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Documentation of statistics: Indices of Average Earnings for the Private Sector (Discontinued)

Contact info, Personal Finances and Welfare , Get documentation of statistics as pdf, Indices of Average Earnings for the Private Sector 2019 , Previous versions, Indices of Average Earnings for the Private Sector 2018, Indices of Average Earnings for the Private Sector 2017, Indices of Average Earnings for the Private Sector 2016, Indices of Average Earnings for the Private Sector 2015, Indices of Average Earnings for the Private Sector 2014, The purpose of the index of average earnings is to indicate trends in earnings for different industries in the private sector exclusive of enterprises categorised as public administration or -services (state, regional or municipal). The index of average earnings was first published for the first quarter of 1994 under the name , the index of average earnings in the private sector, . Since then the index has been published based on the Danish Industrial Classification of 1996 (DB96), Danish Industrial Classification of 2003 (DB03) and since the third quarter of 2008 based on the Danish Industrial Classification of 2007 (DB07). Moreover, the index of average earnings replaced the index of hourly earnings for workers in manufacturing industry and the index of monthly earnings for salaried employees in manufacturing industry, which were discontinued at the end of 1997., Statistical presentation, The index of average earnings comprises all employees, salaried employees (white collar employee or officials) and wage-earners (blue collar workers) as well as apprentices and young people under 18 years employed in a business enterprise with 10 or more persons in the private sector. The entire private sector is covered by the indices, including e.g. employees in private schools and private hospitals. Still, the index does not include enterprises belonging to either the agriculture or fisheries industries. In accordance with the nomenclature DB07 (Danish Industrial Classification 2007), the the index is broken down by industry and since the third quarter of 2008 published at the most detailed level according to the 36-grouping in DB07. For a period between the first quarter of 2005 and the second quarter of 2008, the indices were only published at the 10-grouping level., Read more about statistical presentation, Statistical processing, Data are collected from the private enterprises and organisations that are included in the sample and cover the second month of the quarter in question. To start with, a rough search for errors is performed on the data. Then, the change in the average earnings per hour from the previous quarter is calculated for each enterprise. Only enterprises where data exists for both quarters are included in the computations. The average hourly wage per observations in the sample is then weighted to take account of all enterprises in a specific branch of economic activity in the population. A total figure for the average hourly wage and the rate of increase from the last quarter is then calculated for each branch of economic activity. After this the index point and the annual rate of increase is calculated for each branch. Finally the total index point and annual rate of increase is found as a total for all branches., Read more about statistical processing, Relevance, Private corporations and organisations in Denmark and abroad, and ministries and other public institutions are the most frequent users of the index. The index is especially used in relation to regulation of contracts. In addition to that, the index plays a vital part in the wage negotiations of employees in the public sector., Read more about relevance, Accuracy and reliability, The accuracy and reliability is mainly affected by two factors. First of all, the index is based on a sample, which in itself cause some uncertainty. Second of all, there is some uncertainty connected to the completeness in the collected data, which is often caused by errors in the way the system is generated for transmission of data. An example of this is a payroll system where the different wage compositions are not correctly linked or reported, and thus give an inaccurate picture of the development of wages. The problem with errors like these is that they tend to be difficult to discover. For example would reporting of a low and wrong value for irregular payments result in too high calculation of wage developments, as the irregular payments could not be separated from the wage component., Read more about accuracy and reliability, Timeliness and punctuality, The index of average earnings is published approximately 60 days after the end of the quarter in question. The punctuality of the publication is considered high and there has been no delays of any kind during the last years., Read more about timeliness and punctuality, Comparability, The index of average earnings for Corporations and Organizations, replace , the index of average earnings of the private sector, which was last published for the fourth quarter of 2013. The comparability of the two indices is considered to be high. The difference has to do with the new applied delimitations of the sectors, where some of the public owned enterprises, such as Danish Railways (DSB) and some of the municipal owned resource centers, now according to the new delimitations of the sectors belong to “the index of average earnings of Corporations and Organizations”. The new sector delimitations were applied in the indices going back to first quarter of 2013, where it caused a small data breach., Read more about comparability, Accessibility and clarity, These statistics are published in the Statbank under , Implicit index of average earnings, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/indices-of-average-earnings-for-the-private-sector--discontinued-

