Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Polandul. Niepodległości 208,00-925 Warszawa


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

Statistics Poland
ul. Niepodległości 208,
00-925 Warszawa
1.2. Contact organisation unit

Labour Market Department
1.5. Contact mail address

Małgorzata Długołęcka
Labour Market Department
Statistics Poland
ul. Niepodległości 208,
00-925 Warszawa


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, however we collect also some information on members of household staying in  collective household if they are part of target population. The target population covers all persons 15 years old and older with usual residence in Poland.

Persons living in institutional households (army, hospital, prison, hostels etc.) for a total period exceeding one year are excluded from the survey. The same applies to persons living permanently or temporarily (for more than one year) in other countries.

 Housekeeping Members living regularly together in the same dwelling, sharing income, household expenditures, food and other essentials for living The following categories of people are considered as members of a household:

- persons present in a household (registered for a permanent or temporary stay, staying or intending to stay without registering for 12 months and more in a household),
-persons absent for duration shorter than 12 months in a household (e.g. persons staying temporarily abroad, living in institutional households or other households in the country for duration shorter than 12 months).

Persons living in institutional households (army, hospital, prison, hostels etc.) for a total period exceeding one year are excluded from the survey. The same applies to persons living  permanently or temporarily (for more than one year) in other countries.

 15 years and more (no upper limit)

 

Population concept  Specific population subgroups
Primary/secondary students Tertiary students People working out of family home for an extended period for the purpose of work People working away from family home but returning for weekends Children alternating two places of residence
Usual residence (12 months) Family home Term address 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)                                  
Y  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)
Two-stage stratified probability sampling of dwelling units. OBS - statistical sampling frame for social surveys continuously updated The primary sampling units refer with few exceptions to census clusters in towns and enumeration districts in rural 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.)
PSUs are sampled within strata with sampling probability proportional to the number of dwellings in a PSU. In the second stage a total of 55536 (in quarters 2, 3, 4) dwelling units per quarter are sampled from selected PSU's stratified by size of the municipality The primary sampling units are stratified by urban/rural division of NUTS2 regions; stratification within NUTS2 regions depends on the size of the place, with rural areas included among the smallest ones  70 The quarterly sample is divided into four sub-samples, subject to the rotation  scheme 2-(2)-2. In each quarter are surveyed two elementary samples surveyed in the previous quarter, one sample introduced into the survey for the first time and one sample which was introduced into the survey exactly a year before (overlap of 50% between samples in two successive quarters)

 

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)
 1.6% of dwelling units  55497 (first quarter) + 55536 x 3 = 222 105 dwelings

  

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)
 0.4% of dwelling units  55536 dwellings

 

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
The weights are computed using a four-step procedure. First the initial design weights are calculated for dwelling units, i.e. the reciprocals of the selection probabilities for the final sampling units in each stratum. Secondly, the weighted response rates are calculated for sampling units stratified a posteriori by six place-of-residence categories in each NUTS2 region. Thirdly, the initial weights are adjusted by the response rates. The final step consists of modifying the adjusted weights using the population estimates stratified a posteriori by the urban-rural division, sex and 12 age groups plus 3 age groups for children (children - people with age under 15 years) separately in each NUTS2 region.  N Reference population covers entire population excluding members of households living temporarily abroad for more than 12 months or living in institutional households. Y 0-4 years, 5-9 years, 10-14 years, 15-17 years, 18-19 years, 20-24 years, 25-29 years, 30-34 years, 35-39 years, 40-44 years, 45-49 years, 50-54 years, 55-59 years, 60-64 years, 65 years and more  NUTS 2 6 categories of place of residence of a given dwelling (the rural area or one of the five town classes).

 

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 subsampling is not applied to survey yearly variables. Yearly weights are calculated as averages of quarterly weights.   Y 0-4 years, 5-9 years, 10-14 years, 15-17 years,    18-19 years, 20-24 years, 25-29 years, 30-34 years, 35-39 years, 40-44 years, 45-49 years, 50-54 years, 55-59 years, 60-64 years, 65 years and more  NUTS 2  6 categories of place of residence of a given dwelling (the rural area or one of the five town classes)

 

