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Documentation of statistics: Housing benefits

Contact info, Labour Market, Social Statistics , Morten Steenbjerg Kristensen , +45 20 40 38 73 , MRT@dst.dk , Get documentation of statistics as pdf, Housing benefits 2025 , Previous versions, Housing benefits 2024, Housing benefits 2023, Housing benefits 2022, Housing benefits 2021, Housing benefits 2020, Housing benefits 2019, Housing benefits 2018, Housing benefits 2017, Housing benefits 2016, Housing benefits 2015, Housing benefits 2014, Housing benefits 2013, Documents associated with the documentation, Social tryghed i de nordiske lande (pdf) (in Danish only), Housing benefit is a tax free subsidy granted to households with high housing expenses relative to the household income. The purpose of the statistics on housing benefit is to elucidate the number of beneficiaries of housing benefit and the amount received in benefit. The housing benefit statistics date back to 1967, but is in the current format comparable back to 2007., Statistical presentation, The statistics on housing benefits cover statistics on the number of all beneficiaries (i.e. households), and amounts granted on a monthly basis. Rent subsidies (for non-pensioners, as well as to early retirees, who have been assigned pension after January 1st 2003) and housing allowances (for retirees) depending on a number of variables (type of benefit, rent income and number of children)., Read more about statistical presentation, Statistical processing, Data for these statistics are collected monthly from Udbetaling Danmark via a system-to-system connection. Data are treated annually. Invalid data are excluded. Afterwards, the data is aggregated by the type of housing benefit, municipality and age., Read more about statistical processing, Relevance, These statistics are relevant for various Ministries, municipalities, researchers, and KL- Local Government Denmark and researchers. The statistics are used internally in Statistics Denmark, Municipal budgets and to assess the law on individual housing benefits., Read more about relevance, Accuracy and reliability, The statistics are based on administrative registers of housing benefits, but errors and duplicates may occur in the register. Invalid data and duplicates are removed (less than 0.01 pct.). The housing benefit amounts are overestimated compared to reality, since months with less than a full month's housing eligibility are included as a full month in the statistics. Only final figures are published., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published three months after the end of the reference period. Publications are released on time, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, Statistics on housing benefits in Denmark date back to 1967. The statistics are comparable since 1983 in its current format. The statistics are produced according to common European guidelines and are therefore comparable to statistics from other countries published in Eurostat., 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 , Housing benefits, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/housing-benefits

Documentation of statistics

Documentation of statistics: Newspapers and Magazines

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

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

Documentation of statistics

Documentation of statistics: Sales of real property

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 real property 2025 , Previous versions, Sales of real property 2024, Sales of real property 2023, Sales of real property 2022, Sales of real property 2021, Sales of real property 2020, Sales of real property 2019, Sales of real property 2018, Sales of real property 2017, Sales of real property 2016, The statistics for Sales of real estate property measure the number of sales and prices of transactions of Danish real estate properties. The statistics are used for monitoring developments in the real estate market, as well as economic developments. The current price indices link back to 1992. There are price indices for previous years, but there are methodological differences., Statistical presentation, This statistics are published monthly including price and volume trends in real estate transactions, such as one-family houses, owner-occupied flats, agricultural properties and business properties. These statistics contain key figures broken down by category of real estate property, region, type of transfer, price index and period. The statistics include all registered real estate transactions, which include land, both newly built and existing properties., Read more about statistical presentation, Statistical processing, Data concerning the registration of ownership of real estate properties is collected on a monthly basis from the electronic land registration system via Datafordeleren. The data is checked for errors by Statistics Denmark. The individual real estate transactions are divided according to category of real property, region, type of transfer and period. Aggregated figures are then calculated for number of sales, average prices and the ratio between purchase price and appraisal value (spar-value). Finally, the price index is calculated., Read more about statistical processing, Relevance, There is a great interest for the published numbers among users, which follows the currently economic business cycle. The statistics of sales of real properties are relevant for the banking- and financial sector, real estate agents, politicians, researchers and the news media. The users consider the statistics for sales of real estate properties as an important economic indicator. The statistics have a high profile in the press and among other professional users., Read more about relevance, Accuracy and reliability, The precision of the price development is the result of the quality of the appraisals and of the assumptions in the SPAR-method, which seeks to correct the quality of the sold properties in order to measure the pure price development. There is no significant bias in the preliminary figures for the price development, while the preliminary figures for the average prices are underestimated, as they are not corrected for the bias in the registration pattern., Read more about accuracy and reliability, Timeliness and punctuality, The statistics for sales of real property publish preliminary quarterly and annual figures 3 months after the end of the reference period. Monthly figures are published only as final figures. Final figures are available 13 months after the end of the reference period. The statistics are published without delays in the planned releases. , 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 sales of real properties is published in , News from Statistics Denmark, . Detailed figures can be found in , StatBank, and in the [Online payment data bank](https://www.dst.dk/betalingsdatabank. Historical figures can be found in the publication series , Ejendomssalg, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sales-of-real-property

