1.1. Contact organisation
National Statistics Office
1.2. Contact organisation unit
Labour Market and Information Society Statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
National Statistics Office,
Lascaris,
Valletta, VLT 2000,
Malta
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
15 June 2025
2.2. Metadata last posted
15 June 2025
2.3. Metadata last update
15 June 2025
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.
|
3.2. Classification system
The EU-LFS uses international classifications and nomenclatures for the country, region, degree of urbanisation, education, occupation, economic activity and professional status.
3.3. Coverage - sector
MT LFS covers all private households which is defined as members living regularly together in the same dwelling, sharing income, household expenditures, food and other essentials for living.
3.3.1. Coverage
Individuals living in private households in Malta.
3.3.2. Inclusion/exclusion criteria for members of the household
Persons who are residing in a private household in Malta for less than a year but have the intention to stay for at least 1 year are included.
Persons who are abroad and do not have the intention to return in Malta within a year are excluded.
Persons who live in another dwelling or live in an institution are excluded.
3.3.3. Questions relating to labour status are put to all persons aged
15 - 90 years
3.4. Statistical concepts and definitions
The Labour Force Survey classifies individuals in three categories: employed, unemployed and inactive. The definitions used in the EU-LFS follow the Resolution of the 13th International Conference of Labour Statisticians by the ILO. There are no deviations or discrepancies from the ESS and/or international standards.
3.4.1. Household concept
Housekeeping concept which refers to either:
- a one-person household, i.e., a person who lives alone in a separate housing unit or who occupies, as a lodger, a separate room (or rooms) of a housing unit but does not join with any of the other occupants of the housing unit;
- a group of two or more persons who combine to occupy the whole or part of a housing unit and to provide themselves with food and possibly other essentials for living. Members of the group may pool their incomes to a greater or lesser extent.
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.
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) |
Family home |
Family home (if financially dependent) |
Family home |
Most of the time |
Most of the time |
3.5. Statistical unit
Data collection is carried out for a sample of observation units consisting of private households in Malta.
3.6. Statistical population
The statistical population consists of all persons having their usual residence in private households in Malta.
3.7. Reference area
Not requested for the LFS quality report.
3.8. Coverage - Time
Data is available from 2000.
3.9. Base period
Not requested for the LFS quality report.
The LFS produces different indicators with different measures:
- Numbers;
- Percentages.
- 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:
The Labour Force Survey (LFS) is a household sample survey which provides quarterly and annual results on the employment situation of persons aged 15 years and over in accordance to the Integrated European Social Statistics (IESS) framework regulation (EU) 2019/1700.
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 NSO’s Privacy Policy, together with its Information Classification and Handling Procedure and Data Retention Policy, sets out strict rules on the collection, secure processing, restricted access and time-limited retention of personal data, ensuring all information is used exclusively for statistical purposes.
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.
8.2. Release calendar access
The NSO news release calendar is available on the NSO website.
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.
All national news releases and reports can be accessed from the NSO website with free access. News releases and other published information are accompanied by commentary, sampling errors and a list of definitions for all technical terms used.
Results are disseminated to all users at the same time.
First release, quarterly (4x), yearly (1x), ad hoc module results (1x)
10.1. Dissemination format - News release
News releases are published regularly on the NSO website.
10.2. Dissemination format - Publications
Publications are also published on the NSO website.
10.3. Dissemination format - online database
A statistical database is available on the NSO website.
10.3.1. Data tables - consultations
Not requested for the LFS quality report.
10.3.2. Web link to national methodological publication
Methodological publications are published on the NSO website.
10.3.3. Conditions of access to data
Aggregated data is available to the public while microdata is available to researchers. Users can request further information, i.e., data that is not available within news releases, by submitting a form on our website through this link
Annexes:
Access to microdata
10.3.4. Accompanying information to data
Questionnaire and methodological explanations are provided where necessary.
10.3.5. Further assistance available to users
Further assistance is available via phone or email.
10.4. Dissemination format - microdata access
At the NSO, access to anonymised microdata is only granted to research entities or researchers for use in research projects. These terms are defined below:
A recognised research entity or researcher is able to demonstrate, to the satisfaction of the Director General of the NSO, that it/she/he:
- Has the appropriate knowledge and experience necessary for handling potentially identifiable information;
- Has provided satisfactory evidence supporting the application that illustrates professionalism and technical competence to carry out the research proposal;
- Demonstrates a commitment to protecting and maintaining the confidentiality of the data during the creation of outputs and publications that arise during the proposal.
A research project serves, in the opinion of the Director General of the NSO, one of the following public benefits:
- Supports the formulation and development of public policy or public service delivery;
- Carries out research which will significantly benefit the Maltese economy, society or quality of life of people in Malta;
- Supports an obligation of public law (e.g. Local Development Plans);
- Explores new statistical methods that can be used to produce statistics that serve the public good;
- Replicates, validates or challenges existing research.
