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Documentation of statistics: Sales of food and beverages to food service

Contact info, Food Industries, Business Statistics , Martin Lundø , +45 51 46 15 12 , MLU@dst.dk , Get documentation of statistics as pdf, Sales of food and beverages to food service 2024 , Previous versions, Sales of food and beverages to food service 2023, Sales of food and beverages to food service 2022, Sales of food and beverages to food service 2021, Sales of Organic Products to Foodservice 2020, Sales of Organic Products to Foodservice 2019, Sales of Organic Products to Foodservice 2018, Sales of Organic Products to Foodservice 2017, Sales of Organic Products to Foodservice 2016, Sales of Organic Products to Foodservice 2015, Sales of Organic Products to Foodservice 2014, Sales of Organic Products to Foodservice 2013, The purpose of the statistics Sales of food and beverages to food service is to provide an overall picture of sales of food and beverages to commercial kitchens, restaurants, institutions, etc. There is a special focus on organic foods, as a supplement to Retail sales of organic foods. The statistics have been compiled annually since 2013 with grant funding from the Ministry of Food, Agriculture and Fisheries., Statistical presentation, The statistics are an annual web-based questionnaire survey on wholesalers' sales of food and beverages to the foodservice area - i.e. commercial kitchens, restaurants, institutions, etc. – i.e. companies and institutions where food is served. The questions relate partly to total turnover for foodservice, partly to turnover for organic foodservice, distributed over a limited number of product groups and customer groups. The turnover is calculated in terms of value (DKK million) and quantity (tons)., Read more about statistical presentation, Statistical processing, Data for the statistics is collected via a questionnaire-based total count of food wholesalers with over 40 million DKK in turnover. Data is validated in connection with the collection in an online form. Data is subsequently checked and corrected after re-contact with the food wholesalers. Data is then summed up for statistics and key figures are calculated., Read more about statistical processing, Relevance, The purpose of the statistics is to provide an overall picture of sales of food and beverages to commercial kitchens, restaurants, institutions, etc. There is a special focus on organic foods, as a supplement to the statistics Retail sales of organic foods. Foodservice has become more important in recent years and a group of industry organizations and companies have wanted comprehensive statistics on the area. The statistics are also included in the formulation and follow-up of objectives for organic food service., Read more about relevance, Accuracy and reliability, Since the statistics are a total count of companies with over 40 million in turnover, there is no sampling error. Smaller companies' sales are not known, but based on the total turnover, it is estimated that less than 5 percent of total sales to foodservice are from these companies. More than 95 percent of the companies have answered the survey. For some companies, it is difficult to obtain the figures for the survey. These have provided best estimates instead. The total sales are more certain than sales divided into product or customer groups., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 9 months after the end of the reference period. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, There are no common guidelines for international statistics on foodservice., The statistics can be compared to a limited extent with the Retail turnover of organic food. However, this survey measures retail turnover including VAT, in contrast to Sales of food and beverages to foodservice, which measures wholesale turnover excluding VAT., Read more about comparability, Accessibility and clarity, The statistics are published in news release from Statistics , Nyt fra Danmarks Statistik, under the subject Miljø og Energi, Økologi (in Danish only). Statistics Bank publishes figures for Sales of organic goods for foodservice under the subject , Environment and Energy, Ecology, . See more on the statistics' , Subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sales-of-food-and-beverages-to-food-service

Documentation of statistics

Documentation of statistics: The annual and quarterly working time accounts before the 2016 revision (Discontinued)

