1.1. Contact organisation
National Statistics Office
1.2. Contact organisation unit
Public Finance Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
NSO
Lascaris
Valletta VLT2000
Malta
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
1 October 2025
2.2. Metadata last posted
1 October 2025
2.3. Metadata last update
1 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 | National classification = NABS |
|---|---|
| Correspondence table with NABS | Not available |
3.2.2. NABS classification
| Deviations from NABS | No deviations |
|---|---|
| Problems in identifying / separating NABS chapters and sub chapters | Since R&D projects in Malta are rather small, a problem would be encountered should they be broken down further by sub-chapters |
| Ability to distribute Non-oriented research and General University Funds (GUF) by fields of R&D | They are distributed by field of science |
3.3. Coverage - sector
R&D statistics are compiled for three institutional sectors of performance: Business Enterprise (BES), Government (GOV), and Higher Education (HES). Private Non-Profit (PNP) is considered to be negligible
3.3.1. General coverage
| Definition of R&D | Corresponds to the FM |
|---|---|
| Coverage of R&D or S&T in general | R&D is covered |
| Fields of R&D (FORD) covered | Corresponds to the FM |
| Socioeconomic objective (SEO by NABS) | Corresponds to the FM |
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 | In this sub-sector all government ministries and departments, and extra budgetary units are included | Included | |
| Regional (state) government | Not applicable to MT | Not included | |
| Local (municipal) government | In this sub-sector all government local councils are included | Included |
3.4. Statistical concepts and definitions
Main concepts and definitions used to produce R&D statistics are given by the Frascati Manual, the "Proposed standard practice for surveys of research and experimental development", OECD 2002, which is internationally recognized standard methodology for collecting R&D statistics.
"Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications." (§ 63, Frascati Manual, OECD 2002).
"Intramural R&D expenditures are all expenditures for R&D performed within a statistical unit or sector of the economy during a specific period, whatever the source of funds." (§ 358, Frascati Manual, OECD 2002).
"R&D personnel include all persons employed directly on R&D, as well as those providing direct services such as R&D managers, administrators, and clerical staff. Those providing an indirect service, such as canteen and security staff, should be excluded." (§ 294 - 295, Frascati Manual, OECD 2002).
"Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems and also in the management of the projects concerned." (§ 301, Frascati Manual, OECD 2002).
3.5. Statistical unit
The registered institutions are statistical units.
3.6. Statistical population
R&D statistics are compiled for R&D activity performed in the whole economy.
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.
The objective of the European R&D statistics is to cover all intramural R&D activities. In line with this objective, the target population for the national R&D survey of the Government Sector should consist of all R&D performing units (including known R&D performers or assumed to perform R&D). In practise however, countries in their R&D surveys might have difficulty in identifying R&D activities at the municipality level.
| Definition of the national target population | The GBARD data is mainly collected from the annual R&D survey, there is a specific section on GBARD, which is submitted by all government Ministries and Departments and government entities. In addition, we supplement other information but there are no specific R&D budget items in the National Budget. |
|---|---|
| Estimation of the target population size | Full coverage. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
R&D data for GOV and HES sector are available from 2004 onwards
3.9. Base period
Not requested. The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
Not requested.
Reference period is the calendar year.
a) Calendar year: January - December.
b) Fiscal year:
Start month: January.
End month: December.
6.1. Institutional Mandate - legal acts and other agreements
The Malta Statistics Authority (MSA) Act empowers the NSO to collect, compile, extract and release official statistics related to demographic, social, environment, economic and general activities and conditions of Malta.
