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      Documentation of statistics: High Growth Enterprises

      Contact info, Business Dynamics, Business Statistics , Kalle Emil Holst Hansen , +45 21 58 48 87 , KHS@dst.dk , Get documentation of statistics as pdf, High Growth Enterprises 2024 , Previous versions, High Growth Enterprises 2023, High Growth Enterprises 2022, High Growth Enterprises 2020, High Growth Enterprises 2018, High Growth Enterprises 2017, High Growth Enterprises 2016, High Growth Enterprises 2015, High Growth Enterprises 2014, High Growth Enterprises 2012, The statistics High growth enterprises in Denmark was published the first time in 2008. High growth enterprise as well as Gazelles were at that time measured. However, later the statistics was limited to only include Gazelles. The purpose of the statistics "Gazelles in Denmark" is to illustrate the development in the number of gazelles and jobs created in the growth period., Statistical presentation, The statistics counts yearly the number of gazelles in Denmark, as well as jobs created in the growth period. In addition the turnover at the beginning and end of the growth period is available., The growth indicator is the number of employees. The number of employees is converted into full-time equivalents (FTEs). The number of FTEs is used as a measure of the total amount of work performed by the gazelles employees during the year in question., The statistics covers only Non-Agricultural Private Sector., Read more about statistical presentation, Statistical processing, The statistics are based on the Business demography statistics and the information regarding surviving firms up to 5 years old. The information of survival is used to the delimitation of the population to be measured. The enterprise's development in number of full-time employment is measured from start to end of the growth period., Read more about statistical processing, Relevance, The statistics is used by ministries and governmental agencies, regional and county authorities as well as private sector institutions and enterprises. Number of gazelles in Denmark is used in analysis of the development of young high-growth enterprises (gazelles). Moreover, it illustrates the creation of new jobs amongst these enterprises in the growth period. No user satisfaction is collected., Read more about relevance, Accuracy and reliability, There exist a certain uncertainty regarding the identification of real new enterprises in the statistics of business demography, which the statistics Gazelles is based on. If the Business Demography has identified new administrative units incorrectly in relation to whether they are really new, it can affect the start population for these statistics, and thus the companies that have the opportunity to become new high-growth companies., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is available with final figures around 18 months after the end of the reference year. The statistics is published with preliminary data around 10 months after the end of the reference year., The statistics has not previously been delayed., Read more about timeliness and punctuality, Comparability, The statistics can not be directly compared to the statistics of Gazelles published by Eurostat, see the paragraph '7.01 International sammenlignelighed' for further explanation. The statistics are based on the real new enterprises from the business demography statistics. There have not been changes in methods since the beginning of the series., Read more about comparability, Accessibility and clarity, The data is published in NYT and is available in the , StatBank, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/high-growth-enterprises

