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.
Statistics on international supply of services (ISS) by modes of supply (MoS) show how and where services are supplied internationally, namely by answering the question of 'how' services are exchanged across countries and 'where' services are supplied to foreign customers. Detailed information on international supply of services statistics by services category, mode of supply and partner country help policymakers carry out the ongoing and future trade negotiating agenda with facts and strong, evidence-based arguments and they allow to monitor the impact of services trade agreements.
The General Agreement on Trade in Services (GATS), the first multilateral agreement to cover trade in services, defines trade in services as the supply of a service through any of four modes of supply, outlined in the bullet points below.
Mode 1 - cross-border supply: from the territory of one country into the territory of another country; Mode 2 - consumption abroad: in the territory of one country to the service consumer of another country; Mode 3 - commercial presence: by a service supplier of one country, through a commercial presence in the territory of another country. The FATS framework is designed to provide information on the activities of enterprises located in foreign markets; Mode 4 - presence of natural persons: by a service supplier of one country, through the presence of natural persons of that country in the territory of any other country.
Total international supply of services (total of modes 1, 2, 3 and 4)
Mode 1 (‘cross border transactions’),
Mode 2 (‘consumption abroad’),
Mode 3 (‘commercial presence’), and
Mode 4 (‘presence of natural persons’).
3.5. Statistical unit
Not applicable.
3.6. Statistical population
Current Scope: Total international supply of services by modes 1, 2, 3, and 4.
Future Scope: Total international supply of services categorized into services by all four modes of supply. For each mode, the totals are categorized into subcategories of services.
3.7. Reference area
GEO level 5 (Commission Implementing Regulation (EU) 2020/1470 of 12 October 2020, Annex II)
3.8. Coverage - Time
2023-2024
3.9. Base period
Not applicable.
Data are reported in national currency (thousands).
Eurostat disseminates data in million euro.
Calendar year.
6.1. Institutional Mandate - legal acts and other agreements
Regulation (EU) 2019/2152 on European business statistics sets the data requirements in the field of international supply of services by modes for the EU Member States and EFTA countries. The exact technical specifications are listed in Commission Implementing Regulation (EU) 2020/1197. The requirements concerning the MoS domain are defined in table 38 "Statistics on international activities – International Supply of Services by Mode of Supply – annual data" of the Commission Implementing Regulation (EU) 2020/1197. The variable must be reported annually with first reference year 2023.
6.2. Institutional Mandate - data sharing
Statistics on the international supply of services (ISS) by mode of supply (MoS) primarily rely on data available within Statistics Netherlands (CBS) and publicly accessible data from Eurostat.
The Dutch International Trade in Services Statistics (ITSS) serve as the primary source for MoS compilation. Parameters from the generic Eurostat-WTO model have been refined to suit the Dutch context through expert judgment and supplementary research conducted among a sample of major traders.
7.1. Confidentiality - policy
Section 37 of the Statistics Netherlands Act addresses the use and confidentiality of data obtained under its legal mandate. The confidentiality policy of Statistics Netherlands ensures that statistical information regarding the international trade of services is published in a manner that prevents the identification of individual persons, households, enterprises, or institutions.
The confidentiality framework distinguishes between primary and secondary confidentiality:
Primary Confidentiality: Ensures that data from individual units (enterprises, institutions, households or persons) can never be directly inferred from the statistical information provided
The implementation of this safeguard relies on two simple basic rules:
1 - Data will not be published if it originates from fewer than 'N' individual companies; and
2 - Data will not be published if one individual company is responsible for more than 'X' percent of the data
Secondary Confidentiality (Support Confidentiality): Safeguards primary confidential cells by ensuring that additional related cells are also protected from disclosure.
Primary confidential data can sometimes still be calculated based on other, non-confidential cells or totals if no additional measures are taken. To prevent this, some cells - which do not have a confidential status - are also excluded from publication.
7.2. Confidentiality - data treatment
A table cell is flagged as confidential if there are fewer than 3 contributors to the cell total (minimum frequency rule) or if one individual contributor is responsible for more than 81 percent of the total trade value in this specific cell (concentration rule). This prevents individual contributors from being identified. Secondary confidentiality checks, as well as internal consistency checks between subsets of the data and cross-domain checks (i.e., consistency with regular ITSS), are also applied.
8.1. Release calendar
At the moment, MoS data are only disseminated by Eurostat.
In the future, MoS data may also be published by Statistics Netherlands.
8.2. Release calendar access
Not applicable.
8.3. Release policy - user access
At the moment, MoS data are only disseminated by Eurostat.
In the future, MoS data may also be published by Statistics Netherlands.
Annual.
10.1. Dissemination format - News release
No news/press releases planned yet.
Statistics Netherlands might use MoS data for news articles on the international supply of services.
10.2. Dissemination format - Publications
No publications planned yet.
Statistics Netherlands might use MoS data for publications on the international supply of services.
10.3. Dissemination format - online database
At the moment, MoS data are only disseminated by Eurostat.
In the future, MoS data may also be published by Statistics Netherlands, using the StatLine database.
In general, according to the information available from the quality reports, the data providers have applied the recommendations available in the Regulation (EU) 2019/2152.
