1.1. Contact organisation
NATIONAL INSTITUTE OF STATISTICS ROMANIA
1.2. Contact organisation unit
DEPARTMENT OF SHORT TERM ECONOMIC INDICATORS STATISTICS
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
16 Libertatii Bvd., Bucharest 5, ROMANIA, Postal code 050706
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
19 February 2026
2.1. Metadata last certified
19 February 2026
2.2. Metadata last posted
19 February 2026
2.3. Metadata last update
19 February 2026
3.1. Data description
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit 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 private non-profit 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.
The 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 Eurostat’s 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 distribution of principal economic activity and by product field is based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
- 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 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.
NSH and SSH separately available.
Starting with 2011, available only for one digit FOS level.
3.3.2. Sector institutional coverage
| Private non-profit sector | Separately included. |
|---|---|
| Inclusion of units that primarily do not belong to PNP and the borderline cases | Not applicable. |
3.3.3. R&D variable coverage
| R&D administration and other support activities | No deviations from FM; personnel is not included but expenditure is included. |
|---|---|
| External R&D personnel | Starting with 2018 reference year, new questions related External R&D researchers.External R&D researchers included in personnel by occupation, but separately by employment status. Total personnel including external personnel. External personnel is mention separately in total. |
| Clinical trials: compliance with the recommendations in Frascati Manual §2.61. | Not included. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Not available |
|---|---|
| Payments to rest of the world by sector - availability | Not available |
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 | Starting with 2018, we included in questionnaire a specific questions for intramural and extramural current costs related R&D personnel. |
| Difficulties to distinguish intramural from extramural R&D expenditure | Difficulties to distinguish and understand for respondents the new indicators for External R&D personnel expenditure. |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | Calendar year. |
|---|---|
| Source of funds | In line with FM. |
| Type of R&D | In line with FM. |
| Type of costs | In line with FM, starting with 2018 reference year, detailed breakdown of current costs, for internal and external R&D perssonel expenditure. |
| Defence R&D - method for obtaining data on R&D expenditure | Data is obtained in the survey questionnaire. Data for Defence makes reference only to the expenditure for civilian purpose. |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | Data refer to end of period. |
|---|---|
| Function | Data compatible with ISCO-08. |
| Qualification | Data according with ISCED -2011, levels 0-8, in line with FM. |
| Age | Since 2011, not included. |
| Citizenship | We assimilate the citizenship with the origin country. Since 2011, not included. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | Calendar year. |
|---|---|
| Function | Data compatible with ISCO-08. |
| Qualification | Data according with ISCED -2011, levels 0-8, in line with FM. |
| Age | Since 2011, not included. |
| Citizenship | We assimilate the citizenship with the origin country. Since 2011, not included. |
3.4.2.3. FTE calculation
The respondent unit calculates the hours worked in research projects by the post-graduate students and computes in full time equivalent.
The method for calculated FTE indicators are mention in the questionnaire.
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 PNP 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 target population is defined by sectors of performance according to the methodology stipulated in the Frascati Manual 2015. |
|
| Estimation of the target population size | PNP units involved in R&D projects. Also, all units that stated in the last survey in the filter question intention to carry out CD activity in the reference year. |
3.7. Reference area
Not requested.
3.8. Coverage - Time
Not requested. See concept 12.3.2. (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.
Reference period is the calendar previous year - 2023 reference year.
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 the 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.
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 | Yes. National research, development and innovation strategy 2014-2020 - National R&D Strategy Modification and completion of the National Strategy for research, development and innovation 2014 - 2020, approved by GD 929/2014 - National Legislation National Education Law – National Education Law Government Ordinance 57/2002 on scientific research and technological development Law 319/2003 on the Statute of research and development staff Evaluation and classification in order to certify the institutions from the national research-development system Government Ordinance 41/2015 amending and supplementing Government Ordinance no. 57/2002 on scientific research and technological development Law 206/2004 on good conduct in scientific research, technological development and innovation – National Legslation on R&D Law on the organization and functioning of official statistics in Romania no. 226/2009 - National Statistical Legislation Government Decision no. 586/2020 on the approval of the National Annual Statistical Program 2020 - National Statistical Legislation This right derives from Law 206/2004 on good conduct in scientific research, technological development and innovation – National Legislation on R&D NIS President Order no 530/31.07.2001 National Law 544/2001 |
|---|---|
| Are respondents obliged by the national law to provide raw and administrative data: | Yes. |
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
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:
No deviations from secure procedure.
Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of such data and repealing Directive 95/46 / EC (General Regulation on data protection) - Data Protection Regulation
Law no. 190 of 18 July 2018 on measures to implement Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of these data and repealing Directive 95/46 / EC (General Data Protection Regulation) - General Data Protection Regulation
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.
LAW no. 363 of December 28, 2018 on protection natural persons regarding the processing of personal data by the competent authorities for the purpose of preventing, detecting, investigating, prosecuting and combating crime or the execution of punishments, educational and security measures, and regarding the free movement of such data.
Law no. 102/2005 on the establishment, organization and functioning of the National Authority for the Supervision of Personal Data Processing, with subsequent amendments and completions.
- Confidentiality commitments of survey staff: A confidentiality certificate agreement is signed upon employment, where the official terms of confidentiality are established.
7.2. Confidentiality - data treatment
Primary confidentiality:
- The rule of three (all cells with 3 and less units);
- The rule of dominance unit.
Secondary confidentiality:
- Disclosure by subtraction (differencing).
8.1. Release calendar
On the NIS website there are two calendars one for the press releases and the other for publications; both of them are accessible to the general public.
The final data are target to be published in press release and also in national publication to 11 months after the end of the reference year (in November).
8.2. Release calendar access
For Eurostat this is: Release calendar - Eurostat (europa.eu)
For NIS Romania this is:
- Catalogul_Publicatiilor_INS - for publications
- Press releases of INS - for press release
8.3. Release policy - user access
The NIS has on the web page a section “Calendar of press releases”, with links to the monthly lists of publications planned for the current year. Each monthly list is sorted by date of publication and contains a brief description of the statistics to be provided. The monthly calendar is established for the following year in December of the previous year. NIS publishes annually on the site the calendar of press releases, calendar based on the terms of the Annual National Statistical Program and contains: title of the press release, reference period, date of issue. The monthly calendar is established and posted on the NIS website from December of the previous year. The calendar of press releases on the NIS website covers only the statistics published by the NIS.
In the event of a change in the broadcast date, this is announced 24 hours before the calendar date, specifying the new broadcast date.
The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.
The frequency of R&D data dissemination at the national data is annual.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1) | Links | |
|---|---|---|
| Regular releases | Yes | The NIS press releases are sent directly by the NIS Press Office to the accredited media and ministries and are posted online at 9:00 a.m. in the dedicated section. Also, on the site there is the archive of these press releases, structured on statistical topics. |
| Ad-hoc releases | No |
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 | Yes | Web-site of Romanian National Institute of Statistics |
| Specific paper publication (e.g. sectoral provided to enterprises) | Yes | "Research and development activity in 2023" - R&D Activity |
1) Y – Yes, N - No
10.3. Dissemination format - online database
Data for non profit sector of performance are available in database TEMPO ONLINE: National Statistical 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 | NIS does not have a "Safe center" for access to microdata. Due to the confidential nature of microdata, direct access to anonymized data is offered only for scientific research projects according to European and national legislation in the field, through an access contract. Legal framework The current European and national legal framework enables access to anonymised microdata available only for scientific purposes.
The access is, in principle, limited to universities, research institutes, national statistical institutes, central banks within the EU and euro area countries, as well as to the European Central Bank. Individuals cannot be granted direct access to microdata. |
|---|---|
| Access cost policy | No |
| Micro-data anonymisation rules | Not applicable. |
10.5. Dissemination format - other
See below.
10.5.1. Metadata - consultations
Not requested.
10.5.2. Availability of other dissemination means
| Dissemination means | Availability (Y/N)1) | Micro-data / Aggregate figures | Comments |
|---|---|---|---|
| Internet: main results available on the national statistical authority’s website | Yes | ||
| Data prepared for individual ad hoc requests | Yes | ||
| Other | No |
1) Y – Yes, N - No
10.6. Documentation on methodology
Detail information about R&D national survey for PNP sector of performance applied are methodological notes, metadata and quality report.
Data are accompanied of metadata describing the indicators and the calculation thereof.
To all other questions regarding the methodology or the manner of designing the tables and the data we respond whenever necessary.
In the TEMPO online database, each indicator is accompanied by the related metadata.
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, graphs, methodological notes and quality report. |
|---|---|
| Requests on further clarification, most problematic issues | Further clarifications were not needed. To all other questions regarding the methodology or the manner of designing the tables and the data we respond whenever necessary. |
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).
