Employment and unemployment (Labour force survey) (employ)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: STATBEL


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

STATBEL
1.2. Contact organisation unit

Thematic Division Society
1.5. Contact mail address

North Gate - Koning Albert II-laan 16 - 1000 Brussels


2. Metadata update Top
2.1. Metadata last certified

9 December 2025
2.2. Metadata last posted

9 December 2025
2.3. Metadata last update

9 December 2025


3. Statistical presentation Top
3.1. Data description

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.

On a national level, the survey is usually referred to as Enquête naar de Arbeidskrachten (Dutch) or Enquête sur les Forces de Travail (French). 

Abbreviation

Explanation

CV

Coefficient of variation (or relative standard error)

Y/N

Yes / No

H/P

Households/Persons

M?

Member State doesn’t know

NA

Not applicable/ Not relevant

UNA

Information unavailable

NR

Non-response: Member State doesn’t answer to Eurostat request for information. Blank is allowed only in boxes with comments

LFS

Labour Force Survey

NUTS

Nomenclature of territorial units for statistics or corresponding statistical regions in the EFTA and candidates countries

 
3.2. Classification system

The following common concepts and definitions apply under the Integrated European Social Statistics (IESS):

  • the International Standard Classification of Education (ISCED) 2011 published in the following breakdowns: low (ISCED levels 0-2: no formal education, primary education or lower secondary education), medium (ISCED levels 3-4: upper secondary or post-secondary non-tertiary education) and high (ISCED levels 5-6: tertiary programmes which normally need a successful completion of ISCED 3 or 4, or second-stage tertiary education leading to an advanced research qualification);
  • the International Standard Classification for Occupation ISCO-08 at the 4-digit level;
  • the Classification of Economic Activities (NACE Rev.2-2008), at 5-digit level;
  • the Common classification of territorial units for statistics (NUTS 2 level);
  • the SCL - Geographical code list;
3.3. Coverage - sector

Data on employees from all economic sectors and all size classes are included. 
3.3.1. Coverage

Individuals living in private households, in Belgium. 
3.3.2. Inclusion/exclusion criteria for members of the household

Households, all members of which are 90 or older, are excluded before the sample is drawn.
3.3.3. Questions relating to labour status are put to all persons aged

15-89
3.4. Statistical concepts and definitions

Statistical concepts and definitions for EU-LFS are specified in Regulation (EU) 2019/1700, Commission Implementing Regulation (EU) 2019/2240  , and Commission Implementing Regulation (EU) 2019/2242.

Further details provided below. 
3.4.1. Household concept

Housekeeping 
3.4.2. Definition of household for the LFS

Members living together in the same dwelling, sharing meals and expenditures (criteria not explicitly checked in sampling frame and during interview)
3.4.3. Population concept

Registered population, i.e. all citizens living at Belgian territory. This means that the source of the sample is the central population register. This register includes all private households and their current members residing officially in the territory. Persons living in collective households and in institutions are excluded from the target population. During fieldwork the household composition can be changed by the household, so we end up with the de facto household composition. People registered there can be removed, people not registered there (or not even registered in Belgium) can be added.
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
 

 Family home

Family home 

Family home 

Familiy home 

Family home 
3.5. Statistical unit

Statistical units are private households and all persons living in these households who have usual residence in the Member State.

 
3.6. Statistical population

The statistical population consist of all persons having their usual residence in private households in Belgium. 
3.7. Reference area

Not requested for the LFS quality report.
3.8. Coverage - Time

2023 (all 52 reference weeks)

 
3.9. Base period

Not requested for the LFS quality report.


4. Unit of measure Top

A large range of indicators are produced with different measures: 

  • numbers (e.g. employed persons, unemployed persons, employees with a temporary working contract,... ).
  • rates or percentages (e.g. employment rate, NEET, ... ).
  • averages (e.g. average working time).
  • currency (e.g. Gross monthly pay from the main job).

 


5. Reference Period Top

The main reference period is the reference week: most questions refer to the situation from the reference week (e.g. ILO status, number of hours worked, etc... ).

