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An overview of the Danish economy

Combining the selection of indicators presented below provides a general view of the state of the Danish economy. What is the growth rate of the economy and how is it going with government finances and inflation? What is the situation of the labour market and the housing market? What expectations do economic operators have for the future and what is the outlook for the green targets? Dive into the numbers by clicking the graphs., Danish economy here and now, Consumer expectations, i,   , -13.1, Feb/26, Information, ×, Consumer expectations of the economic situation of not only themselves but also Denmark as a whole, now and in one year , Consumer price index, i,   , 0.8, % Jan/26, Information, ×, Percentage change in the consumer price index total against the same month the preceding year , Core inflation, i,   , 1.9, % Jan/26, Information, ×, Percentage change in the consumer price index excl. energy and unprocessed foodstuff against the same month the preceding year , Retail trade index, i,   , 99.7, Dec/25, Information, ×, Index, 2021=100, quantity indicies seasonally adjusted , Business sentiment indicator, i,   , 103.3, Feb/26, Information, ×, Index=100 calculated as the average for the period 1998 - 2024 , Industrial production index, i,   , 126.4, Dec/25, Information, ×, Index, 2021=100, seasonally adjusted , Bankruptcies, i,   , 175, Jan/26, Information, ×, Bankruptcies in active companies, seasonally adjusted , Persons in employment, i,   , 3,078,702, Dec/25, Information, ×, Total number of employees in the business sector, seasonally adjusted , Unemployed, i,   , 89,480, Dec/25, Information, ×, Most recent number of unemployed persons from either the unemployment indicator or the gross unemployment. Seasonally adjusted, full-time persons , Other indicators, Economic growth (GDP), i,   , 0.2, % Q4/25, Information, ×, Real growth in per cent against the preceding period, seasonally adjusted , Production index of the service sector, i,   , 100.0, Nov/25, Information, ×, The change in the production index for service industries compared to the previous month. , Government surplus/deficit (% of GDP), i,   , 4.5, % 2024, Information, ×, Government EMU surplus or deficit as per cent of GDP , Government debt (% of GDP), i,   , 30.5, % 2024, Information, ×, Government EMU debt as per cent of GDP , Exports, i,   , 188,434, mio. kr. Dec/25, Information, ×, Current account revenue in million DKK from goods and services, seasonally adjusted , Balance of payments surplus, i,   , 39,972, mio. kr. Dec/25, Information, ×, Current account net revenue in million DKK, seasonally adjusted , Price development of single-family houses, i,   , 6.4, % Q3/25, Information, ×, Percentage change in the price index against the same quarter the preceding year, seasonally adjusted , Share index, i,   , 1,305, Dec/25, Information, ×, Index 1995=100 for shares in total on OMXC , Development in single-family house sales, i,   , 9.3, % Q3/25, Information, ×, Percentage change in number of sales against the same quarter the preceding year, seasonally adjusted , Price development of owner-occupied flats in Copenhagen, i,   , 14.0, % Q3/25, Information, ×, Percentage change in the price index against the same quarter the preceding year for owner-occupied flats in the city of Copenhagen, seasonally adjusted , Interest rates, i,   , 2.76, % Jan/26, Information, ×, Average bond yield for all listed bond series (government and mortgage bonds, etc.) , Greenhouse gas emissions, i,   , 38,785, 1.000 ton 2023, Information, ×, The emission of greenhouse gases stated in 1000 tonnes from Danish territory, incl. LULUCF and excl. CO2 from biomass , Share of renewable energy, i,   , 48.4, % 2024, Information, ×, Renewable energy share in per cent of total final energy consumption ,  

