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    Prices and price agreements

    The price of a Research Services assignment is based on the time it takes to solve the part elements of the assignment. We have two types of price agreements: , fixed-price agreements and framework agreements, . You can also commission a combined fixed-price and framework agreement. Furthermore, you will be paying rent for disk space for active projects on Statistics Denmark’s servers. If you have your own-hosted server set up at Statistics Denmark, you must pay for the set-up and for routine maintenance., Table 1: Hourly rate and renting of disk space, Hourly rate for private institutions, DKK 2,299 excl. VAT, Hourly rate for public institutions*, DKK 1,674 excl. VAT (after deduction of the special contribution from the Danish e-infrastructure Cooperation via the coordinating organ for register research, KOR)., Renting of disk space, DKK 16 excl. VAT per 5 Gigabyte (GB) disk space per quarter, *For public authorised institutions, a special contribution is given towards the hourly rate from the Danish e-infrastructure Cooperation via KOR., Research Services offers paid-for services to users of Statistics Denmark’s microdata schemes. Initially, we offer consultancy in connection with questions for clarification of an assignment. For this, we invoice the actual time used at the hourly rate in force at any time. This also applies should you decide to not proceed with the assignment. If we subsequently enter into a specific fixed-price agreement for the assignment, the service and consultancy will be included in this (within reason)., Fixed-price agreements and framework agreements, Both fixed-price agreements and framework agreements are based on the time it takes to process and deliver an assignment. The time is charged by the hourly rate in force at any time. Research Services uses standardised prices based on the average estimated time consumption for a given service assignment., Fixed-price contract, The price is determined based on an estimated time consumption for a given service. With a fixed-price agreement, you thus pay the same price for comparable services., Further on the structure of fixed-price agreements, The price of a fixed-price agreement is based on one or more of the following assignment elements. The below table shows the various elements of the assignment, which are charged on the basis of fixed-price agreements and associated time consumption., Assignment element, Time consumption, Project proposal (processing and approval hereof), 2, Extraction of one data set from register, 1.05, Extraction of two data sets from register*, 1.09, No additional time charge in case of data extraction from register <= 15 variables,  0, Additional time charge in case of data extraction from register > 15 variables,  0.5, *The price increases with 0,047 hours pr. dataset, Further, the assignment price consists of a fixed extra charge for additional services and consultancy of 20 per cent of the price of the assignment part elements, which are not necessarily in direct contact with you. Such part elements are, for example, participation in meetings etc., internal documentation, documentation requirements, invoicing etc., Data extraction from registers include time consumption for e.g. programming, pseudonymisation and control of data extractions from , Research Services databank of basic data, . The fixed price agreement may also include time consumption for processing and pseudonymisation of a population submitted to Research Services from other sources than the Research Services databank of basic data., Framework agreements, The price is variable and the service is charged according to the actual time consumption on the specific service. We invoice every hour of work commenced. If we have used less than one hour on an individual assignment, we invoice for the first hour of work commenced., Further on the structure of framework agreements, The following assignments, Research Services carries out based on a framework agreement:, Population creation as well as case control populations. The service covers counselling regarding the extraction description as well as the subsequent population creation. , Data from statistical division or Survey in Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes, for example, data extraction from register in the statistical division, pseudonymisation and direct communication and consultancy, back office activities and internal communication., Data submitted from sources outside Statistics Denmark. This is charged via a framework agreement based on the actual time consumption. The service includes control and pseudonymisation of the submitted data. See estimated time consumption and prices for delivery of submitted data under , Linking other data, .,  , Part elements of an assignment, The total price of a given assignment depends on the time it takes to solve the assignment and the part elements involved. For that reason, the price may vary from one assignment to the next. For example, the price depends on how many registers that are required to create a population, or from how many registers the project requires extraction of data., See the part elements of the assignment, Project proposal, : Processing and approval. The project proposal is charged via a fixed-price agreement, which is based on a fixed time value corresponding to two hours., Population, : Population creation is charged via a framework agreement, which is based on the time it takes Research Services to create the population., Standardised data from Statistics Denmark’s databank of basic data, : This is charged via a fixed-price agreement, which is based on fixed time values per number of registers and variables., Additional services and consultancy, : Direct communication and consultancy, back office activities and internal communication. This is charged via a fixed-price agreement that is based on fixed time values depending on the scope of the assignment., Additional data from Statistics Denmark, : Data extraction from register, direct communication and consultancy, back office activities and internal communication. This is charged via a framework agreement that is based on actual time consumption., Data from other data providers, : Processing of data submitted from you or other data providers. The data processing is charged via a framework agreement that is based on actual time consumption., Special data from Statistics Denmark, : Data compiled especially for the users (not in connection with statistics). The compilation is charged via a fixed-price or framework agreement that is based on actual time consumption for compilation divided by expected sales.,  , Examples of price calculations, Example of price calculation for a new research project, The following price calculation includes processing of the project proposal as well as data extraction on demographics (BEF), educational attainment (UDDA), income (FAIK and IND) as well as employment information (DREAM). The price calculation is based on a project with full register extraction where the user creates the population. , Since Research Services rounds up to the nearest whole number due to the standardised price calculation method, the price is calculated according to the following table., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 6, Data extraction from register > 15 variables, 0,  , Subtotal, 8 ,  , Additional services and consultancy (extra charge 20 per cent)*, 1 ,  , Total hours used, 9,  , Public user,  , 9 hours * 1,674.00 DKK = 15,066.00 DKK, Private user,  , 9 hours * 2,299.00 DKK = 20,691.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., Please note that the price calculation does not include population creation. If Research Services should create the population, this will be carried out based on a framework agreement., Example of price calculation for a new research project enriched with data from the Danish Health Data Authority, This price calculation includes processing of the project proposal, population creation (based on a framework agreement) as well as data extraction on demographics (BEF, BEFADR, VNDS, DOD) and registrations in the National Patient Register (LPR_ADM, LPR_BES, LPR_DIAG, LPR_SKSUBE). The population consists in persons with a consumption of some specific types of medicinal products found via variables in the Danish National Prescription Registry (LMDB2005-2015). These persons must not be registered as emigrated in the register ‘Historiske vandringer’ (VNDS), meaning that they must be marked INDUD_KODE=U. Furthermore, they must not be registered in ‘Døde i Danmark’ (DOD). Moreover, the population from Statistics Denmark is transferred to the Danish Health Data Authority for enrichment with data from the Danish Pathology Register. The processing and pseudonymisation of data from the Danish Health Data Authority are not included in the price., Assignment element, Time consumption, Price, Project proposal, 2, Data extraction from register, 14, Data extraction from register > 15 variables, 0,  , Subtotal, 16 ,  , Additional services and consultancy (extra charge 20 per cent)*, 4 ,  , Total hours used, 20,  , Public user,  , 20 hours * 1,674.00 DKK = 33,480.00 DKK, Private user,  , 20 hours * 2,299.00 DKK = 45,980.00 DKK, Framework agreement for the population creation, Assignment element , Estimated time consumption**, Price, Population creation, 5, Public user,  , 5 hours * 1,674.00 kr. = 8,370.00 DKK, Private user,  , 5 hours * 2.299,00 kr. = 11,495.00 DKK, *The additional service fee corresponds to 20% of the hours for processing of the project proposal, data extraction as well as other requirements (programing/data)., **After the population is created, the time actually sepnt by Research Services is billed at the hourly rate applicable at any given time.,  , Determination of the hourly rate, The hourly rate is determined once a year based on four part elements. The final hourly rate consists in a number of part elements including a development contribution of 3 per cent., Surcharge, : Income forecast for the current year and accumulated surplus/deficit from previous years, Overhead Statistics Denmark and externally funded activities, : Joint expenses, for example for staff, rent, electricity etc. and common administration of externally funded activities, such as maintenance of data bank of basic data, development of externally funded activities etc., Overhead Research Services, : For example, authorisation of new institutions, control of transferred files, sanctioning and general development of the microdata schemes and Statistics Denmark’s Data Portal etc.,  , Other services, Renting of disk space, Projects take up space on Statistics Denmark’s servers. For that reason, we have introduced renting of disk space, so that you as a user are made aware of how much storage capacity your project takes up on Statistics Denmark’s servers. You will only pay for disk space for active projects using a storage capacity over 5 Gigabyte (GB) on the servers. An active project is defined by a minimum of one user logging on to the