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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: Childcare before school start

Contact info, Population and Education, Social Statistics , Jens Bjerre , +45 29 16 99 21 , jbe@dst.dk , Get documentation of statistics as pdf, Childcare before school start 2024 , Previous versions, Childcare before school start 2023, Childcare before school start 2022, Childcare before school start 2021, Childcare before school start 2020, Childcare before school start 2019, Childcare before school start 2018, Childcare before school start 2017, Childcare before school start 2016, The purpose of the statistics Childcare Before Starting School is to shed light on the extent of and the resources used for childcare in day care services for children below school age. The statistics are used to compare the allocation of resources across municipalities. Data is available dating back to 1943, but in its current form, the statistics are comparable from 2015 onwards, when the method of calculation was changed to full-time units., Statistical presentation, The statistics provide an annual overview of the number of enrolled children and the number of staff with pedagogical responsibilities in municipal and independent day care institutions as well as pool scheme institutions and municipal day care. Both children and staff are measured in full-time equivalents (FTEs)., The statistics also include staffing ratios, calculated as the ratio between children and staff. The ratios are gross staffing levels, meaning that all working hours are included, including time for planning and parent meetings. Adjustments are made for parental leave, substitutes are included, and both pedagogical leaders and centrally based support staff are part of the calculation., Read more about statistical presentation, Statistical processing, Information on enrolled children and employees are obtained primarily from registration in municipalities through the municipalities' and regions' payroll office. Data is examined for errors and all municipalities validate their data in dialogue with Statistics Denmark., Read more about statistical processing, Relevance, There are different and diverse users of the statistics. The Danish Ministries use the statistics to compare the resource allocation to childcare in different municipalities and to develop policies on child care. Interest organizations, such as the National Association of Pedagogues (BUPL), the National Associations of Municipalities (KL) and The Association of Parents (FOLA) use the statistics to assess the service level in the childcare area. Data has been collected on an agreement between Statistics Denmark and the Ministry of Children and Education., Read more about relevance, Accuracy and reliability, The inventory for 2024 has information from all 98 municipalities. The accuracy is affected by errors in municipal registrations and whether keys for distributing staff in age groups 0-2 and 3-5 years in 0-5 year institutions are correct. Employees and children from private institutions are not included in the statistics, because of an unrealistic high or low ratio of children pr. employee in such institutions. Moreover uncertainty comes from single registration errors that do not give systematic errors in the calculation., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approx. ten months after the end of the reference year. The statistics are published without delay in relation to the pre-announced release date in the release calendar., Read more about timeliness and punctuality, Comparability, Statistic on childcare can be dated back to 1943. From 1975 it was the number of children enrolled in the age groups 0-2 years and 3-6 years. Until 2004, the date of measurement was a day in spring, but from 2004 it becomes the first of October. As of 2015, children and staff are measured as full-time units. This gives a lower number of children and staff compared to before 2015. Figures from before 1983 can be found in statistical yearbooks, while figures from 1983 onwards can be found at the Statbank. Statistics on childcare do not have common guidelines across countries., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release, at the same time as the tables are updated in the StatBank. In the StatBank, statistics on the number of children enrolled in institutions, pedagogical employees, the ratio between children and employees and the number of institutions can be found under the subject , Childcare, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/childcare-before-school-start