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)
The final weights for generalizations concerning households since the Ist quarter 2016 are calculated as mean values of final weights attributed to household members. In case when only some persons in a household submitted the questionnaire for the respondents, other members of such household who did not submit the questionnaire for the respondents are given zero final weight. The final weight for a household is the mean value of the final weights of the household members including persons with zero final weight. The final weight is attributed to the person who is the household head, while the estimate of the number of households in a given quarter is calculated by adding such weights for all household heads.  N Number of household members (household size) gender, 15 age groups, NUTS2 regions, 6 categories of place of residence of a given dwelling (the rural area or one of five town classes) 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?
The data were collected in 2020 mainly with the use of telephone interviews (CATI method) and only in the 1st quarter face-to-face interviews - CAPI method were used (in case of problems with IT applications, equipment or on respondent request paper questionnaires were used). Y (we use for some variables historical data from previous observations which are during the interview verified by the respondent, however, information about each respondent known prior to the interview is not used to determine question routing and wording).  voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 23.08  74.46  2.46  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)
 We have many users of our data, and for all of them (e.g policy makers, academic researchers, students) our data are important.
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?
 LAU  NUTS-2 NUTS-2    3-year average from the LFS dataset
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
 10000  20000  NA  NA
6.2.1. Sampling error - indicators
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 0.28 0.28 2.52 2.60 2.62 5.05 0.15
 SE 45203.51 0.21 23037.91 13984.26 0.08 0.55 0.06
 CI (**) 15889387.5/16066585.2 73.14/73.96 867757.7/958066.3 509479.7/564298.0 3.00/3.33 9.76/11.91 39.20/39.43

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The denominator for the calculation of the CV for the employment rate is the estimate of the employment rate as a percentage of the population

 

Reference on software used: Reference on method of estimation:
 SAS Base Botstrap method with calibration of bootstrap weights

Shao J. and Tu D., The Jackknife and Bootstrap, Springer-Verlag, New York 1995.

 

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 
PL21 Małopolskie 1.13 1.13 10.65 11.69 11.73 26.98 0.54
PL22 Śląskie 0.93 0.93 7.02 9.11 9.09 16.95 0.46
PL41 Wielkopolskie 1.08 1.08 8.55 11.91 11.94 23.06 0.60
PL42 Zachodniopomorskie 1.18 1.18 8.99 9.91 9.93 23.65 0.60
PL43 Lubuskie 1.05 1.05 7.89 11.76 11.86 21.69 0.45
PL51 Dolnośląskie 1.25 1.25 9.19 11.23 11.32 23.68 0.61
PL52 Opolskie 0.93 0.93 7.94 10.51 10.50 21.28 0.51
PL61 Kujawsko-pomorskie 1.19 1.19 8.58 10.03 10.03 21.23 0.66
PL62 Warmińsko-mazurskie 1.46 1.46 13.19 13.60 13.66 22.35 0.58
PL63 Pomorskie 1.08 1.08 9.02 10.66 10.82 21.25 0.59
PL71 Łódzkie 1.34 1.34 9.37 13.04 13.36 32.51 0.71
PL72 Świętokrzyskie 1.13 1.13 7.90 8.35 8.47 13.16 0.50
PL81 Lubelskie 1.17 1.17 10.77 9.05 8.93 16.03 0.93
PL82 Podkarpackie 1.05 1.05 10.83 9.36 9.40 18.49 0.59
PL84 Podlaskie 0.91 0.91 8.96 9.36 9.36 20.40 0.52
PL91 Warszawski stołeczny 0.88 0.88 8.38 10.21 10.25 23.29 0.48
PL92 Mazowiecki regionalny 1.05 1.05 9.98 8.16 8.13 14.87 0.58

(*) 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  4.48  UNA New dwellings underrepresented in the sample - dwellings are selected once a year from the register of housing units and due to differences in time span there is no current information about addresses or flats. Overcoverage consists of dwellings in which inhabitants are not present for a long time, not inhabited or inhabited seasonally, changed into inhabitable space (for example shop), in liquidation, not found (incorrect address)  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)?
 Y

Since Q1 week 12th there were introduced additional questions targeted at assessment of the  impact of  the COVID-19 pandemic on the labour market situation. 

