Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Inclusion/exclusion criteria for members of the household
Questions relating to employment status are put to all persons aged ...
The Labour Force Survey covers the whole country. The target population comprises all persons who usually reside in Montenegro or intend to stay in Montenegro for at least 12 months. Only private households are surveyed.
Housekeeping
Members usually living together in the same dwelling and sharing food and other essentials for living, income and household expenses.
Members of the household temporary absent for a period exceeding 12 months are excluded from the survey. If the person in the household resides in the country for less than one year and intends to stay in the country less than one year, the interview stops and the person will be excluded from the sample. Persons permanently living in collective units are not included in the survey.
15 to 89 years
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
Most of the time
Most of the time
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)
N
Y
Participation is voluntary/compulsory?
Voluntary
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]
3.1. 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
The sample design is a two-stage sampling with stratification of the primary units.
From 2012 the sampling frame is Census of Population, Households and Dwellings 2011
NA
Enumeration Area
Households
December 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.)
Enumeration areas of the Census of Population, Households and Dwellings 2011 are used as the primary sampling units (PSU). Within each stratum an indirect additional stratification is made by partial ordering of PSU – within each stratum PSU are sorted by municipality (and within municipality in a random order). Within each stratum sampling of PSU is made by systematic probabilities proportional to size (the number of households) sampling with a random starting point.
At the second stage necessary number of households is selected by simple random procedure within PSUs that are sampled for the first time.
Population is subdivided in 8 strata by region and the degree of urbanization – (1) urban areas of Podgorica, the capital city; (2) urban areas of the Central Region (without Podgorica municipality); (3) urban areas of the Northern Region; (4) urban areas of the Coastal Region; (5) rural areas of Podgorica municipality; (6) rural areas of the Central Region (without Podgorica municipality); (7) rural areas of the Northern Region; (8) rural areas of the Coastal Region.
Each PSU is included in the sample for 2 consecutive quarters, then it is out of the sample for 2 next quarters, and then again it is included 2 quarters in the sample. As a rule, after 6 quarters PSU is not included in the sample anymore for a long time.
Population is subdivided in 8 strata by region and the degree of urbanization – (1) urban areas of Podgorica, the capital city; (2) urban areas of the Central Region (without Podgorica municipality); (3) urban areas of the Northern Region; (4) urban areas of the Coastal Region; (5) rural areas of Podgorica municipality; (6) rural areas of the Central Region (without Podgorica municipality); (7) rural areas of the Northern Region; (8) rural areas of the Coastal Region.
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)
6.29
11 856 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)
1.57
2 964 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
Weights are used to compensate unequal chances of different persons to be included in the LFS sample. Calculation of weights is made in several successive steps. At first, so-called design weights are calculated. Since sampling of PSU is made with probabilities proportional to number of households, we will have that the inclusion probability of PSU from stratum in the sample at the first stage. At the second stage within each selected PSU households are sampled by simple random sampling procedure. Therefore, inclusion probability of household at the second stage is equal to multiplication these two inclusion probabilities. The design weight of a household is calculated as the inverse of its inclusion probability.
All persons of the same household have the design weight equal to the design weight of that household.
The design weights are further adjusted according to the actual response level, and calibrated according to the population demographic data by strata, sex and age groups in order to reach consistency between survey estimates and the official demographic statistics.
Podgorica, Central Region (without Podgorica municipality), Northern Region, Coastal Region
N
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)
Calculation of weights for households is made in several successive steps. At first, so-called design weights are calculated. Since sampling of PSU is made with probabilities proportional to number of households, we will have that the inclusion probability of PSU from stratum in the sample at the first stage. At the second stage within each selected PSU households are sampled by simple random sampling procedure. Therefore, inclusion probability of household at the second stage is equal to multiplication these two inclusion probabilities.
The design weight of a household is calculated as the inverse of its inclusion probability.
All persons of the same household have the design weight equal to the design weight of that household.
N
N
Age groups, gender, 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?
