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Documentation of statistics: Register-Based Labour Force Statistics

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

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

Documentation of statistics

Documentation of statistics: Standardised index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Standardised index of average earnings 2025 , Previous versions, Standardised index of average earnings 2024, Standardised index of average earnings 2023, Standardized Index of Average Earnings 2021, Standardized Index of Average Earnings 2020, Standardized Index of Average Earnings 2019, Standardized Index of Average Earnings 2018, Documents associated with the documentation, Standardberegnet lønindeks. Metode efter serviceeftersyn 2022-2023 (pdf) (in Danish only), The purpose of the standardised index of average earnings is to estimate the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the labour market’s occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics are used for e.g. monitoring of business cycles, regulation of contracts, analyses of developments in pay levels as well as input in the calculation of the National Accounts., The statistics have been prepared since 2018 with data back to the first quarter of 2016. A revised index and time series are published in May 2023 with data back from 2016., In parallel, Statistics Denmark is calculating the implicit index of average earnings. Unlike the standardised index, the implicit index of average earnings does not take changes in the occupational composition into account., Statistical presentation, The standardised index of average earnings is a quarterly estimate of the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics show the development in the average hourly earnings for employees by sector, industry (DB07) and main occupation (DISCO-08). Each quarter, an index value and an annual increase are published., Read more about statistical presentation, Statistical processing, Data for these statistics are collected quarterly. For the public sector all payroll information are collected while data are collected via a sample from the private sector. The collected data is validated at an aggregate level for key enterprises (only in the private sector) and at an individual level through a combination of validation rules for the hourly earnings for the individual employment relationship. The hourly earnings are assessed based on sector, industry, main occupation and type of employment. Once data has been validated, base index is calculated for each homogeneous group, which afterwards is aggregated to sub- and total indices at sector, industry or main occupation level., Read more about statistical processing, Relevance, These statistics are relevant for private enterprises and organisations, as well as ministries and other public institutions for analysis, contractual regulation etc. The statistical data are also used in other areas within Statistics Denmark, e.g the calculation of the Danish National Accounts., Read more about relevance, Accuracy and reliability, The accuracy of these statistics are higher for employees in the public sector than in the private sector. The reason for this is that the statistics for employees in the public sector (more or less) consists of all payroll information, while the statistics for employees in the public sector is based on a sample of enterprises. The accuracy of the statistics for the private sector is therefore affected by sampling uncertainty, completeness of the reported information and non-response. The impact on the indices are unknown., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published two months after the end of the reference period. The statistics are released typically without delay according to scheduled dates of publication. , In February 2022, the statistics were paused and a comprehensive service review was initiated. As a result, the method for calculating standardized index of average earnings was revised. This publication therefore contains revised index values and annual increases for the entire period from the first quarter of 2016 until the first quarter of 2023. This means that the series contains revised values from the first quarter of 2016 until the third quarter of 2021 as well as previously unpublished values from the fourth quarter of 2021 until the first quarter of 2023., Read more about timeliness and punctuality, Comparability, The standardised index of average earnings was first published in December 2018 with a time series starting in the first quarter of 2016. The standardised index of average earnings utilize the same data as the implicit index of average earnings, which however has a different purpose and is therefore calculated using a different method. There exist a few sets of statistics abroad that are partly comparable with the standardised index of average earnings. , 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. In the StatBank, these statistics can be found under the subject , Indices of average earnings, . For further information, visit the subject page for , Income and earnings, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/standardised-index-of-average-earnings

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, Documents associated with the documentation, Genudgivelse af barselsdagpengedata for fødselsårgange 2017-2023 (pdf) (in Danish only), 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: Population Projections

