Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Czech Statistical Office


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



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

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1. Contact Top
1.1. Contact organisation

Czech Statistical Office
1.2. Contact organisation unit

6402 - Unit for Labour Force, Migration and Equal Opportunities
1.5. Contact mail address

Na padesátém 81
100 82 Praha 10
Czech Republic


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 survey covers the whole country. Only private households are surveyed. Housekeeping Members living together in the same dwelling, sharing household expenditures. The target population comprises all persons living usually in the selected dwellings, disregarding the type of their stay there (permanent, temporary or non-registered). The temporarily absent persons (plan to stay for not more than 1 year) and domestic servants are included. It does not cover persons (students, workers, migrants) living in collective accommodation establishments. Lodgers are considered as independent budget keeping households. People living abroad are excluded. 15+

 

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 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)                                  
 Evenly spread over the 52 weeks of the year, based on a reference fixed week  N
2.2. Classification system

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

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

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

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

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

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

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

[not requested for the LFS quality report]


3. Statistical processing Top
3.1. Source data
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.) Base used for the sample (sampling frame)  Last update of the sampling frame (continuously updated or date of the last update) Primary sampling unit (PSU)   Final sampling unit (FSU)
The sampling plan is stratified two-stage probability sample of dwelling units Register of Census Areas 2013 Census areas Dwelling units

 

Sampling design & procedure
First (and intermediate) stage sampling method   Final stage sampling method Stratification (variable used) Number of strata (if strata change quarterly, refer to Q4). Rotation scheme (2-2-2, 5, 6, etc.)
The primary sampling units are census (enumeration) areas that are sampled (by randomised systematic sampling) with probability proportional to size, i.e. a number of dwellings per census area. In the second stage, dwellings are selected from the initial sample by simple random sampling. The strata consist of 77 districts, including Prague considered as one district 77  5

 

Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate Size of the theoretical yearly sample
(i.e. including non-response) (i.e. including non-response)
 2.4% The initial (1st wave) sample of PSUs is 4 520 census areas (totally 22 600 census areas), while the approximate final sample size is 135 500 dwelling units per year. Regarding response rate it amounts to 95 500 households on an yearly basis. (About 92 000 households were contacted during the covid measures.)

  

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)
 0.6% The initial (1st wave) quarterly sample of PSUs is 1 130 census areas (totally 5 650 census areas), while the approximate final sample size is 33 900 dwelling units per quarter. Regarding response rate it amounts to 23 800 households on a quarterly basis. (About 23 000 households were contacted during the covid measures.)

  

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)
 1st wave  Yes  NA  SUPVISOR, SIZEFIRM, WAYJFOUN, FTPTREAS, TEMPREAS, TEMPAGCY, SHIFTWK, EVENWK, NIGHTWK, SATWK, SUNWK, WAYMORE, HOMEWK, LOOKREAS, LEAVREAS, SEEKREAS, AVAIREAS, PRESEEK, NEEDCARE, REGISTER, WSTAT1Y, STAPRO1Y, NACE1Y2D_rev2, COUNTR1Y, REGION1Y, REG3D1Y

 

Brief description of the method of calculating the quarterly core weights Is the sample population in private households expanded to the reference population in private households? (Y/N) If No, please explain which population is used as reference population Gender is used in weighting (Y/N) Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)? Which regional breakdown is used in the weighting (e.g. NUTS 3)? Other weighting dimensions
The weights are based on the post-stratification into 13 age groups, sex and the 77 districts. Demographic figures for each quarter 2020 were forecasted from the definitive demographic data for end-of-year 2019 with assuming a migration and natural increase.  N  to the total population Y   13 age groups (0-14,15-19,…,60-64,65-69, 70+)  77 districts  N

 

Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables) Gender is used in weighting (Y/N) Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)? Which regional breakdown is used in the weighting (e.g. NUTS 3)? Other weighting dimensions
The weights are based on the post-stratification into 6 age groups, sex and the 8 districts.   Y 6 age groups (0-14,15-24,25-34,…,55+)

 8 districts, NUTS2

 economic activity, 2 phases due to the absence of some stratum

 

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)
Person's weight as of the household unit  N (base sample of Register of Census Areas) household size gender, age, region N
3.2. Frequency of data collection

[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description Use of dependent interviewing (Y/N)? Participation is voluntary/compulsory?
Data are collected in first visits with face-to-face interviews, with repeated interviews are partly made by telephone (20%). Interviewers for the lack of time usuallywrite on a paper questionnaire, then overwrite the notebook.

