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Publication: Agriculture and Danish farm returns through 100 years 1916-2015

Since the first farm returns were reported for statistical purposes for the , financial year 1916-17, , Danish agriculture has lived through quite a few things., In the first year of the statistics, World War I implied that the countries at war experienced increased demand for e.g. food. As a result, Denmark, which did not participate in the war, was able to sell agricultural products at high prices. By contrast, it was difficult to export in the years of recession in the 1930s and it was necessary to implement emergency farm aid, e.g. in order to reduce high levels of debt.,      2. World War II boosted the technological development and, in the post-war years, horses were ,      increasingly replaced by engine power., When Denmark became a member of the EEC in 1973, new demands were made on the agricultural accounts in the statistics, which were to conform to the same method as that of the other member countries. With the book , Agriculture and Danish farm returns through 100 years,, Statistics Denmark gives the reader an insight into Danish agriculture and its development, in particular in the 20th century., The publication includes e.g.:, Mechanisation and specialisation of the agricultural sector, which has experienced soaring productivity., Accounting figures for 100 years, which show e.g. the development in gross output, operating costs, economic indicators, capital and debts., The preparation of the statistics has undergone method changes, increased the level of detail and, as a result, it has become more applicable in research., Moreover, the table, JORD100, has been added to Statbank.dk to mark the centennial year for the agricultural accounts., Here you can extract accounting figures for agriculture back to 1916 and up to 2015, , which is the last stated year with accounts statistics for agriculture, (only in Danish).,  , Get as pdf, Agriculture and Danish farm returns through 100 years, Colophone, Agriculture and Danish farm returns through 100 years, Business, ISBN pdf: 978-87-501-2279-1, Released: 28 September 2017 09:00, No of pages: 59, Contact info:, Henrik Bolding Pedersen, Phone: +45 20 57 88 87

Publication

JORD1: Profit and loss accounts for all farms (average)

type of farm region standard output, quartile group, items and time
2008-2024 (Avg.)

https://www.statbank.dk/JORD1

Tables in StatBank

LABY36A: 20 year-olds upper secondary school (share in per cent))

municipality groups, educational graduation statement and time
2008-2024 (Share in per cent)

https://www.statbank.dk/LABY36A

Tables in StatBank

LIGELI2: Gender equality indicator of gender pay gap

indicator, occupation, age and time
2010-2024 (Per cent)

https://www.statbank.dk/LIGELI2

Tables in StatBank

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

Classification of education (DISCED-15), completed educations, v1:2025

Name: , DISCED15_AUDD_HOVED_V1_2025 , Description: , DISCED-15 is Statistics Denmark's classification system for education., DISCED-15 acts as a classification system across statistics-producing authorities within the education sector in Denmark. At the same time it ensures a clear connection to the international classification system , International Standard Classification of Education (ISCED), ., All educations in DISCED-15 have a four-digit code, e.g. , 4280: Electrician, , which is aggregated in four different ways. The classification system thus organises education and training programs in the following four dimensions:, Main area, Classification of educational programs which follow the structure of the Danish education system, as regulated by law for higher education and for the admission to vocational education., Types of education, Classification of education programs by type, which makes it possible to differentiate the educations in the Danish education system by type of education, regardless of the level of the educations, fields of education or main area., Levels of education, Classification of education programs in the Danish education system by levels, which are consistent with the international education classification ISCED-P (levels of education)., Fields of education, Classification of educational programs by fields, regardless of the levels of the educations. The basic principle in the construction of the fields of education follows the idea of ​​which employment function or industry the education is oriented towards with a view to later employment. Classification by fields of education ensures complete comparability between the Danish education classification and the international education classification ISCED-F (fields of education and training)., Valid from: , February 1, 2025 , 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 (DISCED-15), completed educations, v1:2025, February 1, 2025, Still valid, Classification of education (DISCED-15), completed educations, v1:2024, February 1, 2024, January 31, 2025, Classification of education (DISCED-15), completed educations, v1:2023, February 1, 2023, January 31, 2024, Classification of education (DISCED-15), completed educations, v1:2022, February 1, 2022, January 31, 2023, Classification of education (DISCED-15), completed educations, v1:2021, February 1, 2021, January 31, 2022, Classification of education (DISCED-15), completed educations, v1:2020, February 1, 2020, January 31, 2021, Classification of education (DISCED-15), completed educations, v1:2019, February 1, 2019, January 31, 2020, Classification on education (DISCED-15), completed educations, v1:2018, February 1, 2018, January 31, 2019, Classification on education (DISCED-15), completed educations, v1:2017, February 1, 2017, January 31, 2018

