- Methods and Projects
- Standards and Classifications
Standardised Methodological Report
Statistics on R&D Activities in the Business Sector
- 1Contact
- 1.1Contact organisation
National Statistics Institute of Spain
- 1.5Contact mail address
Avenida de Manoteras 50-52 - 28050 Madrid
- 1.1Contact organisation
- 2Metadata update
- 2.1Metadata last certified
14/11/2023
- 2.2Metadata last posted
28/11/2023
- 2.3Metadata last update
14/11/2023
- 2.1Metadata last certified
- 3Statistical presentation
- 3.1Data description
The Statistics on R&D activities in the Business Enterprise sector arose for the purpose of measuring the economic and human resources (inputs) earmarked for these activities, to meet a dual objective:
- To provide a tool for the management, planning, decision and control, with regard to national scientific policy.
- To provide statistical institutions with the information that they request, obtained in accordance with international regulations which facilitate comparability between various countries.The methodology follows the recommendations set out by the OECD in the Frascati Manual https://www.oecd.org/sti/inno/frascati-manual.htm, which is one of the pillars for better understanding the role of science and technology. Moreover, it provides internationally-accepted R&D definitions and classifications.
IMPORTANT NOTE ON THE STATISTICAL CONCEPT OF 'ENTERPRISE':
In accordance with the European Statistical System, for 2021 the R&D Statistics in the Business Enterprise Sector (R&D in BES) have implemented a new practical application of the statistical concept of 'Enterprise'. The reasons and details of the adaptation of the statistical concept of the Enterprise were announced by the INE in a Press Release of December 17, 2019.
Under this new approach, an Enterprise can be formed by one or several Legal Units, and in the latter case, the Statistical Enterprise will condense the economic and employment variables of the Legal Units that comprise it. This criterion differs from that previously applied, by which each separate Legal Unit was considered a business. Although the new approach affects only Legal Units that are part of business groups -which are highly relevant entities in terms of economics and employment- the statistical results of the R&D in BES and its distribution by activities and sizes is affected. So that users can compare the R&D in BES data under the traditional approach (based on separate Legal Units) and the new approach (based on Statistical Enterprises for the 2021 reference period the INE has released both versions of the statistical results.
Since the reference period 2022, for the purposes of disseminating results, only the version based on Statistical Enterprises will prevail.
- 3.2Classification system
- Clasificaciones utilizadas
The statistics use the National Classification of Economic Activities, CNAE-2009, to encode the activity of the companies, process and disseminated their data.
Further information on the statistics methodology may be obtained at: http://ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176754&menu=metodologia&idp=1254735576669
- Clasificaciones utilizadas
- 3.3Sector coverage
The target population of study is the group of companies, located in the country, from all of the activity branches, with the exception of CNAE 84 and CNAE 854 ("Public Administration and Defence; Compulsory Social Security" and "Post-secondary Education", respectively).
- 3.4Statistical concepts and definitions
- Economic activity
The economic activity carried out by a company is defined as the creation of added value by means of the production of goods and services.
Each one of the statistical units (companies) studied frequently carries out various activities that should be classified in separate classes of the National Classification of Economic Activities. In general, the activities carried out by an economic unit may be of three types: main, secondary and auxiliary activities. The main activity differs from secondary activities in that it generates greater added value; whilst auxiliary activities are those that generate services that are not sold on the market and that only serve the unit on which they depend (administration departments, transport services or storage).
Due to the difficulties faced by companies in calculating added value when various activities are carried out, the activity which generates the greatest volume of business is considered the main activity or, failing that, that which employs the greatest number of persons. - Main economic activity code
The companies in the CCD present the encoded main activity according to the CNAE-2009 Classification. For the purposes of use, different levels are used, depending on the number of categories considered
- Economic activity
The economic activity carried out by a company is defined as the creation of added value through the production of goods and services.
The main economic activity is understood to be that which generates greatest added value. Facing the difficulty of calculated the added value for those companies that perform several activities, this considers the main activity to be that which generates the greatest turnover, or failing this, that which occupies the most employees.
