Quality report of the European Union labour force survey : 2018 edition.
Date: 2018-10-30
Institutions: Eurostat
Subjects: European Union, employment statistics, labour force, labour market, persons in work, unemployment

Quality report of the 
European Union 
Labour Force Survey 2016

2018 edition

S T A T I S T I C A L 
R E P O R T S

STATISTICAL REPORTSMain title 2018 editionManuscript completed in October 2018 

Neither the European Commission nor any person acting on behalf of the Commission is responsible for 
the use that might be made of the following information. 

Luxembourg: Publications Office of the European Union, 2018 

© European Union, 2018 
Reuse is authorised provided the source is acknowledged.  
The reuse policy of European Commission documents is regulated by Decision 2011/833/EU (OJ L 330, 
14.12.2011, p. 39). 

Copyright for the cover picture: © Shutterstock/Olivier Le Moal 

For any use or reproduction of photos or other material that is not under the EU copyright, permission 
must be sought directly from the copyright holders. 
For more information, please consult: https://ec.europa.eu/eurostat/about/policies/copyright 

The information and views set out in this publication are those of the authors and do not necessarily 
reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor 
any person acting on their behalf may be held responsible for the use which may be made of the  
information contained therein. 

Collection:  
Theme:  

Statistical reports 
Population and social conditions 

PDF 

ISBN 978-92-79-96567-8      ISSN 2529-3222       doi: 10.2785/387993  KS-FT-18-008-EN-N 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Contents 

1.  Introduction ............................................................................................ 5 

2.  Overview of designs and methods of the EU-LFS in 2016 ................. 6 

2.1  Coverage ............................................................................................................................. 6 

2.2 

Legal basis .......................................................................................................................... 6 

2.3  Reference period ................................................................................................................ 7 

2.4 

Sampling designs .............................................................................................................. 7 

2.5  Rotation schemes .............................................................................................................. 8 

2.6  Calculation of weighting factors ....................................................................................... 9 

2.7  Data collection methods .................................................................................................... 9 

2.8  Use of subsamples to survey structural variables ....................................................... 10 

3.  Relevance ............................................................................................. 11 

3.1  Definition ........................................................................................................................... 11 

3.2 

The users .......................................................................................................................... 11 

3.3  Completeness ................................................................................................................... 12 

4.  Accuracy .............................................................................................. 14 

4.1  Definition ........................................................................................................................... 14 

4.2 

Sampling errors ................................................................................................................ 14 

4.3  Non-sampling errors ........................................................................................................ 17 

5.  Timeliness and punctuality ................................................................. 24 

5.1  Definition ........................................................................................................................... 24 

6.  Comparability ....................................................................................... 26 

6.1  Definition ........................................................................................................................... 26 

6.2   Comparability over space ............................................................................................... 26 

6.3  Comparability over time .................................................................................................. 28 

7.  Coherence ............................................................................................ 30 

7.1  Definition ........................................................................................................................... 30 

7.2  Coherence with population statistics ............................................................................ 30 

7.3  Coherence with other employment and unemployment estimates ............................. 32 

8.  Accessibility and clarity ...................................................................... 36 

8.1  Definition ........................................................................................................................... 36 

8.2  Available information ....................................................................................................... 36 

9.  Regional labour market statistics ...................................................... 37 

9.1 

Introduction ...................................................................................................................... 37 

Quality report of the European Union Labour Force Survey 2016 

3 

 
 
 
 
Contents 

9.2 

Sources for NUTS 3 level labour market statistics ....................................................... 37 

10. Annex .................................................................................................... 39 

10.1 

10.2 

Tables .......................................................................................................................... 39 

Data presentation and abbreviations ........................................................................ 56 

Quality report of the European Union Labour Force Survey 2016 

4 

 
 
 
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

1 Introduction 

The quality concept applied in this report is in conformity with the definition developed by the 
European Statistical System and reported in the European Statistics Code of Practice. According to 
this definition the quality of a statistical output includes the following components: relevance, 
accuracy and reliability, timeliness and punctuality, comparability and coherence, accessibility and 
clarity. Each quality component consists of several sub-components and is shortly explained at the 
start of the respective section in this report (1). 

The individual country quality reports that were delivered to Eurostat during summer 2017 constitute 
the main source for the present report. Other sources that have been used or consulted are 
additional metadata provided to Eurostat from countries, national quality reports from previous years, 
websites of the individual National Statistical Institutes (NSIs), the LFS datasets for 2016 and the 
reference metadata on the data sets disseminated by Eurostat. 

The present quality report closely follows the standard Quality Report format that has been 
developed within Eurostat. In many instances, however, it is impossible to present the data exactly 
as required by the standard Eurostat format, as this is targeted to report homogeneous production 
processes within each country and the EU-LFS is the result of the collection of national data sets 
from the NSIs. Information from the individual countries was in some cases not sufficient to provide a 
comprehensive summary.  

The last chapter of the present report covers the regional aspects of the EU-LFS and has been 
written jointly by the units within Eurostat dealing with labour market and regional statistics.  

This quality report complements the statistical report describing the characteristics of the national 
surveys in the Member States, Candidate Countries and the EFTA countries, also available on the 
Eurostat website (2).  

Eurostat wishes to thank all experts in the countries participating in conducting the EU-LFS and 
providing the data and descriptions as well as their support necessary for compiling this report.  

(1)  Most of the introductory texts shortly explaining each quality component are taken from the ‘ESS Standard for Quality Reports’, 

available at: http://ec.europa.eu/eurostat/documents/3859598/5909785/KS-RA-08-015-EN.PDF 

(2)  Available at: http://ec.europa.eu/eurostat/en/web/products-statistical-reports/-/KS-TF-18-002 

Quality report of the European Union Labour Force Survey 2016 

5 

 
 
 
 
 
 
 
 
                                                           
 
 
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

2 Overview of designs and 

methods of the EU-LFS in 
2016 

2.1  Coverage 

This document covers all the thirty-three countries (participating countries) providing Eurostat with 
micro-data from their labour force surveys in 2016: the 28 Member States of the European Union, 
three EFTA countries (Iceland, Norway and Switzerland), and two candidate countries, i.e. the 
Former Yugoslav Republic of Macedonia (3) and Turkey. All the territories of participating countries 
are covered, except for Cyprus which only covers the areas under the control of the government of 
the Republic of Cyprus. Since 2014, also the French overseas departments are covered 
(Guadeloupe, Martinique, Guyane, La Réunion), with the exception of Mayotte (4).  

The EU-LFS covers persons in private households. However, in several countries also members of 
collective households are sampled, either directly (register based sampling frames) or indirectly 
through their relationship with the sampled household.  

The population interviewed about the employment status is 15 years and more for all participating 
countries, with the exception of Spain, Italy and the United Kingdom (which interview people aged 16 
and more) as well as Denmark, Estonia, Latvia, Hungary, Finland, Sweden and Norway (people 
aged 15-74), Iceland (people aged 16-74) and the Former Yugoslav Republic of Macedonia (people 
aged 15-79).  

2.2  Legal basis 

The EU-LFS is based on European legislation since 1973. The principal legal act is the Council 
Regulation (EC) No 577/98. The regulations are an important element assuring the quality of the EU-
LFS. They stipulate rules and guidelines to assure the comparability of the results by regulating the 
survey designs, the survey characteristics and the methodology of the EU-LFS. A detailed overview 
of the EU-LFS regulations is published in Statistics Explained at ‘EU-LFS – main features and legal 
basis’ (5). 

(3) 

In some tables of this report the abbreviation MK is used for the Former Yugoslav Republic of Macedonia. This is a provisional code 
which does not prejudice in any way the definitive nomenclature for this country, which will be agreed following the conclusions of 
negotiations currently taking place on this subject at the United Nations. 

(4)  Until 2014 the French overseas departments (Département d'outre-mer – DOM) only had a partial coverage over time, as data 
collection only referred to quarter 2. In Mayotte this is still the case and 2016 data for this department is still not included in the 
standard French datasets. 

(5)  https://ec.europa.eu/eurostat/statistics-

explained/index.php/EU_labour_force_survey_%E2%80%93_main_features_and_legal_basis 

Quality report of the European Union Labour Force Survey 2016 

6 

 
 
 
 
                                                           
 
 
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

In addition to European regulations, many participating countries have their own national legislation 
for the conduct of a labour force survey. Detailed information on the national laws or regulations is 
not collected for this report. 

The participation in the EU-LFS is compulsory in fourteen participating countries (Belgium, Germany, 
Greece, Spain, France, Italy, Cyprus, Luxembourg, Malta, Austria, Portugal, Slovakia, Norway and 
Turkey), and voluntary in the other countries. 

2.3  Reference period 

The EU-LFS is designed as a continuous quarterly survey with interviews spread uniformly over all 
weeks of a quarter. Each reference week starts on Monday and ends on Sunday. The first week of a 
year or quarter is defined as the week that includes the first Thursday of the year or the quarter. All 
countries conduct the LFS as a continuous survey. 

All participating countries in the EU-LFS produce quarterly and annual estimates (6). 

2.4  Sampling designs 

The sampling designs applied in the EU-LFS are very varied. Most NSIs use some kind of multi-
staged stratified random sample design, especially those that do not have central population 
registers available. 
Bases used for the sample 
Population registers and the latest population census or list of addresses used in that census are the 
two main sources for the sampling frame; other sources include registers of dwellings or lists of 
addresses from, e.g., the postal authorities or utility databases. Belgium, Italy, Lithuania, 
Luxembourg, Austria, Slovenia, Finland, Sweden, Iceland, Norway and Switzerland use the 
population registers as the sole basis while the Netherlands complete this information with postal 
data, Denmark and Latvia with other registers and Spain with census information. Germany grounds 
the sample frame on the 2011 census integrated with information from the register of new dwellings. 
France uses the tax register for Metropolitan France and the annual population census for the 
overseas departments. Poland uses a statistical sampling frame for social surveys based on 
information coming from administrative sources, regarding persons residing at a given address. In 
the United Kingdom the survey base is represented by the Royal Mail's PAF (Postcode Address 
File), a database of all addresses receiving mail, the telephone directories in the far north of Scotland 
and the Rating and Valuation Lists (which serves for the administration of land taxes) in Northern 
Ireland. 
Sampling stages and primary sampling units (PSU) 
Denmark, Germany, Estonia, Cyprus, Lithuania, Luxembourg, Malta, Austria, Slovenia, Finland, 
Sweden, the United Kingdom, Iceland, Norway and Switzerland use a single stage sampling or 
single stage cluster sampling design. All other countries use a two or three stage sampling design, 
usually selecting municipalities, administrative districts or census enumeration areas in the first 
stage. 

(6)   Under Regulation (EC) No 577/98 a specific set of variables, referred to as structural variables, need to be surveyed only as annual 

averages with reference to 52 weeks rather than as quarterly averages (see section 2.8). 

Quality report of the European Union Labour Force Survey 2016 

7 

 
 
 
                                                           
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

Final sampling units 
Three types of final sampling units are employed: 1) households, 2) dwellings/addresses and 3) 
persons. Germany and France sample clusters of dwelling units. In samples of dwellings or 
addresses usually all persons, and thus all households, residing within the dwelling/address are 
interviewed. When persons constitute the primary sampling units, the selected persons either 
constitute the final sample (Denmark, Finland, Sweden, Iceland, and Switzerland) or the sampled 
persons lead to a final sample comprised of the sampling units and their household members 
(Estonia, Lithuania, Luxembourg). 
Overall sampling rate 
The theoretical sampling rate (in % of final sampling units), for all participating countries, per quarter 
of the EU-LFS is 0.39% (EU-28: 0.41%). Malta (1.9%) has the highest sampling rate per quarter 
followed by Iceland (1.7%) and Luxembourg (1.6%), while most other participating countries have 
sampling rates of 1% or less. On average, the achieved quarterly sample in 2016 in all participating 
countries is 1.718 million individuals (EU-28: 1.523 million), of which 1.318 million are in the age 
group 15–74 years (EU-28: 1.168 million). The achieved sample in the EU-LFS is thus approximately 
0.29% of the total population.  
Stratification 
All countries, except Lithuania, Luxembourg, Malta and Iceland, stratify the sample frame prior to the 
sampling. All countries but Denmark use the region, either at NUTS 2, NUTS 3, and NUTS 4 level or 
nationally defined areas, as stratification variable. The degree of urbanization or the classification in 
‘urban/rural area’ is also a common stratification variable. Other stratification variables concerning 
information about the characteristics (size, type) of the primary sampling units are also considered in 
some countries.  

2.5  Rotation schemes 

All participating countries except Belgium use a rotating panel design for the samples. The number of 
panels (waves) ranges from two to eight. All panel designs include an overlap between one quarter 
and the successive one, except for Germany, which only has a year-to-year overlap. The most 
common panel design with a quarterly overlap in 2016, adopted by 13 participating countries, is 2-
(2)-2, where sampled units are interviewed for two consecutive quarters, than stay out of the sample 
for the next two quarters and are included again two more times afterwards. Other widespread 
rotation patterns are in for 5 and in for 6 waves, used respectively in seven and six countries, where 
each panel is interviewed consecutively for five or six quarters before permanently leaving the 
sample. Three other rotation schemes are used by one or maximum two countries.  

Depending on national priorities with regard to the desired precision of change estimates, levels or 
annual averages, the number of waves and skip patterns lead to different percentages of overlapping 
population between two successive quarters or between the same quarters in two successive years. 
All panel designs, with a quarter-to-quarter overlap, result in an overlap of 50% or more (7) of the 
sample between two successive quarters. There is less emphasis on the overlap between 
corresponding quarters in two successive years. Belgium has no overlap; seven countries have an 
overlap of 20% while most other countries have an overlap ranging from 33% to 50%. Germany has 
75% overlap with the previous year.  

(7)  These percentages are only theoretical; the actual overlaps may be lower due to non-response and panel attrition. 

Quality report of the European Union Labour Force Survey 2016 

8 

 
 
 
                                                           
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

2.6  Calculation of weighting factors 

Council Regulation (EC) No 577/98 on the EU-LFS stipulates that weighting factors should take into 
account ‘in particular the probability of selection and external data relating to the distribution of the 
population being surveyed, by sex, age (five-year age groups) and region (NUTS 2 level), where 
such external data are held to be sufficiently reliable by the Member States concerned’ (Article 3(5)). 

The methods of calculating the weights differ considerably between countries. Two main methods 
are used, depending on the detail of the external information and whether or not this external 
information can be cross-tabulated: 1) post-stratification where the inverse of the selection 
probabilities are adjusted a posteriori to the population’s distribution by sex, age groups and other 
external (administrative) sources, and 2) calibration which consist in different variations of adjusting 
to marginal totals. Most of the countries adjust for non-response either directly in the weighting 
process or in a preliminary step before adjusting the weights to external sources. 

Due to the complexity and number of factors taken into account in some of the weighting 
calculations, the requirement of the Regulation to use five-year age groups is not implemented in all 
countries. Almost all countries adjust the weighting factors to regional levels. These regions may, 
however, not necessarily correspond to the NUTS 2 regional classification. 

All countries use data on sex in the weighting process. Almost all countries use five-year age groups, 
for people aged between 15 and 74, in calculating the weighting factors: exceptions are Germany, 
Greece, and Slovenia who use broader age groups than five-year ones (8). All countries that have 
NUTS 2 regions defined use at least NUTS 2 regions for calculating the weights, but twenty-two 
countries (Bulgaria, the Czech Republic, Germany, Estonia, Ireland, Spain, Croatia, Italy, Latvia, 
Lithuania, Hungary, Malta, the Netherlands, Portugal, Slovenia, Slovakia, Finland, Sweden, the 
United Kingdom, Norway, Switzerland and the Former Yugoslav Republic of Macedonia) use a more 
detailed regional classification (NUTS 3 or LAU; groups of NUTS 3). 

Denmark, Latvia, the Netherlands, Austria, Finland, Sweden, Norway and Switzerland use register 
statistics on employment and/or unemployment directly for weighting. In other countries, different 
external distributions or sources are frequently used both for weighting and stratification, such as 
urban/rural distinction, nationality, ethnicity, and size classes of regions or local areas. 

Thirteen countries, namely Belgium, the Czech Republic, Germany, Estonia, Ireland, Portugal, 
Romania, Slovenia, Slovakia, Finland, Sweden, Iceland and Norway, gross the sample to the total 
population, i.e. including people living in institutional households, although some of them do not 
(Belgium, the Czech Republic, Ireland and Slovenia) or only partially (Portugal, Romania, and 
Slovakia) cover the institutional population in data collection. 

2.7  Data collection methods 

The EU-LFS data collection is carried out through mainly four modes: personal visits, telephone 
interviews, web interviews and self-administered questionnaires. 

Most countries conduct the interview only with computerised questionnaires. Six (Germany, Greece, 
Malta, Poland, Slovakia and the Former Yugoslav Republic of Macedonia) use both computerised 
and paper questionnaires and two countries (Bulgaria and Romania) rely solely on paper 
questionnaires. 

As described above, all countries but Belgium interview responding units several times: about half of 
the countries (the Czech Republic, Estonia, Spain, France, Croatia, Italy, Cyprus, Latvia, Hungary, 

(8)   The Czech Republic, Denmark, Spain, Luxembourg, Poland, and Turkey use the five-year age groups up to the 60–64 years old. 

Quality report of the European Union Labour Force Survey 2016 

9 

 
 
 
                                                           
 
 
Overview of designs and methods of the EU-LFS in 2016 

Labour Force Survey 

2 

Malta, Austria, Poland, Portugal, Slovenia, Slovakia and the United Kingdom) conduct the first 
interview always or mainly via CAPI while in subsequent waves the interviews are performed by 
CATI, if a telephone contact is available. Germany collects data mainly with face-to-face interviews 
(using CAPI); persons not available for the interview or refusing oral interviews are in a few cases 
interviewed by telephone or more frequently fill in self-administered questionnaires. Belgium 
conducts the interviews by CAPI, but in households of retired persons, interviews can be conducted 
by telephone. Denmark, Lithuania, Luxembourg and the Netherlands use computer assisted web 
interviews (CAWI) in combination with other methods. Five countries (Finland, Sweden, Iceland, 
Norway and Switzerland) rely solely on telephone interviews. Four countries (Bulgaria, Ireland, 
Romania and Turkey) collect data using only face-to-face interviews.  

