Employment and unemployment (Labour force survey) (employ)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: National Statistics Office


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. 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 Unit
1.5. Contact mail address

Labour Market Statistics Unit,

NSO, Lascaris, Valletta

Malta


2. Statistical presentation Top
Please take note of the abbreviations used in the report 
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
2.1. Data description
Coverage   
Coverage Household concept Definition of household for the LFS Inclusion/exclusion criteria for members of the household Questions relating to employment status are put to all persons aged ...
 All private households Housekeeping Members living regularly together in the same dwelling, sharing income, household expenditures, food and other essentials for living. A person who is abroad during the reference week and who visits Malta on a regular basis, i.e. at least twice a year, is considered to be part of the household. Children or any other members who are living in another dwelling or institution are excluded. Employment is addressed to all persons aged 15 and over

 

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

 

Reference week
Fixed week (data collection refers to one reference week, to which the observation unit has been assigned prior to the fieldwork) Rolling week (data collection always refers to the week before the interview)                                  
 Yes  No
2.2. Classification system

[not requested for the LFS quality report]
2.3. Coverage - sector

[not requested for the LFS quality report]
2.4. Statistical concepts and definitions

[not requested for the LFS quality report]
2.5. Statistical unit

[not requested for the LFS quality report]
2.6. Statistical population

[not requested for the LFS quality report]
2.7. Reference area

[not requested for the LFS quality report]
2.8. Coverage - Time

[not requested for the LFS quality report]
2.9. Base period

[not requested for the LFS quality report]


3. Statistical processing Top
3.1. Source data
Sampling design & procedure
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)
Systematic sampling.  Eligible households are ordered by address details, number of males in household, number of females in household, and number of persons aged 0-14, 15-24, 25-44, 45-64, and 65+. Statistical population register using a number of administrative sources  Sampling frame was last updated at end of 2017. Monthly deaths updates are also carried out.  NA Households (All persons in households are selected)

 

Sampling design & procedure
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 Systematic sampling. Eligible households are ordered by address details, number of males in household, number of females in household, and number of persons aged 0-14, 15-24, 25-44, 45-64, and 65+.

All persons living in household are selected.

  NA  NA  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.

 

Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate Size of the theoretical yearly sample
(i.e. including non-response) (i.e. including non-response)
6.16% 12 800

  

Quarterly sample size & Sampling rate
Overall theoretical quarterly sampling rate Size of the theoretical quarterly sample
(i.e. including non-response) (i.e. including non-response)
1.54% 3 200

  

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. 430/2005, Annex I) (Y/N) If not please list deviations List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 377/2008, Annex II)
 NA  NA  NA  NA

 

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 All persons living in private households are weighted at individual level to represent the reference population of private households in Malta.  (All persons within the household are surveyed.)  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, 75 - 79, 80+   NUTS 4  Nationality, panel and number of registered employed of non-nationals

 

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. NUTS 3)? Other weighting dimensions
Quarterly Weights / 4 -

No Subsampling is used

  Y 5 year age groups except at 0 - 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, 75 - 79, 80+  NUTS 4 Nationality, panel and number of registered employed of non-nationals

 

Brief description of the method of calculating the weights for households 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.) Identical household weights for all household members? (Y/N)
 NA  NA  NA  NA  NA
3.2. Frequency of data collection

[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description Use of dependent interviewing (Y/N)? Participation is voluntary/compulsory?
 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 ie Personal or by Telephone.  In 2020, due to the COVID-19 pandemic, the majority of households were carried out over the phone as per Health authorities guidelines. 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  Compulsory 

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 N/A  92%  8%  N/A  N/A
3.4. Data validation

[not requested for the LFS quality report]
3.5. Data compilation

[not requested for the LFS quality report]
3.6. Adjustment

[not requested for the LFS quality report]


4. Quality management Top
4.1. Quality assurance

[not requested for the LFS quality report]
4.2. Quality management - assessment

[not requested for the LFS quality report]


5. Relevance Top
5.1. Relevance - User Needs
Assessment of the relevance of the main LFS statistics at national level (e.g. for policy makers, other stakeholders, media and academic research)
 LFS statistics are used for official studies influencing policy making, by academics for scientific research, by students and it is also mentioned by national media for the general public.
5.2. Relevance - User Satisfaction

[not requested for the LFS quality report]
5.3. Completeness
NUTS level of detail   
Regional level of an individual record (person) in the national data set Lowest regional level of the results published by NSI Lowest regional level of the results delivered to researchers by NSI Brief description of the method which is used to produce NUTS-3 unemployment and labour force data sent to Eurostat?
 NUTS 4  NUTS 2 Mostly NUTS 2, however this also depends on the request. NUTS 3 is published in regional publications. The codification of localities in the national questionnaire is carried out at NUTS 5 level.  Hence NUTS 3 can be derieved from this information.
5.3.1. Data completeness - rate

