Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Sweden


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

Statistics Sweden
1.2. Contact organisation unit

Labour force survey Unit
1.5. Contact mail address


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 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 population consists of all individuals in the population aged 15-74 who are domiciled in Sweden. The sampling frame is Statistics Sweden’s Register of the Total Population. Through sampling of individuals persons living in both private and collective households are covered. Persons living in a collective household are also recorded in the central population register and are therefore sampled as well as persons living in private households. The resident population for the purposes of the survey comprises persons between the ages of 15 and 74 who are domiciled in Sweden according to the population register. Housekeeping concept Members of the household are included in wave 8 (the last wave) according to EU definitions of economic households  15-74

 

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)                                  
 Yes  
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)
 Stratified single stage systematic sampling The sampling frame is Statistics Sweden’s Register of the Total Population.
Information for the stratification is retrieved from the following register: Register of the total population (RTB): Information of sex, age, region (county) is used. 		  30/9/2018  NA  Individuals

 

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.)
 NA  The sample is drawn at the end of the fourth quarter every year to cover the coming year’s need of new sample persons. The total sample consists of two seperate samples. One sample is stratified according to county and sex. In this way 48 strata are constructed. The inclusion probabilites are in general proportional to the size of the strata, although some small countis have to be overrepesented in the sample, we also overrepresent the age group 16-64. The second sample is stratified according to region, sex, country of birth, age group (13-24, 25-54, 55-66) and information from Statistics Sweden's Income and Taxation register (IoT) combined with information from Statistics Sweden's Longitudinal integration database for health insurance and labour market studies (LISA). In this way 105 strata are constructed. We overrepresent individuals that have specific characteristics according to IoT and LISA. One sample is stratified according to county, sex and age.

The other sample is stratified according to region, sex, country of birth, age group (13-24, 25-54, 55-66).		  

Sample stratified according to county, sex and age results in 24x2 = 48 strata.

 

Sample stratified according to region, sex, country of birth, age group (13-24, 25-54, 55-66) results in 105 strata.

 The LFS sample consists of three separate samples, one for each month in the quarter. Every monthly sample consists of 8 rotationpanels (waves), of which 7/8 reccur after 3 months and 1/8 is replaced by new indidividuals. Persons in the sample are interviewed once a quarter with a total of eight interviews during a two-year period, after which they leave the sample.

 

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)
The inclusion probabilities for individuals in a monthly sample vary primarily with the share of the current sample that consists of the total sample in a month. Every month samples from 2 or 3 different years are represented. The yearly sampling rate is approximately 1.7%. Every year about 60 000 unique persons are included in the sample. (see Description of the rotation scheme below). The overall theoretical yearly sample size was 182 700 persons in 2019. This is lower than previous years due to the sample being halved after problems with an external sub-contractor was discovered.

  

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 %  45680

  

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 estimates build on regression estimators (GREG) with a set of auxiliary information. The auxiliary variables are: sex*age, region, nation of birth, information on employed persons by industry and persons who have enrolled at a job-center as unemployed and are looking for work. The registers which are used to obtain the auxiliary variables are the Register of Total Population (RTB), The Employment Register (RAMS) and the Swedish Public Employment Service´s register of job-seekers (SOK).  N The registered population according to the total population register   Y In the estimation procedure five year ranges are used.  NUTS 3  See above

 

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
 NA  NA NA  NA  NA 

 

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)
Each month the last wave of the individual LFS-sample is used as the starting point for identifying sampled households, i.e. the household sample is a network sample. The weights are based on the calibration approach for two-phase sampling in Estevao and Särndal (2002). Design weights according to the network sampling design, adjusted for nonresponse at the household level, are used as starting weights in the calibration. Only information at the individual level is used in the calibration.

