Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Croatian Bureau of Statistics


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: EUROPEAN STATISTICAL DATA SUPPORT

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1. Contact Top
1.1. Contact organisation

Croatian Bureau of Statistics

1.2. Contact organisation unit

Economic Activity of Population Statistics Unit

1.5. Contact mail address

Branimirova 19, 10000 Zagreb, Republic of Croatia


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 Labour Force Survey covers the whole country since 2000. The target population comprises all persons who usually reside in Croatia or intend to stay in Croatia for at least 12 months. Only private households are surveyed. Dwelling Members living regularly together in the same dwelling, sharing food and other essentials for living. Household members are persons who are permanently present in the household or absent less than 1 year.  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 living in the country) 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)                                  
Households are interviewed throughout the year. This means that every week is both a reference and an interviewing week. Data collection refers to the reference week, to which the observation unit has been assigned prior to the fieldwork and interviewing week is normally one week after the reference week. But since the beginning of 2Q_2020  we have introduced a two interviewing-week dynamics because of circumstances caused by COVID-19 epidemic. This dynamic persisted until the end of the year 2020.  
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)
Croatian LFS is using stratified two-stage random sample survey of private households (persons in private households).Starting with 2014, stratification is done by two NUTS2 regions and both of them further divided in urban and rural part, so, 4 strata at final. In accordance to decreased number of strata (before there were 21 strata according to counties), square root of proportional allocation have been used. Population Census 2011 Sample frame was updated in 2020 by removing deceased persons from sample frame. This updated sample frame is used in 2020. The primary sampling units are segments (PSUs) and were defined according to the results of the Census 2011 which consisted of a number of private households according to each enumeration area. As segments consist of one or more enumeration districts near each other, crucial requirement was that one segment cannot consist of enumeration districts which belong to different municipalities or counties. The secondary and final sampling units are inhabited dwellings according to the Census 2011.

 

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.)
Segments are selected by PPS systematic sampling, where measure of size of segment is number of private households in segment according to Population Census 2011. They are used for a whole year. Within selected segments, dwellings are selected by simple random sampling. Since 2007 the LFS is a continuous quarterly survey. After selecting a sample of segments, 13 (number of weeks in a quarter) non-overlapping sub-samples of segments are selected from sample of segments by systematic sampling (for every week in the quarter). Within selected segments, 10 dwellings are selected by simple random sampling. Since stratification is done prior to sample selection, subjective choices can be made in determining the definition criteria, number and boundaries of the strata. Also, it was concluded that it is more effective to use a multiplicity of stratification variables, each with few categories, than to use many fine categories of a single variable. That is the reason why CBS abandoned stratification according to just one variable (counties). At the end, after all those analyses, it was decided to divide each stratum (NUTS2 region) into urban and rural part, so level of urbanisation will be used as additional stratification variable. Thus, for now we will further use geographical stratification, as in many situations, geographical, administrative and urban-rural classification provides a most effective form of stratification.  4  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)
  1.14%  16 380 (without multiplicity)

  

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)
 0.51% 7 280

  

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
First, design weights are calculated. Sample consists of 4 independently selected subsamples (rotational groups or panels). Allocation of sample within each stratum is square root of proportional. So, PSUs are chosen with (square root) probability proportional to a number of private households in each PSU. On other side, SSUs (occupied dwellings) are selected from each PSU (segment) with equal probability. Total probability of selection of the dwellings in the sample are product of probability of selecting segments in first stage with probability of selecting 10 occupied dwellings from each segment in the second stage. Design weights are inverse value of the selection probabilities of choosing dwellings in a sample. They are equal for dwellings, households and persons in one segment. That’s because all households and persons in each selected dwelling are interviewed.
Then, there are defined weighting groups regarding non-response, and response rates are calculated for each of these groups. Urban part of each 21 county form one group, and rural parts in each county form second group. As there are 21 counties, multiplying 2 groups (urban and rural) gives 42 groups within counties for defining non-response rates (and calculating response rates in each one). Non-response weights are inverse value of these response rates. They are also equal for each segment.
At the end, calibration was used for adjustment weighting. It has more possibilities in comparison to other techniques (e.g. linear weighting and post-stratification), such as imposing constraints on the values of the weights. So, distributions of the 5-year age groups, gender, regions and household size) for the subsample of respondents was calibrated to known auxiliary information from Census 2011. It reduced sampling error, effecting the ‘old’ weights, but in limits of previously defined constraints in CALMAR software. Bounded linear method was used for calibration, and lower limit was set on 0.5, and upper on 3.
 Y  NA  Y  0-14, 15-19, ..., 70-74, 75+ NUTS 2 for calculation of design weights as it is one of the two stratification variables, NUTS 3 for nonresponse adjustment and NUTS 2 for calibration Calibration (see 1st column A)

