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      Documentation of statistics: Harmonized Index of Consumer Prices (HICP)

      Contact info, Prices and Consumption, Economic Statistics , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Harmonized Index of Consumer Prices (HICP) 2025 , Previous versions, Harmonized Index of Consumer Prices (HICP) 2024, Harmonized Index of Consumer Prices (HICP) 2023, Harmonized Index of Consumer Prices (HICP) 2022, Harmonized Index of Consumer Prices (HICP) 2021, Harmonized Index of Consumer Prices (HICP) 2020, Harmonized Index of Consumer Prices (HICP) 2019, Harmonized Index of Consumer Prices (HICP) 2018, Harmonized Index of Consumer Prices (HICP) 2017, Harmonized Index of Consumer Prices (HICP) 2016, Harmonized Index of Consumer Prices (HICP) 2015, Harmonized Index of Consumer Prices (HICP) 2014, Documents associated with the documentation, Notat-om-forbruger-og-nettoprisindekset-i-forbindelse-med-corona-krisen (pdf) (in Danish only), ECOICOP (pdf), Vægtgrundlag 1991 til i dag (xlsx) (in Danish only), Weightings 2025 (xlsx), The harmonized index of consumer prices (HICP) is compiled by all EU Member States and Norway, Iceland and Switzerland. The purpose of the harmonized consumer price indices is to be able to estimate the development in the countries' consumer prices on a comparable basis. HICP is used both by the Commission and by the European Central Bank in connection with the valuation of the price development in the individual countries in connection with the implementation and monitoring of the 3rd phase of the EMU. All the EU Member States and Norway and Iceland have compiled HICP since January 1997., Statistical presentation, HICP 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 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 HICP 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 HICP, are first grouped according to approx. 500 elementary aggregates for which elementary aggregate indices are calculated. The elementary aggregate indices are mainly calculated as geometric indices. The elementary aggregate indices are weighted together into sub-indices that are in turn aggregated into the total HICP., Read more about statistical processing, Relevance, The HICP is generally viewed as a reliable statistic based on the views of users., Important users are among others The European Central Bank, The European Commission, The Ministry of Finance, The Ministry of Economic Affairs and the Interior, The Danish Central Bank as well as 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 HICP as the sample is not randomly drawn, but the quality of the HICP is accessed to be high. In connection with COVID-19, uncertainty is greater than usual as it has been difficult to collect prices and many industries have been closed down., 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., Read more about accuracy and reliability, Timeliness and punctuality, The HICP 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., Read more about timeliness and punctuality, Comparability, The Danish HICP can be compared directly with other countries' HICPs. Using the HICPs it is possible to compare the inflation rates between different countries directly., The Danish HICP is also related to the national consumer price index., 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. , From January till December 2000, the only difference between the national consumer price index and the HICP is that both owner-occupied dwellings and private hospitals are only recorded in the consumer price index and not in the HICP. , Before January 2000, there are differences in calculation and methodology between the two indices as well as several differences as regards their coverage of goods and services., Read more about comparability, Accessibility and clarity, These statistics are published monthly in a Danish press release and in the StatBank under , Harmonized index of consumer prices (HICP), . The HICP of all Member States is also published by Eurostat in , Statistics in Focus/Economy and Finance, and on , Eurostat, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/harmonized-index-of-consumer-prices--hicp-

      Documentation of statistics

      Documentation of statistics: Employees (monthly)