 

Estevao V., and Särndal, C-E. (2002) The Ten Cases of Auxiliary Information for Calibration in Two-Phase Sampling. Journal of Official Statistics, 18, 233-255		 The following sources are used to obtain the totals and estimated totals used in the calibration: 
  • The total population register
    • Region of residency
    • Country of birth
    • The individual LFS
    • Sex * Age * Status I
    • Sex * Status II
For more information on the variables used, see “Which factors at individual level are used in the weighting (gender, age, regional breakdown etc.)?”.		  

None

 The following variables, all  at the individual level, are used in the calibration:
  • Region of residency, 26 categories
  • Country of birth, 4 categories
  • Sex * Age * Status I, 40 categories
  • Sex * Status II, 10 categories

 where 

  • Age: 15-19, 20-24, 25-34, 35-44, 45-54, 55-64, 65-74 years
  • Status I: employed, unemployed, inactive (Since only a very small number of individuals in the age-group 65-74 are unemployed, Status I corresponds to in the labor force and inactive for individuals in the age-group 65-74.)
  • Status II: in the labor force, full-time student, retired, ill, anything else
  Yes
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 information is collected using computer assisted telephone technology and techniques. Currently 100% of the interviews are conducted by interview staff at Statistics Sweden.

An interview with the sample person him/herself is preferred and is done to the extent possible, given the time allowed to complete the interviews. Proxy interviews are conducted when the sample person is not available within the time frame because of vacation, illness, etc. A proxy respondent  is usually a person close to the sample person who can provide informed answers. Proxy interviews comprise 2,1% of all interviews.

All sample persons are informed in a letter that they have been chosen to participate in the LFS. The letter arrives about two weeks before the first interviewer contact. The letter explains that the person will be contacted for a telephone interview. A brochure describing the survey accompanies the letter. To obtain the respondent’s telephone number, an automated telephone number service is used. The sample person’s name is matched to a register of telephone numbers. Telephone numbers for about 85% of  the sample are obtained in this way. The remaining 15% receive a request to fill in his/her telephone number on an enclosed card and return the card to Statistics Sweden. The information requested on the card concerns the telephone number and suitable times to call. The interviews start the day after the reference week has passed. Most interviews are completed within the course of one week.

  Y  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 NA  100  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)
The LFS meets important parts of economic and social research needs concerning data in the labour market area.

The most important users of statistics include the Riksdag (the Parliment), the Government (the Ministry of Employment, the Ministry of Enterprise and Innovation, the Ministry of Finance), the National Institute of Economic Research, the Riksbank, Arbetsförmedlingen (employment office), and the social partners. The LFS is also used at Statistics Sweden in the national accounts and labour force analyses and forecasts.
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-3  LAU if considered big enough.  The methods used are the same as for national level and NUTS II level.
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
3200 6400 NA  NA 
6.2.1. Sampling error - indicators
Coefficient of variation (CV) Annual estimates
Sampling error - indicators - Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)       
 

Number of employed persons

Employment rate as a percentage of the population

Number of part-time employed persons

Number of unemployed persons

Unemployment rate as a percentage of labour force

Youth unemployment rate as a percentage of labour force

Average actual hours of work per week(*)
 

Age group: 20 - 64

Age group: 20 - 64

Age group: 20 - 64

Age group: 15 -74

Age group: 15 -74

Age group: 15 -24

Age group: 20 - 64
 CV 0.24915 0.24824 1.31231 1.78185 1.72531 3.25703 0.22503
 SE 25.6224 0.43747 28.1698 17.7103 0.31154 1.73626 0.17669
 CI(**) 4769-4815.8 81.8-82.6 974.6-1026 359.8-385.8 6.6-7 18.8-21.2 36.4-36.8

 