 

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
As sample data from each quarter represent whole country, when we combine 4 quarterly data in one yearly dataset, we divide final quarterly weights after calibration by 4. Subsampling is not applied to survey yearly variables.  See above   See above   See above   See above

 

Brief description of the method of calculating the weights for households External reference for number of households etc.? Which factors at household level are used in the weighting (number of households, household size, household composition, etc.) Which factors at individual level are used in the weighting (gender, age, regional breakdown etc.) Identical household weights for all household members? (Y/N)
See above in the "Brief description of the method of calculating the quarterly core weights"  Census 2011  Number of households and household size Gender, age and regional breakdown  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?
Since the beginning of 2016, the earlier method of data collection "on paper" has been replaced by new interviewing methods, CAPI and CATI. All households selected to sample for the first time and households that either do not have a telephone/cell phone or do not want, for whatever reason, to be interviewed by telephone, are interviewed by CAPI method. All households that in the first interviewing accepted to be interviewed by phone, are interviewed by CATI method. Since the beginning of 2Q_2020 until the end of year 2020, because of new circumstances caused by COVID-19 epidemic, we have introduced a new method of interviewing: CAPI  interviewers were conducting interviews from their homes or from offices by telephone. Because it was not possible to go to households, our CAPI interviewers for all households for which a telephone number was available, conducted interview by telephone. We have sent regularly announcement letters to households and asked them to send us on our e-mail address their phone number, in order to make a contact with them and to make an interview.  Y  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 28.13 71.87  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)
High relevance 
5.2. Relevance - User Satisfaction

[not requested for the LFS quality report]

5.3. Completeness
NUTS level of detail   
Regional level of an individual record (person) in the national data set Lowest regional level of the results published by NSI Lowest regional level of the results delivered to researchers by NSI Brief description of the method which is used to produce NUTS-3 unemployment and labour force data sent to Eurostat?
 NUTS 3 (county)  NUTS 2 (region)  NUTS 1 (country)  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 grossed up persons
frequency less than 11 - not published (not zero, but extremely innacurate estimation)
10000 grossed up persons
frequency 11-43 - published nationally in two brackets ((  )) (inaccurate estimation); frequency 44-99 - published nationally in one bracket (  ) (less accurate estimation) 
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  2.29%  0.84%  6.10%  4.92%  4.67%  8.05%  0.32%
 SE  36291  0.56%  4429  6489  0.35%  1.73%  0.12
 CI(**)  [1513706, 1656077]  [65.77%, 67.97%]  [63901, 81274]  [119155,  144613]  [6.85%, 8.22%]  [18.08%, 24.87%]  [38.18, 38.66]

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
Calibration was used for adjustment weighting, i.e. the weights were calibrated to reproduce the population distribution estimates by the 5-year age groups, gender, regions and household size for the 2020. The totals were estimated based on 2011 Census data, which was updated with data on live births and deaths as well as on population migrations. Therefore, population estimates calculated from collected data are equal to estimated population totals. Calibration was done with SAS macro CALMAR using Bounded linear method, where lower limit was set on 0.45 and upper on 2.5.

 

Reference on software used: Reference on method of estimation:
 SAS System  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 

 HR03 Jadranska Hrvatska   3.80%  1.48%   9.13%  8.52%  7.65%   16.84%   0.46%
 HR04 Kontinentalna Hrvatska   2.85%  1.01%   8.13%  6.03%  5.84%   9.03%   0.41%

(*) 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: 13.60%

Q2: 13.52%

Q3: 11.87%

Q4: 12.25%

Annual average:12.81%

 UNA Since the beginning of 2014, the new sample frame based on the data from the Census of Population, Households and Dwellings in 2011 has been in use. This sample frame includes addresses of private households on the whole territory of Croatia; hence, the LFS results relate to the whole country. As the Census database was not updated since 2011, it is becoming obsolete, and some problems regarding migration and/or newly built dwellings are present in a larger extent. Overcoverage rates are actually non-eligibility rates of addresses selected in sample.  UNA See comments on "Undercoverage"

 