Contact info, Population and Education, Social Statistics , Annika Klintefelt , +45 23 31 14 33 , AKF@dst.dk , Get documentation of statistics as pdf, Population Projections 2025 , Previous versions, Population Projections 2024, Population Projections 2023, Population Projections 2022, Population Projections 2021, Population Projections 2020, Population Projections 2019, Population Projections 2018, Population Projections 2017, Population Projections 2016, Population Projections 2015, Population Projections 2014, A population projection gives an estimate of the size and composition of the future population with respect to sex, age, municipality and origin. The estimate is subject to a number of conditions and assumptions on migration, mortality and fertility. The projection is based on the assumption that the development in recent years continues. Often the development in e.g. in-migration is different from what was assumed and, for that reason, the projection will typically not match the actual development exactly., Statistics Denmark has prepared population projections since 1963. Since 2010, the projections have been produced in collaboration with DREAM (Danish Research Institute for Economic Analysis and Modelling), which is an independent institution whose purpose it is to develop and maintain tools for structural policy analysis. , Statistical presentation, Based on the projection for all of Denmark, Statistics Denmark subsequently makes projections that can be disaggregated by sex, age, provinces and municipalities. As part of the projections, figures are also available on demographic changes in terms of liveborn children, deaths, immigrants and emigrants., Read more about statistical presentation, Statistical processing, The population projections are based on historical data regarding the composition of the population in terms of sex, age and ancestry as well as fertility, mortality, immigration and emigration, and internal migration., Assumptions on the future development in fertility, mortality and migration are necessary to be able to make the projections., The projections are made every year using the population on 1 January. They are released in the beginning of May., A projection is made for the whole country as well as projections for the 11 provinces and 98 municipalities., Read more about statistical processing, Relevance, The projections for municipalities are widely used by the municipalities, and they create the basis for the municipalities’ own projections, which often incorporate a number of local factors that are not part of Statistics Denmark’s projections. The municipalities may use the projections in their planning of institutions, schools and the need for nursing homes in the future. Local media across the country take great interest in Statistics Denmark’s projection., Read more about relevance, Accuracy and reliability, The population projection is built on previous years’ development and is an estimate of the population development. The estimate is subject to a number of conditions and assumptions on migration, mortality and fertility. The projection is based on the assumption that the development seen in recent years will continue. Often the development in e.g. in-migration is different from what was assumed and, for that reason, the projection will typically not match the actual development exactly., In 2024 the projection for Denmark was 0.1 percentage points below actual population growth. To a wide extent, the uncertainty at municipal level is linked to the fact that local development plans and local decisions are not part of the model. Especially in 2020 and 2021, the COVID-19 pandemic has created uncertainty. In 2024, 60 per cent of the municipalities were within minus 0.5 percentage points of the actual population growth the first year. , Read more about accuracy and reliability, Timeliness and punctuality, Statistics have been published as announced without delay in the month of May or June., Read more about timeliness and punctuality, Comparability, Each projection is a new set of statistics and must not be used for time series together with previous projections., With the projection 2010, Statistics Denmark made the projection for all of Denmark for the first time in collaboration with DREAM, and in connection with this, a switch was made to a new projection model based on DREAM’s previous model., Read more about comparability, Accessibility and clarity, The population projections are published in Nyt fra Danmarks Statistik (Statistics Denmark’s news series in Danish) under the subject , Population projections, . For further information, go to the subject page for these statistics., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/population-projections

