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Documentation of statistics: Labour Market Account

Contact info, Labour Market , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Labour Market Account 2021 , Previous versions , Labour Market Account 2019, Labour Market Account 2016, Labour Market Account 2015, Labour Market Account 2013, Labour Market Account 2014, New Labour Market Account concerning the population´s labour market status have been developed by Statistics Denmark. , The primary purpose of the Labour Market Accounts (LMA) is to provide a complete overview of the population´s labour market status compiled in terms of full-time persons, covering a given period of time or a given point-in-time., Statistical presentation, The Labour Market Account is compiled annually and provides information on the population´s labour market status, where labour-market related activities are given the highest priority. The statistics are compiled in terms of full-time persons. , Data on the population´s labour market status are broken down by socio-economic groups i.e. persons in employment, students, unemployed persons and other persons receiving public benefits, children and young people and other people outside the labour force., Read more about statistical presentation, Statistical processing, The primary statistical data for the LMA is a newly developed register called the AMR-UN (LMA without standardization of hours)., The AMR-UN is composed of administrative data, which are integrated and harmonised in a statistical system. , On the basis of the AMR-UN, the LMA is constructed by means of an hourly standardization of the population´s labour market status, where a person can at maximum contribute with 37 hours per week, corresponding to the existing hourly standard., Read more about statistical processing, Relevance, Over a number of years Statistics Denmark has carried out work on developing the LMA. Several users have indicated their great interest in and expectations with regard to the statistics/register. , Users of the LMA are typical ministries, organisations and research institutes, etc., Read more about relevance, Accuracy and reliability, In the LMA, a wide range of data sources are subjected to data editing and harmonisation in one statistical system. This implies that the LMA can conduct far better analyses of the labour market than the analyses that can be conducted by each individual statistic. At the same time, the LMA constitutes a census of the population and consequently, the statistical uncertainty is reduced compared to statistics compiled on the basis of sample surveys., Against this background, the quality of the statistics is considered to be relatively high. Despite this, there is still some degree of uncertainty linked to the statistics., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately 15 months after the reference year., Read more about timeliness and punctuality, Comparability, The statistics cover the period 2008 to 2021, and during this period the development are comparable. , Read more about comparability, Accessibility and clarity, The statistic is published i the statbank , Labour market accounts, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/labour-market-account

Documentation of statistics

Documentation of statistics: Sale of Organic Foods in Retail Shops

Contact info, Food Industries, Business Statistics , Martin Lundø , +45 51 46 15 12 , MLU@dst.dk , Get documentation of statistics as pdf, Sale of Organic Foods in Retail Shops 2024 , Previous versions , Sale of Organic Foods in Retail Shops 2023, Sale of Organic Foods in Retail Shops 2022, Sale of Organic Foods in Retail Shops 2021, Sale of Organic Foods in Retail Shops 2020, Sale of Organic Foods in Retail Shops 2019, Sale of Organic Foods in Retail Shops 2018, Sale of Organic Foods in Retail Shops 2017, Sale of Organic Foods in Retail Shops 2016, Sale of Organic Foods in Retail Shops 2015, Sale of Organic Foods in Retail Shops 2014, Sale of Organic Foods in Retail Shops 2013, These statistics cover the size and composition of the turnover of organic food in supermarkets and department stores. The study was conducted for the first time for the year 2003. From 2017 companies who exclusively sell online, including subscriptions, have been included in the survey., Statistical presentation, 'Sale of organic foods in retail shops' is an annual statement of the sale of organic food and beverages in the retail trade, calculated by quantity and value. The statistics are divided into product groups. Data basis for the survey is reports from the major supermarket chains and wholesalers, who sell food to retailers., Read more about statistical presentation, Statistical processing, Survey population: the major supermarket chains and wholesalers, who sell food to retailers. Questionnaires are quality controlled (correlation between value and quantity, developments from previous years) and respondents are recontacted if necessary. Retail sales that originate from wholesalers are calculated on the basis of their volume sales and kilo prices from retailers, so that the reported information is comparable with the other reported information from supermarkets and department stores., Read more about statistical processing, Relevance, The statistics is used by interest groups, authorities etc. to assess the level and composition of organic consumption., Read more about relevance, Accuracy and reliability, Census, no sampling error., There is some uncertainty in the calculation of data from the wholesalers. After a detailed analysis of the questionnaires received, Statistics Denmark asses that the information overall gives a true picture of retail sales of organic food and drinks in supermarkets and department stores, however, sales of dairy products can be underestimated., The reported figures are estimated to be of good quality., Read more about accuracy and reliability, Timeliness and punctuality, Dissemination 4-5 months after the survey year. The statistics is usually published as scheduled., Read more about timeliness and punctuality, Comparability, There is no public comparable statistics. However, some comparison can be made to statistics on the the overall retail, for example, e.g. Retail Index., In Sweden and Norway one can find partially comparable statistics. The Danish statistics are comparable from 2003 to now., Read more about comparability, Accessibility and clarity, The statistics are published in yearly in a Danish press release, at the same time as the table is updated in the StatBank. In the Statbank, these statistics can be found under the subject , Trade in organic food, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sale-of-organic-foods-in-retail-shops

