Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Finland


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 Finland
1.2. Contact organisation unit

Social Statistics

Working life and wages and salaries
1.5. Contact mail address

Statistics Finland

Working life and wages and salaries

FI-00022 Statistics Finland

FINLAND


2. Statistical presentation Top
Please take note of the abbreviations used in the report 
Abbreviation Explanation
CV Coefficient of variation (or relative standard error)
Y/N Yes / No
H/P Households/Persons
M? Member State doesn’t know
NA Not applicable/ Not relevant
UNA Information unavailable
NR Non-response: Member State doesn’t answer to Eurostat request for information. Blank is allowed only in boxes with comments
LFS Labour Force Survey
NUTS Nomenclature of territorial units for statistics or corresponding statistical regions in the EFTA and candidates countries
2.1. Data description
Coverage   
Coverage Household concept Definition of household for the LFS Inclusion/exclusion criteria for members of the household Questions relating to employment status are put to all persons aged ...
The target population contains population aged 15 to 74 who are registered as permanently resident in Finland, including those who are temporarily abroad for a period of less than a year, members of the armed forces, and institutional population. The population also includes foreign nationals who have been living in Finland for at least a year or intend to do so. Persons living in institutions can not be separated from the total population.
The sample consists of persons. The information concerning the household composition and other members of the household are collected in the last (fifth) wave. 
In Finland, the LFS covers the whole country and the Autonomous Territory of the Åland Islands		 Housekeeping Members living regularly together in the same dwelling sharing meals or income.  NA  15 to 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
Registered population Family home Family home (if family ties are kept) Family home (if family ties are kept 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)
Stratified systematic sampling of elements The sampling frame is the total population database maintained by Statistics Finland. It is based on the Population Information System of The Digital and Population Data Services Agency. The sample of the first half of year 2020 was picked up in Nov 18, 2019 (the sampling frame updated Nov 15, 2019) and the sample of the second half of year 2020 was picked up in May 22, 2020 (the sampling frame updated May 20, 2020).  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 Stratified systematic sampling of elements, where sampling is performed separately within each stratum. A systematic random selection is applied to the frame sorted according to the domicile code which yields implicit geographic stratification. So far no indications of selection bias due to systematic sampling has been encountered, so the selection procedure can be approximated by simple random sampling without replacement (SRSWOR) The strata are formed according to NUTS 1 regions.  2 The quarterly rotation scheme of 3-1-2.

 

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)
 3.52%  145545 (15-74, excluding over-coverage)

  

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)
 0.88% Q1: 36374 (15-74, excluding over-coverage)

Q2: 36324 (15-74, excluding over-coverage)

Q3: 36409 (15-74, excluding over-coverage)

Q4: 36438 (15-74, excluding over-coverage)

  

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)
 5th wave  Y  NA HHLINK, HHSPOU, HHFATH, HHMOTH, SUPVISOR, SIZEFIRM, WAYJFOUN, EVENWK, NIGHTWK, SATWK, SUNWK, WAYMORE, HOMEWK, LOOKREAS, SEEKREAS, AVAIREAS, PRESEEK, NEEDCARE, REGISTER, COURPURP, COURWORH, WSTAT1Y, STAPRO1Y, NACE1Y2D, COUNTR1Y, REGION1Y, INCDECIL, COEFFY, COEFFH, REG3D1Y. Since year 2012, TEMPREAS has been a quarterly variable in the Finnish EU-LFS.

 

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
COEFFQ for reference population aged 15-74 years; HHLINK=1 and age 15 to 74.

Two-step reweighting of individuals: (i) post-stratified weights (the 194 post-strata are constructed by gender, age group and region); and (ii) calibrated weights (the post-stratified weights are calibrated according to gender, age group, region, reference week and register-based job-seeker indicator).

NOTE: COEFFQ for children (aged 0-14) and for elderly persons (aged 75+) is derived by COEFFH*4.

  N A sampling frame based on the total population register which contains individuals living in both private and collective households.  Y  5-year age groups (15-19, ..., 70-74) NUTS level 3 and the Greater Helsinki area The register-based job-seeker status (e.g. three categories according to the length of being unemployed in the register)

 

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
COEFFY for target population aged 15-74 years (the subsample): HHLINK=1 and age=15 to 74 and INTWAVE=5.