Documentation of statistics

Documentation of statistics: Indices of Earnings for the Public Sector (Discontinued)

Contact info, Personal Finances and Welfare , Get documentation of statistics as pdf, Indices of Earnings for the Public Sector 2019 , Previous versions, Indices of Earnings for the Public Sector 2018, Indices of Earnings for the Public Sector 2017, Indices of Earnings for the Public Sector 2016, Indices of Earnings for the Public Sector 2015, Indices of Earnings for the Public Sector 2014, The purpose of the index is to indicate trends in wages paid in the public sector (central and local governments) analyzed by main sectors of economic activity. The index covers more or less all employees in the public sector, including salaried employees, apprentices and young employees under the age 18. Data are mainly extracted from the public pay transfer systems and refer to the second month in the quarter of interest. The published index is broken down by main sectors of economic activity (38-grouping of NACE rev. 2), and indicate trends in relation to the basic quarter (first quarter of 2005) and in relation to the same quarter of the previous year. Since the release of the third quarter of 2008 there has been a change in the base period of the index, which is now the first quarter of 2005., Statistical presentation, The index is based on information on wages obtained from more or less all employees in the public sector. Data are mainly extracted from the public pay transfer systems and refer to the second month in the quarter of interest. The published index is broken down by main sectors of economic activity (38-grouping of NACE rev. 2), and indicate trends in relation to the basic quarter (first quarter of 2005) and in relation to the same quarter of the previous year. , From the first quarter of 2013 a new delimitation regarding the categorizing of sectors (state, regional, municipal or private) came into force. The new sector delimitation now follows the same principles as the one applied for the national accounts. The previous delimitation of sectors is available until the fourth quarter of 2013. , This documentation of statistics relates to the index of average earnings with the base period 1. quarter of 2005=100. The documentation of statistics with the base period 1. quarter of 1995 is attached as an annex., Read more about statistical presentation, Statistical processing, Data are collected for more or less all persons employed in the public sector in Denmark and refer to the second month of the quarter in interest. Before production of the index is started, the data are roughly searched for errors. But there are also performed search for errors later in the process, e.g. by looking at the rate of increase in the average wages for each company or organisation. Each employment is given a weight after the share of hours worked in relation to a full-timer’s normal hours, which is used when adding observations to calculate the rate of increase for an enterprise or branch of economic activity., Read more about statistical processing, Relevance, Private enterprises and organizations in Denmark and abroad, and ministries and other public institutions are the most frequent users of the index. The index is especially used in relation to regulation of contracts. In addition to that, the index plays a vital part in the wage negotiations of employees in the public sector., Read more about relevance, Accuracy and reliability, Since the index is based on information on wages obtained from more or less all publicly employed persons through public pay transfer systems, the accuracy and reliability of the index is considered to be high. At the same time, there are some small uncertainties regarding the index which it is a good idea to be aware of when applying the index., Read more about accuracy and reliability, Timeliness and punctuality, The index of average earnings is published approximately 45 days after the end of the quarter in question. The punctuality of the publication is considered high and there has been no delays of any kind during the last years., Read more about timeliness and punctuality, Comparability, Improvements in the index are continuously being made. If major errors have been rectified, the index has, as far as possible, been revised back to the first quarter of 1995 when calculations of the index began. From the first quarter of 2013 a new delimitation of sectors (state, regional, municipal or private) has been applied. Hence causing a breach in the data between the fourth quarter of 2012 and the first quarter of 2013. , The index of average earnings in the public sector, is comparable and in many ways similar to the , index of average earnings for Corporations and Organisations, . Internationally, the index is to some degree comparable to wage indices of the public sector in other countries., Read more about comparability, Accessibility and clarity, These statistics are published in the Statbank under , Implicit index of average earnings, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/indices-of-earnings-for-the-public-sector--discontinued-

