Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
General Sub-Directorate of Statistics of Economic Sectors
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Avenida Manoteras, 50-52. 4th floor
28050 Madrid. SPAIN
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
17 November 2025
2.2. Metadata last posted
17 November 2025
2.3. Metadata last update
17 November 2025
3.1. Data description
Global Value Chain Statistics (GVC) is an operation compiled under Implementing Regulation (EU) 2022/918 whose overall objective is to measure the phenomenon of global value chains in which Spanish companies are involved for the 2021-2023 reference period, where this concept encompasses the entire range of cross-border activities necessary to bring a product or service from its conception to end consumers, through the various stages of production and delivery.
The specific objectives established are:
To ascertain the distribution of employment in each company according to the business functions it performs.
To ascertain how many companies are involved in global value chains, i.e. are buying and/or selling goods and/or services abroad.
To ascertain how many companies have been involved in international outsourcing operations during the reference period, and how many jobs are affected.
To ascertain the extent to which certain international events have impacted global value chains.
The information needed to compile these statistics is collected in the Structural Business Statistics questionnaire, through a series of additional questions specific to certain legal units in the sample that meet the criteria for the target population of global value chains. The aim of this approach is to obtain the necessary information while reducing the statistical burden on respondents by generating a new statistical operation, without compromising the quality of the aggregate estimates.
3.2. Classification system
NACE Rev. 2 coding is used to code the activity of the enterprises.
The rest of the classifications are described in Regulation (EU) 2022/918 or in the GVC Compliers' Manual.
3.3. Coverage - sector
The economic sectors referred to in these statistics are those listed in sections B to N of the NACE Rev. 2 classification. Another condition is that enterprises must have 50 or more employees or self-employed persons.
3.4. Statistical concepts and definitions
Concepts
Global value chains encompass the entire range of cross-border activities necessary to bring a product or service from conception, through the various stages of production and delivery, to end consumers.
A business group is an association of companies linked by legal and/or financial ties. A group of companies may have more than one decision-making centre, particularly with regard to production, sales and profit policies. It may centralise certain aspects of financial and tax management. It constitutes an economic entity that has the capacity to make decisions, particularly with regard to the units that comprise it. (Source: Council Regulation (EEC) No 696/93).
A good or material refers to any type of movable property.
A service results from a productive activity that changes the conditions of consumer units (transformation services) or facilitates the exchange of products or financial assets (margin services). Services are often difficult to separate from the goods with which they may be associated to varying degrees. Typical examples of services are ICT services, administrative services, marketing, sales, tourism services, catering services or R&D services.
In the context of this operation, sourcing refers to the total or partial transfer of business functions from one company to another.
It is important to note that these functions were previously performed within the company before being outsourced during the reference period. On the other hand, if a company has been acquiring a business function (e.g. through the purchase of services) since its creation, then this is not considered to be sourcing.
Variables
Employees and self-employed persons corresponds to the average number of employees and self-employed workers in the last year of the reference period used. The number of self-employed workers is the average number of persons who, at any time during the reference period, were sole proprietors or co-proprietors of the statistical unit in which they work. It also includes family workers and home-based workers whose remuneration depends on the value of the statistical unit's production.
An enterprise is defined as “the smallest combination of legal units constituting an organisational unit for the production of goods and services and enjoying a certain degree of autonomy in decision-making, particularly in the use of the resources at its disposal. An enterprise may carry out one or more activities in one or more locations. An enterprise may correspond to a single legal unit” (definition from European Union Regulation 696/93).
The number of active enterprises is the number of all statistical units that, at some point during the reference period, were “enterprises” as defined in the Regulation and were also active during that same reference period.
A statistical unit is considered to have been active during the reference period if, during that period, it has had a positive net turnover, produced goods or services, had employees or made investments.
Jobs created in the company due to international outsourcing: total number (gross) of domestic jobs created in the company as a result of international outsourcing.
A common reason for job creation is the increased availability of resources resulting from international outsourcing. These resources may, in some cases, enable the creation of new jobs in another business function (for example, outsourcing part of the IT staff generated savings that allowed the company to hire more sales staff).
Jobs lost or relocated abroad due to international outsourcing: total (gross) number of domestic jobs that have been lost or relocated abroad as a result of international outsourcing.
Domestic job losses that have occurred for reasons other than international outsourcing are not included in this concept.
It should be noted that even if jobs have been relocated abroad, it is possible that the people who performed those functions are still employed by the company performing other tasks (which may even be new tasks related to jobs created by international outsourcing). In these cases, the jobs count as jobs relocated abroad.
Therefore, in general terms, the concept of jobs relocated abroad is not related to the change observed in the number of employees and self-employed persons in the company; a company may, for example, report jobs relocated abroad due to international outsourcing and still record an increase in its number of employees and self-employed persons.
Business functions are defined as groupings of common tasks that companies must perform on a regular basis, either internally or externally, to bring goods or services to market.
