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Documentation of statistics: Environmental accounts for Denmark (Discontinued)

Contact info, National Accounts, Climate and Environment , Ingeborg Vind , +45 24 83 51 49 , INV@dst.dk , Get documentation of statistics as pdf, Environmental accounts for Denmark (discontinued) 2013 , Previous versions, Environmental accounts for Denmark (discontinued) 2012, These statistics are no longer compiled under the name Environmental Accounts for Denmark. Now specific documentations of statistics can be found under the subject page Environmental-Economic Accounts., Statistical presentation, The environmental accounts contain information on a) Material flows in the form of the the weight of Danish resource extraction, import and exports, b) Air emissions of different substances (CO2, N2O, CH4, PFC, HFC, SF6, NOx, NMVOC, CO, PM10, PM2.5, SO2, NH3), c) Public expenditure and revenue on the environment as well as d) Environmental related taxes etc., The definitions used in the environmental accounts ensures that the information immediately can be used for analyses of the interaction between the economic activities and e.g. air emissions of some of the above-mentioned substances., Read more about statistical presentation, Statistical processing, Emission accounts are compiled taking energy accounts as a starting point for the emissions caused by the use of energy. Emissions caused by other factors than energy use are added subsequently and distributed among the relevant industries. , Tax revenues are broken down by industries on the basis of detailed information from National Accounts., Material Flow Accounts are compiled on the basis of internal and external sources on resource extraction., Read more about statistical processing, Relevance, Environmental Accounts are relevant for those interested in the correlation between the economy on the one side and environment and natural resources on the other side. Ministries and consultant firms are among the main users of environmental accounts. Accounts are included in the overall European environmental accounts, collected and compiled by Eurostat., Read more about relevance, Accuracy and reliability, Figures on statistical uncertainty have not been estimated., Read more about accuracy and reliability, Timeliness and punctuality, Data is normally published without delays., Read more about timeliness and punctuality, Comparability, The industry classification in the tables is the same as the one used in the national accounts. The tables can therefore be compared to other statistics based on the industry classification. Accounts are compiled in form of time series. For example accounts for air emissions are available for each year from 1990 until the last year that is published. Accounts are consistent and fully comparable within these years. On the more aggregated level (NACE 64), the Danish accounts are comparable with accounts of other EU countries compiled according to the Regulation no. 691/2011 on European environmental economic accounts., Read more about comparability, Accessibility and clarity, Environmental-economic accounts, Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/environmental-accounts-for-denmark--discontinued-

Documentation of statistics

Classification of education (DDU), completed educations, v1:2023

Please note, a more current version of this classification is now available. See the current version , here., Name: , DDU_AUDD_V1_2023 , Description: , DDU stands for Den Danske Uddannelsesklassifikation and is the Danish classification system for all educations in Denmark. Statistics Denmark operates the classification in cooperation with The Ministry of Higher Education and Science (UFM) as well as the Ministry of Children and Education (BUVM). , The classification covers both regulated and private educations and serves as a national standard for organising, describing and comparing the different possibilities for educations within Denmark’s educational system., All educations in DDU have a unique four-digit completed educations code, called AUDD-code, e.g. 4443: Miller. The education is placed in four groups in a hierarchical structure, which categorises the educations based level, differences in content and kinship:, Main area, A one-digit classification which describes the level of education at an aggregated level, Main group, A two-digit classification that represents the element of a legal or functional difference between the main areas in the education types within the same overall educational level. For example, distinctions can be made between vocational bachelors, academic bachelors and other medium cycle further educations within the main area=6,’’Medium cycle further education’’., Middle group, A three-digit classification and the first level in the classification of education where a division is made based on the content differences of the educational programs. Here, the education- and admission regulations are included., Sub group, A four-digit classification, which gives a more detailed content based division of educations within the same middle group., So far, three new statbank tables based on DDU have been published:, UDDALL10: , Educational activity by region, education (DDU), age, sex and status (2005-2022), EUD34: , Educational activity at upper secondary vocational educations by education (DDU), age, ancestry, national origin, sex, status and education part (2005-2022), KVEU20: , Participation in supplementary courses by field of education (DDU), region, age, sex, points in time and unit (2005-2022), Valid from: , December 1, 2023 , Valid to: , January 31, 2026 , Office: , Population and Education , Contact: , Martin Herskind, , hrs@dst.dk, , ph. +45 21 34 03 31 , Codes and categories, Codes and categories are only available in Danish , All versions, Name, Valid from, Valid to, Classification of education (DDU), completed educations, v1:2026, February 1, 2026, Still valid, Classification of education (DDU), completed educations, v1:2023, December 1, 2023, January 31, 2026