Documentation of statistics

Documentation of statistics: Maritime Transport over Danish Ports

Contact info, Short Term Statistics, Business Statistics , Heidi Sørensen , +45 24 79 86 81 , HSN@dst.dk , Get documentation of statistics as pdf, Maritime Transport over Danish Ports 2025 Quarter 1 , Previous versions, Maritime Transport over Danish Ports 2024 Quarter 1, Maritime Transport over Danish Ports 2023 Quarter 1, Maritime Transport over Danish Ports 2022 Quarter 1, Maritime Transport over Danish Ports 2021 Quarter 4, Maritime Transport over Danish Ports 2021 Quarter 3, Maritime Transport over Danish Ports 2021 Quarter 2, Maritime Transport over Danish Ports 2021 Quarter 1, Maritime Transport over Danish Ports 2020 Quarter 4, Maritime Transport over Danish Ports 2020 Quarter 3, Maritime Transport over Danish Ports 2020 Quarter 2, Maritime Transport over Danish Ports 2020 Quarter 1, Maritime Transport over Danish Ports 2019 Quarter 4, Maritime Transport over Danish Ports 2019 Quarter 3, Maritime Transport over Danish Ports (Quaterly) 2019 Quarter 2, Maritime Transport over Danish Ports 2019 Quarter 1, Maritime Transport over Danish Ports 2018 Quarter 4, Maritime Transport over Danish Ports 2018 Quarter 3, Maritime Transport over Danish Ports 2018 Quarter 2, Maritime Transport over Danish Ports 2018 Quarter 1, Maritime Transport over Danish Ports 2017 Quarter 4, Maritime Transport over Danish Ports 2017 Quarter 3, Maritime Transport over Danish Ports 2017 Quarter 2, Maritime Transport over Danish Ports 2017 Quarter 1, Maritime Transport over Danish Ports 2016 Quarter 4, Maritime Transport over Danish Ports 2016 Quarter 3, Maritime Transport over Danish Ports 2016 Quarter 2, Maritime Transport over Danish Ports 2015 Quarter 4, Maritime Transport over Danish Ports 2015 Quarter 3, Maritime Transport over Danish Ports 2014 Quarter 3, The purpose of statistics on maritime transport over Danish ports is to describe the volume of and the development in ship traffic to and from Danish ports as well as data on port infrastructure. Also data on accidents on sea on board Danish vessels and in Danish sea territory are published., The statistics have been compiled in the present form since 1997. Maritime statistics have been produced since 1834 and published annually from about 1900. In the period from 1991 to 1996, Statistics Denmark compiled only summary statistics on the throughput of ports., Statistical presentation, The main variables in the statistics are: Calls at port, type of ship, size of ship, flag state, port of loading/unloading, weight of goods and type of goods and passengers., The statistics are based on two separate data collections: Maritime traffic on larger Danish ports (quarterly) and Maritime traffic on minor Danish ports (annually). It is supplemented with data from Ferries and Passenger ships (quarterly)., Annual data on accidents at sea are collected from the Danish Maritime Authority., Data on investments in ports are received from the National Accounts in Statistics Denmark., Read more about statistical presentation, Statistical processing, Annual statistics cover all Danish ports handling goods or passengers. Quarterly statistics cover only major ports., The statistics are collected through a spreadsheet solution via the data collection portal, http://www.Virk.dk. Response rate is 100 percent., Data are validated for the correct use of codes and classifications and for internal consistency within each report. Furthermore the development over time is validated at both micro and macro level., Read more about statistical processing, Relevance, The statistics are used by the ports themselves, Eurostat and other parts of the EU-commission, ministries, organisations, researchers and in general to monitor the goods transport activity in Danish ports and to develop transport statistics., Read more about relevance, Accuracy and reliability, Maritime statistics are based on censuses among all goods handling ports. The majority of data stems from the quarterly reports from all major ports. The data from the remaining minor ports are summarised annual data. On the main variables there is full coverage and accurate within 3 percent. Minor revision occur without systematic bias., Read more about accuracy and reliability, Timeliness and punctuality, Statistics are usually published around 70 days after the end of a quarter. Annual statistics are published around 130 days after the end of reference year. It is always published at the preannounced time., Read more about timeliness and punctuality, Comparability, The statistics are consistent from 2000 and onwards and directly comparable to similar statistics from other EU and EFTA member states., Read more about comparability, Accessibility and clarity, Maritime statistics are published annually in Nyt fra Danmarks Statistik (Statistical News)., Quarterly and annually data can be found in , http://www.Statbank.dk, ., Annual tables are published in Statistical Yearbook until 2017 and Statistical 10-year Review., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/maritime-transport-over-danish-ports

