1.1. Contact organisation
Statistics Denmark
1.2. Contact organisation unit
Work and Income Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Skt. Kjelds Plads 11
2100 København Ø
Denmark
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
7 September 2026
2.2. Metadata last posted
7 September 2026
2.3. Metadata last update
7 September 2026
3.1. Data description
| The EU Labor Force Survey (EU-LFS) is the largest European interview-based sample survey. The unit of the Danish LFS is persons and the sample is based on a quarterly sample of the Danish population between the ages of 15 and 89. Its main statistical objective is to classify the population of working age (15 years and over) into three mutually exclusive and exhaustive groups: employed persons, unemployed persons, which together represent the ‘labour force’, and the people outside the labour force. Members of the household are interviewed in the main respondents' fourth and last wave. Household members are derived from registers as persons belonging to the same familiy.
|
3.2. Classification system
Reference can be found in the dedicated webpage at:
EU_labour_force_survey_-_documentation#Classifications
3.3. Coverage - sector
See sections below
3.3.1. Coverage
Individuals living in private households in the Country
3.3.2. Inclusion/exclusion criteria for members of the household
Members of the household are interviewed in the main respondents' fourth and last wave. Household members are derived from registers as persons belonging to the same familiy. Please find more information regarding Definition of family (Only available in Danish).
3.3.3. Questions relating to labour status are put to all persons aged
15-89 years
3.4. Statistical concepts and definitions
Labour market status: The main variable in the Labour Force Survey is the labour market status of the population. The survey classifies people into two main categories: people in the labour force and people outside the labour force. Furthermore, people in the labour force are categorized as either employed or unemployed. Conscripts are considered employed.
The classification of respondents is based on their labour market status and follows EU definitions and recommendations from the International Labour Organization (ILO) definitions: Every respondent is interviewed about one specific reference week. All questions on work, working hours, unemployment etc. relate to this specific week.
Unemployed: Unemployed are all people without employment, who have actively been looking for work in the past four weeks prior to the reference week and who are able to begin a job within two weeks after the reference week ends. Active job-search methods include contact with a public employment office, applications to employers, contact with friends, relatives or trade unions, or for example studying or answering advertisements in newspapers or journals. Looking for permits, licencs, financial resources, land, premises or equipment for potential self-employment are also considered as active job search.
Unemployment rate: The unemployment rate is the number of unemployed persons compared to the number of persons in the same group of age in the labour force (employed and unemployed).
Employed: Employed are all people, who in the reference week worked for payment or worked as self-employed or family workers for at least one hour. People temporarily absent perhaps due to vacation, illness, or maternity leave are considered to be employed.
Employment rate: The employment rate is the number of employed persons compared to the number of persons in the same group of age in the population. Economic activity rate: The number of individuals in the labor force (employed and unemployed) as a proportion of a given population group
Weighting method: The way in which the sample is weighted to the entire population, in order to make the results as representative as possible. It is always weighted figures that are being published. The method of weighting practically means that each person participating in the LFS gets his or her own weight and hereby represents a specific sample of the population with regards to sex and age. The method of weighting has been revised several times over the years (read more under Documentation on methodology. Person: 15-89 years old. Reference week: The specific week that the respondent is asked about. Whether you are employed or LFS unemployed, how many hours you have worked during the week etc., is related to the specific reference week. The date of the interview can be up to four weeks after the reference week, typically 1-2 weeks after. There are 13 reference weeks per quarter.
Member of the household are interviewed in the main respondents' fourth and last wave. Household members are derived from registers as persons belonging to the same familiy.
3.4.1. Household concept
Common housekeeping
3.4.2. Definition of household for the EU-LFS
Members regularly living together in the same dwelling sharing income, household expenditures, food and other essentials for living.
Is the same as the family concept from Danish population registers. Plaese find more information Definition of family (Only available in Danish).
