1.1. Contact organisation
Ministry of education, science and innovation
1.2. Contact organisation unit
Directorate for Scientific Research Activity
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
Vaka Đurovića bb, 81000 Podgorica, Montenegro
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
2.1. Metadata last certified
29 May 2026
2.2. Metadata last posted
29 May 2026
2.3. Metadata last update
10 June 2026
3.1. Data description
Statistics on Government R&D (GOVERD) measure research and experimental development (R&D) performed in the Government sector, i.e. R&D expenditure and R&D personnel. 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 all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
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, which is the internationally recognised standard methodology for collecting R&D statistics and by the European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
The guiding document to preparing the quality reports is the European Statistical System (ESS) Handbook for Quality and Metadata Reports — re-edition 2021.
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.
3.2. Classification system
- The local units for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
- The distribution by socioeconomic objectives (SEO) is based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
- The fields of research and development are based on Classification and distribution by Fields of Research and Development (FORD).
- The R&D personnel and researchers by educational attainment are classified by the International Standard Classification of Education ISCED 2011
3.3. Coverage - sector
See below.
3.3.1. General coverage
Definition of R&D
R&D comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge.
"Given that the Ministry of Education, Science and Innovation became the official producer of R&D statistics in November 2024, additional methodological improvements and strengthening of the statistical production process are ongoing. Concepts currently marked as 'Not available' or 'Not applicable' will be updated in future publications as additional data and methodological evidence become available."
3.3.2. Sector institutional coverage
| Government sector | The Government sector used for R&D statistics in Montenegro is defined in accordance with the OECD Frascati Manual 2015 recommendations, excluding units classified within the Higher Education Sector (HES). The sector includes central and local government institutions, public research organisations, public agencies and non-market non-profit institutions controlled by government units and performing R&D activities. Government sector institutions performing R&D activities include public research and health institutions, laboratories, agencies and other publicly controlled entities. Examples include the Institute of Public Health of Montenegro, the Specialist Veterinary Laboratory, the Institute for Medicines and Medical Devices and the Clinical Centre of Montenegro. Higher education institutions are excluded and reported separately within HES. |
|---|---|
| Hospitals and clinics | Public hospitals and clinics are included in the Government sector when they perform research and development activities and fulfil the criteria for classification within GOV according to the Frascati Manual 2015 recommendations. Public medical institutions carrying out R&D activities may therefore be reported within GOVSI. University hospitals and medical units belonging to higher education institutions are excluded from GOVSI and reported within HES where applicable. |
| Inclusion of units that primarily do not belong to GOV and the borderline cases. |
No major deviations from the Frascati Manual 2015 recommendations were identified. |
3.3.3. R&D variable coverage
| R&D administration and other support activities | R&D administration and support activities are covered in accordance with the OECD Frascati Manual 2015 recommendations (§2.122). Administrative and supporting activities are considered as R&D only when they are directly linked to research and development projects and contribute to their implementation. The national R&D survey includes categories of support personnel directly contributing to R&D activities, including administrative, financial, legal, information and other support activities related to the implementation of R&D projects. |
|---|---|
| External R&D personnel | External R&D personnel are covered in accordance with Frascati Manual 2015. The national survey collects information on persons engaged in R&D activities on the basis of service contracts and copyright agreements, including researchers, doctoral candidates, professional staff, technical staff and supporting staff. External personnel are included when they directly contribute to R&D activities and are integrated into research projects or activities of the reporting unit. Full Time Equivalent (FTE) information is also collected for externally engaged personnel. |
| Clinical trials: compliance with the recommendations in FM §2.61. | Activities related to clinical trials are included when they satisfy the criteria for research and experimental development. Public medical institutions performing R&D activities may report such activities within the Government sector, while university medical institutions are reported separately under the Higher Education Sector. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Information on receipts from the rest of the world is available through the national R&D survey. Reporting units provide information on foreign sources of funding for R&D activities, including funding from enterprises within the same group, other foreign enterprises, foreign governments, European Structural and Investment Funds, EU Framework Programmes, other European Commission sources, foreign higher education institutions, private non-profit organisations, international organisations and other foreign sources. These data are collected separately and allow identification of foreign funding contributions to R&D activities. |
|---|---|
| Payments to rest of the world by sector - availability | Information on payments to the rest of the world is available through dedicated questions on expenditures for purchased R&D services. Reporting units separately report expenditures for R&D services acquired from foreign enterprises, public research institutions, private research institutes and laboratories, higher education institutions, private non-profit organisations and international organisations. The survey therefore enables identification of expenditures related to R&D services purchased from abroad. |
3.3.5. Extramural R&D expenditures
According to the Frascati Manual (FM), expenditure on extramural R&D (i.e. R&D performed outside the statistical unit) is not included in intramural R&D performance totals (FM, §4.12).