Documentation of statistics

Documentation of statistics: Research and development in the public sector

Contact info, Science, Technology and Culture, Business Statistics , Mille Wilhjelm Poulsen , +45 40 18 78 40 , MWP@dst.dk , Get documentation of statistics as pdf, Research and development in the public sector 2024 , Previous versions , Research and development in the public sector 2023, Research and development in the public sector 2022, Research and development in the public sector 2021, Research and development in the public sector 2020, Research and development in the public sector 2019, Research and development in the public sector 2018, Research and development in the public sector 2017, Research and development in the public sector 2016, Research and development in the public sector 2015, Statistics on Research and Development – Public sector 2014, Statistics on Research and Development – Public Sector 2013, Statistics on Research and Development – Public sector 2012, The purpose of the statistics on Research and Development in the public sector is to illustrate the extent of R&D activities carried out within the public sector. The statistics are used, among other things, to assess the share of GDP devoted to research and development. The survey is conducted according to the OECD guidelines for research and development (R&D) statistics, as set out in the Frascati Manual. The statistics have been produced since 1997, but are comparable in their current form from 2007 onwards., Statistical presentation, The statistics provide an annual account of R&D in the public sector, showing both expenditure (in millions of kroner) and personnel (in numbers and full-time equivalents). The data are distributed by main sectors, types of expenditure, scientific fields, and type of research., Read more about statistical presentation, Statistical processing, The statistics are based on questionnaires and are collected annually from approximately 650 public and private non-profit units, which together are assumed to carry out all significant R&D in the public sector. The reported data undergo extensive validation, focusing on a number of high-priority variables, particularly R&D expenditure and R&D full-time equivalents. Validation is performed at both the macro and micro level., Read more about statistical processing, Relevance, There is a general political objective of increasing the share of GDP, which is applied for research and development, and in the light of this objective, there is great interest in compiling statistics on research and development. The main users are Ministries, public authorities, business organisations, researchers, private business enterprises and the media. In addition, the European Commission (The statistical office Eurostat) and the OECD are important users. Data are available for purposes of research., Read more about relevance, Accuracy and reliability, They are based on a complete census, of the expected research-active institutions, of approximately 650 public institutions, with a response rate close to 100 percent. The large dataset undergoes extensive validation, and except for a single question, the extent of imputation for missing values is relatively limited. Imputation may, for example, involve inserting calculated values from other institutions’ reports in place of missing information., Read more about accuracy and reliability, Timeliness and punctuality, National release is done 1 year after the end of the reference period. It is the aim to publish preliminary figures 1 year after the end of the reference period. Final figures are published 1 year after the preliminary figures. Transmission of data to Eurostat follows rules laid down in the relevant legal act. , Read more about timeliness and punctuality, Comparability, Comparable figures are available for 1997–2006, when the statistics were compiled by the Centre for Research Analysis, and from 2007 onwards. In the 2007 statistics, some changes were made to the accounting principles compared with earlier compilations, and between 2006 and 2007 a number of structural changes affected a large number of research institutions. This means that the data in the new survey are only partially comparable with previous surveys., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Research and development, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/research-and-development-in-the-public-sector