      Documentation of statistics

      Documentation of statistics: Social resources

      Contact info, Personal Finances and Welfare , Birgitte Lundstrøm , +45 24 21 39 65 , BLS@dst.dk , Get documentation of statistics as pdf, Social resources 2022 , Previous versions, Social resources 2021, Social resources 2020, Social Resources 2019, Social Resources 2018, Social Resources 2017, Social Resources 2016, Social Ressources – Elderly and Adults 2015, Social Ressources – Elderly and Adults 2014, The purpose of the survey is to establish the available social resources (capacity, number of users, and general organization, etc.) in Danish municipalities. Furthermore, the survey analyses the social- and health-care related services administered by municipalities. These services include care for the elderly, dental services for children and young people and special institutions for children and young people etc. The social resources survey includes public and privately owned institutions. The statistics are published for the first time in 1972 but have been changed over time due to changes in legislation an user needs., Statistical presentation, Social resources is a yearly measurement of social services delivered by municipalities concerning care for elderly, adults and children and young people receiving social benefits . The data are published for Denmark as a whole. Some data are further more grouped by regions or municipalities. , Read more about statistical presentation, Statistical processing, Data are collected yearly from municipalities from six questionnaires. Data are validated against previously collected information and controlled for large variances over time. Further more data are checked for inconsistency and validated against legal developments at the area. Some data concerning age distribution are imputed where municipalities have only registered total data. , Read more about statistical processing, Relevance, The statistics are primarily of interests for the central government and various government boards and are used for estimating and planning capacity and occupancy rates within social services. Core actors and users of the survey are actively involved in adjusting the content each year which means that user needs are taken into account., Read more about relevance, Accuracy and reliability, The survey is a full-scale census based on responses from all municipalities. In some cases it is difficult for the municipalities to provide the correct data from their systems or they change their way of reporting data. In these cases data received might be less accurate of vary over time. A certain statistical uncertainty is caused by municipalities difficulties with estimating different services and caused by different administrative practices between municipalities. , Read more about accuracy and reliability, Timeliness and punctuality, Most of the information are collected for one single week in April depending on Easter. In some cases data are collected for the entire previous year. A Danish press release and a number of corresponding tables (RESI01, RESP01, RESDHJCE, RESMAD, RESANDHJ, RESPLEJV, RESPRVHJ, RESTAND) are published at the end of November then same year. The rest of the tables (RESFAMPL, RESHJMTR, RESLED, RESFDPJ, RESSBU2) are published in the Statbank at the end of March the following year. These statistics are normally published without delay, with reference to the announced time of publication in the release calendar., Read more about timeliness and punctuality, Comparability, The survey goes back to 1972. However, due to yearly changes the version used in 1972 has little in common with the one used today. Furthermore, due to the municipal reform there was a break in times series in 2006 and 2007. The totals for the country as a whole are, however, comparable before and after the reform., Read more about comparability, Accessibility and clarity, These statistics are published once a year in a Danish press release. Further more the statistics are published in the StatBank under the subjects:, Elderly people receiving social benefits, , , Disadvantaged children and young people, , , Disability care, , , Health, Visits to physicians, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/social-resources

      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 2025 , Previous versions, Sales of housing cooperatives 2024, 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 validated. Finally, price indices and the distribution of valuation principles are calculated., Read more about statistical processing, Relevance, The statistics are relevant for banks and the financial sector, estate agents, politicians and actors in the cooperative housing sector who use the figures for analyses of price developments and assessments of regulation in the housing market. As there used to be limited statistics on cooperative housing, the statistics contribute to a more transparent 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: Productivity

      Contact info, National Accounts, Climate and Environment, Economic Statistics , Magnus Børre Eriksen , +45 29 12 27 56 , MBE@dst.dk , Get documentation of statistics as pdf, Productivity 2024 , Previous versions, Productivity 2023, Productivity 2022, Productivity 2021, Productivity 2020, Productivity 2019, Productivity 2018, Productivity 2017, Productivity 2015, Productivity 2014, Productivity 2011, The purpose of the statistics Productivity is to examine the change in production per unit of the resources involved and which contributes to the change. The simplest and most commonly used concept of productivity is labor productivity, which is used here. Labor productivity (LP) and the causes for the change in LP is calculated back to 1966., Statistical presentation, Productivity is basically a measure of how efficiently you use your resources (labor, capital, etc.) when producing goods and services. In this statistic it is also calculated which resources contribute most to the change in productivity. Productivity change is distributed across industries for the various productivity components. The statistics are disseminated in News from Statistics Denmark and the StatBank., Read more about statistical presentation, Statistical processing, Labor productivity is defined as the real value of Gross value added (GVA) per hour worked. The calculations are based on figures from market activity from national accounts, i.e. the total economy excluding the sectors: General government (S.13) and NPISH (S.15). The sources used for calculating the productivity growth is fixed capital, Labor force education statistics and sector account figures for Gross value added and hours worked., Read more about statistical processing, Relevance, The national accounts (including Productivity statistics) constitute core indicators of the analyses of economic growth. Users are primary researchers, economic departments and organizations., The division of national accounts continuously evaluates feedback from our users., Read more about relevance, Accuracy and reliability, The precision of the calculation of productivity growth is closely related to the uncertainty of the variables that are included in the calculation. I.e. how well, the value of an hour's work is reflected in the gross value added in fixed prices for the industry; the quality of the calculated hours and whether there are special conditions in the industry that make labor productivity less relevant, e.g. high capital intensity. For multiple industries, labor productivity growth should not stand alone in productivity analyzes. This applies, for example, to dwellings, public administration, education and health., Read more about accuracy and reliability, Timeliness and punctuality, First preliminary version of Labor productivity (LP) for year t is published end of March in year t+1. The final version of LP for year t is published end of June in year t+3. First preliminary version of Productivity growth (Sources of LP) for year t is published no later than December year t+1. The final version of Productivity growth (Sources of LP) is published no later than December year t+3. The productivity statistics are published according to schedule., Read more about timeliness and punctuality, Comparability, This statistic is based on national accounts. Therefore this statistic is consistent with respect to national accounts and comparable over time. Moreover this statistic is comparable to other countries productivity figures if they are also based on ESA2010., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release and in the StatBank under , Productivity, . See more information , here, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/productivity

