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    Documentation of statistics: Job Vacancies

    Contact info, Labour Market, Social Statistics , Monica Wiese Christensen , +45 21 73 34 69 , MWC@dst.dk , Get documentation of statistics as pdf, Job Vacancies 2026 Quarter 1 , Previous versions, Job Vacancies 2025 Quarter 4, Job Vacancies 2025 Quarter 3, Job Vacancies 2025 Quarter 2, Job Vacancies 2025 Quarter 1, Job Vacancies 2024 Quarter 4, Job Vacancies 2024 Quarter 3, Job Vacancies 2024 Quarter 2, Job Vacancies 2024 Quarter 1, Job Vacancies 2023 Quarter 4, Job Vacancies 2023 Quarter 3, Job Vacancies 2023 Quarter 2, Job Vacancies 2023 Quarter 1, Job Vacancies 2022 Quarter 4, Job Vacancies 2022 Quarter 3, Job Vacancies 2022 Quarter 2, Job Vacancies 2022 Quarter 1, Job Vacancies 2021 Quarter 4, Job Vacancies 2021 Quarter 3, Job Vacancies 2021 Quarter 2, Job Vacancies 2021 Quarter 1, Job Vacancies 2020 Quarter 4, Job Vacancies 2020 Quarter 3, Job Vacancies 2020 Quarter 2, Job Vacancies 2020 Quarter 1, Job Vacancies 2019 Quarter 4, Job Vacancies 2019 Quarter 3, Job Vacancies 2019 Quarter 2, Job Vacancies 2019 Quarter 1, Job Vacancies 2018 Quarter 4, Job Vacancies 2018 Quarter 3, Job Vacancies 2018 Quarter 2, Job Vacancies 2018 Quarter 1, Job Vacancies 2017 Quarter 4, Job Vacancies 2017 Quarter 3, Job Vacancies 2017 Quarter 2, Job Vacancies 2017 Quarter 1, Job Vacancies 2016 Quarter 4, Job Vacancies 2016 Quarter 3, Job Vacancies 2016 Quarter 2, Job Vacancies 2016 Quarter 1, Job Vacancies 2015 Quarter 4, Job Vacancies 2015 Quarter 3, Job Vacancies 2015 Quarter 2, Job Vacancies 2015 Quarter 1, Job Vacancies 2014 Quarter 4, The statistic illustrate the quarterly development in number of job vacancies and the job vacancy rate. The statistics are based on both survey and register data. Survey data are used for workplaces in the private sector, whereas register data are used for workplaces in the public sector., The statistics can be used as a labour market indicator together with other indicators. The Job Vacancy Statistics are subject to EU regulation and are compiled according to the same guidelines in all EU Member States., Statistical presentation, The statistics illustrate the quarterly development in the real number of job vacancies and the job vacancy rate. The job vacancy rate is calculated as the number of job vacancies in relation to the sum of job vacancies and occupied posts., The statistics are broken down by industry (economic activity), size, region and sector., Read more about statistical presentation, Statistical processing, For the private sector: Data are collected via electronic questionnaires on https://virk.dk/ as a sample of approximately 9,000 workplaces. Before 2026, when only industry groups B-N were covered, the sample consisted of approximately 7,000 workplaces. Data are checked for errors and missing values are imputed before grossing-up to a population total., For the public sector: Register data are used primarily from https://www.jobnet.dk. Based on a comprehensive survey, partly financed by EUROSTAT, models have been established that make register data from https://www.Jobnet.dk compatible with the statistical requirements., Read more about statistical processing, Relevance, The users of the statistics are primary the press, private companies, private persons and Eurostat. The statistic is used in analysis about the demand for labour and in the public debate. Data on job vacancies are collected in accordance with similar guidelines by all EU Member States, which implies that the statistics are suitable for comparing the development in the number of job vacancies across the EU Member States., Read more about relevance, Accuracy and reliability, For the private sector: As with all other sample-based statistics, there is some uncertainty associated with the estimates. As in other EU Member States, the coefficient of variation (CV), which is the standard deviation in relation to the estimate, is used in calculating the uncertainty. For the total number of occupied posts, the coefficient of variation (CV) is normally below 1 percent, while for the total number of job vacancies it is 2-5 percent. For industry groups and size groups, the CV is relatively high. This is primarily due to the large variations between the reported number of job vacancies and the many reports with zero job vacancies., For the public sector: Since public workplaces are legally obliged to post job vacancies on https://www.jobnet.dk, the administrative data source is assumed to be close to full coverage for the public labour market. However, there will be workplaces that do not post vacancies on https://www.jobnet.dk, even though this is legally required. Methodological decisions have been made based on assumptions in the models for handling intended job vacancies and handling presumed misreporting, and calibrated on the basis of the test survey in May 2024 financed by EUROSTAT. The number of occupied posts is measured as the number of occupied posts at the end of the quarter, obtained from SBR data, and therefore not on the counting date., Read more about accuracy and reliability, Timeliness and punctuality, Data are released around 75 days after the reference quarter., Read more about timeliness and punctuality, Comparability, As of the 1st quarter of 2026, the statistics changed from Dansk Branchekode 2007 (DB07, Danish subdivision of the EU classification NACE Rev 2) to Dansk Branchekode 2025 (DB25, defined on the new EU classification NACE Rev. 2.1)., From 2026 onwards, the population sample is drawn based on DB25. In 2026, the sample population was also expanded from covering industries B-N (DB07), corresponding to B-O (DB25), to covering industries B-TUV (DB25). This implies a transition from partial to full industry coverage, with the exception of industry group A (Agriculture, Forestry and Fishing). The number of job vacancies by industry in the period 2010-2025 has been converted from DB07 to DB25 using a conversion matrix that takes quarter, enterprise size and industry into account., In connection with the conversion, industry G has been split into three industries: G, J and TUV. The former partial industry coverage did not include industry TUV. Units belonging to industry TUV have therefore been omitted from the conversion. In 2025, this led to a reduction of the population by 3,497 units, corresponding to 8.5 percent of the old industry G. As a result, the archived pre-2026 tables and the updated post-2026 tables in StatBank Denmark will not have the same totals., Read more about comparability, Accessibility and clarity, These statistics are published quarterly in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Job vacancies, . For further information, go to the , subject page, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/job-vacancies