Case 1: subsample wave n+1 = subsample wave n. During the (n+1)th interview, interviewers try to reach the whole sample of the first wave, including the non-respondents.

Sample of PSU is dwelling then they are distinguished households, number will increase only 0.7 percent.

N voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 8%  25%  40%  NA  27%
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)
 One of two sources of CZ unemployment awareness
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 NUTS 4 for total employment by sex onlyby NSI Brief description of the method which is used to produce NUTS-3 unemployment and labour force data sent to Eurostat?
Census area NUTS 3 LAU for total employment by sex only No method is used. The all database is sent.
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
500 3000 1000 6000
6.2.1. Sampling error - indicators
Coefficient of variation (CV) Annual estimates
Sampling error - indicators - Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)       
 

Number of employed persons

Employment rate as a percentage of the population

Number of part-time employed persons

Number of unemployed persons

Unemployment rate as a percentage of labour force

Youth unemployment rate as a percentage of labour force

Average actual hours of work per week(*)
 

Age group: 20 - 64

Age group: 20 - 64

Age group: 20 - 64

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24

Age group: 20 - 64
 CV  0.27  0.55  2.50  3.29  3.30  7.27  0.14
 SE  27.7 (thousand)  0.44%  7.2 (thousand)  4.5 (thousand)  0.08%  0.58%  0.05 (hours)
 CI(**) 5012.2, 5120.7 (thousand)  78.87, 80.57 %  269.7, 298.0 (thousand)  128.1, 145.9 (thousand)  2.39, 2.72 %  6.83, 9.10 %  38.10, 38.31 (hours)

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 NR

 

Reference on software used: Reference on method of estimation:
 R 1.3.959  Svydesign in package Survey

 

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 
 CZ01 Praha  0.85  1.74  6.71  11.37  11.46  31.37  0.59
 CZ02 Stredni Cechy  0.69  1.51  7.95  9.31  9.30  22.23  0.32
 CZ03 Jihozapad  0.67  1.45  6.39  9.77  9.80  20.24  0.29
 CZ04 Severozapad  0.93  1.73  9.22  8.62  8.63  19.14  0.38
 CZ05 Severovychod  0.68  1.41  6.32  8.75  8.80  20.26  0.38
 CZ06 Jihovychod  0.63  1.33  5.55  7.84  7.84  18.03  0.34
 CZ07 Stredni Morava  0.80  1.66  8.02  9.58  9.60  19.35  0.39
 CZ08 Moravskoslezsko   0.85  1.58  6.91  8.89  8.94  17.28  0.40

 

(*) The coefficient of variation for actual hours worked should be calculated for the sum of actual hours worked in 1st and 2nd jobs, and restricted to those who actually worked 1 hour or more in the reference week.

(**) The value is based on a CI of 95%. For the rates the CI should be given with 2 decimals.
6.3. Non-sampling error

 [not requested for the LFS quality report]
6.3.1. Coverage error
Frame quality (under-coverage, over-coverage and misclassifications(b))      
Under-coverage rate (%) Over-coverage rate (%) Misclassification rate (%)  Comments: specification and impact on estimates(a)   
 Undercoverage  Overcoverage  Misclassification(b)  Reference on frame errors
 UNA  NA  UNA  Households are selected once a year from the Register of Census Areas. Due to differencies in time span there is not the current information about addresses or  flats. The sampling frame contains only private households. Persons living in institutional households are not covered  Not existing or not inhabited flats remain in the Register of Census Areas.  UNA  UNA

 

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

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

[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)   
Was the questionnaire updated for the 2019 LFS operation? (Y/N) Synthetic description of the update Was the questionnaire tested? (Y/N) If the questionnaire has been tested, which kind of tests has been applied (pilot, cognitive, internal check)?
 N  NA  Y  internal check

 

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)
 N  Y
Interviewer  Periodical training (at least 1 time per year) (Y/N)  Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
 Y  N
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)
 N  N  Y
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 Y  Y
Other / Comments  NA
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
 N  NA  NA
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
 UNA  UNA  UNA  NA  UNA

 

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  29.09  16.38  3.11  UNA
2  28.64  16.28  3.94  UNA 
3  22.43  17.00  4.81  UNA 
4  24.62  15.94  3.05  UNA 
Annual  26.23  16.40  3.72  UNA 

 

