1.1. Contact organisation
National Statistical Institute
1.2. Contact organisation unit
Labour Statistics, Research and Development, Innovation and Information Society Department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
2 Panayot Volov Street, Sofia 1038, Bulgaria
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
30 October 2023
2.2. Metadata last posted
30 October 2023
2.3. Metadata last update
30 October 2023
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).
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. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
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).
3.2.1. Additional classifications
| Additional classification used | Description |
| Yes. | International Standard Classification of Education (ISCED 2011). |
3.3. Coverage - sector
See below.
3.3.1. General coverage
| Definition of R&D | Definition of R&D is in line with FM2015 recommendations. |
| Fields of Research and Development (FORD) | Data for all 6 main fields of R&D are available. |
| Socioeconomic objective (SEO) | There are no deviations from NABS 2007 classification. All SEO are covered. |
3.3.2. Sector institutional coverage
| Private non-profit sector | All non-profit institutions serving households, as defined in the SNA 2008, with exclusion of those included in HES. |
| Inclusion of units that primarily do not belong to GOV | No. |
3.3.3. R&D variable coverage
| R&D administration and other support activities | According to FM2015 recommendations. |
| External R&D personnel | The categories of external R&D personnel, as specified in Table 5.2 of FM2015 are included in total R&D personnel. Data on internal and external R&D personnel are not separately available. |
| Clinical trials | Clinical trials are included in line with FM2015 recommendations. |
3.3.4. International R&D transactions
| Receipts from rest of the world by sector - availability | Data are available broken down in accordance with FM2015 by foreign enterprises, by EU, by international organisations and by other foreign sources. |
| Payments to rest of the world by sector - availability | Not available. |
3.3.5. Extramural R&D expenditures
According to the Frascati Manual, 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) | No. |
| Method for separating extramural R&D expenditure from intramural R&D expenditure | Not applicable. |
| Difficulties to distinguish intramural from extramural R&D expenditure | Not applicable. |
3.4. Statistical concepts and definitions
See below.
3.4.1. R&D expenditure
| Coverage of years | Calendar year. |
| Source of funds | Source of funds data are available in line with the requirements of Commission Implementing Regulation (EU) 2020/1197. Data on internal/external funds and transfer/exchange funds can not be distinguished. |
| Type of R&D | Data for all 3 types of R&D are available in line with FM2015. |
| Type of costs | Data on four types of costs are available: labour costs; other current R&D costs (incl. costs for external R&D personnel); total capital expenditure of which: expenditure for instruments and equipment. |
| Defence R&D - method for obtaining data on R&D expenditure | Defence R&D data are obtained through R&D Survey. |
3.4.2. R&D personnel
See below.
3.4.2.1. R&D personnel – Head Counts (HC)
| Coverage of years | Headcount data are reported by the respondents as an average number of persons engaged in R&D during the calendar year. |
| Function | Data for two types of ocupations are available – ‘Researchers’ and ‘Other R&D personnel’. |
| Qualification | Data for researchers and other R&D personnel are available by formal qualification (in accordance with ISCED 2011). Distinction can be made between ISCED8, ISCED 6+7, ISCED 4 and below. |
| Age | Data are available for researchers. |
| Citizenship | Data are available for researchers. |
3.4.2.2. R&D personnel – Full Time Equivalent (FTE)
| Coverage of years | Calendar year. Data on R&D personnel in FTE are provided by the reporting units, based on given guidelines. |
| Function | Data for two types of occupations are available - Researchers and Other R&D personnel. |
| Qualification | Data for researchers and other R&D personnel are available by formal qualification (in accordance with ISCED 2011). Distinction can be made between ISCED8, ISCED 6+7, ISCED 4 and below. |
| Age | Data not available. |
| Citizenship | Data not available. |
3.4.2.3. FTE calculation
Data on R&D personnel in FTE are provided by the reporting units based on given guidelines.
3.4.2.4. R&D personnel - Cross-classification by function and qualification
| Cross-classification | Unit | Frequency |
| Cross-classification by function and qualification for R&D personnel is available. | HC and FTE. | Annual. |
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 | Target population covers all known or assummed R&D performing private non-profit institutions serving households, with exclusion of those included in HES. | Not applicable. |
| Estimation of the target population size | 21 units. | Not applicable. |
3.7. Reference area
Not requested. R&D statistics cover national and regional data.
3.8. Coverage - Time
Not requested. See point 3.4.
