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Follow this link to get access to , reports, documents and working papers of older date, ., Projects in collaboration with external institutions, Regarding economic effects on Denmark and Italy in connection with EU's enlargement. December 2001., Eastern enlargement of the EU: Economic costs and benefits for the EU present member states?, The case of Denmark, The case of Italy, Economic Working Papers,  (ADAM and DREAM), The DREAM group moved to the ministry of finance in march 2002., 2001:6   [DREAM] , The Optimal Level of Progressivity in the Labor Income Tax in a Model with Competitive Markets and Idiosyncratic Uncertainty, Toke Ward Petersen, September 2001 , 2001:5   [DREAM] , Interest Rate Risk over the Life-Cycle: A General Equilibrium Approach, Toke Ward Petersen, September 2001 ,  , 2001:4   [DREAM] , Indivisible Labor and the Welfare Effects of Labor Income Tax Reform, Toke Ward Petersen, September 2001 , 2001:3   [DREAM] , General Equilibrium Tax Policy with Hyperbolic Consumers, Toke Ward Petersen, July 2001 , 2001:2   [ADAM] , Modelling private consumption in ADAM, Henrik Hansen, N. Arne Dam og Henrik C. Olesen, August 2001 , 2001:1   [DREAM] , Fiscal Sustainability and Generational Burden Sharing in Denmark, Svend Erik Hougaard Jensen, Ulrik Nødgaard og Lars Haagen Pedersen, Maj 2001 ,  , 2000:5  [DREAM], V, elfærdseffekter ved skattesænkninger i DREAM, Anders Due Madsen, December 2000 ,  , 2000:4  [DREAM] , Har vi råd til velfærdsstaten ?, Lars Haagen Pedersen og Peter Trier, December 2000 ,  , 2000:3  [ADAM] , Current Price Identities in Macroeconomic Models, Asger Olsen and Peter Rørmose Jensen, August 2000 ,  , 2000:2  [ADAM] , General Perfect Aggregation of Industries in Input-Output Models, Asger Olsen, August 2000 ,  , 2000:1  [ADAM-DREAM] , Langsigtsmultiplikatorer i ADAM og DREAM - en sammenlignende analyse, Lars Haagen Pedersen og Martin Rasmussen, Maj 2000  ,   , 1999:4  [ADAM] , Løn-pris spiraler og crowding out i makroøkonometriske modeller, Carl-Johan Dalgaard og Martin Rasmussen, December 1999 ,  , 1999:3  [DREAM] , Earned Income Tax Credit in a Disaggregated Labor Market with Minimum Wage Contracts, Lars Haagen Pedersen & Peter Stephensen, November 1999, En kortere version af papiret er publiceret i Harrison, Hougaard Jensen, Pedersen & Rutherford (ed.): , Using Dynamic General Equilibrium Models for Policy Analysis, , North-Holland 2000,  , 1999:2 [ADAM] , Aggregation in Macroeconomic Models: An empirical Input-Output Approach, Asger Olsen, August 1999, Den endelige version er publiceret i , Economic Modelling, , 17:4 (2000) pp. 545-558 ,  , 1999:1  [ADAM] , Efterspørgslen efter produktionsfaktorer i Danmark, Thomas Thomsen, August 1999 ,  , 1998:6  [DREAM], A CGE Analysis of the Danish 1993 Tax Reform, Martin B. Knudsen, Lars Haagen Pedersen, Toke Ward Petersen, Peter Stephensen and Peter Trier, Oktober 1998,  , 1998:5  [DREAM] , Wage Formation and Minimum Wage Contracts, Lars Haagen Pedersen, Nina Smith (CLS) and Peter Stephensen, April 1998 ,  , 1998:4  [DREAM] , An introduction to CGE-modelling and an illustrative application to Eastern European Integration with the EU, Toke Ward Petersen, September 1997 ,  , 1998:3  [DREAM], I, Introduktion til CGE-modeller, Toke Ward Petersen, Oktober 1997, En kortere version er publiceret i Nationaløkonomisk Tidskrift 135 (1997) pp. 113-134,  , 1998:2  [ADAM] , Links between short- and long-run factor demand, Thomas Thomsen, December 1997, Den endelige version er publiceret i , Journal of Econometrics, , 97:1 (2000) pp. 1-23 ,  , 1998:1  [ADAM] , Faktorblokkens udviklingshistorie, 1991-1995, Thomas Thomsen, December 1997 ,  ,  

