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Documentation of statistics: Personal assets and Liabilities

Contact info, Labour Market, Social Statistics , Jarl Christian Quitzau , +45 23 42 35 03 , JAQ@dst.dk , Get documentation of statistics as pdf, Personal assets and Liabilities 2024 , Previous versions, Personal assets and Liabilities 2023, Personal assets and Liabilities 2022, Personal assets and Liabilities 2021, Personal assets and Liabilities 2020, Personal assets and Liabilities 2019, Personal assets and Liabilities 2018, Personal assets and Liabilities 2017, Assets and Liabilities 2016, Assets and Liabilities 2015, Assets and Liabilities 2014, Documents associated with the documentation, Værdiansættelse af unoterede aktier og fordeling på personer i 2022 (pdf) (in Danish only), Estimering af aldersopsparing (pdf) (in Danish only), New data on individual pension wealth growth (pdf), Fordeling af unoterede aktier 2023 (pdf) (in Danish only), Beskrivelse af formueloftet 2023 (pdf) (in Danish only), Effekt af overgang til midlertidigt datagrundlag om ejendomme fra 2023 (pdf) (in Danish only), The purpose of the Wealth and Debt statistics is to provide insights into the wealth and debt of individuals, families, and various population groups. The statistics were first created in the aftermath of the financial crisis in collaboration with Danmarks Nationalbank (the Danish Central Bank) and were intended, among other things, to analyze families' resilience to economic shocks. Additionally, the statistics are used in analyses of the pension system and to measure economic inequality. The statistics have been produced since 2014., Statistical presentation, The statistics produces annual data on the value of value of real estate, cars, financial assets, pension wealth and debts. There are also separate and more detailed publications on pension wealth. The statistics are register based and are based on data at the individual level. It is linked to other registers in order to do subdivisions on age, gender, municipality etc., Read more about statistical presentation, Statistical processing, Data is collected from multiple sources and undergoes statistical processing, including debt classification and market value assumptions for assets such as homes, cars, and unlisted shares. Registers are compiled using anonymized identifiers. In pension statistics, bonuses and reserves are allocated proportionally to pension funds, and anonymized contract numbers enable time-series analysis, except in cases of mergers and acquisitions., Read more about statistical processing, Relevance, These statistics are relevant for researchers, ministries, Economic think tanks, pension funds and the media. It is used for forecasts on the pension system and, analyses on the level of wealth in different strata, the level of prosperity and the level of economic inequality. The statistical data and results are also used in other statistical areas within Statistics Denmark, e.g. in national accounting and as a supplement to the income statistics. Data on pension wealth are also used for the macro economic Model ADAM., Read more about relevance, Accuracy and reliability, The quality of the financial data is high since most of the data is validated by the tax authorities. There is much larger uncertainty on the imputed market value of owned property, cars, unquoted stocks and the value of lifetime pensions. Data on assets that can not be linked to persons is not included. Data Wealth held abroad by Danes is likely lacking as well. For discretionary reasons the register is top-coded with a maximum wealth of DKK 1.93 bio. , Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published approximately 12 months after the end of the reference year. Publications are released on time without delays, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, These statistics have been compiled since 2014. Albeit unlisted stocks and defaulted public debt is only available from 2020. These statistics are compiled according to common European guidelines, but are unique as the only complete register based statistics with almost full coverage on wealth and liabilities. Use caution if doing international comparisons., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, these statistics can be found under , Wealth and liabilities, and , Pension assets, . For further information, go to the , subject page, . , Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Notifications of concern for children and young people

