Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
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 population consists of individuals residing in private households aged 15-89 and who were contained in the Swedish population register on 31 December (reference year). However, people below the age of 15 do not take part in the survey until, at the earliest, the month after they turned 15. People who cannot work due to long-term health problems, and people not in employment who are aged 70 or older and who are not looking for work, are interviewed once a year and in the eighth survey round.
Housekeeping
Members living together in the same dwelling, sharing food and other essentials for living and household expenditures.
Members of the household are included in wave 8 (the last wave) according to EU definitions of economic households.
15-89
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
Registered population
Family home
Term address
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)
Yes
Participation is voluntary/compulsory?
Voluntary
2.2. Classification system
[not requested for the LFS quality report]
2.3. Coverage - sector
[not requested for the LFS quality report]
2.4. Statistical concepts and definitions
[not requested for the LFS quality report]
2.5. Statistical unit
[not requested for the LFS quality report]
2.6. Statistical population
[not requested for the LFS quality report]
2.7. Reference area
[not requested for the LFS quality report]
2.8. Coverage - Time
[not requested for the LFS quality report]
2.9. Base period
[not requested for the LFS quality report]
3.1. Source data
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.)
Base used for the sample (sampling frame)
Last update of the sampling frame (continuously updated or date of the last update)
Primary sampling unit (PSU)
Final sampling unit (FSU)
Date of sample selection
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 Register of the total population (RTB).
30 September 2021
NA
Individuals
17 November 2021
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 parts, one for the age group 15-74 and one for the age group 75-89.
The sample for the age group 15-74 is stratified according to county and sex. In this way 48 strata are constructed. The inclusion probabilities are in general proportional to the size of the strata, although some small counties are overrepresented in the sample, we also overrepresent the age group 16-64. Systematic sampling is performed within strata.
No stratification is performed for the age group 75-89. Systematic sampling is used.
The sample for the age group 15-74 is stratified according to county and sex.
Sample stratified according to county and sex results in 24x2 = 48 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 2.2%.
Every year about 71 000 unique persons are included in the sample. (see Description of the rotation scheme below). The overall theoretical yearly sample size was 205 000 persons in 2022.
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 %
51 100
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. This auxiliary information has varied over time and today information is used on the Total Population Register (TPR), the monthly employer reports at individual level (AGI) and the Swedish Public Employment Service’s job-seeker register (SOK). This auxiliary information consists of variables that are correlated with central LFS variables and with the breakdown into response and non-response.
N
We do not have access to administrative data on the population in private households. Therefore, the sample is selected from the total population and those living in private households are identified by questions in the interview. The population in private households are thereafter estimated by using these questions.
Y
In the estimation procedure five year ranges are used.
NUTS 3
Country of birth, information on employment and information on unemployment.
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 the households for which data are to be collected. Thus, the sampling design is a two-phase design, where network sampling is used in the second phase. The weights are based on the calibration approach for two-phase sampling in Estevao and Särndal (2002). In the calibration, non-response adjusted design weights according to the network sampling design are used as starting weights. Only information at the individual level is used in the calibration.
Estevao, V.M. 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 Total Population Register (TPR)
Type of household, defined as a categorical variable corresponding to number of persons in the household. The corresponding calibration totals are derived from the TPR. In the TPR, a household refer to the person or persons who, according to information kept by the Swedish Tax Agency, were registered in the same dwelling. In the calibration, the information is used at the individual level.
For information on the factors used in the first phase-calibration, please the section on quarterly core weights. In the second phase-calibration, the following information is used in addition to Type of household:
Sex*Age*Status
where Sex is a categorical variable with categories corresponding to males and females, Age is a categorical variable with categories corresponding to the following age-groups:
0-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65-89 years
and Status is a categorical variable with categories corresponding to the following groups:
In the population for age-group 0-14 years
In the labour force, Not in the labour force for age-group 65-89 years
Employed, Unemployed, Not in the labour force for the remaining age-groups
Yes
The variables used for stratification are the Districts and the urban/rural areas within each district.
3.2. Frequency of data collection
[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description
Use of dependent interviewing (Y/N)?
In case of Computer Assisted Methods adoption for data collection, could you please indicate which software is used?
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 of around 2% 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
Windati
Are any LFS data collected from registers (Y/N)?
If Yes, please indicate which variables are collected from registers.
Y
COUNTRY, REGION, SEX, YEARBIR, PASSBIR, AGE, CITIZENSHIP, COUNTRYB - Register of the total population (RTB)
EDUCFED4, EDUCLEV4, EDUCFED12, EDUCLEV12, HATPAR - Register of the Educational attainment of the population. Collected data from the interview person always takes precedence over register data, as valid data appear in both variables.