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:
 SAS  - Clan  The Sampling - and the Estimation Procedure in the Swedish Labour Force 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 
 SE11 Stockholm 0.80905 0.53863 2.98673 4.0786 3.9756 7.0327 0.43426
 SE12 Östra Mellansverige  1.10462 0.72098 3.42061 4.61902 4.3976 7.4965 0.61982
 SE21 Småland med öarna  1.53253 0.899 4.18255 5.61532 5.79246 4.7252 0.7451
 SE22 Sydsverige  1.26076 0.92542 3.39819 5.27141 5.19148 8.9079 0.67606
 SE23 Västsverige  0.91659 0.62823 3.10049 5.04667 4.88609 6.6804 0.48549
 SE31 Norra Mellansverige 1.67411 1.10464 4.68597 6.57157 6.74732 10.6314 0.7905
 SE32 Mellersta Norrland  2.17742 1.31428 6.00305 9.43801 9.22426 7.5509 0.97391
 SE33 Övre Norrland  2.03583 1.28149 7.17004 9.61726 9.09516 17.3917 1.13556

 

(*) 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
 Less than 1% Less than 1%   UNA  UNA  UNA  NA

Declaration of quality, Total Population Register (in Swedish)  https://www.scb.se/contentassets/9299bfcd87ba4c828a8d46b4db49d67a/be0101_kd_2019.pdf

 

 

(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  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 Y 
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)
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  Auxiliary information is retrieved from the following registers:
(1) Register of the total population (RTB): Information on sex, age, region (county) and nation of birth.  
(2) Annual employment register (RAMS): Information on employment and industry group according to RAMS is used. RAMS is a statistical register with information on employment for the total population. (3) the Swedish Public Employment Service´s register of job-seekers (SOK).: Information on if a person i registered at SOK. No imputations are done. 		 Non response is adjusted according to the mean value method and auxiliary information in the GREG estimation. Item non-response for certain questions result in unit non-response, i.e. questions concerning labour status and degree of attachment to the labour market.  
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
 NA  48,3% 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  50.9  14.7  35.2  UNA
2  49.7  15.2  33.5  UNA 
3  49.3  21.6  24.7  UNA 
4  49.2  17.0  30.2  UNA 
Annual  NR  NR  NR  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_2019 Quarter2_2019 Quarter3_2019 Quarter4_2019
Subsample_Q2_2017 1280      
Subsample_Q3_2017 1236 1257    
Subsample_Q4_2017 1231 1324 1332  
Subsample_Q1_2018 1126 1267 1335 1159
Subsample_Q2_2018 1192 1205 1357 1126
Subsample_Q3_2018 1073 1255 1254 1017
Subsample_Q4_2018 943 1070 1197 937
Subsample_Q1_2019 903 973 1136 792
Subsample_Q2_2019   1035 1066 876
Subsample_Q3_2019     1013 801
Subsample_Q4_2019       911
Total in absolute numbers Total Total Total Total
Total in % of theoretical quarterly sample        

 

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_2019 Quarter2_2019 Quarter3_2019 Quarter4_2019
Subsample_Q2_2017 1333      
Subsample_Q3_2017 1309 1279    
Subsample_Q4_2017 1397

1310

 1273  
Subsample_Q1_2018 1387 1329 1240 1487
Subsample_Q2_2018 1337 1349 1256 1553
Subsample_Q3_2018 1407 1297 1369 1708
Subsample_Q4_2018 1449 1424 1382 1716
Subsample_Q1_2019 1757 1471 1448 1841
Subsample_Q2_2019   1601 1500 1857
Subsample_Q3_2019     1621 1738
Subsample_Q4_2019       1635
Total in absolute numbers Total Total Total Total
Total in % of theoretical quarterly sample        

 

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_2019 Quarter2_2019 Quarter3_2019 Quarter4_2019
Subsample_Q2_2017 UNA      
Subsample_Q3_2017 UNA UNA    
Subsample_Q4_2017 UNA UNA UNA  
Subsample_Q1_2018 UNA UNA UNA UNA
Subsample_Q2_2018 UNA UNA UNA UNA
Subsample_Q3_2018 UNA UNA UNA UNA
Subsample_Q4_2018 UNA UNA UNA UNA
Subsample_Q1_2019 UNA UNA UNA UNA
Subsample_Q2_2019   UNA UNA UNA
Subsample_Q3_2019     UNA UNA
Subsample_Q4_2019       UNA
Total in absolute numbers Total Total Total Total
Total in % of theoretical quarterly sample        