      Contact info, Labour Market , Thomas Thorsen , +45 23 69 94 27 , TST@dst.dk , Get documentation of statistics as pdf, Employees (monthly) 2024 Month 07 , Previous versions, Employees (monthly) 2024 Month 06, Employees (monthly) 2024 Month 05, Employees (monthly) 2024 Month 04, Employees (monthly) 2024 Month 03, Employees (monthly) 2024 Month 02, Employees (monthly) 2024 Month 01, Employees (monthly) 2023 Month 12, Employees (monthly) 2023 Month 11, Employees (monthly) 2023 Month 10, Employees (monthly) 2023 Month 09, Employees (monthly) 2023 Month 08, Employees (monthly) 2023 Month 07, Employees (monthly) 2023 Month 06, Employees (monthly) 2023 Month 05, Employees (monthly) 2023 Month 04, Employees (monthly) 2023 Month 03, Employees (monthly) 2023 Month 02, Employees (monthly) 2023 Month 01, Employees (monthly) 2022 Month 11, Employees (monthly) 2022 Month 10, Employees (monthly) 2022 Month 09, Employees (monthly) 2022 Month 08, Employees (monthly) 2022 Month 07, Employees (monthly) 2022 Month 06, Employees (monthly) 2022 Month 05, Employees (monthly) 2022 Month 04, Employees (monthly) 2022 Month 03, Employees (monthly) 2022 Month 02, Employees (monthly) 2022 Month 01, Employees (monthly) 2021 Month 12, Employees (monthly) 2021 Month 11, Employees (monthly) 2021 Month 10, Employees (monthly) 2021 Month 09, Employees (monthly) 2021 Month 08, Employees (monthly) 2021 Month 07, Employees (monthly) 2021 Month 06, Employees (monthly) 2021 Month 05, Employees (monthly) 2021 Month 04, Employees (monthly) 2021 Month 03, Employees (monthly) 2021 Month 02, Employees (monthly) 2021 Month 01, Employees (monthly) 2020 Month 12, Employees (monthly) 2020 Month 11, Employees (monthly) 2020 Month 10, Employees (monthly) 2020 Month 09, Employees (monthly) 2020 Month 08, Employees (monthly) 2020 Month 07, Employees (monthly) 2020 Month 06, Employees (monthly) 2020 Month 05, Employees (monthly) 2020 Month 04, Employees 2018 Month 08, Employees 2018 Month 07, Employees 2018 Month 06, Employees 2018 Month 04, Employees 2018 Month 03, The purpose of these statistics is to clarify the short-term development in the employment of employees in Danish enterprises. The statistics contains employment data from the beginning of 2008. , Statistical presentation, The employment statistics for employees is published on a quarterly and monthly basis. The statistics shows the development in the number of people with employee job. On a quarterly basis the number of full-time employees is also published. The statistics is distributed by sector and industries both in the monthly statistics and in the quarterly statistics. Furthermore, workplace geography, residence geography, age, sex and ancestry is also illustrated on a quarterly basis., Read more about statistical presentation, Statistical processing, Data are debugged, adjusted and quality guaranteed in relation to breakdowns on industry, sector and geography. Data for both the number of full-time employees and number of people with employee job is seasonally adjusted, broken down by both industry, sector and geography on residence., Read more about statistical processing, Relevance, Users interested in the social and economic statistics have expressed satisfaction with the quality of the statistics., Read more about relevance, Accuracy and reliability, The uncertainty in the development of the number of employees is estimated to be less than 1 per cent of the total number of full-time employees, where 1 per cent corresponds to approx. 20,000 full-time employees. As regards more detailed statistics in terms of industry and geographical distribution the uncertainty is much greater. For the monthly statements there has not yet been a systematic quality studies of statistics. Compared to the quarterly statements of full-time employees, there are two factors pulling in opposite directions: on the one hand, the monthly statements are published earlier, leading to increased uncertainty, because fewer reports has been reported at that time. On the other hand, jobs are imputed for periods where the employees for up to 45 days have not received wages, but subsequently returned to the same employer in the calculation of persons with employee jobs, which helps to reduce uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The preliminary figures of the monthly statistics are published approx. 52 days after the end of the reference month. These statements are revised every month until final estimates are released in the quarterly statistics., The preliminary employment statistics for employees are published approx. 52 days after the end of the quarter. The revised statement will be published within 3 months after the reference quarter and the final statement 3 months later together with the new preliminary data for the following quarter. There is usually no delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, There are no changes in methodology since these statistics where first introduced. Data are comparable during the whole period., 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 the subject , Employees, . For further information, go to the , subject page, . , Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/employees--monthly-

      Documentation of statistics

      Documentation of statistics: Public sector employment (quarterly)