Business functions are often distinguished from business processes, which refer to work organised on a temporary basis to achieve a specific objective. Business functions are therefore relatively stable within an organisation, while business processes only last until that objective has been achieved.
This statistic considers the following business functions:
Core business function (Production of goods or provision of services for the market)
Support business functions
Production of goods and materials
ransport, logistics and storage
Marketing, sales, and after-sales service
Information technology
Management and administration
Engineering and related technical services
Research and development
Other services
Employment is defined as a set of tasks and responsibilities performed, or expected to be performed, by a person, either for an employer or on their own account (ISCO-08). Jobs are carried out in the statistical observation unit, i.e. in the company.
Highly skilled persons are those who hold a university degree, i.e. with tertiary education. Consequently, highly skilled jobs mainly comprise expert occupations, such as professionals, associate technicians, managers, senior officials, researchers, IT experts or other technical occupations.
In general, highly skilled jobs require a high level of education (ISCED 5 or above).
Type of goods: information on the type of goods that can be traded within global value chains.
The following typology is proposed:
Raw materials used in enterprise's production process
Components of enterprise's product
Machinery and other technical equipment used by the enterprise
Raw materials used by customers abroad in their production process
Components used by customers abroad as part of their product
Machinery and other technical equipment used by customers abroad
Product designed by the enterprise
Product designed by another enterprise
Other goods
The classification of goods by type takes into account their end use. All goods, except those included in the “other goods” category, are traded for intermediate use. This also applies to the category of final goods, which would be more accurately named finished goods. These goods are considered “finished” in the sense that their production has been completed, but value can still be added to them through various services (e.g. marketing, logistics and distribution).
Type of services: information on the type of services that are traded within global value chains.
The following typology is proposed:
Distribution and logistics
Marketing, sales, and after-sales service
Information and communication technology services
Administrative and management
Engineering and related technical services
Research and development
Other services
In order to increase the likelihood of identifying trade in global value chains and improve data quality, a threshold of €100,000 per year is set for reporting on the type of services traded. This does not refer to a specific type of service but to the type of service defined in the survey (e.g. administration and management services versus ICT services).
3.5. Statistical unit
The basic statistical unit for this operation is the enterprise, understood as "the smallest combination of legal units that constitutes an organisational unit for the production of goods and services and enjoys a certain degree of decision-making autonomy, mainly in the use of the resources at its disposal. The enterprise may carry out one or more activities in one or more locations. An enterprise may correspond to a single legal unit" (definition from European Union Regulation 696/93).
The increasing complexity of the internal operations of business groups today has led the European Statistical System (ESS) to seek a way to reflect the activity of these groups in official business statistics. Indeed, legal units belonging to business groups sometimes sell their products or provide their services exclusively or mainly within the group, without being market-oriented or having decision-making autonomy over the entire production process.
For all these reasons, and in accordance with the European Statistical System (ESS), an “enterprise” can be:
Either an independent Legal Unit, which is not part of a business group, and therefore is assumed to have decision-making autonomy.
Or a business group formed for one or more Legal Units.
Or a subset of one or more Legal Units of a business group.
The basic 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 vertically integrated production process or provide services as an auxiliary), these servile legal units must be combined with the others they support to form the true statistical unit ‘enterprise’.
It should be noted that most enterprises are independent legal units. For this majority, the identity Enterprise = Legal Unit applies. However, legal units that are part of enterprise groups (3% of the total) may be composed of two or more legal units.
3.6. Statistical population
The GVC statistics are aimed at all companies, corporations and individuals that are market producers, with 50 or more employees and self-employed persons in the the reference period and whose main activity is between NACE Rev. 2 sections B-N. Also, the only enterprises that will report data for variables 2 to 5 will be those that have traded goods or services with at least €100,000.
3.7. Reference area
All statistical units located within the national territory (Spain) are subject to investigation.
3.8. Coverage - Time
This is a structural statistical operation carried out every three years.
3.9. Base period
This statistic does not use index numbers, therefore it is not applicable.
Business functions: number of employees.
GVC arrangements: number of enterprises.
International outsourcing: number of enterprisesand, number of jobs lost or created as a result of outsourcing, as applicable.
Motivations and barriers for international outsourcing: number of enterprises.
Effects on GVCs: number of enterprises.
Data referring to the period: Triennial 2021–2023, excluding variables 1 to 5 which refer only to 2023.
6.1. Institutional Mandate - legal acts and other agreements
The entry into force of the new Regulation (EU) 2019/2152 of the European Parliament and of the Council on European Business Statistics (EBS) and its Implementing Regulation (EU) 2020/1197 of the Commission of 30 July 2020 gave rise to a subsequent specific implementing act, Commission Implementing Regulation (EU) 2022/918 of 13 June 2022, which determined that information on the participation of enterprises in global value chains should be obtained and specified the aggregate information required.
