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      Documentation of statistics: Productivity

      Contact info, National Accounts, Climate and Environment, Economic Statistics , Magnus Børre Eriksen , +45 29 12 27 56 , MBE@dst.dk , Get documentation of statistics as pdf, Productivity 2025 , Previous versions , Productivity 2024, Productivity 2023, Productivity 2022, Productivity 2021, Productivity 2020, Productivity 2019, Productivity 2018, Productivity 2017, Productivity 2015, Productivity 2014, Productivity 2011, The purpose of the statistics Productivity is to examine the change in production per unit of the resources involved and which contributes to the change. The simplest and most commonly used concept of productivity is labor productivity, which is used here. Labor productivity (LP) and the causes for the change in LP is calculated back to 1966., Statistical presentation, Productivity is basically a measure of how efficiently you use your resources (labor, capital, etc.) when producing goods and services. In this statistic it is also calculated which resources contribute most to the change in productivity. Productivity change is distributed across industries for the various productivity components. The statistics are disseminated in News from Statistics Denmark and the StatBank., Read more about statistical presentation, Statistical processing, Labor productivity is defined as the real value of Gross value added (GVA) per hour worked. The calculations are based on figures from market activity from national accounts, i.e. the total economy excluding the sectors: General government (S.13) and NPISH (S.15). The sources used for calculating the productivity growth is fixed capital, Labor force education statistics and sector account figures for Gross value added and hours worked., Read more about statistical processing, Relevance, The national accounts (including Productivity statistics) constitute core indicators of the analyses of economic growth. Users are primary researchers, economic departments and organizations., The division of national accounts continuously evaluates feedback from our users., Read more about relevance, Accuracy and reliability, The precision of the calculation of productivity growth is closely related to the uncertainty of the variables that are included in the calculation. I.e. how well, the value of an hour's work is reflected in the gross value added in fixed prices for the industry; the quality of the calculated hours and whether there are special conditions in the industry that make labor productivity less relevant, e.g. high capital intensity. For multiple industries, labor productivity growth should not stand alone in productivity analyzes. This applies, for example, to dwellings, public administration, education and health., Read more about accuracy and reliability, Timeliness and punctuality, First preliminary version of Labor productivity (LP) for year t is published end of March in year t+1. The final version of LP for year t is published end of June in year t+3. First preliminary version of Productivity growth (Sources of LP) for year t is published no later than December year t+1. The final version of Productivity growth (Sources of LP) is published no later than December year t+3. The productivity statistics are published according to schedule., Read more about timeliness and punctuality, Comparability, This statistic is based on national accounts. Therefore this statistic is consistent with respect to national accounts and comparable over time. Moreover this statistic is comparable to other countries productivity figures if they are also based on ESA2010., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release and in the StatBank under , Productivity, . See more information , here, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/productivity

      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: Car Register and Publications