3.9. Base period
Not requested. The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.
R&D expenditure - thousand BGN; R&D personnel - numbers in HC and FTE.
Calendar year 2021.
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. 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. |
| Nature of the “obligations” of responsible national organisations to produce statistics and report to international organisations | Mandatory. |
6.1.2. National legislation
| Existence of R&D specific statistical legislation | There is not R&D specific statistical legislation. The production of national R&D statistics is governed by the Statistics Act and National Statistical Programme, available at the following link: Legal Basis | National statistical institute (nsi.bg) |
| Legal acts | Statistics Act. Statistics Act (nsi.bg) |
| Obligation of responsible organisations to produce statistics (as derived from the legal acts) | Yes. |
| Right of responsible organisations to collect data – obligation of (natural / legal) persons to provide raw and administrative data (as derived from the legal acts) | Yes. |
| Obligation of responsible organisations to protect confidential information from disclosure (as derived from the legal acts) | Yes. |
| Rights of access of third organisations / persons to data and statistics (as derived from the legal acts) | No. |
| Planned changes of legislation | No. |
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
Confidentiality, being one of the process quality components, concerns the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and the extent of its use for statistical purposes.
A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.
a) Confidentiality protection required by law: The national Statistics Act (Chapter 6 “Protection of secrecy”) guarantees the protection of statistical confidentiality and the use of individual data of enterprises for statistical purposes only.
b) Confidentiality commitments of survey staff: Confidentiality commitments of survey staff are specified in the national Statistics Act, Article 27.
7.2. Confidentiality - data treatment
The two criteria (national confidentiality rules) applied for defining cells with direct disclosure risk (primary confidentiality), according to which certain data cannot be made public or released, are specified in Article 25 of the national Statistics Act: ‘statistical information, which aggregates data about less than three statistical units or about a population, in which the relative share of the value of a surveyed parameter of a single unit exceeds 85 per cent of the total volume of such parameter for all units in the population’. Secondary confidentiality treatment is carried out in way making it impossible to recalculate confidential data by subtraction from row and column aggregates.
8.1. Release calendar
R&D data are published in accordance with the deadline specified in the Release Calendar presenting the results of the statistical surveys carried out by the NSI, which is publicly accessible on the NSI website.
8.2. Release calendar access
The Release Calendar presenting the results of the statistical surveys carried out by the NSI of Bulgaria is available at the following link: Release Calendar | National statistical institute (nsi.bg)
8.3. Release policy - user access
The release policy of the NSI determines the dissemination of statistical data on R&D to all users at the same time - standard tables for free access. The users are informed that the data are being released by a press release. Specific data/breakdowns are provided to everyone with a specific request.
R&D data are disseminated annually.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Availability (Y/N)1 | Content, format, links, ... | |
| Regular releases | Y | Regular press release accessible free of charge by all users, published on 31 October 2022. Research and Development Activity in 2021 (preliminary data) (nsi.bg) |
| Ad-hoc releases | N |
1) Y - Yes, N – No
10.2. Dissemination format - Publications
See below.
10.2.1. Availability of means of dissemination
| Means of dissemination | Availability (Y/N)1 | Content, format, links, ... |
| General publication/article (paper, online) |
Y | Summary tables with key R&D figures, accomplished with definitions and explanatory notes, are published annually in: • 'Statistical Reference Book' Statistical Reference Book 2023 (Bulgarian version) | National statistical institute (nsi.bg) • 'Brochure Bulgaria' Brochure_Bulgaria2023.pdf (nsi.bg) |
| Specific paper publication (e.g. sectoral provided to enterprises) (paper, online) |
N |
1) Y – Yes, N - No
10.3. Dissemination format - online database
R&D data set is available in online database - Information System for online requests for statistical information (INFOSTAT) - at the following link: https://infostat.nsi.bg/infostat/pages/module.jsf?x_2=88
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
See below.