Data are collected by face-to-face interview, using paper questionnaires. Data are collected with identical questionnaires through the whole year. There are two questionnaires: the household questionnaire (addressed to all household members, collecting socio-demographic and information concerning the relationship with the head of household and the presence in the household) and the individual questionnaire (addressed only to the household members aged 15 to 89 years).
N
NA
Are any LFS data collected from registers (Y/N)?
If Yes, please indicate which variables are collected from registers.
N
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]
4.1. Quality assurance
[not requested for the LFS quality report]
4.2. Quality management - assessment
[not requested for the LFS quality report]
5.1. Relevance - User Needs
Description of users with respect to the statistical data
Relevance of the main LFS statistics at national level is high. These statistics is used by policy makers, media, researchers, students etc.
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
NA
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-1, NUTS-2, NUTS-3 represent the whole territory in Montenegro.
NUTS-1, NUTS-2, NUTS-3 represent the whole territory in Montenegro.
NA
NA
5.3.1. Data completeness - rate
[not requested for the LFS quality report]
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
1.2
1.9
NA
NA
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
1.2
1.9
1.2
1.9
1.2
1.9
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
1.05
0.00
8.47
SE
0.56
0.00
2.49
CI(**)
52.33 - 54.53
0.09 - 0.10
24.53 - 34.29
Unemployment-to-population ratio 15-74 (NUTS 2 regions)
CV
SE
CI(**)
Region 1
NA
NA
NA
Region 2
…
…
Region n
Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The employment rate for those aged 15-74 is the estimated number of those aged 15-74 in employment divided by estimated number of population aged 15-74. The denominator for the CV calculation is estimated number of population aged 15-74.
Reference on software used:
Reference on method of estimation:
Statistical Analysis System – SAS/STAT
Horvitz-Thompson’s estimates were used (for notations see Särndal et al (1992), p.42).
(*) 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: 11.6
Q2: 14.0
Q3: 14.2
Q4: 13.3
Annual average: 13.3
UNA
The undercoverage rate is difficult to measure because it is not possible to know which units are not included in the target population.
The sample frame based on the data from Census of Population, Households and Dwellings 2011 has been used since 2012. As the Census database was not updated since 2011, it is becoming obsolete and some problems regarding migration and/or new built dwellings can be present.
Over coverage rates are actually non-eligibility rates of households selected in sample:
- Definitely unavailable household
- Household moved out
The sample frame based on the data from Census of Population, Households and Dwellings 2011 has been used since 2012. As the Census database was not updated since 2011, it is becoming obsolete and some problems regarding migration and/or new built dwellings can be present.
We do not measure misclassification rate.
(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
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)
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
Location of household in EA
The design weights of household adjusted according to the actual response level. In order to adjust the weights according to the actual response level the sample size is replaced by the number of households participating in the survey (number - by the number of PSUs where LFS was actually carried out).
The number of PSUs within stratum where LFS was actually carried out is the number of households participating in the survey within PSU of the stratum.
Substitution of non-responding units (Y/N)
Substitution rate
Criteria for substitution
N
Other methods (Y/N)
Description of method
N
Rates of non-response by survey mode. Annual average
Survey
CAPI
CATI
PAPI
CAWI
POSTAL
NA
NA
25.1
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
24.4
7.1
14.6
2
24.5
6.7
15.0
3
26.5
7.4
16.2
4
24.8
6.3
16.1
Annual
25.1
6.9
15.5
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_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q4_2020
48
Subsample_Q1_2021
51
54
Subsample_Q2_2021
49
57
Subsample_Q3_2021
58
60
Subsample_Q4_2021
45
43
Subsample_Q1_2022
42
42
Subsample_Q2_2022
25
47
Subsample_Q3_2022
26
26
Subsample_Q4_2022
34
Total in absolute numbers
186
170
188
163
Total in % of theoretical quarterly sample
6.3
5.7
6.3
5.5
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_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q4_2020
58
Subsample_Q1_2021
76
56
Subsample_Q2_2021
77
58
Subsample_Q3_2021
92
70
Subsample_Q4_2021
90
80
Subsample_Q1_2022
158
111
Subsample_Q2_2022
139
108
Subsample_Q3_2022
154
118
Subsample_Q4_2022
147
Total in absolute numbers
382
383
412
415
Total in % of theoretical quarterly sample
12.9
12.9
13.9
14.0
Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)
Non response rate (%)
NA
NA
* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview
6.3.3.2. Item non-response - rate
Item non-response (*) - Quarterly data (Compared to the variables defined by the Commission 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
283-284
ABSHOLID
100
100
100
100
This variable will be included in 2023.