Two-step reweighting of individuals: (i) post-stratified weights (the 194 post-strata are constructed by gender, age group and region); and (ii) calibrated weights (the post-stratified weights are calibrated according to region, register-based job-seeker indicator and the annual average of quarterly estimates for employment, unemployment and inactive population by gender and for the following age groups: 15-24, 25-34, 35-44, 45-54, 55+).

NOTE: COEFFY for children (aged 0-14) and for elderly persons (aged 75+) is copied by COEFFH.

  Y 15-24, 25-34, 35-44, 45-54,55+ NUTS level 3 and the Greater Helsinki area The register-based job-seeker status (e.g. three categories according to the length of being unemployed in the register)

 

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)
COEFFH for the subsample of households

Two-step reweighting of households: (i) post-stratified weights were calculated separately for the household sample part (the 20 post-strata defined by region) and the technical sample of households (all persons in the household were aged 75+ and the two post-strata defined by gender); and (ii) calibrated weights (the post-stratified weights are calibrated according to region, household size, gender, age group, register-based job-seeker indicator and the annual average of quarterly estimates for the following factors: employment and unemployment by gender and age groups; and level of education and number of employees by gender).

 The household estimates produced by the income distribution statistics (Statistics Finland 2018) NUTS level 3 and the Greater Helsinki area, number of households and household size Gender, age groups (0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-74, 75-84, 85+), the register-based job-seeker status (e.g. three categories according to the length of being unemployed in the register)  Y
3.2. Frequency of data collection

[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description Use of dependent interviewing (Y/N)? Participation is voluntary/compulsory?
The use of a computer-aided system (CATI, CAPI) in the data collection. Interviews are carried out in Finnish, Swedish and English.  Y  Voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 0.20 %  99.80 %  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)
 High
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?
 Municipality  NUTS3 region Region (NUTS3). Lower regional level results (quarterly averages) are delivered providing the relative standard errors are approximately same size than at NUTS3 level.  Quarterly average from LFS dataset.
5.3.1. Data completeness - rate

[not requested for the LFS quality report]


6. Accuracy and reliability Top
6.1. Accuracy - overall

[not requested for the LFS quality report]
6.2. Sampling error
Publication thresholds   
Annual estimates Annual estimates - wave approach 
(if different from full sample thresholds) 
 Limit below which figures cannot be published  Limit below which figures must be published with warning  Limit below which figures cannot be published Limit below which figures must be published with warning
 2 000  4 000  2 000  4 000
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  0.27  0.27  1.48  1.61  1.56  2.93  0.22
 SE  6453  0.21  4694  3433  0.12  0.63  0.08
 CI(**)  2368145-2393440  76.07-76.88  308805-327205  205948-219405  7.52-8.00  20.14-22.59  36.33-36.65

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 The denominator of the employment rate is treated as a population figure without sample variance.

 

Reference on software used: Reference on method of estimation:
ETOS - a program developed by Statistics Sweden for calibration and GREG estimation. Inflation Coefficient approximation presented in Handbook on precision requirements and variance estimation for ESS households surveys, 2013, p. 77.

 

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 
 FI19 Länsi-Suomi  0.63  0.61  2.88  3.56  3.49  5.79  0.46
 FI1B Helsinki-Uusimaa  0.51  0.50  2.73  3.20  3.14  5.46  0.38
 FI1C Etelä-Suomi  0.75  0.72  3.50  4.18  4.10  6.88  0.51
 FI1D Pohjois- ja Itä-Suomi  0.74  0.70  3.25  3.55  3.47  5.83  0.51
 FI20 Åland  2.97  1.90  10.68  21.69  21.57  23.39  1.80

 

(*) 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
 Not significant  1.19%  UNA The sampling frame used is the total population database maintained by Statistics Finland. It is based on the Population Information System of The Digital and Population Data Services Agency and updated regularly. Undercoverage fairly small (no large-scale immigration). Mostly emigration in wave 1, deaths and emigration for later waves.  UNA  UNA

 

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

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

[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)   
Was the questionnaire updated for the 2019 LFS operation? (Y/N) Synthetic description of the update Was the questionnaire tested? (Y/N) If the questionnaire has been tested, which kind of tests has been applied (pilot, cognitive, internal check)?
 N  NA  NA  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)
 Y  N  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 Gender, age, region, reference week and register-based job-seeker indicator Reweighting methods (post-stratification and GREG-estimator)
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  40.74   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  39.16  20.62  18.25  UNA
2  40.44  19.88  20.34  UNA
3  41.36  19.88  21.22  UNA
4  42.00  19.45  22.31  UNA
Annual  40.74  19.96  20.53  UNA

