Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistical Office of the Republic of Serbia


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

Statistical Office of the Republic of Serbia
1.2. Contact organisation unit

Labor Force Survey Unit
1.5. Contact mail address

Milana Rakića No5, 11000 Beolgrade, Republic of Serbia


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 ...
Labor Force Survey covers total population that resides in the Republic of Serbia  excluding Kosovo and Metohija. Housekeeping Members living together in the same dwelling sharing income and household expenses. Excluded are persons in institutional households (students’ homes, homes for children and young people with developmental disability, homes for socially imperiled children, old / retired people homes, homes for adults with disability, monasteries, nunneries, etc.). For the temporary absent persons (less than 1 year) data are obtained from other family member. Persons absent more than one year are excluded. For students who live in other town/village within country data are obtained from original households in the case when they are economic dependent from that household.   15 and more

 

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 (if economically dependent otherwise term address) Family home (if they visit once a week otherwise term address) Family home Most of the time

 

Reference week
Fixed week (data collection refers to one reference week, to which the observation unit has been assigned prior to the fieldwork) Rolling week (data collection always refers to the week before the interview)                                  
In 2020, each week in a year is regarded as referent week, where referent weeks are fixed. Period of interview last two weeks after referent week.

The period of observation for the first quarter included 13 referent weeks and lasted from 30 December 2019 to 29 March 2020.

For the second quarter the period of observation included 13 referent weeks – from 30 March  to 28 June 2020.

For the third quarter the period of observation included 13 referent weeks – from  29 June  to 27 September 2020.

For the fourth quarter the period of observation included 14 referent weeks – from 28 September 2020 to 3 January 2021.

  
2.2. Classification system

[not requested for the LFS quality report]
2.3. Coverage - sector

[not requested for the LFS quality report]
2.4. Statistical concepts and definitions

[not requested for the LFS quality report]
2.5. Statistical unit

[not requested for the LFS quality report]
2.6. Statistical population

[not requested for the LFS quality report]
2.7. Reference area

[not requested for the LFS quality report]
2.8. Coverage - Time

[not requested for the LFS quality report]
2.9. Base period

[not requested for the LFS quality report]


3. Statistical processing Top
3.1. Source data
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.) Base used for the sample (sampling frame)  Last update of the sampling frame (continuously updated or date of the last update) Primary sampling unit (PSU)   Final sampling unit (FSU)
 The sample is based on a two-stage stratified rotation panel design.  Population Census 2011  2011 Primary sampling units (PSUs) are enumeration districts.  Final sampling units are households.

 

Sampling design & procedure
First (and intermediate) stage sampling method   Final stage sampling method Stratification (variable used) Number of strata (if strata change quarterly, refer to Q4). Rotation scheme (2-2-2, 5, 6, etc.)
Primary sampling units (enumeration districts), are selected systematically with probability proportional to size (PPS) within each stratum (territory and settlement type) from EDs list. Size measure for each ED was number of persons, age 15 and more. EDs were sorted within each stratum according to the municipality and serial numbers. Using systematic selection on the sorted list, high level of implicit geographical stratification and effective sample distribution were provided. Final stage units -  households were randomly selected, from household list, obtained for each ED. Enumeration districts (PSUs) for each rotation group are stratified according to the type of settlement (urban and other) and 25 areas (NUTS3 level).  UNA Sample for each quarter consists of 4 rotation groups (sub-samples), with 2-2-2 rotation scheme.  The overlap between two consecutive quarters is 50%.

 

Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate Size of the theoretical yearly sample
(i.e. including non-response) (i.e. including non-response)
3.2% 76960 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)
0.8 for the first quarter

0.8 for the second quarter

0.8 for the third quarter

0.8 for the fourth quarter

 19240 households

19240 households

19240 households

19240 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
Initial weight for household is equal to inverse of inclusion probability (this inclusion probability is a product of inclusion probabilities from each stage), and correction for non-response. In order to obtain estimates for population that corresponds to current demographics projections, calibration procedure is perfomed, relating to the  distribution of population according to sex, age (five-year age groups), at the level of  territory (level NUTS 3) and distribution of  households according to number of  household members (six groups), at the level of  territory, provided that a household and each person from the relevant household have the same final weigh.  N Beside population in private households reference population also includes population in collective households.  Y 0-14, 15-19, ..., 70-74, 75+  NUTS 3 number of  household members 1,2,…,6+

 

Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables) Gender is used in weighting (Y/N) Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)? Which regional breakdown is used in the weighting (e.g. NUTS 3)? Other weighting dimensions
Yearly weights are calculated as an average of quarterly weights.  as core weights  as core weights  as core weights  as core weights

 

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)
Calibration procedure is performed to provide that a household and each person from the relevant household have the same final weigh.  Y  Number of households by size  Gender, age, NUTS 3 level  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?
Two modes of data collection were used in 2020: CAPI (Computer assisted personal interviewing) and CATI (Computer assisted telephone interviewing).