| Data collection on extramural R&D expenditure (Yes/No) | Yes |
|---|---|
| Method for separating extramural R&D expenditure from intramural R&D expenditure | Intramural R&D expenditure includes all current and capital expenditures related to R&D activities performed within the reporting institution. Extramural R&D expenditure is collected separately through dedicated survey questions covering purchased R&D services performed by third parties outside the reporting unit. The national questionnaire distinguishes intramural expenditure from purchased R&D services and separately records expenditures by institutional sector and location (national and foreign providers). |
| Difficulties to distinguish intramural from extramural R&D expenditure | Some reporting units may encounter difficulties in distinguishing purchased R&D services from other external services related to R&D support activities. Additional guidance and methodological explanations are provided through survey instructions in order to improve consistency and ensure proper separation between intramural and extramural R&D expenditure. |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | R&D expenditure data are collected on an annual basis using the calendar year as the reference period. Reporting refers to activities and expenditures performed during the reference year. |
|---|---|
| Source of funds | The national R&D survey collects information on internal and external sources of funding in accordance with Frascati Manual. Reporting units provide information on own funds, funding from national sources and foreign sources. Foreign funding sources include enterprises, foreign governments, European Structural and Investment Funds, EU Framework Programmes, other European Commission sources, higher education institutions, private non-profit organisations and international organisations. Internal institutional resources are collected separately. |
| Type of R&D | The survey distinguishes three categories of R&D activities in accordance with Frascati Manual recommendations:
Information is collected separately by scientific field and type of R&D activity. |
| Type of costs | R&D expenditure is divided into current and capital expenditure in accordance with Frascati Manual section 4.2. Current expenditure includes:
Capital expenditure includes:
|
| Defence R&D - method for obtaining data on R&D expenditure | No separate defence R&D survey is currently implemented. |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | R&D personnel data are collected annually using the calendar year as the reference period. Head Count (HC) information refers to personnel engaged in R&D activities during the reference year. |
|---|---|
| Function | The national R&D survey collects Head Count information according to the functional classification recommended by the Frascati Manual. Personnel are reported separately as:
Information is collected separately for full-time and part-time R&D engagement. External personnel engaged through service contracts and copyright agreements are also covered. |
| Qualification | R&D personnel are classified according to educational attainment levels based on ISCED classification:
Qualification data are collected separately by sex and personnel category. |
| Age | Researchers are classified by age groups:
Age information is collected separately for male and female researchers and distinguishes full-time and part-time R&D engagement. |
| Citizenship | Not available. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | R&D personnel in Full Time Equivalent (FTE) are collected annually using the calendar year as the reference period. FTE information refers to the share of working time devoted to R&D activities during the reference year. |
|---|---|
| Function | FTE data are collected according to Frascati Manual recommendations and reported separately for:
Information is collected separately for internal and externally engaged personnel. |
| Qualification | FTE information is collected according to educational attainment using ISCED classification:
Data are reported separately by personnel category and sex. |
| Age | Researchers in FTE are classified according to age groups:
Age data are collected separately by sex and R&D engagement level. |
| Citizenship | Not available. |
3.4.2.3. FTE calculation
Full Time Equivalent (FTE) is calculated on the basis of the proportion of working time devoted to research and development activities during the reference year.
The national R&D survey collects information on the percentage of time spent on R&D activities for all categories of R&D personnel, including researchers, doctoral candidates, professional staff, technical staff and supporting staff.
FTE values are calculated by converting the reported share of R&D working time into full-time equivalent units in accordance with Frascati Manual recommendations. External personnel engaged through service contracts and copyright agreements are also included when they perform R&D activities.
The calculation is based on actual R&D engagement and not on contractual working time only.
3.5. Statistical unit
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
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 of institutional units.
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.
| Target population when sample/census survey is used for collection of raw data | Target population when administrative data or pre-compiled statistics are used | |
|---|---|---|
| Definition of the national target population | The national target population consists of all Government sector institutions known, identified or assumed to perform R&D activities during the reference period. The survey covers regular and occasional R&D performers and includes public research institutes, agencies, public health institutions, laboratories, museums and other government-controlled non-market institutions performing R&D activities. Higher education institutions are excluded and reported separately within HES. |
Administrative sources are used to identify actual or potential R&D performers within the Government sector. The target population includes institutions identified through official records, registers of licensed scientific and research institutions and other institutional information maintained by the Ministry of Education, Science and Innovation. |
| Estimation of the target population size | The target population size is estimated using institutions identified as actual or potential R&D performers through survey implementation, previous survey rounds and institutional verification procedures. The target population includes only R&D performers and is therefore smaller than the overall Government sector population. |
The target population size is estimated using administrative records, registers of licensed scientific and research institutions and other institutional information sources available to the Ministry of Education, Science and Innovation. Only institutions known or assumed to perform R&D activities are included. |
3.6.2. Frame population – Description
In ESS countries, the frame population for GOV R&D statistics is defined as the list of all the institutional units classified by the national accounts (ESA) as included in the General government (S.13), with the exclusion of those units included in the Higher education sector (HES).
