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Publication: The business sector and the sustainable development goals - Denmark and neighbouring countries 2021

In this publication the development of the Business sector in relation to selected SDG-goals in Denmark and 7 neighbouring countries are shown. Existing statistics in Eurostat, The European Union Statistical office, are used in the analyses. The developments on economic, environmental and social issues are followed for 14 groups of industries across country., Positive developments in all 8 countries in relation to the SDGs – only minor change, however, as regards gender equality in occupation and earnings, The results, mainly from 2010 to 2019, shows a positive trend in the Business sector in the contribution to fulfilment of the Sustainable Development Goals. In particular, this is the case in relation to emission of climate gasses, where all countries show improvement in the relation between emission and value added. This has, however, also been caused by domestic or European policies on the matter., Connected to the comparisons of the development in the indicators across country, also the differences in business structure are presented together with the actual size of indicators in 2010. The baseline and the room for change is necessary knowledge when assessing the development since. , Expenditures for R&D, relevant information in relation to change to improved sustainability in the Business sector has in general increased since 2010, as well in actual prices as related to the value added in the sector. Poland shows the highest increase, however from a low level, why a decrease in the indicator is the case for Denmark and Finland., A significant decrease in emission of climate gasses from business activities can been seen, as well in actual figures at related to value added. United Kingdom shows larges decrease independent of indicator, while Poland and Netherlands shows only low decrease. The overall figures from Norway is deviating from the general trend, maybe caused by insecurity in emission figures., The gender composition of the employees by type of industry show largely similar pictures in the countries, but also a slight tendency towards more equal composition. Germany and Poland has the highest share of women in the sector, while Norway and Sweden has the lowest share., Regarding gender pay gap, only a rough comparison for the business sector is possible. The figures, however, indicates that Germany and United Kingdom have the largest gender pay gap, while Poland, Sweden and Norway are more close to a situation where women get equal pay for equal  work., Exact references to the Eurostat database tables can be found in the publication. This makes it possible for everyone to make further calculations, for others countries or types of industry and also for the coming years. For 2020 and 2021, however, impact from COVID-19 has to be taken into account in the analyses., Corrections:, Page 28: Greenhouse gases emission, Get as pdf, The business sector and the sustainable development goals - Denmark and neighbouring countries, Colophone, The business sector and the sustainable development goals - Denmark and neighbouring countries, Business, ISBN pdf: 978-87-501-2407-8, Released: 25 May 2022 08:00, No of pages: 37, Contact info:, Ole Olsen, Phone: +45 29 77 14 98

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https://www.dst.dk/en/Statistik/planlagte

Documentation of statistics: Consumer Price Index

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

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

Documentation of statistics

Documentation of statistics: 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: 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: 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

Documentation of statistics: Personal assets and Liabilities

Contact info, Labour Market, Social Statistics , Jarl Christian Quitzau , +45 23 42 35 03 , JAQ@dst.dk , Get documentation of statistics as pdf, Personal assets and Liabilities 2024 , Previous versions, Personal assets and Liabilities 2023, Personal assets and Liabilities 2022, Personal assets and Liabilities 2021, Personal assets and Liabilities 2020, Personal assets and Liabilities 2019, Personal assets and Liabilities 2018, Personal assets and Liabilities 2017, Assets and Liabilities 2016, Assets and Liabilities 2015, Assets and Liabilities 2014, Documents associated with the documentation, 2022-Revision af formuestatistikken_vs1.1 (pdf) (in Danish only), Værdiansættelse af unoterede aktier og fordeling på personer i 2022 (pdf) (in Danish only), Estimering af aldersopsparing (pdf) (in Danish only), New data on individual pension wealth growth (pdf), Fordeling af unoterede aktier 2023 (pdf) (in Danish only), Beskrivelse af formueloftet 2023 (pdf) (in Danish only), Effekt af overgang til midlertidigt datagrundlag om ejendomme fra 2023 (pdf) (in Danish only), Beskrivelse af formueloftet 2024 (pdf) (in Danish only), Fordeling af unoterede aktier 2024 (pdf) (in Danish only), Databrud i ejendomsformuerne, 2024 (pdf) (in Danish only), The purpose of the Wealth and Debt statistics is to provide insights into the wealth and debt of individuals, families, and various population groups. The statistics were first created in the aftermath of the financial crisis in collaboration with Danmarks Nationalbank (the Danish Central Bank) and were intended, among other things, to analyze families' resilience to economic shocks. Additionally, the statistics are used in analyses of the pension system and to measure economic inequality. The statistics have been produced since 2014., Statistical presentation, The statistics produces annual data on the value of value of real estate, cars, financial assets, pension wealth and debts. There are also separate and more detailed publications on pension wealth. The statistics are register based and are based on data at the individual level. It is linked to other registers in order to do subdivisions on age, gender, municipality etc., Read more about statistical presentation, Statistical processing, Data is collected from multiple sources and undergoes statistical processing, including debt classification and market value assumptions for assets such as homes, cars, and unlisted shares. Registers are compiled using anonymized identifiers. In pension statistics, bonuses and reserves are allocated proportionally to pension funds, and anonymized contract numbers enable time-series analysis, except in cases of mergers and acquisitions., Read more about statistical processing, Relevance, These statistics are relevant for researchers, ministries, Economic think tanks, pension funds and the media. It is used for forecasts on the pension system and, analyses on the level of wealth in different strata, the level of prosperity and the level of economic inequality. The statistical data and results are also used in other statistical areas within Statistics Denmark, e.g. in national accounting and as a supplement to the income statistics. Data on pension wealth are also used for the macro economic Model ADAM., Read more about relevance, Accuracy and reliability, The quality of the financial data is high since most of the data is validated by the tax authorities. There is much larger uncertainty on the imputed market value of owned property, cars, unquoted stocks and the value of lifetime pensions. Data on assets that can not be linked to persons is not included. Data Wealth held abroad by Danes is likely lacking as well. For discretionary reasons the register is top-coded with a maximum wealth of DKK 2.07 bio. , Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published approximately 12 months after the end of the reference year. Publications are released on time without delays, as stated in the release calendar. , Read more about timeliness and punctuality, Comparability, Comparability over time varies depending on the wealth component. In the wealth and debt statistics, one must choose whether to use the 2020 series, which includes unlisted shares and debt subject to enforcement, or the 2014 series, which does not. In 2023–2025, there is a major data break due to the transition to new assessment systems, and the coverage of unlisted shares has gradually improved since they were included in the statistics from 2020. Apart from these breaks there is good consistency over time. Caution should be exercised when using the statistics for international comparisons., Read more about comparability, Accessibility and clarity, These statistics are published yearly 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 , Wealth and liabilities, and , Pension assets, . For further information, go to the , subject page, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/personal-assets-and-liabilities

Documentation of statistics