 

 Units who refused to participate in the survey  (Please indicate the number of the units concerned in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018  1904      
Subsample_Q1_2019  1766  1875    
Subsample_Q2_2019    1773  1935  
Subsample_Q3_2019  1574    1755  1930
Subsample_Q4_2019  1308  1517    1749
Subsample_Q1_2020  947  1271  1565  
Subsample_Q2_2020    784  1105  1374
Subsample_Q3_2020      877  1181
Subsample_Q4_2020        854
Total in absolute numbers  7499  7220  7237  7088
Total in % of theoretical quarterly sample  20.62  19.88  19.88  19.45

 

Units who were not contacted (including people who migrated (or moved) internally or abroad) (Please indicate the number of units only in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018  755      
Subsample_Q1_2019  973  871    
Subsample_Q2_2019    1029  847  
Subsample_Q3_2019  1202    1064  915
Subsample_Q4_2019  1555  1345    1184
Subsample_Q1_2020  2155  1732  1417  
Subsample_Q2_2020    2410  1938  1619
Subsample_Q3_2020      2460  1952
Subsample_Q4_2020        2458
Total in absolute numbers  6640  7387  7726  8128
Total in % of theoretical quarterly sample  18.25  20.34  21.22  22.31

 

 of which people who migrated (or moved) internally or abroad) (Please indicate the number of units only in the cells where the wave is mentioned)
Subsample Quarter1_2020 Quarter2_2020 Quarter3_2020 Quarter4_2020
Subsample_Q4_2018  UNA      
Subsample_Q1_2019  UNA  UNA    
Subsample_Q2_2019    UNA  UNA  
Subsample_Q3_2019  UNA    UNA  UNA
Subsample_Q4_2019  UNA  UNA    UNA
Subsample_Q1_2020  UNA  UNA  UNA  
Subsample_Q2_2020    UNA  UNA  UNA
Subsample_Q3_2020      UNA  UNA
Subsample_Q4_2020        UNA
Total in absolute numbers  UNA  UNA  UNA  UNA
Total in % of theoretical quarterly sample  UNA  UNA   UNA  UNA

 

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)  Non response rate (%)
 FI19 - Länsi-Suomi  39.20
 FI1B - Helsinki-Uusimaa  42.62
 FI1C - Etelä-Suomi  42.66
 FI1D - Pohjois-Suomi  38.68
 FI20 - Åland  29.91

* 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_112 - Employed METHODJ C C . C Passive job search methods are asked only if none of the active methods have been used.
compulsory Col_112 - Not employed METHODJ . . C . Passive job search methods are asked only if none of the active methods have been used.
compulsory Col_113 - Employed METHODK . C . .  Passive job search methods are asked only if none of the active methods have been used.
compulsory Col_113 - Not employed METHODK C . . .  Passive job search methods are asked only if none of the active methods have been used.
compulsory Col_114 - Employed METHODL . C C C  Passive job search methods are asked only if none of the active methods have been used
compulsory Col_114 - Not employed METHODL C C . C  Passive job search methods are asked only if none of the active methods have been used
compulsory Col_115 - Not employed METHODM . . C .  

 

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_146 WSTAT1Y 23.1  Information concerning year before has obviously not been available.
compulsory Col_150/151 COUNTR1Y 43.4 Information concerning year before has obviously not been available; others, no explanations found so far.
compulsory Col_200/203 HATYEAR 10.3  -
optional Col_133/135 COURFILD 100  Optional. 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 
 NA  NA  NA
6.3.5. Model assumption error

