Quality report of the European Union : labour force survey : 2015 edition.
Date: 2015-10-02
Institutions: Eurostat
Subjects: EU statistics, European Union, data collection, labour force, report, sample survey, statistical method, statistics, working population

ISSN 1681-4789
ISSN 2315-0807

Statistical working papers

Quality report of the European Union  
Labour Force Survey
2014

2015 edition

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Statistical working papers

Quality report of the European Union
Labour Force Survey 
2014

2013 edition
2015 edition

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Luxembourg: Publications Office of the European Union, 2015 

ISBN 978-92-79-50393-1 
ISSN 2315-0807 
doi:10.2785/649745
Cat. No: KS-TC-15-004-EN-N 

Theme: Population and social conditions 
Collection: Statistical working papers 

© European Union, 2015 
Reproduction is authorised provided the source is acknowledged. 

 
 
 
 
 
 
 
 
Table of contents 

Table of contents ............................................................................................................................................... 3 

1 

Introduction............................................................................................................................................... 4 

2  Overview of designs and methods of the EU-LFS in 2014....................................................................... 5 

2.1 

2.2 

2.3 

2.4 

2.5 

2.6 

2.7 

2.8 

Coverage........................................................................................................................................ 5 

Legal basis..................................................................................................................................... 5 

Compulsory participation .............................................................................................................. 5 

Reference week .............................................................................................................................. 5 

Periodicity of the results ................................................................................................................ 6 

Sampling designs ........................................................................................................................... 6 

Rotation schemes ........................................................................................................................... 7 

Calculation of the weighting factors.............................................................................................. 7 

2.9  Data collection methods ................................................................................................................ 8 

2.10  Use of subsamples to survey structural variables.......................................................................... 9 

3 

Relevance.................................................................................................................................................. 9 

3.1 

3.2 

The users........................................................................................................................................ 9 

Completeness ............................................................................................................................... 10 

4  Accuracy ................................................................................................................................................. 12 

4.1 

4.2 

Sampling errors ........................................................................................................................... 12 

Non-sampling errors.................................................................................................................... 14 

5 

Timeliness and punctuality ..................................................................................................................... 19 

6  Accessibility and clarity.......................................................................................................................... 20 

7 

Comparability ......................................................................................................................................... 21 

7.1 

 Comparability over time ............................................................................................................. 21 

7.2   Comparability over space............................................................................................................ 23 

8 

Coherence ............................................................................................................................................... 24 

8.1 

8.2 

Coherence with population statistics ........................................................................................... 24 

Coherence with other employment estimates............................................................................... 26 

9 

Regional labour market statistics ............................................................................................................ 29 

9.1 

9.2 

Introduction ................................................................................................................................. 29 

Sources for NUTS 3 level labour market statistics ...................................................................... 29 

10  Annex I: Item non-response for the variables defined by Commission Regulation (EC) No 377/2008 

and clarifications provided by Member States........................................................................................ 31 

11  Annex II: Data presentation and abbreviations ....................................................................................... 48 

Data presentation.................................................................................................................................... 48 

Geographical aggregates and country codes.......................................................................................... 48 

Quality report of the European Union Labour Force Survey — 2014 

3

 
 
 
 
1 

Introduction 

The present report is the Quality Report on the European Union Labour Force Survey (EU-
LFS) for the year 2014. 

The quality concept applied in this report is in conformity with the definition developed by 
the  European  Statistical  System.  In  this  definition  quality  consists  of  the  following 
components:  relevance,  accuracy,  timeliness  and  punctuality,  accessibility  and  clarity, 
comparability  and  coherence.  Each  quality  component  consists  also  of  several  sub-
components.  Each  of  the  quality  components  is  explained  shortly  at  the  start  of  each 
section in the following report (1). 

The individual country quality reports that were delivered to Eurostat during summer 2015 
constitute  the  main  source  for  the  present  report.  Other  sources  that  have  been  used  or 
consulted  are  meta-data  information  collected  by  Eurostat,  national  quality  reports  from 
previous  years,  websites  of  the  individual  countries,  the  LFS  datasets  for  2014  and  the 
documentation of the public free data set maintained by Eurostat. 

The present quality report follows closely the standard Quality Report format that has been 
developed within Eurostat. In many instances, however, it is impossible to present the data 
exactly  as  prescribed  by  the  standard  Eurostat  format,  as  this  is  geared  to  report 
homogeneous production processes within each country. This is not the case for the EU-
LFS, which is the result of the collection of national data sets from NSIs. In some cases the 
information from the individual countries was not sufficient to provide an exact summary.  

The quality reports provide also information on unemployment statistics at regional level, 
as the reporting of quality is a joint effort of the units within Eurostat dealing with labour 
force  surveys  and  with  regional  employment  and  unemployment.  The  last  chapter  of  the 
present report covers the regional aspects. 

This  quality  report  complements  the  methodological  working  paper  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 the many experts in the countries participating in the conduct of 
the EU-LFS, providing the data and descriptions as well as their support necessary for 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/web/products-statistical-working-papers/-/KS-TC-15-003 

Quality report of the European Union Labour Force Survey — 2014 

4

 
 
 
 
 
 
 
 
                                                           
2  Overview of designs and methods of the EU-LFS in 2014 

2.1  Coverage 

This  document  covers  all  the  thirty-three  countries  (participating  countries)  providing 
Eurostat with micro-data from their labour force surveys in 2014: 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.  

In Eurostat datasets all age groups are represented for all participating countries, with the 
exception  of  Iceland,  Norway,  Sweden  and  Switzerland,  which  only  provide  data 
respectively for those aged 16-74, 15-74 (Norway and Sweden) and 15 and more.  

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 the rules and guidelines to assure the comparability 
of the results by regulating the survey designs, the survey characteristics, methods and the 
decision  making  processes  of  the  EU-LFS.    A  detailed  overview  on  the  EU-LFS 
regulations is published in Statistics Explained ‘EU-LFS – main features and legal basis’. 

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

2.3  Compulsory participation 

In 2014 the participation in the EU-LFS was compulsory in thirteen participating countries 
(Belgium,  Germany,  Greece,  Spain,  France,  Italy,  Cyprus,  Malta,  Austria,  Portugal, 
Slovakia, Norway and Turkey), and voluntary in the other countries. 

2.4  Reference week 

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. 

(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 referred to quarter 2. 

Quality report of the European Union Labour Force Survey — 2014 

5

 
 
                                                           
2.5  Periodicity of the results 
All participating countries in the EU-LFS in 2014 produce quarterly estimates (5).  

2.6  Sampling designs 

The sampling designs 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  lists  of 
addresses from, e.g., the Postal Authorities or Utility databases. Belgium, Italy, Lithuania, 
Austria, Norway, Finland, Sweden, Iceland, Slovenia and Switzerland use the Population 
Registers  as  the  sole  basis  while  the  Netherlands  complete  this  information  with  postal 
data, Denmark with other registers, Latvia and Spain with Census information. Germany 
grounds  the  sample  frame  on  the  1987  Census  in  the  western  part (6)  and  on  the  Central 
Population Register, based on the 1981 Census, in the east, both updated by the Register of 
new  dwellings.  France  uses  the  tax  register  for  Metropolitan  France  and  the  annual 
Population Census for the oversea departments. 

Sampling stages and primary sampling units (PSU) 

Denmark,  Germany,  Cyprus,  Estonia,  Luxembourg,  Malta,  Austria,  Slovenia,  Finland, 
Sweden,  the  United  Kingdom,  Iceland,  Lithuania,  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 (7). 
Ultimate sampling units 

Three  types  of  ultimate  sampling  units  are  employed:  1)  households,  2)  dwellings/ 
addresses  and  3)  persons.  Germany,  France,  Portugal  and  Romania  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 (Finland, 
Sweden, Denmark, Iceland, and Switzerland) or the sampled persons lead to a final sample 
comprised of the sampling units and their household members (Estonia, Lithuania, Norway 
and Slovenia). 

Overall sampling rate 

The theoretical sampling rate per quarter (ultimate sampling units) of the EU-LFS is 0.5 % 
(EU-28: 0.53 %). Luxembourg (5.0 %) and Malta (2.1 %) have by far the highest sampling 
rates per quarter, followed by Iceland (1.9 %), Cyprus and Ireland (both 1.5 %) while most 
other participating countries have sampling rates of 1 % or less. On average, the achieved 
quarterly sample in 2014 in all participating countries was 1.754 million individuals (EU-28: 

(5)  Under  Regulation  (EC)  No  577/98  a  specific  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 
chapter 2.10). 

(6)  The continuous population updating procedure which updates last German census in 1987 in the western 
part  and  the  Central  Population  Register  in  the  east  by  using  statistics  on  births,  deaths  and  migration 
provides population figures used for calibration. These old updated bases which are used also as sample 
frame for dwellings not built after 1987 and 1981 respectively may lead to some bias in LFS results. 

(7) Ireland is a special case, using a two-stage cluster design (see EU-LFS quality report 2009). 

Quality report of the European Union Labour Force Survey — 2014 

6

 
 
                                                           
1.551 million), of which 1.348 million were in the age group 15–74 years (EU-28: 1.195 
million).  The  achieved  sample  in  the  EU-LFS  is  thus  approximately  0.30 %  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 include for example register status of individuals in 
employment/unemployment  registers  and  auxiliary  information  about  the  characteristics 
(size, type) of the primary sampling units.  

2.7  Rotation schemes 

All participating countries except Belgium and Luxembourg use a rotating panel design for 
the  samples.  The  number  of  panels  (waves)  ranges  from  two  to  eight.  All  panel  designs 
foresee 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 
2014,  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, each used by six countries, are in for 5 and in for 6 waves, 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  the  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  outcomes  of  overlaps  between  two  successive  quarters  or  between  the  same 
quarters  in  two  successive  years.  All  panel  designs  with  a  quarter-to-quarter  overlap 
foresee  an  overlap  of  50  %  or  more (8)  of  the  sample  between  two  successive  quarters. 
There is less emphasis on overlap between corresponding quarters in two successive years. 
Two countries, Belgium and Luxembourg, have no overlap; six 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.  