https://www.dst.dk/en/Statistik/ADAM/Dokumentation/AndetDok

Documentation of statistics: Population Projections

Contact info, Population and Education, Social Statistics , Annika Klintefelt , +45 23 31 14 33 , AKF@dst.dk , Get documentation of statistics as pdf, Population Projections 2025 , Previous versions, Population Projections 2024, Population Projections 2023, Population Projections 2022, Population Projections 2021, Population Projections 2020, Population Projections 2019, Population Projections 2018, Population Projections 2017, Population Projections 2016, Population Projections 2015, Population Projections 2014, A population projection gives an estimate of the size and composition of the future population with respect to sex, age, municipality and origin. The estimate is subject to a number of conditions and assumptions on migration, mortality and fertility. The projection is based on the assumption that the development in recent years continues. Often the development in e.g. in-migration is different from what was assumed and, for that reason, the projection will typically not match the actual development exactly., Statistics Denmark has prepared population projections since 1963. Since 2010, the projections have been produced in collaboration with DREAM (Danish Research Institute for Economic Analysis and Modelling), which is an independent institution whose purpose it is to develop and maintain tools for structural policy analysis. , Statistical presentation, Based on the projection for all of Denmark, Statistics Denmark subsequently makes projections that can be disaggregated by sex, age, provinces and municipalities. As part of the projections, figures are also available on demographic changes in terms of liveborn children, deaths, immigrants and emigrants., Read more about statistical presentation, Statistical processing, The population projections are based on historical data regarding the composition of the population in terms of sex, age and ancestry as well as fertility, mortality, immigration and emigration, and internal migration., Assumptions on the future development in fertility, mortality and migration are necessary to be able to make the projections., The projections are made every year using the population on 1 January. They are released in the beginning of May., A projection is made for the whole country as well as projections for the 11 provinces and 98 municipalities., Read more about statistical processing, Relevance, The projections for municipalities are widely used by the municipalities, and they create the basis for the municipalities’ own projections, which often incorporate a number of local factors that are not part of Statistics Denmark’s projections. The municipalities may use the projections in their planning of institutions, schools and the need for nursing homes in the future. Local media across the country take great interest in Statistics Denmark’s projection., Read more about relevance, Accuracy and reliability, The population projection is built on previous years’ development and is an estimate of the population development. The estimate is subject to a number of conditions and assumptions on migration, mortality and fertility. The projection is based on the assumption that the development seen in recent years will continue. Often the development in e.g. in-migration is different from what was assumed and, for that reason, the projection will typically not match the actual development exactly., In 2024 the projection for Denmark was 0.1 percentage points below actual population growth. To a wide extent, the uncertainty at municipal level is linked to the fact that local development plans and local decisions are not part of the model. Especially in 2020 and 2021, the COVID-19 pandemic has created uncertainty. In 2024, 60 per cent of the municipalities were within minus 0.5 percentage points of the actual population growth the first year. , Read more about accuracy and reliability, Timeliness and punctuality, Statistics have been published as announced without delay in the month of May or June., Read more about timeliness and punctuality, Comparability, Each projection is a new set of statistics and must not be used for time series together with previous projections., With the projection 2010, Statistics Denmark made the projection for all of Denmark for the first time in collaboration with DREAM, and in connection with this, a switch was made to a new projection model based on DREAM’s previous model., Read more about comparability, Accessibility and clarity, The population projections are published in Nyt fra Danmarks Statistik (Statistics Denmark’s news series in Danish) under the subject , Population projections, . For further information, go to the subject page for these statistics., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/population-projections

