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Documentation of statistics: Educational expenditure (UOE Finance)

Contact info, Government Finances, Economic Statistics , Marianne Ahle Møller , +45 24 66 00 28 , MNM@dst.dk , Get documentation of statistics as pdf, Educational expenditure (UOE Finance) 2023 , Previous versions, Educational expenditure (UOE Finance) 2022, Educational expenditure (UOE Finance) 2020, Educational expenditure (UOE Finance) 2019, Educational expenditure (UOE Finance) 2018, The purpose of the statistics is to show how education expenditures are distributed across source of funding, expenditure type, type of institution along with the level of education. The statistic is based on international standards for education expenditures by the manual UOE data collection on formal education (UOE2020) , which is developed by UNESCO, OECD and Eurostat. The statistic is used as an input to OECD's publication Education at a Glance, which compares educational systems across countries. The statistics are developed from finance year 2016 and onwards. Data is consistent and comparable throughout the entire period. , Statistical presentation, The statistic is an annually two-dimensional publication of education expenditures, which shows the consumption of education seen from the perspective of both sources of funding and educational institutions. The statistic is calculated in DKK millions and divided across financing sources, expenditure type, type of institutions and education level. , Read more about statistical presentation, Statistical processing, Data for this statistics is collected annually from a number of both internal and external sources using data extracts and data deliveries. The collected data is validated on a macro level by controls of time series and different reasonableness checks. When data have been validated, the classification according to UOE2020 begins following by imposed distributions based on student data gather internally from Statistics Denmark. Lastly, data is integrated and complied into the final result. , Read more about statistical processing, Relevance, The statistic is relevant for professionals and analysts. The statistic is included in the annual publication by OECD Education at a Glance and will be launch in OECD's database OECD Data Explorer along with Eurostat. Professionals and analysts use the statistics to get a detailed overview of the expenditure to education across education levels and the funding of those in Denmark. , Read more about relevance, Accuracy and reliability, The overall accurancy of the statistics i considered to be high, as the primary data sources is contributed by the general government finances. However, there are uncertainty associated with the funding of households and international sources to education. Moreover, misclassifications can occur as it can be difficult to determined whether some areas are within the scope of UOE2020. The detail level from annual reports used for private tertiary educations are fraught with uncertainty because of the overall coding. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 11 months after the end of the reference period and are published without delays in relation to planned release times., Read more about timeliness and punctuality, Comparability, The statistic follow common European guidelines in the manual UOE data collection on formal education (UOE2020). The statistic is fully comparable across time and countries for the entire published time period. Previously the reporting burden to UNESCO, OECD and Eurostat was acquired from the National Agency of IT and Learning under the Ministry of Children and Education. , Read more about comparability, Accessibility and clarity, The statistic is published in New from Statistics Denmark and in the StatBank under , Education expenditures, . For more information see the , subject page, . In addition, the figures are included in OECD's annual publication , Education at a Glance, . Moreover, data is published by , OECD, and , Eurostat, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/educational-expenditure--uoe-finance-

Documentation of statistics

Documentation of statistics: Cereal Prices used for Regulation of Land Rents

Contact info, Food Industries, Business Statistics , Karsten Kjeld Larsen , +45 21 29 55 76 , KKL@dst.dk , Get documentation of statistics as pdf, Cereal Prices used for Regulation of Land Rents 2024 , Previous versions, Cereal Prices used for Regulation of Land Rents 2023, Cereal Prices used for Regulation of Land Rents 2022, Cereal Prices used for Regulation of Land Rents 2021, Cereal Prices used for Regulation of Land Rents 2020, Cereal Prices used for Regulation of Land Rents 2019, Cereal Prices used for Regulation of Land Rents 2018, Cereal Prices used for Regulation of Land Rents 2016, Cereal Prices used for Regulation of Land Rents 2014, The purpose of the statistics is to show the development of the farm gate prices (basic prices) for wheat and barley. Farm gate prices are used for example for regulating rents of agricultural land in tenancy and have existed since the beginning of the 17th century. For the period 1910-1970 the prices were calculated for dioceses (church districts under the jurisdiction of a bishop). In the years 1937-1953 only prices for the diocese of Zealand were calculated. In its present form the statistics have been comparable since 1985 with figures for eight different geographic areas., Statistical presentation, The statistics are a yearly calculation of farm gate prices for barley and wheat defined as basic prices. The figures are calculated for eight regions. Due to the structural reform in 2007 the names of the regions have been revised but are otherwise unchanged. , The eight districts are described in the manual to the law on cereal prices called , kapitelstakster, . Go to http://www.retsinfo.dk and search for number 10053 of the 24th of November 2006 (24/11/2006), also termed , vejledning om opgørelse af kapitelstakster, . , Read more about statistical presentation, Statistical processing, Basic prices for wheat and barley are calculated based on yearly reports from traders of cereals on bought quantities and values of wheat and barley in connection with direct trade with farmers. Normally the same firm from last years survey are selected, men periodically, every third or fourth year, new firms might be added from within the industry. In 2024 14 firms took part. , Read more about statistical processing, Relevance, The figures are used primarily by farmers to determine the rent for agricultural land. The important users are ministries, agricultural organisations, local authorities, farmers and lawyers. There is a high level of satisfactory among users., Read more about relevance, Accuracy and reliability, There is no measure of the uncertainty of the statistics, e.g. sample error or measurement error. There is no reason to believe that statistics should be subject to bias., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published about seven weeks 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, Official prices have been around since the beginning of the 17th century. From 1910-1970 the statistic covers the former Parishes "Stifter" which were the old zoning. In the period 1937-1953 statistic covers only Zealand diocese. The statistics are fully comparable back to 1985., 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 the subject , Agricultural and horticultural economy, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/cereal-prices-used-for-regulation-of-land-rents

Documentation of statistics

Documentation of statistics: Corporate Taxation

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

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

Documentation of statistics

Documentation of statistics: 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