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Unemployment concepts

There are three different unemployment concepts – net unemployment, gross unemployment and LFS unemployment., Statistics Denmark regularly publishes two sets of unemployment statistics, which use different unemployment concepts and consequently result in different unemployment figures. The register-based unemployment statistics, which assess net unemployment and gross unemployment, and the interview-based Labour Force Survey (LFS), which assesses LFS unemployment. , Net unemployment covers recipients of unemployment benefits, cash benefits and student grants who are job-ready and not in job activation. The numbers are converted into ‘full-time equivalent (FTE) unemployed persons’. , In addition to net unemployment, gross unemployment also covers recipients of unemployment benefits, cash benefits and student grants who are job-ready and in job activation, including persons employed with wage subsidies, also converted into ‘FTE unemployed persons’. , LFS unemployment covers persons who indicate in the Labour Force Survey that they were not in employment during the week that the survey took place, , and, that they actively sought employment in the four weeks up to the week in which the survey took place, , and, that they were able to start a job within two weeks. , When to use which unemployment concept, In Denmark, gross unemployment is the most common unemployment concept used in the debate. Gross unemployment (and net unemployment, which is a subset hereof) gives monthly details on unemployment, e.g. at municipal level, broken down by age groups or by unemployment insurance funds. Moreover, gross unemployment is ideal for highlighting the extent of part-time unemployment and for linking with other register variables such as education and country of origin. LFS unemployment is mainly used in international comparisons of unemployment rates and trends in different countries. Furthermore, the LFS can show the extent of unemployed persons who are not entitled to unemployment benefits or cash benefits, or be used to assess the number of persons who want to find a job. , Overview of unemployment concepts,  , LFS unemployment, Net unemployment , Gross unemployment, Based on, QUESTIONNAIRE, (figures from the Labour Force Survey), REGISTERS, (data from STAR - the Danish Agency for Labour Market Recruitment), REGISTERS, (data from STAR - the Danish Agency for Labour Market Recruitment), Is, sample-based questionnaire , survey with 72,000 interviews each year, register-based complete census, register-based complete census, Published, quarterly, monthly, monthly, Unemployed persons, Complies with the international ILO definition:, - are completely jobless and, - are available to take up employment and, - have carried out activities to seek employment, are registered as unemployed recipients of unemployment benefits or job-ready recipients of cash benefits, excl. those in activation, are registered as unemployed recipients of unemployment benefits, incl. those in activation, What is, counted, number of PERSONS, persons converted to FTE PERSONS, persons converted to FTE PERSONS, Time series, in Statbank Denmark , From 2008, From 1979, From 2007, Strengths, - useful in international comparisons, - shows also unemployed persons who are not entitled to unemployment benefits or cash benefits, - shows persons who want to get a job, - shows youth unemployment (15-24-year-old persons), - allows for supplementary questions, - a monthly flash unemployment indicator , - a long time series from 1979, - shows small groups of persons , - shows available hours, - shows breakdown by unemployment benefit funds , - linkage with other register variables, - a monthly flash unemployment indicator , - shows small groups of persons, - shows available hoursr, - shows breakdown by unemployment benefit funds, - linkage with other register variables, Weaknesses, - statistical uncertainty, - high uncertainty for small groups, complies only partly with the ILO definition, as it only covers persons who are entitled to unemployment benefits or cash benefits, complies only partly with the ILO definition, as it only covers persons who are entitled to unemployment benefits or cash benefits,  ,  