2.8  Calculation of the 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)  inverse  of  the  selection  probabilities 
adjusted a posteriori to the population’s distribution by sex, age groups and other external 
(administrative)  sources,  and  2)  different  variations  of  adjusting  to  marginal  totals, 
including generalized calibration and generalized regression. Most of the countries adjust 

(8)  These  percentages  are  only  theoretical;  the  actual  overlaps  are  lower  due  to  non-response  and  panel 

attrition. 

Quality report of the European Union Labour Force Survey — 2014 

7

 
 
                                                           
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    in  calculating  the  weighting  factors,  exceptions  are  Germany,  Greece,    and 
Slovenia) (9). The three countries use broader age groups than five-year ones. All countries 
that have NUTS 2 regions defined use at least NUTS 2 regions for calculating the weights, 
but  twenty-one  countries  (Bulgaria,  the  Czech  Republic,  Germany,  Croatia,  Estonia, 
Greece,  Spain,  Ireland,  former  Yugoslav  Republic  of  Macedonia,  Italy,  Hungary,  Latvia, 
Lithuania,  Malta,  Slovakia,  Slovenia,  Portugal,  Finland,  Sweden,  Switzerland,  and 
Norway) use a more detailed regional classification (NUTS 3 or LAU1; groups of NUTS 
3). 

Denmark,  Finland,  Sweden,  Norway  and  Austria  use  register  statistics  on  employment/ 
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. 

Fifteen  countries,  namely  Belgium,  the  Czech  Republic,  Germany,  Estonia,  Ireland, 
Lithuania, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, the United Kingdom, 
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,  Czech  Republic, 
Ireland,  Slovenia)  or  only  partially  (Portugal,  Romania,  Slovakia)  cover  the  institutional 
population in data collection. 

2.9  Data collection methods 

Four modes of data collection exist for the EU-LFS: personal visits, telephone interviews, 
web  interviews  and  self-administered  questionnaires.  More  than  half  of  the  countries 
conduct  the  first  wave  always  or  mainly  via  personal  visit,  while  subsequent  waves  are 
interviewed  with  telephone,  if  available.  Germany  collects  data  mainly  with  face-to-face 
interviews  (using  CAPI);  persons  not  available  for  the  interviewer  or  refusing  oral 
interviews  are  in  a  few  cases  interviewed  by  telephone  or  more  frequently  fill  in  self-
administered postal questionnaires. Denmark collects data for the core-LFS with telephone 
interviews  (CATI),  but  for  the  household  subsample  computer  assisted  web  interviews 
(CAWI) are used. Belgium conducts the interviews by means of face-to-face (CAPI), but 
in  households  of  retired  persons,  interviews  can  be  conducted  by  telephone.  The 
Netherlands uses computer assisted web interviews (CAWI), interviews by means of face-
to-face  (CAPI)  and  telephone  interviews  (CATI).  Six  countries  (Luxembourg,  Finland, 
Sweden,  Iceland,  Norway  and  Switzerland)  rely  solely  on  telephone  interviews.  Italy, 
Spain and Portugal use a mixed mode CAPI-CATI: CAPI mainly for first wave and CATI 
mainly  for  later  waves.  Five  countries  (Bulgaria,  Ireland,  Romania,  Croatia  and  Turkey) 
collect  data  using  only  face-to-face  interviews.  Among  those  Ireland  and  Turkey  using 
computerized questionnaires (CAPI). 

(9)  Luxembourg, Poland, and Turkey use the five-year age groups up until the 60–64 years old. 

Quality report of the European Union Labour Force Survey — 2014 

8

 
 
                                                           
Most countries conduct the interview only with computerized questionnaires. Six (Malta, 
Germany, Greece, Lithuania, Poland and the former Yugoslav Republic of Macedonia) use 
both  computerized  and  paper  questionnaires  and  three  countries  (Bulgaria,  Romania, 
Croatia) rely solely on paper questionnaires. 

Due to the different data collection mode information on how long the interview lasted per 
household  or  person  are  hardly  comparable.  On  average  the  overall  time  to  collect  the 
information for the household is around 30 minutes for the first waves and 20 minutes for 
the subsequent waves.   

2.10  Use of subsamples to survey structural variables 

In  2014,  nine  countries  (Bulgaria,  Czech  Republic,  Spain,  France,  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 possibility offered by 
Regulation (EC) No 2257/2003. The subsample coincides with one rotation panel in total 
sample,  except  for  Norway,  which  use  both  the  first  and  the  last  survey  waves,  and 
Switzerland, which uses the first and the penultimate 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.  In  2014,  such  consistency  is  ensured  by  all  countries  with  small 
deviations for France and the Netherlands.  

3  Relevance  

Relevance  is  the  degree  to  which  statistics  meet  current  and  potential  user  needs.  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. Examining 
the  completeness  of  the  statistics  measured  against  the  relevant  regulation  is  therefore  a 
way to assess the actual relevance of those statistics. 

3.1  The users 

Eurostat  does  not  carry  out  regular  satisfaction  surveys  targeted  only  at  users  of  labour 
markets statistics. 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  data  are  equally 
important  or  even  essential  for  most  users  from  universities,  research  institutes  and 
businesses (10).  

(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 — 2014 

9

 
 
                                                           
For major topics of interest, the instrument of ad hoc modules has proven to be useful and 
flexible  in  addition  to  the  standard  EU-LFS.  Some  users,  however,  seek  for  more  timely 
data release, at least of a few main indicators. The availability of a release calendar for the 
main  indicators  produced  by  the  EU-LFS,  even  with  conservative  delays,  has  been 
favorably received by users.  

3.2  Completeness 

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

Even if otherwise 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 the variable in the national questionnaire.   

A  special  case  is  the  coverage  of  the  household  variables  by  the  countries  sampling 
individuals,  i.e.  the  Nordic  countries  and  Switzerland.  In  2014  no  coverage  of  such 
variables  was  undertaken  by  Iceland  and  Switzerland  (derogation),  while  Denmark, 
Finland  and  Sweden  covered  them  in  special  household  datasets.  Norway  only  covered 
household  information  on  the  family  members  of  working  age,  but  provided  no 
information on other possible members of the household (i.e. children under the age of 15). 

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

Table 3.1 Completeness of the EU-LFS variables, 2014 

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

Number of 
participating countries 

Of which: 
EU-28 Member States 

0 

1–4 

5–9 

10+ 

Total 

24 

6 

3 

0 

33 

23 

4 

1 

0 

28 

(1) Not including variables that are empty because the filtering variable excluded any response. The variable INCDECIL is 
not included. The INCDECIL data may be forwarded to Eurostat within twenty-one months of the end of the reference 
period. 

Quality report of the European Union Labour Force Survey — 2014 

10

 
 
 
Table  3.2  Compulsory  EU-LFS  variables  having  one  or  more  country  returning  100  %  non-
response or constant value (¹), 2014 

Column 
number (2) 

Brief description 

Col_001/2 

Sequence number in the household  

Col_017/18 

Nationality 

Col_028 

Continuing receipt of the wage or salary 

Col_039/40 

Country of place of work 

Col_055 

Col_067/68 

Col_073/74 

Col_075 

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_117  

Col_118  

Col_119 

Col_120 

Col_121 

Col_146 

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 

Working at home 

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  

Availability to start working within two weeks  

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) 

Need for care facilities 

Registration at a public employment office 

Situation with regard to activity one year before survey 

Col_150/151 

Country of residence one year before survey 

Col_152/153 

Region of residence (within Member State) one year before survey 

Col_168 

Col_195 

Col_209 

Degree of urbanization 

Sequence number of the survey wave 

Level of this education or training 

Number of 
countries 
3 

Of which: 
EU-28 
1 

1 

2 

5 

3 

1 

2 

1 

1 

1 

1 

2 

1 

1 

2 

1 

1 

1 

2 

2 

12 

11 

4 

6 

16 

7 

1 

3 

2 

1 

4 

1 

3 

6 

2 

3 

1 

0 

2 

2 

1 

0 

0 

0 

1 

0 

0 

1 

0 

0 

0 

0 

0 

0 

0 

1 

9 

7 

3 

4 

11 

5 

0 

1 

1 

0 

2 

1 

1 

3 

0 

3 

0 

(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 of the end of the reference period.  

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

Quality report of the European Union Labour Force Survey — 2014 

11

 
 
 
 
 
 
 
 
 
 
4  Accuracy  

The accuracy of statistical outputs in the general statistical sense is the degree of closeness 
of estimates to the true values. Statistics can be different from the true values because of 
random  variability  (the  statistics  change  from  implementation  to  implementation  of  the 
survey  due  to  random  effects)  and/or  bias  (the  average  of  the  possible  values  of  the 
statistics  from  implementation  to  implementation  is  not  equal  to  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. Processing errors; 4. Non-response errors. 

4.1  Sampling errors 

Sampling errors affect only sample surveys and arise from the fact that 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. Frame population is the set of population 
units which can be accessed through the frame and the survey’s conclusions apply to this 
population.  Official  surveys,  like  the  EU-LFS,  use  probability  sampling.  This  makes  it 
possible  to  quantify  the  sampling  errors  and  can  be  expressed  in  terms  of  confidence 
intervals.  Table  4.1  provides  the  estimates  and  95  %  confidence  limits  for  the  annual 
results 2014 reached for the five main indicators. For example, interval 217 841–218 743 
covers  the  true  value  of  employed  persons  on  aggregated  EU-28  level  with  a  95  % 
probability.   