Documentation of statistics

Documentation of statistics: Victims of Reported Criminal Offences

Contact info, Personal Finances and Welfare, Social Statistics , Iben Birgitte Pedersen , +45 23 60 37 11 , IPE@dst.dk , Get documentation of statistics as pdf, Victims of Reported Criminal Offences 2025 , Previous versions, Victims of Reported Criminal Offences 2024, Victims of Reported Criminal Offences 2023, Victims of Reported Criminal Offences 2022, Victims of Reported Criminal Offences 2021, Victims of Reported Criminal Offences 2020, Victims of Reported Criminal Offences 2019, Victims of Reported Criminal Offences 2018, Victims of Reported Criminal Offences 2017, Victims of Reported Criminal Offences 2016, Victims of Reported Criminal Offences 2015, Victims of Reported Criminal Offences 2014, Victims of Reported Criminal Offences 2013, Documents associated with the documentation, Note on victims of rape (2025) (docx), The purpose of "Victims of reported criminal offences" is to analyze the number of victims of police reported offences assaulting or causing harm to people. The statistics on victims of reported criminal offences date back to 2001., Statistical presentation, The statistics on victims of reported criminal offences form part of the Danish System of Criminal Statistics which includes data on criminal cases from the reported offences and victims and charges to the convictions plus arrests and imprisonments. The statistics of victims of reported criminal offences are case statistics, which show the number of victims of some particular police recorded offences, i.d. sexual offences, violence and some property offences as robbery and bag snatching., Read more about statistical presentation, Statistical processing, The source of the statistics is The Administrative System of the National Police. Data are delivered yearly via System-to-system transmission. The data go through a probability check in form of a comparison with data from the previous year, key variables are checked for valid values and irrelevant victim cases are deleted., Read more about statistical processing, Relevance, The statistics are used broadly by the authorities, organizations, researchers, the press etc. The tables in the http://www.statbank.dk are used frequently. Views and suggestions from key users are taken into consideration in the preparation of the statistics., Read more about relevance, Accuracy and reliability, The data come from a single administrative register system, and Statistics Denmark receives one total register extract containing all the victims of criminal offences reported to the police in Denmark. , However, it is evident from victimization surveys that the statistics on reported criminal offences underestimate the actual number of crimes, as it is far from all crimes which are reported to the police (hidden criminality). , Read more about accuracy and reliability, Timeliness and punctuality, The publishing time for the statistics is about 2-3 months. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The statistics are comparable over time. However, the number of victims of homicide is underestimated for the years 2001-2009. , UN collects annual data from the member states on victims of homicide and publishes statistics based on this. However, the definition of homicide can differs between countries and comparisons based upon absolute figures can therefore be misleading., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release. In the StatBank, these statistics can be found under , Victims of reported criminal offences, . For further information, go to the , subject page, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/victims-of-reported-criminal-offences