CAPI was applied for households in the first wave and for the households in the later waves without phone contact. CATI was applied for the households in the 2, 3 or 4 wave with the phone contacts.

In average 47 interviewers per month were engaged in 2020 (37 of them in the field and 10 of them in the call center). Interviewing was done through 16 regional offices.		 Dependent interviewing is used, except for variables by which ILO status is defined and for variables which relate to the specific period.  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 34.8  65.2  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)
LFS data are used by national and international users.

National users are the Government organizations of the Republic of Serbia such as: the Ministry of Labour and Social Affairs, Ministry of Science and Technology, Ministry of Youth and Sports, National Bank, National Employment Service, local authorities, etc. Other national users are various academic and research institutions (universities and institutes), enterprises, journalists and individual users such as students, scientists, researchers and others.

The National Accounts use LFS data to produce the adequate estimations of the labour input. For this purpose, the variables used are: actual hours of work, section of activity, professional status, type of labour contract etc.

The international users are: Eurostat (for main LFS indicators), UNESCO and UNICEF (for educational data), ILO (for employment and unemployment), World Bank, International Monetary Fund (IMF) and others. Some countries from the region need LFS data for various regional projects.
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?
 In LFS individual data are collected at NUTS3 regional level.   At the quarterly level data are published at NUTS2 regional level. At annual level only basic indicators such as rates of activities, employment, unemployment and inactivity are published at NUTS3 level.  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 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
 1000  1000-3800  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%

 0.39

  0.39  2.31  2.09  2.07  3.88  0.23
 SE  10.50  0.26  5.50  5.98  0.19  1.03  0.10
 CI (**) 2704.88±20.58  65.88±0.50  237.65±10.78  286.56±11.71  9.10±0.37  26.65±2.03  42.81±0.19

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
Coefficient of variation for the number of employed persons (aged 20-64) and the employment rate (aged 20-64) are identical. Since the denominator of the employment rate is the total population and for this particular age group (individuals aged 20-64) it is one of the population totals used in the calibration procedure. Thus the only source of sampling variability is the numerator.

 

Reference on software used: Reference on method of estimation:
 ReGenesees  Taylor linearization

 

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 
RS11 Beograd  0.68  0.68  4.71  4.47  4.43  8.69  0.34
RS12  Vojvodina  0.78  0.78  4.87  4.71  4.66  8.35  0.42
RS21  Šumadija i Zapadna Srbija  0.77  0.77  4.42  3.73  3.71  6.94  0.52
RS22  Južna i Istočna Srbija  0.89  0.89  4.36  3.95  3.91  7.08  0.51

 

(*) 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 Q1: 2.71

Q2: 2.40

Q3: 3.77 

Q4: 3.30

Annual average: 3.05

Over-coverage is calculated un-weighted

  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]

For calculation of over-coverage following non-response categories are included: destroyed house, changed purpose of the apartment and permanently empty apartment.
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  NA  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)
 N  Y
Other / Comments  
6.3.3. Non response error

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

IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *

Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N) Variables used for non-response adjustment Description of method
 Y  Number of households  Response rates were calculated for each enumeration area and used to adjust the design weights calculated for each cluster.
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
 38.75  22.88  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 30.7 5.63 23.89 0.19
2 33.48 4.80 28.13 0.04
3 27.66 5.73 21.57 0.06
4 26.03 6.51 19.26 0.10
Annual 29.47 5.67 23.21 0.59

 

 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  199      
Subsample_Q1_2019 174   144    
Subsample_Q2_2019   184   137  
Subsample_Q3_2019     188  139 
Subsample_Q4_2019