6.2. Institutional Mandate - data sharing
Various administrative records and available statistics are consulted:
Value Added Tax (VAT) and International Trade in Goods Statistics (ITGS), both provided by the Spanish Tax Agency, AEAT
International Trade in Services Survey (ITSS), compiled by the National Statistical Institute of Spain.
7.1. Confidentiality - policy
Law 12/1989 on Public Statistics establishes that the National Statistical Institute of Spain (INE) cannot disseminate or make available in any way individual or aggregate data that could lead to the identification of previously unknown data for a person or entity.
The INE adopts the necessary logical, physical and administrative measures to ensure the effective protection of confidential data, from data collection to publication.
Also, the confidenciality of the data is ensured by Regulation (EC) 223/2009 on European statistics and Regulation (EU) 2019/2152.
7.2. Confidentiality - data treatment
Survey questionnaires include a legal clause informing respondents of the protection afforded to the data collected.
During the information processing stages, data that allow direct identification are only kept for as long as is strictly necessary to guarantee the quality of the processes.
When publishing the results tables, the information is analysed in detail to prevent confidential data from being deduced from the statistical units. Cells that could lead to the identification of individual data are marked as confidential and do not show the information they contain (primary and secondary confidentiality).
The same treatment is applied to customised requests in order to preserve statistical confidentiality.
8.1. Release calendar
In Spain, the calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.
In line with the Community legal framework and the European Statistics Code of Practice, INE disseminates national GVC statistics on its website (www.ine.es/en) respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably.
Triennal
10.1. Dissemination format - News release
News release for GVC 2021-2023 will be published on INE's website on 27 November: GVC National Publication
10.2. Dissemination format - Publications
The results of the statistics are published on the INE website (INEBase). Some results are included in publications such as the Anuario Estadistico [Statistical Yearbook], Cifras INE [INE Figures], etc.
10.3. Dissemination format - online database
Information on Global Value Chain Statistics can be found at the following link: GVC National Database
10.4. Dissemination format - microdata access
GVC microdata are not disseminated
10.5. Dissemination format - other
Users may request specific customised information analyses, which are carried out while preserving data confidentiality at all times, through the User Support Area at the following link: User Request
Based on Regulations 2019/2152 and 2020/1197 of the European Parliament and of the Council, the European Commission (Eurostat) assesses the quality of the data transmitted and produces reports on the quality of European statistics. Eurostat produces an internal quality report containing quantitative and qualitative information.
Sections 11 to 19 of this document constitute the user-oriented quality report for this operation.
11.1. Quality assurance
Based on Regulations 2019/2152 and 2020/1197 of the European Parliament and of the Council, the European Commission assesses the quality of the data transmitted and produces reports on the quality of European statistics.
The National Statistical Institute of Spain ensures data quality in line with ESS Quality Assurance Framework (QAF).
Several validation checks are involved in this statistical process from the beginning:
All the data sources used in the statistics are subject to integrity checks.
Once the integration of data from all sources has been completed, various checks are performed again, verifying whether the information is accurate.
11.2. Quality management - assessment
The statistics are guided by the European Statistics Code of Practice and, in line with this, focus primarily on:
Evaluating and verifying the quality of primary data from the administrative records of the Tax Agency and the INE itself.
Guaranteeing statistical confidentiality.
Clearly describing the methodology and reviewing it annually.
Not adding statistical burden to reporting units.
Using definitions and standards that allow consistency with data from other European statistical institutes.
Planned improvements on analysing the results in greater depth, focusing on the meaning and integrity of the variables in relation to each other and their totals.
12.1. Relevance - User Needs
The primary users of this survey are the European Commission and the Spanish economic authorities with a view to the implementation and review of the General Agreement on Trade in Services (AGCS) and the Agreement on Trade-Related Aspects of Intellectual Property Rights (ADPIC):
Eurostat
Chambers of Commerce
Central and Regional Governments
Scholars
Researchers
Individuals.
12.2. Relevance - User Satisfaction
The INE has carried out general user satisfaction surveys in 2007, 2010, 2013, 2016, 2019 and 2025 (not carried out yet). 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. (User Satisfaction Surveys)
In the latest general user satisfaction survey of 2019, the assessment of the product quality dimensions (relevance, precision, timeliness, coherence and comparability) for the groups of statistics referring to the Industry and Services (in which this statiscal operation in framed) can be consulted.
On the other hand, those responsible for this statistical operation are in permanent contact with the main users, in order to meet any specific need for information.
Likewise, given the possibility that there are requests not attended due to their complexity, these are evaluated as well as any suggestions made by the main users. Most of these demands are satisfied.
12.3. Completeness
This statistical operation covers all the variables required by Eurostat regulations and guidelines.
13.1. Accuracy - overall
The statistics use data from INE surveys (SBS and ITSS), as well as statistics and administrative records from the AEAT (VAT and ITGS). These data are highly reliable as they are refined and definitive in the corresponding sources.