  N  NA

 

Main methods of reducing measurement errors 
Error source  
Respondent  Letter introducing the survey (Y/N) Phone call for booking or introducing the survey (Y/N)
 Y  N
Interviewer  Periodical training (at least 1 time per year) (Y/N)  Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
 Y  Y
Fieldwork  Monitoring directly by contacting the respondents after the fieldwork (Y/N) Monitoring directly by listening the interviews (Y/N) Monitoring remotely through performance indicators (Y/N)
 Y  N  Y
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 N  Y
Other / Comments  
6.3.3. Non response error

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

IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *

Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N) Variables used for non-response adjustment Description of method
 Y variable: place of residence (5 categories of towns and rural area) in the NUTS2 regions The interview rates R are calculated by the formula: R=(K-N)/K, where K is the number of interviewed dwellings estimated using primary weights and N is the estimate of the number of dwellings that were qualified for the survey but were not interviewed regardless of the reasons. The interview rates are calculated for each of 17 NUTS2 regions in six categories of place of residence. The secondary weights are calculated by dividing the primary weights (reciprocals of selection probabilities for dwellings) by the corresponding R rate (the R rate depends on the NUTS2 region and the category of a place of residence of a given dwelling).
Substitution of non-responding units (Y/N) Substitution rate Criteria for substitution
 N  NA  NA
Other methods (Y/N) Description of method
 N  

  

Non-response rates by survey mode. Annual average (% of the theoretical yearly sample by survey mode)
Survey
CAPI CATI  PAPI  CAWI  POSTAL
 51.69  33.06  0.00  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 48.53 22.09 17.73  UNA
2 14.04  2.35  3.91  UNA
3 37.10 17.15 11.04  UNA
4 29.18 11.47  9.89  UNA
Annual 33.93 14.45 11.34  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_Q4_2018 2674      
Subsample_Q1_2019 2761 146    
Subsample_Q2_2019   159 86  
Subsample_Q3_2019     620 621
Subsample_Q4_2019 2702     152
Subsample_Q1_2020 2663 103    
Subsample_Q2_2020   283 4022  
Subsample_Q3_2020     3859 491
Subsample_Q4_2020       3723
 Total in absolute numbers 10800 691 8587 4987
 Total in % of theoretical quarterly sample  19.46  2.24  16.39 10.60

  

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 1862      
Subsample_Q1_2019 1916 255    
Subsample_Q2_2019   272 229  
Subsample_Q3_2019     713 649
Subsample_Q4_2019 2301     240
Subsample_Q1_2020 2778 168    
Subsample_Q2_2020   580 2203  
Subsample_Q3_2020     2123 1235
Subsample_Q4_2020       2014
 Total in absolute numbers 8857 1275 5268 4138
 Total in % of theoretical quarterly sample  15.96  4.13  10.06  8.79

  

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

  

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
PL21-Małopolskie 43.85
PL22-Śląskie 35.55
PL41-Wielkopolskie 31.87
PL42-Zachodniopomorskie 39.76
PL43-Lubuskie 36.13
PL51-Dolnośląskie 41.14
PL52-Opolskie 28.96
PL61-Kujawsko-pomorskie 29.34
PL62-Warmińsko-mazurskie 22.91
PL63-Pomorskie 33.27
PL71-Łódzkie 33.79
PL72-Świętokrzyskie 26.11
PL81-Lubelskie 26.34
PL82-Podkarpackie 27.03
PL84-Podlaskie 25.85
PL91-Warszawski stołeczny 45.81
PL92-Mazowiecki regionalny 24.90

* 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_114 - Employed METHODL . C . . In the second quarter of 2020 the Awaiting the results of a competition for recruitment to the public sector as one of the method of seeking job didn’t occur for the employed looking for another job, that’s why the variable METHODL=0 for WSTATOR=1, 2 and LOOKOJ=1 (there is no METHODL=1 for this group).

 

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  69.7  Very sensitive question. No answer allowed.