Documentation of statistics

Documentation of statistics: Social benefits for senior citizens

Contact info, Personal Finances and Welfare, Social Statistics , Marie Borring Klitgaard , +45 21 55 83 71 , MGA@dst.dk , Get documentation of statistics as pdf, Social benefits for senior citizens 2025 , Previous versions, Social benefits for senior citizens 2024, Social benefits for senior citizens 2023, Social benefits for senior citizens 2022, Social benefits for senior citizens 2021, Social benefits for senior citizens 2020, Elderly - Indicators 2019, Elderly - Indicators 2018, Elderly - Indicators 2017, Elderly - Indicators 2016, Elderly - Indicators 2015, Elderly - Indicators 2014, Elderly - Indicators 2013, Documents associated with the documentation, Kommentarer til 2024 - korte udgaver (xlsx) (in Danish only), Kommentarer til 2025 - korte udgaver (xlsx) (in Danish only), The purpose of these statistics is to display the quality level of municipal services in the elderly care. The statistics are a part of a cross-public cooperation, intended to ensure coherent documentation of important areas of municipal service, as well as to increase the comparability of the services provided in the different municipalities. The statistics are used to determine impact targets, frameworks and results requirements for key management initiatives and are comparable from 2008 onwards. Statistics Denmark is responsible for the composition and publication of the statistics., Statistical presentation, The statistic for 2025 covers data from the first 6 months of 2025. The statistic is an annual survey including a number of national impact- and background indicators which document and describe the quality of the municipal effort at the elderly area. The indicators consist of referral and provided home care, home nursing, nursing homes, exercise services, rehabilitation and preventative home visits. Primarily, the indicators are targeted at the elderly area, however home care, exercise services, home nursing as well as nursing homes also include data for citizens under 67 years., Read more about statistical presentation, Statistical processing, Before publishing data from the municipalities' EOJ system (electronic care journal), tables and figures are developed, which all municipalities are asked to approve. After the approval, Statistics Denmark detects for data errors as missing numbers, abnormal values and etc., Read more about statistical processing, Relevance, The authorities and public institutions and the population use the indicators for analysis, research, debate, etc. The focus is to ensure more valid documentation at the elderly area. This is achieved by retrieving the information directly from the municipalities' care systems (EOJ), which is constantly updated as a part of the municipalities' case management., Read more about relevance, Accuracy and reliability, The municipalities receive control tables, which they are asked to approve. Only approved information is included in the statistics. In the absence of approvals, previous years' information is included in the national totals and averages. For the publication for the first 6 months 2025, between 97 and 98 municipalities are included, depending on the indicator. Lack of approval may be due to the municipality's registration practices, which determine which data is reported, and system or supplier changes, where the reported data may be flawed. There are varying registration practices between municipalities in several areas, which can lead to distortions., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published as pre-advertised. The statistics are released approximately 6 months after the reference period has ended. , Read more about timeliness and punctuality, Comparability, The statistics are generally comparable over time, but there are minor data breaks. The municipalities' change of EOJ provider every five years can affect certain indicators. As of October 1, 2023, new reporting requirements for food service and supplier types resulted in a data break in the statistics on designated home care. Therefore, the figures for 2023 should be compared with previous years with reservations. For hospital usage, there has been no adjustment for the severity of diseases, which affects the comparability between municipalities., Read more about comparability, Accessibility and clarity, The statistics are published in a , Danish press release, . The figures are published in the StatBank under the subject , Social benefits for senior citizens, . See more on the subject page for the , Social benefits for senior citizens, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/social-benefits-for-senior-citizens

Documentation of statistics

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

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: Nights spent on camp sites