The classification used in the National Classification of Economic Activities (CNAE-2009), prepared according to the conditions set out in the Regulation passing NACE Rev.2. This classification serves to determine who is carrying out the research.
In the case of research associations and companies whose main activity is the performance of R&D activities, mainly at the service of a given company or group of companies, units with CNAE 7211, 7219 or 7220; information is also requested on the main activity of those companies or groups of companies that benefit from their R&D activities, and their results will be computed within the branch of activity benefited by the research - Turnover
This includes the total amounts invoiced by the observation unit, during the reference period, for the sales of goods and services supplied to third parties, considering both those carried out directly by the observation unit itself, and those from temporary outsourcing.
These sales of goods or services are accounted for in net terms, that is, including the charges to the client (transport, packages, etc.), though invoiced separately, but deducting the discount on sales for early payment, returns of sales or the value of returned packages, as well as taxes on sales. This includes taxes and fees on goods or services invoiced by the unit, but excludes the VAT paid by the client.
From an administrative point of view, the General Accounting Plan (PGC) (RD 1514/2007, of 16 November) defines the Total net value of turnover, using the following accounting items: C700+C701+C702+C703+C704+C705-C706-C708-C709 with:
C700. Sales of merchandise
C701. Sales of finished products
C702. Sales of semi-finished products
C703. Sales of sub-products and waste
C704. Sales of packages and packaging
C705. Provision of services
C706. Discount on sales for early payment
C708. Returns of sales and similar transactions
C709. "Taxes" on sales
Therefore, turnover includes neither subsidies nor other operating income. It also excludes financial and extraordinary income, and other income that affects the results of the fiscal year. - Purchase of R&D (external R&D)
It includes funds paid to research services firms or other units performing R&D under contract. It excludes the internal funds to support a unit's active participation in collaborative R&D projects, these projects should be recorded as part of a unit's intramural performance.
- Dimension or size of the company
This dimension may be established by considering the magnitude of turnover, or by considering the number of persons that constitute the company workforce.
- Company
The company is the smallest combination of legal units that is an organizational unit producing goods or
services, which benefits from a certain degree of autonomy in decision-making, especially for the
allocation of its current resources. A company carries out one or more activities at one or more
locations. A company may be a sole legal unit. - Expenditures in activities of internal R&D
Defined as internal expenditure on R&D are all the amounts earmarked for R&D activities, carried out within the research department or unit, irrespective of the source of the funds. Expenditure incurred outside the department, but related to internal support tasks of R&D (acquisition of supplies for R&D, for example) is also included as internal R&D expenditure.
- Research and experimental development (R&D)
Research and experimental development (R&D)
It is defined as the set of creative work that is systematically undertaken for the purpose of increasing the volume of knowledge, including the knowledge of man, culture and society, as well as the use of this sum of knowledge to conceive new applications.
For an activity to be an R&D activity, it must satisfy five core criteria.
The activity must be: novel, creative, uncertain, systematic, transferable and/or reproducible.
R&D encompasses three types of activity:
a) Basic research. This consists of original, experimental or theoretical work that is mainly undertaken to obtain new knowledge on the essentials of the phenomena and observable facts, without being directed at a specific application or use.
Basic research analyses properties, structures and relationships, for the purpose of formulating and contrasting hypothesis, theories or laws. The researcher may not know of real applications when performing the research. The results of basic research are not normally offered for sale, but rather, are generally published in scientific magazines or are directly disseminated among institutions or interested persons.
b) Applied research. This also consists of original work undertaken with the objective of acquiring new knowledge. However, it is mainly directed towards a specific practical objective.
Applied research is undertaken to determine the possible uses of the results of basic research, or to determine new methods or forms for attaining specific predetermined objectives. This type of research implies taking into consideration all existing knowledge, in depth, with the intention of solving specific problems. This research facilitates putting ideas into practice.
c) Technological development. This consists of systematic work based on existing knowledge, obtained through research and/or practical experience, directed at the manufacture of new materials, products or devices; to establish new processes, systems and services; or to the significant improvement of those already existing. - Occupation of R&D personnel
R&D personnel are classified according to the following categories:
· Researchers
These are the scientists and engineers involved in the concept or creation of new knowledge, products, processes, methods and systems in the management of the corresponding projects.