10.4.1. Provisions affecting the access
| Access rights to the information | Article 26a of the national Statistics Act reads as follows: ‘individual anonymous data under Art. 25 may be provided for the purposes of scientific research to higher schools or legal entities, whose main activity is scientific research, with a permission of the Chairperson of the National Statistical Institute’. |
| Access cost policy | Feasibility of provision of data requested and payment of expenses are checked and users are informed. |
| Micro-data anonymisation rules | Anonymization method/rules are applied in way making it impossible to identify the micro data provider. |
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. | Research and development activity (R&D) | National statistical institute (nsi.bg) |
| Data prepared for individual ad hoc requests | Y | Aggregate figures. | More detailed data available on request. |
| Other | N |
1) Y – Yes, N - No
10.6. Documentation on methodology
National reference metadata file is available on NSI website. Research and development activity (R&D) | National statistical institute (nsi.bg)
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.) | Disseminated R&D data are accompanied with metadata. Research and development activity (R&D) | National statistical institute (nsi.bg) |
| Request on further clarification, most problematic issues | Additional explanations (assistance) are provided to the users if required. |
| Measure to increase clarity | Not foreseen. |
| Impression of users on the clarity of the accompanying information to the data | Nevertheless that systematic feedback report is not available the expressed opinions of some of the regular users indicate that they are satisfied with the accompanying meta - information disseminated alongside R&D data and usually they don’t need further clarifications. |
11.1. Quality assurance
NSI of Bulgaria follows the recommendations on organization and quality management provided in the European Statistics Code of Practice (CoP) and implements the guidelines given in the European Statistical System Quality Assurance Framework (QAF). As part of the European Statistical System (ESS), NSI of Bulgaria endorses the Quality Declaration of the ESS.
Quality management system established in NSI (respectively of R&D statistics domain) is in conformity with the requirements of ISO 9001:2015. More information on the quality assurance and procedures that describe the quality policy in NSI of Bulgaria can be found on the NSI website at the following link: Quality | National statistical institute (nsi.bg)
11.2. Quality management - assessment
Quality checks are conducted throughout the entire statistical production process of R&D data on PNP, including comparisons with data from the previous survey, valid values checks, consistency and completeness checks, etc. The overall quality of the R&D data on PNP is assessed as very good. Data for all obligatory and optional R&D variables on PNP are annually produced strictly on time. As far as the R&D survey in Bulgaria is a census, sampling error does not exist, misclassification rate=0, completeness is 100%, data accuracy is very good as the response rate is 100 %. Coherence between preliminary and final PNP R&D data is very good as both data series are obtained from one and the same survey source.
12.1. Relevance - User Needs
See below.
12.1.1. Needs at national level
| Users’ class1 | Description of users | Users’ needs |
| 1 | Eurostat, DG RTD. | Tabulated data used for the compilation of EU aggregates for R&D, for international comparisons and dissemination to the users. Data used for R&D policy assessment and policy creation at EU level and for international comparisons. |
| 1 | Ministry of economy, Ministry of Education and Science, Ministry of Finance. | Data used for development and coordination of national R&D policy, for monitoring of the National Strategy for development of scientific research, for strategic programming, and other economic analysis. |
| 1 | Ministry of Regional Development and Public works, local authorities. | Data used for regional benchmarking, comparisons at regional level, follow up of the development and for policy purposes. |
| 3 | National and regional media (newspapers, magazines, TV). | Data used for general and specific analysis and comments released to the audience. |
| 4 | Bulgarian academy of science, public and private research institutes, universities, higher education institutions, students and postgraduates. |
Data used for a vast variety of scientific analysis, for research purposes and benchmarking, for teaching and advanced training of researchers and students, for scientific publications, studies, diploma works. |
| 5 | Agencies, companies, PNPO. | Data used for analyses and strategies. |
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 survey carried out by the NSI of Bulgaria (http://www.nsi.bg/en/node/16537) does not provide special information relevant for PNP R&D data. |
| User satisfaction survey specific for R&D statistics | User satisfaction survey for PNP R&D statistics has not been undertaken, but the effort to meet the needs of our users is an ongoing process. |
| Short description of the feedback received | No additional demands for R&D statistics on PNP are addressed to the NSI and the comments received so far from the key users (ministries, researches) prove that they are satisfied with the available information on R&D-related variables. |
12.3. Completeness
See below.
12.3.1. Data completeness - rate
100%.
12.3.2. Data availability
Share of PNP R&D expenditure in GERD (Gross Domestic Expenditure on R&D): 0,6%.
12.3.2.1. Incorporation of PNP sector in another sector
| Incorporation of PNP in another sector | Data on PNP sector are compiled separately. |
| 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 | PNP R&D statistics is compiled. |
| PNP R&D expenditure/ GERD*100) | 0,6%. |
| Share of PNP R&D Personnel in the respective figure of the total national economy | 0,5%. |
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 |
| Not available. | - | - | - | - | - |
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
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.