project within a quarter., Disk space renting is charged on a quarterly basis, and you are invoiced for all projects for which your institution is data controller. For an individual active project using a storage capacity of more than 5 GB, the institution will be charged quarterly in units of 5 GB. Disk space renting will be charged, regardless of the reason for logging onto the project and how often during a quarter., Hosted server, Statistics Denmark also offers to host your own servers, which will be located at Statistics Denmark. , Read more about requirements and prices for hosted servers ,  , FAQ on prices, We have gathered some of our frequently asked questions on prices below., FAQ on prices, Why does the price vary from one assignment to the next?, An assignment is composed of several part elements. The assignment is priced based on the part elements of the assignment. This is why the price may vary, for example depending on the number of registers used for population creation, populations from other data providers or the number of registers from which the project needs data extraction. The part elements of the assignment are described in the section “Part elements of an assignment”., The hourly rate has changed over the years – why?, You can see the changes in the hourly rates of Research Services below., All institutions, 2013, 1,248 DKK, 2012, 1,187 DKK, 2011, 1,167 DKK, 2010 2nd half, 1,197 DKK, 2010 1st half, 1,229 DKK, 2009, 1,229 DKK , 2008, 1,229 DKK, Prices after 2014, Private institutions, Other public institutions, 2024, 2,130 DKK, 1,538 DKK, 2023, 2,130 DKK , 1,568 DKK,  , 2022, 2,130 DKK, 1,568 DKK,  , 2021,  2,168 DKK, 1,735 DKK,  , 2020, 2,202 DKK, 1,745 DKK ,  , 2019,  2,202 DKK, 1,607 DKK,  , 2018, 2nd half,  1,749 DKK, 1,050 DKK,  , 2018, 1st half,  1,749 DKK, 1,050 DKK,  , 2017,  1,650 DKK, 1,050 DKK,  , 2016,  1,650 DKK, 1,050 DKK,  , 2015,  1,750 DKK, 1,050 DKK,  , 2014,  1,650 DKK, 1,050 DKK, There are various reasons for the price changes., Each year, we adjust the hourly rate for surcharge, which accumulates the surplus/deficit of previous years. Moreover, we include an income forecast for the current year, which can cause variations from one year to the next., Public institutions are not allowed to generate a profit. For that reason, Statistics Denmark regularly adjusts the hourly rates so that they reflect the actual costs and make the accounts balance., In 2014, a distinction was made between private and public institutions, when Research Services for the first time received a special contribution from the coordinating organ for register research, KOR, among others, supporting the hourly rate for public users. This accounts for the difference in price depending on whether a private or a public institution owns the project., Why must I pay for other variables to be added to my project?, Changes in an already existing project must be described in the project proposal and/or the variables documentation. Furthermore, they must be documented and the approval must be renewed in Research Services.  The only exception that does not require renewed approval is an update of an already approved population or variable., The approval requires a number of processes, which can be anything from dialogue between you and Research Services to a review of the project and its variables documentation for renewed approval of the project. The process can vary considerably depending on the project, and the time consumption up until the approval is in the range of 1-4 hours whether for new projects, updates or extensions. The price of processing a project proposal is therefore set at two hours. If the time consumption exceeds four hours, a supplementary agreement is made in the form of a framework agreement to cover the actual processing time., We encourage you to make a professional assessment of when and how often you apply for approval of project changes,, so that we can reduce the number of ongoing and minor changes., For how long is a quotation valid?, A quotation is valid for 30 days starting from the date of the quotation. After that, we recalculate the quotation at the current hourly rate., How we charge for a project database? , The charge is based on an annual contract with a fixed-price agreement that includes update of agreed register data in the project database as well as a possible framework agreement for additional services, such as deliveries from the project database to sub-projects and consultancy according to the needs of the project database., The establishment of a project database follows the same pricing guidelines as a new project. Since the project database has a longer time perspective than a project, an annual contract on updating is entered. Thus, the pricing is based on an expected average time consumption for the service., The settlement period appears from the below table. The fixed-price agreement for updating of the project database is settled together with the Q2 settlement of ‘Additional services’. ‘Additional services’ are settled quarterly., Invoiced in the calendar year yyyy, Invoiced in the calendar year, The annual contract covers, Mid-January, Mid-April, Mid-July, Mid-October, Mid-January, Data extraction, Fixed-price agreement for data, Additional services, Consumption Q4 from the previous year, Consumption Q1, Consumption Q2, Consumption Q3, Consumption Q4, Why do prices of comparable services vary?, The price of services is based on past experience and averages. Comparable services may imply small differences in the various part elements that affect the price, for example, the price of processing external data (submitted from other data providers) compared to processing of standardised data extractions from registers in Statistics Denmark’s databank of basic data. If project changes appear later in the process, the price may change based on the changes. Furthermore, the hourly rate is calculated annually, which can also affect the assignment price., What is the background for Statistics Denmark’s prices?, Statistics Denmark is the central producer of statistics in Denmark, and the costs of carrying this obligation as an authority are covered by the Danish Finance Act., The data that we collect and store can be used for scientific and statistical surveys under Statistics Denmark’s researcher scheme. Only authorised research and analysis environments are granted access to data, and we charge for making data available for the surveys., In principle, the price must cover the costs associated with performing the assignments from the initial dialogue to the final dialogue no later than 30 days after the assignment has been delivered., The price must further contribute towards the costs associated with:, Consultancy on the use of data in the individual project., Administration of the scheme, for example authorisation, Data access rights, Standardisation of register data, Development of our user services, Securing continued high data security and data confidentiality, Overhead costs, Statistics Denmark’s pricing is subject to the rules on externally funded activities in the public sector and is checked by the National Audit Office of Denmark. Income and expenditure must balance, and the income from services must not be used to fund the obligations of the authority. The financial balance is continuously monitored across a ten-year average.

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

    Labour Force Survey (LFS)

    The Labour Force Survey is the most comprehensive continuous survey in Denmark. The survey is conducted quarterly and is based on a sample of the population. Each year 85,000 Danes aged 15-74 years participate. The Labour Force Survey in Denmark, called Arbejdskraftundersøgelsen (AKU), is the Danish contribution to the European Labour Force Survey and the survey is included in the unemployment statistics of Eurostat and the OECD. Data is collected and processed according to the same principles in all EU member states. The survey has been conducted continuously since 1994., The main purpose of the Labour Force Survey is to cast light upon the attachment of the population to the labour market. The population aged 15-74 years is generally divided into employed persons, LFS unemployed persons and persons outside the labour force., Furthermore the survey covers a range of other matters, and it is especially suited for:, Drawing international comparisons , Providing knowledge about unemployed persons who are not entitled to claim social benefits , Knowledge about youth unemployment (15-24-year-olds) , Specifications on working time. , In addition to the fixed questions, the questionnaire is regularly supplemented with additional questions with regard to a variety of subjects, e.g. disabled persons in the labour marker, work and family life or the transition to retirement.    , The results from the Labour Force Survey are published quarterly in the publication Nyt fra Danmarks Statistik (News from Statistics Denmark)., Quality Declaration, The quality declaration provides information about the Labour Force Survey. You can find information about the purpose of the survey, the possible applications and who the typical users of the survey are. Furthermore there is information about the basic definitions and the methodological prerequisites that the LFS is built upon. In addition the quality declaration contains contact information on the administration of the Danish LFS., Read , Quality Declaration: Labour Force Survey, Documentation, The documentation contains information on the methodological basis for LFS. Here you can find papers on the most central statistical and methodological changes influencing the development of the LFS. Also more in-depth explanation to external users of the LFS that wish to publish figures from the LFS can be found. Furthermore it is possible to get the survey questionnaire and the codifications applied in the LFS. At the same time you can get information on the special modules that are often linked to the LFS (the so-called Ad hoc modules)., Here is a range of information about the Labour Force Survey central to the documentation of the survey. For example how the questionnaire is constructed, which codifications are used and furthermore papers describing the conceptual and methodological conditions and developments in the Labour Force Survey. These papers are supplementary to the declaration of content of the LFS. In addition, guidelines for the use of data from the LFS are described., Read:, The LFS-questionnarie, Codification,  , Publishing LFS-data, Statistics Denmark has described some guidelines for the use of data from the LFS. The purpose is to assure quality in the analysis based on the LFS and furthermore inform external users of the LFS on e.g. sampling errors. It is possible to achieve knowledge about publishing limits on yearly and quarterly basis. For further information:, Paper on guidelines to inform external users,  , Paper on additional guidelines to inform external users,  ,  , Method, The incoming results from the Labour Force Survey are weighted before publishing the results for the entire population. The