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Documentation of statistics: Manufacturers’ Sales of Goods (quarterly)

Contact info, Short Term Statistics, Business Statistics , Morten Skovrider Kollerup , +45 24 52 61 68 , MSL@dst.dk , Get documentation of statistics as pdf, Manufacturers Sales of Goods (quarterly) 2024 Quarter 4 , Previous versions, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2024 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2023 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2022 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2021 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 3, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 2, Manufacturers’ Sales of Goods (quarterly) 2020 Quarter 1, Manufacturers’ Sales of Goods (quarterly) 2019 Quarter 4, Manufacturers’ Sales of Goods (quarterly) 2019 Quarter 3, Manufacturers’ Sales of Goods 2019 Quarter 2, Manufacturers’ Sales of Goods 2019 Quarter 1, Manufacturers’ Sales of Goods 2018 Quarter 4, Manufacturers’ Sales of Goods 2018 Quarter 3, Manufacturers’ Sales of Goods 2018 Quarter 2, Manufacturers’ Sales of Goods 2018 Quarter 1, Manufacturers’ Sales of Goods 2017 Quarter 4, Manufacturers’ Sales of Goods 2017 Quarter 3, Manufacturers’ Sales of Goods 2017 Quarter 2, Manufacturers’ Sales of Goods 2017 Quarter 1, Manufacturers’ Sales of Goods 2016 Quarter 4, Manufacturers’ Sales of Goods 2016 Quarter 3, Manufacturers’ Sales of Goods 2016 Quarter 2, Manufacturers’ Sales of Goods 2016 Quarter 1, Manufacturers’ Sales of Goods 2015 Quarter 4, Manufacturers’ Sales of Goods 2015 Quarter 3, Manufacturers’ Sales of Goods 2015 Quarter 2, Manufacturers’ Sales of Goods 2015 Quarter 1, Manufacturers’ Sales of Goods 2014 Quarter 4, Manufacturers’ Sales of Goods 2014 Quarter 1, The purpose of the statistics is to describe the Danish industrial production by detailed type of goods. Manufacturers' sales of goods is the source for Danish Prodcom statistics, regulated by and submitted to Eurostat., Statistical presentation, The statistics describe manufacturers' sales of goods measured in terms of volume and value by detailed types of goods according to the international classifications CN and SITC. In addition to this, total sales (turnover) are distributed by industries (NACE groups)., The data collecting for the statistics for 2020 has partly been affected by the COVID-19 situation. However, it is assessed that the overall statistics has not been affected in any great extent., Since 2020, Statistics Denmark has carried out extensive work to ensure the quality of the reports from the largest companies. This has led to some audits for the years 2018 to 2022., Read more about statistical presentation, Statistical processing, Data are collected through a quarterly survey of all enterprises in manufacturing (including mining and quarrying) with at least 10 employees or a yearly turnover over 100 mio. dkk, approx. 3,000 units. Reported data are validated, by checking against previous reports as well as against other sources. Data are then aggregated by industrial groupings as well as commodity groups. Series with seasonality are seasonally adjusted., Read more about statistical processing, Relevance, The statistics are in high demand from many different users, including the National Accounts, ministries, trade associations, market analysts, researchers, consultants and businesses., Read more about relevance, Accuracy and reliability, The main non-sampling error is the measurement error concerning classification at the most detailed CN level, as respondents do not always report sales according to the correct codes. Furthermore, data on quantities are generally less reliable than those on values, as some respondents estimate quantities and others do not answer, implying that estimations must be made in the statistical production process., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published two months after the end of the reference quarter. Publications are released on time, as stated in the release calendar., Read more about timeliness and punctuality, Comparability, In its present form and as available in StatBank Denmark, the statistics are comparable since 1995, but the statistics have been produced in some form since 1905. The Prodcom-version of the statistics can be compared to Prodcom statistics of other EU countries. The statistics can be compared to Foreign Trade in Goods to create statistics on apparent consumption - for this, it is important to note the difference in coverage and the potential quality issues at the most detailed CN code level. The tables with sales by industry are consistent from 2000 following the DB07 classification. , Read more about comparability, Accessibility and clarity, These statistics are published annually at the beginning of March in a Danish press release. Quarterly figures are published in the StatBank under , Purchases and sales by manufacturing industries, . Internationally, these statistics are available through Eurostat's , database, and at the UN, where the statistics are disseminated under , Industrial Commodity Statistics, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/manufacturers--sales-of-goods--quarterly-

