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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

Documentation of statistics: Corporate Taxation

Contact info, Government Finances, Economic Statistics , Ida Balle Rohde , +45 61 24 24 85 , ILR@dst.dk , Get documentation of statistics as pdf, Corporate Taxation 2023 , Previous versions, Corporate Taxation 2022, Corporate Taxation 2021, Corporate Taxation 2020, Corporate Taxation 2018, Corporate Taxation 2016, Corporate Taxation 2013, Corporate Taxation 2012, The purpose of the statistics Corporate taxation is to shed light on trends in companies' taxable income and tax payments. The statistics cover the period from from 1996 and is published yearly in March. The statistics were first published in 1922 and the method used for calculating the corporate tax has not changed since the first publication. , Statistical presentation, The statistics are an annual account of the taxable income and tax for all companies. The statistics provide information about how many companies that actually pay corporate tax in Denmark. The statistics are shown by type of company and type of industry. The tax is divided by industry and type. , Read more about statistical presentation, Statistical processing, Data is received annually from the Danish Tax Agency. The companies’ information is combined and checked for consistency between a tax declaration part, an assessed part, a joint taxation part, and a deficit part. The validation takes place by comparing the level of the total corporate taxes in relation to the previous year, where both business tendencies and possible tax rate changes are taken into account., Read more about statistical processing, Relevance, The statistics are part of the general economic debate. The statistics are in demand from ministries, politicians, public and private institutions, researchers, enterprises and news media. The statistics often gets a lot of attention in the media and among other professional users., Read more about relevance, Accuracy and reliability, The statistics cover all taxable companies. The data are subject to error detection and results control before publication. Error are corrected in collaboration with the Danish Tax Agency. In general, companies have great incentive to report on time, as they otherwise have to pay a tax supplement. The tax can unpredictably either increase or decline, which is impossible to correct for. The unpredictable changes occurs among other things because of errors in either taxable income or a long review time and process. The corrections are allocated to the relevant year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published in March year two after the income year. The finalised corporate taxes are published in March year three after the income year. The statistics are usually published without delay in respect to the scheduled time. , Read more about timeliness and punctuality, Comparability, The statistics were published for the first time in 1922 and the method for computing the tax has not changed – only the tax rate has changed. The taxation systems vary widely across countries, both in terms of conceptual and computational differences which makes the comparison difficult. The statistics are used when computing the overall surplus (Net lending / net borrowing) in government finance statistics. , Read more about comparability, Accessibility and clarity, The statistics are published annually in a Danish press release. In the StatBank the figures are published under , Corporation taxation, Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/corporate-taxation

Documentation of statistics

Documentation of statistics: Market Value for Households Real Estate

Contact info, Government Finances, Economic Statistics , Mikkel Bjerre Trolle , +45 29 36 68 25 , MIT@dst.dk , Get documentation of statistics as pdf, Market Value for Households Real Estate 2024 , Previous versions, 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 , Real estate, , and the , theme 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: Sales of housing cooperatives

Contact info, Prices and Consumption, Economic Statistics , Jakob Holmgaard , +45 24 87 64 56 , JHO@dst.dk , Get documentation of statistics as pdf, Sales of housing cooperatives 2024 , Previous versions, Sales of housing cooperatives 2022, The purpose of the statistics for cooperative housing is to monitor the price development in the property value of the cooperative housing units traded. The statistics has been produced since November 2023 and covers the period from 2015Q1 and onwards and it is comparable throughout the entire period., Statistical presentation, The statistics for cooperative housing is a quarterly price index for the property value of the cooperative housing units traded. The statistics contains price indices to describe the price development over time and numbers for the use of different valuation principles. The statistics includes all traded cooperative housing units that have been registered through http://www.andelsboliginfo.dk. This registration has been mandatory for the cooperative housing associations since June 1st 2021., Read more about statistical presentation, Statistical processing, Key figures on cooperative housing associations and cooperative housing units are reported to Statistics Denmark through http://www.andelsboliginfo.dk on a quarterly basis. The collected data is validated by Statistics Denmark and enriched with data from the Danish Buildings and Dwellings Register which is altså validated. Finally, price indices and the distribution of valuation principles are calculated., Read more about statistical processing, Relevance, Cooperative housing units constitutes 8 pct. of all housing units in Denmark and there are more than 210.000 cooperative housing units nationally. More than a third of apartment buildings in Copenhagen are cooperative housing which is a larger share than for the owner-occupied housing. The price development on the cooperative housing market is thus highly influential on the prices for the remaining housing market., Read more about relevance, Accuracy and reliability, The precision of the calculated price development depends on the hedonic regression which ensures the quality correction of the cooperative housing units sold and on the collected data. The development in the choice of valuation principles in the data from 2015 and onwards is assessed to be fairly accurate., The statistics for cooperative housing is based on information from http://www.andelboliginfo.dk which is a register of sold cooperative housing in Denmark. Thus, the reliability of the preliminary figures is assessed to be acceptable. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics on cooperative housing publishes preliminary quarterly figures two months after the end of the reference period. It has not been decided when the figures are final. The statistics on cooperative housing is published without delay with regards to the planned publications., Read more about timeliness and punctuality, Comparability, Comparable house sales statistics for all EU member states can be found on the , Eurostats website, where figures are published around 100 days after the end of a quarter (reference period)., Read more about comparability, Accessibility and clarity, The statistics for cooperative housing is published on a quarterly basis in the Statbank and yearly in , Nyt fra Danmarks Statistik, along with the publication of the 4th quarter., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sales-of-housing-cooperatives