method of weighting has been revised several times over the years, which can influence the development in the figures of employment and unemployment at the aggregate level, as well as the developments of figures for subgroups., One should be aware of four revisions in the method of weighting: 2003, 2007, 2011 and 2015. In connection with the method of weighting in 2011, data going back to 2007 were revised. The present method of weighting was implemented in Q3 2015 and the method now includes a weighting method based on the panels. The new weighting method led to marginal changes in the data, and therefore the data was not revised back in time., The actual effect of the revision in the method of weighting in 2011 is described in the paper below. Here you can read about in which way the revision in the method of weighting has influenced the level of employment in general and additional the size of subgroups (i.e. age groups, part-time and fulltime employees, educational groups and employed/self-employed persons)., Paper on the 2011 weighting-method (practically), (Danish version) , The theoretical considerations behind the changes in the method of weighting as well as the gains the revisions have led to on the LFS, are described in the following document. Here one can read about the background and the motivation for the revisions. Among other things, the revisions has led to a more precise age distinction and improved use of help information from several registers., Paper on the 2011 weighting-method (theoretically), (Danish version), Prior to 2007 a method implemented in 2003 was used. This revision implemented a correction where sex is corrected according to secondary age groups. At the same time it is described how the register of unemployment (CRAM) was used to divide the LFS-unemployed in the survey., Paper on the 2003 weighting-method, (Danish version) , EU modules, The Labour Force Survey can be supplemented with additional questions, so-called “EU modules”. The main focus of the EU modules changes yearly, but at the same time the construction “rotates” meaning that the same subjects are repeated regularly. In Denmark, ¼ of the respondents participate in the survey during a year., How can one use the EU modules?, If your organization or firm is interested in the subjects from the EU modules, it is possible to:, • Gain access to data from already completed EU modules, • Link additional questions to forthcoming EU modules, • Get involved in the development of EU modules,  For an overview of the EU modules: , Information om EU moduler 1999 - 2025, (Danish version),  , Concepts, Here you can find definitions of the central concepts in the LFS e.g. who is counted as employed, LFS unemployed and outside the labour force. In addition there are a range of papers that deepens the LFS concepts on unemployment, employment and working time, and compare them with the concepts of the register-based labour force statistics., Concepts applied in the LFS, The definitions in the LFS comply with the guidelines as laid down by the ILO, the international labour market organization of the UN. The operationalization of the concepts is made by Eurostat, who coordinates the common European Labour Force Survey. The operationalization is hereby recommended by ILO and Eurostat., Read: , International definitions,  , The general definition of the attachment to the labour market is built up hierarchically implying that:,  , Employed , are: Persons, who in a given reference week have worked for payment for at least one hour, and persons temporarily absent from their job., For further information about the concept of employment in the LFS and other relevant statistics read , Paper on Employment concepts in the Labour Force Survey, National Accounts and Working Time Accounts, and for a brief overview read , Employment concepts, (Danish version).  , LFS unemployed, are: Persons, who are not defined as being employed, and who have actively been looking for work in the past four weeks, and furthermore are able to start a new job within two weeks. Unemployed persons in the LFS are not defined equally to unemployed persons in the registered unemployment. Despite this fact, there will be overlaps between the two statistics if the unemployed persons in the registers also meet the criteria defined in the LFS. Groups that will be present in both statistics are the following: , - , Net unemployed, : Persons who are actively seeking for and are ready to start a job (so-called match group 1), who receive unemployment benefits or social assistance and furthermore fulfill the criteria of LFS unemployment., - , Activated persons, : Persons in activation who receive unemployment benefits or social assistance and who are ready to start a job (match group 1) and furthermore fulfill the criteria of LFS unemployment. The net unemployed together with the activated persons ready to start a job form the group of , gross unemployment, .,  Other groups that will not be included in the registered unemployment but will be included in the LFS are:, - , Students, : This group will typically not be included in the registered unemployment, while this group receives educational support (SU) which is not an unemployment benefit. If students, as well as other persons, fulfill the definition of unemployment in the LFS, they are included in the LFS unemployment.   , - , Other LFS-unemployed, : Other LFS-unemployed is a group that can contain all the persons who fulfill the definition of unemployment in the LFS, but are not gross unemployed or students. This group is very inhomogeneous. Some of the typical groups will be unemployed who are not able to receive unemployment benefits or social assistance (i.e. because of their spouse’s income or because of a missing membership of an unemployment insurance or unemployed who are not ready to start a job (match group 2 and 3), but have still not surpassed to early retirement etc. and hereby left the workforce)). , Read more about the concept of unemployment in LFS and other statistics , Paper on Unemployment in LFS and other Danish statistics, (Danish version) and for an overview , Unemployment concepts, (Danish version)  , • , Outside the labour force are:, er: Persons, who neither comply with the employment definition, nor the unemployment definition. This could be minors, pensioners and students, who either do not have a job or have actively been seeking for a job.  , Other central concepts for the LFS are:, • , Reference week, : The specific week that the respondent is asked about. Whether you are employed or LFS unemployed, how many hours you have worked during the week etc., is related to the specific reference week. The date of the interview can be up to four weeks after the reference week, typically 1-2 weeks after. There are 13 reference weeks per quarter.,  • , Weighting method, : The way in which the sample is weighted to the entire population, in order to make the results as representative as possible. It is always weighted figures that are being published. The method of weighting practically means that each person participating in the LFS gets his or her own weight and hereby represents a specific sample of the population with regards to sex and age. The method of weighting has been revised several times over the years (read under “Documentation/Method” for more information).,  • , Sample bias (uncertainty), : This covers the general uncertainty connected to sample based surveys as the Labour Force Survey. The uncertainty is approximately +/- 10,000 persons on the general quarterly unemployment figure and approximately +/- 20,000 persons on the general quarterly employment figure.,  • , Seasonal adjustment, : A method that removes yearly recurrent patterns in the three time series: employment, unemployment and people outside the labour force. There is not introduced seasonal adjustment on more disaggregated levels. The purpose of seasonal adjustment is to take into account i.e. unemployment or employment caused by seasons that can affect the development.,  • , Working time, : The Labour Force Survey asks about three different types of working time in a specific reference week; usual, contractual and actual working hours. For more information about working time read , Paper on Working time in LFS and other Danish statistics, (Danish version), Other relevant statistics, Statistics Denmark is also publishing register based statistics compiling the population’s labour market status. For further details see the subject pages and the papers present on this site., For more information on the Register-based labour force, employment (RAS) , Labour force participation, For more information on the registered unemployment , Unemployment, For more information on the statement of employment in RAS, the Working Time Accounts (ATR) and Public Sector Employment (BFL) , Employment, Time Series, Here it is possible to get a description of the developments and breaks in the time series that have been analyzed more in-depth. There will be general information about the time series and short presentations of i.e. the employment series, unemployment series and the working time series., The LFS has been conducted since 1994 and in general it is possible to compile consistent time series based on LFS data going back to 2000. Continuous LFS tables from 1996 and onwards are available from Statistics Denmark’s database StatBank Denmark. However, following adjustments in the method of weighting, changes have been made in some data series. As a consequence, these cannot be used in monitoring developments in specific quarters or years. Developments in long durations of time can however be applied., It is furthermore possible to find yearly data for some selected estimates back to 1983 at Eurostat’s Stat bank. However the yearly data between 1983-1993 are based on results from the 2nd quarter and should therefore be treated with caution. , The employment series, In Statbank Denmark, you can find more data on Labour force status (AKU110A),  , The employment series measure how many persons are employed having minimum 1 hour of paid work or are temporary absence in the reference week. As figure 1 shows the total employment in 2000 initially was 2,700,000. The following two years until 2003/2004, employment is relatively stable. In 2004 the employment raises with 23,000 persons compared to 2003, which indicates a raise on 0.9 percentages. It is important to notice that the employment series was affected in 2003 when a new method of weighting was implemented, and the stratification of the sample was changed. Both these conditions made the number of employed persons rise and are the reason for the development from 2003-2004., In 2007 the sample was expanded and the panel structure changed, and furthermore data from 2007 and forthcoming have been revised on the basis of the method of weighting from 2011. This has led to a decrease in the estimated number of persons employed. The decline in the employment in the period of 2006/2007 is untypical, since the employment rises from 2005-2006 and again from 2007-2008. Consequently, caution should be made with