      Documentation of statistics

      Documentation of statistics: Producer price index for construction of dwellings

      Contact info, Prices and Consumption, Economic Statistics , Peter Fink-Jensen , +45 21 34 76 92 , PFJ@dst.dk , Get documentation of statistics as pdf, Producer price index for construction of dwellings 2025 , Previous versions, Producer price index for construction of dwellings 2024, Producer price index for construction of dwellings 2023, Producer price index for construction of dwellings 2021, Producer price index for construction of dwellings 2019, Producer price index for construction of dwellings 2018, Producer price index for construction of dwellings demonstrates trends in prices at the first stage of commercial transactions for the construction of free standing one-family houses, i.e. the producer price incl. direct construction costs and profits, but excl. VAT, cost of land and other costs not directly linked to the construction. The statistic is typically used in analyses of price developments in the construction sector. It has been compiled since 2019 with indices dating back to 2015., Statistical presentation, The Producer Price Index for Construction of Dwellings is a quarterly measurement of price developments of commercial transactions related to the construction of new dwellings, i.e. the price a household or a developer pays the construction company for the construction of a dwelling. The statistic only covers construction of free standing one-family houses, and is therefore not representative of e.g. multi-family houses, terraced houses, general housing, vacation homes or commercial/industrial buildings., Read more about statistical presentation, Statistical processing, Every quarter approximately 500-1200 prices are collected from a sample of relevant type house construction companies in Denmark. Prices and addresses are merged with relevant information from the Danish Buildings and Dwellings Register (BBR) on e.g. floor area and various amenities. This information is used to calculate the price development of construction of new dwellings., Read more about statistical processing, Relevance, The Producer Price Index for Construction of Dwellings is a business cycle indicator, which is used in analyses of economic developments in Denmark. It is used in the Danish National Accounts, and is part of the framework of EU short term business statistics. Surveys of user satisfaction are not performed, but the statistics is part of Danish Statistics' expert committee for statistics on housing and civil engineering., Read more about relevance, Accuracy and reliability, The collected price observations are examined for errors both manually and by computer. The extend of different error types is therefore considered to be negligible. As the collected data originates solely from typehouse companies, the statistic is considered to be more accurate for typical housing constructions and less so for unique constructions. Also, the used hedonic statistical model does not consider the quality of applied building materials or the quality of the work carried out., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published quarterly, approx. 3-4 month after the end of the reference period., Read more about timeliness and punctuality, Comparability, The statistic has a continuous time series from 2015 until present day. The statistic follows international standards and is therefore comparable with similar statistics from other countries., Read more about comparability, Accessibility and clarity, The statistic is published quarterly in the Statbank as , Producer Price Index for Construction of Dwellings (PRIS90), and can be found at the subject page , Indices for the construction sector, . Once a year, in conjunction with the publication of 4th quarter indices (in April), the statistic is published in , News from Statistics Denmark, , which is available only in Danish under the title "Producentprisindeks for byggeri". The statistics is reported to the Danish National Archives on a yearly basis., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/producer-price-index-for-construction-of-dwellings

