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    Documentation of statistics: Cultural Business Structure and Labour Market

    Contact info, Science, Technology and Culture, Business Statistics , Søren Østerballe , +45 23 42 32 97 , SRB@dst.dk , Get documentation of statistics as pdf, Cultural Business Structure and Labour Market 2023 , Previous versions, Cultural Business Structure and Labour Market 2022, Cultural Business Structure and Labour Market 2021, Cultural Business Structure and Labour Market 2020, Cultural Business Structure and Labour Market 2019, Cultural Business Structure and Labour Market 2018, Cultural Business Structure and Labour Market 2017, Cultural Business Structure and Labour Market 2016, Cultural Business Structure and Labour Market 2015, Cultural Business Structure and Labour Market 2014, Cultural Business Structure and Labour Market 2013, Cultural Business Structure and Labour Market 2012, The purpose of the statistics is to analyze workplaces as well as persons employed within the cultural sector. The statistics is compiled from 2008 and is published annually., Statistical presentation, The statistics on Cultural Business Structure and Labour Market are compiled annually and provide data on workplaces, entrepreneurs, jobs and persons employed in the cultural sector. Detailed results are disseminated through a number of tables in StatBank Denmark and main results and links to tables can be accessed at the subject page for economic conditions for culture as well as in the annual publication Culture (from 2015 and onwards)., Read more about statistical presentation, Statistical processing, The statistics is based on edited register data from the Establishment-related Business Statistics, the Register-based Labour Force Statistics, Educational Attainment, and Business Demography. The number of jobs are calculated for workplaces (establishments) in relevant activity sectors and are linked to personal data on e.g. age and educational status for employees., Read more about statistical processing, Relevance, The statistics is accessible for everybody and can be used for summaries of the entrepreneurship, educational status and employment within the cultural sector. The statistics may be used for analyses, planning and debates on the topic of cultural employment, etc., Read more about relevance, Accuracy and reliability, The statistics is based on validated data from Statistics Denmark's central registers that form the basis of official statistics, refer to the documentations of statistics for Establishment-related Business Statistics, the Register-based Labour Force Statistics, Educational Attainment, and Business Demography. No actual measurement of the quality and no calculations on measures of accuracy has been performed., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published 20 months after the end of the reference period awaiting the compilation of source register data. It is a fairly new statistics that has been published punctually., Read more about timeliness and punctuality, Comparability, The current time series starts in 2008 and is without any data breaks. The statistics can be compared to selected results from the Establishment-related Business Statistics, the Register-based Labour Force Statistics, Educational Attainment, and Business Demography. Eurostat and Unesco regularly publish reports on the same subject matters as this statistics., Read more about comparability, Accessibility and clarity, These statistics are published annually in the StatBank under the subject , Education and employment in the cultural field, . For further information, go to the , subject page, . , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/cultural-business-structure-and-labour-market