respect to drawing conclusions on the basis of the development between the years 2006 and 2007, especially with regards to subgroups, while longer time series can be concluded upon., More details about the development in employment , Paper on Employment concepts in the Labour Force Survey, National Accounts and Working Time Accounts, The unemployment series, In Statbank Denmark, you can find more data on Labour force status (AKU110A), The unemployment series in the LFS is built upon the ILO definition of unemployment, where a person is unemployed if he or she is not employed in the specific reference week. Besides fulfilling this criterion, furthermore it is demanded that the person is actively seeking a job and is able to start working within 14 days. If the person does not fulfill these criteria, one is categorized as being outside the labour force and not LFS unemployed., At the same time one should take notice of the revisions in the method of weighting in 2003, 2007 and 2011. The latest revisions from 2011 revise the figures back to 2007., Consequently, caution should be made with respect to conducting analyses directly on the basis of the developments over the years 2003/2004 and 2006/2007, especially with regards to sub groups. In longer time series the before mentioned periods are not so problematic., More details about the development in unemployment , Paper on Unemployment in LFS and other Danish statistics, (Danish version), The educational series, The education series is also affected by the discontinuity in data series from 2006 to 2007. The percentage of the population aged 30-34 years with a higher education fell from 2006 to 2007 from 43 to 38 percentages. The percentage has risen since then and in 2009, 2010 and 2011 the percentage was once again above the 2020-goal (40 percentage). This development is a consequence of the 2011-weigthing method that has a better correction with regards to the bias on education caused by age. , This remarkable shift is first of all caused by the change in method of weighting in 2007. Before 2007 the LFS tends to have an overrepresentation of persons with higher education. With the implementation of the latest method of weighting from 2011 (that is revised back to 2007), the educational level falls. From here on the level of education in the LFS is more in compliance with the level of education in the register of education. The fall from 2006-2007 is thereby not a real decline in the educational level., For the educational series, the changes caused by the method of weighting are so significant, that one cannot make long-term analysis over the years 2006-2007. Therefore it is recommended to initiate time series in 2007., More details about the development in the educational series , Paper on the development in the educational level in the LFS , (Danish version), The working time series, The development in the average working time in the LFS (in hours), In Statbank Denmark, you can find more data on Average weekly hours of work in main job (AKU410A), In the Danish LFS there are three types of working time; the contractual, usual and actual working hours. The working time series do not contain any substantial changes in connection with the adjustment in 2006/2007 in general. However, this is not the case for the working time for persons aged 15-24 years. The average estimated working time has increased by one hour for persons aged 15-24 years from 2006 to 2007, which probably is due to the method of weighting. This must be taken into account in the case of long time series for the working time of young people. In line with this change, there has also been a shift from the group of persons working “1-15 hours” to the group of persons working “38-48 hours” among young people. However, this is primarily the case between the 4th quarter of 2006 and the 1st quarter of 2007. Subsequently, there is again a fall that is instrumental in reducing the general change in the level, which implies that the shift is problematic only to a minor degree., More details about the development in the working time series , Paper on Working time in LFS and other Danish statistics, (Danish version), Tailor-made analyses, Here it is possible to gain information on tailor-made analyses coupled to the LFS. One can include questions in the Danish LFS and furthermore it is possible to ask for special analysis on existing data., What are your needs?, If your organization or firm is in need of new or updated knowledge about the labour market e.g. social engagement, working time or undeclared work, the LFS is a straightforward alternative to initialize a survey from point zero., How can you use the LFS?, The Labour Force Survey makes it possible to carry out special analyses that are based on the regular analyses of the LFS i.e. by introducing questions or tailor-made analyses., In this regard, tailor-made analyses, are specific operations of data from the LFS that are not published elsewhere (i.e. in Statbank). An example of this could be the number of part-time employees that works nighttime in the capital area or how many people with the highest educational level that are currently working on temporary basis etc., Special analyses, cover variables defined by the user that are included in the questionnaire. These variables can be measured against all other variables from the LFS as well as variables from registers. An example of this could be the number of working accidents or the satisfaction one has with the membership of a union etc. This can be linked to the additional results from the LFS. Special analyses will be developed in close connection with the staff of the Danish LFS., Advantages, By using the LFS to get your specific subjects examined, you will have access to the staff of the LFS’ expertise, infrastructure, our respondents and other data., We can promise a flexible solution that suits you well. We are able to deliver data three months after the quarter terminates., The costs, The prize of tailor-analyses is depended on the numbers of interviews, the audience, the panel structure, which quarter is chosen, as well as the preparations and the complexity of the questions (simple or complex).,  , More information, For further information about the LFS feel free to contact us: +45 39 17 34 00 or write an email to one of the employees from the Labor Force Survey.

    https://www.dst.dk/en/Statistik/dokumentation/metode/aku-arbejdskraftundersoegelsen

    Rules on transfer of analysis results

    Users of Statistics Denmark’s Researcher machines must comply with Statistics Denmark’s rules and guidelines on transfer and data security. Non-compliance may involve sanctions. Read here what you can transfer and how to do it., Never transfer data that includes microdata, Data that includes microdata may never be transferred, not via the transfer tool nor in any other way, for example by transcribing information from Statistics Denmark’s researcher machines, taking a screendump or a photo of the screen with you mobile phone. , Read more under Rules for working with microdata, Transfer of analysis results – what is allowed? , As a user of Statistics Denmark’s researcher machines, you can transfer analysis results and other material, when all three conditions have been met:, All data with information on individual/enterprise level and pseudonymised key variables has been removed, so that neither direct nor indirect identification or recognition of, for example, individual persons, households, families or enterprises in the material is possible. Read further below under ‘What is microdata’, and , Your material has been subjected to sufficient statistical disclosure control, so that you cannot neither directly nor indirectly identify or recognise individual units, for example, individual persons or enterprises.  Read further below under ’Statistics Denmark’s rules on statistical disclosure control – in brief’, and, The file type of your material is approved for transfer and the transfer happens via the transfer tool in Denmark’s Data Portal (DDV). Read further below under ’Transfer via transfer tool in DDV - guide’ and ’Transfer via transfer tool - allowed file types’, When you have transferred your analysis results or other material in compliance with all three conditions, you are allowed to continue processing them on your own server, for example by making charts or performing analyses in statistical programmes., Note, : Statistics Denmark’s rules on transfer and data security apply for all data on Statistics Denmark’s researcher machines. This includes data you have been granted access to via Statistics Denmark as well as external data that has been transferred from other providers or own sources. Non-compliance may involve sanctions. , Read more under Sanction rules,  , What is microdata?, Statistics Denmark defines microdata as data related to single observations, except for sex, age, industry and municipality/sector. Examples of microdata include:, Pseudonymised key variables, that refer directly to an individual person, household, family or enterprise, for example, PNR (civil registration numbers), CVR numbers, establishment numbers, address codes such as BOPIKOM and FAMILIE-ID, etc., Data sets or parts of data sets, that hold background information such as income, education and socio-economic status, or calculated variables on an individual level, where the pseudonymised civil registration number has been removed. The same applies to data on enterprises., The main objective of Statistics Denmark’s Data Confidentiality Policy is to ensure that microdata made available through the microdata schemes cannot be used to identify individual persons or enterprises. This is why all analysis results and other materials must be completely stripped of microdata, before these can be transferred. , Are you in doubt about the rules? This is how you get answers , If you have questions about the rules, or if you are in doubt whether your material for transfer contains microdata, you may not transfer until you have found guidance. You can find further guidance in Statistics Denmark’s guide materials: , Rules for data safety under the microdata schemes (pdf), If you do not find the answer here, you should seek guidance from a more experienced user in your institution. Make sure that the person you are asking for guidance has access to the same project as you, before you show your screen to that person and receive specific guidance. , In case of questions of a more general nature, you can also contact Research Services at , FSEHjemtag@dst.dk, . In your request, you must indicate your ident and, if relevant, your project number. , Note, : If you want to describe a data set or what you suspect could be microdata, you must never include actual data or information. Always use fictitious figures and examples., Statistics Denmark’s rules on statistical disclosure control for personal data – in brief, As a main rule, analysis results, aggregate tables or figures may only be transferred, if it is not possible neither directly nor indirectly to identify or recognise individual units, such as individual persons or