)
a) Calendar year: The data delivered corresponds to the calendar year 2023
b) Fiscal year: 01 January- 31 December 2023
Start month: January 2023
End month: 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
Legal basis for the production of GBARD statistics in country level are:
- Law No.17/2018 "On Official Statistics";
- Official Statistics National Program, 2022-2026;
- The annual plan for the implementation of the Official Statistics Program.
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: ensured
b) Confidentiality commitments of survey staff: ensured
7.2. Confidentiality - data treatment
Albanian Institute of Statistics protects and does not disseminate data it has obtained or it has access to, which enable the direct or indirect identification of the statistical units. Albania Institute of Statistics takes all appropriate preventive measures so as to render impossible the identification of individual statistical units by technical or other means that might reasonably be used by a third party. Statistical data that could potentially enable the identification of the statistical unit are disseminated by Albania Institute of Statistics if and only if:
- The data have been treated, as it is specifically set out in the Regulation Regulation (EC) No 223/2009 on European statistics, in such a way that their dissemination does not prejudice statistical confidentiality or
- The statistical unit has given its consent, without any reservations, for the disclosure of data.
The confidential data that are transmitted to Albania Institute of Statistics are used exclusively for statistical purposes and the only persons who have the right to have access to these data are the personnel engaged in this task. Issues referring to the observance of statistical confidentiality are examined by the staff working in Albania Institute of Statistics. The responsibilities of this staff are to recommend on: which detailed level the statistical data can be disseminated, so as the identification, either directly or indirectly, of the surveyed statistical unit is not possible; the anonymization criteria for the microdata provided to users; the access granting to researchers on confidential data for scientific purposes.
8.1. Release calendar
No data published for GBARD statistics.
8.2. Release calendar access
No data published for GBARD statistics.
National Institute of Statistics of Albania Calendar: Instat's Calendar
8.3. Release policy - user access
No data published for GBARD statistics.
In accordance with Article 34 of Law no. 17/2018 "On Official Statistics", are distributed so that all users have immediate and equal rights, all available media formats, INSTAT and agencies are used, having distribution responsibilities in the program, requiring meet any requirement of any organization or individual for unpublished data or specific analyses. Channels from which users can get the results are as follows:
- Website - online release;
- Written requests (by mail or email);
Data request, session available for external users.
GBARD data are disseminated annually.
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 | No data published for GBARD statistics. |
| Specific paper publication (paper, online) |
N | No data published for GBARD statistics. |
1) Y – Yes, N - No
10.3. Dissemination format - online database
No data published for GBARD statistics
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Not applicable |
|---|---|
| Access cost policy | Not applicable |
| Micro-data anonymisation rules | Not applicable |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
|---|---|---|---|
| Internet: main results available on the national statistical authority’s website | N | No data published for GBARD statistics. | |
| Data prepared for individual ad hoc requests | N | No data published for GBARD statistics. | |
| Other | N | No data published for GBARD statistics. |
1) Y – Yes, N - No
10.6. Documentation on methodology
Detailed information about the national survey methods applied (Metadata) as well as about the quality of the data (Quality Reports) is provided by the countries to Eurostat systematically on an annual base according to the new legal base. The new format for metadata and quality reports is the Single Integrated Metadata Structure (SIMS reporting).
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.) | Not requested |
|---|---|
| Request on further clarification | Not requested |
| Measure to increase clarity | Not requested |
| Impression of users on the clarity of the accompanying information to the data | Not requested |
11.1. Quality assurance
INSTAT is committed to ensure the highest quality with respect to the compilation of statistical information. In accordance with the Statistics Law No 17/2018 "On Official Statistics", INSTAT use statistical methods and processes in compliance with internationally recognized scientific principles and standards conduct ongoing analyses of the statistics with a view to quality improvements and ensure that statistics are as up-to-date. In performing its tasks it follows the general principles of quality management from the European Statistics Code of Practice. INSTAT declares that it takes into account the following principles: impartiality, quality of processes and products, user orientation, employee orientation, effectiveness of statistical processes, reducing the workload for respondents.
