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    Documentation of statistics: Public sector employment (quarterly)

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

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

    Documentation of statistics

    Documentation of statistics: A-Income Statistics (income subject to provisional tax)

    Contact info, Labour Market, Social Statistics , Uwe Pedersen , +45 23 72 65 69 , UWP@dst.dk , Get documentation of statistics as pdf, A-Income Statistics (income subject to provisional tax) 2024 , Previous versions, A-Income Statistics (income subject to provisional tax) 2023, A-Income Statistics (income subject to provisional tax) 2022, A-Income Statistics (income subject to provisional tax) 2021, A-Income Statistics (income subject to provisional tax) 2020, A-Income Statistics (income subject to provisional tax) 2019, A-Income Statistics (income subject to provisional tax) 2018, A-Income Statistics (income subject to provisional tax) 2017, A-Income Statistics (income subject to provisional tax) 2016, A-Income Statistics (income subject to provisional tax) 2015, A-Income Statistics (income subject to provisional tax) 2015, A-Income Statistics (income subject to provisional tax) 2013, The purpose of the Provisional Income Statistics is to provide a more up to date picture of the compilation of income than is possible, by means of the final Personal Income Statistics. Compilation of the final Personal Income Statistics have to wait until the tax assessment process has reached a sufficiently acceptable level concerning the A-income (wages, salaries, unemployment benefits and social pensions etc.) and other income, e.g. entrepreneurial income. This does not apply to the Provisional Income Statistics., Statistical presentation, The a-income statistics mainly comprise of wages and transfers. It illustrates the level and composition of the a-income for the tax year and can be split into wages and various types of transfer incomes. The a-income amounts to 90 per cent of the total gross income. The statistics are based on the provisional tax statement for the income. The data is acquired four months after the end of the tax year. The final income statistics is based on a-incomes acquired eight month after the end of the tax year. The final statistics are based on the Statistics Denmark's Register of Incomes Statistics., Read more about statistical presentation, Statistical processing, The type of income in the e-income register is adjusted in-case of inconsistencies between the filing-entity and the type of income., The total transfers are grouped into the different type of transfers by merging the e-income register with the register of people receiving public benefits., Data on specifically 2020 and 2021 are supplemented with data from the Danish Business Authority on employer´s compensation on wages and salaries paid to staff, not able to work during the lockdown, caused by the COVID-19 pandemic., Read more about statistical processing, Relevance, One or two annual meeting with some of the main users of the income and wealth statistics is held in Statistics Denmark. On a daily to weekly basis users call with questions related to the statistics. Trough these interactions with the users we assess the need for improvements of the statistics., Read more about relevance, Accuracy and reliability, All persons receiving unemployment income is included in the statistics., As we are dealing with a provisional data based on relatively early data from the e-income Register the data are subject to certain margins of inaccuracy. The data may be revised by the Tax authorities after the date on which we extract the information from the Register. This applies in particular to the salary information slips containing wages and salaries. However, the uncertainty caused by the revisions linked to the income data is marginal., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published 4 to 5 months after the reference period. The statistics are published as planned., Read more about timeliness and punctuality, Comparability, Changing several social benefits from net sum into gross sum (taxable) in connection with the tax reform of 1st January 1994 has caused a minor break in the time series from 1993 to 1994. , There are no similar statistics internationally., Read more about comparability, Accessibility and clarity, The statistics are published on our , website, , in an annual , newsletter, and via the Statistikbanken)., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/a-income-statistics--income-subject-to-provisional-tax-

    Documentation of statistics

    Documentation of statistics: Employees (monthly)