    Documentation of statistics

    Databank of basic data

    Here you can read a general description of the databank of basic data in Denmark’s Data Portal (DDP)., Basic data (also called ‘DDP basic data’ or ‘data in the databank of basic data in Denmark’s Data Portal’) refers to the microdata that DDP offers to external users for research and statistical purposes. Statistics Denmark (DST) has collected a wide range of register data with historical information in a bank of basic data within the DDP App. The various registers come from both external sources and internal statistical offices. Thematically, the data cover a broad spectrum, and the statistical unit may be individuals, addresses, enterprises, library loans, motor vehicles, and more. All basic data must comply with a set of standards for formats and naming etc., The data undergo extensive processing before being placed in the bank of basic data. There are several reasons for this:, Standardization saves users time-consuming preparation: by ensuring uniform data, external users can avoid a significant amount of manual data processing., Key variables must be standardized to enable data linkage: combining data across years and registers requires a common standard for key variables., Key variables must be standardized to enable pseudonymization: data can only be pseudonymized correctly if variables follow fixed standards and naming., Purpose of the databank of basic data, The purpose of the databank of basic data is to collect microdata for research and analysis in a way that makes it easy and straightforward to make microdata available to researchers., Content and use of the databank of basic data, DDP aims to ensure that all DST data from the official statistical program are available as basic data. This primarily includes microdata related to individuals, enterprises, or addresses., DST also holds data that are not part of the official statistical program but which DDP has received or collected for various reasons. This type of data is also made available as basic data to support reuse, rather than requiring the statistical offices to design customized extracts for the users., To qualify as basic data, a number of conditions must be met. For certain data, special considerations regarding data confidentiality, funding arrangements or data quality may influence how the data can be used. DST enters into agreements with other authorities (and data owners) for regular deliveries of register data that can be made available to researchers. These data are also placed in the databank of basic data. Read more under , Data from other data providers for the databank of basic data, ., Before data may be used on the research server, variables that can directly identify individuals undergo pseudonymization. This means that all variables containing identification information such as CPR numbers, CVR numbers, addresses, and property numbers, are recoded in a pseudonymization process before being transferred to the user’s project. Each register includes a marking of which variables must be pseudonymized. When new variables are added to a register, DDP assesses, together with the data owner and based on the data confidentiality policy, whether the variables must be pseudonymized before the data can be released for research and analysis., Applying the procedures and guidelines described, ensures that data stored in the databank of basic data and presented within DST follow a standardized format. This makes it easy for researchers to access the data and navigate the available datasets. Read more about where to find documentation for basic data on the page , Documentation of data, .

    https://www.dst.dk/en/TilSalg/data-til-forskning/generelt-om-data/grunddatabanken