Also included are managers and administrators dedicated to the planning and management of the scientific and technical aspects of the work of the researchers, and which normally have a category higher than or equal to that of persons employed directly as researchers, often dealing with former researchers or part-time researchers.
It includes graduate students with a study wage/grant who carry out R&D activities as well.
As a general rule, they possess advanced university education, but for the purposes of this study, also included as researchers are those persons who, being devoid of the aforesaid qualification, occupy positions of this nature.
· Technicians
Technicians and similar personnel are persons whose main tasks require knowledge and technical experience in one or more fields: engineering, biological and physical sciences, or social sciences and humanities. They participate in R&D projects, carrying out scientific and technical tasks, applying operational principles and methods, generally under the supervision of researchers. Similar personnel carry out tasks corresponding to social sciences and humanities under the supervision of researchers.
Their tasks are mainly the following:
- search for bibliographic material and discover appropriate information sources in archives and libraries
- prepare computer programmes
- prepare the material and equipment necessary for carrying out experiments, tests and analyses
- perform experiments, tests and analyses
- carry out measurements and calculations and prepare tables and graphs
- carry out surveys and interviews
- ensure logistic support to researchers.
Normally they possess intermediate-level university education (technical engineers and university diplomas), but others do not, although they occupy positions of an comparable level. It can also include top-level personnel entrusted with the use of very sophisticated appliances, but they are distinguished from researchers in that the latter are in charge of directing or orienting the research tasks.
· Assistants (auxiliaries)
Auxiliary staff includes workers, whether qualified or unqualified, and secretarial and office personnel who participate in the realisation of R&D projects, or who are directly related to said projects.
This category includes all managers and administrators mainly occupied in financial matters, personnel management and administration in general, provided that their activities are directly related to R&D tasks. - Source of R&D funds
Total expenditure on activities of internal R&D must be disaggregated by source of the received funds for R&D, we distinguish between internal funds and external funds.
It entails those transfers of resources that an unit, organisation or sector has received from another unit, organisation or sector for the realisation of activities of internal R&D.
Two conditions must be met for this financial flow to be correctly identified:
- a direct transfer of resources must exist
- this transfer should be foreseen at the same time and truly be used for R&D activities.
The transaction may be in the form of a contract, financial assistance or a donation, and may consist of a monetary contribution or the contribution of other resources (for example, personnel or material). - Personnel employed in R&D activities
R&D personnel is defined as all personnel directly employed in R&D activities, without distinguishing their level of responsibility, as well as those who supply services directly linked to R&D work, such as managers, administrators and office personnel.
Persons rendering indirect services, such as canteen, security, maintenance,etc. are excluded, even though their wages must be accounted for as other current expenditure on R&D.
Personnel data may be measured in two ways: in the number of individuals and in the personnel on a full-time equivalent (the sum of the personnel working full-time, plus the sum of the fractions of time of the personnel working part-time). - Staff on a full-time equivalent (FTE) dedicated to R&D
This is all staff (working full-time, plus the sum of the fractions of time of the staff working part-time) employed in R&D activities, without distinguishing their level of responsibility, as well as those who supply services directly linked to R&D work, such as managers, administrators and office staff.
Since the measurement criterion is in FTE, staff on a full-time equivalent (full-time) plus the sum of plus the sum of the fractions of time of the staff working part-time are taken into account. - Personal no remunerado
El personal ocupado no remunerado está constituido por las personas que trabajan con regularidad en la unidad de observación y no perciben una remuneración en forma de sueldo, salario, comisión, gratificación, destajo o en especie.