Contact info, Personal Finances and Welfare, Social Statistics , Marko Malic , +45 51 70 56 95 , MMC@dst.dk , Get documentation of statistics as pdf, Notifications of concern for children and young people 2024 , Previous versions, Notifications of concern for children and young people 2023, Notifications of concern for children and young people 2022, Notifications of concern for children and young people 2021, Notifications of concern for children and young people 2020, Notifications of concern for children and young people 2019, Notifications of concern for children and young people 2018, Notifications of concern for children and young people 2017, Notifications of concern for children and young people 2016, Notifications of concern for children and young people 2015, The purpose of the statistics is to shed light on notifications concerning children and young people received by municipalities in Denmark. The data are used for purposes such as policy development and legislation, public debate and research in the field., The statistics were first compiled by the Danish Social Appeals Board (Ankestyrelsen) in 2015 and have been part of Statistics Denmark’s publications since 2016., Statistical presentation, The statistics provide an annual overview of notifications concerning children and young people under the age of 18., The data include information on the number, age, and gender, date of the notification, the notifier’s relation to the child, reason for the notification, and the administrative municipality., The statistics are published in the StatBank and in the Nyt from Statistics Denmark series., Read more about statistical presentation, Statistical processing, Municipalities report information on child welfare notifications to Statistics Denmark. This is done either automatically through system-to-system solutions or manually via a web-based reporting tool., Once a reporting year has ended, each municipality receives a summary of the data submitted. In cooperation with Statistics Denmark, any errors or missing information are corrected. The municipality then confirms that the data accurately reflect the number of notifications for the year. This process is called data validation., Read more about statistical processing, Relevance, The statistics are relevant to researchers, journalists, public authorities – including ministries and municipalities – and others who seek knowledge about the conditions of vulnerable children and young people., Read more about relevance, Accuracy and reliability, Non-response and measurement errors introduce only minimal bias., The figures are approved by the municipalities, and the overall level of uncertainty is considered low., Data in the StatBank Denmark are republished with updates going back up to two years. These updates mainly consist of minor corrections due to non-response and measurement errors, and do not affect the overall picture., Read more about accuracy and reliability, Timeliness and punctuality, The final statistics are published no later than nine months after the end of the reference period. The statistics are generally published on schedule, without delays. For the reporting years 2021–2024, publication followed the planned timeline. A delay occurred for the 2020 reporting year due to data delivery issues, but these were resolved before the subsequent release., Read more about timeliness and punctuality, Comparability, The statistics have been compiled since 2015 and are comparable over time, taking into account the revision in 2017 and the addition of new categories in 2022 and 2024. The annual count makes the data directly comparable, unlike other statistics from Statistics Denmark on vulnerable children and young people (such as placements and support measures), which are status-based. There is some potential for international comparison, particularly with statistics from Sweden and Norway., The statistics are partially internationally comparable, for example with equivalent statistics from Sweden, Norway, and – to some extent – Finland., Read more about comparability, Accessibility and clarity, The statistics are published in , Nyt fra Danmarks Statistik, . Data is available in the StatBank under the topic , Disadvantaged children and youth, . For more information, visit the , topic page of the statistics, . , Contact DST Consulting for access to micro-data., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/notifications-of-concern-for-children-and-young-people

Documentation of statistics

Documentation of statistics: Retail Trade Index

Contact info, Short Term Statistics, Business Statistics , Kari Anne Janisse Arildsen , +45 40 43 38 12 , KJS@dst.dk , Get documentation of statistics as pdf, Retail Trade Index 2025 , Previous versions, 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 42 industries and for three commodity groups: food and other everyday commodities, clothing etc., and other commodities. 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 three main commodity groups 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 42 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. On commodity group level, the uncertainty of the group Food and other convenience goods is about the same, whereas for Clothing etc. it can be up to 3 per cent and for other consumer goods up to 2 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 commodity 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 1939, 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 May 2012, where the time series back to 2000 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: Manufacturers’ Sales of Goods (quarterly)