2.8  Use of subsamples to survey structural 
variables 

In 2016, ten countries (Bulgaria, the Czech Republic, Spain, France, Luxembourg, the Netherlands, 
Finland, the United Kingdom, Norway and Switzerland) use a subsample to survey all or some of the 
thirty-nine structural variables, taking advantage of this option offered by Regulation (EC) No 
2257/2003. The subsample coincides with one rotation panel in the total sample, except for Norway, 
which uses both the first and the last survey waves, and Switzerland, which uses the first and the 
third wave.   

Regulation (EC) No 377/2008 stipulates that the estimates produced from the yearly subsample 
should be consistent with those obtained as annual averages of the full quarterly samples, at least as 
regards the ILO labour force status broken down by sex and 10-year age groups. This requirement 
aims at ensuring the consistency of the main indicators (e.g. the employment or the unemployment 
rates) and their break-downs produced from the two different databases.  

Quality report of the European Union Labour Force Survey 2016 

10 

 
 
 
 
 
 
 
Relevance 

3 

3 Relevance 

3.1  Definition  

Relevance is an attribute of statistics measuring the degree to which statistical information 
meets current and potential needs of the users.  

It depends on whether all statistics that are needed are produced and the extent to which concepts 
used (definitions, classifications etc.) reflect user needs. It can be assessed by analyzing the 
different users, who they are, what needs they have, whether they are satisfied, etc.  

Most EU statistics are compiled according to regulations containing a defined list of variables, which 
reflect in particular the most relevant institutional users' needs. If certain variables required by the 
regulation are not covered, the statistics are incomplete. Hence, lack of completeness affects the 
relevance of the statistics provided. 

3.2  The users 

Eurostat does not carry out regular satisfaction surveys targeted only at users of labour market 
statistics but a general Eurostat User Satisfaction Survey is carried out every year to collect feedback 
on the quality of its statistics 9).The survey is usually addressed to the registered Eurostat users who 
are mainly students, academic, private users, business government and international organizations. 
According to the results of the 2016 User Satisfaction Survey, 62.0% of the users express a "very 
good/good" judgement of the statistics provided by Eurostat. 

In 2011, Eurostat carried out a LFS Rolling Review through its Quality Assurance Framework which 
included a user survey.  Most users stressed the importance of the EU-LFS results. The results were 
acknowledged as essential both for the European Commission and its agencies and for international 
organisations. The EU-LFS data are equally important or even essential for users from universities, 
research institutes and businesses. Moreover in 2015 the EU-LFS was subject of an assessment by 
the European Commission concerning its relevance in supporting European Union policies (10). 

For major topics of interest not covered by the standard EU-LFS, the instrument of ad hoc modules 
has proven to be useful and flexible. 

Some users, seek for more timely data releases, at least for few main indicators. The availability of a 
release calendar for the main indicators produced by the EU-LFS, even with conservative delays, 
has been favourably received by users.  

(9) 

http://ec.europa.eu/eurostat/web/quality/general-evaluation-results 

(10)   http://ec.europa.eu/eurostat/c/portal/layout?p_l_id=64257&p_v_l_s_g_id=0 

Quality report of the European Union Labour Force Survey 2016 

11 

 
 
 
 
 
                                                           
 
 
 
 
Relevance 

3 

3.3  Completeness 

All Member States of the EU provide quarterly and annual results.  

Although adhering to the EU-regulations on the EU-LFS, countries do not always provide data for all 
the variables. The reason can be for example the (temporary) inability to implement a variable in the 
national questionnaire or because of insufficient time for testing a required change.  

Structural variables may be collected and transmitted for an annual sub-sample only (see section. 
2.8). Household data is another special case. In line with the provisions of Council Regulation 
577/98, Denmark, Luxembourg, Finland and Sweden provide data for complete households only for 
an annual sub-sample of their normal samples of individuals. Norway only covers family members of 
working age, but e.g. no children below 15 yet. Iceland does not send any data for households, while 
Switzerland has a general derogation in that respect.   

A country by country and variable by variable analysis of the situation is provided in the Annex. 
Tables 3.1 and 3.2 below summarize the completeness of data. 

Table 3.1: Completeness of the EU-LFS variables, 2014 - 2016 

Number of 
compulsory 
variables with 
100 % item non-
response (¹) 

0 

1-4 

5-9 

10+ 

2016 

20 

10 

3 

0 

Number of participating countries 

Of which: 
EU-28 
Member 
States 

2015 

Of which: 
EU-28 
Member 
States 

2014 

Of which: 
EU-28 
Member 
States 

19 

8 

1 

0 

26 

25 

24 

23 

6 

1 

0 

2 

1 

0 

6 

3 

0 

4 

1 

0 

Total 
(¹)   The variable INCDECIL is not included. The INCDECIL data may be forwarded to Eurostat within twenty-one 

33 

33 

28 

33 

28 

28 

months after the end of the reference period. 

Quality report of the European Union Labour Force Survey 2016 

12 

 
 
 
 
 
 
 
 
 
Relevance 

3 

Table 3.2: Compulsory EU-LFS variables having one or more country returning 
100% non-response or constant value (¹), 2016 

Column 
number (²) 

Brief description 

Number of 
countries 

Of which: 
EU-28 

Col_003 
Col_017/18 
Col_023 
Col_028 
Col_039/40 
Col_055 

Col_067/68 

Col_073/74 
Col_093 

Col_094/95 
Col_096/98 
Col_101 
Col_102 
Col_103 

Col_104 
Col_105 
Col_106 

Col_107 

Col_108 
Col_109 
Col_110 
Col_111 
Col_112 

Col_113 

Col_114 
Col_115 

Col_118 

Col_119 
Col_121 

Col_146 
Col_150/151 

Relationship to reference person in the 
household 
Nationality 
Nature of participation in the survey 
Continuing receipt of the wage or salary 
Country of place of work 
Contract with a temporary employment agency 
Unpaid overtime in the reference week in the 
main job 
Number of hours that the person would like to 
work in total 
Professional status in last job 
Economic activity of the local unit in which 
person last worked 
Occupation of last job 
Type of employment sought  
Duration of search for employment  
Contacted public employment to find work  
Contacted private employment agency to find 
work  
Applied to employers directly  
Asked friends, relatives, trade unions etc.  
Inserted or answered advertisements in 
newspapers or journals  
Studied advertisements in newspapers or 
journals  
Took a test, interview or examination  
Looked for land, premises or equipment  
Looked for permits, licenses, financial resources  
Awaiting the results of an application for a job  
Waiting for a call from a public employment 
office  
Awaiting the results of a competition for 
recruitment to the public sector  
Other method used  

Reasons for not being available to start working 
within 2 weeks 
Situation immediately before person started to 
seek employment (or was waiting for new job to 
start) 
Registration at a public employment office 
Situation with regard to activity one year before 
survey 
Country of residence one year before survey 
Region of residence (within Member State) one 
year before survey 
Degree of urbanisation 
Sequence number of the survey wave 
Level of this education or training 

1 
1 
1 
1 
4 
1 

1 

1 
1 

1 
1 
2 
1 
1 

3 
1 
1 

1 

2 
2 
15 
13 
5 

8 

17 
8 

2 

1 
2 

1 
2 

1 
0 
1 
1 
1 
0 

0 

0 
1 

0 
0 
1 
0 
0 

1 
0 
0 

0 

0 
1 
12 
9 
4 

4 

12 
6 

1 

1 
1 

1 
1 

Col_152/153 
Col_168 
Col_195 
Col_209 
(¹)   Excluding variables which are constant by default such as country, reference year, region (if NUTS 2 is the whole 
country). The variable INCDECIL is not included. The INCDECIL data may be forwarded to Eurostat within twenty-
one months after the end of the reference period. 

7 
2 
2 
1 

5 
0 
2 
0 

(²)   According to Commission Regulation (EC) No 377/2008.

Quality report of the European Union Labour Force Survey 2016 

13 

 
 
 
 
Timeliness and punctuality 

5 

4 Accuracy 

4.1  Definition  

The accuracy of statistical outputs in the general statistical sense is the degree of closeness 
of computations or estimates to the exact or true values that the statistics were intended to 
measure.  

Statistics can be different from the true values because of random variability (the statistics change 
from one to another implementation of the survey due to random effects) and/or bias (the average of 
possible values of the statistics is different from the true value due to systematic effects). 

Several types of error, stemming from all survey processes, contribute to the error of the statistics 
(their bias and variability). A certain typology of errors is widely adopted in statistics. Sampling errors 
affect only sample surveys; they are due to the fact that only a subset of the population, usually 
randomly selected, is surveyed. Non-sampling errors affect sample surveys and complete 
enumerations alike and comprise: 1. Coverage errors; 2. Measurement errors; 3. Non-response 
errors; 4. Processing errors. 

4.2  Sampling errors 

Sampling errors affect only sample surveys and arise because not all units of the frame population 
are surveyed. The frame is a device that permits access to population units, such as a list of 
households with addresses. The sampling frame is the reference list(s) from which the sample (e.g. 
individuals, households, addresses or dwellings) is drawn. Official surveys, like the EU-LFS, use 
probability sampling. This makes it possible to quantify the sampling errors which can be expressed 
in terms of confidence intervals. Tables 4.1a and 4.1b provide the estimates and 95% confidence 
limits for the annual results 2016 reached for seven main indicators. For example, interval 214 411 – 
215 015 covers the true value of employed persons at the aggregated EU-28 level with a 95% 
probability.   

Quality report of the European Union Labour Force Survey 2016 

14 

 
 
 
 
 
 
 
 
 
 
Timeliness and punctuality 

5 

Table 4.1a: Confidence limits(1) for employment variables, annual average 2016 
Employment 
rate as a 
percentage of 
the population 
(age group 20-
64) (%) 

Number of part-
time employed 
persons (age 
group 20-64)  
(x1000) 

Average actual 
hours of work 
per week (age 
group 20-64)(²)  
(Hrs.) 

Number of 
employed (age 
group 20-64) 
(x1000) 

214 713 ±302 
4 508 ±25 
2 943 ±59 
4 995 ±27 
2 575 ±10 
39 068 ±100 
 606 ±12 
1 913 ±12 
3 597 ±74 
18 087 ±  96 
25 874 ±122 
1 549 ±66 
22 158 ±83 
 352 ±  5 
 857 ±  5 
1 309 ±37 
 257 ±  7 
4 285 ±23 
 184 ±  3 
7 693 ±23 
3 998 ±13 
15 821 ±74 
4 337 ±35 
8 078 ±139 
 894 ±14 
2 460 ±17 
2 314 ±14 
4 616 ±15 
29 389 ±75 
 167 ±  1 
2 440 ±10 
4 204 ±16 

EU-28 
Belgium 
Bulgaria 
Czech Republic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United Kingdom 
Iceland 
Norway 
Switzerland 
Former Yugoslav 
Republic of 
Macedonia 
Turkey 
(1)  The confidence limits at 95% level of significance. 
(2)  By people who worked at least one hour in the reference week. The hours are calculated as the sum of actual hours 

40 550 ±164 
1 102 ±20 
 57 ±  6 
 279 ±13 
 573 ±11 
10 452 ±61 
 57 ±  5 
 399 ±  7 
 349 ±18 
2 696 ±52 
4 694 ±84 
 86 ±  9 
4 097 ±58 
 47 ±  3 
 71 ±  4 
 92 ±10 
 48 ±  3 
 204 ±10 
 24 ±  1 
3 583 ±27 
1 127 ±17 
 984 ±32 
 399 ±18 
 579 ±41 
 79 ±  4 
 141 ±  8 
 311 ±  9 
1 041 ±17 
6 979 ±63 
 35 ±  2 
 581 ±16 
1 598 ±22 

71.0 ±0.1 
67.7 ±0.4 
67.7 ±1.4 
76.7 ±0.8 
77.4 ±0.3 
78.6 ±0.1 
76.6 ±1.0 
70.3 ±0.4 
56.2 ±0.6 
63.9 ±0.3 
70.0 ±0.3 
61.4 ±1.1 
61.6 ±0.2 
68.7 ±1.0 
73.2 ±0.4 
75.2 ±1.2 
70.7 ±1.2 
71.5 ±0.4 
69.6 ±1.0 
77.1 ±0.2 
74.8 ±0.2 
69.3 ±0.1 
70.6 ±0.6 
66.3 ±0.8 
70.1 ±0.7 
69.8 ±0.5 
73.4 ±0.4 
81.2 ±0.3 
77.5 ±0.2 
87.8 ±0.7 
78.6 ±0.3 
82.0 ±0.3 

37.3 ±0.0 
37.5 ±0.2 
40.3 ±0.1 
39.8 ±0.1 
35.9 ±0.1 
36.0 ±0.1 
39.0 ±0.3 
36.3 ±0.1 
41.2 ±0.2 
37.4 ±0.1 
36.6 ±0.1 
38.7 ±0.3 
36.7 ±0.1 
38.4 ±0.3 
39.6 ±0.2 
39.1 ±0.4 
38.1 ±0.4 
39.2 ±0.1 
38.7 ±0.3 
34.0 ±0.2 
36.0 ±0.1 
40.8 ±0.1 
39.1 ±0.8 
39.5 ±0.2 
39.2 ±0.2 
39.0 ±0.1 
37.0 ±0.1 
36.9 ±0.1 
36.9 ±0.1 
41.4 ±0.4 
35.3 ±0.2 
37.6 ±0.1 

 708 ±25 
24 981 ±277 

 31 ±  3 
2 234 ±60 

53.3 ±1.1 
54.4 ±0.3 

41.6 ±0.3 
46.8 ±0.1 

in the main and second job.  

Note: Confidence limits for the EU aggregates are Eurostat’s own approximation. 

Quality report of the European Union Labour Force Survey 2016 

15 

 
 
 
 
 
  
 
Timeliness and punctuality 

5 

Table 4.1b: Confidence limits(1) for unemployment variables, annual average, 
2016 

Number of unemployed 
persons (age group 15-
74) (x1000) 

Unemployment rate as 
a percentage of labour 
force (age group 15-74) 
(%) 

Youth unemployment 
rate as a percentage of 
labour force (age group 
15-24) (%) 

20 919 ±147 
 390 ±13 
 247 ±16 
 211 ±11 
 187 ±  6 
1 774 ±32 
 47 ±  4 
 173 ±  5 
1 131 ±38 
4 481 ±79 
2 972 ±70 
 240 ±18 
3 012 ±50 
 54 ±  3 
 95 ±  4 
 116 ±12 
 17 ±  2 
 235 ±12 
 9 ±  1 
 539 ±13 
 270 ±  8 
1 063 ±35 
 573 ±22 
 530 ±30 
 80 ±  5 
 267 ±10 
 237 ±  7 
 369 ±  8 
1 599 ±36 
 6 ±  1 
 129 ±  7 
 238 ±10 

EU-28 
Belgium 
Bulgaria 
Czech Republic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United Kingdom 
Iceland 
Norway 
Switzerland 
Former Yugoslav 
Republic of 
Macedonia 
Turkey 
 (1)  The confidence limits at 95% level of significance. 
Note: Confidence limits for the EU aggregates are Eurostat’s own approximation. 

8.9 ±0.1 
7.8 ±0.3 
7.6 ±0.5 
4.0 ±0.2 
6.2 ±0.2 
4.1 ±0.1 
6.8 ±0.6 
7.9 ±0.2 
23.5 ±0.6 
19.6 ±0.3 
10.1 ±0.2 
13.1 ±0.8 
11.7 ±0.2 
13.0 ±0.8 
9.6 ±0.4 
7.9 ±0.8 
6.3 ±0.8 
5.1 ±0.3 
4.7 ±0.4 
6.0 ±0.1 
6.0 ±0.2 
6.2 ±0.2 
11.1 ±0.4 
5.9 ±0.4 
8.0 ±0.5 
9.7 ±0.4 
8.8 ±0.2 
7.0 ±0.2 
4.8 ±0.1 
3.0 ±0.3 
4.7 ±0.2 
4.9 ±0.2 

 225 ±13 
3 308 ±83 

23.7 ±1.7 
10.8 ±0.3 

18.7 ±0.3 
20.1 ±1.5 
17.2 ±2.2 
10.5 ±1.1 
12.0 ±0.7 
7.1 ±0.3 
13.4 ±2.8 
17.2 ±1.0 
47.3 ±2.5 
44.4 ±1.4 
24.6 ±0.9 
31.3 ±3.2 
37.8 ±1.0 
29.1 ±4.1 
17.3 ±1.7 
14.5 ±4.2 
18.9 ±4.1 
12.9 ±1.0 
11.0 ±1.7 
10.8 ±0.4 
11.3 ±0.7 
17.7 ±1.1 
28.0 ±2.7 
20.6 ±2.3 
15.2 ±2.5 
22.2 ±1.7 
20.2 ±1.1 
18.9 ±0.8 
13.0 ±0.5 
6.5 ±1.2 
11.2 ±0.8 
8.6 ±0.7 

48.2 ±3.6 
19.5 ±0.7 

Quality report of the European Union Labour Force Survey 2016 

16 

 
 
 
 
 
  
 
 
Timeliness and punctuality 

5 

4.3  Non-sampling errors 

Coverage errors 

Coverage errors (or frame errors) are due to divergences between the target population and the 
frame population. 

