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Analyses: Large language models and the Danish labour market

Generative artificial intelligence (AI) tools such as large language models are spreading rapidly. The most prominent example is ChatGPT, which gathered more than 100 million active users within two months. This type of generative AI has the potential to change the way people work, creating opportunities for innovation and productivity gains. However, the opportunities and challenges will most likely be unequally distributed across the workforce., This analysis explores the unequal economic impact of large language models (LLMs) on the Danish Labour Market. The analysis uses the so-called AI Occupational Exposure (AIOE) scores from a study of the American labour market and merges these scores with administrative data from Statistics Denmark. The AIOE scores reflect the relatedness between AI applications and human abilities connected to different occupations. Thus, the scores express potential economic impact of AI applications across occupations through either labour-augmenting or labour-displacing effects., Main conclusions:, Occupations dominated by cognitive routine tasks have the highest potential to change through large language models. , Legal Professionals, is the occupation with the highest LLM score. The occupation with the lowest score is , Painters, building structure cleaners & related trades worker, ., Economic activities influenced by cognitive abilities have higher LLM scores than activities dominated by physical tasks. The activity with the highest LLM score is , Higher Education, . The activity with the lowest score is , Building completion and finishing, ., Employed females altogether have more potential to apply large language models than employed males. However, within , Human Health & Social Work activities, women have a slightly lower LLM score than males., Employees with high personal yearly income generally have more potential to use and take advantage of large language models than employees with lower income.,  , The analysis is available in Danish here: , Store sprogmodeller og det danske arbejdsmarked,   , Get as pdf, Large language models and the Danish labour market, Colophone, Large language models and the Danish labour market, Subject group: Labour and income, Released: 8 February 2024 08:00, No. 2024:2, ISSN pdf: 2446-0354, Contact:

Analysis

Analyses: Who uses weight loss medicines in Denmark?

In 2023, 117,500 adults redeemed a prescription for a weight loss medicine. This corresponds to 2.4 per cent of the adult population. Weight loss medicines are mainly targeted at people with a BMI of at least 30, but what else characterises the users?, This analysis takes a closer look at the users of weight loss medicines, with a special focus on users in the first half of 2023. In the analysis, data on redeemed prescriptions is combined with information from Statistics Denmark’s registers. This allows, among other things, to examine the users’ sex, age, income, and municipality of residence.,  , Main conclusions:, The number and proportion of adults who have redeemed at least one prescription for weight loss medicines has increased significantly from 15,200 (0.3 per cent) in 2021 to 27,800 (0.6 per cent) in 2022 and 117,500 (2.4 per cent) in 2023. However, the number is still lower than 25 years ago when 131,100 adults (3.1 per cent) used weight loss medicines., The proportion of users of weight loss medicines is higher for women in all years. In the first half of 2023, 72 per cent of the users were women and 28 per cent were men., The proportion of users was highest in the age group of 50-59-year-olds (3.2 per cent) and lowest in the age group of 80-year-olds and older (0.1 per cent)., The proportion of users of weight loss medicines increases with income. In the first half of 2023, 1.6 per cent of the people in the lowest income quintile used weight loss med-icines, while it was about 3.4 per cent of the people in the highest income quintile - when using the equivalised disposable family income among the 30-59-year-olds., There is a difference in the proportion of users of weight loss medicines across municipalities. The highest proportion of users was in Tårnby (2.9 per cent), while the lowest proportion was in Læsø (0.8 per cent)., Gentofte municipality had the highest proportion of users of weight loss medicines in the first part of 2023 when the proportion is related to people with self-reported obesity in 2021. In Gentofte, there were 24.5 users of weight loss medicines per 100 people liv-ing with obesity, while in Læsø, there were 2.9 users per 100 people living with obesity.,  , The analysis is available in Danish here: , Hvem bruger slankelægemidler?, Get as pdf, Who uses weight loss medicines in Denmark?, Colophone, Who uses weight loss medicines in Denmark?, Subject group: People, Released: 6 May 2024 08:00, No. 2024:3, ISSN pdf: 2446-0354, Contact:, Emilie Rune Hegelund, Telephone: +45 20 56 47 11

Analysis

Documentation of statistics: Quarterly national accounts (Discontinued)