https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/disced15-audd

Documentation of statistics: Development in Rents (housing)

Contact info, Prices and Consumption , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Development in Rents (housing) 2022 , Previous versions, Development in Rents (housing) 2021, Development in Rents (housing) 2014, The statistics measure the development in rent (housing). The survey has been carried out since the 1950s. , Statistical presentation, The statistics show the development in rents before and after rent subsidies. The average development in rent before rent subsidies is used for the consumer price index and the average development in rent after rent subsidies is used for the index of net prices., Read more about statistical presentation, Statistical processing, The rent survey is based on a sample of privately owned rented dwellings, social rental housing and cooperative dwellings. The rent development for the social rental housing is based on administrative data from Landsbyggefonden and thus covers the entire population of social rental housing. Privately owned rented dwellings are covered by a sample of approx. 110,000 (only approx. 85,000 for 1. quarter of 2022) for dwellings out of a population of approx. 500,000 privately owned rented dwellings. Cooperative dwellings are covered by a sample of approx. 600 dwellings. , Social rental housing and private rental housing as well as cooperative housing each amount to almost half of the total rental housing market whereas cooperative dwellings account for approx. 10 per cent., Read more about statistical processing, Relevance, The statistic measures the development in rent (housing). , The statistic is primarily used in calculating sub-indices in the consumer price index, the index of net retail prices and the harmonized index of consumer prices (HICP). Development in rent is used as an indicator for price development for rented dwellings and for regulating (indexation) rent contracts.s., Read more about relevance, Accuracy and reliability, It is not possible to quantify the uncertainty in the rent survey, as the sample behind is not randomly drawn . However, for social housing, the statistics are based on the population of social housing, which is why there is no uncertainty here. For the private rental homes, the sample consists of approx. 110,000 (only approx. 85,000 for 1. quarter 2022) rental homes out of a population of approx. 500,000 rental housing, so here there is limited sample uncertainty. Cooperative dwellings are covered by a sample of approx. 600 dwellings, so here there is sample uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The consumer price index including the rents index is published on the 10th or the first working day thereafter, following the month in which the data was collected. , The statistics are published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The statistics have been compiled in the same way since 1982. The rent survey is directly comparable with similar rent-indices from other countries' EU harmonized consumer price index (HICP)., Read more about comparability, Accessibility and clarity, Figures for the rent survey can be found in the statistics bank under group 04.1-2 under resp. the consumer price index, the net price index and the EU Harmonized Index of Consumer Prices (HICP)., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/development-in-rents--housing-