Contact info, Labour Market , Get documentation of statistics as pdf, The Annual and Quarterly Working Time Accounts Before the 2016 revision 2016 Quarter 1 , Previous versions, The Annual and Quarterly Working Time Accounts 2014 Quarter 3, The Annual and Quarterly Working Time Accounts 2014 Quarter 4, The Annual and Quarterly Working Time Accounts 2015 Quarter 1, The Annual and Quarterly Working Time Accounts 2015 Quarter 2, The Annual and Quarterly Working Time Accounts 2015 Quarter 3, The Annual and Quarterly Working Time Accounts 2015 Quarter 4, The Danish Working Time Accounts (WTA) is an integrated statistics with consistent time series on employment, number of jobs, hours worked and compensation of employees in both annual and quarterly basis. The current time series goes back to 2008 (quarterly statistics as from the 1st quarter of 2008)., Statistical presentation, The Working Time Accounts produce integrated statistics with consistent time series on employment, jobs, number of hours worked and compensation of employees on an annual and quarterly basis. The data basis is made up by a number of primary statistical data, which are adapted and adjusted to achieve agreement of the concepts and definitions used in the WTA system., The statistical sources used in the WTA are: , The Register-Based Labour Force statistics (RAS), , Establishment-related employment statistics (ERE statistics), , The Structural Earning Statistics (SES), , Employment Statistics for Employees (BfL) og , The Labour Force Survey (LFS)., Read more about statistical presentation, Statistical processing, The population and concepts as well as levels of the variables are defined by annual structural data sources. Short-term data sources are applied in projecting these levels over the months of the year and in periods for which structural data are not available. Summation of the data in the Working Time Account is conducted before they are projected. Data in the Working Time Account are seasonally adjusted both for use in Denmark as well as for use in Eurostat’s STS. The system contains a data-editing system, a correction system and a dissemination system., Read more about statistical processing, Relevance, Users interested in the social and economic statistics have expressed satisfaction with the quality of the statistics. However, they also expressed frustration over large data breaches, especially in the transition to e-Income-based sources., Read more about relevance, Accuracy and reliability, There are no calculations of the measures of accuracy., See section quality assessment., Read more about accuracy and reliability, Timeliness and punctuality, Working hours are regularly published in accordance with Statistics Denmark's benchmark goals. , For quarterly statistics concerned, this goal implies that the publications to be released at the latest by the end of the following quarter. For the sake of short-term business regulation (STS), this implies that the WTA to be published typically by the middle of the last month of the following quarter. (The requirement for most employment series for STS is 2 months and 15 days). For annual statistics concerned, this implies that publications to be released at the latest by the end of the following year. In the interest of national accounts the annual WTA will be published in June with provisional figures for the previous year. This makes the annually WTA for the year , t, to be published in the same month as the publication of the quarterly WTA for the period , 1 quarter t +1, . , The transition to the new WTA resulted, however, that annual WTA 2011, based on the new eIncome sources, were not published until December 2012, whereas the publication of the quarterly statistics has not given rise to any delay., Read more about timeliness and punctuality, Comparability, WTA deliver labour market data to Eurostat's corporate short-term regulation (STS) and the national accounts (ESA / ESA). Therefore, changes in these regulations typically result in changes in the WTA. A description of the transitional tables between the WTA and the National Accounts can be found in the publications on the National Accounts. Transitional tables between the WTA and the Register-based Labour Force Statistics and the Establishment-related Employment Statistics are published in Statistical News ("Statistiske Efterretninger") for the annual WTA., Read more about comparability, Accessibility and clarity, The statistics are published in: , News from Statistics Denmark (Nyt fra Danmarks Statistik), , in the series Statistical News ("Statistiske Efterretninger") and , in the Statbank Denmark ("Danmarks Statistikbank")., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/the-annual-and-quarterly-working-time-accounts-before-the-2016-revision--discontinued-

Documentation of statistics

Documentation of statistics: Social benefits for senior citizens

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

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

Documentation of statistics

Documentation of statistics: Purchases and sales by enterprises

Contact info, Short Term Statistics , Lina Pedersen , +45 51 68 72 80 , LIP@dst.dk , Get documentation of statistics as pdf, Purchases and sales by enterprises 2024 , Previous versions, Purchases and sales by enterprises 2020, Purchases and sales by enterprises 2019, The purpose of the statistics Purchases and sales by enterprises is to monitor business cycles in Denmark, based on sales of enterprises. The statistics is based on information on value added tax (VAT) reported by the enterprises to the Danish Tax Authorities. , The statistics is compiled and disseminated monthly and provides a short-term status of Danish business economy. The statistics have been published with variation in calculation methods and frequencies, since value added tax (VAT) was introduces in Denmark in 1967. In its current form, the statistics is comparable from 2011 onwards., Statistical presentation, Purchases and sales by enterprises is a monthly statement of purchases and sales of goods and services. The Statement is calculated in millions (Danish kroner). The statement is calculated at industry level defined in the Danish Industrial Classification of All Economic Activities 2007 (DB07). In addition, the statistics are divided into domestic purchases and sales. , Read more about statistical presentation, Statistical processing, Data originates from the Danish Tax Agency’s VAT registers plus information from the Central Business Register (CVR). Missing reports are replaced with imputed values, which are values estimated for each missing report. Imputed values are provisional and removed when the enterprise has reported VAT to the Tax Agency or the enterprise's business status in the CVR register is updated as inactive. The report follows the enterprise's main industry. , Read more about statistical processing, Relevance, Users of the statistics are ministries, researchers, students and organizations. Used for e.g. analysis of business trends and market research. In Statistics Denmark, the statistic provides supporting information to e.g. the National Accounts and statistics on foreign trade. Data contribute to the Danish compliance with requirements in the European business statistics regulation regarding turnover on industries on service and trade. In order to comply with requirements, monthly turnover must be distributed to Kind of Activity Units (KAU). A model is used to split legal units into KAU. , Read more about relevance, Accuracy and reliability, The statistics is based on VAT, reported by enterprises to the Tax Agency. The precision is strengthened by the fact that all companies subject to VAT are included. It is weakened by too little information sales not subject to VAT, e.g. train tickets and recycled clothes. The reliability increases as the enterprises report and revise values. It's possible to revise up to three years after submission. Values are considered final after three years. The sales are used as an estimate for turnover. Please notes that turnover includes more than sales, e.g. revenue from investments., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximate 40 days after the end of the reference period. The statistics contain a statement of sales that are subject to VAT. A statement of an enterprise's sales subject to VAT can be used as an estimate of the enterprise's turnover, which is why the statistics are used for short-term statistics on turnover. The publication date is announced at least 6 months in advance, and it is rare that a publication of the statistics is delayed. , Read more about timeliness and punctuality, Comparability, From 2010, the statistics are based on register data, the information on VAT that enterprise report to the Tax Agency. From the year 2010, data is comparable year to year, as it includes all enterprises that report VAT. The variable "salg i alt" can be used as estimate for the enterprises' net turnover and can be compared with the net turnover in other statistics, e.g. General Enterprise Statistics. When comparing, take into account the differences, for example which types of sales or revenue are included, whether excise duties are included, and whether smaller companies are included. , Read more about comparability, Accessibility and clarity, The statistics are published on the webpage , StatBank Denmark, under the topic Purchases and sales by Enterprises. Until December 2023, the statistics was published monthly in a Danish newsletter called NYT. , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/purchases-and-sales-by-enterprises

