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    Documentation of statistics: Leisure and Business Trips

    Contact info, Short Term Statistics , Kari Anne Janisse Arildsen , +45 40 43 38 12 , KJS@dst.dk , Get documentation of statistics as pdf, Leisure and Business Trips 2023 , Previous versions, Leisure and Business Trips 2022, Leisure and Business Trips 2021, Leisure and Business Trips 2020, Leisure and Business Trips 2016, Leisure and Business Trips 2013, The purpose of the survey is to describe the travel patterns of the Danish population. Information is given on use of infrastructure and accommodation. Further information is given on the preferred destinations and expenditures concerning the trips. Statistics Denmark has compiled similar surveys in 1972, 1976 and 1980. In 1995, the survey covered only trips with at least four overnight stays for personal purposes. Since 1996, short leisure trips with 1-3 overnight stays and business trips with at least one overnight stay have also been compiled., Statistical presentation, The survey covers leisure and business trips with nights spent as well as same-day visits made by adult Danes aged 15 or older. In broader terms, the survey covers the travel habits of the adult Danish population., Read more about statistical presentation, Statistical processing, The survey is made on the basis of a randomly selected sample with approx. 6000 interviews in net value (unit nonresponse excluded) among Danish residents aged 15 years+. The sample is then grossed up to the target population (Danish residents aged 15 years+) by using different strata, which refers to groupings based on for instance gender, age, family type, family income and socio group in order to make the sample represent the target population the best way possible. , Read more about statistical processing, Relevance, The survey is used by The European Commission, Danish ministries and business and tourism organizations in the industry in order to monitor the market and develop potential tourism policies. In broader terms, the survey can also be used for educational purposes and as an indicator that tells something about the travel habits and behavior of the Danish population and of the society and the economic situation in general., Read more about relevance, Accuracy and reliability, The statistics are affected by statistical sampling errors and memory bias, especially regarding the expenditure questions., Due to the sampling method, statistical errors do occur. For the net propensity to undertake a holiday trip the interval made up as the estimated value +/- 2 per cent will contain the true value in 95 per cent of the cases., Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published annually approx. 7 months after the end of the reference year. The statistics is published according to schedule., Read more about timeliness and punctuality, Comparability, The statistics is mandatory and in coherence with other EU-statistics. The statistics for 1995 and subsequent years are fully comparable. The key figures for the period before 1995 data are generally comparable. Changes were made in the questionnaire in 2008, 2010 and 2017, and the statistic is therefore not comparable over time. , Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , Holiday and business trips, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/leisure-and-business-trips

    Documentation of statistics

    Documentation of statistics: Home to work commuting

    Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , psd@dst.dk , Get documentation of statistics as pdf, Home to work commuting 2024 , Previous versions, Commuting 2016, The statistics measure commuting between place of residence and workplace within Denmark, including the distances between commuters’ homes and workplaces. Commuting statistics viewed as commuting between municipalities can be compiled from 1980 onwards. The distance between home and workplace was first calculated in 2006. The statistics are comparable in its current form from 2008 onwards., Statistical presentation, The statistics provide an annual, individual-based account of employed persons’ commuting between place of residence and workplace on the last working day of November. The distance between commuters’ home and workplace is also calculated in kilometres (km). The commuting statistics are published the StatBank, where the data can be distributed on place of residence, workplace, commuting distance, gender, industry (DB07), and socio-economic status., Read more about statistical presentation, Statistical processing, The commuting statistic is compiled on the register-based labour force statistic (RAS), which is based on the Labour Market Account (LMA) - a longitudinal register. A comprehensive data validation is done in the production of AMR. RAS is compiled taking a snapshot (on the populations primary attachment to the labour market) on the last working day in November based on LMA. Based on the information about the address of residence and workplace for employed persons the commuting distance is calculated. , Read more about statistical processing, Relevance, The statistic is relevant for users interested in mobility on the labour market and the data foundation makes it possible to connect detailed information for analysis. , Read more about relevance, Accuracy and reliability, The commuting statistics are based on the Register-Based Labour Force Statistics (RAS), which are used to describe the population’s attachment to the labour market. RAS is compiled from a wide range of data sources that are integrated, error-checked, and harmonised within the labour market accounts. RAS is produced as a snapshot at the end of November based LMA. Therefore, RAS does not carry the same level of uncertainty as statistics based on sample surveys., It is also important to be aware that the calculated commuting distance reflects an ideal situation where every person is believed to travel from residence to workplace by the shortest route and by car. , Read more about accuracy and reliability, Timeliness and punctuality, Commuting statistics for commuting between municipalities are published approximately 11 months after the reference date. Commuting distances are published approximately 17 months after the reference date. , Read more about timeliness and punctuality, Comparability, The statistics can be compiled from 1980 and are comparable from 2008 onwards. Historically, there have been various data breaks in the RAS statistics, which are described in the statistical documentation for RAS., Read more about comparability, Accessibility and clarity, In the StatBank the statistics is published can be found under the subject , Home to work commuting, . For further information, go to the , subject page, . , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/home-to-work-commuting