Documentation of statistics

Documentation of statistics: International Trade in Goods

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

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

Documentation of statistics

Documentation of statistics: National Accounts: Institutional Sectors

Contact info, Government Finances, Economic Statistics , Ulla Ryder Jørgensen , +45 51 49 92 62 , urj@dst.dk , Get documentation of statistics as pdf, National Accounts Institutional Sectors 2024 , Previous versions, National Accounts, Institutional Sectors 2023, National Accounts, Institutional Sectors 2022, National Accounts, Institutional Sectors 2021, National Accounts, Institutional Sectors 2020, National Accounts, Institutional Sectors 2019, National Accounts, Institutional Sectors 2018, The statistics National Accounts by sectors, are part of the national accounts system and consist of coherent definitions and classifications that show how the income of the sectors is created, distributed and redistributed. They provide both a description of the economy in general and of the transactions between persons, enterprises and institutions. The national accounts also include transactions between Denmark and the rest of the world. This set of statistics was first published in 1982. Coherent annual time series are available back to 1995, while quarterly figures are available from the first quarter of 1999 onwards., Statistical presentation, National accounts by sectors provide an overview of the activities and the development of the Danish economy. They contain key indicators such as the gross value added (GDP) and figures for private consumption, investments, exports and imports, earnings and property incomes as well as the profit in six main sectors (non-financial corporations, financial corporations, general government, households, non-profit institutions serving households (NPISH) and the external sector) and productivity in the industries. They also include figures for the many sub-classifications, which facilitates analysis of various cross-sections of the national economy. , Read more about statistical presentation, Statistical processing, Basically, all economic statistics available are used for the national accounts. When the first estimate for a given period is prepared, it is done before all source data for the period is available. The calculations are based on the structure of the last final national accounts, which is projected with indicators from e.g. the business cycle statistics. When new source data becomes available, it is incorporated in the national accounts at set intervals. Three years after a given period, the national accounts are regarded as final., Read more about statistical processing, Relevance, The purpose of these statistics is to clarify how income is generated as a result of the productive activity in society, which is then redistributed before it provides a basis for demand for goods and services for consumption and investment. The institutional sectors are relevant to everyone concerned with socio-economic conditions. The field ranges from the financial, economic and fiscal ministries’ use of the national accounts to common interest in knowledge about the trend of the economy. The press is particularly interested in the figures for the household sector. , Read more about relevance, Accuracy and reliability, The ability of the national accounts to describe the economic reality accurately depends partly on the uncertainty associated with the sources and partly on the model assumptions guiding their preparation. It is possible to draw up some parts more accurately than others, as better source data is available. The first estimates of national accounts for a period will be more uncertain than the final version, which is released after three years, as revisions are made regularly as new source data becomes available., Read more about accuracy and reliability, Timeliness and punctuality, The first version of the quarterly sector accounts is released 90 days after the end of the quarter. In connection with the publication of the fourth quarter at the end of March, the first version of the annual sector accounts is also published. Almost three years after the end of the year, the final annual and quarterly national accounts are published. The sector accounts are published punctually., Read more about timeliness and punctuality, Comparability, The national accounts are prepared according to international guidelines and, as a result, they will be comparable across countries. The current guidelines were implemented in 2014 and have been applied for revision of the national accounts back to 1966, however 1971 for institutional sectors. They reflect all parts of the national economy, so that most economic statistics contain figures that have their counterparts in the national accounts, which are e.g. fully consistent with the balance of payments and general government. For other statistics, the transition will often be complicated due to different definitions and requirements for coverage., Read more about comparability, Accessibility and clarity, The statistics are published in a number of tables in the StatBank under , National accounts and government finances, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/national-accounts--institutional-sectors