Contact info, National accounts, Economic Statistics , Carmela Moreno , cam@dst.dk , Get documentation of statistics as pdf, Quarterly National Accounts 2018 Quarter 4 , Previous versions, Quarterly National Accounts 2018 Quarter 3, Quarterly National Accounts 2018 Quarter 2, Quarterly National Accounts 2018 Quarter 1, Quarterly National Accounts 2017 Quarter 4, Quarterly National Accounts 2017 Quarter 3, Quarterly National Accounts 2017 Quarter 2, Quarterly National Accounts 2017 Quarter 1, Quarterly National Accounts 2016 Quarter 4, Quarterly National Accounts 2016 Quarter 3, Quarterly National Accounts 2016 Quarter 2, Quarterly National Accounts 2016 Quarter 1, Quarterly National Accounts 2015 Quarter 4, Quarterly National Accounts 2015 Quarter 3, Quarterly National Accounts 2015 Quarter 2, Quarterly National Accounts 2015 Quarter 1, Quarterly National Accounts 2014 Quarter 4, Quarterly National Accounts 2014 Quarter 3, The quarterly national accounts present an overall picture of the short-term economic development within the framework of a system of coherent definitions and classifications., Statistical presentation, The National Accounts are designed to present a complete picture of the economy. The National Accounts provide the conceptual and actual tool to bring to coherence all economic activity and development in Denmark., Read more about statistical presentation, Statistical processing, The quarterly national accounts are compiled on the basis of all relevant short-term statistics describing parts of the economy. Combining these statistics with the definitions and classifications of the national accounts and the detailed annual national accounts makes it possible to balance all the information regarding the supply and use to a complete picture of the economic activity. For more information detailed descriptions of sources and methods can be found in , Danish Quarterly National Accounts, and , Danish Sector National Accounts, ., Read more about statistical processing, Relevance, As the basic data for everyone dealing with socioeconomic conditions like economic ministries, organizations, the press, the financial sector, larger companies, students and researchers. Quarterly national accounts are used as the basis for analyzing the economic development. National accounts continuously evaluate feedback from users via national and international forums., Read more about relevance, Accuracy and reliability, The quarterly national accounts are compiled using a number of primary statistics. Inaccuracy in these primary statistics as well as the adjustment of the statistics to conform to the national account framework will affect the reliability. However, the juxtaposition in the framework of the national accounts will contribute to reduce the inaccuracy., Read more about accuracy and reliability, Timeliness and punctuality, The quarterly national accounts are published first time 60 days after the end of the quarter and in a revised form 90 days after the end of the quarter. The quarterly sector accounts are published 90 days after the end of the quarter., The statistics are published according to schedule., Read more about timeliness and punctuality, Comparability, The time series in the quarterly national accounts are consistent with the annual national accounts., Read more about comparability, Accessibility and clarity, News from Statistics Denmark (Nyt fra Danmarks Statistik): , Kvartalvist nationalregnskab, ., Statistical News (Statistiske Efterretninger, Nationalregnskab og offentlige finanser)., The annual publication National Accounts (Nationalregnskab)., Data in , Statbank Denmark, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/quarterly-national-accounts--discontinued-

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: Labour Market Account

Contact info, Labour Market , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Labour Market Account 2021 , Previous versions, Labour Market Account 2019, Labour Market Account 2016, Labour Market Account 2015, Labour Market Account 2013, Labour Market Account 2014, New Labour Market Account concerning the population´s labour market status have been developed by Statistics Denmark. , The primary purpose of the Labour Market Accounts (LMA) is to provide a complete overview of the population´s labour market status compiled in terms of full-time persons, covering a given period of time or a given point-in-time., Statistical presentation, The Labour Market Account is compiled annually and provides information on the population´s labour market status, where labour-market related activities are given the highest priority. The statistics are compiled in terms of full-time persons. , Data on the population´s labour market status are broken down by socio-economic groups i.e. persons in employment, students, unemployed persons and other persons receiving public benefits, children and young people and other people outside the labour force., Read more about statistical presentation, Statistical processing, The primary statistical data for the LMA is a newly developed register called the AMR-UN (LMA without standardization of hours)., The AMR-UN is composed of administrative data, which are integrated and harmonised in a statistical system. , On the basis of the AMR-UN, the LMA is constructed by means of an hourly standardization of the population´s labour market status, where a person can at maximum contribute with 37 hours per week, corresponding to the existing hourly standard., Read more about statistical processing, Relevance, Over a number of years Statistics Denmark has carried out work on developing the LMA. Several users have indicated their great interest in and expectations with regard to the statistics/register. , Users of the LMA are typical ministries, organisations and research institutes, etc., Read more about relevance, Accuracy and reliability, In the LMA, a wide range of data sources are subjected to data editing and harmonisation in one statistical system. This implies that the LMA can conduct far better analyses of the labour market than the analyses that can be conducted by each individual statistic. At the same time, the LMA constitutes a census of the population and consequently, the statistical uncertainty is reduced compared to statistics compiled on the basis of sample surveys., Against this background, the quality of the statistics is considered to be relatively high. Despite this, there is still some degree of uncertainty linked to the statistics., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately 15 months after the reference year., Read more about timeliness and punctuality, Comparability, The statistics cover the period 2008 to 2021, and during this period the development are comparable. , Read more about comparability, Accessibility and clarity, The statistic is published i the statbank , Labour market accounts, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/labour-market-account

