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Documentation of statistics: International Trade in Goods

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

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

Documentation of statistics

Documentation of statistics: Producer and Import Price Index for Commodities

Contact info, Prices and Consumption, Economic Statistics , Nicklas Milton Elversøe , +45 61 15 35 98 , nel@dst.dk , Get documentation of statistics as pdf, Producer and Import Price Index for Commodities 2025 , Previous versions, Producer and Import Price Index for Commodities 2024, Producer and Import Price Index for Commodities 2023, Producer and Import Price Index for Commodities 2022, Producer and Import Price Index for Commodities 2021, Producer and Import Price Index for Commodities 2020, Producer and Import Price Index for Commodities 2019, Producer and Import Price Index for Commodities 2018, Producer and Import Price Index for Commodities 2017, Producer and Import Price Index for Commodities 2016, Producer and Import Price Index for Commodities 2015, Producer and Import Price Index for Commodities 2014, The statistics Producer and Import Price Index for Commodities show the price development of commodities in the first stage of transaction. The primary use is as deflators (converting nominal values to real values), but is also used as a business cycle indicator and for contract adjustments in the business sector. The index can be divided into Producer price index for commodities, Import price index for commodities and Price index for domestic commodities supply. The Price index for domestic supply of commodities can be traced back to 1876 and in the current form back to 1981. Producer Price Index for Commodities dates back to 2000 and Import Price Index for Commodities to 2005., Statistical presentation, The Producer and Import Price Index for Commodities contains monthly indices of the price development of commodities in the first stage of turnover (business-to-business), i.e. typically sales from producer to wholesaler or retailer, for commodities produced by Denmark for the domestic market and export, or for commodities imported into Denmark. The statistics are divided by product and industry groups., Read more about statistical presentation, Statistical processing, Approximately 7800 prices from selected producers and importers in Denmark. Of these, approximately 3800price reports for calculation of Producer Price Index for Commodities, approximately 3600 for calculation of Import Price Index for Commodities and approximately 5900 price reports are used to calculate the Price Index for Domestic Supply. The prices are validated automatically in connection with the collection. Unusually large price developments are subsequently checked manually. The validated price developments are then aggregated in a hierarchical system, where they are given weight according to their significance to the overall price index., Read more about statistical processing, Relevance, The Producer and Import price index for commodities serves as economic key figures, cyclical indicator, deflator and a contract regulations tool. The primary users of the statistics are the Danish National Accounts, business and stakeholders in the Danish economy. The statistics meet all the requirements of the EU in terms of industry coverage, aggregation level, frequency and publication date, etc., Read more about relevance, Accuracy and reliability, The prices covered by the data collection have a direct coverage of approximately 70 percent of total revenue in the Danish economy. Weights are based on the National Accounts product balances, which covers the main part of trading in the first stage of sales within the delimitation of the statistics. Sample units are selected on a purposive basis using a top-down approach. As a random sampling method is not being utilised a subsequent assessment of sampling error is not enabled. , Published statistics are considered final. , Producer and import price index for commodities are not considered to have an increased uncertainty due to COVID-19. Data collection has been largely not impacted as a result of the crisis and subsequent non-response levels have remained at their historically low levels., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published on a monthly basis. The statistics for a given month are published on the 15th of the following month or the first business day thereafter. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, Statistics Denmark has calculated variations of this statistic since 1876. The Producer and import price index for commodities can be found as an unbroken monthly time series from 2005 to today. The statistics have been prepared according to international standards and can therefore be compared to similar statistics from other European countries., Read more about comparability, Accessibility and clarity, The statistics are published monthly by Statistics Denmark via press release ", Nyt fra Danmarks Statistik, " (in Danish only) and specifically regard Producer and Import Price Index for Commodities., In the StatBank, the statistics are published under the topic , Producer and import price index for commodities, . , For more information visit the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/producer-and-import-price-index-for-commodities

Documentation of statistics

Documentation of statistics: Purchasing Power Parities (PPP)