12.1. Relevance - User Needs
Statistics Netherlands has regular contacts with internal and external business partners in order to assure that users' needs are met and to assure relevancy and usefulness of statistics and applied methodologies.
Statistics Netherlands also participates in a variety of statistical meetings and seminars organized by international organizations (for instance Eurostat, OECD and the Nordic meeting on Trade in Goods and Services). In these meetings, new and emerging data requirements are identified and discussed. Statistics Netherlands is receptive to remarks and requests from the users of its statistics.
12.2. Relevance - User Satisfaction
Occasionally, Statistics Netherlands discusses user needs and user satisfaction with respect to international trade in services statistics with internal and external users. Important users include the National Accounts department and various research departments within Statistics Netherlands, as well as the Dutch Central Bank and various Ministries. In addition to this there is a Customer Council within Statistics Netherlands, which acts as a consultation platform and advisory board, offering both solicited and unsolicited advice on products and services to Statistics Netherlands.
12.3. Completeness
All content requirements originating from relevant legislation, regulations and guidelines are met.
12.3.1. Data completeness - rate
100% of required data cells are provided
13.1. Accuracy - overall
The accuracy of MoS data depends not only on the precision of International Trade in Services Statistics (ITSS) but also on the quality of the secondary data used. Examples include, but are not limited to, TEC and SBS data from Eurostat, which are utilized to calculate distribution services. Other secondary data that is used includes: International Trade in Goods Statistics (ITGS), Foreign Affiliates Statistics (FATS), Statistics of Finances of Enterprises, Production Statistics. Additionally, MoS accuracy is influenced by the numerous assumptions that must be made. Some of these assumptions are inherent to the standard Eurostat-WTO model, while others are necessary for estimating distribution services, the goods component in certain services, and other elements.
The primary source for compiling data on modes 1, 2, and 4 is the International Trade in Services Statistics (ITSS). Within ITSS, accuracy is pursued by minimizing non-sampling errors as much as possible. However, revisions in Dutch international trade in services figures can be substantial, as initial estimates may undergo significant adjustments when more accurate and comprehensive data become available.
This is especially true for Special Purpose Entities (SPEs). SPEs are companies often established for specific financial or legal purposes, such as tax optimization or facilitating international investments. These entities typically have minimal physical presence and few employees in the Netherlands, yet their financial activities can cause considerable fluctuations in reported economic data. As a result, given the significant number of SPEs in the Netherlands, initial international trade in services figures are often subject to substantial revisions when improved data from these SPEs becomes available.
Mode 3 is primarily based on FATS data. The import side is derived from the IFATS statistics. To determine the domestic turnover, the Statistics of Finances of Enterprises (SFO) is used. The share of services in turnover is then calculated using the ITGS and ITSS microdata. If necessary, the Production Statistics (PS) is used to determine the output value.
On the export side, the OFATS data is utilized. Further distributions for the export side are made based on the import side data.
All statistics are carefully compiled to ensure reliability. However, in linking these data, some necessary assumptions have been made, solely for the purpose of ensuring the required accuracy.
13.2. Sampling error
To reduce sampling errors, several improvements have been implemented in the compilation of International Trade in Services Statistics (ITSS) in recent years. An important example includes the new sampling design based on an enhanced stratification strategy that was implemented in 2020.
Specifically for MoS compilation, the standard allocation shares from the Eurostat-WTO model have been finetuned to the Dutch context based on expert judgement and supplementary research conducted among a sample of major traders. Traders were selected in such a way as to get adequate coverage for all type of services and trade flows (import and export) to minimise sampling errors. Only those services for which more modes of supply might apply or which were subject to debate in the Dutch context were included. For other services, the standard allocation shares from the Eurostat-WTO model are applied
13.2.1. Sampling error - indicators
Not applicable.
13.3. Non-sampling error
The accuracy of MoS data is primarily affected by issues in:
(1) The collection and compilation of trade in services statistics, such as thresholds, non-response, delayed declarations, estimated or imputed trade values, and statistical weighting;
(2) Various modeling assumptions that have to be made. Examples include the assumptions implicit in the Eurostat-WTO model or the assumptions that had to be made to estimate distribution services in mode 1 or the share of goods in certain services categories
(3) The compilation of Mode 3 relies on a set of key assumptions that underpin the data integration and estimation process. These assumptions are crucial for ensuring the consistency and reliability of the final estimates, although they also introduce potential sources of bias or inaccuracies if not carefully evaluated. A central assumption is that the data sources are complete and representative of the population of businesses involved in international trade. Another key assumption is that output can be estimated based on turnover, using a stable output-to-turnover ratio derived from the Product Statistics (PS). It is assumed that this ratio is consistent within each SBI code, which is used to group businesses with similar economic activities. Furthermore, it is assumed that the proportion of goods and services in domestic turnover is the same as in international trade, based on the observed distribution in international trade. This assumption is considered acceptable by the MoS-compiler’s guide. The method also assumes that domestic turnover can be estimated as total turnover minus export value, using data from ITGS and ITSS. This approach is applied when IFATS or SFO data are not available, and relies on the accuracy of export value estimates. Additionally, missing data—such as the output-to-turnover ratio—are imputed by taking the average per SBI code. In summary, while these assumptions are necessary to produce Mode 3 estimates, they must be regularly reviewed and potentially refined to ensure the accuracy and reliability of the International Trade Statistics.