| Method used to define the frame population | The frame population for GOV R&D statistics is defined in accordance with ESA principles and consists of institutional units classified within the General Government sector (S.13), excluding units belonging to the Higher Education Sector (HES). The frame includes government institutions, public agencies, public research organisations, public health institutions and other non-market institutions controlled by government performing or potentially performing R&D activities. |
|---|---|
| Methods and data sources used for identifying a unit as known or supposed R&D performer | Identification of actual or potential R&D performers is based on administrative records maintained by the Ministry of Education, Science and Innovation, registers of licensed scientific and research institutions, previous survey rounds, institutional verification procedures and information obtained during implementation of the national R&D survey. Additional institutional information is used where necessary. |
| Inclusion of units that primarily do not belong to the frame population | Units primarily belonging to other institutional sectors are not included in the GOV frame population. Higher education institutions are excluded and reported separately within HES. Public enterprises operating as market producers are also excluded. No major deviations from the ESA and Frascati Manual recommendations were identified. |
| Systematic exclusion of units from the process of updating the target population | No systematic exclusion of units is applied. The process of updating the target population includes review of existing reporting units, identification of new institutions and verification of their R&D activities through administrative and survey sources. |
| Estimation of the frame population | The frame population size is estimated using official administrative records and registers of licensed scientific and research institutions maintained by the Ministry of Education, Science and Innovation, complemented by institutional information and sector classification procedures. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested, see concept 12.3.3 (Data availability).
3.9. Base period
The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
R&D expenditure is published in the following units: Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).
R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.
The reference period used for R&D statistics in the Government sector is the calendar year.
R&D expenditure, personnel and other survey variables refer to activities performed during the reference year.
The collection, processing and dissemination of R&D statistics in Montenegro are carried out by the Ministry of Education, Science and Innovation as the official producer of R&D statistics.
The legal basis is established by the Law on Official Statistics and the Official Statistics System, as well as by the Five-Year Programme and Annual Plan of Official Statistical Surveys adopted by the Statistical Office.
R&D statistics are produced in accordance with OECD Frascati Manual recommendations and relevant European statistical requirements. The Ministry is responsible for methodological development, survey implementation, data processing, validation and dissemination activities. Cooperation with the Statistical Office and other relevant institutions is ensured where applicable.
6.1. Institutional Mandate - legal acts and other agreements
See below.
6.1.1. European legislation
Legal acts / agreements:
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 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. The transmission of R&D data is mandatory for Member States and EEA countries.
The Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology was in force until the end of 2020.
6.1.2. National legislation
| Existence of R&D specific statistical legislation | R&D statistics in Montenegro are produced on the basis of the national legal framework for official statistics. The legal basis is established by the Law on Official Statistics and the Official Statistics System and implemented through the Five-Year Programme of Official Statistics and the Annual Plan of Official Statistical Surveys. The Ministry of Education, Science and Innovation acts as the official producer of R&D statistics and is responsible for collection, processing and dissemination of R&D statistical data. R&D statistics are produced in accordance with OECD Frascati Manual recommendations and relevant European statistical requirements. |
|---|---|
| Are respondents obliged by the national law to provide raw and administrative data: | Respondents are obliged to provide statistical information in accordance with the national legislation governing official statistics. Reporting obligations derive from the Law on Official Statistics and Official Statistical System and the implementation of statistical surveys included in the official statistical programme. The reporting obligation applies to institutions included within the scope of the national R&D survey. Raw data collected through the survey are treated as confidential and used exclusively for statistical purposes. |
6.1.3. Standards and manuals
- Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development
- European Business Statistics Methodological Manual on R&D Statistics
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
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.
At the level of the ESS the EU regulation 223/2009 on European statistics defines confidential data as data which allows statistical units (respondents) to be identified, either directly - by formal identifiers such as respondents’ names, addresses, identification numbers - or indirectly - by using a combination of variables or characteristics such as age, gender, education - thereby disclosing individual information (see Article 2(1)(e) of regulation 223/2009).
At national level:
- Confidentiality protection required by law:
Statistical confidentiality is ensured under the Law on Official Statistics and the Official Statistical System. Individual data collected through R&D surveys are used exclusively for statistical purposes and protected against direct and indirect identification of reporting units.
- Confidentiality commitments of survey staff:
Employees involved in statistical production sign confidentiality commitments and access to individual data is restricted to authorised personnel only. This ensures controlled use of micro-data and protection of confidential information throughout the statistical production process.
7.2. Confidentiality - data treatment
Individual survey responses and microdata are accessible only to authorised personnel involved in statistical production activities. Direct identifiers and information allowing identification of reporting units are protected and are not disseminated.
For dissemination purposes, aggregated data are used.
Prior to transmission and dissemination, statistical outputs are reviewed in order to identify potentially confidential cells.
The same principles are applied to data delivered to Eurostat. Confidentiality checks are performed before transmission in order to prevent disclosure of sensitive information.
8.1. Release calendar
The dissemination of R&D statistics follows the Programme of Official Statistics, the Annual Plan of Official Statistical Surveys and the release calendar prepared within the national statistical system. Release dates are predefined and publicly communicated.
8.2. Release calendar access
For Eurostat this is: Release calendar - Eurostat (europa.eu).