Documentation of statistics

Documentation of statistics: Retail Trade Index

Contact info, Short Term Statistics, Business Statistics , Kari Anne Janisse Arildsen , +45 40 43 38 12 , KJS@dst.dk , Get documentation of statistics as pdf, Retail Trade Index 2025 , Previous versions, Retail Trade Index 2024, Retail Trade Index 2021, Retail Trade Index 2020, Retail Trade Index 2019, Retail Trade Index 2018, Retail Trade Index 2017, Retail Trade Index 2016, Retail Trade Index 2015, Retail Trade Index 2014, The Retail Trade Index shows the development in turnover within the retail trade sector. The statistics is published monthly and is primarily used as short term indicator for private consumption as well as the general business cycle movement., Statistical presentation, Retail trade indices are published for 42 industries and for three commodity groups: food and other everyday commodities, clothing etc., and other commodities. Value and volume indices are produced. The volume index is made for the commodity groups and special industry aggregates for Eurostat. The statistics are based on survey data from all large retail trade enterprises and a sample of the remaining retail trade enterprises, which are requested to submit information about their turnover each month. Seasonal adjustment is performed of the three main commodity groups and the total., Read more about statistical presentation, Statistical processing, The survey is based on a sample of Danish retail trade enterprises. The sample includes approximately 2,200 enterprises, and at the time of the first publication, the figures for a month are based on responses from approximately 1.800 of these enterprises for the initial publication. , The sample consist of 42 subgroups and enterprises are sampled based on their share of the yearly turnover for the given subgroup. The companies are ranked from largest to smallest and the companies, whose rank constitutes the bottom 10 pct. of turnover for their subgroup when summed, are never selected to participate. The companies whose rank lies between 11 and 49 pct. of the subgroup’s yearly summed turnover, are randomly selected. Lastly, the larger firms whose turnover altogether lies in the top 50 pct. of the yearly turnover for their subgroup are always included in the sample. The companies are selected based on VAT-declarations to the Danish tax administration. , Read more about statistical processing, Relevance, Many users who monitor the current business trends take an interest in the published statistics of retail trade. The demand for the statistics is broadly based in trade associations, the bank and finance sector, politicians, public and private institutions, researchers, enterprises, news media and Eurostat. The statistics provide input to the quarterly national accounts statistics and to Eurostat's pan-European statistics. The users view the retail trade index as an important short term indicator, and it often gets a lot of attention in the media and amongst other professional users. , Read more about relevance, Accuracy and reliability, The overall uncertainty of the total retail trade index is estimated to be less than 1 per cent. On commodity group level, the uncertainty of the group Food and other convenience goods is about the same, whereas for Clothing etc. it can be up to 3 per cent and for other consumer goods up to 2 per cent., The accuracy of the monthly growth rate is generally very high. For the total index, the uncertainty is estimated to be maximum 0.2 percentage points, while it can be a little higher on commodity group level., Read more about accuracy and reliability, Timeliness and punctuality, Indices on the main commodity groups are published already 22-28 days after the end of the month. This is rather quick for statistics based on a survey such as this. One month later the indices on the most detailed industry level are published. The punctuality is very high with delays happening very rarely. , Read more about timeliness and punctuality, Comparability, These statistics have been compiled since 1939, but they are not suited for long term time series analysis because of structural changes in the retail trade sector. The sample design and the calculation methods have been adjusted several times, last time in May 2012, where the time series back to 2000 where recalculated using new methods. , Read more about comparability, Accessibility and clarity, These statistics are published in a Danish press release and in the StatBank under , Retail Trade Index, . The Retail Trade Index also has a , subject page, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/retail-trade-index