households. This is why Statistics Denmark requires that analysis results and other material for transfer be subjected to statistical disclosure control. Below, you will find a description of the rules on statistical disclosure control for personal data. , Personal data – Statistics Denmark’s statistical disclosure control requirements , The requirements for statistical disclosure control in relation to personal data determine that analysis results or other material that is requested transferred from Statistics Denmark’s researcher machines may not contain information on individual units. In practice, this means that it must not be possible to identify, recognise or obtain information on individual persons or enterprises, neither directly nor indirectly, in the transferred material., Statistics Denmark’s requirements for statistical disclosure control applicable for personal data are:, There must be , minimum 3 observations per table cell, for transfer of analysis results or other material from Statistics Denmark’s researcher machines to be allowed. The requirements may be stricter for some registers, for example minimum 5 observations per table cell. If this is the case, it will be indicated in Denmark’s Data Portal when you order data., For formats that do not include table cells, such as figures or graphs, a good rule of thumb is that they should have at least 3 observations per table cell if converted to tables. If this is not the case, further aggregation is required. Aggregation means merging of cells/figures until they comply with the statistical disclosure control requirement and ensure anonymity., It must not be possible by backward calculation or cross reading to deduce observations that have been aggregated or otherwise obscured or removed in a table, graph or figure. If this is possible, further aggregation is required., Note, : The above description is intended only as a guide. The final responsibility that your material has been subjected to sufficient statistical disclosure control lies with you as user. The level of aggregation depends on a specific assessment of your material, and if you are in doubt whether 3 or in some cases 5 observations are enough to ensure anonymity, you should aggregate further. , You can find further guidance and examples in Statistics Denmark’s guide materials: , Rules for data safety under the microdata schemes (pdf), Are you in doubt? This is how you get help, If you are in doubt whether your file complies with Statistics Denmark’s requirements for statistical disclosure control, you must refrain from transfer until you have aggregated your material further or received guidance from a more experienced user in your institution. Make sure that the person you are asking for guidance has access to the same project as you, in order for you to be allowed to show your screen to that person and receive specific guidance. , In case of questions of a more general nature, you can also contact Research Services at , FSEHjemtag@dst.dk, . In your request, you must indicate your ident and, if relevant, your project number. , Note, : If you want to describe a data set or what you suspect could be microdata, you must never include actual data or information. Always use fictitious figures and examples., Statistics Denmark’s rules on statistical disclosure control for business data – in brief, As a main rule, analysis results, aggregate tables or figures may only be transferred, when it is not possible neither directly nor indirectly to identify or recognise individual units, such as enterprises. This is why Statistics Denmark requires that analysis results and other material for transfer be subjected to statistical disclosure control. Below, we go through the main rules for business data., Business data – Statistics Denmark’s statistical disclosure control requirements, The requirements for statistical disclosure control in relation to business data establishes that analysis results or other material that is requested transferred from Statistics Denmark’s researcher machines, may not contain information on individual units. In practice, this means that it must not be possible to identify, recognise or obtain information on enterprises or workplaces, neither directly nor indirectly, in the transferred material. , Statistics Denmark’s requirements for statistical disclosure control applicable for business data are:, There must be minimum 3 observations per table cell to allow transfer of the analysis results or other material from Statistics Denmark’s researcher machine. For formats that do not include table cells, such as figures or graphs, a good rule of thumb is that they should have at least 3 observations per table cell if converted to tables. If this is not the case, further aggregation is required. Aggregation means merging of cells/figures until they comply with the statistical disclosure control requirement and ensure anonymity., It must not be possible by backward calculation or cross reading to deduce observations that have been aggregated or otherwise obscured or removed in a table, graph or figure. If this is possible, further aggregation is required., In case of analysis results on operating economy variables, it must be taken into account that individual enterprises must not dominate the data set so that publication of the total exposes too much. In practice, this means that the one or two biggest statistical units (enterprises) combined must not account for more than 85 per cent of the total. You can read about the statistical disclosure control methods by the dominance rule in , Statistics Denmark’s Data Confidentiality Policy, , pp. 15-17. , Note, : The above description is intended only as a guide. A sufficient level of aggregation depends on a concrete assessment of your material, and you, as a user, has the final responsibility that your material ensures anonymity. , You can find further guidance and examples in Statistics Denmark’s guide materials: , Rules for data safety under the microdata schemes (pdf), Are you in doubt? This is how you get help, If you are in doubt whether your file complies with Statistics Denmark’s requirements for statistical disclosure control, you must refrain from transfer until you have aggregated your material further or received guidance from a more experienced user in your institution. Make sure that the person you are asking for guidance has access to the same project as you, before you show your screen to that person and receive specific guidance. , In case of questions of a more general nature, you can also contact Research Services at , FSEHjemtag@dst.dk, . In your request, you must indicate your ident and, if relevant, your project number. Note: If you want to describe a data set or what you suspect could be microdata, you must never include actual data or information. Always use fictitious figures and examples., Transfer via the transfer tool via Denmark’s Data Portal - guide, Unless a special agreement has been entered, any transfer from Statistics Denmark’s researcher machines must happen via the transfer tool in Denmark’s Data Portal (DDV). The process takes place in three steps: First, you must upload the files that you want to transfer. Then you must check the files, and eventually, you can download them to your own computer., When the files are uploaded, they will be scanned for possible microdata, so that you can get a warning before you transfer the material, in case is contains data that resembles microdata. In this way, you can correct any errors and avoid breaches. , Note, : The scanning tool is a supplement and cannot replace manual checking. You as a user has the final responsibility that your material has been subjected to sufficient statistical disclosure control and does not contain microdata., Step-by-step guide for transfer and downloading of files, Upload the files, To upload files for transfer, you must use the Researcher machine. First log into remote.dst.dk, and then log into the server to which your project is linked. When you log into the Researcher machine, you will see a number of tools on the remote desktop, including the shortcut “Transfer”. If you click this, an application will open in your web browser, and you will be taken to a page where you can upload files from your project’s work folders for transfer. , Here you can read about Statistics Denmark’s guidelines for transfer of analysis results., Please note that through Denmark’s Data Portal (DDV), you can find information on which server your project is located on, your project-specific username, as well as the option to reset your password for logging into the server., Select which files you want to transfer either by clicking ‘Add files’ or by dragging the files to the page. You can both add individual files and whole folders of files. Note that you can only select files of the allowed file type and size. Read further below under ’Transfer via transfer tool in DDV - allowed file types’ If you select a file that cannot be transferred, you will get an error message., When you have selected the files that you want to transfer, click the button ‘Check’., Check the files, You will now be taken to the page that scans and checks for possible microdata. On the page, you can once more read the guidelines for transfer of files., If you get a risk warning that a file may contain microdata, it is mandatory to add a comment with information on what the file contains. The comment is needed for Research Services’ checking of transferred files. You will be guided on the page. If you find out that you have forgotten to add a file, you can easily navigate back and forth between the upload page and the check page., Before you can transfer the files, you must approve that the selected files comply with Statistics Denmark’s Data Confidentiality Policy and the guidelines for transfer. You approve this by clicking the field next to ‘Approve transfer’. When you have done so, you can transfer the files by clicking ‘Transfer’. You will then get a message saying that your files have been sent from the researcher server., Download the files to your own computer via Denmark’s Data Portal, You are now ready to download the files you have just transferred. To do so, you must log into Denmark’s Data Portal (DDV) in the same way as usual. , Once you have logged in, click ’My overview’. Find the relevant project under the ‘Projects’ tab, and then click the tab ‘Transfers’. Here you will find all the files that have been transferred for the project in question. The files are sorted by the date of transfer., When you click the separate date, you can see all the files that you have transferred on that day. You can also see which comments you have made earlier for the file by clicking the speech bubble, and you can delete the file by clicking the wastebasket., You download the files to your own computer by clicking the downward arrow., Problems transferring?, If you have problems transferring via the transfer tool in Denmark’s Data Portal (DDV), please write to , forskningsservice@dst.dk, ., Transfer via the transfer tool – allowed file types, Only file types approved by Statistics