3.4.3. Population concept
Persons with registered address in Denmark
3.4.4. Specific population subgroups
| Population concept |
Specific population subgroups |
||||
| Primary/secondary students |
Tertiary students |
People working out of family home for an extended period for the purpose of work |
People working away from family home but returning for weekends |
Children alternating two places of residence |
|
| Registered address |
Registered address |
Registered address |
Registered address |
Registered address |
Registered address |
|---|---|---|---|---|---|
3.5. Statistical unit
The data collection is carried out for each Member State for a sample of observation units constituted by private households or by persons belonging to private households who have their usual residence in Denmark
3.6. Statistical population
The statistical population consists of all persons having their usual residence in private households in Denmark.
3.7. Reference area
Not requested for the LFS quality report.
3.8. Coverage - Time
The time period covered by the data is 1995-2024.
Issues concerning comparability over time are discussed in 15. Coherence and comparability
3.9. Base period
Not requested for the LFS quality report.
The LFS produces different indicators with different measures: Numbers and Percentages
The measured observations refer to quarters
6.1. Institutional Mandate - legal acts and other agreements
EU level:
The EU-LFS is based on European legislation since 1973. The principal legal acts, currently in force, are the Regulation (EU) 2019/1700 establishing a common framework for European social statistics, the Commission Delegated Regulation (EU) 2020/256 establishing a multiannual rolling planning, the Commission Implementing Regulation (EU) 2019/2181 regarding items common to several datasets, and the Commission Implementing Regulation (EU) 2019/2240 which specifies the implementation rules, technical items and contents of the EU-LFS.
National level:
No mandate
6.2. Institutional Mandate - data sharing
Member States shall make available to the Commission (Eurostat) the data and metadata required under the Regulation 2019/2240 using the statistical data and metadata exchange standards specified by the Commission (Eurostat) and the Single Entry Point.
The Commission (Eurostat) shall, in cooperation with Member States, publish the aggregated data on the Commission (Eurostat) website, in a user‐friendly way, as soon as possible and within six months of the transmission deadline for annual and infra‐annual data collection.
Data sharing and exchange between international data producing agencies, for example, a Eurostat data collection or production that is in common with the OECD or the UN.
Anonomized disaggregated data can be shared with national institutions through the Research Service Unit of Statistics Denmark.
7.1. Confidentiality - policy
EU level:
Regulation (EU) No 557/2013 17 June 2013 as regards access to confidential data for scientific purposes and repealing Commission Regulation (EC) No 831/2002. It implements the Regulation (EC) No 223/2009 of the European Parliament and of the Council on European Statistics, which sets criteria for confidentiality of data.
National level:
The Danish Labour Force Survey follows the guidelines of the Data Confidentiality Policy at Statistics Denmark: Data Confidentiality Policy. Statistics Denmark has described the guidelines for the use of data from the LFS. The purpose is to assure quality in the analysis based on the LFS and furthermore inform external users of the LFS on e.g. sampling errors. It is possible to achieve knowledge about publishing limits on yearly and quarterly basis.
7.2. Confidentiality - data treatment
Data is released after checking it does not reveal confidential data. Administrative identifiers, interconnecting statistical identifiers and any other identification data shall be removed (or they shall be modified to an extent where they cannot directly identify the unit to which they relate).
8.1. Release calendar
(1) the Member States shall transmit pre‐checked microdata without direct identifiers, according to the following two‐
step procedure:
(a) during the first three years of implementation of this Regulation, as provided for in Article 11(4):
- for quarterly data: within ten weeks of the end of the reference period,
- for other data: by 31 March of the following year;
(b) from the fourth year of implementation as follows:
- for quarterly data: within eight weeks of the end of the reference period,
- for other data regularly transmitted: by 15 March of the following year,
- for other data concerning ad‐hoc subjects: by 31 March of the following year.
Where those deadlines fall on a Saturday or Sunday, the effective deadline shall be the following Monday. The detailed topic income from work may be transmitted to the Commission (Eurostat) within fifteen months of the end of the reference period.
(2) The Member States shall transmit aggregated results for the compilation of monthly unemployment statistics within 25 days of the reference or calendar month, as appropriate. If the data are transmitted in accordance with the ILO definition, that deadline may be extended to 27 days.
National level:
Data is released nationally 50-60 days following the end of the reference quarter.