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: 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

Documentation of statistics: Harmonized Index of Consumer Prices (HICP)

Contact info, Prices and Consumption, Economic Statistics , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Harmonized Index of Consumer Prices (HICP) 2026 , Previous versions, Harmonized Index of Consumer Prices (HICP) 2025, Harmonized Index of Consumer Prices (HICP) 2024, Harmonized Index of Consumer Prices (HICP) 2023, Harmonized Index of Consumer Prices (HICP) 2022, Harmonized Index of Consumer Prices (HICP) 2021, Harmonized Index of Consumer Prices (HICP) 2020, Harmonized Index of Consumer Prices (HICP) 2019, Harmonized Index of Consumer Prices (HICP) 2018, Harmonized Index of Consumer Prices (HICP) 2017, Harmonized Index of Consumer Prices (HICP) 2016, Harmonized Index of Consumer Prices (HICP) 2015, Harmonized Index of Consumer Prices (HICP) 2014, Documents associated with the documentation, Notat-om-forbruger-og-nettoprisindekset-i-forbindelse-med-corona-krisen (pdf) (in Danish only), ECOICOP (pdf), Vægtgrundlag 1991 til i dag (xlsx) (in Danish only), The harmonized index of consumer prices (HICP) is compiled by all EU Member States and Norway, Iceland and Switzerland. The purpose of the harmonized consumer price indices is to be able to estimate the development in the countries' consumer prices on a comparable basis. HICP is used both by the Commission and by the European Central Bank in connection with the valuation of the price development in the individual countries in connection with the implementation and monitoring of the 3rd phase of the EMU. All the EU Member States and Norway and Iceland have compiled HICP since January 1997., Statistical presentation, HICP shows the development of prices for goods and services bought by private households in Denmark. Thus, the index also covers foreign households' consumption expenditure in Denmark, but not Danish households' consumption expenditure abroad. The index shows the monthly changes in the costs of buying a fixed basket of goods, the composition of which is made up in accordance with the households' consumption of goods and services., The price indices for April, May, June, July, August, September, October, November, December 2020 and January, February, March, April, May and June 2021 are more uncertain than usual, as the non-response rate has been significantly larger than normal and some businesses have been shut down due to COVID-19., Read more about statistical presentation, Statistical processing, The HICP is calculated on the basis of 23,000 prices collected from approx. 1,600 shops, companies and institutions throughout Denmark. Most prices are by far collected monthly. The data material received is examined for errors, both by computer (using the so called HB-method) and manually. The different goods and services, which are included in the HICP, are first grouped according to approx. 500 elementary aggregates for which elementary aggregate indices are calculated. The elementary aggregate indices are mainly calculated as geometric indices. The elementary aggregate indices are weighted together into sub-indices that are in turn aggregated into the total HICP., Read more about statistical processing, Relevance, The HICP is generally viewed as a reliable statistic based on the views of users., Important users are among others The European Central Bank, The European Commission, The Ministry of Finance, The Ministry of Economic Affairs and the Interior, The Danish Central Bank as well as private banks and other financial organizations., Read more about relevance, Accuracy and reliability, No calculation has been made of the uncertainty connected with sampling in the HICP as the sample is not randomly drawn, but the quality of the HICP is accessed to be high. In connection with COVID-19, uncertainty is greater than usual as it has been difficult to collect prices and many industries have been closed down., In addition to the "general" uncertainty connected with sampling, there are a number of sources of potential bias in the consumer price index. One source is the consumers substitution between goods and shops and another source is changes in the sample., Read more about accuracy and reliability, Timeliness and punctuality, The HICP is published on the 10th or the first working day thereafter, following the month in which the data was collected. , The statistics are published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, The Danish HICP can be compared directly with other countries' HICPs. Using the HICPs it is possible to compare the inflation rates between different countries directly., The Danish HICP is also related to the national consumer price index., From January 2001, the only difference between the national consumer price index and the HICP is the coverage of goods and services, as owner-occupied dwellings is only recorded in the consumer price index and not in the HICP. , From January till December 2000, the only difference between the national consumer price index and the HICP is that both owner-occupied dwellings and private hospitals are only recorded in the consumer price index and not in the HICP. , Before January 2000, there are differences in calculation and methodology between the two indices as well as several differences as regards their coverage of goods and services., Read more about comparability, Accessibility and clarity, These statistics are published monthly in a Danish press release and in the StatBank under , Harmonized index of consumer prices (HICP), . The HICP of all Member States is also published by Eurostat in , Statistics in Focus/Economy and Finance, and on , Eurostat, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/harmonized-index-of-consumer-prices--hicp-