[not requested for the LFS quality report]
6.4. Seasonal adjustment
Do you apply any seasonal adjustment to the LFS Series? (Y/N) If Yes, is your adopted methodology compliant with the ESS guidelines on seasonal adjustment? (ref. http://ec.europa.eu/eurostat/web/research-methodology/seasonal-adjustment) (Y/N) If Yes, are you compliant with the Eurostat/ECB recommendation on Jdemetra+ as software for conducting seasonal adjustment of official statistics. (ref. http://ec.europa.eu/eurostat/web/ess/-/jdemetra-officially-recommended-as-software-for-the-seasonal-adjustment-of-official-statistics) (Y/N) If Not, please provide a description of the used methods and tools
 Y  Y  Y  NA
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N) Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. http://ec.europa.eu/eurostat/documents/3859598/5935517/KS-RA-13-016-EN.PDF) (Y/N)
 Y  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  NA
Identification of the main job (*)  Y  NA
Employment  Y  NA
Unemployment  Y  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  NA  NA  NA  NA  NA
coverage (i.e. target population)  NA  NA  NA  NA  NA
legislation  NA  NA  NA  NA  NA
classifications  NA  NA  NA  NA NA 
geographical boundaries  NA  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  NA  NA  NA  NA  NA
sample design  NA  NA  NA  NA  NA
rotation pattern  NA  NA  NA  NA  NA
questionnaire  NA  NA  NA  NA  NA
instruction to interviewers  NA  NA  NA  NA  NA
survey mode  NA  NA  NA  NA  NA
weighting scheme  NA  NA  NA  NA  NA
use of auxiliary information  NA  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 Finland has no short-term business surveys. Annual statistics of  employment in private sector are published in the 'Structural Business and Financial Statement Statistics'. Annual data covers enterprises and businesses, that have been in operation for at least six months during the reference year. Also, the enterprises will have to exceed at least one of the following criteria: turnover more than 12 000 €, employment of at least 0.5 full-time equivalent units, at least 50 000€ in investments, at least 170 000€ as the balance sheet total. Enterprises that do not fulfil these criteria are not included in the aforementioned statistics. The total number of personnel comprises paid employees and entrepreneurs and is in terms of full-time workers. Structural Business and Financial Statement statistics are produced from the integrated business statistics microdata production database and -warehouse (abbreviated 'YTY'), which consists of statistical business register integrated with annual business statistics Data is collected mainly from two sources. The sources include estimation from the National Board of Taxation's data on annual and monthly taxes, inquiries addressed to all enterprises with at least 10 employees, enterprises with multiple local units, enterprises involved in mergers or fusions, high-growth enterprises and a random sample of enterprises for which location and contact information is verified. Public sector is included in the YTY system, but employment data is not published.  For enterprises with multiple local units, surveys are the most important source of information. For enterprises with a single local unit, estimation from annual taxation data is the main source.

In comparison of the private sector employment in 2015, the LFS shows 19% more than the Business Statistics.

(We have no resources to date information)

 The differences in private sector employment are mainly due to the differences in definition (enterprise statistics are in full-time equivalents).
Total employment by NACE see above  see above

Private sector employment difference by industry in the LFS compared to the Business statistics in 2015 is under 10% for NACE C, F, H and L, between 11-20% for Nace B, E, G, K, and between 21-30% for NACE I, J and M. The difference was was considerably bigger for the industries A, D, N, P, Q, R, and S.

(We have no resources to date information)

 The differences in private sector employment are mainly due to the differences in definition (enterprise statistics are in full-time equivalents)
Number of hours worked  Not available form Business Statistics  NA  NA  NA

 

Coherence of LFS data with registered unemployment  
Description of difference in concept Description of difference in measurement Give references to description of differences
 Registered unemployment is an administrative concept, which differs considerably from the LFS unemployment. Some population groups are considered as unemployed in LFS but are not registered unemployed and vice versa.
In addition to different definitions of unemployment, differences between the unemployment figures of LFS and the Ministry of Employment and the Economy (TEM) are due to:
- Different reference period (LFS uses continuous reference week and TEM uses last weekday of each month)
- Delay in updating the registers of the TEM
- Asylum seekers who have not received permanent resident status are not included in the sampling frame		 Differences are due to different reference dates and to different conceptual frameworks. The LFS uses definition based on ILO recommendations, whereas registered unemployment follows national legislation and administrative regulations.  

A description of differences is available on LFS Home page on the Statistics Finland's web-site

https://www.tilastokeskus.fi/til/tyti/tyti_2019-09-13_men_001_en.html

 

Assessment of the effect of differences of LFS unemployment and registered unemployment     
Give an assessment of the effects of the differences          
Overall effect Men under 25 years Men 25 years and over Women under 25 years Women 25 years and over Regional distribution (NUTS-3)

Differences are due to different reference dates and conceptual frameworks. The LFS uses a definition based on ILO recommendations, whereas registered unemployment follows national legislation and administrative regulations. In 2013, the total number of registered unemployment was 34 % higher than the LFS estimate. Legislation and administrative regulations are often age specific.