(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 2020 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 In questionnaire for 3Q_2020 and 4Q_2020 for national needs we have introduced new questions regarding coronavirus reasons for certain behavior. After variables NOWKREAS, HOURREAS, HOMEWK, LEAVREAS, SEEKWORK and AVAIREAS in the questionnaire we have put the question: Was it related to a situation caused by a coronavirus?  (1) Yes, (2) No.  Y  Internal checks

 

Main methods of reducing measurement errors 
Error source  
Respondent  Letter introducing the survey (Y/N) Phone call for booking or introducing the survey (Y/N)
Y Y
Interviewer  Periodical training (at least 1 time per year) (Y/N)  Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
N, because of the circumstances caused by COVID-19 epidemic we didn't organize training for the interviewers in 2020, but we have sent to interviewers by e-mail a word document "Methodological guidelines" on new questions that are related to reasons for certain behavior caused by coronavirus. Also we have inserted in electronic questionnaire detailed instructions on that questions. 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
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
Y Y
Other / Comments  
6.3.3. Non response error

[not requested for the LFS quality report]

6.3.3.1. Unit non-response - rate

IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *

Methods used for adjustments for statistical unit non-response

Adjustment via weights (Y/N) Variables used for non-response adjustment Description of method
 Y 1. NUTS 3 (counties)

2. Degree of urbanisation

There are defined weighting groups regarding non-response, and response rates are calculated for each of these groups. Urban part of each 21 county form one group, and rural parts in each county form second group. As there are 21 counties, multiplying 2 groups (urban and rural) gives 42 groups within counties for defining non-response rates minus 1 as City of Zagreb is all urban, so 41 groups (and calculating response rates in each one). Non-response weights are inverse value of these response rates. They are also equal for each segment.
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
50.28% 6.65 %  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 42.15 24.67 13.88 NA
2 42.41 23.7 15.44 NA 
3 44.06 23.64 17.18 NA 
4 43.41 24.33 15.94 NA 
Annual 43.01 24.09 15.61 NA 

 

 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 457      
Subsample_Q1_2019 427 455    
Subsample_Q2_2019   475 510   
Subsample_Q3_2019     429 479
Subsample_Q4_2019 419      480 
Subsample_Q1_2020 249 325    
Subsample_Q2_2020   237 326   
Subsample_Q3_2020     252  343
Subsample_Q4_2020       252 
 Total in absolute numbers 1552  1492 1517 1554
Total in % of theoretical quarterly sample 21.32% 20.49% 20.84%  21.35%

 

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 127      
Subsample_Q1_2019 150  102    
Subsample_Q2_2019   162  149  
Subsample_Q3_2019     195  155
Subsample_Q4_2019 218     174 
Subsample_Q1_2020 378 260     
Subsample_Q2_2020   448  319   
Subsample_Q3_2020     439  304 
Subsample_Q4_2020       385 
 Total in absolute numbers 873  972 1102 1018 
Total in % of theoretical quarterly sample 11.99% 13.35% 15.14% 13.98% 

 

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 NA      
Subsample_Q1_2019 NA NA    
Subsample_Q2_2019   NA NA  
Subsample_Q3_2019     NA NA
Subsample_Q4_2019 NA     NA
Subsample_Q1_2020 NA NA    
Subsample_Q2_2020   NA NA  
Subsample_Q3_2020     NA NA
Subsample_Q4_2020       NA
 Total in absolute numbers NA NA NA NA
Total in % of theoretical quarterly sample  NA  NA  NA  NA

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
 HR03 Jadranska Hrvatska 47.19%
 HR04 Kontinentalna Hrvatska 39.98%

* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview

6.3.3.2. Item non-response - rate
Item non-response (*) - Quarterly data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)       
Variable status Column Identifier Quarter 1 Quarter 2 Quarter 3 Quarter 4 Short comments on reasons for non-available statistics and prospects for future solutions
Compulsory / optional
compulsory Col_065/66 HWOVERP 98.6 98.2 98.0 97.4 Persons who did not work overtime, and in that case do not answer the question about paid overtime.
compulsory Col_110 - Employed METHODH C . . . This method is rarely or never used in the job search.
compulsory Col_110 - Not employed METHODH . C . . This method is rarely or never used in the job search.
compulsory Col_111 - Employed METHODI . . . C This method is rarely or never used in the job search.
compulsory Col_113 - Employed METHODK C . . . This method is rarely or never used in the job search. 
compulsory Col_129/131 COURLEN 13.6 18.4 . . Most of this non-response is related to a proxy interview. Proxy respondents do not usually know the number of hours spent on all taught learning activities. 