Table 4.2: Frame quality, coverage rates and methodological notes, 2016 

Under-coverage 

Over-coverage 

Misclassification 

Belgium 

Bulgaria 

Czech Republic 

Denmark 

Germany 

Estonia 

Ireland 

Greece 

Spain 

France 

Croatia 

Italy 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 
Netherlands 

Austria 

Poland 

Portugal 

Romania 

Slovenia 

Slovakia 

Finland 

Sweden 

United Kingdom 
Iceland 

Norway 

Switzerland 

X 

X 

X 

- 

X 

X 

X 

X 

X 

negligible 

X 

X 

X 

X 

X 

X 

negligible 

X 
- 

X 

X 

X 

X 

X 

X 

negligible 

X 

X 
- 

X 

- 

negligible 

negligible 

X 

X 

- 

X 

- 

X 

X 

X 

- 

X 

X 

- 

X 

X 

negligible 

X 

X 
- 

- 

X 

X 

X 

X 

X 

X 

X 

X 
- 

- 

- 

X 

X 

- 

X 

- 

X 

X 

- 

- 

- 

X 

X 

X 

X 

X 

X 

- 
- 

- 

X 

- 

- 

- 

negligible 

X 

X 

X 
- 

X 

negligible 

Former Yugoslav 
Republic of Macedonia 
Turkey 
Notes:  (x) indicates the presence of the coverage error; (-) indicates that information has not been provided by the 

X 

X 

X 

X 

X 

X 

country. 

Quality report of the European Union Labour Force Survey 2016 

17 

 
 
 
 
 
 
  
 
Timeliness and punctuality 

5 

Possible divergence types are: 

  Under-coverage: the frame population does not include all units of the target population. 

  Over-coverage: the frame population includes units which do not belong to the target 

population. 

  Misclassification: units in the frame population which belong to the target population but are 

wrongly classified. 

Table 4.2 summarises the information on coverage errors given by the participating countries. For 
more details see Table 10.1 in the Annex.  

Measurement errors 

Measurement errors are errors that occur during data collection and cause recorded values of 
variables to be different from the true ones. 

Their causes are commonly categorized as: 

  Survey instrument: the form, questionnaire or measuring device used for data collection may 

lead to the recording of wrong values. 

  Respondent: respondents may, consciously or unconsciously, give erroneous information. 

 

Interviewer: interviewers may influence the answers given by respondents. 

  Measurement errors may cause both bias and extra variability of statistical outputs. 

One part of the respondent measurement error can be represented by the level of proxy interviews 
which are interviews where a person (the proxy) answers questions on behalf of another person. The 
proxy is generally a household member of the person from whom information is being sought. Table 
4.3 below shows the reported information related to measurement errors as the number of proxy 
interviews and their evolution in the recent years. The proxy rate shows a trend quite stable over the 
years and around the amount of 30% of total interviews with huge differences among the countries. 
In 2016, in five countries (Ireland, Spain, Croatia, Slovakia and the Former Yugoslav Republic of 
Macedonia) the proxy rate exceeds 50%, while in seven further countries it is more than 40%. On the 
other hand in six countries (Denmark, Luxembourg, Finland, Sweden, Iceland and Switzerland) the 
proxy rate is under 10%; in all of these countries the sampling unit is the individual and the need to 
directly contact the selected person in the sample leads to a lower proxy rate. 

Table 4.4 shows the main methods adopted by the countries to reduce the measurement error. 
Almost all countries provide training to the interviewers on the contents and possible changes of the 
survey compared to previous exercise (31 countries) and send an introduction letter for the survey in 
advance to the sampled units (30 countries). Less widespread but still used by half of the countries 
are phone calls for booking or introducing the survey (15 countries) or monitoring directly the survey 
by listening to the interviews (18 countries). 

For a detailed picture by country see Table 10.2 in Annex. 

Quality report of the European Union Labour Force Survey 2016 

18 

 
 
 
 
 
 
 
 
Timeliness and punctuality 

5 

Table 4.3: Share of proxy interviews (people aged 15-74), 2012 - 2016 

2016 

2015 

2014 

2013 

2012 

EU-28 
Belgium 
Bulgaria 
Czech 
Republic 
Denmark 

Germany 

Estonia 
Ireland 
Greece 
Spain(1) 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg(2) 
Hungary 
Malta 
Netherlands 
Austria 
Poland 

Portugal 

Romania 
Slovenia 
Slovakia 
Finland 

Sweden 

29.8 
17.8 
33.0 

42.3 

5.0 

23.9 

36.8 
50.2 
41.1 
51.8 
26.6 
52.3 
20.3 
34.5 
39.7 
35.8 
41.8 
42.6 
48.3 
45.5 
24.3 
37.2 

48.3 

22.2 
49.7 
51.1 
4.1 

3.1 

30.0 
17.8 
33.8 

44.1 

5.8 

25.6 

35.7 
50.3 
41.2 
52.2 
27.9 
48.0 
19.0 
33.6 
39.4 
34.5 
23.2 
42.7 
49.2 
46.2 
23.2 
37.8 

47.9 

24.6 
53.4 
50.4 
4.2 

2.7 

30.2 
19.0 
33.7 

44.6 

4.8 

26.0 

36.4 
50.5 
41.4 
52.5 
27.8 
46.3 
18.0 
32.5 
37.9 
34.5 
39.8 
44.0 
49.8 
46.5 
25.2 
40.0 

47.7 

25.8 
55.6 
49.8 
4.1 

2.6 

30.4 
19.8 
36.0 

45.8 

5.0 

25.7 

32.6 
49.8 
41.9 
52.5 
28.2 
47.9 
17.7 
31.2 
37.0 
32.4 
37.3 
45.4 
50.7 
46.4 
24.0 
40.7 

48.3 

28.3 
55.7 
46.4 
4.0 

2.6 

35.0 

34.9 

35.5 

0.8 
17.2 
3.0 

United 
Kingdom(1) 
Iceland(1) 
Norway 
Switzerland 
Former 
Yugoslav 
Republic of 
Macedonia 
Turkey 
 (1) Respondents aged 16–74 years. 
 (2) In 2015 the Luxembourgish LFS became an individual survey. No proxies are allowed. 

0.3 
16.7 
1.9 

0.9 
16.5 
2.7 

54.5 

20.9 

54.2 

11.6 

50.8 

13.9 

35.3 

0.2 
15.6 
1.8 

55.3 

33.6 

30.4 
20.7 
35.3 

45.9 

5.4 

25.9 

32.0 
48.3 
41.0 
52.7 
31.4 
46.1 
16.0 
32.4 
33.3 
31.6 
43.8 
44.4 
51.2 
48.8 
23.8 
40.9 

48.7 

27.9 
54.4 
44.0 
3.9 

2.7 

35.0 

2.4 
14.3 
1.7 

52.2 

38.0 

Quality report of the European Union Labour Force Survey 2016 

19 

 
 
 
 
 
  
 
 
 
 
 
 
 
Table 4.4: Methods used for reducing measurement errors, 2016 

Timeliness and punctuality 

5 

Methods 

Respondent 

Letter introducing the survey 

Phone call for booking or 
introducing the survey 

Interviewer 

Periodical training (at least one 
time per year) 
Feedbacks from the interviewer 
(reports, debriefings, etc.) 

Fieldwork 

Monitoring directly contacting  
the respondents 
Monitoring directly listening 
interviews 
Monitoring remotely by 
indicators 

Questionnaire 

Questionnaire in different 
languages 
On-line checks(1) 

Number of participating countries 

2016 

Of which: EU-28 Member 
States 

30 

15 

31 

27 

24 

18 

21 

20 

28 

14 

26 

22 

21 

15 

19 

17 

25 
(1) In Bulgaria and Romania this item is not foreseen due to the only use of the PAPI data collection technique. 

21 

Non-response errors 

Non-response errors occur when the survey fails to get a response to one, or possibly all, of the 
questions. 

The term encompasses a wide variety of reasons for non-collection of data: impossible to contact, 
not at home, unable to answer, incapacity, refusal, inaccessible, unreturned questionnaire, etc. Non-
response could lead to a reduction in the actual size of the sample, and consequently to an increase 
in variance. This also produces a bias if the non-respondents have different characteristics from the 
respondents for the survey variables.  

There are two types of non-response: 

 

 

unit non-response which occurs when no data are collected about a population unit 
designated for data collection; 

item non-response which occurs when data only on some but not all the survey variables 
are collected about a designated population unit.  

This section only covers the issue of unit non-response while item non-response is presented 
variable by variable in the Annex (Table 10.3).  

Table 4.5 shows unit non-response rates, but they are not fully comparable across countries. Most of 
them calculate non-response on the basis of the household unit, except Denmark, Estonia, 
Luxembourg, Malta, Slovakia, Finland, Sweden, Iceland, Norway and Switzerland, which compute 
non-response at the level of individuals.  

Quality report of the European Union Labour Force Survey 2016 

20 

 
 
 
 
 
 
 
 
  
  
  
  
  
  
  
  
 
 
Timeliness and punctuality 

5 

Table 4.5: Unit non-response rate, 2012 - 2016 

2016 

2015 

2014 

2013 

2012 

Belgium 

Bulgaria 
Czech 
Republic 
Denmark 

Germany 

Estonia 

Ireland 

Greece 

Spain 

France 

Croatia 

Italy 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 

Netherlands 

Austria 

Poland 

Portugal 

Romania 

Slovenia 

Slovakia 

Finland 

Sweden 
United 
Kingdom 
Iceland 

Norway 

Switzerland 
Former 
Yugoslav 
Republic of 
Macedonia 
Turkey 

28.4 

20.3 

20.2 

52.0 

2.6 

30.2 

27.3 

25.5 

12.6 

19.3 

38.6 

13.3 

4.3 

38.0 

21.3 

47.5 

19.3 

23.1 

47.0 

5.3 

37.6 

15.8 

13.3 

21.4 

15.2 

30.4 

43.0 

44.6 

26.8 

18.4 

19.2 

15.6 

5.3 

26.7 

22.2 

20.5 

47.0 

3.4 

28.1 

25.1 

25.9 

12.4 

20.3 

30.3 

12.5 

5.4 

37.9 

20.3 

48.0 

17.2 

23.4 

45.5 

7.8 

34.9 

15.4 

12.2 

21.3 

15.2 

29.2 

40.1 

47.4 

22.7 

20.3 

18.3 

25.6 

5.2 

27.8 

23.7 

20.6 

46.2 

2.3 

31.3 

23.9 

24.6 

15.2 

20.9 

31.3 

11.8 

4.2 

35.7 

19.6 

84.6 

17.2 

23.7 

42.7 

5.7 

31.5 

14.8 

9.5 

21.3 

11.0 

28.0 

35.7 

39.8 

21.0 

19.9 

18.8 

24.6 

9.3 

28.8 

23.6 

20.4 

47.1 

2.1 

32.5 

22.9 

23.7 

15.2 

19.8 

26.2 

11.7 

2.7 

35.2 

19.0 

79.4 

18.5 

26.7 

20.6 

5.7 

28.1 

14.3 

9.4 

21.7 

8.2 

27.1 

30.8 

39.4 

19.2 

21.1 

20.4 

25.1 

9.3 

32.0 

21.5 

19.3 

47.3 

1.8 

31.8 

20.3 

25.0 

15.5 

15.3 

24.8 

10.7 

3.3 

34.4 

17.3 

71.8 

16.2 

26.7 

20.9 

6.5 

24.2 

15.4 

8.9 

23.7 

7.8 

26.1 

27.2 

43.1 

16.8 

19.5 

17.1 

18.0 

9.7 

Quality report of the European Union Labour Force Survey 2016 

21 

 
 
 
 
 
 
  
 
 
 
Timeliness and punctuality 

5 

Table 4.6 presents the non-response rate by main reasons for non-response (refusal, non-contact, 
other). The main reason for non-response for most countries is the impossibility to contact the 
sampling unit; in the Czech Republic, Croatia, the Netherlands, Poland, Slovenia, Slovakia, the 
United Kingdom and the Former Yugoslav Republic of Macedonia the main reason is the refusal to 
reply to the LFS while in Belgium, Ireland and Greece non-response is mainly due to other reasons.  

Table 4.6: Non-response by category, 2016 

Non-response rate (%) 

Total  

Refusals 

Non-contacts 

Other reasons  

Belgium 

Bulgaria 

Czech Republic 

Denmark 

Germany 

Estonia 

Ireland 

Greece 

Spain 

France 

Croatia 

Italy 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 

Netherlands 

Austria 

Poland 

Portugal 

Romania 

Slovenia 

Slovakia 

Finland 

Sweden 

United Kingdom 

Iceland 

Norway 

28.4 

20.3 

20.2 

52.0 

2.6 

30.2 

27.3 

25.5 

17.1 

19.3 

38.6 

13.3 

4.3 

38.0 

21.3 

47.5 

19.3 

23.1 

47.0 

5.3 

37.1 

15.8 

13.3 

21.4 

15.2 

30.4 

43.0 

44.6 

26.8 

18.4 

5.0 

4.3 

15.5 

6.0 

- 

13.2 
7.5 

8.0 

7.7 

3.7 

23.1 

4.7 

1.6 

9.6 
5.9 

2.9 

7.9 

1.1 

36.0 

1.3 

20.5 

2.4 

2.9 

13.0 

12.4 

18.1 

14.3 

36.4 

8.8 

1.2 

19.2 

Switzerland 
Former Yugoslav 
Republic of 
Macedonia 
Turkey 
5.3 
Notes: (-) indicates that information has not been provided by the country. 

8.7 
0.1 

15.6 

2.6 

8.6 

14.6 

4.1 

42.0 

 - 

13.1 
8.8 

7.3 

9.4 

15.0 

12.4 

7.7 

2.3 

27.1 
14.8 

39.6 

10.4 

22.0 

7.0 

4.1 

14.7 

9.9 

6.6 

2.0 

1.2 

12.1 

27.1 

8.2 

14.1 

12.7 

9.1 

4.5 
3.7 

14.9 

1.4 

0.6 

4.0 

 - 

3.9 
11.0 

10.2 

0.0 

0.6 

3.1 

0.9 

0.1 

1.3 
0.6 

4.9 

1.0 

0.0 

4.0 

0.0 

1.8 

3.4 

3.8 

6.4 

1.6 

0.3 

1.6 

0.0 

3.9 

3.6 

7.5 

2.4 
1.5 

Quality report of the European Union Labour Force Survey 2016 

22 

 
 
 
 
 
 
 
  
Timeliness and punctuality 

5 

Processing errors 

Between data collection and the beginning of statistical analysis for the production of statistics, data 
must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors 
introduced at these stages are called processing errors.  

According to national quality report information, 18 countries adopt editing and correction procedures 
to LFS data. These countries are Belgium, Bulgaria, the Czech Republic, Denmark, Ireland, Spain, 
Croatia, Italy, Latvia, Lithuania, Luxembourg, Malta, Austria, Portugal, Romania, Slovenia, Slovakia 
and the United Kingdom. 

In their national quality report, 15 countries also mention to use item non-response data imputation: 
Belgium, Bulgaria, Estonia, Spain, Italy, Latvia, Lithuania, Hungary, Malta, Austria, Romania, 
Slovenia, Slovakia, Finland and the United Kingdom. Imputation is mainly used for the INCDECIL 
variable and in some countries for variables related to job characteristics or education. 

No estimates can be produced at Eurostat about the rate of processing errors in the EU-LFS. 

Quality report of the European Union Labour Force Survey 2016 

23 

 
 
 
 
 
 
 
Timeliness and punctuality 

5 

5 Timeliness and punctuality 

5.1  Definition  

Timeliness is the length of time between data availability and the event or phenomenon they 
describe. 

Punctuality is the time lag between the actual delivery of data and the target date on which 
they were scheduled for release as announced in an official release calendar, laid down by 
Regulations or previously agreed among partners.  

According to Council Regulation (EC) No 577/98 data shall be delivered to Eurostat within twelve 
weeks from the end of a reference quarter. A release calendar for the EU-LFS main indicators is in 
place, scheduling the release of the LFS main indicators around four weeks after the data delivery 
deadline. In addition, Eurostat continuously updates the Eurostat online database (other tables) 
whenever new data becomes available. 

Table 5.1 shows that data are transmitted to Eurostat for most countries in the third month after the 
end of the quarter. Eurostat hence disseminates most national data in the third month after the end 
of the quarter as well. Timeliness and punctuality of the transmission to Eurostat and Eurostat’s 
dissemination of national data have improved in 2016. 

Quality report of the European Union Labour Force Survey 2016 

24 

 
 
 
 
 
 
 
 
Timeliness and punctuality 

5 

Table 5.1: Transmission to Eurostat and Eurostat’s dissemination of LFS data by 
number  of  calendar  days  from  the  end  of  the  reference  period,  2014  -  2016 
quarterly LFS data 

Number of calendar days from end of reference period 

Transmission to Eurostat 

<31 

31-60 

61-90 

91+ 

Total 

Average number of calendar days 

Eurostat’s dissemination of national data (web site) 

<31 

31-60 

61-90 

91+ 

Total 

Average number of calendar days 

Number of countries 

2016 

2015 

2014 

All  EU-28  All  EU-28  All  EU-28 

1 

11 

21 

0 

33 

62 

0 

5 

27 

1 

33 

73 

1 

9 

1 

8 

1 

5 

0 

9 

18 

24 

22 

24 

0 

28 

63 

0 

3 

0 

33 

67 

0 

2 

0 

28 

68 

0 

2 

0 

33 

66 

0 

2 

24 

29 

24 

27 

1 

28 

74 

2 

33 

80 

2 

28 

80 

4 

33 

77 

0 

7 

21 

0 

28 

66 

0 

2 

24 

2 

28 

77 

Quality report of the European Union Labour Force Survey 2016 

25 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
Timeliness and punctuality 

5 

6 Comparability 

6.1  Definition  

Comparability is a measurement of the impact of differences in applied statistical concepts, 
measurement tools and procedures where statistics are compared between geographical 
areas or over time. 

6.2   Comparability over space 
A common framework regulation (11), common variable definitions (12), common explanatory notes (13) 
and a common regulation regarding the definition of unemployment and the twelve principles of 
questionnaire construction (14) serve to ensure comparability of the statistics between the participating 
countries. This is, however, mainly true for the main characteristics of employment and 
unemployment, where particular definitions and sequences of questions are part of the EU 
legislation. For the other variables, each country has the responsibility to ensure that the national 
survey provides data compatible with the EU definitions and of the same quality as for the core 
variables. 

As most of the variables are defined in accordance with recommendations of the International Labour 
Organization (ILO) and other international organizations, the main statistics from the EU-LFS are 
directly comparable to those of other industrialized countries, especially those of the other members 
of the Organisation for Economic Co-operation and Development (OECD). In Table 6.1 the main 
divergences of national concepts from the European framework are reported. 

