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.
The environmental goods and services sector (EGSS) accounts report on an economic sector that generates goods and services produced for environmental protection or the management of natural resources.
Products for environmental protection prevent, reduce and eliminate pollution or any other degradation of the environment. Examples are electric vehicles, catalysts and filters to decrease pollutant emissions, wastewater and waste treatment services, noise insulation works or restoration of degraded habitats.
Products for resource management safeguard the stock of natural resources against depletion. Examples are renewable energy production, energy-efficient and passive buildings, seawater desalinization or rainwater recovery, and materials recovery.
EGSS accounts provide data on output and export of environmental goods and services and on the value added of and employment in the environmental goods and services sector.
In addition, the data contain information on investments for climate change mitigation (CCM). Those investments aim at reducing the emission of greenhouse gases either by source or enhancing the removal from the atmosphere. This includes both characteristic activities (such as production of renewable energy) or resource efficient goods (such as electric vehicles).
EGSS and CCM data are compiled following the statistical concepts and definitions set out in the UN System of Environmental-Economic Accounting 2012 – Central Framework.
This includes both investments by characteristic activities (such as production of renewable energy) and investments in resource efficient goods (such as electric vehicles).
3.2. Classification system
Data are reported cross-classified by 1) the type of environmental purpose and 2) economic activity. The environmental activities are classified by purpose according to the classification of environmental purposes (CEP). Economic activity is classified according to the Statistical Classification of Economic Activities in the European Community, Rev. 2 (2008).
For CCM data also "Out of CEP" categories are included.
3.3. Coverage - sector
EGSS comprises a sector of the economy that produces goods and services aimed at environmental protection and resource management (see SEEA CF 2012 chapter 4). Environmental goods and services either reduce environmental pressures or help maintaining the stock of natural resources or they are designed to be cleaner and more resource efficient than conventional products. Environmental goods and services can be produced by corporations, households, governments and non-profit institutions. The list of environmental activities and products has been set out in the Commission Implementing Regulation (EU) 2015/2174 ('the indicative compendium of environmental goods and services').
CCM investments are closely linked the EGSS but also include investments beyond the scope of the CEP.
3.4. Statistical concepts and definitions
Environmental Goods and Service Sector:
EGSS has the same system boundaries as the European System of Accounts (ESA 2010) and consists of all environmental products within this production boundary. ESA defines production as the activity carried out under the control and responsibility of an institutional unit that uses input of labour, capital, goods and services to produce output of goods and services.
Only goods and services produced for environmental purposes are included in the scope of the environmental goods and services sector.
'Environmental purpose' means that a good or service helps either 1) preventing, reducing and eliminating pollution and any other degradation of the environment or 2) preserving and maintaining the stock of natural resources and hence safeguarding against depletion.
The EGSS statistics aim at compiling data for the following economic variables:
Output: consists of products that become available for use outside of the producer unit, any goods and services produced for own final use and goods that remain in the inventories at the end of the period in which they are produced. Apart from market output, output for own final use and non-market output, EGSS statistics also include ancillary output, comprising output intended for use within an enterprise.
Market output is to be valued at basic prices, that is, the prices receivable by the producer from the purchaser minus taxes and plus subsidies on products. Output for own final use is to be valued at basic prices of similar products sold on the market or by the total costs of production. Non-market output is to be estimated by the total costs of production. Ancillary output is measured as a total of recurrent production costs (such as intermediate consumption, compensation of employees and consumption of fixed capital) incurred by enterprises to: 1) reduce environmental pressures arising from their production process or 2) produce environmental goods or services not intended for use outside the enterprise, but instead supporting other (non-environmental) activities undertaken within the enterprise (e.g. waste management services carried out in-house). For market producers, a mark-up for net operating surplus is added to the value of the EGSS ancillary output. Gross Value Added: represents the contribution made by the production of environmental goods and services to GDP. It is the difference between the value of the output and intermediate consumption.
Employment: is measured in full-time equivalent jobs engaged in the production of output of environmental goods and services. Full-time equivalent is defined as total hours worked divided by the average annual working hours in a full-time job.
Exports: consist of sales, barter, gifts, or grants, of environmental goods and services from residents to non-residents.
Investments for climate change mitigation:
The reporting covers the capital expenditure to reduce the emissions of greenhouse gases (GHG) by source or enhance their removal from the atmosphere by sinks.
Capital expenditure includes:
For activities and products covered by the CEP:
Gross fixed capital formation (GFCF – ESA 2010 code: P51g) for climate change mitigation related characteristic activities (i.e. GFCF for the production of specific services related to climate change mitigation)
GFCF in specific and cleaner and resource efficient goods related to climate change mitigation, unless they are already included in GFCF by CCM (characteristic) activities
and final consumption (ESA 2010 code: P3) in specific and cleaner and resource efficient goods related to climate change mitigation.
For activities and products relevant for CCM but outside the scope of CEP:
GFCF for the production of nuclear energy and for R&D related to nuclear energy
GFCF for the transmission and distribution of energy, in particular electricity
GFCF for the production of low carbon transport activities
GFCF in transport infrastructure for low carbon transport activities.
Where:
GFCF for climate change mitigation characteristic activities is broken down by corporations, government and households together with non-profit institutions serving households (NPISH).
GFCF for specific and cleaner and resource efficient goods, mitigating climate change, is broken down by corporations, government and households together with NPISH
Final consumption of specific and cleaner and resource efficient goods, mitigating climate change, is broken down by government and households together with NPISH.
3.5. Statistical unit
Council Regulation (EEC) No 696/93 of 15 March 1993 on the statistical units for the observation and analysis of the production system in the Community describes the different statistical units of the production system.
The recommended statistical unit for the data collection and compilation of private corporations is the establishment. For general government, households and NPISH, the recommendation is to use institutional units and groupings of units as defined in the European System of Accounts (ESA 2010).
