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    Analyses: How big are Danish exports and who are our main trading partners?

    In recent decades it has become more common to produce goods across national borders. Increasing globalisation challenges our understanding of what a country's exports encompass and what different statistical measures of exports show., Previously, different export statistics provided a fairly similar picture of Denmark’s exports and trading partners. However, an increasing proportion of Danish exported goods never crosses Danish borders, and that has resulted in increasing differences across the various export statistics. This analysis describes Danish exports and trading partners, based on the different export statistics., Main conclusions:, Danish exports in goods are largest when measured in Denmark’s balance of payments, where the sale of goods that have never crossed Danish borders are included as exports. Today, around a sixth of the total Danish export of goods takes place outside of Danish borders., Only goods which have crossed the Danish border are classified as exports in the international trade in goods statistics which implies that the export of goods appears lower here than in the balance of payments., Exports appear lowest when measured by Danish value added, as these calculations discount the value of the imports included in the production of the exported goods and services. Estimates from an Input-Output model in Statistics Denmark suggest that imported contents in exported goods and services constitute nearly half of the total value. , Regardless of the type of export statistics, Germany is Denmark’s most important export market., On the basis of goods which cross the Danish border, the US is Denmark’s sixth largest export market. When goods sold outside Denmark’s border are taken into account, the US is Denmark’s third largest export market., Looking at the final markets for the part of exports resulting from production in Denmark the US is the second largest export market as measured by Danish value added according to estimates in an OECD international Input-Output model., Get as pdf, How big are Danish exports and who are our main trading partners?, Colophone, How big are Danish exports and who are our main trading partners?, Subject group: Economy, Released: 5 March 2018 08:00, No. 2018:4, ISSN pdf: 2446-0354, Contact:, Mads Møller Liedig, Telephone: +45 40 12 97 72

    Analysis

    Analyses: The global organisation of industrial groups has an impact on the measurement of Danish production and income

    The way in which Danish enterprises choose to organise their production and sales in the global economy impacts whether it is reflected as domestic production and value added (GDP) or only as income (GNI) in the national accounts. When Danish enterprises sell products abroad, the activities are included in Danish GDP, whereas income based on sales via subsidiaries abroad is only included in GNI. In this way, the choice of sales channel impacts the statistics on Danish production and income., This analysis describes the global set-up of Danish industrial groups and their impact on the Danish economy. Focus is on the close correlation between Danish exports and in-come from subsidiaries abroad. The analysis is an extension of a Statistics Denmark analysis from 2016 dealing with goods exports outside Denmark by Danish manufactu¬ring enterprises. Income data from the central bank of Denmark, Nationalbanken, has allowed us to further document the importance of the industrial groups to the Danish economy., Main conclusions:, The industrial groups are important to the Danish economy; they export goods and services produced in Denmark or abroad and receive income from subsidiaries abroad. , In 2016, Danish industrial groups’ sale abroad of goods not crossing the Danish border accounted for almost a third of their total sale of goods abroad of DKK 524 billion., The income from subsidiaries of DKK 42.1 billion accounts for approximately one third of total earnings from Danish industrial groups’ manufacturing activities abroad. These ear-nings could have been counted as exports had the group chosen a different role for the production taking place in subsidiaries abroad., In 2016, the industrial groups’ activities abroad accounted for approximately 6 per cent of the Danish gross national income (GNI) and approximately 4 per cent of the gross domestic product (GDP).,  , This is a translation of an analysis previously published in Danish 1 October 2018. See the analysis , here., Get as pdf, The global organisation of industrial groups has an impact on the measurement of Danish production and income, Colophone, The global organisation of industrial groups has an impact on the measurement of Danish production and income, Subject group: Economy, Released: 27 May 2019 08:00, No. 2019:7, ISSN pdf: 2446-0354, Contact:, Mads Møller Liedig, Telephone: +45 40 12 97 72

    Analysis

    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: 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: Number of Persons Employed in the Construction Industry

