Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Lithuania


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

Statistics Lithuania
1.2. Contact organisation unit

Living Standard and Employment Statistics Division
1.5. Contact mail address

29 Gedimino Ave
LT-01500 Vilnius, Lithuania


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 ...
The Lithuanian Labour Force Survey is a private households survey. The population of the survey – all permanent residents of the Republic of Lithuania, living in private households, including those who are temporarily abroad for a period of less than one year. The population also includes foreign nationals who have been living in Lithuania at least a year. Housekeeping Members living regularly together in the same dwelling, sharing household expenditures, food and other essentials for living. Only members actually living in the selected private household are interviewed. Household is a person or a group of persons  sharing the same living accommodation and expenditures, including collective provision of vital needs.  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 Family home Family home Term address Family home Family home

 

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)                                  
 The reference weeks are distributed uniformly over the 13 weeks of the quarter.   
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)
The sample is constructed as follows: having selected a simple random sample of the fixed number of persons of the sampling frame, the members of their households are also included. Even in case turned out that according to the address denoted, a part of people or all of them were not included into the list of the sample, all household members actually living there were interviewed. The cluster sample of persons is thus obtained. All the persons living at the address selected belong to the same cluster. The actual composition of the cluster is indicated during the survey. The Population register. The Population register has some shortcomings: it suffers from the undercoverage and overcoverage; not all the addresses are included in the frame, part of them are imprecise, and it is impossible to follow the person selected up to his correct address. The Population register for persons of age under the survey coverage with the addresses of residence in towns and at least the name of the village in rural area is used as a sampling frame. This frame is actually used as a frame of addresses. The sampling frame is being updated every day.  NA  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.)
 NA The survey base is the Population register. The sampling unit is the person living in the private household. All household members are surveyed. The sampling plan is a one-stage simple random sample of about 2 000 households per quarter aged 15 years and over. NA  NA Each quarter, one-fourth of addresses is new and three-fourth of addresses come from the previous waves. Each dwelling is kept in the survey for four quarters. The rotation scheme is 2-(2)-2.

 

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)
 3.8% population 15 years and older per year  About 32 000 households per year

  

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)
 1.0% population 15 years and older per quarter  About 8000 households per quarter

  

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 weighting method for the Lithuanian LFS is based on the generalised calibration method introduced by Deville and Särndal in 1992. The initial household design weights are adjusted by the use of auxiliary information relating to population data on 60 municipalities and the intersection of 13 age-groups, sex and urban/rural living place. All household members have the same sampling weight. 
  Y  NA  Y 13 age groups (0-14,15-19, 20-24, 25-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75+ )  Municipalities (LAU)   Urban/rural living place 

 

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
 Yearly weights are calculated as the average of the quarterly weights.  Y  13 age groups (0-14,15-19, 20-24, 25-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75+ )   Municipalities (LAU) Urban/rural living place 

 

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)
 As described above.  N  Number of households, household size. Gender, 13 age groups (0-14,15-19, 20-24, 25-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75+ ), regional breakdown (LAU), urban/rural living place.  Y
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?
 At first respondents can answer the LFS questionnaire by themselves on the internet (CAWI). If they choose not to do so, interviews are conducted by face-to-face (CAPI) or telephone (CATI) according to the circumstances. The interview normally takes place during the week immediately following the reference week but never later than five weeks after the reference week.
The interview is on average about 13 minutes in the first interview and shorter in the subsequent interviews. If the target persons selected to the sample cannot be reached, a proxy may by used on certain conditions. 		  Y  Voluntary 

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 UNA  UNA  NA  UNA  NA
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 users of statistical information are State and municipal authorities and agencies, international organisations, the media, research and business communities, students, whose needs are satisfied without a breach of the confidentiality principle. 
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?
 LAU  NUTS 3, employement by municipalities (LAU)  NUTS 3  Used methods are the same as methods used for national level data produce.
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
 <1100  1100-4000  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  1.53  0.84  6.81  5.78  5.47  14.46  0.67
 SE  20674.64  0.64  5302.45  7231.39  0.46  0.28  0.23
 CI(**)  [1310659:1391662]  [75.33:77.86]  [67361:88136]  [111796:140128]  [7.62:9.44]  [14.16:25.00]  [34.40:35.91]

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 NR

 

Reference on software used: Reference on method of estimation:
 Clan 97-a SAS program for computation  of point and standard error estimates in sample survey.  Calibration

 

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 
LT01 Sostinės regionas  3.31  1.32  13.33  12.77  12.04  31.97  3.19
LT02 Vidurio ir vakarų Lietuvos regionas  2.05  2.26  7.99  6.51  6.09  16.10  1.66

 