https://www.dst.dk/en/Statistik/dokumentation/metode/ledighedsbegreber

Documentation of statistics: Implicit index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Implicit index of average earnings 2025 , Previous versions, Implicit index of average earnings 2024, Implicit index of average earnings 2023, Implicit index of average earnings 2021, Implicit index of average earnings 2020, These statistics show the development in average earnings, calculated on the basis of an arithmetic average of salaries of all employees within the same sector and economic industry. In relation to the publication of the new Standardised index of average earnings, these indices were renamed to Implicit index of average earnings. In the new index changes in the workforce is taken into account when calculating the development in earnings., The Implicit index of average earnings goes back to first quarter of 2005 for the private sector and first quarter of 2007 for the public sector., Statistics Denmark has decided to discontinue the implicit index of average earnings at the beginning of 2026 with the publication of the index for the fourth quarter of 2025. Instead, users are advised to use the standardised index of average earnings, which also illustrates the development in pay level for employees in Denmark. The discontinuation of the implicit index of average earnings will not have any impact on the standardised index of average earnings, which will be the only wage index from Statistics Denmark in the future. The historical series of the implicit index of average earnings will continue to be accessible in StatBank Denmark. In order for users to handle the transition to the standardised index of average earnings, a guide (in Danish) has been prepared on how to switch from the implicit to the standardised index of average earnings in practice. It is available on Statistics Denmark's information page on , indexation, ., Statistical presentation, The Implicit index of average earnings is a quarterly statistic of the development in wages for all employees in Denmark, including students and young persons under 18. The indices are available by sector and economic industries and follow the classifications Dansk Branchekode (DB07) and sector (SBR)., Read more about statistical presentation, Statistical processing, Data is collected from a sample of companies and organisations as well as the entire public sector, covering the middle month of the quarter., Data is validated by using fixed boundaries, both at individual and company level. Manual corrections are also made if required. Only companies that are present in both quarters are included in the calculations., In the calculation of the most detailed sub-indices, data for the private sector are weighted to the target population and the individual employment types are weighted with the hours worked., Read more about statistical processing, Relevance, The Implicit index of average earnings is a so-called unit value index, where wage trends are estimated on the basis of a simple salary average of all employees in the same industry. This means that wages partly reflect changes in staff composition in a given industry., Private enterprises as well as ministries etc are the central users. The index is used especially in connection with various contract regulations, as well as the regulatory scheme in the public wageagreements., The Implicit index of average earnings is the wage index that comes closest to being comparable to the European LCI., Read more about relevance, Accuracy and reliability, For the public sector the statistics are based on data for virtually all employees. For the private sector, there are two factors that can affect accuracy, namely uncertainty in the sample statistics and that there may be problems with the completeness of the reported data from the company., This index is an where the sum of wages and hours worked is counted in each group (etc. activity sector). Thus, changes in personnel in a given industry will have an impact on the measured wage development., The figures do not undergo revision; the published figures are usually final., Read more about accuracy and reliability, Timeliness and punctuality, The implicit index of average earnings are published approx. 60 days after the end of the reference quarter, at the same time as the standardised index of average earnings is published. These statistics are published without delay., Read more about timeliness and punctuality, Comparability, The implicit index of average earnings is comparable since first quarter 2005 but for some sectors, comparable wage indices also exist further back in time. The implicit index of average earnings is based on the same data as the standardised index of average earning, but there are significant differences in methodology that allow the two wage indices to be used only partially for comparison., Internationally, the implicit index of average earnings can be compared to the labor cost index collected and published by Eurostat for all EU countries., Read more about comparability, Accessibility and clarity, The implicit index of average earnings is published in Statistics Denmark’s newsletter on [https://www.dst.dk/da/statistik/nyheder-analyser-publ/nyt?psi=1931), together with the standardized index of average earnings. In Statbank Denmark, indices and annual increases are published under the , implicit index of average earnings , . More information can be found on the subject page on , Income and earnings, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/implicit-index-of-average-earnings