https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/ddu-audd?id=00735784-1738-48d5-bd10-aa37a912580f

Classification of education (DDU), current educations, v1:2023

Please note, a more current version of this classification is now available. See the current version , here., Name: , DDU_UDD_V1_2023 , Description: , DDU stands for Den Danske Uddannelsesklassifikation and is the Danish classification system for all educations in Denmark. Statistics Denmark operates the classification in cooperation with The Ministry of Higher Education and Science (UFM) as well as the Ministry of Children and Education (BUVM). , The classification covers both regulated and private educations and serves as a national standard for organising, describing and comparing the different possibilities for educations within Denmark’s educational system., All educations in DDU have a unique four-digit education code, also known as UDD, e.g. 4443: Miller. The education is placed in four groups in a hierarchical structure, which categorises the educations based on level, differences in content and kinship:, Main area, A one-digit classification which describes the level of education at an aggregated level, Main group, A two-digit classification that represents the element of a legal or functional difference between the main areas in the education types within the same overall educational level. For example, distinctions can be made between vocational bachelors, academic bachelors and other medium cycle further educations within the main area=6,’’Medium cycle further education’’., Middle group, A three-digit classification and the first level in the classification of education where a division is made based on the content differences of the educational programs. Here, the education- and admission regulations are included., Sub group, A four-digit classification, which gives a more detailed content based division of educations within the same middle group., So far, three new statbank tables based on DDU have been published:, UDDALL10: , Educational activity by region, education (DDU), age, sex and status (2005-2022), EUD34: , Educational activity at upper secondary vocational educations by education (DDU), age, ancestry, national origin, sex, status and education part (2005-2022), KVEU20: , Participation in supplementary courses by field of education (DDU), region, age, sex, points in time and unit (2005-2022), Valid from: , December 1, 2023 , Valid to: , January 31, 2026 , Office: , Population and Education , Contact: , Martin Herskind, , hrs@dst.dk, , ph. +45 21 34 03 31 , Codes and categories, Codes and categories are only available in Danish , All versions, Name, Valid from, Valid to, Classification of education (DDU), current educations, v1:2026, February 1, 2026, Still valid, Classification of education (DDU), current educations, v1:2023, December 1, 2023, January 31, 2026

https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/ddu-udd?id=ef405e38-a2db-4498-be2d-50bf54c2248d

Analyses: How big are Danish exports and who are our main trading partners?