[not requested for the LFS quality report]


6. Accuracy and reliability Top
6.1. Accuracy - overall

[not requested for the LFS quality report]
6.2. Sampling error
Publication thresholds   
Annual estimates Annual estimates - wave approach 
(if different from full sample thresholds) 
 Limit below which figures cannot be published  Limit below which figures must be published with warning  Limit below which figures cannot be published Limit below which figures must be published with warning
450 1150  NA  NA
6.2.1. Sampling error - indicators
Coefficient of variation (CV) Annual estimates
Sampling error - indicators - Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)       
 

Number of employed persons

Employment rate as a percentage of the population

Number of part-time employed persons

Number of unemployed persons

Unemployment rate as a percentage of labour force

Youth unemployment rate as a percentage of labour force

Average actual hours of work per week(*)
 

Age group: 20 - 64

Age group: 20 - 64

Age group: 20 - 64

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24

Age group: 20 - 64
 CV  0.67  0.67  4.66  7.33  7.31  12.02  0.73
 SE 0.52  0.52  0.50  0.32  0.32  1.29  0.25 
 CI(**) 3317  1.02  2462  1689  0.62  2.53  0.49 

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 Employed, unemployed and inactive 20-64 years

 

Reference on software used: Reference on method of estimation:
R Software - Vardpoor package  Ultimate Cluster Method

 

Coefficient of variation (CV) Annual estimates at NUTS-2 Level        
NUTS-2  CV of regional (NUTS-2) annual aggregates (in %)     
Regional Code  Region

Number of employed persons

Employment rate as a percentage of the population

Number of part-time employed persons

Number of unemployed persons

Unemployment rate as a percentage of labour force

Youth unemployment rate as a percentage of labour force

 Average actual hours of work per week(*)
   

Age group: 20 - 64

Age group: 20 - 64

Age group: 20 - 64

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24

Age group: 20 - 64 
NA  NA NA NA NA NA NA NA NA

 

(*) The coefficient of variation for actual hours worked should be calculated for the sum of actual hours worked in 1st and 2nd jobs, and restricted to those who actually worked 1 hour or more in the reference week.

(**) The value is based on a CI of 95%. For the rates the CI should be given with 2 decimals.
6.3. Non-sampling error

 [not requested for the LFS quality report]
6.3.1. Coverage error
Frame quality (under-coverage, over-coverage and misclassifications(b))      
Under-coverage rate (%) Over-coverage rate (%) Misclassification rate (%)  Comments: specification and impact on estimates(a)   
 Undercoverage  Overcoverage  Misclassification(b)  Reference on frame errors
UNA  6.7 UNA Undercoverage may be observed in the foreign component and in households which we are not aware about. This is due to the fact that there is a time-lag in updates to the frame. Hence, the rate of under coverage for private households cannot be worked out.     Not applicable since the main classification systems used in LFS (NACE, ISCO, ISCED, field of education) are not available in the sampling frame.   

(a) Mention specifically which regions / population groups are not suitably represented in the sample.

(b) Misclassification refers to statistical units having an erroneous classification where both the wrong and the correct one are within the target population.
6.3.1.1. Over-coverage - rate

[Over-coverage rate, please see concept 6.3.1 Coverage error in the LFS quality report]
6.3.1.2. Common units - proportion

[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)   
Was the questionnaire updated for the 2020 LFS operation? (Y/N) Synthetic description of the update Was the questionnaire tested? (Y/N) If the questionnaire has been tested, which kind of tests has been applied (pilot, cognitive, internal check)?
 Y To fulfill ad hoc requirements and fine tune LFS core questions  Y  Internal Checks

 

Main methods of reducing measurement errors 
Error source  
Respondent  Letter introducing the survey (Y/N) Phone call for booking or introducing the survey (Y/N)
 Y  Y
Interviewer  Periodical training (at least 1 time per year) (Y/N)  Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
 Y  Y
Fieldwork  Monitoring directly by contacting the respondents after the fieldwork (Y/N) Monitoring directly by listening the interviews (Y/N) Monitoring remotely through performance indicators (Y/N)
 Y  Y  N
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 Y  Y
Other / Comments  
6.3.3. Non response error