Documentation of statistics

Documentation of statistics: Cost index for refuse collection, sludge removal and freight transport by road

Contact info, Prices and Consumption, Economic Statistics , Peter Fink-Jensen , +45 21 34 76 92 , PFJ@dst.dk , Get documentation of statistics as pdf, Cost index for refuse collection, sludge removal and freight transport by road 2025 , Previous versions, Cost index for refuse collection, sludge removal and freight transport by road 2024, Cost index for refuse collection, sludge removal and freight transport by road 2022, Cost Indices for Refuse Collection and Slurry Pump 2021, Cost Indices for Refuse Collection and Slurry Pump 2020, Cost Indices for Refuse Collection and Slurry Pump 2019, Cost Indices for Refuse Collection and Slurry Pump 2018, Cost Indices for Refuse Collection and Slurry Pump 2017, Cost Indices for Refuse Collection and Slurry Pump 2016, Cost Indices for Refuse Collection and Slurry Pump 2015, Cost Indices for Refuse Collection and Slurry Pump 2014, Documents associated with the documentation, Vægtgrundlag, Omkostningsindeks for dagrenovation, slamsugning og lastvognskørsel (pdf) (in Danish only), The purpose of these indices is to show trends in prices for refuse collection, slurry pump and freight transport by road in Denmark. The indices are made at the request of Dansk Transport og Logistik (DTL - Danske Vognmænd) and are, among others, used for price regulation of contracts. The indices have been published since 1997., Statistical presentation, The indices are produced on a quarterly basis and separately for refuse collection, slurry pump and freight transport by road. They are calculated separately for each industry. In addition, separate indices for each industry excl. the cost of fuel, are also published., Read more about statistical presentation, Statistical processing, The Cost index for refuse collection, slurry pump and freight transport by road includes costs of labor, repairs and maintenance, fuel, tires, administration, insurance and capital costs. These are weighed together to form the total indices. The weights reflect the cost shares of the total costs of performing refuse collection, slurry pump and freight transport by road. For indices excl. fuel, the fuel category has been removed from calculations., Read more about statistical processing, Relevance, The purpose of the indices is to reflect the development in the costs of refuse collection, slurry pump and freight transport by road., Read more about relevance, Accuracy and reliability, Index weights are established in cooperation with Dansk Transport og Logistik (the Danish Transport and Logistics Association) and Dansk Industri (Confederation of Danish Industry). The indices are deemed representative for refuse collection, slurry pump and freight transport by road performed in Denmark., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published quarterly at the beginning of February, May, August and November. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The cost indices for refuse collection and slurry pump are comparable over time from 1997 until today. The cost index for freight transport by road is comparable over time from 2022 until today., There are no international statistics which are directly comparable to the Danish indices., Read more about comparability, Accessibility and clarity, The statistic is published in the Statbank as , BYG91, . See more on the statistic's , subject page, A subscription service is available, where overviews of the statistic are send quarterly by email. The subscription is only available in Danish and can be ordered , here, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/cost-index-for-refuse-collection--sludge-removal-and-freight-transport-by-road

