Employment and unemployment (Labour force survey) (employ)

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

Compiling agency: Statistics Netherlands


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 Netherlands
1.2. Contact organisation unit

Division of socio-economic and spatial statistics
1.5. Contact mail address

Statistics Netherlands

Post box 4481

6401 CZ Heerlen

The Netherlands


2. Statistical presentation Top
Please take note of the abbreviations used in the report 
Abbreviation Explanation
CV Coefficient of variation (or relative standard error)
Y/N Yes / No
H/P Households/Persons
M? Member State doesn’t know
NA Not applicable/ Not relevant
UNA Information unavailable
NR Non-response: Member State doesn’t answer to Eurostat request for information. Blank is allowed only in boxes with comments
LFS Labour Force Survey
NUTS Nomenclature of territorial units for statistics or corresponding statistical regions in the EFTA and candidates countries
2.1. Data description
Coverage   
Coverage Household concept Definition of household for the LFS Inclusion/exclusion criteria for members of the household Questions relating to employment status are put to all persons aged ...
 The survey covers only private households. The resident population comprises persons residing in the Netherlands. Housekeeping Members living regularly together in the same dwelling, sharing household expenditures, food and other essentials for living.  The private household comprises either persons living alone or two or more persons, whether or not they are of the same family, who usually occupy the same dwelling and share a joint budget  15 years and older

 

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 Most of the time Most of the time Most of the time Most of the time 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)                                  
   The year is divided into quarters of 13 weeks: January to March, April to June, July to September and October to December. Each quarter is divided into months of four or five weeks. The survey is based on sliding reference weeks, meaning that respondents answer the questions on the current week.
2.2. Classification system

[not requested for the LFS quality report]
2.3. Coverage - sector

[not requested for the LFS quality report]
2.4. Statistical concepts and definitions

 [not requested for the LFS quality report]
2.5. Statistical unit

[not requested for the LFS quality report]
2.6. Statistical population

[not requested for the LFS quality report]
2.7. Reference area

[not requested for the LFS quality report]
2.8. Coverage - Time

[not requested for the LFS quality report]
2.9. Base period

[not requested for the LFS quality report]


3. Statistical processing Top
3.1. Source data
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.) Base used for the sample (sampling frame)  Last update of the sampling frame (continuously updated or date of the last update) Primary sampling unit (PSU)   Final sampling unit (FSU)
Two stage stratified probability sample of addresses The survey base is a list of all addresses drawn up by the postal services in combination with the Population Register. All institutions are eliminated from the sample. The file also contains information on the number of letterboxes at each address (mailing addresses), which are used as sampling units. The sampling frame is updated continuously. Local governments can process all changes in their local population into the population registration. It depends on the local government how often this process takes place. Municipality Household address

 

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.)
In the first stage, municipalities are selected systematically with a probability proportional to the number of addresses in the municipalities. All municipalities with a population of more than 18 000 persons (about 200 municipalities), are permanently represented in the survey. In the first stage, also the number of addresses which have to be selected in the second stage, are determined for selected municipalities. For municipalities which are selected with probability 1, the number of addresses which have to be selected in the second stage equals the product of the sampling rate and the number of addresses in the municipality. With the current sample size, every municipality is selected with probability 1. Mailing addresses are selected systematically out of a mailing list sorted by postal code. At addresses with more than one letterbox, all letterboxes appear in the list. In the second stage, addresses are selected randomly in the selected municipalities, with the number of addresses per municipality as determined in the first stage. 

If a selected mailing address includes only one household, this household is questioned. If the address includes more than one household, only half of the households are questioned, with a maximum of three households. This makes it possible to increase the effectiveness of the survey.

  NUTS 3 (in Dutch: Corop) regions  66 strata are defined 5

 

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)
2.2%  174200

  

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)
0.5%   43500

  

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)
 wave 2  N Consistency for the ILO status by sex and age groups: 15-24, 25-44 and 45-74.
  • All variables concerning atypical work (SHIFTWK, EVENWK, NIGHTWK, SATWK, UNWK)
  • HOMEWK
  • All variables concerning previous work experience of person not in employment ( EXISTPR, YEARPR, MONTHPR, LEAVREAS, STAPROPR, NACEPR2D, ISCOPR3D)
  • MAINSTAT
  • All variables concerning education or training successfully completed (HATLEVEL, HATFIELD, HATYEAR)
  • LFS ad hoc module       