Under no circumstance will access to anonymised microdata be granted to research entities or researchers whose main purpose of conducting the research project is for general information and/or commercial activity; and/or if alternative data sources are available.
Recognition as a research entity or researcher is limited to the stipulated time period and for the purposes of the particular research project.
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 entities and researchers
10.4.3. Conditions of access to data
A research project serves, in the opinion of the Director General of the NSO, one of the following public benefits:
- Supports the formulation and development of public policy or public service delivery;
- Carries out research which will significantly benefit the Maltese economy, society or quality of life of people in Malta;
- Supports an obligation of public law (e.g. Local Development Plans);
- Explores new statistical methods that can be used to produce statistics that serve the public good;
- Replicates, validates or challenges existing research.
10.4.4. Accompanying information to data
Access to anonymised microdata will be granted subject to the terms of reference included in the application form and contract agreement. Access is normally granted for a definite period which is specified in the agreement.
10.4.5. Further assistance available to users
Further assistance is available via phone or 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
Methodological papers are available at the NSO website.
Past papers include:
- Impact of 2021 Census of Population and Housing on the Labour Force Survey (LFS) headline indicators- 2024 - Authors: Tania Borg and Charlene Abela
- Labour Force Survey – 2021 new methodology - 2022 - Authors: Tania Borg and Charlene Abela
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 notes are published with each release.
Metadata on the LFS is also available at the NSO website.
10.7. Quality management - documentation
NA
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
LFS statistics are used by policy makers, academics, students and journalists. Users make use of LFS statistics for official studies influencing policy making, for scientific research and to inform the general public. The NSO’s primary channel for the dissemination of official statistics is the NSO website. Tailored requests for statistical information may also be submitted through the NSO website. In addition, institutions or persons accredited as research entities or researchers often request anonymised microdata which is provided under strict conditions.
12.2. Relevance - User Satisfaction
Not requested for the LFS quality report.
12.3. Completeness
NA
12.3.1. Data completeness - rate
Not requested for the LFS quality report.
12.3.2. NUTS level of detail
The codification of localities in the national questionnaire is carried out at NUTS 5 level. Hence, NUTS 3 can be derieved from this information.
12.3.2.1. Regional level of an individual record (person) in the national data set
NUTS 4
12.3.2.2. Lowest regional level of the results published by NSI
NUTS 2
12.3.2.3. Lowest regional level of the results delivered to researchers by NSI
Mostly NUTS 2, however, this also depends on the request. NUTS 3 is published in regional publications.
13.1. Accuracy - overall
Not requested for the LFS quality report.
13.2. Sampling error
Refer to sub-sections.
13.2.1. Sampling error - indicators
The sampling error is worked out for the following indicators:
- Employment rate 15-74 years
- Unemployment to population ratio 15-74 years
- Youth unemployment rate 15-24 years
13.2.1.1. Coefficient of variation (CV) Annual estimates %
Refer to Annex File.
13.2.1.2. Coefficient of variation (CV) Annual estimates at NUTS-2 Level %
Refer to Annex File.
13.2.1.3. Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
Working Population 15-74 years
13.2.1.4. Reference on software used
R Software - Vardpoor package
13.2.1.5. Reference on method of estimation
Ultimate Cluster Method
13.3. Non-sampling error
Not requested for the LFS quality report.
13.3.1. Coverage error
Refer 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
Refer to Annex File.
13.3.2. Measurement error
See below.
13.3.2.1. Errors due to the media (questionnaire)
Refer to Annex File.
13.3.2.2. Main methods of reducing measurement errors
Refer 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
Refer to Annex File.
13.3.3.1.2. Non-response rates. Annual averages (% of the theoretical yearly sample)
Refer to Annex File.
13.3.3.1.2.1. Non-response rates. Annual averages (% of the theoretical yearly sample) – NUTS-2 level
Refer to Annex File.
13.3.3.1.3. Units who did not participate in the survey
Refer to Annex File.
13.3.3.2. Item non-response - rate
All variables with item non-response are imputed in the MT LFS.
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)
Refer 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)
Refer to Annex File.
13.3.3.2.3. Item non-response for INCGROSS variable
Refer to Annex File.
13.3.4. Processing error
Data editing procedures to detect and correct errors are applied to the data.
13.3.4.1. Editing and imputation process
Refer to Annex File.
13.3.5. Model assumption error
Not requested for the LFS quality report.
14.1. Timeliness
Refer 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
LFS data transmission was in line with the guidelines stipulated in the IESS regulation.
14.2.1. Punctuality - delivery and publication
Not requested for the LFS quality report.
15.1. Comparability - geographical
There is no divergence of national concepts from European concepts in terms of geographical comparability.