Documentation of statistics

Documentation of statistics: Employee Trade Unions

Contact info, Labour Market, Social Statistics , Mikkel Zimmermann , +45 51 44 98 37 , MZI@dst.dk , Get documentation of statistics as pdf, Employee Trade Unions 2024 , Previous versions, Employee Trade Unions 2023, Employee Trade Unions 2022, Employee Trade Unions 2021, Employee Trade Unions 2020, Employee Trade Unions 2019, Employee Trade Unions 2018, Employee Trade Unions 2017, Employee Trade Unions 2016, Employee Trade Unions 2015, Employee Trade Unions 2014, Employee Trade Unions 2013, The purpose of the statistics is to compile aggregated annual statistics showing the number of members of employee organisations with attachment to the labour market. The statistics been complied since 1994, but is in its current form comparable from 2007 and onwards. , Statistical presentation, The statistics provide an overview of the number of members of employee organisations with attachment to the labour market i.e. excl. trainees, retirees, early retirees and self-employed. The statistics are grouped by central organisations/individual organisations and gender. The statistics are published annually and disseminated in the newsletter Nyt fra Danmarks Statistik and in the StatBank., Read more about statistical presentation, Statistical processing, These statistics are based on annual reports from employees' organisations on the number of members attached to the labour market per December 31. Data are typically validated by comparing the current year’s reporting with that of previous years for each organisation. As of the reference date 31 December 2023, total membership figures are also reported for each organisation. These totals are then compared with the reported number of members with labour market affiliation per organisation to ensure consistency., Read more about statistical processing, Relevance, Users of the statistics are typically employee and employer organisations, researchers and the media. No dissatisfaction has been expressed with the statistics., Read more about relevance, Accuracy and reliability, The statistics are based on reports from Central Employee Organisations and other employee organisations. Not all employee unions are able to calculate the precise figures exclusive members not attached to the labor market, i.e.. students, early retirees and pensioners, and self-employed. The data are therefore believed to be a little overestimated for some organisations. On the other hand, there may be small employee organisations that are not included. The data are normally not revised, but if errors are detected they are corrected back in time as far as possible. Although participation in the statistics is voluntary, all employee organisations appear to submit data., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 4-5 months after the reference date. , The statistics are usually published on the scheduled date without delay., Read more about timeliness and punctuality, Comparability, The statistics have been compiled (without data breach) since 2007. Minor breaks in the time series may occur when employee organisations change their reporting methods. For example, the previously observed sharp decline in membership figures for some organisations (mainly those under LO) from 2011 to 2012 was due to the inclusion of members without labour market affiliation in earlier reporting. However, this decline has been addressed as of the publication on 19 May 2025, by revising the reported figures downwards for the period 2007–2011., Read more about comparability, Accessibility and clarity, The statistics is published yearly in a Danish press release (Nyt fra Danmarks Statistik) at the same time as the tables are updated in the StatBank. In the StatBank, the statistics ca be found under the subject , Trade unions, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/employee-trade-unions

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

Documentation of statistics: Climate footprint (experimental statistics)