Documentation of statistics

Land cover, v3:2018

Name: , BASEMAP_V3_2018 , Description: , Land cover is the observed physical and biological cover of the Earth’s surface which include natural vegetation and abiotic (non-living) surfaces. Land cover is classified based on the UN [System of Environmental Economic Accounting](https://seea.un.org/content/land-accounts) (SEEA), adapted to Danish conditions. This classification has three levels, where [BASEMAP03](http://colectica:25233/File/51ea95a6-293a-4a1f-8d15-5a805f2576cd) constitutes the third level., Valid from: , January 1, 2018 , Valid to: , December 31, 2018 , Office: , Nationalregnskab, Klima og Miljø , Contact: , Ingeborg Vind, , inv@dst.dk, , ph. +45 24 83 51 49 , Codes and categories , Open hierarchy, Download , CSV, DDI, A: Roads, railroads and runways, A1: Road, paved, 141000: Road, paved, A2: Railroads, 150000: Railway, A3: Runways, 126000: Airport/runway, A15: Road, not paved, 142000: Road, not paved, B: Buildings and built-up areas, B1: Buildings, 110000: Building, 121110: Low built up. Building, 122110: High built up. Building, 123110: City centre. Building, 124110: Other built up. Building, 125110: Industry/business. Building, 126110: Airport/runway. Building, 130110: Recreation area/sports ground. Building, 150110: Railway. Building, B2: Built-up areas, 121000: Low built up, 122000: High built up, 123000: City centre, 124000: Other built up, 125000: Industry/business, C: Other artificial surfaces, C1: Pits and quarries, 160000: Resource extraction, C2: Parks, sport facilities and recreational areas, 130000: Recreation area/sports ground, D: Agricultural crops, D1: Herbaceous crops, 211000: Agriculture, intensive, temporary crops, D2: Woody crops, 212000: Agriculture, intensive, permanent crops, D3: Permanent grass and other extensive crops, 220000: Agriculture, extensive, D4: Crops, unspecified, 230000: Agriculture, not classified, E: Forest, E1: Forest, 311000: Forest, 312000: Forest, wet, F: Nature (dry and wet habitat types), F1: Nature, dry (heathers, dunes, etc.), 321000: Nature, dry, 321220: Nature, dry. Agriculture, extensive, F2: Nature, wet (meadows, bogs, etc.), 322000: Nature, wet, 322220: Nature, wet. Agriculture, extensive, G: Lakes and streams, G1: Lakes, 411000: Lake, G2: Streams, 412000: Stream, H: Unmapped, H: Unmapped, 800000: Unmapped, All versions, Name, Valid from, Valid to, Land cover, v3:2018, January 1, 2018, Still valid