Documentation of statistics

Documentation of statistics: Standardised index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Standardised index of average earnings 2025 , Previous versions, Standardised index of average earnings 2024, Standardised index of average earnings 2023, Standardized Index of Average Earnings 2021, Standardized Index of Average Earnings 2020, Standardized Index of Average Earnings 2019, Standardized Index of Average Earnings 2018, The purpose of the standardised index of average earnings is to estimate the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the labour market’s occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics are used for e.g. monitoring of business cycles, regulation of contracts, analyses of developments in pay levels as well as input in the calculation of the National Accounts., The statistics have been prepared since 2018 with data back to the first quarter of 2016. A revised index and time series are published in May 2023 with data back from 2016., In parallel, Statistics Denmark is calculating the implicit index of average earnings. Unlike the standardised index, the implicit index of average earnings does not take changes in the occupational composition into account., Statistical presentation, The standardised index of average earnings is a quarterly estimate of the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics show the development in the average hourly earnings for employees by sector, industry (DB07) and main occupation (DISCO-08). Each quarter, an index value and an annual increase are published., Read more about statistical presentation, Statistical processing, Data for these statistics are collected quarterly. For the public sector all payroll information are collected while data are collected via a sample from the private sector. The collected data is validated at an aggregate level for key enterprises (only in the private sector) and at an individual level through a combination of validation rules for the hourly earnings for the individual employment relationship. The hourly earnings are assessed based on sector, industry, main occupation and type of employment. Once data has been validated, base index is calculated for each homogeneous group, which afterwards is aggregated to sub- and total indices at sector, industry or main occupation level., Read more about statistical processing, Relevance, These statistics are relevant for private enterprises and organisations, as well as ministries and other public institutions for analysis, contractual regulation etc. The statistical data are also used in other areas within Statistics Denmark, e.g the calculation of the Danish National Accounts., Read more about relevance, Accuracy and reliability, The accuracy of these statistics are higher for employees in the public sector than in the private sector. The reason for this is that the statistics for employees in the public sector (more or less) consists of all payroll information, while the statistics for employees in the public sector is based on a sample of enterprises. The accuracy of the statistics for the private sector is therefore affected by sampling uncertainty, completeness of the reported information and non-response. The impact on the indices are unknown., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published two months after the end of the reference period. The statistics are released typically without delay according to scheduled dates of publication. , In February 2022, the statistics were paused and a comprehensive service review was initiated. As a result, the method for calculating standardized index of average earnings was revised. This publication therefore contains revised index values and annual increases for the entire period from the first quarter of 2016 until the first quarter of 2023. This means that the series contains revised values from the first quarter of 2016 until the third quarter of 2021 as well as previously unpublished values from the fourth quarter of 2021 until the first quarter of 2023., Read more about timeliness and punctuality, Comparability, The standardised index of average earnings was first published in December 2018 with a time series starting in the first quarter of 2016. The standardised index of average earnings utilize the same data as the implicit index of average earnings, which however has a different purpose and is therefore calculated using a different method. There exist a few sets of statistics abroad that are partly comparable with the standardised index of average earnings. , 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 , Indices of average earnings, . For further information, visit the subject page for , Income and earnings, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/standardised-index-of-average-earnings

Documentation of statistics

Population description

In the project proposal, you must describe the population shortly and precisely (without technical terms, details or data specifications), and document who creates the population. You do so under the population description in Denmark's Data Portal. , Private institutions are able to create the population themselves and get a full register extraction if the project is surveying a major group of entities. To get a full register extraction, private institutions must give reasons for this need based on the size of the population. ,  , When Research Services must create the population, If Research Services is going to create the population for your project, this is done on the basis of a framework agreement. Under the population description in Denmark's Data Portal, you describe the population shortly and precisely (without involving technical details) and add that Statistics Denmark is going to create the population. When Research Services have received the project proposal, they will contact you about the creation of the population. , Examples of population descriptions:, `The population consists of all persons who have been hospitalised with asthma, which is matched with five controls on sex and birth year per case. The controls must be alive and be residing in Denmark on the index data of the case. Statistics Denmark creates the population.', `The population consists of persons who have had residence permits as refugees, and family members reunited with refugees. Statistics Denmark creates the population.', Framework agreement for extraction description and population creation , Research Services prepares a framework agreement, which covers counselling regarding the extraction description as well as the subsequent population creation. Based on the framework agreement, we prepare a detailed extraction description in collaboration with the relevant institution. Research Services uses the extraction description for the final population creation. Based on the institution's criteria and needs regarding the population, we give advice on which registers, variables and variable values that are necessary to create the wanted population. The final extraction description is attached as an appendix to the project proposal. When the extraction description is ready, Research Services creates the population for the project., How to make the extraction description for the population?, The following elements must be uncovered for the extraction description:, Registers or additional data to be used , Periods, including if you want to use registers that are updated annually, quarterly or monthly (for example, BEF (population) is updated quarterly), Conditions based on specific variables and delimitation on specific variable values (for example, if the population must be delimited by age from 15-76 years), How registers must be linked (if several registers are applied), including linking based on specific variables and, if relevant, key register,  , Especially about case control populations , Research Services uses the term `case control populations' for analyses where cases (e.g. exposed) are compared with a reference group (controls). The term is used regardless of the type of study. Under the population description in Denmark's Data Portal, enter a short and precise description of the criteria for cases and controls in the case control population, without involving technical details (including registers and variables). , In collaboration with Research Services, we prepare a detailed extraction description of the case control population. The final extraction description is attached as an appendix to the project proposal. Please note that Research Services only creates case control populations based on date and register criteria, not based on more complicated statistical methods such as for example Propensity Score Matching., How to make the extraction description for the case control population?, The following elements must be uncovered for the extraction description: , What characterises cases:, Registers, periods, conditions, and how registers are linked (see description below), If relevant, index date (for example date of first completed vocational education, first hospital discharge date), What characterises the pool of possible controls:, Registers to be used for creating the pool of possible controls, Inclusion and exclusion criteria based on specific variables and variable values (for example sex = 2 (women), municipality = 607 (Fredericia), residence in the period 01-01-2020 until 31-12-2023), Specific criteria for the case control population including:, How many controls are extracted per case?, Whether cases are allowed to be controls of other cases, If controls are allowed to change status in the inclusion period, Extraction with or without replacement: , is a control allowed to be used as a control for more than one case (replacement)?, or can a control only be a control for a specific case (without replacement)?