Contact info, Prices and Consumption, Economic Statistics , Zdravka Bosanac , +45 61 15 16 74 , ZBO@dst.dk , Get documentation of statistics as pdf, Purchasing Power Parities (PPP) 2024 , Previous versions, Purchasing Power Parities (PPP) 2023, Purchasing Power Parities (PPP) 2022, Purchasing Power Parities (PPP) 2021, Purchasing Power Parities (PPP) 2020, Purchasing Power Parities (PPP) 2019, Purchasing Power Parities (PPP) 2018, Purchasing Power Parities (PPP) 2017, Purchasing Power Parities (PPP) 2016, Purchasing Power Parities (PPP) 2015, Purchasing Power Parities (PPP) 2014, PPP tells how many currency units a given amount of goods and services cost in different countries. The statistics are used, among other things, to convert countries' gross domestic product (GDP) into comparable figures and for analyses of expenditure levels. Denmark has participated in the work on purchasing power parities since the 1970s, but the statistics in their current form are comparable from 2000 onwards., Statistical presentation, Purchasing power parities (PPP) is an annual price level indicator which expresses the price level in a given country at a given time, relative to the price level in one or more countries. This means that PPP for a particular country indicate how many units of national currency are needed in that country to maintain the purchasing power of €1 in the EU. PPP can be calculated for individual products or aggregates, such as GDP., Read more about statistical presentation, Statistical processing, Price surveys are conducted in order to provide price input data for household consumption, individual government consumption, collective consumption and gross fixed capital formation (investment goods and services). Reference (imputed) PPPs are used for NPISH consumption, inventories, and net exports., Read more about statistical processing, Relevance, The EU Commission uses GDP per capita PPP converted, as basis for allocating funds from the Structural Fund to reduce the financial inequalities among and within the 27 EU Member States. Furthermore, indicators derived from PPPs are used for a wide range of analytic purposes, often providing background information for policymaking in the European institutions, in international organizations like the International Monetary Fund and the World Bank, and in national governments., Read more about relevance, Accuracy and reliability, In the price surveys, the most important source of statistical margins of sampling errors is the range of goods and services, which are not equally representative of all countries included in the international comparisons. The composition of consumption expenditure differs among countries, and this gives rise to potential conflicts between representativeness and data comparability. For some areas, e.g. health it is particularly difficult to provide comparable information. The structure of the health sector differs among countries, and there are no "pure" market prices for these services, which constitutes another statistical margin of sampling error. The margins of sampling errors are not estimated., Read more about accuracy and reliability, Timeliness and punctuality, Provisional results from the surveys of purchasing power parities are published one year after the reference period, whereas the final results are published three years after the reference period. The statistics are usually published without any delay in relation to the scheduled date of publication., Read more about timeliness and punctuality, Comparability, Purchasing power parities are compiled for the purpose of conducting price and volume comparisons for a specific year among countries. Consequently, they are comparable across the participating countries. Comparisons over time must be interpreted with caution, as the basket of goods and services differs from one year to another., In the calculation of PPP, price level index and volume index, the average of EU28 was used as a reference country (group of countries) until 2020. With the United Kingdom's withdrawal from the European Union (EU), the EU27 (excluding the UK) = 100 will be used as a reference country (group of countries) from 2020. This has only a minor impact on the comparability of PPPs, the price level index and the volume index between 2019 and 2020., Read more about comparability, Accessibility and clarity, These statistics are published annually in a Danish press release, at the same time as the tables are updated in the statbank. In the statbank, these statistics can be found under , International volume and price comparision, . Internationally, these statistics are available through , OECD, , , Eurostat, and , Nordic Statistics database, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/purchasing-power-parities--ppp-

Documentation of statistics

Documentation of statistics: Consumer Expectations Survey

Contact info, Prices and Consumption, Economic Statistics , Zdravka Bosanac , +45 61 15 16 74 , ZBO@dst.dk , Get documentation of statistics as pdf, Consumer Expectations Survey 2025 , Previous versions, Consumer Expectations Survey 2024, Consumer Expectations Survey 2023, Consumer Expectations Survey 2022, Consumer Expectations Survey 2021, Consumer Expectations Survey 2020, Consumer Expectations Survey 2019, Consumer Expectations Survey 2018, Consumer Expectations Survey 2017, Consumer Expectations Survey 2016, Consumer Expectations Survey 2015, The purpose of the survey is to analyze the consumer climate through questions about the economic situation as perceived by consumers at a given time concerning both the general economic situation in Denmark and the financial situation of the family. The main results are coordinated in the so-called consumer confidence indicator. The Danish surveys have been conducted since 1974. From 1996 data is collected in all 12 months of the year., Statistical presentation, Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements., Read more about statistical presentation, Statistical processing, This survey are sample surveys, where a representative sample of persons 16-74 years are asked among other things about the consumer expectations. The results are corrected from the effects of non-sampling and non-response and then enumerated so that the figures can directly be classed with the population of adult persons and families in Denmark. Data are validated using logical validation rules. A seasonal pattern could not be identified in the series and no seasonal adjustment was undertaken., Read more about statistical processing, Relevance, The most important user is the European Commission for Economy and Finances (ECFIN), which receives detailed tables for all questions and publishes seasonally adjusted consumer confidence indicators for all EU member states. The figures are also of great interest to the news media., Read more about relevance, Accuracy and reliability, As the results are based on a sample survey, they are subject to a certain degree of statistical uncertainty. This depends on both the size of the sample and the number of completed interviews, which vary from survey to survey. With a sample of approximately 1,500 persons and a response rate of about 65%, which has normally been achieved in the last few years, the statistical uncertainty is in 95 pct. of the cases estimated ranged within +/- 3 percentage points. A change in an indicator should be greater than 5 percentage points to indicate a significant change., Read more about accuracy and reliability, Timeliness and punctuality, There is no difference between planned and actual release time., Read more about timeliness and punctuality, Comparability, The questions asked in connection with these statistics in Denmark are also asked in the European Commission's Consumer confidence survey '. The European Commission publishes figures for all EU countries in its database. Eurostat's consumer confidence is based on a slightly different composition of questions than the current one in Denmark. Therefore, the overall consumer confidence indicators calculated in Denmark and in Eurostat are not directly comparable, whereas all sub-indicators are directly comparable. The questions shown in the section 2.01. Data description, have been asked in all the omnibus surveys since 1974. Due to minor changes in the calculation method, an immediate comparison is only possible from 2007 onwards. , Read more about comparability, Accessibility and clarity, The results are published in , News from Statistics Denmark, and , Statbank Denmark, . Further, there is a subject page for , Consumer Expectations, ., After each survey, Statistics Denmark submits detailed tables giving a number of background variables as well as the consumer confidence indicator and net figures to the European Commission, which publishes monthly both seasonally adjusted and not seasonally adjusted indicator and the net figures for each members state (incl. Denmark), at European Commission database: , European Commission database, The access to the more detailed data and Micro-data can be granted through Statistics Denmark's agreement for researchers., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/consumer-expectations-survey

