Search result

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

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

Publication

STRAF49: Average length of unsuspended sentences (month)

sex, age, type of offence, type of decision and time
2007-2024 (Number)

https://www.statbank.dk/STRAF49

Tables in StatBank

Scheduled Releases

Select filtering, Subject group, All subjects, People, Labour and income, Economy, Social conditions, Education and research, Business, Transport, Culture and leisure, Environment and energy, About Statistics Denmark, Subsubject, All subsubjects, Absence and labour disputes, Accommodation and travel, Adult education and continuing training, Agriculture, horticulture and forestry, Area, Balance of payments and international trade, Business economy, Business tendency surveys, Construction, Consumption, Crime and justice, Cultural heritage, Danmark i Tal, Democracy, Digital behaviour and cultural habits, Digital payments, Education, economy and employment in the cultural field, Educational pathways, Educational status of the population, Employment and unemployment, Energy consumption and energy prices, Environmental-economic accounts, Film and theatre, Financial markets, Financial sector, Fishery and aquaculture, Full-time education programmes, General government economy, Goods transport, Health, Households and family matters , Housing, Income and earnings, International enterprises, Labour market status of the population, Libraries, Living conditions, Manufacturing industries, Means of transport, Migration, Museums and zoos, Music, Names, National accounts, National church, News media and literature, Nordic Statistical Yearbook, Organic production and trade, Passenger transport, Persons on public benefits, Population, Price index, Property, Publications, Research, development and innovation, Service sector, Social support services, Sports, Statistisk Tiårsoversigt, Statistisk Årbog, Structure of business, Trade, Traffic accidents, Traffic and infrastructure, Wealth, Udgivelsestype, All releases, News from Statistics Denmark, StatBank tables, Publications, Analysis, Periode, Today, 8 days, 1 month, 3 months, 6 months, 1 year, Showing 1 to 68 of 68,  , Delayed releases

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

Documentation of statistics: Register-Based Labour Force Statistics

Contact info, Labour Market, Social Statistics , Pernille Stender , +45 24 92 12 33 , PSD@dst.dk , Get documentation of statistics as pdf, Register-Based Labour Force Statistics 2024 , Previous versions, Register-Based Labour Force Statistics 2023, Register-Based Labour Force Statistics 2022, Register-Based Labour Force Statistics 2021, Register-Based Labour Force Statistics 2020, Register-Based Labour Force Statistics 2019, Register-Based Labour Force Statistics 2018, Register-Based Labour Force Statistics 2017, Register-Based Labour Force Statistics 2016, Register-Based Labour Force Statistics 2015, Register-Based Labour Force Statistics 2014, The purpose of the Register-Based Labour Force Statistics (RAS) is to measure the population’s primary attachment to the labour market. This attachment is recorded at the end of November and compiled once a year. The first RAS compilation was made at the end of November 1980., Statistical presentation, RAS is an annual, individual-based compilation that records the population’s attachment to the labour market on the last working day of November. The population’s attachment is divided into three main socio-economic groups: employed, unemployed, and persons outside the labour force. The statistics can be broken down by demographic variables and education, as well as by industry, sector, and municipality of the workplace for employed persons. The data are published in News from Statistics Denmark and in the Statistics Denmark StatBank, and detailed micro-data are made available through Statistics Denmark’s Research Service., Read more about statistical presentation, Statistical processing, The register-based labor force statistics (RAS) are based on the Labor Market Account (AMR_UN), which is a longitudinal register. When RAS is compiled, a status assessment (in relation to the population's primary attachment to the labor market) is carried out on the last working day of November in the AMR. Based on AMR_UN, it is also possible to perform status assessments on arbitrary days throughout the year., Read more about statistical processing, Relevance, The register based labour force statistic (RAS) is primarily been used to structural analysis of the labour market, because the statistic has a very detailed level of information. Many external as well as internal users are using the statistic., Read more about relevance, Accuracy and reliability, RAS is a register-based compilation that uses many data sources to measure the population's affiliation to the labor market. This means that RAS does not have the same uncertainty as statistics based on samples. RAS consists of a wide range of data sources, which are integrated, checked for errors, and harmonized, making it possible to provide a better picture of the population's connection to the labor market than the individual statistics can., Read more about accuracy and reliability, Timeliness and punctuality, From the publication of figures for the end of November 2018 onwards, the release is carried out in two stages. In the first release, persons outside the labor force are grouped together in a single category. This publication takes place approximately 11 months after the reference point. In the second publication, which occurs approximately 15 months after the reference point, persons outside the labor force are divided into different socioeconomic groups., Read more about timeliness and punctuality, Comparability, The first version of the RAS statistics includes the population resident in Denmark as of the 1 January 1981 and its attachment to the labour market at the end of November 1980. The statistic has been compiled once every year since. New and better data foundations and changes in the labour market have however caused a number of data breaks over time, which have influence on the possibility of comparing data over time. Since RAS is based on administrative registers with national distinctive marks, it is very difficult to compare the statistic in an international level. , Read more about comparability, Accessibility and clarity, The statistics is published in Statbank Denmark: , Labour market status (RAS), and , Employed persons (RAS), . , For further information go to the subject pages , Labour market status (RAS), and , Employed persons (RAS), ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/register-based-labour-force-statistics

