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Fishery and aquaculture

Fishery , Accounts statistics for fishery as well as vessels and landings statistics for the fishing industry., Aquaculture, Accounts statistics for aquaculture as well as production statistics for the aquaculture industry.

https://www.dst.dk/en/Statistik/emner/erhvervsliv/fiskeri-og-akvakultur

Subject page

Educational pathways

From primary and secondary education to continued education, Tracks student year groups year by year from they finish primary and lower secondary school and complete an upper secondary programme through their educational pathways., From education to labour market, Shows what happens after a student has left the educational system., Completion of education, Shows how many , discontinue , and complete an education within an education group after 1 and 5 years.

https://www.dst.dk/en/Statistik/emner/uddannelse-og-forskning/veje-gennem-uddannelsessystemet

Subject page

Area

Land use accounts, Shows the size of Denmark and the individual municipalities in square kilometres and how much of the area that is covered by fields, forests, buildings, lakes, etc.

https://www.dst.dk/en/Statistik/emner/miljoe-og-energi/areal

Subject page

Trade

Retail trade index, Shows the development in retail trade, including in consumables, clothing and other consumer goods., Wholesale stocks, Shows the development in wholesale stocks. The statistics also offer a breakdown by industry., Sales of alcohol and tobacco, Shows the sales of alcohol distributed on beer, wine and spirits as well as tobacco products distributed on cigarettes, cigars and smoking tobacco.

https://www.dst.dk/en/Statistik/emner/erhvervsliv/handel

Subject page

Construction

Construction activity, Shows the construction activity requiring a building permit, stated as total floor area and number of dwellings., Turnover in construction, Shows turnover in private construction activities broken down by the type of work and by industry., Building stock, The statistics include information about the buildings’ use, size, ownership, year of construction, type of heating and location., Employment in construction, Shows the number of persons employed in workplaces in Denmark with construction activities., Indices for the construction sector, Shows the development in the cost of housing construction and civil engineering projects as well as statistics on productivity in the construction sector.

https://www.dst.dk/en/Statistik/emner/erhvervsliv/byggeri-og-anlaeg

Subject page

Environmental-economic accounts

The environmental-economic accounts are a system of accounts for the economy, the climate and the environment that supplements the conventional national accounts. The environmental-economic accounts are based on an international statistical standard called the System of Environmental-Economic Accounting (SEEA). Statistics Denmark often refers to the environmental-economic accounts as green national accounts. , Energy and air emission accounts, Shows the production and consumption of various kinds of energy, emission of CO2, other greenhouse gases and air pollution, and the Danish climate footprint., Material flow and waste accounts, Shows the material consumption of the economy and how much waste we generate. For example, you can see how much waste is sorted for recycling., Water and wastewater, Shows the abstraction of water, the water consumption of households and businesses, and how much waste water we produce., Green economy, Shows the public revenue from green taxes, expenditure on environmental protection, environmental transfers, and the turnover of green goods and services., Natural resource accounts, Shows how many natural resources Denmark has in the form of oil, natural gas, fish and forests, and how much of the Danish area that is agricultural land, nature, buildings, etc., System of Environmental-Economic Accounting (SEEA), The environmental-economic accounts are based on guidelines drawn up by the UN, World Bank, IMF, OECD, FAO and the EU. Read more about the international standard SEEA CF - System of Environmental-Economic Accounting - Central Framework.