https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/basemap

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

Documentation of statistics: Market Value for Households Real Estate

Contact info, Government Finances, Economic Statistics , Mathias Spindler Juhl Bundgaard , +45 29 36 68 25 , BUN@dst.dk , Get documentation of statistics as pdf, Market Value for Households Real Estate 2025 , Previous versions , Market Value for Households Real Estate 2024, Market Value for Households Real Estate 2023, Market Value for Households Real Estate 2022, Market Value for Households Real Estate 2021, Market Value for Households Real Estate 2020, Market Value for Households Real Estate 2019, Market Value for Households Real Estate 2018, Market Value for Households Real Estate 2017, Market Value for Households Real Estate 2016, Market Value for Households Real Estate 2015, This is the first publication of the households’ assets in real estate on individual level. The purpose is to follow the development of the households’ real estate. Sector delimitation of units in the sector of households is defined in European system of national accounts (ESA2010). From this it appears that sole proprietorships are a part of the households’ sector. Registers on individual level can be used for distribution analyses, e.g. in relation to income, financial liabilities or socioeconomic status., Statistical presentation, The statistics provides closing values for each year. The household’s real estate consisting of owner occupied dwellings and co-operative dwellings. All figures are reported in current prices. , Read more about statistical presentation, Statistical processing, Data from the various registers are merged through property identification and personal identification. There are made classifications, aggregations and calculation of the market value. For publication there is added relevant background information about the families., Read more about statistical processing, Relevance, The statistic has a lot of interested parties including ministries, politicians, organizations and the press.., Read more about relevance, Accuracy and reliability, The adjustment factor is the same within a geographic area, even though the actual sales value can vary a lot due to e.g. differences in the location of the owner-occupied dwellings (amenity), which are not reflected completely in the official real estate valuations. The preliminary year are dependent primarily on sales data for real estate. When the final year are calculated all of the sources are available. Experience from 2019 and 2020 shows that the preliminary year tends to underestimate the total market value of the final year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics i published with preliminary figures in march, 3 months after the reference date. Final figures is published a year later. One year and 3 months after the reference date., Read more about timeliness and punctuality, Comparability, The statistic is consistent over time. However, one must be aware that the figures are calculated at current prices. There is no knowledge of any individual based register of household wealth in real estate, which is comparable to the Danish. Figures for total household wealth in real estate are also published in the statistics concerning financial national accounts which is published in June and November., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , Home equity, , and the , subject page, Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/market-value-for-households-real-estate

Documentation of statistics

Documentation of statistics: Wholesale Trade, by Goods (Discontinued)

Contact info, Business Dynamics , Get documentation of statistics as pdf, Wholesale Trade, by Goods 2013 , Previous versions , Wholesale Trade, by Goods 2008, The purpose of the analysis is to shed light on the turnover structures of wholesale trade. Surveys have been conducted for the first time in 2009 with reference year 2008 ., Statistical presentation, The statistics provide data on the structure of wholesale trade turnover, industry turnover breakdown by product groups as well as product group wholesales by industries., Read more about statistical presentation, Statistical processing, Data are collected by web from 2,000 enterprises from Wholesales Trade sector. In the questionnaire the enterprises are asked to breakdown their turnover by a number of products, services and client categories. The reported data are checked by comparing the distribution of turnover among enterprises that are similar. Survey data is grossed up in part by including information from administrative sources on the VAT turnover in the reference year for the entire population., Read more about statistical processing, Relevance, The results are of interest to those monitoring the current business trends as well as the structural developments within wholesale trade. The statistics is in demand from trade and industry associations, bank and finance sector, politicians, public and private institutions, researchers, enterprises, news media and Eurostat. It is also of great interest to many enterprises within whole trade, as the results may allow them to compare their own business to their sector of trade or the wholesale trade more broadly., Read more about relevance, Accuracy and reliability, The survey is based on a sample and thus some uncertainty is attached to the results. For the whole retail trade sector, however, the uncertainty is considered to be small, since the coverage is extensive and the response rate high. For a few sectors with a relatively higher share of small enterprises, the limit of DKK 2.5 mil. may imply a higher uncertainty due to lower coverage., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published once every fem years and approximately 11 months after the reference year. The statistics is published usually without delay regarding to the announced date. To EU the data must be delivered within 18 months after the reference year., Read more about timeliness and punctuality, Comparability, It can be problems in comparing figures over time. This is because the data are only collected every five years. The survey has been carried out for the reference periods 2008 and 2013., Read more about comparability, Accessibility and clarity, Nyt, and , STATBANK, from Statistics Denmark., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/wholesale-trade--by-goods--discontinued-