Documentation of statistics

Documentation of statistics: National Accounts: Quarterly

Contact info, National Accounts, Climate and Environment, Economic Statistics , Oliver Nygaard Sørensen , +45 51 83 40 39 , ons@dst.dk , Get documentation of statistics as pdf, National Accounts Quarterly 2025 Quarter 3 , Previous versions, National Accounts: Quarterly 2025 Quarter 2, The quarterly national accounts provide a comprehensive and up-to-date description of the economy and its development. The main focus is on short-term economic fluctuations, making it particularly useful for business cycle analysis, assessing economic conditions, and as a basis for economic models and forecasts. The statistics describe the economy as a whole, including transactions between households, businesses, and institutions, as well as transactions between Denmark and abroad. It has been compiled since 1988 and is fully comparable from first quarter 1990., Statistical presentation, The quarterly national accounts provide an overview of short-term activities and developments in the Danish economy. The quarterly national accounts include figures for key aggregates such as gross domestic product (GDP), private consumption, public consumption, investment, exports and imports, employment and wages, as well as profits and productivity across different industries. In addition, quarterly figures are available for a wide range of subcategories that can shed light on business cycle developments in the economy., Read more about statistical presentation, Statistical processing, The quarterly national accounts are compiled based on almost all short-term statistics that describe sub-areas of the economy and employment. When the first estimate for a given period is prepared, not all information for that period is yet available. The calculations are therefore based on the structure of the recent final national accounts, which are projected using indicators from, for example, short-term statistics. As new sources become available, they are gradually incorporated into the quarterly national accounts according to a fixed schedule., Read more about statistical processing, Relevance, The quarterly national accounts are relevant for anyone working with short-term and cyclical macroeconomic conditions. The use of the quarterly accounts ranges by the economic ministries for planning, analysis, forecasting, and modelling purposes, to similar uses by business organisations and other interest groups, as well as for the public’s interest in understanding the structure and development of the economy., Feedback from users is continuously evaluated through the Economic Statistics user Committee, user group meetings, direct contact with users, and through international forums., Read more about relevance, Accuracy and reliability, The quarterly national accounts’ ability to accurately describe the economic reality depends partly on the uncertainty associated with the sources. Some areas are measured more precisely than others due to better source data. Initial releases may lack data or be preliminary, and errors in sources or their combination with the national accounts system can affect reliability. Unforeseen economic shocks can increase uncertainty, but the accounts system’s consolidation of information helps reduce it., Read more about accuracy and reliability, Timeliness and punctuality, The first version of the quarterly national accounts is published 50 days after the end of the quarter, and a revised version is published 90 days after the end of the quarter. In connection with the publication of the fourth quarter at the end of February, the first version of the annual national accounts is also released. The national accounts are published on schedule., Read more about timeliness and punctuality, Comparability, The quarterly national accounts follow international guidelines (ESA 2010, implemented in 2014) and are comparable across countries. They cover all parts of the economy, and most economic statistics have their counterpart here. However, caution is advised when comparing with other statistics due to differences in definitions and coverage. The national accounts are fully consistent with the balance of payments and general government., Read more about comparability, Accessibility and clarity, The quarterly national accounts statistics are published in the StatBank under , Economy, and National accounts. The publications are accompanied by , Danish press releases, - in Danish., Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Job Vacancies