3.6. Statistical population
The statistical population is the national economy as defined in SEEA CF 2012 and the European System of Accounts (ESA 2010). It includes all economic activities undertaken by resident units.
3.7. Reference area
The Netherlands
3.8. Coverage - Time
2021-2023
For now we have only transmitted the required data for 2021-2023. We have data available from 2001 onwards.
3.9. Base period
Not requested for this metadata collection.
Output, gross value added, exports and CCM investments are measured in million units of national currency. Employment is measured in full time equivalents (i.e., full time equivalent jobs).
The reference period for EGSS data (including CCM investments) is the calendar year.
6.1. Institutional Mandate - legal acts and other agreements
EGSS accounts and CCM investments are compiled and reported in accordance with Regulation (EU) No. 691/2011 on European environmental economic accounts (EEEA), and Regulation (EU) No. 2025/1131 on CCM investments and the CEP classification.
The EEEA follow internationally agreed concepts and definitions set out in the SEEA Central Framework (2012), the international statistical standard adopted by the UN Statistical Commission. They present data in a way that is compatible with National Accounts (ESA, 2010).
6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
CBS collects data from people, companies and institutions. Upon receipt of these data, all directly identifying personal details are removed as soon as possible and replaced by a pseudo key. CBS uses these so-called pseudonymised data to conduct statistical research. CBS will only publish statistical information without identifiable or traceable personal data. Furthermore, CBS has taken measures to ensure protection from theft, loss or abuse of personal data. CBS will never supply identifiable data to third parties, including other government institutions. However, (academic) institutions may, under strict conditions, be given access to pseudonymised personal or corporate data. These are referred to as microdata.
CBS meets the most stringent requirements as regards data protection. Every year, a privacy audit takes place which is carried out by an accredited external organisation and which results in a Privacy Audit Proof certificate.
This is how CBS demonstrates its compliance with the regulations of the GDPR (the accountability principle). External registrars (data suppliers) are controllers in themselves and in many cases bear a statutory obligation to supply datasets to CBS. The controlling responsibility of data suppliers under the GDPR ceases to exist as soon as data have been received by CBS.
For the data for the environmental goods and services sector each cell must comprise data of at least 3 companies and the share of the largest company should be maximum 70. For secondary confidentiality we look to first put the secondary confidentiality disclaimer on an 'other' category, before assigning secundary confidentiality to other fields. We do this to maximise the amount of cells being able to be shown, and we prefer to show values for categories that insist upon themselves, opposed to being the remainder that cannot be properly defined. These 'other' categories are CEP08 (cross-cutting and other environmental purposes), NACE C31-C33 (Manufacture of furniture; other manufacturing; repair and installation of machinery and equipment) and NACE S (other service activities).
For the CCM investments data, each cell may contain the sum of several subcategories. For each subcategory the confidentiality is checked if it contains data of at least 5 companies. Besides that also the p%-rule is applied for each indicator: if (T – x2 – x1)/x1 < p% (with p = 15), the indicator is confidential. In this equation T represents the total value of the indicator, and x1 and x2 are the largest and second largest contributors respectively. When the cells in the questionnaire are filled, for each cell the contributions of the underlying indicators are checked. If one or more of the indicators is marked confidential, the resulting data in the cell will only be shown if the contribution of these confidential indicators is less than 70% of the total value of that cell. For secondary confidentiality we have the same approach for CCM-data as for EGSS-data, both in CEP-scope and out of CEP-scope.
8.1. Release calendar
The environmental goods and services sector data, including the CCM data, (including for the Netherlands) are released around 15 months after the end of the calendar year.
8.2. Release calendar access
Not applicable.
8.3. Release policy - user access
The environmental goods en services data are publicly available and freely accesible online.
The environmental goods en services data for the Netherlands are released annually.
The EGSS provides useful insights regarding green growth, i.e. number of green jobs. Especially the breakdown to CEP02 (the former CReMA 13 focusing) on renewable energy production and energy saving is of interest to policy makers, and is also required in other publications such as the KEV (National Climate and Energy publication (energy transition).
However, with respect to the growing interest in the Circular economy EGSS does not provide all the required data. CEP activities are a starting point, but more CE activities (such as repair/second hand shops/ wholesale trade in scrap) have to be added. Most circular activities, related to resource management, are not within the scope of the EGSS.
The CCM-investment data provides usuful insight in the investments related to different aspects of climate change mitigation. Because of the broad scope of this dataset, a big picture of the green transition can be formed. This interests policy makers, as they can see the trend for different aspects with this transition (ranging from energy grids to renewable energy). However, more detailed information on several upcoming techniques is welcomed.
12.3. Completeness
Statistics Netherlands has been producing the EGSS data for several years now, and since it becames obligatory we had to make several improvements, mainly related to breaking down the data by NACE class. Although there are still some components of the EGSS that require extra attention, as far as we are aware we now fully comply to the reporting obligations. Please let us know if this is not the case.
In the CCM data, there are still some cells in the filled in questionnaire which are not compiled yet. As this is the first year that the CCM data is compiled, Statistics Netherlands has put the focus on the categories that are expected to have the largest contribution. This means that at the moment some (obligatory) cells are filled with zeroes, but with an explanatory note. These cells are filled with zeroes, in order to be able to calculate total sums of the investments.
12.3.1. Data completeness - rate
Not requested for this metadata collection.
13.1. Accuracy - overall
Most EGSS data is derived directly from National Accounts, COFOG or other official statistics.
The population of businesses is of lower quality. It is time consuming to keep the population up to date, furthermore the environmental share of businesss is constant so we do not measure (within company) development over time accurately. Furthermore allocating environmental shares (and CEP distribution) to businesses is quite subjective and a rough estimate.
Most CCM data is derived from National Accounts, Investments statistics, vehicle statistics and energy statistics.