    Documentation of statistics

    Documentation of statistics: Quarterly Labour Force

    Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , psd@dst.dk , Get documentation of statistics as pdf, Quarterly Labour Force 2024 , Previous versions, Quarterly Labour Force 2019, Quarterly Labour Force 2018, The purpose the Quarterly Labour Market Status (KAS) is to to provide a description of the Danish population's affiliation to the labour market. KAS is an averaging of the populations affiliation to the labour market per quarter and per year and is published annually. KAS covers the hole population from 2017 and on, while it covers the employed part of the population 1st. - 4th. quarter from 2008 to 2017. , Statistical presentation, The Quarterly Labour Market Status (KAS) is an annually individual-based averaging which is calculating the Danish population's affiliation to the labour market per quarter and per year. The statistic is among other things also distributed on information about demography and information about the work place for employees. The statistic is published in StatBank Denmark., Read more about statistical presentation, Statistical processing, The quarterly labour force statistic is based on the Labour Market Account (LMA) which is a longitudinal register. LMA contains information about the populations primary attachment to the labour market on every day of the year. KAS is an average calculation of the population's primary attachment to the labour market broken down by quarters and years. If a person is employed for 91 days in a quarter of 91 days, that person counts as 1 employed. If a person is employed for 30 days, unemployed for 15 days and in education for 46 days, that person counts as 30/91 employed, 15/91 unemployed and 46/91 in education in the quarter. , Read more about statistical processing, Relevance, The quarterly labour force statistic (KAS) is primarily used to structural analysis of the labour market, because the statistic has a very detailed level of information. The statistic is therefore relevant to external as well as internal users and as foundation for analyzing the populations employment over the year. , Read more about relevance, Accuracy and reliability, KAS is an average calculation of the populations primary attachment to the labour market, and the statistic uses the Labour Market Account (LMA) as data source. KAS does not have the same uncertainties as statistics based on surveys. KAS is produced by using a wide range of data sources which are integrated, corrected, and harmonized, and can therefore measure the populations attachment to the labour market significantly better than the single 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 statistics were first published in 2018 with data for employed persons in the first to fourth quarters of 2008-2016. With the exception of a change in the occupational classification in 2010, the statistics for employed persons are comparable throughout the period 2008-2016. From 2017, in addition to persons in employment, the statistics also include the rest of the population with information about their primary attachment to the labour market. KAS is based on administrative registers with national characteristics, which makes it difficult to compare the statistics internationally. , Read more about comparability, Accessibility and clarity, The statistics are published in the StatBank under , Quarterly employed persons, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/quarterly-labour-force

