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      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: National Accounts: Input-Output and Supply-Use

      Contact info, National Accounts, Climate and Environment, Economic Statistics , Peter Rørmose Jensen , +45 40 13 51 26 , PRJ@dst.dk , Get documentation of statistics as pdf, National Accounts Input-Output and Supply-Use 2022 , Previous versions, Input-Output Tables 2020, Input-Output Tables 2019, Input-Output Tables 2018, Input-Output Tables 2017, Input-Output Tables 2016, Input-Output Tables 2015, Input-Output Tables 2011, Supply and use tables are the cornerstone of the Danish national accounts. Here, data for the circulation of goods and services, between Denmark and abroad, enterprises and final consumption are organized in a way that enables full balancing. A number of national accounts variables, including GDP, are published from here. The tables are used to compile input-output tables, which detail the relationships between production, imports and uses in the economy. Conversion to an input-output model enables calculations of multiplier effects, which are indirect relationships in the economy., Statistical presentation, Supply‑use and input‑output tables describe how goods and services are produced, imported and used in the economy. They balance supply and demand and form the basis for GDP calculations. The system covers about 2,350 products and 117 industries and provides detailed breakdowns of consumption, investment and exports. Input‑output tables enable analysis of direct and indirect economic effects and support modelling and environmental‑economic studies., Read more about statistical presentation, Statistical processing, The supply and use tables are compiled from a wide range of sources that have been collected by Statistics Denmark, including accounting statistics and foreign trade statistics. When source data are inserted into the framework, extensive validation, error correction and adaptation to the national accounts definitions are carried out. Data are reconciled to full consistency using both automatic and manual methods. Input-output tables are compiled on the basis of the supply and use tables based on international guidelines. Upon receipt, Eurostat thoroughly checks the data again., Read more about statistical processing, Relevance, Supply‑use tables are mainly used by Statistics Denmark to calculate GDP and other key indicators and to construct input‑output tables. A few external users access them via Research Services, but the most detailed tables are not published due to confidentiality. Input‑output tables support detailed analyses of economic structures, policy impacts and environmental effects and are central to models such as ADAM, MAKRO and Green Reform. Data comply with ENS2010., Read more about relevance, Accuracy and reliability, Supply, use and input-output tables are based on extensive primary data that are checked for errors and reconciled to ensure high precision and consistency, especially in the GDP calculation. Provisional tables are less reliable due to incomplete sources. The necessary central model assumption in compiling input-output tables may lead to some minor over- and under-estimations. Quality is ensured through ongoing checks, audits and compliance with international standards., Read more about accuracy and reliability, Timeliness and punctuality, The input-output tables are released once every year at the same time as the final national accounts. The time of release is 2.5 years after the end of the reference year., Read more about timeliness and punctuality, Comparability, In an international perspective the comparability between Danish and foreign input-output tables is generally good, but not quite as good as in the case of national accounts itself. This is due to the fact that there is an important assumption to be made and this assumption may vary between countries. However, within the framework of the ESA2010 manual it is tried to secure comparability between EU-countries., Read more about comparability, Accessibility and clarity, National accounts and input-output data is disseminated in the , Statbank, and the , input-output subject page, where data can be downloaded in various file formats. Data that are transmitted to Eurostat can be found , here, Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/national-accounts--input-output-and-supply-use

      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 2026 , Previous versions, Nights spent at hotels, holiday resorts and youth hostels 2025, 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: 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 2026 , Previous versions, Nights spent on camp sites 2025, 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: Retail Trade Index