As this is the first year of publication of CCM data, the data compilation will be improved in the upcoming years. Some existing results can be further improved, and missing indicators will be added. Some examples of indicators which are not included in the current publication are: bicycle lanes, electrolysers, home batteries, investments related to reducing other GHG than CO2. Also Near Zero Energy Buildings as a whole are not included yet, only the energy reducing measures such as isolation.
13.2. Sampling error
EGSS accounts and CCM investments are compiled using a range of primary statistical sources. The sampling and non-sampling errors are described in the metadata of the underlying statistical data.
13.2.1. Sampling error - indicators
Not requested for this metadata collection.
13.3. Non-sampling error
EGSS accounts and CCM investments are compiled using a range of primary statistical sources. The sampling and non-sampling errors are described in the metadata of the underlying statistical data.
13.3.1. Coverage error
Not requested for this metadata collection.
13.3.1.1. Over-coverage - rate
Not requested for this metadata collection.
13.3.1.2. Common units - proportion
Not requested for this metadata collection.
13.3.2. Measurement error
Not requested for this metadata collection.
13.3.3. Non response error
Not requested for this metadata collection.
13.3.3.1. Unit non-response - rate
Not requested for this metadata collection.
13.3.3.2. Item non-response - rate
Not requested for this metadata collection.
13.3.4. Processing error
Not requested for this metadata collection.
13.3.5. Model assumption error
Not requested for this metadata collection.
14.1. Timeliness
Statistics Netherlands disseminates data with a delay of about 12 months after the end of the reference year
14.1.1. Time lag - first result
12 months
14.1.2. Time lag - final result
20 months
14.2. Punctuality
The data will be delivered to Eurostat in September 2025. The reporting deadline for EGSS (including CCM investments) to Eurostat is 31 October.
14.2.1. Punctuality - delivery and publication
Not applicable because there is no release calendar
15.1. Comparability - geographical
Not applicable
15.1.1. Asymmetry for mirror flow statistics - coefficient
Other wood production when complying with sustainability measures (not relevant)
Organic aquaculture activities (not economically significant yet, might be included in the future)
Manufacture of vehicles for wastewater treatment, vehicles for sewer cleaning, trucks for waste collection (probably not relevant, also not been able to identify)
15.1.3. Comparability - geographical - products not present in Indicative compendium - included
Because we use several different approaches (not a product-approach) to estimate 'environmental activities', it is sometimes difficult to know exactly whether certain products or activities (e.g. 'Manufacture of boards, blocks and similar articles of vegetable fibre, straw or wood waste, agglomerated with mineral binders) are completely included.
15.2. Comparability - over time
Comparable time series are available starting with 2001 reference year. Data were classified according to the CEPA 2000 and CReMa classifications; from 2023 onwards, according to the CEP classification.
15.2.1. Length of comparable time series
EGSS: Comparable time series are available starting with 2001 reference year.
CCM investments: Comparable time series are available starting with 2021 reference year.
15.2.2. Comparability - over time detailed
Time series from 2000 to 2009 are calculated using a factor (sometimes at a higher aggregated level) from previous publications.
Since 2010, a microapproach (MDL) method has been used. Every effort has been made to ensure that these two methods are compatible. We do a search for companies every three years. Every three years has a possibility for a break in the data. The most recent edition of the recheck was in 2023.
Not relevant for CCM (yet).
15.3. Coherence - cross domain
EGSS: please see following sub-chapters. The data are coherent with the National Accounts and the Environmental Accounts.
15.3.1. Coherence - sub annual and annual statistics
Only annual statistics are used for the compilation of this statistic.
15.3.2. Coherence - National Accounts
We do not have procedures in place to check coherence, but we do use SUT and COFOG directly to compile EGSS figures.
Some procedures to check coherence of our final results with SUT and COFOG could be useful. Especially because we use many different methods which may overlap.
The statistics regarding government production, gross value added and employment used for the calculation of the EGSS come out of the same source data as the EPEA. This ensures the data should be consistent between the EPEA and the EGSS.
15.3.4. Coherence - other statistics
EGSS statistics are not compared to other statistics. They do however often come directly out of microdata of other sources, like trade statistics and business statistics.
15.4. Coherence - internal
EGSS: In general the same data sources are used to compile the various EGSS variables, mostly National Account data. In some cases GVA or Employment figures have to be estimated, this is done by determining GVA/output and Emp/output ratios, which are in most cases directly derived form corresponding NACE-classes. In some cases, for instance the results from the business population, data is not directly derived from NA and definitions and measurement rules may deviate slightly.
Currently about 0,3 FTE for the EGSS, this includes dissemination of data (data tables, news articles, improving/developing data quality, etc.)
For CCM this is roughly 0,5 FTE, mainly because a lot of development and improvement is necessary in the upcoming years.
16.1. Cost and Burden - other accounts
Currently about 0,3 FTE, this includes dissemination of data (data tables, news articles, improving/developing data quality, etc.).
17.1. Data revision - policy
In the long-run we aim to follow the general revision strategy of the Dutch NA, which means we will only revise once every 5 years (the NA-revision will affect EGSS estimates in 2025), except for the rebase of the business population which will be revised once every 3 years (which has been revised in 2023 and will be revised in 2026). However, in the short term there are still many aspect of EGSS that need further improvement, so we will try to continuously improve the EGSS statistic and its scope in the coming years. Also, the update of the compendium means we need to have another look at the scope and extent/improve where needed.
For the CCM data the same applies as for EGSS. On the long run we aim to follow the general revision of the Dutch NA.
17.2. Data revision - practice
The last major revision of National Accounts was the 2024 revision.
17.2.1. Data revision - average size
Not applicable
17.2.2. Status of data
In 2023 we worked on a rebase of our microdata. This means that the results of previous years can differ.
In 2025 we have made changes to the export data regarding services. This means the results of previous years can differ.
