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Documentation of statistics: Producer Price Index for Services

Contact info, Prices and Consumption, Economic Statistics , Nicklas Milton Elversøe , +45 61 15 35 98 , NEL@dst.dk , Get documentation of statistics as pdf, Producer Price Index for Services 2025 , Previous versions, Producer Price Index for Services 2024, Producer Price Index for Services 2023, Producer Price Index for Services 2021, Producer Price Index for Services 2020, Producer Price Index for Services 2019, Producer Price Index for Services 2018, Producer Price Index for Services 2017, Producer Price Index for Services 2016, Producer Price Index for Services 2015, Producer Price Index for Services 2014, The purpose of these statistics, is to analyze price trends in the first stage of commercial transaction of services, i.e. producers' selling prices to other producers (business to business), ex VAT. These statistics have been compiled since 2006., Statistical presentation, The , Producer Price Index for Services, is a quarterly measurement of service prices relating to the first commercial transaction (business to business), for the domestic market and export. The statistics contains a number of service price indices in different industries, e.g. price indices for transport services, consultancy services and cleaning services etc. , Read more about statistical presentation, Statistical processing, Approx. 2.300 prices are collected quarterly from selected companies in Denmark in order to calculate these indices. Prices are collected through an electronic questionnaire. The prices are automatically validated during the collecting process and changes that are greater than a predetermined threshold value, are checked manually by the staff. The Price indices are calculated in a hierarchical system, where the first calculation is made for the most detailed industries, i.e. elementary indices. These elementary indices are calculated based on a number of , basic prices, , as geometric Jevons Indices. The elementary indices are subsequently weighted together as aggregated price indices. These are calculated as arithmetic Laspeyres indices., Read more about statistical processing, Relevance, The , Producer Price Index for Services, serves as a deflator, key economic indicator and a contract regulation tool. The primary users of the statistics are the Danish National Accounts plus an array of public and private sector decision-makers. The statistics meet all the requirements of the EU in terms of industry coverage, aggregation level, frequency and publication date, etc., Read more about relevance, Accuracy and reliability, The prices covered by the data collection have a direct coverage of approximately 70 percent of total revenue within the selected services. The weight base also covers the main part of all trade in the first turnover, within the demarcation of the statistics, and there is constant monitoring of the quality of the sample. The sample is not extracted simply randomly, so no measure of sample error is able to be produced. , Only final figures are published. , In general, the producer price index for services is not assessed to have increased uncertainty as a result of Covid-19, as the data collection and thus the lapse has been largely unchanged as Follow of the crisis. But a single industry has been affected, which you can read more about less than "Non-sampling error"., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published quarterly, approx. 1,5 months after the end of the reference period, as far as possible on the 15th of the month or the first business day thereafter. Publications are released on time, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, The , Producer Price Index for Services, can be found as a time series from 2006 to present. The statistic follows international standards and is therefore comparable with similar statistics from other European countries., Read more about comparability, Accessibility and clarity, These statistics can be found in the StatBank, under the subject , Producer Price Index for Services, . For further information, go to the , subject page, ., Read more about accessibility and clarity

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

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: 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 2024 , Previous versions, 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: 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: Announcements of forced sales of real property

Contact info, Prices and Consumption, Economic Statistics , Maya Drewsen , +45 20 36 69 89 , MDR@dst.dk , Get documentation of statistics as pdf, Announcements of forced sales of real property 2024 , Previous versions, Announcements of forced sales of real property 2023, Announcements of forced sales of real property 2022, Announcements of forced sales of real property 2021, Announcements of forced sales of real property 2020, Announcements of forced sales of real property 2019, Announcements of forced sales of real property 2018, Announcements of forced sales of real property 2017, Announcements of forced sales of real property 2016, Announcements of forced sales of real property 2015, The purpose of the statistics is to document the trend in the number of announced forced sales in the Danish Official Gazette. The development in this figure is considered to be an important economic indicator. The quarterly statistics figures are comparable from 1979 onwards, while the monthly figures are comparable from 1993 onwards. The annual municipal figures are comparable from 2012 onwards. , Statistical presentation, These statistics document the development in the number of forced sales of real property, announced in the Danish Official Gazette, broken down by type of property and geographical location., Read more about statistical presentation, Statistical processing, Data for these statistics are collected electronically from the Danish Official Gazette. To avoid major fluctuations, Statistics Denmark performs trouble-shooting of the collected data to ensure that the same owner is only counted once within the month in question. Furthermore, trouble-shooting is performed to make sure that second announcements about the same real property, cancellations, confirmations, reprints, change of court date, discontinuance, affirmation, attachment, delay, default etc. are not included in the statistics. Subsequently, the forced sales are broken down into the various property categories and geographical areas. , Read more about statistical processing, Relevance, The statistics are used by public and private decision-makers to assess the trend in the number of announced forced sales of real property. , Read more about relevance, Accuracy and reliability, The forced sales of real property statistics provide a monthly total count of the number of announced forced sales of real property in the Danish Official Gazette with unique owners within the month in question. In this way it is ensured that major fluctuations in the statistics are minimised. The primary purpose of this set of statistics is to be informative regarding trends and it is not an assessment of the number of forced sales actually carried out. , Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published 4 weekdays after the expiry of the month except the figures of December which are published 8 weekdays after the expiry of the month., Read more about timeliness and punctuality, Comparability, The statistics are comparable at a national level since 1979. Due to the structural reform in 2007, there is a geographical breach of data., Read more about comparability, Accessibility and clarity, The statistics is published monthly in News from Statistics Denmark. Figures can also be found in StatBank. The figures are also included in the Statistical Ten-year review and Statistical Yearbook (has been discontinued)., Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Labour Market Account