Documentation of statistics

Documentation of statistics: Rent indices for housing

Contact info, Prices and Consumption, Economic Statistics , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Rent indices for housing 2021 , Previous versions , The purpose of the statistic Rent indices for housing is to measure the development in rent (housing). The statistic covers the years from 2021. , Statistical presentation, The statistic is a quarterly statistics who show the development in rents before rent subsidies. , Read more about statistical presentation, Statistical processing, The Rent indices for housing are 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 The National Bulding Fund (Landsbyggefonden) and thus covers the entire population of social rental housing. Privately owned rented dwellings is covered by a sample of approx. 110.000 dwellings out of a population of approx. 500.000 privately owned rented dwellings. Cooperative dwellings is covered by a sample of approx. 600 dwellings. Social rental housing and private rental 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). , Read more about relevance, Accuracy and reliability, It is not possible to quantify the uncertainty in the rent indices for housing, 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 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 2021. The statistics are not necessarily comparable with other statistics within the same area due to different methods. , Read more about comparability, Accessibility and clarity, These statistics are published in the StatBank under , rent and rental vacancy, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/rent-indices-for-housing

Documentation of statistics

Documentation of statistics: Accounts Statistics for Agriculture

Contact info, Food Industries, Business Statistics , Henrik Bolding Pedersen , +45 20 57 88 87 , HPE@dst.dk , Get documentation of statistics as pdf, Accounts Statistics for Agriculture 2025 , Previous versions , Accounts Statistics for Agriculture 2024, Accounts Statistics for Agriculture 2023, Accounts Statistics for Agriculture 2022, Accounts Statistics for Agriculture 2021, Accounts Statistics for Agriculture 2020, Accounts Statistics for Agriculture 2019, Accounts Statistics for Agriculture 2018, Accounts Statistics for Agriculture 2017, Accounts Statistics for Agriculture 2016, Accounts Statistics for Agriculture 2015, Accounts Statistics for Agriculture 2014, Accounts Statistics for Agriculture 2013, Accounts Statistics for Agriculture 2012, The purpose of the Farm Account Statistics for Agriculture is to provide information on the accounting results of agricultural holdings and horticultural holdings in Denmark. The statistics are considered an important input for the calculation of the agricultural sector accounts, the national accounts, and the EU Farm Sustainability Data Network (FSDN). The statistics have been compiled since 1916, but in their current form they are comparable from 2008 onwards., Statistical presentation, The Farm Account Statistics for Agriculture is an annual statistic describing the economy of Danish agricultural and horticultural holdings through detailed accounting items such as turnover, purchases, costs, operating result of the year, assets, liabilities and investments,, as well as key financial indicators. In addition, the statistics include information on household finances, including income outside agriculture, taxes paid and private consumption. The statistics cover holdings with a standard output of at least EUR 25,000 and are broken down by full-time and part-time holdings, farm types, conventional and organic production, and geographical areas such as regions and parts of the country., Read more about statistical presentation, Statistical processing, Data for these statistics are collected annually from farm accounts submitted by accounting offices and private accountants and are supplemented with data from various administrative registers. The data are collected electronically and undergo extensive validation procedures. Holdings are classified according to economic size and type of farming based on their Standard Output (SO), which is calculated for all crop and livestock types as the average actual output per unit (hectare or animal) over a five-year reference period. After validation, the sample is weighted to represent the target population and the final statistics are compiled., Read more about statistical processing, Relevance, These statistics are relevant to Ministries, researchers and agricultural organizations to measure the income of agricultural holdings. The data collection fulfils Denmark's obligations under the EU Farm Sustainability Data Network (FSDN)., Read more about relevance, Accuracy and reliability, The sample covers all holdings in the target population with a Standard Output (SO) of at least EUR 25,000. Sampling uncertainty is reduced by selecting relatively more large holdings, where variability is greater, and relatively fewer small holdings. Potential sources of uncertainty include voluntary participation and differences in accounting periods, although both are considered to have only a limited impact on overall accuracy. Standard errors and coefficients of variation are calculated for four key variables across 22 groups of holdings. Expected non-response is taken into account by increasing the sampling rate in strata where higher non-response has been observed, Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 7–10 months after the end of the reference year. Since the 2015 reference year, preliminary results for agriculture have been published in early July., Read more about timeliness and punctuality, Comparability, The statistics are comparable back to 2008, where data have been calculated on the basis of Standard Output., The statistics are partly comparable with data from SEGES (Danish agricultural advisory service), which compiles economic key figures for different types of farming. A coordination of the concepts is conducted., Read more about comparability, Accessibility and clarity, The figures are published in , Nyt from Danmarks Statistik, . The statistics is published in StatBank Denmark under , Agricultural and horticultural economy, . More information is available on the statistics , subject page, ., Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Farm Structure Survey