Documentation of statistics

Danish data SDDS plus

The data shown in this page correspond to the data described on the International Monetary Fund's Dissemination Standards Bulletin Board (DSBB) and includes links to the SDDS plus data. , For a fuller explanation of the DSBB and the statistical standards to which Denmark has committed, please click on , DSBB Home Page, ., This page is updated on the day that data are released. , Real sector, Fiscal sector, Financial sector, External Sector, Socio-demographic Data, Gender, Data category, National website, SDMX data, Metadata, Real sector, National accounts , Statistics Denmark, SDMX, Metadata, Sectoral balance sheets , Statistics Denmark, SDMX, Metadata, Industrial production, index , Statistics Denmark, SDMX, Metadata, Industrial production, manufacturing and mining, index , Statistics Denmark, SDMX, Metadata, Retail sales, index , Statistics Denmark, SDMX, Metadata, Employment , Statistics Denmark, SDMX, Metadata, Unemployment, number of persons, SA , Statistics Denmark, SDMX, Metadata, Unemployment, number of persons, NSA , Statistics Denmark, SDMX, Metadata, Unemployment rate, percent, SA , Statistics Denmark, SDMX, Metadata, Wages/earnings , Statistics Denmark, SDMX, Metadata, Consumer price index , Statistics Denmark, SDMX, Metadata, Producer price index , Statistics Denmark, SDMX, Metadata, Import price index , Statistics Denmark, SDMX, Metadata, Fiscal sector, General government total gross debt in nominal values , Statistics Denmark, SDMX, Metadata, General government - Memorandum items , Statistics Denmark, SDMX, Metadata, General government operations - Transactions in financial assets and liabilities (Financing) - Quarter , Statistics Denmark, SDMX, Metadata, General government operations - Transactions in financial assets and liabilities (Financing) - Annual , Statistics Denmark, SDMX, Metadata, General government operations - Transactions affecting net worth - Quarter , Statistics Denmark, SDMX, Metadata, General government operations - Transactions affecting net worth - Annual , Statistics Denmark, SDMX, Metadata, Central government operations , Danmarks Nationalbank, SDMX, Metadata, Central government debt , Danmarks Nationalbank, SDMX, Metadata, Financial sector, Analytical accounts of the banking sector - Domestic assets and liabilitites including lending , Danmarks Nationalbank, SDMX, Metadata, Analytical accounts of the banking sector - Foreign assets and liabilities , Danmarks Nationalbank, SDMX, Metadata, Analytical accounts of the banking sector - Monetary aggregates , Danmarks Nationalbank, SDMX, Metadata, Analytical accounts of the Central Bank (Danmarks Nationalbank) - Domestic lending and securities holding , Danmarks Nationalbank, SDMX, Metadata, Analytical accounts of the Central Bank (Danmarks Nationalbank) - External position , Danmarks Nationalbank, SDMX, Metadata, Interest rates , 2, Danmarks Nationalbank, Metadata, Financial soundness indicators - Deposit taking institutions , Danmarks Nationalbank, SDMX, Metadata, Financial soundness indicators - Residential real estate prices , Statistics Denmark, SDMX, Metadata, OFCS balance sheet , Statistics Denmark, SDMX, Metadata, Debt securities , Danmarks Nationalbank, SDMX, Metadata, External Sector, Balance of payments , Statistics Denmark, SDMX, Metadata, International reserves , Danmarks Nationalbank, SDMX, Metadata, Template on international reserves and foreign liquidity , Danmarks Nationalbank, SDMX, Metadata, Merchandise trade, value of exports and imports (FOB, CIF) , Statistics Denmark, SDMX, Metadata, Merchandise trade, volume of exports and imports, (FOB, CIF), index , Statistics Denmark, SDMX, Metadata, Merchandise trade, deflator/unit value of exports and imports, (FOB, CIF), index , Statistics Denmark, SDMX, Metadata, International investment position , Danmarks Nationalbank, SDMX, Metadata, Gross external debt , Danmarks Nationalbank, SDMX, Metadata, Coordinated portfolio investment survey , Danmarks Nationalbank, Metadata, Coordinated direct investment survey , Danmarks Nationalbank, Metadata, Currency composition of official foreign exchange reserves , 3, Danmarks Nationalbank, Metadata, Exchange rates , 2, Danmarks Nationalbank, Metadata, Socio-demographic Data, Population , 4, Statistics Denmark, SDMX, Metadata, Gender, Labor Force Participation Rate by Gender , Statistics Denmark, SDMX, 1, ) Data will be released no later than 2018, 2, ) SDMX dissemination is not required for this category., 3, ) Participate, 4, ) Population at the first day of the quarter