Additionally, there are a number of questions that focus on the reference month, or more specifically: the reference week and the three weeks precedeing the reference week (e.g. irregular working hours, participation in education last 4 weeks). 

Finally, there are a number of questions that focus on the past 12 months (e.g. participation in education last 12 months).   

Data are processed on a quarterly and yearly basis, which means that the results are representative for all reference weeks of that particular quarter or year. 


6. Institutional Mandate Top
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:

Participation is obligatory by national law: Arrêté royal relatif à l'organisation d'une enquête par sondage sur les forces de travail du 10 janvier 1999, tel que modifié par l’Arrêté royal du 25 mars 2016 - MB 12 04 2016. 
6.2. Institutional Mandate - data sharing

Pre-filled example for the EU level to describe the arrangements, procedures or agreements to facilitate data sharing practice:

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. Confidentiality Top
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:

Law of 4th of July 1962 regarding offical statistics and protection of data: Justel databank (fgov.be)

Privacy policy explained on our site: https://statbel.fgov.be/en/about-statbel/privacy/privacy-gdpr

 
7.2. Confidentiality - data treatment

According to Statbel procedures, data treatment is strictly separated from data collection at Statbel. The data processing team does not have access to personal information of the respondents that would allow an identification. Linkages to register information is always done with a pseudonymized ID-variable. 

At the Belgian level, the dissemination of pseudonymised microdata is strictly regulated. The procedure is described on the website. In order to get the permission of Statbel's Data Protection Officer team and finally as data controller, Statbel's director-general, the third party should follow a procedure and sufficiently motivate the proportionality and relevance of its request. The more confidential the information requested, the better the need for it should be motivated.

Access to microdata for scientific purposes may be granted on the  basis of Commission Regulation 557/2013 and Regulation 223/2009 of  the European Parliament and the Council on European statistics.


8. Release policy Top
8.1. Release calendar

EU level:

(1) the Member States shall transmit pre‐checked microdata without direct identifiers, according to the following two‐step procedure:

  • 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;
  • 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: 

Quarterly results on the main quarterly indicators and the labour market flows are released around twelve or thirtheen weeks after the end of reference quarter.

For 2023 the quarterly results were published on the following dates: 

  • Q1: 14 June 2023
  • Q2: 14 September 2023
  • Q3: 14 December 2023
  • Q4: 13 March 2024

Yearly results were published on different dates. A first set of main indicators was release together with the results of the fourth quarter on 13 March 2024. More detailed results, on different topics were published on 26, 27 and 28 March 2024. 

Results of the ad hoc module 2023 on Pensions and labour market participation. will be released in July 2024.  

Microdata for recurrent users were disseminated on the dates of national publications. 
8.2. Release calendar access

Please refer to the Release calendar - Eurostat (europa.eu) publicly available on the Eurostat’s website.

Statbel release calendar is published on the website.
8.3. Release policy - user access

EU level:

In line with the Community legal framework and the European Statistics Code of Practice, Eurostat disseminates European statistics on Eurostat's website (see section 10 - 'Accessibility and clarity'), respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.

Additional information about microdata access is available on Labour force survey - Eurostat (europa.eu)

 

National level: 

The same policiy on equal treatment of all types of users is applied on a national level. Users can access all standard tables and open data on Statbel's website.


9. Frequency of dissemination Top

Quarterly (4x), yearly (1x), ad hoc module results (1x)


10. Accessibility and clarity Top
10.1. Dissemination format - News release

Press releases are published at least quarterly about the main indicators and the flow statistics, yearly results and results of the ad hoc modules. 

Occasionally we put our LFS data in the spotlight, for instance on Labour Day, Women's Day, etc...
10.2. Dissemination format - Publications

Publications are available in different formats such as press releases, downloadable excel tables, our online database be.stat.  
10.3. Dissemination format - online database

Online database Be.Stat available here.
10.3.1. Data tables - consultations

Not requested for the LFS quality report.
10.3.2. Web link to national methodological publication

Link to the national web page (national language(s)):
10.3.3. Conditions of access to data

Standard aggregated tables are available on our website http://statbel.fgov.be

Users can also make their own tables via our dynamic application be.STAT.
Other aggregated data can be made available on demand in excel-format without special conditions or costs.

