Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Norway


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 Norway
1.2. Contact organisation unit

Division for labour market and wage statistics
1.5. Contact mail address

Statistics Norway,

Postboks 8131 Dep.
NO-0033 Oslo


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 ...
Population: The total population aged 15-74, residing in Norway (according to the Central Population Register). Geographical: The whole country (representative samples in each county). Housekeeping Members living together in the same dwelling linked by family ties. The information about households concerns housekeeping units, i.e. persons living in the same dwelling with joint board 15-74

 

Population concept  Specific population subgroups
Primary/secondary students Tertiary students People working out of family home for an extended period for the purpose of work People working away from family home but returning for weekends Children alternating two places of residence
Usual residence (12 months) Family home Family home or term address (case-by-case) Family home (case-by-case) Family home Family home

 

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)
Inhabitants in all municipalities are randomly selected, on the basis of a register of family units. Each family member aged 15-74 participates in the survey, answering questions about their situation during a specified reference week.  The Central Population Register, which is continuously updated by the local population registration offices.  Every quarter  NA Family of the reference person (all persons aged 15-74 in the family).

 

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 Inhabitants in all municipalities are randomly selected, on the basis of a register of family units. Each family member aged 15-74 participates in the survey, answering questions about their situation during a specified reference week.  County (NUTS3-regions).  18  8

 

Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate Size of the theoretical yearly sample
(i.e. including non-response) (i.e. including non-response)
 2.41% 96 000 persons (48 000 families) per year.

  

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)
 0.60% 24000

  

Use of subsamples to survey structural variables (wave approach)

Only for countries using a subsample for yearly variables
 Wave(s) for the subsample  Are the 30 totals for ILO labour status (employment, unemployment and inactivity) by sex (males and females) and age groups (15-24, 25-34, 35-44, 45-54, 55+) between the annual average of quarterly estimates and the yearly estimates from the subsample all consistent? (Ref.: Commission Reg. 430/2005, Annex I) (Y/N) If not please list deviations List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 377/2008, Annex II)
1st and 8th waves  Y  NA wayjfoun, ftptreas, tempreas, tempagcy, shiftwk, evenwk, nightwk, satwk, sunwk, waymore, homewk, leavreas, seekreas, avaireas, preseek, needcare, wstat1y, stapro1y, nace1y2d, coeffy

 

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 estimation method in LFS is done in several stages and are called multiple model calibration (MMK). Initially, the main labour market status of LFS, which is employed, unemployed, outside the workforce, are modelled consistent with a multinomial logit model, explained with a number of register variables known to all in the population. The model provides predicted probabilities every month for each main labour market status in LFS for everybody in the population. The monthly weights in LFS are calibrated using these predicted probabilities and some register variables directly. This means that the weights also become consistent with the population for the number in the population register by gender, different age groups and region, as well as consistent weights for the number of full / part-time wage earners by gender and registered employed (yes/no) cross classified by immigrants in 2 groups. The initial weights before calibration, which is the ratio of the number of people in the population to the gross sample per. county (NUTS3) at the reference time for the statistics (proxy design weights).

For more detailed technical information about the new estimation method, please see Documents 2018/16: 

New estimation methodology for the Norwegian Labour Force Survey - SSB

 

In order for all reference weeks to weight evenly in quarterly averages, we make week-proportional adjustment of monthly weights in our quarterly averages. That is, the monthly weights are multiplied by 4/13 or 5/13 depending on whether the months in the LFS contain respectively 4 or 5 whole weeks.

  N Total population  Y  5-year age groups NUTS2 and NUTS3 Marital status, level of education, family size, register labour market employment status (with the consistency treated categories: fulltime, part-time employee, self-employed, register unemployed more /less than 3 months, disability pensioner, others), immigrant status and country of origin and on government measures and persons with disabilities at Norwegian Labour and Welfare Administration (NAV) income. 

 

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
A sub-sample is used to survey some of the structural variables (mostly for atypical work, reasons for leaving last job/ not seeking employment/ not being available to start work within two weeks and others) under Commission Regulation (EC) No 377/2008, for which only yearly results are required. The sub-sample is determined according to a wave approach, i.e. it includes the units of each full quarterly sample which, according to the rotation scheme, are interviewed for the first and for the eighth and last time (1st and 8th wave).