Contact info, Labour Market, Social Statistics , Monica Wiese Christensen , +45 21 73 34 69 , MWC@dst.dk , Get documentation of statistics as pdf, Job Vacancies 2025 Quarter 3 , Previous versions, Job Vacancies 2025 Quarter 2, Job Vacancies 2025 Quarter 1, Job Vacancies 2024 Quarter 4, Job Vacancies 2024 Quarter 3, Job Vacancies 2024 Quarter 2, Job Vacancies 2024 Quarter 1, Job Vacancies 2023 Quarter 4, Job Vacancies 2023 Quarter 3, Job Vacancies 2023 Quarter 2, Job Vacancies 2023 Quarter 1, Job Vacancies 2022 Quarter 4, Job Vacancies 2022 Quarter 3, Job Vacancies 2022 Quarter 2, Job Vacancies 2022 Quarter 1, Job Vacancies 2021 Quarter 4, Job Vacancies 2021 Quarter 3, Job Vacancies 2021 Quarter 2, Job Vacancies 2021 Quarter 1, Job Vacancies 2020 Quarter 4, Job Vacancies 2020 Quarter 3, Job Vacancies 2020 Quarter 2, Job Vacancies 2020 Quarter 1, Job Vacancies 2019 Quarter 4, Job Vacancies 2019 Quarter 3, Job Vacancies 2019 Quarter 2, Job Vacancies 2019 Quarter 1, Job Vacancies 2018 Quarter 4, Job Vacancies 2018 Quarter 3, Job Vacancies 2018 Quarter 2, Job Vacancies 2018 Quarter 1, Job Vacancies 2017 Quarter 4, Job Vacancies 2017 Quarter 3, Job Vacancies 2017 Quarter 2, Job Vacancies 2017 Quarter 1, Job Vacancies 2016 Quarter 4, Job Vacancies 2016 Quarter 3, Job Vacancies 2016 Quarter 2, Job Vacancies 2016 Quarter 1, Job Vacancies 2015 Quarter 4, Job Vacancies 2015 Quarter 3, Job Vacancies 2015 Quarter 2, Job Vacancies 2015 Quarter 1, Job Vacancies 2014 Quarter 4, The purpose of the statistics is to analyze the development in the number of job vacancies held by employers in the Danish labour market. The job vacancy statistics is an important labour market indicator as businesses typically reduce the number of job vacancies before they begin the dismissal of employees. Data on job vacancies is collected in accordance with similar guidelines by all EU Member States, which implies that the statistics are suitable for comparing the development in the number of job vacancies across the EU Member States., Statistical presentation, The statistics shows the quarterly development in the real number of job vacancies and job vacancy rates in relation to the sum of job vacancies and occupied posts in the Danish labour market. The statistics are broken into economic activity and size, which makes it possible to monitor and analyse the scope and structure of the demand for labour by industry and size level of the workplaces. Furthermore, the number of job vacancies and job vacancy rates at regional level are estimated., Read more about statistical presentation, Statistical processing, The statistics are compiled with use off a digital questionnaire, with a quarterly survey population of approximately 7,000 local units . Data are corrected for errors and for not reported data an imputation is conducted. , Read more about statistical processing, Relevance, The users of the statistics are primary the press, private companies, private persons and Eurostat. The statistic is used in analysis about the demand for labour and in the public debate. Data on job vacancies are collected in accordance with similar guidelines by all EU Member States, which implies that the statistics are suitable for comparing the development in the number of job vacancies across the EU Member States., Read more about relevance, Accuracy and reliability, As with all other sample-based statistics, there are some sample errors associated with the estimates. As is the case in other EU Member States, the variation coefficient (CV), which is the standard deviation in relation to the estimate, is used in calculating the sample errors. For the total number of occupied posts the variation coefficient normally is under 1 per cent, while for the total number of job vacancies the variation coefficient is 3-5 per cent. For the NACE sections and size classes the CV are relatively high. This is due to the great variations between the number of job vacancies reported and the many data reported concerning zero vacancies.., Read more about accuracy and reliability, Timeliness and punctuality, Data are released around 75 days after the reference quarter. The punctuality is very high, as delays in planned releases happen very rarely., Read more about timeliness and punctuality, Comparability, From the third quarter of 2012 a new more updated population is used in the enumeration process. The population is drawn from the ESR-register and contains information on the number of occupied posts, which are only three quarters old compared to the former population which was based on a less updated register. The changed enumeration process is estimated to have impact on the number of job vacancies, but not on the JVR (Job Vacancy Rate), which means that the number of job vacancies are not comparable historically in contrast to the JVR., Read more about comparability, Accessibility and clarity, Data are published quarterly in News from Statistics Denmark. Figures are published in the tables , LSK01, , , LSK02, and , LSK03, . See more at the statistics subject page , Job vancancies, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/job-vacancies

