Employment and unemployment (Labour force survey) (employ)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: National Statistics Office


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

National Statistics Office
1.2. Contact organisation unit

Labour Market and Information Statistics Unit
1.5. Contact mail address

Labour Market Statistics Unit,
NSO, Lascaris, Valletta
Malta


2. Metadata update Top
2.1. Metadata last certified

13 June 2023
2.2. Metadata last posted

13 June 2023
2.3. Metadata last update

13 June 2023


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.

  

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 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 livingregularly together in thesame 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

A person who is abroad during thereference week year, is considered to be part of thehousehold. Children living in another dwelling or institutions 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. 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

b. 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 LFS

Members living regularly 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
dependents)

 Family home

 Most of the time

 Most of the time
3.5. Statistical unit

 The data collection is carried out in each Malta for a sample of observation units constituted by private households who have their usual residence 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.


4. Unit of measure Top

The LFS produces different indicators with different measures:

  • Numbers;
  • Percentages.


5. Reference Period Top
  • Quarter
  • 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:

The Labour Force Survey (LFS) is a household sample survey which provides quarterly and annual results on the employment situation of persons 15 years and over in accordance with 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. 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:

The Information Classification and Handling Procedure and the Data Retention Policy outline the purposes, methods, storage limitation and retention period of personal data. 
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).

The purposes, methods, storage limitation and retention period of personal data must be consistent with the Information Classification and Handling Procedure and with the Data Retention Policy. The accuracy, integrity, confidentiality and relevance of personal data based on the processing purpose must always be maintained. Adequate security mechanisms designed to protect personal data must be used to prevent personal data from being stolen, misused, or abused, and prevent personal data breaches. These measures are described within the Anonymisation and Pseudonymisation Policy implemented at NSO.


8. Release policy Top
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 can be accessed from this link: https://nso.gov.mt/calendars/
8.3. Release policy - user access

EU level:

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 news releases and reports can be accessed from the NSO website with free access. News releases and otherpublished information areaccompanied by a list of definitions used, a commentary and sampling errors. In addition,our website includes extracts ofthis quality report under 'Sourcesand Methods'.

Results are disseminated to all users at the same time.


9. Frequency of dissemination Top

First release, quarterly (4x), yearly (1x), ad hoc module results (1x)

 


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

Newsreleases are published regularly on the NSO website: https://nso.gov.mt/labour_market/ 

 
10.2. Dissemination format - Publications

Publications are also published on the NSO website: https://nso.gov.mt/labour_market/ 

 
10.3. Dissemination format - online database

A statistical database is available on the NSO website available on https://statdb.nso.gov.mt
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 via this link https://nso.gov.mt/statistical-papers/
10.3.3. Conditions of access to data

Users can request further information,which is not found in the news releases. 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

Pre-filled example:

Further assistance 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:

1) Has the appropriate knowledge and experience necessary for handling potentially identifiable information;

2) Has provided satisfactory evidence supporting the application that illustrates professionalism and technical competence to carry out the research proposal;

3) 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:

1) Supports the formulation and development of public policy or public service delivery;

2) Carries out research which will significantly benefit the Maltese economy, society or quality of life of people in Malta;

3) Supports an obligation of public law (e.g. Local Development Plans);

4) Explores new statistical methods that can be used to produce statistics that serve the public good;

5) 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 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:

1) Supports the formulation and development of public policy or public service delivery;

2) Carries out research which will significantly benefit the Maltese economy, society or quality of life of people in Malta;

3) Supports an obligation of public law (e.g. Local Development Plans);

4) Explores new statistical methods that can be used to produce statistics that serve the public good;

5) 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

NA
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 via this link https://nso.gov.mt/statistical-reports/

 

Impact of 2021 Census of Population and Housing on the Labour Force Survey (LFS) headline indicators- 2024 - Authors: Tania Borg and Charlene Abela - https://nso.gov.mt/wp-content/uploads/Impact-of-2021-census-on-LFS.pdf

Labour Force Survey – 2021 new methodology - 2022 - Authors: Tania Borg and Charlene Abela - https://nso.gov.mt/wp-content/uploads/2023/01/Labour-Force-Survey-2021-methodological.pdf

 
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 online: https://metadata.nso.gov.mt
10.7. Quality management - documentation

NA


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

LFS statistics are used for 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 microdatawhich is provided 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

NUTS4
12.3.2.2. Lowest regional level of the results published by NSI

NUTS2
12.3.2.3. Lowest regional level of the results delivered to researchers by NSI

Mostly NUTS 2, however this also depends on the request. NUTS 3 is published in regional publications.