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_Q1_2019  694      
Subsample_Q2_2019  989  669    
Subsample_Q3_2019  1215  932  771  
Subsample_Q4_2019  1162  1108  981  750
Subsample_Q1_2020  1313  1285  1071  876
Subsample_Q2_2020    1298  1211  1095
Subsample_Q3_2020      1357  1134
Subsample_Q4_2020        1251
Total in absolute numbers  5373  5292  5391  5106
Total in % of theoretical quarterly sample  17 %  16 %  17 %  16 %

 

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_Q1_2019  408      
Subsample_Q2_2019  233  482    
Subsample_Q3_2019  153  290  582  
Subsample_Q4_2019  122  206  425  372
Subsample_Q1_2020  103  143  228  209
Subsample_Q2_2020    159  181  162
Subsample_Q3_2020      109  116
Subsample_Q4_2020        117
Total in absolute numbers  1019  1280  1525  976
Total in % of theoretical quarterly sample  3 %  4 %  5 %  3 %

 

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_Q1_2019 M?      
Subsample_Q2_2019 M? M?    
Subsample_Q3_2019 M? M? M?  
Subsample_Q4_2019 M? M? M? M?
Subsample_Q1_2020 M? M? M? M?
Subsample_Q2_2020   M? M? M?
Subsample_Q3_2020     M? M?
Subsample_Q4_2020       M?
Total in absolute numbers M? M? M? M?
Total in % of theoretical quarterly sample       M?

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
 CZ01- Praha  34.49
 CZ02- Stredni Cechy  18.67
 CZ03- Jihozapad  24.53
 CZ04- Severozapad  33.81
 CZ05- Severovychod  25.79
 CZ06- Jihovychod  23.13
 CZ07- Stredni Morava  26.67
 CZ08- Moravskoslezsko  24.77

* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview
6.3.3.2. Item non-response - rate
Item non-response - Quarterly data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)       

Variable status

 Column Identifier Quarter 1 Quarter 2 Quarter 3 Quarter 4 Short comments on reasons for non-available statistics and prospects for future solutions

Compulsory / optional
compulsory Col_110 - Not employed METHODH . C . .  
compulsory Col_123 EDUCSTAT 10.9 9.3 3.4 5.5  Only persons aged 15-69 

 

Item non-response - Annual data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)    
Variable status Column Identifier This reference year Short comments on reasons for non-available statistics and prospects for future solutions
compulsory  Col_154/155  INCDECIL    It will be solved by imputation with a one-year delay.
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, Supervisors in regions check text description of codes and chosen classification code.

(In the electronic questionnaire there are integrated checkings to control logic links of variables.)

  2 %
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
 Y  Y  Y  Demetra ver. 2.2.2
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N) Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF) (Y/N)
Y  Y, by option
6.6. Data revision - practice

[not requested for the LFS quality report]
6.6.1. Data revision - average size

[not requested for the LFS quality report]


7. Timeliness and punctuality Top
7.1. Timeliness
Restricted from publication
7.1.1. Time lag - first result
Restricted from publication
7.1.2. Time lag - final result
Restricted from publication
7.2. Punctuality
Restricted from publication
7.2.1. Punctuality - delivery and publication
Restricted from publication


8. Coherence and comparability Top
8.1. Comparability - geographical

Divergence of national concepts from European concepts

(European concept or National proxy concept used) List all concepts where any divergences can be found

    
Is there a divergence between the national and European concepts for the following characteristics? (Y/N) Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)  N  NA
Identification of the main job (*)  N  NA 
Employment  N  NA 
Unemployment  N  NA 
8.1.1. Asymmetry for mirror flow statistics - coefficient

[not requested for the LFS quality report]
8.2. Comparability - over time
Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes in (Y/N) Description of the impact of the changes Statistics also revised backwards (if Y: year / N) Variables affected Break in series to be flagged (if Y: year and quarter/N)  
concepts and definition N  NA  NA  NA  NA
coverage (i.e. target population) N  NA  NA  NA  NA
legislation N  NA  NA  NA  NA
classifications N  NA  NA  NA  NA
geographical boundaries N  NA  NA  NA  NA

 

Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes to (Y/N) Description of the impact of the changes Statistics also revised backwards (if Y: year / N) Variables affected Break in series to be flagged (if Y: year and quarter/N)
sampling frame  N  NA  NA  NA  NA
sample design  N  NA  NA  NA  NA
rotation pattern  N  NA  NA  NA  NA
questionnaire  N  NA  NA  NA  NA
instruction to interviewers  N  NA  NA  NA  NA
survey mode  N  NA  NA  NA  NA
weighting scheme  N  NA  NA  NA  NA
use of auxiliary information  N   NA  NA  NA  NA
8.2.1. Length of comparable time series

