Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: National Statistical Institute


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

National Statistical Institute
1.2. Contact organisation unit

Labour Market Statistics Department
1.5. Contact mail address


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 whole country is covered. The objects of the survey are non-institutional households - collective households are not surveyed, except student and worker hostels. All persons of 15 to 89 years of age, members of the selected households are interviewed. Foreign nationals, except diplomats working at the foreign embassies and members of their families, are included in the resident population if they have lived in Bulgaria for more than one year or if they intend to stay for at least an year. Housekeeping concept A household is defined as one person, who lives in a self-contained dwelling, or two or more persons, who live together in one dwelling or part of dwelling and have a common budget, regardless of the fact that some of them may not have kinship ties with each other. Included are:
 - persons staying in hospitals, sanatoriums  for less than one year;
 - students in secondary schools even though studying and living in different place;
- students in military schools;
- persons who have left for seasonal or temporary work outside the country;

Information about the persons absent from the household is obtained from another household’s member.

Excluded are:
- tertiary students, living in other town/village;
- persons, living in boarding schools, homes for social and medical care for children, homes for elderly people, homes for disabled people, monasteries;
- persons who have been  abroad for more than a year and persons settled permanently in other countries.		 from 15 to 89 years of age

 

Population concept  Specific population subgroups
Primary/secondary students Tertiary students People working out of family home for an extended period for the purpose of work People working away from family home but returning for weekends Children alternating two places of residence
Usual residence (12 months) Family home Term address Family home Family home Most of the time

 

Reference week
Fixed week (data collection refers to one reference week, to which the observation unit has been assigned prior to the fieldwork) Rolling week (data collection always refers to the week before the interview)                                  
 Y  N

 

Participation is voluntary/compulsory?
 voluntary
Reference quarter(s): Q2 or Q1-Q4, etc
 Q1-Q4
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) Date of sample selection
Two stage stratified sample  2011 Population Census 2016 Census enumeration district  Household Primary sampling units were selected in 2017, final sampling units for 2021 were selected in 2020.

 

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 clusters at the first stage (2444 enumeration districts) are selected with probability proportional to the size. Within each PSU randomly equal number of households (8 per quarter) are selected. The sample is stratified by districts (28 administrative districts, corresponding to NUTS3), crossing with type of place of residence (3 groups). 83 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)
2.60%  78 208

  

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)
0.65% 19 552 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)
 3 rd  Y  NA HOMEWORK, TEMPREAS, TEMPAGCY, MAINCLNT, VARITIME, SUPVISOR, SIZEFIRM, LOOKOJ, HWWISH, NEEDCARE, HATFIELD, HATYEAR, HATWORK, WAYJFOUN, FINDMETH, INCGROSS, INCGROSS_F

 

 

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 calculated in three steps:
- initial weights are obtained as inverse of  inclusion probability of household;
- the initial weights are multiplied by correction factor for households' non-response which is calculated as ratio between the total number of selected households in a stratum and the number of interviewed households from the same stratum;
- in the final step the intermediate (corrected for non-response) weights are calibrated to the population estimates by the following variables:
•          at national level - by 5-years age group, sex and type of place of residence (urban/rural);
•          at districts level (NUTS 3) - by 3 age groups (0-14, 15-64, 65+), sex and type of place of residence (urban/rural).
For calculation of weights the population estimates as of the end of previous quarter are used. Population, living in institutional households is excluded from these estimates.		 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, 75 +  NUTS 3          Type of place of residence (urban/rural)

 

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
The quarterly core weights for the subsample (the units from the 3rd wave in all quarters) are additionally calibrated to achieve consistency with the annual averages for main estimates Y 0-14, 15-24, 25-34, 35-44, 45-54, 55+ NUTS 2 Labour status (employment, unemployment, inactivity)

 

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)
1) Initial weight is obtained as inverse of  inclusion probability of each household.
2) The initial weight is multiplied by correction factor for households' non-response which is calculated as ratio between the total number of selected households in a stratum and the number of interviewed households from the same stratum;
3) Finally, the intermediate (corrected for non-response) weights are calibrated to the estimated total number of households by urban/rural area and NUTS2.
Consistency between annual sub-sample totals using the household weighting factors and full-sample annual averages using the individual weighting factors is achieved for employed, unemployed and persons outside the labour force by sex and for the age groups 15-24, 25-34, 35-44, 45-54 and 55+.   		  Y number of households by urban/rural area – SILC estimates sex, age groups, urban/rural, NUTS3 regions N

The variables used for stratification are the Districts and the urban/rural areas within each district.