    Non-standard forms of employment

    How many people work on a temporary contract, for only a few hours per week, through digital platforms, or have more than one job? Non-standard forms of employment refer to work arrangements that differ from the traditional permanent full-time position, as well as from self-employed individuals with employees. Here, you can gain insight into how widespread selected atypical forms of employment are among employed people in Denmark and follow developments over time., Non-standard forms of employment , includes forms of work that differ from the traditional permanent full-time position and from traditional self-employment with employees. Examples include temporary employment, digital platform work, temp work, and holding multiple jobs simultaneously. A defining characteristic is that the connection to the labor market is typically less stable than in standard full-time employment., Temporary Employment , Is a paid job with a fixed or limited duration. This means that the job either ends at a predetermined date or upon completion of a specific task or period, such as a project or the temporary replacement of an absent employee. Temporary employment therefore differs from permanent jobs, which do not have a predetermined end date., Economically active indicator , An enterprise is considered economically active if it is assessed to carry out economic activity of a certain scale. This may, for example, be the case if the labour input corresponds to at least 0.5 full-time equivalent (FTE) employment, or if the enterprise's turnover, purchases of goods and services, imports, exports, value added, or total assets exceed specified thresholds., Prevalence and development in non-standard forms of employment, The figure shows the prevalence and development of selected forms of non-standard forms of employment. Five indicators are included, each describing a different type of employment and presented as a share of either all employed persons or employees only. , The indicators are not mutually exclusive, meaning that the same individual may be included in more than one indicator., Read about the individual indicators in the methodology documentation (pdf) in danish,  , In Statbank Denmark, you can find more data on Non-standard forms of employment (per cent) (ATYP001), More about the figure, Last update, 9.6.2026, Next update, 26.11.2026, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Employed persons with multiple jobs and fee-based income, Here you can see the share of employed persons with multiple concurrent jobs or fee-based income (multiple job-holders). This includes, among others, employees with a secondary job or fee-based work, as well as self-employed persons who have additional work alongside their business., In Statbank Denmark, you can find more data on Employed persons (per cent of employed persons) (ATYP013), More about the figure, Last update, 9.6.2026, Next update, 26.11.2026, Source data, Starting from the publication on April 28, 2015, RAS is based on the Labor Market Account (AMR_UN), which is a longitudinal register. In this context, RAS has been revised back to November 2008. At the same time, the dating of the statistics was changed, so that it is now dated according to the reference point at the end of November. This means that the most recent assessment is labeled as the end of November 2024, whereas previously it would have been labeled 2025. , Data in AMR_UN come from a number of other sources:, The eIncome Register, The Business Statistics Register, The Statistics on People Receiving Public Benefits, The Education Statistics, The Income Statistics, The Population Statistics, The Maternity and Sickness Benefits Statistics, The Occupational Classification Module, Before 2008, the basic data for employees came from the central information form register at SKAT, and these data were not longitudinal., Read more about sources, method and quality in the documentation of statistics on Register-Based Labour Force Statistics, Self-employed without employees, The figure shows the number and income distribution of self-employed persons without employees, broken down by level of economic activity. Income is measured as total pre-tax income in Danish kroner., In Statbank Denmark, you can find more data on Self-employed (primary work) without employees (ATYP021), More about the figure, Last update, 9.6.2026, Next update, 26.11.2026, Source data, Starting from the publication on April 28, 2015, RAS is based on the Labor Market Account (AMR_UN), which is a longitudinal register. In this context, RAS has been revised back to November 2008. At the same time, the dating of the statistics was changed, so that it is now dated according to the reference point at the end of November. This means that the most recent assessment is labeled as the end of November 2024, whereas previously it would have been labeled 2025. , Data in AMR_UN come from a number of other sources:, The eIncome Register, The Business Statistics Register, The Statistics on People Receiving Public Benefits, The Education Statistics, The Income Statistics, The Population Statistics, The Maternity and Sickness Benefits Statistics, The Occupational Classification Module, Before 2008, the basic data for employees came from the central information form register at SKAT, and these data were not longitudinal., Read more about sources, method and quality in the documentation of statistics on Register-Based Labour Force Statistics, Involuntary part-time employment, The figure shows the share of employed persons who report working part-time because they have been unable to find a full-time job., In Statbank Denmark, you can find more data on Involuntary part-time work (15-74-year-olds) (per cent and number) (ATYP041), More about the figure, Last update, 9.6.2026, Next update, 9.3.2027, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Part-time work of less than 15 hours per week, Here you can see the development in the share of employees with a weekly working time of less than 15 hour. The measure includes working hours from all employee jobs., In Statbank Denmark, you can find more data on Employees (per cent) (ATYP083), More about the figure, Last update, 9.6.2026, Next update, 26.11.2026, Source data, Starting from the publication on April 28, 2015, RAS is based on the Labor Market Account (AMR_UN), which is a longitudinal register. In this context, RAS has been revised back to November 2008. At the same time, the dating of the statistics was changed, so that it is now dated according to the reference point at the end of November. This means that the most recent assessment is labeled as the end of November 2024, whereas previously it would have been labeled 2025. , Data in AMR_UN come from a number of other sources:, The eIncome Register, The Business