Documentation of statistics

Documentation of statistics: Household Budget Survey

Contact info, Prices and Consumption, Economic Statistics , A Solange Lohmann Rasmussen , +45 61 15 17 93 , slr@dst.dk , Get documentation of statistics as pdf, Household Budget Survey 2023 , Previous versions, Household Budget Survey 2022, Household Budget Survey 2021, Household Budget Survey 2020, Household Budget Survey 2019, Household Budget Survey 2018, Household Budget Survey 2017, Household Budget Survey 2016, Household Budget Survey 2015, Household Budget Survey 2014, Household Budget Survey 2013, The Household Budget Survey describes in detail the Danish households' expenditure on goods and services and the economic condition of the households. The statistics are used to compile weightings in the Consumer Price Index and for calculation of the private consumption in the National Accounts. The statistics were first compiled in 1897 and annually since 1994., Statistical presentation, The Household budget survey is an annual statement of the detailed private consumption at household level for private households in Denmark. The survey covers private households in Denmark. The household budget survey provides a detailed breakdown of consumption. In the most detailed breakdown, consumption is divided into approx. 1,200 different consumption types., Read more about statistical presentation, Statistical processing, The survey is based on a sample where the number of households accounts for about 2,200 out of Denmark's total of approximately 2.8 million households. , The survey included data from three different data sources: Accounting booklets, CAPI interviews and data from registers. In this way the sample can give results which are good approximations for all private households. The data from the 3 different sources are validated. We are constantly looking at how we can improve and compile the statistic in a more efficient way., Data is collected annually from approximately 1,100 households and the sample for one years household budget survey is based on the sample from two years. All expenses, income, etc. are converted to the price and volume level of the end year., Read more about statistical processing, Relevance, In addition to the general public the Household Budget Survey has a wide application. Internally in Statistics Denmark during the compilation of national accounts and price indexation. Public authorities' planning and feasibility studies, etc. Internationally, where especially EUROSTAT is very active in order to establish comparable figures between countries. Research in a number of areas, as well as for marketing purposes., Read more about relevance, Accuracy and reliability, With only 12 pct. of the households who have been contacted participating in the Household Budget Survey. This creates uncertainty, not least for detailed consumer groups. For total consumption, this means that there is an uncertainty margin of +/- 1.8 per cent. while that for that for bread is 2 per cent. and 24 per cent. for a rarely purchased item such as offal. There is underreporting in a number of areas such as alcohol, tobacco, prostitution and undeclared work. The uncertainty is greater when data is based on accounting rather than interviews, and it will be greater if one looks at smaller subgroups of households., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately12 months after the end of the reference year. The statistics are usually published according to the time announced. , Read more about timeliness and punctuality, Comparability, The Household Budget Survey is conducted in accordance with guidelines from the European statistical agency Eurostat. Comparable figures are published by Eurostat. Since 1994, the survey has been methodologically rearranged and is now conducted annually by the same method and on a comparable basis., Data for 2014 and onwards are based on a two-year-old sample and COICOP5 nomenclature (Classification of Individual Consumption). To ensure comparability and continuity over time, data from 1994 to 2013 were recalculated in compliance with the new nomenclature in both current and constant prices, From 2023 onwards, data is based on the COICOP2018 nomenclature. To ensure comparability and continuity over time, data from 2015 to 2022 has been recalculated according to new nomenclature in both current and fixed prices., Read more about comparability, Accessibility and clarity, The Danish Household Budget Survey is 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 , Household Budget Survey, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/household-budget-survey

Documentation of statistics

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