NATIONAL INSTITUTE OF STATISTICS

Department of Short Terms Economic Indicators Statistics

16 Libertatii Bvd, Bucharest 5, Romania

Statistics on Government Budget Allocations for R&D (GBARD) measure government support to research and development (R&D) activities, and thereby provide information about the priority governments give to different public R&D funding activities. This type of funder-based approach for reporting R&D involves identifying all the budget items that may support R&D activities and measuring or estimating their R&D content.

Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities (FM 2015, Chapter 12), which is the internationally recognised standard methodology for collecting R&D statistics and by Eurostat’s European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics).

Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020.

The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail (Commission Implementing Regulation (EU) 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics (europa.eu)).

Statistics on science, technology and innovation were collected until the end of 2020 based on Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.

Distribution by socioeconomic objectives (SEO) is based on the Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS) at one digit level.

See below.

GBARD statistics are assumed to report detailed data on all the government's budget items that may support R&D activities and to measure or estimate their R&D content. For the purposes of GBARD, the Government sector comprises (a) the central (federal) government, (b) regional (state) government and (c) local (municipal) government subsectors (FM2015, Chapter 12).

Not requested.

All government legal units.

See below.

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.

Not requested.

Not requested. See point 5.

Not requested. The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.

Not requested.

a) Calendar year:

Reference period is the calendar previous year.

 b) Fiscal year: N/A

    Start month: N/A

    End month: N/A

See below.

Since the beginning of 2021, GBARD statistics are based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail.  GBARD statistics were based until the end of 2020 on the Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology.

National research, development and innovation strategy 2014-2020 https://www.mcid.gov.ro/wp-content/uploads/2022/12/hg-929-2014.pdf

Modification and completion of the National Strategy for research, development and innovation 2014 - 2020, approved by GD 929/2014 http://legislatie.just.ro/Public/DetaliiDocument/187003

National Education Law – http://legislatie.just.ro/Public/DetaliiDocument/125150

Government Ordinance 57/2002 on scientific research and technological development https://www.mcid.gov.ro/wp-content/uploads/2022/12/ordonanta-57-2002.pdf

 Law 319/2003 on the Statute of research and development staff https://legislatie.just.ro/Public/DetaliiDocumentAfis/45166

Evaluation and classification in order to certify the institutions from the national research-development system https://www.mcid.gov.ro/wp-content/uploads/2022/12/hg-1062-2011.pdf

Government Ordinance 41/2015 amending and supplementing Government Ordinance no. 57/2002 on scientific research and technological development –https://www.mcid.gov.ro/wp-content/uploads/2022/12/ordonanta-41-2015.pdf

Law 206/2004 on good conduct in scientific research, technological development and innovation –

http://legislatie.just.ro/Public/DetaliiDocument/52457

Law on the organization and functioning of official statistics in Romania no. 226/2009     https://insse.ro/cms/ro/content/cadru-legal-ins

Government Decision no. 586/2020 on the approval of the National Annual Statistical Program 2020; https://insse.ro/cms/ro/content/cadru-legal-ins

-          Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development

-          EBS Methodological Manual on R&D Statistics

Not requested.

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:

 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) https://insse.ro/cms/ro/content/norme-de-confiden%C8%9Bialitate

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)

https://insse.ro/cms/ro/content/norme-de-confiden%C8%9Bialitate

 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.

b)       Confidentiality commitments of survey staff:

A confidentiality certificate agreement is signed upon employment, where the official terms of confidentiality are established.

Not the case.

Generally, 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.

At NIS level, not exist specific press release related GBARD data.

Not applicable.

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.

Not applicable for GBARD data.

Frequency of dissemination is bi-annual.

See below.

1) Y - Yes, N – No

See below.

1) Y – Yes, N - No 

According with Commission 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

Preliminary GBARD data are transmitted to Eurostat via EDAMIS at 6  months after the end of the reference year.

Final GBARD data are transmitted  to Eurostat via EDAMIS at 12  months after the end of the reference year.

Not requested.

See below.

See below.

Not requested.

1) Y – Yes, N - No 

Explanatory notes in specific GBARD chapter from national questionnaire dedicated government sector of performance.

Not requested.

See below.

We have  included in GOV questionnaire a chapter dedicated for GBARD data.

The main part of data are provided from Ministry of Research, respectively National Authority of Scientific Research.

GBARD data are provided from administrative sources and  on-line questionnaire /self-administration statistical questionnaire.

See below.

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.)

To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.

See below.

GBARD data are collected by national questionnaire dedicated to government sector of performance in a specific chapter.

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197.

1)  Criteria: Obligatory data (provisional budget and final budget). Only 'Very Good' = 100% and 'Very Poor' <100% apply.

2)  Criteria: Optional data (final budget). 'Very Good' = 100%; 'Good' = >75%;'Satisfactory' 50 to 75%%; 'Poor' 25 to 50%; 'Very Poor' 0 to 25%.

See below.

1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.

