Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Estonia


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 Estonia
1.2. Contact organisation unit

Population and Social Statistics Department

Statistics Design Department
1.5. Contact mail address

Tatari street 51, 15174 Tallinn, Estonia


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 target population comprises all persons (living both in private and institutional households) aged 15-74 years with permanent residence in Estonia, i.e. the people who have lived or intend to live in Estonia for more than one year.		 Dwelling A household is a group of people who live in a common dwelling (at the same address) and share joint financial and/or food resources. Persons included in the household are members of the household. A household may also consist of one member only.
Temporarily absent household members should be considered members if they have no other main dwelling, have retained economic ties with the household and their absence is shorter than 1 year; are children absent due to studies or a partner absent due to work.		  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), including people living in institutions Family home Family home (if economically dependent). Family home (if they share income and family ties are kept) 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)
 Y  N
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 systematic sampling of individuals, whose households are included in the sample. A list of 15–74-year-old permanent residents of Estonia compiled based on the population and housing census (2011) and the Population Register  15/06/2020  NA Individual (all household members are interviewed)

 

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 sample is selected by systematic stratified sampling of individuals. All persons aged 15-74 years belonging into household of selected individual are interviewed. The 15 counties of Estonia and Tallinn are divided into four strata according to the population size (I – Tallinn, II – four bigger counties, III – ten smaller counties, IV – Hiiu county) and different inclusion probabilities are used in stratas, the highest being for Hiiu county. 4 Every sampled household is interviewed four times; during two consecutive quarters and after a two-quarter period they are again interviewed twice in the corresponding quarters of the following year. According to such a 2-(2)-2 rotation plan every quarter 25% of the households are participating in the survey for the first time. 50% of the households were also interviewed in the preceding quarter and 50% were interviewed in the same quarter of the previous year (including 25% of the households interviewed in the previous quarter and also in the same quarter of the previous year).

 

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)
2.9%  18 000 households

  

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)
 0.73%  4 500 households

   

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 weights are formed in a sequence of steps. A weight resulting from the previous step is multiplied by the correction factor calculated at the current step. The correction factors are scaled in such a way that their sample average is unity at each step. As a result, the final weight is a product of the initial weight and correction factors.
As stratified sampling is used on the first step of sample formation, first the initial weight that is inversely proportional to the inclusion probability in each strata is calculated.
For non-response adjustment the non-response correction factors are computed. The response homogenity groups of reasonably uniform size of sampled households are formed on the basis of the place of residence of the household according to the non-response rate in the region. Within each group the correction factor is inversely proportional to the overall response rate in the region.
In the next step the weights are calibrated so that they produce exact population numbers in certain subgroups known from demographic data (including institutional population). For working-age persons the subgroups by sex, age (5-years age groups), the place of residence (urban/rural area, 15 counties (LAU) and the capital city) and Estonians/non-Estonians are considered. For this purpose the Linear consistent weighting method is applied. For nonworking age persons the non-calibrated household's weights are calibrated by sex and 5-years age groups.		  N  

The sample population aged 15-74 (including private and collective households) is expanded to the total population aged 15-74 (including private and collective households). 

The population aged 75+ (including private and collective households) is expanded to the total population aged 75+ (including private and collective households). 

  Y Age groups: 0-4, 5-9, 10-14, 15-19, … , 70-74, 75-79, 80-84, 85+ LAU Urban - rural population, Estonians - non-Estonians

 

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 by dividing the quarterly weights by 4  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)
 See core weights  See core weights  See core weights  See core weights  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?
Data collection method is computer assisted personal interviewing (CAPI). Since 2012, during later waves (2nd, 3rd and 4th waves) in exceptional cases interviews may be carried out by phone (CATI). Since 2016, during later waves (2nd, 3rd and 4th waves) the interviews with repondents from households with 1 or 2 working-aged members are mainly CATI-interviews and with repondents from households with more than 2 working-aged members are CAPI-interviews. Since 2018, during the later waves (2nd, 3rd and 4th waves) most of the interviews are CATI-interviews.