 

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
Weighting of the respondents is done in two stages. In the first stage all respondents are assigned an inclusion weight. These inclusion weights are calculated in such a way that unequal inclusion probabilities that occur because of the sampling method are corrected. In the second stage final weights are determined. In this stage biases because of non-respons are reduced. For this, information on gender, age, ethnic background, place of residence and some other regional classifications are used. In addition, administrative sources on the income and registration at unemployment office are used. Also information on the correlation in the panel-overlap between subsequent quarters is used and all waves together are weighted in one step.  Y  NA  Y "0-14 ", "15 ", "16 ", "17 ", "18 ", "19 ", "20 ", "21 ", "22 ", "23 ", "24 ", "25 ", "26 ", "27 ", "28 ", "29 ", "30 ", "31-34 ", "35-39 ", "40-44 ", "45-49 ", "50 ", "51 ", "52 ", "53 ", "54 ", "55 ", "56 ", "57 ", "58 ", "59 ", "60 ", "61 ", "62 ", "63 ", "64 ", "65 ", "66 ", "67 ", "68 ", "69 ", "70-74 ", "75-125 " municipalities with over 30 thousand residents ethnic background, income, type of household, registration unemployment office

 

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
Similar to calculation of quarterly core weights. Subsampling is applied for the second wave.  Y  Equal to quarterly core weighting  Equal to quarterly core weighting Equal to quarterly core weighting

 

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)
Similar to calculation of quarterly core weights.  N Household size (one vs. multiple person households) Equal to quarterly core weighting  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?
 Since 2010 interviews in the first wave are carried out mixed-mode (CATI, CAPI); as from the 4th quarter of 2012 CAWI is introduced. First everyone is approached by CAWI. Non-respondents are re-approached by CATI or CAPI. When a telephone number is available, people are re-approached by telephone (CATI). When there is no telephone number available, the approach is face-to-face with the help of portable computers (CAPI). Interviews in the next four waves are carried out by telephone (CATI). In the CATI questionnaire, data previously gathered in the preceding wave (CAWI, CATI or CAPI) are included.  Y  voluntary

 

Final sampling unit collected by interviewing technique (%)
CAPI CATI PAPI CAWI POSTAL - OTHER
 4  69  NA  27  NA
3.4. Data validation

[not requested for the LFS quality report]
3.5. Data compilation

[not requested for the LFS quality report]
3.6. Adjustment

[not requested for the LFS quality report]


4. Quality management Top
4.1. Quality assurance

[not requested for the LFS quality report]
4.2. Quality management - assessment

[not requested for the LFS quality report]


5. Relevance Top
5.1. Relevance - User Needs
Assessment of the relevance of the main LFS statistics at national level (e.g. for policy makers, other stakeholders, media and academic research)
The LFS information is highly relevant at national level. Next to the mandatory LFS variables, we use the LFS to gather information on f.e. the subjects of ‘combining work and care responsibilities’ and ‘job security‘ in order to provide the national ministries with relevant information to monitor their policies in these fields. LFS yields several publications, and data are published in, among others news articles (continuously), a statistical year book, on Statline (updated monthly, quarterly and yearly), socio-economic trends (quarterly), and a barometer of the Dutch labour force (quarterly). The relevance of LFS is especially high for policy makers, social actors, the media and for researchers and students.
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?
 NUTS 2  NUTS 3  NUTS 3  Annual average from the LFS
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
 1500  2500  1500  6500
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 0.14 0.14 0.37 1.51 1.26 1.93  NR
 SE 11 0.11 14 5 0.05 0.18  NR
 CI (**)

 8079000 ; 8123000

  79.75 ; 80.19  3663000 ; 3717000  346000 ; 368000  3.74 ; 3.93  8.76 ; 9.45  NR

 

Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
 We use the total number of private households, and the total number of people living there, as calibration margin. These numbers are calculated from the population register and are not subject to (sampling) variation. 