13. Accuracy Top
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 %

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

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

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

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)

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

Data editing procedures to detect and correct errors are applied to the data.
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

LFS data transmission was in line with the guidelines as stipulated 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

There are 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

 

(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

There were no changes in LFS 2023 which could limit the use of LFS data for comparisons over time. 
15.2.1. Length of comparable time series

2000 until 2023
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

 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 andA*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 thehours per head and per weekfor employees and self-employed. This is thenapplied 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 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)

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 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 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 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 explained above, 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 natinal PES in order to receive the unemployment benefit.

 Same as for men under 25years

 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 agegroups 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

References to Annex File.
15.4. Coherence - internal

Not requested for the LFS quality report.


16. Cost and Burden Top

NA
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

Average duration of the interview is 35 minutes:

  • 40 minutes for first wave respondents
  • 20 minutes for later waves due to depending interviewing.


17. Data revision Top
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? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF)

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. Statistical processing Top
18.1. Source data

LFS is based on survey data.
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

 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)

 

06/12/2022
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.)

 NA

 

One-stage stratified random sampling to choose eligible households. All persons living in household are selected.

Locality (68) and type of household (MT vs Foreign vs Mixed).

 204

All eligible households that responded in the first wave are chosen for the second wave which is carried out in the following quarter. The household will be absent for two quarters and then reintroduced, followed by another contact the following quarter. The pattern can be described as follows: 2-(2)-2. In addition, households who fail to be contacted at any point in time are approached when it is their turn just like all other households.
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)

 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


Bienial variables (in odd years): SHIFTWK, EVENWK, NIGHTWK,SATWK, SUNWK, MIGREAS
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 isassigned to a group of households carries the interview in either of two ways ie Personal (CAPI) or by Telephone. In 2023, the majority ofhouseholds were still being carried out over the phone. Households are then selected for the second to fourth panel which in turn, are contacted bytelephone 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 (%)

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

 Commissioner for Revenue Register for INCGROSS variable.
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

 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.

 Yes

 NA

 Y

 5 year age groups except at 0 to 19 years. (Hence, age groups areas follows: 0 -14, 15 - 17, 18 -19, 20 - 24, 25 -29, 30 - 34, 35 -39, continue 5 year age groups until, 75 - 79,80+

 NUTS 4

 Nationality (also including the 15-64 subgroup), panel and number of registered employed of non-nationals, 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.
Consistency checks are then carried out between annual totals of sub-samples for annual and biennial structural variables is done for employment, unemployment and outside the labour force by sex and for the following age groups: 15 to 24, 25 to 34, 35 to 44, 45 to 54 and 55+

 Y

 5 year age groups exceptat 0 to 19 years. (Hence,age groups are asfollows: 0 - 14, 15 - 17,18 - 19, 20 - 24, 25 - 29,30 - 34, 35 - 39, continue5 year age groups until,75 - 79, 80+

 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

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)

 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.
Consistency checks are then carried out between annual totals of sub-samples for annual and biennial structural variables is done for employment, unemployment and outside the labour force by sex and for the following age groups: 15 to 24, 25 to 34, 35 to 44, 45 to 54 and 55+. For household weights, all persons in the same household have the same weight, were additional benchmarks at household levels are added. These are household size and NUTS 4.

 Population estimates for the number of households taken from the population statistics

 Number of households, household size, distribution of households by NUTS 4

 

Panel, district of residence of respondents, nationality and registered
employed non-nationals and also
nested demographics of sex and age groups

 Y
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


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Related metadata Top


Annexes Top
Annex [LFS_QR_Multiple+1.0_upd]