      Contact info, Short Term Statistics, Business Statistics , Nina Thøgersen , +45 21 20 32 67 , NIT@dst.dk , Get documentation of statistics as pdf, Retail Trade Index 2026 , Previous versions, Retail Trade Index 2025, Retail Trade Index 2024, Retail Trade Index 2021, Retail Trade Index 2020, Retail Trade Index 2019, Retail Trade Index 2018, Retail Trade Index 2017, Retail Trade Index 2016, Retail Trade Index 2015, Retail Trade Index 2014, The Retail Trade Index shows the development in turnover within the retail trade sector. The statistics is published monthly and is primarily used as short term indicator for private consumption as well as the general business cycle movement., Statistical presentation, Retail trade indices are published for 33 industries. Value and volume indices are produced. The volume index is made for the commodity groups and special industry aggregates for Eurostat. The statistics are based on survey data from all large retail trade enterprises and a sample of the remaining retail trade enterprises, which are requested to submit information about their turnover each month. Seasonal adjustment is performed of the industries and the total., Read more about statistical presentation, Statistical processing, The survey is based on a sample of Danish retail trade enterprises. The sample includes approximately 2,200 enterprises, and at the time of the first publication, the figures for a month are based on responses from approximately 1.800 of these enterprises for the initial publication. , The sample consist of 33 subgroups and enterprises are sampled based on their share of the yearly turnover for the given subgroup. The companies are ranked from largest to smallest and the companies, whose rank constitutes the bottom 10 pct. of turnover for their subgroup when summed, are never selected to participate. The companies whose rank lies between 11 and 49 pct. of the subgroup’s yearly summed turnover, are randomly selected. Lastly, the larger firms whose turnover altogether lies in the top 50 pct. of the yearly turnover for their subgroup are always included in the sample. The companies are selected based on VAT-declarations to the Danish tax administration. , Read more about statistical processing, Relevance, Many users who monitor the current business trends take an interest in the published statistics of retail trade. The demand for the statistics is broadly based in trade associations, the bank and finance sector, politicians, public and private institutions, researchers, enterprises, news media and Eurostat. The statistics provide input to the quarterly national accounts statistics and to Eurostat's pan-European statistics. The users view the retail trade index as an important short term indicator, and it often gets a lot of attention in the media and amongst other professional users. , Read more about relevance, Accuracy and reliability, The overall uncertainty of the total retail trade index is estimated to be less than 1 per cent. The accuracy of the monthly growth rate is generally very high. For the total index, the uncertainty is estimated to be maximum 0.2 percentage points, while it can be a little higher on commodity group level., Read more about accuracy and reliability, Timeliness and punctuality, Indices on the main industry groups are published already 22-28 days after the end of the month. This is rather quick for statistics based on a survey such as this. One month later the indices on the most detailed industry level are published. The punctuality is very high with delays happening very rarely. , Read more about timeliness and punctuality, Comparability, These statistics have been compiled since 1940, but they are not suited for long term time series analysis because of structural changes in the retail trade sector. The sample design and the calculation methods have been adjusted several times, last time in January 2026, where the time series back to 2015 where recalculated using new methods. , Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , Retail Trade Index, . The Retail Trade Index also has a , subject page, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/retail-trade-index