Pseudonymised microdata can be delivered (with confidentiality contract). The procedure can be found on our website: https://statbel.fgov.be/en/microdata-research. Data are mostly free of charge if concerns the standard microdata products. If additional variables are requested, a cost of 500 euro is charged. 
10.3.4. Accompanying information to data

Metadata, questionnaires and methodological information can be found on our website, in different languages: 

English: https://statbel.fgov.be/en/themes/work-training/labour-market/employment-and-unemployment

Dutch: https://statbel.fgov.be/nl/themas/werk-opleiding/arbeidsmarkt/werkgelegenheid-en-werkloosheid

French: https://statbel.fgov.be/fr/themes/emploi-formation/marche-du-travail/emploi-et-chomage

 
10.3.5. Further assistance available to users

We have introduced a FAQ page on our website: https://statbel.fgov.be/nl/themas/werk-opleiding/arbeidsmarkt/faq

Additional information and specific questions can be sent to our contact centre or to statbel@economie.fgov.be. If the Statbel contact center can not help, the question will be dispached to the LFS team. 

For media and journalists, a specific address is in use: statpress@economie.fgov.be. 

 

 
10.4. Dissemination format - microdata access

Microdata for research available. More information about the application procedure on the Statbel website. 
10.4.1. Accessibility to LFS national microdata (Y/N)

LFS national microdata are available for researchers, under specific conditions. More information about the application procedure on the Statbel website. 

 
10.4.2. Who is entitled to the access (researchers, firms, institutions)?

(copied from: Microdata for research | Statbel (fgov.be))

 Who can request microdata?

  • Federal public services or public interest bodies subject, with the exception of tax authorities;
  • Regional and community ministerial departments or public interest bodies, with the exception of tax authorities;
  • Provincial or municipal administrations, with the exception of tax authorities;
  • Multilateral organisations of which the Belgian State is a member;
  • All scientific and research institutions that pursue a scientific research goal and are recognised by Statbel as research institutions.

To be recognised as such, the institution must, among others, meet the criteria set out in Article 4 of the Commission Regulation (EU) Nº 557/2013 of 17 June 2013 implementing Regulation (EC) Nº 223/2009 of the European Parliament and of the Council on European Statistics as regards access to confidential data for scientific purposes and repealing Commission Regulation (EC) Nº 831/2002:

  • The institution’s statute, mission or another declaration purpose includes statistical or scientific research as purpose;
  • Based on the lists of publications and research projects, the institution demonstrates its established record and reputation as a body producing quality research and making it publicly available;
  • The institution demonstrates, based on the internal organisational arrangements, that it is independent and autonomous in formulating scientific conclusions and separated from policy areas of the body it belongs to;
  • The institution demonstrates that it takes adequate technical and organisational measures to ensure adequate data security.

 
10.4.3. Conditions of access to data

(copied from: Microdata for research | Statbel (fgov.be))

For what purposes can microdata be requested?

Researchers can request microdata if the data is necessary for their statistical or scientific research. Necessary means that the research is not possible on the basis of global and anonymous data that Statbel disseminates without restrictions via the website https://statbel.fgov.be/en

  • Be.STAT , Statbel's electronic database, allows researchers to create customised tables; 
  • Through Open data , Statbel makes aggregated data available at a fairly detailed level.

The purpose for which the data is requested is limited to statistical and scientific research. However, this goal may be interpreted broadly. Policy preparatory research or research by private institutions are also eligible, provided that the processing happens independently, transparently and by making use of scientific methods. The results of the research should also be made public.  

The result of the processing must consist of global and anonymous statistics and research reports that may not have any individual impact on the citizens or enterprises concerned. Of course, these published global and anonymous results can be freely used afterwards for non-statistical or non-scientific purposes.   