    Documentation of statistics

    Documentation of statistics: Hospitalization

    Contact info, Personal Finances and Welfare, Social Statistics , Line Neerup Handlos , +45 26 64 03 00 , lha@dst.dk , Get documentation of statistics as pdf, Hospitalization 2024 , Previous versions, Hospitalization 2023, Hospitalization 2022, Hospitalization 2021, Hospitalization 2019, Hospitalization 2018, Hospitalisation 2017, Hospitalization 2016, Hospitalization 2015, Hospitalization 2014, Hospitalization 2013, The purpose of the Hospital Utilisation Statistics is to shed light on the connection between hospitals stays and social and demographic conditions. The statistics have been compiled since 1990, but are comparable in their current form only from 2017 onwards., Statistical presentation, The statistics are an annual inventory of stays at public and private somatic and psychiatric hospital wards within one calendar year. The statistics show how hospital stays vary with demographic and social factors, such as residence, sex, age, educational level, labour market affiliation and relatives. The statistics are published in News from Statistics Denmark and in the StatBank., Read more about statistical presentation, Statistical processing, The statistics are based on data retrieved from the National Patient Registry, which is shared with Statistics Denmark by the Danish Health Data Authority. Background data from Statistics Denmark are linked to the registry, and summaries and counts are produced — for example, the number of hospital stays and patients in public and private somatic and psychiatric hospital departments during the calendar year., Read more about statistical processing, Relevance, Public and private stakeholders, as well as the general population, can use the statistics to extract data on the population’s hospital utilisation for various analyses, research, public debate, etc. The statistics make it possible to produce figures for specific diagnosis groups and to link information on hospital utilisation with sociodemographic factors such as place of residence, education, labour market attachment, and origin. This is made possible by linking data from the National Patient Register with population register data from Statistics Denmark., Read more about relevance, Accuracy and reliability, The National Patient Register is validated by the Danish Health Data Agency and the accuracy of the register data must be considered to be high because the registration has a long tradition and a high priority for administrative purposes. Accordingly, the overall accuracy of the Hospital Utilisation Statistics is high. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published within approximately nine months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The statistics have been developed since 1990, but are only comparable in their current form from 2017 onwards., Eurostat and the OECD make comparable statistics in this field. There are a number of organizational and institutional conditions that we must keep in mind when comparing countries. , Read more about comparability, Accessibility and clarity, The statistics are released in the newsletter Nyt from Statistics Denmark (in Danish only) and the Statbank, Statbank tables on hospitalisation utilisation (https://www.Statbank.dk/20050). Statistical Yearbook and Statistical Ten-Year Review contain selected sections about hospitalisation rates. For further information, go to the , subject page, ., Read more about accessibility and clarity

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

    Documentation of statistics

    Documentation of statistics: Account Statistics for Fishery