Contact info, Food Industries, Business Statistics , Karsten Kjeld Larsen , +45 21 29 55 76 , KKL@dst.dk , Get documentation of statistics as pdf, Farm Structure Survey 2026 , Previous versions , Farm Structure Survey 2025, Farm Structure Survey 2024, Agricultural and Horticultural Survey 2023, Agricultural and Horticultural Survey 2022, Agricultural and Horticultural Survey 2021, Agricultural and Horticultural Survey 2020, Agricultural and Horticultural Survey 2019, Agricultural and Horticultural Survey 2018, Agricultural and Horticultural Survey 2017, Agricultural and Horticultural Survey 2016, Agricultural and Horticultural Survey 2014, The purpose of the survey is to describe the structure of agriculture, e.g. number of farms by size and geography., The statistics have comparable time series going back to 1982. The agricultural statistics, however, are much older than that with figures for number of farms, livestock, crops etc. going back to around 1900. , Statistical presentation, The farm structure statistics are yearly and include figures on number of farms, livestock, crops and technology distributed by for instance size and geography. The statistics are published "Nyt fra Danmarks Statistik (News from Statistics Denmark) and in the statbank., Read more about statistical presentation, Statistical processing, The information is collected by means of a yearly questionnaire based survey where the farmers complete the questionnaire online. The answers are validated for non probable values., Information on crops and cattle is collected from registers, and is thereby not reported by every single farmer. , The survey is a sample survey stratified by region, size and type of farming., Read more about statistical processing, Relevance, The statistics fulfill a need for structural information on the Danish agriculture, e.g. number of farms by size and region. Important users are EU, the ministries and agricultural organizations., Read more about relevance, Accuracy and reliability, The precision varies for the different items of the statistics. The precision is thus highest for the total agricultural area and less precise for specific crops, especially crops grown by only few farmers. Likewise the precision is best for livestock which many farmers have. This is in particular true for cattle. In the same way the uncertainty is high for small geographical units, e.g. Bornholm., Read more about accuracy and reliability, Timeliness and punctuality, The survey is published about 9-12 after the survey day. This difference is due to the fact that survey varies in size from year to year, both with respect to the questionnaire and the sample size., Read more about timeliness and punctuality, Comparability, The survey is almost comparable from 1982 onwards. There is also a high degree of comparability with other European countries. Between 2009 and 2010 there is, however, a small break in the comparability since the statistics from 2010 onwards includes a number of small farms and additionally farms with fur animals. It means that the number of farms in 2010 is about 1.200 bigger than it otherwise would have been., From around 1900 to 1981 the statistical surveys also included very small farms with an area of only hectares. These figures are available for the users in paper publications, but not online. , Read more about comparability, Accessibility and clarity, The survey is published here: Online, http://www.Statbank.dk, New from Statistics and in the analyses of Statistics Denmark, see this analyse on [Analyse]https://www.dst.dk/da/Statistik/Analyser/visanalyse?cid=29376 , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/farm-structure-survey

Documentation of statistics