https://www.dst.dk/en/Statistik/emner/miljoe-og-energi/groent-nationalregnskab

Subject page

Documentation of statistics: Home to work commuting

Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , psd@dst.dk , Get documentation of statistics as pdf, Home to work commuting 2024 , Previous versions, Commuting 2016, The statistics measure commuting between place of residence and workplace within Denmark, including the distances between commuters’ homes and workplaces. Commuting statistics viewed as commuting between municipalities can be compiled from 1980 onwards. The distance between home and workplace was first calculated in 2006. The statistics are comparable in its current form from 2008 onwards., Statistical presentation, The statistics provide an annual, individual-based account of employed persons’ commuting between place of residence and workplace on the last working day of November. The distance between commuters’ home and workplace is also calculated in kilometres (km). The commuting statistics are published the StatBank, where the data can be distributed on place of residence, workplace, commuting distance, gender, industry (DB07), and socio-economic status., Read more about statistical presentation, Statistical processing, The commuting statistic is compiled on the register-based labour force statistic (RAS), which is based on the Labour Market Account (LMA) - a longitudinal register. A comprehensive data validation is done in the production of AMR. RAS is compiled taking a snapshot (on the populations primary attachment to the labour market) on the last working day in November based on LMA. Based on the information about the address of residence and workplace for employed persons the commuting distance is calculated. , Read more about statistical processing, Relevance, The statistic is relevant for users interested in mobility on the labour market and the data foundation makes it possible to connect detailed information for analysis. , Read more about relevance, Accuracy and reliability, The commuting statistics are based on the Register-Based Labour Force Statistics (RAS), which are used to describe the population’s attachment to the labour market. RAS is compiled from a wide range of data sources that are integrated, error-checked, and harmonised within the labour market accounts. RAS is produced as a snapshot at the end of November based LMA. Therefore, RAS does not carry the same level of uncertainty as statistics based on sample surveys., It is also important to be aware that the calculated commuting distance reflects an ideal situation where every person is believed to travel from residence to workplace by the shortest route and by car. , Read more about accuracy and reliability, Timeliness and punctuality, Commuting statistics for commuting between municipalities are published approximately 11 months after the reference date. Commuting distances are published approximately 17 months after the reference date. , Read more about timeliness and punctuality, Comparability, The statistics can be compiled from 1980 and are comparable from 2008 onwards. Historically, there have been various data breaks in the RAS statistics, which are described in the statistical documentation for RAS., Read more about comparability, Accessibility and clarity, In the StatBank the statistics is published can be found under the subject , Home to work commuting, . For further information, go to the , subject page, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/home-to-work-commuting

Documentation of statistics

Documentation of statistics: Persons below the state pension age on public benefits

Contact info, Labour Market, Social Statistics , Mikkel Zimmermann , +45 51 44 98 37 , MZI@dst.dk , Get documentation of statistics as pdf, Persons below the state pension age on public benefits 2025 , Previous versions, Persons below the state pension age on public benefits 2024, Persons below the state pension age on public benefits 2022, Persons below the state pension age on public benefits 2020, Persons below the state pension age on public benefits 2019, People Receiving Public Benefits (16-64-years-old) 2018, People Receiving Public Benefits (16-64-years-old) 2017, People Receiving Public Benefits (16-64-years-old) 2015, People Receiving Public Benefits (16-64-years-old) 2014, The purpose of the statistics is to show trends in average/full-time participation in labour market policy measures. Based on a report prepared by the activation statistics committee (report no. 1259) the first statistics were compiled as from the first quarter of 1994. The reason for setting up the committee was that the Danish statistics at that time were unable to provide reliable data on the wide variety of municipal activation schemes. The committee's work was performed over the period December 1992 to October 1993. Since 1994 new measures have been introduced and others have ceased. As from the third quarter of 1999 the number of persons working in flex- and sheltered jobs are published concurrently with the labour market policy measures. Persons participating in activation according to the job integration act were included from the first quarter of 2000. As from the third quarter of 2003, and with effect in the publications as from the first quarter of 2004, a number of changes to the codes/names were undertaken due to a political reform that meant the introduction of new activation schemes, whereas other schemes ceased to exist. From 2007 the statistics is extended with persons on early retirement pay, sickness benefit, maternity leave and from 2008 it is extended furthermore with young people in ordinary education ('SU-modtagere')., Statistical presentation, The statistics provide data on trends in the average number of participants (beneath their state pension age) with public benefits, analyzed by labour market policy measure. The activities take place within the following main groups: Unemployed, persons in supported employment, leave, education/training, other activation, integration allowance, sickness benefit and different kinds of early retirement pay. The figure on average number of participants (full-time participants), is a volume measurement. The figures is comparable with the average number of full-time unemployed in the unemployment statistics., From June 2022 the statistics is extended to include persons receiving 'Early Pension", 'Senior Pension' and 'Adult apprenticeship support'. From March 2025 and again from September 2025 the statistics on sickness benefit recipients is changed., Read more about statistical presentation, Statistical processing, All data necessary for the statistics is collected from administrative registers. The data is collected through SAS-files and FTP-servers. When the data files are collected we make a preliminary validation of each file. Afterwards the data is loaded in the database (PSD) on a uniform format. After that illegal overlapping time periods where the same person is receiving different conflicting public benefits are eliminated before the total data amount is transmitted into a 'production database' from where the statistics is published., Read more about statistical processing, Relevance, 'Users': Municipalities, regions, ministries, organizations and the media. 'Fields of application': Public labour market surveillance. There has not been any actual 'satisfaction-examination' carried out, but the general use of the statistics, media, has always been considerable, and the statistics is expected to be an important part of the future 'Labour market account' (AMR), which is going to be released in the spring 2015., Read more about relevance, Accuracy and reliability, All data necessary for the statistics is collected from administrative registers. The statistics cover the population aged 16-64 who is receiving some sort of public benefits. Conflicting and erroneous information about each individual person may frequently occur as the statistics are compiled from a variety of administrative registers. Examples are a person who is regarded as both a recipient of cash benefits and as a person entitled to claim unemployment benefits, or a person participating in several activation schemes at the same time, which exceed 37 hours per week, or a person participating in the same activation over an unrealistic long period of time. The main reason for these errors is that the respondents fail to update the existing data as soon as new data is available. Error correction is some times undertaken by Statistics Denmark on the basis of logical requirements and some times by the respondents themselves. However, the best possible solution is for error correction to be undertaken by the respondents themselves. The municipalities report data on persons entitled to claim cash benefits and similar allowances in various ways. Currently there is no estimates/numbers available on the total statistical errors., Read more about accuracy and reliability, Timeliness and punctuality, The quarterly statistics is published roughly 80 days after the end of the reference quarter and the yearly statistics is published roughly 100 days after the end of the reference year. The exact release dates are advertised a year ahead., Read more about timeliness and punctuality, Comparability, The current statistics on persons receiving public benefits covers in general the time period from the 1. of January 2007 and onwards. Persons receiving ordinary education (SU-modtagere) is only included from the 1. of January 2008 and onwards. From 2006 to 2007 there are some differences in the covering and in the concepts. However, some time series in the stat bank starts back in the first quarter of 1994. The general comparability is reduced by the many changes in the measures over time. When the statistics is based on a number of national administrative registers it is obviously very difficult to make any international comparisons. However, Eurostat has tried to make some international comparisons in the area of participants/expenditures on some sorts of public benefits through their Labour Market Policy (LMP)-database., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , Persons below the state pension age on public benefits, . For more information please see the subject page for , Persons receiving public benefits, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/persons-below-the-state-pension-age-on-public-benefits