The quality quantifies how well the statistics are fit for their purpose. The criteria to judge statistical quality correspond to: relevance, accuracy and reliability, timeliness and punctuality, accessibility and clarity, comparability, coherence and cost and burden. The aim is to reduce the errors of coverage, the non-response, the measurements errors, the processing errors.
The legal acts and other document related quality assurance are: Legislation concerning quality assurance, Task Forces or Working Groups, Law No. 226/2009 on the organisation and functioning of official statistics in Romania, Internal procedures, European Statistics Code of Practice, Quality Guidelines for Romanian Official Statistics.
Statistical practices used to compile national R&D data for non profit sector of performance are in compliance with Frascati Manual recommendations.
11.2. Quality management - assessment
Weaknesses that need immediate attentions:
- We try to find out more units belonging non-profit sector;
- Since 2011 we designed a specific questionnaire for PNP sector of performance to collect data in order to reduce the respondent burden.
The methodology was improved through the identification of non profit units.
The R&D survey for non profit sector of performance is conducted to provide knowledge about R&D indicators (mandatory and optional) and to allow comparisons with other European countries.
At every R&D survey for non profit sector of performance, before the finalization of the national questionnaire, the main national users and the representatives of regional NIS departments are invited to a discussion, by Romanian NIS, to express their opinions and suggestions about the final national questionnaire (clarity, difficulties, understanding and perception of the questions and about other national statistical needs).
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1) | Description of users | Users’ needs | |
|---|---|---|---|
| 1 |
European Commission, European Council, European Parliament. | Data used for the European R&D statistics and its further development. | |
| 1 | Governmental departments: Ministry of National Education, Ministry of Finance, Ministry of Economy, Authorities for Regional Development. | Data used for R&D national and regional strategy and policy, publications, training. | |
| 1 | OECD | Data used for international comparability. | |
| 2 | Scientific institutes and universities; Trade unions; Employer’s associations. | Data used for analyses. | |
| 3 | International or regional media. | Data used for analyses and comments to the general public. | |
| 4 | Researchers and students. | Data used for analyses and projects. | |
| 5 | Enterprises or businesses. | Market analysis, marketing strategy, consultancy services. |
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 | A user satisfaction survey is carried out by National Institute of Statistics. This survey is addressed to a selection of users of all statistical fields. Last one survey in 2024. Also, we receive information about from the Department of data dissemination, where the user 's requests are recorded |
|---|---|
| User satisfaction survey specific for R&D statistics | National users satisfaction survey is not specific for R&D statistics, but we have comments received from the large users' categories. |
| Short description of the feedback received | Not received detailed requests. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
Data completeness of final mandatory data are very good and good. National questionnaire survey for non profit sector of performance included also mandatory and optional R&D indicators.
12.3.2. Data availability
Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 0.80%
12.3.2.1. Incorporation of PNP sector in another sector
| Incorporation of PNP in another sector | not applicable |
|---|---|
| Reasons for not producing separate R&D statistics for the PNP sector | not applicable |
| Share of PNP expenditure in the total expenditure of the other sector | not applicable |
| Share of PNP R&D Personnel in the respective figure of the other sector | not applicable |
12.3.2.2. Non-collection of R&D data for the PNP sector
| Reasons for not compiling R&D statistics for the PNP sector | not applicable |
|---|---|
| PNP R&D expenditure/ GERD*100) | 0.80% |
| Share of PNP R&D Personnel in the respective figure of the total national economy | 1.09% |
12.3.2.3. Data availability on more detail level
| Additional dimension/variable available at national level1) | Availability2) | Frequency of data collection | Breakdown variables | Combinations of breakdown variables | Level of detail |
|---|---|---|---|---|---|
| Number of scientific meetings organised at national level with international participation. | not availability | ||||
| Training courses of R&D personnel. | not availability | ||||
| Publications papers by scientific programms according with NABS clasiffications (domestic level and international level). | not availability | ||||
| Number of R&D projects by NABS programms and by sources of funds. | not availability | ||||
| Breakdown of public funds by type of national R&D projects. | not availability |
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
12.3.2.4. R&D personnel - Cross-classification by function and qualification (if available in FTE and HC)
| Cross-classification | Unit | Frequency |
|---|---|---|
| YES | HC | annual |
| YES | FTE | annual |
| YES | both | annual |
| YES | expenditure | annual |
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:
- 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.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors,
- Processing errors.
Model assumption errors should be treated under the heading of the respective error they are trying to reduce.