    Contact info, Labour Market , Thomas Thorsen , +45 23 69 94 27 , TST@dst.dk , Get documentation of statistics as pdf, Employees (monthly) 2024 Month 07 , Previous versions, Employees (monthly) 2024 Month 06, Employees (monthly) 2024 Month 05, Employees (monthly) 2024 Month 04, Employees (monthly) 2024 Month 03, Employees (monthly) 2024 Month 02, Employees (monthly) 2024 Month 01, Employees (monthly) 2023 Month 12, Employees (monthly) 2023 Month 11, Employees (monthly) 2023 Month 10, Employees (monthly) 2023 Month 09, Employees (monthly) 2023 Month 08, Employees (monthly) 2023 Month 07, Employees (monthly) 2023 Month 06, Employees (monthly) 2023 Month 05, Employees (monthly) 2023 Month 04, Employees (monthly) 2023 Month 03, Employees (monthly) 2023 Month 02, Employees (monthly) 2023 Month 01, Employees (monthly) 2022 Month 11, Employees (monthly) 2022 Month 10, Employees (monthly) 2022 Month 09, Employees (monthly) 2022 Month 08, Employees (monthly) 2022 Month 07, Employees (monthly) 2022 Month 06, Employees (monthly) 2022 Month 05, Employees (monthly) 2022 Month 04, Employees (monthly) 2022 Month 03, Employees (monthly) 2022 Month 02, Employees (monthly) 2022 Month 01, Employees (monthly) 2021 Month 12, Employees (monthly) 2021 Month 11, Employees (monthly) 2021 Month 10, Employees (monthly) 2021 Month 09, Employees (monthly) 2021 Month 08, Employees (monthly) 2021 Month 07, Employees (monthly) 2021 Month 06, Employees (monthly) 2021 Month 05, Employees (monthly) 2021 Month 04, Employees (monthly) 2021 Month 03, Employees (monthly) 2021 Month 02, Employees (monthly) 2021 Month 01, Employees (monthly) 2020 Month 12, Employees (monthly) 2020 Month 11, Employees (monthly) 2020 Month 10, Employees (monthly) 2020 Month 09, Employees (monthly) 2020 Month 08, Employees (monthly) 2020 Month 07, Employees (monthly) 2020 Month 06, Employees (monthly) 2020 Month 05, Employees (monthly) 2020 Month 04, Employees 2018 Month 08, Employees 2018 Month 07, Employees 2018 Month 06, Employees 2018 Month 04, Employees 2018 Month 03, The purpose of these statistics is to clarify the short-term development in the employment of employees in Danish enterprises. The statistics contains employment data from the beginning of 2008. , Statistical presentation, The employment statistics for employees is published on a quarterly and monthly basis. The statistics shows the development in the number of people with employee job. On a quarterly basis the number of full-time employees is also published. The statistics is distributed by sector and industries both in the monthly statistics and in the quarterly statistics. Furthermore, workplace geography, residence geography, age, sex and ancestry is also illustrated on a quarterly basis., Read more about statistical presentation, Statistical processing, Data are debugged, adjusted and quality guaranteed in relation to breakdowns on industry, sector and geography. Data for both the number of full-time employees and number of people with employee job is seasonally adjusted, broken down by both industry, sector and geography on residence., Read more about statistical processing, Relevance, Users interested in the social and economic statistics have expressed satisfaction with the quality of the statistics., Read more about relevance, Accuracy and reliability, The uncertainty in the development of the number of employees is estimated to be less than 1 per cent of the total number of full-time employees, where 1 per cent corresponds to approx. 20,000 full-time employees. As regards more detailed statistics in terms of industry and geographical distribution the uncertainty is much greater. For the monthly statements there has not yet been a systematic quality studies of statistics. Compared to the quarterly statements of full-time employees, there are two factors pulling in opposite directions: on the one hand, the monthly statements are published earlier, leading to increased uncertainty, because fewer reports has been reported at that time. On the other hand, jobs are imputed for periods where the employees for up to 45 days have not received wages, but subsequently returned to the same employer in the calculation of persons with employee jobs, which helps to reduce uncertainty., Read more about accuracy and reliability, Timeliness and punctuality, The preliminary figures of the monthly statistics are published approx. 52 days after the end of the reference month. These statements are revised every month until final estimates are released in the quarterly statistics., The preliminary employment statistics for employees are published approx. 52 days after the end of the quarter. The revised statement will be published within 3 months after the reference quarter and the final statement 3 months later together with the new preliminary data for the following quarter. There is usually no delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, There are no changes in methodology since these statistics where first introduced. Data are comparable during the whole period., Read more about comparability, Accessibility and clarity, These statistics 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 the subject , Employees, . For further information, go to the , subject page, . , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/employees--monthly-