INCGROSS, INCGROSS_F - From the Swedish Tax Agency
3.4. Data validation
[not requested for the LFS quality report]
3.5. Data compilation
[not requested for the LFS quality report]
3.6. Adjustment
[not requested for the LFS quality report]
4.1. Quality assurance
[not requested for the LFS quality report]
4.2. Quality management - assessment
[not requested for the LFS quality report]
5.1. Relevance - User Needs
Description of users with respect to the statistical data
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.
Indication of the needs and uses for which users want the statistical outputs; information on unmet user needs and any plans to satisfy them in the future
N
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?
NAU
NTS-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]
6.1. Accuracy - overall
[not requested for the LFS quality report]
6.2. Sampling error
Publication thresholds
Annual average estimates
Yearly estimates - wave approach
Limit below which figures cannot be published
Limit below which figures must be published with warning
Limit below which figures cannot be published
Limit below which figures must be published with warning
3200
6400
NA
NA
Biennial variables estimates
Household estimates
Household average estimates
Limit below which figures cannot be published
Limit below which figures must be published with warning
Limit below which figures cannot be published
Limit below which figures must be published with warning
Limit below which figures cannot be published
Limit below which figures must be published with warning
UNA
UNA
UNA
UNA
UNA
UNA
6.2.1. Sampling error - indicators
Coefficient of variation (CV) Annual estimates Sampling error - indicators - Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)
Employment rate
Unemployment-to-population ratio
Youth unemployment rate as a percentage of labour force
Age group: 15 -74
Age group: 15 -74
Age group: 15 -24
CV
0.24
1.59
2.82
SE
0.36
0.24
1.64
CI(**)
68.64-69.29
5.39-5.74
20.53-22.94
Unemployment-to-population ratio 15-74 (NUTS 2 regions)
CV
SE
CI(**)
SE11
4.05
0.60
5.08-5.96
SE12
4.41
0.80
6.20-7.37
SE21
7.11
0.86
3.90-5.17
SE22
4.07
0.74
6.23-7.31
SE23
4.59
0.59
4.35-5.21
SE31
7.44
1.10
4.70-6.31
SE32
9.31
1.20
3.94-5.70
SE33
10.33
1.01
2.91-4.39
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
(*) 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%
NA
UNA
UNA
NA
Declaration of quality, Total Population Register (in Swedish), p. 8-9 SCB website.
(a) Mention specifically which regions / population groups are not suitably represented in the sample. (b) Misclassification refers to statistical units having an erroneous classification where both the wrong and the correct one are within the target population.
6.3.1.1. Over-coverage - rate
[Over-coverage rate, please see concept 6.3.1 Coverage error in the LFS quality report]
6.3.1.2. Common units - proportion
[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)
Was the questionnaire updated for the 2021 LFS operation? (Y/N)
Synthetic description of the update
Was the questionnaire tested? (Y/N)
If the questionnaire has been tested, which kind of tests has been applied (pilot, cognitive, internal check)?
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)
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
Information is used from the Total Population Register (RTB) (sex, age, county and nation of birth), employer returns at the individual level and the Swedish Public Employment Service’s job-seeker register (SOK) (Information on if a person i registered at SOK).
