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.
CENTRAAL BUREAU VOOR DE STATISTIEK (CBS, STATISTICS NETHERLANDS)
1.2. Contact organisation unit
EBD (Enterprise statistics Den Haag)
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Postbus 24500
2490 HA Den Haag
The Netherlands
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
26 August 2025
2.2. Metadata last posted
26 August 2025
2.3. Metadata last update
26 August 2025
3.1. Data description
Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS covers all activities of the business economy with the exception of agricultural activities, public administration and (largely) non-market services such as education and health. Main characteristics (variables) of the SBS data category:
Business demographic variables (e.g. Number of active enterprises)
"Output related" variables (e.g. Net turnover, Value added)
"Input related" variables: labour input (e.g. Number of employees and self-employed persons, Hours worked by employees); goods and services input (e.g. Purchases of goods and services); capital input (e.g. Gross investments)
Business services statistics (BS) collection contains harmonised statistics on business services. From 2008 onwards BS become part of the regular mandatory annual data collection of SBS. The BS’s data requirement includes variable “Turnover” broken down by products and by type of residence of client.
The annual regional statistics collection includes three characteristics due by NUTS-2 country region and detailed on NACE Rev 2division level (2-digits).
3.2. Classification system
Statistical Classification of Economic Activities in the European Community (NACE): NACE Rev.2 is used from 2008 onwards. Key data were double reported in NACE Rev.1.1 and NACE Rev.2 only for 2008. From 2002 to 2007 NACE Rev. 1.1 was used and until 2001 NACE Rev.1
The product breakdown is based on the Classification of Products by Activity (CPA) as stated in the Regulation establishing CPA 2008 and its amending Commission Regulation (EU) No 1209/2014 (from reference year 2015 onwards).
3.3. Coverage - sector
Starting reference year 2021 onwards SBS cover the economic activities of market producers within the NACE Rev. 2 Sections B to N, P to R and Divisions S95 and S96. Until 2007 the SBS coverage was limited to Sections C to K of NACE Rev.1.1 and from the reference year 2008 to 2020 data was available for Sections B to N and Division S95 of NACE Rev.2. From 2013, as the first reference year, to 2020 information is published on NACE codes K6411, K6419 and K65 and its breakdown.
From 2008 reference year data collection BS covers NACE Rev 2 codes: J62, N78, J582, J631, M731, M691, M692, M702, M712, M732, M7111, and M7112.
3.4. Statistical concepts and definitions
SBS constitutes an important and integrated part of the new European Business Statistics Regulation (EU) 2019/2152
Surveying all legal units belonging to a complex enterprise
yes
Surveying all legal units within the scope of SBS belonging to a complex enterprise
no
Surveying only representative units belonging to the complex enterprise
no
Other criteria used, please specify
Comment
The observation unit in questionnaires is the enterprise.
3.5.2. Consolidation
Consolidation method
Consolidation carried out by the NSI
yes
Consolidation carried out by responding enterprise/legal unit(s)
yes
Other methods, please specify
Comment
For variables number of enterprises / employees / employees and self-employed persons consolidation is performed at the NSI as the source data is at the legal unit level. For other variables data is collected from questionnaires and collected at the enterprise level.
3.6. Statistical population
Sections B to N, P to R and Divisions S95 and S96 are fully covered (market producers)
All size classes are covered
Market producers are selected using sector codes in the business register
The frame for SBS statistics is the business register, all data is provided at enterprise level.
3.7. Reference area
The Netherlands, including the requested information on NUTS1 and NUTS2 level.
Data for the Caribbean Netherlands (special municipalities that are located in the Caribbean sea) are not included.
3.8. Coverage - Time
1997-present
3.9. Base period
Not applicable.
Number of enterprises and number of local units are expressed in units.
Monetary data are expressed in millions of €.
Employment variables are expressed in units.
Per head values are expressed in thousands of € per head.
Ratios are expressed in percentages.
The reference year for persons employed indicators is the calendar year
The reference year for the financial indicators is the calendar year.