 

Reference on software used: Reference on method of estimation:
 No specific software   Very rough estimates

 

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 

NL11

Groningen

 0.9 0.9 1.9 7.1 5.7 8.3  NR

NL12

Friesland

 0.7 0.7 1.7 7.6 6.2 9.5  NR

NL13

Drenthe

 0.8 0.8 2.0 9.1 7.4 10.2  NR

NL21

Overijssel

 0,5 0.5 1.4 6.0 5.0 7.9  NR

NL22

Flevoland

 0.9 0.9 2.6 10.2 8.7 11.8  NR

NL23

Gelderland

 0.4 0.4 1.0 4.4 3.7 5.7  NR

NL31

Utrecht

 0.4 0.4 1.2 5.4 4.6 6.7  NR

NL32

Noord-Holland

 0.4 0.4 1.0 3.8 3.2 4.9  NR

NL33

Zuid-Holland

 0.3 0.3 0.9 3.2 2.7 4.0  NR

NL34

Zeeland

 0.9 0.9 2.6 12.7 10.4 16.6  NR
 

NL41

 Noord-Brabant 0.3 0.3 0.9 4.0 3.4 5.3  NR
 

NL42

  

Limburg

 0.6 0.6 1.4 6.0 4.9 8.0  NR

 

(*) 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  UNA  UNA  UNA  UNA  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  Y  cognitive and internal check

 

Main methods of reducing measurement errors 
Error source  
Respondent  Letter introducing the survey (Y/N) Phone call for booking or introducing the survey (Y/N)
 Y  N
Interviewer  Periodical training (at least 1 time per year) (Y/N)  Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
 Y  Y
Fieldwork  Monitoring directly by contacting the respondents after the fieldwork (Y/N) Monitoring directly by listening the interviews (Y/N) Monitoring remotely through performance indicators (Y/N)
 Y  Y  Y
Questionnaire  Questionnaire in several languages (Y/N)  On-line checks (for computer assisted interviews (Y/N)
 N  Y
Other / Comments  Respondents:
  • Making use of computer assisted questionnaires;
  • questions that are easy to answer;
  • routings in questionnaire to provoke only the relevant questions for respondent;
  • pretesting

Interviewers:

  • extended instructions and regularly refreshing courses on basic skills abd LFS contents;
  • using interviewer manuals;
  • Monitoring system and regularly walk along with interviewers;
  • regular meetings with a regional manager;
  • central helpdesk;
  • 5% of the interviews are checked (response analysis)

Questionnaires

  • input specialised expertise in developing questionnaires;
  • routings in the questionnaires to provoke only the relevant questions for respondents;
  • cognitive labaratory experiments with focus groups and indept interviewing;
  • opportunity to make remarks in the questionnaire;
  • Evaluations of the questionnaire

Other

  • A stable automation system of data communication and production;
  • Monitoring system;
  • Once a day interviewers have to transfer their data to Statistics Netherlands;
  • Each record contains interview accounts as well as interview data
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  See description of weighting in 3.1  See description of weighting in 3.1
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
 NR  NR  NA  NR  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 52.86 37.48 11.49  3.3
2 51.28 36.74 12.16  3.6
3 53.07 37.36 13.30  3.1
4 52.69 37.22 11.94  3.9
Annual 52.47 37.19 12.21  3.5

 

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_Q1_2019 wave 5: 30      
Subsample_Q2_2019 wave 4: 70  wave 5: 30    
Subsample_Q3_2019 wave 3: 140  wave 4: 70  wave 5: 30  
Subsample_Q4_2019 wave 2: 350  wave 3: 170  wave 4: 60  wave 5: 50
Subsample_Q1_2020 wave 1: 2840  wave 2: 300  wave 3: 160  wave 4: 120
Subsample_Q2_2020    wave 1: 1980  wave 2: 320  wave 3: 170
Subsample_Q3_2020      wave 1: 2640  wave 2: 360
Subsample_Q4_2020        wave 1: 3010
Total in absolute numbers  3430  2540  3200  3720
Total in % of theoretical quarterly sample  UNA  UNA  UNA  UNA

 

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_Q1_2019 wave 5: 510      
Subsample_Q2_2019 wave 4: 750 wave 5: 390    
Subsample_Q3_2019 wave 3: 1300 wave 4: 510 wave 5: 400  
Subsample_Q4_2019 wave 2: 2810 wave 3: 1190 wave 4: 660 wave 5: 400
Subsample_Q1_2020 wave 1: 5520 wave 2: 2890 wave 3: 1430 wave 4: 590
Subsample_Q2_2020    wave 1: 6200 wave 2: 3200 wave 3: 1220
Subsample_Q3_2020     wave 1: 7810 wave 2: 3070
Subsample_Q4_2020       wave 1: 6150
Total in absolute numbers  10880  11170 13490  11420
Total in % of theoretical quarterly sample  UNA  UNA UNA  UNA