As mentioned in section 13.1 and 17.1, the data in the CCM questionnaire are compiled for the first time this year (2025). Next year we will try to improve the existing data and expand the measured set of data. Possible additions next year may include bicycle lanes, electrolysers, home batteries, investments related to reducing other GHG than CO2. Also Near Zero Energy Buildings will be further investigated.
18.1. Source data
National Account data forms the basis of the Dutch EGSS for all economic variables. Supply and use tables provide market output and gross value added figures for several NACE classes (e.g. NACE A01, E36, E37, E38, E39, M71.2, S94.996) while Labour Accounts data is used to provide employment figures. In some cases (e.g. A01 agriculture) additional sources (e.g. data on organic farming certificates) are used to estimate the environmental share (ha organic agriculture / ha total agriculture) of a specific NACE class.
COFOG data is used to derive economic variables (output, employment and gross value added) for environmentally related government activities. No export of environmentally related government activities is measured.
A part of the remaining environmental activities, that cannot be linked directly to NA data, is estimated by the so called micro-approach. A population of businesses (mainly activities related to sustainable energy, construction, consultancy and engineering) is set up and linked to the Dutch Business Register, statistics on employment (SWL) and International Trade Statistics.
The population of businesses has been revised and updated recently (as we try to do every 3 years). This was mainly done by using a webcrawl to identify environmental businesses that were not included before. As a result, the whole time series has been revised.
For some environmental activities, such as education, additional data from external sources is used to provide more accurate estimates. In a few cases some other approaches were used, e.g. to estimate export figures of specific goods a selection of CN-codes was made and linked to international trade data.
For CCM the main source of information is the Investment-statistics, in which companies provide detailed insight in different type of investments from their company. From these data it is possible to derive for a complete NACE class the relevant investments (no investments in land included, and no second-hand, to comply with National Account rules on investments). For example in the case of freight transport per rail we use NACE 49.20.
Other important statistics entail the energy statistics, used for CEP 0201. In this case the investments are based on physical data (added capacity). This is combined with external information on investments prices per added capacity. CEP 0101 includes electric vehicles. To estimate these investments we used transport statistics, which gives the number of newly purchased (electric) vehicles and some information on the average price.
For investment amounts (by companies) in renewable energy (green gas, geothermal) and energy savings and energy grids (including energy efficiency, district heating networks, hydrogen, smart grids, and biofuels), microdata from various subsidy schemes is used. For some subcategories (charging stations) external information is used.
COFOG data/government statistics is used mainly for investments in “Low carbon transport infrastructures”, both for inland waterways and rail infrastructure.
Investments in energy efficient buildings are based on detailed market information from several secondary sources on production activities of the construction sector related to insulation of buildings. Data is available on purchases of insulation materials and insulation glass, and on installation costs for application in different market segments (i.e. owner-occupied housing, rental and social housing, utility buildings, new and existing buildings).
18.1.1. Source data - detailed - environmental accounts
EGSS: We do not use any other environmental accounts as data sources. However we do use the same source as the EPEA (COFOG data).
CCM investments: the same holds as for EGSS
18.1.2. Source data - detailed - other statistics
EGSS: We use agricultural statistics to estimate the production, gross value added, employment and export of the biological agricultural sector. We also use energy statistics (physical energy production) to estimate a part of the statistics regarding these NACEs. We use statistics regarding education as well.
Furthermore we use microdata regarding international trade statistics, production statistics and labour statistics to extimate our population of microdata.
CCM investments: We use investment-statistics as a primary source for many CEP and out of CEP categories. In addition we use energy statistics for added capacity, in order to estimate investments in CEP0201. Furthermore we use transport statistics (CEP0101), COFOG data and subsidy data.
18.1.3. Source data - survey
EGSS: No additional surveys are held to produce the Dutch EGSS data. Data is derived from existing data sources.
For CCM investments the same applies as for EGSS.
18.1.4. Source data - detailed - other macro economic data (trade, VAT etc.)
EGSS: We do not use other macro-economic data not mentioned in points 18.1.1 or 18.1.2. We mostly use micro-economic data.
The same holds for CCM-investments data.
18.2. Frequency of data collection
Annual
18.3. Data collection
Not applicable
18.4. Data validation
If (new) external data sources are used (for instance on organic agriculture) we try to find multiple sources or historic sources to check their validity, further we check whether this new data deviates from previous data (and how much and why). The quality of data that is directly derived from the National Accounts is not checked. When applying new compilation methods, for instance we now compile government activities based on COFOG data, we compare the new and old results and analyze the differences.
Another check on for instance export is to compare them with production value. We compare export and production data in detail (i.e. at lowest CEPA/NACE categories possible), and make sure exports cannot exceed production value. This is the case sometimes, because we use different approaches (product vs activity) for exports and production value which may lead to different (inconsistent) results.
18.5. Data compilation
Scope EGSS:
The scope of the Dutch EGSS has been determined in the past by identifying (16) different environmental activites, these still form the basis of the Dutch EGSS. However, the EGSS has developed since and the EGSS operational lists and EGSS handbook have been developed and improved. The operational list of activities is used to identify missing activities. In some cases these activities are excluded on purpose, either because they are economically irrelevant and not worth the effort to include them (a lot of work for an insignificant improvement, e.g. inspection of vehicles on air emissions), or we lack the data sources to estimate them. However, we continuously try to improve the EGSS by identifying new data sources and including new activities.
Additional data is used to determine the share of environmental activities. For instance, for education data on the number of students enrolled in an environmental study was used (and compared to total number of students), for organic agriculture the SKAL-certification (i.e. organic farming certificate) was used which shows the hectares used for organic agriculture (compared to total hectares in agriculture). Furthermore, a business population is used to identify certain environmental activities (see source data paragraph). The environmental share of these businesses (and CEP-subdivision) is based on company year reports, websites and is basically and expert guess.