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

Access to business data

Business data refers to data on Danish enterprises and Danish trade and industry. This page gives an overview of who can get access to business data from Statistics Denmark and the possibilities to apply for an exemption to get access. , Business data and business data with limited access, Business data from Statistics Denmark covers a wide range of data on industries and data on the size, location, accounts, employment, development over time, etc. of Danish enterprises. Some types of business data involve competition- and market-sensitive information, which is why access is limited. For example when data concerns the activities or financial affairs of enterprises., See the overview of business data with limited access in Statistics Denmark (Excel, in Danish) , Note, : To protect competition- or market-sensitive information, business data with limited access is not available until at least one year after the reference year., Business data – who has access?, A person can get access to all (pseudonymised) business data in Statistics Denmark, including business data with limited access, if that person has an approved association agreement with a Danish institution that is authorised under Statistics Denmark’s Research scheme and that is , a Danish public institution, or , a private Danish institution in the category “interest organisation, think tank, etc.”, ‘Danish institution’ means an institution within the national community of Denmark, Greenland and the Faroe Islands. You can find the special rules for Greenland and the Faroe Islands under , Authorisation of institutions, ., Business data with limited access – who does not have access?, Generally, people employed in Danish private consultancies may not get access to business data with limited access., People employed by other Danish or foreign private companies (such as banks, pension funds and insurance companies) or by foreign consultancy firms are not permitted to access business data with restricted access., Business data with limited access – who can apply for an exemption? , In connection with specific projects, Danish private consultancies that do not have access in general to business data with limited access can apply for an exemption. This is only an option if:   , the data controller institution for the project is a public, Danish and authorised institution (see “a” above) or , the data controller institution for the project is a private and Danish institution in the category “interest organisation, think tank, etc.” (see “b” above) or, the data controller institution for the project is a public, Danish institution and an institution authorised as a client, which engages a private consultancy to perform an analysis for the institution for which business data with limited access is needed and the consultancy’s authorisation does not grant access to this data. , Read more under Authorisation of institutions, Apply for an exemption , If you are eligible to apply for an exemption (and thus comply with item 1, 2 or 3 above) and want to apply, please inform the project owner in Statistics Denmark early in the project proposal process. This ensures that the project owner can take this into consideration during the approval of the project proposal.  , Furthermore, you need to complete the request template from Statistics Denmark and send it to your project owner, when the project for which you are applying for business data with limited access has been approved., Template for request for exemption for business data with limited access (docx, template only available in Danish), Note, : The request template must be adjusted with your own official business stationery design, signed and sent (in Word or PDF format). If you need help filling in the template, for example purpose and description, you can consult Statistics Denmark’s guide on , how to create a project proposal, . , Request for exemption – how does it work?, For every request for exemption, Statistics Denmark makes a thorough assessment in four steps: , When the project proposal has been approved, the data controller institution completes a request template, adapt it with their own official business stationery design, sign it and send it to the project owner in Research Services., The project owner in Research Services assesses if there are grounds for an exemption. Note: The criteria for approval are the same as for a project proposal. , Read more in How to create a project proposal, The project owner in Research Services sends the request for exemption for approval by the Director General of Statistics Denmark., When the request for exemption has been approved, the approval is returned to the data controller institution and the consultancy charged with the task., If you have questions about exemption, please contact , Forskningsservice@dst.dk, or your project owner in Research Services. In the subject field, you should write: , ’Project number xxx - Re. exemption with respect to business data with limited access’, .,  

https://www.dst.dk/en/TilSalg/data-til-forskning/anmodning-om-data/adgang-til-erhvervsdata