 

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_Q1_2019 wave 5: 0      
Subsample_Q2_2019 wave 4: 0  wave 5: 0    
Subsample_Q3_2019 wave 3: 30  wave 4: 10   wave 5: 0  
Subsample_Q4_2019 wave 2: 190   wave 3: 20   wave 4: 0   wave 5: 0
Subsample_Q1_2020  wave 1: 140  wave 2: 230   wave 3: 40   wave 4: 10
Subsample_Q2_2020    wave 1: 150   wave 2: 240   wave 3: 20
Subsample_Q3_2020       wave 1: 110   wave 2: 230
Subsample_Q4_2020         wave 1: 190
Total in absolute numbers  360 400   390  450
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 (%)

NL11 Groningen

  UNA

NL12 Friesland

  UNA

NL13 Drenthe

  UNA

NL21 Overijssel

  UNA

NL22 Flevoland

  UNA

NL23 Gelderland

  UNA

NL31 Utrecht

  UNA

NL32 Noord-Holland

  UNA

NL33 Zuid-Holland

  UNA

NL34 Zeeland

  UNA

NL41 Noord-Brabant

  UNA

NL42 Limburg

  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_029/31 NACE3D . . 10.1 . This sector of industry information is retrieved from administrative data. For the majority of the cases this works properly, yet for the remaining part we were unable to match the sector successfully.
compulsory Col_054 TEMPDUR 64.7 62.6 61.7 63.5 3 main reasons for missings:

First, this is due to respondents who have a ‘0’ on the variable for the year in which they started searching for a job, and who subsequently did not fill in the number of months they have been searching.

The second reason is related to a change in 2010. Since then respondents who do not want to work are asked if they are looking for work, but unfortunately these respondents do not get the questions regarding the year and month they started searching.

The third reason is related to respondents who state that they have recently searched for a job, but also indicate that they have already found a new job which they will start working in within 3 months. They do not get the questions regarding the year and month they have started searching for a job.
compulsory Col_080/81 NACE2J2D 27.2 26.3 26.3 26.1  Variable collected by registers. Some difficulties in finding Nace code for second activity.
compulsory Col_101 - Not employed SEEKTYPE 11.2 . . .  

Partly related to a change in 2010. Since then respondents who do not want to work are asked if they are looking for work, but unfortunately these respondents do not get the questions regarding the year and month they started searching.

Also related to respondents who state that they have recently searched for a job, but also indicate that they have already found a new job which they will start working in within 3 months. They do not get the questions regarding the year and month they have started searching for a job.
compulsory Col_102 - Not employed SEEKDUR 19.2 16.7 17.3 14.5  More reasons due to issues with questions about year and month when the search for job has started
compulsory Col_110 - Employed METHODH C C C C  
compulsory Col_111 - Employed METHODI C C C C  
compulsory Col_112 - Employed METHODJ C C C C  
compulsory Col_112 - Not employed METHODJ C C C .  
compulsory Col_114 - Employed METHODL C C C C  
compulsory Col_114 - Not employed METHODL C C C .  
optional Col_021/22 COUNTRYB 13.2 14.3 14.1 13.8  Variable is only filled for those having previously indicated the number of ‘years of residence in the member state’. So, if we have a 'no answer' on this question, country of birth is not filled.

 

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_053 TEMPREAS 32.9  Mostly due to questionnaire related matters
compulsory Col_093 STAPROPR 59.7  Mostly due to questionnaire related matters
compulsory Col_094/95 NACEPR2D 65.7  Mostly due to questionnaire related matters 
compulsory Col_096/98 ISCOPR3D 77.6  Mostly due to questionnaire related matters 
compulsory Col_118 - Not employed AVAIREAS 36.4  Mostly due to questionnaire related matters 
compulsory Col_119 PRESEEK 72.2  Mostly due to questionnaire related matters 
compulsory Col_146 WSTAT1Y 14.5  Mostly due to questionnaire related matters 
compulsory Col_148/149 NACE1Y2D 12.7  Mostly due to questionnaire related matters 
compulsory Col_200/203 HATYEAR 10.5  Mostly due to questionnaire related matters 
optional Col_136 COURWORH 13.7  Mostly due to questionnaire related matters 

(*) "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  N  N  Structural Time Series modelling is used for filtered trend (so excluding seasonal effects)monthly unemployment rates
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)
 N (no preliminary data published.)  NA
6.6. Data revision - practice