    Documentation of statistics

    Documentation of statistics: Standardised 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, Standardised index of average earnings 2025 , Previous versions, Standardised index of average earnings 2024, Standardised index of average earnings 2023, Standardized Index of Average Earnings 2021, Standardized Index of Average Earnings 2020, Standardized Index of Average Earnings 2019, Standardized Index of Average Earnings 2018, Documents associated with the documentation, Standardberegnet lønindeks. Metode efter serviceeftersyn 2022-2023 (pdf) (in Danish only), The purpose of the standardised index of average earnings is to estimate the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the labour market’s occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics are used for e.g. monitoring of business cycles, regulation of contracts, analyses of developments in pay levels as well as input in the calculation of the National Accounts., The statistics have been prepared since 2018 with data back to the first quarter of 2016. A revised index and time series are published in May 2023 with data back from 2016., In parallel, Statistics Denmark is calculating the implicit index of average earnings. Unlike the standardised index, the implicit index of average earnings does not take changes in the occupational composition into account., Statistical presentation, The standardised index of average earnings is a quarterly estimate of the developments in pay levels for employees in Denmark, adjusted to the extent possible for changes in the occupational composition, e.g. shifts of employees between industries and/or occupation. The statistics show the development in the average hourly earnings for employees by sector, industry (DB07) and main occupation (DISCO-08). Each quarter, an index value and an annual increase are published., Read more about statistical presentation, Statistical processing, Data for these statistics are collected quarterly. For the public sector all payroll information are collected while data are collected via a sample from the private sector. The collected data is validated at an aggregate level for key enterprises (only in the private sector) and at an individual level through a combination of validation rules for the hourly earnings for the individual employment relationship. The hourly earnings are assessed based on sector, industry, main occupation and type of employment. Once data has been validated, base index is calculated for each homogeneous group, which afterwards is aggregated to sub- and total indices at sector, industry or main occupation level., Read more about statistical processing, Relevance, These statistics are relevant for private enterprises and organisations, as well as ministries and other public institutions for analysis, contractual regulation etc. The statistical data are also used in other areas within Statistics Denmark, e.g the calculation of the Danish National Accounts., Read more about relevance, Accuracy and reliability, The accuracy of these statistics are higher for employees in the public sector than in the private sector. The reason for this is that the statistics for employees in the public sector (more or less) consists of all payroll information, while the statistics for employees in the public sector is based on a sample of enterprises. The accuracy of the statistics for the private sector is therefore affected by sampling uncertainty, completeness of the reported information and non-response. The impact on the indices are unknown., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published two months after the end of the reference period. The statistics are released typically without delay according to scheduled dates of publication. , In February 2022, the statistics were paused and a comprehensive service review was initiated. As a result, the method for calculating standardized index of average earnings was revised. This publication therefore contains revised index values and annual increases for the entire period from the first quarter of 2016 until the first quarter of 2023. This means that the series contains revised values from the first quarter of 2016 until the third quarter of 2021 as well as previously unpublished values from the fourth quarter of 2021 until the first quarter of 2023., Read more about timeliness and punctuality, Comparability, The standardised index of average earnings was first published in December 2018 with a time series starting in the first quarter of 2016. The standardised index of average earnings utilize the same data as the implicit index of average earnings, which however has a different purpose and is therefore calculated using a different method. There exist a few sets of statistics abroad that are partly comparable with the standardised index of average earnings. , Read more about comparability, Accessibility and clarity, These statistics are published quarterly 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 the subject , Indices of average earnings, . For further information, visit the subject page for , Income and earnings, . , Read more about accessibility and clarity