https://www.dst.dk/en/Statistik/IMF/Imf

Older documents

Follow this link to get access to , reports, documents and working papers of older date, ., Projects in collaboration with external institutions, Regarding economic effects on Denmark and Italy in connection with EU's enlargement. December 2001., Eastern enlargement of the EU: Economic costs and benefits for the EU present member states?, The case of Denmark, The case of Italy, Economic Working Papers,  (ADAM and DREAM), The DREAM group moved to the ministry of finance in march 2002., 2001:6   [DREAM] , The Optimal Level of Progressivity in the Labor Income Tax in a Model with Competitive Markets and Idiosyncratic Uncertainty, Toke Ward Petersen, September 2001 , 2001:5   [DREAM] , Interest Rate Risk over the Life-Cycle: A General Equilibrium Approach, Toke Ward Petersen, September 2001 ,  , 2001:4   [DREAM] , Indivisible Labor and the Welfare Effects of Labor Income Tax Reform, Toke Ward Petersen, September 2001 , 2001:3   [DREAM] , General Equilibrium Tax Policy with Hyperbolic Consumers, Toke Ward Petersen, July 2001 , 2001:2   [ADAM] , Modelling private consumption in ADAM, Henrik Hansen, N. Arne Dam og Henrik C. Olesen, August 2001 , 2001:1   [DREAM] , Fiscal Sustainability and Generational Burden Sharing in Denmark, Svend Erik Hougaard Jensen, Ulrik Nødgaard og Lars Haagen Pedersen, Maj 2001 ,  , 2000:5  [DREAM], V, elfærdseffekter ved skattesænkninger i DREAM, Anders Due Madsen, December 2000 ,  , 2000:4  [DREAM] , Har vi råd til velfærdsstaten ?, Lars Haagen Pedersen og Peter Trier, December 2000 ,  , 2000:3  [ADAM] , Current Price Identities in Macroeconomic Models, Asger Olsen and Peter Rørmose Jensen, August 2000 ,  , 2000:2  [ADAM] , General Perfect Aggregation of Industries in Input-Output Models, Asger Olsen, August 2000 ,  , 2000:1  [ADAM-DREAM] , Langsigtsmultiplikatorer i ADAM og DREAM - en sammenlignende analyse, Lars Haagen Pedersen og Martin Rasmussen, Maj 2000  ,   , 1999:4  [ADAM] , Løn-pris spiraler og crowding out i makroøkonometriske modeller, Carl-Johan Dalgaard og Martin Rasmussen, December 1999 ,  , 1999:3  [DREAM] , Earned Income Tax Credit in a Disaggregated Labor Market with Minimum Wage Contracts, Lars Haagen Pedersen & Peter Stephensen, November 1999, En kortere version af papiret er publiceret i Harrison, Hougaard Jensen, Pedersen & Rutherford (ed.): , Using Dynamic General Equilibrium Models for Policy Analysis, , North-Holland 2000,  , 1999:2 [ADAM] , Aggregation in Macroeconomic Models: An empirical Input-Output Approach, Asger Olsen, August 1999, Den endelige version er publiceret i , Economic Modelling, , 17:4 (2000) pp. 545-558 ,  , 1999:1  [ADAM] , Efterspørgslen efter produktionsfaktorer i Danmark, Thomas Thomsen, August 1999 ,  , 1998:6  [DREAM], A CGE Analysis of the Danish 1993 Tax Reform, Martin B. Knudsen, Lars Haagen Pedersen, Toke Ward Petersen, Peter Stephensen and Peter Trier, Oktober 1998,  , 1998:5  [DREAM] , Wage Formation and Minimum Wage Contracts, Lars Haagen Pedersen, Nina Smith (CLS) and Peter Stephensen, April 1998 ,  , 1998:4  [DREAM] , An introduction to CGE-modelling and an illustrative application to Eastern European Integration with the EU, Toke Ward Petersen, September 1997 ,  , 1998:3  [DREAM], I, Introduktion til CGE-modeller, Toke Ward Petersen, Oktober 1997, En kortere version er publiceret i Nationaløkonomisk Tidskrift 135 (1997) pp. 113-134,  , 1998:2  [ADAM] , Links between short- and long-run factor demand, Thomas Thomsen, December 1997, Den endelige version er publiceret i , Journal of Econometrics, , 97:1 (2000) pp. 1-23 ,  , 1998:1  [ADAM] , Faktorblokkens udviklingshistorie, 1991-1995, Thomas Thomsen, December 1997 ,  ,  