No additional surveys are held to produce the Dutch EGSS data. Data is derived from existing data sources.
data compilation process:
National Account data forms that basis of the Dutch EGSS for all economic variables. Supply and use tables provide market output and gross value added figures for several NACE classes (e.g. NACE A01, E36, E37, E38, E39, M71.2, S94.996) while Labour Accounts data is used to provide employment figures. In some cases (e.g. A01 agriculture) additional sources (e.g. data on organic farming certificates) are used to estimate the environmental share (ha organic agriculture / ha total agriculture) of a specific NACE class.
COFOG data is used to derive economic variables (output, employment and gross value added) for environmentally related government activities. No export of environmentally related government activities is measured.
A part of the remaining environmental activities, that cannot be linked directly to NA data, is estimated by the so called micro-approach. A population of businesses (mainly activities related to sustainable energy, construction, consultancy and engineering) is set up and linked to the Dutch Business Register, statistics on employment (SWL) and International Trade Statistics.
For some environmental activities, such as education, additional data from external sources is used to provide more accurate estimates. In a few cases some other approaches were used, e.g. to estimate export figures of specific goods a selection of CN-codes was made and linked to international trade data.
Share:
In most cases the same environmental share is applied to all economic variables. CEP-classification shares differ for each company, so does their corresponding NACE class.
It depends on the method used whether the share is fixed over time. E.g. education and agriculture have a changing share over time (and are updated yearly). However, the environmental share of the business population has been fixed over time. However, we are looking for a method to allow for changing environmental shares for companies over time. However, it is an impossible task (time consuming) to check and update the environmental shares of all companies (>2000) year-to-year.
Shares in the micro-approach are updated every 3 years. Shares related to other activities such as agriculture and education are updated annually.
Description:
OUTPUT
Most data is derived directly from National Accounts. Business population is not directly linked, but is based on sources that are used to produce the NA data.
GROSS VALUE ADDED (GVA)
NA-data uses supply and use tables which include data on GVA. When COFOG data is applied we calculate GVA by taking total output minus intermediate use. In some cases GVA is not available at the required level of detail ( e.g. NACE 7.1.2.x (DUTCH SBI 7.1.2.0.3), then a corresponding output/GVA ratio (of NACE 7.1.2) is used to calculate GVA. In case of the population of businesses, each business is linked to the Production Statistics which also includes GVA figures on a business level.
EXPORTS
We use several different methods. For some activities it is based on the total exports of the corresponding NACE-class. The population of businesses can be linked directly to export figures on business level. For some activities there is no (clear) export at all. For organic agriculture we use an external source.
EMPLOYMENT
In most cases we derive FTEs directly from the Labour Accounts or other source data on employment (e.g. linking the business population to employment data per business(. In some cases an output/employment ratio is used of a corresponding/similar NACE class as best estimation available.
CCM-investments:
Data compilation process:
The investment statistics forms the base for many categories (for example energy grids, public transport, freight transport, nuclear energy, CEP 040203). We match the approach of national accounts on investments (excluding investments in land and second hand items, and the approach to include investments in projects under construction). This statistics can both supply data for S11-S12 and for S13, as they are both included in the population. One exception to this overall approach is the investments from energy network companies. If we would include all investments, this would also include investments in gas networks. In the Netherlands most network companies own and maintain both electricity and gas networks. In order to exclude the investments from gas networks from these companies, the ratio “revenue from electricity network” over the “total revenue of gas and electricity networks” is used, as a proxy. Another complication lies within inland waterways transport versus sea transport (same for its infrastructure). As many companies (harbors and shipping companies) serve both ways of transport, a fraction is applied to all sea transport companies and harbors. To only include the part that serves the inland waterways transport.
For electric vehicles a combination has been made between transport statistics (in order to obtain information on the number of electric and non-electric vehicles and some global price information), and the investments statistics, which includes companies investments in vehicles. The electric vehicles which are included are: FEV (Full Electric Vehicle), PHEV (Plug-in Hybrid Electric Vehicle) and HEV (Hybrid Electric Vehicle). From the transport statistics we can also extract the electric vehicles purchased by households (S14), next to the ones purchased by companies (S11-S12). The investments in renewable energy production (CEP 0201) contain information from the energy statistics. The investments are based on physical data (added capacity by sector) from these statistics, multiplied with external information on investments prices per added capacity. In order to further divide these investments by NACE-category, some information from relevant subsidy schemes is used as a way to allocate the overall investments to different NACE-categories.
For investment amounts (by companies) in renewable energy (green gas, geothermal) and energy savings and energy grids (including energy efficiency, district heating networks, hydrogen, smart grids, and biofuels), microdata from various subsidy schemes is used. The microdata from these subsidies already include sector and NACE-category.
For investments in energy efficient buildings, source data from market information agencies is available by market segment. Owner-occupied housing is assigned to S14 (households), the other market segments to S11_S12 (companies). Other market segments consist of utility buildings and rental and social housing. A breakdown to NACE-category is made based on microdata from investments statistics for national accounts SUTs. Investments by company are available by detailed type of good (including insulations goods) and NACE-category.
18.5.1. Imputation - rate
Not requested for this metadata collection.
18.5.2. Data compilation - by variable and type of output
We sum up the data that follows from the microdata and the separate estimates for which the use microdata isn't suited. These are summed for all the four types of output in the questionnaire of the EGSS. We generally only consider market output, with exceptions for NACEs O and P, which we generally assume to be non-market output.
National accounts
For the relevant NACE codes that can entirely be attributed to the EGSS (like 37, 38, 39...), we use the SUT and labour accounts in order to select the statistics for these entire sectors.
COFOG
From the COFOG data it is possible to identify the environmental expenditure of the government (which equals the production value). We also know the intermediary use, thus we can calculate the gross value added. We can derive the labour statistics of the COFOG by dividing the wage sum by the average wage for the relevant government sector.
Separate estimates
We will give a few examples of the separate estimates. This is not an exhaustive list.
