Search result

Detention

How many persons are arrested annually in Denmark? How many arrests end with release, custody, and sentence?

https://www.dst.dk/en/Statistik/emner/sociale-forhold/kriminalitet/frihedsberoevelser

Subject page

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 2 , Previous versions , Job Vacancies 2026 Quarter 1, 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

Documentation of statistics: Hospitalization

Contact info, Personal Finances and Welfare, Social Statistics , Line Neerup Handlos , +45 26 64 03 00 , LHA@dst.dk , Get documentation of statistics as pdf, Hospitalization 2025 , Previous versions , Hospitalization 2024, Hospitalization 2023, Hospitalization 2022, Hospitalization 2021, Hospitalization 2019, Hospitalization 2018, Hospitalisation 2017, Hospitalization 2016, Hospitalization 2015, Hospitalization 2014, Hospitalization 2013, The purpose of the Hospital Utilisation Statistics is to shed light on the connection between hospitals stays and social and demographic conditions. The statistics have been compiled since 1990, but are comparable in their current form only from 2017 onwards., Statistical presentation, The statistics are an annual inventory of stays at public and private somatic and psychiatric hospital wards within one calendar year. The statistics show how hospital stays vary with demographic and social factors, such as residence, sex, age, educational level, labour market affiliation and relatives. The statistics are published in News from Statistics Denmark and in the StatBank., Read more about statistical presentation, Statistical processing, The statistics are based on data retrieved from the National Patient Registry, which is shared with Statistics Denmark by the Danish Health Data Authority. Background data from Statistics Denmark are linked to the registry, and summaries and counts are produced — for example, the number of hospital stays and patients in public and private somatic and psychiatric hospital departments during the calendar year., Read more about statistical processing, Relevance, Public and private stakeholders, as well as the general population, can use the statistics to extract data on the population’s hospital utilisation for various analyses, research, public debate, etc. The statistics make it possible to produce figures for specific diagnosis groups and to link information on hospital utilisation with sociodemographic factors such as place of residence, education, labour market attachment, and origin. This is made possible by linking data from the National Patient Register with population register data from Statistics Denmark., Read more about relevance, Accuracy and reliability, The National Patient Register is validated by the Danish Health Data Agency and the accuracy of the register data must be considered to be high because the registration has a long tradition and a high priority for administrative purposes. Accordingly, the overall accuracy of the Hospital Utilisation Statistics is high. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published within approximately seven months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The statistics have been developed since 1990, but are only comparable in their current form from 2017 onwards., Eurostat and the OECD make comparable statistics in this field. There are a number of organizational and institutional conditions that we must keep in mind when comparing countries. , Read more about comparability, Accessibility and clarity, The statistics are released in the newsletter Nyt from Statistics Denmark (in Danish only) and the Statbank, Statbank tables on , hospitalisation utilisation, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/hospitalization

Documentation of statistics

Labour Force Survey (LFS)

How high is the employment rate in Denmark? How many work part time? And how many are working from home?

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

Subject page

Data in general

Denmark’s Data Portal has gathered a vast series of historical register data in a databank of basic data. Here you can find information on the various types of data made available and on the documentation of data.

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

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

Surveys

Contact Information, Senior Advisor, Bo Lønberg Bilde, , mobile +45 91 37 64 26, Head of Division, Marie Fuglsang, , mobile +45 20 35 39 25, Statistics Denmark conducts surveys for both private and public customers. We carry out nationwide surveys with a random sample of the Danish population and businesses. We can also use our extensive registers as a basis to form a sample. This means that we can carry out interviews among almost any sample in Denmark, such as: , Parents of children in kindergarten , Nurses who completed their training 3-5 years ago , Car owners in the metropolitan area , Export Companies in the capital area , Companies of a certain size in Jutland   , There are many more options than the ones mentioned above. Contact us to learn more about the possibilities., The surveys are carried out either via a web form, using telephone interviews or a postal questionnaire or a combination of these three methods., Delivery, Results from the survey can be delivered as anonymised data on an individual and company level and/or coupled with register data in tables. If you want to analyze data from Statistics Denmark registers coupled with data from the study on an individual or company level this can be done through our Division of Research. Read more about the possibilities here , www.dst.dk/research, ., Price, The price depends on the content and scope of the survey. When the design of a particular survey is settled, we will send you a final price quote. It is also possible to get supplementary questions included on the monthly omnibus survey – an inexpensive way to conduct small studies with high quality.

https://www.dst.dk/en/TilSalg/interview

Not in Employment, Education or Training (NEET)