Compulsory
285-286
ABSILLINJ
100
100
100
100
This variable will be included in 2023.
Compulsory
287-288
ABSOTHER
100
100
100
100
This variable will be included in 2023.
Compulsory
277-279
CONTRHRS
100
100
100
100
This variable will be included in 2025.
Compulsory
189-191
COUNTRPR
100
100
100
100
This variable will be included in 2025.
Compulsory
289-291
EXTRAHRS
100
100
100
100
This variable will be included in 2023.
Compulsory
295-297
HWUSU2J
100
100
100
100
This variable will be included in 2023.
Compulsory
154
DEGURBA
100
100
100
100
We still do not have DEGURBA defined on the national level.
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
Compulsory
252
HATWORK
This variable will be included in 2025.
(*) "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
Not measured.
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
Not measured.
Main variables
Imputation rate
Describe method used, mentioning which auxiliary information or stratification is used
N
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. Seasonal-adjustment) (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. Eurostat/documents) (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]
7.1. 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
[not requested for the LFS quality report]
7.2.1. Punctuality - delivery and publication
[not requested for the LFS quality report]
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
Identification of the main job (*)
N
Employment
N
Unemployment
N
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
There were not any changes
N
There were not any changes
N
coverage (i.e. target population)
N
There were not any changes
N
There were not any changes
N
legislation
N
There were not any changes
N
There were not any changes
N
classifications
N
There were not any changes
N
There were not any changes
N
geographical boundaries
N
There were not any changes
N
There were not any changes
N
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
There were not any changes
N
There were not any changes
N
sample design
N
There were not any changes
N
There were not any changes
N
rotation pattern
N
There were not any changes
N
There were not any changes
N
questionnaire
Y
We have included in the questionnaire following variables: GALI, GENHEALTH, EDUCFED12, EDUCLEV12, EDUCNFE12
N
NA
N
instruction to interviewers
N
There were not any changes
N
There were not any changes
N
survey mode
N
There were not any changes
N
There were not any changes
N
weighting scheme
N
There were not any changes
N
There were not any changes
N
use of auxiliary information
N
There were not any changes
N
There were not any changes
N
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 data on annual and monthly number of employees are obtained on the basis of records regulated by the Law on Records in Area of Labour and Employment (Official Gazette of Montenegro No 45/12), and kept by the Central Register of Payers and Insured Persons (Official Gazette of Montenegro No 45/08, 80/08, 15/09, 43/09, 32/10), and regularly used by Statistical Office. The term “employees” refers to all persons being employed in enterprises, institutions, organizations or by self-employed individuals no matter whether their employment status is based on a permanent or temporary contract and whether they work on a full-time or part-time basis.
LFS: survey based on the sample of private households
UNA
Notes on methodology (e.g. in Statistical Yearbook)
Total employment by NACE
The data on annual and monthly number of employees are obtained on the basis of records regulated by the Law on Records in Area of Labour and Employment (Official Gazette of Montenegro No 45/12), and kept by the Central Register of Payers and Insured Persons (Official Gazette of Montenegro No 45/08, 80/08, 15/09, 43/09, 32/10), and regularly used by Statistical Office. The term “employees” refers to all persons being employed in enterprises, institutions, organizations or by self-employed individuals no matter whether their employment status is based on a permanent or temporary contract and whether they work on a full-time or part-time basis.