    Documentation of statistics

    Classification of education (DISCED-15), completed educations, v1:2025

    Name: , DISCED15_AUDD_HOVED_V1_2025 , Description: , DISCED-15 is Statistics Denmark's classification system for education., DISCED-15 acts as a classification system across statistics-producing authorities within the education sector in Denmark. At the same time it ensures a clear connection to the international classification system , International Standard Classification of Education (ISCED), ., All educations in DISCED-15 have a four-digit code, e.g. , 4280: Electrician, , which is aggregated in four different ways. The classification system thus organises education and training programs in the following four dimensions:, Main area, Classification of educational programs which follow the structure of the Danish education system, as regulated by law for higher education and for the admission to vocational education., Types of education, Classification of education programs by type, which makes it possible to differentiate the educations in the Danish education system by type of education, regardless of the level of the educations, fields of education or main area., Levels of education, Classification of education programs in the Danish education system by levels, which are consistent with the international education classification ISCED-P (levels of education)., Fields of education, Classification of educational programs by fields, regardless of the levels of the educations. The basic principle in the construction of the fields of education follows the idea of ​​which employment function or industry the education is oriented towards with a view to later employment. Classification by fields of education ensures complete comparability between the Danish education classification and the international education classification ISCED-F (fields of education and training)., Valid from: , February 1, 2025 , Office: , Population and Education , Contact: , Martin Herskind, , hrs@dst.dk, , ph. +45 21 34 03 31 , Codes and categories, Codes and categories are only available in Danish , All versions, Name, Valid from, Valid to, Classification of education (DISCED-15), completed educations, v1:2025, February 1, 2025, Still valid, Classification of education (DISCED-15), completed educations, v1:2024, February 1, 2024, January 31, 2025, Classification of education (DISCED-15), completed educations, v1:2023, February 1, 2023, January 31, 2024, Classification of education (DISCED-15), completed educations, v1:2022, February 1, 2022, January 31, 2023, Classification of education (DISCED-15), completed educations, v1:2021, February 1, 2021, January 31, 2022, Classification of education (DISCED-15), completed educations, v1:2020, February 1, 2020, January 31, 2021, Classification of education (DISCED-15), completed educations, v1:2019, February 1, 2019, January 31, 2020, Classification on education (DISCED-15), completed educations, v1:2018, February 1, 2018, January 31, 2019, Classification on education (DISCED-15), completed educations, v1:2017, February 1, 2017, January 31, 2018

    https://www.dst.dk/en/Statistik/dokumentation/nomenklaturer/disced15-audd

    Documentation of statistics: Legal Activities

    Contact info, Business Dynamics, Business Statistics , Emil Tappe Bang-Mortensen , +45 24 67 85 25 , ebm@dst.dk , Get documentation of statistics as pdf, Legal Activities 2023 , Previous versions, Legal Activities 2021, Legal Activities 2020, Legal Activities 2019, Legal Activities 2018, Legal Activities 2017, Legal Activities 2016, Legal Activities 2015, Legal Activities 2013, The purpose of the statistics Legal Activities is to provide information on turnover and types of services in enterprises with Computer services as main activity. The statistics is also used in the compilation of the national accounts and for revision of activity classifications in the Business Statistical Register. The Statistics is part of the EU's Structural Business Statistics (SBS). The statistics was first published for the reference year 2003. Prior to 2012 it was called Product Statistics for Legal Activities. From 2023 the statistics has been changed to only cover enterprises with at least 5 employees. , Statistical presentation, The statistics provides information on the distribution of total turnover and export on products and services. Furthermore information is collected on the turnover broken down by clients and information on the export broken down by residence of client (resident or Non-resident intra-EU or Non-resident extra-EU). , Read more about statistical presentation, Statistical processing, Data are collected by online questionnaire from a total count of enterprises in the sector Legal activies. In the questionnaire the enterprises are asked to breakdown their turnover by a number of products, services and client categories. It also reported information about export. The reported data are checked by comparing the distribution of turnover among enterprises that are similar. Survey data is grossed up in part by including information turnover from the Accounts Statistics for Non-Agricultural Private Sector in the reference year for the entire population., Read more about statistical processing, Relevance, The statistics is used among enterprises when planning and provides an overview of the development taking place in the service sector. The statistics is also used of the European Statistic bureau, Eurostat, to create EU-statistics about Business Services., Read more about relevance, Accuracy and reliability, All enterprises within the population are required to submit to the statistics and the submitted turnover is subject to adjustments against the turnover from Accounts Statistics for Non-Agricultural private sector, which consists of a large sample, administrative sources and XBRL reports from the Danish Business Authority. Therefore, the statistics accurately reflect the turnover and its distributions on the various services. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics is published once a year and approximately 10 months after the reference year. The statistics is published usually without delay regarding to the announced date. To EU the data must be delivered within 18 months after the end of the reference year. , Read more about timeliness and punctuality, Comparability, The statistics has been compiled since 2003, but it can be problems in comparing figures over time. The questionnaire, the sample design and the calculation method have been adjusted a few time, in 2013, where the time series back to 2012 has been backcasted using new method and from the reference year 2023 where the statistics only covers enterprises with at least 5 employees. , Read more about comparability, Accessibility and clarity, These statistics are published in a collective News from Statistics Denmark , Serviceydelser for serviceerhverv, . The figures can be found in the StatBank under , Legal activities, . For more information go to the subject page for the , Service sector, . International comparable figures are available through Eurostat's webpage under , Business Services, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/legal-activities