Documentation of statistics

Documentation of statistics: Services of service industries

Contact info, Business Dynamics, Business Statistics , Emil Tappe Bang-Mortensen , +45 24 67 85 25 , EBM@dst.dk , Get documentation of statistics as pdf, Services of service industries 2024 , Previous versions, Services of service industries 2023, Documents associated with the documentation, Anden virksomhedsrådgivning (Spørgeskema 2023) (pdf) (in Danish only), Arkitektvirksomhed (Spørgeskema 2023) (pdf) (in Danish only), Bogføring, revision og skatterådgivning (Spørgeskema 2023) (pdf) (in Danish only), It-servicevirksomhed (Spørgeskema 2023) (pdf) (in Danish only), Juridisk bistand (Spørgeskema 2023) (pdf) (in Danish only), Markedsanalyse og offentlig meningsmåling (Spørgeskema 2023) (pdf) (in Danish only), Reklamevirksomhed (Spørgeskema 2023) (pdf) (in Danish only), Rådgivende ingeniørvirksomhed og anden teknisk rådgivning (Spørgeskema 2023) (pdf) (in Danish only), Teknisk afprøvning og analyse (Spørgeskema 2023) (pdf) (in Danish only), Vikarbureauer (Spørgeskema 2023) (pdf) (in Danish only), The purpose of the statistics Services of Service Industries is to provide information about turnover and types of services provided by enterprises within a number of service industries. The statistics is also used for revision of activity classifications in the Business Statistical Register., The statistics is a part of EU Structural Business Statistics (SBS). Some industries have been covered since 1995, whilst others have been covered since 2007. , In its current form the statistics is comparable from the reference year 2023 where the statistics was changed to only cover enterprises with at least 20 employees. , Statistical presentation, The statistics encompasses 10 sub-statistics where each one provides information on the distribution of total turnover on products and services provide by enterprises in a specific industry according to the classification of products by activity (CPA). , Read more about statistical presentation, Statistical processing, Data is collected by online questionnaire from all enterprises within the population. In the questionnaire the enterprises have to break down their turnover by products and their total exports broken down by residence of client within and outside of the EU. The reported data is checked for errors, for instance by comparing the turnover distribution with previous submissions. The collected data is grossed up to the population level by including turnover from the Accounts Statistics for Non-Agricultural Private Sector. , Read more about statistical processing, Relevance, The statistics is used among enterprises when planning and provides an overview of the development taking place in the service sector. Furthermore the statistics is an input to national accounts in Statistics Denmark regarding the service sector. The statistics is also used of the European Statistic bureau, Eurostat, to create EU-statistics about Business Services., Read more about relevance, Accuracy and reliability, This statistics turnover breakdowns by product is sourced from submission from enterprises that that make up between 96 and 100 pct. of the total turnover within each of the activities. This precision is achieved by having only a few missing enterprises within each activity. Additionally the turnover is aligned with information from the Accounts Statistics for Non-Agricultural Private Sector, which in turn is complied from a large sample, administrative sources and XBRL-accounts from the Danish Business Authority. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published ca. 11 months after the end of the reference year. Usually the statistics is published without delays in regards to the announced publication date. , Read more about timeliness and punctuality, Comparability, For some industries the statistics was first compiled in 1995 and 1996, whilst others were first compiled in 2001, 2003 and 2007. Since then there have been various adjustments and changes to the calculation method, activity codes, sampling method and questionnaire. There is consistent a consistent timeseries for the reference years 2012/2013 to 2021/2022. In its current form the statistics is comparable from 2023 and onwards, covering only enterprises with at least 20 employees. These statistics are produced according to the guidelines in the European Business Statistics Manual, and is thus comparable to similar statistics from other EU countries. , Read more about comparability, Accessibility and clarity, These statistics are published in a danish press release about Services of Service Industries. In the StatBank, these statistics can be found under the subject , Services of service industries, . For more information go to the , subject page, . International comparable figures are available through Eurostat's webpage under , Business Services, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/services-of-service-industries