(We have no resources to date information)

 The number LFS unemployed was about 54 % higher than registered unemployment in 2013 The number of LFS unemployed was about 23 % less than the registered unemployment in 2013 The number LFS unemployed was about 96 % higher than registered unemployment in 2013 The number of LFS unemployed was about 39 % less than the registered unemployment in 2013. Regional data is not fully comparable due to differences in geographical classifications in use
8.4. Coherence - sub annual and annual statistics

[not requested for the LFS quality report]
8.5. Coherence - National Accounts

ESA Employment, Finland – Comparisons of National Accounts, Labour Force Survey and Structure of Earnings Survey, 2000.

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 Unlike national employment in the LFS, domestic employment in the NA includes non-resident frontier workers and non-resident seasonal workers working in Finland. Number of employed persons is, however, very close to LFS estimates.  UNA The annual and quarterly statistics on total employment in the NA and in the LFS are close to each other ESA Employment, Finland – Comparisons of National Accounts, Labour Force Survey and Structure of Earnings Survey, 2000.
Total employment by NACE NA employment includes conscripts and in principle certain unpaid groups if they participate in production of goods while the LFS considers these groups as economically inactive. NA also excludes persons on maternity leave.The main source of the data on employment and hours worked in the NA is the LFS. However, the LFS statistics are not used as such but combined with data obtained from other available sources, i.e. registers, establishment statistics and enterprises’ annual report  UNA  The annual and quarterly statistics on total employment in the NA and in the LFS are close to each other
Number of hours worked  NA uses LFS estimates on hours actually worked, but adjusts them in harmony with other NA data sources  UNA NA figures of total number of hours worked differ about 1-5% from LFS figures

 

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)
In Quarterly National Accounts (QNA) the LFS is used as the main indicator for total employment and hours worked.  N  N  N  N In Annual National Accounts (ANA) the main source is business register and the LFS is used as a comparison.
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 results of the Labour Force Survey are published in the Labour market series of the Official Statistics of Finland and released monthly, quarterly and annually on predefined days in the Internet on the home page of the Labour Force Survey http://tilastokeskus.fi/til/tyti/index_en. Key results of the Labour Force Survey are published as press releases about three weeks after the reference month jointly with the Ministry of Employment and the Economy. The released statistics are final. Monthly and quarterly publications are available in electronic format (pdf). Annual data is released in one yearly review and in an annual publication. The yearly reviews are available in electronic format. Tables and graphs are available on the internet for public use (StatFin database, LFS home page). Additionally, Statistics Finland's chargeable time series (ASTIKA) include LFS statistics. Tables and graphs are also delivered as special compilations according to customers’ needs.
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)):
http://www.tilastokeskus.fi/til/tyti/index.html
http://www.tilastokeskus.fi/til/tyti/index_sv.html
Link to the national web page (English):
http://www.tilastokeskus.fi/til/tyti/index_en.html		  Basic statistics are available free of charge via internet, phone or e-mail. Printed and pdf-publications as well as special compilations are chargeable (see 4.1). Labour Force Survey's anonymised microdata sets are available for scientific research according to the application to licence to use statistical data, either from Statistics Finland or Eurostat. Both of them use a specific confidential data access procedure. All statistics collected and published by Statistics Finland are governed by the Statistics Act of Finland (280/2004). Other national legislation applied within this context are e. g. the Act on the Openness of Government Activities (621/1999) and the Personal Data Act (523/1999). Information about the Labour Force Survey is available at Statistics Finland’s Internet pages (www.stat.fi). The LFS yearbook includes a description of the methodology. Information services related to LFS are provided to the users by the Information Services Unit (ISU) and Labour Force Survey Unit (LFSU) by means of up-to-date web-pages, e-mail and telephone services. Phone and e-mail services are available during office hours.
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 Following conditions are general for the use of Researcher Services for microdata access (not specially for the LFS data).

Researchers apply for a licence to use microdata by sending an application that includes a research plan and a pledge of secrecy. The need for the requested data has to be justified in the application. Research services find out if the data is available and if  the licence can be granted. The Ethics Committee is consulted in cases involving large datasets with confidential data.

  UNA  UNA
9.5. Dissemination format - other

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

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

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

[not requested for the LFS quality report]


10. Cost and Burden Top
Restricted from publication


11. Confidentiality Top
11.1. Confidentiality - policy

[not requested for the LFS quality report]
11.2. Confidentiality - data treatment
Please provide information on the policy for anonymizing microdata in your country
 NR


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top