Documentation of statistics

Documentation of statistics: National Accounts: Annual

Contact info, National Accounts, Climate and Environment, Economic Statistics , Christina Just Brandstrup , +45 21 45 52 79 , CJB@dst.dk , Get documentation of statistics as pdf, National Accounts Annual 2024 , Previous versions, National Accounts 2023, National Accounts 2022, National Accounts 2021, National Accounts 2020, National Accounts 2019, National Accounts 2018, Annual national accounts, total economy 2017, Annual national accounts, total economy 2016, Annual national accounts, total economy 2015, Annual national accounts, total economy 2014, Annual national accounts, total economy 2013, The national accounts are a description of a country's economy and its development. It consists of a description of the economy as whole and the economic transactions between individuals, companies and institutions. The national accounts also include transactions between Denmark and abroad. The first Danish national accounts date back to the 1930's. Consistent time series of annual national accounts goes back to 1966, while quarterly national accounts are available as of first quarter 1990., Statistical presentation, The National Accounts provide an overview of the activities and developments in the Danish economy. The statistics include figures for economic aggregates such as gross domestic product (GDP), household consumption, government finances, investment, export and import, employment and wages, and profits and productivity in the various industries. In addition, there are figures for the many subdivisions that can illuminate different 'sections' throughout the Danish economy., Read more about statistical presentation, Statistical processing, Virtually all available economic statistics are applied as data sources when making the national accounts. When the first version for a given period is prepared, it takes place before all information about the period is available. Then the calculations are made on the basis of the structure of the latest final national accounts, which is projected with indicators from, for example, cyclical statistics. When new sources are ready, they are continuously incorporated into the national accounts according to a fixed rhythm. Three years after a given period, the national accounts are considered to be final., Read more about statistical processing, Relevance, The National Accounts are relevant to anyone involved in economic matters ranging from the economic ministries use of the National Accounts in planning, analysis, forecasting and modeling purposes for industry organizations and other similar organizations, to the general interest in knowledge of the economy’s structure and development. The National Accounts division is evaluating feedback from users at an ongoing basis., Read more about relevance, Accuracy and reliability, The ability of the National Accounts to describe the economic reality accurately partly depends on the uncertainty associated with the sources and partly on the model assumptions underlying the calculation of the national accounts. Some parts can be calculated more accurately than others, as there is better access to source data. The first versions for a period's national accounts will be more uncertain than the final version, which comes after three years, as new sources are continuously revised., Read more about accuracy and reliability, Timeliness and punctuality, The first version of the quarterly national accounts is published 50 days after the end of the quarter. In connection with the publication of the fourth quarter at the end of February, the first version of the annual national accounts is also published. Almost two and a half years after the end of the year, the final annual and quarterly national accounts are published in June. The national accounts are published in a timely manner., Read more about timeliness and punctuality, Comparability, The national accounts are prepared in accordance with international guidelines and will therefore be comparable across countries. The current guidelines were implemented in 2014 and are used to revise the national accounts back to 1966. The national accounts reflect all parts of the economy, so most economic statistics contain figures that have their counterparts in the national accounts. However, be careful to compare figures from the national accounts with other economic statistics, as the transition is often complicated by different definitions and requirements for coverage. However, the national accounts are in full compliance with the balance of payments and government finance statistics., Read more about comparability, Accessibility and clarity, The National Accounts statistics are published in the StatBank under , Economy, and , National accounts, . The publications are accompanied by Danish press releases., Read more about accessibility and clarity

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

Documentation of statistics

Documentation of statistics: Consumer Price Index

Contact info, Prices and Consumption, Economic Statistics , Martin Sædholm Nielsen , +45 24 49 72 81 , MNE@dst.dk , Get documentation of statistics as pdf, Consumer Price Index 2025 , Previous versions, Consumer Price Index 2024, Consumer Price Index 2023, Consumer Price Index 2022, Consumer Price Index 2021, Consumer Price Index 2020, Consumer Price Index 2019, Consumer Price Index 2018, Consumer Price Index 2017, Consumer Price Index 2016, Consumer Price Index 2015, Consumer Price Index 2014, Documents associated with the documentation, Klassifikationskoder og beskriveler (pdf), Notat om forbruger-og nettoprisindekset i forbindelse med coronakrisen (pdf) (in Danish only), Weightings 2025 (xlsx), Vægtgrundlag 1991 til i dag (xlsx) (in Danish only), Vejledning til regulering med prisindeks (pdf) (in Danish only), Vægte 2021 og corona (pdf) (in Danish only), FPI-dokumentation - opdateret maj 2020 (pdf) (in Danish only), The purpose of the consumer price index is to measure the development of the prices charged to consumers for goods and services bought by private households in Denmark. The consumer price index has been calculated since 1914, but there are estimated figures for the development in consumer prices back to 1872. From January 1967 the index has been calculated on a monthly basis., Statistical presentation, The consumer price index 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 consumer price indices divided by group of households show the price development for different households. , 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 consumer price index 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 consumer price index, are first grouped according to approx. 500 elementary aggregates for which elementary aggregate indices are calculated. The elementary aggregate indices are weighted together into sub-indices that are in turn aggregated into the total consumer price index. In calculating a price index it is assumed that the baskets of goods that are compared are identical, also with respect to the quality of the goods. Mainly indirect quality adjustment methods are being applied in the consumer price index in connection with changes in the sample. , Read more about statistical processing, Relevance, The consumer price index is generally viewed as a reliable statistic based on the views of users., Important users are among others the Ministry of Finance, The Ministry of Economic Affairs and the Interior, The Danish Central Bank and 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 consumer price index as the sample is not randomly drawn, but the quality of the consumer price index is accessed to be high., 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 (se chapter regarding "Non-sampling error")., Read more about accuracy and reliability, Timeliness and punctuality, The consumer price index 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., The consumer price indices divided by group of households are published twice a year., Read more about timeliness and punctuality, Comparability, The consumer price index is related to the European Union harmonized consumer price index (HICP) and to the index of net retail prices. 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. The consumer price index is also related to the index of net retail prices. The two indices comprise the same groups of goods and services and are calculated according to the same methodology. Consequently, the only difference between the two indices is the price concept used, as indirect taxes and VAT are subtracted in the index of net retail prices, and the weighting., Read more about comparability, Accessibility and clarity, These statistics are published monthly in a Danish press release and in the StatBank under , Consumer Price Index, ., Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/consumer-price-index