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
The main indicator used to measure sampling errors is the coefficient of variation (CV).
Definition of coefficient of variation:
CV= (Square root of the estimate of the sampling variance) / (Estimated value)
Confidence interval for Total R&D expenditure: not applicable
Confidence interval for Total R&D personnel (FTE): not applicable
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
- Extent of non-sampling errors: Not applicable.
- Measures taken to reduce the extent of non-sampling errors: Not applicable.
- Methods used in order to correct/adjust for such errors: Not applicable.
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.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.2. Measurement error
Not requested.
13.3.3. Non response error
Not requested.
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
Not requested.
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: 15 November 2024.
- Lag (days): 319.
14.1.2. Time lag - final result
- End of reference period: 31 December 2023.
- Date of first release of national data: 29 November 2024.
- Lag (days): 333.
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) | 10 | 18 |
| Actual date of transmission of the data (T+x months) | 10 | 18 |
| 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
Data are available since 2003; PNP sector is underestimated (there are not known all potential providers of data for this sector).
Since 2011 reference year, specific questionnaire for PNP sector of performance.
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 or Frascati manual (FM) paragraphs and the EBS Methodological Manual on R&D Statistics 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 | |
| Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel | FM2015, §5.25 | 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 | |
| Intramural R&D expenditure | FM2015,Chapter 4 (mainly sub-chapter 4.2). | No deviation | |
| Statistical unit | FM2015, § 10.40-10.42 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation | |
| Target population | FM2015, § 10.40-10.42 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation | |
| Sector coverage | FM2015, § 10.2-10.8 ((in combination with Eurostat's EBS Methodological Manual on R&D Statistics). | No deviation | |
| Reference period for the main data | Reg. 2020/1197: Annex 1, Table 18 | No deviation | |
| Reference period for all data | 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, 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 10 (mainly sub-chapter 10.6). | No deviation | |
| Survey questionnaire / data collection form | FM2015 Chapter 10 (mainly sub-chapter 10.6). | No deviation | |
| Cooperation with respondents | FM2015 Chapter 10 (mainly sub-chapter 10.6). | No deviation | |
| Data processing methods | FM2015 Chapter 10 (mainly sub-chapter 10.6). | No deviation | |
| Treatment of non-response | FM2015 Chapter 10 (mainly sub-chapter 10.6). | No deviation | |
| 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
| Length of comparable time series | Break years1) | Nature of the breaks | |
|---|---|---|---|
| R&D personnel (HC) | |||
| Function | none | ||
| Qualification | 2003 | 1993-2003 first stage tertiary education teoretical (ISCED-5A) and practical (ISCED-5B) were surveyed together; since 2003 we have comparable data as they were surveyed separately. | |
| R&D personnel (FTE) | |||
| Function | none | ||
| Qualification | 2003 | 1993-2003 first stage tertiary education teoretical (ISCED-5A) and practical (ISCED-5B) were surveyed together; since 2003 we have comparable data as they were surveyed separately. | |
| R&D expenditure | |||
| Source of funds | 1993,1994 | during 1993 - 1994 we have data breakdown only by sources of funds for the current costs. | |
| Type of costs | 1993,1994 | there are included only current costs and not sub-total capital expenditures. | |
| Type of R&D | 1993,1994 | we have only total expenditures and not breakdown by sectors of performance. | |
| Other | 1996 2011 |
first year for total intramural expenditures by main field of science,
|
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
Yes.
The same as in the odd years.
15.3. Coherence - cross domain
See below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
R&D statistics for non profit sector of performance are compiled in according with institutional PNP sector as defined based on the System of National Account (SNA).
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.
| Total PNP R&D expenditure (in 1000 of national currency) | Total PNP R&D personnel (in FTEs) | Total number of PNP researchers (in FTEs) | |
|---|---|---|---|
| Preliminary data (delivered at T+10) | 66517 | 383 | 320 |
| Final data (delivered T+18) | 66517 | 383 | 320 |
| Difference (of final data) | - | - | - |
Comments:
....
15.4.2. Consistency between R&D personnel and expenditure
| Average remuneration per year (cost in national currency) | Explanation of consistency issues if any |
|
|---|---|---|
| Consistency between FTEs of internal R&D personnel and R&D labour costs (1) | 140308 | |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | 10469 |
(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
| Costs for the statistical authority (in national currency) | Cost for the NSI in time use/person/day | |
|---|---|---|
| Staff costs | not available separately | |
| Data collection costs | not available separately | |
| Other costs | not available separately | |
| Total costs | 130.372,89 |
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: Total costs is calculated for reference year 2024. Not available for reference year 2023.