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
There were no changes in LFS 2024 which could limit the use of LFS data for comparisons over time.
15.2.1. Length of comparable time series
2000 until 2024
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)
Refer 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)
Refer 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 |
Total employment in persons is based on administrative sources in case of full-time employment and on LFS in case of part-time employment. |
LFS data is collected from private households only and refers to physical persons employed while National Accounts data is based on administrative sources for full-time employment and on LFS for part-time employment. |
There is no significant difference in totals. |
UNA |
| Total employment by NACE |
Employment by NACE in persons is derived using the breakdown of employment by NACE in jobs. Data on employment in jobs is based on employment registers and/or enterprise surveys. Data in persons is disseminated at A*11 and A*64. Data in jobs is not disseminated. |
The level of detail which is often requested by National Accounts is NACE 2 digit level. Despite the fact that national LFS concepts are in line with NA criteria, the survey is not designed to provide reliable estimates at this level for all NACE categories (except in those categories where a good number of persons are engaged). |
Given this limitation, National Accounts make use of a combination of sources. |
UNA |
| Number of hours worked |
National Accounts use LFS data at A*11 to derive the hours per head and per week for employees and self-employed. This is then applied on the number of full-time and part-time jobs at A*88 derived by NA using administrative data and other sources. |
Employment [in jobs] is converted to full-time equivalent using information from 1995 Census of Population and Housing. This is then converted in hours using LFS data on hours worked. |
UNA |
UNA |
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. employment registers and/or enterprise surveys) |
| No, LFS data is supplemented by administrative sources with respect to full-time employment. LFS data is used for part-time employment. |
LFS is the only source used by National Accounts when compiling hours worked. Data on hours worked have been used since 2002. |
Y |
N |
N |
LFS data is supplemented by administrative sources with respect to full-time employment. LFS data is used for part-time employment. |
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 |
Employment in Business Statistics does not include unpaid family workers. |
UNA |
UNA |
UNA |
| Total employment by NACE |
Employment in Business Statistics does not include unpaid family workers. |
UNA |
UNA |
UNA |
| Number of hours worked |
UNA |
UNA |
UNA |
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 |
|---|---|---|
| Registered unemployed data includes those persons who register with the National Employment Agency, and who are either new job seekers or workers who have been dismissed from work. On the other hand, LFS unemployment is measured according to the Implementation of the 12 principles of unemployment regulation. |
Measurement at the National Employment Agency is carried out as at the end of the month whilst LFS measures unemployment on a continuous basis. |
UNA |
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) |
| LFS unemployment figures tend to be higher than those of the registered unemployed since LFS's definition is broader and includes persons who are looking for a job but who have no interest in registering for work with the public employment agency. The main reason for not registering with the public employment agency is the fact that in order to qualify for unemployment benefits, a person must have paid enough contribitions and must also be registering for work with the public employment agency. Persons who are looking for a job but who have not paid any contributions because, for instance, they are looking for their first job, do not have any interest in registering for work and consequently do not normally feature in the registered unemployment figures but may feature in LFS. |
This age group is more likely to be higher in LFS because as previously explained, these persons tend to be looking for their first job and therefore have no interest in registering for work with the public employment agency because they will not get any unemployment benefits. Moreover, the younger unemployed especially the better educated ones, tend to resort to other means when looking for a job. |
This age group is more likely to be in line with LFS figures as men are likely to register with the national PES in order to receive the unemployment benefit.
|
Same as for men under 25 years. |
Not likely to be on the unemployment register because once more there is no access to unemployment benefit, since in most cases the spouse would be in gainful employment and therefore the wife will not be entitled to get any benefits. In addition, the activity rate for the older age groups tends to be very low for females, hence it is not likely to have them on the unemployment register. |
NA |
15.3.7. Comparability and deviation for the INCGROSS variable
Refer to Annex File.
15.4. Coherence - internal
Not requested for the LFS quality report.
Cost
The data collection for the LFS is centralised and carried out in-house.This approach ensures a more efficient work process. In addition, the module of 2025 is incorporated with the core LFS, which keeps costs to a minimum.
Efficiency is bound to be ensured since the different aspects of the project will be handled by different units which are more focused on data collection, analysis and dissemination.
The financial department handles the budget for the EU_LFS data collection. Monitoring and processing of payments will be handled by this department in collaboration with information provided by the Data Collection Unit.
Burden
The following procedures are applied to minimise respondents' burden:
- Module: In order to reduce the response burden, the questions related to the 8 yearly module was addressed to the first and last panels of the Labour Force Survey.
- Dependent Interviewing: In subsequent survey waves, dependent interviewing techniques are used whereby information collected in previous interviews for certain variable is prefilled and used to guide the current interview. Respondents are asked to confirm, update, or correct previously reported information, reducing interview length and minimising respondent burden.