      Contact info, Labour Market, Social Statistics , Mads Housø Hansen , +45 24 43 40 61 , MHU@dst.dk , Get documentation of statistics as pdf, Public sector employment (quarterly) 2024 Quarter 4 , Previous versions, Public sector employment (quarterly) 2024 Quarter 3, Public sector employment (quarterly) 2024 Quarter 2, Public sector employment (quarterly) 2024 Quarter 1, Public sector employment (quarterly) 2023 Quarter 4, Public sector employment (quarterly) 2023 Quarter 3, Public sector employment (quarterly) 2023 Quarter 2, Public sector employment (quarterly) 2023 Quarter 1, Public sector employment (quarterly) 2022 Quarter 4, Public sector employment (quarterly) 2022 Quarter 3, Public sector employment (quarterly) 2022 Quarter 2, Public sector employment (quarterly) 2022 Quarter 1, Public sector employment (quarterly) 2021 Quarter 4, Public sector employment (quarterly) 2021 Quarter 3, Public sector employment (quarterly) 2021 Quarter 2, Public sector employment (quarterly) 2020 Quarter 4, Public sector employment (quarterly) 2020 Quarter 3, Public sector employment (quarterly) 2020 Quarter 2, Public sector employment (quarterly) 2020 Quarter 1, Public sector employment 2018 Quarter 3, Public sector employment 2018 Quarter 2, Public sector employment 2018 Quarter 1, Public Employment Statistics 2017 Quarter 4, Public Employment Statistics 2017 Quarter 3, Public Employment Statistics 2017 Quarter 1, Public Employment Statistics 2016 Quarter 3, Public Employment Statistics 2014 Quarter 4, Public Employment Statistics 2015 Quarter 1, Public Employment Statistics 2015 Quarter 2, Public Employment Statistics 2015 Quarter 3, Public Employment Statistics 2015 Quarter 4, Public Employment Statistics 2016 Quarter 1, Public Employment Statistics 2016 Quarter 2, Public Employment Statistics 2016 Quarter 4, Public Employment Statistics 2014 Quarter 3, Documents associated with the documentation, Notat om revision af COFOG (pdf) (in Danish only), The public employment statistics cover general government sector and its subsectors. The statistics are published quarterly and are distributed by subsector and by purpose. The classification by purpose follows the classification COFOG (Classification of the functions of Government)., Statistical presentation, The statistics publish quarterly the number of full-time employees in general government sector. The statistics are broken down by subsector and the COFOG classification., Read more about statistical presentation, Statistical processing, The data source of the statistics is the eIncome Register of Statistics Denmark. This is combined with information on e.g. public account numbers from public reports., Data are always quality controlled at a cross-level between COFOG and the subsectors of general government. , The COFOG distributions are revised occasionally and data are revised in accordance with the data source. Time-series are seasonally adjusted., Read more about statistical processing, Relevance, Among users of the statistics are ministries, government agencies and municipalities, various organizations, researchers, politicians and others interested in the development of employment and the number of staff employed within the general government sector., Read more about relevance, Accuracy and reliability, The data source of the statistics is the eIncome Register of Statistics Denmark which is the main data source for register-based employment statistics published by Statistics Denmark. This register is considered as highly reliable., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are expected to be published without any delay in relation to the time for publication announced., Read more about timeliness and punctuality, Comparability, Comparable data are available based on the new statistics from first quarter 2008 onwards. Based on the former statistics historical data are available for the period first quarter 2002 until fourth quarter 2012., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistics Denmark and in the database Statbank Denmark., Table OBESK1, ,, Table OBESK2, ,, Table OBESK3, and, Table OBESK4, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/public-sector-employment--quarterly-

      Documentation of statistics

      Documentation of statistics: A-Income Statistics (income subject to provisional tax)