In most cases the fiscal year equals the calendar year.
If the fiscal year is unequal to the calendar year, all financial indicators of the enterprise are calibrated using VAT data (calendar year).
For some multinational enterprises ad hoc corrections are made if the fiscal year results are expected to deviate from calendar year results.
6.1. Institutional Mandate - legal acts and other agreements
Starting with reference year 2021 two new regulations currently form the legal basis of SBS:
Regulation (EU) 2019/2152 repealing 10 legal acts in the field of business statistics (EBS Regulation), and
The Council Regulation No 58/97 has been amended three times: by Council Regulation No 410/98, Commission Regulation No 1614/2002 and European Parliament and Council Regulation No 2056/2002. As a new amendment of the basic Regulation it was decided to recast the Regulation No 58/97 in order to obtain a new "clean" legal text. In 2008 the European Parliament and Council adopted Regulation No 295/2008 and the provisions of this Regulation were applicable from the reference year 2008 to reference year 2020. Regulation No 295/2008 was amended by Commission Regulation (EU) No 446/2014.
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
Statistics Netherlands guarantees the privacy of respondents (persons, enterprises and other), the confidential nature of the information provided and the sole use for statistical purposes.
This is captured in law:Act of 20 November 2003, enacting a law governing Statistics Netherlands (Statistics Netherlands Act)
Section 37 of this act:
The data received by the director general in connection with the performance of his duties to implement this act shall be used solely for statistical purposes.
The data referred to in the first subsection shall not be provided to any persons other than those charged with carrying out the duties of the CBS.
The data referred to in the first subsection shall only be published in such a way that no recognisable data can be derived from them about an individual person, household, company or institution, unless, in the case of data relating to a company or institution, there are good reasons to assume that the company or institution concerned will not have any objections to the publication.
SBS is also subject to the General Data Protection Regulation (GDPR) as enterprises also comprise sole proprietorship.
7.2. Confidentiality - data treatment
Primary confidentiality according to P% rule. This approach takes into account that a contributor to a publication group can use own data to make an estimation of competitors values.
Furthermore, the weight of secondary confidentiality cells are minimised.
The confidentiality treatment is performed using the Tau-Argus package available within the NSI.
Measures to reduce the number of confidential cells:
Use the P% rule.
Apply the same confidentiality pattern to strongly correlated indicators.
The procedure of confidentiality treatment is only applied to (potential) output cells.
7.2.1. Confidentiality processing
Data treatment
Confidentiality rules applied
yes
Threshold of number of enterprises (Number)
According to P% rule restrictions
Number of enterprises non confidential, if number of employments is confidential
yes
Dominance criteria applied
yes
If dominance criteria applied specify the threshold (Number)
According to P% rule restrictions
Secondary confidentiality applied
yes
Comment
P% rule is applied
8.1. Release calendar
The SBS indicators are derived from several datasets which are available online, each with its own release policy. The release policy is articulated in the explanation accompanying the datasets.
8.2. Release calendar access
The release calendar is part of the explanation paragraph of the online tables.
Statistics Netherlands follows the Code of Practice for European Statistics
More information on quality assurance is available on the website: Quality | CBS
11.2. Quality management - assessment
Statistics Netherlands uses administrative data as much as possible as it provides almost data completeness.
12.1. Relevance - User Needs
National accounts use the structural information and Year-to-Year growth rates to calculate the Gross Domestic product.
The Centre for Policy Related Statistics: under certain conditions, Statistics Netherlands can make microdata (anonymous data at the level of individual persons and businesses) available for statistical research. The data can, for example, be used to measure the performance of specific categories of enterprises.
Ministry of Economic Affairs and Climate Policy: SBS data is used for policy purposes. Special interest in data on SME's (small and medium sized enterprises).
Ministry of Health, Welfare and Sport: SBS data on NACE Q (86-88) and R (93).
Eurostat, ECB, and other international organisations for various policy purposes.