All interviews are conducted by interviewers of the Interviewers Network Department of Statistics Estonia. The interviewing is normally done during the week immediately following the reference week but never later than during the five weeks following the reference week, since 2012 never later than during the three weeks following the reference week, since 2013 never later than during the two weeks following the reference week.

  N Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 18  82  NA NA  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)
Since 1996 the Statistical Office conducts reputation surveys and user surveys. The survey is conducted at least once a year, the existing as well as potential consumers are interviewed.
The aims of user surveys are:
  • to find out the reputation of the Statistical Office among consumers,
  • to find out the need for statistical information,
  • to study the consumers’ preferences in using various statistical products,
  • to get the necessary information for production development.
The results of the surveys are applied for better serving the consumers, as well as in improvement of products.
All results are available on the website http://www.stat.ee/user-surveys.
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 5 (rural municipality/town) NUTS 4 (county) NUTS 5 (rural municipality/town) In 2004-2011, annual average labour force data and 3-year average unemployment data of the Estonian LFS by sex, age (15-24,25+) and NUTS3 region were sent to Eurostat. Since 2009, NUTS3 code is included in the LFS microdata sent to Eurostat for calculation of regional indicators.
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
CV: 30%; Size: 1 000   CV: 20%; Size: 2 400   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  0.79  0.53  3.31  3.90  3.81  7.86  0.33
 SE  4842,92  0.42  2410.02  1868.53  0.26   1.40  12.40
 CI(**)  604459.88; 623444.12  77.79; 79.42  68124.37; 77571.63  44269.67; 51594.33  6.30; 7.31  15.12; 20.62  13.32; 61.91

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 Estimated total number of population, aged 20-64 

 

Reference on software used: Reference on method of estimation:
 SAS  Taylor expansion method 

 

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

Number of employed persons

Employment rate as a percentage of the population

Number of part-time employed persons

Number of unemployed persons

Unemployment rate as a percentage of labour force

Youth unemployment rate as a percentage of labour force

 Average actual hours of work per week(*)
   

Age group: 20 - 64

Age group: 20 - 64

Age group: 20 - 64

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24

Age group: 20 - 64 
EE00 Eesti 0.79 0.53 3.31 3.90 3.81 7.86 0.33

(*) 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  NA  NA In 2020, 13 284 households of 18 688 households sampled for the survey, were interviewed. Among the households not interviewed, in 197 cases (1.1% of total number of sampled households) the reason was an error or inaccuracy of the frame (person emigrated or left the county, person deceased, wrong address, etc). By counties the share of frame errors varied from 0.2% to 2.4%.  NA  NA Estonian Labour Force Survey. Methodology. https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701

 

(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  AHM included  Y  Pilot survey

 

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

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

IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *

Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N) Variables used for non-response adjustment Description of method
 Y Sex, 5-years age groups, urban/rural area, Estonians/non-Estonians, county  1. Non-response correction. Design weights are corrected according to different response probabilities according to place of residence (county and urban/rural), sex and 5-year age group.
 2. Calibration by sex and 5-years age groups and the place of residence (county) using a linear consistent weighting method. It is based on the distribution of the Estonian population by sex, age, urban/rural area, Estonians/non-Estonians and county as of 1st January of the reference year. 
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
 45.1  23.1  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 28.65  14.08  13.37  16.06
2 25.11  12.92  10.71  44.78
3 29.28  12.92  10.71  24.59
4 29.24  14.46  14.12  53.97
Annual 28.16  13.98  3.12  24.44

 

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 55      
Subsample_Q1_2019 76 42    
Subsample_Q2_2019   98 53  
Subsample_Q3_2019     84 50
Subsample_Q4_2019 136     89
Subsample_Q1_2020 369 160    
Subsample_Q2_2020   291 179  
Subsample_Q3_2020     365 148
Subsample_Q4_2020       390
 Total in absolute numbers 636 591 681 677
Total in % of theoretical quarterly sample        

 

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 38      
Subsample_Q1_2019 50 7    
Subsample_Q2_2019   13 12  
Subsample_Q3_2019     9 5
Subsample_Q4_2019 79     15
Subsample_Q1_2020 219 18    
Subsample_Q2_2020   29 20  
Subsample_Q3_2020     20 14
Subsample_Q4_2020       29
 Total in absolute numbers 386 67 61 63
Total in % of theoretical quarterly sample        