 
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)? In case of Computer Assisted Methods adoption for data collection, could you please indicate which software is used?
The data are collected by face-to-face interview (using pencil and paper questionnaire).
Other method - telephone interview (not computer assisted).		 N NA

 

Are any LFS data collected from registers (Y/N)? If Yes, please indicate which variables are collected from registers.
NA NA
Is the data collection mode for AHM the same as for the LFS core?(Y/N)

If No could you please provide a brief description of the data collection mode adopted for AHM, highlighting the differences with the one adopted for the core?

Is the participation in the AHM voluntary or compulsory?
Y N/A Voluntary
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
Description of users with respect to the statistical data
The results from the labour force survey are widely used at national and international level. The main users of LFS statistics are:
- Ministries and State agencies;
- Local government;
- Bulgarian National Bank;
- Trade Unions and Employers' organisations;
- Non-governmental organisations;
- Universities and research institutions;
- Media;
- Companies, agencies - for own marketing researches or consultancy activities;
- International organisations (European Commission - DG Employment and other Directorates; Eurostat, European Central Bank, OECD, International Labour Organisation, UNECE, UNESCO, UNICEF.
Indication of the needs and uses for which users want the statistical outputs; information on unmet user needs and any plans to satisfy them in the future
The LFS based indicators are used for monitoring numerous National and European strategies. There is increasing interest form the researchers in LFS micro-data. The user needs that the National LFS still could not answer are the needs for more detailed regional data (e.g. at LAU1 level).
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?
 NUTS3  NUTS3  NUTS3 NA
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 average estimates Yearly estimates - wave approach 
 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
3300 7400 5400 12200
Biennial variables estimates Household estimates Household average estimates
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 Limit below which figures cannot be published Limit below which figures must be published with warning
5400 12200 5400 12200 4000 10000
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)       
 

            Employment rate                                 

Unemployment-to-population ratio                      

Youth unemployment rate as a percentage of labour force
 

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24
 CV 1.12 3.88 7.64
 SE 0.65 0.13 1.21
 CI(**) 57.22;59.78 3.01;3.5 13.46;18.20
                                      Unemployment-to-population ratio 15-74 (NUTS 2 regions)                                 
  CV       SE         CI(**)  
SEVEROZAPADEN 10.67 0.66 4.87;7.45
SEVEREN TSENTRALEN 9.97 0.40 3.24;4.82
SEVEROIZTOCHEN 7.44 0.28 3.24;4.35
YUGOIZTOCHEN 9.68 0.32 2.71;3.98
YUGOZAPADEN 8.59 0.20 1.93;2.71
YUZHEN TSENTRALEN 9.26 0.22 1.94;2.80
Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
For the calculation of the CV for total employment rate the denominator of employment rate is treated as a population figure without sample variance.

 

Reference on software used: Reference on method of estimation:
 SPSS, Complex Samples  Taylor linearisation

  

(*) 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 8.82  UNA  UNA  UNA  UNA  UNA

 

(a) Mention specifically which regions / population groups are not suitably represented in the sample.
(b) Misclassification refers to statistical units having an erroneous classification where both the wrong and the correct one are within the target population.
6.3.1.1. Over-coverage - rate

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

[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)   
Was the questionnaire updated for the 2021 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 Since Q1 2021 all variables are in compliance with the COMMISSION IMPLEMENTING REGULATION (EU) 2019/2240. Y pilot

 

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 (occasionally) N N
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 Y (Bulgarian, English - only if required) N
Other / Comments  N
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 NUTS3, type of place of residence, sequence number of wave  The sampling weights are multiplied by correction factor for households' non-response which is calculated as a ratio between the total number of selected households in a stratum and the number of interviewed households from the same stratum, by wave
Substitution of non-responding units (Y/N) Substitution rate Criteria for substitution
 N  NA  NA
Other methods (Y/N) Description of method
N NA