[not requested for the LFS quality report]
6.3.3.1. Unit non-response - rate

IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *

Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N) Variables used for non-response adjustment Description of method
 N  NA Calibration is done to adjust for population estimates taking into account non response adjustments.
Substitution of non-responding units (Y/N) Substitution rate Criteria for substitution
 Y For the first panel the substitution rate was 47% which results into a 12% substitution rate when taking into consideration all panels in Quarter 1. Due to a change in the sampling frame in 2019, a number of households selected for the LFS were without a contact number, leading to high non contacts in the first wave. For this reason and to enhance the sample counts, an oversampling exercise was carried out in Q1 2020 so that these households without a contact number were substituted with others with a contact number. 
Other methods (Y/N) Description of method
 N  NA

  

Non-response rates by survey mode. Annual average (% of the theoretical yearly sample by survey mode)
Survey
CAPI CATI  PAPI  CAWI  POSTAL
 NA  36.7%  29.1%  NA  NA

 

Divisions of non-response into categories. Quarterly data and annual average
Quarter Non-response rate
Total (%)             of which:
 Refusals (%)        Non-contacts (including people who migrated (or moved) internally or abroad) (%) of which people who migrated (or moved) internally or abroad (%)
1 39.6 2.9 36.6   
2 30.4 2.2  28.1   
3 32.5 2.7 29.8  
4 35.3 2.7 32.6  
Annual  34.6  2.7 32.0  

 

 Units who refused to participate in the survey  (Please indicate the number of the units concerned in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018  7      
Subsample_Q1_2019 2  3    
Subsample_Q2_2019   5  10  
Subsample_Q3_2019     13  12
Subsample_Q4_2019 24      25 
Subsample_Q1_2020 73  14     
Subsample_Q2_2020   51  23   
Subsample_Q3_2020     33  21 
Subsample_Q4_2020       31 
 Total in absolute numbers  106 73 79  89 
 Total in % of theoretical quarterly sample  2.9 2.2  2.7  2.7 

 

Units who were not contacted (including people who migrated (or moved) internally or abroad) (Please indicate the number of units only in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018 212      
Subsample_Q1_2019 217  196     
Subsample_Q2_2019   281  280  
Subsample_Q3_2019     205   227
Subsample_Q4_2019 290      428 
Subsample_Q1_2020 303  281    
Subsample_Q2_2020   158  200   
Subsample_Q3_2020     183  215 
Subsample_Q4_2020       191 
 Total in absolute numbers  1322  916 868  1061 
 Total in % of theoretical quarterly sample

 36.6

  28.1  29.8  32.6

 

of which people who migrated (or moved) internally or abroad) (Please indicate the number of units only in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018        
Subsample_Q1_2019        
Subsample_Q2_2019        
Subsample_Q3_2019        
Subsample_Q4_2019        
Subsample_Q1_2020        
Subsample_Q2_2020        
Subsample_Q3_2020        
Subsample_Q4_2020        
 Total in absolute numbers        
 Total in % of theoretical quarterly sample        

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
NA NA

* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview
6.3.3.2. Item non-response - rate
Item non-response (*) - Quarterly data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)       

Variable status

 Column Identifier Quarter 1 Quarter 2 Quarter 3 Quarter 4 Short comments on reasons for non-available statistics and prospects for future solutions

Compulsory / optional
compulsory Col_089/90 MONTHPR . . 14.9 13.5  Respondents find it difficult to recall the month when they started their employment.
compulsory  Col_110 - Employed METHODH . . C .  
compulsory Col_110 - Not employed METHODH C C . C  
compulsory Col_111 - Employed METHODI . C C C  
compulsory Col_112 - Employed METHODJ C C C C  
compulsory Col_112 - Not employed METHODJ C C C C  
compulsory Col_113 - Employed METHODK C C C C  
compulsory Col_113 - Not employed METHODK C C C C  
compulsory Col_114 - Employed METHODL C C C C  
compulsory Col_114 - Not employed METHODL C C C C  

 

Item non-response - Annual data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)    
Variable status Column Identifier This reference year Short comments on reasons for non-available statistics and prospects for future solutions
compulsory Col_118 - Employed AVAIREAS 90.8 Information on this variable is not collected.
compulsory Col_150/151 COUNTR1Y C  Information on this variable is not collected.
optional Col_133/135 COURFILD 100  Information on this variable is not collected.
optional Col_136 COURWORH 100  Information on this variable is not collected.