https://www.dst.dk/en/Statistik/temaer/overblik-dansk-oekonomi

Documentation of statistics: Manufacturers’ Purchases of Goods and Services

Contact info, Short Term Statistics, Business Statistics , Morten Skovrider Kollerup , +45 24 52 61 68 , MSL@dst.dk , Get documentation of statistics as pdf, Manufacturers Purchases of Goods and Services 2023 , Previous versions, Manufacturers’ Purchases of Goods and Services 2022, Manufacturers’ Purchases of Goods and Services 2021, Manufacturers’ Purchases of Goods and Services 2020, Manufacturers’ Purchases of Goods and Services 2019, Manufacturers’ Purchases of Goods and Services 2018, Manufacturers’ Purchases of Goods and Services 2017, Manufacturers’ Purchases of Goods and Services 2016, Manufacturers’ Purchases of Goods and Services 2015, Manufacturers’ Purchases of Goods and Services 2014, Manufacturers’ Purchases of Goods and Services 2013, Manufacturers’ Purchases of Goods and Services 2012, The purpose of the statistics is to give detailed information about the input structure of industrial production. The input measured is raw and auxiliary materials used in the processing and production of commodities, packing materials, and purchases of services. The data are divided by detailed industrial groups (NACE-groups). , The main use of the survey is in the National Accounts., Statistical presentation, The survey describes the use of raw materials, semi-manufactured products, intermediary products, purchase of services, and packing costs in the production of industrial commodities., The statistics are distributed to groups of industries., Read more about statistical presentation, Statistical processing, The reported data are validated and aggregated. In addition, imputations are made for non-response. But there is no grossing up, and the published figures cover only the covered enterprises (at least 50 employees or yearly turnover of 100 mio. DKK)., Read more about statistical processing, Relevance, The most important user of the statistics is the National Accounts, but they are also used in research and for analytical purposes., Read more about relevance, Accuracy and reliability, The statistics have a quality concerning the description of purchases by the covered enterprises, i.e. enterprises with at least 50 employees or a yearly turn over of at least 100 million DKK. It can be considered a lack in quality that purchases by smaller enterprises are not included, as these purchases are presumably different from purchases of the largest enterprises., The statistics do not cover the entire Manufacturing industry, but only enterprises with over 50 employees or an annual turnover of DKK 100 million. DKK and thus cannot say anything about the smaller enterprises' purchases, as their purchases must be assumed to be different. The detailed distribution of the individual commodity codes is subject to some uncertainty, as these are often based on an estimate. The total purchase for the covered enterprises is less uncertain, as only less than 2 per cent of responses are missing and last year's purchases figures are used for these enterprises., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published mid-March, i.e. 10.5 months after the end of the reference period. Punctuality is very high., Read more about timeliness and punctuality, Comparability, The statistics are comparable since 2002, as no significant changes have been made since then., Read more about comparability, Accessibility and clarity, The statistics are published in StatBank Denmark., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/manufacturers--purchases-of-goods-and-services

Documentation of statistics

Documentation of statistics: The Use of Cereals

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 2024 , Previous versions, 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/the-use-of-cereals

Documentation of statistics

Labour Force Survey (LFS)

For further details see the subject pages and the papers present on this site.

https://www.dst.dk/en/Statistik/dokumentation/metode/aku-arbejdskraftundersoegelsen

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

Documentation of statistics: Indices of Earnings for the Public Sector (Discontinued)