The core weights are adjusted so that estimated numbers from the yearly variables are consistent with LFS-numbers for employment status (employed, non-employed) by age (ten-year age groups) and sex. The core weights are multiplied by an adjustment factor that are calculated as the sample size of the yearly variables divided by the sample size of LFS in each of the groups formed by combining employment status, age and sex.

  Y 10 year age groups 15-74 years implementet in the core weights  

 

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 LFS weight variable transmitted to Eurostat which can be used as household weight has different non-zero values according to the household member.  The number of households is computed by summing the weight values on the reference persons. Population and/or demographic register(s), employment and/or unemployment register(s), Income/tax register, Register of registered families from the CPR. Number of registered families from the CPR, also including (resident) conscripts, and generally not restricted to private household/families  Gender, Age, Registeremployment - by industry (3 groups) and County  N
3.2. Frequency of data collection

[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description Use of dependent interviewing (Y/N)? Participation is voluntary/compulsory?
All Interview are carried out by telephone, using computers (CATI). Information from previous interviews are used to some extent for persons with a stable connection to the labour market, while asking about any changes in the situation, instead of the same, comprehensive data collection every time.

For the coding of industry information from some registers is used. Moreover some demographic data are collected from the Central Population Register, and data on education are based on the Central Register of Education. 

  Y  Compulsory

 

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 labour force survey is one of the main inputs for the National Accounts, which again is one of the main inputs for the monetary policy of the national bank. The survey results are also extensively used by the media and research institutions.
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; Municipalitiy County for employed or persons in the labour force  LAU; 7 types of municipalities (density)  No spesific method used, Statistics Norway never publish the number or rate of unemployment by NUTS-3
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
 5 000 10 000 5 000  10 000
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  0.2  0.2  1.07  2.17  2.12  3.33  0.31
 SE  4969 0.15  5851  2830  0.1  0.38  0.11 
 CI(**)  2 497 589  -  2 517 066 78.53  -  79.13  535 208  -  558 145  124 776  -  135 868  4.39  -  4.77  10.68  -  12.17  34.08  -  34.5 

 

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:
 NR  NR 

 

 
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 
NO01 Oslo and Akershus  0.4  0.39  2.44  4.3  4.17  7.11  0.62
NO02 Hedmark and Oppland 0.7  0.7  3.51  8.44  8.26  12.17  1.1 
NO03 Sør-Østlandet 0.48  0.48  2.42  4.81  4.68  6.88  0.74 
NO04 Agder and Rogaland 0.51  0.51  2.44  5.26  5.11  7.51  0.79 
NO05 Vestlandet 0.49  0.48  2.7  5.18  5.08  8.6  0.79 
NO06 Trøndelag 0.64  0.64  3.36  8.25  8.11  11.7  1.03 
NO07 Nord-Norge 0.67  0.64  3.72  7.76  7.6  12.35  1.04 

 (*) 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  0%  UNA Do not include those 75 years and older. We impute them as outside the labour foce. Number of persons employed about 0.25 per cent too low.

The sampling frame consists of registered family units where the main person in the family is aged 15-74 years. Women married to men 75 years or older are underrepresented.

  N Using familiy as a proxy for household at the moment  Documents 46/2013, Statistics Norway

 

(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)?
 NR  NR   NR   NR 

 