Documentation of statistics

R-training in Georgia

In Georgia there is definitely something to celebrate! Despite difficulties coming from the new COVID19-normal, 22 participants have just completed their first training in the IT software ‘R’ at the Georgian National Statistical Office (GeoStat) as part of the EU Twinning project. A success assigned to coordination and cooperation across different sectors and domains with multiple partners and interest groups., 18 May 2021 8:00 ,  , An IT review and a discussion with Expertise France... , EU Twinning projects run with a specific set of objectives and clearly defined activities. But in GeoStat something more is bustling as an IT review combined with an ongoing coordination across projects has led to supplementary and essential goals to be pursued., Georgia - table with gear ready for Covid19 and online meeting. , Photo: Steen B. Pedersen,  , IT-resources are scarce in GeoStat why an IT-sector review led by the , UN Economic Commission on Europe (, UNECE), which the Twinning project was invited to take part in, encouraged them to develop an IT-training strategy for both IT and statistical staff. Training of IT staff will raise the skills and competence level of staff and in the long run hopefully attract new IT staff to GeoStat. Training of statistical staff will on the other hand, loosen the pressure on IT-resources. , The IT-sector review also suggested that GeoStat considers alternatives to Excel and MS-Access for statistical production processes. And meanwhile, Twinning experts on different subject areas were working with colleagues from GeoStat on implementing new statistical products and procedures – and choosing IT software was an essential part of that work. Selecting a well-known solution would of course be the easiest on the short run, but this did not happen!  , The Resident Twinning Advisor and the Project leader from Expertise France implementing the EU funded project “Statistics for the Eastern Partnership” (STEP) had long been discussing opportunities for possible areas of cooperation and synergies between the two projects with ‘R’ being a top priority for cooperation. Now to build from the bricks of the IT-sector review and the parallel discussions around cooperation efforts, ‘R’ was instead added to both work plans and course materials with efforts to take the first steps towards implementing an open source software more systematically as an integrated part of the statistical production process.  , Conducting training in times of COVID19, Like so much else, COVID19 also challenges statistical capacity building across borders why the first R-mission in the frame of the Twinning project was conducted online. On a positive note, this allowed for more employees to participate compared to the original plan. 6 sessions, of three hours each, in a combination of plenary introductions and practical training in “breakout rooms” - covered subjects such as data manipulation, data visualisation and more advanced loops and function procedures. , The next training mission will be conducted during the summer 2021. Meanwhile GeoStat employees have the opportunity to test/put their newly adapted skills into practice.,  , # Facts , about the EU Twinning project:, Name: , Strengthening the capacity of the Georgian Statistical system, Partner: ,  , National Statistics Office of Georgia  & Statistics Denmark, Duration: , April 2019 – July 2021,  

https://www.dst.dk/en/consulting/news-from-international-consulting/2021/18-05-2021-R-training-in-Georgia

Documentation of statistics: Health of vulnerable groups (Discontinued)

Contact info, Personal Finances and Welfare , Anne-Sofie Dam Bjørkman , +45 20 37 54 60 , ASD@dst.dk , Get documentation of statistics as pdf, Health of vulnerable groups 2017 , Previous versions, This set of statistics documents the use of health services by vulnerable groups compared to that of the rest of the population within the same age group. The statistics are used to find out whether selected vulnerable groups have a different consumption of health services than the rest of the population. The statistics will be published for the first time in 2018, with figures from 2015 upwards. , Statistical presentation, This set of statistics is an annual compilation of vulnerable groups’ use of health services, measured on the basis of selected health indicators, for comparison with that of the rest of the population. The health indicators include contact with the primary sector (general practitioner, medical specialists, dentists, physiotherapists, chiropractors etc.) as well as the secondary sector (somatic and psychiatric hospitals). Statistics Denmark has not previously released data on psychiatric hospitals. The first vulnerable group for this set of statistics is Vulnerable children and young persons, as defined in the statistics for Vulnerable children and young persons. , Read more about statistical presentation, Statistical processing, Data for the statistics is retrieved from the registers for Vulnerable children and young persons, Visits to physicians etc. Hospitalisation rates. The statistical population is identical with the statistics for Vulnerable Children and Young Persons. A control population is created on the basis of the population register and includes the rest of the children and young persons aged 0-22 (at the beginning of the year). Data has been validated in advance for the individual set of statistics, which is why data is not further validated. The two generated populations are coupled with background data (Visits to physicians etc., Hospitalisation rates (and psychiatry) and the population (age, sex and municipality)). Age is age at the end of the year. Tables for Statbank Denmark are created crossing variables and removing sums where they are irrelevant. We have made no standardisation for age and sex. , Read more about statistical processing, Relevance, The statistics are relevant for citizens, authorities and organisations as a knowledge base for vulnerable groups’ use of the primary and secondary health services in Denmark. In future, the plan is to extend the statistics to include more vulnerable groups and data on the consumption of medicinal products. This would increase the utility of the statistics. The statistics were presented to Statistics Denmark’s user committee for Welfare statistics in 2018. , Read more about relevance, Accuracy and reliability, In connection with the creation of the population, it should be noted that differences in the municipal case management systems imply that the municipalities do not register information about vulnerable children and young persons in the exact same way and systematically. This may result in inconsistency from one municipality to the next as to exactly which children and young persons to include in the population. We do not know the size of this source of error, nor do we know how much it affects the accuracy of the statistics. Furthermore, you should note that the statistical population also includes children and young persons with physical disabilities who – due to their disabilities – have been removed from parental care or have support measures. We do not currently know the size of this group. , Read more about accuracy and reliability, Timeliness and punctuality, This set of statistics is published within the subsequent calendar year. The population of Vulnerable children and young persons must first be defined for the year before the statistics can be released, Read more about timeliness and punctuality, Comparability, In its present form with Statistics Denmark, the statistics are compiled for a period from 2015-2017 and are comparable in the period. , Read more about comparability, Accessibility and clarity, The publication date appears from the scheduled releases. The date will be confirmed in the weeks ahead., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/health-of-vulnerable-groups--discontinued-