13.3.1. Coverage error
Information on the international supply of services is provided by two distinct statistical frameworks: the balance of payments (BOP) and the foreign affiliates statistics (FATS). BOP records transactions between residents and non-residents based on the centre of economic interest (residence) of an institutional unit. It primarily covers GATS Modes 1, 2, and 4, through the international trade in services statistics (ITSS). FATS, on the other hand, includes various indicators on the activities of controlled foreign affiliates, thus providing information on the supply of services through GATS Mode 3.
To further reduce sampling and coverage errors, several improvements have been implemented in the compilation of International Trade in Services Statistics (ITSS) in recent years. One significant example is the new sampling design, based on an enhanced stratification strategy, which was implemented in 2020.
Coverage errors might also occur when refining the standard allocation shares from the Eurostat-WTO model to fit the Dutch context. However, traders that were interviewed te refine the allocation shares were selected to ensure adequate coverage of all service types and trade flows (imports and exports), thereby minimizing coverage errors.
FATS uses data from other statistics, which are typically final at the time of integration, ensuring high accuracy and minimizing coverage errors. The nationality of UCI’s is verified by comparing data from multiple sources, and discrepancies are checked. Additionally, IFATS is kept consistent with underlying statistics, as monitored by both Statistics Netherlands and Eurostat. This helps to prevent coverage errors and ensures a reliable dataset.
13.3.1.1. Over-coverage - rate
Not applicable.
13.3.1.2. Common units - proportion
No information available
13.3.2. Measurement error
Measurement errors in ITSS and MoS can have several causes. Important sources of measurement errors may arise from non-response, sampling errors, or processing errors.
The impact of non-response is minimized by the fact that the ITSS survey is obligatory (i.e., non-responding enterprises can be fined), by sending multiple reminders to non-responding enterprises, and by specifically contacting non-responding enterprises that are expected to be major contributors to either total services trade or specific services categories. Furthermore, responses are validated in multiple ways. During the data collection phase itself, the survey software automatically checks if the submitted numbers are very different from previous quarters and asks for an explanation. Subsequently, the data are checked at the micro level. For instance, developments at the level of the statistical entity (which is usually an enterprise) are checked against previous quarters and years to ensure internal consistency (i.e., compared to the firm’s history), and the VAT information exchange system (more specifically the intra-Community trade declarations) is used as a frame of reference and as a lower limit to intra-EU trade. Additionally, quarterly and annual top-down analyses of the largest mutations over time and checks for consistency with developments at the macro, meso, and micro levels take place. For instance, when the costs of transport are increasing internationally due to supply chain interruptions, it makes sense that the value of transport imports and exports increases substantially for some firms.
Sampling errors are minimized by a new survey design implemented in 2020, and processing errors are minimized by continuously improving the compilation process.
Sampling error is generally not applicable to IFATS, as it is based on complete and administrative data from other statistics, rather than on a sample of businesses. These data sources are typically fully covered and definitive, meaning that the sampling error is negligible or non-existent. This contributes to the reliability of IFATS as a source for international trade statistics. For additional information regarding data checks/collection: Section 18.3
13.3.3. Non response error
Not applicable.
13.3.3.1. Unit non-response - rate
Not applicable.
13.3.3.2. Item non-response - rate
Not applicable.
13.3.4. Processing error
See 13.3.2.
13.3.5. Model assumption error
MoS compilation generally relies on assumptions, estimations, and expert judgments. This is particularly evident in the standard Eurostat-WTO model, where allocation shares are fixed regardless of the trading partner or reporting country. For the Dutch context, these shares have been adjusted, but the results remain highly dependent on various assumptions, such as the use of uniform shares across all partner countries and types of enterprises.
Furthermore, the adjustments required on the BOP side of MoS (primarily Modes 1, 2, and 4) depend significantly on broad assumptions. Some examples include:
Distribution services
These are estimated using the TiSMOS approach developed by the World Trade Organization. This approach draws on data from structural business statistics (SBS) and trade in goods by enterprise characteristics (TEC), focusing on businesses engaged in wholesale and retail trade activities (NACE activity G). From SBS, the gross margin on goods for resale is divided by net turnover to estimate the trade margins of wholesalers and retailers involved in merchandise trade. The export value of goods by enterprises in NACE section G is then multiplied by this share to estimate the value of distribution services.
Separating goods from construction and travel items
This process is challenging and partly relies on expert judgment and rough analyses of the available data.
For construction, multiple data sources were analyzed. First, annual production statistics (SBS) were reviewed, comparing foreign revenues and costs of large multinational construction companies (NACE 41, 42, 43) with ITSS data to estimate the proportion of goods and services in foreign revenues. Next, financial information from several large traders in the construction sector was examined to assess foreign revenues and costs of construction projects, accounting for potential discrepancies in reporting. Finally, the annual reports of 16 major construction companies were analyzed to collect data on total construction costs and raw material purchases, aiming to estimate the share of goods. Based on this method, it is estimated that 19% of the total trade value of construction in regular ITSS originates from the value of goods/services acquired in the country where the project is carried out (for comparison, the World Trade Organization estimated a 25% share in the TiSMOS project). This corresponding trade value is excluded from the construction item.