      Documentation of statistics

      Documentation of statistics: International Trade in Goods

      Contact info, External Economy, Economic Statistics , Stefan Gottschalck Anbro , +45 51 60 58 46 , SFB@dst.dk , Get documentation of statistics as pdf, International Trade in Goods 2025 , Previous versions, International Trade in Goods 2024, International Trade in Goods 2023, International Trade in Goods 2022, International Trade in Goods 2021, International Trade in Goods 2020, International Trade in Goods 2019, International Trade in Goods 2018, International Trade in Goods 2017, International Trade in Goods 2016, International Trade in Goods 2015, International Trade in Goods 2014, Documents associated with the documentation, Omlægning af tabeller om betalingsbalance og udenrigshandel i statistikbanken den 10. juni 2024 (pdf) (in Danish only), The statistics shows the development in Denmark's external trade in goods at a detailed level (imports and exports) by country and type of commodity. The statistics have been compiled regularly since 1838 covering 1836 and onwards., Statistical presentation, The statistics show Denmark's imports and exports of goods from/to all countries in the world distributed by about 9,300 different commodity codes. The statistics do not cover the External trade of the Faroe Islands and Greenland., Read more about statistical presentation, Statistical processing, Trade data is collected on monthly basis using the various data sources. The collected data are validated for logical errors and completeness and a credibility check of the reported data is carried out., The collected data are used to compile the trade figures and full coverage of trade is ensured by estimation for missing. There is thus full coverage of International Trade in Goods in the disseminated statistics. , In connection with the release of trade figures some time series are seasonal adjusted and furthermore indices are calculated., Read more about statistical processing, Relevance, There is great interest in the disseminated statistics of External Trade in Goods among users who monitor the Danish economy. The statistics are demanded widely by trade and industry organisations, the bank and finance sector, politicians, public and private institutions, researchers, enterprises, news media, embassies and international organisations. , The statistics is also used for compilation of National Accounts and Balance of Payments Statistics. Furthermore, Eurostat use the statistics to make joint EU trade statistics., The users view the External Trade in Goods Statistics as an important short term indicator, and it often gets a lot of attention in the media and amongst professional users., Read more about relevance, Accuracy and reliability, The reliability of the final statistics at aggregated level is relatively high. In Extrastat, the reliability at detailed commodity/country levels is also high, while the reliability is comparatively lower in Intrastat due to the margins of uncertainty involved in estimating trade by enterprises exempted from reporting data., However, the first publications of the external figures are subject to some uncertainty, as a relatively high number of errounous data reports cannot be included at the time of publication. Compensation for this is made by estimation and a later correction. The reliability of figures for a given month is greatly increased by later publications of statistics. Similarly, the highest reliability is achieved at aggregated level., Read more about accuracy and reliability, Timeliness and punctuality, Aggregated statistics for selected countries and country groups and for aggregated commodity groups are published monthly 40 days after the end of the reference period. Detailed statistics are published 70 days after the end of the reference period., The statistics are usually published without delay in relation to the scheduled date, which is announced at least 3 months in advance on Statistics Denmark's website, Read more about timeliness and punctuality, Comparability, At overall level, the statistics are comparable across time and with statistics from other countries., Read more about comparability, Accessibility and clarity, These statistics are published monthly 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 , Imports and exports in detail, . For further information, go to the , subject page, . , Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/international-trade-in-goods

      Documentation of statistics

      Documentation of statistics: The Population

      Contact info, Population and Education , Dorthe Larsen , +45 23 49 83 26 , DLA@dst.dk , Get documentation of statistics as pdf, The Population 2024 , Previous versions, The Population 2020, The Population 2019, The Population 2017, The Population 2016, The Population 2014, The purpose of the population statistics is to focus on the size, composition and development of the population living in Denmark. The statistics create a basis for a number of analyses on demography and society and are used as a basis for planning tasks on a national, regional and municipal level. In their basic form, the statistics have been compiled since 1769 but have undergone a series of changes as society developed and legislation followed. Most of the present table series in Statbank Denmark comprise data from 2007 and forward, while a few of these go back further., Statistical presentation, The population statistics are usually a quarterly aggregation of the population living in Denmark broken down by e.g. sex, age, ancestry, marital status and municipality of residence. In connection with COVID-19, however, the number of deceased persons was aggregated on a weekly basis broken down by date of death, age bracket and province. The population statistics show the population in figures at the reference date in terms of persons, households and families. The statistics also show changes in the population, such as births, deaths and migrations etc., in the period between the two reference dates. Similarly, the statistics contain information about fertility, life expectancy and divorce rate. , Read more about statistical presentation, Statistical processing, Data for the statistics is collected on a daily basis from the Civil Registration System (CPR) by means of a system-to-system solution. The civil registration number and the updating of residence information and marital status information etc. is required for a vast number of public services, which serves as continuous validation of the content of the register. The number of immigrants, descendants, households, families, marriages and divorces is assessed on the basis of data from the Civil Registration System. It is also used to calculate e.g. fertility rates, life expectancy and divorce rates. In addition, data is applied from the Birth Register and the Cause of Death Register from the Danish Health Data Authority from which data is collected annually., Read more about statistical processing, Relevance, These statistics are relevant for municipalities, regions, ministries, other government organisations and private companies in analyses of a number of conditions of society and as a basis for planning of e.g. schools, roads, facilities and services for the elderly etc. Statistics Denmark also uses the basic data and results of the statistics for a vast number of other assessments., Read more about relevance, Accuracy and reliability, The statistics are based on the population registered in the Civil Registration System (CPR). Since correct registration in CPR is a condition for being able to lead a normal life in Denmark, the general quality and reliability of the register is regarded as very high. Failure to report immigrations and emigrations means that the published population is considered to be overestimated by 10,000 people or 0.14 per cent., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are usually published one and a half months after the end of the reference period. The statistics are released without delay according to the scheduled dates of publication. The weekly publication of the number of deaths is released five days after the reference week. , Read more about timeliness and punctuality, Comparability, Denmark bases its population statistics on an administrative register, which also applies for a few other countries, whereas many countries take censuses every five or ten years. The population figure for the period 1971 and onwards is based on the same source, i.e. the Civil Registration System (CPR). The population figure from before this period is based on censuses., Read more about comparability, Accessibility and clarity, The statistics are published in “Nyt fra Danmarks Statistik” (in Danish). Figures for the population and its movements are published in Statbank Denmark. In addition, the figures are included in the publications , Befolkningens udvikling, and , Indvandrere i Danmark, (both in Danish with summaries in English). For further information, go to the subject pages of the statistics., Read more about accessibility and clarity