    Documentation of statistics

    Documentation of statistics: Educational expenditure (UOE Finance)

    Contact info, Government Finances, Economic Statistics , Marianne Ahle Møller , +45 24 66 00 28 , MNM@dst.dk , Get documentation of statistics as pdf, Educational expenditure (UOE Finance) 2024 , Previous versions, Educational expenditure (UOE Finance) 2023, Educational expenditure (UOE Finance) 2022, Educational expenditure (UOE Finance) 2020, Educational expenditure (UOE Finance) 2019, Educational expenditure (UOE Finance) 2018, The purpose of the statistics is to show how education expenditures are distributed across source of funding, expenditure type, type of institution along with the level of education. The statistic is based on international standards for education expenditures by the manual UOE data collection on formal education (UOE2020) , which is developed by UNESCO, OECD and Eurostat. The statistic is used as an input to OECD's publication Education at a Glance, which compares educational systems across countries. The statistics are developed from finance year 2016 and onwards. Data is consistent and comparable throughout the entire period. , Statistical presentation, The statistic is an annually two-dimensional publication of education expenditures, which shows the consumption of education seen from the perspective of both sources of funding and educational institutions. The statistic is calculated in DKK millions and divided across financing sources, expenditure type, type of institutions and education level. , Read more about statistical presentation, Statistical processing, Data for this statistics is collected annually from a number of both internal and external sources using data extracts and data deliveries. The collected data is validated on a macro level by controls of time series and different reasonableness checks. When data have been validated, the classification according to UOE2020 begins following by imposed distributions based on student data gather internally from Statistics Denmark. Lastly, data is integrated and complied into the final result. , Read more about statistical processing, Relevance, The statistic is relevant for professionals and analysts. The statistic is included in the annual publication by OECD Education at a Glance and will be launch in OECD's database OECD Data Explorer along with Eurostat. Professionals and analysts use the statistics to get a detailed overview of the expenditure to education across education levels and the funding of those in Denmark. , Read more about relevance, Accuracy and reliability, The overall accuracy of the statistics i considered to be high, as the primary data sources is contributed by the general government finances. However, there are uncertainty associated with the funding of households and international sources to education. Moreover, misclassifications can occur as it can be difficult to determined whether some areas are within the scope of UOE2020. The detail level from annual reports used for private tertiary educations are fraught with uncertainty because of the overall coding. , Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 11 months after the end of the reference period and are published without delays in relation to planned release times., Read more about timeliness and punctuality, Comparability, The statistic follow common European guidelines in the manual UOE data collection on formal education (UOE2020). The statistic is fully comparable across time and countries for the entire published time period. Previously the reporting burden to UNESCO, OECD and Eurostat was acquired from the National Agency of IT and Learning under the Ministry of Children and Education. , Read more about comparability, Accessibility and clarity, The statistic is published in New from Statistics Denmark and in the StatBank under , Education expenditures, . For more information see the , subject page, . In addition, the figures are included in OECD's annual publication , Education at a Glance, . Moreover, data is published by , OECD, and , Eurostat, . , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/educational-expenditure--uoe-finance-

    Documentation of statistics

    Documentation of statistics: Finance Companies, Accounts Statistics (Discontinued)