214 

     218 
Subsample_Q1_2020 289  180     
Subsample_Q2_2020   253   282  
Subsample_Q3_2020     309  259 
Subsample_Q4_2020       404 
 Total in absolute numbers  876  761 916  1020 
 Total in % of theoretical quarterly sample 5.63  4.80  5.73  6.51 

5.63 

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  639      
Subsample_Q1_2019 844   640    
Subsample_Q2_2019   898   606  
Subsample_Q3_2019      760  493
Subsample_Q4_2019 1027       693
Subsample_Q1_2020 1204  1130     
Subsample_Q2_2020   1785   1044  
Subsample_Q3_2020      1038  779
Subsample_Q4_2020        1054
 Total in absolute numbers 3714   4453  3448  3019
 Total in % of theoretical quarterly sample  23.89  28.12  21.57  19.26

 

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  2      
Subsample_Q1_2019  4  UNA    
Subsample_Q2_2019    1  UNA  
Subsample_Q3_2019      2  UNA
Subsample_Q4_2019  1      2
Subsample_Q1_2020  UNA  1    
Subsample_Q2_2020    UNA  UNA  
Subsample_Q3_2020      UNA  1
Subsample_Q4_2020        UNA
 Total in absolute numbers  7  2  2  3
 Total in % of theoretical quarterly sample  0.05  0.01  0.01  0.02

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
 RS11-Beograd  28.16
 RS12-Vojvodina  31.98
 RS21-Šumadija i Zapadna Srbija  25.86
 RS22-Južna i Istočna Srbija  31.60

* 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 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
               

 

Item non-response - Annual data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)    
Variable status Column Identifier This reference year Short comments on reasons for non-available statistics and prospects for future solutions
compulsory Col_154/155 INCDECIL 37.51 Lack of information due to: reluctant of respondents to reveal their personal earnings, proxy interview. Part of this item non-response relates to the employees who have not yet received salary/wage because they have just started to work. Data is unweighted.
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 )
 N  NA
 Main variables Imputation rate  Describe method used, mentioning which auxiliary information or stratification is used 
 NA  NA  NA
6.3.5. Model assumption error

[not requested for the LFS quality report]
6.4. Seasonal adjustment
Do you apply any seasonal adjustment to the LFS Series? (Y/N) If Yes, is your adopted methodology compliant with the ESS guidelines on seasonal adjustment? (ref. http://ec.europa.eu/eurostat/web/research-methodology/seasonal-adjustment) (Y/N) If Yes, are you compliant with the Eurostat/ECB recommendation on Jdemetra+ as software for conducting seasonal adjustment of official statistics. (ref. http://ec.europa.eu/eurostat/web/ess/-/jdemetra-officially-recommended-as-software-for-the-seasonal-adjustment-of-official-statistics) (Y/N) If Not, please provide a description of the used methods and tools
 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 Definition of registered employment: the term employed comprises persons who have formal legal employment contract, i.e. who entered into employment with an employer for definite or indefinite period of time and persons who work on the basis of contract on performing temporary or occasional jobs, persons performing occupations/activities independently or who are founders of enterprises or unincorporated enterprises, as well as persons performing agricultural activities up to 65 years old, and are in the records of Central Register of Compulsory Social Insurance
 LFS - each person is regarded as employed if in the respective week they did some work for remuneration (in money or in kind) for minimum one hour.		 Registered employment – based on administrative data. Observation period- the next to last working day in the month. Quarterly data are calculated as the arithmetic mean of the number of employees for three months of the reference quarter; annual average as the arithmetic mean of the number of employees for 12 months.

LFS - survey based on the sample of private households. Observation unit for the LFS is each member of random selected household. Data source for the LFS is the statement which the interviewers collect from interviewed persons.

  UNA  Notes on methodology (e.g. in Statistical Yearbook
Total employment by NACE Registered employment- cover sections of activity from A to S, according to NACE Rev.2.
LFS – cover all the sections of activity according to NACE rev2 classification.		  Registered employment - Statistical unit corresponds to local-kind-of-activity unit (LKAU).  UNA  UNA
Number of hours worked Business statistic surveys:Hours worked include: hours worked during normal periods of work, periods of paid overtime, short rest periods at the place of work like tea or coffee breaks.

 LFS – Usual hours of work – which are the modal of actual hours of work over a long reference period (at least four weeks), excluding weeks of absence. For those with an employment contract are accepted contractual hours plus regular overtime.