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
As a member of the European Union (EU), Malta has to observe the Council Regulations. Until 2003 R&D data were collected under gentleman's agreement. In 2003, Decision No 1608/2003/EC of the European parliament and of the Council of 22 July 2003 concerning the production and development of community statistics on science and technology was adopted. Between reference years 2003 to 2011 the data collection was based on the Commission Regulation No 753/2004 on statistics on science and technology (OJ L 118, page 23 from 23 April 2004), and as amended by the Commission Regulation (EC) No 973/2007 (OJL 216, page 10 from 21 August 2007). From the reference year 2012 onwards, the Commission Implementing Regulation on statistics science and technology No 995/2012 (OJ L 299, page 18 from 27 October 2012) applies
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:
Article 40 of the MSA Act stipulates the restrictions on the use of information while Article 41 stipulates the prohibition of disclosure of information. Furthermore, Section IX of the Act (Offences and Penalties) lays down the measures to be taken in case of unlawful exercise of any officer of statistics regarding confidentiality of data.
b) Confidentiality commitments of survey staff:
Upon employment, all NSO employees are informed of the rules and duties pertaining to confidential information and its treatment. In line with stipulations of the MSA Act, before commencing work, every employee is required to take an oath of secrecy whose text is included in the same Act.
An internal policy on anonymisation and pseudo-anonymisation is in place to ascertain that adequate methods are used for the protection of data which the office collects and shares with the public in its capacity as the National Statistics Office. The policy is meant to safeguard confidentiality of both personal and business data entrusted to the NSO. The document provides guidance for all NSO employees who process data on a daily basis as to how anonymisation and pseudo-anonymisation methods should be applied. The policy applies to all confidential, restricted and internal information, regardless of form (paper or electronic documents, applications and databases) that is received, processed, stored and disseminated by the NSO.
7.2. Confidentiality - data treatment
Data is disseminated in aggregate form and no statistical disclosure is applied onto it.
8.1. Release calendar
An advance release calendar is maintained by the NSO and published on the NSO website. The calendar projects three months of news releases (including the current and two subsequent months).
8.2. Release calendar access
8.3. Release policy - user access
An internal policy on dissemination is in place to govern the dissemination of official statistics in an impartial, independent and timely manner, making them available simultaneously to all users.
The NSO’s primary channel for the dissemination of official statistics is the NSO website. Tailored requests for statistical information may also be submitted through the NSO website.
Moreover, dedicated news releases are available in electronic format on the NSO website.
A news release is issued in June/July. This release is also uploaded on the NSO's website for future reference. See Release calendar.
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 | A news release is published once a year. In this news release we publish data for BES, GOV, HES and GBARD GBARD data is published in the annual R&D news release in table 8 |
| Ad-hoc releases | N |
1) Y - Yes, N – No
10.2. Dissemination format - Publications
A news release is published annually and all tables are available online on the NSO website.
Transmission tables sent to Eurostat are uploaded on the Eurobase under “Science and technology” at the following link: Eurostat database.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
|---|---|---|
| General publication/article (paper, online) |
Y | GBARD is only published in the Annual News Release. Not published in a database. GBARD data is available in table 8 of the R&D news release. R&D releases can be found at: Data release |
| Specific paper publication (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
A news release is published annually and all tables are available online on the NSO website.
Transmission tables sent to Eurostat are uploaded on the Eurobase under “Science and technology” at the following website: Database.
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Not published |
|---|---|
| Access cost policy | Not applicable |
| Micro-data anonymisation rules |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1 | Micro-data / Aggregate figures | Comments |
|---|---|---|---|
| Internet: main results available on the national statistical authority’s website | Y | A news release is issued in June/July. This release is also uploaded on the NSO’s website for future reference. | |
| Data prepared for individual ad hoc requests | N | ||
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
Accompanying information has been uploaded on the NSO website including an explanation of the major fields of science, socio-economic objectives as well as transnational coordinated research. Methodological notes were also included in the questionnaire with definitions on what constitutes R&D and what should be excluded.