On the other hand, the data is not exactly tailored to the statistics, so certain information needs to be imputed, which lowers the level of accuracy of the data.
13.2. Sampling error
Not applicable, as the Central Business Register compiled by the INE is used as the census.
13.3. Non-sampling error
Throughout the statistical process, non-sampling errors are monitored. The overcoverage rate and non-response rate per unit are calculated:
Overcoverage = 2,4% Non-response rate = 3,6%
14.1. Timeliness
Data and metadata were transmitted to Eurostat within the legal deadline of T+21 months. However, the INE had to do a second transmission of the data due to some inconsistencies detected in tables T2, T3, T6 and T7. This transmission was on 4 November.
14.2. Punctuality
The survey data was collected according to the established deadlines. This data was cleaned, validated, and processed approximately one year prior to transmission.
However, we were dependent on the aforementioned entities to send us the data. Therefore, managing the collection of some results was a bottleneck.
15.1. Comparability - geographical
The consistency provided by the data sent to Eurostat by member countries allows for accurate geographical comparability at international level.
15.2. Comparability - over time
As this is a newly created statistic, there is no comparability over time with other series, since it has only been published once.
15.3. Coherence - cross domain
The statistics use the DIRCE (Central Business Register) to construct the target population. This register is a national reference, so cross-referencing with data from INE statistics and external sources will be consistent.
15.4. Coherence - internal
The results are consistent with each other, as an exhaustive imputation and cleansing process has been carried out in accordance with the nature of the statistical data as a whole.
Some internal validation routines were carried out at the final stage. All the validation rule were checked with Python programming.
Although this statistic makes extensive use of existing sources, information from surveys is also necessary. Therefore, the budgetary appropriations required for its financing in 2025 are €212.500, as provided for in the INE budget.
17.1. Data revision - policy
The data are final once published. If errors are detected and the data need to be modified, an explanatory note will be added alongside the information, thus warning that the results have been altered. Where possible, users are directly informed of these errors.
17.2. Data revision - practice
The data is published when it is final. It may only be modified if an error is detected in the data sources.
18.1. Source data
The INE obtains most of the information needed to produce these statistics from the module attached to the Structural Business Statistics surveys. However, as mentioned above, this information is based on the DIRCE for the construction of the target population, the Spanish Tax Administration Agency (AEAT) for information relating to foreign trade operations, and the International Trade in Services Survey (ECIS) produced by the INE itself.
The EEE is produced annually. However, in the case of these statistics, many of the questions referred to the three-year period 2021-2023.
DIRCE is updated once a year using administrative sources, mainly tax and social security data, and information from INE statistical operations. It is an integrated information system at various levels, ranging from lowest to highest: establishment, Legal Unit, Enterprise and Business Group. For each of these levels, DIRCE contains information on the main economic activity, the number of employees and turnover, as well as identification and location data necessary for the correct collection of information. The DIRCE used as a population framework refers to the year prior to the reference period, although two main quantitative variables, number of employees and turnover, are updated to the year of study. Since the 2018 reference year, the DIRCE has included the new EE level, which is equal to the ULE in the case of independent ULEs, or to a set of ULEs in a business group, or to the entire business group, as determined by profiling techniques.
As for the other sources, this was annual information for the 2023 reference year, not for the entire three-year period.
18.2. Frequency of data collection
For each reference year t, data collection is organised through the direct collection of Structural Business Statistics questionnaires with the attached global value chains module, aimed at selected legal units (field collection, under the IRIA system). This takes place from April to September of year t+1.
18.3. Data collection
Data collection using questionnaires and modules through the IRIA system is carried out by the INE's Collection Units. Almost all questionnaires are collected online.
The Collection Units are responsible for managing the collection, recording and cleaning of the modules, as well as answering telephone enquiries from respondents. Telephone contact is also made with companies in cases where no response is received within the established deadline or where the response is considered insufficient or inconsistent.
In order to monitor fieldwork, the different situations that may arise during the collection of information are taken into account. A company will be considered to have been effectively surveyed if its main activity is included in the population under study, the completed module has been obtained, and the data verify the established completeness and consistency controls.
In addition, a series of incidents may arise during the information collection process that prevent the module from being obtained. Rigorous handling of these incidents is of great importance, as their analysis allows the survey framework to be updated and has an impact on the processing of the information.
The incidents taken into account are:
Permanent closure or cessation of activity: the Legal Unit has permanently ceased its activity, a situation that is justified by an official document certifying this.
Temporarily closed or inactive: the Legal Unit remains closed during the information collection period and no informant can be located, or it has no activity during the year.
Incorrectly included: the Legal Unit's main activity is outside the scope of the survey.
Outside scope: other characteristics of the unit, other than its main activity, place it outside the scope of the survey.
Duplicated: the Legal Unit appears in the directory more than once.