13.2. 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)
Coefficient of variation for Total R&D expenditure: Not applicable. Census survey.
Coefficient of variation for Total R&D personnel (FTE): Not applicable. Census survey.
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.
a) Extent of non-sampling errors: Not known, assumed to be small.
b) Measures taken to reduce the extent of non-sampling errors: The survey questionnaire accompanied with detailed instructions. Respondents are support by phone if needed.
c) Methods used in order to correct / adjust for such errors: -
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)
a) End of reference period: 31 December 2021.
b) Date of first release of national data: 31 October 2022.
c) Lag (days): 303
14.1.2. Time lag - final result
a) End of reference period: 31 December 2021.
b) Date of first release of national data: 28 February 2023.
c) Lag (days): 423
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) | 0 | 0 |
| Reasoning for delay | Not applicable. | Not applicable. |
15.1. Comparability - geographical
See below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. General issues of comparability
Compliance is achieved with FM2015 methodological recommendations in terms of applied concepts and definitions of the observed variables, type and coverage of the survey, data collection method, unit of observation, reference period. No problems regarding international comparability 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 or Frascati manual 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 paragraph 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 paragraph 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 | Deviation from recommendations | Comments on national treatment / treatment deviations from recommendations |
| Data collection method | No deviation. | |
| Survey questionnaire / data collection form | No deviation. | |
| Cooperation with respondents | No deviation. | |
| Data processing methods | No deviation. | |
| Treatment of non-response | No deviation. | |
| Data compilation of final and preliminary data | 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) | Since 1980 onwards. | No breaks. | |
| Function | Since 1980 onwards. | No breaks. | |
| Qualification | Since 1993 onwards. | No breaks. | |
| R&D personnel (FTE) | Since 1993 onwards. | No breaks. | |
| Function | Since 1993 onwards. | No breaks. | |
| Qualification | Since 1993 onwards. | No breaks. | |
| R&D expenditure | Since 1987 onwards. | No breaks. | |
| Source of funds | Since 1987 onwards. | No breaks. | |
| Type of costs | Since 1987 onwards. | No breaks. | |
| Type of R&D | Since 1987 onwards. | No breaks. | |
| Other | Since 1987 onwards. | No breaks. |
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 data are produced in the same way in the odd and even 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
Data from R&D survey are used for estimating R&D as capital formation in the National Accounts.
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) | 6254 | 124 | 104 |
| Final data (delivered T+18) | 6254 | 124 | 104 |
| Difference (of final data) | 0 | 0 | 0 |
15.4.2. Consistency between R&D personnel and expenditure
| Average remuneration (cost in national currency) | |
| Consistency between FTEs of internal R&D personnel and R&D labour costs (1) | Data on internal R&D personal are not separately available. |
| Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2) | Data on external R&D personal are not separately available, but they are included in total R&D personnel. |
(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) | % sub-contracted1) | |
| Staff costs | Not available. | No work sub-contracted to third parties. |
| Data collection costs | Not available. | No work sub-contracted to third parties. |
| Other costs | Not available. | No work sub-contracted to third parties. |
| Total costs | Not available. | No work sub-contracted to third parties. |
| Comments on costs | ||
| No comment | ||
1) The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.
16.2. Components of burden and description of how these estimates were reached
| Value | Computation method | |
| Number of Respondents (R) | 21 | |
| Average Time required to complete the questionnaire in hours (T)1 | Unknown. | |
| Average hourly cost (in national currency) of a respondent (C) | Unknown. | |
| Total cost | Unknown. |
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. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
18.1.1. Data source – general information
| Survey name | R&D survey. |
| Type of survey | Census survey. |
| Combination of sample survey and census data | No. |
| Combination of dedicated R&D and other survey(s) | No. |
| Sub-population A (covered by sampling) | Not applicable. |
| Sub-population B (covered by census) | Not applicable. |
| Variables the survey contributes to | All R&D variables and breakdowns requested by the Commission Implementing Regulation (EU) 2020/1197 and additional variable-dimension combinations. |
| Survey timetable-most recent implementation | R&D survey starts at 1 January after the end of the reference year. The deadline for receiving back the filled questionnaires is 30 of June after the reference year. Preliminary results for the variables with an annual frequency are available within 10 months of the end of the calendar year of the reference period. Final data compiled in line with the requirements of Commission Implementing Regulation (EU) 2020/1197 are transmitted to Eurostat 18 months after the reference year. |
18.1.2. Sample/census survey information
| Stage 1 | Stage 2 | Stage 3 | |
| Sampling unit | Institutional units - R&D performing private non-profit institutions serving households, with exclusion of those included in HES. | ||
| Stratification variables (if any - for sample surveys only) | Not applicable. | ||
| Stratification variable classes | Not applicable. | ||
| Population size | 21 | ||
| Planned sample size | Census survey. | ||
| Sample selection mechanism (for sample surveys only) | Not applicable. | ||
| Survey frame | National Business Register. | ||
| Sample design | Not applicable. Census survey. | ||
| Sample size | Not applicable. Census survey. | ||
| Survey frame quality | Good. |
18.1.3. Information on collection of administrative data or of pre-compiled statistics
| Source | No collection of administrative data or of pre-compiled statistics in PNP. |
| Description of collected data / statistics | Not applicable. |
| Reference period, in relation to the variables the survey contributes to | Not applicable. |
18.2. Frequency of data collection
R&D data are collected annually.