Contact info, Short Term Statistics, Business Statistics , Morten Skovrider Kollerup , +45 24 52 61 68 , MSL@dst.dk , Get documentation of statistics as pdf, Manufacturers Sales of Goods (quarterly) 2024 Quarter 4 , Previous versions, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2019 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2019 Quarter 3, Manufacturers’ Sales of Goods 2019 Quarter 2, Manufacturers’ Sales of Goods 2019 Quarter 1, Manufacturers’ Sales of Goods 2018 Quarter 4, Manufacturers’ Sales of Goods 2018 Quarter 3, Manufacturers’ Sales of Goods 2018 Quarter 2, Manufacturers’ Sales of Goods 2018 Quarter 1, Manufacturers’ Sales of Goods 2017 Quarter 4, Manufacturers’ Sales of Goods 2017 Quarter 3, Manufacturers’ Sales of Goods 2017 Quarter 2, Manufacturers’ Sales of Goods 2017 Quarter 1, Manufacturers’ Sales of Goods 2016 Quarter 4, Manufacturers’ Sales of Goods 2016 Quarter 3, Manufacturers’ Sales of Goods 2016 Quarter 2, Manufacturers’ Sales of Goods 2016 Quarter 1, Manufacturers’ Sales of Goods 2015 Quarter 4, Manufacturers’ Sales of Goods 2015 Quarter 3, Manufacturers’ Sales of Goods 2015 Quarter 2, Manufacturers’ Sales of Goods 2015 Quarter 1, Manufacturers’ Sales of Goods 2014 Quarter 4, Manufacturers’ Sales of Goods 2014 Quarter 1, The purpose of the statistics is to describe the Danish industrial production by detailed type of goods. Manufacturers' sales of goods is the source for Danish Prodcom statistics, regulated by and submitted to Eurostat., Statistical presentation, The statistics describe manufacturers' sales of goods measured in terms of volume and value by detailed types of goods according to the international classifications CN and SITC. In addition to this, total sales (turnover) are distributed by industries (NACE groups)., The data collecting for the statistics for 2020 has partly been affected by the COVID-19 situation. However, it is assessed that the overall statistics has not been affected in any great extent., Since 2020, Statistics Denmark has carried out extensive work to ensure the quality of the reports from the largest companies. This has led to some audits for the years 2018 to 2022., Read more about statistical presentation, Statistical processing, Data are collected through a quarterly survey of all enterprises in manufacturing (including mining and quarrying) with at least 10 employees or a yearly turnover over 100 mio. dkk, approx. 3,000 units. Reported data are validated, by checking against previous reports as well as against other sources. Data are then aggregated by industrial groupings as well as commodity groups. Series with seasonality are seasonally adjusted., Read more about statistical processing, Relevance, The statistics are in high demand from many different users, including the National Accounts, ministries, trade associations, market analysts, researchers, consultants and businesses., Read more about relevance, Accuracy and reliability, The main non-sampling error is the measurement error concerning classification at the most detailed CN level, as respondents do not always report sales according to the correct codes. Furthermore, data on quantities are generally less reliable than those on values, as some respondents estimate quantities and others do not answer, implying that estimations must be made in the statistical production process., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published two months after the end of the reference quarter. Publications are released on time, as stated in the release calendar., Read more about timeliness and punctuality, Comparability, In its present form and as available in StatBank Denmark, the statistics are comparable since 1995, but the statistics have been produced in some form since 1905. The Prodcom-version of the statistics can be compared to Prodcom statistics of other EU countries. The statistics can be compared to Foreign Trade in Goods to create statistics on apparent consumption - for this, it is important to note the difference in coverage and the potential quality issues at the most detailed CN code level. The tables with sales by industry are consistent from 2000 following the DB07 classification. , Read more about comparability, Accessibility and clarity, These statistics are published annually at the beginning of March in a Danish press release. Quarterly figures are published in the StatBank under , Purchases and sales by manufacturing industries, . Internationally, these statistics are available through Eurostat's , database, and at the UN, where the statistics are disseminated under , Industrial Commodity Statistics, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/manufacturers--sales-of-goods--quarterly-

