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Statistics on R&D Activities in the Public Administration Sector

• 1Contact
  • 1.1Contact organisation
    National Statistics Institute of Spain
    
  • 1.5Contact mail address

    Avenida de Manoteras 50-52 - 28050 Madrid

    
    
• 2Metadata update
  • 2.1Metadata last certified
    25/11/2024
  • 2.2Metadata last posted
    27/11/2024
  • 2.3Metadata last update
    25/11/2024
• 3Statistical presentation
  • 3.1Data description

    The Statistics on R&D activities in the Public Administration 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.

  • 3.2Classification system
    • Clasificaciones utilizadas

      The analysis units are grouped by sector, whose content is largely based on the National System of Accounts for the case in question, the Public Administration Sector, which are all those public institutions (except public companies and higher education institutions), regardless of the way in which they are included in the budgets and their level of jurisdiction.

      
      
      

      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

  • 3.3Sector coverage

    This includes all of the public institutions and non-profit institutions that are controlled by governmet units, except the public companies and higher education institutions, throughout the national territory.

  • 3.4Statistical concepts and definitions
    • 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.
    • Government Sector
      The Government sector comprises all units of central, regional and municipal (local) government, including social security funds, except those units that fit the description of higher education institutions, as well as all non-market non-profit institutions that are controlled by government units, and that are not themselves part of the Higher education sector. The public business enterprises are included in the Business enterprise sector.
    • 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.
    • 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).
    • Public organisations
      These are the organisations that supply society with public interest services that it would be neither economical nor easy to provide otherwise, free-of-charge or at conventional prices, and that administer public affairs and take charge of carrying out the economic and social policy of the group.
      These centres perform very numerous and diverse activities, and are usually related with the public administration, defense, public order, health, education, culture, economic promotion and development, well-being, scientific and technical development, etc.
    • 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.
    • 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.
    • 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.
    • 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).
    • 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.
  • 3.5Statistical unit

    The statistical unit is the public institution or non-profit institution that is controlled by government unit.

  • 3.6Statistical population

    Those public institutions and non-profit institutions that are controlled by government units, 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

    The Statistics on R&D Activities in the Public Administration sector has results available on R&D (including occasional R&D) as of reference year 2002. The year 2002 is the base period.

• 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.

• 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: 2023

• 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 OF THE COUNCIL of 27 November 2019 on European business statistics", https://www.ine.es/normativa/leyes/UE/minine.htm#30058

  • 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.

• 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)”.

• 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

    
    
• 9Frequency of dissemination
  • 9.1Frequency of dissemination

    The data is disseminated annually.

• 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.

    
    

    The link that allows for access to the online database is the following: https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176754&menu=ultiDatos&idp=1254735576669

     

    No. of data table queries: AC1=147.862 queries in 2023.

    No. of  metadata queries:  AC2=445.

  • 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
    

    The microdata from the statistics is not available.

  • 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 http://ine.es/ss/Satellite?L=es_ES&c=Page&cid=1254735550786&p=1254735550786&pagename=ProductosYServicios%2FPYSLayout#a1254735626789

  • 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

     

    The metadata completeness rate, AC3, is the ratio of the amount of metadata elements supplied to the total number of elements in the standardised methodological report.

    Metadata completeness rate, AC3=100%, as all the fields in the methodological file are filled in.

  • 10.7Quality documentation

    Based on Regulation (EU) 2019/2152 of the European Parliament and of 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. That report can be found in the following link:

    https://ec.europa.eu/eurostat/cache/metadata/en/rd_esms.htm

    Fields 10.6 to 17 from this document are the quality report targeting users for this operation.

• 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 errors in the information obtained by the unit responsible for the statistics.

    - 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

    Among the main strong points of these statistics are the following:

    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 electronic questionnaires, thus enabling their completion.

    4) Obtaining high response rates.

• 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)

     

    
    

    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 meet 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 of the Council of 27 November 2019 on European business statistics. Therefore, the rate of statistical information supplied is R1=100%.

• 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

    Given that the statistics in the Public Administration sector are a census operation, 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=2.11%

    Over-coverage rate: A2=1.69%

     

• 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.

    Punctuality (delay in publication): TP3=0

• 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 OF 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.

    There are CC2=22 comparable elements for the time series of the R&D expenditure and personnel variable.

  • 15.3Coherence - cross domain

    The data collected by the statistics does not allow for 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 Public Administration Sector is 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).

• 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 2024 Annual Program is estimated at 1,559.26 thousand euros⁽¹⁾. 

    The use of electronic questionnaires has been implemented in order to facilitate completion thereof, and decrease the response burden.

     

    (1) Formed by the statistical operations of the IOE: 30056 Directory of Enterprises and Public Organizations Potential Researchers, 30057 Statistics on R&D Activities in the Business Sector, 30058 Statistics on R&D Activities in the Public Administration Sector, 30059 Statistics on R&D Activities in the Non-Profit Private Institutions Sector, 30060 Statistics on R&D Activities in the Higher Education Sector.

• 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-.

    
    

    On Statistics on R & D, there are only extraordinary revisions which are due to errors detected once the data has been published.

  • 17.2Data revision - practice

    There has been no situation which would lead to the revision of data, both methodological as extraordinary items.

• 18Statistical processing
  • 18.1Source data

    The data is obtained from the questionnaires submitted by public institutions and hospitals.

    There are two questionnaire models: one for the public administration and the other for public hospitals.

  • 18.2Frequency of data collection

    The data is collected once a year, during the period from Abril to September.

    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 statistics 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 prior to the compilation of the complete file for the statistics, and therefore, at the beginning of the joint information processing.

  • 18.5Data compilation

    During the micro-filtering process, the detection and filtering of errors and inconsistencies in the identification variables of each register are carried out, as well as the filtering and imputation of content errors. The imputations and content errors are not performed automatically, but the parameters used for their calculation are calculated automatically.

    In the macro-filtering phase, different analysis tables are obtained that enable detecting and eliminating those errors and inconsistencies that were not detected in the micro-filtering (change in the type of administration, sector, type of research, scientific discipline).

    Imputation rate: A7=0.56%

  • 18.6Adjustment

    Given the annual nature of the statistics, no seasonal adjustment is performed.

• 19Comment
  • 19.1Comment

    .