Montenegro: Kalendar2026_eng_210125.
8.3. Release policy - user access
R&D statistics are disseminated in accordance with the general dissemination policy applied within the official statistical system of Montenegro.
The scope of dissemination includes public users, national institutions, policy makers, researchers, international organisations and European statistical bodies.
Statistical information is released after completion of data collection, validation and quality assurance procedures. Users are informed through official dissemination channels, including institutional websites, statistical publications and other official communication tools.
No advance briefing of the press is applied before official release of the data.
The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1) | Links | |
|---|---|---|
| Regular releases | Y | Official dissemination activities are currently under preparation. The Ministry of Education, Science and Innovation is preparing an official release to be published on the website, which includes a dedicated section for Official Statistics In addition, relevant R&D statistical information is disseminated through annual reports on the work of the Ministry and through regular reporting to the European Union, including reporting related to Chapter 25 – Science and Research, where extracted statistical indicators and supporting information are provided. |
| Ad-hoc releases | Y | Ad-hoc dissemination is carried out through thematic reports, official communications, responses to specific requests and reporting activities related to European integration processes, international reporting obligations and sectoral analyses. |
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) | Links |
|---|---|---|
| General publication/article | Y | R&D statistics are disseminated through annual reports, official publications, reporting documents, quality reports and materials prepared within the Official Statistics section of the Ministry website. Statistical information is also used in reporting activities related to EU integration processes and Chapter 25 – Science and Research. |
| Specific paper publication (e.g. sectoral provided to enterprises) | Y | Sector-specific dissemination may be performed through thematic reports, sectoral analyses, materials prepared for international reporting, European Commission requests. |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Online Database
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
As Eurostat receives no R&D micro-data from the reporting countries, users should contact directly the respective national statistical institute (NSI) for access to the micro-data.
10.4.1. Provisions affecting the access
| Access rights to the micro-data |
Access to R&D micro-data is restricted to authorised personnel involved in statistical production, while use for research purposes may be considered only under confidentiality requirements and applicable legislation. |
|---|---|
| Access cost policy | No access costs apply for aggregated statistical information disseminated through official channels. |
| Micro-data anonymisation rules | Micro-data are protected through anonymisation, aggregation and disclosure control procedures, while direct and indirect identifiers are restricted. |
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 |
Main R&D statistical outputs are planned for publication through the Official Statistics section of the Ministry of Education, Science and Innovation website and through official reporting documents. |
| Data prepared for individual ad hoc requests | Y | Only aggregated information will be disseminated. |
|
| Other | Y | Additional dissemination is carried out through annual reports, EU reporting activities, Chapter 25 materials and statistical documentation. |
1) Y – Yes, N - No
10.6. Documentation on methodology
OECD Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development
Commission Implementing Regulation (EU) 2020/1197
National Methodology for Research and Development Statistics
Annual Survey on Research and Development
Law on Official Statistics and Official Statistical System of Montenegro
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, quality reports, etc.) | Metadata, methodological documentation, quality reports, survey instructions, analytical materials and quality management documentation based on ESMS/SIMS structures are available for R&D statistics. |
|---|---|
| Requests on further clarification, most problematic issues | Requests for clarification mainly concern Frascati concepts, HC/FTE calculation, sector classification, intramural and extramural R&D expenditure, quality reporting and international comparability of R&D statistics |
11.1. Quality assurance
At Eurostat level, the common quality framework of the European Statistical System (ESS) is composed of the European Statistics Code of Practice, the Quality Assurance Framework of the ESS, and the general quality management principles (such as continuous interaction with users, continuous improvement, integration, and harmonisation).
11.2. Quality management - assessment
The overall quality of GOV R&D statistics is assessed as satisfactory and continuously improving. Quality assurance is based on the use of multiple data sources, application of validation procedures, communication with reporting units, follow-up actions to improve response quality and methodological checks during data processing. Particular attention is given to harmonisation with the OECD Frascati Manual and European statistical requirements. Current improvement activities focus on strengthening digital data collection, quality documentation, metadata systems and further development of R&D statistical capacities.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1) | Description of users | Users’ needs |
|---|---|---|
| 1 | Institutions (European institutions, ministries, statistical offices, international |
Data for policy making, monitoring of R&D and innovation systems, international reporting, European integration and statistical coordination. |
| 2 | Social actors (employers’ associations, trade unions, other organisations) |
Information on R&D activities, human resources, innovation performance and sector developments. |
| 3 | Media |
Reliable statistical indicators, analytical information and explanatory materials for dissemination to the public. |
| 4 | Researchers and students |
R&D indicators, metadata, methodological information and analytical data for research and educational purposes. |
| 5 | Enterprises or businesses |
Information on R&D investments, innovation trends, market analysis and cooperation opportunities. |
| 6 | Other users (general public, NGOs, innovation ecosystem actors) |
General information on research, innovation activities and science policy developments. |
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 | User satisfaction is monitored through communication with reporting institutions, methodological consultations, feedback received during data collection and cooperation within the official statistical system. |
|---|---|
| User satisfaction survey specific for R&D statistics | No specific user satisfaction survey dedicated exclusively to R&D statistics has been implemented so far. |
| Short description of the feedback received | Feedback mainly concerns requests for methodological clarification, additional metadata, international comparability, HC/FTE calculation, sector classification and further guidance related to Frascati concepts and R&D expenditure reporting. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Not available.