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)
 N N N
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 Register-employment, age, sex and county (NUTS3)  Correction for total non-response is done in the estimating procedure (post-stratification and calibration by use of register data).  
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  14.7  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 16.0  UNA  UNA   UNA 
2 15.8  1.2  13.4  UNA  
3 13.0  1.3  10.5  UNA  
4 14.0  1.3  10.5  UNA  
Annual 14.7  UNA    UNA    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_Q2_2018        
Subsample_Q3_2018   37     
Subsample_Q4_2018   44  57  
Subsample_Q1_2019   35  45  48 
Subsample_Q2_2019   35  35  44 
Subsample_Q3_2019   27  35  45 
Subsample_Q4_2019   38  35  36 
Subsample_Q1_2020   32  27  26 
Subsample_Q2_2020   41  34  37 
Subsample_Q3_2020     42  30 
Subsample_Q4_2020       41 
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_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q2_2018        
Subsample_Q3_2018    332    
Subsample_Q4_2018   424   283  
Subsample_Q1_2019   426  285  286
Subsample_Q2_2019   458  335  366 
Subsample_Q3_2019   422  362  356 
Subsample_Q4_2019   493  406  396 
Subsample_Q1_2020   478  365  411 
Subsample_Q2_2020   539  426  431 
Subsample_Q3_2020     406  405 
Subsample_Q4_2020       462 
Total in absolute numbers        
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_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q2_2018        
Subsample_Q3_2018   12    
Subsample_Q4_2018   16   11  
Subsample_Q1_2019   33  22  12 
Subsample_Q2_2019   38  28  20 
Subsample_Q3_2019   42  44  28 
Subsample_Q4_2019   53  46  43 
Subsample_Q1_2020   61  50  49 
Subsample_Q2_2020   72  60  49 
Subsample_Q3_2020     71  55 
Subsample_Q4_2020       67 
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 (%)
NO01-Oslo and Akershus  UNA  
NO02-Hedmark and Oppland  UNA  
NO03-Sør-Østlandet  UNA  
NO04-Agder and Rogaland  UNA  
NO05-Vestlandet  UNA  
NO06-Trøndelag  UNA  
NO07-Nord-Norge  UNA  

* 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_047/48 MSTARTWK 26.9 32 35.2 38.4  
compulsory Col_054 TEMPDUR 37 38 37 43.4 Many employed do not have any date for the end of their temporary work. 
compulsory Col_101 - Not employed SEEKTYPE . . 13.1 11.5 Due to proxy
compulsory Col_102 - Employed SEEKDUR 10.2 . . . Due to proxy 
compulsory Col_102 - Not employed SEEKDUR . 14 14.4 11.1 Due to proxy 
compulsory Col_110 - Not employed METHODH . C C . Search method rarely used. 
compulsory Col_111 - Not employed METHODI . C C C Search method rarely used. 
compulsory Col_114 - Employed METHODL . C . C Search method rarely used. 
compulsory Col_114 - Not employed METHODL C C C C Search method rarely used. 
compulsory Col_210 EDUCVOC 100 100 100 100  

 

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_049 WAYJFOUN 30.7  
compulsory Col_051 FTPTREAS 23.9 Due to proxy
compulsory Col_053 TEMPREAS 10.2  
compulsory Col_093 STAPROPR 19.3  
compulsory Col_094/95 NACEPR2D 100  
compulsory Col_096/98 ISCOPR3D 100  
compulsory Col_100 SEEKREAS 26.3 Due to proxy
compulsory Col_118 - Employed AVAIREAS 23.1 Due to proxy 
compulsory Col_118 - Not employed AVAIREAS 13.1 Due to proxy 
compulsory Col_119 PRESEEK 26 Due to proxy 
compulsory Col_121 REGISTER 100  
compulsory Col_150/151 COUNTR1Y 100 Variable not delivered.
compulsory Col_152/153 REGION1Y C  
compulsory Col_154/155 INCDECIL 100 Variable not delivered.
optional Col_132 COURPURP 100 we do not deliver this variable
optional Col_133/135 COURFILD 16.9 difficulties in coding
optional Col_136 COURWORH 100 we do not deliver this variable 

(*) "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  N Seasonally adjusted data are calculated by using the X12-ARIMA method, done indirectly for time series of employed persons and unemployed persons are seasonally adjusted separately by age over/under 24 years. All the seasonally adjusted age-divided subgroup series, which are seasonally adjusted directly, are summed up for totals 15-74 afterwards. The official seasonally adjusted figures divided by age groups are broken down into gender-divided figures by utilizing monthly gender distributions calculated from trend-cycle figures from additional unofficial seasonal adjustments of the LFS. Partial concurrent adjustment is done. For model selection in the annual review, the pickmdl-procedure in Version 0.3 of  X12-ARIMA is used. Regression models in X-12-ARIMA pre-adjust the series, where we define the explanatory variables for holidays not falling on weekdays in the same month in LFS every year according to the Norwegian calendar and for outliers. The seasonally adjusted time series for employed persons over 24 year and unemployed persons over 24 year are pre-adjusted if Easter is in March. Only 3-months moving averages of the seasonally adjusted time series are published. For more detailed information, see About seasonal adjustment at https://www.ssb.no/en/akumnd
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  Due to Norwegian register definition a person is resident if he is staying or intends to stay 6 months or more in Norway.
Identification of the main job (*) N   NA 
Employment N   NA 
Unemployment N   NA 
8.1.1. Asymmetry for mirror flow statistics - coefficient