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.) | A description of each R&D project undertaken is provided, making it easier for us to determine whether the figures reported are actually for Research and Development |
|---|---|
| Request on further clarification | Requests for further clarifications are quite limited however they are dealt with personally over the phone or by email. These are quite subjective to the type of organisation involved and cannot be attributed to one specific issue. |
| Measure to increase clarity | For now, no measures to increase clarity are planned since overall, the questionnaire is understood by all. However, measures to increase clarity are put in place when the need for the collection of a new variable arises. |
| Impression of users on the clarity of the accompanying information to the data | Accompanying information is quite detailed and we never received any negative comments as regards this information hence, it is assumed sufficient. |
11.1. Quality assurance
The NSO ensures that the statistical practices used to compile national R&D data follow the Frascati Manual recommendations.
The NSO has developed an internal Quality Management Framework (QMF) which is built on common requirements of the ESS Code of Practice (ESS CoP). A document was prepared to include a set of general quality guidelines spanning over all statistical domains. Assuring methodological soundness is an integral part of the QMF, nonetheless, the document spans also on other areas related to institutional aspects.
Every five to seven years, the NSO participates in a Peer Review exercise through which the compliance of its operations with principles of the ESS CoP is assessed by an expert team. Peer Reviews are indeed part of the European Statistical System (ESS) strategy to implement the ESS CoP. Each NSI is expected to provide information as requested by a standard self-assessment questionnaire. Following this, an expert team visits the office to meet NSI representatives and main stakeholders. Peer Reviews result in a compliance report and the listing of a set of Improvement Actions which need to be followed up by the NSI.
11.2. Quality management - assessment
Malta's overall quality of the GOV R&D methodology is quite satisfactory. All data required by the commission is collected and transmitted on time. All entities in the HES provide us with high quality data.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
|---|---|---|
| 1 | Malta Council for Science and Technology | Public body established by the Central Government with the mandate of advising government on science and technology policy. Detailed data on capacity and trends of Malta's R&D performance for R&D and innovation and education policy decisions and strategy planning. |
| 1 | Parliament, Ministries, political parties, government departments and International Organisations. |
Aggregated R&D data. |
| 3 | Media for general public | Analysis of changes in Malta’s R&D performance together with international comparisons |
| 4 | Researchers and Students | Statistics and analysis |
1) Users' class codification
1- Institutions:
• European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
• in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
• International organisations: OECD, UN, IMF, ILO, etc.
2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.
3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.
4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)
5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)
6- Other (User class defined for national purposes, different from the previous classes.)
12.2. Relevance - User Satisfaction
To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.
12.2.1. National Surveys and feedback
| Conduction of a user satisfaction survey or any other type of monitoring user satisfaction | The most recent User Satisfaction survey was carried out by the National Statistics Office in 2022. Occasionally we ask our main users to comment on the overall quality |
|---|---|
| User satisfaction survey specific for GBARD statistics | No |
| Short description of the feedback received | Our main users were asked to comment on the overall quality of our R&D data published. Their feedback was that the data is useful, on time and in sufficient detail. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Data completeness of both preliminary and final mandatory data is 100% satisfactory.
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 of 30 July 2020. The Regulation (EU) stipulates periodicity of variables that should be provided, breakdowns and if they should be provided mandatory or on voluntary basis.
| 5 (Very Good) |
4 (Good) |
3 (Satisfactory) |
2 (Poor) |
1 (Very poor) |
Reasons for missing cells | |
|---|---|---|---|---|---|---|
| Provisional budget statistics1 | x | |||||
| Obligatory final budget statistics1 | x | |||||
| Optional final budget statistics2 | x |
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-2003 | Annual | no gaps | t+6 | |
| NABS Chapter level | y-2003 | Annual | no gaps | t+6 | |
| 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
12.3.3.2. 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-2003 | annual | no gaps | t+18 | |
| NABS Chapter level | y-2003 | annual | no gaps | t+18 | |
| 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 |
|---|---|---|---|---|---|---|
| Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
- Stage: P - provisional, F - final.
- Availability of the data: No, data are not available, Y: Yes, data are available + start year.
- 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 |
- 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 ‘-‘.
- The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for GBARD.