Contact info, Short Term Statistics, Business Statistics , Karen Keller , +45 21 19 85 61 , kke@dst.dk , Get documentation of statistics as pdf, Nights spent on camp sites 2025 , Previous versions, Nights spent on camp sites 2024, Nights spent on camp sites 2023, Nights spent on camp sites 2022, Nights spent on camp sites 2021, Nights spent on camp sites 2020, Nights spent on camp sites 2019, Nights spent on camp sites 2018, Nights spent on camp sites 2017, These statistics describe the capacity and occupancy at Danish campsites. The statistics are used by i.e. EU, tourism organizations and municipalities in order to analyze the development in camping tourism. The survey has been compiled since 1971, but in its current form comparable from 1992 and onwards. , Statistical presentation, These statistics are a monthly summary of occupancy and capacity in Danish campsites with a minimum of 75 camping units. The statistics are broken down by nationality of the guests, permanent leased pitches and geography by NUTS 2 level. Furthermore there is a annual summary of occupancy and capacity in Danish campsites with 10-74 camping units. , Read more about statistical presentation, Statistical processing, Data for the statistics are collected monthly from Danish campsites with a minimum of 75 camping units and yearly from Danish campsites with 10-74 camping units using an online questionnaire on Virk.dk, or by using a system-to-system solution where the campsites booking system automatically sends data to Statistics Denmark. Collected data are validated on micro-level during the data collection and again on macro-level when aggregated. The validated data are then imputed with missing values and afterwards aggregated into geographical and nationality totals. , Read more about statistical processing, Relevance, The statistics are for example relevant for accommodation businesses, Eurostat, ministries and business and tourism organizations for forecasts, analysis and planning. , Read more about relevance, Accuracy and reliability, The monthly statistic only covers campsites with at least 75 camping units. The annual statistics also cover campsites with 10-74 camping units. A possible source of error can be that the respondents have difficulties distinguishing between the concepts of nights spent and arrivals. Another possible source of error may be the fact that the reported data is in many cases based on estimations by the respondents. Missing answers are imputed which may lead to revisions of published data. , Read more about accuracy and reliability, Timeliness and punctuality, The monthly statistics for campsites with a minimum of 75 camping units are published approx. 40 days after the end of the reference period. Publications are released on time, as stated in the release calendar. The annual statistics for the final data and for campsites with 10-74 camping units are published approx. 100 days after the end of the reference year., Read more about timeliness and punctuality, Comparability, Statistics Denmark includes nights from permanent leased pitches, which can cause an overestimation compared to other European camping statistics which do not include data from nights spent on permanent leased pitches. The statistical organisation of EU "Eurostat" does not include nights spent on permanent leased pitches when they publish data from countries in EU. From 2013, the number of nights on permanent leased pitches is based on factors of average lead times on camp sites. This change may result in a lack of comparability, but it is not expected to be significant. The number of nationalities has expanded from 13 to 51 nationality groups. This can lead to a lack of consistency when comparing data over time. , Read more about comparability, Accessibility and clarity, The statistics are published in , News from Statistics Denmark, . Data are published in statbank at , Camping sites, and , All types of overnight accommodation, and in an annual publication with all types of overnight accommodation. For more information about the statistics look at subject page. (https://www.dst.dk/da/Statistik/emner/erhvervslivets-sektorer/turisme/campingpladser)., Statistics on a municipality level or for a province can be found at , VisitDenmark, . If you wish to combine statistics of tourism with other types of variables or combine variables in a different way please contact , DST Consulting, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/nights-spent-on-camp-sites

Documentation of statistics

Documentation of statistics: Nights spent at hotels, holiday resorts and youth hostels