Contact info, Personal Finances and Welfare , Get documentation of statistics as pdf, Indices of Earnings for the Public Sector 2019 , Previous versions, Indices of Earnings for the Public Sector 2018, Indices of Earnings for the Public Sector 2017, Indices of Earnings for the Public Sector 2016, Indices of Earnings for the Public Sector 2015, Indices of Earnings for the Public Sector 2014, The purpose of the index is to indicate trends in wages paid in the public sector (central and local governments) analyzed by main sectors of economic activity. The index covers more or less all employees in the public sector, including salaried employees, apprentices and young employees under the age 18. Data are mainly extracted from the public pay transfer systems and refer to the second month in the quarter of interest. The published index is broken down by main sectors of economic activity (38-grouping of NACE rev. 2), and indicate trends in relation to the basic quarter (first quarter of 2005) and in relation to the same quarter of the previous year. Since the release of the third quarter of 2008 there has been a change in the base period of the index, which is now the first quarter of 2005., Statistical presentation, The index is based on information on wages obtained from more or less all employees in the public sector. Data are mainly extracted from the public pay transfer systems and refer to the second month in the quarter of interest. The published index is broken down by main sectors of economic activity (38-grouping of NACE rev. 2), and indicate trends in relation to the basic quarter (first quarter of 2005) and in relation to the same quarter of the previous year. , From the first quarter of 2013 a new delimitation regarding the categorizing of sectors (state, regional, municipal or private) came into force. The new sector delimitation now follows the same principles as the one applied for the national accounts. The previous delimitation of sectors is available until the fourth quarter of 2013. , This documentation of statistics relates to the index of average earnings with the base period 1. quarter of 2005=100. The documentation of statistics with the base period 1. quarter of 1995 is attached as an annex., Read more about statistical presentation, Statistical processing, Data are collected for more or less all persons employed in the public sector in Denmark and refer to the second month of the quarter in interest. Before production of the index is started, the data are roughly searched for errors. But there are also performed search for errors later in the process, e.g. by looking at the rate of increase in the average wages for each company or organisation. Each employment is given a weight after the share of hours worked in relation to a full-timer’s normal hours, which is used when adding observations to calculate the rate of increase for an enterprise or branch of economic activity., Read more about statistical processing, Relevance, Private enterprises and organizations 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, Since the index is based on information on wages obtained from more or less all publicly employed persons through public pay transfer systems, the accuracy and reliability of the index is considered to be high. At the same time, there are some small uncertainties regarding the index which it is a good idea to be aware of when applying the index., Read more about accuracy and reliability, Timeliness and punctuality, The index of average earnings is published approximately 45 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, Improvements in the index are continuously being made. If major errors have been rectified, the index has, as far as possible, been revised back to the first quarter of 1995 when calculations of the index began. From the first quarter of 2013 a new delimitation of sectors (state, regional, municipal or private) has been applied. Hence causing a breach in the data between the fourth quarter of 2012 and the first quarter of 2013. , The index of average earnings in the public sector, is comparable and in many ways similar to the , index of average earnings for Corporations and Organisations, . Internationally, the index is to some degree comparable to wage indices of the public sector in other countries., 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-earnings-for-the-public-sector--discontinued-

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: Highest Education Attained

Contact info, Population and Education, Social Statistics , Lars Peter Smed Christensen , +45 20 42 35 51 , LPC@dst.dk , Get documentation of statistics as pdf, Highest Education Attained 2024 , Previous versions, Highest Education Attained 2023, Highest Education Attained 2022, Highest Education Attained 2021, Highest Education Attained 2020, Highest Education Attained 2019, Highest Education Attained 2018, Highest Education Attained 2017, Highest Education Attained 2016, Highest Education Attained 2015, Highest Education Attained 2014, Highest Education Attained 2013, The purpose of the statistics on educational attainment is to give an overall statistical description of the educational level of the population at any given time. The primary data source to these statistics is the Student Register with data from 1970 onwards. In addition, the Qualification Register is used. Since the Student Register is the primary source for information, the Attainment Register gives nearly complete coverage from 1970 onwards. There is, however information before this time coming from The Qualification Register., Statistical presentation, The Attainment Register gathers information about the highest completed education for each single person based on the information in the Student Register and the Qualification Register. It is a longitudinal register based on an assessment of each person's education "career" and shows how the qualification career develops over time. The register is formed by interpreting the qualification career (skills in chronological order) in order to determine a change in the skill level. Once a year a status register is also produced with the population and information about education the 30. September the current year., Read more about statistical presentation, Statistical processing, The Attainment Register is a longitudinal register based on a assessment of each persons education career in The Student Register and The Qualification Register. It shows how the qualification career develop over time, and it is updated once a year. The status register is produced on the basis of the longitudinal register and contains information about the population and their highest completed education per. September 30 the given year., Read more about statistical processing, Relevance, There is a great variety of users. The information is generally used in connection with describing the population or sections hereof. The register is used in connection with status reports for other statistical fields. Data reports are thus submitted for (mainly on the population's highest level of education completed) a wide number of integration registers operated by Statistics Denmark. Furthermore, the register is frequently used in connection with external service activities order by Danish ministries, municipalities, research institutions, professional organization, private enterprises, private individuals and, not least, requests made by the news media., Read more about relevance, Accuracy and reliability, The Accuracy and reliability vary depending on the source of information. More than 80 pct. of the information comes from administrative sources, such as student systems of educational institutions, which are highly reliable. These sources have priority one when the registry is created and will be used if there is information from one of these sources. Other sources are not so closely linked to the education programs and will often be less reliable. Examples of these sources are the surveys of immigrants' education and the population and housing census in 1970, based on self-reported education. In addition, information is imputed for persons who do not respond in the study of immigrants' education. The imputed data is useful in overall statistical statements, but cannot be considered as valid information on individuals' educational attainment. , In connection with the annual reports from the education institutions there is information which also relate to previous years. These delayed notifications concern particularly the last year., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published around 6 months after the end of the reference time. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The longitudinal register is produced once a year and the entire period is thus calculated in the same way. Based on the longitudinal register, a status register is produced with the population per. September 30 that year. In the event of significant changes in the way the longitudinal register is produced, the status registers for all years will be reproduced. It happens that an education changes level from one year to the next. Typically, this will not cause a reproduction of all the status registers and therefore affect comparability over time. Labor force survey provide information too Eurostat about the educational attainment level and this is these figures that are used for international comparison of the attainment level., Read more about comparability, Accessibility and clarity, Statistics are published once a year in "News from Statistics Denmark" . At the same time data are released in the Statbank and on the homepage: , Homepage, Information also appears in the annual publications Statistical 10-Year Review and the Statistical Yearbook., Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Environmental Multiplier Tables

