1.1. Contact organisation
Statistics Estonia
1.2. Contact organisation unit
Population and Social Statistics Department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
51 Tatari Str, 10134 Tallinn, Estonia
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
9 June 2025
2.2. Metadata last posted
9 June 2025
2.3. Metadata last update
9 June 2025
3.1. Data description
|
Pre-filled example:
The EU Labour Force Survey (EU-LFS) is the largest European household sample survey. 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.
Country can modify or add more information.
|
3.2. Classification system
- Nomenclature of territorial units for statistics (NUTS)
- Statistical classification of economic activities (NACE Rev. 2)
- International Standard Classification of Occupations (ISCO 08)
- International Standard Classification of Education (ISCED 2011)
- Classification of fields of education and training 2013
- Classification of Ethnicities 2011
- International Standard Codes for the Representation of the Names of Countries (ISO 3166)
- Codes for the Representation of Names of Languages (ISO 639-2)
3.3. Coverage - sector
Geographical: Whole country.
Population groups: The target population comprises persons living in private households aged 15 and older with permanent residence in Estonia, i.e. the people who have lived or intend to live in Estonia for more than one year.
3.3.1. Coverage
Individuals living in private households in Estonia.
3.3.2. Inclusion/exclusion criteria for members of the household
Persons included in the household are members of the household. A household may also consist of one member only.
When a person regularly lives in more than one dwelling, the dwelling where one spends the majority of the year is taken as one’s place of usual residence. It applies for example for persons with main and second homes, or for children alternating between two places of residence or for persons living outside the family home for an extended period of time for the purpose of work.
3.3.3. Questions relating to labour status are put to all persons aged
15-89
3.4. Statistical concepts and definitions
Economically inactive population / outside of labour force – persons who do not wish or are not able to work.
Employed – a person who during the reference period:
- worked at least one hour and was paid as a wage earner, entrepreneur or freelancer;
- worked without direct payment in a family enterprise or on his/her own farm;
- participated in work-related training;
- was temporarily absent from work due to holidays, illness, pregnancy and maternity leave or work-related training;
- was on child care leave and received or had the right to receive work-related income or (parental) benefits or was to remain on child care leave presumably for less than three months;
- was temporarily absent from work for other reasons and the presumable leave period was less than three months;
- was a seasonal worker outside the work season if he/she continued to regularly fulfil work-related tasks or responsibilities (excl. legal or administrative responsibilities);
- produced agricultural products, of which the main share was meant for sale or exchange.
Employment rate – the share of the employed in working-age population.
Household – a group of people who live in a common dwelling (at the same address) and share joint financial and/or food resources. Persons included in the household are members of the household. A household may also consist of one member only.
Inactive persons, or persons not included in the labour force – persons who belong to one of the following categories:
- persons aged under 15 (in full years, as at the end of the survey week);
- persons aged 89 and older (in full years, as at the end of the survey week);
- persons aged 15–89 (in full years, as at the end of the survey week) who were neither employed nor unemployed, based on the definitions of employment and unemployment given in the previous points.
Labour force participation rate / activity rate – the share of the labour force (total number of the employed and unemployed) in working-age population.
Underemployed – a person who works part-time, but would like to work more and is available for additional work (within two weeks).
Unemployed – a person who fulfils the following three conditions:
- is without work (does not work anywhere during the survey week and is not temporarily absent from work);
- is currently (within two weeks) available for work if there was work;
- is actively seeking work.
Unemployment rate – the share of the unemployed in the labour force.
3.4.1. Household concept
Shared dwelling and resources
3.4.2. Definition of household for the EU-LFS
A household is a group of people who live in a common dwelling (at the same address) and share joint financial and/or food resources.
3.4.3. Population concept
Usual residence (12 months).
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 |
|
| Usual residence (12 months) |
Primary/secondary students and persons working away from family home during the week but returning to family home for weekends always have family home as usual residence. |
Tertiary students can also consider their family home as their usual residence in case they benefit from the household income and are not usual resident of any other private household |
Family home (if they share income and family ties are kept) |
Family home |
Children alternating two places of residence and spending an equal amount of time with both guardians/parents can also have the place of usual residence of the legal guardian who receives the child benefits (if applicable) or the place of residence of the legal guardian who contributes more towards the child-related costs |
3.5. Statistical unit
The data collection shall be carried out in 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 that Member State.