Quality report of the European Union Labour Force Survey — 2014 

12

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 4.1 Confidence limits (1), annual average 2014 

Number of 
employed 

(x1000) 

Number of part-
time employed 

Number of 
unemployed 

Rate of 
unemployment 

(x1000) 

(x1000) 

(%) 

Average number of 
hours actually 
worked (2) 
(Hrs.) 

218 292 ±451 
142 066 ±391 
221 094 ±451 
4 544 ±  25 
2 981 ±  61 
4 974 ±  38 
2 714 ±  10 
39 879 ±109 
625 ±  12 
1 914 ±  11 
3 536 ±  78 
17 344 ±316 
26 377 ±145 
1 566 ±  66 
22 279 ±  87 
363 ±    6 
885 ±    9 
1 319 ±  41 
246 ±    6 
4 101 ±  23 
181 ±    3 
8 236 ±  32 
4 113 ±  13 
15 861 ±  65 
4 500 ±  41 
8 614 ±169 
917 ±  16 
2 363 ±  18 
2 447 ±  13 
4 772 ±  18 
30 642 ±  84 
176 ±    2 
2 627 ±  11 
4 535 ±  22 
690 ±  31 
25 931 ±508 

44 601 ±253 
EU-28 
31 610 ±232 
EA-19 
45 335 ±254 
EEA 
1 095 ±  19 
BE 
79 ±    7 
BG 
316 ±  13 
CZ 
692 ±  10 
DK 
11 017 ±  67 
DE 
60 ±    5 
EE 
450 ±    7 
IE 
336 ±  18 
EL 
2 759 ±180 
ES 
4 999 ±104 
FR 
HR (3) 
97 ±  13 
4 091 ±  59 
IT 
51 ±    3 
CY 
65 ±    5 
LV 
120 ±  13 
LT 
46 ±    3 
LU 
262 ±  12 
HU 
30 ±    1 
MT 
4 153 ±  27 
NL 
1 146 ±  17 
AT 
1 234 ±  35 
PL 
589 ±  21 
PT 
860 ±  58 
RO 
103 ±    5 
SI 
124 ±    8 
SK 
377 ±  10 
FI 
1 247 ±  19 
SE 
8 204 ±  68 
UK 
36 ±    1 
IS 
698 ±  14 
NO 
1 721 ±  24 
CH 
41 ±    4 
MK 
TR 
3 024 ±105 
(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 in 

24 807 ±280 
18 634 ±270 
24 911 ±280 
423 ±  13 
385 ±  21 
324 ±  13 
191 ±    6 
2 090 ±  34 
50 ±    4 
243 ±    6 
1 274 ±  41 
5 610 ±240 
3 026 ±  91 
327 ±  23 
3 236 ±  52 
70 ±    4 
108 ±    6 
158 ±  15 
15 ±    2 
343 ±  13 
11 ±    1 
660 ±  12 
245 ±    8 
1 567 ±  39 
726 ±  24 
629 ±  32 
98 ±    5 
359 ±  12 
232 ±    7 
412 ±    8 
1 995 ±  38 
9 ±    1 
95 ±    5 
215 ±  11 
269 ±  17 
2 843 ±  97 

10.2 ±0.26 
11.6 ±0.35 
10.1 ±0.26 
8.5 ±0.3 
11.4 ±0.6 
6.1 ±0.2 
6.6 ±0.2 
5.0 ±0.1 
7.4 ±0.6 
11.3 ±0.3 
26.5 ±0.6 
24.4 ±1.1 
10.3 ±0.3 
17.3 ±1.1 
12.7 ±0.2 
16.1 ±0.8 
10.8 ±0.5 
10.7 ±1.0 
5.9 ±0.8 
7.7 ±0.3 
5.9 ±0.4 
7.4 ±0.2 
5.6 ±0.2 
9.0 ±0.2 
13.9 ±0.5 
6.8 ±0.5 
9.7 ±0.5 
13.2 ±0.6 
8.7 ±0.2 
8.0 ±0.2 
6.1 ±0.1 
4.9 ±0.4 
3.5 ±0.2 
4.5 ±0.2 
28.0 ±1.4 
9.9 ±0.3 

36.8 ±0.05 
36.3 ±0.07 
36.8 ±0.05 
37.3 ±0.2 
40.1 ±0.1 
39.4 ±0.1 
35.0 ±0.1 
35.6 ±0.1 
38.3 ±0.3 
35.6 ±0.1 
40.9 ±0.2 
37.4 ±0.3 
36.1 ±0.3 
39.3 ±0.3 
36.3 ±0.1 
38.0 ±0.3 
39.3 ±0.3 
38.8 ±0.4 
38.3 ±0.5 
38.5 ±0.1 
37.5 ±0.3 
32.3 ±0.2 
35.9 ±0.1 
40.4 ±0.1 
38.7 ±0.2 
39.2 ±0.2 
39.1 ±0.2 
39.0 ±0.2 
36.0 ±0.1 
35.9 ±0.2 
36.0 ±0.1 
39.9 ±0.3 
34.7 ±0.2 
36.5 ±0.2 
41.7 ±0.4 
47.1 ±0.2 

the main and second job. For IE the confidence limits not available. 

(3)  The results are based non-calibrated data from the quality report.  
Note: Confidence limits for the EU aggregates are Eurostat’s own approximation. 

Source: EU-LFS Standard Quality Report 

Quality report of the European Union Labour Force Survey — 2014 

13

 
 
 
 
 
 
 
 
 
 
 
4.2  Non-sampling errors 

Coverage errors 

Coverage errors (or frame errors) are due to divergences between the target population and 
the  frame  population.  Possible  divergence  types  are  undercoverage  (i.e.  the  frame 
population does not include all units of the target population), overcoverage (i.e. the frame 
population 
target  population)  and 
misclassification (i.e. units in the frame population which belong to the target population 
but are wrongly classified). Table 4.2 summarizes the information on the coverage errors 
given by the participating countries.  

includes  units  which  do  not  belong 

the 

to 

Table 4.2 Frame quality, coverage rates and methodological notes 

Under-
coverage 
< 0.5 % 

Over-
coverage 
(cid:180)0 

Misclas-
sification 
(cid:180)0 

6.5 % 

(cid:180)0 

(cid:180)0 

(cid:180)0 

1.0% 

8.4% 

23 % 

NA 

BE 

BG 

CZ 

DK 
DE 

EE 

IE 

EL 

ES 

FR 

Comments 

from  Population  Census. During 

Undercoverage:  Households,  all  members  of  which  are  77  years  or 
older  and  collective  households  (about  0.15 %  of  all  households)  are 
excluded before draw. 
Overcoverage:  The  sample  is  drawn  from  the lists  of  households 
obtained 
field  work 
problems are found on:  non-occupied houses or houses used for other 
purposes;  one  household  (according  to  the  Census  list)  divided  into 
two or more separate households or the opposite. 
Undercoverage:  Households  are  selected  once  a  year  from  the 
Register of Census Areas. Due to differences in time span there is not 
the  current  information  about  addresses  or  flats.  The  sampling  frame 
contains  only  private  households.  Persons 
institutional 
households are not covered. 
Overcoverage: Not existing or not inhabited flats remain in the Register 
of Census Areas. 

the  survey 

living 

in 

living 

in  370  cases  (2.7 %  of 

Undercoverage: 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.  Main 
problem: The basis (census 1987) annually updated by the register of 
new dwellings is very old. The census 2011 will give the German LFS a 
better frame quality. A new sample plan based on the census 2011 will 
probably be implemented from 2016 onwards. 
Undercoverage:  In  2014,  9,226  households  of  13,800  households 
sampled  for  the  survey,  were  interviewed.  Among  the  households  not 
interviewed, 
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 0.4 % to 5.0 %. 
Undercoverage: Our frame is the Census of population and as such we 
have no quality concerns regarding our frame. 
Undercoverage:  Population 
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. 
Overcoverage: 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) 
Undercoverage  Percentage  calculated  as  ‘omitted’  dwellings  detected 
in 
impact  not  available. 
Overcoverage:  Average  of  the  four  quarter  percentages  of  dwellings 
out of frame (‘no encuestables’). The touristic areas are more prone to 
higher  rates.  Misclassification:  The  dwelling  cannot  be 
‘wrong 
classified’ and within the target population, at the same time. 
Undercoverage: The sample, when it is updated several months before 
the reference year, does not cover the most recent buildings (less than 
2  years  old  at  the  end  of  the  reference  year  (less  than  3  years  in 
overseas departments)); yet, this is taken into account in the weighting 
procedure since the calibration method uses the number of newly-built 
dwellings. 

‘quality  control.  Measures  of 

in  collective  households  or 

the 

Quality report of the European Union Labour Force Survey — 2014 

14

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Under-
coverage 
: 

HR 

Misclas-
sification 
: 

Over-
coverage 
Q1: 9.6 % 
 Q2: 10.5 % 
Q3: 9.8 % 
Q4: 9.8 % 

IT 

: 

2.4 % 

2.0 % 

CY 

2.0 % 

LV 

1.5 % 

LT 

LU 

HU 

MT 

NL 

AT 

PL 

14.0 % 

: 

: 

: 

: 

: 

12.9% 

: 

: 

: 

PT 

Approx. 
< 1% 

14.0 % 

: 

Comments 

inclusions 

they  cover 

(recent  emigration)  and  missed 

to  maintain  as  much  as  possible 

Undercoverage:  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.  Overcoverage:  Overcoverage  rates 
are actually non-eligibility rates of addresses selected in sample. 
Undercoverage:  Households  are  selected  once  a  year  from  the 
municipalities’  registry  offices; 
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 
(recent 
immigration).  It  is  required  that  each  non-responding  household  be 
replaced with a household having similar characteristics of the first one, 
in  order 
the  sample 
representativeness  and  to  minimize  the  impact  of  unit  non-response. 
No more than 3 replaces are admitted. 
Undercoverage: The sample was drawn from the Census of Population 
frame  of  2011.  In  a  post  enumeration  survey  conducted  after  the 
census an undercoverage of 1.97 % was estimated. However updating 
to  include  newly  constructed  dwellings  has  not  yet  been  carried  out. 
This is usually carried out on an annual basis. 
Undercoverage: 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. Overcoverage: Overall in the year 1.5 % of 
overcoverage  from  sample.  Main  reason  of  it  are,  rarely  updated 
register  were  can  be  old  information.  Also  other  reasons  will  be 
checked. 
Overcoverage:  Among  not  interviewed  households,  in 1 498  cases 
(5 % 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  (a  hairdresser’s,  shop,  etc.),  the 
building was knock down, etc). 
Undercoverage: Households with no telephone will not be in the frame. 