Contact info, National Accounts, Climate and Environment, Economic Statistics , Peter Rørmose Jensen , +45 40 13 51 26 , PRJ@dst.dk , Get documentation of statistics as pdf, Environmental Multiplier Tables 2023 , Previous versions, Environmental Multiplier Tables 2022, Environmental Multiplier Tables 2021, Environmental Multiplier Tables 2020, Environmental Multiplier Tables 2019, Environmental Multiplier Tables 2018, Environmental Multiplier Tables 2017, Dissemination of environmental multipliers is a service for users interested in the interaction between the environment and the economy. The multipliers connect environmental statistics with national accounts statistics at a detailed level and provides a picture of the effects that changes in economic final demand have on selected environmental variables. The environmental multipliers are aggregated measures of the total environmental effect on industries of specific changes in final demand in terms of waste generation, water consumption, generation of waste, CO2 emissions or other impacts., Statistical presentation, The environmental multiplier tables are organized in the following way. Firstly, they contain a reproduction of certain environmental data, which are also found in the Green National Accounts. Secondly, they contain an estimate of some direct effects calculated as the relative share between the same environmental data by industry and and central national accounts variables, typically total output by industry. Finally, the tables contain direct effects (in one industry) and indirect effects (all involved industries) of various types of final demand calculated with an input-output model., Read more about statistical presentation, Statistical processing, This statistics is based on two already published sources, namely the green national accounts and input-output tables. Thus, data was not collected specifically for this statistic. Certain parts of the two sources are reproduced in the tables, but the primary contribution lie in the use of an input-output model that contains both physical environmental data and economic national accounts data in the form of input-output tables. This hybrid model is used in various configurations to calculate so-called indirect (multiplier) effects., Read more about statistical processing, Relevance, Users are, in principle, all who are interested in the extent to which different types of demand (consumption, investment, exports) have an impact on the environment (e.g. CO2 emissions, water consumption or waste) and in which industries the direct effect appears and which derived effects appears other industries. The tables thus link environmental issues with aspects of economic development and should therefore be of interest to users working with integrated planning of economic and environmental development., Read more about relevance, Accuracy and reliability, The multipliers are the result of model calculations, which are based on national accounting statistics and input-output tables. In each section, polls and adjustments are made under assumptions, which together mean that the calculation process builds some uncertainty about the figures. At the most detailed level, therefore, one can not necessarily expect the results to be accurate representations of reality. Conclusions from the tables should be drawn with some caution, taking account of the uncertainties that may arise in the various stages of the process., Read more about accuracy and reliability, Timeliness and punctuality, The tables have so far been published punctually in relation to the pre-announced release date. The multiplier tables, based on the energy accounts, are published for the first time approx. 6 months after the end of the reference year, while the emission multipliers are published in the first version approx. 10 months after the end of the reference year. Final figures are published at the same time as the national accounts become final, approx. 36 months after the end of the reference year., Read more about timeliness and punctuality, Comparability, The statistics are fully comparable over time. The two source statistics are both consistent over time. Multipliers are calculated at constant prices, which is necessary to get a correct impression of the development in an economic time series. This is not statutory statistics, but to the extent that other countries have produced a similar statistic, the results should be fully comparable, as it is known as internationally known source data and calculation methods., Read more about comparability, Accessibility and clarity, Data is only disseminated in the StatBank under , Green National Accounts, , and statistics are not reported to international bodies. There are so far no publications related to it., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/environmental-multiplier-tables