Table 6.1: Divergence of national concepts from European concepts, 2016 

Belgium 

Divergences in definition of resident population 

The Registered population definition in the sampling frame is used. At the beginning of the 
interview, the interviewer checks with the respondent(s) whether the list of household 
members as taken from the sampling frame corresponds to the actual situation. Interviewers 
are instructed to drop household members that no longer live at the given address since at 
least 6 months (but in practice they sometimes drop household members earlier) and also 
add new members in the household if any.  

(11)  Council Regulation (EC) No 577/98. 
(12)  Commission Regulation (EC) No 377/2008. 
(13)  EU Labour Force Survey Explanatory Notes, available at: http://ec.europa.eu/eurostat/statistics-

explained/index.php/EU_labour_force_survey_-_methodology 

(14)  Commission Regulation (EC) No 1897/2000. 

Quality report of the European Union Labour Force Survey 2016 

26 

 
 
 
 
 
 
  
                                                           
 
 
 
 
Timeliness and punctuality 

5 

Denmark 

Austria 

Sweden 

United 
Kingdom 

Norway 

Bulgaria 

Germany 

Croatia 

Hungary 

Portugal 

Turkey 

Belgium 
Slovenia 

The definition of the resident population in the Danish LFS is harmonised with the Danish 
population register. The permanent address is therefore defined as the place where you 
regularly sleep, when you are not abroad because of holidays, business trips, or the place 
where you have your belongings. The definition does therefore not explicitly include the 
minimum of 1 year, as stated in the Explanatory notes. This solution complies with art. 2(d) 
of EP and Council Regulation (EC) No 763/2008. 
Prospective information (intention to stay at least one year) is not available 
To belong to the Swedish resident population the residence permit is needed. This means 
that some immigrants group, i.e. persons with citizenship outside the EU, don’t belong to the 
population even if they are staying or intended to stay in the country for a period longer than 
one year. These people can’t work or seek job by defaults and they don’t exist in the 
populations register and thereby neither in the sample frame. 
Persons resident in NHS/Health Trust accommodation and students in institutions are 
included in national survey results. 
In the Norwegian register definition a person is resident if he/she is staying or intends to stay 
6 months or more in Norway. 

Divergences in concept of employment 
Persons on maternity leave for raising a child up to 1 year of age are considered employed. 
According to the legislation during this period they receive compensation equal to about 90% 
of their normal earning. Persons on leave for raising a child between 1- and 2-years of age 
are considered as not in employment. According to the legislation during this period they 
receive fixed amount of compensation (near to the national minimum wage). Persons on 
unpaid parental leave (with duration of 6 months) are considered employed. 
The category "lay-off" is not implemented in WSTATOR, because there are no lay-offs in 
Germany. 
The persons on sick leave, maternity or paternity leave, paid parental leave are always 
considered as employed, regardless of the length of the absence. 

According to the ILO recommendation drafted for countries in transition in Prague in 
November 1995, persons receiving child care allowance or child care benefit during parental 
leave have been classified since 1998 on the basis of their activity performed in the 
reference week. Therefore these persons are not classified as persons with a job from which 
he/she was absent during the reference week, if they are not working beside receiving child 
care allowance or benefit. Questions about how long they have been out of his/her main job 
are skipped for this persons. 
In case of persons older than 74 ‘other’ category (WSTATOR=5) can’t be used because we 
don’t know whether they have a job or not.   
Persons who work on their own small agriculture farms and produce only for their own 
consumption are considered as employed if the output is considered important (by the 
household) for the household budget. 
Persons on compensation leave, sick leave, maternity or paternity leave, paid parental leave 
are always considered to be employed, regardless of the length of the absence. 
Three months absence criterion defined by Eurostat is not followed for unpaid family 
workers, they're not covered as employed if they didn't work in the reference week even one 
hour. 
Farmers who only produce for own-consumption are considered as employed if the amount 
of this production is considerable within total household consumption (if the total amount of 
this product is at least 51% of total food expenditure). 

Divergences in concept of unemployment 
In Belgium, unemployment rate is calculated for persons aged 15-64 and not 15+ (Eurostat). 
There is a divergence in the unemployment concept. Nevertheless, the figures can be 
calculated in both ways (national and Eurostat approach). In general, the unemployment rate 
calculated by Eurostat and by the Slovenian statistical office differs for max. 0.1%. 

United 
Kingdom 

Turkey 

All those waiting to start a job already obtained are counted as ILO unemployed. The 
restriction of job starting within a period of three months is not applied to national estimates. 
All job search methods counted including passive methods. Differences are not large. 
For national calculation of unemployment passive job search methods are covered besides 
the active ones. 

Quality report of the European Union Labour Force Survey 2016 

27 

 
 
 
 
 
  
  
 
Timeliness and punctuality 

5 

6.3  Comparability over time 

For a detailed overview of the availability of quarterly EU-LFS microdata and the uniform spreading 
of the sample over the whole year, please consult: EU Labour Force Survey EU — Methodology 
(Statistics Explained). 

Every year, a certain number of changes are introduced in some national LFSs, to take into account 
changes introduced at European level, to better align the national surveys to the already existing EU 
regulations or methodological guidelines, or to take into consideration national needs. These 
changes can concern the conceptual level (i.e. concepts and definitions used by the LFS, the survey 
coverage and the geographical boundaries, the target population, the legislation, the classifications 
used) or the measurement level (i.e. the sampling strategy, the data collection, and the weighting 
scheme). 

Table 6.2 reports changes to the national labour force surveys introduced in 2016 by the participating 
countries. Such changes may introduce some discontinuity in the time series. 

Table 6.2: Changes in LFS in 2016 compared to previous year(s) 

Changes to survey concepts (legislation, definitions, coverage and classifications) 

All 

The new Classification on fields of education (ISCED-F 2013) was introduced in 2016, variables 
affected: HATFIELD; CORFIELD. 

Changes to sampling strategy (sampling frame, sample design, rotational pattern)  

BE  On the one hand, reduction of sample size in Q1 and Q2 2016 for budgetary reasons (reduction of 

group size from 26 to 23 for Brussels region and from 23 to 20 for the other two regions). This 
could affect the precision of all indicators.  
The sample is quarterly based on a stratified sample. The sample size was reduced in the 1st 
quarter of 2016. Before 2016, individuals who had research protection were not interviewed, but 
this protection has been removed from the first quarter of 2016. This effectively means an 
expansion of the number of people that actually can be interviewed. This is compensated by 
reducing the number of people who are drawn out to the sample. The reduction was implemented 
successively and the sample size for persons aged 15 to 74 was reduced from 38,979 in the 1st 
quarter of 2016 to 37,426 in the 4th quarter of 2016. The reduction will be fully implemented in the 
2nd quarter of 2017. A series of tests on this show, however, that it does not appear to have 
influenced the figures for the labour market participation. Before 2016 the quarterly sample size 
was 40,532. Persons aged 16-64 years that were registered as unemployed in a specific quarter 
prior to the survey quarter are selected with a higher probability than their relative proportion of 
the total population. 
A new sample was introduced in 2016. Although still based on the 2011 Census of Population, the 
stratification method changed from using administrative county and population density to 
administrative county and the Pobal HP (Haaske and Pratschke) Deprivation Index.  The 
introduction in the new sample was highlighted in the background notes to the quarterly 
publication and in the briefings with users and press. 
All elementary samples (i.e. sub-samples included in quarterly samples) surveyed for the first time 
in the year 2016 were designed according to the new sample design (in which sample size was 
slightly increased and sample distribution in all NUTS2 regions was changed). 

DK 

IE 

PL 

 Changes to data collection (questionnaire, national explanatory notes, survey mode) 

DK 

EL 

From the 1st quarter 2016 data collection is carried out by CATI and CAWI techniques. CAWI has 
been introduced in the core-LFS (previously it was used for the household subsample. A general 
break in all variables, also due to a significant low response rate. 
Changes concerning variables: TMPREAS, COURATT, COURLEN, COURPURP, COURFIELD, 
COURWORH, REGIONW, REGION1Y. 

Quality report of the European Union Labour Force Survey 2016 

28 

 
 
 
 
 
 
Timeliness and punctuality 

5 

HR 

LV 
LT 
PL 

Since the beginning of 2016, the earlier PAPI method of data collection has been replaced by 
CAPI and CATI interviewing methods. Accordingly, the questionnaire was adapted to computer 
assisted telephone and personal interviewing. Instructions to the interviewers were supplemented 
by explanations related to intention in terms of length of residence in/out the country and by notes 
on the operation and the features of the electronic questionnaire. 
Improved wording of some answers in a few questions. 
Updating of Instruction to the interviewers. 
Reasons for having temporary work/contract of limited duration contacted with period 
of apprenticeship or training (TEMPREAS – Col 53), fields of education (e.g. HATFIELD col. 
205/208 or COURFILD Col. 133/135). 

Changes to weighting scheme 

CZ 
HR 

CY 
PL 

Added strata for annual weights 
Due to availability of new and more up-to-date estimates of the total population, data for 2015 and 
2016 have been revised in order to adjust the Survey data with demographic figures for the 
Republic of Croatia. 
Calibration used for annual estimates. 
In the year 2016 quarterly weights were adjusted to the demographic estimates at voivodship 
(NUTS2) level, while previously demographic data at the country level were used. 

CH  More accurate calculation of quarterly and yearly weights due to the inclusion of information 

stemming from the social security register into the weighting scheme for years 2010-2016. From 
2016Q1 onwards, the information for a set of sociodemographic variables is no longer gathered 
through the interview, but derived from the communal and cantonal resident's registers. This 
change does not only reduce respondent burden, but the information stemming from the resident's 
registers have also been proven to be more reliable then surveyed information (Variables 
affected: SEX, YEARBIR, DATEBIR, MARSTAT, NATIONAL, COUNTRYB, YEARESID). 

Quality report of the European Union Labour Force Survey 2016 

29 

 
 
 
 
 
  
 
 
Accuracy 

4 

7 Coherence 

7.1  Definition  

Coherence measures the adequacy of the statistics to be combined in different ways and for 
various uses. 

The coherence of two or more statistical outputs refers to the degree to which the statistical 
processes by which they were generated used the same concepts — classifications, definitions, and 
target populations — and harmonized methods. Coherent statistical outputs have the potential to be 
validly combined and used jointly. It is, however, generally easier to show cases of incoherence than 
to prove coherence.  

The following sections assess coherence with similar data from other sources, the population 
statistics and the employment data from National Accounts and Structural Business Statistics. Other 
comparisons are possible as well, such as with employment data from the Labour Cost Survey. 

7.2  Coherence with population statistics 

The coherence with population statistics is of importance for the users, as often the most recent 
population estimates are available from the EU-LFS statistics. These two statistics are, however, not 
fully comparable. 

Differences that need to be considered are: 

  EU-LFS statistics usually cover the population in private households, while population 

statistics cover the whole population, including those living in collective households (e.g. 
conscripts). 

  Sometimes the rules for defining the usual resident population in the LFS differ from the 

rules in population statistics. 

  Population statistics usually refer to particular dates, e.g. 1st January or mid-year for 

population level and characteristics. The EU-LFS statistics generally refer to the average 
quarterly or annual situation. 

Most of the participating countries carried out a population census in the 2011 round. New censuses 
often result in new weights, new sample frames or new sample designs. By 2014 all of the 
participating countries had revised the weights to reflect new population estimates, including re-
weighting of back data series at least back to 2010. Table 7.1 shows the comparison between 
population statistics and LFS for people aged 15-64 years.  

Quality report of the European Union Labour Force Survey 2016 

30 

 
 
 
 
 
 
 
 
Accuracy 

4 

Table 7.1: Coherence between population statistics and EU-LFS for persons 
aged 15-64, 2016 

Population 15-64 
(in thousands) 

LFS annual average 15-64 (in 
thousands) 

Relative difference 

01/01/2016 
Men 

Total 

Women 

Total 

2016 
Men 

Women 

[(L-P)/P*100] 
Total  Men  Women 

EU-28 

333,077 

166,701 

166,376 

328,734 

164,202 

164,532 

-1.3 

-1.5 

7,327 
4,694 

3,690 
2,373 

3,637 
2,321 

7,290 
4,659 

3,661 
2,351 

3,628 
2,308 

-0.5 
-0.7 

-0.8 
-0.9 

6,998 

3,550 

3,447 

6,968 

3,537 

3,432 

-0.4 

-0.4 

3,673 
53,994 
854 
3,097 
6,934 
30,721 
41,854 
2,774 
39,014 
581 
1,282 
1,916 
399 
6,609 
303 
11,094 
5,849 
26,199 
6,740 
13,259 
1,378 
3,810 
3,468 
6,187 

1,855 
27,415 
423 
1,535 
3,410 
15,437 
20,646 
1,388 
19,432 
282 
623 
928 
204 
3,282 
156 
5,578 
2,944 
13,086 
3,262 
6,689 
708 
1,916 
1,757 
3,152 

1,818 
26,579 
431 
1,562 
3,524 
15,283 
21,207 
1,386 
19,582 
299 
659 
988 
195 
3,328 
147 
5,516 
2,905 
13,112 
3,477 
6,570 
670 
1,895 
1,711 
3,034 

3,669 
53,802 
849 
3,013 
6,937 
30,536 
40,890 
2,753 
38,871 
556 
1,254 
1,899 
396 
6,478 
287 
10,988 
5,790 
24,649 
6,700 
13,263 
1,371 
3,810 
3,445 
6,214 

1,854 
27,264 
420 
1,492 
3,431 
15,304 
20,072 
1,377 
19,342 
266 
608 
920 
201 
3,203 
146 
5,507 
2,900 
12,308 
3,238 
6,695 
703 
1,916 
1,738 
3,169 

1,816 
26,539 
430 
1,521 
3,505 
15,232 
20,818 
1,376 
19,529 
290 
647 
980 
194 
3,275 
141 
5,481 
2,890 
12,341 
3,462 
6,568 
668 
1,895 
1,707 
3,045 

-0.1 
-0.4 
-0.6 
-2.7 
0.0 
-0.6 
-2.3 
-0.8 
-0.4 
-4.3 
-2.2 
-0.9 
-0.9 
-2.0 
-5.4 
-1.0 
-1.0 
-5.9 
-0.6 
0.0 
-0.5 
0.0 
-0.7 
0.4 

-0.1 
-0.6 
-0.9 
-2.8 
0.6 
-0.9 
-2.8 
-0.8 
-0.5 
-5.7 
-2.5 
-0.9 
-1.3 
-2.4 
-6.2 
-1.3 
-1.5 
-5.9 
-0.7 
0.1 
-0.8 
0.0 
-1.1 
0.5 

42,069 

20,977 

21,092 

41,397 

20,581 

20,816 

-1.6 

-1.9 

220 
3,422 
5,595 

111 
1,755 
2,827 

108 
1,667 
2,769 

208 
3,425 
5,556 

106 
1,754 
2,805 

102 
1,671 
2,751 

-5.6 
0.1 
-0.7 

-5.4 
-0.1 
-0.7 

-1.1 

-0.2 
-0.6 

-0.5 

-0.1 
-0.2 
-0.2 
-2.6 
-0.5 
-0.3 
-1.8 
-0.8 
-0.3 
-3.0 
-1.8 
-0.9 
-0.5 
-1.6 
-4.5 
-0.6 
-0.5 
-5.9 
-0.5 
0.0 
-0.2 
0.0 
-0.2 
0.3 

-1.3 

-5.8 
0.3 
-0.6 

Belgium 
Bulgaria 
Czech 
Republic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United 
Kingdom 
Iceland 
Norway 
Switzerland 
Former 
Yugoslav 
Republic of 
Macedonia 
Turkey 

1,457 

740 

717 

1,456 

739 

717 

-0.1 

-0.1 

-0.1 

53,360 

26,973 

26,387 

52,267 

26,209 

26,058 

-2.0 

-2.8 

-1.2 

Source: Eurostat (online data codes: demo_pjan and lfsa_pganws), exctracted on 2 March 2018. 

Quality report of the European Union Labour Force Survey 2016 

31 

 
 
 
 
  
  
 
 
 
 
Accuracy 

4 

7.3  Coherence with other employment and 
unemployment estimates 

Coherence of employment for LFS and Business 
Statistics 
Business statistics, whether Structural Business Statistics (SBS) or Short-term Business Statistics 
(STS), are focused on production-related variables like output, turnover or value added, but they also 
produce some estimates of employment. These estimates may be and frequently are different from 
LFS results. The main reasons for the differences are: 

  Different scope: business surveys gather information on production units operating in the 

territory whereas LFS gathers information on people living in the country. Cross-border 
workers or seasonal workers are correspondingly recorded in different countries.  

  Different coverage: the LFS usually does not collect information for people living in collective 

households (Business Statistics do not exclude the information). The LFS covers all 
economic activities and all firm sizes, whereas Business Statistics typically do not gather 
information on agriculture, government or some service activities. In addition, business 
registers used to compile Business Statistics may not include small enterprises below a 
certain threshold or may leave out employment not included in the payroll or in the 
accounting books such as family workers. 

  Different units: business surveys estimate the number of jobs whereas LFS counts 

jobholders. Business surveys rarely have access to jobholders’ features like age, gender, 
etc. for which LFS is the only source.  

Coherence of employment for LFS and National 
Accounts 
Key concepts used in National Accounts, such as domestic employment, have no correspondence in 
the EU-LFS, which uses instead number of persons employed based on residency within the national 
border (national employment). There are also differences in coverage, with the EU-LFS covering 
persons living in private households only, while National Accounts cover all persons regardless of 
their type of residence. In addition, the EU-LFS does not consider conscripts and unpaid trainees as 
employed whereas these are explicitly or implicitly accounted for in the National Accounts. The 
reference period for the measurement could also contribute to some differences. The LFS estimates 
represent the average on all weeks in the year (for annual results) or in the quarter (for quarterly 
results). National Accounts stock estimates refer to the mid of the year (for annual accounts) or the 
mid of the quarter (for quarterly accounts).  