Data Access for Educational Institutions

Through Statistics Denmark’s Thesis Scheme, public educational institutions can give their students access to pseudonymized microdata for use in thesis projects. On this page, you can find guidance materials and read more about the Thesis Scheme., Thesis Scheme – Data Access for Thesis Projects, The Thesis Scheme is the newest addition to Statistics Denmark’s microdata scheme. The scheme allows approved public educational institutions in Denmark to grant thesis students access to pseudonymized microdata for use in thesis projects. To gain access, , the thesis project must have a research-level focus, ., Note, : If you, as a student, wish to access pseudonymized microdata for your thesis project, please contact your educational institution to learn about the available options., Which Institutions Can Access the Thesis Scheme?, Educational institutions that offer master’s programs ending with a master’s thesis (typically 30–60 ECTS). The educational institution must be affiliated with a faculty, institute, or center under one of eight publicly recognized research universities in Denmark*., University of Copenhagen, including affiliated university hospitals such as Rigshospitalet., Aarhus University, including the AUH University Hospital in Skejby., University of Southern Denmark, including Odense University Hospital., Roskilde University., Aalborg University, including Aalborg University Hospital., Technical University of Denmark., Copenhagen Business School., IT University of Copenhagen., *If other institutions offering master’s programs in Denmark wish to establish an educational authorization, they can apply by sending a description of the institution and its needs to , Forskningsservice@dst.dk, ., How Does the Application Process for the Thesis Scheme Work?, To gain access to microdata under the Thesis Scheme, the educational institution must have an educational authorization with Statistics Denmark., Reference is made to the current rules for authorization, and the institution must be one of the educational institutions listed above to obtain an educational authorization., Statistics Denmark - Authorisation of Institutions, If you have questions about applying for educational authorization or need guidance, you are welcome to contact Research Service at , FSEautorisation@dst.dk, ., Please include "Regarding Statistics Denmark’s Thesis Scheme" in the subject line so that we can process your inquiry as quickly as possible., Which Data Does the Scheme Provide Access To?, The program provides access to pseudonymized microdata under the same conditions as the researcher scheme within Statistics Denmark’s microdata schemes, except that each educational authorization may create a maximum of five broad projects., Pseudonymized microdata are personal and business data where all identifying information, such as names, identification numbers (e.g., CPR and CVR), and addresses, have been removed., Price, The fee for the Thesis Program is lower than for the other microdata schemes offered by Statistics Denmark. For more information, see the document below: "Rules for Access to Pseudonymized Microdata under Statistics Denmark’s Thesis Scheme.", Rules for Access to Pseudonymised Microdata under Statistics Denmark’s Thesis Scheme, Special rules apply for access to pseudonymised microdata under Statistics Denmark’s Thesis Scheme. Please read more about these in the document below (in Danish)., Regler for adgang til pseudonymiserede mikrodata under Danmarks Statistiks specialeordning (pdf), Guidelines on Data Security and Agreements, Data confidentiality is a fundamental prerequisite for the existence of Statistics Denmark’s microdata schemes, including the Thesis Scheme. All datasets made available under the scheme are confidential. Therefore, as authorised educational institutions and users, you are obliged—through agreements with Statistics Denmark—to act in accordance with Statistics Denmark’s rules and guidelines. Below you will find the agreements and documents you are required to comply with., Statistics Denmark’s Information Security and Data Confidentiality Policy, Information security and data confidentiality policy – Statistics Denmark, Guidelines on Special Data Security Rules under the Master’s Thesis Scheme, The guidelines set out the rules and requirements that apply to Statistics Denmark’s Thesis Scheme. These rules constitute an adapted version of the general provisions that apply to all of Statistics Denmark’s microdata schemes. For the release of analysis results and in the event of breaches under the Thesis Scheme, the rules in these guidelines apply (in Danish)., Vejledning - Datasikkerhedsregler under Specialeordningen herunder regler for hjemtagning af analyseresultater og sanktioner ved databrud (pdf), Agreements, The Authorisation Agreement, Affiliation Agreement, and User Agreement must be signed and can be found , under the heading “Other agreements, documents, and guides (in Danish).”, Questions about the Program?, If your educational institution has questions about the program, its setup, the process, fees, etc., you can direct them to Research Service. Please include ", Regarding Statistics Denmark’s Thesis Program, " in the subject line.

https://www.dst.dk/en/TilSalg/data-til-forskning/mikrodataordninger/data-til-uddannelsesinstitutioner