https://www.dst.dk/en/Statistik/ADAM/Dokumentation/AndetDok

Documentation of statistics: Transport by Ferries and Passenger Ships

Contact info, Short Term Statistics, Business Statistics , Heidi Sørensen , +45 24 79 86 81 , POT@dst.dk , Get documentation of statistics as pdf, Transport by Ferries and Passenger Ships 2025 Quarter 3 , Previous versions, Transport by Ferries and Passenger Ships 2025 Quarter 1, Transport by Ferries and Passenger Ships 2024 Quarter 1, Transport by Ferries and Passenger Ships 2023 Quarter 1, Transport by Ferries and Passenger Ships 2022 Quarter 1, Transport by Ferries and Passenger Ships 2021 Quarter 4, Transport by Ferries and Passenger Ships 2021 Quarter 3, Transport by Ferries and Passenger Ships 2021 Quarter 2, Transport by Ferries and Passenger Ships 2021 Quarter 1, Transport by Ferries and Passenger Ships 2020 Quarter 4, Transport by Ferries and Passenger Ships 2020 Quarter 3, Transport by Ferries and Passenger Ships 2020 Quarter 1, Transport by Ferries and Passenger Ships 2019 Quarter 4, Transport by Ferries and Passenger Ships 2019 Quarter 3, Transport by Ferries and Passenger Ships (Quaterly) 2019 Quarter 2, Transport by Ferries and Passenger Ships 2019 Quarter 1, Transport by Ferries and Passenger Ships 2018 Quarter 4, Transport by Ferries and Passenger Ships 2018 Quarter 3, Transport by Ferries and Passenger Ships 2018 Quarter 2, Transport by Ferries and Passenger Ships 2018 Quarter 1, Transport by Ferries and Passenger Ships 2017 Quarter 4, Transport by Ferries and Passenger Ships 2017 Quarter 3, Transport by Ferries and Passenger Ships 2017 Quarter 2, Transport by Ferries and Passenger Ships 2017 Quarter 1, Transport by Ferries and Passenger Ships 2016 Quarter 4, Transport by Ferries and Passenger Ships 2016 Quarter 3, Transport by Ferries and Passenger Ships 2016 Quarter 2, Transport by Ferries and Passenger Ships 2014 Quarter 3, The purpose of the statistics on transport by ferries and passenger ships is to describe the transport of passengers and goods by ferries and passenger ships on domestic routes and in traffic between Danish and foreign ports., The statistics are together with the other transport statistics used for analyses of the transport of passengers and goods. In the current form the statistics has been made since 1990., Statistical presentation, The statistics on transport by ferries and passenger ships are a monthly and annual statistics on the transport of passengers and goods by ferries and by passenger ships between Danish ports or between Danish and foreign ports. , The most important variables used in the statistics are: Trips, passengers, vehicles, goods on road vehicles and other goods., The statistics are published annually in , Nyt fra Danmarks Statistik, and quarterly in the Statbank., Read more about statistical presentation, Statistical processing, Data for the statistics are collected through an electronic questionnaire. The statistics cover all ferry lines and passenger ships with goods or passenger traffic in route to or from Denmark., The response rate is 100 percent., Data are checked both automatically and manually at the time of data collection and in case of large deviations or missing reports the reporting company is contacted again. For a few operators the total freight weight is imputed based on the number of freight vehicles reported. The validated micro-data is aggregated and then checked for major fluctuations., Read more about statistical processing, Relevance, The statistics are used regularly by new media, consultancies, business associations, port enterprises, shipping lines and other enterprises as well as Eurostat for e.g. analyses of maritime traffic, investments in infrastructure, analyses of the maritime transport sector, economic development and environment., Read more about relevance, Accuracy and reliability, The statistics is assessed to be reliable as the main series are based on financial information from the reporters (ticket sale). Furthermore the reporters are obliged to monitor the number of passengers and vehicles onboard., There is few and minor revisions and few errors are found in reported data., The smallest ferry lines are not included in the statistics. Usually this is lines to the smallest Danish islands or crossing fjords., In the main series uncertainty is largest for goods by goods motor vehicles that in some cases are estimated based on the number of goods motor vehicles. Additionally, the number of bicycles and caravans are uncertain., Read more about accuracy and reliability, Timeliness and punctuality, The quarterly statistics are published around 55 days after the end of the quarter. Since statistics for the first quarter 2012 the statistics has been published at the pre-announced date., Read more about timeliness and punctuality, Comparability, In its present form the statistics is consistent since 1990 for annual figures and 2000 for monthly figures. The statistics are processed according to common EU guidelines and therefore comparable with statistics from other countries published by Eurostat., Read more about comparability, Accessibility and clarity, These statistics are 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 the subject , Passengers and routes, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/transport-by-ferries-and-passenger-ships