As expected, the employment estimates based on LFS data usually lie somewhat below the 
estimates of employment as estimated by National Accounts. This results from table 7.2, where the 
data are grouped on the basis of the importance of the LFS in the production of the National 
accounts data. National Accounts estimates on employment are in general higher, especially in 
countries with a considerable percentage of irregular economy. 

Apart from the coverage, measurement and conceptual differences mentioned above only account 
for a relatively small part of the difference between the two estimates. As a rule of thumb, relative 
differences higher than 1.5% need to be explained by other reasons. This would concern seventeen 
participating countries as shown in table 7.2. Germany, France and Italy are responsible for the bulk 
of the absolute EU difference between the National Accounts employment estimates and the LFS 

Quality report of the European Union Labour Force Survey 2016 

32 

 
 
 
 
Accuracy 

4 

employment estimates, while in relative terms Bulgaria, Germany, Greece, France, Italy, Malta and 
Slovenia show the highest discrepancies, with a difference of more than 5% (15).  

When comparing data from LFS and National Accounts, users are also interested in whether the two 
sources show the same trend or not. Table 7.2 also compares the data on employment growth in 
2016. The results show that both sources are broadly comparable as regards the direction of the 
employment growth for the EU-28 and that the differences mostly lie in the size of the growth figures. 

The reasons for the disparities, either in levels or in the direction of the employment growth, are not 
fully known. In general, the actual sources of incoherence are quite diverse across countries. The 
issue of incoherence between the LFS and National Accounts employment estimates has been 
addressed by a Eurostat-coordinated Task Force on the Quality of the Labour Force Survey (16). By 
the use of reconciliation tables, a range of potential sources of incoherence on the LFS side was 
identified, either related to a biased measurement of specific areas of employment, such as marginal 
employment, employment in hidden/undeclared labour activities, employment in private households, 
illegal immigrants, or emerging from data collection, as in the case of non-response and proxy 
interviews.  

National Accounts combines data from all available data sources in the country. This method allows 
better coverage of the non-observed economy. For this reason, National Accounts estimates are 
frequently higher than LFS employment estimates. In addition, it can be pointed out that LFS 
estimates are subject to sampling error, both with regard to levels and changes between periods (cf. 
tables 4.1a and 4.1b). When changes between periods are small, this may result in diverging trends 
between National Accounts and LFS figures, just because for the LFS the changes are within the 
margin of error. As regards National Accounts, some indicative reasons for incoherence can be 
mentioned: National Accounts may use sources different than LFS (or LFS combined with other 
sources) to estimate employment; National Accounts may introduce adjustments to reach 
consistency between the employment reported by its sources and other related variables, like 
salaries or production; the National Accounts approach, by comparing and combining different 
sources, is also more prone than LFS to identify and address underreporting or systematic biases. 
All in all, National Accounts are judged more suitable to measure employment levels, employment 
growth and industry breakdowns while LFS is more adequate to measure participation in the labour 
market (i.e. employment rates, activity rates, etc.), or to analyse the situation of specific socio-
economic groups of the population (e.g. by age, gender or educational level). 

(15)  No data is available for the Former Yugoslav Republic of Macedonia and Turkey. 

(16)  See http://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-RA-09-020 

Quality report of the European Union Labour Force Survey 2016 

33 

 
 
 
 
                                                           
 
 
Table 7.2: Employment (national concept) in levels and growth rates, in two 
different datasets on the Eurostat website (LFS and NA), 2016 
2016 levels 

2015–2016 growth rates 

Accuracy 

4 

Labour 
Force 
Survey 
(in 
thousands) 

National 
Accounts 

LFS-NA 

(in 
thousands) 

(in 
thousands) 

(LFS -
NA)/NA 
*100 

Labour 
Force 
Survey 

National 
Accounts(1) 

LFS-NA 

(%) 

(%) 

(%) 

(p.p.) 

1 Countries using LFS as their only source for employment in National Accounts.  
   LFS is only adjusted for conceptual alignment to ESA2010 

5,138.6 

644.6 

1,589.9 

893.3 

8,448.8 

4,909.9 

5,232.8 

647.3 

1,599.2 

900.0 

8,579.2 

4,910.1 

-94.2 

-2.7 

-9.3 

-6.7 

-130.4 

-0.2 

-1.8 

-0.4 

-0.6 

-0.7 

-1.5 

0.0 

1.9 

0.6 

0.3 

-0.3 

-1.0 

1.5 

1.3 

0.6 

0.3 

-0.2 

-1.1 

1.5 

0.6 

0.0 

0.0 

-0.1 

0.1 

0.0 

2 Countries using mainly LFS, but replacing it in a few industries (or labour status), on a 

case-by-case basis 
3,673.6 

1,361.4 

31,627.7 

4,083.0 

1,362.1 

31,726.0 

-409.4 

-10.0 

-0.7 

-98.3 

-0.1 

-0.3 

3 Countries not using LFS, or making minimal use of it 
-3.1 

4,586.7 

4,735.4 

-148.7 

2,839.7 

26,583.8 

2,841.0 

28,040.0 

-1.3 

-1,456.2 

363.1 

260.5 

191.9 

381.6 

250.3 

203.2 

4,220.2 

4,249.8 

915.0 

190.5 

967.9 

188.7 

-18.5 

10.3 

-11.3 

-29.6 

-52.9 

1.8 

0.0 

-5.2 

-4.9 

4.1 

-5.6 

-0.7 

-5.5 

1.0 

1.7 

2.0 

1.4 

0.8 

3.2 

0.6 

1.4 

1.2 

3.2 

1.7 

-0.3 

3.8 

0.5 

2.0 

1.4 

1.2 

1.8 

0.7 

3.2 

2.3 

3.7 

1.2 

2.8 

4.6 

4 Countries combining sources for labour supply and demand, LFS being one source 

among others. This group is rather heterogeneous and can be sub-divided as follows: 

4a  Countries giving precedence to labour supply sources (i.e. LFS) 

18,341.5 

16,196.9 

4,605.2 

4,604.4 

19,043.8 

16,196.0 

4,673.7 

4,604.4 

-702.3 

0.9 

-68.5 

0.0 

-3.7 

0.0 

-1.5 

0.0 

2.7 

0.7 

1.2 

1.5 

4b  Countries not giving precedence to any labour side  

3,016.8 

4,351.6 

3,463.4 

4,351.6 

-446.6 

0.0 

-12.9 

0.0 

-0.5 

3.4 

2.6 

0.7 

1.5 

1.5 

0.5 

3.4 

4c  Countries giving precedence to labour demand sources (i.e. employment 

registers and/or enterprise surveys) 

41,267.3 

2,020.0 

22,757.8 

8,427.1 

2,492.1 

2,448.1 

2,638.2 

43,544.0 

2,045.5 

24,318.7 

8,763.0 

2,492.1 

2,510.4 

2,764.0 

-2,276.7 

-25.5 

-1,560.9 

-335.9 

0.0 

-62.3 

-125.8 

-5.2 

-1.2 

-6.4 

-3.8 

0.0 

-2.5 

-4.6 

2.6 

2.9 

1.3 

1.3 

2.8 

0.5 

-0.1 

1.3 

2.8 

1.3 

1.0 

2.8 

0.3 

0.3 

1.2 

0.0 

0.0 

-0.4 

1.4 

-0.1 

-1.8 

-1.1 

-0.5 

0.5 

-3.1 

-0.8 

0.1 

0.0 

-0.3 

0.0 

-1.0 

0.0 

1.3 

0.1 

0.0 

0.3 

0.0 

0.2 

-0.4 

CZ 

EE 

HR 

LV 

RO 

SE 

EL 

LT 

UK 

BE 

DK 

FR 

CY 

LU 

MT 

AT 

SI 

IS 

ES 

PL 

PT 

CH 

BG 

HU 

DE 

IE 

IT 

NL 

SK 

FI 

NO 

(p) Provisional and (e) estimated 
Source: Eurostat Labour Force Survey, Annual averages (online data code: lfsi_emp_a) and Eurostat National 
Accounts, national concept (online data code: nama_10_pe) – data extracted on 2 March 2018. 

Quality report of the European Union Labour Force Survey 2016 

34 

 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
Accuracy 

4 

Coherence of unemployment for LFS and registers 
The main coherence issues between unemployment estimated by the LFS and that derived from 
registers are the different definitions and the different modes of measurement. According to the ILO 
definition adopted by the LFS, unemployed persons comprise persons aged 15 to 74 who fulfil the 
three following conditions: 

 

 

 

not employed during the reference week; 

available to start work within the two weeks following the reference week; 

actively seeking work in the four weeks preceding the reference week or have already found 
a job to start within the next three months. 

The definition of register unemployment varies from country to country. In general, the registration as 
a job seeker at the public employment office is the common basis for being counted in the 
unemployment register. 

The actual sources of incoherence between LFS and register unemployment figures are quite 
diverse across countries; this may be due to several reasons: 

  The LFS excludes from unemployment all individuals who have any kind of job (1-hour 

criterion), whereas registers can include individuals who have temporary jobs, jobs with less 
than a certain number of hours,  or salaries below a given amount; 

  The immediate availability for a job required by LFS is based on self-declarations. On the 

other hand, registers could exclude individuals who miss periodical meetings or refuse a fair 
job offer; 

 

In the LFS, registration at the public employment office in order to find a job is only one of 
the possible active search actions;  

  Persons who are looking for a job but who have not paid any contributions and are not 

eligible for unemployment benefits may not have any interest in registering for work and 
consequently do not feature in the registered unemployment figures but may feature in LFS; 

  Different reference periods (LFS uses continuous reference week and registers often  use a 

specific day of each month as reference); 

  Any delay in updating the registers;  

 

In some countries unemployed persons, 65 years and older, who are looking for a job, 
cannot be registered; 

  Persons on lay-off (until 3 months) are not classified as unemployed in the LFS, but as 

employed persons (temporarily absent from work) while they can be registered at the public 
employment office as unemployed; 

  Figures from registers may not include full-time students looking for employment which 

could be considered unemployed if they comply with the ILO criteria; 

Moreover, LFS estimates are subject to sampling errors which does not affect estimates based on 
registers. 

In fourteen countries (Denmark, Estonia, Greece, Spain, Cyprus, Latvia, Luxembourg, Hungary, 
Malta, Romania, Sweden, the United Kingdom, Norway and Switzerland) unemployment estimates 
coming from LFS exceed figures from registers while in thirteen countries (Belgium, Bulgaria, the 
Czech Republic, Germany, France, Lithuania, the Netherlands, Austria, Poland, Portugal, Slovenia, 
Slovakia and Finland) is the opposite. Six countries (Ireland, Croatia, Italy, Iceland, the Former 
Yugoslav Republic of Macedonia and Turkey) are not able to provide any assessment about the 
direction of the differences.   

Quality report of the European Union Labour Force Survey 2016 

35 

 
 
 
 
 
Accuracy 

4 

8 Accessibility and clarity 

8.1  Definition  

Accessibility and clarity refer to the simplicity and ease, the conditions and modalities by 
which users can access, use and interpret statistics, with the appropriate supporting 
information and assistance. 

8.2  Available information  

Eurostat publishes both quarterly and annual results. Eurostat also publishes annually a 
compendium describing the main characteristics of the national surveys. 

Eurostat's public website is free of charge and includes main indicators, derived from the Labour 
Force Survey, as well as detailed, constantly updated results from the EU-LFS. All data on the 
website are supplemented by meta-data in Euro SDMX Metadata Structure (ESMS), giving basic 
information on the background and a summary of the methodology. More detailed information can be 
found at the dedicated EU-LFS web page and at the EU-LFS Statistics Explained. 

Customized tabulations of EU-LFS results in electronic format can be requested by users. Eurostat 
extracts more than 1,000 customized tables for users each year. These data are also produced free 
of charge. 

Since 2011 researchers can get anonymised datasets containing microdata free of charge if certain 
conditions are fulfilled. Data from EU Member States and from Iceland, Norway and Switzerland are 
available in this format. In 2016 around 300 researchers or research groups work with EU-LFS 
microdata (new contracts and amendments). 

Quality report of the European Union Labour Force Survey 2016 

36 

 
 
 
 
 
 
 
Regional labour market statistics 

9 

9 Regional labour market 

statistics(17) 

9.1 

Introduction 

The EU-LFS is designed to give accurate quarterly information at national level and accurate annual 
information at NUTS 2 regional level. Microdata including the NUTS 2 level codes are provided by all 
participating countries with a good degree of geographical comparability, which allows the production 
and dissemination of a wide set of comparable indicators. Eight countries, namely Estonia, Cyprus, 
Latvia, Lithuania, Luxembourg, Malta, Iceland and the Former Yugoslav Republic of Macedonia 
comprise a single NUTS 2 region, i.e. the national result is also the NUTS 2 result (as well as the 
NUTS 1 result). 

For the purposes of regional analyses as well as for monitoring the progress towards regional 
cohesion, data at NUTS 3 level are also often requested by users. However, as the transmission of 
data at NUTS 3 level has no legal basis, the figures are provided by participating countries on a 
voluntary basis with the purpose of deriving other regional aggregations. Therefore, available NUTS3 
data is currently only used for publication at a more aggregated level. For example, unemployment 
and employment figures are disseminated by urban-rural typology, coastal regions, mountain 
regions, island regions, border regions as well as metropolitan and coastal regions, which are based 
on data of groups of NUTS 3 regions (18). 

The compilation of NUTS 2 figures is well specified in the EU-LFS. As this is not the case for the 
NUTS 3, the sources and compilation methods for this dataset are described below. 

9.2  Sources for NUTS 3 level labour market 
statistics 

A majority of EU Member States provide the NUTS 3 code in the LFS micro data. Most of these 
countries have given their consent to Eurostat to use the micro data to produce the aggregations by 
regional typologies. For 2016, 20 Member States (Austria, Belgium, Bulgaria, the Czech Republic, 
Denmark, Estonia, Finland, France, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Malta, the 
Netherlands, Slovakia, Spain, Sweden and the United Kingdom) as well as Iceland, Norway and the 

(17)  Chapter 9 was jointly written by Eurostat Units F3 – Labour market and lifelong learning and E4 – Regional statistics and 

geographical information. 

(18)  SFor a detailed description of  this regional typologies, see:  

http://ec.europa.eu/eurostat/web/rural-development/methodology 
http://ec.europa.eu/eurostat/web/metropolitan-regions/overview 
http://ec.europa.eu/eurostat/web/maritime-policy-indicators/methodology 

Quality report of the European Union Labour Force Survey 2016 

37 

 
 
 
 
 
 
                                                           
 
 
 
 
Regional labour market statistics 

9 

Former Yugoslav Republic of Macedonia send the NUTS 3 codes in the LFS micro data. All but two 
of these countries (France and Spain) have given their consent that this data can be used to publish 
estimates by regional typologies. Four of the 23 countries providing NUTS 3 micro data, namely 
Austria, Ireland, France and Spain, also transmit tabulated results. Six countries (Germany, Croatia, 
Poland, Portugal, Romania and Slovenia) only transmit tabulated results, partly because the data is 
not always based on annual LFS results. However, due to non-sampling errors and the combined 
use of LFS data with the information from other sources (e.g. registers, small area estimates), it is 
difficult to assess the accuracy of NUTS 3 level labour market data according to scientific standards. 
Portugal and Germany transmit employment and unemployment data already aggregated by regional 
typologies. In 2016, for Switzerland and Turkey, no NUTS 3 data are available. For two Member 
States, Cyprus and Luxembourg, the NUTS 3 level does not differ from the NUTS 1 and the NUTS 2 
level. 

From 2014 onwards, the LFS reliability limits used for annual averages of quarterly data(19) are 
applied directly on the aggregated labour market data by regional typologies. In past years the LFS 
reliability limits used for NUTS 2 data were also applied for the individual NUTS 3 data, which 
resulted in an unnecessary high number of missing aggregate values. 