3.6. Statistical population
The statistical population shall consist of all persons having their usual residence in private households in each Member State.
3.7. Reference area
Not requested for the LFS quality report.
3.8. Coverage - Time
Data is available from 1989.
3.9. Base period
Not requested for the LFS quality report.
The LFS produces different indicators with different measures:
- Numbers;
- Percentages.
- Month
- Quarter
- Year
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:
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.
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 dissemination of data collected for the purpose of producing official statistics is guided by the requirements provided for in § 32, § 34, § 35, § 38 of the Official Statistics Act.
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
Pre-filled example for the EU level.
(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:
Notifications about the dissemination of statistics are published in the release calendar, which is available on the website (see p 8.2). Every year on 1 October, the release times of the statistical database, news releases, main indicators by IMF SDDS and publications for the following year are announced in the release calendar (in the case of publications – the release month).
8.2. Release calendar access
National realease calendar access.
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:
All users have been granted equal access to official statistics: dissemination dates of official statistics are announced in advance and no user category (incl. Eurostat, state authorities and mass media) is provided access to official statistics before other users. Official statistics are first published in the statistical database. If there is also a news release, it is published simultaneously with data in the statistical database. Official statistics are available on the website at 8:00 a.m. on the date announced in the release calendar.
Quarterly (4x), yearly (1x), ad hoc module results (1x)
10.1. Dissemination format - News release
Quarterly /yearly press releases are published, Y2024/Q4Y2024 press release.
10.2. Dissemination format - Publications
No regular publications.
10.3. Dissemination format - online database
10.3.1. Data tables - consultations
Not requested for the LFS quality report.
10.3.2. Web link to 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
Questionnaire, methodological explanations
10.3.5. Further assistance available to users
Further assistance available via phone or email
10.4. Dissemination format - microdata access
Access to microdata and anonymisation of microdata are regulated by Statistics Estonia’s procedure for dissemination of confidential data for scientific purposes
10.4.1. Accessibility to EU-LFS national microdata (Y/N)
Y
10.4.2. Who is entitled to the access (researchers, firms, institutions)?
Research institutions
10.4.3. Conditions of access to data
Access to microdata and anonymisation of microdata are regulated by Statistics Estonia’s procedure for dissemination of confidential data for scientific purposes.
10.4.4. Accompanying information to data
Questionnaires, metadata on variables and classifications, data base description
10.4.5. Further assistance available to users
Further assistance available via phone and 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 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
- Estonian Labour Force Survey methodology
- Changes in the methodology of Estonian Labour Force Survey.
10.7. Quality management - documentation
Links to Quality documentation.
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
The survey serves as a basis for the analysis of changes in the labour market, which is used mainly by different ministries, universities and research organisations. At the European Union level, the data are used to make comparisons between member states. The main representative of the public interest is the Ministry of Social Affairs. In addition to the Ministry of Social Affairs survey data are also used by Ministry of Education and Research, Ministry of Economic Affairs and Communications, University of Tartu, University of Tallinn, and Bank of Estonia.
12.2. Relevance - User Satisfaction
Not requested for the LFS quality report.
12.3. Completeness
The data are complete and correspond to the data composition requirements prescribed by the European Commission regulation on labour force survey statistics.
12.3.1. Data completeness - rate
Not requested for the LFS quality report.
12.3.2. NUTS level of detail
NUTS 3,4,5
12.3.2.1. Regional level of an individual record (person) in the national data set
NUTS 5 (rural municipality/town)
12.3.2.2. Lowest regional level of the results published by NSI
NUTS 4 (county)
12.3.2.3. Lowest regional level of the results delivered to researchers by NSI
NUTS 4 (county)
13.1. Accuracy - overall
Not requested for the LFS quality report.
13.2. Sampling error
.
13.2.1. Sampling error - indicators
Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)
13.2.1.1. Coefficient of variation (CV) Annual estimates %
References to Annex File.
13.2.1.2. Coefficient of variation (CV) Annual estimates at NUTS-2 Level %
References to Annex File.