Undercoverage:  Hard-to-access  groups  are  characterized  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, it 
is supposed to be not significant. 
Undercoverage:  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,  households  created  after  2011  are  not  well  represented.   
Overcoverage:  There  is  over-representation  for  households  created 
prior  to  2011  and  for  households  which  were  present  in  2011  and  no 
longer exist after 2011. 

Undercoverage:  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. This could mean an undercoverage of recent migrants. 
Undercoverage:  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 not the current information about 
addresses  or  flats,  also  population  living  in  collective  (institutional) 
households  staying/or  planning  to  stay  in  this  places  for  over  a  year, 
homeless  people  and  other  people  without  registered  residence  (e.g. 
people  living  in  huts,  caravans)  are  out  of  the  frame,  emigrants  staying 
abroad  for  more  than  one  year.  Overcoverage  consist  of  dwellings:  in 
which  inhabitants  are  not  present  for  a  long  time,  not  inhabited  or 
inhabited seasonally, changed into inhabitable space (for example shop), 
in liquidation, not found (incorrect address). 
Undercoverage:  The  sampling  frame  doesn’t  cover  the  individuals 
living  in  collective  dwellings.  This  population  represents  less  than 
approximately 1 %. 

Quality report of the European Union Labour Force Survey — 2014 

15

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Under-
coverage 
3.7 % 

RO 

Misclas-
sification 
: 

Over-
coverage 
Q1: 4.0 % 
Q2: 4.1 % 
Q3: 4.1 % 
Q4: 4.0 % 

SI 

SK 

(cid:180)0 

(cid:180)0 

(cid:180)0 

FI 

(cid:180)0 

1.6% 

SE 

1 % 

0.2 % 

: 

UK 

Approx. 
1.5 % 

(cid:180)0 

(cid:180)0 

(cid:180)0 

Comments 

Undercoverage:  Due  to  the  lack  of  appropriate  information,  the  new 
dwellings, built after 2002 Census of the Population and Dwellings, that 
could possibly constitute a sampling frame of the new dwellings, have 
not  been  taken  into  account.   Thus,  an  updates  has  be  done  for  the 
PSU  included  in  EMZOT,  on  the  basis  of  a  micro-census  type  survey 
(2006).  The  micro-census  has  aimed  in  particular  the  updating  of  the 
addresses of the dwellings. Undercoverage rate was estimated as the 
ratio  between  number  of  new  permanent  dwellings,  built  in  the  period 
end of 2002 year (the year of the census)– end of 2013 year (Source: 
Romanian Statistical Yearbook, 2014), and number of dwellings at the 
end  of  2013  year  (Source:  Romanian  Statistical  Yearbook,  2014). 
Thus, it was assumed that the proportion of the new dwellings in total 
dwellings  should  be  the  same  in  the  master  sample.  Overcoverage: 
Overcoverage  rates  were  estimated  on  the  basis  of  the  survey 
samples, as ratio between number of not-eligible dwellings and number 
of sampled dwellings. 
Negligible  

It 

to 

(no 

live 

fairly  small 

is  based  on 

regularly.  Undercoverage 

Undercoverage:   The  LFS  sample  is  based  on  a  Population  Census 
conducted once each 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, partially student halls 
of  residence  (although  they  are  surveyed  via  other  members  of  the 
households),  members  of  the  Slovak  embassies  and  institutions 
abroad.  Under-coverage  comprises  people  born  abroad  and  living  in 
collective  houses  Overcoverage:  Mainly  young  residents  working 
temporarily  abroad  can  stay 
there.  Misclassification: 
Misclassification by incorrect identification is negligible 
Undercoverage:  The  sampling  frame  used  is  the  total  population 
database  maintained  by  Statistics  Finland. 
the 
Population Information System of The Population Register Centre and 
large-scale 
updated 
immigration).  Overcoverage:  Mostly  emigration  in  wave  1,  deaths  and 
emigration for later waves.  
Undercoverage:  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. Overcoverage: There is a certain over coverage in 
RTB  and  consequently  in  the  sampling  frame.  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 
this  over-
non-response.  According 
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 %). 
Undercoverage: 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. 
No significant problems 

to  evaluation-studies  made 

IS 

NO 

CH 

MK 

TR 

: 

Undercoverage:  Do  not  include  those  75  years  and  older.  Imputes  as 
outside the labour force. Number of persons employed about 0.25 per 
cent too low. 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. 
Overcoverage: Overcoverage rates were estimated on the basis of the 
survey samples, as ratio between number of not-eligible dwellings and 
number of sampled dwellings. 

Q1: 10.9 % 
Q2: 11.3 % 
Q3: 11.5 % 
Q4: 12.4 % 
10.1 % 

: 

Note: (:) indicates that information is not provided. Blank indicates that information is not available to NSI. 
Source: EU-LFS Standard Quality Report 

Quality report of the European Union Labour Force Survey — 2014 

16

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Measurement errors 

Measurement  errors  are  errors  that  occur  during  data  collection  and  cause  the  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. 

No  regular  estimates  of  these  errors  are  available.  However,  the  number  of  proxy 
interviews and statistics on the last updates of the questionnaire are all related to the error 
sources listed above (Table 4.3). 

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.  No 
estimates can be produced indicating the rate of processing errors in the EU-LFS. 

Non-response errors 

Non-response is the failure of a survey to collect data on all survey variables, from all the 
population units designated for data collection in a sample or complete enumeration. The 
difference between the statistics computed from the collected data and those that would be 
computed if there were no missing values is the non-response error. 

Tables  4.4  shows  non-response  rates,  but  they  are  not  fully  comparable.  Most  of  the 
countries  calculate  non-response  on  the  basis  of  the  household  unit,  except  Denmark, 
Finland,  Sweden,  Iceland,  Norway  and  Switzerland,  which  calculate  non-response  on 
person  basis.  The  treatment  of  non-response  in  the  follow-up  waves  is  also  different 
between  countries.  Some  participating  countries  do  not  take  previous  non-response  into 
account  when  calculating  the  non-response  in  later  waves,  whereas  others  do.  Thus  the 
former countries may show lower non-response rates on the average than the latter. 

Quality report of the European Union Labour Force Survey — 2014 

17

 
 
 
 
 
 
 
 
 
 
 
 
 
Table 4.3 Share of proxy interviews and last update of the questionnaire 

% of proxy 
interviews 
(unweighted) (¹) 

Date of last 
update of the 
questionnaire 

Date of the last pilot survey in 
order to test the questionnaire 

Number of respondents to 
the pilot survey 

EU-28 

BE 

BG 

CZ 

DK 

DE 

EE 

IE 

EL 

ES (2) 

FR 

HR 

IT 

CY 

LV 

LT 

LU 

HU 

MT 

NL 

AT 

PL 

PT 

RO 

SI 

SK 

FI 

SE 

UK (2) 
IS (2) 

NO 

CH 

MK 

– 
No pilot survey for the 
changes in 2014 

– 

N/A 

30.2 

19.0 

33.7 

44.6 

4.8 

– 

Nov. 2013 

Q1 2011 

31.12.2012 

1st of Dec.  
2014 

2007 

2001 

N/A 

Approx. 1 060 persons 

891 persons 

N/A 

N/A 

26.0 

yearly 

no pilot surveys, only yearly 
conducted cognitive pretests  

36.4 

50.5 

41.4 

52.5 

27.8 

September 
2013 
Last major field 
update was Q2 
2012. 

Oct-Dec 2013 

189 persons 

N/A 

N/A 

31.11.2012 

No pilot 

2005 

2004 

3 500 households were 
interviewed.  

2013 Q1 with 
some correct. 
during 2013 
and 2014 Q1  

2011 

1 200 persons 

46.3 

2014 

N/A 

N/A 

Jan. 2014 for 
Q1, Q3 and Q4 
– April 2013 for 
AHM in Q2 

November 2013 

1 005 households 

October 2013 

October 2013 

150 persons 

Nov. 2013 

16.05.2005-29.05.2005 testing 
of CAPI 

Nov.2013 

04.2010 

Yearly update 

November 2012 

N/A 

35 

25 

October 2013 

September 2013 

About 2 000 persons 

End of 2013 

No pilot survey was carried out  N/A 

18.0 

32.5 

37.9 

34.5 

39.8 

44.0 

49.8 

46.5 

25.2 

Q1 2014  

Pilot study in Q3 2013 
(education - ISCED11 from 
2014 onwards) 

1 353 persons  

40.0 

47.7 

25.8 

55.6 

49.8 

4.1 

2.6 

35.5 

0.3 

16.7 

1.9 

54.5 

Q1 2013 

There was no test survey 

2014 

Starting with 
Q1 2014 

2013 

2014 

January 2014 

April 2014 

From 3rd quarter 2009 to 2nd 
quarter 2010 

Around 40 000 individuals 
by quarter 

Q3 2013 

51 482 persons 

Pilot studies in March/June 
2004. 