(19)  For more information, see 

http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey 

Quality report of the European Union Labour Force Survey 2016 

38 

 
 
 
 
 
 
 
 
 
                                                           
 
 
 
Annex 

10 Annex 

10.1  Tables 
Table 10.1: Comments and methodological notes about coverage errors 

Belgium 

Bulgaria 

Czech Republic 

Germany 

Estonia 

Greece 

Spain 

France 

Croatia 

Italy 

Comments 

Under-coverage: Households, all members of which are 77 years or older and collective 
households (about 0.15% of all households) are excluded before draw. Delay between draw 
of household (from National Population Register, kept up to date "permanently") and 
fieldwork: between 2 and 6 months. 
Over-coverage: non-occupied dwellings. 
Under-coverage: Households are selected once a year from the Register of Census Areas. 
Due to differences in time span there is not the actual information about addresses or flats. 
The sampling frame contains only private households. Persons living in institutional 
households are not covered. 
Over-coverage:  Not existing or not inhabited flats remain in the Register of Census Areas. 
Under-coverage: Homeless people and other people without registered residence (e.g. 
people living in huts, caravans) are out of the frame. Apart from that German LFS is an area 
sample. All inhabited dwellings belong to the frame. Thus, changes of the population (e.g. 
by immigration, emigration) are included in the frame automatically. 
Under-coverage: Among the households not interviewed, in 165 cases (1.2% of total 
number of sampled households) the reason was an error or inaccuracy of the frame (person 
emigrated or left the county, person deceased, wrong address, etc.). By counties the share 
of frame errors varied from 0.3% to 2.1%. 
Under-coverage: Population living in collective households or in dwellings outside the 
borders of built areas is not covered. Frames are compiled at census, and sampling rates 
are based at census population. Frames are updated at the first time when the primary 
sampling units are selected but not at subsequent waves. 
Over-coverage: The sample in Greek LFS is a sample of dwellings. The percentage of 
over-coverage is computed as the percentage of dwellings that are either used as 
"secondary residence" of the household or they are used solely for business purposes (e.g., 
a doctor's office). 
Under-coverage: Percentage calculated as 'omitted' dwellings detected in the 'quality 
control survey'; measures of impact are not available. 
(See: http://www.ine.es/en/inebaseDYN/epa30308/docs/epa05_disenc_en.pdf). 
Over-coverage:  Average of the four quarter percentages of dwellings out of frame ('no 
encuestables') The touristic areas are more prone to higher rates. 
Under-coverage: No impact on estimates. The sample is usually updated several months 
before the reference year and it does not cover the most recent buildings. The number of 
newly-built dwellings is taken into account in the weighting procedure. 
Under-coverage: Since the beginning of 2014, the new sample frame based on the data 
from the Census of Population, Households and Dwellings in 2011 has been in use. This 
sample frame includes addresses of private households on the whole territory of Croatia; 
hence the LFS results relate to the whole country. As the Census database was not updated 
since 2011, it is becoming obsolete, and some problems regarding migration and/or newly 
built dwellings will be present in a larger extent. 
Over-coverage: Overcoverage rates are actually non-eligibility rates of addresses selected 
in sample. 
Under-coverage: Households are selected once a year from the municipalities’ registry; 
they cover the whole reference population. The data might contain errors as for information 
such as addresses (due for instance to recent change of the address), wrong inclusions 

Quality report of the European Union Labour Force Survey 2016 

39 

 
 
 
 
 
 
  
 
 
Annex 

Comments 

(recent emigration) and missed inclusions (recent immigration). As for the survey’s 
management strategies, ISTAT requires that each non-responding household has to be 
replaced with a household having similar characteristics, in order to maintain as much as 
possible the sample representativeness and to minimize the impact of unit non-response. 
No more than 3 replaces are admitted. 
Under-coverage: The sample was drawn from the Census of Population household frame 
of 2011. In a post enumeration survey conducted after the census, under-coverage of 1.97% 
was estimated.  
Under-coverage: In general the list of counting areas covers all territory of Latvia, but there 
could be some territories not covered by the list. It is due to active building of new dwellings 
in previously unoccupied areas during the last years. 
Over-coverage:  Overall in year there is 1.36 % of over-coverage from sample. Main 
reason of it are, rarely updated register were can be old information. Also other reasons will 
be checked. 
Over-coverage: Among not interviewed households, in 735 cases (2% of total number of 
sampled households) the reason was an error or inaccuracy of the frame (imprecise 
address, the premises at the indicated address are non-residential, etc.).  
Under-coverage: homeless people and other people without registered residence are out of 
the frame. The sampling frame does only cover private households i.e. persons living in 
institutional and/or collective households are not being covered. According to population 
statistics collective households amount to 1.8% of total population. The sample from the 
Register of Residents is drawn on average four months before the start of the interviews. 
Persons that moved in after the due date are not covered. 
Over-coverage: Wrong address and wrong telephone numbers due to time lag or incorrect 
information in the register of residents. 
Under-coverage: Hard-to-access groups are characterised either by extremely bad traffic 
conditions to get to their place or by collective reluctance -- usually within a small community 
-- towards being interviewed. Though the effect of these factors cannot be estimated even 
though it is supposed to be not significant. 
Under-coverage: The sampling frame being used covers private households.  Hence 
persons living in institutional households are not being covered. Since the 2011 Census is 
being used as a sampling frame so households created after 2011 are not well represented.  
Over-coverage: There is over-representation for households created prior to 2011 and for 
households which were present in 2011 and no longer exist after 2011.  
Under-coverage: From 2004 onwards the sample for the Austrian LFS is drawn from the 
Austrian Register of Residents. This register was set up in 2002. The sample is drawn three 
months before the start of the quarter. This results in a time lag of three to six months. 
Therefore dwellings where persons moved in after the due date for the survey are not 
covered. Furthermore, undercoverage of migrants can be observed, although the 
questionnaires are translated into several languages. 
Under-coverage: New dwellings underrepresented in the sample - dwellings are selected 
once a year from the register of housing units and due to differences in time span there is no 
current information about addresses or flats. In addition population living in collective 
(institutional) households staying/or planning to stay in such places for over a 
year,  homeless people and other people without registered residence, emigrants staying 
abroad for more than one year are all out of the  survey frame. 
Over-coverage:  Overcoverage consist of dwellings in which inhabitants are not present for 
a long time, the dwelling is non-residential (shop) or not found (incorrect address). 
Under-coverage: The sampling frame does not cover the individuals living in collective 
dwellings. This population represents less than approximately 1%. 
Under-coverage: Due to the lack of appropriate information, the new dwellings, built after 
2011 Census of the Population and Dwellings, that could possibly constitute a sampling 
frame of the new dwellings, have not been taken into account.  
Over-coverage:  Over-coverage rates were estimated on the basis of the survey samples, 
as ratio between number of not-eligible dwellings and number of sampled dwellings. 
Under-coverage: The LFS sample is based on a Population Census conducted once every 
ten years (last time in 2011). There is the lack of information on new statistical units during a 
rather long period. Errors as for information on addresses of dwellings; missing coverage of 
collective households, persons living in convents, members of the Slovak embassies and 
institutions abroad. Under-coverage comprises people born abroad and living in collective 
houses. 
Over-coverage:  Mainly young residents working temporarily abroad can stay to live there. 
Under-coverage: The sampling frame used is the total population database maintained by 
Statistics Finland. It is based on the Population Information System of The Population 
Register Centre and updated regularly. Undercoverage fairly small (no large-scale 
immigration). 
Over-coverage: Overcoverage: mostly emigration in wave 1, deaths and emigration for 
later waves. 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 

Austria 

Poland 

Portugal 

Romania 

Slovakia 

Finland 

Quality report of the European Union Labour Force Survey 2016 

40 

 
 
 
 
 
  
Annex 

Comments 

Under-coverage: The LFS sample is drawn once a year and the sampled persons are 
interviewed eight times during a two year period. No additional sample selection is made in 
order to update the sample with immigrants during this two-year period. The average time 
span between sample selection and the reference week is about 19 months which means 
an under-coverage of about 50 000 persons or 1 % of the population. This under-coverage 
is judged to have marginal effects on the LFS-estimates. 
Over-coverage: The over coverage consists of people born abroad who left Sweden 
without reporting this to the Swedish authorities. When these persons are included in the 
sample there are no information that they have moved out from Sweden. They cannot be 
reached for interview and will be classified as non-response. According to evaluation-studies 
made this over-coverage is mainly concentrated to non-Nordic immigrants and is of a 
magnitude of 25,000-50,000 persons in the total population (0.2%). 
Under-coverage: The LFS coverage omits communal establishments, excepting NHS 
housing and students in halls of residence. Members of the armed forces are only included if 
they live in private accommodation. The LFS, by not sampling from communal 
establishments, excludes approximately 1.5% of the total GB population. 
Under-coverage: Do not include those 75 years and older. We impute them as outside the 
labour force. 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.  
Misclassification: Using family as a proxy for household at the moment. 
Misclassification: Differing household composition. Unit non response if the selected 
person is not living in the selected household (anymore), else no impact on estimates. 

Sweden 

United Kingdom 

Norway 

Switzerland 

Quality report of the European Union Labour Force Survey 2016 

41 

 
 
 
 
 
  
 
Table 10.2: Data collection facilities and methods of reducing measurement 
errors 

Annex 

Respondent 

Interviewer 

Letter 
introdu
cing 
the 
survey 

Phone 
call 
introduc
ing the 
survey 

Periodi
cal 
training 

Feedbac
ks 

Monitorin
g directly 
by 
responde
nts 

Y 

N 

Y 

N 

Y 

Y 

Y 

Y 

Y 

N 

N 

Y 

Y 

Y 

N 

N 

Questionnaire 

Monitori
ng 
remotely 
by 
indicator
s 

Questionna
ire in 
different 
languages 

Fieldwork 
Monitori
ng 
directly 
listening 
intervie
ws 
N 

NA 

N 

N 

N 

N 

Y 

N 

Country 

Belgium 

Bulgaria 

Czech 
Republic 

Denmark 

Germany 

Estonia 

Ireland 

Greece 

Spain 

France 

Croatia 

Italy 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

Malta 

Netherlands 

Austria 

Poland 

Portugal 

Romania 

Slovenia 

Slovakia 

Finland 

Sweden 

United 
Kingdom 

Iceland 

Norway 

Switzerland 

Former 
Yugoslav 
Republic of 
Macedonia 

Turkey 

Y 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

-  

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

- 

Y 

Y 

Y 

Y 

UNA 

UNA 

UNA 

UNA 

UNA 

UNA 

Y 

N 

Y  

N 

Y 

Y 

N 

N 

N 

Y 

-  

N 

Y 

N 

Y 

N 

Y 

N 

N 

Y 

Y 

Y 

Y 

- 

N 

Y 

N 

N 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

-  

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

N 

N 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

- 

Y 

N 

Y 

Y 

Y 

N 

N 

Y 

Y 

Y 

Y 

N 

Y 

N 

Y 

Y 

Y 

Y 

Y 

N 

Y 

N 

Y 

N 

N 

Y 

Y 

- 

N 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

- 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

Y 

Y 

- 

N 

Y 

N 

Y 

On-
line 
chec
ks 

Y 

NA 

Y 

Y 

UNA 

Y 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

-  

N 

Y 

Y 

Y 

Y 

Y 

NA 

Y 

N 

Y 

Y 

Y 

- 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

N 

N 

Y 

N 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

N 

Y 

N 

N 

N 

N 

N 

Y 

Y 

N 

- 

Y 

Y 

N 

Y 

Notes: (-) indicates that information has not been provided by the country; NA indicates Not Applicable (for example 
online checks with computerized questionnaire when only PAPI technique is used for interviews). UNA indicates 
Information not provided by the country. 

Quality report of the European Union Labour Force Survey 2016 

42 

 
 
 
 
 
 
Annex 

Table 10.3: Item non-response for the variables defined by Commission 
Regulation (EC) No 377/2008 and clarifications provided by Member States 

Quarterly data 2016 

Variable 
status 

Belgium 

Identifier 

Q1 

Q2 

Q3 

Q4 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

compulsory 

HWWISH 

90.1 

90 

89.5 

90.2 

HHWISH is only asked to persons who declared to 
wish to work more.  
Very few respondents answered METHODH as 
method used to find work. 

compulsory 

compulsory 

METHODH - 
employed 
WANTWORK  44 

. 

. 

. 

C 

43.1 

45.6 

45.2  We don't ask 'wantwork' to all persons with 

compulsory 

INTWAVE 

C 

. 

C 

C 

Bulgaria 

compulsory 

TEMPDUR 

15 

13.4 

13 

11.4 

compulsory 

HWACTUA2 

18.9 

22.1 

21.4 

24.5 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

METHODH - 
employed 
METHODI- 
employed 
METHODJ- 
employed 
METHODL- 
employed 
METHODM - 
employed 

compulsory 

METHODM - 
not employed 

C 

C 

. 

C 

C 

C 

Czech Republic  

. 

C 

C 

C 

C 

. 

C 

C 

. 

. 

C 

C 

C 

C 

. 

. 

C 

C 

seekwork =3. We have no info about 'wantwork' for 
persons with statbit=2 & seekwork=3 neither for 
persons with seekwork = 3 but who are (early) 
retired. 99% or more of the item non-response 
concerns (early) retired persons. We can consider 
them as not willing to work anymore since they 
don't seek work. 
No panel data in 2016 (only one wave) 

For persons without employment contract (main 
part of the variable non-response) the duration of 
job is often unclear 
Respondents meet difficulties to answer the 
question, especially self-employed. More than a 
half of non-responded persons were self-employed 
on the second job. 
This method is rarely used by employed persons to 
find other job 
This method is rarely used by employed persons to 
find other job 
This method is rarely used by employed persons to 
find other job 
This method is rarely used by employed persons to 
find other job 
Only methods corresponding to variables from 
METHODA to METHODI are considered as active 
methods. 
Only methods corresponding to variables from 
METHODA to METHODI are considered as active 
methods. 

compulsory 

EDUCSTAT 

18.5 

18.9 

19 

19.2 

Only persons aged 15-69  

Denmark 

compulsory 

SIGNISAL 

C 

compulsory 
compulsory 

NACE2J2D 
EXISTPR 

21.3 
34.3 

PROXY 
HWOVERP 
HWOVERPU 
HWWISH 
METHODL- 
employed 
INTWAVE 

. 
. 
. 
14.2 
C 

Germany 

compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

optional 

Estonia 

compulsory 

 Respondents included in the filter are coded with 
'don't know'. 

C 

. 
32 

. 
. 
. 
14.3 
C 

C 

C 

. 
32.5 

. 
31.4 

11.1 
. 
. 
15.4 
. 

11.7 
10 
10.2 
16.8 
. 

100 

100 

100 

100 

COUNTRYB 

100 

100 

100 

100 

This variable is not filled because there are no 
intra-annual waves in the German LFS. 
This variable is not filled in for legal reasons. 

METHODH - 
not employed 

. 

. 

C 

. 

Due to small absolute numbers very few cases, if 
any 

Quality report of the European Union Labour Force Survey 2016 

43 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Annex 

Variable 
status 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Ireland 

Identifier 

Q1 

Q2 

Q3 

Q4 

METHODI - 
employed 
METHODK - 
employed 
METHODL - 
employed 
METHODL - 
not employed 
METHODM - 
not employed 

. 

C 

C 

. 

. 

C 

C 

. 

C 

C 

. 

. 

C 

C 

. 

C 

C 

C 

. 

. 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

Due to small absolute numbers very few cases, if 
any 
Due to small absolute numbers very few cases, if 
any 
Due to small absolute numbers very few cases, if 
any 
Due to small absolute numbers very few cases, if 
any 
Due to small absolute numbers very few cases, if 
any 

compulsory 

TEMPDUR 

59 

52.8 

46.4 

49.7 

Persons are asked the question and the level of 
non-response generally reflects people not knowing 
what the duration of temporary employment will be. 

compulsory 
compulsory 

HWWISH 
NACE2J2D 

. 
. 

10.4 
14.3 

10.3 
10.8 

. 
. 

Spain 

compulsory 
compulsory 

TEMPDUR 
HWWISH 

44.9 
84.8 

44.5 
85.2 

42.1 
85.9 

45.8 
85.2  Most of the blanks come from people that don't 

C 

C 

C 

C 

C 

C 

C 

C 

wish to work more/less hours (perhaps the filter for 
this variable should be changed or add proper 
categories).  
 No 'other' active method in the survey 

 No 'other' active method in the survey 

40.3 
11 

40.4 
11.1 

49.4 
12.4 

41.7 
11.3 

 People aged 15 plus 'don't know' number of hours 
 People aged 15. 

compulsory 

compulsory 

compulsory 
compulsory 

France 

METHODM - 
employed 
METHODM - 
not employed 
COURLEN 
EDUCLEVL 

compulsory 

TEMPDUR 

13.2 

13.2 

11.6 

11.7 

compulsory 

HWWISH 

15.8 

15.9 

16.7 

16 

compulsory 

STAPRO2J 

15.6 

14.3 

13.3 

12.8 

compulsory 

NACE2J2D 

28.9 

27.7 

27.1 

26.6 

compulsory 

HWACTUA2 

14.5 

13.3 

10.5 

11.5 

compulsory 

compulsory 

METHODL - 
employed 
INTWEEK 

C 

. 

. 

. 

10.7 

11.1 

11.5 

11.3 

Croatia 

compulsory 

HWOVERP 

97.4 

96.9 

97.1 

97.3 

A part of the non-response comes from the people 
that declare to be in internship. We do not ask or 
use the duration of the internship. Other part of the 
non-response comes from some people who say 
they do not have any work contract and thus 
cannot be asked about its duration. 
Most of the non-response is due to people saying 
they don't want to work more or less than their 
currently amount of hours, and have more than one 
job. A solution will be studied. 
The code for EXIST2J has recently changed to 
correct some errors. The code of STAPRO2J was 
not changed to take this into account. It will be 
corrected for next year. 
The code for EXIST2J has recently changed to 
correct some errors. The code of NACE2J2D was 
not changed to take this into account. It will be 
corrected for next year. 
The code for EXIST2J has recently changed to 
correct some errors. The code of HWACTUA2 was 
not changed to take this into account. It will be 
corrected for next year. 

For households where all persons are aged 65 or 
more and are inactive, the variables are imputed for 
waves 2 to 5; thus there is no interview week for 
them.  

According to our calculation, non-response is 
negligible. This calculation refers to persons who 
did not work overtime, and in that case did not 

Quality report of the European Union Labour Force Survey 2016 

44 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Variable 
status 

Identifier 

Q1 

Q2 

Q3 

Q4 

compulsory 

HWWISH 

90.9 

91.8 

92 

91 

Annex 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

answer the question about paid overtime. 
According to our calculation, non-response is 
negligible. This calculation refers to people who do 
not wish to work usually more than the current 
number of hours (WISHMORE=0) and which in that 
case do not answer to the question about number 
of hours that the person would like to work in total. 
Will be implemented in the future. 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

SEEKTYPE - 
employed 
SEEKTYPE - 
not employed 
METHODH - 
employed 
METHODH - 
not employed 
COURLEN 

100 

100 

100 

100 

100 

100 

100 

100 

Will be implemented in the future. 

. 

. 

. 

. 

. 

C 

C 

. 

This method is rarely or never used in the job 
search. 
This method is rarely or never used in the job 
search. 

20.6 

15.7 

24 

10.9  Most of this non-response is related to a proxy 

Italy 

compulsory 

HWWISH 

. 

. 

16.1 

. 

interview. Proxy respondents do not usually know 
the number of hours spent on all taught learning 
activities. 

The questions on WISHMORE-HWWISH in the IT 
questionnaire are referred to the wish of working 
more than the actual number of hours. Most of the 
item non-responses are due to persons that did not 
want to work at all in the reference week (code "0" 
is not available); they are mainly concentrated in 
the 3rd quarter in which there are summer holidays.  
Item non-responses are due to persons that do not 
have preferences about an employment as self-
employed or employee. 
Item non-responses are due to persons that do not 
have preferences about an employment as self-
employed or employee. 

SEEKTYPE - 
employed 

SEEKTYPE - 
not employed 

21.6 

19.1 

19.4 

18.1 

27.5 

25.9 

26 

25.3 

compulsory 

compulsory 

Cyprus 

compulsory 
compulsory 
compulsory 

Latvia 

COUNTRYW  C 
C 
REGIONW 
C 
METHODI - 
employed 

C 
C 
C 

C 
C 
. 