About microdata schemes

Statistics Denmark’s Research Services makes data available to authorised institutions for specific research, fact-finding and analytical tasks. Access to data can be granted under various data schemes depending on the institution or the project to which you seek access., The researcher scheme , Researchers and other analysts from authorised institutions can create a project with access to Statistics Denmark’s register data. , Read more about authorisation of institutions, The project database scheme , The project database scheme is intended for institutions that are continuously creating projects with significant overlap in data content. Under this scheme, it is not allowed to carry out research directly on the project database, and the scheme must not be used for projects or tasks that are not directly related to the purpose of the project database. Furthermore, the institution must have one or more employees at who can serve as project database managers, of whom at least one can functions as an administrator. The duties of the project database manager include population generation, data extraction etc. as well as ongoing communication with Statistics Denmark., If you want to apply for a project database to be set up, you must contact the Project database group at , FSEProjektdatabase@dst.dk, ., More on the project database scheme, An authorised institution can have a maximum of one project database. The project database is a collection of pseudonymised microdata. It is used over time for multiple projects (called subprojects) under the relevant project database scheme., For the project database, data is selected from Statistics Denmark’s databank of basic data and, if relevant, data from other sources (such as the institution’s own data). The data content in project databases is subject to the data minimisation principle, and for that reason, data in a project database must be applied in several subprojects., In the project database scheme, the project database is called the main project. Other projects in the project database scheme are subprojects of the project database. The authorised institution that owns the project database therefore owns both the main project and the subprojects in the scheme., The target group of the project database scheme is institutions that:, are authorised for microdata schemes at Statistics Denmark., have at least five active projects with significantly overlapping data., continuously extend their project portfolio with new subprojects with significant overlap in the underlying data., Terms of a project database scheme, Project databases are subject to the following terms:, The institution is required to appoint one to three experienced project database managers who will be the assigned liaison officers with Statistics Denmark. Only project database managers get access to the actual project database., The project database and subprojects are subject to the data minimisation principle., The user must pay for all costs associated with the creation, operation and maintenance of the relevant project database. Subprojects are considered regular projects and are handled and invoiced separately., You can keep a project database going for as long as it is used for active subprojects. The project database can only be preserved as long as it is used for subprojects to an extend that is consistent with the data made available in the project database. The project database can thus be limited or discontinued if Statistics Denmark estimates that this is no longer the case., The authority scheme, The authority scheme makes microdata available to Danish institutions that carry out tasks for the authorities, i.e. departments, agencies and directorates, regions and municipalities. The scheme meets the demand for ad hoc analyses with tight deadlines. , Read more about the Authority scheme,  (in Danish), Data confidentiality and access rules, Access to data is given in agreement with the principles of the General Data Protection Regulation, especially article 5(1)(c): , “Personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed (‘data minimisation’).” , This also applies to section 10 of the Danish Data Protection Act: , “Data as mentioned in Article 9(1) and Article 10 of the General Data Protection Regulation may be processed where the processing takes place for the sole purpose of carrying out statistical or scientific studies of significant importance to society and where such processing is necessary in order to carry out these studies.” , Read more on Statistics Denmark’s Data confidentiality policy and Information security policy 

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

Documentation of statistics: Benefits during sickness or in connection with childbirth (Discontinued)