Documentation of statistics

Documentation of statistics: Consumer Expectations Survey

Contact info, Prices and Consumption, Economic Statistics , Zdravka Bosanac , +45 61 15 16 74 , ZBO@dst.dk , Get documentation of statistics as pdf, Consumer Expectations Survey 2025 , Previous versions, Consumer Expectations Survey 2024, Consumer Expectations Survey 2023, Consumer Expectations Survey 2022, Consumer Expectations Survey 2021, Consumer Expectations Survey 2020, Consumer Expectations Survey 2019, Consumer Expectations Survey 2018, Consumer Expectations Survey 2017, Consumer Expectations Survey 2016, Consumer Expectations Survey 2015, The purpose of the survey is to analyze the consumer climate through questions about the economic situation as perceived by consumers at a given time concerning both the general economic situation in Denmark and the financial situation of the family. The main results are coordinated in the so-called consumer confidence indicator. The Danish surveys have been conducted since 1974. From 1996 data is collected in all 12 months of the year., Statistical presentation, Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements., Read more about statistical presentation, Statistical processing, This survey are sample surveys, where a representative sample of persons 16-74 years are asked among other things about the consumer expectations. The results are corrected from the effects of non-sampling and non-response and then enumerated so that the figures can directly be classed with the population of adult persons and families in Denmark. Data are validated using logical validation rules. A seasonal pattern could not be identified in the series and no seasonal adjustment was undertaken., Read more about statistical processing, Relevance, The most important user is the European Commission for Economy and Finances (ECFIN), which receives detailed tables for all questions and publishes seasonally adjusted consumer confidence indicators for all EU member states. The figures are also of great interest to the news media., Read more about relevance, Accuracy and reliability, As the results are based on a sample survey, they are subject to a certain degree of statistical uncertainty. This depends on both the size of the sample and the number of completed interviews, which vary from survey to survey. With a sample of approximately 1,500 persons and a response rate of about 65%, which has normally been achieved in the last few years, the statistical uncertainty is in 95 pct. of the cases estimated ranged within +/- 3 percentage points. A change in an indicator should be greater than 5 percentage points to indicate a significant change., Read more about accuracy and reliability, Timeliness and punctuality, There is no difference between planned and actual release time., Read more about timeliness and punctuality, Comparability, The questions asked in connection with these statistics in Denmark are also asked in the European Commission's Consumer confidence survey '. The European Commission publishes figures for all EU countries in its database. Eurostat's consumer confidence is based on a slightly different composition of questions than the current one in Denmark. Therefore, the overall consumer confidence indicators calculated in Denmark and in Eurostat are not directly comparable, whereas all sub-indicators are directly comparable. The questions shown in the section 2.01. Data description, have been asked in all the omnibus surveys since 1974. Due to minor changes in the calculation method, an immediate comparison is only possible from 2007 onwards. , Read more about comparability, Accessibility and clarity, The results are published in , News from Statistics Denmark, and , Statbank Denmark, . Further, there is a subject page for , Consumer Expectations, ., After each survey, Statistics Denmark submits detailed tables giving a number of background variables as well as the consumer confidence indicator and net figures to the European Commission, which publishes monthly both seasonally adjusted and not seasonally adjusted indicator and the net figures for each members state (incl. Denmark), at European Commission database: , European Commission database, The access to the more detailed data and Micro-data can be granted through Statistics Denmark's agreement for researchers., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/consumer-expectations-survey