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

[not requested for the LFS quality report]


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


8. Coherence and comparability Top
8.1. Comparability - geographical

Divergence of national concepts from European concepts

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

    
Is there a divergence between the national and European concepts for the following characteristics? (Y/N) Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)  N  NA
Identification of the main job (*)  N  NA
Employment  N  NA
Unemployment  N   NA
8.1.1. Asymmetry for mirror flow statistics - coefficient

[not requested for the LFS quality report]
8.2. Comparability - over time
Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes in (Y/N) Description of the impact of the changes Statistics also revised backwards (if Y: year / N) Variables affected Break in series to be flagged (if Y: year and quarter/N)  
concepts and definition  N  NA  NA  NA  NA
coverage (i.e. target population)  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  Via registration of wages employees employed in The Netherlands are covered in registration. Self-employed living in the Netherlands are covered in the income register. Employment is then defined as having a job or having a business. Publicationa are usually on jobs instead of persons.  Registration  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
 Registration at employment office is (with some exceptions) obliged if you receive social benefits. It is not directly linked to searching employment.  Online registration  UNA 

 

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)
 Less than 1/3 registered unemployed are actually ILO-unemployed. Young people are often not registered because they are often not entitled to benefits.   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 Generally applicable differences due to ILO vs SNA concepts National Accounts are mainly based on registered jobs  See link:

https://www.cbs.nl/-/media/imported/documents/2016/53/2016st01-werknemers-en-zelfstandigen.pdf
Total employment by NACE  UNA  UNA   UNA   UNA 
Number of hours worked  UNA  UNA   UNA   UNA 

 

Which is the use of LFS data for National Account Data?   
Country uses LFS as the only source for employment in national accounts. Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis Country not make use of LFS, or makes minimal use of it Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS) Country combines sources for labour supply and demand not giving precedence to any labour side Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employment registers and/or enterprise surveys)
 N  N N  N  N  Y (For overwork hours and self-employed)
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
 Statistisch Jaarboek/ Statisitical Yearbook
  • Statline (monthly, quarterly and yearly)
  • Press release unemployment (monthly)
  • Webmagazine (continuously)
  • Sociaaleconomische Trends (quarterly)
  • Barometer Beroepsbevolking (quarterly)
  • Themepages about labour market and about education (continuously)
  • Statistisch Bulletin (continuously)
  • Several tables made to measure on request of local and national authorities ( i.e. department of Social affairs; department of Welfare, Health and Cultural affairs)

Horizontal publications:

  • Jaarboek Integratie (Yearbook Integration)
  • Emancipation monitor (Every 2 years)
  • Jaar in cijfers (Year in figures)
  • Jaarboek Onderwijs (Yearbook Education)
  • De Nederlandse economie (The Dutch economy)
  • De Digitale economie (The Digital economy)
  • Nederland langs de Europese meetlat (The Netherlands in European perspective)
  • De Nederlandse Samenleving (The Dutch society)
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

https://www.cbs.nl/en-gb/our-services/methods/surveys/korte-onderzoeksbeschrijvingen/labour-force-survey--lfs--

 Our data are accessible on statline

Our micro data are accessible under certain conditions: The CCS-criteria for research institutions who want to have access to the micro-data are:

Declination of these criteria is possible in certain cases. However the Central Commission of the Statistics needs to motivate this deviation explicitly. 

1. the institution has an independent legal individuality, or belongs to a public service.

On this last case you can think of a statistical or research department of ministries, provinces or municipalities.

These research institutions have to make a reasonable case for executing their research task under the condition mentioned under 2.

2. the institution isn't subjected to the authority of an administrative body.

3. the institution has to have a primary research aim.

4. the institution has to publish publicly. If the institution executes their research for a customer then the institution has to make public the results for which the data are used.

5. the institution enjoys a good reputation.

 Questionnaire in scheme;  users’ handbook; codebook; a description of the methodology and a description of the derivations.  http://www.cbs.nl/en-gb/

https://www.cbs.nl/en-gb/publication-calendar

 
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

 https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research

  NR  NR  NR
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.cbs.nl/en-gb/our-services/methods/surveys/korte-onderzoeksbeschrijvingen/dutch-labour-force-survey--lfs--
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
 Personal data are anonimized by deleting variables that can reveal identification of persons and a unique identification key is used for matching.


12. Comment Top

[not requested for the LFS quality report]


Related metadata Top


Annexes Top