Documentation of statistics

Documentation of statistics: Income and consumption distribution in the household sector (experimental statistics)

Contact info, Government Finances, Economic Statistics , Ulla Ryder Jørgensen , +45 51 49 92 62 , URJ@dst.dk , Get documentation of statistics as pdf, Income and consumption distribution in the household sector (experimental statistics) 2022 , Previous versions, The purpose of the statistics is to bring together the benefits from the national accounts system, which provides a coherent description of the economy, and from microeconomic statistics on households, so that one can take a closer look at how incomes and consumption are distributed between different types of households., Statistical presentation, The distribution of income and consumption for the household sector of the national accounts is an experimental annual calculation of income and private consumption at household level, which is aggregated by quintiles and household types. The survey covers private households in Denmark., Read more about statistical presentation, Statistical processing, Virtually all economic statistics that are available are used for the national accounts. When new sources are ready, they are continuously incorporated into the national accounts according to a fixed rhythm. Three years after a given period, the national accounts are considered final., The consumption survey is a sample survey, where the number of households is 2,200 out of Denmark's total of approx. 2.8 million private households. From 2024, 3,200 will be asked. The study includes information from three data sources: Accounts, CAPI interviews and registers., Read more about statistical processing, Relevance, The statistics are relevant to everyone who deals with socio-economic conditions for households., Read more about relevance, Accuracy and reliability, The ability of the national accounts to accurately describe economic reality depends partly on the uncertainty associated with the sources and partly on the model assumptions underlying the preparation. Some parts can be calculated more precisely than others, as there is better access to source data. The first estimates of a period's national accounts will be more uncertain than the final version, which comes after three years, as they are continuously revised when new sources become available., The participation rate for the Consumption Survey in the years 2018-2022 has varied with . This creates uncertainty, not least for detailed consumption groups. For the total consumption, this means that there is an uncertainty margin of +/- 1.2 per cent. while for bread, for example, it is 2 per cent. For Food and non-alcoholic beverages, it is 1.2 per cent. , while for Alcoholic beverages and tobacco it is 4.8. There is under-reporting in a number of areas such as alcohol, tobacco, prostitution and undeclared work. The uncertainty is greater when data is based on accounting instead of interviews, and it will be greater if you look at smaller subgroups of households. , In these statistics, we have chosen a more general level to ensure greater consistency between the national accounts and the consumption survey, as well as to minimize uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics were first published approx. 23 months after the end of the reference year., Read more about timeliness and punctuality, Comparability, The national accounts and the consumption survey are carried out according to guidelines from the European statistical office Eurostat. Comparable figures are published by Eurostat. The distributional figures are still experimental in both Eurostat and Denmark., Read more about comparability, Accessibility and clarity, In the Statistics Bank, the results of the statistics are published under the subject , Complete national accounts - Household consumption, total economy, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/income-and-consumption-distribution-in-the-household-sector--experimental-statistics-

Documentation of statistics

Documentation of statistics: International Trade in Goods by Enterprise Characteristics