For travel, the estimation of the goods component is based on multiple sources and assumptions, with specific percentages allocated to cross-border workers, seasonal workers, students, and tourists. Surveys and existing studies are used to determine spending patterns. The analyses for the travel component align with the Dutch methodology described in Section 13.2.3 of the MoS Compilers Guide, although the estimations of the goods shares have been updated with updated information.
To ensure accurate estimation in Mode 3, domain-specific models are employed to define the target variables—particularly the distinction between domestic and foreign trade for both import and export sides. These models are essential due to the structure of the data sources and the need to estimate trade flows based on incomplete or aggregated data.
For the import side, the target is defined by identifying businesses in the Netherlands with a foreign parent company, using data from the UCI list and NACE rev. 2 classifications. Specific rules are applied to allocate domestic and foreign turnover based on data from IFATS, SFO, ITGS, and ITSS. These rules include scenarios where net turnover is zero, where foreign turnover is missing, or where discrepancies exist between IFATS and SFO data. Each rule is based on assumptions, such as the equivalence of the domestic share of turnover in domestic and foreign trade, which is considered acceptable by the MoS-compiler’s guide but may require refinement.
For the export side, the target is defined using OFATS data, which includes foreign subsidiaries of Dutch parent companies. Here, the domestic service turnover is estimated by scaling OFATS turnover data with ratios derived from the import side, based on NACE codes and the relationship between output and turnover. These models rely on assumptions such as the consistency of service share across domestic and foreign trade and the representativeness of the average output-to-turnover ratio per NACE code.
14.1. Timeliness
The first data transmission for each reference year includes modes 1, 2, and 4, with a transmission deadline of T+10 months. The second data transmission, which includes mode 3, has a deadline of T+22 months. For the first reference periode, the year 2023, the first data transmission was completed by the end of October 2024, and the second transmission by the end of October 2025. The October 2025 transmission also includes the first data transmission for reference year 2024.
This time lag exists due to the complex process of data collection, integration, and estimation across multiple data sources, as well as the need to apply specific models and assumptions. Specifically, the estimation of mode 3 requires the use of FATS statistics, which are available at a later stage and contribute to the longer time lag for the second transmission.
14.1.1. Time lag - first result
Not applicable.
14.1.2. Time lag - final result
The first data transmission deadline for a particular reference year is 10 months after the end of the reference period (T+10M). Potential revisions will be implemented one year later (T+22M).
14.2. Punctuality
Final transmission date: 31 October 2025
Data transmission deadline: 31 October 2025
The submitted data successfully passed validation.
14.2.1. Punctuality - delivery and publication
Not applicable.
15.1. Comparability - geographical
Data comparability is pursued by adhering as closely as possible to international recommendations and guidelines, particularly the MoS Compilers Guide. Efforts are made to align with these standards, aiming to ensure consistent and comparable data across geographical areas.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
Reference year 2024 is fully comparable with reference year 2023, as both are based on the same methodology. Note that Mode 3 is only covered for reference year 2023, not for reference year 2024
15.2.1. Length of comparable time series
Two reference periods (2023,2024)
15.3. Coherence - cross domain
In general, comparability between International Trade in Services Statistics and Modes of Supply (MoS) statistics is ensured by the application of common concepts and definitions of BPM6, the 2008SNA/ESA2010 and MSITS 2010.
15.3.1. Coherence - sub annual and annual statistics
Not applicable.
15.3.2. Coherence - National Accounts
Not applicable.
15.4. Coherence - internal
Each set of outputs is internally consistent.
Developing and compiling MoS data is a time-consuming process for compilers due to methodological challenges and the complexity of integrating and ensuring the compatibility of multiple data sources. However, the additional burden on respondents (enterprises) is minimized by relying on existing sources whenever possible.
MoS data are obtained mainly by integrating existing official data sources maintained by Statistics Netherlands with publicly available data from Eurostat. Specifically, these data are generated by combining Dutch international trade in services statistics (ITSS) with trade in goods by enterprise characteristics (TEC) from Eurostat, as well as structural business statistics (SBS) from Eurostat. Additionally, expert judgment and various secondary sources were employed. For example, financial statements of major construction companies were analyzed to estimate the goods component in construction services, while detailed microdata from the Continuous Holiday Survey were used to estimate the goods component in travel services.
A small increase in the burden on respondents (enterprises) arises because the allocation shares from the general Eurostat-WTO model have been fine-tuned to the Dutch context. This adjustment was based on supplementary research conducted among a sample of major traders through phone interviews. Further details about this supplementary research can be found in section 13.4.3 of the MoS compilers guide. Note that there is no increase in the burden on respondents for the construction of Mode 3 as already accessible data is used.
17.1. Data revision - policy
The first data transmission deadline for a particular reference year is 10 months after the end of the reference period (T+10M). Potential revisions will be implemented one year later (T+22M).
17.2. Data revision - practice
By the end of October 2025, the MoS data of reference year 2023 is updated in order to be consistent with the published ITSS (and other used data) figures.