Contact info, Short Term Statistics, Business Statistics , Karen Keller , +45 21 19 85 61 , kke@dst.dk , Get documentation of statistics as pdf, Nights spent at hotels, holiday resorts and youth hostels 2025 , Previous versions, Nights spent at hotels, holiday resorts and youth hostels 2024, Nights spent at hotels, holiday resorts and youth hostels 2023, Nights spent at hotels, holiday resorts and youth hostels 2022, Nights spent at hotels, holiday resorts and youth hostels 2021, Nights spent at hotels, holiday resorts and youth hostels 2020, Nights spent at hotels, holiday resorts and youth hostels 2019, Nights spent at hotels, holiday resorts and youth hostels 2018, Nights spent at hotels, holiday resorts and youth hostels 2017, The purpose of the statistics "Nights spent at hotels, holiday centers and hostels" is to describe the occupancy and capacity of Danish hotels, holiday centers and hostels. The survey is used by i.e. EU, business and tourism organizations and municipalities in order to analyze the development in tourism. The survey has been compiled since 1969, but is only comparable from 1992 and onwards. , Statistical presentation, The accommodation survey "Nights spent at hotels, holiday centers and hostels" is a monthly summary on occupancy and capacity in Danish hotels, holiday centers and hostels with a minimum capacity of 40 bed places. The accommodation survey is broken down by capacity and geography of the establishment as well as the purpose and country of residence of the guest. Furthermore there is an annual census on occupancy and capacity for hotels, holiday centers and hostels with 10-39 bed places., Read more about statistical presentation, Statistical processing, Data for the statistics are collected monthly from Danish hotels, holiday resorts, hostels etc. with a minimum of 40 bed places and yearly from Danish hotels, holiday resorts, hostels etc. with 10-39 bed places using an online questionnaire or by using a system-to-system solution where the accommodations booking system automatically sends data to Statistics Denmark. Collected data are validated on micro-level during the data collection and again on macro-level when aggregated. The validated data are then imputed with missing values and afterwards aggregated into geographical and nationality totals. , Read more about statistical processing, Relevance, The accommodation statistics are relevant for accommodation businesses, Eurostat, ministries and business and tourism organizations for forecasts, analysis and planning. The accommodation statistics are under constant review and the user needs are rapidly changing with the emergence of peer-to-peer platforms such as AirBnB. , Read more about relevance, Accuracy and reliability, The monthly statistic only cover hotels, holiday resorts and hostels etc. with at least 40 bed places. The annual statistics also cover hotels, holiday resorts and hostels etc. with 10-39 bed places. A possible source of error can be that the respondents have difficulties distinguishing between the concepts of nights spent and arrivals. Missing answers are imputed which may lead to revisions of published data. , Read more about accuracy and reliability, Timeliness and punctuality, The monthly statistics for hotels, holiday centers and hostels etc. with a minimum of 40 bed places are published monthly approx. 40 days after the end of the reference month. The statistics is published without delay according to the planned publication tables. The final statistics are published annually together with the statistics for Hotels, holiday centers and hostels etc. with 10-39 bed places. The Annual statistics are published approx. 100 days after the end of the reference year., Read more about timeliness and punctuality, Comparability, The accommodation statistics is comparable with the other EU-statistics on tourism. The breakdown into nationalities has expanded from 13 to 51 since 1996 and this can weaken the comparability when using time series. , Read more about comparability, Accessibility and clarity, The statistics are published in , Nyt fra Danmarks Statistik, . Data are published in statbank at , Hotels, holiday centres and hostels, og , All types of overnight accommodation, and in an annual publication with all types of overnight accommodation. For more information about the statistics look at the , subject page, ., Statistics on a municipality level or for a province can be found at VisitDenmark. If you wish to combine statistics of tourism with other types of variables or combine variables in a different way please contact DST Consulting., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/nights-spent-at-hotels--holiday-resorts-and-youth-hostels