      Contact info, Short Term Statistics , Karina Moric Ingemann , +45 24 78 42 12 , KAM@dst.dk , Get documentation of statistics as pdf, Car Register and Publications 2024 , Previous versions , Car Register and Publications 2020, Car Register and Publications 2019, Car Register and Publications 2018, Car Register and Publications 2017, Car Register and Publications 2016, Car Register and Publications 1992, The purpose of The Car Register and Publications is to provide a basis for statistics concerning vehicles in Denmark, their owners and users. The statistics have been compiled since 1992, and is in its current state comparable from 1992 and onward. The register forms the foundation for statistic calculation, concerning the population of car availability and purchase of cars, where the vehicles owners and users is visualized using data from the population statistics area. The car register and other registers are also used for statistics and data extracts to internal and external users., Statistical presentation, The Statistics includes monthly and yearly calculations of current and historical information’s about vehicles and their owners. The most significant calculations of the newly registered vehicles, is their use for assessment of households and businesses use and investments. Important information’s about the vehicles is type, use, model and variant, weight and fuel type, owner/user relationship, geographic location as well as purchase price. Stock figures, new registrations and used car trade are calculated, as well as energy efficiency, families' availability of cars and car purchases., Read more about statistical presentation, Statistical processing, Data for the Vehicle Register is collected monthly from the Digital Motor Register (DMR). In addition, data from various registers in Statistics Denmark are collected. The central database tables from DMR are transformed for statistical use. Depending on the purpose, data from the other registers is connected using the owner or user IDs. The series with new registrations, accession of and leasing as well as used car sales of passenger cars are seasonally adjusted. The quality measures for the seasonally adjusted series indicate that there are clear seasonal patterns., Read more about statistical processing, Relevance, The statistics is relevant for short-term assessments (new registers etc.), in the road transport statistics (random sample basis) and to illustrate the populations purchase of and access to vehicles., The basic data of the statistics is included in the government's legal model, in the national accounts and in calculations of the value of the cars of households and businesses, as well as family assets. Data from the register are used to prepare statistics on paid services., The register's vehicle and personal data are also used for other social statistics, including service tasks for a fee., Read more about relevance, Accuracy and reliability, The register and the publications are generally highly precise and reliable with only very limited changes to former published data. These corrections does by experience only result in very limited corrections in the main figures formerly published, i.e. less than 0.5 per mille. , The seasonal adjusted series are of good quality with well-defined seasonal patterns., The number of families in the publications of the families' purchase of or access to private cars are fully compatible with the numbers in the area of population statistics., Read more about accuracy and reliability, Timeliness and punctuality, Newly registered vehicles, monthly: Publishing time 2023 9,75 days. , Energy efficiency for newly registered private cars, yearly: Publishing time 2024 88 days, “Motorparken” yearly: expected publication time 2024 88 days., Families' car purchases, annual: Publication time 2023 183 days., Families car availability, yearly: Publication time 2022 177 days. , The value of newly registered private cars, yearly: publication time 2023 64 days. , The register is updated 3 days after the end of the preceding month's calculations., Read more about timeliness and punctuality, Comparability, The statistics are compiled since 1992, and are comparable from 1992 and onwards., There are only limited differences between the statistical concepts in Denmark and other countries and they have no influence on the main figures., There have since 1994 been a few alterations with respect to employment status/job groups, definition of families, municipalities and weight limits. There is therefore no full comparability over time at a detailed level within these., The transition from CRM to the Digital Motor Register, DMR has caused no breaks in data., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistical Denmark:, Latest article with new registrations in News from Statistics Denmark, Latest article with stock figures in News from Statistics Denmark, Paid services with individual and tailor-made tables as well as research access are obtainable. See:, DST Consulting, Research Services homepage, Documentation of the car register and its data, Segment overview, Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/car-register-and-publications

      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: Regional Accounts

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

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

      Documentation of statistics

      Documentation of statistics: Consumer Price Index

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

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

      Documentation of statistics

      Documentation of statistics: Number of Persons Employed in the Construction Industry

      Contact info, Short Term Statistics , Kasper Emil Dueholm Freiman , +45 23 45 47 32 , KFR@dst.dk , Get documentation of statistics as pdf, Number of Persons Employed in the Construction Industry 2024 , Previous versions , Number of Persons Employed in the Construction Industry 2020, Number of Persons Employed in the Construction Industry 2019, Number of Persons Employed in the Construction Industry 2018, Number of Persons Employed in the Construction Industry 2017, Number of Persons Employed in the Construction Industry 2016, Number of Persons Employed in the Construction Industry 2015, Number of Persons Employed in the Construction Industry 2014, The purpose of the statistic is to show trends in the number of employed within the private construction industry by kind of activity and type of work (new buildings, repair and maintenance of buildings, civil engineering, etc.). The first sample survey of employment in the construction industry was conducted in 1961., Statistical presentation, The statistic provides information on trends in the number of employed within the private construction industry. Employment is analyzed by kind of activity and type of work (new buildings, repair and maintenance of buildings, and other)., Read more about statistical presentation, Statistical processing, The reported data is scaled to the total population of professional units with main activity in construction. No numbers are imputed. The total employment in each construction industry and each type of construction work is seasonally adjusted. The cross between construction industry and type of construction work is not seasonally adjusted., Read more about statistical processing, Relevance, Interest in the statistic is high among users. Users of the statistics are trade associations, banks, politicians, public authorities, international organizations, private business enterprises and the news media. The statistics are a supplement to the other short-term statistics relating to this area., Read more about relevance, Accuracy and reliability, The quality of the statistic is assessed as being high. There are no quantitative measures of the total uncertainty. The sample uncertainty for the total employment is estimated to be approximately 0.5 pct. The uncertainty that results from non-response, wrong reported numbers and misunderstandings has little effect on the numbers. The statistic is reliable in the sense that previously published numbers rarely are revised., Read more about accuracy and reliability, Timeliness and punctuality, The statistic is published four times a year, media January, April, July and October. Time from the census-date to publication is about 9 weeks. The statistic is normally published at the announced time., Read more about timeliness and punctuality, Comparability, I the archive there are unemployment numbers dating back to 1994 Numbers from years before 2000 are not comparable to the new time series. The statistics on employment in the construction industry supplement the other short-term statistics relating to this area., Read more about comparability, Accessibility and clarity, The newest numbers are published at , STATBANK, ., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/number-of-persons-employed-in-the-construction-industry