LFS: survey based on the sample of private households
UNA
Notes on methodology (e.g. in Statistical Yearbook)
Number of hours worked
UNA
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
Guide on manner of determining survey and registered unemployment rate
Give an assessment of the effects of the differences
Give references to description of differences
Total employment
UNA
UNA
UNA
UNA
Total employment by NACE
UNA
UNA
UNA
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)
UNA
UNA
UNA
UNA
UNA
UNA
8.6. Coherence - internal
[not requested for the LFS quality report]
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
Quarterly Release
Annual Release
Statistical Yearbook
Publication Montenegro in figures (annual)
Publication Women and men in Montenegro (annual)
9.3. Dissemination format - online database
The LFS Release is available simultaneously to all interested parties on the day of release. The new release is published on the official site of Statistical Office of Montenegro.
The access to microdata is defined according to Law on Official Statistics and Official Statistical System of Montenegro.
Documentation, explanations, quality limitations, graphics etc.
The LFS Release is available simultaneously to all interested parties on the day of release. The new release is published on the official site of Statistical Office of Montenegro.
The access to microdata is defined according to Law on Official Statistics and Official Statistical System of Montenegro.
The LFS Release includes a short methodological explanation on the main indicators.
Every release has information of a reference person, telephone number, mail address and e-mail address to whom it is possible to ask for any clarification. Additionally, user can provide any question to our official mail address.
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 Law on Official Statistics and Official Statistical System (Official Gazette of Montenegro No 18/12) regulates rules under which external users can obtain an access to individual data for needs of research. Article 58 defines types of scientific and research organizations that can obtain such data. Providing individual data without identifier is possible only upon a written request of scientific and research institutions, with purpose of performing scientific and research activities as well as international statistical organizations and statistical producers from other countries. Research entity signs the agreement with Statistical Office, and it signs the statement on respecting the confidentiality principle. Official statistical producers keep separate records on users and purpose of using the statistical data given to these users. Law on statistics: Monstat.
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
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]
Restricted from publication
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
Articles 53-60 of the Law on Official Statistics and Official Statistical System (Official Gazette of Montenegro No 18/12) provide a framework for protection, use, and transmission of confidential data. MONSTAT has produced two comprehensive rulebooks that cover the procedures for individual data protection as well as keeping individual records. With purpose of the meeting legal framework on functioning of security system and statistical confidentiality there was adopted the Rulebook on Keeping Statistical Data by which Manner, Time, Technical Conditions and Organization of Statistical Data Storage to Prevent Their Destroying, Misappropriation, and Unauthorized Use is Regulated as well as the Rulebook on Contents and Manner of Keeping Records on Users of Individual Statistical Data by which contents and manner of keeping records on users of individual statistical data is regular. Pursuant to the Article 59, an access to the confidential data is limited to persons performing duties and tasks of official statistical producer and up to the stage the data are necessary for official statistical production. Persons that perform duties and tasks within official statistical producers must sign the statement on respecting the principle of confidentiality. Law on Official Statistics and Official Statistical System is aligned with the Regulation No 223/2009 and the Regulation (EU) 2015/759 from 29 April 2015 that also regulates confidentiality provisions. The Government of Montenegro adopted the Statement on Commitment of Confidence in Official Statistics (Commitment of Confidence).
[not requested for the LFS quality report]
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 Labour Force Survey covers the whole country. The target population comprises all persons who usually reside in Montenegro or intend to stay in Montenegro for at least 12 months. Only private households are surveyed.
Housekeeping
Members usually living together in the same dwelling and sharing food and other essentials for living, income and household expenses.
Members of the household temporary absent for a period exceeding 12 months are excluded from the survey. If the person in the household resides in the country for less than one year and intends to stay in the country less than one year, the interview stops and the person will be excluded from the sample. Persons permanently living in collective units are not included in the survey.
15 to 89 years
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
Most of the time
Most of the time
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)
N
Y
Participation is voluntary/compulsory?
Voluntary
Not Applicable
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
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
The sample design is a two-stage sampling with stratification of the primary units.