In recent decades it has become more common to produce goods across national borders. Increasing globalisation challenges our understanding of what a country's exports encompass and what different statistical measures of exports show., Previously, different export statistics provided a fairly similar picture of Denmark’s exports and trading partners. However, an increasing proportion of Danish exported goods never crosses Danish borders, and that has resulted in increasing differences across the various export statistics. This analysis describes Danish exports and trading partners, based on the different export statistics., Main conclusions:, Danish exports in goods are largest when measured in Denmark’s balance of payments, where the sale of goods that have never crossed Danish borders are included as exports. Today, around a sixth of the total Danish export of goods takes place outside of Danish borders., Only goods which have crossed the Danish border are classified as exports in the international trade in goods statistics which implies that the export of goods appears lower here than in the balance of payments., Exports appear lowest when measured by Danish value added, as these calculations discount the value of the imports included in the production of the exported goods and services. Estimates from an Input-Output model in Statistics Denmark suggest that imported contents in exported goods and services constitute nearly half of the total value. , Regardless of the type of export statistics, Germany is Denmark’s most important export market., On the basis of goods which cross the Danish border, the US is Denmark’s sixth largest export market. When goods sold outside Denmark’s border are taken into account, the US is Denmark’s third largest export market., Looking at the final markets for the part of exports resulting from production in Denmark the US is the second largest export market as measured by Danish value added according to estimates in an OECD international Input-Output model., Get as pdf, How big are Danish exports and who are our main trading partners?, Colophone, How big are Danish exports and who are our main trading partners?, Subject group: Economy, Released: 5 March 2018 08:00, No. 2018:4, ISSN pdf: 2446-0354, Contact:, Mads Møller Liedig, Telephone: +45 40 12 97 72

Analysis

Analyses: The global organisation of industrial groups has an impact on the measurement of Danish production and income

The way in which Danish enterprises choose to organise their production and sales in the global economy impacts whether it is reflected as domestic production and value added (GDP) or only as income (GNI) in the national accounts. When Danish enterprises sell products abroad, the activities are included in Danish GDP, whereas income based on sales via subsidiaries abroad is only included in GNI. In this way, the choice of sales channel impacts the statistics on Danish production and income., This analysis describes the global set-up of Danish industrial groups and their impact on the Danish economy. Focus is on the close correlation between Danish exports and in-come from subsidiaries abroad. The analysis is an extension of a Statistics Denmark analysis from 2016 dealing with goods exports outside Denmark by Danish manufactu¬ring enterprises. Income data from the central bank of Denmark, Nationalbanken, has allowed us to further document the importance of the industrial groups to the Danish economy., Main conclusions:, The industrial groups are important to the Danish economy; they export goods and services produced in Denmark or abroad and receive income from subsidiaries abroad. , In 2016, Danish industrial groups’ sale abroad of goods not crossing the Danish border accounted for almost a third of their total sale of goods abroad of DKK 524 billion., The income from subsidiaries of DKK 42.1 billion accounts for approximately one third of total earnings from Danish industrial groups’ manufacturing activities abroad. These ear-nings could have been counted as exports had the group chosen a different role for the production taking place in subsidiaries abroad., In 2016, the industrial groups’ activities abroad accounted for approximately 6 per cent of the Danish gross national income (GNI) and approximately 4 per cent of the gross domestic product (GDP).,  , This is a translation of an analysis previously published in Danish 1 October 2018. See the analysis , here., Get as pdf, The global organisation of industrial groups has an impact on the measurement of Danish production and income, Colophone, The global organisation of industrial groups has an impact on the measurement of Danish production and income, Subject group: Economy, Released: 27 May 2019 08:00, No. 2019:7, ISSN pdf: 2446-0354, Contact:, Mads Møller Liedig, Telephone: +45 40 12 97 72

Analysis

Analyses: Large language models and the Danish labour market

Generative artificial intelligence (AI) tools such as large language models are spreading rapidly. The most prominent example is ChatGPT, which gathered more than 100 million active users within two months. This type of generative AI has the potential to change the way people work, creating opportunities for innovation and productivity gains. However, the opportunities and challenges will most likely be unequally distributed across the workforce., This analysis explores the unequal economic impact of large language models (LLMs) on the Danish Labour Market. The analysis uses the so-called AI Occupational Exposure (AIOE) scores from a study of the American labour market and merges these scores with administrative data from Statistics Denmark. The AIOE scores reflect the relatedness between AI applications and human abilities connected to different occupations. Thus, the scores express potential economic impact of AI applications across occupations through either labour-augmenting or labour-displacing effects., Main conclusions:, Occupations dominated by cognitive routine tasks have the highest potential to change through large language models. , Legal Professionals, is the occupation with the highest LLM score. The occupation with the lowest score is , Painters, building structure cleaners & related trades worker, ., Economic activities influenced by cognitive abilities have higher LLM scores than activities dominated by physical tasks. The activity with the highest LLM score is , Higher Education, . The activity with the lowest score is , Building completion and finishing, ., Employed females altogether have more potential to apply large language models than employed males. However, within , Human Health & Social Work activities, women have a slightly lower LLM score than males., Employees with high personal yearly income generally have more potential to use and take advantage of large language models than employees with lower income.,  , The analysis is available in Danish here: , Store sprogmodeller og det danske arbejdsmarked,   , Get as pdf, Large language models and the Danish labour market, Colophone, Large language models and the Danish labour market, Subject group: Labour and income, Released: 8 February 2024 08:00, No. 2024:2, ISSN pdf: 2446-0354, Contact:

Analysis

Analyses: Who uses weight loss medicines in Denmark?

In 2023, 117,500 adults redeemed a prescription for a weight loss medicine. This corresponds to 2.4 per cent of the adult population. Weight loss medicines are mainly targeted at people with a BMI of at least 30, but what else characterises the users?, This analysis takes a closer look at the users of weight loss medicines, with a special focus on users in the first half of 2023. In the analysis, data on redeemed prescriptions is combined with information from Statistics Denmark’s registers. This allows, among other things, to examine the users’ sex, age, income, and municipality of residence.,  , Main conclusions:, The number and proportion of adults who have redeemed at least one prescription for weight loss medicines has increased significantly from 15,200 (0.3 per cent) in 2021 to 27,800 (0.6 per cent) in 2022 and 117,500 (2.4 per cent) in 2023. However, the number is still lower than 25 years ago when 131,100 adults (3.1 per cent) used weight loss medicines., The proportion of users of weight loss medicines is higher for women in all years. In the first half of 2023, 72 per cent of the users were women and 28 per cent were men., The proportion of users was highest in the age group of 50-59-year-olds (3.2 per cent) and lowest in the age group of 80-year-olds and older (0.1 per cent)., The proportion of users of weight loss medicines increases with income. In the first half of 2023, 1.6 per cent of the people in the lowest income quintile used weight loss med-icines, while it was about 3.4 per cent of the people in the highest income quintile - when using the equivalised disposable family income among the 30-59-year-olds., There is a difference in the proportion of users of weight loss medicines across municipalities. The highest proportion of users was in Tårnby (2.9 per cent), while the lowest proportion was in Læsø (0.8 per cent)., Gentofte municipality had the highest proportion of users of weight loss medicines in the first part of 2023 when the proportion is related to people with self-reported obesity in 2021. In Gentofte, there were 24.5 users of weight loss medicines per 100 people liv-ing with obesity, while in Læsø, there were 2.9 users per 100 people living with obesity.,  , The analysis is available in Danish here: , Hvem bruger slankelægemidler?, Get as pdf, Who uses weight loss medicines in Denmark?, Colophone, Who uses weight loss medicines in Denmark?, Subject group: People, Released: 6 May 2024 08:00, No. 2024:3, ISSN pdf: 2446-0354, Contact:, Emilie Rune Hegelund, Telephone: +45 20 56 47 11