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

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

Documentation of statistics

Documentation of statistics: 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: Employee Trade Unions

Contact info, Labour Market, Social Statistics , Mikkel Zimmermann , +45 51 44 98 37 , MZI@dst.dk , Get documentation of statistics as pdf, Employee Trade Unions 2024 , Previous versions, Employee Trade Unions 2023, Employee Trade Unions 2022, Employee Trade Unions 2021, Employee Trade Unions 2020, Employee Trade Unions 2019, Employee Trade Unions 2018, Employee Trade Unions 2017, Employee Trade Unions 2016, Employee Trade Unions 2015, Employee Trade Unions 2014, Employee Trade Unions 2013, The purpose of the statistics is to compile aggregated annual statistics showing the number of members of employee organisations with attachment to the labour market. The statistics been complied since 1994, but is in its current form comparable from 2007 and onwards. , Statistical presentation, The statistics provide an overview of the number of members of employee organisations with attachment to the labour market i.e. excl. trainees, retirees, early retirees and self-employed. The statistics are grouped by central organisations/individual organisations and gender. The statistics are published annually and disseminated in the newsletter Nyt fra Danmarks Statistik and in the StatBank., Read more about statistical presentation, Statistical processing, These statistics are based on annual reports from employees' organisations on the number of members attached to the labour market per December 31. Data are typically validated by comparing the current year’s reporting with that of previous years for each organisation. As of the reference date 31 December 2023, total membership figures are also reported for each organisation. These totals are then compared with the reported number of members with labour market affiliation per organisation to ensure consistency., Read more about statistical processing, Relevance, Users of the statistics are typically employee and employer organisations, researchers and the media. No dissatisfaction has been expressed with the statistics., Read more about relevance, Accuracy and reliability, The statistics are based on reports from Central Employee Organisations and other employee organisations. Not all employee unions are able to calculate the precise figures exclusive members not attached to the labor market, i.e.. students, early retirees and pensioners, and self-employed. The data are therefore believed to be a little overestimated for some organisations. On the other hand, there may be small employee organisations that are not included. The data are normally not revised, but if errors are detected they are corrected back in time as far as possible. Although participation in the statistics is voluntary, all employee organisations appear to submit data., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 4-5 months after the reference date. , The statistics are usually published on the scheduled date without delay., Read more about timeliness and punctuality, Comparability, The statistics have been compiled (without data breach) since 2007. Minor breaks in the time series may occur when employee organisations change their reporting methods. For example, the previously observed sharp decline in membership figures for some organisations (mainly those under LO) from 2011 to 2012 was due to the inclusion of members without labour market affiliation in earlier reporting. However, this decline has been addressed as of the publication on 19 May 2025, by revising the reported figures downwards for the period 2007–2011., Read more about comparability, Accessibility and clarity, The statistics is published yearly in a Danish press release (Nyt fra Danmarks Statistik) at the same time as the tables are updated in the StatBank. In the StatBank, the statistics ca be found under the subject , Trade unions, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/employee-trade-unions