 

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_037/38 SIZEFIRM 15.5 Persons actually do not know information on number of persons working at the local unit. 
compulsory Col_077 LOOKREAS 21.8  Will be improved in the future.
compulsory Col_118 - Employed AVAIREAS 90  Will be improved in the future.
compulsory Col_118 - Not employed AVAIREAS 18.2  Will be improved in the future.
compulsory Col_154/155 INCDECIL 24.1 Persons do not want to give answer on this sensitive issue, especially in the case of proxy interview.
optional Col_133/135 COURFILD 100  Not collected as the variable is optional.

(*) "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 CAPI and CATI electronic questionnaire has logical control built in. Some errors occur and are corrected at later phase (by supervisors at the field and by LFS methodologists). Therefore it is not possible to estimate the overall editing rate.
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
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)
There is no standard revision policy for Labour Force Survey but due to availability of new and more up-to-date estimates of the total population, data is being revised in order to adjust the Survey data with demographic figures for the Republic of Croatia.  UNA
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 21/06/2020 29/05/2020  NA  NA   NA   NA 
 2 20/09/2020 02/09/2020  NA   NA   NA   NA 
 3 20/12/2020 02/12/2020  NA   NA   NA   NA 
 4 21/03/2021 05/03/2021  NA   NA   NA   NA 
Yearly weights (*) 31/03/2021 NA   NA   NA   NA   NA 

 

Measures to improve timeliness and punctuality
 NA

 

(*) Only if ad hoc yearly weights are used for yearly variables

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 The persons on sick leave, maternity or paternity leave, paid parental leave are always considered to be employed, regardless of the length of absence.
Unemployment  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  Y In questionnaire for 3Q_2020 and 4Q_2020 for national needs we have introduced new questions regarding coronavirus reasons for certain behavior. After variables NOWKREAS, HOURREAS, HOMEWK, LEAVREAS, SEEKWORK and AVAIREAS in the questionnaire we have put the question: Was it related to a situation caused by a coronavirus?  (1) Yes, (2) No.  N  NA  N
instruction to interviewers  Y Because of the circumstances caused by COVID-19 epidemic we didn't organize training for the interviewers in 2020, but we have sent to interviewers by e-mail a word document "Methodological guidelines" on new questions that are related to reasons for certain behavior caused by coronavirus, and we have inserted detailed instructions for interviewers in the electronic questionnaire.  N  NA  N
survey mode  Y Since the beginning of 2Q_2020 until the end of year 2020, because of new circumstances caused by COVID-19 epidemic, we have introduced a new survey mode: CAPI  interviewers were conducting interviews from their homes or from offices by telephone. Because it was not possible to go to households, our CAPI interviewers for all households for which a telephone number was available, conducted interview by telephone. We have sent regularly announcement letters to households and asked them to send us on our e-mail address their phone number, in order to make a contact with them and to make an interview.  N All interviews that were conducted by CAPI interviewers from their homes or offices by phone, in variable MODE we have coded (2)-CATI .  N
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 Administrative sources: definition of persons in paid employment - based on the national labour law: "Persons in paid employment are all persons who have signed a work contract with the employer for a fixed or unspecified period of time, irrespective of type of ownership and of whether they work full time or less than full time.

Data on persons in employment in crafts and trades and free lances are processed according to data on active pension insurance beneficiaries, which are taken over from the records of the Croatian Institute for Pension Insurance. Data on insured persons − private farmers are taken over from the Croatian Institute for Pension Insurance.

"LFS: definition: "persons performed at least one working hour in the reference week"

Until 2016 the number of persons in employment in legal entities was compiled from regular monthly surveys. The survey on persons in paid employment in legal entities includes all persons who have signed a work contract, regardless of the type of work contract and whether they work full time or less than full time. Since 2016 data on persons in employment in legal entities were gathered by processing data from the “Report on income, income tax and surtax as well as contributions for mandatory insurances” (JOPPD form) in effect since 1 January 2014. The survey on persons in crafts and trades and free-lances includes owners and employees registered with the Croatian Institute for Pension Insurance. Data on insured persons − private farmers are taken over from the Croatian Institute for Pension Insurance.

Data collection: reports filled in by legal entities according to the records of persons in employment. Administrative data sources (Croatian Institute for Pension Insurance and Tax Administration) .