    Contact info, Short Term Statistics , Kasper Emil Dueholm Freiman , +45 23 45 47 32 , KFR@dst.dk , Get documentation of statistics as pdf, Number of Persons Employed in the Construction Industry 2024 , Previous versions, Number of Persons Employed in the Construction Industry 2020, Number of Persons Employed in the Construction Industry 2019, Number of Persons Employed in the Construction Industry 2018, Number of Persons Employed in the Construction Industry 2017, Number of Persons Employed in the Construction Industry 2016, Number of Persons Employed in the Construction Industry 2015, Number of Persons Employed in the Construction Industry 2014, The purpose of the statistic is to show trends in the number of employed within the private construction industry by kind of activity and type of work (new buildings, repair and maintenance of buildings, civil engineering, etc.). The first sample survey of employment in the construction industry was conducted in 1961., Statistical presentation, The statistic provides information on trends in the number of employed within the private construction industry. Employment is analyzed by kind of activity and type of work (new buildings, repair and maintenance of buildings, and other)., Read more about statistical presentation, Statistical processing, The reported data is scaled to the total population of professional units with main activity in construction. No numbers are imputed. The total employment in each construction industry and each type of construction work is seasonally adjusted. The cross between construction industry and type of construction work is not seasonally adjusted., Read more about statistical processing, Relevance, Interest in the statistic is high among users. Users of the statistics are trade associations, banks, politicians, public authorities, international organizations, private business enterprises and the news media. The statistics are a supplement to the other short-term statistics relating to this area., Read more about relevance, Accuracy and reliability, The quality of the statistic is assessed as being high. There are no quantitative measures of the total uncertainty. The sample uncertainty for the total employment is estimated to be approximately 0.5 pct. The uncertainty that results from non-response, wrong reported numbers and misunderstandings has little effect on the numbers. The statistic is reliable in the sense that previously published numbers rarely are revised., Read more about accuracy and reliability, Timeliness and punctuality, The statistic is published four times a year, media January, April, July and October. Time from the census-date to publication is about 9 weeks. The statistic is normally published at the announced time., Read more about timeliness and punctuality, Comparability, I the archive there are unemployment numbers dating back to 1994 Numbers from years before 2000 are not comparable to the new time series. The statistics on employment in the construction industry supplement the other short-term statistics relating to this area., Read more about comparability, Accessibility and clarity, The newest numbers are published at , STATBANK, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/number-of-persons-employed-in-the-construction-industry

    Documentation of statistics

    Documentation of statistics: Nights Spent at Marinas

    Contact info, Short Term Statistics, Business Statistics , Majbrit Holst , +45 24 94 08 24 , mbj@dst.dk , Get documentation of statistics as pdf, Nights Spent at Marinas 2025 , Previous versions, Nights Spent at Marinas 2024, Nights Spent at Marinas 2023, Nights Spent at Marinas 2022, Nights Spent at Marinas 2021, Nights Spent at Marinas 2020, Nights Spent at Marinas 2019, Nights Spent at Marinas 2018, Nights Spent at Marinas 2017, The purpose of the survey Overnight stays in marinas is to supply information on the tourism activity in the Danish marinas. Users of the statistics is e.g. business and tourism organisations as well as municipalities and regions to analyse the development in tourism. Furthermore the statistics is used to identify the most popular marina areas in Denmark. The survey is collected on a voluntary basis and is made in collaboration with VisitDenmark. The survey has been compiled since 1992. The survey went from mandatory to voluntary in 2004 which has had an impact on the response rate and thus also the comparability over time., Statistical presentation, The statistics regarding marinas is a monthly seasonally survey about boats and guest nights spent by visiting yachts in marinas in the months of May-September. The statistics are divided into nationalities of the guests, as well as geographically by regions, parts of the country and waters. In addition, there is an annual assessment of the capacity of marinas divided into parts of the country and the size of the marina. Numbers of Municipal distribution is published at the homepage of VisitDenmark., Read more about statistical presentation, Statistical processing, Data for the statistics is collected monthly for for the reference months May to September. The monthly statistics shows temporary data for the activity in the marinas. If a marina has not reported data from the same month the year before is imputed. At the end of the reference year the imputed data is replaced by reported final data for the year. The numbers of nights spent at marinas are calculated by using a average factor for the size of the crew. The average factor is based by a survey made by VisitDenmark in 2017. Data for the statistics is collected via an upload solution or by a electronis questionaire. 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 marina statistics was made voluntary from 2004 which may influence the comparability over time as well as the coverage. Some reports are based on a best estimate by the respondent and therefore in risk of being wrong. , Read more about accuracy and reliability, Timeliness and punctuality, The survey is published on a monthly basis for the reference months May-September approx. 40 days after the end of the reference month. Furthermore, an annual publication is made that is published approx. 75 days after the end of the reference year. The survey is published according to the scheduled time table and therefore has a high degree of punctuality., Read more about timeliness and punctuality, Comparability, From 2004 the statistics are voluntary which minimize the comparability over time. From 2007-20016 a new factor regarding the size of the crew has been phased in. From 2017 an onwards this factor is fully phased in. , Read more about comparability, Accessibility and clarity, The statistics are published in , Nyt from Statistics Denmark, . In the statbank the figures are published under the subject , Marinas, and , All 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 marinas 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/nights-spent-at-marinas

    Documentation of statistics