12.3.2. Completeness - overview
Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197 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.
Please see note in Concept 3.3.1.
| Reasons for missing cells | |
|---|---|
| Preliminary variables | |
| Obligatory data on R&D expenditure | |
| Optional data on R&D expenditure | |
| Obligatory data on R&D personnel | |
| Optional data on R&D personnel | |
| Regional data on R&D expenditure and R&D personnel |
12.3.3. Data availability
See below.
12.3.3.1. Data availability - R&D Expenditure
Please see note in Concept 3.3.1.
| Availability1) | Frequency of data collection | Gap years – years with missing data | Changes - Description | Changes - Year of introduction | Changes - Reasons | |
|---|---|---|---|---|---|---|
| Source of funds | ||||||
| Type of R&D | ||||||
| Type of costs | ||||||
| Socioeconomic objective | ||||||
| Region | ||||||
| FORD | ||||||
| Type of institution |
1) Y-start year, N – data not available
12.3.3.2. Data availability - R&D Personnel (HC)
Please see note in Concept 3.3.1.
| Availability1) | Frequency of data collection | Gap years – years with missing data | Changes - Description | Changes - Year of introduction | Changes - Reasons | |
|---|---|---|---|---|---|---|
| Sex | ||||||
| Function | ||||||
| Qualification | ||||||
| Age | ||||||
| Citizenship | ||||||
| Region | ||||||
| FORD | ||||||
| Type of institution |
1) Y-start year, N – data not available
12.3.3.3. Data availability - R&D Personnel (FTE)
Please see note in Concept 3.3.1.
| Availability1) | Frequency of data collection | Gap years – years with missing data | Changes - Description | Changes - Year of introduction | Changes - Reasons | |
|---|---|---|---|---|---|---|
| Sex | ||||||
| Function | ||||||
| Qualification | ||||||
| Age | ||||||
| Citizenship | ||||||
| Region | ||||||
| FORD | ||||||
| Type of institution |
1) Y-start year, N – data not available
12.3.3.4. Data availability - other
| Additional dimension/variable available at national level1) | Availability2) | Frequency of data collection | Breakdown variables | Combinations of breakdown variables | Level of detail |
|---|---|---|---|---|---|
1) This question is optional. It refers to variables and breakdowns NOT asked by the Commission Implementing Regulation (EU) No 2020/1197 (neither as 'optional').
2) Y-start year
12.3.3.5. R&D personnel - Cross-classification by function and qualification (if available in FTE and HC)
Please see note in Concept 3.3.1.
| Cross-classification | Unit | Frequency |
|---|---|---|
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'
Please see note in Concept 3.3.1.
| Sampling errors1) | Non-sampling errors1) | Model-assumption Errors1) | Perceived direction of the error2) | ||||
|---|---|---|---|---|---|---|---|
| Coverage errors | Measurement errors | Processing errors | Non response errors | ||||
| Total intramural R&D expenditure | |||||||
| Total R&D personnel in FTE | |||||||
| Researchers in FTE | |||||||
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 (6). If errors of a particular type do not exist, the sign ‘:‘ is used.
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 R&D.
13.1.2. Assessment of the accuracy with regard to the main indicators
| Indicators | 5 (Very Good)1) |
4 (Good)2) |
3 (Satisfactory)3) |
2 (Poor)4) |
1 (Very poor)5) |
|---|---|---|---|---|---|
| Total intramural R&D expenditure | x | ||||
| Total R&D personnel in FTE | x | ||||
| Researchers in FTE | x |
1) 'Very Good' = High level of coverage (annual rate of substitution in the target population lower than 5%). High average rates of response (>80%) in census and sample surveys. Full data consistency with reference to totals and relationships between variables in the dataset sent to Eurostat.
2) 'Good' = If at least one out of the three criteria described above is not fully met.
3) 'Satisfactory' = If the average rate of response is lower than 60%, even by meeting the two remaining criteria.
4) 'Poor' = If the average rate of response is lower than 60% and at least one of the two remaining criteria is not met.
5) 'Very Poor' = If all the three criteria are not met.
13.2. Sampling error
That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.
13.2.1. Sampling error - indicators
See below.
13.2.1.1. Variance Estimation Method
Not applicable
13.2.1.2. Confidence interval for R&D expenditure by source of funds
Not applicable
| Source of funds | R&D expenditure |
|---|---|
| Business enterprise | |
| Government | |
| Higher education | |
| Private non-profit | |
| Rest of the world | |
| Total |
13.2.1.3. Confidence interval for R&D personnel by occupation and qualification
Not applicable
| R&D personnel (FTE) | ||
|---|---|---|
| Occupation | Researchers | |
| Technicians | ||
| other support staff | ||
| Qualification | ISCED 8 | |
| ISCED 5-7 | ||
| ISCED 4 and below |
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.