13.1.2. Assessment of the accuracy
| Indicators | 5 (Very Good)1 | 4 (Good)2 | 3 (Satisfactory)3 | 2 (Poor)4 | 1 (Very poor)5 |
|---|---|---|---|---|---|
| GBARD | x | ||||
| National public funding to transnationally coordinated R & D | x |
- High level of coverage (At least all national or federal ministries and the ministries and agencies responsible for R&D funding at state or regional level). High rate of response (>90%) in data collection. All figures broken down by NABS.
- If at least one out of the three criteria described above would not be fully met.
- In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.
- In the event that the average rate of response would be lower than 70% and at least one of the two remaining criteria would not be met.
- If all the three criteria described above are not met.
13.2. Sampling error
Not requested.
13.2.1. Sampling error - indicators
Not requested.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
a) Description/assessment of coverage errors:
No coverage errors because the data is collected from the whole population, i.e. all Government Sector.
b) Measures taken to reduce their effect:
Not applicable
13.3.1.1. Over-coverage - rate
Not requested
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:
Typical measurement errors occur during data entry.
b) Measures taken to reduce their effect:
Data entry errors were reduced as the compiled questionnaire are being automatically uploaded in our system.
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:
Unit non-response may happen.
b) Measures taken to reduce their effect:
In the event of a unit non-response from an entity known that it provides R&D funding, we first chase and if unsuccessful we repeat last year's figures.
c) Effect of non-response errors on the produced statistics:
Minimal.
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:
The filled-in questionnaires are uploaded to our R&D IT system and the processing and outputs are generated within the system.
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:
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+12
14.1.2. Time lag - final result
Date of first release of national data: t+18
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) | T+12 | T+18 |
| Actual date of transmission of the data (T+x months) | T+12 | T+18 |
| Delay (days) | 5 | 0 |
| Reasoning for delay | Issues with the R&D IT system | Not applicable |
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 | An R&D annual questionnaire is sent out to all government ministries,departments and local councils. The R&D questionnaire includes a specific section on GBARD. It specifically asks for the:
|
| 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 | Corresponds to the FM |
| Stages of data collection | FM2015 §12.41 | No | The R&D questionnaire includes a specific section on GBARD |
| Gross / net approach, net principle | FM2015 §12.20 and 12.21 | Yes | Does not correspond to the FM. We do not exclude revenue from other government sources or other sectors |
| EU/other funds | Eurostat's EBS Methodological Manual on R&D Statistics | No | Only the national co-financing of the EU funds are included |
| 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 | Not applicable | |
| Loans | FM §12.31, 12.32, 12.34 | Loans are not applicable in context of R&D in MT | |
| Indirect funding, tax rebates, etc. | FM §12.31 - 12.38 | No deviation | Indirect funding, tax rebates, etc, are not applicable in context of R&D in MT |
| Treatment of multi-annual projects | FM2015 §12.44 | No deviation | |
| Treatment of GBARD going to R&D abroad | FM2015 §12.19 | Not applicable | |
| Criterion for distribution by socioeconomic objective | FM2015 §12.50 to 12.71 | Yes | We only collect the data on socio-economic objectives |
| 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 | Not applicable | ||
| Final data | 2004 | 2006 2007 2015 |
In previous years, compilation of GBAORD data was done by reporting the figure of total expenditure by socio-economic objective hence including all expenditure, that funded by government and abroad. From 2010, following the grant addressing GBAORD data, compilation of GBAORD has started to exclude foreign funds and report only expenditure funded by the government. This arrangement has been applied backwards until 2006. From 2007, we started including the amount of public funding towards private enterprises. From 2007, we included public funding towards private enterprises engaged in EUREKA projects whereas from 2010, data are inclusive of public funding towards private enterprises under the National R&I programme. As from 2015 onwards, there were some further enhancements; in addition to the actual R&D expenditure financed government sources of funds (obtained from the questionnaire), the budgeted amounts of the National R&I programme are included, less the disbursed amounts provided to GOV and HES sectors (these are excluded so as to avoid double counting issues). Furthermore, other local programmes for funding R&D programmes, the national co-financing to EU funded R&D programmes and the transcordinated research are being included. |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.3. Coherence - cross domain
GBARD data includes government funds towards private enterprises.