Contact info, External Economy , Søren Burman , +45 30 51 45 62 , SBU@dst.dk , Get documentation of statistics as pdf, International Trade in Goods by Enterprise Characteristics 2022 , Previous versions, International Trade in Goods by Enterprise Characteristics 2021, International Trade in Goods by Enterprise Characteristics 2019, International Trade in Goods by Enterprise Characteristics 2018, International Trade in Goods by Enterprise Characteristics 2017, The purpose of Trade in Goods by Enterprise Characteristics (TEC) is to describe enterprises engaging in foreign trade, how large they are, which economic sector they belong to, how many countries they trade with etc. These statistics have been compiled since 2010 are comparable until 2018 for legal units. From 2019 and onwards the statistics have been compiled on the basis of the enterprise unit., Statistical presentation, Trade in Goods by Enterprise Characteristics is an annual measurement of enterprises involved in foreign trade and their characteristics, stated in number of enterprises and value. The statistics are grouped by economic activity, enterprise size, partner countries, ownership, type of trade and concentration of trade until 2022. From 2023 the statistics will be a measurement of enterprises involved in foreign trade and their characteristics, stated in value and they will be grouped by economic activity, items, enterprise size and ownership. The statistics can be found in our statbank under the subject External Economy. , Read more about statistical presentation, Statistical processing, These statistics are compiled by combining data for International Trade in Goods (ITGS) with Business register data. Data is validated by comparing data with the sources used for compiling the statistics and by comparing the different tables compiled in this statistic., Read more about statistical processing, Relevance, These statistics are relevant for analysts and enterprises, for analyses of e.g. globalization and enterprises which contribute to external trade in Denmark., Read more about relevance, Accuracy and reliability, The accuracy for International Trade in Goods by Enterprise Characteristics is closely related to the accuracy of International Trade in Goods Statistics which is high on an aggregated level. The revisions follow the revision structure of International Trade in Goods Statistics., There may be changes in enterprise characteristics (e.g. size, industry and ownership) during a given year, which can give rise to a change the trade flows, but the statistics reflect the characteristics at the end of the year., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published 10 months after the reference period. They are published without any delays., Read more about timeliness and punctuality, Comparability, These statistics have been disseminated since 2014 and contains values from 2010 and onwards. It is in its present form comparable from 2010 and onwards. These statistics are compiled according to common European guidelines and are therefore comparable with statistics from other EU countries published by Eurostat. The comparability can be influenced by the difference between the general- and special trade system., Read more about comparability, Accessibility and clarity, These statistics are published annual 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 , International Trade in Goods, . The statistics can also be found in various publications and analysis’ and it is possible to gain access to microdata through our program for authorized research institutions., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/international-trade-in-goods-by-enterprise-characteristics

Documentation of statistics

Documentation of statistics: Emission Accounts

Contact info, National Accounts, Climate and Environment , Leif Hoffmann , +45 23 69 58 63 , LHF@dst.dk , Get documentation of statistics as pdf, Emission Accounts 2023 , Previous versions, Emission Accounts 2022, Emission Accounts 2021, Emission Accounts (including the climate footprint) 2020, Emission Accounts 2019, Emission Accounts 2018, Emission Accounts 2017, Emission Accounts 2016, Emission Accounts 2015, Air Emission Accounts 2013, Documents associated with the documentation, Metodedokument for statistikbanktabel LABY34 (pdf) (in Danish only), The purpose of the Air Emission Account is to illustrate the emission of greenhouse gases and other air pollutants related to industry and households energy consumption and other activities. The accounts can be used for climate and environmental-economic analysis. The emission accounts are developed for 1990 and onwards according to EEA, System of Environmental Economic Accounting, which is a statistical standard published by the UN and several other international organizations provides the "State of the art" for Green National Accounts. The statistics is part of the Environmental-Economic Accounts for Denmark (Green National Accounts)., Statistical presentation, The air emission accounts are annually accounts on the emission of greenhouse gases and other air pollutants. The air emission accounts follow the same definitions and classification as National Accounts, which allows for analyses of the connection between the economy and air pollution. The accounts are published in a Danish press release and in StatBank under the subject , Energy and air emissions, ., 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., 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, There is an uncertainty connected to the compilation of Air Emission Accounts as a combination of scientific assumptions and calculations have to be made. Uncertainty inherited in the source data is transferred to the Air Emission Accounts. However, conceptually consistent and over time uniform treatment of source data contribute to increasing the certainty of data., 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, These statistics are published annually 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 , Energy and air emissions, . For further information, go to the subject page for , Environmental-Economic Accounting, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/emission-accounts

