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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

Documentation of statistics: Nights spent at hotels, holiday resorts and youth hostels

Contact info, Short Term Statistics, Business Statistics , Nanna Nikander Nonboe-Nygaard , NIO , nio@dst.dk , Get documentation of statistics as pdf, Nights spent at hotels, holiday resorts and youth hostels 2025 , Previous versions, Nights spent at hotels, holiday resorts and youth hostels 2024, Nights spent at hotels, holiday resorts and youth hostels 2023, Nights spent at hotels, holiday resorts and youth hostels 2022, Nights spent at hotels, holiday resorts and youth hostels 2021, Nights spent at hotels, holiday resorts and youth hostels 2020, Nights spent at hotels, holiday resorts and youth hostels 2019, Nights spent at hotels, holiday resorts and youth hostels 2018, Nights spent at hotels, holiday resorts and youth hostels 2017, The purpose of the statistics "Nights spent at hotels, holiday centers and hostels" is to describe the occupancy and capacity of Danish hotels, holiday centers and hostels. The survey is used by i.e. EU, business and tourism organizations and municipalities in order to analyze the development in tourism. The survey has been compiled since 1969, but is only comparable from 1992 and onwards. , Statistical presentation, The accommodation survey "Nights spent at hotels, holiday centers and hostels" is a monthly summary on occupancy and capacity in Danish hotels, holiday centers and hostels with a minimum capacity of 40 bed places. The accommodation survey is broken down by capacity and geography of the establishment as well as the purpose and country of residence of the guest. Furthermore there is an annual census on occupancy and capacity for hotels, holiday centers and hostels with 10-39 bed places., Read more about statistical presentation, Statistical processing, Data for the statistics are collected monthly from Danish hotels, holiday resorts, hostels etc. with a minimum of 40 bed places and yearly from Danish hotels, holiday resorts, hostels etc. with 10-39 bed places using an online questionnaire or by using a system-to-system solution where the accommodations booking system automatically sends data to Statistics Denmark. Collected data are validated on micro-level during the data collection and again on macro-level when aggregated. The validated data are then imputed with missing values and afterwards aggregated into geographical and nationality totals. , Read more about statistical processing, Relevance, The accommodation statistics are relevant for accommodation businesses, Eurostat, ministries and business and tourism organizations for forecasts, analysis and planning. The accommodation statistics are under constant review and the user needs are rapidly changing with the emergence of peer-to-peer platforms such as AirBnB. , Read more about relevance, Accuracy and reliability, The monthly statistic only cover hotels, holiday resorts and hostels etc. with at least 40 bed places. The annual statistics also cover hotels, holiday resorts and hostels etc. with 10-39 bed places. A possible source of error can be that the respondents have difficulties distinguishing between the concepts of nights spent and arrivals. Missing answers are imputed which may lead to revisions of published data. , Read more about accuracy and reliability, Timeliness and punctuality, The monthly statistics for hotels, holiday centers and hostels etc. with a minimum of 40 bed places are published monthly approx. 40 days after the end of the reference month. The statistics is published without delay according to the planned publication tables. The final statistics are published annually together with the statistics for Hotels, holiday centers and hostels etc. with 10-39 bed places. The Annual statistics are published approx. 100 days after the end of the reference year., Read more about timeliness and punctuality, Comparability, The accommodation statistics is comparable with the other EU-statistics on tourism. The breakdown into nationalities has expanded from 13 to 51 since 1996 and this can weaken the comparability when using time series. , Read more about comparability, Accessibility and clarity, The statistics are published in , Nyt fra Danmarks Statistik, . Data are published in statbank at , Hotels, holiday centres and hostels, og , All types of overnight accommodation, and in an annual publication with all types of overnight accommodation. For more information about the statistics look at the , subject page, ., Statistics on a municipality level or for a province can be found at VisitDenmark. If you wish to combine statistics of tourism with other types of variables or combine variables in a different way please contact DST Consulting., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/nights-spent-at-hotels--holiday-resorts-and-youth-hostels