Efforts were made to engage more units in the process by sending reminders via official letters or emails. We also provided continuous support to ensure accurate data and maintained regular communication with the respondents.
11.2. Quality management - assessment
GBARD statistics involve identifying all the budget items of all public administration units that may support R&D activities and measuring or estimating their R&D content. Advantages of this approach include the ability both to report significantly more timely government R&D funding totals since they are based on budgets and to link these totals to policy considerations through classification by socioeconomic objectives. Concerns exist in the lack of information for the possible or potential units which can not be identified to declare data on transnationally coordinated funds on R&D.
Efforts were made to engage more units in the process by sending reminders via official letters or emails. We also provided continuous support to ensure accurate data and maintained regular communication with the respondents.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1. European level | Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc. | |
| 1. 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 | |
| 1. International organisations: | OECD, UN, IMF, ILO, etc. | |
| 2- Social actors | Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level. |
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 national user satisfaction survey has been undertaken |
|---|---|
| User satisfaction survey specific for GBARD statistics | No national user satisfaction survey has been undertaken |
| Short description of the feedback received | No national user satisfaction survey has been undertaken |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not applicable
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 | ||||||
| Obligatory final budget statistics1 | x | |||||
| Optional final budget statistics2 |
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 | |||||
| NABS Chapter level | |||||
| NABS Sub-chapter level | Yes |
Annual |
No |
T+12 |
|
| Special categories - Biotech | |||||
| Special categories - Nanotech | |||||
| Special categories - Security |
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 | Yes |
Annual |
No |
T+12 month |
|
| NABS Chapter level | Yes |
Annual |
No |
T+12 month |
|
| NABS Sub-chapter level | Yes |
Annual |
No |
T+12 month |
|
| Special categories - Biotech | |||||
| Special categories - Nanotech | |||||
| Special categories - Security |
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 |
|---|---|---|---|---|---|---|
| not applicable |
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, administrative data used | ||||||
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 | |||||
| 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: Not applicable
13.3.3. Non response error
Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
a) Problems in obtaining data from targeted information providers: Not applicable
b) Measures taken to reduce their effect: Not applicable
c) Effect of non-response errors on the produced statistics: Not applicable
13.3.3.1. Unit non-response - rate
Not requested.
13.3.3.2. Item non-response - rate
Not requested.
13.3.4. Processing error
Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.
a) Data processing and editing processes: Not applicable
b) Description of errors: Not applicable
c) Measures taken to reduce their effect: Not applicable
13.3.5. Model assumption error
Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).
Description/assessment: Not applicable
14.1. Timeliness
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
14.1.1. Time lag - first result
Date of first release of national data: No data released
14.1.2. Time lag - final result
Date of first release of national data: No data released
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) | Not applicable |
T+12 |
| Delay (days) | Not applicable |
No |
| Reasoning for delay | Not applicable |
No |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.
| Concept / Issue | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Research and development | FM2015 Chapter 2 (mainly paragraphs 2.3 and 2.4). | No deviation | |
| Coverage of levels of government | FM2015, §12.5 to 12.9 | No deviation | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197: Annex 1, Table 20 | No deviation | |
| Reference period | Reg. 2020/1197: Annex 1, Table 20 | No deviation |
15.1.3. Deviations from recommendations
GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.
| Methodological issues | Reference to recommendations | Deviation from recommendations | National definition / Treatment / Deviations from recommendations |
|---|---|---|---|
| Definition of GBARD | FM § 12.9 | No deviation |
|
| 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 | ||
| Current and capital expenditure | FM §12.15 | ||
| Extra budgetary funds | FM §12.8, 12.20, 12.38 | ||
| Loans | FM §12.31, 12.32, 12.34 | ||
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | ||
| Treatment of multi-annual projects | FM2015 §12.44 | ||
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | ||
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | ||
| Method of identification of primary objective | Eurostat's EBS Methodological Manual on R&D Statistics, topic 2, statement B.6 |
15.2. Comparability - over time
See below.
15.2.1. Length of comparable time series
See below.