  

Rates of non-response by survey mode. Annual average
Survey
CAPI CATI  PAPI  CAWI  POSTAL
NA NA 22.7 NA NA

 

Non-response rates by survey mode. Annual average (% of the theoretical yearly sample by survey mode)
Quarter Non-response rate
Total (%)             of which:
 Refusals (%)                                              Non-contacts (including people who migrated (or moved) internally or abroad) (%) 
1 22.25 4.86 17.01
2 22.44 4.02 17.83
3 24.34 3.87 19.92
4 23.93 3.91 19.39
Annual 23.24 4.17 18.54

 

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_2021 Quarter2_2021 Quarter3_2021 Quarter4_2021
Subsample_Q4_2019 198      
Subsample_Q1_2020 239 200    
Subsample_Q2_2020   191 185  
Subsample_Q3_2020     172 158
Subsample_Q4_2020 229     190
Subsample_Q1_2021 206 165    
Subsample_Q2_2021   161 154  
Subsample_Q3_2021     176 154
Subsample_Q4_2021       192
Total in absolute numbers 872 717 687 694
Total in % of theoretical quarterly sample 4.86 4.02 3.87 3.91

 

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_2021 Quarter2_2021 Quarter3_2021 Quarter4_2021
Subsample_Q1_2019 537      
Subsample_Q1_2020 716 613    
Subsample_Q2_2020   620 563  
Subsample_Q3_2020     650 580
Subsample_Q4_2020 762     591
Subsample_Q1_2021 1035 788    
Subsample_Q2_2021   1162 921  
Subsample_Q3_2021     1405 977
Subsample_Q4_2021       1298
Total in absolute numbers 3050 3183 3539 3446
Total in % of theoretical quarterly sample 17.01 17.83 19.92 19.39

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
BG31-SEVEROZAPADEN 12.20
BG32-SEVEREN TSENTRALEN 24.59
BG33-SEVEROIZTOCHEN 15.94
BG34-YUGOIZTOCHEN 19.52
BG41-YUGOZAPADEN 32.02
BG42-YUZHEN TSENTRALEN 22.60

* 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 Implementing Regulation (EC) No 2019/2240)       

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  224  TEMPDUR_224 15.9 28.3 26.7 20.9 For persons without employment contract (main part of the variable non-response) the duration of job is often unclear.
 Compulsory  295_297  HWUSU2J_295_297 22.7 23.0 24.0 23.5 Respondents meet difficulties to answer the question, especially self-employed. More than a half of non-responded persons were self-employed on the second job.
 Compulsory  298_300  HWACTU2J_298_300 22.7 24.6 32.0 44.1 Respondents meet difficulties to answer the question, especially self-employed. More than a half of non-responded persons were self-employed on the second job.
               
               
               
               
               

 

Item non-response (*) - Annual data (Compared to the variables defined by the Commission Implementing Regulation (EC) No 2019/2240)    
Variable status Column Identifier This reference year Short comments on reasons for non-available statistics and prospects for future solutions
UNA UNA UNA UNA UNA

(*) "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 
Characteristics of main job (economic activity, occupation, full-part time, permanency of job) and duration of unemployment.  isolated cases  Historical Imputation, Hot-desk imputation
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
 UNA  UNA  UNA  UNA
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
Quarterly LFS Data
Quarter  Full dataset Single characteristic(s) 
Deadline Delivery date Reason for late delivery Characteristic(s) Delay (days)  Reason for late delivery 
 1 11.6.2021 8.6.2021  NA  NA  NA  NA
 2 13.9.2021 3.9.2021  NA  NA  NA  NA
 3 13.9.2021 8.12.2021  NA  NA  NA  NA
 4 17.3.2021 25.2.2021  NA  NA  NA  NA
7.2.1. Punctuality - delivery and publication

[not requested for the LFS quality report]