12.2. Relevance - User Satisfaction
Feedback of the most important user, National Accounts, is received on a structural basis. Data quality in general is perceived as good. A quality issue of SBS statistics is the limited sample size for SME enterprises. The accuracy of the results on the most detailed level is therefore also limited.
Feedback from Eurostat (e.g. the compliance score but also the results from the validation process) is used to improve statistics.
12.3. Completeness
Most datasets are 100% complete or almost complete.
13.1. Accuracy - overall
Statistics Netherlands uses administrative sources as the main source for Number of enterprises and employment indicators. For some sections (NACE Q and R) corporate (for legal persons) and individual (for natural persons) tax data is also used for financial variables. NACE Q also uses administrative data from the ministry of Health, Welfare and Sport. Administrative data is furthermore used as auxiliary information in the weighing process of most financial variables and most NACE groups. The sampling errors which are associated with traditional survey sampling are therefore reduced, especially on the higher levels of NACE aggregation.
Remaining sources for inaccuracies:
- Sampling errors (not all variables are covered by administrative data)
- The use of administrative data could potentially result in a small bias in some cases (e.g. different definitions of the source compared to SBS definitions).
- Measurement errors are possible especially for multinational enterprises. As a countermeasure Statistics Netherlands has installed a large case unit for the largest enterprise groups.
The preliminary results can be slightly biased. For preliminary data the estimates rely more heavily on previous year data, and extrapolations from administrative data. For NACE Q larger biases can occur as VAT data is not used in this sector because of many VAT exemptions.
The first release of the data is 10 months after the reporting period (preliminary data deliveries)
The second and final release is 17/18 months after the reporting period.
13.2. Sampling error
Sample surveys are used for the calculation of financial variables. The sampling error is usually small but especially in smaller NACE groups or NACE x size class groups the sampling error can be large.
Sampling errors are calculated following the guidelines provided by Eurostat.
13.3. Non-sampling error
Non-sampling errors could potentially arise in SBS:
- Coverage errors: the completeness of the Business Register in Statistics Netherlands is considered to be very good. Most SBS indicators are based on statistics that use the business register. Lack of completeness is therefore not considered to be a big problem. Effect negligible.
- Data collection and access errors: in general the results of mistakes in data collection are considered to be small and acceptable. Most difficulties arise with multinational enterprises as they can have complex business structures within and outside the borders of the Netherlands. The effect is small.
However, there is an exemption into section Q and R. The tax corporate and individual tax data is incomplete due to tax exempt status of enterprises, reporting after data collection period, and incomplete linking with Business Register. The effect is still unknown and more research is needed.
- Unit non-response: the weighted response rates are considered high (around 90% depending on the variable and NACE group). The strategy to minimise non-response is mainly focused on one or more telephone reminders. Effect is negligible.
- Item non-response for the key variables: for Total turnover and Total investments, the weighted response rate is around 90%. Number of enterprises and number of employed persons are calculated using administrative data (non-response not applicable). Effect negligible.
- Editing, coding and imputation errors: imputation errors for the financial variables are minimised by using T-1 data and VAT information on the microdata level and in some cases using information from the company financial statement. Editing errors are minimised by following a different approach for small enterprises (automatic editing) and large enterprises (manual editing). Effect negligible.
- Modelling errors: the grossing procedure uses auxiliary information (VAT data and information on persons employed for the whole population). This reduces bias resulting from selectivity in response. Effect small.
-Modelling errors for Nace Q: flag D (definition differs) is applied in NACE Q because administrative data used does not align with SBS variables: in the variable 'Purchases of goods and services for resale' are included the fee costs for independent medical specialists from the annual reporting data of health care institutions data and the purchased services of costs of sales from the tax data; for variable 'Value of output' see different definition for ‘Purchases of goods and services for resale’
-Modelling errors for Nace R: flag U (unreliable) is applied for 'Purchases of goods and services for resale' because available data sources do not align with this SBS variable. Flag E (estimated) is applied for almost all NACE R categories for 'Expenses on services provided through agency workers' because of adjusting for incorrect and partly missing relations of tax data to the business register.