(*) "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 )
 N  NA
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 NA
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N) Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF) (Y/N)
 Y  We are compliant (Y), however the PEEIS are computed by Eurostat not by the national statistical offices.
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) Y The samples surveyed for the first time in the 3rd and 4th quarter 2020 were redrawn from the sampling frame subset comprising only dwellings with telephone numbers available N UNA N
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 Y The sample surveyed for the first time in the 2nd quarter 2020 was replaced by joined parts of two samples surveyed previously for which telephone numbers were available. In the 3rd and 4th quarter 2020 two additional samples surveyed for the 5th and 6th time were used together with the samples foreseen by the rotation scheme in order to assure satisfactory response rate. The changes result from the organisation of the survey during the COVID – 19 pandemic. N UNA N
rotation pattern N NA NA NA NA
questionnaire N NA NA NA NA
instruction to interviewers Y UNA UNA UNA UNA
survey mode Y In the 2nd, 3rd and 4th quarter 2020 data were collected only by telephone interviews (CATI method) N UNA N
weighting scheme Y Since the third quarter of 2020, an additional calibration condition has been introduced taking into account the structure of the population by level of education. It was introduced in order to ensure comparability of the survey results with the previous periods. N NA N
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 Business surveys comprise only persons employed in enterprises. LFS in contrary to business statistics covers employment in informal economy and all forms of contracts (contracts of specific work, contract of mandate). LFS does not cover people living in collective households. LFS covers residents of Poland working abroad (if they absence in households is less than 12 months) and business statistics covers persons working in Poland for Polish entities (which are not Polish residents). In business statistics number of persons employed is measured at the end of the reference period and the number of employees as average in FTE. In LFS generally it is counted as number of persons in a given quarter.  UNA  UNA
Total employment by NACE LFS cover all NACE groupings, STS industry, construction, retail trade, repairs and other services (but for example without financial ones); SBS covers industry, construction, distributive trade, services (but without not market ones e.g. health, education) NACE code in LFS depends on the knowledge of respondent regarding the economic activity of firm in which this respondent works. In business statistics the NACE code is based on declaration of the company.  UNA  UNA
Number of hours worked NA- differences not present or not known. Hours actually worked but not recognized by employer are not counted in business statistics in contrary to LFS.  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
Registered unemployment is measured according to national legislation and its definition differs from ILO unemployment concept. Labour offices use the definition of the unemployed according to the Act of 20 April 2004 on Promotion of Employment and Labour Market Institutions (uniform text Journal of Laws 2020 item 1409, with later amendments) in which as unemployed are classified: persons aged 18 and more and who have not reached the retirement age (in case of LFS the possible age is 15 years and more without upper age limit, person may be in retirement and be unemployed), are not employed and not performing any other kind of paid work, capable of work and ready to take full-time employment or in the case of disabled persons ― able and ready to take work comprising no less than a half of working time (in case of LFS looking actively for any work matters), not attending school with the exception of schools for adults (or taking extra curriculum exam covering this school as well as those studying at the stage II sectoral vocational school and post-secondary school, providing full-time, evening or weekend education) or tertiary schools in part-time programme (in case of LFS person looking for work even if she/he is student/pupil can be unemployed), registered in the local labour office, appropriate for their (permanent or temporary) place of residence (in case of LFS person don`t have to be registered in powiat labour office), and seeking employment or any other income-generating work (in case of LFS person must actively look for work), with additional provisions concerning the sources of income, included in the law. Registered unemployment:  number of unemployed persons on the end of the period - that is on the end of the month or end of the quarter.  LFS: there are an average number of unemployed persons through the period (quarter).  https://stat.gov.pl/en/topics/labour-market/working-unemployed-economically-inactive-by-lfs/labour-force-survey-in-poland-iv-quarter-2020,2,40.html

 

https://stat.gov.pl/en/topics/labour-market/registered-unemployment/registered-unemployment-i-iv-quarter-2020,2,44.html

 

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)
III quarter 2020

1023.7 - registered unemployment

561 - unemployment LFS

Difference: 462.7

 

IV quarter 2020

1046.4 - registered unemployment

531 -unemployment LFS

Difference: 515.4 

 

all data in thousands

 III quarter 2020

59.0 - registered unemployment

71- unemployment LFS

Difference: -12.0

 

IV quarter 2020

57.0 - registered unemployment

79 - unemployment LFS

Difference: -22.0

 

all data in thousands

 III quarter 2020

411.8  -registered unemployment

212- unemployment LFS

Difference: 199.8

 

IV quarter 2020

427.9 - registered unemployment

211 - unemployment LFS

Difference: 216.9

 

all data in thousands

 III quarter 2020 

75.9 -registered unemployment

65 -unemployment LFS

Difference: 10.9

 

IV quarter 2020

73.9 - registered unemployment

56 - unemployment LFS

Difference: 17.9

 

all data in thousands

 III quarter 2020

477.0  -registered unemployment

212- unemployment LFS

Difference: 265.0

 