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

    Documentation of statistics

    Documentation of statistics: Absence from work

    Contact info, Labour Market, Social Statistics , Nete Nielsen , +45 40 10 48 87 , NDN@dst.dk , Get documentation of statistics as pdf, Absence from work 2024 , Previous versions, Absence from work 2023, Absence from work 2022, Absence from work 2021, Absence from work 2020, Absence 2019, Absence 2018, Absence 2017, Absence 2016, Absence 2015, Absence 2014, Absence 2013, Absence 2012, The purpose of the statistics of absence is to describe the amount of work that is lost due to absence. Absence is divided into "Own sickness", "Children's sickness", "Occupational injury" and "Maternity and adoption leave". The statistics are published on a yearly basis and are used for estimating and comparing the level of absence within different groups of employees., Statistical presentation, The statistics of absence are published yearly for the governmental sector, the local governmental sector and the private sector. Statistics according to the new sector definition from 2013 are also published for the labour market as a whole. The absence is grouped by the variables occupation, education, industry, region, age and sex. From 2013 own sickness is published by lengths of period. In the governmental and municipal sector all employees are included while the private sector is described by a representative sample of enterprises with 10 or more employees., Read more about statistical presentation, Statistical processing, On a yearly bases information on absence is collected from all of the public sector and from a sample 2600 private enterprises with 10 or more employees. After validating the absence data the periods of absence are connected to the job from which the person was absent. The information about the extent of the employment is found in the earnings statistics. The information on absence from the private sector is enumerated to the total population of enterprises with 10 employees or more., Read more about statistical processing, Relevance, Absence has both personal and economic consequences that have an impact on both employees, employers and the community. The statistics are tools used in estimating and comparing the level of absence within different groups of employees, and can be a foundation on which economic and political decisions are made. The statistics are of interest for the central government, municipalities and regions, private business enterprises, non-governmental organizations, researchers and news media. , Read more about relevance, Accuracy and reliability, The governmental and local government sector in principle include all employed persons. For these sectors there is immeasurable inaccuracy mainly caused by measuring errors., The private sector is based on a representative sample of about 2600 enterprises. The inaccuracy can be divided into sampling inaccuracy and the immeasurable inaccuracy that derives from measuring errors. The total absence rate for own sickness is determined with a 95 percent confidence interval to vary around +/- 0.05 percent. Sampling errors for divisions on e.g. gender or industry are considerably higher., Read more about accuracy and reliability, Timeliness and punctuality, The statistics of absence refers to the whole year to which the absence periods belongs The statistics is published on a yearly basis at the end of October following the reference period. The information is published without delay compared to schedule., Read more about timeliness and punctuality, Comparability, The statistics of absence for the central governmental sector covers the year 2003 and forward, while the first data for the local governmental sector was published for the year 2005. The statistics for the private sector covers the period from 2007 and forward. From 2010 the municipality sector and the regional sector are published separately. Before 2010 the two sectors were only published together., The method and quality of data have continuously been improved especially the first years of the statistics. Comparisons between sectors and years (especially the earliest published data) should only be made with reservations., Read more about comparability, Accessibility and clarity, The latest results are published once a year in a Danish press release, at the same time as tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Absence from work, . It is possible to buy more detailed results and to get access to micro-data through Statistics Denmark's Research services., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/absence-from-work

    Documentation of statistics

    Documentation of statistics: Parental leave benefits

    Contact info, Labour Market, Social Statistics , Anna Skovbæk Mortensen , +45 21 77 67 54 , AOM@dst.dk , Get documentation of statistics as pdf, Parental leave benefits 2024 , Previous versions, Parental leave benefits 2023, Parental leave benefits 2022, Parental leave benefits 2021, Parental leave benefits 2020, Benefits in connection with childbirth 2019, Documents associated with the documentation, Genudgivelse af barselsdagpengedata for fødselsårgange 2017-2023 (pdf) (in Danish only), The statistics Parental leave benefits in connection with childbirth shed light on the use of the Maternity Act, including equality between mothers and fathers. The statistics have been compiled since 1995, but in 2017 changed data source. Since 2017, data from ATP / Udbetaling Danmark's IT system for the administration of payment of parental benefits in connection with birth, adoption, child illness etc., Statistical presentation, Childbirth allowance annually calculate a parent's year's use of the rights the Maternity Act gives them, and the distribution of parental leave between the father and mother, as well as the number of persons, and days on benefits. Furthermore, the statistics provide the data basis for calculating amounts paid out in connection with childbirth. , Read more about statistical presentation, Statistical processing, The data basis of the statistics is based on a total extraction from 13 central tables in the database for ATP/Udbetaling Danmark's administrative IT system, UDK-Barsel, and a delta extraction from a 14th table, which is very large. Selected variables from the 14 tables are merged into a single table that constitutes a longitudinal register, the Barselsdagpenge Register, with a well-defined record structure. The Barselsstatistik Register is formed by combining the Barselsdagpenge Register with an extract from the Population Register and other Danish Statistics registers., Read more about statistical processing, Relevance, The maternity and paternity leave part of the statistic is used by ministries for reasons of gender equality policy and of the unions and the employers' organizations in connection with collective bargaining agreements. The statistics are included as an important data element concerning analyzes of the productivity of the Danish workforce (economic model calculations), the labor market accounts, the statistics statistics on Public dependents and the absence statistics, Read more about relevance, Accuracy and reliability, The statistics summarize the reports of birth or adoption that have triggered the payment of due to maternity leave. The expectation is that all cases are reported. However, there are a number of cases that will only be reported long after the end of the year to which the case relates, why the last year is not fully updated. In order to get a picture of a parent's year's use of the maternity law, it has been necessary to link several registers and set up an algorithm for calculating the parents' entitlement. There is a risk of programming errors here, just as the algorithm rules are a choice., Read more about accuracy and reliability, Timeliness and punctuality, These statistics are published annually three months after the reference year in March-April. March-April is chosen as the compromise of current interest and waiting for the last reports of the year to appear. At publishing time the newest data will be less than three months old. , Read more about timeliness and punctuality, Comparability, The statistics are influenced by local Danish legislation, which makes comparison with similar statistics from other countries difficult. In addition, maternity leave can be calculated in 18 different ways, which is why it requires a good knowledge of the documentation for countries' calculation methods before comparing their figures. At the moment, the statistics cover data for the years 2015-2023, where no data breach has been detected, with the exception that the 1st quarter of 2015 is under-updated, which gives a minor data breach for total counts., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release, at the same time as tables are updated in the StatBank. In the StatBank, these statistics can be found under the subject , Parental leave benefits, . For further information, go to the , subject page, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/parental-leave-benefits