Statistics Register, The Statistics on People Receiving Public Benefits, The Education Statistics, The Income Statistics, The Population Statistics, The Maternity and Sickness Benefits Statistics, The Occupational Classification Module, Before 2008, the basic data for employees came from the central information form register at SKAT, and these data were not longitudinal., Read more about sources, method and quality in the documentation of statistics on Register-Based Labour Force Statistics, Temporary employment, The figure shows the share of employees in temporary employment, broken down by age groups., In Statbank Denmark, you can find more data on Temporary employment (15-74-year-olds) (per cent and number) (ATYP051), More about the figure, Last update, 9.6.2026, Next update, 9.3.2027, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Reasons for temporary employment, Here you can see the reasons for temporary employment among employees, broken down by age groups. Reasons may include structurally time-limited positions such as internships and project-based contracts, the individual’s own preference for temporary work, or the inability to obtain permanent employment., In Statbank Denmark, you can find more data on Temporary employment (15-74-year-olds) (per cent) (ATYP053), More about the figure, Last update, 9.6.2026, Next update, 9.3.2027, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Digital platform work, The table shows the share of employed persons who have performed digital platform work within the past month. Digital platform work refers to work tasks mediated through digital platforms or apps., Share of employed persons who have performed digital platform work within the past month, Unit: , Per cent, Has worked on digital platforms, Has not worked on digital platforms, 2024Q3, 0.3, 99.7, In Statbank Denmark, you can find more data on Employees (15-74-year-olds) (per cent) (ATYP091), More about the figure, Last update, 9.6.2026, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Reasons for temp work, The figure shows the reasons for temp work, broken down by age groups. Individuals are classified according to whether they work as temp workers because they have been unable to obtain a permanent job or because they have chosen to do so themselves., In Statbank Denmark, you can find more data on Temp workers (15-74-year-olds) (per cent) (ATYP063), More about the figure, Last update, 9.6.2026, Next update, 9.3.2027, Source data, The Labour Force Survey is quarterly based on a stratified sample. The sample was reduced in the 1st quarter of 2016. The reduction will be implemented successively and the sample size will be reduced from 40,532 individuals to 34.320 persons aged 15 to 74 years in the 1st quarter of 2017 when the reduction is fully implemented. Until the year 2020 the LFS has been collected at the individual level for 15-74-year-olds. From 2021 the population has changed to also include the age group from 75-89 years. On a quarterly basis the sample has thus increased from 34,320 people to 36,020 people. , In 2022q1, a new stratification was introduced in the LFS. Register data on employment and register unemployment are utilized to a greater extent, in order to obtain a greater number of responses in some of the groups that suffer from low response rates. For starters, the population is divided into four groups: 1) in stable employment, 2) in registered unemployment, 3) neither in stable employment nor registered unemployment and 4) persons aged 75 to 89. In addition, groups 1 and 3 are divided into the age groups 15-29, 30-64 and 65-74. This results in eight different strata, which are used in the sample selection from 2022q1 onwards. As the LFS consists of four panels, each appearing for six quarters, this stratification was fully implemented in Q2 2023., The sample is weighted to represent the population as it was at the end of the previous quarter. Different administrative resources are used to select the sample. Administrative sources are also used to obtain various background information on the people interviewed, for example on educational level or workplace., These registers (among others) are being used for the Labour Force Survey: , Central Population Register (CPR) , Population Register , The Register of Labour Market Statistics (RAM) , Register based-labour force statistics (RAS) , Education classification (DISCED) , Employees, Register of income, Business statistics register, Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), On the statistics – documentation, sources and method, Gain an overview of the purpose, contents and quality of the statistics. Learn about the data sources of the statistics, the contents of the statistics and how often they are published., See the documentation of statistics to learn more:, Labour Force Survey (LFS), The purpose of the Labour Force Survey (LFS) is giving a description of the labour market status of the population. The LFS gives insight into how many people are employed, unemployed or outside the labour force (economically inactive). The LFS also manages to measure information like how many people are working part time; how many hours men in their 30s or 40s usually work; or how many elderly people outside the labour market would like to have a job. The LFS has been conducted yearly since 1984, and from 1994 the survey has been conducted continuously throughout the year., Read more about sources, method and quality in the documentation of statistics on Labour Force Survey (LFS), Labour Market Account, New Labour Market Account concerning the population´s labour market status have been developed by Statistics Denmark. , The primary purpose of the Labour Market Accounts (LMA) is to provide a complete overview of the population´s labour market status compiled in terms of full-time persons, covering a given period of time or a given point-in-time., Read more about sources, method and quality in the documentation of statistics on Labour Market Account, Register-Based Labour Force Statistics, The purpose of the Register-Based Labour Force Statistics (RAS) is to measure the population’s primary attachment to the labour market. This attachment is recorded at the end of November and compiled once a year. The first RAS compilation was made at the end of November 1980., Read more about sources, method and quality in the documentation of statistics on Register-Based Labour Force Statistics, Need more data on Non-standard forms of employment?, More detailed figures are available, for example for multiple job holders by sex, age, educational attainment, or municipality of residence, as well as temp work by industry. There are also statistics linking employee jobs with immigrant background., Go to the StatBank, Contact, Ida Frederikke Mathiesen, Phone: +45 21 49 48 53, Mail: , ifm@dst.dk