    Contact info, Food Industries , Charlotte Spliid Hansen , +45 29 41 97 76 , CHH@dst.dk , Get documentation of statistics as pdf, Account Statistics for Fishery 2023 , Previous versions, Account Statistics for Fishery 2022, Account Statistics for Fishery 2021, Account Statistics for Fishery 2020, Account Statistics for Fishery 2019, Account Statistics for Fishery 2018, Account Statistics for Fishery 2017, Account Statistics for Fishery 2016, Account Statistics for Fishery 2015, Account Statistics for Fishery 2014, Account Statistics for Fishery 2013, Account Statistics for Fishery 2012, The purpose of the Account Statistics for Fishery is to review the economy of the fishery sector. The statistics is used in economic models and as a basis for yearly economic statistical reports for the fishery to EU (DG Mare). The statistics has been produced by Department of Food and Resource Economics at University of Copenhagen since 1996 and was transferred to Statistics Denmark from January 2009., Statistical presentation, The Account Statistics for Fishery covers the commercially fishery by fishing vessels registered in Denmark. The statistics is based on vessel units and is calculated for groups of fishing vessels (fleet segments) based on vessel size and main gear use., Read more about statistical presentation, Statistical processing, The authorized accountants report yearly the account for their fishery client. The collected accounts are thoroughly tested. When all accounts has been approved for statistical use, the sample of approved accounts are used together with register data for the entire population to simulate individual accounts for all units not in the sample. The complete dataset with individual balanced accounts for all units in the population is merged with register data on vessel characteristics, gear use etc. in order to calculate parameters for statistical groups (vessel segments)., Read more about statistical processing, Relevance, The statistics is relevant for government administration, researchers and stakeholders within the fisheries. Furthermore the data is used in the Fleet Economic Report to EU. , Read more about relevance, Accuracy and reliability, The statistic is based on a sample and the results are uncertain. The precision rely on the covering of the sample. Therefore the sample rate is bigger for vessels with high revenue. The aim is each year to include the 100 biggest vessels in the sample, and that approximately 80 per cent of the total value of landings in Danish fishery come from the vessels in the sample. Investments have the most uncertainty, because exchange of a vessel could result in closure of the fishing firm, and set up a new firm to run the new vessel., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is normally made public before one year after the conclusion of the refence year., Read more about timeliness and punctuality, Comparability, The Account Statistics for Fishery is prepared using the same overall principles as the account statistics for agriculture, horticulture and aquaculture. The statistics has been prepared yearly since 1996. Break in series occurs in 2022 due to changes in methods for calculation population cutoff, as well as a new and improved basis for classifying which fishing types the vessels are grouped into. Break in series also occurs in 2001 due to inclusion of unpaid salary to active (working) partners, and in 2009 and again 2012 due to improved calculation of the capital value of fishing rights., Read more about comparability, Accessibility and clarity, The statistics is published yearly in NYT from Statistics Denmark. Data is accessible on StatBank Denmark in the tables AKFIREGN, FIREGN1, FIREGN2 and NFISK. More information on the statistics subject web-page: , Fishery, Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/account-statistics-for-fishery