    Documentation of statistics

    Documentation of statistics: Reported criminal offences

    Contact info, Population and Education, Social Statistics , Iben Birgitte Pedersen , +45 23 60 37 11 , IPE@dst.dk , Get documentation of statistics as pdf, Reported criminal offences 2025 , Previous versions, Reported criminal offences 2024, Reported criminal offences 2023, Reported criminal offences 2022, Reported Criminal Offences 2021, Reported Criminal Offences 2020, Reported Criminal Offences 2019, Reported Criminal Offences 2018, Reported Criminal Offences, Year 2017, Reported Criminal Offences, Year 2016, Reported Criminal Offences 2015, Reported Criminal Offences, Year 2014, Reported Criminal Offences, Year 2013, Documents associated with the documentation, Rape: Reported criminal offences 2024 (docx), Kriminalitetsstatistikkens grundbegreber og kilder (pdf) (in Danish only), The statistics analyze the number of criminal offences in violation of the criminal code and the special laws (except those contained in the Danish Road Traffic Act) to the police. The statistics on reported criminal offences date back to 1921. Until 1990, Statistics Denmark received monthly copies of the offence reports from the police for registration. Since 1 January 1990, Statistics Denmark has received data both quarterly and annually from the Central Register of Reported Offences, a register administered by the National Commissioner of the Danish Police., Statistical presentation, The statistics show the number of offences of criminal code and special laws/legislation reported to the police or discovered by the police itself., The statistics on reported criminal offences form part of the Danish System of Criminal Statistics. The System of Criminal Statistics includes data on criminal cases from the reported offences and charges to the convictions plus arrests and imprisonments., Read more about statistical presentation, Statistical processing, The source of the statistics is The Central Register of Reported Criminal Offences - administered by the National Commissioner of the Danish Police. Data are delivered yearly via System-to-system transmission., The data go through a probability check in form of a comparison with data from the previous year, key variables are checked for valid values and irrelevant offences are deleted., Read more about statistical processing, Relevance, The statistics are used broadly by the authorities, organizations, researchers, the press etc. The tables in the statbank.dk are used frequently. Views and suggestions from key users are taken into consideration in the preparation of the statistics., Read more about relevance, Accuracy and reliability, The accuracy of the statistics on reported criminal offences is considered to be good. The data come from a single administrative register system storing information on all reported crimes. Analyses have shown that approximately 5 percentages of the crimes registered in a calendar year, are committed in an earlier year. Corresponding approximately 5 percentages of all crimes reported committed in a calendar year are not registered until a following year. The statistics do not include information on the hidden criminality, i.e. committed criminal offences not reported to the police., Read more about accuracy and reliability, Timeliness and punctuality, The publishing time for the statistics is about 2 months. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The statistics have been prepared on the same basis since 1990. Due to changes in the grouping of the criminal offences and changes in the 'clear-up-concept' caution should be shown by comparing figures over time before this year., Eurostat collects annual data from the member states on reported criminal offences and publishes statistics based on this. However, according to the Eurostat metadata, the range of items included in the different groups of crime differs between countries and comparisons based upon absolute figures are therefore misleading., Read more about comparability, Accessibility and clarity, These statistics are published yearly in a Danish press release. In the StatBank, these statistics can be found under , Reported criminal offences, . For further information, go to the , subject page, . , Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/reported-criminal-offences

    Documentation of statistics

    Documentation of statistics: Reported Criminal Offences (Quarterly)

