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      Documentation of statistics: Government deficit and debt in the EU-countries

      Contact info, Government Finances, Economic Statistics , Jesper Lillebro Feddersen , +45 20 51 61 92 , JEF@dst.dk , Get documentation of statistics as pdf, Government deficit and debt in the EU-countries 2024 , Previous versions, Government deficit and debt in the EU-countries 2023, Government deficit and debt in the EU-countries 2022, Government deficit and debt in the EU-countries 2021, Government deficit and debt in the EU-countries 2020, Government deficit and debt in the EU-countries 2019, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2018, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2017, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2016, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2015, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2014, EMU-Deficit and EMU-Debt in Denmark and Government Deficit and Debt in the EU 2013, EMU-debt and EMU-deficit (Government deficit and debt) is the statistical data required for the excessive deficit procedure (EDP) in the Economic and Monetary Union in according to the Maastricht Treaty and Stability- and Growth Pact. The EU-Commission uses the statistics to monitor and examine the development of the budgetary situation and government debt in Denmark in accordance with the Maastricht Treaty convergence criteria. The Compilations are based on the European System of Accounts (ESA2010). However, on some points they differ from ESA2010, e.g. on the valuation of debt, which is at nominal value., Statistical presentation, The compilation of consolidated gross debt at nominal value for general government is sometimes referred to as EMU-debt/government debt. The deficit is sometimes referred to as the EMU-deficit/government deficit. Government deficit and debt in EU was first published in spring 2003. Covering data on ESA2010 back from 2010, at the moment. Danish Government deficit and debt was first published in fall 2004. Covering data on ESA2010 back from 2000., Read more about statistical presentation, Statistical processing, Main sources are balance sheets and income statements from the central government, regions and municipalities and and social security funds. Frequency of data collection is Semi-annual and quarterly. Because of the number of consistency checks and data confrontations facilitated by the system of accounts. Further more Eurostat/EU-commission assess the quality of EDP-data by a detailed inventory, a clarificationproces after the notifications and by standard dialogue and upstream visits every second year., Read more about statistical processing, Relevance, High., Read more about relevance, Accuracy and reliability, The government deficit and debt is based on accounts figures for the whole general government sector that have a very limited degree of inaccuracy. , The statistical uncertainty is not calculated. , The overall accuracy is considered to be relatively high., Read more about accuracy and reliability, Timeliness and punctuality, Debt: End of the quarter and end of the year., Deficit: Current year., The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, Government EMU-debt is to a certain degree comparable with quarterly financial accounts for general government since both statistics are based on the sectors and instruments defined in ESA2010. The primary differences are: Government EMU-debt is based on nominal values, while quarterly financial accounts for General Government are based on market values., In a similar way, Government Deficit is comparable with the national accounts compilations of net-lending for General Government in the so called March- and June-versions., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , EMU debt and EMU balance, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/government-deficit-and-debt-in-the-eu-countries