Register-based indicator for the share of young persons from 16-29 years who are not in education, employment, or training (NEET). , Introduction , NEET is an acronym for "Not in Employment, Education or Training", and this set of statistics accounts for the number of young persons from 16-29 years who are not in employment or education. The statistical data period is the last week of November, and a person is categorised as not active (NEET), if he or she is not in employment in that week and is not in education either in that same week as well as the preceding three weeks., The statistics are based on the Labour Market Accounts (LMA) and facilitate the calculation of a NEET indicator based on register data. The statistics have taken inspiration from the NEET indicator, which is defined by Eurostat as well as the OECD, and which is calculated from the interview-based Labour Force Survey (LFS)., Documentation , Documentation of statistics, Get an overview of the purpose, content and quality of the statistics. Here you can find information on the sources that the statistics are derived from, what the statistics contains and how often it is published., Labour Market Account, Key figures , In Statbank Denmark, you can find more data on Population (16-29 years) (NEET3), Population (16-29 years) by NEET status, age, sex and time, Unit: , Number, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, Active, Age, total, Men, 456,881, 465,724, 471,014, 472,558, 469,944, 469,774, 480,662, 479,900, 479,777, 486,052, Women, 434,930, 442,651, 449,283, 452,928, 451,233, 451,979, 460,859, 462,820, 462,684, 466,940, Not active (NEET), Age, total, Men, 68,397, 68,158, 68,275, 68,594, 69,540, 66,924, 58,135, 61,620, 62,925, 58,669, Women, 67,627, 68,284, 67,428, 66,534, 66,661, 62,689, 55,789, 59,073, 60,303, 57,473, In Statbank Denmark, you can find more data on Population (16-29 years) (NEET4), Related content in Not in Employment, Education or Training (NEET), Tables in Statbank , Scheduled releases , Contact, Pernille Stender, Phone: +45 24 92 12 33, Mail: , psd@dst.dk

https://www.dst.dk/en/Statistik/emner/arbejde-og-indkomst/befolkningens-arbejdsmarkedsstatus/unge-uden-for-beskaeftigelse-og-uddannelse-neet