    Contact info, Population and Education, Social Statistics , Iben Birgitte Pedersen , +45 23 60 37 11 , ipe@dst.dk , Get documentation of statistics as pdf, Reported Criminal Offences (Quarterly) 2025 Quarter 4 , Previous versions, Reported Criminal Offences (Quarterly) 2025 Quarter 3, Reported Criminal Offences (Quarterly) 2025 Quarter 2, Reported Criminal Offences (Quarterly) 2025 Quarter 1, Reported Criminal Offences (Quarterly) 2024 Quarter 4, Reported Criminal Offences (Quarterly) 2024 Quarter 3, Reported Criminal Offences (Quarterly) 2024 Quarter 2, Reported Criminal Offences (Quarterly) 2024 Quarter 1, Reported Criminal Offences (Quarterly) 2023 Quarter 4, Reported Criminal Offences (Quarterly) 2023 Quarter 3, Reported Criminal Offences (Quarterly) 2023 Quarter 2, Reported Criminal Offences (Quarterly) 2023 Quarter 1, Reported Criminal Offences (Quarterly) 2022 Quarter 4, Reported Criminal Offences (Quarterly) 2022 Quarter 3, Reported Criminal Offences (Quarterly) 2022 Quarter 2, Reported Criminal Offences (Quarterly) 2022 Quarter 1, Reported Criminal Offences (Quarterly) 2021 Quarter 4, Reported Criminal Offences (Quarterly) 2021 Quarter 3, Reported Criminal Offences (Quarterly) 2021 Quarter 2, Reported Criminal Offences (Quarterly) 2021 Quarter 1, Reported Criminal Offences (Quarterly) 2020 Quarter 4, Reported Criminal Offences (Quarterly) 2020 Quarter 3, Reported Criminal Offences (Quarterly) 2020 Quarter 2, Reported Criminal Offences (Quarterly) 2020 Quarter 1, Reported Criminal Offences (Quarterly) 2019 Quarter 4, Reported Criminal Offences (Quarterly) 2019 Quarter 3, Reported Criminal Offences (Quarterly) 2019 Quarter 2, Reported Criminal Offences (Quarterly) 2019 Quarter 1, Reported Criminal Offences (Quarterly) 2018 Quarter 4, Reported Criminal Offences (Quarterly) 2018 Quarter 3, Reported Criminal Offences (Quarterly) 2018 Quarter 2, Reported Criminal Offences (Quarterly) 2018 Quarter 1, Reported Criminal Offences (Quarterly) 2017 Quarter 4, Reported Criminal Offences (Quarterly) 2017 Quarter 3, Reported Criminal Offences (Quarterly) 2017 Quarter 2, Reported Criminal Offences (Quarterly) 2017 Quarter 1, Reported Criminal Offences (Quarterly) 2016 Quarter 4, Reported Criminal Offences, Quarter 2016 Quarter 3, Reported Criminal Offences, Quarter 2016 Quarter 2, Reported Criminal Offences, Quarter 2016 Quarter 1, Reported Criminal Offences, Quarter 2015 Quarter 4, Reported Criminal Offences, Quarter 2015 Quarter 3, Reported Criminal Offences, Quarter 2015 Quarter 2, Reported Criminal Offences, Quarter 2015 Quarter 1, Documents associated with the documentation, Rape: Reported criminal offences 2025Q4 (docx), The purpose of the statistics is to show the number of criminal offenses in violation of the penal code and the special laws (except those contained in the Danish Road Traffic Act) to the police. The statistics on reported criminal offences date back to 1921, but are in its present form comparable from 1995 onwards., Statistical presentation, The statistics are a quarterly statement of the number of offences of penal code and special laws/legislation reported to the police or discovered by the police itself. The reported criminal offences can be broken down by type of offenses and geographical on regions and municipalities., Read more about statistical presentation, Statistical processing, The source of the statistics is The Central Register of Reported Criminal Offences - administered by the National Commissioner of the Danish Police. Data are delivered quarterly via system-to-system transmission., The data go through a probability check in form of a comparison with data from the previous year, key variables are checked for valid values and irrelevant offences are deleted., Read more about statistical processing, Relevance, The statistics are used broadly by the authorities, organizations, researchers, the press etc. as a basis for public and private planning, training, research and public debate. Views and suggestions from key users are taken into consideration in the preparation of the statistics., Read more about relevance, Accuracy and reliability, The statistics are made based on the data recorded at the time the extract is made. There is also produced an annual statistics for this area which is more complete. Comparisons between the quarterly statistics and the annual statistics reveal that the quarterly statistics under-estimate the number of reported criminal offences with approximately 6 percentages. There is, from quarter to quarter, a shift in the data; part of the registered reported crimes in a given quarter may refer to a previous quarter., The statistics do not include information on the hidden criminality, i.e. committed criminal offences not reported to the police., Read more about accuracy and reliability, Timeliness and punctuality, The publishing time for the statistics is about 20 days. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The statistics have been prepared on the same basis since 1995. Due to changes in the grouping of the criminal offences caution should be shown by comparing figures over time before this year., Read more about comparability, Accessibility and clarity, The statistics are publiced in the StatBank under the subject , Reported criminal offences, . For further information, go to the , subject page, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/reported-criminal-offences--quarterly-