Documentation of statistics

Documentation of statistics: Cultural Habits Survey

Contact info, Science, Technology and Culture, Business Statistics , Anders Yde Bentsen , +45 40 33 68 81 , AYB@dst.dk , Get documentation of statistics as pdf, Cultural Habits Survey 2025 , Previous versions, Cultural Habits Survey 2024, Cultural Habits Survey 2023, Cultural Habits Survey 2022, Cultural Habits Survey 2021, Cultural Habits Survey 2018-2021, Cultural Habits Survey 2018, Cultural Habits Survey 2012, Documents associated with the documentation, Spørgeskema for Kulturvaneundersøgelsen 2018-2023, faste spørgsmål (pdf) (in Danish only), Spørgeskema for Kulturvaneundersøgelsen 2024 (pdf) (in Danish only), Spørgeskema for Kulturvaneundersøgelsen 2025 (pdf) (in Danish only), The purpose of the Cultural Habits Survey is to document the cultural habits of the residents of Denmark. Culture is broadly defined, as the survey covers habits within the topics of culture, media and recreational activities, e.g. concerts, performing arts, cinema, literature, exercise, digital games and hobbies. The survey has been carried out regularly since 1964. Statistics Denmark has carried out the survey from 2018-2023 and in 2024-, while previous surveys have been carried out by the Ministry of Culture. The survey has been carried out with a new questionnaire since the first quarter of 2024, and is therefore not directly comparable with previous versions., Statistical presentation, The Cultural Habits Survey is an interview based quarterly survey among a random sample of Danish residents 16 years or older, which documents the consumption of cultural and recreational activities. The consumption of these activities may occur both in Denmark and abroad. The cultural consumption is grouped in various statistics by i.a. age, gender, education and degree of urbanisation. The current Cultural Habits Survey is ongoing and was first collected in the first quarter of 2024. The survey is communicated in Danish language press releases and in StatBank Denmark., Read more about statistical presentation, Statistical processing, The Cultural Habits Survey is an interview based quarterly survey among a random sample. The survey is carried out by both computer-assisted web interviews (CAWI) and computer-assisted telephone interviews (CATI). Approximately 4,800 responses are collected each quarter. The questionnaire is divided into a general part answered by all participants and four sub-parts, each answered by roughly a fourth of the respondents surveyed via CAWI. Using demographic information from Statistics Denmark's register of the Danish population, the respondents are weighted to compensate for non-response. Data is inspected for errors. A yearly dataset is compiled by the combination of the data for each quarter of the year., Read more about statistical processing, Relevance, The Cultural Habits Survey is carried out and developed in close cooperation with the Ministry of Culture and is the ninth in the series of the cultural habits of Danish residents carried out since 1964. The current survey accommodates a series of user needs, among which are more frequent statistics, the possibility for investigating geographic variation and the surveying of a broader definition of culture. The user needs have been identified through a thorough assessment of the Cultural Habits Survey 2018-2023. The assessment comprised the Ministry of Culture, researchers and users from public institutions., Read more about relevance, Accuracy and reliability, The Cultural Habits Survey is based on approximately 4,800 responses per quarter, which is a robust amount of data, contributing to lessening the sampling error. The error of the estimates are further reduced by the use of a mixed mode of data collection and multiple attempts at contacting each respondent. The error is however significantly greater for those questions which are part of the four sub-parts as these are each based on an amount of data roughly one fourth the size of the total amount., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published two months after the end of the reference period. The statistics are published without delay compared to scheduled publishing times., The statistic on membership for youth and outdoor activities organisations is published yearly in June, with data for the preceding year., Read more about timeliness and punctuality, Comparability, The survey has been carried out since 1964, but is in its current form only comparable with earlier versions to a limited degree. This is partly due to societal and technological changes and partly due to changes in the needs of users which has resulted in major revisions of the questionnaire in 2018 and 2024. The questionnaire is developed according to UN guidelines and is therefore partly comparable to statistics from other countries, among these the Nordic countries and EU countries., Read more about comparability, Accessibility and clarity, The statistics are published in a , Danish press release, . In the StatBank, the figures are published under , Cultural and recreational activities, . For more information, see the , topic page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/cultural-habits-survey