Unlocatable, Negative and No response. These situations, which are in the minority at the end of the collection process, are dealt with specially by the Collection units in order to minimise non-response.
18.4. Data validation
During the data collection phase, an initial process of data cleansing and coding is carried out. Both the electronic questionnaires completed by respondents online and the application used by the INE's Data Collection Units to manage, record and cleanse the data collected have error detection systems programmed to validate the data as it is entered by the user. A distinction is made between serious errors (which must be corrected) and second-level anomalies (which, once confirmed, must be justified). In addition, during data collection and cleaning, measures are also taken to reduce non-response.
The records recorded by the Collection Units are used to create and feed, at least every two weeks, the complete recording files on which the subsequent phases of joint information processing are carried out. These files are processed at Central Services, where a new information coverage check is carried out to ensure the completeness of the recorded data, detect duplicates and coverage errors, and, at the same time, assess the quality of the variables collected.
As for DIRCE, ITSS, ITGS and VAT, these are highly reliable and definitive data, and therefore their validation is not the responsibility of the GVC.
18.5. Data compilation
As the collection of Legal Units progresses and complete recording files are created, the data undergoes additional micro-cleaning checks at INE, which are selectively focused on detecting and cleaning up errors and inconsistencies in the variables of each record, as well as cleaning up and imputing content errors. Depending on the characteristics of each type of error, automatic imputation procedures are used in certain cases. Likewise, systematic errors detected in previous studies and analyses of the recorded data are corrected.
There may be several reasons why a response needs to be imputed:
Total or partial lack of response: due to lack of information from respondents or the application of prior filters.
Units not surveyed intentionally
Directory updates: the sample is obtained from a population frame based on the year prior to the last year of the three-year reference period, as the sample for the last year is not available at the time the EEE sample is drawn.
Not all questions included in the ECVG module are addressed to all reporting units, and a series of prior filters are applied to adjust the volume of units that will receive the ECVG module to the work capacity that can be assumed by the INE's collection units, selecting the most important ones in terms of size by number of employees or turnover, as appropriate.
Imputation techniques are therefore applied, varying according to the section:
Variable 1: Employment by business function Information from the Structural Business Statistics and the Commercial Register on employment and activity CNAE-2009 is used.
Subsequently, the conversion table from CNAE-2009 to Business Functions provided by Eurostat is applied.
Variables 2-5: International transactions in global value chains The imputation data for goods is obtained through a KNN (K Nearest Neighbours) imputation model developed in Python, taking as donors the units that have responded to the module in a valid manner. The proximity variables chosen to determine the nearest neighbour were the autonomous community, the sector of activity, the number of employees, turnover, whether or not it is a group, and if so, what type of group it is, whether it is a head, the country of that head, and continuous variables from VAT.
The model proposes k=1 neighbours and a weighting method based on Minkowski distance. An overfitting system is desirable, as we want to specify the characteristics of the unit to be imputed as accurately as possible. This is why k=1 has been selected.
On the other hand, the imputation of services is obtained directly from the International Trade in Services Statistics produced by the National Institute of Statistics.
Variables 6-8: International outsourcing In general, the responses provided by the surveyed unit acting as the HEAD of the group apply to all units within the group. It is difficult to determine whether each unit actually outsources activities, as the public information available in the Consolidated Annual Accounts does not provide that level of detail.
Average outsourcing percentages are calculated and applied to the number of employees and self-employed workers in each Legal Unit (LeU).
It is assumed that small businesses do not outsource abroad.
Variable 9: Motivations and barriers to outsourcing business functions Within the group, priority is given to the response that assigns the greatest importance to each item, and this response is transferred to the allocated units whenever possible.
For all other units, a null response (Not applicable / Don't know) is assigned.
Variable 10: Impact of recent events on economic globalisation A combination of methods is applied: direct imputation when data from units within the same group are available, and KNN imputation when no information can be obtained.
The imputation carried out did not consist of a correction of the values already obtained with the survey attached to the EEA, but rather an extension of the survey to obtain data for the entire target population. The results by section are as follows:
The imputation rate (IMP) was calculated with these results:
Variable 1: IMP=36.59%
Variable 2-3: IMP=1.64%
Variable 4-5: IMP=100%
Variable 6-8: IMP=0.61%
Variable 9: IMP=0.61%
Variables 10: IMP=3.77%
It should be noted that many results were obtained through consistency between the unit and the response. In other words, if a unit had to be imputed but, due to its intrinsic characteristics, did not have to answer a specific question, it was directly imputed with ‘Not applicable’. These cases have not been included when calculating IMP.
In order to obtain a single record for each Statistical Enterprise, the responses of the Legal Units belonging to the same enterprise are aggregated following the delimitation established by the Profiling methodology.
The approach to combining responses depends on the type of variable:
For employment figures, the values are aggregated.
For the number of companies, the response with the highest declared intensity is selected.