Denmark can be transferred. If you try to upload a file of a non-approved file type, you will get the message: “File type not allowed" in the system. , Note, : Changing the file extension in relation to the file content is not allowed., Allowed file types for transfer from Statistics Denmark’s researcher machines, File type, File extension, Spreadsheet, xls, xlsx, xlsm, xlm, xml, csv, ods, Text, tab, txt, HTML, htm, html, mht, Logs, Log, Latex, Tex, PDF, Pdf, Word, doc, docx, rtf, Programme code, sas, r, do, doh, ado, SAS, lst, sas7bdat, SPSS, sps, sav, spv, Stata, dta, smcl, Graphics, eps, png, wmf, tif, jpg, gif, emf, jpeg, svg, bmp, tiff, Other, ppt, pptx, pptm, odp, Problems, questions or requests? Contact Research Services, If you have problems transferring via the transfer tool in Denmark’s Data Portal (DDV), please write to , forskningsservice@dst.dk, ., Statistics Denmark’s control efforts – control screening and samples, Research Services check the transfer of analysis results under Statistics Denmark’s Microdata schemes by means of a system-supported control tool in Denmark’s Data Portal (DDV) as well as by sampling. The purpose is to ensure that microdata are not transferred and that Statistics Denmark’s statistical disclosure control requirements are observed. , In Research Services’ control screening of transferred materials from Statistics Denmark’s researcher machines, three file types are sampled for control, including: , Files that are risk marked (i.e. files with content that resembles microdata), Files exceeding the maximum size of 1 MB, Files that cannot be scanned  , In addition, 10 per cent of the transferred files from the researcher machines are randomly sampled for checking. , If Research Services’ identifies a breach when checking, it can lead to sanctions. , Read more under Sanction rules,  , Data security and transfer – your responsibility, As a user of Statistics Denmark’s researcher machines, it is your responsibility to familiarise yourself with Statistics Denmark’s rules and to observe them. This means that:, You are responsible for your work on the researcher machines being compliant with Statistics Denmark’s data security rules. Read more under Rules for working with microdata  , You are responsible for transferring analysis results and other materials in compliance with Statistics Denmark’s transfer rules, and, You are responsible for notifying Research Services immediately, if you suspect that you or someone else has breached Statistics Denmark’s data security and transfer rules  , Non-compliance may involve sanctions. , Read more under Sanction rules ,  , Breach of the rules? This is how you handle it, If you fail to comply with Statistics Denmark’s rules or you suspect that you have failed to do so, you have a duty of notification. If you comply with your duty of notification, this will be regarded as a mitigating circumstance., Please notify both the person responsible for authorisation in your institution and Research Services. You notify Research Services by sending an email to , FSEHjemtag@dst.dk, with the following: , Your ident , Project number, if any, A description of the breach or where you suspect a breach, Date and time of the breach , If the breach involves files, for example files you have transferred, image files on your computer, in your mailbox or similar, you must delete them immediately from your PC, Denmark’s Data Portal, mail folders etc. and inform about this in your email to Research Services. , Guides, agreements and documents in relation to data security and responsibility, Statistics Denmark’s data security rules under the Microdata schemes, Rules for data safety under the microdata schemes (pdf), Statistics Denmark’s information security and data confidentiality policy , Information security and data confidentiality policy – Statistics Denmark, Agreements (in Danish), Autorisationsaftale (pdf), Databehandleraftale (pdf), Tilknytningsaftale (pdf), Brugeraftale (pdf)

    https://www.dst.dk/en/TilSalg/data-til-forskning/regler-og-datasikkerhed/regler-for-hjemtagelse-af-analyseresultater

    Data from other sources

    Here you can get an overview of data from other sources than Statistics Denmark., COVID-19 test data and vaccination data from SSI (Statens Serum Institut), Statistics Denmark has entered into an agreement with SSI (Statens Serum Institut) on making COVID-19 test data and vaccination data available to researchers under Statistics Denmark’s microdata schemes., COVID-19 testdata, includes people who from February 2020 have taken a COVID-19 PCR test and/or antigen test (rapid test) with the microbiological departments, TestCenter Danmark, private COVID-19 test providers or municipalities, schools and educational institutions that can report to MiBa (test data for all test results) via various solutions and technical levels., COVID-19 vaccination data, includes citizens who have taken a COVID-19 vaccination, who have a Danish civil registration number, are alive and have an active address in Denmark on the date of the data extraction, as well as people who were alive and had an active address in Denmark on 27 December 2020 (vaccination data)., See SSI’s documentation for COVID-19 data, Denmark's Study Survey by the Ministry of Higher Education and Science, Statistics Denmark has entered into an agreement with the Ministry of Higher Education and Science on making survey data from Denmark’s Study Survey available to researchers under Statistics Denmark’s microdata schemes., Data will be released as register UFM_STUD for reference years 2018 and 2020 and subsequently every other uneven reference year., The variable content in the register is listed under , Register- og variabeloversigter, and described in more detail in the below documentation., Spørgeskemaer, Spørgeskema - Studerende 2023 (pdf), Spørgeskema - Studerende 2021 (pdf), Spørgeskema - Studerende 2020 (pdf), Spørgeskema - Studerende 2018 (pdf), Kodebog, Kodebog (xlxs), Metodenotater, Metodenotat - Studerende 2023 (pdf), Metodenotat - Studerende 2021 (pdf), Metodenotat - Studerende 2020 (pdf), Metodenotat - Studerende 2018 (pdf), Data from the Danish Health Data Authority, The Danish Health Data Authority's Research Service does not enter into agreements on data disclosure for projects at Statistics Denmark until Statistics Denmark has approved the project. , When you apply for disclosure of data from the Danish Health Data Authority for a new project with Statistics Denmark, the Health Data Authority’s Research Service must thus see the documentation showing that the project has been created and approved by Statistics Denmark. You can submit the documentation in the form of the approved project proposal that you receive as a pdf file from Statistics Denmark., You can create the project proposal with the Health Data Authority while waiting for approval of your project proposal from Statistics Denmark. Your application will be put on hold until the Health Data Authority has received an approved project proposal, but it is possible to make an agreement so that they continue the review process. However, you should be aware as a researcher that the Danish Health Data Authority will invoice you for the time they spend reviewing the case, and this also applies if Statistics Denmark does not approve the project., The trans-regional register for the Oresund region, In connection with the establishment of the Oresund statistics and the Oresund databank, a so-called trans-regional register has also been established linking all relocation, commuting and payroll data across the Oresund region in the period 2001-2015. This Research register was established in connection with the establishment of the ØRESTAT statistical bank for the Oresund region., The trans-regional register is structured as three separate datasets, which can be combined via a common serial number system., Dataset 1 contains relocation data for relocation across the Oresund strait., Dataset 2 is a corresponding commuting dataset, where the commuting is delimited by rules corresponding to those of the national commuting statistics, i.e. the main activity must take place on the other side of the Oresund strait., Dataset 3 includes everyone who has earned wages across Oresund, regardless if the person is categorised as a commuter., Note that the register is no longer being updated, and that the most recent data is from 2015., If you have enquiries about access to the register, please write to , forskningsservice@dst.dk, The DREAM database, The longitudinal database, DREAM, belongs to the Danish Ministry of Employment and is managed by The Danish Agency for Labour Market and Recruitment. The database contains employment information and other basic personal data, and the documentation below gives a more detailed description of it., Statistics Denmark has made an agreement with the Danish Agency for Labour Market and Recruitment on access to DREAM under the researcher scheme. Research projects that are to use data from Dream can gain access via Statistics Denmark Research Services., DREAM - Manual - Version 51, Handicnota, The HANDICNOTA register includes people who are dyslexic, visually impaired or have another disability that prevents them from reading regular printed text., Data has been obtained from NOTA (Danish Library and Expertise Centre for people with print disabilities). The register only has information about the disability reported to NOTA for each member, meaning either dyslexia, visual impairment or another disability. In addition to the three categories of disability, the register contains a fourth member group of teachers. This group needs to renew their NOTA membership each year as opposed to the other three member groups., The documentation of the register is available under , Forudsætninger for brug af HANDICNOTA, Aid package data from the Danish Business Authority, Since the end of May 2020, it has been possible to gain access to aid package data in the form of compensation for loss of earnings in Research Services’ databank of basic data., Two datasets on compensation for loss of earnings, The compensation for loss of earnings data are in two separate registers: LONKOMP - compensation for employees and KOMPSEL - compensation for self-employed persons., The data has been updated weekly in the databank of basic data upon reception of the aid package data from the Danish Business Authority. On 4 September 2021, data was released for the last week of the aid packages, which expired at the end of August 2021. In the subsequent weeks, data has been updated on a regular basis as the Danish Business Authority has completed its review of the applications. Weekly updates have continued up to and including week 18 in 2022, after which the deliveries from the Danish Business Authority are made occasionally and so are the present and future updates in the databank of basic data., A dataset on fixed costs, Data for the third aid package on fixed costs is available in the register KOMPFAST - compensation for fixed costs. This data has been available since the end of September 2021. Weekly updates have continued up to and