    Documentation of statistics

    Statistics on income and living conditions (SILC)

    How large a share of the population is economically vulnerable? How many struggle to make ends meet? The Statistics on Income and Living Conditions (SILC) is a questionnaire-based survey conducted annually in all EU countries, including Denmark. As such, it reflects the respondents' own perception at the time of the interview. It is well-suited for cross-country comparisons., Economically vulnerable , Indicator based on individuals' subjective perceptions of the economic situation of their household as reported in a survey. Individuals living in households where at least three of the following five types of economic deprivation exists are considered economically vulnerable: 1) Difficult/very difficult making ends meet 2) Arrears the past year 3) Unable to pay an unexpected expense of 10,000 DKK 4) Cannot afford to have a car 5) Cannot afford one week annual holiday away from home., The economically vulnerable, The figure shows the share of economically vulnerable citizens (see definition above) within each household type., In Statbank Denmark, you can find more data on Economically vulnerable (SILC10), More about the figure, Last update, 24.1.2025, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), Five types of economic deprivation, The SILC indicator for economic vulnerability is based on five types of economic deprivation. Here you can see the share of the population that has experienced each type of deprivation over the past four years., In Statbank Denmark, you can find more data on Economically vulnerable (SILC10), More about the figure, Last update, 24.1.2025, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), General life satisfaction by income, The figure shows the population's self-perceived life satisfaction by income. Income is one of several background variables through which life satisfaction can be viewed. The life satisfaction scale goes from 0–10, and for each income quintile you see an average. The first quintile represents the fifth of the population with the lowest income, and the fifth quintile the fifth of the population with the highest income., In Statbank Denmark, you can find more data on Overall life satisfaction (SILC50), More about the figure, Last update, 18.12.2024, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), General life satisfaction by household type, The figure shows the population's self-perceived life satisfaction by household type. Household type is one of several background variables through which life satisfaction can be viewed. The life satisfaction scale goes from 0–10., In Statbank Denmark, you can find more data on Overall life satisfaction (SILC50), More about the figure, Last update, 18.12.2024, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), Housing costs as a heavy financial burden, The figure shows the share of various age groups who experience housing costs as a heavy financial burden., In Statbank Denmark, you can find more data on Housing burden: Percentage of persons (SILC1B), More about the figure, Last update, 18.12.2024, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), Expected decline in income, The figure shows the share of households in various regions that expect their total household income to decrease in the coming year., In Statbank Denmark, you can find more data on Change in household income (SILC80), More about the figure, Last update, 18.12.2024, Next update, 12.12.2025, Source data, The EU-SILC is a survey which combines interviews with administrative data from the registers at Statistics Denmark., The primary source for SILC data is interviews with 6,010 households from a sample of 12.428 households. This sample is a combination of persons who participated the previous years and 7.365 added households. The interview data are combined with administrative registers to form the EU-SILC datasets. Denmark uses a selected respondent model and only interview one person per household. The selected respondent is asked personal questions, question related to the household and labor market status for all household members. , From 2016 the sample is stratified on Regions. From 2020 the sample is stratified on both Regions and the income intervals 0-60 per cent of the median, 60-100 per cent of the median and above 100 per cent of the median. , The target population is "persons living in Denmark", while the survey population is "persons living in private households in Denmark". Thus, persons living in institutions, prisons and the homeless are not included in the survey. , Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), On the statistics – documentation, sources and method, Gain an overview of the purpose, contents and quality of the statistics. Learn about the data sources of the statistics, the contents of the statistics and how often they are published., See the documentation of statistics to learn more:, Survey on Living Conditions (SILC), In Denmark EU-SILC (Statistics on income and living conditions) is a combination of survey and register data. The purpose of EU-SILC is to provide a statistics on income, living conditions and risk of social exclusion. Statistics Denmark only disseminate a small part of EU-SILC. Dissemination is by Eurostat primarily., The survey is conducted in all EU member states once a year following the same guidelines. In Denmark the survey has been conducted since 2004., Read more about sources, method and quality in the documentation of statistics on Survey on Living Conditions (SILC), Need more data on Statistics on income and living conditions (SILC)?, You can go on searching on your own in Statbank Denmark. Find more detailed figures e.g., on economically vulnerable individuals broken down by gender, age, income, housing type, and much more., Go to the StatBank, Contact, Martin Faris Sawaed Nielsen, Phone: +45 23 69 90 67, Mail: , mfs@dst.dk