      Documentation of statistics

      Documentation of statistics: Use of cereals and oilseeds

      Contact info, Food Industries, Business Statistics , Mads Haaning Andersen , +45 51 85 76 27 , MHG@dst.dk , Get documentation of statistics as pdf, The Use of Cereals 2025 , Previous versions , The Use of Cereals 2024, The Use of Cereals 2023, The Use of Cereals 2022, The Use of Cereals 2021, The Use of Cereals 2018, The Use of Cereals 2016, The Use of Cereals 2014, The purpose of the statistics is to compile a grain balance, primarily with the aim of calculating the quantities of grain that go to feed consumption, both for each individual crop and for the total amount of grain. In the grain balance, the amount of grain from harvest and import is calculated, and it is distributed among different uses. The statistics are used to calculate the Economic Accounts for Agriculture. Supply balance sheets for cereals for the crop year have been compiled since 1900/01. Balance sheets for the calendar year have been compiled since 1961. Data in its present form is comparable from 1995 onwards., Statistical presentation, The statistics is an annual calculation of the supply balance sheets for cereals in million kg. The utilization of cereals is calculated both for calendar year and crop years and is published for 6 different cereals and cereals in total. The supply balance sheets contain for each type of cereals statistics on cereals available: harvest, imports and initial stocks, as well as statistics on the use of cereals for different purposes: exports, final stocks, seeds, flour production and other manufacturing, feeding. Moreover, the supply balance sheets are produced based on the origin of the cereals, whether it is produced in Denmark or abroad., Read more about statistical presentation, Statistical processing, The data is collected in biannual and annual questionnaires where the incoming data is checked. Data is from different sources where some are sample surveys and others are censuses why there can be differences in how the further data is calculated. Censuses are aggregated whereas sample surveys are listed according to known target variable. , Read more about statistical processing, Relevance, It is relevant for the agricultural organizations, ministries and agencies, who uses it to follow the development in the use of cereals in Denmark. Moreover it is an input to the Economic Accounts for Agriculture. The users can comment on the statistics in the user committee for agricultural statistics and the users have expressed satisfaction with the statistics. , Read more about relevance, Accuracy and reliability, The utilization of cereals are build on sample surveys for stock of cereals at farms, the harvest of cereals and international trade of goods and the results are therefore subject to some uncertainty. The data on the use of cereals for feeding are subject to some margin of errors, as the use for feeding is calculated as a residual in the balance sheets. The data on the use of cereals for feeding are subject to some margin of errors, as the use for feeding is calculated as a residual in the balance sheets., Read more about accuracy and reliability, Timeliness and punctuality, It is published twice a year- The statistics concerning the crop year, end of period June 30th, is published in January/February together with the feed consumption, approximately 6 months after the end of the reference period. The statistics following the calendar year is published in May together with the Economic Accounts for Agriculture, barely 6 months after the end of the reference period. Data is preliminary until 2,5 years after the end of the reference period. The statistics is punctual and is published without delay., Read more about timeliness and punctuality, Comparability, The utilization of cereals is comparable back to the crop year 1960/61 and the calendar year 1960. Stocks were not a part of the statistics before 1960. It is in compliance with the current EU legislation and it is an input to the Economic Accounts for Agriculture which is comparable to the Economic Accounts for Agriculture published by Eurostat., Read more about comparability, Accessibility and clarity, These statistics are published in the StatBank under , Crop production, . For further information, go to the , Crop production, . , Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/use-of-cereals-and-oilseeds

