Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Central Statistical Bureau of Latvia


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 Statistical Bureau of Latvia
1.2. Contact organisation unit

Social Statistics Methodology Section
1.5. Contact mail address

1, Lacplesa Street, Riga, Latvia, LV 1301


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 ...
Geographical:  Whole country.
Population groups: The population were residents of Latvia.		 Housekeeping Members living regularly together in the same dwelling, sharing household expenditures. Persons are excluded from the household, if they are not preserving family relations with the household one year and more.   15-74

 

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 Family home 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)                                  
 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)
The sampling design is a stratified two-stage sampling design. Two sampling frames are built for each sampling stage due to two-stage sampling is used. At the first stage the list of sampling areas is used as sampling frame. The sampling areas are territories. Territories contains information about the number of dwellings in each sampling area.

At the second stage sampling frame is built from the Demographic Statistics Data Processing System. The Demographic Statistics Data Processing System includes data from Population register, The National Real Estate.

 2 month before each calendar quarter for the second stage sampling frame. Sampling areas- territories are used as the primary sampling units   Dwelling

 

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 sampling areas are selected from each stratum using systematic sampling with probability proportional to size. The final sampling units are selected from the PSUs by a simple random sampling method in each sampled PSU. The strata were defined by type of territory (capital city - Riga, eight other cities of Republic, towns and rural areas formed four strata).   4 Rotation scheme- each household was interviewed four times
(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)
 Overall yearly sample rate in 2020 is about 3.54%  Size of the yearly sample was 29952 dwellings

  

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)
Overall theoretical quarterly sampling rate in 2020 is about 0.89%  7488

 

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)
 Wave 1  Y  NA  See file attached

 

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 initial weights are calculated according to the sample design, with all persons within the same PSU having equal design weights. The design weights are adjusted using the data of response level in each strata for each wave and each mode (CAPI/CATI). These weights were then adjusted on the basis of demographic data,State Employment Agency and State Revenue Service information.

For adjustment of the quarterly weights demographic data are broken down by type of municipality (as in stratification), 14 age groups and sex  as well as in NUTS 3 (6 regions), 3 age groups, eight cities of Republic, the information from the State employment agency by sex and 5 age groups and the information from the State Revenue Service by sex and 7 age groups.

  Y  NA  Y (0-14; 15-19; 20-24; 25-29; 30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-69; 70-74; over 75)  NUTS-3  Type of municipality

 

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 design weights were divided by four and corrected based on the non-response.  Design weights were adjusted using response homogeneity group method. The design weights were adjusted using the data of response level in each stratum for each mode (CAPI/CATI).

Calibration was applied using raking-ratio method.

Average annual statistics on usually resident population living in Latvia households (by sex, 5-year age group, in territorial breakdown) as well as the State Employment Agency (SEA) data on registered unemployed persons (by age group on average per year) were used as the auxiliary information for the weights calibration.

To meet the requirements of the Regulation No 377/2008 Annex 1 Clause 3 on the consistency of totals, in the weights calibration additionally also LFS full-sample employment, unemployment and inactive population estimated by sex and 10-year age group were used. 

  Y (0-14; 15-19; 20-24; 25-29; 30-34; 35-39; 40-44; 45-49; 50-54; 55-59; 60-64; 65-69; 70-74; over 75)  NUTS-3  Type of territory 

 

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 initial weights are calculated according to the sample design, with all households within the same PSU having equal design weights. The design weights are adjusted using the data of response level in each strata for each wave and each mode (CAPI/CATI). These weights were then adjusted on the basis of demographic data.  NA  NA For adjustment of the quarterly weights demographic data are broken down by type of territory (as in stratification), 14 age groups and sex as well as in NUTS 3 (6 regions), 3 age groups, eight large cities, the information from the State employment agency by sex and 5 age groups and the information from the State Revenue Service by sex and 7 age groups.  Y


Annexes:
Yearly variables in LV LFS
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?
 There are 3 data collection modes in Latvian LFS. CAWI was introduced from 2018. Face to face interviews by using portable computer (CAPI interviews) and telephone assisted interviews (CATI ) are conducted by interviewers of the Interviewer's Co-ordination Section and Household Survey Preparation and Supervision Section. The interviewing is normally done during the week immediately following the reference week. The 1st interview is only CAPI, ,  in 2nd - 4th interviews CAWI,CATI, CAPI.  Y  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 10.6 84.0   NA  5.4 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)
 Most frequently policy makers, academic researchers, media and students asked information on employment (number and rate, by socio-demographic breakdown (age, sex, education) by territorial NUTS 3 breakdown, by economic activity (NACE) breakdown), unemployment (number and rate, by socio-demographic breakdown (age, sex, education),by territorial NUTS 3 breakdown),  long-term unemployment and youth unemployment.
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 3  NUTS 3  NUTS 3  The method is annual average from LFS data set.
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
  Under 1.8 thousand persons  
  1.8 - 2.5 thousand persons   Under 1.6 thousand persons 1.6 - 2.3 thousand persons
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  0.32  0.32  3.39  2.70  2.61  9.34  0.28
 SE  2.74  0.25  2.50  2.13  0.21  1.39  0.11
 CI(**)  842.41; 853.15  76.53; 77.51 68.77; 78.56  74.52; 82.86  7.68; 8.51  12.15; 17.60  38.14; 38.55 

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The denominator of the emloyment rate is the population size in the age group 20-64. The number of population in age group 20-64 was used as a margins in the calibration.