 
10.4.4. Accompanying information to data

Each microdata dataset is accompagnied by a codebook containing information on the variables and their labels, the use of weights, etc... Questionnaires are also freely available on our website. 
10.4.5. Further assistance available to users

A contact person (statistician) is designated for each microdata request. He or she is responsible for the follow up of the request and remains available for additional information both during the procedure as well as afterwards when using the data. 
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

Methodological papers were published after the 2017 and 2021 reforms: 

The 2017 reform: 

https://statbel.fgov.be/sites/default/files/Over_Statbel_FR/Analyse_eak_2017_nl_20181220.pdf

https://statbel.fgov.be/sites/default/files/Over_Statbel_FR/Analyse_eak_2017_fr_20181220.pdf

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/EN/4_ENG_Arbeidskrachten_web.pdf

The 2021 reform: 

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/NL/Analyse_20_NL_version10.pdf

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/EN/Analyse_20_EN_version6.pdf

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/FR/Analyse_20_FR_version12.pdf

Methodological paper on the methodology for flow statistics: 

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/NL/17_Transities_EAK_NL.pdf

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/FR/17_Transitions_EFT_FR.pdf

https://statbel.fgov.be/sites/default/files/files/documents/Analyse/EN/17_Transitions_LFS_EN.pdf

 

 

 



Annexes:
https://statbel.fgov.be/sites/default/files/files/documents/Analyse/EN/17_Transitions_LFS_EN.pdf
https://statbel.fgov.be/sites/default/files/files/documents/Analyse/FR/17_Transitions_EFT_FR.pdf
https://statbel.fgov.be/sites/default/files/files/documents/Analyse/NL/17_Transities_EAK_NL.pdf
10.7. Quality management - documentation

The quality department is responsible for quality management in cooperation with and in support of the statisticians:

  • Elaboration and updating of quality indicators
  • Describing the different production steps in line with GSBPM
  • Validation of results
  • Metadata maintenance

The department is organized with a service in charge of quality which is consulted when significant changes are made to the production process of a statistic.

Since 2018, and starting with the most “critical” processes the ARIS software programme is used to describe statistical production in line with the BPMN standard (Business Process Model and Notation). The description is made available to the staff. Ultimately, the objective is to describe all existing processes, statistical and non-statistical, and to make the link between these descriptions and the national version of GSBPM.

The process descriptions in ARIS will complement the already existing task lines of the overall planning tool that is used to steer the production of statistics.

Risk management is applied at different levels:

  • A risk analysis has been carried out for the strategic objectives and action plans have been set out to reduce residual risks;
  • Risk analyses are carried out for operational processes and actions are identified to reduce residual risks.

 Links to public documents:

  1. Specific section of the website of Statistics Belgium dedicated to quality.
  2. Code of practice on website Statistics Belgium.


11. Quality management Top
11.1. Quality assurance

Not requested for the LFS quality report.
11.2. Quality management - assessment

Not requested for the LFS quality report.


12. Relevance Top
12.1. Relevance - User Needs

Data are used by a diversity of users: policy makers, other stakeholders, media, academic research, students, general public...

There is a large demand for the Belgian LFS data and the data are used a lot in official studies and reports, for decision making and for scientific research.
12.2. Relevance - User Satisfaction

Not requested for the LFS quality report.
12.3. Completeness

see below
12.3.1. Data completeness - rate

Not requested for the LFS quality report.
12.3.2. NUTS level of detail

see below
12.3.2.1. Regional level of an individual record (person) in the national data set

Municipality level
12.3.2.2. Lowest regional level of the results published by NSI

NUTS 1 (region (gewest / région)) + a limited number of variables on NUTS 2 level.
12.3.2.3. Lowest regional level of the results delivered to researchers by NSI

NUTS 2 (province (provincie /province)) and in a limited cases (for specific uses) NUTS 3 or municipal data.