(*) 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  1%  UNA  UNA  Among not interviewed households, in 371 cases (1% of total number of sampled households) the reason was an error or inaccuracy of the frame (imprecise address, the premises at the indicated address are non-residential (a hairdresser’s, shop, etc.), the building was knock down,  etc).   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 2019 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 Questions related to informal education hve been updated .  Y  Internal check

 

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  N  Y
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 Y  Y
Other / Comments   Explanatory notes for interviewers.
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 Sex, age, urban/rural, administrative teritory Parameters are estimated using a calibration method. Weights for households classified according to the inequality probabilities of household dependency to the sample.  For the calculation of weights, demographic data are used.
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
 UNA  UNA  NA  UNA  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 23.2 27.41  71.05 UNA
2 28.3 18.82  80.16 UNA
3 20.7 44.44  53.73 UNA
4 17.8 40.67  56.85 UNA
Annual  NR  NR  NR UNA

 

 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  103      
Subsample_Q1_2019  427  146    
Subsample_Q2_2019    286  271  
Subsample_Q3_2019      285  188
Subsample_Q4_2019  350      210
Subsample_Q1_2020  701  255    
Subsample_Q2_2020    609  937  
Subsample_Q3_2020      799  367
Subsample_Q4_2020        765
 Total in absolute numbers  1581  1296  2292  1530
 Total in % of theoretical quarterly sample  6.75%  5.54%  9.13%  6.54%

 

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  618      
Subsample_Q1_2019  828  819    
Subsample_Q2_2019    1046  533  
Subsample_Q3_2019      523  364
Subsample_Q4_2019  855      420
Subsample_Q1_2020  1797  1274    
Subsample_Q2_2020    2381  770  
Subsample_Q3_2020      912  628
Subsample_Q4_2020        854
 Total in absolute numbers  4098  5520  2738  2266
 Total in % of theoretical quarterly sample  17.49%  23.58%  10.91%  9.68%

 

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 NA      
Subsample_Q1_2019 NA NA    
Subsample_Q2_2019   NA NA  
Subsample_Q3_2019     NA NA
Subsample_Q4_2019 NA     NA
Subsample_Q1_2020 NA NA    
Subsample_Q2_2020   NA NA  
Subsample_Q3_2020     NA NA
Subsample_Q4_2020       NA
 Total in absolute numbers NA NA NA NA
 Total in % of theoretical quarterly sample NA NA  NA  NA

 

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

LT01 Sostinės regionas

 29.99%

LT02 Vidurio ir vakarų Lietuvos regionas

  20.89%

* 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_114 - Employed METHODL . . . C This method used to find  work is not very popular among employed respondents.

 

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_154/155 INCDECIL 18.2  
optional Col_132 COURPURP 100  Variable is not collected because it is optional.
optional Col_133/135 COURFILD 100  Variable is not collected because it is optional.
optional Col_136 COURWORH 100  Variable is not collected because it is optional. 

(*) "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  UNA
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
 INCDECIL  UNA  Administrative data from State Social Fund Boart database are used for imputation of missing values for the INCDECIL variable.
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  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 Y Updated  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 The LFS data includes total employment (employees, self-employed with employees, self-employed without employees, family workers). All persons who worked at least one hour or more for pay or profit in the reference week are considered to have been employed.
The Business statistics data includes only employees who working under written employment contract. Also employees number excludes persons on parental, maternity or paternity leave who are calculated in LFS.		  The LFS is a sample survey. Data are collected from private households.
In Business statistics the statistical unit is an enterprise, institution or organization.		 In 2020, the Business Statistics shows 4.5% more employees than the LFS.   No official publication.
Total employment by NACE  Identical to total employment  Identical to total employment In 2020, the highest number of employees difference by activity in the LFS compared to the Business statistics was observed in H, L activities. The lowest difference in C activity was about 1.1%.  No official publication.
Number of hours worked  The main differences are:
  • in the LFS hours usually worked (the typical length of a working week over a longer period of time) and average number of hours actually worked in the main job and second job (hours worked in the reference week) are collected;
  • in Business statistics average number of hours actually worked per employee per week are calculated;
  • in Business statistics average number of hours actually worked per employee per week in main and second job are collected;
  • in Business statistics number of average number of hours actually worked per employee per week in individual enterprises are excluded. 
  UNA In comparison of the employees number of hours actually worked in 2020, the Business statistics shows 2.93% less than the LFS.  No official publication. 

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
Statistics Lithuania estimates and publishes the number of the unemployed based on an ILO definition of the term “unemployed”.

The Lithuanian Labour Exchange uses the term “unemployed” as defined in the Law on Support for Employment of the Republic of Lithuania according to which an unemployed person means a jobless person of working age capable of work who does not study under either a general or a formal vocational education curriculum or is not a full-time student in higher education and has registered with the local labour exchange in the manner laid down by law.