      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

      Documentation of statistics: Long Term Unemployed Persons

      Contact info, Labour Market, Social Statistics , Carsten Bo Nielsen , +45 23 74 60 17 , CAN@dst.dk , Get documentation of statistics as pdf, Long Term Unemployed Persons 2024 , Previous versions, Long Term Unemployed Persons 2020, Long Term Unemployed Persons 2019, Long Term Unemployed Persons 2018, Long Term Unemployed Persons 2017, Long Term Unemployed Persons 2016, Long Term Unemployed Persons 2015, Long Term Unemployed Persons 2014, This statistics show the structure and development of long-term unemployment, defined as gross unemployment spells of minimum 52 weeks. The statistics cover all months in the period from January 2009 onwards. The statistics also covers shorter and longer unemployment spells, these different spells was published for the first time in October 2018., Statistical presentation, The statistics cover the persons who are long-term unemployed due to administrative data. A long-term unemployed person has been gross unemployed for at least 52 consecutive weeks (1 year). Persons who leave the gross unemployment for a period of 4 weeks, within the 12 months, and who is not in ordinary employment during the period of 4 weeks are also included in the statistics. The statistics also covers unemployment spells by duration from 26 weeks (0,5 year) up to 156 weeks (3 years)., Read more about statistical presentation, Statistical processing, The statistics of long-term unemployment is made out of the register of public benefits that covers all persons receiving public benefits in the age below their official pension age. The Register of Employees is also used in the statistics. The employment records cover employed persons in firms registered in Denmark from January 2008 onwards., Both data regarding public benefits and employment is collected quarterly. , Read more about statistical processing, Relevance, Users: Ministries (primary the Ministry of Employment), municipalities, organizations, educational institutions, research institutions, the news media and private persons., The statistics is quite new and there has not been collected any knowledge about the user experience., Read more about relevance, Accuracy and reliability, The statistics measure the number of long-term unemployed persons according to administrative registers and is based on a full sample. The statistics is precise according to the written description of long-term unemployment., Read more about accuracy and reliability, Timeliness and punctuality, The statistic is published quarterly and is published 4 months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The statistic is comparable from one month to another from January 2009 onwards. For international comparison the long unemployment term/figures from the Labour Force Survey is recommended., Read more about comparability, Accessibility and clarity, These statistics are published in the StatBank under the subject , Unemployed persons, . For further information, go to the subject page](https://www.dst.dk/en/Statistik/emner/arbejde-og-indkomst/beskaeftigelse-og-arbejdsloeshed/arbejdsloese). , Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/long-term-unemployed-persons

      Documentation of statistics

      Documentation of statistics: Market Value for Households Real Estate

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

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

      Documentation of statistics

      Documentation of statistics: Cash Benefits

      Contact info, Labour Market, Social Statistics , Carsten Bo Nielsen , +45 23 74 60 17 , CAN@dst.dk , Get documentation of statistics as pdf, Cash Benefits 2024 , Previous versions, Cash Benefits 2023, Cash Benefits 2021, Cash Benefits 2020, Cash Benefits 2019, Cash Benefits 2018, Cash Benefits 2017, Cash Benefits 2016, Cash Benefits 2015, Cash Benefits 2014, The purpose of the statistics Cash Benefits is to measure the number of recipients (actual figures and seasonally adjusted), whole year persons and the amounts paid to person’s who receive cash benefits and related benefits. The statistics are used to public planning, budgeting in the municipalities, education, research and public debate. These statistics have been compiled since 1983, but is in its current form comparable from 2007 and onwards., Statistical presentation, Cash Benefits statistics are a monthly and yearly measurement of receivers of cash benefits and related benefits stated in number of recipients (actual figures and seasonally adjusted), whole year persons and the amounts paid in 1.000 DKK. The statistics cover persons who are above the age of 16 years old. Furthermore we have a yearly statistics grouped by ancestry, family type and national origin., Read more about statistical presentation, Statistical processing, Administrative data for these statistics are collected monthly from KY. The level and the development of the statistics are compared with the previous three months for every account code according to the authorized account plan. The collected data is processed according to the definition of affected persons. The definition can be found in section 2.04 , Statistical concepts and definitions, ., Read more about statistical processing, Relevance, These statistics are relevant for ministries, municipalities, organizations, education institutions, research institutions, the media and private persons, for analysis, public and private planning etc. The statistical data are also used in other areas within Statistics Denmark, e.g. analysis, production and validation of the statistics , People receiving public benefits, ., Read more about relevance, Accuracy and reliability, The statistics are based on records from KY. The records are based on an authorized account plan made by the Ministry of Social Affairs and the Interior. The municipalities have an economic incentive to make valid registrations. Therefore, the overall accuracy is at a high level., Read more about accuracy and reliability, Timeliness and punctuality, The statistic is published quarterly and yearly. The quarterly statistics are published 70 days after the end of the reference period while the yearly statistics are published 5-6 months after the reference period. Publications are released on time, as stated in the release calendar., Read more about timeliness and punctuality, Comparability, These statistics have been compiled since 1983 but is in its present form comparable from 2007 and onwards., Comparability over time can be divided in to three periods:, 1983 Quarter 2 - 1993 Quarter 4 - Number of families., 1994 Quarter 1 - 2006 Quarter 4 - Number of persons. , 2007 Quarter 1 - present - Number of persons. New source and counting., It is not possible directly to compare the statistics internationally, as other countries do not have the corresponding benefits and rules., Read more about comparability, Accessibility and clarity, These statistics are published quarterly in a Danish press release, at the same time as the tables are updated in the StatBank. The yearly statistics are only published in the StatBank. In the StatBank, these statistics can be found under the subject , Living conditions, . For further information, go to the , subject page, ., Read more about accessibility and clarity