13. Accuracy Top
13.1. Accuracy - overall

Not requested for the LFS quality report.
13.2. Sampling error

see annex
13.2.1. Sampling error - indicators

see annex
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

Standard error is estimated using the SAS POULPE macro, taking into account sampling design, non-respons correction, calibration procedure and linearization of ratios.
13.2.1.5. Reference on method of estimation

Standard error is estimated using the SAS POULPE macro, taking into account sampling design, non-respons correction, calibration procedure and linearization of ratios
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

see annex
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

References to Annex File.
13.3.4. Processing error

see below
13.3.4.1. Editing and imputation process

References to Annex File.
13.3.4.2. Outliers treatment and other data editing procedures for INCGROSS

References to Annex File.
13.3.5. Model assumption error

Not requested for the LFS quality report.


14. Timeliness and punctuality Top
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

Quarterly and Yearly data have been delivered in time (cfr. deadlines specified in the IESS regulation). 
14.2.1. Punctuality - delivery and publication

Not requested for the LFS quality report.


15. Coherence and comparability Top
15.1. Comparability - geographical

On European level: see below

On national level: 

The survey is carried our under the same conditions in the different regions, which makes the results comparable over the regions. Nevertheless, some small language effects may be present. 
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)

  Y

Definition of resident population (*)

 Y

 We use the Registered population definition in the sampling frame. At the start of the interview, the interviewer verifies with the respondents whether the list of household members as taken from the sampling frame corresponds to the actual situation. Interviewers are instructed to drop household members that no longer live at the given address since at least 6 months (but in practice they sometimes drop household members earlier). Interviewers can also add new members in the household. Some of the most frequently added kind of persons are newborns, a new partner (or a partner from another member of the household), children in co-parenting that are registered at the address of the other parent, needy family members,...

Identification of the main job (*)

N 

 

Employment

N 

 

Unemployment

N 

 In Belgium, unemployment rate is calculated and published for persons aged 15-64 and not 15 + or 15-74 (Eurostat)
15.2. Comparability - over time

A major break has occurred in 2017 due to a change in methodology (introduction of panel design, change of data collection mode, adaption of calibration methodology), see link to methodological paper under 10.6.2. 

A second (but smaller) break occured, for some indicators, in 2021, after a reform of the questionnaire, see link to methodological paper under 10.6.2. 

 
15.2.1. Length of comparable time series
  • For all indicators: from 2021 on. 
  • For most indicators: from 2017 on. 
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

administrative  concept (national  concept) versus ILO concept 

NA results are based on administrative data (data of social security institutions). There are some additions/corrections f.i. for domestic staff, interim work, seamen, students work, undeclared work, … The employment figures based on LFS are without additions or corrections. LFS measures employment on a continuous basis and results can be seen as an average for a certain quarter or year, NA data measure employment on a certain date (end of the quarter).

Since 2021, people who are temporarily unemployed (on lay-ff) on a full-time basis for more than three months, are no longer counted as employed in LFS whereas they stay employed in NA.

higher number of employed persons in national accounts compared to LFS.

  internal notes

Total employment by NACE

administrative concept (national concept) versus ILO concept

NA: administrative data (declaration of the enterprise) LFS: declaration of the respondents + codification by experts. In NA interims are coded in nace2008 78, in LFS in the sector where they were working.

NA data by NACE are of better quality compared to LFS figures

 UNA

Number of hours worked

 administrative concept (national concept) versus ILO concept

NA: based on administrative data about hours paid + corrections. For hours worked of self employed use is made of LFS data. LFS: hours actually worked based on continuous survey (LFS)

 UNA

 UNA
15.3.3. Which is the use of 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 (LFS is used in the calculation of hours worked of self employed persons)

 N

 N

 N
15.3.4. Coherence of 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 total employment for workers in business statistics is calculated based on the number of people working in the enterprise in a limited number of sectors. In LFS it is about the employment of people living in the country in all sectors. 

The total number of self-dependent people as their main profession can not yet be determined in business statistics. 

 Since 2021, people who are temporarily unemployed (on lay-ff) on a full-time basis for more than three months, are no longer counted as employed in LFS whereas they stay employed in business statistics.

 Lay-off has become less frequent from 2022 on. 

 UNA

Total employment by NACE

 The NACE in business statistics has been assigned based on the added value and monitoring by NACE-experts while LFS NACE is an assesment of the activity of the respondent working in the local unit that is recoded by NACE-experts. 