14.1. Timeliness
Depending on the indicator, figures are published 3 to 16 months after the end of the reporting period.
14.2. Punctuality
The data is in general delivered before or at the target date.
15.1. Comparability - geographical
The same concepts apply for the different regions of the Netherlands
15.2. Comparability - over time
Break in series are usually small but sometimes non-negligible and due to changes in the business register or due to redesign.
Minor breaks in series have occurred in 2000, 2006, 2009, 2013 and 2021 for different reasons and depending on the group of indicators.
15.2.1. Time series
Time series
First reference year available (calendar year)
1997
Calendar year(s) of break in time series
2000, 2006, 2009, 2013, 2021
Reason(s) for the break(s)
For reference year 2000 a complete new methodology and processing unit was developed for indicators 'Output and performance' and 'Purchases and personnel costs'.
For reference 2006 a new version of the business register became operational, improving the linking of administrative data and changing the consolidation process for middle sized enterprises.
For reference 2006 administrative data was introduced for estimating variables on employment.
For reference year 2009 a partial redesign was implemented (methodology and processing unit) for indicators 'Output and performance' and 'Purchases and personnel costs'. Also changes were made in deriving the population frame in line with anticipated changes of the business register in 2010.
For reference 2010 a new version of the Business Register became operational, further improving the linking of administrative data and again changing the consolidation process for middle sized enterprises.
For reference year 2013 the completeness of the business register was improved (recognizing starting enterprises sooner and adding units unavailable in the Chamber of Commerce source. This mainly effected business demography).
For reference year 2021 the definition of indicators changes for Value of Output and Value Added. In line with the EBS regulation subsidies are now treated the same for both indicators.
Market orientation of an enterprise was re-evaluated resulting in elimination of enterprises from the population, largely restricted to NACE R, P , P85, P852, P853 and P854.
The new sectors PQRS have been added starting 2021.
Length of comparable time series (from calendar year to calendar year)
2000-2005, 2006-2008, 2009-2020, 2021 for 'Output and performance' and 'Purchases and personnel costs'
2000-2005, 2006-2008, 2010-now for 'Investments'
2000-2005, 2006-2008, 2010-now for 'employment'
2000-2005, 2006-2009, 2010-2012, 2013-now for ' business demography'
Data for NACE sections P,Q,R,S are only available for 2021 onwards
Comment
15.3. Coherence - cross domain
The SBS statstics use (the market producers of) the Business Register as a population frame (employment variables excluded):
- The number of enterprises in SBS equals the number of enterprises in the Business Register (correcting for administrative renumbering). Turnover, is not available in the Business Register.
- The 'size class for persons employed' in the Business Register is a 'coordinated value' used by most statistics for sampling and raising data/calculating totals. It is also used as a size class proxy for SBS. The Business Register uses previous year (T-1) data from the Policy administration (administrative data on wages, benefits and labour relations) to calculate the persons employed and corresponding size class. SBS uses this size class information in calculating size class data. The SBS indicator on persons employed however is based on the reporting year (T) information from the same Policy register. The size class of SBS and the actual number of employed can be inconsistent due to timelag and an incomplete match between Business Register and the Policy administration.
For Statistics Netherlands Prodcom is based on a separate questionnaire from SBS. The Large Case unit compares production from SBS and Prodcom on the Enterprise level (correcting for different concepts: Ownership principle versus flow of goods). Coherence level is considered to be high.
Value added of National Accounts is not directly calculated from SBS. Both SBS and National Accounts use the same underlying base statistics in its calculations (production statistics, investments, wage statistics etc). Several differences between SBS and National Accounts can be detected: valuation against basic prices (National Accounts) versus factor costs (SBS), undeclared work etc. However the production statistics used by both is the main source for National Accounts in calculating 'Production' and 'Use' and the resulting Value Added.