Documentation of statistics

Documentation of statistics: Register-Based Labour Force Statistics

Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Register-Based Labour Force Statistics 2024 , Previous versions, Register-Based Labour Force Statistics 2023, Register-Based Labour Force Statistics 2022, Register-Based Labour Force Statistics 2021, Register-Based Labour Force Statistics 2020, Register-Based Labour Force Statistics 2019, Register-Based Labour Force Statistics 2018, Register-Based Labour Force Statistics 2017, Register-Based Labour Force Statistics 2016, Register-Based Labour Force Statistics 2015, Register-Based Labour Force Statistics 2014, The purpose of the Register-Based Labour Force Statistics (RAS) is to measure the population’s primary attachment to the labour market. This attachment is recorded at the end of November and compiled once a year. The first RAS compilation was made at the end of November 1980., Statistical presentation, RAS is an annual, individual-based compilation that records the population’s attachment to the labour market on the last working day of November. The population’s attachment is divided into three main socio-economic groups: employed, unemployed, and persons outside the labour force. The statistics can be broken down by demographic variables and education, as well as by industry, sector, and municipality of the workplace for employed persons. The data are published in News from Statistics Denmark and in the Statistics Denmark StatBank, and detailed micro-data are made available through Statistics Denmark’s Research Service., Read more about statistical presentation, Statistical processing, The register-based labor force statistics (RAS) are based on the Labor Market Account (AMR_UN), which is a longitudinal register. When RAS is compiled, a status assessment (in relation to the population's primary attachment to the labor market) is carried out on the last working day of November in the AMR. Based on AMR_UN, it is also possible to perform status assessments on arbitrary days throughout the year., Read more about statistical processing, Relevance, The register based labour force statistic (RAS) is primarily been used to structural analysis of the labour market, because the statistic has a very detailed level of information. Many external as well as internal users are using the statistic., Read more about relevance, Accuracy and reliability, RAS is a register-based compilation that uses many data sources to measure the population's affiliation to the labor market. This means that RAS does not have the same uncertainty as statistics based on samples. RAS consists of a wide range of data sources, which are integrated, checked for errors, and harmonized, making it possible to provide a better picture of the population's connection to the labor market than the individual statistics can., Read more about accuracy and reliability, Timeliness and punctuality, From the publication of figures for the end of November 2018 onwards, the release is carried out in two stages. In the first release, persons outside the labor force are grouped together in a single category. This publication takes place approximately 11 months after the reference point. In the second publication, which occurs approximately 15 months after the reference point, persons outside the labor force are divided into different socioeconomic groups., Read more about timeliness and punctuality, Comparability, The first version of the RAS statistics includes the population resident in Denmark as of the 1 January 1981 and its attachment to the labour market at the end of November 1980. The statistic has been compiled once every year since. New and better data foundations and changes in the labour market have however caused a number of data breaks over time, which have influence on the possibility of comparing data over time. Since RAS is based on administrative registers with national distinctive marks, it is very difficult to compare the statistic in an international level. , Read more about comparability, Accessibility and clarity, The statistics is published in Statbank Denmark: , Labour market status (RAS), and , Employed persons (RAS), . , For further information go to the subject pages , Labour market status (RAS), and , Employed persons (RAS), ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/register-based-labour-force-statistics

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: Harvest of Cereals etc.

Contact info, Food Industries, Business Statistics , Martin Lundø , +45 51 46 15 12 , mlu@dst.dk , Get documentation of statistics as pdf, Harvest of Cereals etc. 2025 , Previous versions, Harvest of Cereals etc. 2024, Harvest of Cereals etc. 2023, Harvest of Cereals etc. 2022, Harvest of Cereals etc. 2021, Harvest of Cereals etc. 2020, Harvest of Cereals etc. 2019, Harvest of Cereals etc. 2018, Harvest of Cereals etc. 2017, Harvest of Cereals etc. 2016, Harvest of Cereals etc. 2015, Harvest of Cereals etc. 2014, The statistics illustrate the Danish harvest of grain, rapeseed, legumes and roughage. The statistics are used for research, EU reporting, calculation of GDP and energy and feed accounts. The statistics have been compiled since 1875, but in their current form are comparable from 1971 onwards. The statistics complement other statistics on vegetable production, including , Production of fruit and vegetables, . , Statistical presentation, The statistics are an annual statement of the Danish harvest of grain, rapeseed, legumes, root vegetables and roughage, calculated in area (1000 hectares), average yield (hectokg per hectare) and production (million kg). The statistics are calculated for crops and divided by region., Read more about statistical presentation, Statistical processing, Harvest of cereals, rapeseed and legumes: Data is collected annually from farmers via questionnaires and is debugged based on yield limits and added to the total population. Roughage: Data is collected from SEGES, Danish Sugar Beet Growers, DAKOFO, the Danish Agricultural Agency and Accounting Statistics for Agriculture. Where current data is missing, yields are projected from related crops with known trends., Read more about statistical processing, Relevance, The users are mainly EU and agricultural organizations. The results are included in the agricultural gross factor income. Information on the use of straw for fuel is used, among other things by the DEA., User needs are covered in the User Committee for food statistics. Statistics Denmark is also in regular contact with key users, including the Ministry of Food and research institutions., Read more about relevance, Accuracy and reliability, The response rate for the calculation of the harvest of grains, rapeseed etc. is over 95 per cent. Precision meets EU quality requirements., For coarse fodder, reliability must be considered reasonable for average yields, while it is high for area information., The forecast for winter seed areas usually deviates by 5-10 percentage points from the later established cultivated areas., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are usually published without delay to the scheduled date., Preliminary data for the harvest of cereals, rape and pulses are published in late November. Final statement, including results for provinces and regions are published April of the following year, where the coarse fodder harvest alsot is published. End of reference Period: October 1. Harvesting of roughage is published April of the following year. End of reference Period: end of November. The forecast for the following year's winter land released in early December. End of reference Period: October 15, Read more about timeliness and punctuality, Comparability, Similar statistics are produced among EU members and are available from the Eurostat's website. The statistics comply with EU standards., Harvest figures are in principle comparable back to 1900 but with methodological changes along the way. The current calculation method has in principle been used since 1971. The statistics for the new regions of the country are made from 2006. Thus there for 2006 is both a statement of the then counties, and the current regions., Read more about comparability, Accessibility and clarity, The statistics are published in the StatBank under , Crop production, and in a Danish press release., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/harvest-of-cereals-etc-