 NACE in LFS is at the local unit, NACE in most business statistics are (currently) at the legal unit level

 Internal analyses have shown that there is some discrepancy, but this is overall rather limited. Most differences arise due to the limited description of the LFS respondents. 

 internal notes

Number of hours worked

 The number of hours worked in business statistics are the number of hours that are paid to the worker. 

  NA

 These data can not be compared

 UNA
15.3.5. Coherence of LFS data with registered unemployment

 

Description of difference in concept

Description of difference in measurement

Give references to description of differences

 ILO concept (LFS) versus administrative concept. There exist different administrative concepts. Here we take into account the persons without work, seeking work and receiving unemployment benefits (concept 'niet -werkende WZ UVW'). These statistics are published by the national employment office. Receiving unemployment benefits is not a condition for being ILO-unemployed.

 Survey versus administrative data. The national employment office publishes figures about persons receiving unemployment benefits which is not a condition for being ILO-unemployed.

 UNA
15.3.6. Assessment of the effect of differences of 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 number of registred unemployed persons who are looking for a job (werkzoekende uitkeringsgerechtigde volledig werklozen, UVW-WZ) is almost equal to the number of ILO unemployed persons but there is a difference in concept and measurement.

Number of registered unemployed persons seeking work (concept niet werkende werkzoekenden) is much higher than the number of ILO unemployed persons because of a difference in measurement.

more ILO unemployed men under 25  years than registered unemployed men (concept 'niet-werkende WZ UVW')

more registered unemployed persons than ILO unemployed persons

more ILO unemployed women under 25 years than registered unemployed men (concept 'niet-werkende WZ UVW')

 more registered unemployed persons than ILO unemployed persons

 UNA
15.3.7. Comparability and deviation for the INCGROSS

References to Annex File.
15.4. Coherence - internal

Not requested for the LFS quality report.


16. Cost and Burden Top

see annex
16.1. Number of staff involved in the LFS in central and regional offices, excluding interviewers. Consider only staff directly employed by the NSI.

Not requested for the LFS quality report.
16.2. Duration of the interview by Final Sampling Unit

see annex


17. Data revision Top
17.1. Data revision - policy

The data revision policy can be found on the website of Statistics Belgium.
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? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF)

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. Statistical processing Top
18.1. Source data

Demographic information (date of birth, sex, geographical information, country of birth, citizenship, etc...) is taken from administrative sources (General Population Register) and all other variables, except INCGROSS, are collected in the survey. 
18.1.1. Sampling design & Procedure frame

 

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

 Two-stage stratified sampling.

 National Population Register (NPR), extended with information from tax and unemployment registers.

 For the primary sampling units, the last update was in September 2020. For the secondary (i.e. final) sampling units, the last update is made one or two months before the start of the quarter.

 Statistical section, or part of a sub-municipality consisting of several statistical sections.

 We select the private household at the dwelling. In case that another household is living in the dwelling, this household will not be interviewed.  

The selection of households is done +- 5 weeks before the start of the quarter. 
18.1.2. Sampling design & Procedure method

First (and intermediate) stage sampling method

  Final stage sampling method

Stratification (variable used)

Number of strata (if strata change quarterly, refer to Q4).

Rotation scheme (2-2-2, 5, 6, etc.)

 

The first stage sampling frame, i.e. the frame, consists of geographic areas, which are either 'statistical sections' or unions of statistical sections within 'statistical letters' or sub-municipalities. Preferably neighbouring sections are joined together, but this is not the rule.  Each PSU must contain a minimum number of eligible private households: if a PSU is sampled in the first stage, it must be possible to select enough households (26 in Brussels Capital Region, and 23 in other sampling strata) to form a 'group of households' (which will be assigned as a whole to an interviewer). There are about 6354 PSUs in the sampling frame, containing 676 households on average; ‘small’ sections only represent 0.15% of the total number of households. The frame of PSUs is stratified by and sorted on some PSU characteristics (for details, see the box headed “Stratification” to the right in this table).

