Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Central 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

Central Statistics Office
1.2. Contact organisation unit

Labour Market Analysis
1.5. Contact mail address

Central Statistics Office

Skehard Road

Cork, Ireland

T12 X00E


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 ...
Permanent private households Dwelling For the Labour Force Survey (LFS), all usual residents of the house that have been selected for inclusion in the sample are interviewed A person is defined to be a 'Usual Resident' of a private household if he/she 

(i) lives regularly at the dwelling in question and 

(ii) shares the main living accommodation (i.e. kitchen, living room or bathroom) with the other members of the household. 

  15+

 

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 Term address Term address Family home 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)                                  
 N  Y
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)
A two stage sampling design is used The Labour Force Survey (LFS) replaced the Quarterly National Survey (QNHS) effective from Q3 2017 and uses mixed mode data collection with the introduction of Computer Assisted Telephone Interviewing (CATI). A new independent sample based on the 2011 Census of Population was selected for the LFS and this was introduced incrementally from Q1 2016. A parallel run was carried out between the QNHS and the new LFS between Q1 2016 and Q2 2017. The sample is stratified using administrative county and the Pobal HP (Haase and Pratschke) Deprivation Index and ran in parallel with the QNHS upto the end of Q2 2017. There was no overlap between the LFS and QNHS samples.  

New samples, both based on the 2011 Census of Population, were introduced incrementally for the QNHS in Q4 2012 and in Q3 2016. The former was stratified using administrative county and population density while the latter was stratified using administrative county and the Pobal HP (Haase and Pratschke) Deprivation Index. 

A further new sample based on the 2016 Census of Population was introduced on a phased basis (over five quarters) from Q2 2019 andhas been fully operational since Q2 2020. As with the expiring sample, the new sample is stratified using administrative county and the Pobal HP (Hasse and Pratschke) Deprivation Index and consists of 32,500 households per quarter.

  2016 Census of Population Block - there is a minimum of 60 households within a small area (minimum 60 occupied on Census night)  Households

 

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.)
The sample frame of households is clustered into blocks (small areas) with each block containing a minimum of 60 occupied households on the night of the 2016 Census of Population. The LFS sample is stratified using administrative county  Pobal HP (Haase and Pratschke) Deprivation Index.

The QHHS sample introduced in 2016 was also stratified using administrative county and the Pobal HP (Haase and Pratschke) Deprivation Index. In the case of the QNHS sample introduced in 2012 the sample frame was stratified using administrative county and population density. For each sample, 1,300 blocks are selected in the first stage using Probability Proportional to Size (PPS) sampling.

The sample introduced in 2019 was also stratified using administrative county and the Pobal HP (Hasse and Pratschke) Deprivation Index

 In the second or final sampling stage, each block is split into rotation groups each containing 20 households. Each quarter, one rotation group from within a given block is surveyed. This gave a total quarterly sample of 26,000 households in the QHNS. The final stage sampling method for the LFS was similar. However, to account for the additional attrition as a result of the introduction of mixed mode data collection, the LFS sample was increased incrementally from Q3 2017. An additional 1,300 households were included in Wave 1 for each quarter and this resulted in a total sample of 31,200 households in Q2 2018. As the sample was being increased by 1,300 households per Wave, the final design sample increased to 32,500 households from Q3 2018 onwards.    The LFS sample from Q1 2016  onwards was stratified using administrative county Pobal HP (Haase and Pratschke) Deprivation Index. A similar stratification was adopted for the 2016 sample for the QNHS. The 2012 QNHS sample was stratified using administrative county and population density.    8 5 waves in total. 20% of sample is replaced at each wave. 

 

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)
2.6% 130,000

  

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)
0.7%  Sample sizes: Q1=32,500,  Q2=32,500, Q3=32,500, Q4=32.500

  

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
The survey results are weighted to agree with population estimates broken down by age (5 year age groups), sex and region (NUTS 3 regions).  Results are then calibrated to broad national totals by broad age and gender.

The estimates are calculated as follows:
1. The previous quarter’s population estimate or census of population at regional level is used as the base population.
2. A quarter of this population is aged on by 1 year.
3. Births for the relevant period are added to each region – source = registered births.
4. Deaths for relevant period are subtracted from each region – source = registered deaths.
5. Net migration (inflows from other regions minus outflows to other regions plus inflows from abroad minus outflows to abroad) is added to each region – main source = LFS.

  N  The total population including private and collective households  Y  5 year age groups from 0 to 84 years and final group of all persons aged 85+  NUTS3 Calibration to nationality population estimates for 2 broad age groups (0-14 and 15+) and gender.

Results are adjusted for non-response.