    Contact info, Government Finances , Jesper Søgaard Dreesen , +45 51 64 92 61 , JSD@dst.dk , Get documentation of statistics as pdf, Finance Companies, Accounts Statistics 2023 , Previous versions, Finance Companies, Accounts Statistics 2022, Finance Companies, Accounts Statistics 2021, Finance Companies, Accounts Statistics 2020, Finance Companies, Accounts Statistics 2019, Finance Companies, Accounts Statistics 2018, Finance Companies, Accounts Statistics 2017, Finance Companies, Accounts Statistics 2016, Finance Companies, Accounts Statistics 2015, Finance Companies, Accounts Statistics 2014, Finance Companies, Accounts Statistics 2013, The purpose of the statistics The activity of finance companies is to analyze the performance of major finance companies, including leasing companies, factoring companies, consumer credit companies and non-banking companies, offering loans to businesses and households. The statistics was first published in 2005 with figures for 2001-2004. It is a replacement for "Major finance companies, account statistics" and "Non-bank Consumer credit, Account Statistics"., Statistical presentation, The data covers the activity of the finance companies through additions during the year and outstanding amounts at the end of the year of leases, factoring and other kinds of lending. Also the sectors aggregated profit and loss account and balance sheet are determined., Read more about statistical presentation, Statistical processing, The annual data collection takes place via an upload solution. The financing companies can access an Excel file with the questionnaire on Statistics Denmark's website. In the absence of a reporting, the company is contacted, which results in a response rate of 100. Once the data has been collected, a manual validation of the data is carried out before the publication of the aggregated data., Read more about statistical processing, Relevance, As part of the general statistical information on the financial sector, the statistics refers to financial institutions, public authorities, business community and the general public. Furthermore, the data contributes to the national account statistics., Read more about relevance, Accuracy and reliability, These statistics accuracy and reliability is considered to be good. Based on the response rate of 100 percent, and the way the statistics are designed. However, there may be some uncertainty associated with coverage error, and measurement error due to new players and ongoing product development in the industry., Read more about accuracy and reliability, Timeliness and punctuality, The publication time of the statistic is approx. eight months. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The population is defined for relatively few units, causing some sensitivity to the constant changes in the population. This adjustment is a result of new players and where companies no longer meet the requirements to be included in the statistics., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistics Denmark here: , Financing companies, ., Data can be found in the following tables in the StatBank:, Leasing by type, Type of kredit, Profit and loss, Balance sheet, Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/finance-companies--accounts-statistics--discontinued-

    Documentation of statistics

    Documentation of statistics: National Accounts: Household Consumption Expenditure

    Contact info, National Accounts, Climate and Environment, Economic Statistics , Mercedes Sophie Louise Bech , +45 51 53 61 56 , mcb@dst.dk , Get documentation of statistics as pdf, National Accounts Household Consumption Expenditure 2024 , Previous versions, Household final consumption expenditure (HFCE) is a central component of the national accounts and reflects households’ purchases of goods and services. The national accounts provide a comprehensive description of the economy as well as the transactions occurring between households, businesses, public institutions, and abroad., Consistent time series for annual HFCE figures are available from 1966, and quarterly figures are available from Q1 1990., Statistical presentation, The statistics cover household consumption of goods and services. The figures are presented in StatBank and Nyt fra Danmarks Statistik, giving users the opportunity to analyze consumption patterns and the contribution of different sectors to total household consumption., Read more about statistical presentation, Statistical processing, A set of economic statistics is used for the households final consumption expenditure. The first estimate for a period is prepared before all information is available and is based on the structure of the most recent final national accounts, with imputations using indicators such as short-term economic statistics. New sources are continuously incorporated according to a set schedule, and three years after the reference period, the national accounts and their functional distribution are considered final., Read more about statistical processing, Relevance, Household final consumption expenditure (HFCE) is relevant for all analyzing private consumption and its economic significance. This includes ministries and public authorities, which use HFCE for planning, trends, forecasts, and modelling; industry and interest organizations for analyzing consumption patterns; and researchers, journalists, and the public seeking insight into household consumption over time. User feedback is continuously considered to keep the statistics relevant and useful., Read more about relevance, Accuracy and reliability, Household final consumption expenditure depends on the uncertainty of sources and the assumptions used. Some components, like retail trade, are measured accurately, while others, such as imputed rent and undeclared work, are more uncertain. Early estimates are less precise, and ongoing revisions improve HFCE’s accuracy and reliability., Read more about accuracy and reliability, Timeliness and punctuality, The first version of a preliminary annual national account for Households final consumption expenditure (HFCE) is published at the end of February the following year. The annual accounts are then revised in March and June, and again in June of the subsequent year. The final national accounts for HFCE are published two and a half years after the reference year., Read more about timeliness and punctuality, Comparability, Household final consumption expenditure (HFCE) is part of the national accounts and compiled according to international guidelines, ensuring cross-country comparability. Covering the period from 1966, it reflects households’ purchases of goods and services and is based on various underlying sources. Direct comparisons with other statistics can be difficult due to differing definitions, but HFCE is fully consistent with the overall national accounts., Read more about comparability, Accessibility and clarity, Information on household consumption expenditure is published in StatBank under the subjects Economy and National Accounts. The releases are accompanied by , Nyt fra Danmarks Statistik, , which provides current perspectives and selected commentary. , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/national-accounts--household-consumption-expenditure