Documentation of statistics

Documentation of statistics: Social benefits for senior citizens

Contact info, Personal Finances and Welfare, Social Statistics , Marie Borring Klitgaard , +45 21 55 83 71 , MGA@dst.dk , Get documentation of statistics as pdf, Social benefits for senior citizens 2025 , Previous versions, Social benefits for senior citizens 2024, Social benefits for senior citizens 2023, Social benefits for senior citizens 2022, Social benefits for senior citizens 2021, Social benefits for senior citizens 2020, Elderly - Indicators 2019, Elderly - Indicators 2018, Elderly - Indicators 2017, Elderly - Indicators 2016, Elderly - Indicators 2015, Elderly - Indicators 2014, Elderly - Indicators 2013, Documents associated with the documentation, Kommentarer til 2024 - korte udgaver (xlsx) (in Danish only), Kommentarer til 2025 - korte udgaver (xlsx) (in Danish only), The purpose of these statistics is to display the quality level of municipal services in the elderly care. The statistics are a part of a cross-public cooperation, intended to ensure coherent documentation of important areas of municipal service, as well as to increase the comparability of the services provided in the different municipalities. The statistics are used to determine impact targets, frameworks and results requirements for key management initiatives and are comparable from 2008 onwards. Statistics Denmark is responsible for the composition and publication of the statistics., Statistical presentation, The statistic for 2025 covers data from the first 6 months of 2025. The statistic is an annual survey including a number of national impact- and background indicators which document and describe the quality of the municipal effort at the elderly area. The indicators consist of referral and provided home care, home nursing, nursing homes, exercise services, rehabilitation and preventative home visits. Primarily, the indicators are targeted at the elderly area, however home care, exercise services, home nursing as well as nursing homes also include data for citizens under 67 years., Read more about statistical presentation, Statistical processing, Before publishing data from the municipalities' EOJ system (electronic care journal), tables and figures are developed, which all municipalities are asked to approve. After the approval, Statistics Denmark detects for data errors as missing numbers, abnormal values and etc., Read more about statistical processing, Relevance, The authorities and public institutions and the population use the indicators for analysis, research, debate, etc. The focus is to ensure more valid documentation at the elderly area. This is achieved by retrieving the information directly from the municipalities' care systems (EOJ), which is constantly updated as a part of the municipalities' case management., Read more about relevance, Accuracy and reliability, The municipalities receive control tables, which they are asked to approve. Only approved information is included in the statistics. In the absence of approvals, previous years' information is included in the national totals and averages. For the publication for the first 6 months 2025, between 97 and 98 municipalities are included, depending on the indicator. Lack of approval may be due to the municipality's registration practices, which determine which data is reported, and system or supplier changes, where the reported data may be flawed. There are varying registration practices between municipalities in several areas, which can lead to distortions., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published as pre-advertised. The statistics are released approximately 6 months after the reference period has ended. , Read more about timeliness and punctuality, Comparability, The statistics are generally comparable over time, but there are minor data breaks. The municipalities' change of EOJ provider every five years can affect certain indicators. As of October 1, 2023, new reporting requirements for food service and supplier types resulted in a data break in the statistics on designated home care. Therefore, the figures for 2023 should be compared with previous years with reservations. For hospital usage, there has been no adjustment for the severity of diseases, which affects the comparability between municipalities., Read more about comparability, Accessibility and clarity, The statistics are published in a , Danish press release, . The figures are published in the StatBank under the subject , Social benefits for senior citizens, . See more on the subject page for the , Social benefits for senior citizens, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/social-benefits-for-senior-citizens