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 Y Changes in employment and unemployment definitions, in particular:
- Persons on leave for looking after a child of one to two years of age who are receiving fixed compensation for the duration of the leave, are considered employed (they used to be considered economically inactive persons up to the end of 2020);
- Persons on an unpaid parental leave for looking after a child of two to eight years of age are considered employed only if the one time duration of using that leave is at most three months, i. e. they do not use all the leave they are entitled to (six months for each parent). These persons used to be considered employed up to 2020.
- Persons who are absent from work due to different reason than holidays, illness, accident or maternity and parental leave are considered employed only if the duration of their absence is up to 3 months (even they are being partially compensated);
- Persons who produce agricultural products for self-consumption are excluded from the employed person’s category even if they satisfy their household’s main consumption needs by that production. Employed are considered only persons growing agricultural produce, intended mainly for sale or barter;
- Persons on a seasonal job are defined as employed out of the active work season if they regularly continue to do tasks and activities connected with their work or business, not including execution of legal or administrative tasks;
- Persons receiving social benefits who are obliged to do free community services are not considered employed. They used to be considered employed if they worked during the reference week up to the end of 2020.		 N All variables concerning employment, unemployment. 2021Q1
coverage (i.e. target population) Y Target population until 2020 was 15 years and over and since Q1 2021 the target population is 15 to 89 years of age. N NA 2021Q1
legislation Y Since Q1 2021 all variables are in compliance with the COMMISSION IMPLEMENTING REGULATION (EU) 2019/2240. N Since Q1 2021 all variables are in compliance with the COMMISSION IMPLEMENTING REGULATION (EU) 2019/2240. 2021Q1
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  Y Since Q1 2021 all variables are in compliance with the COMMISSION IMPLEMENTING REGULATION (EU) 2019/2240.
IESS		  NA  NA  NA
instruction to interviewers  N  NA  NA  NA  NA
survey mode  Y  NA  NA  NA  NA
weighting scheme  Y  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 LFS employment data include all employed persons, incl. self-employed and employees working without formal employment contracts.  The Business statistics (Short term statistics on employment and labour costs) provides quarterly data only on employees working by employment contract. Persons absent from work due to all kind of maternity and parental leaves are included. Armed forces are also excluded. Average quarterly results are estimated from the LFS. Data are collected from a sample of households. Data provided by the Business statistics refer to: 1) the last day of each month (quarter) and 2) average full-time equivalent for the month (quarter). Data are collected from all public and largest private enterprises and from a sample of registered small and medium private enterprises. See Table 1 in the Annex "Labour force survey - main characteristics and comparisons with the Survey of employees, wages and salaries and other labour costs as well as administrative information on registered unemployment" -Statistics Journal 4/2005;
Leaflet "Labour market statistics", issued in 2012; Methodological notes to publications: "Employment and Unemployment - annual data"  and "Statistical Yearbook";
Methodology of LFS survey - NSI web site.
Total employment by NACE LFS provides data of economic activity of local units. Distribution by NACE provided by the Short term statistics on employment and labour costs is based on the economic activity of the enterprise.  Coding of NACE in LFS is based on the description of economic activity, given by the respondents. In the Business statistics NACE codes are obtained from the statistical register of enterprises. See Table 1 in the Annex The same as for "Total Employment"
Number of hours worked In the LFS number of weekly hours usually worked and hours actually worked in the reference week are collected and refer to all employed persons. In the Business statistics only hours actually worked by employees with employment contract are collected on monthly basis.  Weekly hours usually worked and hours actually worked based on LFS refer to the reference week. In the Business statistics hours actually worked are collected on monthly basis.  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
According to LFS as unemployed are considered all persons aged 15-74 years without job, who are actively looking for job (not only by registration in labour offices, but using different active methods), and who are available to start working within 2 weeks after the reference week or who have found a job to start within a period of at most 3 months from the end of the reference week.  Data for registered unemployed persons come from administrative source. Data refer to the last calendar day of each month. "Labour force survey - main characteristics and comparisons with the survey of employed persons, wages and salaries and other labour costs as well as administrative information on registered unemployment"  -Statistics Journal 4/2005; Methodological notes to publications "Statistical Yearbook" and "Employment and Unemployment - annual data" ; Leaflet "Labour market statistics", issued in 2012; Leaflet "Labour market statistics", issued in 2012; LFS Metadata on NSI website