Documentation of statistics

Documentation of statistics: Holiday houses

Contact info, Short Term Statistics, Business Statistics , Nanna Nikander Nonboe-Nygaard , NIO , nio@dst.dk , Get documentation of statistics as pdf, Holiday houses 2025 , Previous versions, Holiday dwellings 2024, Holiday dwellings 2020, Holiday dwellings 2019, Holiday dwellings 2018, Holiday dwellings 2017, The purpose of the statistic Holiday houses is to visualize the capacity and rental activity for Danish holiday houses through from rental agencies. Users of the statistics is e.g. business and tourism organisations as well as municipalities and regions to analyse the development in tourism. The statistics have been compiled since 1968 in various forms. Figures for the first years are available in printed editions of the Statistical Yearbook. In its current form, the statistics are comparable since 1992. Figures on nights spend at holiday houses or holiday apartments complements other tourism statistics on nights spend e.g. hotels, camping., Statistical presentation, The statistics about holiday houses are a monthly and annual calculation of Danish holiday houses that are rented out through rental agencies. The statistics are divided into nationalities of the guests, as well as geographically by regions and parts of the country. In addition, there is an annual assessment of the capacity of vacation houses for rental. Numbers of Municipal distribution is prepared in collaboration with VisitDenmark. , Read more about statistical presentation, Statistical processing, Data for this statistics is collected monthly for reporting that covers approx. 95 pct. of the population, to which is added an enumeration of the annual reports from the previous year, so that the entire population of holiday house rental with a minimum of 25 houses available is covered. The monthly statistics shows temporary data for the holiday house rental. When the reference year is over, the calculated imputed values are replaced with the final data for the year. The annual statistics with the final data include reporting from every holiday house rental with a minimum of 25 houses available for renting., Data for the annual statistics is collected via an upload solution for the rental agencies that only report annually or via an electronic questionnaire for the rental agencies that report monthly. The collected data undergoes micro-level debugging during the actual collection and at the macro-level when the data is aggregated. , Read more about statistical processing, Relevance, The statistics are relevant for e.g. the companies, industry associations, municipalities and regions as well as business and tourism organizations as a basis for forecasts, analyses and planning purposes., Read more about relevance, Accuracy and reliability, The variables of the statistics associates more or less uncertainty. Number of contracts, number of houses available and rented house-weeks are regarded as the most certain variables. The variable Numbers of nights is regarded as more uncertain, because in some cases they are based on reported estimates. , Read more about accuracy and reliability, Timeliness and punctuality, The monthly statistics for holiday house rental is published approx. 40 days after the end of the reference month. The statistics are published without delays in relation to planned publication times. The annual statement for holiday house rental is published together with the final annual figures approx. 100 days after the end of the reference year. , Read more about timeliness and punctuality, Comparability, The statistics date back to 1986 and have undergone changes over time. From 1986-1990, the statistics only covered holiday house rental in the high season. From 1990, the statistics covered an operating year, i.e. early October to and including the end of September. From 1998, the annual statistics are based on the calendar year. In 2011, the overnight figures for 2010 were adjusted upwards by 647,000 as a result of revised information from some rental agencies. As a consequence, the number of overnight stays in 2010 and 2011 and onwards is not immediately comparable with the number of overnight stays in previous years. From 2012, the number of available houses for rent was removed from the monthly statistics. Instead, the figure is calculated once a year with the number of available houses for rent per year. May 1. in the reference year. , Read more about comparability, Accessibility and clarity, The statistics are published monthly and annually in , Nyt from Statistics Denmark, . In the Statistics Bank, the figures are published under the subject , Holiday houses, and , Total types of accommodation, . See more on the statistics , topic page, . Municipality-distributed statistics on holiday rental are financed by VisitDenmark and are freely available on their , website, ., If you want to combine statistics on holiday home rentals with other variables or put them together in another way, you can contact DST Consulting to clarify options and request a quote. , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/holiday-houses