Documentation of statistics

Classification on education (DISCED-15), current educations, v1:2023

Please note, a more current version of this classification is now available. See the current version , here., Name: , DISCED15_UDD_HOVED_V1_2023 , Description: , DISCED-15 is Statistics Denmark's classification system for education., DISCED-15 acts as a classification system across statistics-producing authorities within the education sector in Denmark. At the same time it ensures a clear connection to the international classification system , International Standard Classification of Education (ISCED), ., All educations in DISCED-15 have a four-digit code, e.g. , 4280: Electrician, , which is aggregated in four different ways. The classification system thus organises education and training programs in the following four dimensions:, Main area, Classification of educational programs which follow the structure of the Danish education system, as regulated by law for higher education and for the admission to vocational education., Types of education, Classification of education programs by type, which makes it possible to differentiate the educations in the Danish education system by type of education, regardless of the level of the educations, fields of education or main area., Levels of education, Classification of education programs in the Danish education system by levels, which are consistent with the international education classification ISCED-P (levels of education)., Fields of education, Classification of educational programs by fields, regardless of the levels of the educations. The basic principle in the construction of the fields of education follows the idea of ​​which employment function or industry the education is oriented towards with a view to later employment. Classification by fields of education ensures complete comparability between the Danish education classification and the international education classification ISCED-F (fields of education and training)., Valid from: , February 1, 2023 , Valid to: , January 31, 2024 , 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 on education (DISCED-15), current educations, v1:2025, February 1, 2025, Still valid, Classification on education (DISCED-15), current educations, v1:2024, February 1, 2024, January 31, 2025, Classification on education (DISCED-15), current educations, v1:2023, February 1, 2023, January 31, 2024, Classification on education (DISCED-15), current educations, v1:2022, February 1, 2022, January 31, 2023, Classification on education (DISCED-15), current educations, v1:2021, February 1, 2021, January 31, 2022, Classification on education (DISCED-15), current educations, v1:2020, February 1, 2020, January 31, 2021, Classification on education (DISCED-15), current educations, v1:2019, February 1, 2019, January 31, 2020, Classification on education (DISCED-15), current educations, v1:2018, February 1, 2018, January 31, 2019, Classification on education (DISCED-15), current educations, v1:2017, February 1, 2017, January 31, 2018

https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/disced15-udd?id=36d558f8-5885-46a0-9760-cbd944c6c68d