Documentation of statistics

Documentation of statistics: Producer and Import Price Index for Commodities

Contact info, Prices and Consumption, Economic Statistics , Nicklas Milton Elversøe , +45 61 15 35 98 , nel@dst.dk , Get documentation of statistics as pdf, Producer and Import Price Index for Commodities 2026 , Previous versions, Producer and Import Price Index for Commodities 2026, Producer and Import Price Index for Commodities 2025, Producer and Import Price Index for Commodities 2024, Producer and Import Price Index for Commodities 2023, Producer and Import Price Index for Commodities 2022, Producer and Import Price Index for Commodities 2021, Producer and Import Price Index for Commodities 2020, Producer and Import Price Index for Commodities 2019, Producer and Import Price Index for Commodities 2018, Producer and Import Price Index for Commodities 2017, Producer and Import Price Index for Commodities 2016, Producer and Import Price Index for Commodities 2015, Producer and Import Price Index for Commodities 2014, The statistics Producer and Import Price Index for Commodities show the price development of commodities in the first stage of transaction. The primary use is as deflators (converting nominal values to real values), but is also used as a business cycle indicator and for contract adjustments in the business sector. The index can be divided into Producer price index for commodities, Import price index for commodities and Price index for domestic commodities supply. The Price index for domestic supply of commodities can be traced back to 1876 and in the current form back to 1981. Producer Price Index for Commodities dates back to 2000 and Import Price Index for Commodities to 2005., Statistical presentation, The Producer and Import Price Index for Commodities contains monthly indices of the price development of commodities in the first stage of turnover (business-to-business), i.e. typically sales from producer to wholesaler or retailer, for commodities produced by Denmark for the domestic market and export, or for commodities imported into Denmark. The statistics are divided by product and industry groups., Read more about statistical presentation, Statistical processing, Approximately 7,400 prices from selected producers and importers in Denmark. Of these, approximately 3,800price reports for calculation of Producer Price Index for Commodities, approximately 3,600 for calculation of Import Price Index for Commodities and approximately 5900 price reports are used to calculate the Price Index for Domestic Supply. The prices are validated automatically in connection with the collection. Unusually large price developments are subsequently checked manually. The validated price developments are then aggregated in a hierarchical system, where they are given weight according to their significance to the overall price index., Read more about statistical processing, Relevance, The Producer and Import price index for commodities serves as economic key figures, cyclical indicator, deflator and a contract regulations tool. The primary users of the statistics are the Danish National Accounts, business and stakeholders in the Danish economy. The statistics meet all the requirements of the EU in terms of industry coverage, aggregation level, frequency and publication date, etc., Read more about relevance, Accuracy and reliability, The prices covered by the data collection have a direct coverage of approximately 70 percent of total revenue in the Danish economy. Weights are based on the National Accounts product balances, which covers the main part of trading in the first stage of sales within the delimitation of the statistics. Sample units are selected on a purposive basis using a top-down approach. As a random sampling method is not being utilised a subsequent assessment of sampling error is not enabled. , Published statistics are considered final. , Producer and import price index for commodities are not considered to have an increased uncertainty due to COVID-19. Data collection has been largely not impacted as a result of the crisis and subsequent non-response levels have remained at their historically low levels., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published on a monthly basis. The statistics for a given month are published on the 15th of the following month or the first business day thereafter. The statistics are usually published without delay in relation to the scheduled date., Read more about timeliness and punctuality, Comparability, Statistics Denmark has calculated variations of this statistic since 1876. The Producer and import price index for commodities can be found as an unbroken monthly time series from 2005 to today. The statistics have been prepared according to international standards and can therefore be compared to similar statistics from other European countries., Read more about comparability, Accessibility and clarity, The statistics are published monthly by Statistics Denmark via press release ", Nyt fra Danmarks Statistik, " (in Danish only) and specifically regard Producer and Import Price Index for Commodities., In the StatBank, the statistics are published under the topic , Producer and import price index for commodities, . , For more information visit the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/producer-and-import-price-index-for-commodities