17.2.1. Data revision - average size
MAR_{reference year 2023, 2024 release vs 2025 release} = 24761268000
18.1. Source data
Modes 1,2,4
MoS data are obtained mainly by integrating existing official data sources maintained by Statistics Netherlands with publicly available data from Eurostat. Specifically, these data are generated by combining Dutch international trade in services statistics (ITSS) with trade in goods by enterprise characteristics (TEC) from Eurostat, as well as structural business statistics (SBS) from Eurostat. Additionally, expert judgment and various secondary sources were employed. For example, financial statements of major construction companies were analyzed to estimate the goods component in construction services, while detailed microdata from the Continuous Holiday Survey were used to estimate the goods component in travel services.
The allocation shares from the general Eurostat-WTO model have been fine-tuned to the Dutch context. This adjustment was based on supplementary research conducted among a sample of major traders through phone interviews. Further details about this supplementary research can be found in section 18.3 of this metdata file and section 13.4.3 of the MoS compilers guide.
The most important source for modes 1, 2 and 4 (the BOP-related parts of MoS) is Dutch ITSS data. Approximately 85 percent of both services imports and exports in Dutch ITSS are measured using a survey among enterprises. The remaining 15 percent originates from other sources that cover specific types of services or populations, such as travel, government services, CIF/FOB corrections on transport services, and various estimates for financial and insurance services (some of which cannot be directly observed). The Dutch ITSS survey uses a stratified sample that ensures the selected enterprises represent the vast majority of total services trade by Dutch enterprises. It is estimated that approximately 90 percent of all services traded by Dutch enterprises are captured in the survey, with the remaining 10 percent being adjusted using statistical weighting techniques/grossing up.
Mode 3
The IFATS is an annual statistic on foreign companies in the Netherlands. It describes, among other things, how many jobs, turnover, and added value are generated by foreign companies in the Netherlands. The statistic is compiled based on existing statistics (production statistics, investment statistics, employment statistics, and R&D statistics), combined with data from the Ultimate Controlling Institutional unit (UCI) for the involved companies. This means that IFATS itself does not carry out primary data collection via a survey. IFATS serves as an indicator of the internationalization of the Dutch business community. The data shows eleven variables for companies operating in the Netherlands, broken down by UCI and NACE.The Netherlands is required to submit the output figures to Eurostat, which publishes them at the European level.The population consists of all companies in the Netherlands that have been active during the statistical year and fall under NACE REV 2.0 sections B to N, P to R, and S95 & S96. A company that has been dissolved during the statistical year is still included in the population for that year. The R&D variables (Intramural R&D expenditure and Number of R&D employees) are only provided for sections B to F. The other variables are provided for the entire population. IFATS uses data from other statistics. These statistics are usually final when used for IFATS. As a result, the accuracy is high. The nationality of UCIs is verified by comparing data from multiple sources and checking any discrepancies. Additionally, IFATS must be consistent with the underlying source statistics. Both Statistics Netherlands and Eurostat conduct checks on this.
The Outward Foreign Affiliates Statistics (OFATS) are based on a multisource process combining various data sources to measure the commercial presence of enterprises through foreign affiliates.
Data sources
EGR (Enterprise Group Register): Used to identify enterprise groups with foreign subsidiaries.
Statistics on Finance of Enterprise Groups (SFGO): Provides data on turnover abroad.
Statistics on Investments: Used to track investments and foreign presence.
Chamber of Commerce: Supplies data on business registration.
Private Databases: Provide supplementary business data.
These sources are combined by integrating data into a single table that records the maximum values for subsidiaries, employees, and turnover for each Ultimate Controlling Institutional unit (UCI), with a focus on those with foreign affiliates.
sampling:
The population includes market producers in NACE Sections B to N, P to S in the Netherlands and abroad. The sampling process consists of two parts:
Integral Part: Units of significant size (high turnover, employees, or foreign subsidiaries) that must always be included.
'Real' Sample: All other units from the population, from which a sample is drawn to ensure a representative dataset (approximately 4500 units, minus those in the integral part).
An SQL script is used to determine the population and draw the sample by processing and combining source data from the various databases.
administrative data:
Tax Administration's data: This file identifies OGs with foreign subsidiaries and controlling interests, based on data from the last two observation periods. It is primarily used to track corporate ownership.
UCI data: Provides information on ultimate controlling units for the most recent period.
These datasets are used to identify potential foreign subsidiaries and generate the sample for the FATS, ensuring the accuracy and reliability of the data.
18.2. Frequency of data collection
ITSS: quarterly
FATS: annualy
18.3. Data collection
Modes 1, 2, 4
MoS data are obtained mainly by integrating existing official data sources maintained by Statistics Netherlands with publicly available data from Eurostat. Specifically, these data are generated by combining Dutch international trade in services statistics (ITSS) with trade in goods by enterprise characteristics (TEC) from Eurostat, as well as structural business statistics (SBS) from Eurostat.
The allocation shares from the general Eurostat-WTO model have been fine-tuned to the Dutch context by Statistics Netherlands. This adjustment was based on supplementary research conducted among a sample of major traders through phone interviews.