STS uses SBS Turnover data as weights. In both STS and SBS VAT data is used in the estimation process. The STS approach is more focused on correcting for non-real mutations (in the Business Register or observations).
Labour statistics (LFS, LCI and JVS) and SBS differ in the way employee benefits are calculated. SBS for wages/employee benefits is based on profit and loss information. Labour statistics are primarily based on the Policy Administration. For Statistics Netherlands Health and welfare financial statistics (NACE Q) and SBS differ in the way population is determined. Consolidation of enterprises in annual reporting to ministry of Health, Welfare and Sport are causes for difference in population.
Tourism statistics: there is no coherence with SBS. Mainly because the population is based on a functional approach.
Sectorial statistics (transport, energy etc.) follow a functional approach instead of a institutional (Enterprise/NACE) approach. The data are not used for validation of SBS.
Business Services of SBS are collected using the same questionnaires as the main table from SBS.
15.4. Coherence - internal
Aggregates are consistent with sub-aggregates. An exception are the regional figures. For a small number of enterprises no NUTS code may be available, leading to differences between the sum of the NUTS figures and national figures.
Coherence can be limited between different groups of indicators. The SBS statistics are produced from different sources and by different departments. Employment variables are derived from the Policy administration and the business register is only used for determining the NACE and size class of the activity. Differences between Policy administration (SBS employed persons) and other SBS indicators are possible.
Section K data is for some variables based on the Business Register and for other variables based on Central Bank data or other financial sources.
Statistics Netherlands does not have a separate SBS unit. The data are collected from different surveys and from different statistics.
The costs associated with SBS statistics are not available.
Investment indicators are collected using surveys. The total response burden for respondents is calculated to be 17.000 hours.
Indicators on Output and performance indicators are also collected using surveys. The total response burden for respondents is calculated to be 81.000 hours.
17.1. Data revision - policy
Business demography: quarterly figures. Provisional figures for current year, final figures are published in January T+2 months.
Output and performance, purchases and employee benefits: figures are published at T+15 months. No revisions are made.
Investments: preliminary data published at T+12 months for Manufacturing, final data for all sections at T+18 months.
Employment: preliminary data published at T+9 months, final data at T+21 months.
17.2. Data revision - practice
Business demography: revisions should be small or zero since both estimates are based on (almost complete) administrative data.
Employment: revisions should be small or zero since both estimates are based on (almost complete) administrative data.
Turnover: preliminary data estimations are in most sections based on VAT data and SBS T-1 reporting data. For NACE Q preliminary data estimations are based on auxiliary data and SBS T-1 reporting data due to lack of VAT data (many VAT exemptions in this sector). Larger revisions are possible when observations for the reporting year are available.
18.1. Source data
Business demography: derived from the Business Register. All enterprises in the Business Register are considered to be active and used for calculating (counting) the number of enterprises.
Employment: from 2006 Statistics Netherlands uses a new source for the compilation of the number of jobs of employees: an integral register containing information on wages and social contributions of all employees in the Netherlands. This employee register is controlled by the Social Insurance Institute and is filled with the data of employees from the declaration of earnings which employers send to the Tax Authorities. The employee register contains all employees working for companies and institutions who are obliged to pay taxes on earnings and social contributions. As a first step the number of employees has been determined from the employee register. Then the companies and institutions in the register are linked with the General Business Register of Statistics Netherlands through their tax number. The General Business Register contains the NACE of companies and institutions, which is used to differentiate the number of jobs by economic activity. Besides the General Business Register contains the main office of companies and institutions. The register lacks information on the location of companies and institutions with more than one office in the Netherlands. Therefore an additional survey among these companies with more than one office is held. In this survey, companies are asked to report the number of employees on municipality level. The results of the survey are combined with the number of jobs of employees from the register and result in regional employment figures.