- Personal ocupado
Se corresponde con el número total de personas que trabajan en la unidad de observación (incluidos los propietarios que trabajan, los socios que trabajan con regularidad en la unidad y los familiares no retribuidos que trabajan con regularidad en la unidad) y el de personas que, aunque trabajan fuera de la unidad, pertenecen a ella y son retribuidas por ella (por ejemplo, los representantes de comercio, el personal de mensajería y los equipos de reparación y mantenimiento que trabajan por cuenta de la unidad de observación). Incluye tanto al personal remunerado como al no remunerado.
- Personal remunerado
Son las personas que trabajan para un empresario, tienen un contrato de trabajo y perciben una remuneración en forma de sueldo, salario, comisión, gratificación, destajo o en especie (deben incluirse todas las personas cuyos pagos se registran en el epígrafe "Costes de personal" en la cuenta de pérdidas y ganancias de la empresa, incluso cuando, en algunos casos, no exista contrato de trabajo).
- Business sector
This sector includes all those companies, bodies and institutions whose main activities consists of the mercantile production of goods and services (except higher education) for sale to the public, at a price that corresponds to that of the economic reality. It also includes those private non-profit institutions that are essentially serving companies.
- Sex
Sex refers to the biological sex of the person. According to the WHO, "sex" refers to biological and physiological features defining to men and women, whereas "gender" refers to the roles, behaviour, activities and attributes constructed socially that a specific culture regards as appropriate for men and women. In accordance with this description, the WHO regards "man" and "woman" as sex categories, whereas "male" and "female" are gender categories.
- Economic activity
- 3.5Statistical unit
The basic statistical unit for these operations is the enterprise, which is understood as “the smallest combination of legal units that is an organizational unit producing goods or services, which benefits from a certain degree of autonomy in decision-making, especially for the allocation of its current resources. An enterprise carries out one or more activities at one or more locations. An enterprise may be a sole legal unit “’ (definition of the Regulation of the European Union 696/93).
As previously explained in section 3.1, a new operational concept for 'Enterprise' is applied for the R&D Statistics in BES 2021, which we will hereinafter call the Statistical Enterprise and which differs from previous years in that, beginning this year, the Enterprise = Legal Unit analogy will no longer always be true. In other words, some Statistical Enterprises may be made up of two or more Legal Units.
The reporting unit , or rather, the unit from which the basic information is obtained is the Legal Unit. Given that it is perfectly defined and located and has accounting and employment data, the answer is facilitated and homogeneous information is obtained. The Legal Units can be legal persons (mercantile enterprises) or physical persons (individual entrepreneurs).
And so:
- Under the Legal Unit approach as a statistical unit, the information is obtained from the Legal Units, and the statistics are prepared under said Legal Units.
- Under the Statistical enterprise approach as a statistical unit, the information is obtained from each of the Legal Units that make up the enterprise, and the statistics are prepared by grouping (and where necessary, consolidating) the variables of all the Legal Units that make up the the enterprise.
- 3.6Statistical population
These Statistics study those companies that carry out research and experimental development activities, in any scientific field, and which are located within the national territory.
- 3.7Reference area
This includes all of Spain.
- 3.8Time coverage
The survey is carried out annually.
There are results available as of reference year 1964.
- 3.9Base period
For the 2021 reference period, the new practical application of the statistical concept of 'enterprise' was implemented. This change affects the statistical results of the R&D in BES, and its distribution by activities and sizes. So that users can compare the R&D Statistics in BES data under the traditional approach (based on separate Legal Units) and the new approach (based on Statistical enterprises), for the 2021 reference period the INE has released both versions of the statistical results .
Since the reference year 2022, only the version based on Statistical enterprises will prevail.
- 3.1Data description
- 4Unit of measure
- 4.1Unit of measure
Economic data are provided in thousand euros.
R&D personnel data are provided in headcount and in full-time equivalence.
- 4.1Unit of measure
- 5Reference period
- 5.1Reference period
The main reference period of these statistics is the year immediately prior to the year that the data is collected. For the expenditure feature, the reference period will be the calendar year. With regard to personnel, in order to determine the number of persons who work in R&D, the statistics use both the annual average and the full-time equivalence of the personnel who carry out R&D activities (persons/year).