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

 

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

[not requested for the LFS quality report]
8.3. Coherence - cross domain
Coherence of LFS data with Business statistics data    
  Description of difference in concept Description of difference in measurement Give an assessment of the effects of the differences Give references to description of differences
Total employment  UNA  UNA   UNA   UNA 
Total employment by NACE  UNA  UNA   UNA   UNA 
Number of hours worked  UNA  UNA   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
Persons who were not employed in the reference week, but who had been seeking work during the preceding four weeks, and were available for work in the reference week or within the next two weeks are defined as unemployed in the LFS. Persons registered with the Labour and Welfare Organization (Nav) seeking work and are available for that work, who have not had any work for pay or profit for the last two weeks, are defined as registered unemployed.  LFS includes unemployed persons who do not register with the employment service (Nav) and some of those on labour market measures. On the other hand, a number of those registered as unemployed are not classified as unemployed in the LFS. This particularly applies to older people with long periods of unemployment. Moreover, persons on lay-off (until 3 months) are not classified as unemployed in the LFS, but as employed persons (temporarily absent from work).   http://www.ssb.no/english/subjects/06/arbeid_en/ 

 

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

[not requested for the LFS quality report]
8.5. Coherence - National Accounts
Coherence of LFS data with National Accounts data    
  Description of difference in concept Description of difference in measurement Give an assessment of the effects of the differences Give references to description of differences
Total employment LFS measures employment among persons 15-74 years old registered as resident, while National Accounts measure number of persons employed with resident producers. Foreign employees (non-residents) working in domestic production, of which foreign seamen on Norwegian owned ships or ships rented from abroad are incuded in the National Accounts figures.   NR  Total number of employed persons in National Accounts was 93 000 larger than in the LFS in 2011.  NR 
Total employment by NACE  NR  NR  NR   NR 
Number of hours worked LFS measures hours worked among employed persons 15-74 years old registered as resident, while National Accounts measure hours worked in domestic production during one year.   NR   NR   NR 

 

Which is the use of LFS data for National Account Data?   
Country uses LFS as the only source for employment in national accounts. Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis Country not make use of LFS, or makes minimal use of it Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS) Country combines sources for labour supply and demand not giving precedence to any labour side Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employment registers and/or enterprise surveys)
 N N   N  N N   Y
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
The quarterly results from the Norwegian LFS are published on Internet at Statistics Norway's web-pages: http://www.ssb.no/aku_en. In the publication Labour Force Survey 2001 even more tables are presented, containing long time-series (frequency: each 3rd or 4th year). Some main results also appear in the yearly publication Statistical Yearbook of Norway (both on paper and in electronic version on the Internet). 
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
National language(s):http://www.ssb.no/aku/

English:http://www.ssb.no/english/subjects/06/01/aku_en/

 In addition to the published tables, more tables are available. These and other tables, programmed to the customer's needs, can be ordered from Statistics Norway, Division for Labour Market Statistics. Accompanying information to data is available on Internet: http://www.ssb.no/aku_en ("About the statistics"). In the publication Labour Force Survey 2001 even more documentation is presented.   StatBank Norway is a service where you may select scope and content of each table, and then may export the result in various formats to your own PC.  
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  confidentiality agreement and signing of contracts  metadata  by email
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.ssb.no/en/arbeid-og-lonn/statistikker/aku  About the statistics
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 Commissioned Party is subject to a duty of confidentiality pursuant to Sections 13-13f of the Public Administration Act and relevant special legislation. The Commissioned Party is responsible for ensuring that informants are guaranteed anonymity in compliance with a declaration of consent and generally accepted research principles, also vis-á-vis the Principal.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top