Documentation of statistics

Documentation of statistics: Implicit index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Implicit index of average earnings 2025 , Previous versions, Implicit index of average earnings 2024, Implicit index of average earnings 2023, Implicit index of average earnings 2021, Implicit index of average earnings 2020, These statistics show the development in average earnings, calculated on the basis of an arithmetic average of salaries of all employees within the same sector and economic industry. In relation to the publication of the new Standardised index of average earnings, these indices were renamed to Implicit index of average earnings. In the new index changes in the workforce is taken into account when calculating the development in earnings., The Implicit index of average earnings goes back to first quarter of 2005 for the private sector and first quarter of 2007 for the public sector., Statistics Denmark has decided to discontinue the implicit index of average earnings at the beginning of 2026 with the publication of the index for the fourth quarter of 2025. Instead, users are advised to use the standardised index of average earnings, which also illustrates the development in pay level for employees in Denmark. The discontinuation of the implicit index of average earnings will not have any impact on the standardised index of average earnings, which will be the only wage index from Statistics Denmark in the future. The historical series of the implicit index of average earnings will continue to be accessible in StatBank Denmark. In order for users to handle the transition to the standardised index of average earnings, a guide (in Danish) has been prepared on how to switch from the implicit to the standardised index of average earnings in practice. It is available on Statistics Denmark's information page on , indexation, ., Statistical presentation, The Implicit index of average earnings is a quarterly statistic of the development in wages for all employees in Denmark, including students and young persons under 18. The indices are available by sector and economic industries and follow the classifications Dansk Branchekode (DB07) and sector (SBR)., Read more about statistical presentation, Statistical processing, Data is collected from a sample of companies and organisations as well as the entire public sector, covering the middle month of the quarter., Data is validated by using fixed boundaries, both at individual and company level. Manual corrections are also made if required. Only companies that are present in both quarters are included in the calculations., In the calculation of the most detailed sub-indices, data for the private sector are weighted to the target population and the individual employment types are weighted with the hours worked., Read more about statistical processing, Relevance, The Implicit index of average earnings is a so-called unit value index, where wage trends are estimated on the basis of a simple salary average of all employees in the same industry. This means that wages partly reflect changes in staff composition in a given industry., Private enterprises as well as ministries etc are the central users. The index is used especially in connection with various contract regulations, as well as the regulatory scheme in the public wageagreements., The Implicit index of average earnings is the wage index that comes closest to being comparable to the European LCI., Read more about relevance, Accuracy and reliability, For the public sector the statistics are based on data for virtually all employees. For the private sector, there are two factors that can affect accuracy, namely uncertainty in the sample statistics and that there may be problems with the completeness of the reported data from the company., This index is an where the sum of wages and hours worked is counted in each group (etc. activity sector). Thus, changes in personnel in a given industry will have an impact on the measured wage development., The figures do not undergo revision; the published figures are usually final., Read more about accuracy and reliability, Timeliness and punctuality, The implicit index of average earnings are published approx. 60 days after the end of the reference quarter, at the same time as the standardised index of average earnings is published. These statistics are published without delay., Read more about timeliness and punctuality, Comparability, The implicit index of average earnings is comparable since first quarter 2005 but for some sectors, comparable wage indices also exist further back in time. The implicit index of average earnings is based on the same data as the standardised index of average earning, but there are significant differences in methodology that allow the two wage indices to be used only partially for comparison., Internationally, the implicit index of average earnings can be compared to the labor cost index collected and published by Eurostat for all EU countries., Read more about comparability, Accessibility and clarity, The implicit index of average earnings is published in Statistics Denmark’s newsletter on [https://www.dst.dk/da/statistik/nyheder-analyser-publ/nyt?psi=1931), together with the standardized index of average earnings. In Statbank Denmark, indices and annual increases are published under the , implicit index of average earnings , . More information can be found on the subject page on , Income and earnings, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/implicit-index-of-average-earnings

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