Investments: sample survey. Stratification variables are NACE and size class. Sampling rates vary for each stratum and are determined by Neyman allocation (Total Investments used as the variable for allocation). Total sample around 55.000
Output and performance, purchases, employee benefits (for all sections except K,Q,R): sample survey. Stratification variables are NACE and size class. Sampling rates vary for each stratum and are determined by Neyman allocation (value added used as the variable for allocation). Total sample around 75.000. For some NACE groupings a threshold of 10 or 50 persons employed is used (every 2 out of 3 years) and results are imputed using T-1 or T-2 observations. Administrative data (VAT) is used as auxiliary information to improve the estimation procedure. For Section K data is collected by Dutch Central Bank, with around 1500 survey respondents. For Section Q: a combination of sample survey data, data from annual reporting for health care institutions (DigiMV) collectecd by the minstry of Health, Welfare and Sport and corporate (for legal persons) and individual (for natural persons) tax data are used in the estimation process. For Section R a Combination of sample survey data, annual reports and corporate tax data are used in the estimation process.
18.1.1. Data sources overview
Data sources overview
Survey data
yes
VAT data
yes
Tax data
yes
Financial statements
yes
Other sources, please specify
-Social Insurance Institute, -Dutch Central Bank, -Ministry of Health, Welfare and Sport
Comment
18.2. Frequency of data collection
Annual data collection for Investment indicators and Output and performance indicators (except for section K which is a combination of quarterly and annual data collection).
Quarterly data collection for employment indicators.
18.3. Data collection
For administrative data sources which are collected from the Tax authorities, the Business Register department links the administrative data to the Business Register and gives the statistical departments access to this data.
For the administrative data which are collected from the ministry of Health, Welfare and Sport in NACE Q the statistical department links the data to the Business Register.
Surveys from electronic questionnaires (or paper questionnaires by exception).
Repeated telephone contacts are used to improve response rates. Legal enforcement is used as a last resort in a limited number of cases.
18.4. Data validation
Business demography: plausibility checks. The main check is to compare the annual change in the calculated number of active units with the change in number of Business Register units.
Employment: completeness checks (data integrity rules); validity checks (internal consistency); plausibility checks. The register data have gone through a general imputation-correction method whereby double records are removed and missing records or variables are imputed for example with the use of declarations from other periods. Second, through top down analysis, the units with the highest number of employees are individually controlled and when necessary corrected. The quality of the data is further checked by analysing the development of the data on employment and wages differentiated by economic activity and regions over time. When necessary corrections on the values of the variables of the reporting units are made.
Investments: completeness checks (data integrity rules); validity checks (internal consistency); plausibility checks. Missing values are considered to be 0 values. Inconsistencies are then removed manually. Plausibility is checked using historical data.
Output and performance, purchases, employee benefits: completeness checks (data integrity rules); validity checks (internal consistency); plausibility checks. Missing values are imputed automatically and checked manually for large enterprises. Inconsistencies are removed manually or automatically. There are a number of plausibility checks incorporated in the process. These are compared with T-1 data and compared with similar units.
18.5. Data compilation
Business demography: no non-response, no methods for dealing with non-response needed.
Employment: first, the register data have gone through a general imputation-correction method whereby double records are removed and missing records or variables are imputed, for example with the use of declarations from other periods. Second, through top down analysis, the units with the highest number of employees are individually controlled and, when necessary, corrected. The quality of the data is further checked by analysing the development of the data on employment and wages differentiated by economic activity and regions over time. When necessary corrections on the values of the variables of the reporting units are made.
Investments: the methods for dealing for unit non response are:
Use T-1 data and the development of similar units (imputation of large units)
Use the average values of similar units if T-1 is unavailable (imputation of large units)
The methods for dealing for item non response are: missing values are considered to be 0 values; if the Total investments are unequal to the sum of the parts then a manual check and correction is applied.
Output and performance, purchases, employee benefits: imputation methods by unit non response (only single imputation is applied) are:
- Use VAT data for estimation of the Turnover (not applicaple for NACE Q becasue of VAT exemptions)
- Use unit response from T-1 multiplied by the average Year-to-Year growth rates of similar units.
- Use average or (by exception, medians) of similar units if T-1 is unavailable.