For instance, for the energy production we use the physical production of renewable energy and combine this with price information of the relevant energy source to calculate production value. From here we use production statistics and labour statistics to estimate the fte's used for the production of this energy.
For education for instance we use the share of education that is related to green/sustainable studies. We use this to estimate the share of output/GVA/employment that is related to the EGSS.
We also use physical statistics, like the amount of solar power or wind energy installed in a year in order to calculate the emplyoment related to installation activities.
Microdata population
For the remaining activities we have a database of companies which we link to statistics regarding production, labour and trade in order to calculate their enviromental activities. Some companies we consider to be fully within the EGSS, some of them we consider to be partially within the EGSS. We estimate this with a factor.
Description per output type EGSS:
OUTPUT
Most data is derived directly from National Accounts. Business population is not directly linked, but is based on sources that are used to produce the NA data.
GROSS VALUE ADDED (GVA)
NA-data uses supply and use tables which include data on GVA. When COFOG data is applied we calculate GVA by taking total output minus intermediate use. In some cases GVA is not available at the required level of detail ( e.g. NACE 7.1.2.x (DUTCH SBI 7.1.2.0.3), then a corresponding output/GVA ratio (of NACE 7.1.2) is used to calculate GVA. In case of the population of businesses, each business is linked to the Production Statistics which also includes GVA figures on a business level.
EXPORTS
We use several different methods. For some activities it is based on the total exports of the corresponding NACE-class. The population of businesses can be linked directly to export figures on business level. For some activities there is no (clear) export at all. For organic agriculture we use an external source.
EMPLOYMENT
In most cases we derive FTEs directly from the Labour Accounts or other source data on employment (e.g. linking the business population to employment data per business). In some cases an output/employment ratio is used of a corresponding/similar NACE class as best estimation available.
In CCM investments many out of scope categories are included in the questionnaire. For nuclear energy, energy grids, public and freight transport this is based on the investment statistics. For infrastructure this is based on COFOG/government statistics.
18.5.3. Data compilation - by NACE
We select the NACE in which the activity fits best. For instance the government data fits in NACE O, biological agriculture fits in NACE A. For the company database we use the NACE as used in our National Accounts system.
CCM investments: The microdata which is used for most categories in the questionnaire (the investment statistics, transport statistics, subsidy schemes) already includes per company a sector and a NACE category. Only for ‘renewable energy production’ and ‘energy saving measures for buildings’ a different approach is used and an allocation key is used to break down the total investments into different NACE-categories. Data from government statistics is assigned to S13.
18.5.4. Data compilation – CReMA 13B memo item
As of now we have not looked into this memo item.
18.6. Adjustment
Not relevant
18.6.1. Seasonal adjustment
Not requested for this metadata collection.
No further comments.
The environmental goods and services sector (EGSS) accounts report on an economic sector that generates goods and services produced for environmental protection or the management of natural resources.
Products for environmental protection prevent, reduce and eliminate pollution or any other degradation of the environment. Examples are electric vehicles, catalysts and filters to decrease pollutant emissions, wastewater and waste treatment services, noise insulation works or restoration of degraded habitats.
Products for resource management safeguard the stock of natural resources against depletion. Examples are renewable energy production, energy-efficient and passive buildings, seawater desalinization or rainwater recovery, and materials recovery.
EGSS accounts provide data on output and export of environmental goods and services and on the value added of and employment in the environmental goods and services sector.
In addition, the data contain information on investments for climate change mitigation (CCM). Those investments aim at reducing the emission of greenhouse gases either by source or enhancing the removal from the atmosphere. This includes both characteristic activities (such as production of renewable energy) or resource efficient goods (such as electric vehicles).
EGSS and CCM data are compiled following the statistical concepts and definitions set out in the UN System of Environmental-Economic Accounting 2012 – Central Framework.
This includes both investments by characteristic activities (such as production of renewable energy) and investments in resource efficient goods (such as electric vehicles).
20 October 2025
Environmental Goods and Service Sector:
EGSS has the same system boundaries as the European System of Accounts (ESA 2010) and consists of all environmental products within this production boundary. ESA defines production as the activity carried out under the control and responsibility of an institutional unit that uses input of labour, capital, goods and services to produce output of goods and services.
Only goods and services produced for environmental purposes are included in the scope of the environmental goods and services sector.
'Environmental purpose' means that a good or service helps either 1) preventing, reducing and eliminating pollution and any other degradation of the environment or 2) preserving and maintaining the stock of natural resources and hence safeguarding against depletion.
The EGSS statistics aim at compiling data for the following economic variables:
Output: consists of products that become available for use outside of the producer unit, any goods and services produced for own final use and goods that remain in the inventories at the end of the period in which they are produced. Apart from market output, output for own final use and non-market output, EGSS statistics also include ancillary output, comprising output intended for use within an enterprise.
Market output is to be valued at basic prices, that is, the prices receivable by the producer from the purchaser minus taxes and plus subsidies on products. Output for own final use is to be valued at basic prices of similar products sold on the market or by the total costs of production. Non-market output is to be estimated by the total costs of production. Ancillary output is measured as a total of recurrent production costs (such as intermediate consumption, compensation of employees and consumption of fixed capital) incurred by enterprises to: 1) reduce environmental pressures arising from their production process or 2) produce environmental goods or services not intended for use outside the enterprise, but instead supporting other (non-environmental) activities undertaken within the enterprise (e.g. waste management services carried out in-house). For market producers, a mark-up for net operating surplus is added to the value of the EGSS ancillary output. Gross Value Added: represents the contribution made by the production of environmental goods and services to GDP. It is the difference between the value of the output and intermediate consumption.
Employment: is measured in full-time equivalent jobs engaged in the production of output of environmental goods and services. Full-time equivalent is defined as total hours worked divided by the average annual working hours in a full-time job.
Exports: consist of sales, barter, gifts, or grants, of environmental goods and services from residents to non-residents.