Documentation of statistics

Documentation of statistics: Holiday houses

Contact info, Short Term Statistics, Business Statistics , Karen Keller , +45 21 19 85 61 , kke@dst.dk , Get documentation of statistics as pdf, Holiday houses 2025 , Previous versions, Holiday dwellings 2024, Holiday houses 2022, Holiday dwellings 2020, Holiday dwellings 2019, Holiday dwellings 2018, Holiday dwellings 2017, The purpose of the statistic Holiday houses is to visualize the capacity and rental activity for Danish holiday houses through from rental agencies. Users of the statistics is e.g. business and tourism organisations as well as municipalities and regions to analyse the development in tourism. The statistics have been compiled since 1968 in various forms. Figures for the first years are available in printed editions of the Statistical Yearbook. In its current form, the statistics are comparable since 1992. Figures on nights spend at holiday houses or holiday apartments complements other tourism statistics on nights spend e.g. hotels, camping., Statistical presentation, The statistics about holiday houses are a monthly and annual calculation of Danish holiday houses that are rented out through rental agencies. The statistics are divided into nationalities of the guests, as well as geographically by regions and parts of the country. In addition, there is an annual assessment of the capacity of vacation houses for rental. Numbers of Municipal distribution is prepared in collaboration with VisitDenmark. , Read more about statistical presentation, Statistical processing, Data for this statistics is collected monthly for reporting that covers approx. 95 pct. of the population, to which is added an enumeration of the annual reports from the previous year, so that the entire population of holiday house rental with a minimum of 25 houses available is covered. The monthly statistics shows temporary data for the holiday house rental. When the reference year is over, the calculated imputed values are replaced with the final data for the year. The annual statistics with the final data include reporting from every holiday house rental with a minimum of 25 houses available for renting., Data for the annual statistics is collected via an upload solution for the rental agencies that only report annually or via an electronic questionnaire for the rental agencies that report monthly. The collected data undergoes micro-level debugging during the actual collection and at the macro-level when the data is aggregated. , Read more about statistical processing, Relevance, The statistics are relevant for e.g. the companies, industry associations, municipalities and regions as well as business and tourism organizations as a basis for forecasts, analyses and planning purposes., Read more about relevance, Accuracy and reliability, The variables of the statistics associates more or less uncertainty. Number of contracts, number of houses available and rented house-weeks are regarded as the most certain variables. The variable Numbers of nights is regarded as more uncertain, because in some cases they are based on reported estimates. , Read more about accuracy and reliability, Timeliness and punctuality, The monthly statistics for holiday house rental is published approx. 40 days after the end of the reference month. The statistics are published without delays in relation to planned publication times. The annual statement for holiday house rental is published together with the final annual figures approx. 100 days after the end of the reference year. , Read more about timeliness and punctuality, Comparability, The statistics date back to 1986 and have undergone changes over time. From 1986-1990, the statistics only covered holiday house rental in the high season. From 1990, the statistics covered an operating year, i.e. early October to and including the end of September. From 1998, the annual statistics are based on the calendar year. In 2011, the overnight figures for 2010 were adjusted upwards by 647,000 as a result of revised information from some rental agencies. As a consequence, the number of overnight stays in 2010 and 2011 and onwards is not immediately comparable with the number of overnight stays in previous years. From 2012, the number of available houses for rent was removed from the monthly statistics. Instead, the figure is calculated once a year with the number of available houses for rent per year. May 1. in the reference year. , Read more about comparability, Accessibility and clarity, The statistics are published monthly and annually in , Nyt from Statistics Denmark, . In the Statistics Bank, the figures are published under the subject , Holiday houses, and , Total types of accommodation, . See more on the statistics , topic page, . Municipality-distributed statistics on holiday rental are financed by VisitDenmark and are freely available on their , website, ., If you want to combine statistics on holiday home rentals with other variables or put them together in another way, you can contact DST Consulting to clarify options and request a quote. , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/holiday-houses