No weighting factors are needed for this statistic, as all units in the target population are included, with data collected or imputed.
Finally, a complete data set is obtained, with all companies in the target population in the rows and all required variables in the columns, which serves as the basis for producing the final tables and series.
18.6. Adjustment
No adjustments were applied. Neither outlier correction nor seasonal adjustment.
No additional comments were identified at this stage. We will discuss the future improvements.
Global Value Chain Statistics (GVC) is an operation compiled under Implementing Regulation (EU) 2022/918 whose overall objective is to measure the phenomenon of global value chains in which Spanish companies are involved for the 2021-2023 reference period, where this concept encompasses the entire range of cross-border activities necessary to bring a product or service from its conception to end consumers, through the various stages of production and delivery.
The specific objectives established are:
To ascertain the distribution of employment in each company according to the business functions it performs.
To ascertain how many companies are involved in global value chains, i.e. are buying and/or selling goods and/or services abroad.
To ascertain how many companies have been involved in international outsourcing operations during the reference period, and how many jobs are affected.
To ascertain the extent to which certain international events have impacted global value chains.
The information needed to compile these statistics is collected in the Structural Business Statistics questionnaire, through a series of additional questions specific to certain legal units in the sample that meet the criteria for the target population of global value chains. The aim of this approach is to obtain the necessary information while reducing the statistical burden on respondents by generating a new statistical operation, without compromising the quality of the aggregate estimates.
17 November 2025
Concepts
Global value chains encompass the entire range of cross-border activities necessary to bring a product or service from conception, through the various stages of production and delivery, to end consumers.
A business group is an association of companies linked by legal and/or financial ties. A group of companies may have more than one decision-making centre, particularly with regard to production, sales and profit policies. It may centralise certain aspects of financial and tax management. It constitutes an economic entity that has the capacity to make decisions, particularly with regard to the units that comprise it. (Source: Council Regulation (EEC) No 696/93).
A good or material refers to any type of movable property.
A service results from a productive activity that changes the conditions of consumer units (transformation services) or facilitates the exchange of products or financial assets (margin services). Services are often difficult to separate from the goods with which they may be associated to varying degrees. Typical examples of services are ICT services, administrative services, marketing, sales, tourism services, catering services or R&D services.
In the context of this operation, sourcing refers to the total or partial transfer of business functions from one company to another.
It is important to note that these functions were previously performed within the company before being outsourced during the reference period. On the other hand, if a company has been acquiring a business function (e.g. through the purchase of services) since its creation, then this is not considered to be sourcing.
Variables
Employees and self-employed persons corresponds to the average number of employees and self-employed workers in the last year of the reference period used. The number of self-employed workers is the average number of persons who, at any time during the reference period, were sole proprietors or co-proprietors of the statistical unit in which they work. It also includes family workers and home-based workers whose remuneration depends on the value of the statistical unit's production.
An enterprise is defined as “the smallest combination of legal units constituting an organisational unit for the production of goods and services and enjoying a certain degree of autonomy in decision-making, particularly in the use of the resources at its disposal. An enterprise may carry out one or more activities in one or more locations. An enterprise may correspond to a single legal unit” (definition from European Union Regulation 696/93).
The number of active enterprises is the number of all statistical units that, at some point during the reference period, were “enterprises” as defined in the Regulation and were also active during that same reference period.
A statistical unit is considered to have been active during the reference period if, during that period, it has had a positive net turnover, produced goods or services, had employees or made investments.
Jobs created in the company due to international outsourcing: total number (gross) of domestic jobs created in the company as a result of international outsourcing.
A common reason for job creation is the increased availability of resources resulting from international outsourcing. These resources may, in some cases, enable the creation of new jobs in another business function (for example, outsourcing part of the IT staff generated savings that allowed the company to hire more sales staff).
Jobs lost or relocated abroad due to international outsourcing: total (gross) number of domestic jobs that have been lost or relocated abroad as a result of international outsourcing.
Domestic job losses that have occurred for reasons other than international outsourcing are not included in this concept.
It should be noted that even if jobs have been relocated abroad, it is possible that the people who performed those functions are still employed by the company performing other tasks (which may even be new tasks related to jobs created by international outsourcing). In these cases, the jobs count as jobs relocated abroad.
Therefore, in general terms, the concept of jobs relocated abroad is not related to the change observed in the number of employees and self-employed persons in the company; a company may, for example, report jobs relocated abroad due to international outsourcing and still record an increase in its number of employees and self-employed persons.
Business functions are defined as groupings of common tasks that companies must perform on a regular basis, either internally or externally, to bring goods or services to market.
Business functions are often distinguished from business processes, which refer to work organised on a temporary basis to achieve a specific objective. Business functions are therefore relatively stable within an organisation, while business processes only last until that objective has been achieved.