Subject page

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

Authorisation of institutions

Institutions must be authorised in order to get access to data under Statistics Denmark’s microdata schemes. This page has information on the possibilities of obtaining authorisation, educational authorisation or client authorisation and on the application process., Apply for authorisation, To get access to pseudonymised data under Statistics Denmark’s microdata schemes, your institution must be authorised. To obtain authorisation, an institution must have a permanent research/analysis environment, which involves e.g. employing a head of staff and at least three experienced researchers/analysts. To apply for authorisation, you must complete the application form at the bottom of this page., Read more about our requirements to your institution and the application under ‘Types of institutions eligible for authorisation’ and ‘Requirements to application for authorisation’ below., Types of institutions that can be authorised, The below environments located in the Danish Realm may be considered for authorisation, if these comply with the application criteria:, The user group is defined under the framework agreement between Statistics Denmark and Danish e-infrastructure Cooperation (DeiC): Publicly funded research and analysis environments (i.e. university departments, government research institutes, ministries, government agencies etc.) as well as charitable foundations in Denmark., In the private sector, the following Danish organisations are eligible for authorisation:, Interest organisations., Consultancies. However, consultancies cannot get access to business data. The director general may grant an exemption to consultancies allowing them to gain access to business data when carrying out fact-finding or research on business data for a public authority or an interest organisation, provided that this happens with the authority or organisation as data controller., Other enterprises may be authorised but may not get access to data that includes business data., Requirements to application for authorisation, In order to be eligible for authorisation, your institution must have a high and sustained focus on data security. Statistics Denmark has determined four requirements that you must be able to meet:, In the research/analysis environment, there must be a personnel manager who accepts the responsibility for the authorisation and for overseeing that the rules in the authorisation agreement are kept. This includes continuously ensuring that all persons in need of access are familiar with the rules on access to data and the rules on transfer of results., As a minimum, there must be at least three people in the environment with specific experience in handling large data volumes and solid knowledge of our data security rules. Experience may have been gained, for example, through previous access to pseudonymised data under Statistics Denmark’s microdata schemes, or experience otherwise gained with the handling of register data., For private environments, the research/analysis environment must be at least one year old to be considered for authorisation., The environment must appear from the institution website., If you are a public institution, and your research/analysis environment does not meet the requirements, you can consider commissioning an already authorised private consultancy to solve the analytical task for you. For this, you need a client authorisation. Read more under ‘Requirements to application for client authorisation’., If you have questions about the application for authorisation, please contact , DDVautorisation@dst.dk, . Please write ’Re. application for authorisation’ in the subject field., Specifically for Greenland and the Faeroe Islands, According to the General Data Protection Regulation, the Faroe Islands and Greenland are third countries, which is significant in terms of obtaining authorisation:, The Faeroe Islands has obtained an adequacy decision by the European Commission, which means they can be approved as a secure third country. Institutions and enterprises from the Faeroe Islands can thus obtain authorisation on an equal footing with those from Denmark., Greenland has not obtained an adequacy decision, which is why Greenlandic institutions must enter into transfer agreements to obtain authorisation. Until Greenland is approved as a safe third country, authorisation can only comprise public institutions., For both the Faroe Islands and Greenland, the authorised institution must obtain approval from the Danish Data Protection Agency if it wants access to sensitive data according to the Danish Data Protection Act., Without authorisation – what are the options?, If your research/analysis environment is not eligible for authorisation, or if you do not want to be authorised, you have the following options:, You can get Statistics Denmark’s Consulting team to perform the analytical task for you. , See how you commission a task with Statistics Denmark Consulting, You can commission a private consultancy that is already authorised to make the analytical task for you. For this, you need a client authorisation. , Note: , This solution is only offered to public institutions and requires that the performing consultancy has access to the data you need, or that you are granted an exemption allowing the consultancy to get access. Find further information under ‘Requirements to application for client authorisation’ below., Apply for client authorisation, To be authorised as a client, you must complete the application form at the bottom of this page. Please note that there are special requirements to the completion of specific fields in the form. Look for guidance under ‘Requirements to application for client authorisation’., Requirements to application for client authorisation, To be considered for client authorisation, you must enter a cooperation agreement with a private consultancy that already holds an authorisation. In that case, the analytical task will be carried out at your/the client’s responsibility, but based on the specialised environment at the consultancy charged with the task., Client authorisations are only offered to public institutions and require that the performing consultancy can get access to the data you need. Please inquire with the consultancy if this is the case before you apply for a client authorisation., Note:, If you need business data with limited access, you can apply for an exemption on behalf of the consultancy. Read about the possibility of applying for an exemption under , Access to business data, ., You cannot apply for an exemption until you have been client authorised., Guide to application for client authorisation, To apply for a client authorisation you must use the same form as for an application for authorisation (bottom of the page)., All fields in the form must be completed as specified, except for these six:, Under ’Name of institution’ you must add ’- Client authorisation’ , [Example: Agency for xxx - Client authorisation] , Under ‘Name of person responsible for authorisation (head of staff)’, you enter the name of the head of staff in your institution who is going to act as the person responsible for authorisation. For the person in question, this involves e.g. assigning roles in DDP App and acting as data controller without any supervisory obligation. The supervisory obligation lies with the consultancy charged with the task. Read more about the division of roles under , User roles, ., Under ’Brief description of your research/analysis environment’, you must state the name and authorisation number (1-3 digits) of the consultancy charged with the task , [Example: Name of consultancy, 123], Under ’Number of researchers in your research/analysis environment’, you must enter ’0’, Under ’Number of people in the environment who have specific experience in handling register data/large volumes of data, you must enter ’0’, Under ’Link to the environment website’, you must enter your institution website., If you have questions about the application for client authorisation, please contact , DDVautorisation@dst.dk, . Please write ’Re. application for client authorisation’ in the subject field.,  , The next steps and other documents, How Statistics Denmark assesses applications for authorisation and client authorisation, Assessment of application for authorisation, To assess whether you can be authorised, we make a specific assessment based on your research/analysis environment. In doing so, we focus on your competences in data management and your knowledge of the data security rules that apply for access under Statistics Denmark’s microdata schemes., All authorisations need approval from the director general of Statistics Denmark., If you are approved for authorisation, you must enter into a data processor agreement with Statistics Denmark., Assessment of application for client authorisation, To obtain a client authorisation, your research/analysis environment does not need to be assessed by Statistics Denmark. This is because your analytical tasks will be handled by an authorised consultancy., In the assessment of your application for a client authorisation, Statistics Denmark focuses on whether you are a public institution and whether you have appointed a head of staff as responsible for authorisation., If you are approved for a client authorisation, you must enter into a data processor agreement with Statistics Denmark., Other agreements, documents and guides (in Danish), Autorisationsaftale, Databehandleraftale (pdf), Tilknytningsaftale, Brugeraftale, Read about the rules on transfer of analysis results, Please refer to Statistics Denmark’s Data confidentiality policy and Information security policy, If you have questions about the application for authorisation or client authorisation, please contact , DDVautorisation@dst.dk, .

https://www.dst.dk/en/TilSalg/data-til-forskning/autorisering-af-institutioner