8.2. Release calendar access
Access to country release calender
8.3. Release policy - user access
European social statistics are provided on the basis of equal treatment of all types of users, such as policy‐ makers, public administrations, researchers, trade unions, students, civil society representatives including non‐ governmental organisations, and citizens, which can access statistics freely and easily through Commission (Eurostat) databases on its website and in its publications.
National release policy, for example:
Standard tables for free access are published on the NSI's website.
Results are disseminated to all users at the same time.
National level:
Standard tables for free access are published in the StatBank of Statistics Denmark. Results are disseminated to all users at the same time.
First release, quarterly (4x), yearly (1x), ad hoc module results (1x)
National standard: Quarterly
10.1. Dissemination format - News release
Press releases are published for each quarterly dissemination. Additionally, one annual news release is published following the first dissemination of Q4. Additional news releases are produced on an ad-hoc basis.
Press releases published over the past year:
10.2. Dissemination format - Publications
In addition to the quarterly news releases, the LFS figures are occasionally published in the following:
10.3. Dissemination format - online database
Access to LFS tables in Statbank Denmark: Tables
10.3.1. Data tables - consultations
Not requested for the LFS quality report.
10.3.2. Web link to national methodological publication
National LFS documentation
National methodological publication
10.3.3. Conditions of access to data
Aggregated data available to public, microdata available to researchers.
10.3.4. Accompanying information to data
For questionnaire and methodological explanations see section 10.3.2
10.3.5. Further assistance available to users
Further assistance available via email
10.4. Dissemination format - microdata access
Data are accessible in micro-data form, e.g. for researchers. See section 7. for confidentiality policy
10.4.1. Accessibility to EU-LFS national microdata (Y/N)
Y
10.4.2. Who is entitled to the access (researchers, firms, institutions)?
Researchers and institutions
10.4.3. Conditions of access to data
Projects, users and institutions must all be approved by Eurostat and/or Statistics Denmark
10.4.4. Accompanying information to data
Explanations of e.g. breaks in series and general documentation of variables
10.4.5. Further assistance available to users
Further assistance available via email
10.5. Dissemination format - other
Not requested for the LFS quality report.
10.5.1. Metadata - consultations
Not requested for the LFS quality report.
10.6. Documentation on methodology
See sections below.
10.6.1. Metadata completeness - rate
Not requested for the LFS quality report.
10.6.2. References to methodological notes about the survey and its characteristics
See section 10.3.2 and 10.7
10.7. Quality management - documentation
National LFS documentation:
Quarterly documentation
National methodological publication
11.1. Quality assurance
Not requested for the LFS quality report.
11.2. Quality management - assessment
Not requested for the LFS quality report.
12.1. Relevance - User Needs
Due to register information on employment and unemployment being readily available at a detailed level, the user needs are centered around data for international comparison and variables, that are not available in administrative registers. From 2024 and forward user needs will be assessed through an Expert User Group on Labour Market Satistics.
Users have inquired about more frequent releases on tele work. From Q1 2024 we publish both a quarterly and a yearly table on this.
12.2. Relevance - User Satisfaction
Not requested for the LFS quality report.
12.3. Completeness
See sections below
12.3.1. Data completeness - rate
Not requested for the LFS quality report.
12.3.2. NUTS level of detail
NUTS 2:
Region Hovedstaden
Region Sjælland
Rgion Syddanmark
Region Midtjylland
Region Nordjylland
12.3.2.1. Regional level of an individual record (person) in the national data set
In theory, all regional classifications can be made in the Danish LFS as the Population Register supplies the LFS with information on place of residence; e.g. address and municipality code. However, for the quarterly LFS only estimates at NUTS-2 level are considered reliable. By using annual averages instead of quarterly estimates, aggregated NUTS-3 level estimates of employment and labour force are considered reliable, whereas cross-tabulations of these as well as aggregated NUTS-3 level estimates of unemployment should be made with caution.
12.3.2.2. Lowest regional level of the results published by NSI
NUTS2
12.3.2.3. Lowest regional level of the results delivered to researchers by NSI
LAU
13.1. Accuracy - overall
Not requested for the LFS quality report.
13.2. Sampling error
Being a survey, the LFS is subject to sampling errors.
More information on this concept is provided in the following sub concepts or in the annex file.