From 2012 the sampling frame is Census of Population, Households and Dwellings 2011
NA
Enumeration Area
Households
December 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.)
Enumeration areas of the Census of Population, Households and Dwellings 2011 are used as the primary sampling units (PSU). Within each stratum an indirect additional stratification is made by partial ordering of PSU – within each stratum PSU are sorted by municipality (and within municipality in a random order). Within each stratum sampling of PSU is made by systematic probabilities proportional to size (the number of households) sampling with a random starting point.
At the second stage necessary number of households is selected by simple random procedure within PSUs that are sampled for the first time.
Population is subdivided in 8 strata by region and the degree of urbanization – (1) urban areas of Podgorica, the capital city; (2) urban areas of the Central Region (without Podgorica municipality); (3) urban areas of the Northern Region; (4) urban areas of the Coastal Region; (5) rural areas of Podgorica municipality; (6) rural areas of the Central Region (without Podgorica municipality); (7) rural areas of the Northern Region; (8) rural areas of the Coastal Region.
Each PSU is included in the sample for 2 consecutive quarters, then it is out of the sample for 2 next quarters, and then again it is included 2 quarters in the sample. As a rule, after 6 quarters PSU is not included in the sample anymore for a long time.
Population is subdivided in 8 strata by region and the degree of urbanization – (1) urban areas of Podgorica, the capital city; (2) urban areas of the Central Region (without Podgorica municipality); (3) urban areas of the Northern Region; (4) urban areas of the Coastal Region; (5) rural areas of Podgorica municipality; (6) rural areas of the Central Region (without Podgorica municipality); (7) rural areas of the Northern Region; (8) rural areas of the Coastal Region.
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)
6.29
11 856 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)
1.57
2 964 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
Weights are used to compensate unequal chances of different persons to be included in the LFS sample. Calculation of weights is made in several successive steps. At first, so-called design weights are calculated. Since sampling of PSU is made with probabilities proportional to number of households, we will have that the inclusion probability of PSU from stratum in the sample at the first stage. At the second stage within each selected PSU households are sampled by simple random sampling procedure. Therefore, inclusion probability of household at the second stage is equal to multiplication these two inclusion probabilities. The design weight of a household is calculated as the inverse of its inclusion probability.
All persons of the same household have the design weight equal to the design weight of that household.
The design weights are further adjusted according to the actual response level, and calibrated according to the population demographic data by strata, sex and age groups in order to reach consistency between survey estimates and the official demographic statistics.
Podgorica, Central Region (without Podgorica municipality), Northern Region, Coastal Region
N
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)
Calculation of weights for households is made in several successive steps. At first, so-called design weights are calculated. Since sampling of PSU is made with probabilities proportional to number of households, we will have that the inclusion probability of PSU from stratum in the sample at the first stage. At the second stage within each selected PSU households are sampled by simple random sampling procedure. Therefore, inclusion probability of household at the second stage is equal to multiplication these two inclusion probabilities.
The design weight of a household is calculated as the inverse of its inclusion probability.
All persons of the same household have the design weight equal to the design weight of that household.
N
N
Age groups, gender, regions
N
The variables used for stratification are the Districts and the urban/rural areas within each district.
Not Applicable
Restricted from publication
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
Identification of the main job (*)
N
Employment
N
Unemployment
N
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
There were not any changes
N
There were not any changes
N
coverage (i.e. target population)
N
There were not any changes
N
There were not any changes
N
legislation
N
There were not any changes
N
There were not any changes
N
classifications
N
There were not any changes
N
There were not any changes
N
geographical boundaries
N
There were not any changes
N
There were not any changes
N
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
There were not any changes
N
There were not any changes
N
sample design
N
There were not any changes
N
There were not any changes
N
rotation pattern
N
There were not any changes
N
There were not any changes
N
questionnaire
Y
We have included in the questionnaire following variables: GALI, GENHEALTH, EDUCFED12, EDUCLEV12, EDUCNFE12