including week 18 in 2022, after which the deliveries from the Danish Business Authority are made occasionally, which is reflected in the present and future updates in the databank of basic data., You can see the registers’ content of variables in our lists of research variables, , forskningsvariabellister, The rent register, Statistics Denmark has entered into an agreement with the National Building Fund on making the rent register available to authorised institutions under Statistics Denmark’s microdata schemes. The rent register was established in 2013 and is based on reports from the housing organisations in the non-profit sector., The rent register has information on for example:, The housing organisations, The housing departments, Social housing at tenancy level,  , Huslejeregister - Feltbeskrivelser (pdf), Regnskabsdata - Feltbeskrivelser (pdf), Stamdata - Feltbeskrivelser (pdf),  , If you have enquiries about access to data, please write to Sigrid Krogstrup Jensen, , SIJ@dst.dk, ., Account-specific data from the Tax Administration, Statistics Denmark has entered into an agreement with the Danish Tax Authority on making account-specific data from IRTE, URTE, PANT available to businesses and researchers under Statistics Denmark’s microdata schemes., This agreement is part of a research infrastructure project called DRDS, giving researchers access to a range of recent data. DRDS is a collaboration between Copenhagen Business School, Statistics Denmark, University of Copenhagen, Roskilde University, University of Southern Denmark, Aalborg University, National Centre for Social Research and Analysis, Danmarks Nationalbank, the Secretariat of the Economic Council, and the Rockwool Foundation Research Unit., Data contains information on:, Deposit rates (IRTE) for individuals IRTEPERS 2003-2021, Deposit rates (IRTE) for businesses IRTEVIRK 2003-2019, Lending rates (URTE) for individuals URTEPERS 2003-2021, Lending rates (URTE) for businesses URTEVIRK 2003-2019, Mortgages (PANT) for individuals PANTPERS 2003-2021, Mortgages (PANT) for businesses PANTVIRK 2003-2019, Data is described in more detail in the list of variables below, Variabelliste - IRTE URTE og PANT (pdf), The National Patient Register (LPR), Since 1977, the Danish Health Data Authority’s National Patient Register has functioned as the central registry for information about hospital patients. Statistics Denmark makes National Patient Register (LPR) data available to researchers. In Statistics Denmark, the LPR contains a multitude of particulars on examinations and treatments for all contact with the Danish hospital system, including hospitalisation and outpatient treatment., The reporting to the National Patient Register version 2 (LPR2) transitioned to a new data format (LPR3) between 1 January 2019 and 3 March 2019. The transition occurred gradually from LPR2 to LPR3, and therefore, there are reports in both LPR2 and LPR3 during this period. After 3 March 2019, reporting in LPR2 was closed, and all reports after that date are registered in LPR3., LPR2, Statistics Denmark has LPR2 data from 1977 to 2019., The LPR is a dynamic register that has been continuously updated – even retrospectively. Statistics Denmark has the updated versions of all LPR tables for the years 2005-2019., For hospital admissions to somatic departments, the register dates back to 1977. Emergency room and outpatient contacts have been registered since 1994. Hospital admissions to psychiatric departments have been registered since 1995. Hospital admissions to private hospitals have been registered since 2002., For documentation, see eSundhed.dk: , Documentation of LPR2 (in Danish), For information on data and data breaks (Data from other sources and data breaks in LPR2), see below:, Rates:, DRG and DAGS are not part of LPR, but can be linked to the individual admission and contact via the admission ID (recnum). Research Services has rates from 2002 to 2018., Non-finalised hospital admissions / out-patient contacts (UAF_):, The non-finalised outpatient admissions exist in the LPR that Statistics Denmark has available for the years 1994 onwards., LPR clean-up:, Up to and including 2009, The Danish Health Data Authority made an LPR clean-up, consisting in: , Sorting out all departments with special codes in the range 60-69, Sorting out all healthy companions, DZ763, Sorting out individual departments, for example departments with names such as ’Forskningsafdeling’ (research department)., Other data break, There may be other data breaks that we are unaware of., LPR3_F (researcher-oriented LPR3 data model), Statistics Denmark has LPR3_F data from the Danish Health Data Authority for the years 2019-2021, which can be ordered. The names of the registers begin with LPR_F_ and appear from the , register overview (in Danish), ., Please read , the Health Data Authority’s guide for LPR3_F (in Danish), , before you make a request for data., Medicine statistics register (Lægemiddelstatistikregisteret), Statistics Denmark has made an agreement with the Danish Health Data Authority on access to pharmaceutical products data under Statistics Denmark’s researcher scheme. For a more detailed description of the data content, see the , website of the Danish Health Data Authority, ., If you want access to pharmaceutical products data for your project at Statistics Denmark, you must apply to the Danish Health Data Authority for access. You apply via an online application form, and you must submit a project description, a description of the data extraction and a completed data order form., On the Research Services website, you will find , guidance on how to apply for access., ., When you apply for access to pharmaceutical products data, there are special requirements to the content of your application. On the Research Services website, you will find a , guide for applying for access to pharmaceutical products data, ., When you have the above in place, you can apply for access to data via Statistics Denmark using the application form (in Danish) at , Gå til ansøgningsskema, on the Research Services page., The Birth Register, The Birth Register holds information about all hospital and home births in Denmark and contributes with data for medical research., The Danish National Archives, Statistics Denmark has entered into an agreement with the Danish National Archives on making their data available to researchers via Denmark’s Data Portal., The National Archives collect data from the public administration and Danish research environments, and this data can be relevant for Danish register research, either because data is older than the official statistics registers or because data has a higher degree of detail. Access to data is governed by the Danish Archives Act, which is why there is a special application process for data from the Danish National Archives. This means that all researchers who are active on the project must have permission from the Danish National Archives. If data includes personal data, the National Archives must obtain consent for the permission from the Danish Data Protection Agency before the personal data may be disclosed. If data is less than 20 years old, the National Archives must also obtain consent for the permission from the authority that originally collected the data., The multi-generation register – Lite, The multi-generation register – Lite (MGR-lite) contains family relations for all Danish citizens born around 1953 or later. This means that it contains family relations from 7 years prior to those of the Civil Registration System (CPR). Until 1978, the Civil Registration System deleted information on family relations when an individual turned 18 years, but the National Archives have maintained snapshots of the Civil Registration System from e.g. 1968, 1969 and 2013, which in MGR-lite have been used to recreate family relations back to 1953., If you need data from MGR-lite for a research project, note that all participants in the project must obtain permission from the Danish National Archives, and that the National Archives must obtain consent from the Danish Data Protection Agency and the CPR registry, before data may be disclosed for the research project. Accordingly, you should expect a processing time of at least 1-3 months., You can apply for access to data from MGR-lite via Denmark’s Data Portal., Read more about access to data in Denmark’s Data Portal, You can find more information on MGR-lite at the Danish National Archives (in Danish), Contact , Researcher Service at the National Archives, if you have further questions., Ordering data from the Danish National Archives via Denmark’s Data Portal, It is possible to request data from the National Archives via Denmark’s Data Portal. In addition to Statistics Denmark, the National Archives must also approve the project proposal, which is why there is a different procedure for project proposals where this data has been opted for. Please note that this may increase the processing time by 1-3 months., Basic principles for requesting data from the Danish National Archives, Data relevance and data minimisation, The statement of the purpose of data must be specific, precise and easy-to-understand., The combination of register units and types of populations must be justified., Additional data must also be covered in terms of relevance to society/purpose/description., The proposal must constitute the project overview, while the appendix holds the details, It must be possible to read the proposal and the appendix both separately and as coherent documentation of a project., The proposal is also sent to the Danish National Archives for approval, This means that the institution administrator or contact person with powers will be asked to enter the following information for each researcher associated with the project. Civil registration number, address, city and postal code., Requesting data from the National Archives, Complete the project proposal in Denmark’s Data Portal:, Start by filling in the purpose of the project proposal, description and relevance to society. Data from the National Archives is selected in the same way as data from other registers., Adding the Danish National Archives as an external authorising authority:, When Research Services has approved the project proposal, the institution administrator or contact person with powers must send it to the National Archives for further approval. This is done from the project proposal page by selecting the button ‘Submit to external authority’., Enter necessary information for the Danish National Archives:, When the project proposal is to be submitted to the National Archives, the institution administrator or contact person with powers will be asked to enter the following information for each researcher associated with the project: Civil registration number, address, city and postal code. This must be done for all researchers all at once. This information is necessary, as the National Archives have their separate principles and requirements. This information is not saved in Denmark’s Data Portal for GDPR reasons. If you break off while entering information, you will thus need