(*) "C" means all the records have the same value different from missing.
6.3.4. Processing error
Editing of statistical item non-response
Do you apply some data editing procedure to detect and correct errors? (Y/N) Overall editing rate (Observations with at least one item changed / Total Observations )
  Y  UNA
6.3.4.1. Imputation - rate
Imputation of statistical item non-response
Are all or part of the variables with item non response imputed? (Y/N) Overall imputation rate (Observations with at least one item imputed / Total Observations )
  Y  NA
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
  Gross salary variable - Decile  7.7%  The imputation is based on a Log linear model with gender, ISCO, education, Type of employment, age and hours worked as auxiliary variables.
6.3.5. Model assumption error

[not requested for the LFS quality report]
6.4. 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. http://ec.europa.eu/eurostat/web/research-methodology/seasonal-adjustment) (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
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N) Are you 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/N)
 Y  Y
6.6. Data revision - practice

[not requested for the LFS quality report]
6.6.1. Data revision - average size

[not requested for the LFS quality report]


7. Timeliness and punctuality Top
7.1. Timeliness
Restricted from publication
7.1.1. Time lag - first result
Restricted from publication
7.1.2. Time lag - final result
Restricted from publication
7.2. Punctuality
Restricted from publication
7.2.1. Punctuality - delivery and publication
Restricted from publication


8. Coherence and comparability Top
8.1. Comparability - geographical

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 a 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
8.1.1. Asymmetry for mirror flow statistics - coefficient

[not requested for the LFS quality report]
8.2. Comparability - over time
Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes in (Y/N) Description of the impact of the changes Statistics also revised backwards (if Y: year / N) Variables affected Break in series to be flagged (if Y: year and quarter/N)  
concepts and definition  N  NA  NA  NA  NA
coverage (i.e. target population) N   NA  NA  NA  NA
legislation N   NA  NA  NA  NA
classifications N   NA  NA  NA  NA
geographical boundaries N   NA  NA  NA  NA

 

Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes to (Y/N) Description of the impact of the changes Statistics also revised backwards (if Y: year / N) Variables affected Break in series to be flagged (if Y: year and quarter/N)
sampling frame N NA  NA  N/A  NA
sample design N   NA  NA  NA  NA
rotation pattern N   NA  NA  NA  NA
questionnaire N   NA  NA  NA  NA
instruction to interviewers N   NA  NA NA   NA
survey mode Y Due to the COVID-19 pandemic, in March 2020 households in the first panel were interviewed via CATI to abide by health regulations. Normally in the first wave the LFS is conducted face to face (PAPI).  NA  NA  NA
weighting scheme N  NA
 NA  NA
  NA
use of auxiliary information N   NA  NA  NA  NA
8.2.1. Length of comparable time series

[not requested for the LFS quality report]
8.3. Coherence - cross domain
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  Unavaliable  UNA  UNA  UNA

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
 The LFS definition of unemployment is based on the Commission Regulation No 1897/2000. whereas, 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 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

 

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 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
8.4. Coherence - sub annual and annual statistics

[not requested for the LFS quality report]
8.5. Coherence - National Accounts
Coherence of LFS data with National Accounts 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 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 

 

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 not 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.
8.6. Coherence - internal

[not requested for the LFS quality report]


9. Accessibility and clarity Top
9.1. Dissemination format - News release

[not requested for the LFS quality report]
9.2. Dissemination format - Publications
  Please provide a list of type and frequency of publications
   Quarterly LFS News Releases, Ad Hoc releases on other LFS findings, and a release containing main Indicators of the labour market
9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.    
Web link to national methodological publication Conditions of access to data Accompanying information to data Further assistance available to users
https://nso.gov.mt/en/nso/Sources_and_Methods/Unit_C2/Labour_Market_Statistics/Pages/Labour-Force-Survey.aspx All news releases and reports can be accessed from the NSO website.  Hardcopies can be found at the NSO library. News releases and other published information are accompanied by a list of definitions used, a commentary and sampling errors.  In addition, our website includes extracts of this quality report under 'Sources and Methods'. Users can request further information, which is not found in the news releases.
9.3.1. Data tables - consultations

[not requested for the LFS quality report]
9.4. Dissemination format - microdata access
Accessibility to LFS national microdata (Y/N) Who is entitled to the access (researchers, firms, institutions)? Conditions of access to data Accompanying information to data Further assistance available to users
 Y Researchers  Anonymisation  Methodological notes, and definitions accompany the requested information NA 
9.5. Dissemination format - other

[not requested for the LFS quality report]
9.6. Documentation on methodology
References to methodological notes about the survey and its characteristics
UNA
9.7. Quality management - documentation

[not requested for the LFS quality report]
9.7.1. Metadata completeness - rate

[not requested for the LFS quality report]
9.7.2. Metadata - consultations

[not requested for the LFS quality report]


10. Cost and Burden Top
Restricted from publication


11. Confidentiality Top
11.1. Confidentiality - policy

[not requested for the LFS quality report]
11.2. Confidentiality - data treatment
Please provide information on the policy for anonymizing microdata in your country
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.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top