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

      Documentation of statistics

      Documentation of statistics: Parental leave benefits

      Contact info, Labour Market, Social Statistics , Anna Skovbæk Mortensen , +45 21 77 67 54 , AOM@dst.dk , Get documentation of statistics as pdf, Parental leave benefits 2024 , Previous versions, Parental leave benefits 2023, Parental leave benefits 2022, Parental leave benefits 2021, Parental leave benefits 2020, Benefits in connection with childbirth 2019, The statistics Parental leave benefits in connection with childbirth shed light on the use of the Maternity Act, including equality between mothers and fathers. The statistics have been compiled since 1995, but in 2017 changed data source. Since 2017, data from ATP / Udbetaling Danmark's IT system for the administration of payment of parental benefits in connection with birth, adoption, child illness etc., Statistical presentation, Childbirth allowance annually calculate a parent's year's use of the rights the Maternity Act gives them, and the distribution of parental leave between the father and mother, as well as the number of persons, and days on benefits. Furthermore, the statistics provide the data basis for calculating amounts paid out in connection with childbirth. , Read more about statistical presentation, Statistical processing, The data basis of the statistics is based on a total extraction from 13 central tables in the database for ATP/Udbetaling Danmark's administrative IT system, UDK-Barsel, and a delta extraction from a 14th table, which is very large. Selected variables from the 14 tables are merged into a single table that constitutes a longitudinal register, the Barselsdagpenge Register, with a well-defined record structure. The Barselsstatistik Register is formed by combining the Barselsdagpenge Register with an extract from the Population Register and other Danish Statistics registers., Read more about statistical processing, Relevance, The maternity and paternity leave part of the statistic is used by ministries for reasons of gender equality policy and of the unions and the employers' organizations in connection with collective bargaining agreements. The statistics are included as an important data element concerning analyzes of the productivity of the Danish workforce (economic model calculations), the labor market accounts, the statistics statistics on Public dependents and the absence statistics, Read more about relevance, Accuracy and reliability, The statistics summarize the reports of birth or adoption that have triggered the payment of due to maternity leave. The expectation is that all cases are reported. However, there are a number of cases that will only be reported long after the end of the year to which the case relates, why the last year is not fully updated. In order to get a picture of a parent's year's use of the maternity law, it has been necessary to link several registers and set up an algorithm for calculating the parents' entitlement. There is a risk of programming errors here, just as the algorithm rules are a choice., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published annually three months after the reference year in March-April. March-April is chosen as the compromise of current interest and waiting for the last reports of the year to appear. At publishing time the newest data will be less than three months old. , Read more about timeliness and punctuality, Comparability, The statistics are influenced by local Danish legislation, which makes comparison with similar statistics from other countries difficult. In addition, maternity leave can be calculated in 18 different ways, which is why it requires a good knowledge of the documentation for countries' calculation methods before comparing their figures. At the moment, the statistics cover data for the years 2015-2023, where no data breach has been detected, with the exception that the 1st quarter of 2015 is under-updated, which gives a minor data breach for total counts., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Parental leave benefits, . For further information, go to the , subject page, ., Read more about accessibility and clarity