13.2.1. Sampling error - indicators
See sections below
13.2.1.1. Coefficient of variation (CV) Annual estimates %
See table 13.2.1.1 in annex for detailed information.
13.2.1.2. Coefficient of variation (CV) Annual estimates at NUTS-2 Level %
See table 13.2.1.2 in annex for detailed information.
13.2.1.3. Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The denominator for the calculation of the CV for the employment rate is the estimated employment rate. The estimated employment rate is calculated as the estimated number of employed persons divided by the estimated number of persons in the same age interval in the population. The estimation is done using calibration estimation. This estimation ensures, that the following population totals are recreated by the weighting for each of the four panels: gender, age, education, region of residence and register-based labour market status.
13.2.1.4. Reference on software used
Andersson, C and Nordberg, L (1998). CLAN – A SAS-program for Computation of Point- and Standard Error Estimates in Sample Surveys. Örebro: Statistics Sweden.
13.2.1.5. Reference on method of estimation
Särndal, C. E., Swensson B. and Wretman J. (1992). Model Assisted Survey Sampling. New York: Springer Verlag.
13.3. Non-sampling error
Not requested for the LFS quality report.
13.3.1. Coverage error
See table 13.3.1 in annex for detailed information.
13.3.1.1. Over-coverage - rate
See table 13.3.1. in annex for detailed information.
13.3.1.2. Common units - proportion
Not requested for the LFS quality report.
13.3.1.3. Misclassification errors – detection of mismatches of identifiers
See table 13.3.1. in annex for detailed information.
13.3.1.4. Misclassification errors –description of the main misclassification problems encountered in collecting the data and the methods used to process misclassifications
See table 13.3.1.4 in annex for detailed information.
13.3.2. Measurement error
See sections below.
13.3.2.1. Errors due to the media (questionnaire)
See table 13.3.2.1 in annex for detailed information.
13.3.2.2. Main methods of reducing measurement errors
See table 13.3.2.2 in annex for detailed information.
13.3.3. Non response error
Not requested for the LFS quality report.
13.3.3.1. Unit non-response - rate
See sections below.
13.3.3.1.1. Methods used for adjustments for statistical unit non-response
See table 13.3.3.1.1 in annex for detailed information.
13.3.3.1.2. Non-response rates. Annual averages (% of the theoretical yearly sample)
See table 13.3.3.1.2 in annex for detailed information.
13.3.3.1.2.1. Non-response rates. Annual averages (% of the theoretical yearly sample) – NUTS-2 level
See table 13.3.3.1.2.1 in annex for detailed information.
13.3.3.1.3. Units who did not participate in the survey
See table 13.3.3.1.3. in annex for detailed information.
13.3.3.2. Item non-response - rate
See sections below.
13.3.3.2.1. Item non-response (INR) in % * - Quarterly data (Compared to the variables defined by the Commission Regulation (EC) No 2019/2240)
See table 13.3.3.2.1 in annex for detailed information.
13.3.3.2.2. Item non-response (INR) in % * - Annual data (Compared to the variables defined by the Commission Regulation (EC) No 2019/2240)
See table 13.3.3.2.2. in annex for detailed information.
13.3.3.2.3. Item non-response for INCGROSS variable
See table 13.3.3.2.3. in annex for detailed information.
13.3.4. Processing error
See sections below.
13.3.4.1. Editing and imputation process
See table 13.3.4.1 in annex for detailed information.
13.3.5. Model assumption error
Not requested for the LFS quality report.
14.1. Timeliness
See table 14.1 in annex for detailed information.
14.1.1. Time lag - first result
Not requested for the LFS quality report.
14.1.2. Time lag - final result
Not requested for the LFS quality report.
14.2. Punctuality
All disseminations and press releases have been published on time.
14.2.1. Punctuality - delivery and publication
Not requested for the LFS quality report.
15.1. Comparability - geographical
See section 15.1.2. Divergence of national concepts from European concepts
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested for the LFS quality report.