C 
C 
. 

Country is always CY 
NUTS 2 is the whole of CY 
Rare method to use for searching 

compulsory 

REGIONW 

C 

C 

C 

C 

compulsory 

EXISTPR 

28.6 

29.3 

29.6 

28.7 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

METHODB - 
employed 
METHODH - 
employed 
METHODI - 
not employed 
METHODM - 
employed 
METHODM - 
not employed 
EDUCSTAT 

. 

. 

. 

. 

C 

. 

. 

. 

. 

. 

C 

. 

C 

. 

C 

. 

C 

. 

C 

. 

14.5 

14.3 

14.3 

14.3 

compulsory 

COURATT 

14.5 

14.4 

14.3 

14.4 

Data about workplace are collected at NUTS 1 
level. 
There aren't interviewed persons aged 75 or more 
included in filter (col.123). 
This method is used infrequently and sometimes 
nobody chooses this method. 
This method is used infrequently and sometimes 
nobody chooses this method. 
This method is used infrequently and sometimes 
nobody chooses this method. 
This method is used infrequently and sometimes 
nobody chooses this method. 
This method is used infrequently and sometimes 
nobody chooses this method. 
There aren't interviewed persons aged 75 or more 
included in filter. 
There aren't interviewed persons aged 75 or more 
included in filter. 

Lithuania 

compulsory 

REGIONW 

compulsory 

METHODH - 
employed 

C 

. 

C 

C 

C 

. 

C 

. 

All records have two values: 00 or 99 because 
NUTS2 level is all country.  
This method used to find work is not very popular 
among employed respondents.  

Quality report of the European Union Labour Force Survey 2016 

45 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Annex 

Variable 
status 

compulsory 

compulsory 

Luxembourg 

Identifier 

Q1 

Q2 

Q3 

Q4 

METHODH - 
not employed 
METHODL - 
employed 

. 

. 

C 

. 

C 

C 

. 

C 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

This method used to find work is not very popular 
among employed respondents.  
This method used to find work is not very popular 
among employed respondents.  

compulsory 

PROXY 

compulsory 

NACE3D 

C 

11.3 

compulsory 

MSTARTWK 

11.8 

compulsory 

HWUSUAL 

compulsory 

HWOVERP 

. 

. 

compulsory 

NACE2J2D 

35.9 

compulsory 

HWACTUA2 

. 

compulsory 

MONTHPR 

compulsory 

EDUCLEVL 

17.5 

14.4 

. 

10.2 

20.2 

. 

10.4 

23.6 

. 

25.2 

12.2 

C 

10.5 

10.7 

11.7 

. 

29.9 

10.3 

13.2 

12.5 

C 

12.1 

10.6 

. 

. 

34.1 

. 

17.8 

13 

Hungary 

compulsory 

MSTARTWK 

. 

compulsory 

EXISTPR 

20.8 

13.6 

21.1 

17.7 

21.4 

23.4 

21.3 

compulsory 

MONTHPR 

compulsory 

METHODH - 
employed 

. 

. 

13.5 

19.7 

23.6 

. 

. 

C 

There is an upper-age limit (74 years) in HU-LFS 
for this variable. 
The HU-LFS (in accordance with the EU-LFS) 
gives in some cases more detailed information than 
used in the Eurostat filter. This information is used 
by transcodification program of HU-LFS dataset. 

compulsory 

EDUCSTAT 

11.2 

11.2 

11.2 

11.1 

compulsory 

COURATT 

11.2 

11.2 

11.2 

11.1 

compulsory 

COURLEN 

. 

. 

. 

35.4 

There is an upper-age limit (74 years) in HU-LFS 
for this variable. 
There is an upper-age limit (74 years) in HU-LFS 
for this variable.  
Error in data query, it will be corrected by the end 
2017 

Malta 

compulsory 

REGIONW 

C 

C 

C 

C 

For persons working outside of Malta, information 
is collected on Country of work only and regional 
information is not collected.  Otherwise, all 
information for persons working in Malta is 
collected and transmitted to Eurostat.  

 Information on this variable is not collected. 

 Information on this variable is not collected. 

 Information on this variable is not collected. 

 Information on this variable is not collected. 

 Information on this variable is not collected. 

 Information on this variable is not collected. 

49 

48.4 

17.2 

. 

An error in the data entry program led to a high non 
response rate, which was rather difficult to impute 
all the information. 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Netherlands 
compulsory 
compulsory 
compulsory 

METHODH - 
employed 
METHODI - 
not employed 
METHODJ - 
employed 
METHODJ - 
not employed 
METHODK - 
employed 
METHODK - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 
COURLEN 

C 

. 

C 

C 

C 

C 

C 

C 

. 

. 

C 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

C 

TEMPDUR 
NACE2J2D 
SEEKDUR - 
not employed 

55.4 
26.6 
13.7 

56.3 
25.9 
15.6 

54.9 
26.8 
17.1 

57.6 
28.1 
16.1 

Quality report of the European Union Labour Force Survey 2016 

46 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Identifier 

Q1 

Q2 

Q3 

Q4 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

Annex 

Variable 
status 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

optional 
Portugal 
compulsory 

compulsory 

compulsory 

Romania 
compulsory 

compulsory 

Slovenia 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Slovakia 
compulsory 

METHODH - 
employed 
METHODI - 
employed 
METHODJ - 
employed 
METHODJ - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 
COUNTRYB 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

. 

. 

. 

C 

. 

C 

. 

. 

. 

C 

. 

C 

13.7 

12.9 

12.9 

12.8 

TEMPDUR 

13.5 

15.1 

14.5 

15.5 

METHODM - 
employed 
METHODM - 
not employed 

METHODH - 
employed 
METHODI - 
employed 

HWOVERP 
HWOVERPU 
MONTHPR 
METHODH - 
employed 
METHODH - 
not employed 
METHODI - 
employed 
METHODI - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 

SEEKTYPE - 
employed 

C 

C 

C 

C 

C 

C 

. 

. 

. 

C 

C 

C 

C 

C 

C 

C 

86.9 
92.9 
. 
. 

85.6 
91.2 
15.1 
C 

88.3 
92.9 
16.5 
. 

85.6 
91.2 
13.3 
. 

. 

C 

. 

C 

. 

C 

. 

C 

C 

C 

. 

. 

. 

C 

. 

. 

. 

. 

C 

C 

Corresponds to non-response of the employees 
who did not give an answer this variable. 
This variable does not exist in our national 
questionnaire 
This variable does not exist in our national 
questionnaire 

According to the survey results this is not a popular 
search method among employed 
According to the survey results this is not a popular 
search method among employed 

Almost not available in Slovenia 

Almost not available in Slovenia 

Not available in Slovenia 

Not available in Slovenia 

15.8 

15 

18.8 

18.4  Missing of appropriate code for those who are 

looking for any job (no preference between self-
employed or employee) causes higher value of the 
non-response rate. 

16.5 

16.5 

16.1 

17.6  Missing of appropriate code for those who are 

compulsory 

SEEKTYPE - 
not employed 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Finland 

METHODH - 
employed 

METHODI - 
employed 

METHODL - 
employed 

METHODM - 
employed 

METHODM - 
not employed 

C 

. 

C 

C 

. 

. 

. 

C 

C 

. 

C 

C 

C 

C 

C 

C 

C 

. 

C 

C 

looking for any job (no preference between self-
employed or employee) causes higher value of the 
non-response rate. 
Methods used in job seeking have the same 
question "State all methods you used during the 
last 4 weeks to find work" 
Methods used in job seeking have the same 
question "State all methods you used during the 
last 4 weeks to find work" 
Methods used in job seeking have the same 
question "State all methods you used during the 
last 4 weeks to find work" 
Methods used in job seeking have the same 
question "State all methods you used during the 
last 4 weeks to find work" 
Methods used in job seeking have the same 
question "State all methods you used during the 
last 4 weeks to find work" 

Quality report of the European Union Labour Force Survey 2016 

47 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Annex 

Variable 
status 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Sweden 
compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

Identifier 

Q1 

Q2 

Q3 

Q4 

METHODJ - 
employed 
METHODJ - 
not employed 
METHODK - 
employed 
METHODL - 
employed 
METHODL - 
not employed 

C 

C 

. 

C 

C 

C 

. 

C 

C 

C 

. 

. 

C 

C 

. 

C 

. 

. 

C 

C 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

Passive job search methods are asked only if none 
of the active methods have been used. 
Passive job search methods are asked only if none 
of the active methods have been used. 
Passive job search methods are asked only if none 
of the active methods have been used. 
Not available in Finland 

Not available in Finland 

TEMPDUR 

20.1 

21 

20.9 

24.2 

SEEKDUR - 
employed 
SEEKDUR - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 

10.4 

12.7 

12.2 

10.2 

29.3 

37 

19.1 

21 

. 

. 

C 

. 

C 

C 

. 

. 

Respondents do not always remember start and 
end of work 
People tend to forget how long they have been 
looking for work. 
People tend to forget how long they have been 
looking for work. 
 Very infrequent that this variable has value 1. 
Checked against micro-data. 
 Very infrequent that this variable has value 1. 
Checked against micro-data.  

High level of non-response owing to a relatively 
small proportion of the employed sample in a 
temporary job in the reference week.  
High level of non-response owing to a relatively 
small proportion of the employed sample working 
overtime in the reference week. 
High level of non-response owing to a relatively 
small proportion of the employed sample working 
overtime in the reference week. 
Variable only computed for respondents recorded 
as wishing to work more hours; this group equates 
to only 4% of the employed sample. 
The UK-LFS does not ask if respondents took a 
test, interview or examination. Therefore only 'No' 
responses can be calculated.  
The UK-LFS does not ask if respondents took a 
test, interview or examination. Therefore only 'No' 
responses can be calculated.  
The UK-LFS does not ask if respondents are 
waiting for a call from a public employment office. 
The UK-LFS does not ask if respondents are 
waiting for a call from a public employment office. 
The UK-LFS does not ask if respondents are 
waiting for the results of a competition for 
recruitment to the public sector 
The UK-LFS does not ask if respondents are 
waiting for the results of a competition for 
recruitment to the public sector 
The high level of non-response is due to the fact 
that not all people who have completed a course in 
the last 4 weeks are asked how many hours of 
instruction that have attended in total 

United Kingdom 

compulsory 

TEMPDUR 

55 

56.4 

54.5 

53.2 

compulsory 

HWOVERP 

90.7 

89.7 

90.1 

90.2 

compulsory 

HWOVERPU 

84.3 

82.9 

85.8 

86.1 

compulsory 

HWWISH 

89.9 

90.4 

90.2 

90.6 

compulsory 

METHODG - 
employed 

C 

. 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

METHODG - 
not employed 

METHODK - 
employed 
METHODK - 
not employed 
METHODL - 
employed 

METHODL - 
not employed 

. 

C 

. 

C 

. 

C 

. 

C 

. 

C 

C 

C 

C 

C 

C 

C 

C 

. 

C 

. 

C 

. 

compulsory 

COURLEN 

72.2 

73.6 

73.7 

73.1 

Iceland 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

COUNTRYW  C 
C 
REGIONW 
10.9 
TEMPDUR 
63.4 
HWOVERP 
63.4 
HWOVERPU 
11.2 
HOURREAS 
33.1 
HWWISH 
12.2 
HWACTUA2 
100 
SEEKTYPE - 
employed 
SEEKTYPE - 

. 

C 
C 
. 
65.7 
65.7 
11.5 
33.3 
16.2 
100 

C 
C 
. 
71.7 
71.7 
12.9 
34.6 
17.5 
100 

22.9 

. 

C 
C 
10.4 
71 
70.9 
12.3 
34.7 
13.9 
100 

10.6 

Quality report of the European Union Labour Force Survey 2016 

48 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Identifier 

Q1 

Q2 

Q3 

Q4 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

Annex 

. 

C 

C 

C 

C 

C 

C 

C 

C 

100 

not employed 
SEEKDUR - 
employed 
SEEKDUR - 
not employed 
METHODA - 
employed 
METHODB - 
employed 
METHODC - 
employed 
METHODD - 
employed 
METHODE - 
employed 
METHODF - 
employed 
METHODG - 
employed 
METHODG - 
not employed 
METHODH - 
employed 
METHODI - 
employed 
METHODI - 
not employed 
METHODJ - 
employed 
METHODK - 
employed 
METHODK - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 
METHODM - 
employed 
WANTWORK  27.2 
COURLEN 
EDUCLEVL 

13 
100 

C 

C 

C 

C 

C 

C 

C 

C 

. 

31.1 
48.2 
13.8 
12.7 
10.2 
. 

. 

COUNTRYW  C 
MSTARTWK 
TEMPDUR 
WISHMORE 
LOOKOJ 
HWACTUA2 
SEEKDUR - 
employed 
SEEKDUR - 
not employed 
METHODH - 
not employed 
METHODI - 
employed 
METHODI - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 
COUNTRYB 

C 

C 

C 

. 

C 

17.2 

METHODH - 

. 

100 

100 

100 

23.9 

. 

10.8 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

C 

32.9 
14.6 
100 

. 
35 
46.6 
14.8 
13.6 
10.5 
10.8 

13.4 

. 

. 

. 

30 
18 
100 

. 
37.1 
43 
13.5 
12.5 
10.3 
. 

. 

. 

. 

. 

C 

C 

C 

. 

. 

. 

. 

. 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

27.9 
16.1 
100 

. 
39.3 
46.1 
13.7 
12.2 
. 
11.5 

10.8 

. 

C 

. 

C 

C 

. 

C 

No relevant respondent declared to have used this 

Variable 
status 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 
compulsory 
compulsory 
Norway 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

optional 
Switzerland 
compulsory 

Quality report of the European Union Labour Force Survey 2016 

49 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Annex 

Short comments on reasons for non-available 
statistics and prospects for future solutions 

method. 
No relevant respondent declared to have used this 
method. 
No relevant respondent declared to have used this 
method. 
No relevant respondent declared to have used this 
method. 
No relevant respondent declared to have used this 
method. 
No relevant respondent declared to have used this 
method. 
METHODL is not relevant for Switzerland. 

METHODL is not relevant for Switzerland. 

We plan to introduce this variable in the future 
We plan to introduce this variable in the future 

We plan to introduce this variable in the future 

We plan to introduce this variable in the future 

Variable 
status 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 
Turkey 
compulsory 

Identifier 

Q1 

Q2 

Q3 

Q4 

employed 
METHODH - 
not employed 
METHODI - 
employed 
METHODI - 
not employed 
METHODK - 
employed 
METHODK - 
not employed 
METHODL - 
employed 
METHODL - 
not employed 

. 

. 

C 

C 

. 

C 

C 

C 

C 

. 

. 

. 

C 

C 

REGIONW 
METHODK - 
employed 
METHODL - 
employed 
METHODL - 
not employed 
DEGURBA 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

C 
C 

C 

. 

. 

. 

C 

. 

. 

C 

C 

C 
. 

C 

C 

Former Yugoslav Republic of Macedonia 
compulsory 
compulsory 

C 
. 

C 
. 

100.0  100.0  100.0  100.0  We plan to introduce this variable in the future 

NATIONAL 

100.0  100.0  100.0  100.0  According to the 2010 Address Based Population 

compulsory 

COUNTRYW 

. 

. 

C 

. 

Registration System; 99.7 % of population has 
Turkish Nationality. So, it is not easy to cover non-
nationals with a sample survey. 
There are very few people who are working abroad 
and at the same time considered as household 
member since Turkey is a very broad country. This 
may only occur in border cities, but not common. 
So, this variable is not asked. 

compulsory 

HWOVERPU 

100.0  100.0  100.0  100.0  Only total overtime is asked in the questionnaire 

(paid+unpaid). Since it is not possible to distinguish 
paid and unpaid overtime. Total overtime is given in 
HWOVERP and this variable is coded as blank. 

compulsory 

HWWISH 

100.0  100.0  100.0  100.0  This variable was dropped out from the 

compulsory 

compulsory 

compulsory 

compulsory 

compulsory 

METHODB - 
employed 

METHODF - 
employed 

METHODI - 
employed 

METHODK - 
employed 

METHODL - 
employed 

compulsory 

METHODM - 
not employed 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

. 

C 

C 

C 

C 

C 

. 

. 

. 

. 

. 

. 

C 

questionnaire in 2009 since it was observed that, 
results were not reliable.   
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 
For employed people all the methods are not asked 
in same detail, some of them are grouped looking 
at the frequency. 

compulsory 

DEGURBA 

100.0 

C 

100.0  100.0 

Note: ‘C’ All records have the same value 

Quality report of the European Union Labour Force Survey 2016 

50 

 
 
 
 
 
  
  
  
  
  
  
  
Annual data 2016 

Annex 

Variable 
status 

Belgium 

compulsory 

Bulgaria 

compulsory 

optional 
Czech 
Republic 
compulsory 
optional 
optional 
optional 

Denmark 

optional 
optional 
optional 

Germany 

compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
optional 
optional 
optional 
Estonia 

Identifier 

This 
reference 
year 

Short comments on reasons for non-available statistics and 
prospects for future solutions 

AVAIREAS - 
not employed 

91.0 

Early retired persons are asked if they are searching a job. If not, they 
are not asked if they want a job. So we don't know for these persons if 
they are available. 

AVAIREAS -  
employed 

32.6 

COURWORH 

100.0 

Persons who are employed but temporary absent from work (e.g. on 
parental leave) - cases with SIGNISAL=3, were not asked this question 
due to the limitations of paper questionnaire. The future decision will 
depend on the existence of variable SIGNISAL. 
The variable is not available in the national LFS. 