 The unemployment rate published by Statistics Lithuania is estimated based on the Labour Force Survey data, and is expressed as a ratio of the unemployed to the labour force. Labour force means the total employed persons and the unemployed.

The Lithuanian Labour Exchange publishes data on registered unemployment, expressed as a ratio of the unemployed registered with the labour exchange to the working-age population.

  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)
In 2020, the total number of registered unemployed persons was by 41.7 percent higher than the LFS estimate.  NA (data is not available for all months) NA (data is not available for all months) NA (data is not available for all months) NA (data is not available for all months) Alytaus county -33.01%
Kauno county -44.26%
Klaipedos county -47.40%
Marijampoles county -37.84%
Panevezio county -38.40%
Siauliu county -38.71%
Taurages county -26.04%
Telsiu county -52.31%
Utenos county -23.13%
Vilniaus county -46.14% 
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 The main differences between the employment definitions of Lithuanian LFS and ESA 2010 are:
- according to ESA 2010 employment includes also non-residents working for resident producer units while LFS does not include them;
- according to ESA 2010 employment does not include residents who are working abroad while LFS does.		 For using in National Accounts, the Lithuanian LFS data is adjusted as much as possible to ESA 2010 definition. NA estimates are calculated on LFS database.   Difference 0,6%   No official publication. 
Total employment by NACE  Identical to total employment   Identical to total employment   Identical to total employment   No official publication. 
Number of hours worked  No difference   NA  NA   No official publication. 

 

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  Y  N  N  N  N
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
Statistical information is published in news release Employment and unemployment (not later than on the 48 day after the end of the reference period), monthly publication Economic and Social Development in Lithuania, annual statistical publications Labour Market Yearbook, Statistical Yearbook of Lithuania, and etc. More information on the issue is available on the Official Statistics Portal (http://osp.stat.gov.lt/en/home). 
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
LFS methodology (http://osp.stat.gov.lt/en/metodai18)
is available on the Official Statistics Portal (in Lithuanian only)		 All statistical information, publications and news releases  are available for users on the Official Statistics Portal. Also there is a library in Statistics Lithuania, for users who wants to use printed or scaned information. Most of information request come straight to the Living Standards and Employment Statistics Division. If request is not exceptional or complicated it is answered within ten working days starting from the working day following the registration of the request for information. If specific LFS data is required, user must contact with Statistics Lithuania bookstore, where special request form is filled. 

Metadata (http://osp.stat.gov.lt/en/metainformacija32)  are available on the Official Statistics Portal (http://osp.stat.gov.lt/en/home).

LFS questionnaire is available on Statistics Lithuania web page (http://apklausos.stat.gov.lt/en/statistines-anketos) 

 In case of better contact with users there is a possibility to ask questions on the website of Statistics Lithuania, LFS description and definition are published (in Lithuanian and English languages). Either meetings with users and  media representatives are organised. The anonymous  LFS micro database is available for users from  research institutions. For confidentiality reasons some data (name, address, birth date, name of the workplace,  etc) are excluded from database and some data are given only by major groups (economic activity, occupation, etc). Public use files are available on Official Statistics Portal (http://osp.stat.gov.lt/en/viesos-duomenu-rinkmenos/-/asset_publisher/i2LnhXkrXAbl/content/ketvirtinio-gyventoju-uzimtumo-statistinio-tyrimo-?redirect=http%3A%2F%2Fosp.stat.gov.lt%2Fviesos-duomenu-rinkmenos%3Fp_p_id%3D101_INSTANCE_i2LnhXkrXAbl%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_p_col_id%3Dcolumn-1%26p_p_col_pos%3D3%26p_p_col_count%3D5). 
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 Confidential statistical data can be provided for scientific purposes to the researchers of national and foreign higher education and research institutions and research institutes as defined in the Law on Higher Education and Research of the Republic of Lithuania. Description of Procedures for the Provision of Confidential Statistical Data for Scientific Purposes 
https://osp.stat.gov.lt/documents/10180/3291062/Konfidencialumo_tvarkos_aprasas.pdf		 Further information can be found on Official Statistics Portal:

https://osp.stat.gov.lt/duomenys-mokslo-tikslams
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
 "Explanatory notes for interviewers conducting Labour Force Survey", Vilnius, 2020. 
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
 In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees the confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of Statistics Lithuania. 
Data confidentiality is regulated by Integrated Statistical Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the Integrated Statistical Information System, approved by Order No DĮ-42 of 20 February 2015 of the Director General of Statistics Lithuania.
During the preparation of Lithuanian LFS microdata, it is ensured that direct or indirect identification of respondents is not possible.
Microdata are accessible for scientific purposes and can be provided according to the Description of Procedures for the Provision of Confidential Statistical Data for Scientific Purposes of Statistics Lithuania.
More detailed information is available in a document Data for scientific purposes under agreements (only in Lithuanian).


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top