    https://www.dst.dk/en/Statistik/emner/sociale-forhold/levevilkaar/levevilkaarsundersoegelsen-silc

    Subject page

    Linking of additional data

    Statistics Denmark’s register data can be linked with other data materials, here called additional data. This can be, for example, extractions from registers outside Statistics Denmark, your own data – for example survey data – or data from other data providers., Additional data must be documented and comply with the same requirements to data minimisation and statistical disclosure control that Statistics Denmark applies in general., These requirements must ensure that only additional data needed in the project is provided and that Research Services get the information necessary to be able to handle the additional microdata and make it available in the specific project., Use of additional data must comply with the same rules regarding confidentiality and transfer as those that apply to Statistics Denmark’s microdata. , Read more about the rules on transfer and sanctioning, Any other data must be provided safely to Statistics Denmark. , You will find the guide for uploading additional data sets under ‘Use of FSE upload’, Requirements for additional data, Only approved and documented data:, Additional data must be covered by an approved project proposal. Documentation of the additional data content must be uploaded as an appendix in Denmark’s Data Portal. See below under ‘Documentation of additional data’., No information identifying individuals or businesses:, Personal names, company names, responses with free text in surveys and other information roughly identifying individuals or businesses is not allowed to be included in additional data. Such variables must be removed or categorised before additional data is provided to Research Services., Only the required key variables:, You may include only the key variables, e.g. civil registration number, required to link the additional data with the other data on the project. Key variables that are not needed must be removed before data is provided to Research Services., Only numeric variables and categorised text variables:, Additional data may not include non-categorised text variables, such as free text., Only information required for the specific project:, Key variables for which there is no need, must be removed before data is provided to Research Services., File formats, Additional data may be provided in the following formats:, .ASC, .CSV, .DTA, .ODS, .PDF, .SAS7BCAT, .SAS7BDAT, .SAV, .XLS, .XLSX, Documentation of additional data, Additional data must be documented, so that Research Services gets the information that is necessary to be able to handle the additional data and provide it for the specific project. For that reason, the institution is responsible for uploading an overview with the below content as an appendix in Denmark’s Data Portal., A short description of data (for example origin and content), Name of the data set, names of variables and a description of the variable content., The key variables that must be de-identified. This means the variables required to link the additional data with the other data in the project (e.g. civil registration number)., Which additional variables must be de-identified? This means variables that can be attributed directly to individuals or businesses (e.g. CVR number, grant number for health practitioner, serial number, or other ID numbers)., Does the additional data include key variables that must be linked with key variables in previously provided data sets?, If data is provided directly to Research Services from another data provider, further documentation may be necessary, e.g. variables that must be deleted (see ‘Requirements for additional data’ above)., The overview must be uploaded as an appendix in Denmark’s Data Portal under ’Additional data sources’ in a generally available format (Excel, Word or similar)., If data is to be linked with more populations, the documentation must be attached as an appendix under ‘Additional data sources’ for minimum one of these populations. The additional data must appear under ‘Additional data sources’ for each population., When the additional data has been provided to Statistics Denmark and the documentation has been uploaded in Denmark’s Data Portal, it is recommended that you notify the project owner in Research Services via email., Prices for delivery of submitted data, The price for the delivery of submitted data is variable. Once we have received the data, we prepare a framework agreement with a maximum expected time consumption. After delivery of the data, we settle based on the actual time consumption. , See more about framework agreements under Prices and price agreements, ., The expected time consumption depends on many factors, including the number, size, complexity and format of the files. Therefore, we always prepare framework agreements for submitted data on a case-by-case basis, and only when we have received the specific data sets., The table below provides a guide to the typical relationship between the number of data sets and the maximum expected time consumption. Please note, however, that the number of data sets is only one of many factors, and the table is therefore only a guide. Other factors, such as size, number of variables, or special treatment, may increase or decrease the number of hours in the specific framework agreement. Contact the project manager in Research Services if you need a more precise estimate., See the current hourly rates under Prices and price agreements, Number of datasets, Typical number of hours in framework agreement (indicative), 1-2, 2-4, 3-10, 4-8, 11-20, 8-14, 21-50, 14-20, NOTE: The number of hours in the framework agreement is typically set to accommodate unforeseen circumstances. Since the settlement is based on the actual time spent, the final price will in many cases be lower., Submitting files that do not include microdata, Files that you need in your project and that do not include microdata (e.g. programme files), must not be uploaded