Data referred to the period: Anual A: 2022
- 5.1Reference period
- 6Institutional mandate
- 6.1Legal acts and other agreements
The compilation and dissemination of the data are governed by the Statistical Law No. 12/1989 "Public Statistical Function" of May 9, 1989, and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2021-2024, approved by Royal Decree 1110/2020, of 15 December, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2021-2024. (Statistics of the State Administration).
Regulation (EU) 2019/2152 of the European Parliament and the Council of 27 November 2019 on European business statistics
- 6.2Data sharing
The exchanges of information needed to elaborate statistics between the INE and the rest of the State statistical offices (Ministerial Departments, independent bodies and administrative bodies depending on the State General Administration), or between these offices and the Autonomic statistical offices, are regulated in the LFEP (Law of the Public Statistic Function). This law also regulates the mechanisms of statistical coordination, and concludes cooperation agreements between the different offices when necessary.
They are carried out in collaboration with the Autonomous Communities.
- 6.1Legal acts and other agreements
- 7Confidentiality
- 7.1Confidentiality - policy
The Statistical Law No. 12/1989 specifies that the INE cannot publish, or make otherwise available, individual data or statistics that would enable the identification of data for any individual person or entity. Regulation (EC) No 223/2009 on European statistics stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society
- 7.2Confidentiality - data treatment
INE provides information on the protection of confidentiality at all stages of the statistical process: INE questionnaires for the operations in the national statistical plan include a legal clause protecting data under statistical confidentiality. Notices prior to data collection announcing a statistical operation notify respondents that data are subject to statistical confidentiality at all stages. For data processing, INE employees have available the INE data protection handbook, which specifies the steps that should be taken at each stage of processing to ensure reporting units' individual data are protected. The microdata files provided to users are anonymised.
The questionnaire sent to the collaborating units notifies that "The personal information obtained by the statistical services, both directly from the respondents and from administrative sources, will be subject to protection and are covered by statistical secrecy (Article 13.1 of the Law on Public Statistical Services of May 9 1989, (LFEP)). All statistical personnel has the obligation of preserving statistical secrecy (Article 17.1 of the LFEP)”.
- 7.1Confidentiality - policy
- 8Release policy
- 8.1Release calendar
The advance release calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.
- 8.2Release calendar access
The calendar is disseminated on the INEs Internet website (Publications Calendar)
- 8.3User access
The data are released simultaneously according to the advance release calendar to all interested parties by issuing the press release. At the same time, the data are posted on the INE's Internet website (www.ine.es/en) almost immediately after the press release is issued. Also some predefined tailor-made requests are sent to registered users. Some users could receive partial information under embargo as it is publicly described in the European Statistics Code of Practice
- 8.1Release calendar
- 9Frequency of dissemination
- 9.1Frequency of dissemination
The statistics are disseminated annually.
- 9.1Frequency of dissemination
- 10Accessibility and clarity
- 10.1News release
The results of the statistical operations are normally disseminated by using press releases that can be accessed via both the corresponding menu and the Press Releases Section in the web
- 10.2Publications
The results of the statistics are disseminated via the INE website, and some results are included in publications, such as the Statistical Yearbook, INE Figures, etc.
- 10.3On-line database
INEbase is the system the INE uses to store statistical information on the Internet. It contains all the information the INE produces in electronic formats. The primary organisation of the information follows the theme-based classification of the Inventory of Statistical Operations of the State General Administration . The basic unit of INEbase is the statistical operation, defined as the set of activities that lead to obtaining statistical results on a determined sector or subject based on the individually collected data. Also included in the scope of this definition are synthesis preparation.
Tables and time series may be viewed in INEbase, within the "Science and technology" section at www.ine.es
https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176754&menu=ultiDatos&idp=1254735576669 - 10.4Micro-data access
A lot of statistical operations disseminate public domain anonymized files, available free of charge for downloading in the INE website Microdata Section
That research that wishes to gain access to the microdata must sign an agreement with the National Statistics Institute for access, for statistical purposes, by research personnel, to confidential INE data. The agreement describes the project and the need to access said microdata, specifies the period during which the research team will work in the INE, provides the name of the research team and establishes the agreement clauses, including the statistical confidentiality clause.