      Documentation of statistics

      Documentation of statistics: Mining and Quarrying

      Contact info, Food Industries, Business Statistics , Morten Skovrider Kollerup , +45 24 52 61 68 , MSL@dst.dk , Get documentation of statistics as pdf, Mining and Quarrying 2024 , Previous versions, Mining and Quarrying 2023, Mining and Quarrying 2022, Mining and Quarrying 2020, Mining and Quarrying 2019, Mining and Quarrying 2018, Mining and Quarrying 2017, Mining and Quarrying 2016, Mining and Quarrying 2014, Mining and Quarrying 2013, The mining and quarrying statistics show the amount and type of mining and quarrying in Denmark. The statistics have been made since 1973 but is only comparable since 2006., Statistical presentation, The mining and quarrying statistics are a yearly measurement of extracted raw material types from land and from the sea floor stated in Cubic meters. The statistics are grouped by raw material types, by administrative regions and municipalities., Read more about statistical presentation, Statistical processing, Data are annually collected from all extractors on land. The reported data are controlled for errors by comparing changes over time in the municipalities and for the totals for each resource category. Figures for raw materials extracted from the sea are controlled for errors in the same way., Read more about statistical processing, Relevance, There is great interest for the published figures on raw materials among the Regions, which use the statistics to make extraction plans. The statistics are also requested by municipalities, industry organizations, other public and private institutions, researchers, companies and the news media. The statistics are used in the compilation of the environmental-economic accounts in the national accounts., Read more about relevance, Accuracy and reliability, These statistics are based on a full census with complete coverage, as all extractors of raw materials are required to report. The data form the basis for taxation and are verified by the authorities, who already have a good overview of the quantities extracted., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published about 6 months after the end of the reference period. Publications are generally released on time, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, The statistics are comparable at municipal level back to 1980. The data collected and the level of detail have remained unchanged throughout the period. Data quality and reliability are expected to be higher after 1 January 1990, when a raw material tax was introduced, resulting in increased control of the reporting by the authorities. As of 2007, data are compiled according to the new municipal and regional structure, and reliability is considered slightly lower than before 2007 due to problems with implementation of the new municipality-reform in 2007., 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 , Mining and quarrying, . For further information, go to the , subject page, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/mining-and-quarrying

      Documentation of statistics

      Documentation of statistics: The annual and quarterly working time accounts before the 2016 revision (Discontinued)

      Contact info, Labour Market , Get documentation of statistics as pdf, The Annual and Quarterly Working Time Accounts Before the 2016 revision 2016 Quarter 1 , Previous versions, The Annual and Quarterly Working Time Accounts 2014 Quarter 3, The Annual and Quarterly Working Time Accounts 2014 Quarter 4, The Annual and Quarterly Working Time Accounts 2015 Quarter 1, The Annual and Quarterly Working Time Accounts 2015 Quarter 2, The Annual and Quarterly Working Time Accounts 2015 Quarter 3, The Annual and Quarterly Working Time Accounts 2015 Quarter 4, The Danish Working Time Accounts (WTA) is an integrated statistics with consistent time series on employment, number of jobs, hours worked and compensation of employees in both annual and quarterly basis. The current time series goes back to 2008 (quarterly statistics as from the 1st quarter of 2008)., Statistical presentation, The Working Time Accounts produce integrated statistics with consistent time series on employment, jobs, number of hours worked and compensation of employees on an annual and quarterly basis. The data basis is made up by a number of primary statistical data, which are adapted and adjusted to achieve agreement of the concepts and definitions used in the WTA system., The statistical sources used in the WTA are: , The Register-Based Labour Force statistics (RAS), , Establishment-related employment statistics (ERE statistics), , The Structural Earning Statistics (SES), , Employment Statistics for Employees (BfL) og , The Labour Force Survey (LFS)., Read more about statistical presentation, Statistical processing, The population and concepts as well as levels of the variables are defined by annual structural data sources. Short-term data sources are applied in projecting these levels over the months of the year and in periods for which structural data are not available. Summation of the data in the Working Time Account is conducted before they are projected. Data in the Working Time Account are seasonally adjusted both for use in Denmark as well as for use in Eurostat’s STS. The system contains a data-editing system, a correction system and a dissemination system., Read more about statistical processing, Relevance, Users interested in the social and economic statistics have expressed satisfaction with the quality of the statistics. However, they also expressed frustration over large data breaches, especially in the transition to e-Income-based sources., Read more about relevance, Accuracy and reliability, There are no calculations of the measures of accuracy., See section quality assessment., Read more about accuracy and reliability, Timeliness and punctuality, Working hours are regularly published in accordance with Statistics Denmark's benchmark goals. , For quarterly statistics concerned, this goal implies that the publications to be released at the latest ​​by the end of the following quarter. For the sake of short-term business regulation (STS), this implies that the WTA to be published typically by the middle of the last month of the following quarter. (The requirement for most employment series for STS is 2 months and 15 days). For annual statistics concerned, this implies that publications to be released at the latest by the end of the following year. In the interest of national accounts the annual WTA will be published in June with provisional figures for the previous year. This makes the annually WTA for the year , t, to be published in the same month as the publication of the quarterly WTA for the period , 1 quarter t +1, . , The transition to the new WTA resulted, however, that annual WTA 2011, based on the new eIncome sources, were not published until December 2012, whereas the publication of the quarterly statistics has not given rise to any delay., Read more about timeliness and punctuality, Comparability, WTA deliver labour market data to Eurostat's corporate short-term regulation (STS) and the national accounts (ESA / ESA). Therefore, changes in these regulations typically result in changes in the WTA. A description of the transitional tables between the WTA and the National Accounts can be found in the publications on the National Accounts. Transitional tables between the WTA and the Register-based Labour Force Statistics and the Establishment-related Employment Statistics are published in Statistical News ("Statistiske Efterretninger") for the annual WTA., Read more about comparability, Accessibility and clarity, The statistics are published in: , News from Statistics Denmark (Nyt fra Danmarks Statistik), , in the series Statistical News ("Statistiske Efterretninger") and , in the Statbank Denmark ("Danmarks Statistikbank")., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/the-annual-and-quarterly-working-time-accounts-before-the-2016-revision--discontinued-