    Documentation of statistics

    Documentation of statistics: Income and consumption distribution in the household sector (experimental statistics)

    Contact info, Government Finances, Economic Statistics , Ulla Ryder Jørgensen , +45 51 49 92 62 , URJ@dst.dk , Get documentation of statistics as pdf, Income and consumption distribution in the household sector (experimental statistics) 2022 , Previous versions, The purpose of the statistics is to bring together the benefits from the national accounts system, which provides a coherent description of the economy, and from microeconomic statistics on households, so that one can take a closer look at how incomes and consumption are distributed between different types of households., Statistical presentation, The distribution of income and consumption for the household sector of the national accounts is an experimental annual calculation of income and private consumption at household level, which is aggregated by quintiles and household types. The survey covers private households in Denmark., Read more about statistical presentation, Statistical processing, Virtually all economic statistics that are available are used for the national accounts. When new sources are ready, they are continuously incorporated into the national accounts according to a fixed rhythm. Three years after a given period, the national accounts are considered final., The consumption survey is a sample survey, where the number of households is 2,200 out of Denmark's total of approx. 2.8 million private households. From 2024, 3,200 will be asked. The study includes information from three data sources: Accounts, CAPI interviews and registers., Read more about statistical processing, Relevance, The statistics are relevant to everyone who deals with socio-economic conditions for households., Read more about relevance, Accuracy and reliability, The ability of the national accounts to accurately describe economic reality depends partly on the uncertainty associated with the sources and partly on the model assumptions underlying the preparation. Some parts can be calculated more precisely than others, as there is better access to source data. The first estimates of a period's national accounts will be more uncertain than the final version, which comes after three years, as they are continuously revised when new sources become available., The participation rate for the Consumption Survey in the years 2018-2022 has varied with . This creates uncertainty, not least for detailed consumption groups. For the total consumption, this means that there is an uncertainty margin of +/- 1.2 per cent. while for bread, for example, it is 2 per cent. For Food and non-alcoholic beverages, it is 1.2 per cent. , while for Alcoholic beverages and tobacco it is 4.8. There is under-reporting in a number of areas such as alcohol, tobacco, prostitution and undeclared work. The uncertainty is greater when data is based on accounting instead of interviews, and it will be greater if you look at smaller subgroups of households. , In these statistics, we have chosen a more general level to ensure greater consistency between the national accounts and the consumption survey, as well as to minimize uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics were first published approx. 23 months after the end of the reference year., Read more about timeliness and punctuality, Comparability, The national accounts and the consumption survey are carried out according to guidelines from the European statistical office Eurostat. Comparable figures are published by Eurostat. The distributional figures are still experimental in both Eurostat and Denmark., Read more about comparability, Accessibility and clarity, In the Statistics Bank, the results of the statistics are published under the subject , Complete national accounts - Household consumption, total economy, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/income-and-consumption-distribution-in-the-household-sector--experimental-statistics-

    Documentation of statistics

    Documentation of statistics: Productivity

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

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

    Documentation of statistics