Documentation of statistics

Documentation of statistics: Water and Waste Water

Contact info, National Accounts, Climate and Environment, Economic Statistics , Michael Berg Rasmussen , +45 51 46 23 15 , MBR@dst.dk , Get documentation of statistics as pdf, Water and Waste Water 2024 , Previous versions, Water and Waste Water 2023, Water and Waste Water 2022, Water and Waste Water 2021, Water and Waste Water 2020, Water and Waste Water 2019, Water and Waste Water 2018, Water and Waste Water 2016, Water and Waste Water 2014, The statistics concerning water and waste water estimates the abstraction and use of water as well as discharge of waste water distributed on municipalities., The water account document abstraction of water, use in households and industry groups (as used in the Danish National Accounts) as well as the discharge of waste water via waste water treatment plants to the aquatic environment. The water accounts are based on water and waste water statistics as well as micro-data from the Jupiter database managed by GEUS (Geological Survey of Denmark and Greenland) and reports on point sources from the Danish Environmental Protection Agency., The economic water account document the income in water supply and waste water treatment plants from households and industry groups. The account is based price information from water supply and waste water companies that are member of DANVA, information on individual companies, population, households as well as the physical water account., Statistical presentation, The water account consist of a physical and an economic part. The physical water account document abstraction of water, use well as the discharge of waste water to the aquatic environment in households and 117 industry groups as used in the other parts of the environmental economic account and in the ordinary Danish National Accounts. The economic water account document the income in water supply and waste water treatment plants from households and industry groups. The water accounts are prepared annually and published in Latest releases from Statistics Denmark and in StatBank Denmark., The water account is a module in the environmental economic accounts for Denmark. Read about the , environmental economic accounts, ., Read more about statistical presentation, Statistical processing, Statistics Denmark prepares water statistics based on data from GEUS on abstraction of water and waste water statistics based on data from the Danish Environmental Protection Agency. The distribution of abstraction of water, use of water and discharge of waste water between industrial groups as well as the cost are based on a number of additional sources., Read more about statistical processing, Relevance, Water accounts and statistics are of relevance for administrative bodies, researchers, NGOs, businesses, the educational sector and individuals - all with interests in water, pollution, resources, economic-environmental interactions, etc. To ensure international comparability, the waste accounts are prepared according to the UN statistical standard SEEA (System of Environmental-Economic Accounting) 2012., Read more about relevance, Accuracy and reliability, The coverage of data abstraction water is assessed to be high. However, for fish farming the information may be insufficient. Therefore missing values have been imputed., The coverage of data on waste water discharge is assessed to be high, as the information by law has to be included in development water management plans., The coverage of data on abstraction of water, flows and deliveries to end users is assumed to be high., The distribution on industrial groups - especially the 117 level - is subjected to some uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics as well as physical and economic accounts have been published on time 11 months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The methods and data sources for the Water Accounts are unchanged throughout the period covered by published figures (2010-). International comparison is possible with all other national water accounts based on UN's statistical standard SEEA 2012., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistics Denmark and in the Statbank. They will also be part of future publications from Statistics Denmark on Environmental-Economic Accounts (Green National Accounts)., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/water-and-waste-water

Documentation of statistics