- Use the proportions between variables of similar response units.
Imputation methods by item non response (both multiple and single imputations are applied) are:
- Use the relationship between variables.
- Use the proportions between variables of responding units.
- Use of multiple imputation with Random Forest of variable ‘Expenses on services provided through agency workers’ (sections Q and R) because this item is not available in tax data.
In the grossing procedure non-respondents are excluded. The number of active units in the frame is used in the grossing procedure; VAT is used as auxiliary information in the grossing procedure.
18.6. Adjustment
The reference period which represents the calendar year the most is chosen. Only for units with a large contribution a correction will be made if the length of the reference year is unequal to one year. For smaller units the fiscal year financial data is calibrated using the factor VAT data turnover / fiscal year turnover. The result is more in line with the calendar year.
No comment
Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS covers all activities of the business economy with the exception of agricultural activities, public administration and (largely) non-market services such as education and health. Main characteristics (variables) of the SBS data category:
Business demographic variables (e.g. Number of active enterprises)
"Output related" variables (e.g. Net turnover, Value added)
"Input related" variables: labour input (e.g. Number of employees and self-employed persons, Hours worked by employees); goods and services input (e.g. Purchases of goods and services); capital input (e.g. Gross investments)
Business services statistics (BS) collection contains harmonised statistics on business services. From 2008 onwards BS become part of the regular mandatory annual data collection of SBS. The BS’s data requirement includes variable “Turnover” broken down by products and by type of residence of client.
The annual regional statistics collection includes three characteristics due by NUTS-2 country region and detailed on NACE Rev 2division level (2-digits).
26 August 2025
SBS constitutes an important and integrated part of the new European Business Statistics Regulation (EU) 2019/2152
Sections B to N, P to R and Divisions S95 and S96 are fully covered (market producers)
All size classes are covered
Market producers are selected using sector codes in the business register
The frame for SBS statistics is the business register, all data is provided at enterprise level.
The Netherlands, including the requested information on NUTS1 and NUTS2 level.
Data for the Caribbean Netherlands (special municipalities that are located in the Caribbean sea) are not included.
The reference year for persons employed indicators is the calendar year
The reference year for the financial indicators is the calendar year.
In most cases the fiscal year equals the calendar year.
If the fiscal year is unequal to the calendar year, all financial indicators of the enterprise are calibrated using VAT data (calendar year).
For some multinational enterprises ad hoc corrections are made if the fiscal year results are expected to deviate from calendar year results.
Statistics Netherlands uses administrative sources as the main source for Number of enterprises and employment indicators. For some sections (NACE Q and R) corporate (for legal persons) and individual (for natural persons) tax data is also used for financial variables. NACE Q also uses administrative data from the ministry of Health, Welfare and Sport. Administrative data is furthermore used as auxiliary information in the weighing process of most financial variables and most NACE groups. The sampling errors which are associated with traditional survey sampling are therefore reduced, especially on the higher levels of NACE aggregation.
Remaining sources for inaccuracies:
- Sampling errors (not all variables are covered by administrative data)
- The use of administrative data could potentially result in a small bias in some cases (e.g. different definitions of the source compared to SBS definitions).
- Measurement errors are possible especially for multinational enterprises. As a countermeasure Statistics Netherlands has installed a large case unit for the largest enterprise groups.
The preliminary results can be slightly biased. For preliminary data the estimates rely more heavily on previous year data, and extrapolations from administrative data. For NACE Q larger biases can occur as VAT data is not used in this sector because of many VAT exemptions.
The first release of the data is 10 months after the reporting period (preliminary data deliveries)
The second and final release is 17/18 months after the reporting period.
Number of enterprises and number of local units are expressed in units.
Monetary data are expressed in millions of €.
Employment variables are expressed in units.
Per head values are expressed in thousands of € per head.
Ratios are expressed in percentages.
Business demography: no non-response, no methods for dealing with non-response needed.