18.3. Data collection
See below.
18.3.1. Data collection overview
| Information provider | Micro data collection from the statistical units in PNP. |
| Description of collected information | Information collected through a single statistical survey on R&D activity in PNP comprises data on legally required obligatory and optional R&D variables in accordance with Commission Implementing Regulation (EU) No 2020/1197. |
| Data collection method | Online data collection through electronic web uniform questionnaire (for all sectors of performance). |
| Time-use surveys for the calculation of R&D coefficients | Not applicable. |
| Realised sample size (per stratum) | 21 units. R&D survey is a census. |
| Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.) | R&D data are provided by the respondents through electronic online questionnaire. |
| Incentives used for increasing response | After undertaken recalls to the initially nonresponding units the final non-response rate is 0 %. |
| Follow-up of non-respondents | Units that do not return the filled in R&D questionnaires within the deadlines defined are shortly after that reminded by NSI staff about their legal obligations to provide the required statistics by phone and/or by e-mail. The number of recalls/reminders are two to maximum three. |
| 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) | 100%. |
| 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: | Not available. |
| R&D national questionnaire and explanatory notes in the national language: | R&D QUESTIONNAIRE 2021 in Bulgarian.pdf |
| Other relevant documentation of national methodology in English: | National reference metadata available on NSI website. Research and development activity (R&D) | National statistical institute (nsi.bg) |
| Other relevant documentation of national methodology in the national language: | National reference metadata available on NSI website. Научноизследователска и развойна дейност (НИРД) | Национален статистически институт (nsi.bg) |
18.4. Data validation
During data validation process several types of checks are carried out including valid checks, consistency and completeness checks, comparisons with data from the previous R&D surveys.
18.5. Data compilation
See below.
18.5.1. Imputation - rate
Imputation is not performed.
18.5.2. Data compilation methods
| Data compilation method - Final data (between the survey years) | R&D survey on PNP is an annual mandatory survey. |
| Data compilation method - Preliminary data | Both preliminary and definitive/final R&D data on PNP are compiled on the basis of information collected through one and the same annual census survey on R&D activity in this sector. |
18.5.3. Measurement issues
| Method of derivation of regional data | Regional R&D data are compiled based on NUTS classification. |
| Coefficients used for estimation of the R&D share of more general expenditure items | Coefficients for estimation of R&D share are not used. |
| Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures | VAT and depreciation are excluded from R&D expenditure. |
| Differences between national and Frascati Manual classifications not mentioned above and impact on national statistics | No differences. |
18.5.4. Weighting and estimation methods
| Description of weighting method | Not applicable. Census survey. |
| Description of the estimation method | Not applicable. |
18.6. Adjustment
Not requested.
18.6.1. Seasonal adjustment
Not requested.
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).
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. Statistics on science, technology and innovation were collected until the end of 2020 based on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.
30 October 2023
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. R&D statistics cover national and regional data.
Calendar year 2021.
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 - thousand BGN; R&D personnel - numbers in HC and FTE.
See below.
Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. For simplicity, we call them surveys irrespective of whether they are sample surveys, censuses, collections of administrative data/pre-compiled statistics. This section presents the names of the surveys by sector of performance as well as methodological information for each survey. Depending on the type of survey and sector of performance, only the sections corresponding to that survey and sector are filled in.
R&D data are disseminated annually.
Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.
See below.
See below.