400 persons 

January 2014 

16/06/2013 to 04/07/2014 

1 000 households sampled. 

Nov. and Dec.2002 

Q1 2006 

No pilot survey 

30.03.2010 

15.12.2009 

About 100 persons 

October 2012 

There was no test survey 

20.9 

TR 
(1) 15–74 years respondents; (2) 16–74 years respondents. Notes: (–) indicates that the item is not applicable and 
(:) indicates that information is not provided. Blank indicates that information is not available to NSI. 
Source: EU-LFS Standard Quality Report 

Around 500 households 

2014 

2013 

Quality report of the European Union Labour Force Survey — 2014 

18

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 4.4 Rates of non-response by wave. Annual average 2014 

Total 

4.0 

3.5 

20.0 

2 

3 

Waves 

4 

5 

6 

7 

8 

22.3 
12.3 
20.1 

19.2 
19.5 
45.2 

23.8 
20.5 
48.0 

21.0 
19.5 
46.7 

23.9 
22.8 
12.0 
18.9 

15.5 
23.3 
23.4 
11.4 
19.4 
: 
4.1 
4.1 
33.2 
17.1 

36.3 
23.9 
26.4 
11.7 
21.4 
: 
5.7 
4.3 
35.5 
21.6 

17.1 
23.4  
24.0 
11.7 
20.1 
: 
5.4 
4.2 
33.6 
18.6 

1 
27.8 
30.5 
23.6 
50.5 
2.3 
46.1 
25.0 
28.7 
15.4 
25.2 
31.3 
26.2 
5.15 
38.7 
28.0 
84.6 
33.8 
16.7 
42.6 
3.8 
36.0 
9.6 
11.7 
34.6 
11.0 
27.9 
37.6 
40.8 
21.8 
24.0 
38.8 
27.3 
11.0 

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 
42.6 
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 

BE 
BG 
CZ 
DK 
DE(1) 
EE 
IE 
EL 
ES 
FR 
HR 
IT 
CY 
LV 
LT 
LU 
HU 
MT 
NL(2) 
AT 
PL 
PT 
RO 
SI(3) 
SK 
FI 
SE 
UK 
IS 
NO 
CH 
MK 
TR 
(1) Survey waves are on annual basis. 
(2) Households in the first wave, thereafter persons. 
(3) Conditional non-response in waves 2-5. The non-respondents from previous waves are excluded from the sample in 
subsequent waves (waves 2-5)  
Note: (:) indicates that information is not available.  
Source: EU-LFS Standard Quality Report 

25.1  
26.8 
38.4 
5.7  
31.7 
14.1 
9.8 
21.8 
: 
27.3 
35.2 
35.6 
21.0 
22.1 
7.2 
26.0 
8.6 

11.4  
25.8 
4.6  
5.9 
28.2 
17.0 
7.9 
11.6 
: 
28.4 
35.3 
41.2 
20.7 
19.7 
4.0 
23.9 
7.8 

15.3 
25.6 
9.1 
6.0 
29.9 
14.8 
8.7 
13.3 
: 
27.6 
35.2 
38.9 
20.9 
20.7 
8.9 
21.2 
8.3 

8.2 
: 
28.8 
36.1 
42.5 
20.8 
19.3 

3.7 
5.5 

18.5 

18.5 

16.8 

16.7 

35.9 

35.5 

8.4  

9.6 

34.2 

16.8 

5  Timeliness and punctuality 

The timeliness of statistical outputs is the length of time between the event or phenomenon 
they describe and their availability. 

Punctuality is the time lag between the release date 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.  Table  5.1  shows  that  data  are 
transmitted to Eurostat for most countries in the third month after the end of the quarter. 
First national releases of data in the majority of the participating countries are in the first 
two months after the end of the quarter. 

A release calendar for the EU-LFS main indicators is in place, foreseeing the release of the 
main  indicators  four  weeks  after  the  data  delivery  deadline.  In  addition  Eurostat 
continually updates the Eurostat online database with new data after final data processing 

Quality report of the European Union Labour Force Survey — 2014 

19

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
in  Eurostat.  Timeliness  and  punctuality  of  the  transmission  to  Eurostat  and  Eurostat’s 
dissemination of the national data have not really changed from 2013 to 2014.  

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 – quarterly LFS data (results) 

Number of calendar days from end of reference period 

Transmission to Eurostat 

2013 

All 

Number of countries 

2014 

All 

EU-28 

Euro area 

<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 

Source: EU-LFS Standard Quality Report 

6  Accessibility and clarity 

1 
9 

21 

2 

33 

66 

0 

5 

25 

3 

33 

76 

0 
9 

24 

0 

0 

33 

0 

2 

27 

4 

0 

33 

0 
7 

21 

0 

0 

28 

0 

2 

24 

2 

0 

28 

0 
4 

12 

0 

0 

16 

0 

2 

13 

1 

0 

16 

Accessibility  and  clarity  refer  to  the  simplicity  and  ease  with  which  users  can  access 
statistics,  with  the  appropriate  user  information  and  assistance:  a  global  context  which 
finally enables them to make optimum use of the statistics. 

In 2014 Eurostat published quarterly and annual results as well as an analysis of indicators 
to supplement the unemployment rate in its series Statistics in Focus.  

Eurostat also publishes annually a compendium describing the main characteristics of the 
national surveys. 

The Eurostat public website is free of charge and includes main indicators, derived from 
the Labour Force Survey, as well as detailed, constantly updated main 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). 

Through direct queries, customized tabulations of EU-LFS results are available to users in 
electronic format. Eurostat extracts around 1 300 direct queries 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  all  Member  States  and  from  Iceland,  Norway 
and  Switzerland  are  available  in  this  format.  In  2014  around  300  researchers  or  research 
groups worked with EU-LFS microdata (new contracts and amendments).  

Quality report of the European Union Labour Force Survey — 2014 

20

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7  Comparability 

Comparability refers to statistical outputs comprising the same data items (say employment 
data) but for different reference periods, regions or domains, where the aim is to combine 
them to make comparisons over time, or across regions, or across domains. It can be said 
that  it  is  the  extent  to  which  differences  between  statistics  are  attributed  to  differences 
between the true values of the statistical characteristics.  

7.1 

 Comparability over time 

For a detailed overview on 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, i.e. the target population, the legislation, 
the  classifications  used,  the  geographical  boundaries)  or  the  measurement  level  (i.e.  the 
sampling frame, the sample design, the rotation pattern, the questionnaire, the instructions 
to interviewers, the survey modes, the weighting scheme, the use of auxiliary information). 

Table 7.1 reports changes to the national labour  force surveys introduced in  2014 by  the 
participating countries. Such changes may introduce some discontinuity in the time-series. 

Table 7.1 Improvements or changes compared to previous year 

Changes to sampling frame, sample design or target population

FR  No change in Metropolitan France. In 2014, Overseas departments (Guadeloupe, 

Martinique, Guyane, La Réunion), except Mayotte, have joined the French quarterly LFS, 
which covered only Metropolitan France until 2013. A specific sampling frame for overseas 
departments was set up.  

LV 

PT 

HR  2011 Census has been used as a new sample frame. Furthermore, the new sample design 
has been newly determined. The sample consists of four separately selected subsamples, 
rotation groups or panels. The sample design is two-stage and stratified.  
The all households from dwelling are included in the survey.  Quarterly average 
demographic data has used in calibration.  In comparison with previous year total sample 
size increased for 10.9%. 
Statistics Portugal has released Labour Force Survey results for the 1st quarter of 2014 with 
reference to the population estimates calculated from Census 2011 final results. The back 
series (quarterly and annual; from 1998 to 2013 were also recalibrated and the databases 
revised were sent to Eurostat. 
Whereas the sampling frame used until Q1 2014 covered only households with a fixed-line 
connection, the SFSO's Sampling Frame for Person and Household Surveys (used for the 
SLFS from Q2 2014 on) covers 100% of Switzerland's permanent resident population. 
In 2014 while taking account one week reference period starting Monday ending Sunday 
transition to the new regulations (52 weeks) as the reference period for the survey of the 
whole weeks of the year was implemented continuously instead of fixed reference period. 
The new series in the household Labour Force Survey’s sampling design and frame are 
based on the law called ‘The Law of Establishment of Greater Municipality in Thirteen 
Provinces and Twenty-Six District Municipality’ from 2014 which is valid under the new 
administrative division.  

CH 

TR 

Quality report of the European Union Labour Force Survey — 2014 

21

 
 
 
Changes to questionnaire or national explanatory notes

BE  Next to the introduction of ISCED 11 extra questions and change in wording of the questions 
concerning HATLEVEL and EDUCLEVL were introduced and questions about learning mobility 
were added. 

FR  An additional question has been introduced in case of temporary work, to comply with the 

list of modalities defined by Eurostat for variable TEMPDUR. 

HU  Change of the questionnaire (WSTATOR). 
PL 

In order to meet the requirement of harmonization with the higher level of detail of the 
HATLEVEL variable, the number of variants in the answers to the question about the level of 
education has been increased. 
Introduction of ‘diploma approach’ in the context of implementation of ISCED 2011 

Some required questions included in the questionnaire and some unnecessary questions 
were removed. Some questions or question options have been rearranged.  

RO 

TR 

Changes to weighting schemes

DE  Re-weighting using calibration marginal based on the population census 2011 (impact: 

population –1.70 mill., employed –0.93 mill, unemployed –0.09 mill. persons) 

EE  Data for 2000–2013 have been adjusted using population numbers revised on the basis of 

EL 

2011 Population Census and registers 
Since 1st quarter 2014 new population estimations, based on 2011 census, are used for LFS 
estimates 

ES  Application of Census 2011 as new population base and new auxiliary variables used for 
calibration: size of the households (5 groups) and 3 groups of age for each sex at NUTS 3 
level. 