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

      Documentation of statistics

      Documentation of statistics: Regional Accounts

      Contact info, Government Finances, Economic Statistics , Ulla Ryder Jørgensen , +45 51 49 92 62 , URJ@dst.dk , Get documentation of statistics as pdf, Regional Accounts 2024 , Previous versions, Regional Accounts 2023, Regional Accounts 2022, Regional Accounts 2021, Regional Accounts 2020, Regional Accounts 2019, Regional Accounts 2018, Regional Accounts 2017, Regional Accounts 2016, Regional Accounts 2015, Regional Accounts 2014, Regional Accounts 2013, Regional Accounts 2012, The purpose of regional accounts is to describe the economic activity in the regions and provinces within the framework of national accounts definitions and classifications. The accounts are compiled in accordance with the guidelines set out in ESA2010 and are comparable with regional accounts for other European countries. Regional accounts are published at the NUTS II level (regions) and NUTS III level (provinces). Regional accounts have been compiled since 1999., Statistical presentation, Regional accounts describe the geographical dimension of production and income conditions as these are compiled in the national accounts using the production approach. The regional allocation aims at adding production etc. to the region where production takes place. , Regional accounts contain information on GDP, gross value added, gross fixed capital formation, compensation of employees and employment. Moreover the household sector's incomes are compiled. The regional allocation of the household income is based on the residence of the households and not where the incomes are earned., Read more about statistical presentation, Statistical processing, The statistics are based on regional versions of the national accounts' sources, where this is possible. The main sources are Accounting Statistics for Non-agricultural Private Sector and General Government Finances Statistics. The sources are used either directly or as a distribution key. The regional accounts are revised in line with the publication rhythm of the national accounts. The final figures for the regional accounts are therefore not available until three years after the end of the reference period., Read more about statistical processing, Relevance, National and regional accounts are relevant for all, who deal with economic and regional matters., Read more about relevance, Accuracy and reliability, Regional accounts are subject to the same margins of uncertainty as the annual national accounts and the inaccuracy here relates to the inaccuracy of the various sources used. However, the conceptual consistency and over time uniform adaptation of the sources contribute to reduce the inaccuracy of the national accounts figures. In particular, the combination of the primary sources into a coherent system in many cases reveals errors, which are therefore not reflected in the final national accounts. With regard to the regional dimension the following factors can be mentioned:, Read more about accuracy and reliability, Timeliness and punctuality, First version of regional accounts is published 12 month after the reference year. Final regional accounts are published 3 years after the reference year. Regional accounts have a high degree of punctuality, Read more about timeliness and punctuality, Comparability, Regional accounts are consistent with the national accounts, as the sum of the figures for each region with respect to each individual variable is equal to the national accounts value for the same variables. Consequently, each variable can be interpreted in the same manner as the national accounts variables. Regional accounts are based on guidelines set out in ESA2010 and are thereby directly comparable with other regional accounts from the EU Member States. Consistent time series are available for 1993 onwards., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release. In the StatBank, these statistics can be found under , National accounts by region, . For further information, go to the , subject page, ., Regional accounts by 38 industries and 11 provinces/5 regions are available (at a charge). Furthermore regional data can be provided (at a charge) for groups of municipalities with a joint population of at least 100.000 inhabitants. In addition GDP and other non-industry data is available for municipalities with a population of at least 10.000 inhabitants., Read more about accessibility and clarity