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

      Documentation of statistics

      Documentation of statistics: Children and young persons placed outside own home

      Contact info, Personal Finances and Welfare, Social Statistics , Siri Dencker , +45 21 45 34 92 , SEN@dst.dk , Get documentation of statistics as pdf, Children and young persons placed outside own home 2024 , Previous versions, Children and young persons placed outside own home 2023, Children and young persons placed outside own home 2022, Children and young adults in out-of-home care 2021, Children and young persons placed outside own home 2020, Children and young persons placed outside own home 2019, Children and young persons placed outside own home 2018, The statistics shed light on the activities of municipal authorities regarding placements outside the home., The statistics are used to account for the scope of placements of children and young people outside their own homes. The statistics are comparable from 2011 onwards., Statistical presentation, The statistics contain yearly estimates of the municipalities’ initiated placements and placements of children and young persons in out-of-home care. The figures are classified by provinces, municipalities, type of measure, place of accommodation, cause of placement in out-of-home care, cause of change in the placement of out-of-home care, sex, and age groups. The statistics are published in StatBank Denmark and in a NYT article authored in Danish by Statistics Denmark., Read more about statistical presentation, Statistical processing, Data for these statistics are continually collected from the administrative municipalities. The collected data is then subjected to a meticulous validation process in cooperation with the municipalities. All of the municipalities receive feedback sheets, representing the scope and nature of the reported data, which need to be approved by the municipalities. Data is subsequently gathered in an incident register which forms the basis for a creation of a progress register and a status/stock register., Read more about statistical processing, Relevance, The statistics are used by municipalities, provinces, ministries, the media, researchers, private individuals and organizations. The statistics are used for public planning and administration, research, public debate and education., Read more about relevance, Accuracy and reliability, Data is reported from the municipalities' administrative systems, which are used for case processing. There may be errors or omissions in the reports, or reports may be missing altogether. The municipalities approve an annual status prior to publication of the statistics. In this context, municipalities are requested to correct any errors and deficiencies., Changes in placements are generally underestimated because the changes are only indirectly approved by the municipalities based on the reported placement status., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published 6 months after the end of the reference period. The statistics are published without delay according to the scheduled release date. , Read more about timeliness and punctuality, Comparability, The statistics are comparable from 2011 and onwards., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release, , Nyt fra Danmarks Statistik, . The figures are also published in Statbank Denmark in , Disadvantaged children and young people, Further information can be found at the webpage of the statistics , Udsatte børn og unge, or by contacting Statistics Denmark directly., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/children-and-young-persons-placed-outside-own-home

      Documentation of statistics

      Documentation of statistics: Sickness benefits

      Contact info, Labour Market, Social Statistics , Anna Skovbæk Mortensen , +45 21 77 67 54 , aom@dst.dk , Get documentation of statistics as pdf, Sickness benefits 2024 , Previous versions, The purpose of the Sickness Benefits statistics is to provide information about the costs of sickness benefits and the number of sickness benefit recipients, both in terms of the number of people affected and the number of full-time employees. The statistics have been compiled since 1995, but are in their current form comparable from the year 2020 onwards., Statistical presentation, Sickness benefit is an annual statement of the number of people, benefit days and amounts paid out in connection with illness. Furthermore, the extent of partially resumed work is calculated. The data is broken down by labour market affiliation, age, gender and geography. Furthermore, figures from the Sickness Benefit Statistics are included in the statistics Persons below the state pension age on public benefits, Labour Market Accounts and Absence, where the extent of absence due to illness is put into a larger context., Read more about statistical presentation, Statistical processing, When the data is received, all fields are checked by machine and the number of observations received matches the number of observations sent by KMD. If the data delivery cannot be approved, KMD is contacted in order to correct the delivery., Read more about statistical processing, Relevance, Sickness benefit statistics tell us how many man-years Danish society loses due to long-term illness and how long it will take the long-term sick person to return to the labour market if he or she returns., Read more about relevance, Accuracy and reliability, The statistics summarise the reports of illness that have triggered the payment of unemployment benefits. The expectation is that all sickness benefit cases with payment are reported. Therefore, the statistics can be expected to be accurate in relation to actual payments. However, some cases are not reported until long after the end of the period to which the case relates, which is why the last quarter is not fully updated. The delayed updates result in a revision the following year that is in the order of 0.5 per cent in an upward direction., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published annually at the beginning of April the year after the reference year. The statistics are usually published without delay in relation to the announced date, Read more about timeliness and punctuality, Comparability, The statistics are influenced by Danish legislation. Over the years, the period the employer must pay for in connection with illness has been increased from 14 days to 30 days, and as of December 2012, the right to receive sickness benefits on public holidays was cancelled., Read more about comparability, Accessibility and clarity, These statistics are published 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 , Sickness benefits, . For further information, gp to the , subject page, ., Read more about accessibility and clarity

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

      Documentation of statistics
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