13.2.1.3. Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The denominator of the employment rate is treated as a population figure without sample variance.
13.2.1.4. Reference on software used
R package srvyr.
13.2.1.5. Reference on method of estimation
Taylor expansion method.
13.3. Non-sampling error
Not requested for the LFS quality report.
13.3.1. Coverage error
References to Annex File.
13.3.1.1. Over-coverage - rate
See in the 13.3.1. Coverage error section in Annex.
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 in the 13.3.1. Coverage error section in Annex.
13.3.1.4. Misclassification errors –description of the main misclassification problems encountered in collecting the data and the methods used to process misclassifications
References to Annex File.
13.3.2. Measurement error
See below.
13.3.2.1. Errors due to the media (questionnaire)
References to Annex File.
13.3.2.2. Main methods of reducing measurement errors
References to Annex File.
13.3.3. Non response error
Not requested for the LFS quality report.
13.3.3.1. Unit non-response - rate
See below.
13.3.3.1.1. Methods used for adjustments for statistical unit non-response
References to Annex File.
13.3.3.1.2. Non-response rates. Annual averages (% of the theoretical yearly sample)
References to Annex File.
13.3.3.1.2.1. Non-response rates. Annual averages (% of the theoretical yearly sample) – NUTS-2 level
References to Annex File.
13.3.3.1.3. Units who did not participate in the survey
References to Annex File.
13.3.3.2. Item non-response - rate
References to Annex File.
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)
References to Annex File.
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)
References to Annex File.
13.3.3.2.3. Item non-response for INCGROSS variable
References to Annex File.
13.3.4. Processing error
NA
13.3.4.1. Editing and imputation process
References to Annex File.
13.3.5. Model assumption error
Not requested for the LFS quality report.
14.1. Timeliness
References to Annex File.
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
The data have been published at the time announced in the release calendar.
14.2.1. Punctuality - delivery and publication
Not requested for the LFS quality report.
15.1. Comparability - geographical
The data are comparable with the data of other European Union countries.
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
| European concept or National proxy concept used) List all concepts where any divergences can be found |
|
|
|---|---|---|
| Is there any divergence between the national and European concepts for the following characteristics? |
(Y/N) |
Give a description of difference and provide an assessment of the impact of the divergence on the statistics |
| Definition of resident population (*) |
N |
NA |
| Identification of the main job (*) |
N |
NA |
| Employment |
N |
NA |
| Unemployment |
N |
NA |
15.2. Comparability - over time
Statistics Estonia conducted the first Labour Force Survey at the beginning of 1995 (ELFS 95). In 1997–1999, the survey was conducted in the 2nd quarter. Starting from the year 2000, the Labour Force Survey is a continuous survey providing quarterly and annual results.
In 2021, two new tables were added where previously published indicators (starting from 2018) have been recalculated using the new methodology and weights.
In the other tables, there is a break in the time series between 2020 and 2021. Starting from 2021, the published indicators have been compiled according to a new methodology.
15.2.1. Length of comparable time series
2021–
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)
References to Annex File.
15.2.3. Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
References to Annex File.