Documentation of statistics

Documentation of statistics: Quarterly Labour Force

Contact info, Labour Market , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Quarterly Labour Force 2019 , Previous versions, Quarterly Labour Force 2018, The purpose of KAS is to to provide a description of the Danish population's affiliation to the labour market. KAS is an averaging of the populations affiliation to the labour market per quarter and is published annually. KAS covers the hole population from 2017 and on, while it covers the employed part of the population 1st. - 4th. quarter from 2008 to 2017. , Statistical presentation, KAS is an annually individual-based averaging which is calculating the Danish population's affiliation to the labour market quarter. The statistic is among other things also distributed on information about demography and information about the work place for employees. The statistic is published in StatBank Denmark., Read more about statistical presentation, Statistical processing, The quarterly labour force statistic is based on the Labour Market Account (LMA) which is a longitudinal register. LMA contains information about the populations primary attachment to the labour market on every day of the year. KAS is an averaging of the population's primary attachment to the labour market divided on quarters. , Read more about statistical processing, Relevance, The quarterly labour force statistic (KAS) is primarily used to structural analysis of the labour market, because the statistic has a very detailed level of information. The statistic is therefore relevant to external as well as internal users and as foundation for analyzing the populations employment over the year. , Read more about relevance, Accuracy and reliability, KAS is a register based average calculation of the populations primary attachment to the labour market, and the statistic uses the Labour Market Account (LMA) as data source. That first of all means that KAS doesn't contain the same uncertainties as statistics based on surveys. Second of all the data foundation for KAS provides a better opportunity to illuminate the labour market than before. KAS consists of a series of data sources which are integrated, corrected, and harmonized, and can therefore illuminate the populations attachment to the labour market significantly better than the single statistics can. , Read more about accuracy and reliability, Timeliness and punctuality, The statistic is published approximately 16 months after the reference point in time. RAS is typically published at the scheduled date without delay, and is planned more than a year ahead. , Read more about timeliness and punctuality, Comparability, The statistic is first published in 2018 with data on 1.-4. quarter 2008-2016. Expect from data break in the classification of occupation in 2010 the statistic is comparable in the hole period 2008-2016. From 2019 and on the data foundation is slightly revised, and therefore there is a smaller data break regarding the employed population. Since 2019 the statistic besides from employed persons also includes the rest of the population in Denmark with information about their primary labour market attachment in the 1st.-4.th. quarter 2017. KAS is based on administrative registers with national character which makes it difficult to compare the statistic internationally., Read more about comparability, Accessibility and clarity, The statistics are published in the StatBank under , Quarterly Labor force Statistics, employment, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/quarterly-labour-force

Documentation of statistics

Documentation of statistics: Upper-Secondary Education

Contact info, Population and Education, Social Statistics , Asger Bromose Langgaard , +45 21 59 96 46 , ALG@dst.dk , Get documentation of statistics as pdf, Upper-Secondary Education 2024 , Previous versions, Upper-Secondary Education 2023, Upper-Secondary Education 2022, Upper-Secondary Education 2021, Upper-Secondary Education 2020, Upper-Secondary Education 2019, Upper-Secondary Education 2018, These statistics cover the activity in upper secondary education in Denmark. Upper secondary education is defined from Statistics Denmark's education classification DISCED-15 as all education classified on level 20 or 35. Upper secondary educations are typically 2-3 years in duration. Upper secondary education statistics are in their current form comparable since 2005 and are part of the overall Student Register, which contains information about all students in ordinary education in Denmark., Statistical presentation, These statistics contain figures about the enrollment and completion in upper-secondary education in Denmark. This includes the number of entrants, the number of completed and the number of active students. The statistics are divided by education and the students' age, sex, ancestry and national origin. , Read more about statistical presentation, Statistical processing, The data for these statistics are received yearly in November/December from The Ministry of Children and Education. This means that the data received by Statistics Denmark have already been corrected for errors. In addition, a thorough error searching and validation of data are done by Statistics Denmark, where data is controlled for fluctuations across time and irregularities at the individual level. The Ministry of Children and Education are involved in cases of substantial corrections., Read more about statistical processing, Relevance, The statistics are relevant for public administrators, scientists and other analysts, journalists and citizens etc. as basis for prognoses, analyses and planning purposes in the educational field, but also for example in the labour market field and the integration field. The data of the statistics are used as background data for most of the personal statistics at Statistics Denmark, and are the basis for several tables in StatBank Denmark about education., Read more about relevance, Accuracy and reliability, The administrative systems that are the basis for the statistics are used by the institutions for their own daily administration of the students as well as for the payment of various financial grants. Correct registers are therefore necessary for the economy of the institutions and contributes to an expected high quality of the data source. The Ministry of Children and Education conduct error detection of data and the quality of the received data is high. Errors do occur but they are in most cases corrected the following year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately 4 months after the reference time, which is 1 October. The statistics are usually published without delay in accordance with the scheduled date., Read more about timeliness and punctuality, Comparability, The current version of these statistics go back to 2005. However, statistics pertaining to upper secondary education in Denmark have been produced prior to 2005. The statistics are internationally comparable as upper secondary education is defined in similar ways internationally., Read more about comparability, Accessibility and clarity, In the StatBank, these statistics can be found under the subject , Upper-secondary education, . For further information, see the homepage of the , statistics, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/upper-secondary-education

Documentation of statistics