Analysis

Documentation of statistics: Employee Trade Unions

Contact info, Labour Market, Social Statistics , Mikkel Zimmermann , +45 51 44 98 37 , MZI@dst.dk , Get documentation of statistics as pdf, Employee Trade Unions 2024 , Previous versions, Employee Trade Unions 2023, Employee Trade Unions 2022, Employee Trade Unions 2021, Employee Trade Unions 2020, Employee Trade Unions 2019, Employee Trade Unions 2018, Employee Trade Unions 2017, Employee Trade Unions 2016, Employee Trade Unions 2015, Employee Trade Unions 2014, Employee Trade Unions 2013, The purpose of the statistics is to compile aggregated annual statistics showing the number of members of employee organisations with attachment to the labour market. The statistics been complied since 1994, but is in its current form comparable from 2007 and onwards. , Statistical presentation, The statistics provide an overview of the number of members of employee organisations with attachment to the labour market i.e. excl. trainees, retirees, early retirees and self-employed. The statistics are grouped by central organisations/individual organisations and gender. The statistics are published annually and disseminated in the newsletter Nyt fra Danmarks Statistik and in the StatBank., Read more about statistical presentation, Statistical processing, These statistics are based on annual reports from employees' organisations on the number of members attached to the labour market per December 31. Data are typically validated by comparing the current year’s reporting with that of previous years for each organisation. As of the reference date 31 December 2023, total membership figures are also reported for each organisation. These totals are then compared with the reported number of members with labour market affiliation per organisation to ensure consistency., Read more about statistical processing, Relevance, Users of the statistics are typically employee and employer organisations, researchers and the media. No dissatisfaction has been expressed with the statistics., Read more about relevance, Accuracy and reliability, The statistics are based on reports from Central Employee Organisations and other employee organisations. Not all employee unions are able to calculate the precise figures exclusive members not attached to the labor market, i.e.. students, early retirees and pensioners, and self-employed. The data are therefore believed to be a little overestimated for some organisations. On the other hand, there may be small employee organisations that are not included. The data are normally not revised, but if errors are detected they are corrected back in time as far as possible. Although participation in the statistics is voluntary, all employee organisations appear to submit data., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 4-5 months after the reference date. , The statistics are usually published on the scheduled date without delay., Read more about timeliness and punctuality, Comparability, The statistics have been compiled (without data breach) since 2007. Minor breaks in the time series may occur when employee organisations change their reporting methods. For example, the previously observed sharp decline in membership figures for some organisations (mainly those under LO) from 2011 to 2012 was due to the inclusion of members without labour market affiliation in earlier reporting. However, this decline has been addressed as of the publication on 19 May 2025, by revising the reported figures downwards for the period 2007–2011., Read more about comparability, Accessibility and clarity, The statistics is published yearly in a Danish press release (Nyt fra Danmarks Statistik) at the same time as the tables are updated in the StatBank. In the StatBank, the statistics ca be found under the subject , Trade unions, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/employee-trade-unions

Documentation of statistics

Documentation of statistics: Sports clubs and sporting facilities

Contact info, Science, Technology and Culture, Business Statistics , Trine Jensen , +45 20 13 88 17 , TSN@dst.dk , Get documentation of statistics as pdf, Sports clubs and sporting facilities 2025 , Previous versions, Sports clubs and sporting facilities 2024, Sports clubs and sporting facilities 2023, Sports clubs and sporting facilities 2022, Sports clubs and sporting facilities 2021, Sports infrastructure and resources 2020, Sports infrastructure and resources 2019, Sports infrastructure and resources 2018, Sports infrastructure and resources 2017, The purpose of these statistics is to illustrate the physical and organizational structures of sports in Denmark, as well as memberships under the various sports federations. The statistics have been established since 2017 and are comparable throughout the period., Statistical presentation, These statistics is an annual estimate of the number of associations, number of members and sports facilities in Denmark. These statistic are allocated by organization, facility type and geographical by municipality. , Read more about statistical presentation, Statistical processing, Facilities are compiled per October 1st annually from the Danish Sports Facility Database. The database is a co-operation between the Danish Institute for Sports Studies and the Danish Foundation for Culture and Sports Facilities. The number of sports associations and members are reported annually by DIF, which collects data about sports associations and members from administrative sources., Data processing in Statistics Denmark includes coding of data, tabulation and control of detailed register extracts to the level of publication., Read more about statistical processing, Relevance, Users are Ministries, Agencies and various interest groups. The statistics are developed in cooperation with the Ministry of Culture and a project group comprising representatives of the national sports associations, researchers and other resource persons in this area. The statistics may serve to qualify public debate on sports and cultural policies., Read more about relevance, Accuracy and reliability, The statistics do not take into account missing reports to resp. the Central Association Register or the Facility Database. This could e.g. be an association with non-reporting of a group of members or a municipality's non-reporting of a new sports facility. However, the statistics are based on known authoritative sources and databases regarding the sports organizations' membership and facility numbers., Read more about accuracy and reliability, Timeliness and punctuality, Publications are made annually approximately four months after the end of the reference period. These statistics are published without delay, with reference to the announced time of publication in the release calendar., Read more about timeliness and punctuality, Comparability, No comparison with other countries are made. Selected results may be compared to other presentations of the original sources, e.g. those made by the Central Registry of Sports Associations and the Danish Sports Facility Database., Read more about comparability, Accessibility and clarity, These statistics are published in the StatBank under , Sports clubs and sporting facilities, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sports-clubs-and-sporting-facilities