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 main differences between the employment definitions of Estonian LFS and ESA2010 are the following: |
For using in National Accounts, the Estonian LFS data is adjusted as much as possible to ESA2010 definition i.e. conscripts are included to employment and residents who are working abroad or in the extra-territorial organisations are excluded from employment. This means that LFS data used by National Accounts deviate from the ESA2010 definitions only by not including the foreign workers and volunteers (these groups are not measured in Estonian LFS). |
As the result of including conscripts and excluding residents who are working abroad or in the extra-territorial organisations the difference of total employment between LFS 2022 (700,0 thousands) and National Accounts (703,3 thousands) was 0,5% in 2023. |
|
| Total employment by NACE |
See row "Total employment" |
See row "Total employment" |
See row "Total employment" |
See row "Total employment" |
| Number of hours worked |
See row "Total employment" |
See row "Total employment" |
See row "Total employment" |
See row "Total employment" |
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) |
| Y |
N |
N |
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 |
The LFS data includes total employment (employees, employers, own-account workers, unpaid family workers). It is not relevant from the point of view of the survey whether the job is officially registered or not. All persons who worked at least one hour in the reference week are considered to have been employed. However, it is also possible to extract only employees from the LFS data. The Business statistics data (wages statistics) includes all employees working under employment contract, service contract and Public Service Act. |
The LFS is a sample survey. Data are collected from individuals. |
LFS 2023 employees (annual average, thousands) - 622,1 Wages 2023 employees (annual average, thousands) - 604,1 Difference -2.9% Total difference between LFS and wages statistics is significantly smaller than in previous years now the wages statistics employment is based on administrative data. |
|
| Total employment by NACE |
See row "Total employment" |
See row "Total employment" |
|
See row "Total employment" |
| Number of hours worked |
In the LFS hours usually worked (the typical length of a working week over a longer period of time) and hours actually worked (hours worked in the reference week) are collected. Data are published as weekly hours. |
NA |
NA |
na |
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 Estonian LFS unemployment data includes persons aged 15–74 unemployed according to ILO definition. The registered unemployment data of the Unemployment Insurance Fund includes persons aged 16 to pension age (in 2023: 64,5 years; starting from 2017, the pension age is gradually increasing, reaching 65 years of age by 2026) registered at the state employment offices. |
The LFS data are collected by means of sample survey, i.e. data are collected from only a part of the population. |
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) |
| UNA |
UNA |
UNA |
UMA |
UNA |
UNA |
15.3.7. Comparability and deviation for the INCGROSS variable
References to Annex File.
15.4. Coherence - internal
Not requested for the LFS quality report.
References to Annex File.
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.
References to Annex File.
16.2. Duration of the interview by Final Sampling Unit
References to Annex File.
17.1. Data revision - policy
The data revision policy and notification of corrections are described in the section Principles of dissemination of official statistics of the website of Statistics Estonia.
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
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
Microdata from survey and administrative sources
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 |
|---|---|---|---|---|---|
| The sampling design is a stratified systematic sampling of individuals, whose households are included in the sample. |
A list of 15 and older permanent residents of Estonia compiled based on the list of residents (statistical register of population). |
Sampling frame is updated approx. 15 days before each reference quarter |
NA |
Individual (all household members are interviewed) Sampling takes place approximately 15 days before each quarter |
|
18.1.2. Sampling design & Procedure method
|
18.1.3. Yearly sample size & Sampling rate
References to Annex File.
18.1.4. Quarterly sample size & Sampling rate
References to Annex File.
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 |
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? |
|---|---|---|
| Data collection methods are CAWI (Computer-assisted web interviewing) and CATI (Computer Assisted Telephone Interviewing). CATI interviews are conducted by interviewers of the Interviewers Network Department of Statistics Estonia. The interviewing is normally done during the week immediately following the reference week but never later than during two weeks following the reference week. |
N |
VVIS |
18.3.1. Final sampling unit collected by interviewing technique (%)
References to Annex File.
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 |
EDUCFED4 |
CITIZENSHIP |
|
|
|
|
|
|
|
|
*In case of non-core variables in the EU-LFS, different percentages of imputation may come from administrative data.
18.3.3. Description of data collection and reference period for INCGROSS variable
References to Annex File.
18.3.4. Description of percentiles and bands used for INCGROSS variable
References to Annex File.
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
References to Annex File. Please note that in the Annex file the sheet related to this concept has a slightly different title, ‘Imputation - rate (item non-response)'.
18.5.1.1. Editing and imputation process for INCGROSS variable
References to Annex File.
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 |
|---|---|---|---|---|---|---|
|
The weights are formed in a sequence of steps. A weight resulting from the previous step is multiplied by the correction factor calculated at the current step. The correction factors are scaled in such a way that their sample average is unity at each step. As a result, the final weight is a product of the initial weight and correction factors. As a stratified sampling is used on the first step of sample formation, first the initial weight that is inversely proportional to the inclusion probability in each strata is calculated. For non-response adjustment the non-response correction factors are computed. The response homogenity groups of reasonably uniform size of sampled households are formed on the basis of the place of residence of the household according to the non-response rate in the region. Within each group the correction factor is inversely proportional to the overall response rate in the region. In the next step the weights are calibrated so that they produce exact population numbers in certain subgroups known from demographic data (excluding institutional population). For working age persons the subgroups by sex, age (5-year age groups), the place of residence (urban/rural area, 15 counties (LAU) and the capital city), nationality (Estonian/non-Estonian) and educational level (primary/secondary/tertiary) are considered. For this purpose the linear consistent weighting method is applied. For non-working age persons the non-response adjusted household weights are calibrated by sex and 5-year age groups. |
N |
The sample population aged 15+ (excluding institutional households) is expanded to the total population aged 15+ (excluding institutional households).