For the collection of this data, targeted interviews were conducted with a selection of influential traders. The following steps were taken: companies were selected to ensure maximum coverage of services and trade flows, considering only services for which multiple modes of supply were deemed possible. The interviews utilized standardized questions, based on a document detailing probable modes of supply for each service. This document was derived from the Eurostat-WTO model, supplemented with insights from Statistics Netherlands and results from statistical agencies in other countries. The selected companies were interviewed by phone and asked about MoS information for the relevant services. The results were converted into MoS shares (see table 2 below), which were used for the compilation of Dutch MoS. Further details about this supplementary research can be found in section 13.4.3 of the MoS compilers guide.
Mode 3
In addition to section 18.3.
Ultimately, all totals from the IFATS should align with the totals from their source statistics. Several checks are performed to ensure this consistency.
Consistency between IFATS and SBS
Eurostat has developed a control mechanism within Edamis Acceptance to assess the internal consistency between IFATS and SBS deliveries. To do this, a new dataset is first created that includes the full SBS delivery and IFATS delivery. This combined dataset is then uploaded to Edamis Acceptance, where automatic consistency rules are applied through Eurostat's internal validation tool.
Consistency between IFATS and R&D
Totals are manually checked using the R&D table on Statline.
Select company size = 'Total'
Checks:
IM_RND_EXPN (IFATS) = R&D expenditure for own activities (R&D table)
RND_PER (IFATS) = Number of employees (R&D table)
In addition, automatic consistency rules between IFATS and R&D are applied through Eurostat's internal validation tool. These rules are directly derived from the feedback report in Edamis. No separate dataset or delivery is required for this step (unlike the consistency check between IFATS and SBS, where a separate dataset and delivery are created). Eurostat already receives the R&D delivery via the R&D domain and processes the totals in the validation tool.
Output Analysis for OFATS
In a cyclical process of response assessment, processing, and adjustment, the output of the statistics is determined alongside the output analysis.
The output analysis begins in the Analysis System. At this stage, the output is examined on two levels: the NACE level and the country level. On both levels, the development of the five output variables is analyzed using a score per variable.
Top-down, each variable is evaluated based on a score for each country or NACE. This score is derived from the absolute change in value and the percentage impact of the change on the cell. By using this score, even smaller cells with relatively large changes are highlighted. If, at the aggregate level, a cell is deemed worthy of further examination, a deeper dive is performed to identify which Enterprise Groups are responsible for the change.
The next step involves assessing the relevant enterprise group, focusing on developments such as UCI changes, turnover changes, and acquisitions or divestitures of subsidiaries.
Table 2. MoS allocation shares for the Dutch context
The reported ISS values for Mode 1 include an estimate of distribution services. These estimates were calculated using the TiSMOS approach developed by the World Trade Organization that utilizes data from structural business statistics (SBS) and trade in goods by enterprise characteristics (TEC), specifically focusing on businesses engaged in wholesale and retail trade activities (NACE activity G). From SBS data, the gross margin on goods for resale is divided by net turnover to estimate the trade margins of wholesalers and retailers involved in merchandise trade. The export value of goods by enterprises in NACE section G is then multiplied by this share to estimate the value of distribution services.
Exclusion of goods value
The goods value included in certain EBOPS items — specifically construction services and travel — has been identified and subtracted from the relevant items.
For construction services (SE), multiple data sources were analyzed. Annual production statistics (SBS) were reviewed, and foreign revenues and costs of large multinational construction companies (NACE 41, 42, 43) were compared with ITSS data to estimate the proportion of goods and services in foreign revenues. Additionally, financial information from several major traders in the construction sector was examined to assess the foreign revenues and costs of construction projects, taking into account potential discrepancies in reporting. Annual reports of 16 major construction companies were analyzed to obtain data on total construction costs and raw material purchases, supporting the estimation of the goods share. Based on this method, it was estimated that 19% of the total trade value of construction in regular ITSS originates from the value of goods and services acquired in the country where the project is carried out. For reference, a 25% share was estimated by the World Trade Organization in the TiSMOS project. The corresponding trade value has been excluded from the construction item.
For travel (SD), the goods component was estimated based on multiple data sources and assumptions, with specific percentages allocated to cross-border workers, seasonal workers, students, and tourists. Spending patterns were derived from surveys and existing studies. The analyses for the travel component are consistent with the Dutch methodology described in Section 13.2.3 of the MoS Compilers Guide (2023 edition), with updated information incorporated into the estimates for the goods component.
For maintenance and repair services (SB) and government services (SL), no goods value has been estimated or subtracted. This is in accordance with the recommendation in the MoS Compilers Guide (2023 edition), which states: “As regards maintenance and repair services and government goods and services n.i.e., the current recommendation is not to single out the goods value for these categories, as it is considered negligible in most cases” (page 75).
Statistics on international supply of services (ISS) by modes of supply (MoS) show how and where services are supplied internationally, namely by answering the question of 'how' services are exchanged across countries and 'where' services are supplied to foreign customers. Detailed information on international supply of services statistics by services category, mode of supply and partner country help policymakers carry out the ongoing and future trade negotiating agenda with facts and strong, evidence-based arguments and they allow to monitor the impact of services trade agreements.
The General Agreement on Trade in Services (GATS), the first multilateral agreement to cover trade in services, defines trade in services as the supply of a service through any of four modes of supply, outlined in the bullet points below.