via FSE Upload., The files can be sent directly to the project owner in Research Services, if you are working on a subproject for a project database. If you are working under the researcher scheme, you can send an email to , forskningsservice@dst.dk, . In both instances, you must attach the files to the email. Further, you must:, Confirm that you have checked the files to ensure that they do not include microdata., Confirm that the files do not include microdata., Provide a short description of the content of the files and its relevance in terms of the purpose of the project., Indicate the specific path to where the files must be located., Ensure that the files are submitted in a generally available format that can be opened and checked by Research Services without use of specialised software.,  , De-identification, When the additional data has been received in Research Services it will be de-identified in the same way as any other data that belongs to the project. This happens by de-identifying key variables. Subsequently, the additional data is made available together with any other data in the project., Providing additional data to Research Services, Additional data must be provided safely to Statistics Denmark, Additional data can be provided safely to Statistics Denmark in the ways stated below:, Use of FSE Upload, Under Statistics Denmark’s microdata schemes, it is possible to upload additional files with data to be used in an existing project. Only data and documentation can be uploaded. Programmes etc. can be sent to the Research Services employee who is responsible for the project (project owner)., The documentation must either be sent to the project owner from Statistics Denmark or be uploaded in one of the allowed file formats., Before you upload, Before you upload data to be used in a project, you must ensure that the criteria for use of your data in the project have been met. The requirements are described at the top of the page under ‘Requirements for additional data’., The handling of additional data is invoiced according to the actual time used, unless otherwise agreed., Contact the project owner in Statistics Denmark in advance., How to upload the files, You log in via remote.dst.dk in the same way as when you are going to work on a project., Under 'Applications and Links' select 'FSE-UPLOAD'., Write the project number of the project where your data is to be used., When the project title is shown next to the project number, you must check that you have selected the right project for uploading of data., If relevant, add a comment concerning your data in the comments field for the project owner at Statistics Denmark. Actual correspondence should take place via email. , Add files to be uploaded by clicking `Add file'. You can add one or more files. Each file may run up to 2 GB., Note that not all types of files can be uploaded. You can see the list of allowed types under `File formats' further up on the page., When all files have been selected, you must click `Upload'., When all the files have been uploaded, you can log out in the bottom right-hand corner., If relevant, see , this guide for FSE upload (pdf, in Danish), , which includes screenshots of the upload process., Use of secure email, Data can be sent via secure email to , forskerpost@dst.dk, in one of two ways: , The institution retrieves Statistics Denmark's certificate at the website for download of security certificates (in Danish): Select , forskerpost@dst.dk, . For Outlook, we recommend the Vcf format. , After this, additional data must be sent to , forskerpost@dst.dk, . Always indicate project number and project owner in Research Services in the subject field of the email and notify the project owner in Research Services directly, once the additional data has been sent. Statistics Denmark does not offer any support for encryption or digital signature. Refer to your own IT department for guidance using mitID and secure email., The institution can use a secure, encrypted tunnel (SEPO). The set-up is individual for different institutions and must be handled by the institution's IT department, which should be involved before the additional data is sent., You must always indicate the project number and notify the project owner in Research Services that the email has been sent using an encrypted tunnel (SEPO). If using an encrypted tunnel, additional data must also be sent to , forskerpost@dst.dk, ., Registered letter or personal delivery, For data security reasons, we recommend that you use one of the above options., If this is not possible (e.g. if the files are very big), it is possible to provide password-protected additional data on physical media directly to Statistics Denmark at the below address. The contact person for the project in Research Services and the project number must always appear from the material handed in:, Statistics Denmark, Service Desk, Sankt Kjelds Plads 11, 2100 Copenhagen Ø, Att. Contact person for the project in Research Services, Re. project number: 7XXXXX, Additional data can either be delivered personally at Statistics Denmark's reception or be sent by registered mail to Statistics Denmark on a physical medium (DVD, CD-ROM or USB, which will not be returned). When provided on a physical medium, the additional data must be password-protected. Password must not be provided together with the physical medium., When the additional data has been received, you must send the password via email to the contact person for the project in Research Services.,  , Other data providers, Other data providers can provide additional data directly to Statistics Denmark at the request of the institution and by agreement between Research Services and the data provider. Delivery of additional data must take place in one of the above ways, but you must make sure that the additional data complies with the requirements above before it are delivered to Research Services., Do , not , send data via standard email, Additional data must not be sent via standard email, since this is not a secure delivery mode.