Documentation of statistics

Documentation of statistics: Nights Spent at Marinas

Contact info, Short Term Statistics, Business Statistics , Majbrit Holst , +45 24 94 08 24 , mbj@dst.dk , Get documentation of statistics as pdf, Nights Spent at Marinas 2025 , Previous versions, Nights Spent at Marinas 2024, Nights Spent at Marinas 2023, Nights Spent at Marinas 2022, Nights Spent at Marinas 2021, Nights Spent at Marinas 2020, Nights Spent at Marinas 2019, Nights Spent at Marinas 2018, Nights Spent at Marinas 2017, The purpose of the survey Overnight stays in marinas is to supply information on the tourism activity in the Danish marinas. Users of the statistics is e.g. business and tourism organisations as well as municipalities and regions to analyse the development in tourism. Furthermore the statistics is used to identify the most popular marina areas in Denmark. The survey is collected on a voluntary basis and is made in collaboration with VisitDenmark. The survey has been compiled since 1992. The survey went from mandatory to voluntary in 2004 which has had an impact on the response rate and thus also the comparability over time., Statistical presentation, The statistics regarding marinas is a monthly seasonally survey about boats and guest nights spent by visiting yachts in marinas in the months of May-September. The statistics are divided into nationalities of the guests, as well as geographically by regions, parts of the country and waters. In addition, there is an annual assessment of the capacity of marinas divided into parts of the country and the size of the marina. Numbers of Municipal distribution is published at the homepage of VisitDenmark., Read more about statistical presentation, Statistical processing, Data for the statistics is collected monthly for for the reference months May to September. The monthly statistics shows temporary data for the activity in the marinas. If a marina has not reported data from the same month the year before is imputed. At the end of the reference year the imputed data is replaced by reported final data for the year. The numbers of nights spent at marinas are calculated by using a average factor for the size of the crew. The average factor is based by a survey made by VisitDenmark in 2017. Data for the statistics is collected via an upload solution or by a electronis questionaire. The collected data undergoes micro-level debugging during the actual collection and at the macro-level when the data is aggregated., Read more about statistical processing, Relevance, The statistics are relevant for e.g. the companies, industry associations, municipalities and regions as well as business and tourism organizations as a basis for forecasts, analyses and planning purposes., Read more about relevance, Accuracy and reliability, The marina statistics was made voluntary from 2004 which may influence the comparability over time as well as the coverage. Some reports are based on a best estimate by the respondent and therefore in risk of being wrong. , Read more about accuracy and reliability, Timeliness and punctuality, The survey is published on a monthly basis for the reference months May-September approx. 40 days after the end of the reference month. Furthermore, an annual publication is made that is published approx. 75 days after the end of the reference year. The survey is published according to the scheduled time table and therefore has a high degree of punctuality., Read more about timeliness and punctuality, Comparability, From 2004 the statistics are voluntary which minimize the comparability over time. From 2007-20016 a new factor regarding the size of the crew has been phased in. From 2017 an onwards this factor is fully phased in. , Read more about comparability, Accessibility and clarity, The statistics are published in , Nyt from Statistics Denmark, . In the statbank the figures are published under the subject , Marinas, and , All types of accommodation, . See more on the statistics , topic page, . Municipality-distributed statistics on holiday rental are financed by VisitDenmark and are freely available on their , website, . , If you want to combine statistics on marinas with other variables or put them together in another way, you can contact DST Consulting to clarify options and request a quote., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/nights-spent-at-marinas

Documentation of statistics