Contact info, Labour Market , Torben Lundsvig , TLU , TLU@dst.dk , Get documentation of statistics as pdf, Benefits During Sickness or in Connection with Childbirth 2019 , Previous versions, Benefits During Sickness or in Connection with Childbirth 2018, Benefits During Sickness or in Connection with Childbirth 2017, Benefits During Sickness or in Connection with Childbirth 2016, Benefits During Sickness or in Connection with Childbirth, Benefits During Sickness or in Connection with Childbirth 2013, The purpose of Benefits in connection with sickness and childbirth is to illustrate the use of the law on sickness respectively maternity law. The statistics have been compiled since 1995, but in its present form comparable from 2003. From the year 2017, the statistics contain only information about sickness benefits because Udbetaling Danmark has taken a new administrative IT system for maternity allowance in use. Maternity benefits will be an independent statistics from 2020. , Statistical presentation, The sickness and maternity allowance is an annual statement of the number of persons, days and amounts paid in connection with illness or childbirth. From the year 2017 only information for unemployment benefit paid in connection with illness. The calculations are distributed according to the legal basis for the payment of unemployment benefits, age, sex and geography. In addition, figures from the daily allowance for sickness and birth are included in the statistics, Publicly Provided, where the extent of absence due to illness or maternity leave is included in a larger context. , Read more about statistical presentation, Statistical processing, Data comes from the two administrative registers The Administrative Joint-municipal Register for Sickness Benefits and the National Administrative Register for Childbirth Benefits (ended May 2017). When received there are some mechanical monitoring and doublets are removed. When estimating the duration of a case not having a finale date the final date is set to the last day of the year if the case is about sickness benefits. If the case is about childbirth benefits the final date is estimated as the starting date plus the average length measured in days of similar cases having a finale date., Read more about statistical processing, Relevance, The maternity and paternity leave part of the statistic is used by ministries for reasons of gender equality policy and of the unions and the employers' organizations in connection with collective bargaining. The sickness benefit part of the statistic is together with the maternity and paternity leave part section mostly used as an important data element of Analyses of the Danish workforce productivity (economic modeling), Statistics Labour Market Accounts, Statistics Persons receiving public benefits and general absence statistics., Read more about relevance, Accuracy and reliability, The statistics summarize the reports of illness, birth or adoption that have triggered the payment of unemployment benefit. The expectation is that all sickness benefit issues with payment will be reported. Similarly, the expectation is that all cases of payment due to maternity leave, maternity leave or leave due to adoption are reported. Therefore, the statistics can be expected to be reliable. However, there are a number of cases that will only be reported long after the end of the year to which the case relates, why the last year is not fully updated., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published annually in the month of March the year after the reference year. March is chosen as the compromise of current interest and waiting for the last reports of the year to appear. At publishing time the newest data will be less than three months old., Read more about timeliness and punctuality, Comparability, The statistics is influenced by local Danish law. The law of parental leave is unchanged since 2002 and it is possible to compare the figures back to 2003. Concerning sick leave there has been several adjustment making it more difficult to compare over time., Read more about comparability, Accessibility and clarity, In Statistics Bank Denmark the statistics are published s in the tables under the subject , Sickness benefits, and , Maternity benefits, In addition, the statistics include the Statistical Ten Year Overview., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/benefits-during-sickness-or-in-connection-with-childbirth--discontinued-

Documentation of statistics

Documentation of statistics: Highest Education Attained

Contact info, Population and Education, Social Statistics , Alexander Pfeiffer Cappelen , +45 23 63 72 52 , APF@dst.dk , Get documentation of statistics as pdf, Highest Education Attained 2024 , Previous versions, Highest Education Attained 2023, Highest Education Attained 2022, Highest Education Attained 2021, Highest Education Attained 2020, Highest Education Attained 2019, Highest Education Attained 2018, Highest Education Attained 2017, Highest Education Attained 2016, Highest Education Attained 2015, Highest Education Attained 2014, Highest Education Attained 2013, The purpose of the statistics on educational attainment is to give an overall statistical description of the educational level of the population at any given time. The primary data source to these statistics is the Student Register with data from 1970 onwards. In addition, the Qualification Register is used. Since the Student Register is the primary source for information, the Attainment Register gives nearly complete coverage from 1970 onwards. There is, however information before this time coming from The Qualification Register., Statistical presentation, The Attainment Register gathers information about the highest completed education for each single person based on the information in the Student Register and the Qualification Register. It is a longitudinal register based on an assessment of each person's education "career" and shows how the qualification career develops over time. The register is formed by interpreting the qualification career (skills in chronological order) in order to determine a change in the skill level. Once a year a status register is also produced with the population and information about education the 30. September the current year., Read more about statistical presentation, Statistical processing, The Attainment Register is a longitudinal register based on a assessment of each persons education career in The Student Register and The Qualification Register. It shows how the qualification career develop over time, and it is updated once a year. The status register is produced on the basis of the longitudinal register and contains information about the population and their highest completed education per. September 30 the given year., Read more about statistical processing, Relevance, There is a great variety of users. The information is generally used in connection with describing the population or sections hereof. The register is used in connection with status reports for other statistical fields. Data reports are thus submitted for (mainly on the population's highest level of education completed) a wide number of integration registers operated by Statistics Denmark. Furthermore, the register is frequently used in connection with external service activities order by Danish ministries, municipalities, research institutions, professional organization, private enterprises, private individuals and, not least, requests made by the news media., Read more about relevance, Accuracy and reliability, The Accuracy and reliability vary depending on the source of information. More than 80 pct. of the information comes from administrative sources, such as student systems of educational institutions, which are highly reliable. These sources have priority one when the registry is created and will be used if there is information from one of these sources. Other sources are not so closely linked to the education programs and will often be less reliable. Examples of these sources are the surveys of immigrants' education and the population and housing census in 1970, based on self-reported education. In addition, information is imputed for persons who do not respond in the study of immigrants' education. The imputed data is useful in overall statistical statements, but cannot be considered as valid information on individuals' educational attainment. , In connection with the annual reports from the education institutions there is information which also relate to previous years. These delayed notifications concern particularly the last year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published around 6 months after the end of the reference time. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The longitudinal register is produced once a year and the entire period is thus calculated in the same way. Based on the longitudinal register, a status register is produced with the population per. September 30 that year. In the event of significant changes in the way the longitudinal register is produced, the status registers for all years will be reproduced. It happens that an education changes level from one year to the next. Typically, this will not cause a reproduction of all the status registers and therefore affect comparability over time. Labor force survey provide information too Eurostat about the educational attainment level and this is these figures that are used for international comparison of the attainment level., Read more about comparability, Accessibility and clarity, Statistics are published once a year in "News from Statistics Denmark" . At the same time data are released in the Statbank and on the homepage: , Homepage, Information also appears in the annual publications Statistical 10-Year Review and the Statistical Yearbook., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/highest-education-attained