Documentation of statistics

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

Contact info, Short Term Statistics, Business Statistics , Nanna Nikander Nonboe-Nygaard , +45 20 56 39 57 , nio@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: Implicit index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Implicit index of average earnings 2025 , Previous versions, Implicit index of average earnings 2024, Implicit index of average earnings 2023, Implicit index of average earnings 2021, Implicit index of average earnings 2020, These statistics show the development in average earnings, calculated on the basis of an arithmetic average of salaries of all employees within the same sector and economic industry. In relation to the publication of the new Standardised index of average earnings, these indices were renamed to Implicit index of average earnings. In the new index changes in the workforce is taken into account when calculating the development in earnings., The Implicit index of average earnings goes back to first quarter of 2005 for the private sector and first quarter of 2007 for the public sector., Statistics Denmark has decided to discontinue the implicit index of average earnings at the beginning of 2026 with the publication of the index for the fourth quarter of 2025. Instead, users are advised to use the standardised index of average earnings, which also illustrates the development in pay level for employees in Denmark. The discontinuation of the implicit index of average earnings will not have any impact on the standardised index of average earnings, which will be the only wage index from Statistics Denmark in the future. The historical series of the implicit index of average earnings will continue to be accessible in StatBank Denmark. In order for users to handle the transition to the standardised index of average earnings, a guide (in Danish) has been prepared on how to switch from the implicit to the standardised index of average earnings in practice. It is available on Statistics Denmark's information page on , indexation, ., Statistical presentation, The Implicit index of average earnings is a quarterly statistic of the development in wages for all employees in Denmark, including students and young persons under 18. The indices are available by sector and economic industries and follow the classifications Dansk Branchekode (DB07) and sector (SBR)., Read more about statistical presentation, Statistical processing, Data is collected from a sample of companies and organisations as well as the entire public sector, covering the middle month of the quarter., Data is validated by using fixed boundaries, both at individual and company level. Manual corrections are also made if required. Only companies that are present in both quarters are included in the calculations., In the calculation of the most detailed sub-indices, data for the private sector are weighted to the target population and the individual employment types are weighted with the hours worked., Read more about statistical processing, Relevance, The Implicit index of average earnings is a so-called unit value index, where wage trends are estimated on the basis of a simple salary average of all employees in the same industry. This means that wages partly reflect changes in staff composition in a given industry., Private enterprises as well as ministries etc are the central users. The index is used especially in connection with various contract regulations, as well as the regulatory scheme in the public wageagreements., The Implicit index of average earnings is the wage index that comes closest to being comparable to the European LCI., Read more about relevance, Accuracy and reliability, For the public sector the statistics are based on data for virtually all employees. For the private sector, there are two factors that can affect accuracy, namely uncertainty in the sample statistics and that there may be problems with the completeness of the reported data from the company., This index is an where the sum of wages and hours worked is counted in each group (etc. activity sector). Thus, changes in personnel in a given industry will have an impact on the measured wage development., The figures do not undergo revision; the published figures are usually final., Read more about accuracy and reliability, Timeliness and punctuality, The implicit index of average earnings are published approx. 60 days after the end of the reference quarter, at the same time as the standardised index of average earnings is published. These statistics are published without delay., Read more about timeliness and punctuality, Comparability, The implicit index of average earnings is comparable since first quarter 2005 but for some sectors, comparable wage indices also exist further back in time. The implicit index of average earnings is based on the same data as the standardised index of average earning, but there are significant differences in methodology that allow the two wage indices to be used only partially for comparison., Internationally, the implicit index of average earnings can be compared to the labor cost index collected and published by Eurostat for all EU countries., Read more about comparability, Accessibility and clarity, The implicit index of average earnings is published in Statistics Denmark’s newsletter on [https://www.dst.dk/da/statistik/nyheder-analyser-publ/nyt?psi=1931), together with the standardized index of average earnings. In Statbank Denmark, indices and annual increases are published under the , implicit index of average earnings , . More information can be found on the subject page on , Income and earnings, . , Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Standardised index of average earnings

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

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

Documentation of statistics

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: Benefits during sickness or in connection with childbirth (Discontinued)

Contact info, Labour Market , Torben Lundsvig , TLU , TLU@dst.dk , Get documentation of statistics as pdf, Benefits During Sickness or in Connection with Childbirth 2019 , Previous versions, Benefits During Sickness or in Connection with Childbirth 2018, Benefits During Sickness or in Connection with Childbirth 2017, Benefits During Sickness or in Connection with Childbirth 2016, Benefits During Sickness or in Connection with Childbirth, Benefits During Sickness or in Connection with Childbirth 2013, The purpose of Benefits in connection with sickness and childbirth is to illustrate the use of the law on sickness respectively maternity law. The statistics have been compiled since 1995, but in its present form comparable from 2003. From the year 2017, the statistics contain only information about sickness benefits because Udbetaling Danmark has taken a new administrative IT system for maternity allowance in use. Maternity benefits will be an independent statistics from 2020. , Statistical presentation, The sickness and maternity allowance is an annual statement of the number of persons, days and amounts paid in connection with illness or childbirth. From the year 2017 only information for unemployment benefit paid in connection with illness. The calculations are distributed according to the legal basis for the payment of unemployment benefits, age, sex and geography. In addition, figures from the daily allowance for sickness and birth are included in the statistics, Publicly Provided, where the extent of absence due to illness or maternity leave is included in a larger context. , Read more about statistical presentation, Statistical processing, Data comes from the two administrative registers The Administrative Joint-municipal Register for Sickness Benefits and the National Administrative Register for Childbirth Benefits (ended May 2017). When received there are some mechanical monitoring and doublets are removed. When estimating the duration of a case not having a finale date the final date is set to the last day of the year if the case is about sickness benefits. If the case is about childbirth benefits the final date is estimated as the starting date plus the average length measured in days of similar cases having a finale date., Read more about statistical processing, Relevance, The maternity and paternity leave part of the statistic is used by ministries for reasons of gender equality policy and of the unions and the employers' organizations in connection with collective bargaining. The sickness benefit part of the statistic is together with the maternity and paternity leave part section mostly used as an important data element of Analyses of the Danish workforce productivity (economic modeling), Statistics Labour Market Accounts, Statistics Persons receiving public benefits and general absence statistics., Read more about relevance, Accuracy and reliability, The statistics summarize the reports of illness, birth or adoption that have triggered the payment of unemployment benefit. The expectation is that all sickness benefit issues with payment will be reported. Similarly, the expectation is that all cases of payment due to maternity leave, maternity leave or leave due to adoption are reported. Therefore, the statistics can be expected to be reliable. However, there are a number of cases that will only be reported long after the end of the year to which the case relates, why the last year is not fully updated., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published annually in the month of March the year after the reference year. March is chosen as the compromise of current interest and waiting for the last reports of the year to appear. At publishing time the newest data will be less than three months old., Read more about timeliness and punctuality, Comparability, The statistics is influenced by local Danish law. The law of parental leave is unchanged since 2002 and it is possible to compare the figures back to 2003. Concerning sick leave there has been several adjustment making it more difficult to compare over time., Read more about comparability, Accessibility and clarity, In Statistics Bank Denmark the statistics are published s in the tables under the subject , Sickness benefits, and , Maternity benefits, In addition, the statistics include the Statistical Ten Year Overview., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/benefits-during-sickness-or-in-connection-with-childbirth--discontinued-