This access shall be made through the so-called Secure Place, which consists of computers where said databases are available, and which verify a series of physical and technological provisions to protect the security and integrity of the statistical databases, which in practice implies that strict protocols are applied to those external users who wish to access the microdata for research purposes. The Secure Place is available, not only at the Central Services of the INE, but also in the Provincial Delegations.
- 10.5Other
There is the possibility of requesting customised information from the INE User Care Department. At the time of processing said requests, limitations regarding confidentiality or precision are borne in mind.
See - 10.6Documentation on methodology
A detailed description is available at:
http://ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176754&menu=metodologia&idp=1254735576669 - 10.7Quality documentation
Based on Regulation (EU) 2019/2152 of the European Parliament and the Council of 27 November 2019 on European business statistics assessing the quality of the data transmitted, and publishes reports regarding the quality of European statistics. To this end, within the 20 months following the end of the year, each country provides a quality report.
https://ec.europa.eu/eurostat/cache/metadata/en/rd_esms.htm
Fields 10.6 to 17.2 from this document are the quality report targeting users for this operation.
- 10.1News release
- 11Quality management
- 11.1Quality assurance
Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 16 principles, gathered in three areas: Institutional Environment, Processes and Products. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, Self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation.
In order to guarantee quality information, the information received is processed, following the steps listed below:
- Control and manual filtering of the questionnaires by the units involved in the information collection, with the objective of recovering the possible lack of data or correcting errors in the questionnaires before they are recorded.
- Interactive recording with filtering and correction of the errors in the information obtained by the units involved in the information collection.
- Control of the information received by the unit responsible for the statistics.
- Control of the scope and processing of identification errors.
- Validation of the quality of the information.
- Imputation of the partial non-response.
- Filtering and interactive correction of inconsistencies in the validated information.
- Preparation of a first phase of results analysis tables.
- Macro-publishing of the main aggregates to correct the errors not detected in the previous micro-filtering phase.
- Data analysis.
- Creation of the final data file.
- Obtaining final results tables in the unit responsible for the statistics, compiled from the final data file.
- 11.2Quality assessment
The following may be cited as being among the main strengths of this survey:
1) Rapid collection, analysis and publication of the results of the latter are carried out within the 11 months following the end of the reference period.
2) As these statistics have been compiled since the year 1964, a comprehensive monitoring of the data can be performed, in such a way that possible inconsistencies therein can be detected, as well as obtaining a time series that is consistent over time.
3) In recent years, an effort has been made to collect the information via the Internet, thus enabling its completion.
4) Obtaining high response rates.
- 11.1Quality assurance
- 12Relevance
- 12.1User needs
Survey users include the following:
· Ministries and other public bodies.
· Territorial administrations (Autonomous Communities, municipal councils, etc.).
· Companies and non-profit institutions.
· Researchers and universities.
· Individuals.Each of the users has different needs, according to the destination and use of the information they require.
Among user uses, worth noting is the "Annual Report: Technology and Innovation in Spain", published by COTEC, using the data provided by the INE. On an international level, each year, the OECD prepares the Main Science and Technology Indicators publication, which includes information regarding R&D on an international level, and Eurostat periodically publishes information on a European level.
- 12.2User satisfaction
The INE has carried out general user satisfaction surveys in 2007, 2010, 2013, 2016 and 2019 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...
On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date.(Click next link)
The specific needs of users are borne in mind, so long as methodological revisions of the survey are carried out. In this way, and based on the regulation governing it, the content thereof is adapted as much as possible to the specific requirements of its users, increasing their satisfaction levels.
In the User Satisfaction Surveys conducted to date, it is possible to view the evaluation of the sector Sciencie and Technology in which this statistical operation is centred, which can help direct us with regard to user opinions of it.
- 12.3Completeness
The Statistics on R&D activities meets all the requirements established in the national and international regulations related to science and technology statistics.
Said statistics are governed by Regulation (EU) 2019/2152 of the European Parliament and the Council of 27 November 2019 on European business statistics. Therefore, the rate of statistical information supplied is R=100%.