15.1.2. Divergence of national concepts from European concepts
|
|
15.2. Comparability - over time
Break in Series from 2023 to 2024 to be flagged: In Q4 2023 the data collection period has been increased from two weeks to four weeks – thus giving respondents a bit more time to respond to the questionnaire. This was done to combat falling response rates. Furthermore, this has resulted in a greater number of interviews, but the interviews are not evenly distributed across labour market statuses. There are lager increases in the response rates of employed and unemployed persons, especially younger persons have been more inclined to respond. This is not neutralized completely in the calibration of weights, therefore it shows up in especially the main unemployment indicator as a data break.
Nationally, the break has been handled as a seasonal outlier and the data break does not affect the seasonally adjusted numbers to any large extent.
There has been data-related changes affecting comparability. The changes are not significant enough to be flaged but there is a break in the quarterly data series for LOOKOJ in Q2 and Q3 2024 as well as in GALI in Q1 2024.
See sections below and the table P15.2.3. in annex for detailed information.
15.2.1. Length of comparable time series
Time series are comparable since 2008.
15.2.1.1. Length of time series
Not requested for the LFS quality report.
15.2.1.2. Length of comparable time series
Not requested for the LFS quality report.
15.2.2. Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
See section 15.2. Comparability - over time: Break in Series from 2023 to 2024
See table 15.2.2 in annex for detailed information.
15.2.3. Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
See table 15.2.3 in annex for detailed information.
15.3. Coherence - cross domain
Not requested for the LFS quality report.
15.3.1. Coherence - sub annual and annual statistics
Not requested for the LFS quality report.
15.3.2. Coherence - National Accounts
|
|
Description of difference in concept |
Description of difference in measurement |
Give an assessment of the effects of the differences |
Give references to description of differences |
|---|---|---|---|---|
| Total employment |
The Danish statistics on National Accounts |
NA employment is measured almost entirely through registers. Except the estimation on moonlighting and subdivisions og construction employment, which are edjustments based on surveys. |
Overall level higher in NA. Higher level of employees in NA, but lower level om self-employed in the LFS |
Paper published on the national homepage in English:
|
| Total employment by NACE |
See comment above |
See comment above |
Quite large differences between sectors, largely because of the difference in sources |
NA |
| Number of hours worked |
See comment above. The big difference stems from the unit. The working time accounts compile hours to a huge total, and have no individuals. This creates some differences over time. |
The way to compare the NA and LFS is to calculate the total number of hours worked in the LFS, since the NA only works on aggregate level and not on the level of individual persons’ working hours per week. |
Higher level of hours worked in the LFS - approximately 4 percent. |
NA |
15.3.3. Which is the use of EU-LFS data for National Account Data?
| Which is the use of LFS data for National Account Data? |
|||||
|---|---|---|---|---|---|
| Country uses LFS as the only source for employment in national accounts. |
Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis |
Country doesn’t make use of LFS, or makes minimal use of it |
Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS) |
Country combines sources for labour supply and demand not giving precedence to any labour side |
Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employ- ment registers and/or enterprise surveys) |
| N |
N |
Y |
N |
N |
N |
15.3.4. Coherence of EU-LFS data with Business statistics data
|
|
Description of difference in concept |
Description of difference in measurement |
Give an assessment of the effects of the differences |
Give references to description of differences |
|---|---|---|---|---|
| Total employment |
Business statistics are based on register, where the employers register the number of employed. LFS is based on self-reported working status by the respondents. |
Business statistics are based on register, where employers register the number of employed. LFS is based on self-reported working status by the respondents. |
Expected because of the differences between self-reported information in LFS and registerinformation |
UNA |
| Total employment by NACE |
Business statistics are based on register, where the employers register the number of employed. LFS is based on self-reported working status by the respondents. This also applies looking at NACE level. |
Business statistics are based on register, where employers register the number of employed. LFS is based on self-reported working status by the respondents. This also applies looking at NACE level. |
Expected because of the differences between self-reported information in LFS and registerinformation |
UNA |
| Number of hours worked |