FR  No change in Metropolitan France. 

LV 

HU 

Specific weighting scheme for overseas departments, see §2. Introduction and §5.3.3. Non 
Response Error for more details.  
The calibration procedure is supplemented with new auxiliary information from the State 
Revenue Service.  Strata, wave, CAPI and CATI methods are used as RHG (response 
homogeneity group) for non-response adjustment. 
In 2014 the population totals used in calibration as controls were updated with census 2011 
results. Besides, we changed for a finer breakdown of 5-year age groups, thus having 16 age 
groups in contrast with the former 10 age groups. 

AT  Revision of the weighting scheme (Census 2011 and inclusion of register information on 

TR 

labour status).  
Since 2014, the household labor force survey results were weighted according to the 
population projections renewed together with amendments. Also modifications in the 
calibration stage were introduced.  
Other changes 

ALL  The introduction of ISCED 2011 classification in 2014 Q1 in all countries. 
EL  Use of portable computers in a number of primary sampling units in the 3rd quarter of 2014

Source: EU-LFS Standard Quality Report 

Quality report of the European Union Labour Force Survey — 2014 

22

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

regulation (14) 

regarding 

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 OECD. 

Over  the  last  years,  Eurostat  has  commissioned  several  reports  to  examine  the  degree  to 
which the participating countries adhere to the common set of definitions. The most recent 
study of this kind was carried out on the 2008 questionnaires. As a general conclusion it 
emerges  that,  in  spite  of  the  progress  regarding  the  adherence  to  the  EU  regulations, 
principles  and  guidelines  (i.e.  the  explanatory  notes),  the  national  questionnaires  still 
largely differ even in the collection of key variables such as WSTATOR (Labour status in 
the  reference  week).  Hence,  even  if  labour  market  statistics  are  subject  to  quite 
comprehensive  international  definitions,  principles  and  guidelines,  which  make  it  one  of 
the  most  harmonised  statistical  domains  not  only  in  Europe  but  worldwide,  there  is  still 
room for further improvement of cross-country comparability (15). 

This applies also to the variable INCDECIL on income deciles, which was introduced as 
mandatory in 2009. At present, the comparability of this variable is still low, which is due 
to  several  elements:  some  countries  ask  information  on  monthly  pay  directly  to  the 
interviewees, while others retrieve it from national registers. Some countries ask the exact 
amounts while other ones collect the information in earning bands. Some countries define 
the deciles based on external sources, while others do it on the basis of the collected data. 
Some  countries  collect  net,  others  gross  income.  Finally,  the  treatment  of  bonuses, 
allowances and fringe benefits is likely not fully homogeneous across countries. Work is 
on-going  to  reduce  these  disparities  and  improve  the  comparability  of  the  variable.  The 
dissemination of INCDECIL is pending on a quality assessment of the results by Eurostat.  

(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. 
(15)  A Task Force coordinated by Eurostat is currently working to identify shortcomings and propose possible 
improvements for the cross-country comparability of the national Labour Force Surveys in the EU. 

Quality report of the European Union Labour Force Survey — 2014 

23

 
 
 
 
 
 
                                                           
 
8  Coherence 

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  two  other  sources,  the  population  statistics  and  the 
employment  data  from  national  accounts.  Other  comparisons  are  possible,  such  as  with 
employment data from the Structural Business Statistics and the Labour Cost Survey. 

8.1  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: 

⎯  The  EU-LFS  statistics  cover  only  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 differ in the LFS 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. 

Moreover, 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. Furthermore most countries have already completed the re-weighting 
of previous data series at least back to 2011.  

Quality report of the European Union Labour Force Survey — 2014 

24

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 8.1 Coherence with population statistics 2014 

Population 15-64  
1/1/2014 

LFS annual average 15-64 
 2014 

Relative difference  
[(L-P)/P*100] 

Total 

Men 

Women 

Total 

Men 

Women 

Total 

Men 

Women 

EU-28 

333 782.1 

166 799.3 

166 982.8 

329 340.2 

164 189.9 

165 150.2 

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 

7 303.5 

3 675.8 

3 627.8 

7 265.5 

3 649.4 

3 616.1 

4 831.9 

2 438.9 

2 393.0 

4 795.6 

2 416.9 

2 378.6 

7 109.4 

3 601.2 

3 508.2 

7 081.2 

3 631.8 

1 829.9 

1 801.9 

3 626.3 

3 588.0 

1 827.1 

3 493.3 

1 799.2 

53 336.4 

26 869.9 

26 466.5 

52 737.5 

26 521.9 

26 215.6 

866.0 

427.0 

439.0 

861.7 

423.2 

438.5 

3 011.4 

1 492.9 

1 518.5 

3 007.4 

1 490.7 

1 516.7 

7 069.5 

3 494.9 

3 574.5 

7 040.4 

3 479.8 

3 560.6 

31 005.2 

15 610.5 

15 394.7 

30 750.1 

15 436.1 

15 314.0 

41 767.7 

20 625.7 

21 142.0 

40 931.7 

20 087.2 

20 844.5 

2 836.5 

1 418.9 

1 417.6 

2 826.0 

1 414.1 

1 411.9 

39 319.6 

19 566.3 

19 753.2 

39 161.1 

19 469.2 

19 691.8 

599.4 

1 325.5 

1 970.6 

379.8 

291.3 

642.1 

953.2 

193.6 

308.1 

683.4 

571.5 

1 295.3 

1 017.5 

1 961.0 

186.1 

364.4 

271.9 

624.6 

949.2 

184.6 

299.6 

670.7 

1 011.7 

179.8 

6 719.7 

3 326.5 

3 393.2 

6 587.7 

3 246.7 

3 341.1 

288.1 

147.4 

140.8 

284.8 

145.0 

139.8 

11 060.2 

5 560.9 

5 499.3 

10 980.4 

5 510.3 

5 470.1 

5 731.3 

2 869.6 

2 861.7 

5 675.8 

2 825.5 

2 850.3 

26 639.1 

13 293.3 

13 345.8 

25 277.8 

12 620.4 

12 657.4 

6 835.6 

3 321.1 

3 514.5 

6 794.3 

3 289.1 

3 505.2 

13 556.1 

6 830.3 

6 725.8 

13 526.7 

6 812.0 

6 714.7 

1 399.9 

719.9 

680.1 

1 397.2 

719.4 

677.8 

3 852.9 

1 933.6 

1 919.2 

3 852.8 

1 933.6 

1 919.2 

3 499.7 

1 771.1 

1 728.6 

3 471.7 

1 748.6 

1 723.1 

6 126.6 

3 114.3 

3 012.3 

6 141.3 

3 123.5 

3 017.9 

41 708.7 

20 779.1 

20 929.7 

41 073.1 

20 382.1 

20 691.0 

215.8 

109.2 

106.6 

205.1 

103.2 

101.9 

3 364.4 

1 724.2 

1 640.2 

3 372.2 

1 724.4 

1 647.7 

5 494.6 

2 772.9 

2 721.7 

5 468.5 

2 759.1 

2 709.4 

1 461.6 

741.4 

720.2 

1 461.1 

741.6 

719.5 

TR 
25 689.3 
Source: Eurostat (online data codes: demo_pjan and lfsa_pganws), 31 July 2015 (extracted). 

50 977.1 

25 534.2 

25 442.9 

26 237.0 

51 926.4 

-1.3 

-0.5 

-0.8 

-0.4 

-0.2 

-1.1 

-0.5 

-0.1 

-0.4 

-0.8 

-2.0 

-0.4 

-0.4 

-4.7 

-2.3 

-0.5 

-4.0 

-2.0 

-1.2 

-0.7 

-1.0 

-5.1 

-0.6 

-0.2 

-0.2 

0.0 

-0.8 

0.2 

-1.5 

-5.0 

0.2 

-0.5 

0.0 

-1.8 

-1.6 

-0.7 

-0.9 

-0.4 

-0.2 

-1.3 

-0.9 

-0.1 

-0.4 

-1.1 

-2.6 

-0.3 

-0.5 

-6.7 

-2.7 

-0.4 

-4.7 

-2.4 

-1.6 

-0.9 

-1.5 

-5.1 

-1.0 

-0.3 

-0.1 

0.0 

-1.3 

0.3 

-1.9 

-5.5 

0.0 

-0.5 

0.0 

-2.7 

-1.1 

-0.3 

-0.6 

-0.4 

-0.1 

-0.9 

-0.1 

-0.1 

-0.4 

-0.5 

-1.4 

-0.4 

-0.3 

-2.7 

-1.9 

-0.6 

-3.4 

-1.5 

-0.7 

-0.5 

-0.4 

-5.2 

-0.3 

-0.2 

-0.3 

0.0 

-0.3 

0.2 

-1.1 

-4.4 

0.5 

-0.5 

-0.1 

-1.0 

Quality report of the European Union Labour Force Survey — 2014 

25

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8.2  Coherence with other employment estimates 

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,  where  the  EU-LFS  covers  the  age  groups  15  and  older  in  private  households 
only, while the national accounts cover all persons regardless of age or type of residence. 
In  addition,  the  EU-LFS  doesn’t  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  one  average  of  all  the  weeks  in  the  year  (for  annual  results)  or  the 
quarter  (for  quarterly  results).  National  Accounts  stock  estimates  refer  to  the  mid  of  the 
year (for annual accounts) or mid of the quarter (for quarterly accounts).  

As expected, the employment estimates based on the LFS data usually lie somewhat below 
the estimates of employment as estimated by National Accounts. This emerges from table 
8.2, 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.  For 
three countries, however, the opposite is true. 