Systematic probability proportional to size sampling (PPS-SYS; where a proxy for the number of eligible private households is used as size measurement) is applied in each first stage sampling stratum. The number of PSU draws or selections in each sampling stratum is fixed in advance, such that 6695 HHs are selected in total per quarter in the second stage. Larger PSUs can be selected more than once, while smaller PSUs are probably not selected.

Important to notice is that each PSU draw, i.e. each 'group of households', is assigned to a reference week immediately after the first stage. The 286 groups of households that are selected in total each quarter, are uniformly spread over the 13 weeks of the quarter (i.e. 22 groups per week).

 

In the second, and final, stage of sampling, the PSUs sampled in stage 1 technically serve as sampling strata.

The number of households selected in stage 2 (the final sampling stage) in a selected PSU equals the number of times the PSU is selected in the first stage times the size of the groups of households to be formed in the PSU (i.e. 26 in the Brussels Capital Region and 23 in the other strata). Basically, simple random sampling (SRS) is applied to select households (SSUs or FSUs) in each selected PSU.

Stratification of private households in the second stage is applied since the first quarter of 2021. Two strata are considered in this stage: households containing at least one 15-74 year old person – called type 1 households –, versus households containing no 15-74 year old, but at least one 75-89 year old person – called type 2 households. If a PSU is selected only once in the first sampling stage, STR-SRS is applied to a frame of eligible households, where eligibility means that a household is of type 1 or type 2 considering household members’ age at the reference Sunday, i.e., the last day of the reference week, which is determined after the first sampling stage. If a PSU is selected more than once, the “groups” of households are selected (by STR-SRS) one after another, where the frame of eligible households is adapted to the specific group (i.e., to its reference week/Sunday), considering that households should be selected for only one group. Each selected “group” of households contains exactly 1 type 2 household; the other 25 (=26–1, in the Brussels-Capital Region) or 22 (=23–1, in the other PSU-strata) are type 1 households.

The new sample of households/individuals selected in each quarter, is called a rotation group (RG).

 

In the first stage of sampling, the PSUs are explicitly stratified by NUTS 2 regions (i.e. provinces, where the Brussels Capital Region and the German community are separate strata). The PSU sampling frame, within each stratum, is further sorted on (1) the quintile of the number of private households in the PSU, (2) the quintile of the unemployment rate in the PSU and (3) the quintile of the average household income in the PSU. This implies implicit stratification on the latter three PSU characteristics within each explicit stratum. Serpentine sorting is applied.

Stratification of private households is applied at sampling stage 2. Two strata are considered in this stage: households containing at least one 15-74 year old person – called type 1 households –, versus households containing no 15-74 year old, but at least one 75-89 year old person – called type 2 households. 

 

12 (explicit) strata at stage 1 in each quarter; the stratification variable is denoted PROV12.

2 strata at stage 2; the stratification variable is denoted HHstrat.

 2-(2)-2
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)

 Wave 1

 Y

 NA

 All except 'HOMEWK', 'TEMPREAS', 'TEMPAGCY' . These variables are collected in all waves.
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?

 

For the first wave the detailed information (related to individuals aged 15 years and over) is collected by means of face-to-face interviews in the 3 or 4 weeks following the week of reference. In households of retired persons, interviews can be conducted by telephone. Exceptionally, from March 2020 until the end of March 2022, due to the Covid-crisis, all interviews in the first wave were done in CATI. From 1 April 2022 CAPI interviews were possible again.


For the 2nd to 4th wave, the data are collected using Web (CAWI) or telephone (CATI). The household itself decides in which mode they want to take the next survey. In case of nonresponse in CAWI, the interviewer tries to convince the household to participate and then the interview might take place in CATI. During the second and following waves, interviewers try to reach only the respondents of the previous wave. The previous non-respondents (for wave n) stay non-respondents (for wave n+1).

If the selected household no longer lives at the specified address, but has moved within the same municipality, it can still participate.

  Y (but limited)

 

 CAPI/CATI/CAWI

Blaise software is used.
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 Yes, please indicate which

registers.