Business statistics are based on register, where employers register the number of paid |
Business statistics are based on register, where employers register the number of paid hours. LFS is based on self-reported working time by the respondents. |
Expected because of the differences between self-reported information in LFS and registerinformation |
UNA |
15.3.5. Coherence of EU-LFS data with registered unemployment
| Description of difference in concept |
Description of difference in measurement |
Give references to description of differences |
|---|---|---|
| The Danish concept of registered unemployment has been split in two in 2010. What was previously the main concept is now a subgroup called "net unemployment". The total concept (gross unemployment) includes those in certain labour market activation programmes. Although the total is therefore close to the LFS total, the concept is even further from the ILO definition, as many ILO-employed are among the gross unemployed |
FTE's vs persons |
15.3.6. Assessment of the effect of differences of EU-LFS unemployment and registered unemployment
| Give an assessment of the effects of the differences |
|||||
|---|---|---|---|---|---|
| Overall effect |
Men under 25 years |
Men 25 years and over |
Women under 25 years |
Women 25 years and over |
Regional distribution (NUTS-3) |
| The LFS unemployment was 6.2 and the gross uemployment was 2.9 per cent. |
The LFS unemployment was 15.0 and the gross unemployment was 1.0. This is due to the fact that young persons rarely have the right to receive unemployment benefits. |
The LFS unemployment was 4.4 and the gross unemployment was 3.1 |
The LFS unemployment was 14.2 and the gross unemployment was 0.9. This is due to the fact that young persons rarely have the right to receive unemployment benefits. |
The LFS unemployment was 5.1 and the gross unemployment was 3.4.
|
NA |
15.3.7. Comparability and deviation for the INCGROSS variable
See table 15.3.7 in annex for detailed information.
15.4. Coherence - internal
Not requested for the LFS quality report.
Continuous efforts are made to ensure the efficient implementation of the Danish LFS. This includes the use of digital tools for data collection, as well as automated processes that help reduce resource use. Reducing respondent burden is a key priority. We continuously review and streamline the questionnaire to remove redundant or less relevant questions. Respondents also have the opportunity to leave comments after completing the questionnaire, and these are systematically reviewed and used to identify possible improvements. Flexible interview modes and the use of administrative data where applicable also contribute to minimising burden.
16.1. Number of staff involved in the EU-LFS in central and regional offices, excluding interviewers. Consider only staff directly employed by the NSI.
See table 16.1. in annex for detailed information.
16.2. Duration of the interview by Final Sampling Unit
See table 16.2. in annex for detailed information.
17.1. Data revision - policy
Data is not revised
17.1.1. Is the general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N)
Y: Data are final when they are published.
17.1.2. Is the country revision policy compliant with the ESS guidelines on revision policy for PEEIs?
Y
17.2. Data revision - practice
Not requested for the LFS quality report.
17.2.1. Data revision - average size
Not requested for the LFS quality report.
18.1. Source data
Data for the LFS is a mix of survey data and data from administrative and statistical registers.
18.1.1. Source data - frame population
| Sampling design (scheme; simple random sample, two stage stratified sample, etc.) |
Base used for the sample (sampling frame) |
Last update of the sampling frame (continuously updated or date of the last update) |
Primary sampling unit (PSU) |
Final sampling unit (FSU) |
Date of sample selection |
|---|---|---|---|---|---|
| One stage stratified sample |
The Population Register and other registers (enhanced with information from the labour market register and the income register). |
Continuosly |
NA |
Individuals. One month before each reference quarter. |
|
18.1.2. Sampling design & Procedure method
|
18.1.3. Yearly sample size & Sampling rate
See table 18.1.3. in annex for detailed information.
18.1.4. Quarterly sample size & Sampling rate
See table 18.1.4. in annex for detailed information.
18.1.5. Use of subsamples to survey structural variables (wave approach)
| Only for countries using a subsample for yearly variables |
|||
| Wave(s) for the subsample |
Are the 30 totals for ILO labour status (employment, unemployment and inactivity) by sex (males and females) and age groups (15-24, 25-34, 35-44, 45-54, 55+) between the annual average of quarterly estimates and the yearly estimates from the subsample all consistent? (Ref.: Commission Reg. 2019/2240) (Y/N) |
If not please list deviations |
List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 2019/2240, Annex I) |
|---|---|---|---|
| NA |
NA |
NA |
NA |
Yearly variables are collected from all respondents in the LFS.
18.2. Frequency of data collection
Not requested for the LFS quality report.