Documentation of statistics

Documentation of statistics: Newspapers and Magazines

Contact info, Science, Technology and Culture, Business Statistics , Christian Max Gustaf Törnfelt , +45 21 63 60 20 , CHT@dst.dk , Get documentation of statistics as pdf, Newspapers and Magazines 2023 , Previous versions, Newspapers and Magazines 2022, Newspapers and Magazines 2021, Newspapers and Magazines 2020, Newspapers and Magazines 2019, Newspapers and Magazines 2018, Newspapers and Magazines 2017, Newspapers and Magazines 2016, Newspapers and Magazines 2014, Newspapers and Magazines 2013, The purpose of the statistics for newspapers and magazines is to shed light on the development of the readership and the number of magazines, trade journals and daily newspapers in Denmark. Previously, the statistics were based on circulation figures from Dansk Oplagskontrol, but from 2017 it is based on readership numbers from Index Denmark / Gallup with time series beginning in 2007., Statistical presentation, Daily newspapers and magazines are annual statements of readership and the number of different categories of newspapers and magazines. Newspapers are divided according to whether their reach is nationwide or local / regional. Magazines are distributed on topics and publication frequencies. Trade journals are divided according to the Danish media industry classification, e.g. agriculture or communication. , Read more about statistical presentation, Statistical processing, The statistics are based on official, industry-recognized readership measurements for the printed media that Index Denmark/Gallup compiles and where quality assurance is performed by the Index Denmark Methodology Committee . Data is collected by a sample survey that annually includes 25,000 representative respondents aged 12 years and over. Statistics Denmark publish the data compiled by Index Denmark/Gallup in interactive tabular format. For newspapers, trade journals and magazines, Statistics Denmark aggregates the readerships to gross coverage., Read more about statistical processing, Relevance, The statistics are expected to meet the needs of several user groups for a comprehensive and easily accessible overview of readership for daily newspapers and the development of the printed media. , Read more about relevance, Accuracy and reliability, The statistics is based on a survey based on a sample of respondents and readership figures are therefore subject to uncertainty. Readership figures say nothing about the thoroughness of reading, and reflects the respondents' own perception of their media usage. The statistics are based on official, industry-recognized readership measurements from Index Denmark/Gallup. In addition to the statistical uncertainty in the measurement of readership figures in the original sources, typing, coding and calculation errors in the data processing can be sources of uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately four months after the end of the reference year. The statistics are published at the announced time., Read more about timeliness and punctuality, Comparability, The statistics are comparable in their current form since 2018. Furthermore, deactivated tables present comparable data of 6-months intervals in a time series from 2007-2018. Comparable statistics are available for Nordic daily newspapers based on statistics in the Nordic StatBank. At European level, there is a comparative study of the number of readers reading newspapers published by Eurostat., Read more about comparability, Accessibility and clarity, The figures are published in the StatBank under the subject , News media and magazines, . In addition, selected results are included in the publication , Culture, . See more on the statistics , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/newspapers-and-magazines

Documentation of statistics