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
Rates of non-response by survey mode. Annual average
Survey
CAPI
CATI
PAPI
CAWI
POSTAL
NA
55.5
NA
NA
NA
Non-response rates by survey mode. Annual average (% of the theoretical yearly sample by survey mode)
Quarter
Non-response rate
Total (%)
of which:
Refusals (%)
Non-contacts (including people who migrated (or moved) internally or abroad) (%)
1
54.1
18.1
33.7
2
55.3
19.3
33.8
3
56.3
20.3
33.7
4
56.4
19.8
34.3
Annual
55.5
19.4
33.9
Units who refused to participate in the survey (Please indicate the number of the units concerned in the cells where the wave is mentioned)
Subsample
Quarter1_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q2_2020
1201
Subsample_Q3_2020
1151
1151
Subsample_Q4_2020
1212
1293
1322
Subsample_Q1_2021
1162
1285
1393
1401
Subsample_Q2_2021
1130
1265
1354
1323
Subsample_Q3_2021
1189
1201
1370
1386
Subsample_Q4_2021
875
1195
1283
1309
Subsample_Q1_2022
1210
977
1223
1230
Subsample_Q2_2022
1311
900
1112
Subsample_Q3_2022
1345
895
Subsample_Q4_2022
1321
Total in absolute numbers
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_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q2_2020
2003
Subsample_Q3_2020
2034
2064
Subsample_Q4_2020
2048
2002
1966
Subsample_Q1_2021
2091
2095
2041
2062
Subsample_Q2_2021
2190
2136
2132
2153
Subsample_Q3_2021
2056
2104
2094
2104
Subsample_Q4_2021
2239
2050
2063
2122
Subsample_Q1_2022
1856
2252
2066
2141
Subsample_Q2_2022
1916
2399
2173
Subsample_Q3_2022
1823
2362
Subsample_Q4_2022
1804
Total in absolute numbers
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
55.1
SE12-Östra Mellansverige
55.3
SE21-Småland med öarna
55.4
SE22-Sydsverige
58.4
SE23-Västsverige
54.7
SE31-Norra Mellansverige
55.9
SE32-Mellersta Norrland
54.3
SE33-Övre Norrland
54.0
* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview
6.3.3.2. Item non-response - rate
Item non-response (*) - Quarterly data (Compared to the variables defined by the Commission Implementing Regulation (EC) No 2019/2240)
Variable status
Column
Identifier
Quarter 1
Quarter 2
Quarter 3
Quarter 4
Short comments on reasons for non-available statistics and prospects for future solutions
Compulsory / optional
Compulsory
205
AVAIREAS
21.1
27.0
33.2
33.1
Respondents tend to forget the end and start date of work.
Compulsory
236
SEEKDUR
34.1
37.0
26.3
25.0
Respondents tend to forget how long they have been looking for jobs.
Compulsory
262
EXISTPR
29.7
32.9
33.9
32.3
UNA
Compulsory
224
TEMPDUR
27.0
24.2
23.6
27.4
UNA
Compulsory
326
REGISTER
5.7
6.5
6.6
6.4
UNA
Compulsory
263-266
YEARPR
13.0
14.2
14.9
15.8
UNA
Compulsory
298-300
HWACTU2J
14.5
13.2
24.5
13.2
UNA
Compulsory
253-256
YSTARTWK
14.7
13.0
11.8
10.4
UNA
Item non-response (*) - Annual data (Compared to the variables defined by the Commission Implementing Regulation (EC) No 2019/2240)
Variable status
Column
Identifier
This reference year
Short comments on reasons for non-available statistics and prospects for future solutions
Compulsory
248-251
HATYEAR
38.4
Information from registers is used for HATYEAR.
(*) "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.
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N)
Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. Eurostat/documents) (Y/N)
Y
Y
6.6. Data revision - practice
[not requested for the LFS quality report]
6.6.1. Data revision - average size
[not requested for the LFS quality report]
7.1. Timeliness
Quarterly LFS data Reference period, transmission date and coverage
Quarter
Main dates in the national production process
Start date of data collection
End date of the quality check for statistics requested by Eurostat
Date of national publication
1
03 January 2022
03 June 2022
25 May 2022
2
01 April 2022
29 August 2022
26 August 2022
3
01 July 2022
11 November 2022
18 November 2022
4
03 October 2022
08 February 2023
27 January 2023
7.1.1. Time lag - first result
[not requested for the LFS quality report]
7.1.2. Time lag - final result
[not requested for the LFS quality report]
7.2. Punctuality
Quarterly LFS Data
Quarter
Full dataset
Single characteristic(s)
Deadline
Delivery date
Reason for late delivery
Characteristic(s)
Delay (days)
Reason for late delivery
1
03 June 2022
COUNTRPR,wrong values in data
NA
NA
NA
2
17 August 2022
NA
NA
NA
NA
3
30 November 2022
NA
NA
NA
NA
4
27 January 2023
NA
NA
NA
NA
Yearly dataset
31 March 2023
31 March 2023
NA
NA
NA
NA
7.2.1. Punctuality - delivery and publication
[not requested for the LFS quality report]
8.1. Comparability - geographical
Divergence of national concepts from European concepts
(European concept or National proxy concept used) List all concepts where any divergences can be found
Is there a divergence between the national and European concepts for the following characteristics?
(Y/N)
Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)
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
N
legislation
N
NA
NA
NA
N
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
N
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
N
8.2.1. Length of comparable time series
[not requested for the LFS quality report]
8.3. Coherence - cross domain
Coherence of LFS data with Business statistics data
Description of difference in concept
Description of difference in measurement
Give an assessment of the effects of the differences
Give references to description of differences
Total employment
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.
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.
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]
9.1. 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 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 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.