 

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)
 See Table 2 in the Annex  See Table 2 in the Annex  See Table 2 in the Annex  See Table 2 in the Annex  See Table 2 in the Annex  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 LFS covers all employed persons who are usual residents in Bulgaria. Data from National Accounts meet the domestic concept. NA estimates on agricultural employment are based on Agricultural Census and Farm structure survey data, which refer to all working people in agricultural plots (defined by the minimum size). LFS data are collected from a sample of households. Data provided by the National Accounts are reconciliated data from different sources - LFS, Enterprise surveys on employment and labour costs, Farm structure survey etc.  See Table 3 in the Annex Leaflet "Labour market statistics", issued in 2012; LFS Metadata on NSI website
Total employment by NACE LFS provides data the economic activity of local units. Coding of NACE in LFS is based on the description of economic activity, given by respondents.  See Table 3 in the Annex  UNA 
Number of hours worked The LFS data on number of hours worked by employed persons who are usual residents in Bulgaria. Data from National Accounts meet the domestic concept. LFS data are collected from a sample of households. Data provided by National accounts are reconciliated data from different sources - LFS, Enterprise surveys on employment and labour costs, Farm structure survey etc. In the LFS number of weekly hours usually worked and hours actually worked in the reference week are collected and refer for employed persons. Data on hours worked provided by National Accounts represent the aggregate number of hours actually worked by employees and self-employed during the reference period (quarter, year).  UNA  UNA 

 

Which is the use of LFS data for National Account Data?   
Country uses LFS as the only source for employment in national accounts. Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis Country not make use of LFS, or makes minimal use of it Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS) Country combines sources for labour supply and demand not giving precedence to any labour side Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employment registers and/or enterprise surveys)
N N N N Sources of information for national accounts employment data are the results of statistical surveys on the supply and demand side of the labour force. Data from the survey of enterprises and other institutional units for employed, wages and other labour costs are used for the elaboration of the employees working under labour contract, the working owners. The Labour force survey is used for the elaboration of the self-employed persons, employees working under civil contracts and employees working without any contracts. 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
“Employment  and  unemployment  -  annual  data” - electronic publication on CD, annually; 
“Labour Force Survey” - advertising leaflet, annually;
“Statistical Reference book” - annually ; 
“Statistical Yearbook” - annually;
“Bulgaria” (brochure) -  annually.
9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.    
Web link to national methodological publication Conditions of access to data Accompanying information to data Further assistance available to users
https://www.nsi.bg/bg/content/3990/наблюдение-на-работната-сила
https://www.nsi.bg/en/content/3990/labour-force-survey		 Data are transmitted simultaneously to Senior government officials, to the media (agencies, newspapers, radio and television) and to the NSI web site.  Methodological notes, questionnaire, text and  graphics, presented the main results. Information System (IS Infostat) - on-line system for dissemination of information, provides to users possibility to create tables with data on various indicators, incl. LFS based indicators, as well as for visualising the results graphically.
Special tabulations on CD-ROM or USB flash drive may be obtained by request through the IS Infostat or contacting the NSI offices.
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 1. universities and other higher education institutions;
2. organizations and scientific research institutions;
3. other agencies, organizations or institutions that have specific structural units which carry out scientific and research activities;
4. other legal entities that use data for research and analytical purposes;
5. natural persons that need anonymised data for the purposes of scientific and research activities		 According to the NSI Rules for provision of anonymised individual data for scientific and research purposes:
https://www.nsi.bg/en/content/575/basic-page/rules-provision-anonymised-individual-data-scientific-and-research-purposes		 Y, list of variables, explanatory notes, notes on comparability of data, specific issues Y
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
https://www.nsi.bg/sites/default/files/files/metadata/LFS_Methodology_EN.pdf
https://www.nsi.bg/en/content/4002/annual-data
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
https://www.nsi.bg/en/content/575/basic-page/rules-provision-anonymised-individual-data-scientific-and-research-purposes


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top
Annex