Documentation of statistics

Documentation of statistics: Purchasing Power Parities (PPP)

Contact info, Prices and Consumption, Economic Statistics , Zdravka Bosanac , +45 61 15 16 74 , ZBO@dst.dk , Get documentation of statistics as pdf, Purchasing Power Parities (PPP) 2025 , Previous versions, Purchasing Power Parities (PPP) 2024, Purchasing Power Parities (PPP) 2023, Purchasing Power Parities (PPP) 2022, Purchasing Power Parities (PPP) 2021, Purchasing Power Parities (PPP) 2020, Purchasing Power Parities (PPP) 2019, Purchasing Power Parities (PPP) 2018, Purchasing Power Parities (PPP) 2017, Purchasing Power Parities (PPP) 2016, Purchasing Power Parities (PPP) 2015, Purchasing Power Parities (PPP) 2014, PPP tells how many currency units a given amount of goods and services cost in different countries. The statistics are used, among other things, to convert countries' gross domestic product (GDP) into comparable figures and for analyses of expenditure levels. Denmark has participated in the work on purchasing power parities since the 1970s, but the statistics in their current form are comparable from 2000 onwards., Statistical presentation, Purchasing power parities (PPP) is an annual price level indicator which expresses the price level in a given country at a given time, relative to the price level in one or more countries. This means that PPP for a particular country indicate how many units of national currency are needed in that country to maintain the purchasing power of €1 in the EU. PPP can be calculated for individual products or aggregates, such as GDP., Read more about statistical presentation, Statistical processing, Price surveys are conducted in order to provide price input data for household consumption, individual government consumption, collective consumption and gross fixed capital formation (investment goods and services). Reference (imputed) PPPs are used for NPISH consumption, inventories, and net exports., Read more about statistical processing, Relevance, The EU Commission uses GDP per capita PPP converted, as basis for allocating funds from the Structural Fund to reduce the financial inequalities among and within the 27 EU Member States. Furthermore, indicators derived from PPPs are used for a wide range of analytic purposes, often providing background information for policymaking in the European institutions, in international organizations like the International Monetary Fund and the World Bank, and in national governments., Read more about relevance, Accuracy and reliability, In the price surveys, the most important source of statistical margins of sampling errors is the range of goods and services, which are not equally representative of all countries included in the international comparisons. The composition of consumption expenditure differs among countries, and this gives rise to potential conflicts between representativeness and data comparability. For some areas, e.g. health it is particularly difficult to provide comparable information. The structure of the health sector differs among countries, and there are no "pure" market prices for these services, which constitutes another statistical margin of sampling error. The margins of sampling errors are not estimated., Read more about accuracy and reliability, Timeliness and punctuality, Provisional results from the surveys of purchasing power parities are published one year after the reference period, whereas the final results are published three years after the reference period. The statistics are usually published without any delay in relation to the scheduled date of publication., Read more about timeliness and punctuality, Comparability, Purchasing power parities are compiled for the purpose of conducting price and volume comparisons for a specific year among countries. Consequently, they are comparable across the participating countries. Comparisons over time must be interpreted with caution, as the basket of goods and services differs from one year to another., In the calculation of PPP, price level index and volume index, the average of EU28 was used as a reference country (group of countries) until 2020. With the United Kingdom's withdrawal from the European Union (EU), the EU27 (excluding the UK) = 100 will be used as a reference country (group of countries) from 2020. This has only a minor impact on the comparability of PPPs, the price level index and the volume index between 2019 and 2020. Results for 2024, published in December 2025 are presented in accordance with the new COICOP 2018 classification for product groups., Read more about comparability, Accessibility and clarity, These statistics are published annually 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 , International volume and price comparision, . Internationally, these statistics are available through , OECD, , , Eurostat, and , Nordic Statistics database, . For further information, go to the , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/purchasing-power-parities--ppp-

Documentation of statistics