Documentation of statistics

An overview of the Danish economy

Combining the selection of indicators presented below provides a general view of the state of the Danish economy. What is the growth rate of the economy and how is it going with government finances and inflation? What is the situation of the labour market and the housing market? What expectations do economic operators have for the future and what is the outlook for the green targets? Dive into the numbers by clicking the graphs., Danish economy here and now, Consumer expectations, i,   , -13.1, Feb/26, Information, ×, Consumer expectations of the economic situation of not only themselves but also Denmark as a whole, now and in one year , Consumer price index, i,   , 0.7, % Feb/26, Information, ×, Percentage change in the consumer price index total against the same month the preceding year , Core inflation, i,   , 1.8, % Feb/26, Information, ×, Percentage change in the consumer price index excl. energy and unprocessed foodstuff against the same month the preceding year , Retail trade index, i,   , 102.0, Jan/26, Information, ×, Index, 2021=100, quantity indicies seasonally adjusted , Business sentiment indicator, i,   , 103.3, Feb/26, Information, ×, Index=100 calculated as the average for the period 1998 - 2024 , Industrial production index, i,   , 145.8, Jan/26, Information, ×, Index, 2021=100, seasonally adjusted , Bankruptcies, i,   , 164, Feb/26, Information, ×, Bankruptcies in active companies, seasonally adjusted , Persons in employment, i,   , 3,078,702, Dec/25, Information, ×, Total number of employees in the business sector, seasonally adjusted , Unemployed, i,   , 89,635, Jan/26, Information, ×, Most recent number of unemployed persons from either the unemployment indicator or the gross unemployment. Seasonally adjusted, full-time persons , Other indicators, Economic growth (GDP), i,   , 0.2, % Q4/25, Information, ×, Real growth in per cent against the preceding period, seasonally adjusted , Production index of the service sector, i,   , 101.1, Dec/25, Information, ×, The change in the production index for service industries compared to the previous month. , Government surplus/deficit (% of GDP), i,   , 4.5, % 2024, Information, ×, Government EMU surplus or deficit as per cent of GDP , Government debt (% of GDP), i,   , 30.5, % 2024, Information, ×, Government EMU debt as per cent of GDP , Exports, i,   , 176,798, mio. kr. Jan/26, Information, ×, Current account revenue in million DKK from goods and services, seasonally adjusted , Balance of payments surplus, i,   , 35,397, mio. kr. Jan/26, Information, ×, Current account net revenue in million DKK, seasonally adjusted , Price development of single-family houses, i,   , 6.9, % Q3/25, Information, ×, Percentage change in the price index against the same quarter the preceding year, seasonally adjusted , Share index, i,   , 1,380, Jan/26, Information, ×, Index 1995=100 for shares in total on OMXC , Development in single-family house sales, i,   , 10.6, % Q3/25, Information, ×, Percentage change in number of sales against the same quarter the preceding year, seasonally adjusted , Price development of owner-occupied flats in Copenhagen, i,   , 14.1, % Q3/25, Information, ×, Percentage change in the price index against the same quarter the preceding year for owner-occupied flats in the city of Copenhagen, seasonally adjusted , Interest rates, i,   , 2.67, % Feb/26, Information, ×, Average bond yield for all listed bond series (government and mortgage bonds, etc.) , Greenhouse gas emissions, i,   , 38,785, 1.000 ton 2023, Information, ×, The emission of greenhouse gases stated in 1000 tonnes from Danish territory, incl. LULUCF and excl. CO2 from biomass , Share of renewable energy, i,   , 48.4, % 2024, Information, ×, Renewable energy share in per cent of total final energy consumption ,  

https://www.dst.dk/en/Statistik/temaer/overblik-dansk-oekonomi

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

PRIS03: Consumer price indices by group of households

commodity group, group of households, unit and time
2016M01-2026M02 (-)

https://www.statbank.dk/PRIS03

Tables in StatBank

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