    https://www.dst.dk/en/TilSalg/data-til-forskning/anmodning-om-data/tilknytning-af-ovrige-data

    Documentation of statistics: Accounts Statistics for Aquaculture

    Contact info, Food Industries, Business Statistics , Michael Brogaard , +45 51 62 70 89 , MIB@dst.dk , Get documentation of statistics as pdf, Accounts Statistics for Aquaculture 2023 , Previous versions, Accounts Statistics for Aquaculture 2022, Accounts Statistics for Aquaculture 2021, Accounts Statistics for Aquaculture 2020, Accounts Statistics for Aquaculture 2019, Accounts Statistics for Aquaculture 2018, Accounts Statistics for Aquaculture 2017, Accounts Statistics for Aquaculture 2016, Accounts Statistics for Aquaculture 2015, Accounts Statistics for Aquaculture 2014, Accounts Statistics for Aquaculture 2013, Accounts Statistics for Aquaculture 2012, The purpose of Account statistics for aquaculture is to show the economy in the Danish aquaculture sector. The statistics is used to monitor the economic development and to compare economic key figures from different farm types. The statistics was first made in 2004 and is comparable in its current form since 2017., Statistical presentation, The Account statistics for aquaculture is an annual estimation of the production value and costs, results, assets and liabilities and investments of the aquaculture sector in Denmark., Read more about statistical presentation, Statistical processing, Data for this statistics are collected yearly from the aquaculture companies' chartered accountants using an electronic accounting form. The collected accounts (the sample) are thoroughly tested, and possible errors corrected in cooperation with the reporting accountant. When all accounts are approved for statistical use, the sample of approved accounts are used together with register data for the entire population to simulate individual accounts for all units not in the sample., Read more about statistical processing, Relevance, The statistics is used by the fish farmers and their organization, Danish Aquaculture, as well as authorities and legislators. The statistics is used in economic models and as a basis for yearly economic statistical reports for aquaculture to EU (DG Mare)., Read more about relevance, Accuracy and reliability, The statistic is based on a sample, hence the results are uncertain. The aim is to include the biggest companies in the sample, and that 75 per cent of gross revenue is covered by the sample. There are no planned revisions of the statistics., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is normally made public before one year after the conclusion of the reference year., Read more about timeliness and punctuality, Comparability, The statistics is comparable from 2004 to present. All EU member states submit statistics to the , Directorate-General for Maritime Affairs and Fisheries, . Hence, it's possible to make comparisons within the EU. The Danish Fisheries Agency publish a Structure and production statistics for the profession., Read more about comparability, Accessibility and clarity, The statistics is published yearly in a Danish press release and in the StatBank under , Aquaculture, . For more information please see the , subject page, for these statistics., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/accounts-statistics-for-aquaculture

    Documentation of statistics

    Documentation of statistics: Business Demography

    Contact info, Business Dynamics, Business Statistics , Asbjørn Hviid Mikkelsen , +45 29 42 68 36 , AHM@dst.dk , Get documentation of statistics as pdf, Business Demography 2024 , Previous versions, Business Demography 2023, Business Demography 2022, Business Demography 2020, Business Demography 2018, Business Demography 2017, Business Demography 2016, Business Demography 2015, Business Demography 2014, Business Demography 2013, Business Demography 2012, The purpose of the Business Demography is to provide information about the development of enterprise births and deaths as well as the survival of new enterprises over a period of five years. The statistics is comparable from 2019 onwards., Statistical presentation, The statistics cover the annual number of enterprise births and deaths and provides information on turnover and employment. The results are broken down by industry, size class, enterprise form, and geographical location. The statistics are disseminated in Nyt from Statistics Denmark and in our statbank., Read more about statistical presentation, Statistical processing, Data is collected from the Statistical Business Register. Subsequently various processes are undertaken to determine whether or not an enterprise is new (enterprise birth), terminated (enterprise death), or surviving. The controls are done to validate if the new enterprises, which exists in the administrative reality, are in fact real new enterprises, which enters the economy, or if it is an activity that is continued after a takeover or e.g. a split of an existing enterprise., Read more about statistical processing, Relevance, The statistic is used by ministries and governmental agencies, regional and county authorities as well as private sector institutions and enterprises, The statistic is a central indicator for entrepreneurship and for sustainability in the economy, and there is a large demand for using the output in combination with other sources, and following the development of enterprises who survive., Read more about relevance, Accuracy and reliability, The statistics is based on validated register data., Uncertainty is related to relations between units and work places, which are primarily based on digital income reporting by enterprises, and lack of knowledge concerning the transfer of activities from one enterprise to another, including the separation of activities. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published annually. The publication is usually available 18 months after the end of the reference year. The statistics is also published with preliminary data 12 months after the end of the reference year. , Read more about timeliness and punctuality, Comparability, The national published Business Demography is a sub-population of the Danish published General enterprise statistics., Covering private enterprises excluding agriculture, the Danish published Business demography can be compared to the Business Statistics published by Eurostat., Read more about comparability, Accessibility and clarity, Results are published in , Nyt fra Danmarks Statistik, . Results are also available in the StatBank under the topic , Business demography, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/business-demography

    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