Documentation of statistics

Documentation of statistics: Regional Accounts

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

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

Documentation of statistics

Documentation of statistics: Bankruptcies

Contact info, Short Term Statistics, Business Statistics , Simon Bolding Halifax , +45 51 29 21 91 , sbh@dst.dk , Get documentation of statistics as pdf, Bankruptcies 2023 , Previous versions, Bankruptcies 2022, Bankruptcies 2020, Bankruptcies 2019, Bankruptcies 2018, Bankruptcies 2017, Bankruptcies 2016, Bankruptcies 2015, Bankruptcies 2014, The purpose of these statistics on bankruptcies is to analyze trends in the number of bankruptcies as well as in selected characteristics of companies gone bankrupt. These trends are considered as an essential economic or short time indicators. Compilation of the statistics was established in January 1979 based on a 'simple count method'. In 2009 the method was changed to a registry-based method. Quarterly statistics on selected and aggregated NACE-sections are published from July 2021., Data on petitions for liquidation proceedings are calculated on experimental basis as a high frequent (weekly) short time indicator. They cover the period since 2011., Statistical presentation, The statistics on declared bankruptcies show monthly the development in the number of announcements by industry, region, company age, turn-over and employment. Furthermore average company age, total turn-over and total employment (lost jobs) in bankrupt companies are calculated. The bankruptcies are moreover calculated for so called active companies, i.e. companies with employment and/or turnover >= 1 million DKK, as well as inactive companies, i.e. companies without employment and turnover less than 1 million DKK., Figures on petitions for liquidation proceedings are calculated on experimental basis as a high frequent (weekly) short time indicator. They cover the period since 2011., The declared bankruptcies are from July 2021 published monthly together with figures on new registered enterprises on selected and aggregated sections in the so called Quarterly Business Demography, QBD.. , Read more about statistical presentation, Statistical processing, Data from The Danish Official Gazette (Statstidende) are checked for missing reports and duplicates., The announced bankruptcies in the month of reference are added on business sector, turnover, age, employment and geography. The bankruptcies are moreover calculated for so called active companies, i.e. companies with employment and/or turnover >= 1 million DKK, as well as inactive companies, i.e. companies without employment and turnover less than 1 million DKK. The main series with the total number of bankruptcies are seasonal adjusted together with the series of bankruptcies in active companies., The series on petitions for liquidation proceedings are checked at delivery. Some of the petitions for liquidation proceedings are removed from data as they cover private bankruptcies., Read more about statistical processing, Relevance, The statistics on declared bankruptcies and petitions for liquidation proceedings are used by public and private decision-makers as short time indicators and as indicators of the state of affairs in enterprises., Read more about relevance, Accuracy and reliability, There are no changes to former published data. Company ages can be underestimated due to companies changes in the 'cvr'-number. Turn-over and employment figures does not necessarily reflect the situation on the time of bankruptcy as these data refer to an earlier reference period (year or quarter)., Earlier published figures on petitions for liquidation proceedings can be changed by new data deliveries., Read more about accuracy and reliability, Timeliness and punctuality, The statistics on declared bankruptcies is nearly always published on the fourth working day after the reference month. , Publications on declared bankruptcies are released on time, as stated in the release calendar. , The statistics on petitions for liquidations are normally published every Wednesday but delays may occur., Read more about timeliness and punctuality, Comparability, The figures for declared bankruptcies before 2009 are not fully compatible with the later figures as the former figures also contain personal bankruptcies. The size of the difference is not available., Read more about comparability, Accessibility and clarity, Statistics on declared bankruptcies 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 , Bankruptcies, . For more information, go to the , subject page, Statistics on petitions for liquidations are published weekly in the Statbank and at https://www.dst.dk/da/Statistik/emner/erhvervsliv/erhvervslivets-struktur/konkurser) , Statistics on Quarterly Business Demography are published quarterly in the Statbank. (Link og dokumentation kommer på, når det er oprettet), Read more about accessibility and clarity