Mode 1 - cross-border supply: from the territory of one country into the territory of another country; Mode 2 - consumption abroad: in the territory of one country to the service consumer of another country; Mode 3 - commercial presence: by a service supplier of one country, through a commercial presence in the territory of another country. The FATS framework is designed to provide information on the activities of enterprises located in foreign markets; Mode 4 - presence of natural persons: by a service supplier of one country, through the presence of natural persons of that country in the territory of any other country.
Total international supply of services (total of modes 1, 2, 3 and 4)
Mode 1 (‘cross border transactions’),
Mode 2 (‘consumption abroad’),
Mode 3 (‘commercial presence’), and
Mode 4 (‘presence of natural persons’).
Not applicable.
Current Scope: Total international supply of services by modes 1, 2, 3, and 4.
Future Scope: Total international supply of services categorized into services by all four modes of supply. For each mode, the totals are categorized into subcategories of services.
GEO level 5 (Commission Implementing Regulation (EU) 2020/1470 of 12 October 2020, Annex II)
Calendar year.
The accuracy of MoS data depends not only on the precision of International Trade in Services Statistics (ITSS) but also on the quality of the secondary data used. Examples include, but are not limited to, TEC and SBS data from Eurostat, which are utilized to calculate distribution services. Other secondary data that is used includes: International Trade in Goods Statistics (ITGS), Foreign Affiliates Statistics (FATS), Statistics of Finances of Enterprises, Production Statistics. Additionally, MoS accuracy is influenced by the numerous assumptions that must be made. Some of these assumptions are inherent to the standard Eurostat-WTO model, while others are necessary for estimating distribution services, the goods component in certain services, and other elements.
The primary source for compiling data on modes 1, 2, and 4 is the International Trade in Services Statistics (ITSS). Within ITSS, accuracy is pursued by minimizing non-sampling errors as much as possible. However, revisions in Dutch international trade in services figures can be substantial, as initial estimates may undergo significant adjustments when more accurate and comprehensive data become available.
This is especially true for Special Purpose Entities (SPEs). SPEs are companies often established for specific financial or legal purposes, such as tax optimization or facilitating international investments. These entities typically have minimal physical presence and few employees in the Netherlands, yet their financial activities can cause considerable fluctuations in reported economic data. As a result, given the significant number of SPEs in the Netherlands, initial international trade in services figures are often subject to substantial revisions when improved data from these SPEs becomes available.
Mode 3 is primarily based on FATS data. The import side is derived from the IFATS statistics. To determine the domestic turnover, the Statistics of Finances of Enterprises (SFO) is used. The share of services in turnover is then calculated using the ITGS and ITSS microdata. If necessary, the Production Statistics (PS) is used to determine the output value.
On the export side, the OFATS data is utilized. Further distributions for the export side are made based on the import side data.
All statistics are carefully compiled to ensure reliability. However, in linking these data, some necessary assumptions have been made, solely for the purpose of ensuring the required accuracy.
Data are reported in national currency (thousands).
Eurostat disseminates data in million euro.
Also see section 18.3
Inclusion of distribution services
The reported ISS values for Mode 1 include an estimate of distribution services. These estimates were calculated using the TiSMOS approach developed by the World Trade Organization that utilizes data from structural business statistics (SBS) and trade in goods by enterprise characteristics (TEC), specifically focusing on businesses engaged in wholesale and retail trade activities (NACE activity G). From SBS data, the gross margin on goods for resale is divided by net turnover to estimate the trade margins of wholesalers and retailers involved in merchandise trade. The export value of goods by enterprises in NACE section G is then multiplied by this share to estimate the value of distribution services.
Exclusion of goods value
The goods value included in certain EBOPS items — specifically construction services and travel — has been identified and subtracted from the relevant items.
For construction services (SE), multiple data sources were analyzed. Annual production statistics (SBS) were reviewed, and foreign revenues and costs of large multinational construction companies (NACE 41, 42, 43) were compared with ITSS data to estimate the proportion of goods and services in foreign revenues. Additionally, financial information from several major traders in the construction sector was examined to assess the foreign revenues and costs of construction projects, taking into account potential discrepancies in reporting. Annual reports of 16 major construction companies were analyzed to obtain data on total construction costs and raw material purchases, supporting the estimation of the goods share. Based on this method, it was estimated that 19% of the total trade value of construction in regular ITSS originates from the value of goods and services acquired in the country where the project is carried out. For reference, a 25% share was estimated by the World Trade Organization in the TiSMOS project. The corresponding trade value has been excluded from the construction item.
For travel (SD), the goods component was estimated based on multiple data sources and assumptions, with specific percentages allocated to cross-border workers, seasonal workers, students, and tourists. Spending patterns were derived from surveys and existing studies. The analyses for the travel component are consistent with the Dutch methodology described in Section 13.2.3 of the MoS Compilers Guide (2023 edition), with updated information incorporated into the estimates for the goods component.
For maintenance and repair services (SB) and government services (SL), no goods value has been estimated or subtracted. This is in accordance with the recommendation in the MoS Compilers Guide (2023 edition), which states: “As regards maintenance and repair services and government goods and services n.i.e., the current recommendation is not to single out the goods value for these categories, as it is considered negligible in most cases” (page 75).