- Description/assessment of coverage errors :
The GOV target population is established using multiple administrative and institutional sources and is regularly reviewed during the data collection process. Particular care is taken to distinguish government sector institutions from higher education institutions and private non-profit organisations in accordance with the Frascati Manual and the applicable institutional sector classification.
- Measures taken to reduce their effect:
Several measures are implemented to minimise potential coverage errors:
use of official registers and administrative sources maintained by the Ministry of Education, Science and Innovation;
use of lists of licensed scientific and research institutions and other relevant public bodies;
direct communication with reporting units during data collection and validation;
continuous updating of the target population based on newly identified R&D performers and institutional changes.
- Share of PNP (if PNP is included in GOV):
Private non-profit organisations are treated as a separate institutional sector and are not included in the Government sector statistics.
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 (e.g. difficulty to distinguish intramural from extramural R&D Expenditure). The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.
- Description/assessment of measurement errors:
The main potential sources of measurement error in the GOV R&D survey are related to the interpretation and application of R&D concepts by reporting units, particularly in organisations where research activities are performed alongside other regular functions.
Potential sources of measurement error include:
-
- distinguishing between R&D and non-R&D activities;
- distinguishing between intramural and extramural R&D expenditure;
- estimation of the Full-Time Equivalent (FTE) devoted to R&D activities;
- allocation of labour costs and other expenditure exclusively to R&D activities;
- classification of expenditure by type of research (basic research, applied research and experimental development).
- Measures taken to reduce their effect:
Several measures have been implemented to minimise measurement errors:
-
- the questionnaire is based on the OECD Frascati Manual 2015 and contains detailed methodological guidance and internationally harmonised definitions;
- comprehensive explanatory notes are provided for all major concepts and classifications;
- practical examples are included for the calculation of Full-Time Equivalent (FTE);
- direct communication with reporting units is used to clarify inconsistencies and resolve ambiguities during the data collection and validation process.
13.3.3. Non response error
Non-response occurs 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.
There are two elements of non-response:
- Unit non-response which occurs when no data (or so little as to be unusable) are collected on a designated population unit.
- Item non-response which occurs when data only on some, but not all survey variables are collected on a designated population unit.
The extent of response (and accordingly of non response) is also measured with response rates.
13.3.3.1. Unit non-response - rate
The main interest is to judge if the response from the target population was satisfactory by computing the un-weighted response rate.
Definition: Eligible are the survey units which indeed belong to the target population. Frame imperfections always leave the possibility that some units may not belong to the target population. Moreover, when there is no contact with certain units and no other way to establish their eligibility they are characterised as ‘unknown eligibility units’.
Un-weighted Unit Non- Response Rate = [1 - (Number of units with a response) / (Total number of eligible and unknown eligibility units in the survey)] * 100
13.3.3.1.1. Un-weighted unit non-response rate
Please see note in Concept 3.3.1.
| Number of units with a response in the survey | Total number of units in the survey | Unit non-response rate (Un-weighted) |
|---|---|---|
13.3.3.2. Item non-response - rate
Definition: Un-weighted Item Non-Response Rate (%) = [1-(Number of units with a response for the item) / (Total number of eligible, for the item, units in the sample)] * 100
13.3.3.2.1. Un-weighted item non-response rate
| R&D Expenditure | R&D Personnel (FTE) | Researchers (FTE) | |
|---|---|---|---|
| Item non-response rate (un-weighted) (%) | |||
| Comments |
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.
13.3.4.1. Identification of the main processing errors
Please see note in Concept 3.3.1.
| Data entry method applied | |
|---|---|
| Estimates of data entry errors | |
| Variables for which coding was performed | |
| Estimates of coding errors | |
| Editing process and method | |
| Procedure used to correct errors |
13.3.5. Model assumption error
Not requested.
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
Time lag between the end of reference period and the release date of the results:
Indicator: (Release date of provisional/ first results) - (Date of reference for the data)
- End of reference period: 31 December 2023
- Date of first release of national data: No preliminary national release was published. Provisional data were transmitted to Eurostat in accordance with the applicable transmission schedule.
- Lag (days): Not applicable.
14.1.2. Time lag - final result
- End of reference period: 31 December 2023
- Date of first release of national data: Not available.
- Lag (days): Not available.
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
Please see note in Concept 3.3.1.
| Transmission of provisional data | Transmission of final data | |
|---|---|---|
| Legally defined deadline of data transmission (T+_ months) | 10 | 18 |
| Actual date of transmission of the data (T+x months) | ||
| Delay (days) | ||
| Reasoning for delay |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. General issues of comparability
No major comparability issues are currently known.