Documentation of statistics

Documentation of statistics: Highest Education Attained

Contact info, Population and Education, Social Statistics , Alexander Pfeiffer Cappelen , +45 23 63 72 52 , APF@dst.dk , Get documentation of statistics as pdf, Highest Education Attained 2024 , Previous versions, Highest Education Attained 2023, Highest Education Attained 2022, Highest Education Attained 2021, Highest Education Attained 2020, Highest Education Attained 2019, Highest Education Attained 2018, Highest Education Attained 2017, Highest Education Attained 2016, Highest Education Attained 2015, Highest Education Attained 2014, Highest Education Attained 2013, The purpose of the statistics on educational attainment is to give an overall statistical description of the educational level of the population at any given time. The primary data source to these statistics is the Student Register with data from 1970 onwards. In addition, the Qualification Register is used. Since the Student Register is the primary source for information, the Attainment Register gives nearly complete coverage from 1970 onwards. There is, however information before this time coming from The Qualification Register., Statistical presentation, The Attainment Register gathers information about the highest completed education for each single person based on the information in the Student Register and the Qualification Register. It is a longitudinal register based on an assessment of each person's education "career" and shows how the qualification career develops over time. The register is formed by interpreting the qualification career (skills in chronological order) in order to determine a change in the skill level. Once a year a status register is also produced with the population and information about education the 30. September the current year., Read more about statistical presentation, Statistical processing, The Attainment Register is a longitudinal register based on a assessment of each persons education career in The Student Register and The Qualification Register. It shows how the qualification career develop over time, and it is updated once a year. The status register is produced on the basis of the longitudinal register and contains information about the population and their highest completed education per. September 30 the given year., Read more about statistical processing, Relevance, There is a great variety of users. The information is generally used in connection with describing the population or sections hereof. The register is used in connection with status reports for other statistical fields. Data reports are thus submitted for (mainly on the population's highest level of education completed) a wide number of integration registers operated by Statistics Denmark. Furthermore, the register is frequently used in connection with external service activities order by Danish ministries, municipalities, research institutions, professional organization, private enterprises, private individuals and, not least, requests made by the news media., Read more about relevance, Accuracy and reliability, The Accuracy and reliability vary depending on the source of information. More than 80 pct. of the information comes from administrative sources, such as student systems of educational institutions, which are highly reliable. These sources have priority one when the registry is created and will be used if there is information from one of these sources. Other sources are not so closely linked to the education programs and will often be less reliable. Examples of these sources are the surveys of immigrants' education and the population and housing census in 1970, based on self-reported education. In addition, information is imputed for persons who do not respond in the study of immigrants' education. The imputed data is useful in overall statistical statements, but cannot be considered as valid information on individuals' educational attainment. , In connection with the annual reports from the education institutions there is information which also relate to previous years. These delayed notifications concern particularly the last year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published around 6 months after the end of the reference time. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The longitudinal register is produced once a year and the entire period is thus calculated in the same way. Based on the longitudinal register, a status register is produced with the population per. September 30 that year. In the event of significant changes in the way the longitudinal register is produced, the status registers for all years will be reproduced. It happens that an education changes level from one year to the next. Typically, this will not cause a reproduction of all the status registers and therefore affect comparability over time. Labor force survey provide information too Eurostat about the educational attainment level and this is these figures that are used for international comparison of the attainment level., Read more about comparability, Accessibility and clarity, Statistics are published once a year in "News from Statistics Denmark" . At the same time data are released in the Statbank and on the homepage: , Homepage, Information also appears in the annual publications Statistical 10-Year Review and the Statistical Yearbook., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/highest-education-attained

Documentation of statistics