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

Documentation of statistics

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

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

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

Documentation of statistics

Documentation of statistics: Public Expenditure and Revenue on the Environment

Contact info, Government Finances, Economic Statistics , Jonas Foged Svendsen , +45 21 34 73 19 , JFS@dst.dk , Get documentation of statistics as pdf, Public Expenditure and Revenue on the Environment 2024 , Previous versions, Public Expenditure and Revenue on the Environment 2023, Public Expenditure and Revenue on the Environment 2022, Public Expenditure and Revenue on the Environment 2021, Public Expenditure and Revenue on the Environment 2018, Public sector environmental protection plus environmental related taxes and subsidies 2017, Public sector environmental protection plus environmental related taxes and subsidies 2016, Public sector environmental protection plus environmental related taxes and subsidies 2016, Public sector environmental protection plus environmental related taxes and subsidies 2014, Public Expenditure and Revenue on the Environment 2013, Public Expenditure and Revenue on the Environment 2012, The statistics Public Expenditure and Revenue on the Environment are part of the green national accounts. The statistics establishes a link between public expenditure and revenue and public environmental protection activities. The statistics are used, inter alia, in relation to political decisions in the environmental field, environmental economic analyses and international comparisons of the various EU countries' environmental efforts. The statics date back to 1995. , Statistical presentation, The statistics is an annual measurement and consist of three focus areas: environmental protection, green taxes and environmental subsidies. In conjunction with a number of international classifications, these focus areas form the framework for the link between public expenditure and revenues and the public environmental protection activities. The focus areas of the statistics are also linked to a description of the public sector as a sector consisting of state, municipalities, regions and public corporations., Read more about statistical presentation, Statistical processing, The data sources for this statistics consist of accounts from state, municipalities, regions and public corporations that are coded for national accounts based on the manual of the European National Accounting System (ESA2010) and stored in the database DIOR (Database for Integrated Public Accounts). Based on thorough analyses, a list of criteria is drafted, which determines which account items are to be drawn from DIOR in order to compile the statistics. The selected account items are sorted and aggregated according to environmental purposes and categories, real-economic type and sector., Read more about statistical processing, Relevance, The figures in these statistics are relevant, among other things, in connection with political decisions in the environmental field, environmental economic analyses and international comparisons of the individual EU countries' environmental efforts. The most obvious users of the statistics are various ministries, agencies and organizations, as well as media and research institutions. Statistics Denmark receives information about the users' needs and satisfaction via the Contact Committee for Environmental Economic Accounts and Statistics., Read more about relevance, Accuracy and reliability, It is estimated that green taxes are the most accurate of the three main areas of the statistics, followed by environmental subsidies and environmental protection respectively. Sources of uncertainty include: misstatements in public accounts, the risk of overlooked items, the risk of incorrectly included items, the possibility of misclassification, and uncertainty regarding estimates of the environmental share of various accounts. Furthermore, the industry distribution of green taxes and environmental subsidies is based on a number of assumptions, which are also subject to uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published annually one month after the publication of the public finance accounts. The figures follow the National Accounts audit schedule and will only be finalized three years after the end of the accounting period. The statistics are usually published without delay in relation to the time announced., Read more about timeliness and punctuality, Comparability, The figures in these statistics are comparable to other statistics in several different ways. Through transmissions to Eurostat, the figures are made comparable with the other EU countries according to Regulation No 691/2011 of the European Parliament and of the Council on European environmental economic accounts. The figures are comparable over time, and finally the figures are comparable to other figures within the national accounting framework., Read more about comparability, Accessibility and clarity, These statistics are published in a Danish , press release, . The figures can be found in the StatBank under , Green Economy, . In addition, these statistics feature in the , Environmental-Economic Accounts, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/public-expenditure-and-revenue-on-the-environment

Documentation of statistics

Documentation of statistics: Detailed material flow accounts (physical supply-use tables)

Contact info, National Accounts, Climate and Environment, Economic Statistics , Ole Gravgård Pedersen , +45 30 89 28 39 , OGP@dst.dk , Get documentation of statistics as pdf, Detailed material flow accounts (physical supply-use tables) 2020 , Previous versions, Detailed material flow accounts (physical supply-use tables) 2018, Detailed material flow accounts (physical supply-use tables) 2016, The purpose of the detailed material flow accounts is to shed light on the type and quantity of all materials linked to industries, private and government consumption, etc. , The accounts can be used for analysis of the physical proportions of resource use, output of goods and residuals, external trade, etc. Thereby they give information, which are useful in relation to analysis of circular economy, etc. , The accounts are available for 2018 and 2020. Not all data are fully comparable across the two years due to changes in data sources and introduction of new methods., Statistical presentation, The accounts present information about flows of natural resources, goods and residuals (waste and emissions to air, etc.) measured as tonnes per year. The accounts include all type of materials, which are used or supplied. , The flows are recorded by industries and other categories, e.g. extraction from nature, imports, exports, private and government consumption, emissions to the environment, etc. , The accounts are balanced, which means that the quantity of materials used by an industry equals the quantity of materials, that leaves the industry as sold products and residuals. , Read more about statistical presentation, Statistical processing, The accounts are based on several sources, for instance, International Trade in Goods, Purchases by Manufacturing Industries, National accounts, and Environmental-Economic Accounts supplemented by data from e.g. the Danish Environmental Protection Agency and websites and organizations and companies., The primary data are processed and supplemented by estimations and allocations, after which they are organised in a so-called physical supply-use table. Finally, this table is adjusted in such a way that supply equals use., Read more about statistical processing, Relevance, The accounts are of relevance to all, who are interested in information about those physical material flows that take place in relation to the Danish economy. It can be used as a basis for analysis of the circular economy, e.g. for analysis of which industries that use or produce certain types of materials. , Read more about relevance, Accuracy and reliability, In general it can be assumed that there are less uncertainties associated with data obtained directly from primary statistics, while data that results from estimations and allocations will be associated with more uncertainties. , The balancing item, which is represented in the accounts, is to some extent a result of inaccuracies related to other items in the accounts. However, it cannot directly be used as a measure of the uncertainties, since it may also reflect other special relations., No estimations of the magnitude of the uncertainties have been made. , Read more about accuracy and reliability, Timeliness and punctuality, The accounts for 2020 have been published 4 years and three months after the end of the reference year (2020). The accounts are published without delay compared to the announced time of publication in the release calendar., Read more about timeliness and punctuality, Comparability, The accounts are available for 2020 and 2018, and in an earlier version for 2016. The versions are not fully comparable due to changes in source data and methods. , This type of accounts is - as far as we know - only available for the Denmark and the Netherlands, but with different classifications. Thus, it is not possible to make direct international comparisons. , For certain items it is possible to compare over time and with other countries by looking at the primary data that lie behind the accounts., Read more about comparability, Accessibility and clarity, These statistics are published in the StatBank under the subject , Detailed material flow accounts, . Selected items from the accounts are published in Danish publications., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/detailed-material-flow-accounts--physical-supply-use-tables-