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 | 600 | 600 | 0 |
| Environment | 659.629 | 659.629 | 0 |
| Exploration and exploitation of space | 400 | 400 | 0 |
| Transport, telecommunication and other infrastructures | 56.092 | 56.092 | 0 |
| Energy | 200.452 | 200.452 | 0 |
| Industrial production and technology | 1334.17 | 1334.17 | 0 |
| Health | 213.91 | 213.91 | 0 |
| Agriculture | 982.316 | 982.316 | 0 |
| Education | 116.215 | 116.215 | 0 |
| Culture, recreation, religion and mass media | 479.36 | 479.36 | 0 |
| Political and social systems, structures and processes | 478.123 | 478.123 | 0 |
| General advancement of knowledge: R&D financed from General University Funds (GUF) | 29821.85 | 29821.85 | 0 |
| General advancement of knowledge: R&D financed from other sources than GUF | 0 | 0 | 0 |
| Defence | 0 | 0 | 0 |
| TOTAL GBARD | 35342.12 | 35342.12 | 0 |
The assessment of costs associated with a statistical product is a rather complicated task since there must exist a mechanism for appointing portions of shared costs (for instance shared IT resources and dissemination channels) and overheads (office space, utility bills etc). The assessment must become detailed and clear enough so that international comparisons among agencies of different structures are feasible.
16.1. Costs summary
| Costs for the statistical authority (in national currency) | % sub-contracted1) | |
|---|---|---|
| Staff costs | ||
| Data collection costs | Not available | Not applicable |
| Other costs | Not available | Not applicable |
| Total costs | Not available | Not applicable |
| Comments on costs | ||
| The only cost involved in the process of R&D data collection is the time spent by one statistician in collecting, analysing and reporting data. Questionnaires are sent by email and the responses are also sent back by email, so there are no printing and postage costs. | ||
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | ||
| Average Time required to complete the questionnaire in hours (T)1 | Not possible to estimate - respondents were not asked for the time taken to fill in the questionnaire | |
| Average hourly cost (in national currency) of a respondent (C) | Not possible to estimate the hourly cost of a respondent | |
| 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
At the NSO, there is currently no internal policy governing revisions that occur for all statistics produced. Nonetheless, a revisions policy is being drafted to safeguard a coordinated revisions system across statistical domains.
This policy will take account of the need and causes for revisions; time and frequency of revisions; data and other statistical products affected by such revisions; and length of periods revised.
17.2. Data revision - practice
Data for a reference year are collected twice; the first time, provisional, at t+1 year, while final data are collected at t+2 years. Provisional data are subject to change, but revisions are very minimal.
No further revisions are collected for past years unless brought forward by the entity.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
a) Provisional data: An R&D annual questionnaire is sent out to all government ministries and departments.
As regards government funding towards private enterprises for R&D, we get the data from 2 administrative sources; MEDE (for Scholarships) and Malta Council for Science and Technology (for the National R&I Programme).