    https://www.dst.dk/en/Statistik/emner/arbejde-og-indkomst/befolkningens-arbejdsmarkedsstatus/atypisk-beskaeftigelse

    Subject page

    Certification of users

    All users working with data in one of Statistics Denmark’s microdata schemes must achieve certification. The certification ensures that everybody knows the data security rules under Statistics Denmark’s microdata schemes and feels safe using and transferring data. To ensure continued high focus on the data security rules, all users must subsequently achieve re-certification once a year.,  , Certification in practice, In practice, the certification takes place via DDP App, where you must pass a test with questions on the data security rules described in , Denmark's Data Portal's data security rules under the microdata schemes (pdf), . It is a good idea to read the rules before you start. You have three attempts per day to pass., See the video guide for user certification (in Danish), This is how you do it:, Log into DDP App with your three/four-character ident and password., On your landing page, select the window ‘Learning and certification’. , Then select the tab ‘Certifications’. If it does not drop down automatically, click the small blue arrow., Answer the certification questions by clicking ‘Start certification’ and ‘OK’ in the info box that pops up., Answer the questions by clicking the option you believe to be correct., When you have answered all the questions, you click the button ‘Submit answer’, which has turned blue meanwhile., If you answer all ten questions correctly, you have passed the certification and you are considered able to handle data in accordance with our data security rules., Under ’Result’, your status will be indicated as ’Passed’, and a green info box appears with the text ’Congratulations, you have passed’., Under ’Resultat’ vil din status figurere som ’Bestået’, og der vises en grøn infoboks med teksten ’Tillykke, du har bestået’. , If you do not answer all ten questions correctly, you can see under ’Result’ how many questions you answered incorrectly in your attempt and how many remaining attempts you have. Furthermore, a red info box appears with the text ‘Sorry, you have not passed’., a) If you have more attempts left and want to re-take the test, press ’Certification front page’ and start over. Note that you have three attempts per day and that the questions change from time to time. Consider re-visiting the data security rules, before you try again., b) If you do not have any attempts left, your access to your projects will be locked for 24 hours. The small watch icon indicates when the 24 hours are up. After that, you can take the test again., The certification questions, The test contains questions about the data security rules (, data security rules under the microdata schemes (pdf), ). Since Statistics Denmark’s data security rules may differ from the practice in other institutions, it is important to read and know the rules under the microdata schemes. Knowing the rules is also the basis for answering the ten certification questions correctly. , Read more about the data security rules under Rules on transfer of analysis results , The questions are about access to researcher machines, pseudonymisation, transfer rules and working in general with data. Below you will find an example of a question that you can encounter in the certification test:, Question 1:, You have collected a survey that you are working on locally. You have sent the survey to Statistics Denmark to have the option of linking the survey with register data on the researcher server. Which is the correct statement?, Reply options:, a. You are allowed to download/transfer microdata from the survey that you have uploaded yourself., b. The only microdata you are not allowed to transfer, is microdata provided by Statistics Denmark to your project., c. Retrieval of microdata is never allowed regardless of data source.