- 12.1User needs
- 13Accuracy and reliability
- 13.1Overall accuracy
The statistics are designed to attain a high degree of reliability and accuracy of the data obtained.
The different processes to which the statistics are subjected, from the design thereof, until the final results (scope, collection, error filtering, imputation of non-response, etc.) are obtained, are oriented to obtaining the highest degree of statistical reliability.
- 13.2Sampling error
Statistics on R&D Activities are a census operation, so there are no sampling errors.
- 13.3Non-sampling error
A control of non-sampling errors is carried out throughout the statistical process. Two types of errors are examined:
Errors of congruence (very high variations with respect to last year, lack of mandatory data, incorrect sums, ...)
Errors of range (invalid valor of variables)
Specific information regarding the non-response rate is also available.
Unit non-response rate: A4=8.04%
Imputation rate: A7=3.87%
- 13.1Overall accuracy
- 14Timeliness and punctuality
- 14.1Timeliness
The data from the statistics is published at the end of the year following that of the information reference year.
(time bracket until the publication of the final data) TP2=11 months
- 14.2Punctuality
The dissemination of the data is performed in accordance with the structural statistics availability calendar that the INE prepares and publishes for each year.
- 14.1Timeliness
- 15Coherence and Comparability
- 15.1Comparability - geographical
The availability of a common methodology, design and process for collection, filtering, editing and elevation throughout the geographical scope, guarantees the comparability of the results among the different Autonomous Communities. On the other hand, the methodological adaptation to Regulation (EU) 2019/2152 of the European Parliament and the Council of 27 November 2019 on European business statistics, makes comparability possible with the remaining European Union countries.
- 15.2Comparability - over time
In line with the Frascati Manual, the methodology applied since the implementation of these statistics allows for their comparability over time.
For the 2021 reference period, the new practical application of the statistical concept of 'enterprise' is implemented. This change affects the statistical results of the R&D Statistics in BES, and its distribution by activities and sizes. So that users can compare the R&D Statistics in BES data under the traditional approach (based on separate Legal Units) and the new approach (based on Statistical enterprises), for the 2021 reference period the INE has released both versions of the statistical results .
Since the reference year 2022, only the version based on Statistical enterprises will prevail.
Length of the comparable time series under the Statistical Enterprise approach:CC2=2
- 15.3Coherence - cross domain
The data collected by the statistics do not allow the comparison with other domains or sources, due to the absence thereof.
Regarding the different sectors (Companies, Public Administrations, Higher Education, PNPI) for which the INE collects information, the data provided by the statistics on the Business Sector are coherent with the statistics for the remaining sectors, as the standardised international regulations in the Frascati Manual, and which are extensively used on an international level, are implemented in each one of them.
- 15.4Coherence - internal
Coherence is a fundamental matter, both in the planning of the survey methodology and in all of its preparation process. Coherence between variables is contrasted during all phases of the statistical process.
The statistics are 100% coherent on an internal level (for example, arithmetic and accounting identities are observed).
- 15.1Comparability - geographical
- 16Cost and burden
- 16.1Cost and burden
The budgetary credit necessary to finance the Statistics on R&D Activities (companies, public administration, higher education and PNPI) set out in the 2023 Annual Program is estimated at 412.95 thousand euros.
The use of electronic questionnaires has been implemented in order to facilitation completion thereof, and decrease the response burden.
- 16.1Cost and burden
- 17Data revision
- 17.1Data revision - policy
The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (link).
This general policy sets the criteria that the different type of revisions should follow: routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.
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- 17.2Data revision - practice
There has been no situation which would lead to the revision of data, both methodological as extraordinary items
- 17.1Data revision - policy
- 18Statistical processing
- 18.1Source data
The data from the statistics is obtained from the information that is filled in by legal units that potentially carry out R&D.