Employment: first, the register data have gone through a general imputation-correction method whereby double records are removed and missing records or variables are imputed, for example with the use of declarations from other periods. Second, through top down analysis, the units with the highest number of employees are individually controlled and, when necessary, corrected. The quality of the data is further checked by analysing the development of the data on employment and wages differentiated by economic activity and regions over time. When necessary corrections on the values of the variables of the reporting units are made.
Investments: the methods for dealing for unit non response are:
Use T-1 data and the development of similar units (imputation of large units)
Use the average values of similar units if T-1 is unavailable (imputation of large units)
The methods for dealing for item non response are: missing values are considered to be 0 values; if the Total investments are unequal to the sum of the parts then a manual check and correction is applied.
Output and performance, purchases, employee benefits: imputation methods by unit non response (only single imputation is applied) are:
- Use VAT data for estimation of the Turnover (not applicaple for NACE Q becasue of VAT exemptions)
- Use unit response from T-1 multiplied by the average Year-to-Year growth rates of similar units.
- Use average or (by exception, medians) of similar units if T-1 is unavailable.
- Use the proportions between variables of similar response units.
Imputation methods by item non response (both multiple and single imputations are applied) are:
- Use the relationship between variables.
- Use the proportions between variables of responding units.
- Use of multiple imputation with Random Forest of variable ‘Expenses on services provided through agency workers’ (sections Q and R) because this item is not available in tax data.
In the grossing procedure non-respondents are excluded. The number of active units in the frame is used in the grossing procedure; VAT is used as auxiliary information in the grossing procedure.
Business demography: derived from the Business Register. All enterprises in the Business Register are considered to be active and used for calculating (counting) the number of enterprises.
Employment: from 2006 Statistics Netherlands uses a new source for the compilation of the number of jobs of employees: an integral register containing information on wages and social contributions of all employees in the Netherlands. This employee register is controlled by the Social Insurance Institute and is filled with the data of employees from the declaration of earnings which employers send to the Tax Authorities. The employee register contains all employees working for companies and institutions who are obliged to pay taxes on earnings and social contributions. As a first step the number of employees has been determined from the employee register. Then the companies and institutions in the register are linked with the General Business Register of Statistics Netherlands through their tax number. The General Business Register contains the NACE of companies and institutions, which is used to differentiate the number of jobs by economic activity. Besides the General Business Register contains the main office of companies and institutions. The register lacks information on the location of companies and institutions with more than one office in the Netherlands. Therefore an additional survey among these companies with more than one office is held. In this survey, companies are asked to report the number of employees on municipality level. The results of the survey are combined with the number of jobs of employees from the register and result in regional employment figures.
Investments: sample survey. Stratification variables are NACE and size class. Sampling rates vary for each stratum and are determined by Neyman allocation (Total Investments used as the variable for allocation). Total sample around 55.000
Output and performance, purchases, employee benefits (for all sections except K,Q,R): sample survey. Stratification variables are NACE and size class. Sampling rates vary for each stratum and are determined by Neyman allocation (value added used as the variable for allocation). Total sample around 75.000. For some NACE groupings a threshold of 10 or 50 persons employed is used (every 2 out of 3 years) and results are imputed using T-1 or T-2 observations. Administrative data (VAT) is used as auxiliary information to improve the estimation procedure. For Section K data is collected by Dutch Central Bank, with around 1500 survey respondents. For Section Q: a combination of sample survey data, data from annual reporting for health care institutions (DigiMV) collectecd by the minstry of Health, Welfare and Sport and corporate (for legal persons) and individual (for natural persons) tax data are used in the estimation process. For Section R a Combination of sample survey data, annual reports and corporate tax data are used in the estimation process.
Annual.
Depending on the indicator, figures are published 3 to 16 months after the end of the reporting period.
The same concepts apply for the different regions of the Netherlands
Break in series are usually small but sometimes non-negligible and due to changes in the business register or due to redesign.
Minor breaks in series have occurred in 2000, 2006, 2009, 2013 and 2021 for different reasons and depending on the group of indicators.