      Documentation of statistics

      Documentation of statistics: Indices of Average Earnings for the Private Sector (Discontinued)

      Contact info, Personal Finances and Welfare , Get documentation of statistics as pdf, Indices of Average Earnings for the Private Sector 2019 , Previous versions, Indices of Average Earnings for the Private Sector 2018, Indices of Average Earnings for the Private Sector 2017, Indices of Average Earnings for the Private Sector 2016, Indices of Average Earnings for the Private Sector 2015, Indices of Average Earnings for the Private Sector 2014, The purpose of the index of average earnings is to indicate trends in earnings for different industries in the private sector exclusive of enterprises categorised as public administration or -services (state, regional or municipal). The index of average earnings was first published for the first quarter of 1994 under the name , the index of average earnings in the private sector, . Since then the index has been published based on the Danish Industrial Classification of 1996 (DB96), Danish Industrial Classification of 2003 (DB03) and since the third quarter of 2008 based on the Danish Industrial Classification of 2007 (DB07). Moreover, the index of average earnings replaced the index of hourly earnings for workers in manufacturing industry and the index of monthly earnings for salaried employees in manufacturing industry, which were discontinued at the end of 1997., Statistical presentation, The index of average earnings comprises all employees, salaried employees (white collar employee or officials) and wage-earners (blue collar workers) as well as apprentices and young people under 18 years employed in a business enterprise with 10 or more persons in the private sector. The entire private sector is covered by the indices, including e.g. employees in private schools and private hospitals. Still, the index does not include enterprises belonging to either the agriculture or fisheries industries. In accordance with the nomenclature DB07 (Danish Industrial Classification 2007), the the index is broken down by industry and since the third quarter of 2008 published at the most detailed level according to the 36-grouping in DB07. For a period between the first quarter of 2005 and the second quarter of 2008, the indices were only published at the 10-grouping level., Read more about statistical presentation, Statistical processing, Data are collected from the private enterprises and organisations that are included in the sample and cover the second month of the quarter in question. To start with, a rough search for errors is performed on the data. Then, the change in the average earnings per hour from the previous quarter is calculated for each enterprise. Only enterprises where data exists for both quarters are included in the computations. The average hourly wage per observations in the sample is then weighted to take account of all enterprises in a specific branch of economic activity in the population. A total figure for the average hourly wage and the rate of increase from the last quarter is then calculated for each branch of economic activity. After this the index point and the annual rate of increase is calculated for each branch. Finally the total index point and annual rate of increase is found as a total for all branches., Read more about statistical processing, Relevance, Private corporations and organisations in Denmark and abroad, and ministries and other public institutions are the most frequent users of the index. The index is especially used in relation to regulation of contracts. In addition to that, the index plays a vital part in the wage negotiations of employees in the public sector., Read more about relevance, Accuracy and reliability, The accuracy and reliability is mainly affected by two factors. First of all, the index is based on a sample, which in itself cause some uncertainty. Second of all, there is some uncertainty connected to the completeness in the collected data, which is often caused by errors in the way the system is generated for transmission of data. An example of this is a payroll system where the different wage compositions are not correctly linked or reported, and thus give an inaccurate picture of the development of wages. The problem with errors like these is that they tend to be difficult to discover. For example would reporting of a low and wrong value for irregular payments result in too high calculation of wage developments, as the irregular payments could not be separated from the wage component., Read more about accuracy and reliability, Timeliness and punctuality, The index of average earnings is published approximately 60 days after the end of the quarter in question. The punctuality of the publication is considered high and there has been no delays of any kind during the last years., Read more about timeliness and punctuality, Comparability, The index of average earnings for Corporations and Organizations, replace , the index of average earnings of the private sector, which was last published for the fourth quarter of 2013. The comparability of the two indices is considered to be high. The difference has to do with the new applied delimitations of the sectors, where some of the public owned enterprises, such as Danish Railways (DSB) and some of the municipal owned resource centers, now according to the new delimitations of the sectors belong to “the index of average earnings of Corporations and Organizations”. The new sector delimitations were applied in the indices going back to first quarter of 2013, where it caused a small data breach., Read more about comparability, Accessibility and clarity, These statistics are published in the Statbank under , Implicit index of average earnings, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/indices-of-average-earnings-for-the-private-sector--discontinued-