This statistic considers the following business functions:
Core business function (Production of goods or provision of services for the market)
Support business functions
Production of goods and materials
ransport, logistics and storage
Marketing, sales, and after-sales service
Information technology
Management and administration
Engineering and related technical services
Research and development
Other services
Employment is defined as a set of tasks and responsibilities performed, or expected to be performed, by a person, either for an employer or on their own account (ISCO-08). Jobs are carried out in the statistical observation unit, i.e. in the company.
Highly skilled persons are those who hold a university degree, i.e. with tertiary education. Consequently, highly skilled jobs mainly comprise expert occupations, such as professionals, associate technicians, managers, senior officials, researchers, IT experts or other technical occupations.
In general, highly skilled jobs require a high level of education (ISCED 5 or above).
Type of goods: information on the type of goods that can be traded within global value chains.
The following typology is proposed:
Raw materials used in enterprise's production process
Components of enterprise's product
Machinery and other technical equipment used by the enterprise
Raw materials used by customers abroad in their production process
Components used by customers abroad as part of their product
Machinery and other technical equipment used by customers abroad
Product designed by the enterprise
Product designed by another enterprise
Other goods
The classification of goods by type takes into account their end use. All goods, except those included in the “other goods” category, are traded for intermediate use. This also applies to the category of final goods, which would be more accurately named finished goods. These goods are considered “finished” in the sense that their production has been completed, but value can still be added to them through various services (e.g. marketing, logistics and distribution).
Type of services: information on the type of services that are traded within global value chains.
The following typology is proposed:
Distribution and logistics
Marketing, sales, and after-sales service
Information and communication technology services
Administrative and management
Engineering and related technical services
Research and development
Other services
In order to increase the likelihood of identifying trade in global value chains and improve data quality, a threshold of €100,000 per year is set for reporting on the type of services traded. This does not refer to a specific type of service but to the type of service defined in the survey (e.g. administration and management services versus ICT services).
The basic statistical unit for this operation is the enterprise, understood as "the smallest combination of legal units that constitutes an organisational unit for the production of goods and services and enjoys a certain degree of decision-making autonomy, mainly in the use of the resources at its disposal. The enterprise may carry out one or more activities in one or more locations. An enterprise may correspond to a single legal unit" (definition from European Union Regulation 696/93).
The increasing complexity of the internal operations of business groups today has led the European Statistical System (ESS) to seek a way to reflect the activity of these groups in official business statistics. Indeed, legal units belonging to business groups sometimes sell their products or provide their services exclusively or mainly within the group, without being market-oriented or having decision-making autonomy over the entire production process.
For all these reasons, and in accordance with the European Statistical System (ESS), an “enterprise” can be:
Either an independent Legal Unit, which is not part of a business group, and therefore is assumed to have decision-making autonomy.
Or a business group formed for one or more Legal Units.
Or a subset of one or more Legal Units of a business group.
The basic 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 vertically integrated production process or provide services as an auxiliary), these servile legal units must be combined with the others they support to form the true statistical unit ‘enterprise’.
It should be noted that most enterprises are independent legal units. For this majority, the identity Enterprise = Legal Unit applies. However, legal units that are part of enterprise groups (3% of the total) may be composed of two or more legal units.
The GVC statistics are aimed at all companies, corporations and individuals that are market producers, with 50 or more employees and self-employed persons in the the reference period and whose main activity is between NACE Rev. 2 sections B-N. Also, the only enterprises that will report data for variables 2 to 5 will be those that have traded goods or services with at least €100,000.
All statistical units located within the national territory (Spain) are subject to investigation.
Data referring to the period: Triennial 2021–2023, excluding variables 1 to 5 which refer only to 2023.
The statistics use data from INE surveys (SBS and ITSS), as well as statistics and administrative records from the AEAT (VAT and ITGS). These data are highly reliable as they are refined and definitive in the corresponding sources.
On the other hand, the data is not exactly tailored to the statistics, so certain information needs to be imputed, which lowers the level of accuracy of the data.
Business functions: number of employees.
GVC arrangements: number of enterprises.
International outsourcing: number of enterprisesand, number of jobs lost or created as a result of outsourcing, as applicable.
Motivations and barriers for international outsourcing: number of enterprises.
Effects on GVCs: number of enterprises.
As the collection of Legal Units progresses and complete recording files are created, the data undergoes additional micro-cleaning checks at INE, which are selectively focused on detecting and cleaning up errors and inconsistencies in the variables of each record, as well as cleaning up and imputing content errors. Depending on the characteristics of each type of error, automatic imputation procedures are used in certain cases. Likewise, systematic errors detected in previous studies and analyses of the recorded data are corrected.
There may be several reasons why a response needs to be imputed:
Total or partial lack of response: due to lack of information from respondents or the application of prior filters.
Units not surveyed intentionally
Directory updates: the sample is obtained from a population frame based on the year prior to the last year of the three-year reference period, as the sample for the last year is not available at the time the EEE sample is drawn.