15.1.3. Survey Concepts Issues
The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Implementing Regulation (EU) No 2020/1197, Frascati manual (FM) and EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.
| Concept / Issues | Reference to recommendations | Deviation from recommendations | Comments on national definition / Treatment – deviations from recommendations |
|---|---|---|---|
| R&D personnel | FM2015 Chapter 5 (mainly sub-chapter 5.2). | No deviation. | |
| Researcher | FM2015, § 5.35-5.39. | No deviation. | |
| Approach to obtaining Headcount (HC) data | FM2015, § 5.58-5.61 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Approach to obtaining FTE data | FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | No deviation. | |
| Intramural R&D expenditure | FM2015, Chapter 4 (mainly sub-chapter 4.2). | No deviation. | |
| Statistical unit | FM2015, § 8.64-8.65 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Target population | FM2015, § 8.63 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Sector coverage | FM2015, § 8.2-8.13 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Hospitals and clinics | FM2015, § 8.22 and 8.34 | No deviation. | |
| Borderline research institutions | FM2015, § 8.14-8.23 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation. | |
| Fields of research & development coverage and breakdown | Reg. 2020/1197 : Annex 1, Table 18 | No deviation. | |
| Socioeconomic objectives coverage and breakdown | Reg. 2020/1197 : Annex 1, Table 18 | No deviation. | |
| Reference period | Reg. 2020/1197 : Annex 1, Table 18 | No deviation. |
15.1.4. Deviations from recommendations
The following table lists a number of key methodological issues, which may affect the international comparability of national R&D statistics. The table gives the references in the Frascati manual (FM), where related recommendations are made. Countries are asked to report on the existence of any deviations from existing recommendations and comment upon.
| Methodological issues | Reference to recommendations | Deviation from recommendations | Comments on national treatment / treatment deviations from recommendations |
|---|---|---|---|
| Data collection method | FM2015 Chapter 8 (mainly sub-chapter 8.5). | No deviation. | |
| Survey questionnaire / data collection form | FM2015 Chapter 8 (mainly sub-chapter 8.5). | No deviation. | |
| Cooperation with respondents | FM2015 Chapter (mainly sub-chapter 8.5). | No deviation. | |
| Data processing methods | FM2015 Chapter 8 (mainly sub-chapters 8.5-8.6). | No deviation. | |
| Treatment of non-response | FM2015 Chapter 8 (mainly sub-chapter 8.5). | No deviation. | |
| Variance estimation | FM2015 Chapter 6 (mainly sub-chapter 6.7). | Not applicable |
|
| Data compilation of final and preliminary data | Reg. 2020/1197 : Annex 1, Table 18 | No deviation. |
15.2. Comparability - over time
See below.
15.2.1. Length of comparable time series
See below.
15.2.2. Breaks in time series
Please see note in Concept 3.3.1.
| Length of comparable time series | Break years1) | Nature of the breaks | |
|---|---|---|---|
| R&D personnel (HC) | |||
| Function | |||
| Qualification | |||
| R&D personnel (FTE) | |||
| Function | |||
| Qualification | |||
| R&D expenditure | |||
| Source of funds | |||
| Type of costs | |||
| Type of R&D | |||
| Other |
1) Breaks years are years for which data are not fully comparable to the previous period.
15.2.3. Collection of data in the even years
R&D statistical surveys in Montenegro are currently carried out on an annual basis.
For the establishment of continuous time series and alignment with EU reporting requirements, retrospective surveys were conducted for the period 2021–2023.
15.3. Coherence - cross domain
This part deals with any national coherence assessments which may have been undertaken. It reports results for variables which are the same or relevant to R&D statistics, from other national surveys and / or administrative sources and explains and comments on their degree of agreement with R&D statistics.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
The production of R&D statistics is coordinated with MONSTAT in accordance with the principles of the official statistical system of Montenegro.
15.4. Coherence - internal
See below.
15.4.1. Comparison between preliminary and final data
This part compares key R&D variables as preliminary and final data.
Please see note in Concept 3.3.1.
| Total R&D expenditure – GOVERD (in 1000 of national currency) | Total R&D personnel (in FTEs) | Total number of researchers(in FTEs) | |
|---|---|---|---|
| Preliminary data (delivered at T+10) | |||
| Final data (delivered T+18) | |||
| Difference (of final data) |
Comments:
....
15.4.2. Consistency between R&D personnel and expenditure
Please see note in Concept 3.3.1.
| Average remuneration per year (cost in national currency) | Explanations of consistency issues, if any | |
|---|---|---|
| Consistency between FTEs of internal R&D personnel and R&D labour costs (1) | ||
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) |
(1) Calculate the average remuneration (cost) of individuals belonging to the internal R&D personnel, excluding those who are only formally ‘employees’ (university students, grant holders, etc.).
(2) Calculate the average remuneration (cost) of individuals belonging to the external R&D personnel (FTEs/other current R&D costs for external R&D personnel).
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
Please see note in Concept 3.3.1.
| Costs for the statistical authority (in national currency) | Cost for the NSI in time use/person/day | |
|---|---|---|
| Staff costs | ||
| Data collection costs | ||
| Other costs | ||
| Total 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.
Comments on costs:
....
16.2. Components of burden and description of how these estimates were reached
Please see note in Concept 3.3.1.