Documentation of statistics

Documentation of statistics: Business Enterprise Research and Development (BERD)

Contact info, Science, Technology and Culture, Business Statistics , David Boysen Jensen , +45 61 50 73 82 , DBY@dst.dk , Get documentation of statistics as pdf, Business Enterprise Research and Development (BERD) 2024 , Previous versions, Business Enterprise Research and Development (BERD) 2023, Business Enterprise Research and Development (BERD) 2022, Business Enterprise Research and Development (BERD) 2021, Business Enterprise Research and Development (BERD) 2020, Business Enterprise Research and Development (BERD) 2019, Business Enterprise Research and Development (BERD) 2017, Business Enterprise Research and Development (BERD) 2016, Business Enterprise Research and Development (BERD) 2015, Business Enterprise Research and Development (BERD) 2014, Business Enterprise Research and Development (BERD) 2013, Business Enterprise Research and Development (BERD) 2012, The purpose of the R&D statistics of the enterprise sector is to analyse the scope of research and experimental development undertaken within the sector. This is carried out by estimating the resources used in the area, measured in R&D-expenditure and R&D-personnel broken down on industry, size class and the regional level. The survey is conducted in accordance with OECDs guidelines for R&D statistics as described in the Frascati Manual. The Danish data are comparable with the data of other OECD- and EU-countries. , Statistical presentation, The purpose of the R&D statistics is to present the scope of research and experimental development undertaken within the Danish business sector. The aim is to secure detailed statistical information on the R&D activities., Read more about statistical presentation, Statistical processing, The statistics is based on a survey sample of approx. 3,500 units weighted to a frame of approximately 22,000 enterprises. The statistics is compiled in one joint questionnaire which covers both the R&D domain and the innovation statistics. An extensive validation process of the data is carried out. One part of the validations is integrated in the data collection in the dynamic web-questionnaire, another part is carried out after the data collection using micro- and macro validation techniques., Read more about statistical processing, Relevance, Statistics have users in ministry of science, business organizations, researchers, business and students. Statistics are used in publications on research and in international comparisons. R&D statistics is describing the knowledge society. Part of the EU's Innovations Union Scoreboard. Micro-data is available for research through Research Service at Statistics Denmark., Read more about relevance, Accuracy and reliability, To minimize errors the questionnaires are supported with guidelines and instructions. However some data reports are not error-free and may reflect misinterpretations from the respondents which can lead to certain errors., Coefficients of variance (CV) have been compiled for a range of central indicators., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is normally published no later than 12 months after the end of the reference year. Statistics with reference year 2023 was published 1. April 2025., Read more about timeliness and punctuality, Comparability, The statistics is compiled according to the guidelines of the Frascati Manual and the EU Regulation. There are no other comparable Danish R&D-statistics, but the Danish statistics is comparable to the R&D statistics from other EU-member states and OECD-countries. The statistics is from 2007-2016 comparable. There was a break in time series from 2016 to 2017. From 2017-2024 the statistics is comparable., Read more about comparability, Accessibility and clarity, The statistics are published in Focus On Statistics Denmark (Nyt fra Danmarks Statistik) and are available from Statistics Denmark's website at https://www.dst.dk/fui and from the database StatBank Denmark (https://www.dst.dk/statistikbanken). The statistics can also be found at the Eurostat databases (under the STI-domain). For the years 2012-2020 Statistics Denmark published a more extensive publication concerning R&D and innovation: "Innovation og Forskning 2020" (Innovation and research 2020).The publication is available (Danish only) on https://www.dst.dk, Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/business-enterprise-research-and-development--berd-

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: 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) 2026 , Previous versions, Harmonized Index of Consumer Prices (HICP) 2025, 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), 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: 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) 2025 , Previous versions, Purchasing Power Parities (PPP) 2024, 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. Results for 2024, published in December 2025 are presented in accordance with the new COICOP 2018 classification for product groups., 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: Indices of Average Earnings for the Private Sector (Discontinued)

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

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

Documentation of statistics