Documentation of statistics

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

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

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

Documentation of statistics

Documentation of statistics: Public sector employment (quarterly)

Contact info, Labour Market, Social Statistics , Mads Housø Hansen , +45 24 43 40 61 , MHU@dst.dk , Get documentation of statistics as pdf, Public sector employment (quarterly) 2024 Quarter 4 , Previous versions, Public sector employment (quarterly) 2024 Quarter 3, Public sector employment (quarterly) 2024 Quarter 2, Public sector employment (quarterly) 2024 Quarter 1, Public sector employment (quarterly) 2023 Quarter 4, Public sector employment (quarterly) 2023 Quarter 3, Public sector employment (quarterly) 2023 Quarter 2, Public sector employment (quarterly) 2023 Quarter 1, Public sector employment (quarterly) 2022 Quarter 4, Public sector employment (quarterly) 2022 Quarter 3, Public sector employment (quarterly) 2022 Quarter 2, Public sector employment (quarterly) 2022 Quarter 1, Public sector employment (quarterly) 2021 Quarter 4, Public sector employment (quarterly) 2021 Quarter 3, Public sector employment (quarterly) 2021 Quarter 2, Public sector employment (quarterly) 2020 Quarter 4, Public sector employment (quarterly) 2020 Quarter 3, Public sector employment (quarterly) 2020 Quarter 2, Public sector employment (quarterly) 2020 Quarter 1, Public sector employment 2018 Quarter 3, Public sector employment 2018 Quarter 2, Public sector employment 2018 Quarter 1, Public Employment Statistics 2017 Quarter 4, Public Employment Statistics 2017 Quarter 3, Public Employment Statistics 2017 Quarter 1, Public Employment Statistics 2016 Quarter 3, Public Employment Statistics 2014 Quarter 4, Public Employment Statistics 2015 Quarter 1, Public Employment Statistics 2015 Quarter 2, Public Employment Statistics 2015 Quarter 3, Public Employment Statistics 2015 Quarter 4, Public Employment Statistics 2016 Quarter 1, Public Employment Statistics 2016 Quarter 2, Public Employment Statistics 2016 Quarter 4, Public Employment Statistics 2014 Quarter 3, Documents associated with the documentation, Notat om revision af COFOG (pdf) (in Danish only), The public employment statistics cover general government sector and its subsectors. The statistics are published quarterly and are distributed by subsector and by purpose. The classification by purpose follows the classification COFOG (Classification of the functions of Government)., Statistical presentation, The statistics publish quarterly the number of full-time employees in general government sector. The statistics are broken down by subsector and the COFOG classification., Read more about statistical presentation, Statistical processing, The data source of the statistics is the eIncome Register of Statistics Denmark. This is combined with information on e.g. public account numbers from public reports., Data are always quality controlled at a cross-level between COFOG and the subsectors of general government. , The COFOG distributions are revised occasionally and data are revised in accordance with the data source. Time-series are seasonally adjusted., Read more about statistical processing, Relevance, Among users of the statistics are ministries, government agencies and municipalities, various organizations, researchers, politicians and others interested in the development of employment and the number of staff employed within the general government sector., Read more about relevance, Accuracy and reliability, The data source of the statistics is the eIncome Register of Statistics Denmark which is the main data source for register-based employment statistics published by Statistics Denmark. This register is considered as highly reliable., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are expected to be published without any delay in relation to the time for publication announced., Read more about timeliness and punctuality, Comparability, Comparable data are available based on the new statistics from first quarter 2008 onwards. Based on the former statistics historical data are available for the period first quarter 2002 until fourth quarter 2012., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistics Denmark and in the database Statbank Denmark., Table OBESK1, ,, Table OBESK2, ,, Table OBESK3, and, Table OBESK4, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/public-sector-employment--quarterly-

Documentation of statistics