Documentation of statistics

Documentation of statistics: Water and Waste Water

Contact info, National Accounts, Climate and Environment, Economic Statistics , Michael Berg Rasmussen , +45 51 46 23 15 , MBR@dst.dk , Get documentation of statistics as pdf, Water and Waste Water 2024 , Previous versions, Water and Waste Water 2023, Water and Waste Water 2022, Water and Waste Water 2021, Water and Waste Water 2020, Water and Waste Water 2019, Water and Waste Water 2018, Water and Waste Water 2016, Water and Waste Water 2014, The statistics concerning water and waste water estimates the abstraction and use of water as well as discharge of waste water distributed on municipalities., The water account document abstraction of water, use in households and industry groups (as used in the Danish National Accounts) as well as the discharge of waste water via waste water treatment plants to the aquatic environment. The water accounts are based on water and waste water statistics as well as micro-data from the Jupiter database managed by GEUS (Geological Survey of Denmark and Greenland) and reports on point sources from the Danish Environmental Protection Agency., The economic water account document the income in water supply and waste water treatment plants from households and industry groups. The account is based price information from water supply and waste water companies that are member of DANVA, information on individual companies, population, households as well as the physical water account., Statistical presentation, The water account consist of a physical and an economic part. The physical water account document abstraction of water, use well as the discharge of waste water to the aquatic environment in households and 117 industry groups as used in the other parts of the environmental economic account and in the ordinary Danish National Accounts. The economic water account document the income in water supply and waste water treatment plants from households and industry groups. The water accounts are prepared annually and published in Latest releases from Statistics Denmark and in StatBank Denmark., The water account is a module in the environmental economic accounts for Denmark. Read about the , environmental economic accounts, ., Read more about statistical presentation, Statistical processing, Statistics Denmark prepares water statistics based on data from GEUS on abstraction of water and waste water statistics based on data from the Danish Environmental Protection Agency. The distribution of abstraction of water, use of water and discharge of waste water between industrial groups as well as the cost are based on a number of additional sources., Read more about statistical processing, Relevance, Water accounts and statistics are of relevance for administrative bodies, researchers, NGOs, businesses, the educational sector and individuals - all with interests in water, pollution, resources, economic-environmental interactions, etc. To ensure international comparability, the waste accounts are prepared according to the UN statistical standard SEEA (System of Environmental-Economic Accounting) 2012., Read more about relevance, Accuracy and reliability, The coverage of data abstraction water is assessed to be high. However, for fish farming the information may be insufficient. Therefore missing values have been imputed., The coverage of data on waste water discharge is assessed to be high, as the information by law has to be included in development water management plans., The coverage of data on abstraction of water, flows and deliveries to end users is assumed to be high., The distribution on industrial groups - especially the 117 level - is subjected to some uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The statistics as well as physical and economic accounts have been published on time 11 months after the end of the reference period., Read more about timeliness and punctuality, Comparability, The methods and data sources for the Water Accounts are unchanged throughout the period covered by published figures (2010-). International comparison is possible with all other national water accounts based on UN's statistical standard SEEA 2012., Read more about comparability, Accessibility and clarity, The statistics are published in News from Statistics Denmark and in the Statbank. They will also be part of future publications from Statistics Denmark on Environmental-Economic Accounts (Green National Accounts)., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/water-and-waste-water