    https://www.dst.dk/en/TilSalg/data-til-forskning/brugeradgang/certificering-af-brugere

    Registers and reference types

    Statistics Denmark has gathered a vast series of historical register data in our databank of basic data, which users can access via the platform DDP App. Denmark’s Data Portal manages the databank of basic data and handles access to the platform, support, etc. Most registers in the databank are updated at least once a year in connection with release of the register-based statistics (, see Scheduled releases, ). , The data safari and the List of registers and variables (below) both show the registers in DDP App, and here you can see variables for the individual registers. The documentation of variables is available in Statistics Denmark’s , documentation system, ., Go to Data safari , Go to List of registers and variables (in Danish),  , Overview of rerun registers (in Danish), Genkørte registre 2025-4. kvt (pdf), Genkørte registre 2025-3. kvt (pdf), Genkørte registre 2025-2. kvt (pdf), Genkørte registre 2025-1. kvt (pdf), Genkørte registre 2024-4. kvt (pdf), Genkørte registre 2024-3. kvt (pdf), Genkørte registre 2024-2. kvt (pdf), Genkørte registre 2024 - 1. kvt (pdf), Genkørte registre 2023 - 4. kvt (pdf), Genkørte registre 2023 - 3. kvt (pdf), Genkørte registre 2023 - 2. kvt (pdf) , Genkørte registre 2023 - 1. kvt (pdf), Genkørte registre 2022 (pdf),  , Reference types, Registers in the basic data overview are compiled by means of different reference types. Next to each register in the basic data overview, you can see which reference type a register has: ’Status’, ’Statusperiode’ (status period), ’Forløb’ (longitudinal) or ’Hændelse’ (incident)., Status, The reference type shows the status for a given date. For example, LONN (structure of earnings), which shows what a citizen earns as of the register date (e.g. 31 December 2021). Or BEF, which shows the population as of the quarter date (including status of residence, age, family, etc.)., Data definition: Clear status as of a given date. The population delimitation and all data content is focused on the date., Status period, This reference type shows the period status, where the population is delimited as of a given date, but the variables contain summed up data for a specific period. For example, IND, which contains the labour income for a year (the period appears from ’Opdateringsfrekvens’ (update frequency) in the basic data overview). Other examples of status period registers: PERSBEST (board members and managers), MFR (medical birth register), HANDICB (financial support for disability cars), DMRB (motor vehicles). It is not always easy to see what is being summed up., Data definition: The population delimitation is made as of a given date, but the content of the variables is accumulated over a given period. The period cannot be deduced from dates in microdata, but from the indicated period (shown under ‘Opdateringsfrekvens’ (update frequency)) – meaning that content in for example amounts, volumes, quantities etc. is aggregated over the indicated period (e.g. a quarter, a year)., Longitudinal, Here, data covers a longitudinal study. There will always be just one version of the register available. For example, UDD, which contains Highest educational attainment. Or BEFADR, which is an address key register (where e.g. 1.4m addresses changed key on 1 January 2007 in connection with the local government reform). When a longitudinal register is updated, the individual dataset is updated. This is why there is always only one dataset for a longitudinal register., Data definition: The definition of longitudinal data is that data contains a start date and an end date., Incident, Here, data covers an incident. For example, UDFK, which contains primary and lower secondary school marks (does not include a date but a school year), or OPHGIN (basis of right of residence for immigrants). When a longitudinal register is updated, the individual dataset is updated with new incidents. This is why there is always only one dataset., Data definition: The definition of incidents is first and foremost that data contains a date - only one date - for the occurrence of the incident, and will usually also have one incident type attached., Documentation for the use of registers and data packages, Statistics Denmark has prepared a memo describing the coherence between several of the most used registers in Statistics Denmark’s microdata scheme and their connection with the published statistics., The social statistics registers in Statistics Denmark consist of comprehensive data collections, which have been built and extended since the early 1980s. Data is of high quality and comprises the whole population. This gives the users of data unique possibilities of analysis, allowing them to analyse both status at a given point in time and the development over time., The memo is primarily intended for researchers, analysts and other users of microdata who want to obtain deeper insight into the quality of the coherence between the different registers. , Read more on Documentation for the use of registers (in Danish), Datapackages (pdf - in Danish), Especially on the Data Warehouse for Business Statistics, In January 2024, Statistics Denmark launched the new Data Warehouse for Business Statistics – a significant extension and improvement of the existing business registers. , The new warehouse ensures wider and better access to anonymised data on enterprises and facilitates extraction of unique data by linking data across more statistical registers. The data warehouse also facilitates linking of business statistics and social statistics at micro level, the so-called ‘Linked Employer-Employee Data’ (LEED). , Read more in , this brochure (pdf), or see , the presentationen of The Data Warehouse for Business Statistics on 30 November 2023 (pdf), .