 

Reference on software used: Reference on method of estimation:

R software (package "vardpoor" - https://cran.r-project.org/web/packages/vardpoor/)

 Ultimate cluster method (Hansen, Hurwitz and Madow, 1953) and based on the Berger and Priam (2010) method with linearization for non-linear statistics and residual estimation from the regression model to take weight calibration into account.

 

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 0.81  UNA  UNA  Reasons are not analysed  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)?
N  NA  Y  NA

 

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  Y
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
 Y Stratum, wave  and type of the interview (CAPI or CATI) is used to adjust the unit non-response.   Response homogeneity groups
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
64.08%  21.58%  NA  43.81%  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 39.67 10.78  23.63  UNA
2 47.22 7.60 22.66  UNA 
3 39.86 8.85 22.62  UNA 
4 39.69 9.09 18.40  UNA 
Annual 41.61  9.08  21.83  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  209       
Subsample_Q1_2019  223  96    
Subsample_Q2_2019   144   152  
Subsample_Q3_2019     140   121
Subsample_Q4_2019  205      181
Subsample_Q1_2020  149 118     
Subsample_Q2_2020   210  152   
Subsample_Q3_2020     218   181
Subsample_Q4_2020        196
 Total in absolute numbers  786  568  662  679
 Total in % of theoretical quarterly sample  10.50  7.59  8.84  9.07

 

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  395      
Subsample_Q1_2019 412   423    
Subsample_Q2_2019   343   422  
Subsample_Q3_2019     327   350
Subsample_Q4_2019 455      328 
Subsample_Q1_2020 461  345     
Subsample_Q2_2020   582  602   
Subsample_Q3_2020     340  358 
Subsample_Q4_2020       338 
 Total in absolute numbers  1723 1693  1691   1374
 Total in % of theoretical quarterly sample  23.01  22.61  22.58  18.35

 

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 wave 4      
Subsample_Q1_2019 wave 3 wave 4    
Subsample_Q2_2019   wave 3 wave 4  
Subsample_Q3_2019     wave 3 wave 4
Subsample_Q4_2019 wave 2     wave 3
Subsample_Q1_2020 wave 1 wave 2    
Subsample_Q2_2020   wave 1 wave 2  
Subsample_Q3_2020     wave 1 wave 2
Subsample_Q4_2020       wave 1
 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 (%)
 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_084 EXISTPR 31.1 24.9 24.5 25.2  Persons aged 75+ were not interviewed
compulsory Col_110 - Not employed METHODH C C . .  Method was not frequently used
compulsory Col_113 - Employed METHODK C . . .  Method was not frequently used
compulsory Col_114 - Employed METHODL . C . C  Method was not frequently used
compulsory Col_115 - Not employed METHODM . . . C  Method was not frequently used
compulsory Col_123 EDUCSTAT 15 11.4 10.8 11.3  Method was not frequently used
compulsory Col_128 COURATT 15.2 11.4 10.9 11.4  Method was not frequently used
compulsory Col_197/199 HAT11LEV 15 11.3 10.8 11.3  Persons aged 75+ were not interviewed

 

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_146 WSTAT1Y 10.1  Persons aged 75+ were not interviewed
optional Col_122 MAINSTAT 10.1  Persons aged 75+ were not interviewed

(*) "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  8.4%
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  0.5%
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
 Monthly (take-home) pay  18.7%  In case when respondent doesn’t give an answer about monthly (take-home) pay (neither direct sum, nor monthly pays interval) is used auxiliary information from State Revenue Service (SRS) database.
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  Y  Y 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  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 The LFS data includes total employment ,that is, all persons who worked at least one hour in the reference week are considered to have been employed. It is not relevant - the job is officially registered or not.
The Business statistics data includes full-time and part-time employees working under employment contract.		 The LFS is a sample survey. Data are collected from households.
In Business statistics the statistical unit is an enterprise, institution or organization. State and municipal institutions and organizations and enterprises with more than 50 ( in trade - 20) employees are enumerated completely. From enterprises with 50 or less employees (in trade - with 20 or less) a sample is selected.
Farmer households and private households employing domestic staff are not covered by Business statistics.		 Employees in 2020 (annual average, thousands) LFS: 779.5

 Business statistics: 594.6

 Difference:  60%

 Available only in working papers.
No official publication.
Total employment by NACE The LFS data includes total employment ,that is, all persons who worked at least one hour in the reference week are considered to have been employed. It is not relevant - the job is officially registered or not.
The Business statistics data includes full-time and part-time employees working under employment contract.		 Idem Assessment of the effect of differences of  employees in LFS and Business statistics.