      Documentation of statistics

      Documentation of statistics: Sales of housing cooperatives

      Contact info, Prices and Consumption, Economic Statistics , Malene Lysdahl , +45 40 38 37 54 , MLY@dst.dk , Get documentation of statistics as pdf, Sales of housing cooperatives 2025 , Previous versions , Sales of housing cooperatives 2024, Sales of housing cooperatives 2022, The purpose of the statistics for cooperative housing is to monitor the price development in the property value of the cooperative housing units traded. The statistics has been produced since November 2023 and covers the period from 2015Q1 and onwards and it is comparable throughout the entire period., Statistical presentation, The statistics for cooperative housing is a quarterly price index for the property value of the cooperative housing units traded. The statistics contains price indices to describe the price development over time and numbers for the use of different valuation principles. The statistics includes all traded cooperative housing units that have been registered through http://www.andelsboliginfo.dk. This registration has been mandatory for the cooperative housing associations since June 1st 2021., Read more about statistical presentation, Statistical processing, Key figures on cooperative housing associations and cooperative housing units are reported to Statistics Denmark through http://www.andelsboliginfo.dk on a quarterly basis. The collected data is validated by Statistics Denmark and enriched with data from the Danish Buildings and Dwellings Register which is validated. Finally, price indices and the distribution of valuation principles are calculated., Read more about statistical processing, Relevance, The statistics are relevant for banks and the financial sector, estate agents, politicians and actors in the cooperative housing sector who use the figures for analyses of price developments and assessments of regulation in the housing market. As there used to be limited statistics on cooperative housing, the statistics contribute to a more transparent housing market., Read more about relevance, Accuracy and reliability, The precision of the calculated price development depends on the hedonic regression which ensures the quality correction of the cooperative housing units sold and on the collected data. The development in the choice of valuation principles in the data from 2015 and onwards is assessed to be fairly accurate., The statistics for cooperative housing is based on information from http://www.andelboliginfo.dk which is a register of sold cooperative housing in Denmark. Thus, the reliability of the preliminary figures is assessed to be acceptable. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics on cooperative housing publishes preliminary quarterly figures two months after the end of the reference period. It has not been decided when the figures are final. The statistics on cooperative housing is published without delay with regards to the planned publications., Read more about timeliness and punctuality, Comparability, Comparable house sales statistics for all EU member states can be found on the , Eurostats website, where figures are published around 100 days after the end of a quarter (reference period)., Read more about comparability, Accessibility and clarity, The statistics for cooperative housing is published on a quarterly basis in the , Statbank, and yearly in , Nyt fra Danmarks Statistik, along with the publication of the 4th quarter., Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sales-of-housing-cooperatives

      Documentation of statistics

      Documentation of statistics: Sales of real property

      Contact info, Prices and Consumption, Economic Statistics , Malene Lysdahl , +45 40 38 37 54 , MLY@dst.dk , Get documentation of statistics as pdf, Sales of real property 2026 , Previous versions , Sales of real property 2025, Sales of real property 2024, Sales of real property 2023, Sales of real property 2022, Sales of real property 2021, Sales of real property 2020, Sales of real property 2019, Sales of real property 2018, Sales of real property 2017, Sales of real property 2016, The statistics for Sales of real estate property measure the number of sales and prices of transactions of Danish real estate properties. The statistics are used for monitoring developments in the real estate market, as well as economic developments. The current price indices link back to 1992. There are price indices for previous years, but there are methodological differences., Statistical presentation, This statistics are published monthly including price and volume trends in real estate transactions, such as one-family houses, owner-occupied flats, agricultural properties and business properties. These statistics contain key figures broken down by category of real estate property, region, type of transfer, price index and period. The statistics include all registered real estate transactions, which include land, both newly built and existing properties., Read more about statistical presentation, Statistical processing, Data concerning the registration of ownership of real estate properties is collected on a monthly basis from the electronic land registration system via Datafordeleren. The data is checked for errors by Statistics Denmark. The individual real estate transactions are divided according to category of real property, region, type of transfer and period. Aggregated figures are then calculated for number of sales, average prices and the ratio between purchase price and appraisal value (spar-value). Finally, the price index is calculated., Read more about statistical processing, Relevance, There is a great interest for the published numbers among users, which follows the currently economic business cycle. The statistics of sales of real properties are relevant for the banking- and financial sector, real estate agents, politicians, researchers and the news media. The users consider the statistics for sales of real estate properties as an important economic indicator. The statistics have a high profile in the press and among other professional users., Read more about relevance, Accuracy and reliability, The precision of the price development is the result of the quality of the appraisals and of the assumptions in the SPAR-method, which seeks to correct the quality of the sold properties in order to measure the pure price development. There is no significant bias in the preliminary figures for the price development, while the preliminary figures for the average prices are underestimated, as they are not corrected for the bias in the registration pattern., Read more about accuracy and reliability, Timeliness and punctuality, The statistics for sales of real property publish preliminary quarterly and annual figures 3 months after the end of the reference period. Monthly figures are published only as final figures. Final figures are available 13 months after the end of the reference period. The statistics are published without delays in the planned releases. , Read more about timeliness and punctuality, Comparability, Comparable house sales statistics for all EU member states can be found on the , Eurostats website, where figures are published around 100 days after the end of a quarter (reference period)., Read more about comparability, Accessibility and clarity, The statistics for sales of real properties is published in , News from Statistics Denmark, . Detailed figures can be found in , StatBank, and in the [Online payment data bank](https://www.dst.dk/betalingsdatabank. Historical figures can be found in the publication series , Ejendomssalg, . , Read more about accessibility and clarity

      https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/sales-of-real-property

      Documentation of statistics
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