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | ||
| Average Time required to complete the questionnaire in hours (T)1) | ||
| Average hourly cost (in national currency) of a respondent (C) | ||
| Total cost |
1) T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.
18.1.1. Data source – general information
R&D data are collected through national R&D statistical surveys covering institutional sectors performing research and development activities in Montenegro.
18.1.2. Sample/census survey information
| Sampling unit | Government sector institutional units performing or potentially performing R&D activities |
|---|---|
| Stratification variables (if any - for sample surveys only) | |
| Stratification variable classes | |
| Population size | |
| Planned sample size | |
| Sample selection mechanism (for sample surveys only) | |
| Survey frame | Official administrative sources maintained by the Ministry of Education, Science and Innovation, together with lists of public research institutions and other identified government R&D performers |
| Sample design | |
| Sample size | |
| Survey frame quality | |
| Variables the survey contributes to | Intramural R&D expenditure, R&D personnel (HC and FTE), researchers (HC and FTE), labour costs, funding sources, type of R&D, fields of research and other GOV R&D indicators required under Regulation (EU) 2020/1197 |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | Ministry of Education, Science and Innovation – national R&D information and administrative records |
|---|---|
| Description of collected data / statistics | Lists of licensed scientific and research institutions and other administrative information used for identifying reporting units |
| Reference period, in relation to the variables the administrative source contributes to | 2023 |
| Variables the administrative source contributes to | Not applicable |
18.2. Frequency of data collection
See 12.3.3.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | Government sector institutions identified as actual or potential R&D performers. Data are collected directly by the Ministry of Education, Science and Innovation through the annual R&D survey. |
|---|---|
| Description of collected information | Information on intramural R&D expenditure, R&D personnel (HC and FTE), researchers, labour costs, sources of funding, type of R&D, fields of research (FORD) and other variables required under Commission Implementing Regulation (EU) 2020/1197 and the OECD Frascati Manual 2015. |
| Data collection method | |
| Time-use surveys for the calculation of R&D coefficients | Not applicable. FTE data are reported directly by reporting units in accordance with the OECD Frascati Manual methodology. |
| Realised sample size (per stratum) | Not applicable |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | Self-administered questionnaire distributed by the Ministry of Education, Science and Innovation, with direct communication and methodological support provided where necessary. |
| Incentives used for increasing response | No specific incentives are used. |
| Follow-up of non-respondents | |
| Replacement of non-respondents (e.g. if proxy interviewing is employed) | Not applicable. |
| Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility) | Not available. |
| Non-response analysis (if applicable -- also see section 18.5.4 Data compilation - Weighting and Estimation methods) | No formal non-response analysis is currently available. |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| R&D national questionnaire and explanatory notes in English: | Not available |
| R&D national questionnaire and explanatory notes in the national language: | National R&D questionnaire and methodological instructions |
| Other relevant documentation of national methodology in English: | Not available |
| Other relevant documentation of national methodology in the national language: | Not available |
18.4. Data validation
Validation procedures are carried out throughout the statistical production process.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition:
Imputation rate (for the variable x) % = (Number of imputed records for the variable x) * 100/ (Total number of possible records for x)
18.5.2. Data compilation methods
Please see note in Concept 3.3.1.
| Data compilation method - Final data | |
|---|---|
| Data compilation method - Preliminary data |
18.5.3. Measurement issues
| Method of derivation of regional data | Regional R&D data are currently limited. |
|---|---|
| Coefficients used for estimation of the R&D share of more general expenditure items | Not applicable. |
| Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures | Not applicable. |
18.5.4. Weighting and estimation methods
Not applicable.
| Description of weighting method | |
|---|---|
| Description of the estimation method |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
The national R&D statistical system in Montenegro is currently undergoing further methodological development and consolidation in line with:
OECD Frascati Manual 2015;
Commission Implementing Regulation (EU) No 2020/1197, consolidated;
ESS standards.
Significant efforts have been undertaken in recent years in order to:
establish a harmonised national methodological framework;
strengthen institutional coordination;
improve data quality and validation procedures;
ensure continuity of annual R&D statistical reporting;
improve international comparability of R&D indicators.
Particular attention has been devoted to:
retrospective compilation of R&D data for the period 2021–2023;
strengthening survey coverage;
improvement of metadata and quality reporting;
harmonisation with ESS reporting requirements.
Continuous methodological improvements and further strengthening of the national R&D statistical system are ongoing.
Statistics on Government R&D (GOVERD) measure research and experimental development (R&D) performed in the Government sector, i.e. R&D expenditure and R&D personnel. 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 all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.
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, which is the internationally recognised standard methodology for collecting R&D statistics and by the European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).
The guiding document to preparing the quality reports is the European Statistical System (ESS) Handbook for Quality and Metadata Reports — re-edition 2021.
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.
10 June 2026
See below.
The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.
See below.
Not requested.
The reference period used for R&D statistics in the Government sector is the calendar year.
R&D expenditure, personnel and other survey variables refer to activities performed during the reference 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.
R&D expenditure is published in the following units: Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).
R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.
See below.
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.
The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.
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.