15.2.2. Breaks in time series
| Length of comparable time series | Break years1 | Nature of the breaks | |
|---|---|---|---|
| Provisional data | Not applicable | ||
| Final data | 2023 |
No |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
The GBARD data have been compared with other R&D statistics (such as BERD, GOVERD, HERD) to ensure cross-domain coherence in classifications, funding sources, and total figures. Meanwhile, for business enterprises, statistical surveys are conducted using samples, and in government, and higher education institutions, the data are collected via official administrative records.
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 | Not yet in place | Not yet in place | Not yet in place |
| Environment | Not yet in place | Not yet in place | Not yet in place |
| Exploration and exploitation of space | |||
| Transport, telecommunication and other infrastructures | |||
| Energy | |||
| Industrial production and technology | |||
| Health | |||
| Agriculture | |||
| Education | Not yet in place | Not yet in place | Not yet in place |
| Culture, recreation, religion and mass media | Not yet in place | Not yet in place | Not yet in place |
| Political and social systems, structures and processes | |||
| General advancement of knowledge: R&D financed from General University Funds (GUF) | |||
| General advancement of knowledge: R&D financed from other sources than GUF | Not yet in place | Not yet in place | Not yet in place |
| Defence | No data | No data | No data |
| TOTAL GBARD |
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 separately | No sub-contracting |
| Data collection costs | Not available separately | No sub-contracting |
| Other costs | Not available separately | No sub-contracting |
| Total costs | Not available separately | No sub-contracting |
| 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) | Not applicable | Not applicable |
| Average Time required to complete the questionnaire in hours (T)1 | Not applicable | Not applicable |
| Average hourly cost (in national currency) of a respondent (C) | Not applicable | Not applicable |
| Total cost | Not applicable | 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
There is no data revision policy for GBARD
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: Not applicable
b) Final data: 20 December 2024
c) General University Funds (GUF): Not applicable
18.2. Frequency of data collection
See 12.3.3.
Annual data collection
18.3. Data collection
See below.
18.3.1. Data collection overview
| Provisional data | Final data | Comments | |
|---|---|---|---|
| Data collection method | No provisional data yet |
Administrative data collected via official letter from Institutions and HEIs |
|
| Stage of data collection | Not applicable |
|
|
| Reporting units | Not applicable |
GOV and HEI-s |
|
| Basic variable | Not applicable |
Fundings and NABS |
|
| Time of data collection (T+x)1) | Not applicable |
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)
The data comes from administrative souces via official letter from of the Higher Education Institutions ( Universities).
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Not yet in place |
|---|---|
| Criterion of distribution – purpose or content | Not applicable |
| Method of identification of primary objectives | Not applicable |
| 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: | Not available |
| GBARD national questionnaire and explanatory notes in the national language: | |
| Other relevant documentation of national methodology in English: | Not available |
| Other relevant documentation of national methodology in the national language: |
18.4. Data validation
- Outlier detection (early in the process)
- Checking the population coverage
- Investigating inconsistencies in the statistics.
- Benchmark the responses with the responses of the previous year;
18.5. Data compilation
See below.
18.5.1. Imputation - rate
No imputation due to administrative data
Budget analysis
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 reporting unit is provided with the Frascati Manual definition of R&D and is separating itself R&D from non R&D in the projects. |
|---|---|
| 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 | Frascati Manual |
|---|---|
| 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 | Not applicable |
|---|---|
| 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.
3 October 2025
Not requested.
Bugdet Alocation for RD activity from the Government.
Government Institutions and Higher education institutions (HEI-S).
- Unit responded for GBARD 2023 = 60;
- Unit having GBARD data on GBARD 2023= 46.
See below.
Government Institutions and HEI-s in Albanian territory.
a) Calendar year: The data delivered corresponds to the calendar year 2023
b) Fiscal year: 01 January- 31 December 2023
Start month: January 2023
End month: 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.
National currency (ALL- Albanian Lek)
See below.
a) Provisional data: Not applicable
b) Final data: 20 December 2024
c) General University Funds (GUF): Not applicable
GBARD data are disseminated annually.
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.