Documentation of statistics

Documentation of statistics: Research and development in the public sector

Contact info, Science, Technology and Culture, Business Statistics , Mille Wilhjelm Poulsen , +45 40 18 78 40 , MWP@dst.dk , Get documentation of statistics as pdf, Research and development in the public sector 2024 , Previous versions, Research and development in the public sector 2023, Research and development in the public sector 2022, Research and development in the public sector 2021, Research and development in the public sector 2020, Research and development in the public sector 2019, Research and development in the public sector 2018, Research and development in the public sector 2017, Research and development in the public sector 2016, Research and development in the public sector 2015, Statistics on Research and Development – Public sector 2014, Statistics on Research and Development – Public Sector 2013, Statistics on Research and Development – Public sector 2012, The purpose of the statistics on Research and Development in the public sector is to illustrate the extent of R&D activities carried out within the public sector. The statistics are used, among other things, to assess the share of GDP devoted to research and development. The survey is conducted according to the OECD guidelines for research and development (R&D) statistics, as set out in the Frascati Manual. The statistics have been produced since 1997, but are comparable in their current form from 2007 onwards., Statistical presentation, The statistics provide an annual account of R&D in the public sector, showing both expenditure (in millions of kroner) and personnel (in numbers and full-time equivalents). The data are distributed by main sectors, types of expenditure, scientific fields, and type of research., Read more about statistical presentation, Statistical processing, The statistics are based on questionnaires and are collected annually from approximately 650 public and private non-profit units, which together are assumed to carry out all significant R&D in the public sector. The reported data undergo extensive validation, focusing on a number of high-priority variables, particularly R&D expenditure and R&D full-time equivalents. Validation is performed at both the macro and micro level., Read more about statistical processing, Relevance, There is a general political objective of increasing the share of GDP, which is applied for research and development, and in the light of this objective, there is great interest in compiling statistics on research and development. The main users are Ministries, public authorities, business organisations, researchers, private business enterprises and the media. In addition, the European Commission (The statistical office Eurostat) and the OECD are important users. Data are available for purposes of research., Read more about relevance, Accuracy and reliability, They are based on a complete census, of the expected research-active institutions, of approximately 650 public institutions, with a response rate close to 100 percent. The large dataset undergoes extensive validation, and except for a single question, the extent of imputation for missing values is relatively limited. Imputation may, for example, involve inserting calculated values from other institutions’ reports in place of missing information., Read more about accuracy and reliability, Timeliness and punctuality, National release is done 1 year after the end of the reference period. It is the aim to publish preliminary figures 1 year after the end of the reference period. Final figures are published 1 year after the preliminary figures. Transmission of data to Eurostat follows rules laid down in the relevant legal act. , Read more about timeliness and punctuality, Comparability, Comparable figures are available for 1997–2006, when the statistics were compiled by the Centre for Research Analysis, and from 2007 onwards. In the 2007 statistics, some changes were made to the accounting principles compared with earlier compilations, and between 2006 and 2007 a number of structural changes affected a large number of research institutions. This means that the data in the new survey are only partially comparable with previous surveys., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Research and development, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/research-and-development-in-the-public-sector