18.3. Data collection
| Data collection methods: brief description |
Use of dependent interviewing (Y/N)? |
In case of Computer Assisted Methods adoption for data collection, could you please indicate which software is used? |
|---|---|---|
| From 2016 both the core-LFS and the household subsample is based on a mix of modes where CATI is supplemented with CAWI. |
Y |
UNICOM Intelligence: ISO 27001 certified and compliant with the standards under the Danish Government's IT |
18.3.1. Final sampling unit collected by interviewing technique (%)
See table 18.3.1 in annex for detailed information.
18.3.2. Info from registers
| Are any LFS data collected from registers (Y/N)? |
If Y, please indicate which variable(s) are partly collected from registers. |
If Y, please indicate which variable(s) are fully collected from registers. |
|---|---|---|
| Y |
COUNTRYB, COBFATH, COBMOTH, HHLINK, YEARESID, NACE3D, ISCO4D, NACE2J2D, HATLEVEL, HATFIELD, HATYEAR, NACEPR2D, ISCOPR3D, EDUCFED4, EDUCLEV4 |
SEX, YEARBIR, PASSBIR, AGE, CITIZENSHIP, HHSPOU, HHFATH, HHMOTH, INCGROSS, Register |
18.3.3. Description of data collection and reference period for INCGROSS variable
See table 18.3.3 in annex for detailed information.
18.3.4. Description of percentiles and bands used for INCGROSS variable
See table 18.3.4 in annex for detailed information.
18.4. Data validation
Member States shall transmit to the Commission (Eurostat) quarterly and annual datasets with pre-checked microdata that comply with validation rules according to the specification of variables for their coding and filter conditions set out in Annex I of the Regulation 2019/2240. Member States and the Commission shall agree on additional validation rules that shall be fulfilled as a condition for transmitted data to be accepted.
Arithmetic and qualitative controls are used in the validation process, including comparison with other data. Before data dissemination, the internal coherence of the data is checked.
18.5. Data compilation
Not requested for the LFS quality report.
18.5.1. Imputation - rate
Please note that in the Annex file the sheet related to this concept has a slightly different title, 18.5.1. ‘Imputation - rate (item non-response)'.
Non of the variables with item non-response are imputed.
18.5.1.1. Editing and imputation process for INCGROSS variable
There are no imputations made for INCGROSS
18.5.2. Brief description of the method of calculating the quarterly core weights
| Brief description of the method of calculating the quarterly core weights |
Is the sample population in private households expanded to the reference population in private households? (Y/N) |
If No, please explain which population is used as reference population |
Gender is used in weighting (Y/N) |
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)? |
Which regional breakdown is used in the weighting (e.g. NUTS 3)? |
Other weighting dimensions |
|---|---|---|---|---|---|---|
| Due to the mentioned stratification, the strata are weighted separately: |
N |
Individuals |
Y |
15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-74, 75-89 |
NUTS2 |
NA |
18.5.3. Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables)
| Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables) |
Gender is used in weighting (Y/N) |
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)? |
Which regional breakdown is used in the weighting (e.g. NUTS3)? |
Other weighting dimensions |
|---|---|---|---|---|
| The yearly weights are calculated as one fourth of the qarterly weights. |
Y |
15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-74, 75-89 |
NUTS2 |
NA |
18.5.4. Brief description of the method of calculating the weights for households
|
18.6. Adjustment
Not requested for the LFS quality report.
18.6.1. Seasonal adjustment
| Do you apply any seasonal adjustment to the LFS Series? (Y/N) |
If Yes, is your adopted methodology compliant with the ESS guidelines on seasonal adjustment? (ref. ESS guidelines on seasonal adjustment - Products Manuals and Guidelines - Eurostat (europa.eu) (Y/N) |
If Yes, are you compliant with the Eurostat/ECB recommendation on Jdemetra+ as software for conducting seasonal adjustment of official statistics. (weblink) (Y/N) |
If Not, please provide a description of the used methods and tools |
|---|---|---|---|
| Y |
Y |
Y |
Method = X12-Arima Tool = JDemetra+ |
| The EU Labor Force Survey (EU-LFS) is the largest European interview-based sample survey. The unit of the Danish LFS is persons and the sample is based on a quarterly sample of the Danish population between the ages of 15 and 89. Its main statistical objective is to classify the population of working age (15 years and over) into three mutually exclusive and exhaustive groups: employed persons, unemployed persons, which together represent the ‘labour force’, and the people outside the labour force. Members of the household are interviewed in the main respondents' fourth and last wave. Household members are derived from registers as persons belonging to the same familiy.