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

      Documentation of statistics

      Documentation of statistics: Consumer Price Index

      Contact info, Prices and Consumption, Economic Statistics , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Consumer Price Index 2026 , Previous versions, Consumer Price Index 2025, Consumer Price Index 2024, Consumer Price Index 2023, Consumer Price Index 2022, Consumer Price Index 2021, Consumer Price Index 2020, Consumer Price Index 2019, Consumer Price Index 2018, Consumer Price Index 2017, Consumer Price Index 2016, Consumer Price Index 2015, Consumer Price Index 2014, Documents associated with the documentation, Klassifikationskoder og beskriveler (pdf), Notat om forbruger-og nettoprisindekset i forbindelse med coronakrisen (pdf) (in Danish only), Vægtgrundlag 1991 til i dag (xlsx) (in Danish only), Vejledning til regulering med prisindeks (pdf) (in Danish only), Vægte 2021 og corona (pdf) (in Danish only), FPI-dokumentation - opdateret maj 2020 (pdf) (in Danish only), The purpose of the consumer price index is to measure the development of the prices charged to consumers for goods and services bought by private households in Denmark. The consumer price index has been calculated since 1914, but there are estimated figures for the development in consumer prices back to 1872. From January 1967 the index has been calculated on a monthly basis., Statistical presentation, The consumer price index shows the development of prices for goods and services bought by private households in Denmark. Thus, the index also covers foreign households' consumption expenditure in Denmark, but not Danish households' consumption expenditure abroad. The index shows the monthly changes in the costs of buying a fixed basket of goods, the composition of which is made up in accordance with the households' consumption of goods and services. The consumer price indices divided by group of households show the price development for different households. , The price indices for April, May, June, July, August, September, October, November, December 2020 and January, February, March, April, May and June 2021 are more uncertain than usual, as the non-response rate has been significantly larger than normal and some businesses have been shut down due to COVID-19., Read more about statistical presentation, Statistical processing, The consumer price index is calculated on the basis of 23,000 prices collected from approx. 1,600 shops, companies and institutions throughout Denmark. Most prices are by far collected monthly. The data material received is examined for errors, both by computer (using the so called HB-method) and manually. The different goods and services, which are included in the consumer price index, are first grouped according to approx. 500 elementary aggregates for which elementary aggregate indices are calculated. The elementary aggregate indices are weighted together into sub-indices that are in turn aggregated into the total consumer price index. In calculating a price index it is assumed that the baskets of goods that are compared are identical, also with respect to the quality of the goods. Mainly indirect quality adjustment methods are being applied in the consumer price index in connection with changes in the sample. , Read more about statistical processing, Relevance, The consumer price index is generally viewed as a reliable statistic based on the views of users., Important users are among others the Ministry of Finance, The Ministry of Economic Affairs and the Interior, The Danish Central Bank and private banks and other financial organizations., Read more about relevance, Accuracy and reliability, No calculation has been made of the uncertainty connected with sampling in the consumer price index as the sample is not randomly drawn, but the quality of the consumer price index is accessed to be high., In addition to the "general" uncertainty connected with sampling, there are a number of sources of potential bias in the consumer price index. One source is the consumers substitution between goods and shops and another source is changes in the sample (se chapter regarding "Non-sampling error")., Read more about accuracy and reliability, Timeliness and punctuality, The consumer price index is published on the 10th or the first working day thereafter, following the month in which the data was collected. , The statistics are published without delay in relation to the scheduled date., The consumer price indices divided by group of households are published twice a year., Read more about timeliness and punctuality, Comparability, The consumer price index is related to the European Union harmonized consumer price index (HICP) and to the index of net retail prices. From January 2001, the only difference between the national consumer price index and the HICP is the coverage of goods and services, as owner-occupied dwellings is only recorded in the consumer price index and not in the HICP. The consumer price index is also related to the index of net retail prices. The two indices comprise the same groups of goods and services and are calculated according to the same methodology. Consequently, the only difference between the two indices is the price concept used, as indirect taxes and VAT are subtracted in the index of net retail prices, and the weighting., Read more about comparability, Accessibility and clarity, These statistics are published monthly in a Danish press release and in the StatBank under , Consumer Price Index, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/consumer-price-index

      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
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