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
 SE11-Stockholm 48.7
 SE12-Östra Mellansverige 46.9
 SE21-Småland med öarna 48.2
 SE22-Sydsverige 51.3
 SE23-Västsverige 47.8
 SE31-Norra Mellansverige 49.4
 SE32-Mellersta Norrland 44.4
 SE33-Övre Norrland 46.4

* 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_054 TEMPDUR 17.7 16.2 16.8 16.9   Respondents do not always remember start and end of work
compulsory Col_102 - Employed SEEKDUR . 10.7 . .   People tend to forget how long they have been looking for work
compulsory Col_102 - Not employed SEEKDUR 27.8 39.7 19 18.7   People tend to forget how long they have been looking for work
compulsory Col_113 - Employed METHODK . . C .  Very infrequent that this variable has value 1
compulsory Col_114 - Employed METHODL C . C C  Very infrequent that this variable has value 1
compulsory Col_114 - Not employed METHODL C C C C  Very infrequent that this variable has value 1
compulsory Col_204 HATVOC . . 13.1 .  

 

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_118 - Employed AVAIREAS 76.4 The high non-response is due to employed who doesn't look for another job. 
compulsory Col_121 REGISTER 17.3 The question is not given to employed who are not searching for a job.
compulsory Col_146 WSTAT1Y 46.1  
compulsory Col_200/203 HATYEAR 20.3 Information for HATYEAR is taken from registers, and the share of missing values is about 20%.
optional Col_132 COURPURP 100 Not collected
optional Col_133/135 COURFILD 100 Not collected
optional Col_136 COURWORH 100 Not collected 

(*) "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 
 N  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  N   Consistent seasonal adjustment. SAS used for seasonal adjustment X12 ARIMA. For more info: https://www.scb.se/publikation/21099
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N) Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF) (Y/N)
 Y Y 
6.6. Data revision - practice

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

[not requested for the LFS quality report]


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


8. Coherence and comparability Top
8.1. Comparability - geographical

Divergence of national concepts from European concepts

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

    
Is there a divergence between the national and European concepts for the following characteristics? (Y/N) Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)  Y To belong to the Swedish resident population one must obtained residence permit. This means that some immigrants group, i.e. persons with citizenship from countries outside of EU, don’t belong to the population even if they are staying or intended to stay in the country for a period longer than one year. These people can’t work or seek job by defaults and they don’t exist in the populations register and thereby neither in the sample frame.
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  Y

Weights were revised for the period July 2018 to September 2019, which consists of using only half of the sample, following the detection of quality deficiencies. As the resulting statistics for 2019 are based on half of the usual sample size, this increases the uncertainty, particularly at a more disaggregated level. Reliability limits have been revised accordingly.

  Y All variables   Y
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  Target population of the survey on short -term employment includes all establishments with at least one employee  Short term employment measures the number of employees, and the LFS the number of employed. In short term employment statistics it is possible for an employee to be counted several times.  NR Bakgrundsfakta till Arbetsmarknads- och Utbildnings-statistiken. 2001:7. Individ och företagsbaserad sysselsättningsstatistik- en jämförelse mellan AKU och KS
Bakgrundsfakta till Arbetsmarknads- och Utbildnings-statistiken. 2003:3. Individ och företagsbaserad sysselsättningsstatistik- en fortsatt jämförelse mellan AKU och KS
Total employment by NACE  M?  M?  M?  M?
Number of hours worked  M?  M?  M?  M?