Actual hours of work presents number of hours actually worked during the reference week, which exclude the main meal breaks, absence from work for personal reasons, education or training hours which are not connected with job.		  UNA  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 – According to ILO definition as unemployed persons are considered all persons aged 15-74,  who did not have paid job in the referent week, have been actively looking for job in the previous four weeks, and can start to work within two weeks after referent week, or have not actively looking for job because they have already found job on which they will start working within 3 months.  Registered unemployment: Unemployed persons are persons aged 15-65 years, who are registered at National employment office, and who are available immediately to start to work, do not have registered employment, and actively searching for work.   UNA

 

Assessment of the effect of differences of LFS unemployment and registered unemployment     
Give an assessment of the effects of the differences          
Overall effect Men under 25 years Men 25 years and over Women under 25 years Women 25 years and over Regional distribution (NUTS-3)
Total unemployed 15-65

Registered: 468 967

LFS; 286 020

 

 15-24 Men unemployed

Registered: 24 517

LFS: 31 907

 25-65 Men unemployed

Registered: 184 326

LFS: 121 137		 15-24 Women unemployed

Registered: 25 926

LFS: 21 285

 25-65 Women unemployed

Registered: 234 198

LFS: 112 236
region NUTS3 LFS registered
City of Belgrade 59724 64717
Severnobačka oblast 5383 7123
Srednjobanatska oblast 6545 11086
Severnobanatska oblast 3753 7279
Južnobanatska oblast 7988 19179
Zapadnobačka oblast 7772 12743
Južnobačka oblast 18793 29811
Sremska oblast 12648 12289
Mačvanska oblast 13270 23463
Kolubarska oblast 4026 7406
Podunavska oblast 10878 10072
Braničevska oblast 9639 7067
Šumadijska oblast 17445 25143
Pomoravska oblast 11847 20565
Borska oblast 7397 9031
Zaječarska oblast 7263 8932
Zlatiborska oblast 11276 21496
Moravička oblast 5520 10594
Raška oblast 13750 45037
Rasinska oblast 12429 19506
Nišavska oblast 17013 35956
Toplička oblast 3347 10031
Pirotska oblast 3295 9456
Jablanička oblast 6879 21916
Pčinjska oblast 8685 19069
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 residents in Republic of Serbia (national concept), especially those who work in territory of the Country. National Accounts meet the domestic concept including all employed, which are in production boundary activities. It means NA includes all agriculture employment and all Non Observed Economy employment. National Account (NA) estimate number of employed from different sources such as: official statistical data on the number of formal employed, structure of formal and informal employed from LFS, data on employed persons from financial statement  and tax records. NA use estimate of NA employment for own work tables, only NA estimates NA employment on experimental base only, so description has not been published yet
Total employment by NACE LFS provides data of the economic activity according Nace Rev. 2 classification on 3 digit level NA apply LFS structure of informal employment to correct NA employment  see above  UNA 
Number of hours worked  UNA  UNA  UNA   UNA

 

Which is the use of LFS data for National Account Data?   
Country uses LFS as the only source for employment in national accounts. Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis Country not make use of LFS, or makes minimal use of it Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS) Country combines sources for labour supply and demand not giving precedence to any labour side Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employment registers and/or enterprise surveys)
 N  N   N   N   Y  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

LFS Communication quarterly: for the first quarter on May 29, 2020; for the second on August 31, 2020; for the third on November 30, 2020; and for the fourth quarter on February 26, 2021.

LFS Bulletin – once a year, on 26 March 2021. Statistical yearbook – annually.

Statistical calendar – 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
 Link to the national web page : http://www.stat.gov.rs    Published data are made available to all interested institutions and media. Also, data can be sent to all interested parties at their request by email or phone UNA UNA 
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 and some international orgnaizations. Microdata in SPSS format are available on special request with written contract. Each variable in database contains label and value with belonging description. UNA
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

Detailed methodology is available on the following links:

Methodology for users - “Labour Force Survey, 2017 - methodological guide (No.69)”: http://pod2.stat.gov.rs/ObjavljenePublikacije/G2017/pdfE/G20177069.pdf

Short methodology - “Labour Force Survey”:

http://publikacije.stat.gov.rs/G2017/PdfE/G201720107.pdf
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
 SORS started to apply Eurostat rules for anonymization of microdata for users from 2020, and these rules are implemented for series from 2008 onward


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top