Not all questions included in the ECVG module are addressed to all reporting units, and a series of prior filters are applied to adjust the volume of units that will receive the ECVG module to the work capacity that can be assumed by the INE's collection units, selecting the most important ones in terms of size by number of employees or turnover, as appropriate.
Imputation techniques are therefore applied, varying according to the section:
Variable 1: Employment by business function Information from the Structural Business Statistics and the Commercial Register on employment and activity CNAE-2009 is used.
Subsequently, the conversion table from CNAE-2009 to Business Functions provided by Eurostat is applied.
Variables 2-5: International transactions in global value chains The imputation data for goods is obtained through a KNN (K Nearest Neighbours) imputation model developed in Python, taking as donors the units that have responded to the module in a valid manner. The proximity variables chosen to determine the nearest neighbour were the autonomous community, the sector of activity, the number of employees, turnover, whether or not it is a group, and if so, what type of group it is, whether it is a head, the country of that head, and continuous variables from VAT.
The model proposes k=1 neighbours and a weighting method based on Minkowski distance. An overfitting system is desirable, as we want to specify the characteristics of the unit to be imputed as accurately as possible. This is why k=1 has been selected.
On the other hand, the imputation of services is obtained directly from the International Trade in Services Statistics produced by the National Institute of Statistics.
Variables 6-8: International outsourcing In general, the responses provided by the surveyed unit acting as the HEAD of the group apply to all units within the group. It is difficult to determine whether each unit actually outsources activities, as the public information available in the Consolidated Annual Accounts does not provide that level of detail.
Average outsourcing percentages are calculated and applied to the number of employees and self-employed workers in each Legal Unit (LeU).
It is assumed that small businesses do not outsource abroad.
Variable 9: Motivations and barriers to outsourcing business functions Within the group, priority is given to the response that assigns the greatest importance to each item, and this response is transferred to the allocated units whenever possible.
For all other units, a null response (Not applicable / Don't know) is assigned.
Variable 10: Impact of recent events on economic globalisation A combination of methods is applied: direct imputation when data from units within the same group are available, and KNN imputation when no information can be obtained.
The imputation carried out did not consist of a correction of the values already obtained with the survey attached to the EEA, but rather an extension of the survey to obtain data for the entire target population. The results by section are as follows:
The imputation rate (IMP) was calculated with these results:
Variable 1: IMP=36.59%
Variable 2-3: IMP=1.64%
Variable 4-5: IMP=100%
Variable 6-8: IMP=0.61%
Variable 9: IMP=0.61%
Variables 10: IMP=3.77%
It should be noted that many results were obtained through consistency between the unit and the response. In other words, if a unit had to be imputed but, due to its intrinsic characteristics, did not have to answer a specific question, it was directly imputed with ‘Not applicable’. These cases have not been included when calculating IMP.
In order to obtain a single record for each Statistical Enterprise, the responses of the Legal Units belonging to the same enterprise are aggregated following the delimitation established by the Profiling methodology.
The approach to combining responses depends on the type of variable:
For employment figures, the values are aggregated.
For the number of companies, the response with the highest declared intensity is selected.
No weighting factors are needed for this statistic, as all units in the target population are included, with data collected or imputed.
Finally, a complete data set is obtained, with all companies in the target population in the rows and all required variables in the columns, which serves as the basis for producing the final tables and series.
The INE obtains most of the information needed to produce these statistics from the module attached to the Structural Business Statistics surveys. However, as mentioned above, this information is based on the DIRCE for the construction of the target population, the Spanish Tax Administration Agency (AEAT) for information relating to foreign trade operations, and the International Trade in Services Survey (ECIS) produced by the INE itself.
The EEE is produced annually. However, in the case of these statistics, many of the questions referred to the three-year period 2021-2023.
DIRCE is updated once a year using administrative sources, mainly tax and social security data, and information from INE statistical operations. It is an integrated information system at various levels, ranging from lowest to highest: establishment, Legal Unit, Enterprise and Business Group. For each of these levels, DIRCE contains information on the main economic activity, the number of employees and turnover, as well as identification and location data necessary for the correct collection of information. The DIRCE used as a population framework refers to the year prior to the reference period, although two main quantitative variables, number of employees and turnover, are updated to the year of study. Since the 2018 reference year, the DIRCE has included the new EE level, which is equal to the ULE in the case of independent ULEs, or to a set of ULEs in a business group, or to the entire business group, as determined by profiling techniques.
As for the other sources, this was annual information for the 2023 reference year, not for the entire three-year period.
Triennal
Data and metadata were transmitted to Eurostat within the legal deadline of T+21 months. However, the INE had to do a second transmission of the data due to some inconsistencies detected in tables T2, T3, T6 and T7. This transmission was on 4 November.
The consistency provided by the data sent to Eurostat by member countries allows for accurate geographical comparability at international level.
As this is a newly created statistic, there is no comparability over time with other series, since it has only been published once.