Documentation of statistics

Documentation of statistics: Purchases and sales by enterprises

Contact info, Short Term Statistics , Lina Pedersen , +45 51 68 72 80 , LIP@dst.dk , Get documentation of statistics as pdf, Purchases and sales by enterprises 2024 , Previous versions, Purchases and sales by enterprises 2020, Purchases and sales by enterprises 2019, The purpose of the statistics Purchases and sales by enterprises is to monitor business cycles in Denmark, based on sales of enterprises. The statistics is based on information on value added tax (VAT) reported by the enterprises to the Danish Tax Authorities. , The statistics is compiled and disseminated monthly and provides a short-term status of Danish business economy. The statistics have been published with variation in calculation methods and frequencies, since value added tax (VAT) was introduces in Denmark in 1967. In its current form, the statistics is comparable from 2011 onwards., Statistical presentation, Purchases and sales by enterprises is a monthly statement of purchases and sales of goods and services. The Statement is calculated in millions (Danish kroner). The statement is calculated at industry level defined in the Danish Industrial Classification of All Economic Activities 2007 (DB07). In addition, the statistics are divided into domestic purchases and sales. , Read more about statistical presentation, Statistical processing, Data originates from the Danish Tax Agency’s VAT registers plus information from the Central Business Register (CVR). Missing reports are replaced with imputed values, which are values estimated for each missing report. Imputed values are provisional and removed when the enterprise has reported VAT to the Tax Agency or the enterprise's business status in the CVR register is updated as inactive. The report follows the enterprise's main industry. , Read more about statistical processing, Relevance, Users of the statistics are ministries, researchers, students and organizations. Used for e.g. analysis of business trends and market research. In Statistics Denmark, the statistic provides supporting information to e.g. the National Accounts and statistics on foreign trade. Data contribute to the Danish compliance with requirements in the European business statistics regulation regarding turnover on industries on service and trade. In order to comply with requirements, monthly turnover must be distributed to Kind of Activity Units (KAU). A model is used to split legal units into KAU. , Read more about relevance, Accuracy and reliability, The statistics is based on VAT, reported by enterprises to the Tax Agency. The precision is strengthened by the fact that all companies subject to VAT are included. It is weakened by too little information sales not subject to VAT, e.g. train tickets and recycled clothes. The reliability increases as the enterprises report and revise values. It's possible to revise up to three years after submission. Values are considered final after three years. The sales are used as an estimate for turnover. Please notes that turnover includes more than sales, e.g. revenue from investments., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximate 40 days after the end of the reference period. The statistics contain a statement of sales that are subject to VAT. A statement of an enterprise's sales subject to VAT can be used as an estimate of the enterprise's turnover, which is why the statistics are used for short-term statistics on turnover. The publication date is announced at least 6 months in advance, and it is rare that a publication of the statistics is delayed. , Read more about timeliness and punctuality, Comparability, From 2010, the statistics are based on register data, the information on VAT that enterprise report to the Tax Agency. From the year 2010, data is comparable year to year, as it includes all enterprises that report VAT. The variable "salg i alt" can be used as estimate for the enterprises' net turnover and can be compared with the net turnover in other statistics, e.g. General Enterprise Statistics. When comparing, take into account the differences, for example which types of sales or revenue are included, whether excise duties are included, and whether smaller companies are included. , Read more about comparability, Accessibility and clarity, The statistics are published on the webpage , StatBank Denmark, under the topic Purchases and sales by Enterprises. Until December 2023, the statistics was published monthly in a Danish newsletter called NYT. , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/purchases-and-sales-by-enterprises

Documentation of statistics