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) 2025 , Previous versions, 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), Weightings 2025 (xlsx), 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: Social benefits for senior citizens

Contact info, Personal Finances and Welfare, Social Statistics , Marie Borring Klitgaard , +45 21 55 83 71 , MGA@dst.dk , Get documentation of statistics as pdf, Social benefits for senior citizens 2025 , Previous versions, Social benefits for senior citizens 2024, Social benefits for senior citizens 2023, Social benefits for senior citizens 2022, Social benefits for senior citizens 2021, Social benefits for senior citizens 2020, Elderly - Indicators 2019, Elderly - Indicators 2018, Elderly - Indicators 2017, Elderly - Indicators 2016, Elderly - Indicators 2015, Elderly - Indicators 2014, Elderly - Indicators 2013, Documents associated with the documentation, Kommentarer til 2024 - korte udgaver (xlsx) (in Danish only), Kommentarer til 2025 - korte udgaver (xlsx) (in Danish only), The purpose of these statistics is to display the quality level of municipal services in the elderly care. The statistics are a part of a cross-public cooperation, intended to ensure coherent documentation of important areas of municipal service, as well as to increase the comparability of the services provided in the different municipalities. The statistics are used to determine impact targets, frameworks and results requirements for key management initiatives and are comparable from 2008 onwards. Statistics Denmark is responsible for the composition and publication of the statistics., Statistical presentation, The statistic for 2025 covers data from the first 6 months of 2025. The statistic is an annual survey including a number of national impact- and background indicators which document and describe the quality of the municipal effort at the elderly area. The indicators consist of referral and provided home care, home nursing, nursing homes, exercise services, rehabilitation and preventative home visits. Primarily, the indicators are targeted at the elderly area, however home care, exercise services, home nursing as well as nursing homes also include data for citizens under 67 years., Read more about statistical presentation, Statistical processing, Before publishing data from the municipalities' EOJ system (electronic care journal), tables and figures are developed, which all municipalities are asked to approve. After the approval, Statistics Denmark detects for data errors as missing numbers, abnormal values and etc., Read more about statistical processing, Relevance, The authorities and public institutions and the population use the indicators for analysis, research, debate, etc. The focus is to ensure more valid documentation at the elderly area. This is achieved by retrieving the information directly from the municipalities' care systems (EOJ), which is constantly updated as a part of the municipalities' case management., Read more about relevance, Accuracy and reliability, The municipalities receive control tables, which they are asked to approve. Only approved information is included in the statistics. In the absence of approvals, previous years' information is included in the national totals and averages. For the publication for the first 6 months 2025, between 97 and 98 municipalities are included, depending on the indicator. Lack of approval may be due to the municipality's registration practices, which determine which data is reported, and system or supplier changes, where the reported data may be flawed. There are varying registration practices between municipalities in several areas, which can lead to distortions., Read more about accuracy and reliability, Timeliness and punctuality, The statistics are published as pre-advertised. The statistics are released approximately 6 months after the reference period has ended. , Read more about timeliness and punctuality, Comparability, The statistics are generally comparable over time, but there are minor data breaks. The municipalities' change of EOJ provider every five years can affect certain indicators. As of October 1, 2023, new reporting requirements for food service and supplier types resulted in a data break in the statistics on designated home care. Therefore, the figures for 2023 should be compared with previous years with reservations. For hospital usage, there has been no adjustment for the severity of diseases, which affects the comparability between municipalities., Read more about comparability, Accessibility and clarity, The statistics are published in a , Danish press release, . The figures are published in the StatBank under the subject , Social benefits for senior citizens, . See more on the subject page for the , Social benefits for senior citizens, . , Read more about accessibility and clarity

https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/social-benefits-for-senior-citizens

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