Modes 1,2,4
MoS data are obtained mainly by integrating existing official data sources maintained by Statistics Netherlands with publicly available data from Eurostat. Specifically, these data are generated by combining Dutch international trade in services statistics (ITSS) with trade in goods by enterprise characteristics (TEC) from Eurostat, as well as structural business statistics (SBS) from Eurostat. Additionally, expert judgment and various secondary sources were employed. For example, financial statements of major construction companies were analyzed to estimate the goods component in construction services, while detailed microdata from the Continuous Holiday Survey were used to estimate the goods component in travel services.
The allocation shares from the general Eurostat-WTO model have been fine-tuned to the Dutch context. This adjustment was based on supplementary research conducted among a sample of major traders through phone interviews. Further details about this supplementary research can be found in section 18.3 of this metdata file and section 13.4.3 of the MoS compilers guide.
The most important source for modes 1, 2 and 4 (the BOP-related parts of MoS) is Dutch ITSS data. Approximately 85 percent of both services imports and exports in Dutch ITSS are measured using a survey among enterprises. The remaining 15 percent originates from other sources that cover specific types of services or populations, such as travel, government services, CIF/FOB corrections on transport services, and various estimates for financial and insurance services (some of which cannot be directly observed). The Dutch ITSS survey uses a stratified sample that ensures the selected enterprises represent the vast majority of total services trade by Dutch enterprises. It is estimated that approximately 90 percent of all services traded by Dutch enterprises are captured in the survey, with the remaining 10 percent being adjusted using statistical weighting techniques/grossing up.
Mode 3
The IFATS is an annual statistic on foreign companies in the Netherlands. It describes, among other things, how many jobs, turnover, and added value are generated by foreign companies in the Netherlands. The statistic is compiled based on existing statistics (production statistics, investment statistics, employment statistics, and R&D statistics), combined with data from the Ultimate Controlling Institutional unit (UCI) for the involved companies. This means that IFATS itself does not carry out primary data collection via a survey. IFATS serves as an indicator of the internationalization of the Dutch business community. The data shows eleven variables for companies operating in the Netherlands, broken down by UCI and NACE.The Netherlands is required to submit the output figures to Eurostat, which publishes them at the European level.The population consists of all companies in the Netherlands that have been active during the statistical year and fall under NACE REV 2.0 sections B to N, P to R, and S95 & S96. A company that has been dissolved during the statistical year is still included in the population for that year. The R&D variables (Intramural R&D expenditure and Number of R&D employees) are only provided for sections B to F. The other variables are provided for the entire population. IFATS uses data from other statistics. These statistics are usually final when used for IFATS. As a result, the accuracy is high. The nationality of UCIs is verified by comparing data from multiple sources and checking any discrepancies. Additionally, IFATS must be consistent with the underlying source statistics. Both Statistics Netherlands and Eurostat conduct checks on this.
The Outward Foreign Affiliates Statistics (OFATS) are based on a multisource process combining various data sources to measure the commercial presence of enterprises through foreign affiliates.
Data sources
EGR (Enterprise Group Register): Used to identify enterprise groups with foreign subsidiaries.
Statistics on Finance of Enterprise Groups (SFGO): Provides data on turnover abroad.
Statistics on Investments: Used to track investments and foreign presence.
Chamber of Commerce: Supplies data on business registration.
Private Databases: Provide supplementary business data.
These sources are combined by integrating data into a single table that records the maximum values for subsidiaries, employees, and turnover for each Ultimate Controlling Institutional unit (UCI), with a focus on those with foreign affiliates.
sampling:
The population includes market producers in NACE Sections B to N, P to S in the Netherlands and abroad. The sampling process consists of two parts:
Integral Part: Units of significant size (high turnover, employees, or foreign subsidiaries) that must always be included.
'Real' Sample: All other units from the population, from which a sample is drawn to ensure a representative dataset (approximately 4500 units, minus those in the integral part).
An SQL script is used to determine the population and draw the sample by processing and combining source data from the various databases.
administrative data:
Tax Administration's data: This file identifies OGs with foreign subsidiaries and controlling interests, based on data from the last two observation periods. It is primarily used to track corporate ownership.
UCI data: Provides information on ultimate controlling units for the most recent period.
These datasets are used to identify potential foreign subsidiaries and generate the sample for the FATS, ensuring the accuracy and reliability of the data.
Annual.
The first data transmission for each reference year includes modes 1, 2, and 4, with a transmission deadline of T+10 months. The second data transmission, which includes mode 3, has a deadline of T+22 months. For the first reference periode, the year 2023, the first data transmission was completed by the end of October 2024, and the second transmission by the end of October 2025. The October 2025 transmission also includes the first data transmission for reference year 2024.
This time lag exists due to the complex process of data collection, integration, and estimation across multiple data sources, as well as the need to apply specific models and assumptions. Specifically, the estimation of mode 3 requires the use of FATS statistics, which are available at a later stage and contribute to the longer time lag for the second transmission.
Data comparability is pursued by adhering as closely as possible to international recommendations and guidelines, particularly the MoS Compilers Guide. Efforts are made to align with these standards, aiming to ensure consistent and comparable data across geographical areas.
Reference year 2024 is fully comparable with reference year 2023, as both are based on the same methodology. Note that Mode 3 is only covered for reference year 2023, not for reference year 2024