to enter the information again., Await approval from the National Archives:, After the project proposal has been submitted to the National Archives, its status will be ‘Pending external authority’ in Denmark’s Data Portal. The National Archives will review the project proposal and send you either an approval or a rejection via e-boks., Handling of approval:, When a researcher receives approval in e-boks, he or she also receives a document that must be signed before the data can be delivered. Note that all researchers associated with the project must sign., When each researcher has received and signed the approval, an administrator or contact person with powers must mark this in the project proposal. This is done by clicking ’…’ at the top of the project proposal page. Pay attention to the fact that all researchers must be marked all at once when they have signed the approval., After this, the project proposal can be sent for signature with the signatory of the institution. When all researchers have been marked as approved and ‘Send for signature’ has been selected in the dialogue box, the status of the project changes from ‘Submitted to external authority’ to ‘Approved by external authority’. Now the institution’s signatory can sign the document, and the project is approved. The Danish National Archives and Statistics Denmark will provide data for the project., If the institution’s signatory refuses to sign, the project proposal is returned and the process must be repeated., Handling rejections, If a project receives a negative response, there are three options:, Remove the project access for the researcher(s) who received a negative response. Access the project page and remove the researchers who have received a negative response. When the researchers are removed, an email will be sent from Denmark’s Data Portal to the National Archives notifying them that the researchers are removed from the project. Subsequently, the National Archives will be able to assign data to the project., Withdraw the project proposal if it could not obtain approval from the National Archives. When the project proposal has status as ‘Submitted to external authority’, administrator and contact person have an option to “withdraw” it. In that case, the project proposal will get a new status ‘Pending revision’. When the project proposal has status as ‘Submitted to external authority’ and it is withdrawn, Denmark’s Data Portal will send an email to the National Archives notifying them that the project proposal has been withdrawn. Revise the original project proposal and resubmit it for approval. It is important to note that the project proposal also must be re-approved by Statistics Denmark., Withdraw the project proposal, remove the National Archives register and resubmit the project proposal for approval., In this scenario, only Statistics Denmark has to re-approve., Adding new users to the project after creation, To add a new user after both Statistics Denmark and the National Archives have approved the project, the institution administrator or contact person with powers must go to ‘Project access’, click ‘Add’ and select the person to be added. A window is opened where the researcher’s civil registration number, address, city and postal code must be entered. When the researcher has received approval in e-boks, the institution administrator or contact person with powers can give access to the project. This is done by selecting ’…’ next to the project access and then select ’Confirm approval from external authority’., National Agency for IT and Learning (STIL), Statistics Denmark has made an agreement with the National Agency for IT and Learning (STIL) on access to central registers from the STIL statistical resources under Statistics Denmark’s microdata schemes. Research projects that are to use data from the comprehensive STIL registers can gain access via Statistics Denmark Research Services., Elevfravær i grundskolen, contains information about the number of days pupils in primary and lower secondary school are absent due to illness, absent with permission and absent without permission on a monthly basis., Den nationale trivselsmåling i grundskolen for 0.-3. klasse, contains replies to questions from the question frame for pupils in primary school, which is part of the national survey of the well-being of schoolchildren., Den nationale trivselsmåling i grundskolen for 4.-9. klasse, contains replies to questions from the question frame for pupils in secondary school, which is part of the national survey of the well-being of schoolchildren. It also contains calculated indicators for social well-being, academic satisfaction, support and inspiration as well as their satisfaction with school in general., Nationale test i grundskolen (recalculated results 2014/2015 – 2021/2022), contains test results from the mandatory national adaptive tests of proficiency levels in primary and lower secondary school. For the school years 2020/2021 and 2021/2022, the tests have been adjusted so that only a combined test result is calculated per test. The results for the period 2014/2015 – 2019/2020 have been recalculated to the same scale as the one used in 2020/2021 and 2021/2022., Nationale test i grundskolen (original results 2009/2010 - 2019/2020), contains the originally calculated test results (before the recalculation in 2020/2021) from the mandatory adaptive national tests, including a test result in each of the three profile areas that each test features. , Folkeskolens Nationale Overgangstest, contains test results from the linear transition tests that replaced the national tests as of 2022/2023. Data is updated annually up to and including 2025/2026. , Kompetencedækning i grundskolen, contains information about teachers, the subjects they teach – including whether they have main subject competence in the subject – and about the classes where they are teaching the subjects., Karakterer i grundskolen, contains the test marks and general proficiency marks of pupils in primary and lower secondary school., You can find the data documentation for each register at the , Ministry of children and education, ., Contact , forskerdata@stil.dk, if you have questions regarding data that are not answered in the data documentation., Data on The Danish students Grants and Loans scheme (SU) from the Ministry of Higher Education and Science, Statistics Denmark has entered into an agreement with the Ministry of Higher Education and Science on making The Danish students Grants and Loans scheme (SU) data available to researchers under Statistics Denmark’s microdata schemes., Data will be published as the basic register UFM_SU for reference years 1991 onwards., The variable content in the register is listed in , Register- og variabeloversigter, and described in more detail in the below documentation:, SU-tildeling 1991 og frem, UDD-koder, The future study by the Senior Citizen Organisation (Ældre Sagen), Statistics Denmark has entered into an agreement with the Senior Citizen Organisation (Ældre Sagen) on making survey data from the future study available to researchers under Statistics Denmark’s microdata schemes., Data will be published as the register FREMTIDSSTUDIET. It is a survey of the lives, expectations and desires for the future of 50-89-year-old citizens for the reference years 2010, 2015, and 2021, and subsequently every fifth reference year., In our , register overview (in Danish), , you can see the content of variables in the register. It is described in more detail in the documentation below., The presentation of 2021 data contains background variables bought-in by the senior citizen organisation (Ældre Sagen) in connection with completion of the future study (as of 1 October 2021). The variables pertain to sex, age, highest educational attainment level, socio-economic status, equivalent disposable income for the family, ancestry, municipality and the composition of the family calculated in DST Survey., The bought-in background variables are presented in the register FREMTIDSSTUDIET as at the time of the study in 2021 and are not changed, even though corrections are being made retrospectively in Research Services’ basic data for the affected areas. Updated background variables thus require further bought-in variables from Research Services., On the future study, The future study is a longitudinal study, the purpose of which it is to draw a picture of the present and future lives of elderly citizens and their life situation in general – including their desires, needs, expectations and worries about the future., The study from 2021 is based on answers from 4,990 Danish citizens aged 50 to 89 years to questions revolving around: quality of life, age, health, accommodation, transport, social network, help in everyday life, financial help, loneliness, home care, dignity, welfare and society, volunteering, the labour market, financial circumstances, inheritance, age discrimination and technology., The future study has previously been completed in 2010 and 2015. Data for the future study was collected all three years by Statistics Denmark via online questionnaires and telephone., With the future study, it is possible to examine:, Differences in 2021: How did citizens aged 50 to 89 answer in 2021, and are there differences in the replies of men and women and different age groups?, Generational differences: How did for example 50-54-year-old citizens answer in 2021 compared with 50-54-year-old citizens in 2010 and 2015?, Changes over time for the same people: What did people who participated in 2010 and 2015 answer, now that they have become older?, While the sample of the future study back in 2010 consisted of the four age brackets: 50-54 years, 60-64 years, 70-74 years and 80-84 years, the sample in 2021, just as in 2015, covers all eight five-year age brackets from 50-89 years., The majority of the questions from the future studies 2010 and 2015 recur in 2021. At the same time, questions and answer options have continuously been adjusted to match the social development, and some questions from earlier studies have been excluded, while others have been added. For that reason, it is not possible to compare all questions over time., Read more about the future study and the method behind the documentation below or at , Ældre Sagen, ., Survey, Bilag 1_FTS2010_survey, Bilag 2_FTS2015_survey, Bilag 3_FTS2021_survey, Code book, Bilag 4_FTS2010_kodebog, Bilag 5_FTS2015_kodebog, Bilag 6_FTS2021_kodebog, Method records, population and sample overviews, Bilag 7_FTS2010_metodedokumentation, (inkl stik_pop), Bilag 8_FTS2015_metodedokumentation, Bilag 9_FST2021_metodedokumentation, Bilag 10_FTS2015_populationsoversigt, Bilag 11_FTS2021_populationsoversigt, Bilag 12_FTS2015_stikprøveoversigt, Bilag 13_FST2021_stikprøveoversigt, Note: There is no separate population and sample overview for 2010. It is part of the actual method documentation., Further documentation (also available at the Ældre Sagen website), Bilag 14_FTS2021_temaoversigt_survey, Bilag 15_FTS2010_2015_2021_dataark, Bilag 16_FTS2010_2015_2021_surveyoversigt

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