      Contact info, Labour Market, Social Statistics , Uwe Pedersen , +45 23 72 65 69 , UWP@dst.dk , Get documentation of statistics as pdf, A-Income Statistics (income subject to provisional tax) 2024 , Previous versions, A-Income Statistics (income subject to provisional tax) 2023, A-Income Statistics (income subject to provisional tax) 2022, A-Income Statistics (income subject to provisional tax) 2021, A-Income Statistics (income subject to provisional tax) 2020, A-Income Statistics (income subject to provisional tax) 2019, A-Income Statistics (income subject to provisional tax) 2018, A-Income Statistics (income subject to provisional tax) 2017, A-Income Statistics (income subject to provisional tax) 2016, A-Income Statistics (income subject to provisional tax) 2015, A-Income Statistics (income subject to provisional tax) 2015, A-Income Statistics (income subject to provisional tax) 2013, The purpose of the Provisional Income Statistics is to provide a more up to date picture of the compilation of income than is possible, by means of the final Personal Income Statistics. Compilation of the final Personal Income Statistics have to wait until the tax assessment process has reached a sufficiently acceptable level concerning the A-income (wages, salaries, unemployment benefits and social pensions etc.) and other income, e.g. entrepreneurial income. This does not apply to the Provisional Income Statistics., Statistical presentation, The a-income statistics mainly comprise of wages and transfers. It illustrates the level and composition of the a-income for the tax year and can be split into wages and various types of transfer incomes. The a-income amounts to 90 per cent of the total gross income. The statistics are based on the provisional tax statement for the income. The data is acquired four months after the end of the tax year. The final income statistics is based on a-incomes acquired eight month after the end of the tax year. The final statistics are based on the Statistics Denmark's Register of Incomes Statistics., Read more about statistical presentation, Statistical processing, The type of income in the e-income register is adjusted in-case of inconsistencies between the filing-entity and the type of income., The total transfers are grouped into the different type of transfers by merging the e-income register with the register of people receiving public benefits., Data on specifically 2020 and 2021 are supplemented with data from the Danish Business Authority on employer´s compensation on wages and salaries paid to staff, not able to work during the lockdown, caused by the COVID-19 pandemic., Read more about statistical processing, Relevance, One or two annual meeting with some of the main users of the income and wealth statistics is held in Statistics Denmark. On a daily to weekly basis users call with questions related to the statistics. Trough these interactions with the users we assess the need for improvements of the statistics., Read more about relevance, Accuracy and reliability, All persons receiving unemployment income is included in the statistics., As we are dealing with a provisional data based on relatively early data from the e-income Register the data are subject to certain margins of inaccuracy. The data may be revised by the Tax authorities after the date on which we extract the information from the Register. This applies in particular to the salary information slips containing wages and salaries. However, the uncertainty caused by the revisions linked to the income data is marginal., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 4 to 5 months after the reference period. The statistics are published as planned., Read more about timeliness and punctuality, Comparability, Changing several social benefits from net sum into gross sum (taxable) in connection with the tax reform of 1st January 1994 has caused a minor break in the time series from 1993 to 1994. , There are no similar statistics internationally., Read more about comparability, Accessibility and clarity, The statistics are published on our , website, , in an annual , newsletter, and via the Statistikbanken)., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/a-income-statistics--income-subject-to-provisional-tax-

      Documentation of statistics

      Documentation of statistics: Absence from work

      Contact info, Labour Market, Social Statistics , Nete Nielsen , +45 40 10 48 87 , NDN@dst.dk , Get documentation of statistics as pdf, Absence from work 2024 , Previous versions, Absence from work 2023, Absence from work 2022, Absence from work 2021, Absence from work 2020, Absence 2019, Absence 2018, Absence 2017, Absence 2016, Absence 2015, Absence 2014, Absence 2013, Absence 2012, The purpose of the statistics of absence is to describe the amount of work that is lost due to absence. Absence is divided into "Own sickness", "Children's sickness", "Occupational injury" and "Maternity and adoption leave". The statistics are published on a yearly basis and are used for estimating and comparing the level of absence within different groups of employees., Statistical presentation, The statistics of absence are published yearly for the governmental sector, the local governmental sector and the private sector. Statistics according to the new sector definition from 2013 are also published for the labour market as a whole. The absence is grouped by the variables occupation, education, industry, region, age and sex. From 2013 own sickness is published by lengths of period. In the governmental and municipal sector all employees are included while the private sector is described by a representative sample of enterprises with 10 or more employees., Read more about statistical presentation, Statistical processing, On a yearly bases information on absence is collected from all of the public sector and from a sample 2600 private enterprises with 10 or more employees. After validating the absence data the periods of absence are connected to the job from which the person was absent. The information about the extent of the employment is found in the earnings statistics. The information on absence from the private sector is enumerated to the total population of enterprises with 10 employees or more., Read more about statistical processing, Relevance, Absence has both personal and economic consequences that have an impact on both employees, employers and the community. The statistics are tools used in estimating and comparing the level of absence within different groups of employees, and can be a foundation on which economic and political decisions are made. The statistics are of interest for the central government, municipalities and regions, private business enterprises, non-governmental organizations, researchers and news media. , Read more about relevance, Accuracy and reliability, The governmental and local government sector in principle include all employed persons. For these sectors there is immeasurable inaccuracy mainly caused by measuring errors., The private sector is based on a representative sample of about 2600 enterprises. The inaccuracy can be divided into sampling inaccuracy and the immeasurable inaccuracy that derives from measuring errors. The total absence rate for own sickness is determined with a 95 percent confidence interval to vary around +/- 0.05 percent. Sampling errors for divisions on e.g. gender or industry are considerably higher., Read more about accuracy and reliability, Timeliness and punctuality, The statistics of absence refers to the whole year to which the absence periods belongs The statistics is published on a yearly basis at the end of October following the reference period. The information is published without delay compared to schedule., Read more about timeliness and punctuality, Comparability, The statistics of absence for the central governmental sector covers the year 2003 and forward, while the first data for the local governmental sector was published for the year 2005. The statistics for the private sector covers the period from 2007 and forward. From 2010 the municipality sector and the regional sector are published separately. Before 2010 the two sectors were only published together., The method and quality of data have continuously been improved especially the first years of the statistics. Comparisons between sectors and years (especially the earliest published data) should only be made with reservations., Read more about comparability, Accessibility and clarity, The latest results are published once a year in a Danish press release, at the same time as tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Absence from work, . It is possible to buy more detailed results and to get access to micro-data through Statistics Denmark's Research services., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/absence-from-work