    https://www.dst.dk/en/TilSalg/data-til-forskning/generelt-om-data/registre-og-referencetyper

    Prices and price agreements

    The price of a Denmark's Data Portal's assignment is based on the time it takes to solve the part elements of the assignment. We have two types of price agreements: , fixed-price agreements and framework agreements, . You can also commission a combined fixed-price and framework agreement. Furthermore, you will be paying rent for disk space for active projects on Statistics Denmark’s servers. If you have your own-hosted server set up at Statistics Denmark, you must pay for the set-up and for routine maintenance., Table 1: Hourly rates and renting of disk space, Rates 2026,  , Public institutions*, Private institutions, Pricemodel for existing projects, Hourly rates, DKK 1.674 excl. VAT, DKK 2.077 excl. VAT, Pricemodel for new projects, Data packages per unit per year, DKK 4.400 excl. VAT, DKK 5.500 excl. VAT,  , Project access per unit per year, DKK 700 excl. VAT, DKK 900 excl. VAT,  , Hourly rates, DKK 1.100 excl. VAT, DKK 1.400 excl. VAT, Renting of disk space, DKK 10,8 excl. VAT per 5 Gigabyte (GB) disk space per quarter, Note that for project databases, the price for data packages is 17.600 kr. excl. VAT (public institutions)/ 22.000 kr. excl. VAT (private institutions), thus 4 times the price of projects under the researcher scheme or subprojects. , *For public authorised institutions, a special contribution is given towards the hourly rate from the Danish e-infrastructure Cooperation via KOR., Denmark's Data Portal offers paid-for services to users of Statistics Denmark’s microdata schemes. Initially, we offer consultancy in connection with questions for clarification of an assignment. For this, we invoice the actual time used at the hourly rate in force at any time. This also applies should you decide to not proceed with the assignment. If we subsequently enter into a specific fixed-price agreement for the assignment, the service and consultancy will be included in this (within reason)., Fixed-price agreements and framework agreements, Both fixed-price agreements and framework agreements are based on the time it takes to process and deliver an assignment. The time is charged by the hourly rate in force at any time. Denmark's Data Portal uses standardised prices based on the average estimated time consumption for a given service assignment., Fixed-price contract, The price is determined based on an estimated time consumption for a given service. With a fixed-price agreement, you thus pay the same price for comparable services., Further on the structure of fixed-price agreements, The price of a fixed-price agreement is based on one or more of the following assignment elements. The below table shows the various elements of the assignment, which are charged on the basis of fixed-price agreements and associated time consumption., Assignment element, Time consumption, Project proposal (processing and approval hereof), 2, Extraction of one data set from register, 1.05, Extraction of two data sets from register*, 1.09, No additional time charge in case of data extraction from register <= 15 variables,  0, Additional time charge in case of data extraction from register > 15 variables,  0.5, *The price increases with 0,047 hours pr. dataset, Further, the assignment price consists of a fixed extra charge for additional services and consultancy of 20 per cent of the price of the assignment part elements, which are not necessarily in direct contact with you. Such part elements are, for example, participation in meetings etc., internal documentation, documentation requirements, invoicing etc., Data extraction from registers include time consumption for e.g. programming, pseudonymisation and control of data extractions from , Denmark's Data Portal's databank of basic data, . The fixed price agreement may also include time consumption for processing and pseudonymisation of a population submitted to Denmark's Data Portal from other sources than the Denmark's Data Portal's databank of basic data., Framework agreements, The price is variable and the service is charged according to the actual time consumption on the specific service. We invoice every hour of work commenced. If we have used less than one hour on an individual assignment, we invoice for the first hour of work commenced., Further on the structure of framework agreements, The following assignments, Denmark's Data Portal carries out based on a framework agreement:, Population creation as well as case control populations. The service covers counselling regarding the extraction description as well as the subsequent population creation. , Data from statistical division or Survey in Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes, for example, data extraction from register in the statistical division, pseudonymisation and direct communication and consultancy, back office activities and internal communication., Data submitted from sources outside Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes control and pseudonymisation of the submitted data. See estimated time consumption and prices for delivery of submitted data under , Linking other data, .,  , Part elements of an assignment, The total price of a given assignment depends on the time it takes to solve the assignment and the part elements involved. For that reason, the price may vary from one assignment to the next. For example, the price depends on how many registers that are required to create a population, or from how many registers the project requires extraction of data., See the part elements of the assignment, Project proposal, : Processing and approval. The project proposal is charged via a fixed-price agreement, which is based on a fixed time value corresponding to two hours., Population, : Population creation is charged via a framework agreement, which is based on the time it takes Denmark's Data Portal to create the population., Standardised data from Statistics Denmark’s databank of basic data, : This is charged via a fixed-price agreement, which is based on fixed time values per number of registers and variables., Additional services and consultancy, : Direct communication and consultancy, back office activities and internal communication. This is charged via a fixed-price agreement that is based on fixed time values depending on the scope of the assignment., Additional data from Statistics Denmark, : Data extraction from register, direct communication and consultancy, back office activities and internal communication. This is charged via a framework agreement that is based on actual time consumption., Data from other data providers, : Processing of data submitted from you or other data providers. The data processing is charged via a framework agreement that is based on actual time consumption., Special data from Statistics Denmark, : Data compiled especially for the users (not in connection with statistics). The compilation is charged via a fixed-price or framework agreement that is based on actual time consumption for compilation divided by expected sales.,  , Examples of price calculations, Example of price calculation for a research project on the old price model, The following price calculation includes processing of the project proposal as well as data extraction on demographics (BEF), educational attainment (UDDA), income (FAIK and IND) as well as employment information (DREAM). The price calculation is based on a project with full register extraction where the user creates the population. , Since Denmark's Data Portal rounds up to the nearest whole number due to the standardised price calculation method, the price is calculated according to the following table., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 6, Data extraction from register > 15 variables, 0,  , Subtotal, 8 ,  , Additional services and consultancy (extra charge 20 per cent)*, 1 ,  , Total hours used, 9,  , Public user,  , 9 hours * 1,674.00 DKK = 15,066.00 DKK, Private user,  , 9 hours * 2,299.00 DKK = 20,691.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., Please note that the price calculation does not include population creation. If Denmark's Data Portal should create the population, this will be carried out based on a framework agreement., Example of price calculation for a research project, on the old price model, enriched with data from the Danish Health Data Authority, This price calculation includes processing of the project proposal, population creation (based on a framework agreement) as well as data extraction on demographics (BEF, BEFADR, VNDS, DOD) and registrations in the National Patient Register (LPR_ADM, LPR_BES, LPR_DIAG, LPR_SKSUBE). The population consists in persons with a consumption of some specific types of medicinal products found via variables in the Danish National Prescription Registry (LMDB2005-2015). These persons must not be registered as emigrated in the register ‘Historiske vandringer’ (VNDS), meaning that they must be marked INDUD_KODE=U. Furthermore, they must not be registered in ‘Døde i Danmark’ (DOD). Moreover, the population from Statistics Denmark is transferred to the Danish Health Data Authority for enrichment with data from the Danish Pathology Register. The processing and pseudonymisation of data from the Danish Health Data Authority are not included in the price., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 14, Data extraction from register > 15 variables, 0,  , Subtotal, 16 ,  , Additional services and consultancy (extra charge 20 per cent)*, 4 ,  , Total hours used, 20,  , Public user,  , 20 hours * 1,674.00 DKK = 33,480.00 DKK, Private user,  , 20 hours * 2,299.00 DKK = 45,980.00 DKK, Framework agreement for the population creation, Assignment element , Estimated time consumption**, Price, Population creation, 5, Public user,  , 5 hours * 1,674.00 kr. = 8,370.00 DKK, Private user,  , 5 hours * 2.299,00 kr. = 11,495.