Documentation of statistics

Documentation of statistics: Personal assets and Liabilities

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

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

Documentation of statistics

Documentation of statistics: Implicit index of average earnings

Contact info, Labour Market, Social Statistics , Eva Borg , +45 24 78 53 57 , EVB@dst.dk , Get documentation of statistics as pdf, Implicit index of average earnings 2025 , Previous versions, Implicit index of average earnings 2024, Implicit index of average earnings 2023, Implicit index of average earnings 2021, Implicit index of average earnings 2020, These statistics show the development in average earnings, calculated on the basis of an arithmetic average of salaries of all employees within the same sector and economic industry. In relation to the publication of the new Standardised index of average earnings, these indices were renamed to Implicit index of average earnings. In the new index changes in the workforce is taken into account when calculating the development in earnings., The Implicit index of average earnings goes back to first quarter of 2005 for the private sector and first quarter of 2007 for the public sector., Statistics Denmark has decided to discontinue the implicit index of average earnings at the beginning of 2026 with the publication of the index for the fourth quarter of 2025. Instead, users are advised to use the standardised index of average earnings, which also illustrates the development in pay level for employees in Denmark. The discontinuation of the implicit index of average earnings will not have any impact on the standardised index of average earnings, which will be the only wage index from Statistics Denmark in the future. The historical series of the implicit index of average earnings will continue to be accessible in StatBank Denmark. In order for users to handle the transition to the standardised index of average earnings, a guide (in Danish) has been prepared on how to switch from the implicit to the standardised index of average earnings in practice. It is available on Statistics Denmark's information page on , indexation, ., Statistical presentation, The Implicit index of average earnings is a quarterly statistic of the development in wages for all employees in Denmark, including students and young persons under 18. The indices are available by sector and economic industries and follow the classifications Dansk Branchekode (DB07) and sector (SBR)., Read more about statistical presentation, Statistical processing, Data is collected from a sample of companies and organisations as well as the entire public sector, covering the middle month of the quarter., Data is validated by using fixed boundaries, both at individual and company level. Manual corrections are also made if required. Only companies that are present in both quarters are included in the calculations., In the calculation of the most detailed sub-indices, data for the private sector are weighted to the target population and the individual employment types are weighted with the hours worked., Read more about statistical processing, Relevance, The Implicit index of average earnings is a so-called unit value index, where wage trends are estimated on the basis of a simple salary average of all employees in the same industry. This means that wages partly reflect changes in staff composition in a given industry., Private enterprises as well as ministries etc are the central users. The index is used especially in connection with various contract regulations, as well as the regulatory scheme in the public wageagreements., The Implicit index of average earnings is the wage index that comes closest to being comparable to the European LCI., Read more about relevance, Accuracy and reliability, For the public sector the statistics are based on data for virtually all employees. For the private sector, there are two factors that can affect accuracy, namely uncertainty in the sample statistics and that there may be problems with the completeness of the reported data from the company., This index is an where the sum of wages and hours worked is counted in each group (etc. activity sector). Thus, changes in personnel in a given industry will have an impact on the measured wage development., The figures do not undergo revision; the published figures are usually final., Read more about accuracy and reliability, Timeliness and punctuality, The implicit index of average earnings are published approx. 60 days after the end of the reference quarter, at the same time as the standardised index of average earnings is published. These statistics are published without delay., Read more about timeliness and punctuality, Comparability, The implicit index of average earnings is comparable since first quarter 2005 but for some sectors, comparable wage indices also exist further back in time. The implicit index of average earnings is based on the same data as the standardised index of average earning, but there are significant differences in methodology that allow the two wage indices to be used only partially for comparison., Internationally, the implicit index of average earnings can be compared to the labor cost index collected and published by Eurostat for all EU countries., Read more about comparability, Accessibility and clarity, The implicit index of average earnings is published in Statistics Denmark’s newsletter on [https://www.dst.dk/da/statistik/nyheder-analyser-publ/nyt?psi=1931), together with the standardized index of average earnings. In Statbank Denmark, indices and annual increases are published under the , implicit index of average earnings , . More information can be found on the subject page on , Income and earnings, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/implicit-index-of-average-earnings

Documentation of statistics

Documentation of statistics: Bankruptcies

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

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

Documentation of statistics

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

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

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

Documentation of statistics