 Y

 incgross, country, region, sex, yearbir, passbir, age, citizenship, countryb, cobfath, cobmoth, yearesid, degurba
18.3.3. Description of data collection and reference period for INCGROSS

References to Annex File.
18.3.4. Description of percentiles and bands used for INCGROSS

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.
18.5.1.1. Editing and imputation process for INCGROSS

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 2-step quarterly weighting model can be formulated as: < IND; STRAT12 × SEX × AGECAT + RG_c; d⁄p ; Lin >.

The third component,  d⁄p, in this formal representation of the weighting model, means that, in step 1, the sampling weights d are corrected using estimated response probabilities p at household level; a random intercept logistic regression model, followed by smoothing, is used to estimate the p.

In step 2, proper calibration is applied to further adjust the corrected weights d/p. The first component, IND, within < > indicates that calibration is at individual level. The second component is a formal expression for the linear structure of the calibration model in step 2, indicating that (1) calibration is to the joint distribution of variables STRAT12, SEX and AGECAT in the population, and (2) the totals of calibrated weights for the RGs involved in each quarterly sample are forced to be proportional to the initial sizes of these RGs (the notation RG_c stands for “contrast constraints between RGs”).  The fourth and last component, Lin, indicates the use of the linear method for calibration.

 Y

 NA

 Y, i.e. through the variable SEX as mentioned to the left.

 Variable AGECAT identifies fifteen 5-year age classes (0-4, 5-9, …, 70-74) and the open ended sixteenth age class 75+.

 Variable STRAT12, which is also the stratification variable in the first sampling stage, corresponds to NUTS 2 level.

 The random intercept logistic regression model used to estimate the households’ response probabilities includes fixed effects variables household type, household origin, STRAT12 and level of urbanisation, and the random effects variable PSU identification. This regression model is applied to each RG separately, for each trimester.
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 2-step weighting model can be formulated as: < IND; STRAT12 × SEX × AGECAT + REGION × SEX × AGECAT* × StatBIT; d⁄p; Lin >. This model is comparable to the quarterly weighting model already explained. The differences are: (1)  application of this model to the wave 1 sub-sample of respondents; (2) calibration to not only the joint distribution of STRAT12, SEX and AGECAT in the population, but also to the joint distribution of REGION, SEX, AGECAT* and StatBIT, estimated as full-sample annual averages from LFS; (3) there are no between-RG balancing (or “contrast”) constraints. The new term REGION × SEX × AGECAT* x StatBIT in the linear structure of the model allows to satisfy the consistency requirements imposed by Eurostat.

Exceptionally, consistency on the level of region has to be dropped because of model convergence issues. In 2021, this was the case for the fourth quarter. Nevertheless, the minimum consistency requirements imposed by Eurostat were still met

 Y, i.e. through the variable SEX as mentioned to the left.

 Variable AGECAT (16 classes) is defined as before; variable AGECAT* identifies 7 age classes 0-15, 15-24, 25-34, 35-44, 45-54, 55-64 and 65+.

 Variable STRAT12 (NUTS 2 level) is as before; variable REGION is NUTS 1 level.

 The regression model to estimate the response probabilities is exactly as for the quarterly weighting model.
18.5.4. Brief description of the method of calculating the weights for households

Brief description of the method of calculating the weights for households

Any external reference for number of households etc.?

Which factors at household level are used in the weighting (number of households, household size, household composition, etc.)

Which factors at individual level are used in the weighting (gender, age, regional breakdown etc.)?

Are the household weights identical for all household members? (Y/N)

No specific household weights are calculated. Weight of reference person is used for estimates on household level 

 NA

 NA

 NA

 NA
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. (ref. http://ec.europa.eu/eurostat/web/ess/-/jdemetra-officially-recommended-as-software-for-the-seasonal-adjustment-of-official-statistics) (Y/N)

If Not, please provide a description of the used methods and tools

 N

 NA

 NA

 NA


19. Comment Top


Related metadata Top


Annexes Top
LFS ANNEX [LFS_QR_Multiple+1.0_upd]