 

 

 

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
 NA  NA  NA  NA  NA

 

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)
The household weight is taken as an average of all the weights of the members of the household  NA  NA  Age, sex and NUTS3 regions and nationality  N
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?
 Wave 1 interviews are carried out using using CAPI. The four follow-up interviews are conducted using Computer Assisted Telephone Interviewing (CATI) from a dedicated call centre, where householders have agreed to conduct a telephone interview, and are conducted using face-to-face interviews where householders have not agreed to conduct a telephone interview. However in March of 2020 all face to face or CAPI Interviewing was suspended for all social surveys due to the COVID-19 Pandemic. This suspension remained in force for the remainder of 2020. As a result, households selected to be included in the LFS sample received introductory letters by post asking them to call a dedicated number to schedule an interview. All interviews therefore were carried out over the phone from March 2020. Y  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 50.1*  38.7  0  0  11.2

* Designated for capi interview
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)
 The main LFS statistics at national level are highly relevant for all users (policy makers, other stakeholders, media and academic research); It is viewed as a key economic performance indicator of the domestic ecomony. 
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?
 Data is collected at LAU level. Lowest level of regional classification published or available to researchers is NUTS 3.  NUTS 3  NUTS 3 Unemployment and labour force data at NUTS 3 level is calculated directly from each quarterly dataset.
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
4653 7755 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  0.30  0.3  1.1  2.1  2.1  3.1  0.2
 SE  6538.2  0.2  4058.0  2853.4  0.1  0.5  0.07
 CI(**)  (2136756.4 2162286.2)  (72.9 73.8)  (354192 370099.3) (131081.4 142266.8)   (5.4 5.9)  (14.3 16.2)  (36.3 36.6)

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The CV for the number of employed persons (aged 20-64) and the employment rate (aged 20-64) are identical because the denominator of the employment rate (aged 20-64) is the total population (aged 20-64) which has a zero CV and the total population by age group are margins used in the calibration process.  

 

Reference on software used: Reference on method of estimation:
 SAS - creation of replicates using custom designed software which are then used to generate the variance measures required.  NR

 

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 
IE01 Northern and Western  0.79  0.79  2.78  5.04  4.50  13.56  36.71
IE02  Southern   0.54  0.54  1.89  3.56  5.36  12.62  36.23
IE03 Eastern and Midland  0,35  0.35  1.65  2.73  5.50  14.32  35.96

  

(*) 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
 UNA UNA  Census of Population is sampling frame  UNA  UNA  UNA

 (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 The 2020 LFS questionnaire was updated on a quarterly basis to comply with EU regulation and for the inclusion and exclusion of Eurostat/National module which changed quarter on quarter. Y The 2020 LFS questionnaire was tested both cognitively and operationally.  Cognitive testing was carried out by the Social Data Collection division of the CSO.   The questionnaire was internallly tested by Social Data Collection division and IT division.  This internal testing involved entering specific test cases into the questionnaire, recoding of question outcomes and reporting of findings of testing.   Findings from testing where reviewed and where applicable amendments were made to the 2020 LFS Questionnaire.

 

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  N
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 - CATI only  Y
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 N  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
 Y Various The adjustment involves estimating response rates or propensities to respond as functions of characteristics available for responding and non-responding households, as well as characteristics of the areas where the households are located. Basically, the design weights have to be inflated by the inverse of the response propensities in order to compensate for the loss of units in the sample.

Linking the LFS sample with the Census of Population at household level provides a set of auxiliary variables which are available for both responding and non-responding LFS households. These include a mix of personal characteristics as well as characteristics of the dwelling and location (e.g. gender, age, marital status, education, personal employment status, dwelling type, area etc.). This allows for the comparison of responding and non-responding households with respect to the characteristics available from the Census. This auxiliary information allows the use of “response propensities” to model non-response and adjust the grossing factors to compensate for non-response.

The response propensities are calculated using a logistic regression model where the dependent variable (Y) is an indicator variables corresponding to response (if the household responded then Y=1 and if the household did not respond then Y=0) and the independent variables are the set of auxiliary variables available from the Census. The estimated response propensities are then used to form adjustment cells or strata which are made up of respondents and non-respondents with similar estimated response propensities. Respondents within each cell/stratum are then weighted by the inverse of the observed response rate in that cell. This non-response adjusted weight is then used to inflate the original survey design weight to account for non-response. This approach is referred to as response propensity classification.
Substitution of non-responding units (Y/N) Substitution rate Criteria for substitution
 N  NA   NA 
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
 67.8  31.7 NA 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 54.7 11.0 28.7  Not available
2 59.5 10.4 60  Not available
3 60.2 9.8 67.6  Not available
4 60.3 8.8 71.1  Not available
Annual  57.9  10.1  58.3  Not available

 