b) Final data: R&D annual questionnaire
Data from MEDE and Malta Council for Science and Technology
c) General University Funds (GUF): The R&D questionnaire specifically asks for R&D financed from General University Funds
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 | GBARD data is collected from 2 sources. Question 8 and another question specifically on the Government Budget Allocations in the R&D survey and the administrative data of the National R&I programme that is administered by the Malta Council for Science and Technology and Scholarships administered by MEDE. | GBARD data is collected from 2 sources. Question 8 and another question specifically on the Government Budget Allocations in the R&D survey and the administrative data of the National R&I programme that is administered by the Malta Council for Science and Technology and Scholarships administered by MEDE. | Not applicable |
| Stage of data collection | Data on outlays is collected once a year in February | Data on outlays is collected once a year in February | |
| Reporting units | The reporting units are those which are engaged in R&D activities | The reporting units are those which are engaged in R&D activities | Not applicable |
| Basic variable | Outlays and appropriations | Outlays and appropriations | Data includes both outlays and appropriations |
| Time of data collection (T+x)1) | T+2 | T+26 | |
| Problems in the translation of budget items | In general, budget items taken directly from the national budget documents are not used. The new questionnaire for GBARD requests the budgeted funding allocation for R&D projects. |
||
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)
Not applicable
18.3.3. Distribution by socioeconomic objectives (SEO)
| Level of distribution of budgetary items – institution or programme/project | Purpose/Institutional |
|---|---|
| Criterion of distribution – purpose or content | Purpose |
| Method of identification of primary objectives | Content |
| Difficulties of distribution |
18.3.4. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| GBARD national questionnaire and explanatory notes in English: | Survey of Research and Development in the General Government Sector_2021 |
| GBARD national questionnaire and explanatory notes in the national language: | |
| Other relevant documentation of national methodology in English: | |
| Other relevant documentation of national methodology in the national language: |
18.4. Data validation
GBARD data obtained from the R&D survey is checked through an in-built validation procedure that checks the consistency of Question 14: General University Funds + Own Funds + Direct Government Fund (excluding GUF) is equal to Question 8 Total R&D financed by Government.
The National R&I Programme data is checked for consistency and funds provided to the general government sector are eliminated to avoid double counting
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Not applicable
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 | Not applicable |
|---|---|
| Description of the use of the coefficient (if 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 | Not applicable |
|---|---|
| Description of the use of the coefficient (if 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 a single year |
|---|---|
| Possibility to classify budgetary items by COFOG functions | It is possible to classify the expenditure by COFOG. However, a problem will be encountered when dealing with the University of Malta. Since no information is provided whether students work on the R&D projects or not, this will pose a problem when classifying expenditure by education or by any other function |
| Possibility to classify budgetary items by other nomenclatures e.g. NACE | Not applicable |
| Method of estimation of future budgets | As from 2011, respondents are asked to provide provisional data for the current year |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comments.
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.
1 October 2025
Main concepts and definitions used to produce R&D statistics are given by the Frascati Manual, the "Proposed standard practice for surveys of research and experimental development", OECD 2002, which is internationally recognized standard methodology for collecting R&D statistics.
"Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications." (§ 63, Frascati Manual, OECD 2002).
"Intramural R&D expenditures are all expenditures for R&D performed within a statistical unit or sector of the economy during a specific period, whatever the source of funds." (§ 358, Frascati Manual, OECD 2002).
"R&D personnel include all persons employed directly on R&D, as well as those providing direct services such as R&D managers, administrators, and clerical staff. Those providing an indirect service, such as canteen and security staff, should be excluded." (§ 294 - 295, Frascati Manual, OECD 2002).
"Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems and also in the management of the projects concerned." (§ 301, Frascati Manual, OECD 2002).
The registered institutions are statistical units.
R&D statistics are compiled for R&D activity performed in the whole economy.
Not requested.
Reference period is the calendar year.
a) Calendar year: January - December.
b) Fiscal year:
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.
Not requested.
See below.
a) Provisional data: An R&D annual questionnaire is sent out to all government ministries and departments.
As regards government funding towards private enterprises for R&D, we get the data from 2 administrative sources; MEDE (for Scholarships) and Malta Council for Science and Technology (for the National R&I Programme).
b) Final data: R&D annual questionnaire
Data from MEDE and Malta Council for Science and Technology
c) General University Funds (GUF): The R&D questionnaire specifically asks for R&D financed from General University Funds
A news release is issued in June/July. This release is also uploaded on the NSO's website for future reference. See Release calendar.
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.