Investments for climate change mitigation:
The reporting covers the capital expenditure to reduce the emissions of greenhouse gases (GHG) by source or enhance their removal from the atmosphere by sinks.
Capital expenditure includes:
For activities and products covered by the CEP:
Gross fixed capital formation (GFCF – ESA 2010 code: P51g) for climate change mitigation related characteristic activities (i.e. GFCF for the production of specific services related to climate change mitigation)
GFCF in specific and cleaner and resource efficient goods related to climate change mitigation, unless they are already included in GFCF by CCM (characteristic) activities
and final consumption (ESA 2010 code: P3) in specific and cleaner and resource efficient goods related to climate change mitigation.
For activities and products relevant for CCM but outside the scope of CEP:
GFCF for the production of nuclear energy and for R&D related to nuclear energy
GFCF for the transmission and distribution of energy, in particular electricity
GFCF for the production of low carbon transport activities
GFCF in transport infrastructure for low carbon transport activities.
Where:
GFCF for climate change mitigation characteristic activities is broken down by corporations, government and households together with non-profit institutions serving households (NPISH).
GFCF for specific and cleaner and resource efficient goods, mitigating climate change, is broken down by corporations, government and households together with NPISH
Final consumption of specific and cleaner and resource efficient goods, mitigating climate change, is broken down by government and households together with NPISH.
Council Regulation (EEC) No 696/93 of 15 March 1993 on the statistical units for the observation and analysis of the production system in the Community describes the different statistical units of the production system.
The recommended statistical unit for the data collection and compilation of private corporations is the establishment. For general government, households and NPISH, the recommendation is to use institutional units and groupings of units as defined in the European System of Accounts (ESA 2010).
The statistical population is the national economy as defined in SEEA CF 2012 and the European System of Accounts (ESA 2010). It includes all economic activities undertaken by resident units.
The Netherlands
The reference period for EGSS data (including CCM investments) is the calendar year.
Most EGSS data is derived directly from National Accounts, COFOG or other official statistics.
The population of businesses is of lower quality. It is time consuming to keep the population up to date, furthermore the environmental share of businesss is constant so we do not measure (within company) development over time accurately. Furthermore allocating environmental shares (and CEP distribution) to businesses is quite subjective and a rough estimate.
Most CCM data is derived from National Accounts, Investments statistics, vehicle statistics and energy statistics.
As this is the first year of publication of CCM data, the data compilation will be improved in the upcoming years. Some existing results can be further improved, and missing indicators will be added. Some examples of indicators which are not included in the current publication are: bicycle lanes, electrolysers, home batteries, investments related to reducing other GHG than CO2. Also Near Zero Energy Buildings as a whole are not included yet, only the energy reducing measures such as isolation.
Output, gross value added, exports and CCM investments are measured in million units of national currency. Employment is measured in full time equivalents (i.e., full time equivalent jobs).
Scope EGSS:
The scope of the Dutch EGSS has been determined in the past by identifying (16) different environmental activites, these still form the basis of the Dutch EGSS. However, the EGSS has developed since and the EGSS operational lists and EGSS handbook have been developed and improved. The operational list of activities is used to identify missing activities. In some cases these activities are excluded on purpose, either because they are economically irrelevant and not worth the effort to include them (a lot of work for an insignificant improvement, e.g. inspection of vehicles on air emissions), or we lack the data sources to estimate them. However, we continuously try to improve the EGSS by identifying new data sources and including new activities.
Additional data is used to determine the share of environmental activities. For instance, for education data on the number of students enrolled in an environmental study was used (and compared to total number of students), for organic agriculture the SKAL-certification (i.e. organic farming certificate) was used which shows the hectares used for organic agriculture (compared to total hectares in agriculture). Furthermore, a business population is used to identify certain environmental activities (see source data paragraph). The environmental share of these businesses (and CEP-subdivision) is based on company year reports, websites and is basically and expert guess.
No additional surveys are held to produce the Dutch EGSS data. Data is derived from existing data sources.
data compilation process:
National Account data forms that basis of the Dutch EGSS for all economic variables. Supply and use tables provide market output and gross value added figures for several NACE classes (e.g. NACE A01, E36, E37, E38, E39, M71.2, S94.996) while Labour Accounts data is used to provide employment figures. In some cases (e.g. A01 agriculture) additional sources (e.g. data on organic farming certificates) are used to estimate the environmental share (ha organic agriculture / ha total agriculture) of a specific NACE class.
COFOG data is used to derive economic variables (output, employment and gross value added) for environmentally related government activities. No export of environmentally related government activities is measured.
A part of the remaining environmental activities, that cannot be linked directly to NA data, is estimated by the so called micro-approach. A population of businesses (mainly activities related to sustainable energy, construction, consultancy and engineering) is set up and linked to the Dutch Business Register, statistics on employment (SWL) and International Trade Statistics.
For some environmental activities, such as education, additional data from external sources is used to provide more accurate estimates. In a few cases some other approaches were used, e.g. to estimate export figures of specific goods a selection of CN-codes was made and linked to international trade data.
Share:
In most cases the same environmental share is applied to all economic variables. CEP-classification shares differ for each company, so does their corresponding NACE class.
It depends on the method used whether the share is fixed over time. E.g. education and agriculture have a changing share over time (and are updated yearly). However, the environmental share of the business population has been fixed over time. However, we are looking for a method to allow for changing environmental shares for companies over time. However, it is an impossible task (time consuming) to check and update the environmental shares of all companies (>2000) year-to-year.
Shares in the micro-approach are updated every 3 years. Shares related to other activities such as agriculture and education are updated annually.
Description:
OUTPUT
Most data is derived directly from National Accounts. Business population is not directly linked, but is based on sources that are used to produce the NA data.