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_Q1_2019 203      
Subsample_Q2_2019 373 416    
Subsample_Q3_2019 405 490 515  
Subsample_Q4_2019 489 566 614 611
Subsample_Q1_2020 482 474 516 571
Subsample_Q2_2020   92 169 225
Subsample_Q3_2020     107 164
Subsample_Q4_2020       153
Total in absolute numbers 1952 2038 1921 1724
Total in % of theoretical quarterly sample 6.0 6.3 5.92  5.3

 

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_Q1_2019 582      
Subsample_Q2_2019 817 1206    
Subsample_Q3_2019 910 1569 1518  
Subsample_Q4_2019 1214 2048 2015 1810
Subsample_Q1_2020 1578 2729 2491 2338
Subsample_Q2_2020   4032 3405 3116
Subsample_Q3_2020     3803 3237
Subsample_Q4_2020       3423
Total in absolute numbers 5101 11584 13232 13924
Total in % of theoretical quarterly sample 15.7  35.7  40.8 42.9

 

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_Q1_2019 UNA      
Subsample_Q2_2019 UNA UNA    
Subsample_Q3_2019 UNA UNA UNA  
Subsample_Q4_2019 UNA UNA UNA UNA
Subsample_Q1_2020 UNA UNA UNA UNA
Subsample_Q2_2020   UNA UNA UNA
Subsample_Q3_2020     UNA UNA
Subsample_Q4_2020       UNA
Total in absolute numbers Total Total Total Total
Total in % of theoretical quarterly sample        

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
IE01 (Nothern and Western)  62.2
IE02 (Southern)   56.1
IE03 (Eastern & Miland)  57.3

 

* 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_054 TEMPDUR 21 20.2 25.7 26.6  
compulsory Col_065/66 HWOVERP 11.4 24.6 15.8 15.2  
compulsory Col_067/68 HWOVERPU 11.6 24.6 16.3 15.5  
compulsory Col_073/74 HWWISH 80.5 80.2 80.6 82.5  

 

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_053 TEMPREAS 33.7  
compulsory Col_118 - Employed AVAIREAS 94.6  
compulsory Col_118 - Not employed AVAIREAS 14.4  
compulsory Col_121 REGISTER 100 Not currently collected
compulsory Col_146 WSTAT1Y 100 Not currently collected
compulsory Col_150/151 COUNTR1Y 100 Not currently collected
compulsory Col_152/153 REGION1Y C  
compulsory Col_154/155 INCDECIL 58.6 Question only asked to direct respondents due to sensitive nature of question
compulsory Col_200/203 HATYEAR 14.6  Not stated answers from respondents
optional Col_132 COURPURP 100 Not stated answers arise from respondents
optional Col_133/135 COURFILD 100 Not currently collected
optional Col_136 COURWORH 100 Not stated answers arise from respondents

(*) "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, the routing of the survey questionnaire ensures that all relevant questions to the individual are answered. The survey cannot proceed until they are answered. A series of edit checks are carried out on family unit coding and these are addressed manually. 0.8%
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 )
 N  NA
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
 NA  NA   NA 
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
Y Yes The seasonal adjustment of the LFS is carried out using X-13-ARIMA The seasonal adjustment of data from the QNHS between Q2 2011 and Q2 2017 was completed by applying the X-12-ARIMA model, developed by the U.S. Census Bureau. This seasonal adjustment methodology was reviewed following the introduction of the new LFS in Q3 2017. As a result of this review, from Q3 2017 onwards, the seasonal adjustment of the LFS is conducted using the X-13ARIMA-SEATS software also developed by the U.S. Census Bureau. The adjustments are carried out by applying the X-13-ARIMA model to the unadjusted data. This methodology estimates seasonal factors while also taking into consideration factors that impact on the quality of the seasonal adjustment, such as:
  • Calendar effects e.g. the timing of Easter
  • Outliers, temporary changes, and level shifts in the series

For additional information on the use of X-13ARIMA-SEATS see:

 http://www.census.gov/srd/www/x13as/

 Seasonal adjustment is conducted using the direct approach, where each individual series is independently adjusted. As a result of this direct seasonal adjustment approach it should be noted that the sum of any component series may not be equal to seasonally adjusted series to which these components belong, e.g. the seasonally adjusted number of males in employment and the seasonally adjusted number of females in employment will not necessarily add up to the total employment on a seasonally adjusted basis.

 The X-13-ARIMA method has the X-11 moving averages process at its core, but builds on this by providing options for pre-treating the series using a regARIMA approach for prior adjustment and series extension. In essence, this methodology will estimate seasonal factors while taking account of calendar effects (e.g. timing of Easter), outliers, temporary changes and level shifts.