IV quarter 2020

487.8 -registered unemployment

185 - unemployment LFS

Difference: 302.8

 

all data in thousands 

 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 We use domestic concept and national concept. According to national concept there is no difference with LFS. According to domestic concept there are the following differences. LFS data used in national accounts are adjusted by excluding Polish residents working abroad (residents working outside the economic territory) and by including foreigners working for the Polish employers (non residents working inside the economic territory).The data on foreigners working in Poland are taken from the annual survey Z-06 on employment, wages and salaries, and hours worked. The survey is carried out by the Statistics Poland. The survey covers all enterprises of national economy, in which the number of persons employed is more than 9 persons. Data from Labour Force Survey by excluding residents working abroad and by including foreigners working for the Polish employers. I quarter 2020 LFS data: 16425 thous./ NA*:16379,7 thous./ difference: 45.3 thous.

II quarter 2020 LFS data: 16274 thous./ NA*: 16209,7
thous./ difference: 64.3 thous.

III quarter 2020 LFS data: 16512 thous./ NA*: 16424,7 thous./difference
87.3 thous.

IV quarter 2020 LFS data: 16555 thous./ NA*: 16492,7 thous./ difference:
62.3 thous.

Annual average LFS data: 16442 thous./ NA*: 16376,8 thous. /difference: 65.2 thous.

 

*provisional data

  UNA
Total employment by NACE  No difference in concept.  NA  NA  NA
Number of hours worked The total number of hours worked of all persons employed according to the “domestic concept” consists of: total number of hours worked by employees from the survey LFS (excluding residents working outside the economic territory) and the number of hours worked by foreigners working in resident units (statistical survey Z-06 conducted by enterprises). In the LFS, the average number of hours worked per week is calculated as the ratio of the sum of hours worked in the reference week (the actual number of hours) to the number of persons working in the reference week. The following method of estimation of the number of hours worked by employed is adopted: number of total hours worked by employed persons working in the quarter is multiplied by the number of  employed persons and the average number of hours worked in the reference week and the average number of weeks in the quarter. Data from Labour Force Survey by excluding residents working abroad and by including foreigners working for the Polish employers. 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)
       X    
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

1. Quarterly information on the labour market - short publications with main results from LFS (and also from registered unemployment), prepared every quarter after calculating the LFS results (about 2 months after the reference period)

2. "Labour Force Survey in Poland" (for given quarter of the year) - the main publication including more specific results, precision indicies, methodological issues etc.; published quarterly

3. LFS Module publications - each year

4. Seasonally adjusted basic data  from Labour Force Survey
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
http://stat.gov.pl/en/topics/labour-market/working-unemployed-economically-inactive-by-lfs/  everybody methodological information (e.g. sampling schemes, weighting, classifications used, main changes in methodology etc.), analytical part other assistance available e.g. possibility to obtain guidance or some information during telephone conversation or through e-mail
9.3.1. Data tables - consultations

[not requested for the LFS quality report]
9.4. Dissemination format - microdata access
Accessibility to LFS national microdata (Y/N) Who is entitled to the access (researchers, firms, institutions)? Conditions of access to data Accompanying information to data Further assistance available to users
 Y researchers, science institutes, universities, goverment institutions, National Polish Bank (NBP) Institutions must obtain individual for each case consent of Statistics Poland in order to get access to these data. The institutions must justify the need to obtain access to microdata – give the aim of data use. There are no limits in the range of data which are to be shared by Statistics Poland to these institutions, however in first step we propose in case of some variables (e.g. age, microdata based on the classifications) more aggregated data. All data are anonimizated before dissemination to these institutions. Structure of data phone support
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

Popiński W., Development of the Polish Labour Force Survey, Statistics in Transition – Journal of the Polish Statistical Association, Vol. 7, No. 5, 2006, pp. 1009-1030. 

Publication "Labour Force Survey in Poland" (for a given quarter of the year) - contains a section on methodology of LFS in Poland

Detailed information concerning the Polish LFS methodology is also available in Methodological Report on LFS (on the Statistics Poland website, only in Polish).
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 users receive only anonymized microdata. LFS data are anonymized by cutting off the address data, telephones, names of people. The three IT environments are separated:  for developers, testing and production. Personal data are only available in production environment and only for authorized persons. In first place we are offering access to microdata in which some variables are more or less aggregated (e.g. age, nationality, citizenships, size of business, variables based on NACE, ISCO etc.).


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top