|
7 September 2026
Labour market status: The main variable in the Labour Force Survey is the labour market status of the population. The survey classifies people into two main categories: people in the labour force and people outside the labour force. Furthermore, people in the labour force are categorized as either employed or unemployed. Conscripts are considered employed.
The classification of respondents is based on their labour market status and follows EU definitions and recommendations from the International Labour Organization (ILO) definitions: Every respondent is interviewed about one specific reference week. All questions on work, working hours, unemployment etc. relate to this specific week.
Unemployed: Unemployed are all people without employment, who have actively been looking for work in the past four weeks prior to the reference week and who are able to begin a job within two weeks after the reference week ends. Active job-search methods include contact with a public employment office, applications to employers, contact with friends, relatives or trade unions, or for example studying or answering advertisements in newspapers or journals. Looking for permits, licencs, financial resources, land, premises or equipment for potential self-employment are also considered as active job search.
Unemployment rate: The unemployment rate is the number of unemployed persons compared to the number of persons in the same group of age in the labour force (employed and unemployed).
Employed: Employed are all people, who in the reference week worked for payment or worked as self-employed or family workers for at least one hour. People temporarily absent perhaps due to vacation, illness, or maternity leave are considered to be employed.
Employment rate: The employment rate is the number of employed persons compared to the number of persons in the same group of age in the population. Economic activity rate: The number of individuals in the labor force (employed and unemployed) as a proportion of a given population group
Weighting method: The way in which the sample is weighted to the entire population, in order to make the results as representative as possible. It is always weighted figures that are being published. The method of weighting practically means that each person participating in the LFS gets his or her own weight and hereby represents a specific sample of the population with regards to sex and age. The method of weighting has been revised several times over the years (read more under Documentation on methodology. Person: 15-89 years old. Reference week: The specific week that the respondent is asked about. Whether you are employed or LFS unemployed, how many hours you have worked during the week etc., is related to the specific reference week. The date of the interview can be up to four weeks after the reference week, typically 1-2 weeks after. There are 13 reference weeks per quarter.
Member of the household are interviewed in the main respondents' fourth and last wave. Household members are derived from registers as persons belonging to the same familiy.
The data collection is carried out for each Member State for a sample of observation units constituted by private households or by persons belonging to private households who have their usual residence in Denmark
The statistical population consists of all persons having their usual residence in private households in Denmark.
Not requested for the LFS quality report.
The measured observations refer to quarters
Not requested for the LFS quality report.
The LFS produces different indicators with different measures: Numbers and Percentages
Not requested for the LFS quality report.
Data for the LFS is a mix of survey data and data from administrative and statistical registers.
First release, quarterly (4x), yearly (1x), ad hoc module results (1x)
National standard: Quarterly
See table 14.1 in annex for detailed information.
See section 15.1.2. Divergence of national concepts from European concepts
Break in Series from 2023 to 2024 to be flagged: In Q4 2023 the data collection period has been increased from two weeks to four weeks – thus giving respondents a bit more time to respond to the questionnaire. This was done to combat falling response rates. Furthermore, this has resulted in a greater number of interviews, but the interviews are not evenly distributed across labour market statuses. There are lager increases in the response rates of employed and unemployed persons, especially younger persons have been more inclined to respond. This is not neutralized completely in the calibration of weights, therefore it shows up in especially the main unemployment indicator as a data break.
Nationally, the break has been handled as a seasonal outlier and the data break does not affect the seasonally adjusted numbers to any large extent.
There has been data-related changes affecting comparability. The changes are not significant enough to be flaged but there is a break in the quarterly data series for LOOKOJ in Q2 and Q3 2024 as well as in GALI in Q1 2024.
See sections below and the table P15.2.3. in annex for detailed information.