 

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 1      
Subsample_Q1_2019 6 2    
Subsample_Q2_2019   8 3  
Subsample_Q3_2019     3 1
Subsample_Q4_2019 5     8
Subsample_Q1_2020 50 9    
Subsample_Q2_2020   11 3  
Subsample_Q3_2020     6 9
Subsample_Q4_2020       16
 Total in absolute numbers 62 30 15 34
Total in % of theoretical quarterly sample        

 

Non-response rates by survey mode. (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
EE00-Eesti 28.16

* 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_110 - Employed METHODH . . C . Small figures due to very few cases if any.
compulsory Col_110 - Not employed METHODH . . C . Small figures due to very few cases if any.
compulsory Col_111 - Employed METHODI C C C . Small figures due to very few cases if any.
compulsory Col_111 - Not employed METHODI . C . . Small figures due to very few cases if any.
compulsory Col_113 - Employed METHODK C . . . Small figures due to very few cases if any.
compulsory Col_114 - Employed METHODL C C . . Small figures due to very few cases if any.

 

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 18.4   Persons having ‘no preference’ (D15=3 in the ELFS questionnaire ) are coded as ‘blank’. The variable will be improved during the next revision of the questionnaire (then implementing the IESS Framework Regulation).

(*) "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 )
 N  NA
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 18.23
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
 INCDECIL 18.23  Individual's salary is imputed using SAS macro IVEWare with the combination of hot-deck method. The stratification is done by county, gender, age groups and urbanization type. No auxiliary information is used.
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  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 (employees, employers, own-account workers, unpaid family workers). It is not relevant from the point of view of the survey whether the job is officially registered or not. All persons who worked at least one hour in the reference week are considered to have been employed.
The Business statistics data (wages statistics) includes full-time and part-time employees working under employment contract, service contract and Public Service Act. Data are published in full-time units.		 The LFS is a sample survey. Data are collected from households.
In Business statistics (wages statistics) the statistical unit is an enterprise, institution or organisation. State and municipal institutions and organisations and enterprises with more than 49 employees are enumerated completely. From enterprises with 49 or less employees a sample is selected.		 Employees in full-time units, 2020
(annual average, thousands)
LFS       586,3
Wages  472
Difference -19%		 Methodology of the LFS see https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701 
Total employment by NACE See row "Total employment" See row "Total employment"  
  LFS Wages Differences
A 13,0  11,5  -12% 
B_E 123,7  98,3  -21% 
C 11,6  87,8  -21% 
F 48,5  33,1  -32% 
G_J 163,8  133,8  -18% 
K_N 63,8  54,1  -15% 
O_U 173,5  141,2  -19% 
Total 586,3  472  -19% 
See row "Total employment"
Number of hours worked In the LFS hours usually worked (the typical length of a working week over a longer period of time) 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 annual hours.		 See row "Total employment" UNA See row "Total employment"

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
The Estonian LFS data includes persons aged 15–74 unemployed according to ILO definition.
The registered unemployment data of the Labour Market Board includes persons aged 16 to pension age (in 2016: 63 years; starting from 2017, the pension age is gradually increasing, reaching 65 years of age by 2026) registered at the state employment offices.		 The LFS data are collected by means of sample survey , i.e. data are collected from only a part of the population.
The registered unemployment data are collected by means of complete registration, i.e. each and every event (applying to the state employment office) in the society is registered. The registration of the unemployed is based on the Labour Market Services and Social Protection Act that entered into force on 1 January 2006.		 Estonian Labour Force Survey Methodology. https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701

 