[not requested for the LFS quality report]
8.3. Coherence - cross domain
Coherence of LFS data with Business statistics data    
  Description of difference in concept Description of difference in measurement Give an assessment of the effects of the differences Give references to description of differences
Total employment  BP excludes persons on maternity leave, persons working under “Contract for work”, employees of Ministry of Interior and Defence, majority of state officials.  It is not possible to compare it.  BP is primarily focused on production-related variables in relation to some estimates of employment.  Unknown  UNA
Total employment by NACE  BP classifies NACE as a prevailing activity of the company instead of the local unit. BP classifies NUTS according to the residence of the company instead of the local unit.  It is not possible to compare it.  BP is primarily focused on production-related variables in relation to some estimates of employment.  Unknown  UNA
Number of hours worked  BP uses paid hours instead of actually or usually worked hours.  BP uses paid hours instead of actually or usually worked hours.  Unknown  UNA

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
 LFS is in accordance with ILO definition. Registered unemployment involves all persons who registered with Labour Office due to seeking a job and do not work, however the condition of not working is not officially checked.  LFS-unemployed category includes persons who have not contacted Labour Offices (unregistered) and excludes persons who might have contacted Labour Office but do not satisfy ILO conditions. LFS also provides a figure of registered unemployed that is regularly compared with actual figures of Labour Offices.  Register is an exhaustive source of persons interested in help or support from public services. LFS depends on response rate and reliability of data collected from respondents.

 

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)
 Since 1999 figures on the registered unemployed are higher than LFS-unemployed figures. It is connected with the relatively high rate of refusals in the Czech Republic  Age structure of men is almost identical when comparing ILO unemployed and registered persons.  Age structure of men is almost identical when comparing ILO unemployed and registered persons.  Age structure of women is almost identical when comparing ILO unemployed and registered persons.  Age structure of women is almost identical when comparing ILO unemployed and registered persons.  NA
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  NA use population of residents instead of population usually living in private households, foreigners are added from administrative sources, black economy and self-suppliers are estimated.  Statistics, administrative sources expert estimates.  5% over LFS figures  UNA
Total employment by NACE  NA classify NACE as a prevailing activity of company instead of local unit. NA classify NUTS according to residence of company instead of local unit.  Prevailing activity (NA) versus economic activity of the local unit (LFS)  In average 15% difference over all categories of NACE.  UNA
Number of hours worked  NA do not use hours. Counting of full-time equivalent is based on LFS data.  Full-time equivalent (NA) versus number of hours worked (LFS)  Difference between number of hours in full-time equivalent and number of hours actually worked is in average 5 %  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)
 Y, (also Unemployment as registered unemployed in Employment office)  N  N  N  N  N
8.6. Coherence - internal

[not requested for the LFS quality report]


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

[not requested for the LFS quality report]
9.2. Dissemination format - Publications
Please provide a list of type and frequency of publications

Press releases – monthly, quarterly (Czech/English, electronic version)

Employment and Unemployment in the Czech Republic as Measured by the Labour Force Sample Survey – quarterly publication (Czech/ English, electronic version)
Labour Market in the Czech Republic – time series 1993-2018 (previous year resp.) – yearly publication (Czech/English, electronic version)
Labour Market for each region (NUTS-3) of the Czech Republic 2018 - yearly publication (Czech/English, electronic version)
Anthology of statistical analysis – yearly contribution on specific topic of the ad hoc module
9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.    
Web link to national methodological publication Conditions of access to data Accompanying information to data Further assistance available to users
Link to the national web page: https://www.czso.cz/csu/czso/employment_unemployment_ekon Electronic publications are available on internet website of NSI (www.czso.cz)
Selected tables from publications are available also on internet website of NSI (www.czso.cz)
Press releases are published via website only.
Data which are not published might be ordered via contact through Information department of NSI (infoservis@czso.cz). The data are provided for free, but costs of working time of expert(s) to work out the task must be paid.
It is possible to buy whole dataset of anonymous data.		 Data users are provided with oral explanations and relevant methodological part of instructions for interviewers. Provision of datasets puts an additional burden on our experts in form of following assistance. We provide oral consultation, written evaluation of external analysis on related topic.
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  State enterprise, researcher and educational enterprise  research  general data colletion information  consultation
9.5. Dissemination format - other

[not requested for the LFS quality report]
9.6. Documentation on methodology
References to methodological notes about the survey and its characteristics
 UNA
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
 NR


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top