INCDECIL 
COURPURP 
COURFILD 
COURWORH 

100.0 
100.0 
100.0 
100.0 

 We will send dataset with this variable during the next year (imputation). 
 Czech LFS does not survey this variable 
 Czech LFS does not survey this variable 
 Czech LFS does not survey this variable 

COURPURP 
COURFILD 
COURWORH 

100.0 
100.0 
100.0 

SUPVISOR 
WAYJFOUN 
TEMPREAS 
TEMPAGCY 
NEEDCARE 
WSTAT1Y 
COUNTR1Y 
MAINSTAT 
COURFILD 
COURWORH 

24.4 
15.4 
30.3 
25.5 
30.0 
12.0 
13.5 
100.0 
10.3 
100.0 

compulsory 

TEMPREAS 

22.1 

Persons having ‘no preference’ were coded as ‘blank’. The variable will 
be improved during the next revision of the questionnaire (then 
implementing the IESS Framework Regulation). 

Ireland 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

SIZEFIRM 
WAYJFOUN 
TEMPREAS 
STAPROPR 
AVAIREAS - 
employed 
PRESEEK 
REGISTER 
WSTAT1Y 
COUNTR1Y 
REGION1Y 

compulsory 

INCDECIL 

optional 
optional 
optional 
Greece 

compulsory 

compulsory 
Spain 

compulsory 

COURPURP 
COURFILD 
COURWORH 

AVAIREAS - 
employed 

23.1 

INCDECIL 

11.8 

AVAIREAS - 
employed 

22.1 

13.6 
48.5 
18.9 
100.0 

96.1 

100.0 
100.0 
100.0 
100.0 
C 

71.0 

47.8 
100.0 
22.1 

Not stated answers arise from respondents 

Not stated answers arise from respondents 
Not currently collected 

Not currently collected 
Not currently collected 
Not currently collected 
Not currently collected 

Question only asked to direct respondents due to sensitive nature of 
question 
Not stated answers arise from respondents 
Not currently collected 
Not stated answers arise from respondents 

In the Greek Questionnaire there is the (residual) answer category "Did 
not specify the reason" (which is converted in "No answer"). It should be 
tested if the exclusion of this answer category would reduce the non-
response in this variable. 
It is a sensitive question in which people tend to refuse to answer. 

Quality report of the European Union Labour Force Survey 2016 

51 

 
 
 
 
 
  
  
  
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Annex 

Short comments on reasons for non-available statistics and 
prospects for future solutions 

It will be provided from registers in due time. 
People aged 15. 
People aged 15. 
Not provided. 

Question is not asked to people working in an informal job, or with a 
temporary employment agency contract. 
Some of the people declaring they have no contract are reclassified as 
temporary contracts (TEMP = 2). Yet we don't have the reason. A 
solution will be studied. 
PRESEEK is not asked in the French LFS questionnaire. However, this 
variable is rebuilt for people who have been seeking a job for one year 
or less. 
Information is currently not available for people over 65.  
Question is not asked to people under 15. 
The non-response come from different reasons: for 18%, people did not 
answer to the question; for 50%, people gave a net income, but in 
income groups; for 32%, people only gave a gross income. A solution 
will be studied to lower non response. 
Question is not asked to people over 65. 

This non-response refers to persons under 15 (children) which should 
be coded as a single. Real non-response to this question is not 
possible. 
People do not know information on number of persons working at the 
local unit. In order to reduce non-response, interviewers will be 
instructed to further emphasize the possible selection between codes 14 
(Do not know but less than 11 persons) or 15 (do not know but more 
than 10 persons) which respondents can choose in case of non-
response. 
Will be improved in the future. 

Will be improved in the future. 

Variable 
status 

compulsory 

compulsory 
optional 
optional 
optional 
France 

Identifier 

AVAIREAS - 
not employed 
INCDECIL 
COURPURP 
COURFILD 
COURWORH 

This 
reference 
year 

12.3 

100.0 
17.7 
17.7 
100.0 

compulsory 

WAYJFOUN 

18.8 

compulsory 

TEMPREAS 

11.2 

compulsory 

PRESEEK 

compulsory 
compulsory 

REGISTER 
COUNTR1Y 

47.8 

13.0 
17.8 

compulsory 

INCDECIL 

25.4 

optional 
Croatia 

COURPURP 

11.1 

compulsory 

MARSTAT 

12.5 

compulsory 

SIZEFIRM 

12.6 

compulsory 

compulsory 

compulsory 

LOOKREAS 
AVAIREAS - 
employed 
AVAIREAS - 
not employed 

22.8 

77.3 

16.2 

Will be improved in the future.  

compulsory 

COUNTR1Y 

13.1 

compulsory 

INCDECIL 

optional 
Italy 

COURFILD 

26.1 

100.0 

compulsory 

COUNTR1Y 

12.3 

Non-response refers to children under the age of 15 who do not answer 
the question on country of residence one year before survey. 
People do not want to give an answer on this sensitive issue especially 
in the case of proxy interview. 
Optional. Will not be collected. 

Item non-response is due to people aged less than 15 years, for which 
this information is not collected in the national questionnaire 

Cyprus 
compulsory 
Latvia 
compulsory 
compulsory 
optional 
Lithuania 

REGION1Y 

C 

NUTS 2 is the whole of CY 

WSTAT1Y 
REGION1Y 
MAINSTAT 

14.3 
C 
14.3 

There are not interviewed persons aged 75 or more included in filter. 
Data about workplace are collected at NUTS1 level 
There are not interviewed persons aged 75 or more included in filter. 

All records have two values: 00 or 99. Statistics Lithuania collects 
statistics on NUTS 3 level for this variable. 
This variable is optional and not collected. 
This variable is optional and not collected. 
This variable is optional and not collected. 

compulsory 

REGION1Y 

C 

optional 
optional 
optional 
Luxembourg 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 
compulsory 

COURPURP 
COURFILD 
COURWORH 

100.0 
100.0 
100.0 

HHLINK 
TEMPREAS 
LOOKREAS 
AVAIREAS - 
not employed 
REGISTER 
NACE1Y2D 

C 
21.0 
10.3 

17.2 

10.8 
12.1 

Quality report of the European Union Labour Force Survey 2016 

52 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Annex 

Short comments on reasons for non-available statistics and 
prospects for future solutions 

There is an upper-age limit (74 years) in HU-LFS for this variable. 
Till 2014, for missing values of INCDECIL cold-deck donor imputation 
method was used, missing values were replaced with donor data 
coming from the previous/following periods of LFS data collections 
Since it was proved to be not appropriate, data transmission to Eurostat 
for this variable was stopped. We intend to send INCDECIL data for 
missing values based on hot deck imputation by the end of 2017 (only 
as a temporary solution) 
There is an upper-age limit (74 years) in HU-LFS for this variable. 
There is an upper-age limit (74 years) in HU-LFS for this variable. 
There is an upper-age limit (74 years) in HU-LFS for this variable. 

 Further analysis in the future will be carried out to ensure non response 
rate. 
 Information on this variable is not collected. 
 Information on this variable is not collected. 

Variable 
status 

compulsory 
Hungary 
compulsory 

Identifier 

INCDECIL 

This 
reference 
year 
16.3 

WSTAT1Y 

11.2 

compulsory 

INCDECIL 

100.0 

MAINSTAT 
COURPURP 
COURWORH 

AVAIREAS - 
employed 
COURFILD 
COURWORH 

FTPTREAS 
TEMPREAS 
STAPROPR 
NACEPR2D 
ISCOPR3D 
AVAIREAS - 
not employed 
PRESEEK 
WSTAT1Y 
NACE1Y2D 
COURWORH 

11.2 
11.1 
11.1 

78.7 

100.0 
100.0 

11.9 
33.6 
65.7 
70.0 
79.2 

40.2 

72.8 
16.5 
10.8 
12.6 

optional 
optional 
optional 
Malta 

compulsory 

optional 
optional 
Netherlands 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 
compulsory 
compulsory 
optional 
Austria 
compulsory 
Poland 

INCDECIL 

100.0 

Delivered yearly with delay since basic data originates from registers. 

compulsory 

INCDECIL 

61.3 

Very sensitive variable which makes it possible for respondent to not 
answer this question 

Portugal 

compulsory 

INCDECIL 

optional 
optional 
optional 
Slovenia 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

optional 
Slovakia 

COURPURP 
COURFILD 
COURWORH 

MARSTAT 
WAYJFOUN 
NACEPR2D 
ISCOPR3D 
AVAIREAS - 
employed 
COURFILD 

Corresponds to non-response of the employees who did not give an 
answer to the income variable. 
This variable does not exist in our national questionnaire 
This optional variable was not included in our national questionnaire.  
This optional variable was not included in our national questionnaire.  

11.4 

100.0 
100.0 
100.0 

13.6 
21.7 
64.3 
64.4 

100.0 

100.0 

This optional variable was not collected 

compulsory 

INCDECIL 

28.5 

Finland 

compulsory 

WSTAT1Y 

20.1 

compulsory 

COUNTR1Y 

optional 
Sweden 

compulsory 

compulsory 
compulsory 

COURFILD 

AVAIREAS - 
employed 
REGISTER 
WSTAT1Y 

41.9 

100.0 

75.0 

19.3 
46.1 

Very sensitive nature of question for the field survey. Since 2016 we 
have started to use the new administrative source: Structure of Earnings 
Survey that substituted the LFS variable. 

As Finland is using persons as sampling units, this variable is optional 
for other members of the household. 
As Finland is using persons as sampling units, this variable is optional 
for other members of the household.  
Optional variable not collected 

The high non-response is due to employed who does not look for 
another job. 
The question is not given to employed who are not searching for a job. 
Even if a new solution of collecting the data was used during 2007 only 

Quality report of the European Union Labour Force Survey 2016 

53 

 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Annex 

Variable 
status 

Identifier 

This 
reference 
year 

Short comments on reasons for non-available statistics and 
prospects for future solutions 

some little improvements has been done since then. 

compulsory 
optional 
optional 
optional 
United Kingdom 

INCDECIL 
COURPURP 
COURFILD 
COURWORH 

100.0 
100.0 
100.0 
100.0 

 Optional. Not collected 
 Optional. Not collected 
 Optional. Not collected 

The current calculation of TEMPREAS assigns WHYTMP6 = 5 (some 
other reason) to 'Blank' (no answer). The Eurostat codification allows 
only four values (covered by the first four response categories). It is not 
clear how those respondents who answer 'some other reason' should be 
coded.  
TEMPAGCY is derived from national variable TMPCON (contract with 
employment agency). TMPCON is asked only if HOWGET = 5 (private 
employment agency). If TEMPAGCY were filtered by HOWGET = 5 then 
NR would be < 2%. 

Refusal = 12.63%; non-contact (no proxy data collected) = 3.38%; no 
pay yet received = 0.03% 
Not currently included in UK-LFS. 
The national variable from which COURPURP is calculated - T4PURP - 
is asked only of specific forms of taught-learning. Revisions to the 
national taught-learning variables in 2016 have reduced INR from > 70% 
to the current 15%.   
As for COURPURP 

compulsory 

TEMPREAS 

34.6 

compulsory 

TEMPAGCY 

98.5 

compulsory 

compulsory 

compulsory 

AVAIREAS - 
employed 
AVAIREAS - 
not employed 
NEEDCARE 

compulsory 

INCDECIL 

69.4 

34.3 

56.8 

25.4 

optional 

MAINSTAT 

100.0 

optional 

COURPURP 

75.5 

optional 
Iceland 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 

compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
optional 
Norway 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
compulsory 

compulsory 

compulsory 

compulsory 
compulsory 
compulsory 
compulsory 
compulsory 
optional 
optional 
optional 
Switzerland 

COURWORH 

75.5 

TEMPREAS 
TEMPAGCY 
LOOKREAS 
STAPROPR 
NACEPR2D 
SEEKREAS 
AVAIREAS - 
employed 
AVAIREAS - 
not employed 
PRESEEK 
NEEDCARE 
COUNTR1Y 
REGION1Y 
INCDECIL 
COURFILD 

WAYJFOUN 
FTPTREAS 
TEMPREAS 
NACEPR2D 
ISCOPR3D 
SEEKREAS 
AVAIREAS - 
employed 
AVAIREAS - 
not employed 
PRESEEK 
REGISTER 
COUNTR1Y 
REGION1Y 
INCDECIL 
COURPURP 
COURFILD 
COURWORH 

38.4 
C 
31.6 
67.4 
50.7 
26.7 

100.0 

65.9 

12.8 
91.1 
75.3 
C 
100.0 
100.0 

29.5 
30.1 
19.2 
100.0 
100.0 
33.3 

24.2 

10.8 

21.8 
100.0 
100.0 
C 
100.0 
100.0 
18.5 
100.0 

Quality report of the European Union Labour Force Survey 2016 

54 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
Variable 
status 

Identifier 

This 
reference 
year 

compulsory 

TEMPREAS 

24.1 

compulsory 

NACEPR2D 

11.3 

compulsory 

NEEDCARE 

27.9 

optional 
optional 
optional 
Former Yugoslav Republic of Macedonia 

WAYMORE 
COURFILD 
COURWORH 

29.4 
100.0 
100.0 

Annex 

Short comments on reasons for non-available statistics and 
prospects for future solutions 

A considerable amount of respondents have indicated "other reasons" 
(without specification). As TEMPREAS does not have such a residual 
category, these respondents have to be coded "blank". 
A major part of the non-response in NACEPR2D is due to the fact that 
the local unit indicated by respondents does not (or not anymore) figure 
in the register which is used to derive the economic activity according to 
NACE. 
Filter problem. No adaptation planned for the time being, as there are 
ongoing discussions about future changes of NEEDCARE. 
Filter/codification error, adaptation is planned 
Not asked in the SLFS. 
Not asked in the SLFS. 

15.4 

100.0 

Marital status is the conjugal status of each individual in relation to the 
marriage laws of the country.  
We have implemented the variable. 

96.0 

We have implemented the variable. 

compulsory 

MARSTAT 

compulsory 

compulsory 

compulsory 
compulsory 

HOMEWK 
AVAIREAS - 
not employed 
PRESEEK 
NEEDCARE 

100.0 
100.0 

compulsory 

REGISTER 

86.4 

compulsory 

COUNTR1Y 

16.9 

compulsory 

REGION1Y 

C 

compulsory 
optional 
Turkey 

INCDECIL 
MAINSTAT 

100.0 
100.0 

compulsory 

TEMPAGCY 

100.0 

compulsory 

AVAIREAS - 
employed 

C 

compulsory 

REGISTER 

100.0 

optional 
optional 
optional 

COURPURP 
COURFILD 
COURWORH 

100.0 
100.0 
100.0 

Note: ‘C’ All records have the same value  

This variable is planned to be introduced in the future. 
This variable is planned to be introduced in the future. 
For this variable we did not collect information for persons who are not 
registered in our employment agency because they cannot apply for 
benefit. 
For this variable we collected the information for persons 15-79; for 
other persons we did not have any information. In the future we plan to 
improve this. 
For this variable we collected the information for persons 15-79; for 
other persons we did not have any information. In the future we plan to 
improve this. 
We have implemented the variable. 
The variable is optional but will be introduced in the future. 

This variable is not asked since temporary working agencies are not 
common in Turkey for the moment. 
This variable is not available for employed since 2009. It had been 
asked until 2009 and found unnecessary when examined the frequency. 
This question is not asked since the coverage of unemployment benefits 
is very limited in Turkey (around 10% of registered unemployed are 
receiving unemployment benefit at the current situation). 
This optional variable is not collected since 2014 
This optional variable is not collected since 2014 
This optional variable is not collected since 2014 

Quality report of the European Union Labour Force Survey 2016 

55 

 
 
 
 
 
 
 
 
 
10.2  Data presentation and abbreviations 

Annex 

Not available; 
Not applicable. 

Data presentation 
The following symbols are used, where necessary: 
:  
– 
Geographical aggregates and country codes 
EU-28 
EU 
BE 
BG  
CZ  
DK 
DE  
EE  
IE  
EL 
ES 
FR  
HR 
IT  
CY  
LV  
LT  
LU  
HU  
MT  
NL  
AT  
PL  
PT  
RO  
SI  
SK  
FI  
SE  
UK  
IS 
NO 
CH 
MK(20)  
TR  

European Union of 28 Member States 
European Union 
Belgium 
Bulgaria 
Czech Republic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United Kingdom 
Iceland 
Norway 
Switzerland 
the Former Yugoslav Republic of Macedonia 
Turkey 

(20)  Provisional ISO code which does not prejudge in any way the definitive nomenclature for this country, which is to be agreed 

following the conclusion of negotiations currently taking place on this subject at the United Nations. 

Quality report of the European Union Labour Force Survey 2016 

56 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                           
 
 
Getting in touch with the EU 

In person 
All over the European Union there are hundreds of Europe Direct Information Centres. You can 
find the address of the centre nearest you at: http://europa.eu/contact 

On the phone or by e-mail 
Europe Direct is a service that answers your questions about the European Union. You can 
contact this service  
– by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls),  
– at the following standard number: +32 22999696 or  
– by electronic mail via: http://europa.eu/contact 

Finding information about the EU 

Online 
Information about the European Union in all the official languages of the EU is available on the 
Europa website at: http://europa.eu   

EU Publications 
You can download or order free and priced EU publications from EU Bookshop at: 
http://bookshop.europa.eu. Multiple copies of free publications may be obtained by contacting 
Europe Direct or your local information centre (see http://europa.eu/contact) 

EU law and related documents 
For access to legal information from the EU, including all EU law since 1951 in all the official 
language versions, go to EUR-Lex at: http://eur-lex.europa.eu 

Open data from the EU 
The EU Open Data Portal (http://data.europa.eu/euodp/en/data) provides access to datasets from 
the EU. Data can be downloaded and reused for free, both for commercial and non-commercial 
purposes. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Quality report of the  
European Union 
Labour  Force Survey 2016

The purpose of this quality report is to provide the users of the European 
Union Labour Market Statistics with a tool for assessing the quality of 
these statistics which are based on the European Union Labour Force 
Survey. It provides a brief description of the survey and a summary of the 
main quality indicators which are: relevance, accuracy, accessibility and 
clarity, timeliness and punctuality, comparability, and coherence. The 
quality report is updated annually.

For more information
https://ec.europa.eu/eurostat/

K
S
-
F
T
-
1
8
-
0
0
8
-
E
N
N

-

ISBN  978-92-79-96567-8

Main title 2018 edition