Admittedly 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 eighteen participating countries as shown in table 8.2. Germany, France and 
Italy are responsible for the bulk of the absolute difference between the National Accounts 
employment estimates and the LFS employment, while in relative terms  Bulgaria, Greece, 
Italy,  Germany    and  the  former  Yugoslav  Republic  of  Macedonia  show  the  highest 
discrepancies,  with  a  distance  of  more  than  5.0 % (16).    When  comparing  data  from  LFS 
and National Account, users are also interested in whether the two sources show the same 
trend or not, i.e. change from one period to another. Table 8.2 also compares the data on 
employment growth in 2014. 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 are 
mostly marked 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.  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  black  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  average  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  4.1).  When  changes  between  periods  are 
small,  this  may  result  in  diverging  trends  between  the  National  Accounts’  and  the  LFS’ 

(16) No data is available for Turkey. 

Quality report of the European Union Labour Force Survey — 2014 

26

 
 
                                                           
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.  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). 

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. 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 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.  

Quality report of the European Union Labour Force Survey — 2014 

27

 
 
 
 
 
 
 
 
 
 
 
 
 
Table 8.2 Employment (national concept) 2014 in two different datasets on the Eurostat website. 
Levels and growth rates  

2014 levels 

Labour force 
survey 
(x1000) 

National accounts 
(x1000) 

LFS-NA 
(x1000) 

2013–2014 growth rates 

(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 
-2.9 
-0.5 
-0.3 
0.0 
-0.5 
-81.2 

624.8 
1 913.9 
1 319.0 
4 100.8 
15 861.5 
30 641.8 

627.7 
1 914.4 
1 319.3 
4 100.8 
15 862.0 
30 723.0 

-0.5 
0.0 
0.0 
0.0 
0.0 
-0.3 

0.6 
1.7 
2.0 
5.3 
1.9 
2.3 

0.6 
1.7 
2.0 
5.3 
1.9 
2.3 

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

basis 

2 981.4 
3 536.2 
884.6 
8 613.7 

3434.17 (p) 
3906.08 (p) 
888.2 
8 779.2 

-452.8 
-369.9 
-3.6 
-165.5 

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

4 543.5 
4 974.3 
26 376.9 
245.6 
916.8 
176.1 

4 639.1 
5 094.8 
27 680.0 
238.1 
: 
177.7 

-95.6 
-120.5 
-1 303.1 
7.5 
916.8 
-1.6 

-13.2 
-9.5 
-0.4 
-1.9 

-2.1 
-2.4 
-4.7 
3.1 
: 
-0.9 

1.6 
0.7 
-1.0 
0.8 

0.3 
0.8 
2.4 
2.9 
1.2 
1.7 

0.4 
0.7 
-1.0 
0.6 

0.4 
0.9 
0.3 
2.1 
: 
1.6 

0.0 
0.0 
0.0 
0.0 
0.0 
0.0 

1.2 
0.0 
0.0 
0.2 

-0.1 
-0.1 
2.1 
0.8 
: 
0.1 

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) 

17 344.2 
1 565.7 
22 278.9 
4 499.5 
2 363.1 
2 447.2 
4 772.1 
2 626.6 
4 534.5 

18224.4 (p) 
1 575.0 
23 972.9 
4550.62 (e) 
2 363.1 
2 498.5 
4 738.5 
2 748.0 
: 

-880.2 
-9.3 
-1 694.0 
-51.1 
0.0 
-51.3 
33.6 
-121.4 
: 

-4.8 
-0.6 
-7.1 
-1.1 
0.0 
-2.1 
0.7 
-4.4 
: 

4b  Countries not giving precedence to any labour side  

39 879.1 
4 112.7 

42 640.0 
4 219.3 

-2 760.9 
-106.6 

-6.5 
-2.5 

1.2 
2.7 
0.4 
1.6 
1.5 
-0.4 
1.4 
1.0 
1.7 

0.9 
0.2 

1.3 
2.7 
0.1 
1.5 
1.5 
-0.8 
1.4 
1.1 
: 

0.9 
0.9 

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

and/or enterprise surveys) 

2 714.1 
181.3 
362.7 
8 236.1 
690.2 

2 734.0 
187.5 
351.49 (p) 
8609 (p) 
: 

-19.9 
-6.2 
11.2 
-372.9 
690.2 

-0.7 
-3.3 
3.2 
-4.3 
: 

1.0 
3.1 
-0.7 
-0.6 
1.7 

0.7 
4.5 
-2.0 
-0.2 
: 

-0.1 
0.0 
0.3 
0.1 
0.0 
0.4 
0.0 
-0.1 
: 

0.0 
-0.7 

0.3 
-1.4 
1.3 
-0.4 
: 

EE 
IE 
LT 
HU 
PL 
UK 

BG 
EL 
LV 
RO 

BE 
CZ 
FR 
LU 
SI 
IS 

ES 
HR 
IT 
PT 
SK 
FI 
SE 
NO 
CH 

DE 
AT 

DK 
MT 
CY 
NL 
MK 

(:) indicates that information is not available, (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) – 31 July and 10 August 2015 

Quality report of the European Union Labour Force Survey — 2014 

28

 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  the  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,  Luxembourg,  Malta, 
Latvia,  Lithuania,  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 NUTS 3 data is currently only used for publication at a 
more  aggregated  level.  For  example,  unemployment  and  employment  figures  are 
disseminated by urban-rural typology as well as metropolitan and maritime 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  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  2014,  20  Member  States  (Austria,  Belgium, 
Bulgaria, 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  Norway  and  the  former  Yugoslav  Republic  of  Macedonia  sent  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.  Three  of  the  20  countries  providing  NUTS  3  micro  data,  namely  Austria, 
Ireland  and  Spain,  also  transmitted  tabulated  results.  Six  countries,  Germany,  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. 

(17) The chapter 9 was jointly written by Units F3 and E4.  
(18) For 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 — 2014 

29

 
 
                                                           
 
 
 
For two Member States, Cyprus and Luxembourg, the NUTS 3 level does not differ from 
the NUTS 1 and the NUTS 2 level. In 2014, for Croatia, Switzerland, Iceland and Turkey, 
no NUTS 3 data were available. Portugal has sent to Eurostat tabulated results by NUTS 3 
level  only  for  the  labour  force  population  (active  population)  and  employment  and 
unemployment data already aggregated by regional typologies (metropolitan and maritime 
regions  and  urban-rural  typologies).  For  2014,  for  the  first  time,  Germany  has  provided 
LFS data in all four labour market datasets, aggregated by regional typologies. 

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. 

In  order  to  accommodate  cases  in  which  countries  do  not  want  to  transmit  any  NUTS  3 
data, like Portugal and Germany, Eurostat offers the possibility to transmit the data already 
aggregated by regional typologies. For this purpose, Eurostat can provide the appropriate 
templates to be submitted via eDamis. 

(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 — 2014 

30

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

Quarterly data 2014 

Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

BE 

compulsory  Col_073/74 

HWWISH 

90 

89.7 

90.4 

Q4 

Short comments on reasons 
for non-available statistics and 
prospects for future solutions 
89.4  HHWISH is only asked to persons 

Col_110 - 
Employed 
Col_116 

METHODH 

. 

C 

C 

. 

WANTWORK  43.7 

42.7 

43.3 

43.1 

Col_195 
compulsory  Col_054 

BG 

INTWAVE 
TEMPDUR 

C 
. 

C 
. 

C 
11.8 

C 
10.3 

who declared to wish to work 
more. 
Search method did not occur for 
those quarters 
‘Wantwork' is not asked to all 
persons with seekwork =3.  
Only one wave 
For persons without employment 
contract (main part of the variable 
non-response) the duration of job 
is often unclear 

Col_082/83 

HWACTUA2 

12.7 

20.3 

31.1 

Col_110 - 
Employed 

Col_111 - 
Employed 

Col_114 - 
Employed 

Col_115 - 
Employed 

METHODH 

METHODI 

METHODL 

. 

. 

. 

C 

C 

C 

METHODM 

C 

C 

. 

C 

C 

C 

Col_115 - Not 
employed 

METHODM 

C 

C 

C 

CZ 

compulsory  Col_028 

SIGNISAL 

. 

10.2 

. 

Col_123 

DE 

compulsory  Col_073/74 

Col_195 

EDUCSTAT 
HWWISH 
INTWAVE 

16.6 
. 
100 

16.8 
10.1 
100 

17.2 
11.6 
100 

optional 

Col_021/22 

COUNTRYB 

100 

100 

100 

100 

EE 

compulsory  Col_028 

SIGNISAL 

. 

Col_110 - 
Employed 
Col_110 - Not 
employed 
Col_111 - 
Employed 
Col_111 - Not 
employed 

METHODH 

C 

METHODH 

METHODI 

METHODI 

. 

. 

. 

C 

. 

C 

C 

. 

. 

. 

C 

C 

C 

. 

C 

. 

. 

. 

. 

. 

. 

C 

26.3  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 
Only methods corresponding to 
variables from METHODA 
(col_103) to METHODI (col_111) 
are considered as active 
methods. 
Only methods corresponding to 
variables from METHODA 
(col_103) to METHODI (col_111) 
are considered as active 
methods. 
In definitive database for 2nd 
quarter and for yearly dataset is 
without item-nonresponse, the 
error was in transcodification, 
only 2 records (persons). 
17.4  Only persons aged 15–69 
12.3 
100 

C 

. 

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. 
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 

Quality report of the European Union Labour Force Survey — 2014 

31

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

Col_113 - 
Employed 
Col_113 - Not 
employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
Col_115 - 
Employed 
Col_115 - Not 
employed 

METHODK 

C 

METHODK 

METHODL 

. 

. 

METHODL 

C 

METHODM 

METHODM 

. 

. 

. 

. 

. 

. 

. 

. 

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 
Due to small absolute numbers 
very few cases, if any 

IE 

compulsory  Col_054 

TEMPDUR 

60.4 

50.7 

42.9 

44.4  Persons are asked the question 

Col_073/74 

HWWISH 

11.1 

10.4 

. 