Documentation of statistics

Documentation of statistics: Maritime Transport over Danish Ports

Contact info, Short Term Statistics, Business Statistics , Heidi Sørensen , +45 24 79 86 81 , HSN@dst.dk , Get documentation of statistics as pdf, Maritime Transport over Danish Ports 2025 Quarter 1 , Previous versions, Maritime Transport over Danish Ports 2024 Quarter 1, Maritime Transport over Danish Ports 2023 Quarter 1, Maritime Transport over Danish Ports 2022 Quarter 1, Maritime Transport over Danish Ports 2021 Quarter 4, Maritime Transport over Danish Ports 2021 Quarter 3, Maritime Transport over Danish Ports 2021 Quarter 2, Maritime Transport over Danish Ports 2021 Quarter 1, Maritime Transport over Danish Ports 2020 Quarter 4, Maritime Transport over Danish Ports 2020 Quarter 3, Maritime Transport over Danish Ports 2020 Quarter 2, Maritime Transport over Danish Ports 2020 Quarter 1, Maritime Transport over Danish Ports 2019 Quarter 4, Maritime Transport over Danish Ports 2019 Quarter 3, Maritime Transport over Danish Ports (Quaterly) 2019 Quarter 2, Maritime Transport over Danish Ports 2019 Quarter 1, Maritime Transport over Danish Ports 2018 Quarter 4, Maritime Transport over Danish Ports 2018 Quarter 3, Maritime Transport over Danish Ports 2018 Quarter 2, Maritime Transport over Danish Ports 2018 Quarter 1, Maritime Transport over Danish Ports 2017 Quarter 4, Maritime Transport over Danish Ports 2017 Quarter 3, Maritime Transport over Danish Ports 2017 Quarter 2, Maritime Transport over Danish Ports 2017 Quarter 1, Maritime Transport over Danish Ports 2016 Quarter 4, Maritime Transport over Danish Ports 2016 Quarter 3, Maritime Transport over Danish Ports 2016 Quarter 2, Maritime Transport over Danish Ports 2015 Quarter 4, Maritime Transport over Danish Ports 2015 Quarter 3, Maritime Transport over Danish Ports 2014 Quarter 3, The purpose of statistics on maritime transport over Danish ports is to describe the volume of and the development in ship traffic to and from Danish ports as well as data on port infrastructure. Also data on accidents on sea on board Danish vessels and in Danish sea territory are published., The statistics have been compiled in the present form since 1997. Maritime statistics have been produced since 1834 and published annually from about 1900. In the period from 1991 to 1996, Statistics Denmark compiled only summary statistics on the throughput of ports., Statistical presentation, The main variables in the statistics are: Calls at port, type of ship, size of ship, flag state, port of loading/unloading, weight of goods and type of goods and passengers., The statistics are based on two separate data collections: Maritime traffic on larger Danish ports (quarterly) and Maritime traffic on minor Danish ports (annually). It is supplemented with data from Ferries and Passenger ships (quarterly)., Annual data on accidents at sea are collected from the Danish Maritime Authority., Data on investments in ports are received from the National Accounts in Statistics Denmark., Read more about statistical presentation, Statistical processing, Annual statistics cover all Danish ports handling goods or passengers. Quarterly statistics cover only major ports., The statistics are collected through a spreadsheet solution via the data collection portal, http://www.Virk.dk. Response rate is 100 percent., Data are validated for the correct use of codes and classifications and for internal consistency within each report. Furthermore the development over time is validated at both micro and macro level., Read more about statistical processing, Relevance, The statistics are used by the ports themselves, Eurostat and other parts of the EU-commission, ministries, organisations, researchers and in general to monitor the goods transport activity in Danish ports and to develop transport statistics., Read more about relevance, Accuracy and reliability, Maritime statistics are based on censuses among all goods handling ports. The majority of data stems from the quarterly reports from all major ports. The data from the remaining minor ports are summarised annual data. On the main variables there is full coverage and accurate within 3 percent. Minor revision occur without systematic bias., Read more about accuracy and reliability, Timeliness and punctuality, Statistics are usually published around 70 days after the end of a quarter. Annual statistics are published around 130 days after the end of reference year. It is always published at the preannounced time., Read more about timeliness and punctuality, Comparability, The statistics are consistent from 2000 and onwards and directly comparable to similar statistics from other EU and EFTA member states., Read more about comparability, Accessibility and clarity, Maritime statistics are published annually in Nyt fra Danmarks Statistik (Statistical News)., Quarterly and annually data can be found in , http://www.Statbank.dk, ., Annual tables are published in Statistical Yearbook until 2017 and Statistical 10-year Review., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/maritime-transport-over-danish-ports

Documentation of statistics