 The seasonal adjustment is designed and implemented in full accordance with the ESS Guidelines (2015).
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 definitions 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

 

 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  NA  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 N NA 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 Work has been undertaken by the CSO to compare the differences in the numbers of persons employed as reported by the QNHS (LFS) and the Business Demography releases. See the background notes at the following link http://www.cso.ie/en/releasesandpublications/er/bd/businessdemography2016/ see previous box see previous box  see previous box 
Total employment by NACE see above see above  see above  see above 
Number of hours worked  see above   see above   see above   see above 

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
Ireland does not have a register of unemployment as such but instead we have a construct which is called the 'Live Register'. The Live Register contains data on the number of people (with some exceptions) registering for Jobseekers Benefit (JB) or Jobseekers Allowance (JA) or for various other statutory entitlements at local offices of the Department of Social Protection and was constructed historically at a time when the LFS was conducted annually and was therefore used as a short-term indicator on the Labour Market..
The Live Register is not designed to measure unemployment. It includes part-time workers (those who work up to three days per week), seasonal and casual workers entitled to JB and JA. Unemployment is measured instead by the QNHS/LFS which is based on ILO Labour Force classification		 The Live Register is a count of the number of persons who have registered with the Department of Social Protection for JB or JA or for various other statutory entitlements as per the concept described.

The QNHS/LFS measure of unemployment is according to the ILO Labour Force Classification. Persons classified as unemployed are those who, in the week before the survey, were without work and available for work within the next two weeks, and had taken specific steps, in the preceding four weeks, to find work. As per Eurostat operational implementation, the upper age limit for classifying a person as unemployed is 74 years.

 http://www.cso.ie/en/interactivezone/statisticsexplained/labourmarket/

 

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)
 No assessment is available as both measure different concepts  NA  NA  NA  NA  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 UNA UNA UNA UNA
Total employment by NACE UNA UNA UNA UNA
Number of hours worked UNA UNA 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)
N  N   N   N   N  Yes - CSO uses both LFS (sectors A, T, U) and Earnings Hours and Employment Costs Survey (EHECS) (sectors B-S) employment data for employees (both persons and hours worked) but uses LFS for self-employed data (persons and hours worked).
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
The core LFS release is published nationally in electronic format on a quarterly basis. This release contains 11 core tables along with 2 Annex tables. We continue to print paper copies of the release and tables for the main quarterly Press Conference.

The CSO website also hosts additional data in the PxStat data dissemination portal  and the Labour Market Analysis area also hosts 3 spreadsheets which provide a full time series of the tables we publish in the release, additional supplementary tables formerly in the release and a set of Full-Time Equivalent employment measures calculated from the QNHS.

An annual themed release focusing on Employment Data, first published in June 2015, is updated annually and the latest update was published on 25th June 2020. In addition, the latest update on the themed release focussing on Household and Family Units was  also published on 28th October 2020.  

A new series of Monthly Unemployment statistics was first released by the CSO in June 2015 for the reference month May and the most recent results were issued on June 30th for reference month June 2021.

To provide further context the LFS results during the pandemic the CSO began publishing a bulletin style  insights release to accompany the release of LFS results from Q3 2020. These releases provided additional data over and above what was contained in the standard results release.

In October 2020 and to coincide with the publication by Eurostat of the results of the EU adhoc module on 'Main place of work and commuting time 2019', The CSO published results for Ireland under three separate release headings: 

1. Labour Force Survey Bulletin : Main place of work and commuting time in 2019

2. Labour Force Survey Bulletin; Job autonomy and pressure at work in 2019

3. Labour Force Survey Bulletin: Flexibility at Work in 2019

Please see the following link for further information

https://www.cso.ie/en/statistics/labourmarket/
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
http://www.cso.ie/en/qnhs/qnhsmethodology/

https://www.cso.ie/en/methods/labourmarket/

 All data on our website is made freely available. The anonymised microdata file (AMF) available on the Irish Social Science Data Archive (ISSDA) is freely available to students and researchers for non-commercial purposes. These files create a substantial number of the captured variables.
We also create other microdata files (Research Microdata Files) (RMF) but access to this is only provided to 'Officers of Statistics' as prescribed under the Statistics Act, 1993. The Director General of the CSO is the only person entitled to grant the status of 'Officer of Statistics' to an individual. These files contain almost all variables captured and derived.		 All our publications include analysis text, graphs and background notes (outlining main methodological issues)

A detailed metadata file is made available with RMF and AMF data files

 Ad-hoc queries relating to data that is not available in the releases/publications.
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 All users subject to approval by the Director General of the Central Statistics Office Please see:

https://www.cso.ie/en/aboutus/lgdp/csodatapolicies/dataforresearchers/policies/

 All micro data files are accompanied by detailed metadata files.  Y - to answer any questions that users may have in interpreting the data or the variables in the data files
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

 Please see the attached link in relation to the LFS: https://www.cso.ie/en/methods/labourmarket/labourforcesurvey/
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 CSO does not have a standard policy but all variables that could lead to the identification of an individual or household are removed.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top