The population aged 0-14 (excluding institutional households) is expanded to the total population aged 0-14 (excluding institutional households). |
Y |
5-year groups: 0-4, 5-9, 10-14, 15-19, … , 70-74, 75-79, 80-84, 85+ |
LAU |
Urban/rural area, ethnic nationality (Estonian/non-Estonian), educational level (primary/seconday/tertiary) |
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 |
|---|---|---|---|---|
| Yearly weights are calculated by dividing the quarterly weights by 4. |
NA |
NA |
NA |
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 |
|---|---|---|---|
| N |
NA |
NA |
NA |
|
Pre-filled example:
The EU Labour Force Survey (EU-LFS) is the largest European household sample survey. 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.
Country can modify or add more information.
|
9 June 2025
Economically inactive population / outside of labour force – persons who do not wish or are not able to work.
Employed – a person who during the reference period:
- worked at least one hour and was paid as a wage earner, entrepreneur or freelancer;
- worked without direct payment in a family enterprise or on his/her own farm;
- participated in work-related training;
- was temporarily absent from work due to holidays, illness, pregnancy and maternity leave or work-related training;
- was on child care leave and received or had the right to receive work-related income or (parental) benefits or was to remain on child care leave presumably for less than three months;
- was temporarily absent from work for other reasons and the presumable leave period was less than three months;
- was a seasonal worker outside the work season if he/she continued to regularly fulfil work-related tasks or responsibilities (excl. legal or administrative responsibilities);
- produced agricultural products, of which the main share was meant for sale or exchange.
Employment rate – the share of the employed in working-age population.
Household – a group of people who live in a common dwelling (at the same address) and share joint financial and/or food resources. Persons included in the household are members of the household. A household may also consist of one member only.
Inactive persons, or persons not included in the labour force – persons who belong to one of the following categories:
- persons aged under 15 (in full years, as at the end of the survey week);
- persons aged 89 and older (in full years, as at the end of the survey week);
- persons aged 15–89 (in full years, as at the end of the survey week) who were neither employed nor unemployed, based on the definitions of employment and unemployment given in the previous points.
Labour force participation rate / activity rate – the share of the labour force (total number of the employed and unemployed) in working-age population.
Underemployed – a person who works part-time, but would like to work more and is available for additional work (within two weeks).
Unemployed – a person who fulfils the following three conditions:
- is without work (does not work anywhere during the survey week and is not temporarily absent from work);
- is currently (within two weeks) available for work if there was work;
- is actively seeking work.
Unemployment rate – the share of the unemployed in the labour force.
The data collection shall be carried out in 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 that Member State.
The statistical population shall consist of all persons having their usual residence in private households in each Member State.
Not requested for the LFS quality report.
- Month
- Quarter
- Year
Not requested for the LFS quality report.
The LFS produces different indicators with different measures:
- Numbers;
- Percentages.
Not requested for the LFS quality report.
Microdata from survey and administrative sources
Quarterly (4x), yearly (1x), ad hoc module results (1x)
References to Annex File.
The data are comparable with the data of other European Union countries.
Statistics Estonia conducted the first Labour Force Survey at the beginning of 1995 (ELFS 95). In 1997–1999, the survey was conducted in the 2nd quarter. Starting from the year 2000, the Labour Force Survey is a continuous survey providing quarterly and annual results.
In 2021, two new tables were added where previously published indicators (starting from 2018) have been recalculated using the new methodology and weights.
In the other tables, there is a break in the time series between 2020 and 2021. Starting from 2021, the published indicators have been compiled according to a new methodology.