      Documentation of statistics

      Documentation of statistics: Income Statistics

      Contact info, Labour Market, Social Statistics , Uwe Pedersen , +45 23 72 65 69 , UWP@dst.dk , Get documentation of statistics as pdf, Income Statistics 2024 , Previous versions, Income Statistics 2023, Income Statistics 2022, Income Statistics 2021, Income Statistics 2020, Income Statistics 2019, Income Statistics 2018, Income Statistics 2017, Income Statistics 2016, Income Statistics 2015, Income Statistics 2014, Income Statistics 2013, The purpose of the income statistics - is to provide statistics on the population's incomes and tax payments as well as the distribution of incomes. The statistics are useful in the field of social sciences and form the basis for effective policymaking in areas that affect the economic situation of the households. Statistics Denmark has published statistics on income since 1905 and has coherent time series going back to the 1980’s., Statistical presentation, The income statistics are based on a full-population register. It contains information on annual incomes at both the personal- and family level as well as data on the distribution of income. The income is available both pre- and post taxes and can be split into subcategories such as primary income, transfers, property income and taxes. In the income statistics the population is divided into groups by age, socio-economic status, gender, municipalities (NUTS-3), type of family and into income intervals., Read more about statistical presentation, Statistical processing, Data is collected and published yearly. The primary source is administrative data from the Danish tax authorities. Using secondary sources from the municipalities and unemployment funds the incomes are subdivided into more detailed types of income. Finally other registers in Statistics Denmark, such as the population register, provide background information., In case of inconsistencies between data sources on the total income amounts, the data are fitted to match the level of the tax authorities, which are assumed to be correct., Read more about statistical processing, Relevance, The primary users of the income statistics are ministries, municipalities, research institutes and the media. An annual meeting with some of the users of the main welfare statistics is held in Statistics Denmark. On a daily basis users call with questions related to the statistics or comment on our publications on social media. Through these interactions with the users we continually assess the need for improvements of the statistics., Read more about relevance, Accuracy and reliability, The quality is in general considered to be very good for the income types included in the statistics as data have been validated by the tax authorities. Undeclared incomes, winnings in lotteries etc. may result in a mismatch between actual and registered income., As the income statistics are based on full-population registers, there are no sampling errors., In 2024 data is extracted in August. Thus revisions after this date will not be taken into account in the income statistics., Read more about accuracy and reliability, Timeliness and punctuality, Most tables on income statistics are published in September, nine months after the end of the income reference year along with the annual newsletter. Socio-economic status, imputed rent, disposable income and income distribution indicators are published in November. , The statistics have usually been published as planned., Read more about timeliness and punctuality, Comparability, The statistics are comparable over time, but special circumstances affect individual years. COVID-19 and aid packages are important in 2020-2021. In 2022, one-off payments due to inflation are included, and in 2024, 1 month's free rent for certain rental housing units is included as housing benefit. Holiday funds give differences compared to the national accounts 2018-2021. The statistics were revised in 2013 with retroactive effect to 1987. Internationally, Eurostat and OECD are the recommended sources, but income concepts vary., Read more about comparability, Accessibility and clarity, These statistics are published 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 , Income and earnings, . For further information, go to the , subject page, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/income-statistics

      Documentation of statistics

      Documentation of statistics: Personal assets and Liabilities

      Contact info, Labour Market, Social Statistics , Jarl Christian Quitzau , +45 23 42 35 03 , JAQ@dst.dk , Get documentation of statistics as pdf, Personal assets and Liabilities 2024 , Previous versions, Personal assets and Liabilities 2023, Personal assets and Liabilities 2022, Personal assets and Liabilities 2021, Personal assets and Liabilities 2020, Personal assets and Liabilities 2019, Personal assets and Liabilities 2018, Personal assets and Liabilities 2017, Assets and Liabilities 2016, Assets and Liabilities 2015, Assets and Liabilities 2014, Documents associated with the documentation, 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
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