....
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
|---|---|---|
| Number of Respondents (R) | 23 | All respondents with R&D indicators. |
| Average Time required to complete the questionnaire in hours (T)1) | 5.45 | Total number of hours (from questionnaire)/Number of all respondents with R&D indicators. |
| Average hourly cost (in national currency) of a respondent (C) | Not available | Not available. |
| Total cost | Not available | 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
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 - Research and development activity in specialised units.
Census for units reporting R&D activity in previous year and sampling for the rest units belonging to PNP sector.
Data are collected through a census survey, businesses that are known to perform R&D or to be potential R&D performers.
Number of R&D employees in HC at 31 December and FTE agreggated by occupation, qualification, by sex, by citizen.
Researchers- by sex, status employment, qualification level.
R&D Expenditures- by type of costs, by sources of funds, by type of research, by NABS Programms, by industry served.
In 2014:
- by citizen, nationality, age and by NABS programme are not included.
- for FOS only for one digit level.
R&D Expenditures - payments received from abroad by type of funds institutions.
Data collection: March-April after reference year.
Data processing, validation, comparison:May-September after reference year.
Data Dissemination (Press Release Communicate, Publication, Data base on line, Yearbook): November after reference year.
18.1.2. Sample/census survey information
| Sampling unit | Non Profit unit. |
|---|---|
| Stratification variables (if any - for sample surveys only) | Economic activity; Enterprise size according to the number of employees; Region |
| Stratification variable classes | not applicable |
| Population size | not applicable |
| Planned sample size | not applicable |
| Sample selection mechanism (for sample surveys only) | not applicable |
| Survey frame | not applicable |
| Sample design | not applicable |
| Sample size | not applicable |
| Survey frame quality | not applicable |
| Variables the survey contributes to | not applicable |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | Information are collected from R&D survey only and not from administrative data. |
|---|---|
| Description of collected data / statistics | Not used these methods. |
| Reference period, in relation to the variables the administrative source contributes to | Not applicable. |
| Variables the administrative source contributes to |
18.2. Frequency of data collection
See 12.3.2.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | Data is collected through national survey (R&D) addressed to non profit units. |
|---|---|
| Description of collected information | All providers send the same information filled in the national R&D questionnaire concerning number of personnel and R&D expenditures. |
| Data collection method | Data collection is made by paper questionnaire or electronic online portal questionnaire. |
| Time-use surveys for the calculation of R&D coefficients | Not applicable. |
| Realised sample size (per stratum) | Not applicable. |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | Postal surveys, online electronic questionnaire. |
| Incentives used for increasing response | Not applicable. |
| Follow-up of non-respondents | 2 reminders. |
| 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) | 0.77 |
| Non-response analysis (if applicable -- also see section 18.5. Data compilation - Weighting and Estimation methods) | Not applicable. |
18.3.2. Questionnaire and other documents
| Annex | Name of the file |
|---|---|
| R&D national questionnaire and explanatory notes in English: | |
| R&D 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
The data are validated at NIS level, after ensuring the completeness of the results and checking all correlations between indicators.
The statistical data are compared for each type of indicator with the data of previous years and the errors that present suspicions are discussed and transmitted to the respondents and / or the territorial statistical departments.
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)
Not applicable.
No imputation rate.
18.5.2. Data compilation methods
| Data compilation method - Final data | Annually |
|---|---|
| Data compilation method - Preliminary data | In accordance with the National Statistical Programme approved by the Romanian Government and published in the Official Journal within 10 months of the reference period we provide data for the previous year. |
18.5.3. Measurement issues
| Method of derivation of regional data | Each unit from sample has a specific code in order to regional identification. |
|---|---|
| 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 | Exclusion of VAT and depreciation. |
18.5.4. Weighting and estimation methods
| Description of weighting method | Not applicable |
|---|---|
| Description of the estimation method | Not applicable |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
No comments.
Statistics on Private non-profit R&D (PNPRD) measure research and experimental development (R&D) performed in the private non-profit 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 private non-profit 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.
The 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 Eurostat’s 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.
19 February 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.
Reference period is the calendar previous year - 2023 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:
- 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.
- Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:
-
- Coverage errors,
- Measurement errors,
- Non response errors,
- 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.
The frequency of R&D data dissemination at the national data is annual.
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.