Documentation of statistics

Documentation of statistics: Personal assets and Liabilities

Contact info, Labour Market, Social Statistics , Jarl Christian Quitzau , +45 23 42 35 03 , JAQ@dst.dk , Get documentation of statistics as pdf, Personal assets and Liabilities 2024 , Previous versions, Personal assets and Liabilities 2023, Personal assets and Liabilities 2022, Personal assets and Liabilities 2021, Personal assets and Liabilities 2020, Personal assets and Liabilities 2019, Personal assets and Liabilities 2018, Personal assets and Liabilities 2017, Assets and Liabilities 2016, Assets and Liabilities 2015, Assets and Liabilities 2014, Documents associated with the documentation, 2022-Revision af formuestatistikken_vs1.1 (pdf) (in Danish only), Værdiansættelse af unoterede aktier og fordeling på personer i 2022 (pdf) (in Danish only), Estimering af aldersopsparing (pdf) (in Danish only), New data on individual pension wealth growth (pdf), Fordeling af unoterede aktier 2023 (pdf) (in Danish only), Beskrivelse af formueloftet 2023 (pdf) (in Danish only), Effekt af overgang til midlertidigt datagrundlag om ejendomme fra 2023 (pdf) (in Danish only), Fordeling af unoterede aktier 2024 (pdf) (in Danish only), Databrud i ejendomsformuerne, 2024 (pdf) (in Danish only), The purpose of the Wealth and Debt statistics is to provide insights into the wealth and debt of individuals, families, and various population groups. The statistics were first created in the aftermath of the financial crisis in collaboration with Danmarks Nationalbank (the Danish Central Bank) and were intended, among other things, to analyze families' resilience to economic shocks. Additionally, the statistics are used in analyses of the pension system and to measure economic inequality. The statistics have been produced since 2014., Statistical presentation, The statistics produces annual data on the value of value of real estate, cars, financial assets, pension wealth and debts. There are also separate and more detailed publications on pension wealth. The statistics are register based and are based on data at the individual level. It is linked to other registers in order to do subdivisions on age, gender, municipality etc., Read more about statistical presentation, Statistical processing, Data is collected from multiple sources and undergoes statistical processing, including debt classification and market value assumptions for assets such as homes, cars, and unlisted shares. Registers are compiled using anonymized identifiers. In pension statistics, bonuses and reserves are allocated proportionally to pension funds, and anonymized contract numbers enable time-series analysis, except in cases of mergers and acquisitions., Read more about statistical processing, Relevance, These statistics are relevant for researchers, ministries, Economic think tanks, pension funds and the media. It is used for forecasts on the pension system and, analyses on the level of wealth in different strata, the level of prosperity and the level of economic inequality. The statistical data and results are also used in other statistical areas within Statistics Denmark, e.g. in national accounting and as a supplement to the income statistics. Data on pension wealth are also used for the macro economic Model ADAM., Read more about relevance, Accuracy and reliability, The quality of the financial data is high since most of the data is validated by the tax authorities. There is much larger uncertainty on the imputed market value of owned property, cars, unquoted stocks and the value of lifetime pensions. Data on assets that can not be linked to persons is not included. Data Wealth held abroad by Danes is likely lacking as well. For discretionary reasons the register is top-coded with a maximum wealth of DKK 2.11 bio. , Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published approximately 12 months after the end of the reference year. Publications are released on time without delays, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, Comparability over time varies depending on the wealth component. In the wealth and debt statistics, one must choose whether to use the 2020 series, which includes unlisted shares and debt subject to enforcement, or the 2014 series, which does not. In 2023–2025, there is a major data break due to the transition to new assessment systems, and the coverage of unlisted shares has gradually improved since they were included in the statistics from 2020. Apart from these breaks there is good consistency over time. Caution should be exercised when using the statistics for international comparisons., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under , Wealth and liabilities, and , Pension assets, . For further information, go to the , subject page, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/personal-assets-and-liabilities

Documentation of statistics