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)):
Number of staff involved in the LFS in central and regional offices, excluding interviewers Consider only staff directly employed by the NS
Full-time equivalents
Total
12
- of which professional and managerial
2
Duration of the interview by Final Sampling Unit
Minutes
Total
First wave
Later waves
Average duration of the interview
UNA
UNA
UNA
Core questionnaire (pr person)
UNA
12
8
Ad hoc Modules (pr person)
5
0
5
Note: This table should only show the burden on the respondents, not time spent in the field to contact the household or fill in adminstrative forms.
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.
[not requested for the LFS quality report]
Coverage
Coverage
Household concept
Definition of household for the LFS
Inclusion/exclusion criteria for members of the household
Questions relating to employment status are put to all persons aged ...
The survey population consists of individuals residing in private households aged 15-89 and who were contained in the Swedish population register on 31 December (reference year). However, people below the age of 15 do not take part in the survey until, at the earliest, the month after they turned 15. People who cannot work due to long-term health problems, and people not in employment who are aged 70 or older and who are not looking for work, are interviewed once a year and in the eighth survey round.
Housekeeping
Members living together in the same dwelling, sharing food and other essentials for living and household expenditures.
Members of the household are included in wave 8 (the last wave) according to EU definitions of economic households.
15-89
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
Registered population
Family home
Term address
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)
Yes
Participation is voluntary/compulsory?
Voluntary
Not Applicable
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.)
Base used for the sample (sampling frame)
Last update of the sampling frame (continuously updated or date of the last update)
Primary sampling unit (PSU)
Final sampling unit (FSU)
Date of sample selection
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 Register of the total population (RTB).
30 September 2021
NA
Individuals
17 November 2021
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 parts, one for the age group 15-74 and one for the age group 75-89.
The sample for the age group 15-74 is stratified according to county and sex. In this way 48 strata are constructed. The inclusion probabilities are in general proportional to the size of the strata, although some small counties are overrepresented in the sample, we also overrepresent the age group 16-64. Systematic sampling is performed within strata.
No stratification is performed for the age group 75-89. Systematic sampling is used.
The sample for the age group 15-74 is stratified according to county and sex.
Sample stratified according to county and sex results in 24x2 = 48 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 2.2%.
Every year about 71 000 unique persons are included in the sample. (see Description of the rotation scheme below). The overall theoretical yearly sample size was 205 000 persons in 2022.
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 %
51 100
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. This auxiliary information has varied over time and today information is used on the Total Population Register (TPR), the monthly employer reports at individual level (AGI) and the Swedish Public Employment Service’s job-seeker register (SOK). This auxiliary information consists of variables that are correlated with central LFS variables and with the breakdown into response and non-response.
N
We do not have access to administrative data on the population in private households. Therefore, the sample is selected from the total population and those living in private households are identified by questions in the interview. The population in private households are thereafter estimated by using these questions.
Y
In the estimation procedure five year ranges are used.
NUTS 3
Country of birth, information on employment and information on unemployment.
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 the households for which data are to be collected. Thus, the sampling design is a two-phase design, where network sampling is used in the second phase. The weights are based on the calibration approach for two-phase sampling in Estevao and Särndal (2002). In the calibration, non-response adjusted design weights according to the network sampling design are used as starting weights. Only information at the individual level is used in the calibration.
Estevao, V.M. 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 Total Population Register (TPR)
Type of household, defined as a categorical variable corresponding to number of persons in the household. The corresponding calibration totals are derived from the TPR. In the TPR, a household refer to the person or persons who, according to information kept by the Swedish Tax Agency, were registered in the same dwelling. In the calibration, the information is used at the individual level.
For information on the factors used in the first phase-calibration, please the section on quarterly core weights. In the second phase-calibration, the following information is used in addition to Type of household:
Sex*Age*Status
where Sex is a categorical variable with categories corresponding to males and females, Age is a categorical variable with categories corresponding to the following age-groups:
0-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65-89 years
and Status is a categorical variable with categories corresponding to the following groups:
In the population for age-group 0-14 years
In the labour force, Not in the labour force for age-group 65-89 years
Employed, Unemployed, Not in the labour force for the remaining age-groups
Yes
The variables used for stratification are the Districts and the urban/rural areas within each district.
Not Applicable
Quarterly LFS data Reference period, transmission date and coverage
Quarter
Main dates in the national production process
Start date of data collection
End date of the quality check for statistics requested by Eurostat
Date of national publication
1
03 January 2022
03 June 2022
25 May 2022
2
01 April 2022
29 August 2022
26 August 2022
3
01 July 2022
11 November 2022
18 November 2022
4
03 October 2022
08 February 2023
27 January 2023
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
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
N
legislation
N
NA
NA
NA
N
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)