2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled

1) Availability of the data: N: No, data are not available, Y: Yes, data are available + start year.

2) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled

1) Stage: P - provisional, F - final. 

2) Availability of the data: No, data are not available, Y: Yes, data are available + start year.

3) Time of compilation: T is assumed to represent the end of reference period, x expresses the number of months after (positive) or before (negative) T when data is compiled

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.

1)  Ranking of the type(s) of errors that result in over/under-estimation, from the most important source of error (1) to the least important source of error (5) In the event that errors of a particular type do not exist, is used the sign ‘-‘.

2)  The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for GBARD.

1) High level of coverage (At least all national or federal ministries and the ministries and agencies responsible for R&D funding at state or regional level). High rate of response (>90%) in data collection. All figures broken down by NABS.  

2) If at least one out of the three criteria described above would not be fully met.

3) In the event that the rate of response would be lower than 80% even by meeting the two remaining criteria.

4) In the event that the average rate of response would be lower than 70% and at least one of the two remaining criteria would not be met.

5) If all the three criteria described above are not met.

Not requested.

Not requested.

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.

Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.

a)       Description/assessment of coverage errors:

We analyze the nomenclature specific to the units in the government performance sector in addition to BR, the operating R&D  national laws for this sector, the administrative sources and we find out if there are units that do not belong to GOV.

 All units from government sector of performance answer at chapter dedicated GBARD.

b)      Measures taken to reduce their effect:

For the units described in point a) we take the decision to move to another performance sector if necessary.

We have a specific filter question for respondents by ticking yes or no if they have data related  Government budget allocations for R&D (GBARD).

Not requested.

Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values.

a)       Description/assessment of measurement errors:

Few errors in data collection, especially for indicator  "General advancement of knowledge: R&D financed from general university funds (GUF) "

b)      Measures taken to reduce their effect:

Taking in account that at national level there is no phenomenon attributed for this indicator, we have specific requirement to IT department in order to compare data.

The measures for reducing errors consisted in selection of staff with knowledge in R&D  methodology and experience in data entry and validation checks for online questionnaires. Also, we developed detailed methodological notes regarding  the new terms and their definition.

We recontact the respondents for supplementary clarifications. 

Non response errors: occur when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

a) Problems in obtaining data from targeted information providers:

 We consider that the respondents  understood correctly  the question regarding the credits allocated to the research and development activity

b) Measures taken to reduce their effect:

 In addition, we have in the questionnaire dedicated to the government performance sector a specific question regarding all the units that are subordinated to the responding unit and  receive Government budget allocations for R&D (GBARD).

c) Effect of non-response errors on the produced statistics:

 Obligatory filter  question in GOV survey for chapter related GBARD.

Not requested.

Not requested.

Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.

a)       Data processing and editing processes:

 Few errors from respondents

b)      Description of errors:

 Error related unit measure.

c)       Measures taken to reduce their effect:

We measures for reducing errors consisted in selection of staff with knowledge in R&D  methodology and experience in data entry and validation checks for online questionnaires. Also, we developed detailed methodological notes regarding  the new terms and their definition.

We recontact the respondents for supplementary clarifications.

Model assumption errors occur when the assumptions made for the estimation of parameters, models, the testing of statistical hypotheses, etc., are violated. As a result, the quality of the resulting statistics is affected (e.g. degrees of confidence might be inflated).

Description/assessment: N/A

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.

Date of first release of national data: 6 months after the end of the calendar year (June)

Date of first release of national data: 12 months after the end of the calendar year (December)

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.

Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)

See below.

Not requested.

The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Regulation No 2020/1197, Frascati manual and the EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.

GBARD encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are within the scope only to the extent that their funds are allocated through the budgetary process (FM2015 §12.9). The following table lists a number of key methodological issues, which may affect the international comparability of national GBARD statistics.

See below.

See below.

1)       Breaks years are years for which data are not fully comparable to the previous period.

GERD covers R&D expenditures at national level, having as source the declarations of the units performing R&D activities;

GBARD includes R&D amounts from national budget.

Not requested.

Not requested.

This part compares GBARD statistics from the provisional and final budget for the reference year.

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. 

1)       The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.

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’)

Data revision is done whenever deemed necessary.

Not requested.

Not requested.

a)       Provisional data:

 The main provisional data are provided from  National Authority for Scientific Research and some another governamental units

b)      Final data:

 The final data are provided by the National Authority for Scientific Research and all other government units that complete the dedicated chapter GBARD.

c)       General University Funds (GUF):

Data only for General advancement of knowledge: R&D financed from other sources than GUF

See 12.3.3.

See below.

1) Time of data collection (T+x): T is assumed to represent the end of reference period. x expresses the number of months after (positive) or before (negative) T when data is collected.

Not the case.

Specific rules for data validation. Data are compared with previous years at the same period of reference.

The data are completed in the online portal and all specific validation rules are applied.

See below.

No-imputed data.

See below.

Not requested.

Not requested.