As of the year 2002, this study has been carried out in coordination with the Innovation in Enterprises Survey. As of the 2021 reference period, only the R&D activity is collected for the odd reference years and for even reference years, it continues to be collected in coordination with the E. on Innovation in Enterprises.The directory studied comprises the following:
- a comprehensive part that is contrasted with the CBR (Central Business Register), comprising those companies that potentially could carry out R&D activities (either because they appear as such from previous years, or because they have requested public financing for their own research projects), together with companies with more than 200 employees
- another random part extracted from the CBR, thus obtaining the final sample.
- 18.2Frequency of data collection
The data collection is annual, and is carried out during the months of March/April to July each year.
In this sense, the OECD and Eurostat recommend the collection of R&D data at least during the odd reference years, although in some countries, amongst them Spain, it has been carried out annually.
- 18.3Data collection
The information collection method is a mixed system based on post mailings and interviewer participation, with a significant telephone support for the collection thereof. The respondent units may send their data via the Internet, by ordinary post (completed print questionnaires) or by e-mail.
- 18.4Data validation
The initial stage of the survey information processing coincides with the collection fieldwork, and is carried out in parallel with the duration of the data collection. The articulated system is centred on the following main aspects: a continuous updating process; a filtering of the questionnaire content, integrated in the recording.
The recording and filtering of the questionnaires is carried out continuously by the same collection units responsible for the collection thereof, establishing the control regulations necessary to guarantee a suitable quality level for the whole process. Already in this phase, this facilitates controlling the errors that may affect the data obtained from the respondent units.
Once the data is received, in electronic format, by the unit responsible for the survey, an information coverage control is carried out, for the purpose of guaranteeing the completeness of the recorded data, detecting duplicities and coverage errors, and at the same time, being able to make a first assessment regarding the quality of the variables collected in the questionnaires. This phase is carried out on each one of the monthly files of recorded questionnaires, and its execution is prior to the compilation of the complete survey file, and at the beginning, therefore, of the whole information treatment (data processing).
- 18.5Data compilation
At the level of the Legal Unit:
During the micro-purification process, the detection and purging of errors and inconsistencies in the identification variables of each record is carried out, as well as the purging and imputation of contermination errors. Depending on the characteristics of each type of error, in certain cases, automatic imputation procedures are used, and in others, updates are made to the file in order to incorporate the corrections of the errors detected. Likewise, the systematic errors detected in the previous studies and analyses carried out on the recorded data are corrected.
At the level of Statistical Empreprise:
For the elaboration of the R&D Statistics in BES under the 'Statistical enterprise' approach, a method has been developed that is based on the following steps, each of which is described in more detail in the R&D Statistics Methodology document available on the INE website together to the statistical results of the operation.
- Delineation of the Statistical enterprises that operate in business groups through the so-called Profiling methodology and classification of the Legal Units that compose them (see details in section 3.3 of the R&D STATISTICS Methodology )
- Adequacy of the sample design and the information collection phase (see details in sections 5 and 6 of the R&D STATISTICS Methodology ).
- Aggregation of the Legal Units that make up each Sample Statistical enterprise and study of the combinations of typologies of said Legal Units (see details in section 7.2.1 of the R&D STATISTICS Methodology ).
- Consolidation for sample Statistical enterprises formed by more than one Legal Unit and containing relationships between them. For these enterprises, the flows between their Legal Units are identified to proceed with the cancellation of intra-enterprise transactions (see details in section 7.2.2 of the R&D Statistics Methodology ).
- Construction of the complete statistics, based on Statistical enterprises, whether they are independent Legal Units or enterprises of business groups (see details in section 7.2.3 of the R&D STATISTICS Methodology ).
The essential idea is that if the Legal Units of a Statistical enterprise serve, exclusively or mainly, other Legal Units of the same enterprise (for example, because they sell products under a vertical integration of the production process or provide services as an auxiliary relationship) , said servile Legal Units must be combined with the others to which they support to form the authentic statistical unit "enterprise", therefore having to combine and consolidate the corresponding variables.
- 18.6Adjustment
Given the annual nature of the statistics, no seasonal adjustment is performed.
- 18.1Source data
- 19Comment
- 19.1Comment
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- 19.1Comment