A -60%      B -20%        C -19%
D -7%        E -6%          F -52%
G -14%      H -23%        I -44%
J -9%         K -35%        L -11%
M -28%      N -28%        O -14%
P -8%        Q -19%       R-49%          S -49%

 Idem
Number of hours worked In the LFS hours usually worked  and hours actually worked (hours worked in the reference week) are collected. Data are published as weekly hours.
In the Business statistics hours actually worked are collected. Data are published as total per year.		  Idem  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
LFS
Unemployed persons (both registered and non-registered with the State Employment Board) are persons who do not work and are not temporarily absent from work, are actively seeking a job and immediately available for work if they find it.
The registered unemployed
according to the Law of the Republic of Latvia  “On Employment” (considered as unemployed) is a non-working citizen of the Republic of Latvia or a foreigner (without any citizenship) who has received a licence for permanent stay or who has a mark of the Population Register with identity code in his/her passport, is of working age, able to work, is not engaged in entrepreneurial activities, is looking for work and is registered with the State Employment Agency according to his/her officially registered address and applies to it at least once a month.		 Some population groups are considered as unemployed in LFS and not in registered unemployment and vice versa.
The LFS data are collected by means of sample survey.
The registered unemployment data are collected by means of registration in the state employment office. Registration in State Employment Agency is voluntary.		  Statistical yearbook of Latvia 2019, Riga 2020, p. 76.

 

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)
13% 135% 37% 52% - 14% LV003 Kurzeme - 2%

LV005 Latgale -14%

LV006 Riga 37%

LV007 Pieriga  23%

LV008 Vidzeme 30%

LV009 Zemgale 10%
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 Latvian LFS and ESA 2010 are the following:

1. according to ESA 2010 conscripts are employees while LFS defines them as economically inactive population;

2.  according to ESA 2010 employment includes also non-residents (foreigners staying less than one year in Latvia) working for resident producer units while LFS does not include them;

3. according to ESA 2010 employment includes voluntary employees if their volunteer activities result in goods, e.g. the construction of a abode, church or other building, while LFS does not;

4. according to ESA 2010 employment does not include residents who are working abroad or in the extra-territorial organisations in Latvia while LFS does. National Accounts data includes estimates of employment in enterprises not covered by surveys and hidden employment.		 For using in National Accounts, the Latvian LFS data is adjusted as much as possible to ESA 95 definition i.e. conscripts are included to employment and residents who are working abroad or in the extra-territorial organisations are excluded from employment. This means that LFS data used by National Accounts deviate from the ESA 95 definitions only by not including the foreign workers and volunteers (these groups are not measured in Latvian LFS). Share of non-residents in total employment is not significant.

Number of foreign workers and volunteers is not available.

 Available only in working papers.

No official publication
Total employment by NACE  Idem  Idem  Idem  Idem
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)
 Y  N  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
The news releases were published (in 22.05.2020, 17.08.2020, 16.11.2020, 24.02.2021) on the Internet web site Oficial ststistics portal www.stat.gov.lv. Quarterly LFS results were published on the Oficial stistics portal each quarter-in 22.05.2020 of the first quarter, in 17.08.2020 of the second quarter, in 16.11.2020 of the third quarter, in 24.02 2021 of the fourth quarter of 2020 and results for 2020.
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
Link to national web page (Latvian) https://stat.gov.lv/lv/metadati/4285-nodarbinatiba-un-bezdarbs/sims2
Link to national web page (English)https://stat.gov.lv/en/metadata/4285-employment-and-unemployment/sims2  
 The news releases are available on the Internet web site, the results of quarters and year are published on the  Oficial ststistics portal, The results of year are published  also in the "Statistical Yearbook of Latvia" and other publications of the Central Statistical Bureau of Latvia. On the Internet CSB website are available description of methodology. Enlarging available information on the Internet web site of Oficial statistics portal
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, institutions. The Latvian LFS database is available for users from state and research institutions only in anonymous format. For confidentiality reasons some information (name, address, exact birth date, name of the workplace, description of occupation, etc) is excluded from database. The special contract between Central Statistical Bureau of Latvia and data user stipulates the strict conditions of  use. Detailed description on microdata file. No changes are planned in nearest future.
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
Link to national web page (Latvian)  https://stat.gov.lv/lv/metadati/4285-nodarbinatiba-un-bezdarbs/sims2
Link to national web page (English)   https://stat.gov.lv/en/metadata/4285-employment-and-unemployment/sims2
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
Anonymized microdata are accessible only for scientific and educational purpose. Anonymizing of microdata is realized according to rules of data dissemination. CSB of Latvia concludes agreement with scientists/researchers on delivery of anonymized microdata them.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top