Contact info, National Accounts, Climate and Environment , Peter Rørmose Jensen , +45 40 13 51 26 , PRJ@dst.dk , Get documentation of statistics as pdf, Climate footprint (experimental statistics) 2021 , Previous versions, The purpose of the statistics is to measure the global emission of greenhouse gases from the supply chains for Danish final use (Danish consumption, investment and export). It illustrates correlations between Danish final use and emissions of greenhouse gases from Danish and international production. Global emission of greenhouse gases from Danish consumption and investment constitutes Denmark's Climate Footprint. The statistic is experimental and have been prepared since 2021 in collaboration with the Danish Energy Agency, which uses it for the annual publication "Danmarks Globale Klimapåvirkning – Global Afrapportering"., Statistical presentation, The statistics show the amount of greenhouse gas that has been emitted in the supply chains for Danish final use annually from 1990 onwards. The emissions are distributed by type of final use, emitting industries and countries, as well as by supplying industries., Read more about statistical presentation, Statistical processing, The climate footprint is calculated with a multi-regional environmental economic input-output (MRIO) model that links data from Statistics Denmark on Danish production and greenhouse gas emissions with data from the international database EXIOBASE on international production and greenhouse gas emissions., Read more about statistical processing, Relevance, The climate footprint is relevant for everyone who is interested in relations between Danish consumption and investment and global emissions of greenhouse gases. The climate footprint is prepared in collaboration with the Danish Energy Agency's Center for System Analysis, which uses it in their annual report "Danmarks Globale Klimapåvirkning – Global Afrapportering"., Read more about relevance, Accuracy and reliability, The overall precision of the statistics is not as high as other statistics from Statistics Denmark, which are based on directly observable data. The majority of the figures in this statistic are the result of calculations with Danish and international input-output models. The international input-output model in particular is uncertain because it is a compilation of figures from many countries of uneven quality. However, it is assessed that the precision is as good as it can be at the present time, when available sources and methods are taken into account., Read more about accuracy and reliability, Timeliness and punctuality, The climate footprint is an experimental statistic and does not yet have a fixed publication time. When a publication date is determined, it is published in Statistics Denmark's publication calendar., Read more about timeliness and punctuality, Comparability, The statistics are compiled for 1990 and onwards and are comparable over time. The statistics have been produced in collaboration with the Danish Energy Agency and are used for the Danish Energy Agency's report "Danmarks Globale Klimapåvirkning – Global Afrapportering". there will therefore be full agreement between results published by the Danish Energy Agency and Statistics Denmark., As there is not yet full international agreement on methods and data bases for calculating climate footprints, there will not necessarily be full comparability with the calculations of other institutions or other countries., Read more about comparability, Accessibility and clarity, In the Statbank, the climate footprint is published under the subject , Energy and emissions, in the tables AFTRYK1 and AFTRYK2., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/climate-footprint--experimental-statistics-

Documentation of statistics

Documentation of statistics: Deaths and life expectancy (Discontinued)

Contact info, Population and Education , Get documentation of statistics as pdf, Deaths and life expectancy 2016 , Previous versions, Deaths and life expectancy 2015, Deaths and life expectancy 2013, These statistics cover all deaths among people with usual residence in Denmark regardless of whether the death occurs in Denmark or abroad., Information about cause of death is not available for those people, who have died abroad., The statistics of the dead include in the annual calculation of average life expectancy, compiled by Statistics Denmark. The average life expectancy indicates the expected average life expectancy of a newborn, based on mortality for the last two or five years period, e.g. 2016-2017., Statistical presentation, These statistics contains information on number of deaths by sex, age and municipality of residence., These statistics cover all deaths among people with usual residence in Denmark regardless of whether the death occurs in Denmark or abroad., Information about cause of death is not available for those people who have died abroad., Read more about statistical presentation, Statistical processing, Daily deliveries from the Central Population Register (CPR) and yearly delivery from Statens Serum Institut (SSI) are basis for the statistics., Data is not checked for errors., Read more about statistical processing, Relevance, Municipalities, regions, ministries, the media and private individuals are using the statistics for public and private purposes and as input to the public debate., Read more about relevance, Accuracy and reliability, The statistics are based on the Central Population Register (CPR). The quality of the data is very high., For approximately 5 per cent of the deaths the cause of death is missing. These people have often died abroad., The statistics of death include the annual calculation of average life expectancy, compiled by Statistics Denmark. The average life expectancy indicates the average number of years a newborn is expected to live on the condition that current age-related death rates remain constant in the future. Life expectancy should therefore only be seen as an indicator of the current mortality of the population - not a prediction of how long newborns will live in practice because age-specific mortality generally decreases over time. The average life expectancy by municipality may however be subject to uncertainty - especially for the small municipalities., Read more about accuracy and reliability, Timeliness and punctuality, The statistics concerning deaths is published app. 45 days after the end of the year., Information concerning the causes of deaths however are quite delayed and are disseminated irregularly., Read more about timeliness and punctuality, Comparability, The statistics is comparable over time., The codes for causes of death have been altered. Until 1993 ICD8 (International Classification of Causes of Death 8th Rev) have been applied. This implies that causes of death before and after 1994 can’t necessarily be compared. However, there have been produced comparable statistics at certain levels., Read more about comparability, Accessibility and clarity, News from Statistics Denmark, and the Statbank., Yearly publications: , Vital statistics, , , Statistical Yearbook, and , Statistical ten-year review, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/deaths-and-life-expectancy--discontinued-

Documentation of statistics

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