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., **After the population is created, the time actually sepnt by Denmark's Data Portal is billed at the hourly rate applicable at any given time.,  , Determination of the hourly rate, The hourly rate is determined once a year based on four part elements. The final hourly rate consists in a number of part elements including a development contribution of 3 per cent., Surcharge, : Income forecast for the current year and accumulated surplus/deficit from previous years, Overhead Statistics Denmark and externally funded activities, : Joint expenses, for example for staff, rent, electricity etc. and common administration of externally funded activities, such as maintenance of data bank of basic data, development of externally funded activities etc., Overhead Denmark's Data Portal, : For example, authorisation of new institutions, control of transferred files, sanctioning and general development of the microdata schemes and Statistics Denmark’s Data Portal etc.,  , Other services, Renting of disk space, Projects take up space on Statistics Denmark’s servers. For that reason, we have introduced renting of disk space, so that you as a user are made aware of how much storage capacity your project takes up on Statistics Denmark’s servers. You will only pay for disk space for active projects using a storage capacity over 5 Gigabyte (GB) on the servers. An active project is defined by a minimum of one user logging on to the project within a quarter., Disk space renting is charged on a quarterly basis, and you are invoiced for all projects for which your institution is data controller. For an individual active project using a storage capacity of more than 5 GB, the institution will be charged quarterly in units of 5 GB. Disk space renting will be charged, regardless of the reason for logging onto the project and how often during a quarter., Hosted server, Statistics Denmark also offers to host your own servers, which will be located at Statistics Denmark. , Read more about requirements and prices for hosted servers ,  , FAQ on prices, We have gathered some of our frequently asked questions on prices below., FAQ on prices, Why does the price vary from one assignment to the next?, An assignment is composed of several part elements. The assignment is priced based on the part elements of the assignment. This is why the price may vary, for example depending on the number of registers used for population creation, populations from other data providers or the number of registers from which the project needs data extraction. The part elements of the assignment are described in the section “Part elements of an assignment”., The hourly rate has changed over the years – why?, You can see the changes in the hourly rates of Denmark's Data Portal below., All institutions, 2013, 1,248 DKK, 2012, 1,187 DKK, 2011, 1,167 DKK, 2010 2nd half, 1,197 DKK, 2010 1st half, 1,229 DKK, 2009, 1,229 DKK , 2008, 1,229 DKK, Prices after 2014, Private institutions, Other public institutions, 2024, 2,130 DKK, 1,538 DKK, 2023, 2,130 DKK , 1,568 DKK,  , 2022, 2,130 DKK, 1,568 DKK,  , 2021,  2,168 DKK, 1,735 DKK,  , 2020, 2,202 DKK, 1,745 DKK ,  , 2019,  2,202 DKK, 1,607 DKK,  , 2018, 2nd half,  1,749 DKK, 1,050 DKK,  , 2018, 1st half,  1,749 DKK, 1,050 DKK,  , 2017,  1,650 DKK, 1,050 DKK,  , 2016,  1,650 DKK, 1,050 DKK,  , 2015,  1,750 DKK, 1,050 DKK,  , 2014,  1,650 DKK, 1,050 DKK, There are various reasons for the price changes., Each year, we adjust the hourly rate for surcharge, which accumulates the surplus/deficit of previous years. Moreover, we include an income forecast for the current year, which can cause variations from one year to the next., Public institutions are not allowed to generate a profit. For that reason, Statistics Denmark regularly adjusts the hourly rates so that they reflect the actual costs and make the accounts balance., In 2014, a distinction was made between private and public institutions, when Denmark's Data Portal for the first time received a special contribution from the coordinating organ for register research, KOR, among others, supporting the hourly rate for public users. This accounts for the difference in price depending on whether a private or a public institution owns the project., Why must I pay for other variables to be added to my project?, Changes in an already existing project must be described in the project proposal and/or the variables documentation. Furthermore, they must be documented and the approval must be renewed in Denmark's Data Portal. The only exception that does not require renewed approval is an update of an already approved population or variable., The approval requires a number of processes, which can be anything from dialogue between you and Denmark's Data Portal to a review of the project and its variables documentation for renewed approval of the project. The process can vary considerably depending on the project, and the time consumption up until the approval is in the range of 1-4 hours whether for new projects, updates or extensions. The price of processing a project proposal is therefore set at two hours. If the time consumption exceeds four hours, a supplementary agreement is made in the form of a framework agreement to cover the actual processing time., We encourage you to make a professional assessment of when and how often you apply for approval of project changes,, so that we can reduce the number of ongoing and minor changes., For how long is a quotation valid?, A quotation is valid for 30 days starting from the date of the quotation. After that, we recalculate the quotation at the current hourly rate., How we charge for a project database? , The charge is based on an annual contract with a fixed-price agreement that includes update of agreed register data in the project database as well as a possible framework agreement for additional services, such as deliveries from the project database to sub-projects and consultancy according to the needs of the project database., The establishment of a project database follows the same pricing guidelines as a new project. Since the project database has a longer time perspective than a project, an annual contract on updating is entered. Thus, the pricing is based on an expected average time consumption for the service., The settlement period appears from the below table. The fixed-price agreement for updating of the project database is settled together with the Q2 settlement of ‘Additional services’. ‘Additional services’ are settled quarterly., Invoiced in the calendar year yyyy, Invoiced in the calendar year, The annual contract covers, Mid-January, Mid-April, Mid-July, Mid-October, Mid-January, Data extraction, Fixed-price agreement for data, Additional services, Consumption Q4 from the previous year, Consumption Q1, Consumption Q2, Consumption Q3, Consumption Q4, Why do prices of comparable services vary?, The price of services is based on past experience and averages. Comparable services may imply small differences in the various part elements that affect the price, for example, the price of processing external data (submitted from other data providers) compared to processing of standardised data extractions from registers in Statistics Denmark’s databank of basic data. If project changes appear later in the process, the price may change based on the changes. Furthermore, the hourly rate is calculated annually, which can also affect the assignment price., What is the background for Statistics Denmark’s prices?, Statistics Denmark is the central producer of statistics in Denmark, and the costs of carrying this obligation as an authority are covered by the Danish Finance Act., The data that we collect and store can be used for scientific and statistical surveys under Statistics Denmark’s researcher scheme. Only authorised research and analysis environments are granted access to data, and we charge for making data available for the surveys., In principle, the price must cover the costs associated with performing the assignments from the initial dialogue to the final dialogue no later than 30 days after the assignment has been delivered., The price must further contribute towards the costs associated with:, Consultancy on the use of data in the individual project., Administration of the scheme, for example authorisation, Data access rights, Standardisation of register data, Development of our user services, Securing continued high data security and data confidentiality, Overhead costs, Statistics Denmark’s pricing is subject to the rules on externally funded activities in the public sector and is checked by the National Audit Office of Denmark. Income and expenditure must balance, and the income from services must not be used to fund the obligations of the authority. The financial balance is continuously monitored across a ten-year average.

    https://www.dst.dk/en/TilSalg/data-til-forskning/mikrodataordninger/priser-og-prisaftaler