    Documentation of statistics

    Documentation of statistics: Household Budget Survey

    Contact info, Prices and Consumption, Economic Statistics , A Solange Lohmann Rasmussen , +45 61 15 17 93 , slr@dst.dk , Get documentation of statistics as pdf, Household Budget Survey 2023 , Previous versions, Household Budget Survey 2022, Household Budget Survey 2021, Household Budget Survey 2020, Household Budget Survey 2019, Household Budget Survey 2018, Household Budget Survey 2017, Household Budget Survey 2016, Household Budget Survey 2015, Household Budget Survey 2014, Household Budget Survey 2013, The Household Budget Survey describes in detail the Danish households' expenditure on goods and services and the economic condition of the households. The statistics are used to compile weightings in the Consumer Price Index and for calculation of the private consumption in the National Accounts. The statistics were first compiled in 1897 and annually since 1994., Statistical presentation, The Household budget survey is an annual statement of the detailed private consumption at household level for private households in Denmark. The survey covers private households in Denmark. The household budget survey provides a detailed breakdown of consumption. In the most detailed breakdown, consumption is divided into approx. 1,200 different consumption types., Read more about statistical presentation, Statistical processing, The survey is based on a sample where the number of households accounts for about 2,200 out of Denmark's total of approximately 2.8 million households. , The survey included data from three different data sources: Accounting booklets, CAPI interviews and data from registers. In this way the sample can give results which are good approximations for all private households. The data from the 3 different sources are validated. We are constantly looking at how we can improve and compile the statistic in a more efficient way., Data is collected annually from approximately 1,100 households and the sample for one years household budget survey is based on the sample from two years. All expenses, income, etc. are converted to the price and volume level of the end year., Read more about statistical processing, Relevance, In addition to the general public the Household Budget Survey has a wide application. Internally in Statistics Denmark during the compilation of national accounts and price indexation. Public authorities' planning and feasibility studies, etc. Internationally, where especially EUROSTAT is very active in order to establish comparable figures between countries. Research in a number of areas, as well as for marketing purposes., Read more about relevance, Accuracy and reliability, With only 12 pct. of the households who have been contacted participating in the Household Budget Survey. This creates uncertainty, not least for detailed consumer groups. For total consumption, this means that there is an uncertainty margin of +/- 1.8 per cent. while that for that for bread is 2 per cent. and 24 per cent. for a rarely purchased item such as offal. There is underreporting in a number of areas such as alcohol, tobacco, prostitution and undeclared work. The uncertainty is greater when data is based on accounting rather than interviews, and it will be greater if one looks at smaller subgroups of households., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published approximately12 months after the end of the reference year. The statistics are usually published according to the time announced. , Read more about timeliness and punctuality, Comparability, The Household Budget Survey is carried out in accordance with guidelines from the European Statistical Office, Eurostat. Comparable figures are published by Eurostat. Since 1994, the survey has been methodologically redesigned, so it is now conducted annually using the same method and on a comparable basis., Data for the period 2014 to 2022 were based on a two-year sample and the ECOICOP nomenclature. To ensure comparability over time, data for 1994 to 2013 were recalculated according to this nomenclature in both current and constant prices., From 2023, COICOP2018 has been implemented in the Household Budget Survey as the survey has become subject to a regulation. Therefore, data for 2015–2022 have been recalculated in current and constant prices according to COICOP2018 to ensure continuity., Read more about comparability, Accessibility and clarity, The Danish Household Budget Survey is published 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 , Household Budget Survey, . For further information, go to the , subject page, ., Read more about accessibility and clarity

    https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/household-budget-survey

    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