Documentation of statistics

Documentation of statistics: Home to work commuting

Contact info, Labour Market , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Commuting 2016 , Previous versions, The purpose of the RAS statistic is to provide a description of the Danish population's commuting and distance between place of residence and work place. The commuting statistic has been published since 1984. The distance between residence and work place was first published in 2006. The statistic is in the current form comparable from 2008 and forward. , Statistical presentation, The statistic is an annually and individual based count of the employed persons commuting between residence and work place in the last working day in November. Including a calculation of the distance between the commuters residence and work place i kilometers (km). The commuting statistic is published in the Statbank where the statistic besides from residence, work place and commuting distance also is divided on sex, industry (DB07) and socioeconomic status. Data is also available trough the Division of Research Services and DST Consulting., Read more about statistical presentation, Statistical processing, The commuting statistic is compiled on the register-based labour force statistic (RAS), which is based on the Labour Market Account (LMA) - a longitudinal register. A comprehensive data validation is done in the production of AMR. RAS is done by taking a status (on the populations primary attachment to the labour market) on the last working day in November based on LMA. Based on the information about the address of residence and workplace for employed persons the commuting distance is calculated. , Read more about statistical processing, Relevance, The statistic is relevant for users interested in mobility on the labour market and the data foundation makes it possible to connect detailed information for analysis. , Read more about relevance, Accuracy and reliability, The commuting statistic is compiled from RAS which is used to present the primary connection to the labour market for people resident in Denmark. RAS contains a series of data sources that are integrated, debugged and harmonized. RAS does therefore not contain the same uncertainties as statistics based on samplings. , The definition of the primary job for employed persons is source to uncertainty in the commuting statistic, since the workplace address for the primary job and the address of residence is the foundation for the calculation of the commuting distance. It is also important to be aware that the calculated commuting distance reflects an ideal situation where every person is believed to travel from residence to workplace by the shortest route and by car. , Read more about accuracy and reliability, Timeliness and punctuality, The commuting statistic is published approximately 17 months after the reference point in time. The date of publication, which is normally complied without delay, is defined more than a year ahead. , Read more about timeliness and punctuality, Comparability, The statistic is published since 1984, and is in the current shape comparable from 2008 and forward. The statistic shows commuting within and across municipalities in Denmark, and the data foundation is based on administrative registers with national features. It is therefore difficult to compare the statistic internationally. , New and better data foundations and changes in the labour market have caused a number of data breaks over time, which have influence on the possibility of comparing data over time. , Read more about comparability, Accessibility and clarity, The statistic is 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 , Commuting from home, and , Commuting to workplace, . For further information, go to the subject page for , Commuting, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/home-to-work-commuting

Documentation of statistics

Documentation of statistics: Working time accounts

Contact info, Labour Market, Social Statistics , Morten Steenbjerg Kristensen , +45 20 40 38 73 , MRT@dst.dk , Get documentation of statistics as pdf, Working time accounts 2025 , Previous versions, Working time accounts 2024, Working time accounts 2023, Working time accounts 2022, Working time accounts 2021, Working time accounts 2020, Working time accounts 2019, Working time accounts 2018, Working time accounts 2017, Working time accounts 2016, The purpose of the Danish working time accounts (WTA) is to compile time series on hours worked and calculate wage and employment data for companies registered in Denmark. The statistics integrate and aggregate existing statistics, including the Labor Market Accounts (LMA) and Employees, and it is comparable since 2008., Statistical presentation, The statistics is a quarterly and yearly calculation of hours actually worked, number of employees, number of jobs and wages in DKK million. The statistics are distributed by industry, sector, whether you are an employee or self-employed, and by gender., 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 projections to periods for which structural data are not available. Summation of the data is conducted before they are projected. Data is seasonally adjusted for national use., In the new EU statistics under Council Regulation (EC) No 2019/2152 of 27 November 2019 concerning European Business Statistics, data are trade day adjusted before being compiled into indices, Read more about statistical processing, Relevance, The statistics is relevant for users interested in social and economic statistics., Read more about relevance, Accuracy and reliability, The statistics is mainly based on the Labour Market Accounts (LMA). LMA integrates and harmonizes a wide range of data sources in a statistical system. This means that LMA can illustrate the labour market better than individual statistics can. LMA is at the same time based on a total census of the population, so there is not the same uncertainty as with statistics based on sampling. The quality of the statistics has also been significantly improved by the fact that the projection period has been reduced compared to previous versions., Read more about accuracy and reliability, Timeliness and punctuality, The annual Working Time Accounts (WTA) are published 6 months after the reference year. The quarterly WTA are published two months and 15 days after the reference quarter. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The Working Time Accounts (WTA) provide data for Council Regulation (EC) No 2019/2152 of 27 November 2019 and for the National Accounts (SNA/ESA). Changes in these will typically lead to changes in the ATR. For an explanation of transition tables between ATR and SNA/ESA, see National Accounts publications., Read more about comparability, Accessibility and clarity, The statistics are published in in the , Statbank Denmark, . You can read more on our , website on the Working Time Account, WTA, and our , website on employment, ., S.6.2. Data sharing: In addition to quarterly figures to Eurostat (STS and indirectly via ESA), data from the Danish WTA are also transmitted to OECD (regional questionnaire) and ILO (ILOSTAT database) although the latter are transmitted in annual figures only., Read more about accessibility and clarity

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

Documentation of statistics