GROSS VALUE ADDED (GVA)
NA-data uses supply and use tables which include data on GVA. When COFOG data is applied we calculate GVA by taking total output minus intermediate use. In some cases GVA is not available at the required level of detail ( e.g. NACE 7.1.2.x (DUTCH SBI 7.1.2.0.3), then a corresponding output/GVA ratio (of NACE 7.1.2) is used to calculate GVA. In case of the population of businesses, each business is linked to the Production Statistics which also includes GVA figures on a business level.
EXPORTS
We use several different methods. For some activities it is based on the total exports of the corresponding NACE-class. The population of businesses can be linked directly to export figures on business level. For some activities there is no (clear) export at all. For organic agriculture we use an external source.
EMPLOYMENT
In most cases we derive FTEs directly from the Labour Accounts or other source data on employment (e.g. linking the business population to employment data per business(. In some cases an output/employment ratio is used of a corresponding/similar NACE class as best estimation available.
CCM-investments:
Data compilation process:
The investment statistics forms the base for many categories (for example energy grids, public transport, freight transport, nuclear energy, CEP 040203). We match the approach of national accounts on investments (excluding investments in land and second hand items, and the approach to include investments in projects under construction). This statistics can both supply data for S11-S12 and for S13, as they are both included in the population. One exception to this overall approach is the investments from energy network companies. If we would include all investments, this would also include investments in gas networks. In the Netherlands most network companies own and maintain both electricity and gas networks. In order to exclude the investments from gas networks from these companies, the ratio “revenue from electricity network” over the “total revenue of gas and electricity networks” is used, as a proxy. Another complication lies within inland waterways transport versus sea transport (same for its infrastructure). As many companies (harbors and shipping companies) serve both ways of transport, a fraction is applied to all sea transport companies and harbors. To only include the part that serves the inland waterways transport.
For electric vehicles a combination has been made between transport statistics (in order to obtain information on the number of electric and non-electric vehicles and some global price information), and the investments statistics, which includes companies investments in vehicles. The electric vehicles which are included are: FEV (Full Electric Vehicle), PHEV (Plug-in Hybrid Electric Vehicle) and HEV (Hybrid Electric Vehicle). From the transport statistics we can also extract the electric vehicles purchased by households (S14), next to the ones purchased by companies (S11-S12). The investments in renewable energy production (CEP 0201) contain information from the energy statistics. The investments are based on physical data (added capacity by sector) from these statistics, multiplied with external information on investments prices per added capacity. In order to further divide these investments by NACE-category, some information from relevant subsidy schemes is used as a way to allocate the overall investments to different NACE-categories.
For investment amounts (by companies) in renewable energy (green gas, geothermal) and energy savings and energy grids (including energy efficiency, district heating networks, hydrogen, smart grids, and biofuels), microdata from various subsidy schemes is used. The microdata from these subsidies already include sector and NACE-category.
For investments in energy efficient buildings, source data from market information agencies is available by market segment. Owner-occupied housing is assigned to S14 (households), the other market segments to S11_S12 (companies). Other market segments consist of utility buildings and rental and social housing. A breakdown to NACE-category is made based on microdata from investments statistics for national accounts SUTs. Investments by company are available by detailed type of good (including insulations goods) and NACE-category.
National Account data forms the basis of the Dutch EGSS for all economic variables. Supply and use tables provide market output and gross value added figures for several NACE classes (e.g. NACE A01, E36, E37, E38, E39, M71.2, S94.996) while Labour Accounts data is used to provide employment figures. In some cases (e.g. A01 agriculture) additional sources (e.g. data on organic farming certificates) are used to estimate the environmental share (ha organic agriculture / ha total agriculture) of a specific NACE class.
COFOG data is used to derive economic variables (output, employment and gross value added) for environmentally related government activities. No export of environmentally related government activities is measured.
A part of the remaining environmental activities, that cannot be linked directly to NA data, is estimated by the so called micro-approach. A population of businesses (mainly activities related to sustainable energy, construction, consultancy and engineering) is set up and linked to the Dutch Business Register, statistics on employment (SWL) and International Trade Statistics.
The population of businesses has been revised and updated recently (as we try to do every 3 years). This was mainly done by using a webcrawl to identify environmental businesses that were not included before. As a result, the whole time series has been revised.
For some environmental activities, such as education, additional data from external sources is used to provide more accurate estimates. In a few cases some other approaches were used, e.g. to estimate export figures of specific goods a selection of CN-codes was made and linked to international trade data.
For CCM the main source of information is the Investment-statistics, in which companies provide detailed insight in different type of investments from their company. From these data it is possible to derive for a complete NACE class the relevant investments (no investments in land included, and no second-hand, to comply with National Account rules on investments). For example in the case of freight transport per rail we use NACE 49.20.
Other important statistics entail the energy statistics, used for CEP 0201. In this case the investments are based on physical data (added capacity). This is combined with external information on investments prices per added capacity. CEP 0101 includes electric vehicles. To estimate these investments we used transport statistics, which gives the number of newly purchased (electric) vehicles and some information on the average price.
For investment amounts (by companies) in renewable energy (green gas, geothermal) and energy savings and energy grids (including energy efficiency, district heating networks, hydrogen, smart grids, and biofuels), microdata from various subsidy schemes is used. For some subcategories (charging stations) external information is used.
COFOG data/government statistics is used mainly for investments in “Low carbon transport infrastructures”, both for inland waterways and rail infrastructure.
Investments in energy efficient buildings are based on detailed market information from several secondary sources on production activities of the construction sector related to insulation of buildings. Data is available on purchases of insulation materials and insulation glass, and on installation costs for application in different market segments (i.e. owner-occupied housing, rental and social housing, utility buildings, new and existing buildings).
The environmental goods en services data for the Netherlands are released annually.
Statistics Netherlands disseminates data with a delay of about 12 months after the end of the reference year
Not applicable
Comparable time series are available starting with 2001 reference year. Data were classified according to the CEPA 2000 and CReMa classifications; from 2023 onwards, according to the CEP classification.