LFS: survey based on the sample of private households. Data collection: interviews in selected households

Notes on methodology (e.g. in First release) Notes on methodology (e.g. in Statistical Yearbook)
Total employment by NACE Administrative sources: Until 2016 the number of persons in paid employment in legal entities is a result of data processing of regular annual and monthly surveys, which covers 70% of persons in paid employment in each division of National Classification of Activities, 2007 version ( NKD 2007.).

Since 2016 data on persons in employment in legal entities were gathered by processing data from the "Report on income, income tax and surtax as well as contributions for mandatory insurances" (JOPPD form) in effect since 1 January 2014. 

Data on persons in employment in crafts and trades and free lances are processed according to data on active pension insurance beneficiaries, which are taken over from the records of the Croatian Institute for Pension Insurance. Data on insured persons − private farmers are taken over from the Croatian Institute for Pension Insurance. LFS: definition: "persons performed at least one working hour in the reference week".

Until 2016 the number of persons in employment in legal entities was compiled from regular monthly surveys. The survey on persons in paid employment in legal entities includes all persons who have signed a work contract, regardless of the type of work contract and whether they work full time or less than full time. Since 2016 data on persons in employment in legal entities were gathered by processing data from the “Report on income, income tax and surtax as well as contributions for mandatory insurances” (JOPPD form) in effect since 1 January 2014. The survey on persons in crafts and trades and free-lances includes owners and employees registered with the Croatian Institute for Pension Insurance.

Data collection: reports filled in by legal entities according to the records of persons in employment. Data on insured persons − private farmers are taken over from the Croatian Institute for Pension Insurance. Administrative data sources (Croatian Institute for Pension Insurance and Tax Administration)

LFS: survey based on the sample of private households. Data collection: interviews in selected households

Notes on methodology (e.g. in First release) Notes on methodology (e.g. in Statistical Yearbook, First release) 
Number of hours worked Administrative sources: Hours actually worked include actually worked hours (effective hours of work) in full-time and in working time shorter or longer than full-time. It also includes hours in cases when employees were present at their working place and were paid, but did not work because of damages, cleaning the machines, preparation or cleaning of tools, momentary lack of work, breaks shorter than 30 minutes, writing reports, job stop caused against a person’s will and on no fault of his or her own.

LFS: usual, actual hours of work (excluding the main meal breaks, absences from work within the working period for personal reasons, education and training hours which are not necessary for carrying out the production or ancillary activities)

Until 2016 data on hours actually worked of persons in paid employment in legal entities was compiled from regular monthly surveys. Coverage: This survey covers approximately 70% persons in employment from every division of the National Classification of Activities. The survey comprises persons in employment in legal entities of all types of ownership, government bodies, and bodies of local and regional government and self-government units, on the territory of the Republic of Croatia. Since 2016 data on hours actually worked in legal entities were gathered by processing data from the “Report on income, income tax and surtax as well as contributions for mandatory insurances” (JOPPD form) in effect since 1 January 2014. Persons employed in crafts and trades and free-lances and private farmers are not covered.  Notes on methodology (e.g. in First release) Notes on methodology (e.g. in Statistical Yearbook)

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
 LFS: ILO definition  Registered data on unemployment: Persons registered at the Croatian Employment Service. Notes on methodology (e.g. in the LFS First Release) 

 

Assessment of the effect of differences of LFS unemployment and registered unemployment     
Give an assessment of the effects of the differences          
Overall effect Men under 25 years Men 25 years and over Women under 25 years Women 25 years and over Regional distribution (NUTS-3)
UNA UNA UNA UNA UNA UNA
8.4. Coherence - sub annual and annual statistics

[not requested for the LFS quality report]

8.5. Coherence - National Accounts
Coherence of LFS data with National Accounts data    
  Description of difference in concept Description of difference in measurement Give an assessment of the effects of the differences Give references to description of differences
Total employment LFS: national concept

National Accounts: national concept for data in transmission tables T110Q, T110A, domestic concept for data in transmission tables T111Q, T111A and T303A.

Regional NA: domestic concept for data in transmission tables T1001,T1200 and T1002.

In National Accounts data are a bit higher because part of the illegal economy is involved in NA. This only applies to the national concept. For Domestic concept: Croatian residents who work abroad for up to one year and do not intend to stay longer are expelled, and foreigners who work with us for up to one year and do not intend to stay longer in the Republic of Croatia are expelled.

Introducing the Domestic concept of employment in NA introduces three sources: LFS, Non-observed economy and Census of the Ministry of Interior of people working abroad and of foreign workers working in Croatia for work permits. Accordingly, methodological changes were made in the Regional National Accounts too.