      Documentation of statistics

      Documentation of statistics: Social benefits for senior citizens

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

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

      Documentation of statistics

      Documentation of statistics: Register-Based Labour Force Statistics

      Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Register-Based Labour Force Statistics 2024 , Previous versions, Register-Based Labour Force Statistics 2023, Register-Based Labour Force Statistics 2022, Register-Based Labour Force Statistics 2021, Register-Based Labour Force Statistics 2020, Register-Based Labour Force Statistics 2019, Register-Based Labour Force Statistics 2018, Register-Based Labour Force Statistics 2017, Register-Based Labour Force Statistics 2016, Register-Based Labour Force Statistics 2015, Register-Based Labour Force Statistics 2014, The purpose of the Register-Based Labour Force Statistics (RAS) is to measure the population’s primary attachment to the labour market. This attachment is recorded at the end of November and compiled once a year. The first RAS compilation was made at the end of November 1980., Statistical presentation, RAS is an annual, individual-based compilation that records the population’s attachment to the labour market on the last working day of November. The population’s attachment is divided into three main socio-economic groups: employed, unemployed, and persons outside the labour force. The statistics can be broken down by demographic variables and education, as well as by industry, sector, and municipality of the workplace for employed persons. The data are published in News from Statistics Denmark and in the Statistics Denmark StatBank, and detailed micro-data are made available through Statistics Denmark’s Research Service., Read more about statistical presentation, Statistical processing, The register-based labor force statistics (RAS) are based on the Labor Market Account (AMR_UN), which is a longitudinal register. When RAS is compiled, a status assessment (in relation to the population's primary attachment to the labor market) is carried out on the last working day of November in the AMR. Based on AMR_UN, it is also possible to perform status assessments on arbitrary days throughout the year., Read more about statistical processing, Relevance, The register based labour force statistic (RAS) is primarily been used to structural analysis of the labour market, because the statistic has a very detailed level of information. Many external as well as internal users are using the statistic., Read more about relevance, Accuracy and reliability, RAS is a register-based compilation that uses many data sources to measure the population's affiliation to the labor market. This means that RAS does not have the same uncertainty as statistics based on samples. RAS consists of a wide range of data sources, which are integrated, checked for errors, and harmonized, making it possible to provide a better picture of the population's connection to the labor market than the individual statistics can., Read more about accuracy and reliability, Timeliness and punctuality, From the publication of figures for the end of November 2018 onwards, the release is carried out in two stages. In the first release, persons outside the labor force are grouped together in a single category. This publication takes place approximately 11 months after the reference point. In the second publication, which occurs approximately 15 months after the reference point, persons outside the labor force are divided into different socioeconomic groups., Read more about timeliness and punctuality, Comparability, The first version of the RAS statistics includes the population resident in Denmark as of the 1 January 1981 and its attachment to the labour market at the end of November 1980. The statistic has been compiled once every year since. New and better data foundations and changes in the labour market have however caused a number of data breaks over time, which have influence on the possibility of comparing data over time. Since RAS is based on administrative registers with national distinctive marks, it is very difficult to compare the statistic in an international level. , Read more about comparability, Accessibility and clarity, The statistics is published in Statbank Denmark: , Labour market status (RAS), and , Employed persons (RAS), . , For further information go to the subject pages , Labour market status (RAS), and , Employed persons (RAS), ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/register-based-labour-force-statistics

      Documentation of statistics
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