- Simplification Rules: In accordance with the Integrated European Social Statistics (IESS) Regulation, simplification rules are applied to elderly persons.
- Use of Proxy Interviews: Interviewers may conduct proxy interviews in subsequent survey waves when contacting the household. In such cases, a single household member aged 15 years or over may provide responses on behalf of all household members.
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.
Refer to Annex File.
16.2. Duration of the interview by Final Sampling Unit
Average duration of the interview is 35 minutes:
- 40 minutes for first wave respondents
- 20 minutes for later waves due to dependent interviewing.
17.1. Data revision - policy
The data revision policy is fully compliant with the ESS Code of Practice principles.
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?
Yes
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
LFS is based on survey data.
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 random sampling |
Sampling frame based on 2021 Census |
The last overall update was in 2021, however, deaths are updated monthly and telephone contact details annually. |
NA |
Households (All persons in households are selected) 29 November 2023 |
|
18.1.2. Sampling design & Procedure method
|
18.1.3. Yearly sample size & Sampling rate
Refer to Annex File.
18.1.4. Quarterly sample size & Sampling rate
Refer 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) |
|---|---|---|---|
| 1,4 |
Yes |
NA |
Annual variables: INCGROSS_F, INCGROSS, ISCOPR3D, NACEPR2D,STAPROPR, FINDMETH, WAYJFOUND, HATFIELD, HATYEAR, HATWORK, NEEDCARE, HWWISH, LOOKOJ, SIZEFIRM, SUPVISOR, VARITIME, MAINCLNT,TEMPREAS, TEMPAGCY, HOMEWORK, HHLINK, HHSPOU, HHFATH, HHMOTH, COEFFHH, COEFFMOD, COEFFY, COEFF2Y
|
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? |
|---|---|---|
| Each household is contacted via ordinary mail so that it is informed that the family has been chosen to participate in the LFS. An interviewer who is assigned to a group of households carries the interview in either of two ways, i.e., Personal (CAPI) or by telephone (CATI). In 2024, the majority of households were still being carried out over the phone. Households are then selected for the second to fourth panel which in turn, are contacted by telephone or mobile number. For the latter panels, an interviewer is only sent when households do not provide a telephone number or do not have a telephone line or do not want to be interviewed over the phone. |
Y |
Blaise 4.8.6 |
18.3.1. Final sampling unit collected by interviewing technique (%)
Refer 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 |
NA |
Commissioner for Revenue Register for INCGROSS variable. |
18.3.3. Description of data collection and reference period for INCGROSS variable
Refer to Annex File.
18.3.4. Description of percentiles and bands used for INCGROSS variable
Refer 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
Refer 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
Refer 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 |
|---|---|---|---|---|---|---|
| For the weighting scheme, calibration is done using R-package ‘Sampling’ and the ‘calib’ function applying the logit method based on the following benchmarks: panel, district of residence of respondents, number of households in Malta, nationality and registered employed non-nationals and also nested demographics of sex and age groups. |
Y |
NA |
Y |
5 year age groups except at 0 to 19 years. (Hence, age groups are as follows: 0 -14, 15 - 17, 18 -19, 20 - 24, 25 -29, 30 - 34, 35 -39, continue 5 year age groups until, 70-74, 75+) |
NUTS 4 |
Nationality (also including the 15-64 subgroup), panel, number of registered employed of non-nationals and number of households.
|
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 |
|---|---|---|---|---|
|
For the weighting scheme, calibration is done using R-package ‘Sampling’ and the ‘calib’ function applying the logit method based on the following benchmarks: panel, district of residence of respondents, number of households in Malta, nationality andr egistered employed non-nationals and also nested demographics of sex and age groups. |
Y |
5 year age groups except at 0 to 19 years. (Hence, age groups are as follows: 0 -14, 15 - 17, 18 -19, 20 - 24, 25 -29, 30 - 34, 35 -39, continue 5 year age groups until, 70-74, 75+) |
NUTS 4 |
Nationality, panel and number of registered employed of non-nationals. |
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 |
| 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.
|
15 June 2025
The Labour Force Survey classifies individuals in three categories: employed, unemployed and inactive. The definitions used in the EU-LFS follow the Resolution of the 13th International Conference of Labour Statisticians by the ILO. There are no deviations or discrepancies from the ESS and/or international standards.
Data collection is carried out for a sample of observation units consisting of private households in Malta.
The statistical population consists of all persons having their usual residence in private households in Malta.
Not requested for the LFS quality report.
- 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.
LFS is based on survey data.
First release, quarterly (4x), yearly (1x), ad hoc module results (1x)
Refer to Annex File.
There is no divergence of national concepts from European concepts in terms of geographical comparability.
There were no changes in LFS 2024 which could limit the use of LFS data for comparisons over time.