The national concept in NA gives a slightly higher results than the data from LFS. The domestic concept in relation to the national concept shows a certain trend which tells us that in recent years more and more Croatian residents have worked abroad, but this trend has been declining recently.  UNA
Total employment by NACE See above  See above   See above  UNA
Number of hours worked LFS: national concept

National Accounts: hours worked are not equal in national and domestic concept. Certain adjustments are being made for hours worked of Croatian residents who work abroad, as well as for foreign workers who come to work with us.

Hours worked have been increased in NA comparing to LFS, according to the number of people that are working in illegal economy.   See above  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 Y  N  N
8.6. Coherence - internal

[not requested for the LFS quality report]


9. Accessibility and clarity Top
9.1. Dissemination format - News release

[not requested for the LFS quality report]

9.2. Dissemination format - Publications
Please provide a list of type and frequency of publications
Statistics in Line - main figures from the LFS; published on the CBS website 12 weeks from the end of the quarter

First Release - Labour Force Survey: Labour Force in the Republic of Croatia - four times a year (first quarter: 24 June 2020; second quarter: 23 September 2020; third quarter: 23 December 2020; fourth quarter: 24 March 2021)

Statistical Reports - Labour Force Survey Results, Croatia 2020 - Europe 2020 - annual publication (to be released in October 2021 for LFS 2020)

9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.    
Web link to national methodological publication Conditions of access to data Accompanying information to data Further assistance available to users
www.dzs.hr The First Release is made available simultaneously to all interested institutions, media, individuals, etc. on the day of release. It can be sent to all interested parties at their request by e-mail. At the same time, the news release is also published on the website of the Croatian Bureau of Statistics (www.dzs.hr). All requests for information about the Croatian Labour Force Survey sent to CBS are answered within agreed period of time.  Further assistance is available via telephone or via e-mail to LFS department.
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 Research institutions, other producers of official statistics in the Republic of Croatia, etc.  CONDITIONS UNDER WHICH THE BUREAU TAKES OVER CONFIDENTIAL STATISTICAL DATA TO OTHER PRODUCERS OF OFFICIAL STATISTICS
In carrying out the official statistics activities and aimed at reducing the burden of reporting units and ensuring the harmonisation of the need to produce the official statistics or to estimate the quality of the official statistics results, the Bureau may provide other producers of official statistics in the Republic of Croatia the access to confidential statistical data that the Bureau collected in the statistical surveys, under the condition that it contributes to the effective development, production, dissemination or increasing the quality of the official statistics within the scope of activities of the producers of official statistics who requires the data and that the delivery of such data is legitimate.                                                                                                                                                                      
CONDITIONS OF THE ACCESS TO CONFIDENTIAL DATA FOR SCIENTIFIC PURPOSES                                                                                                                                                                       
The access to confidential data for scientific purposes may be granted only if the following conditions are fulfilled: - the application form has been submitted by a research entity or by an individual researcher (‘research entity’ means a legal entity entered into the register of scientific organisations kept by a competent registry body in the Republic of Croatia in line with special laws, or a legal entity included on a list of recognised research entities of the European Commission (Eurostat), which carry out statistical analyses for scientific purposes pursuant to specific EU laws; “individual researcher” means a scientist entered into the register of scientists kept by a competent registry body in the Republic of Croatia pursuant to specific laws, who individually submits the application for access to the data for scientific purposes) - the application form for the access to confidential data for scientific purposes has been fully completed and signed by the person in charge in the research entity or by the individual researcher - the application for the access to confidential data for scientific purposes has been granted - all researchers for whom the access to confidential data for scientific purposes was requested have signed the individual confidentiality declarations - the contract between the CBS and the research entity or the individual researcher has been signed.
Methodological guidelines, questionnaire, list of variables, list and description of aggregated variables etc. Contacts and meetings with LFS methodologists
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
Methodological notes about the survey and its characteristics are available at request, but only in Croatian language.
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
The anonymised LFS microdata are available for users from research institutions. For confidentiality reasons, some data (eg. name, address, date of birth etc.) are excluded from database; some variables are given only by aggregation at higher level (economic activity, occupation etc.). Depending on the type of access, microdata are more (the access to data on CD-Rom, DVD) or less anonymised (the access to data in the "safe room" and "remote" access). 


12. Comment Top

Referring to field 6.3.3.1. ,  table "Of which people who migrated (or moved) internally or abroad", these data could not be calculated because we do not collect information on reason for non-contact in a way that is requested.


Related metadata Top


Annexes Top