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)
 UNA  UNA  UNA  UNA  UNA  UNA
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 Estonian LFS and ESA2010 are the following:
— according to ESA2010 conscripts are employees while LFS defines them as economically inactive population;
— according to ESA2010 employment includes also non-residents (foreigners staying less than one year in Estonia) working for resident producer units while LFS does not include them;
— according to ESA2010 employment does not include residents who are working abroad or in the extra-territorial organisations in Estonia while LFS does;
— according to ESA2010 employment includes voluntary employees if their volunteer activities result in goods, e.g. the construction of a dwelling, church or other building, while LFS does not.		 For using in National Accounts, the Estonian LFS data is adjusted as much as possible to ESA2010 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 ESA2010 definitions only by not including the foreign workers and volunteers (these groups are not measured in Estonian LFS). As the result of including conscripts and excluding residents who are working abroad or in the extra-territorial organisations total employment decreased by 2% in 2019.
The size of the groups not included (the foreign workers and volunteers) in National Accounts employment is unknown.		 Estonian Labour Force Survey https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701
Total employment by NACE See row "Total employment" See row "Total employment" See row "Total employment" See row "Total employment"
Number of hours worked See row "Total employment" See row "Total employment" See row "Total employment" See row "Total employment"

 

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
  1.  Since 2009 main indicators in "Quarterly Bulletin of Statistics Estonia": 1st quarter data in No 2 (published in June), 2nd quarter data in No 3 (published in September), 3rd quarter data in No 4 (published in December), 4th quarter data in No 1 (published in March). Before 2009 monthly “Estonian Statistics”: 1st quarter data in No 4 (published at the end of May), 2nd quarter data in No 7 (published at the end of August), 3rd quarter data in No 10 (published at the end of November), 4th quarter data in No 10 (published at the end of February).
  2. Before 2006 yearbook "Labour Force" (published in May), in 2006 Yearbook “Labour Market” (2005 results) published in November, in 2007 pocket-sized reference book "Labour Market in Figures" (2006 results) published in November, in 2008 yearbook "A Glimpse into the Working Life" (2007 results) published in December), in 2017 "Economic and Labour Market Trends".
  3. Annual data in chapter “Labour Force” in “Statistical Yearbook of Estonia” (includes also CD, published in July), annual data in chapter “Labour Force” in "Minifacts about Estonia"
  4. Annual data by regions in chapter “Labour Force” in “Regional Statistics of Estonia” (electronic publication in 2004-2005, published in August); "Regional development in Estonia, 2010"; "Regional development in Estonia, young people in Estonia, 2018"
  5. Other publications of Statistics Estonia. 
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 the national methodological publication: Estonian Labour Force Survey. Methodology. https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701
Link to the national web page (national language(s)): http://pub.stat.ee/px-web.2001/Database/Sotsiaalelu/databasetree.asp

Link to the national web page (English): https://andmed.stat.ee/en/stat

 The results of the Estonian Labour Force Survey are available simultaneously to all interested parties at 8:00 on the day of release by issuing a news release, "Employment and Unemployment". It is sent to all interested parties, including the media, at their request either by fax or by e-mail. At the same time, the news release is also published on the Internet website of Statistics Estonia www.stat.ee .
A calendar of precise release dates for the entire year is published at the beginning of the calendar year in a separate news release. For the first quarter of the year, an advance release calendar is posted on the Internet website at the end of September of the previous year. A notice to this effect is given in a weekly calendar of publications which is published every Friday at 9:00 AM.
At the same time with press release (8.00) the Estonian LFS data are published in the statistical database on the web site of the Statistical Office www.stat.ee under the heading “Statistics”.
Information about the publications of Statistics Estonia are available for users in the catalogue of ‘Statistical Publications’. It is published annually and is available also in Internet website (http://www.stat.ee).
The request for information about the Estonian Labour Force Survey sent to Statistics Estonia are answered within five working days starting from the working day following the registration of the request for information.		 There is a link to the short description of the Estonian LFS methodology in all tables in the public database. Users can contact Statistics Estonia for consultation.
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 The anonymised Estonian LFS microdatabase is available for users from state and research institutions. The special contract between Statistics Estonia and data user stipulates the strict conditions of use. For users of the anonymised Estonian LFS microdatabase detailed documentation has been produced. This includes instructions about using the database, description of variables in the database, used classifications, the questionnaire and interviewer’s instructions. Users can contact Statistics Estonia for consultation.
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
Estonian Labour Force Survey. Methodology. https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/40701
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
For confidentiality reasons some information (name, address, exact birth date, name of the workplace, description of occupation, etc) is excluded from database.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top