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
Only persons registered at the Swedish Public Employment Service´s register of job-seekers are counted. These are counted in the last day of the month. Only persons aged 16 and above are included. The LFS unemployed are the average of the refererence weeks of the respective month and includes persons aged 15-74.  Only persons registered at the employment offices are counted. LFS use a survey method.  NA

 

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)
The level of unemployment for those registred at the unemployment office is lower than the level in the LFS. Some participants in labour market programs are included in the full-time student group. Also further, the data from the local unemployment offices measures the number of people still registred at the end of the month while the LFS is mean value for the period. 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 All persons doing military service are counted as employed in The National Account (NA) while persons employed abroad are not included.   NA The difference between published estimates in the LFS and NA is around 30 000 persons.  https://www.scb.se/publikation/35868
Total employment by NACE Non-profit organizations are  given a code outside NACE in NA.   NA    https://www.scb.se/publikation/35868
Number of hours worked Difference in reference periods. NA use calendar month. Employeed abroad are not included in NA. Compulsory military are included in NA. In NA a supplement is made to hours worked to account for untaxed hours for annual estimates.  NA The difference between published estimates in the LFS and NA is around 50 million hours on a quarterly basis.  https://www.scb.se/publikation/35868

 

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 (for employed and total hours)  N  N N  Y (for public sector)   Y (for individual NACE)
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
A first publication of the main results of the reference month is made in the press release and on https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/arbetskraftsundersokningar/arbetskraftsundersokningarna-aku/. Quarterly and annual results are published regularly in Statistical Reports (SM).

Base tables are published every month, quarter and year as excel files on https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/arbetskraftsundersokningar/arbetskraftsundersokningarna-aku/. Standard errors for monthly, quarterly and annual figures are published together with the base tables. The publications consist of standard errors for both level and difference estimates.

On commission additional tables are produced regularly to cover special information needs.

Certain LFS-figures are also published  in Statistics Sweden’s Annual Yearbook and in indicators from Statistics Sweden.

LFS figures are also available in the statistical databases accessible from Statistics Sweden’s website where also the press release is to be found.

Summary presentations concerning results, time series, methods and definitions in the LFS  are published in Statistical Reports.
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 (national language(s)):

https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/arbetskraftsundersokningar/arbetskraftsundersokningarna-aku/

Link to the national web page (English):

https://www.scb.se/en/finding-statistics/statistics-by-subject-area/labour-market/labour-force-surveys/labour-force-surveys-lfs/

 Press releases, official statistics reports and the databases are free of charge and available on Statistics Sweden’s website. Documentation is available on the website. Telephone and e-mail consulting
9.3.1. Data tables - consultations

[not requested for the LFS quality report]
9.4. Dissemination format - microdata access
Accessibility to LFS national microdata (Y/N) Who is entitled to the access (researchers, firms, institutions)? Conditions of access to data Accompanying information to data Further assistance available to users
 Y  Researchers and instutions  Protection of microdata  NA NA 
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
https://www.scb.se/contentassets/c12fd0d28d604529b2b4ffc2eb742fbe/am0401_staf_2020_mt_200218.pdf
9.7. Quality management - documentation

[not requested for the LFS quality report]
9.7.1. Metadata completeness - rate

[not requested for the LFS quality report]
9.7.2. Metadata - consultations

[not requested for the LFS quality report]


10. Cost and Burden Top
Restricted from publication


11. Confidentiality Top
11.1. Confidentiality - policy

[not requested for the LFS quality report]
11.2. Confidentiality - data treatment
Please provide information on the policy for anonymizing microdata in your country
In Sweden data for individual respondents (microdata) are protected by the Secrecy Act. However, it is possible for researchers to apply for access to microdata for use in specified research projects. The system for researchers’ access to microdata stored at Statistics Sweden is called Microdata Online Access (MONA). Data are described through Statistics Sweden’s standard system for documentation of microdata. Information about MONA and the documentation is published on the website in Swedish.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top