. 

EL 

compulsory  Col_039/40 

COUNTRYW  C 

C 

C 

C 

and the level of non-response 
generally reflects people not 
knowing what the duration of 
temporary employment will be 
The issue with this variable will be 
addressed as part of the current 
Household Survey 
Redevelopment project. This 
project is scheduled for 
completion in 2017. 
It is quite rare the incidence of 
persons residing in Greece and 
working abroad. 

ES 

compulsory  Col_073/74 

HWWISH 

82.8 

82.9 

83.9 

83.6  Most of the blanks come from 
people that don't wish to work 
more/less hours (perhaps the 
filter for this variable should be 
changed or add proper 
categories). Other option is to 
code the number of hours 
HHWISH from HWUSUAL.  
No 'other' active method in the 
survey  
No 'other' active method in the 
survey  

C 

C 

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.  
Respondents, primarily proxy 
respondents often do not know 
information on month in which 
person started working. 

Col_115 - 
Employed 
Col_115 - Not 
employed 
Col_129/131 

METHODM 

C 

METHODM 

. 

C 

. 

C 

C 

COURLEN 

36.5 

38.2 

46.9 

36.4  People aged 15 plus ‘don't know’ 

Col_209 
compulsory  Col_054 

FR 

Col_073/74 
Col_080/81 
Col_162/163 

EDUCLEVL 
TEMPDUR 
HWWISH 
NACE2J2D 
INTWEEK 

10 
20 
16.9 
17.5 
10.5 

10.3 
18.1 
16.7 
17.8 
10.6 

11.7 
16.1 
16.7 
17.7 
10.9 

number of hours 
10.6  People aged 15. 
17.2 
16.1 
17.2 
10.6 

HR 

compulsory  Col_047/48 

MSTARTWK 

13 

12 

11.7 

12 

Col_065/66 
Col_073/74 

HWOVERP 
HWWISH 

97 
89.6 

97.5 
89.5 

97.2 
87.2 

97.3 
86.7  One category of persons do not 

Col_101 - 
Employed 
Col_101 - Not 
employed 
Col_111 - 
Employed 

SEEKTYPE 

100 

100 

100 

100 

SEEKTYPE 

100 

100 

100 

100 

METHODI 

. 

. 

. 

. 

. 

C 

16.7 

. 

IT 

compulsory  Col_073/74 

HWWISH 

answer to this question. It is 
planned to be changed from 
2016. 
Variable will be available from 
2015. 
Variable will be available from 
2015. 

The questions on WISHMORE-
HWWISH in the IT questionnaire 

Quality report of the European Union Labour Force Survey — 2014 

32

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
  
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

Col_101 - 
Employed 

SEEKTYPE 

21.9 

23.3 

18.8 

21.9 

Col_101 - Not 
employed 

SEEKTYPE 

25.8 

26.7 

28.1 

28.2 

CY 

compulsory  Col_028 

Col_039/40 
Col_041/42 
Col_110 - 
Employed 
Col_111 - 
Employed 
Col_114 - 
Employed 

SIGNISAL 
. 
COUNTRYW  C 
C 
REGIONW 
C 
METHODH 

METHODI 

METHODL 

C 

C 

C 
C 
C 
. 

C 

. 

C 
C 
C 
C 

C 

. 

. 
C 
C 
C 

C 

. 

LV 

compulsory  Col_023 

PROXY 

13 

13.6 

13.6 

13.8 

Col_041/42 

REGIONW 

C 

C 

C 

C 

Col_084 

EXISTPR 

24.9 

26.1 

26.4 

26.9 

Col_111 - 
Employed 
Col_111 - Not 
employed 
Col_123 

METHODI 

METHODI 

. 

. 

C 

. 

. 

. 

. 

C 

EDUCSTAT 

13 

13.6 

13.6 

13.8 

Col_128 

COURATT 

13.1 

13.6 

13.6 

13.9 

LT 

compulsory  Col_041/42 

REGIONW 

C 

C 

C 

C 

Col_110 - 
Employed 

Col_111 - 
Employed 

Col_114 - 
Employed 

METHODH 

. 

. 

C 

. 

METHODI 

. 

. 

C 

. 

METHODL 

C 

C 

C 

. 

Short comments on reasons 
for non-available statistics and 
prospects for future solutions 
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. A little 
percentage of item non-
responses is due to ‘don't know’ 
answers. 
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. 

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

Rare method to use for searching 

Rare method to use for searching 

There aren't interviewed persons 
aged 75 or more included in filter. 
Data about workplace are 
collected at NUTS 1 level. 
There aren't interviewed persons 
aged 75 or more included in filter 
(col.84). 
This method is used infrequently. 

This method is used infrequently. 

There aren't interviewed persons 
aged 75 or more included in filter 
(col.123). 
There aren't interviewed persons 
aged 75 or more included in filter 
(col.128). 
All records have two values: 00 or 
99 because NUTS2 level is all 
country. Statistics Lithuania 
collects statistics on NUTS 3 level 
for this variable. 
This method used to find work is 
not very popular among 
employed respondents. In third 
quarter non of respondents 
indicated it, so all records had 
value 0 – ‘No’. 
This method used to find work is 
not very popular among 
employed respondents. In third 
quarter non of respondents 
indicated it, so all records had 
value 0 – ‘No’. 
This method used to find work is 
not very popular among 

Quality report of the European Union Labour Force Survey — 2014 

33

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

LU 

compulsory  Col_054 

Col_089/90 
Col_195 

HU 

compulsory  Col_047/48 

TEMPDUR 
MONTHPR 
INTWAVE 
MSTARTWK 

. 
. 
C 
. 

10.4 
. 
C 
11.8 

. 
11.3 
C 
16 

. 
. 
C 
22 

Col_084 

EXISTPR 

19 

19.2 

19.5 

19.7 

Col_089/90 

MONTHPR 

. 

. 

12.6 

20.3 

24.4 

. 

. 

C 

METHODH 

EDUCSTAT 

10.8 

10.8 

10.8 

10.9 

Col_110 - 
Employed 
Col_123 

Col_128 

COURATT 

10.8 

10.8 

10.8 

10.9 

MT 

compulsory  Col_041/42 

REGIONW 

C 

. 

C 

C 

Col_082/83 

HWACTUA2 

. 

. 

18.6 

Col_089/90 

MONTHPR 

. 

15.7 

18 

Col_112 - 
Employed 
Col_112 - Not 
employed 
Col_113 - 
Employed 
Col_113 - Not 
employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
Col_129/131 

METHODJ 

METHODJ 

METHODK 

METHODK 

METHODL 

METHODL 

C 

C 

C 

C 

C 

C 

COURLEN 

53 

C 

C 

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 
employed respondents. In 1–3 
quarters non of respondents 
indicated it, so all records had 
value 0 – ‘No’. 
No answers given by respondents
No answers given by respondents
No wave approach used 
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.

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.
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. 
Persons usually retain their 
secondary job, but reduce their 
working hours in summer. 
Usually this variable is imputed 
on the distribution of the variable 
itself, but when the imputation 
rate is high, the information is left 
empty. 
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. 
An error in the data entry program 
led to a high non response rate, 
which was rather difficult to 
impute all the information. 

NL 

compulsory  Col_054 

Col_080/81 
Col_112 - 
Employed 
Col_112 - Not 
employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
Col_021/22 

optional 
compulsory  Col_054 

Col_115 - 
Employed 
Col_115 - Not 

PT 

TEMPDUR 
NACE2J2D 
METHODJ 

64.3 
26.6 
C 

63.2 
26.5 
C 

62.7 
26.3 
C 

63.5 
26.5 
C 

METHODJ 

METHODL 

METHODL 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

COUNTRYB 
TEMPDUR 
METHODM 

13.9 
15 
C 

13.6 
15.4 
C 

13.4 
15 
C 

13.4 
15.1  NC 
NC 
C 

METHODM 

C 

. 

C 

C 

NC 

Quality report of the European Union Labour Force Survey — 2014 

34

 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

METHODH 

C 

. 

. 

C 

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

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

HWOVERP 
88.1 
HWOVERPU  93.6 
METHODH 

C 

88 
92.8 
. 

89.5 
93.8 
. 

87.8 
92.7 
. 

METHODH 

. 

METHODI 

METHODL 

METHODL 

C 

C 

C 

. 

. 

C 

C 

. 

. 

C 

C 

C 

. 

C 

C 

Almost NA in Slovenia 

Almost NA in Slovenia 

NA in Slovenia 

NA in Slovenia 

SEEKTYPE 

. 

12.4 

14.2 

15.8  Missing of appropriate code for 

those who are looking for any job 
(no preference between self-
employed, employees) causes 
higher value of the non-response 
rate. 

SEEKTYPE 

16.2 

16.2 

17.5 

17.3  Missing of appropriate code for 

RO 

SI 

SK 

employed 
compulsory  Col_110 - 
Employed 

compulsory  Col_065/66 
Col_067/68 
Col_110 - 
Employed 
Col_110 - Not 
employed 
Col_111 - 
Employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
compulsory  Col_101 - 
Employed 

Col_101 - Not 
employed 

Col_110 - 
Employed 

Col_114 - 
Employed 

Col_115 - 
Employed 

METHODH 

. 

. 

C 

C 

METHODL 

C 

C 

C 

C 

METHODM 

C 

C 

C 

C 

Col_115 - Not 
employed 

METHODM 

. 

. 

. 

C 

Col_209 

EDUCLEVL 

FI 

compulsory  Col_084 

EXISTPR 

. 

. 

39.5 

40.6 

40 

10.1 

10.2 

. 

those who are looking for any job 
(no preference between self-
employed, employees) 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’ 
Blank items should be added to 
code 3 
According to our calculations Q1 
non-response rate is 1.9 and Q2 
non-response rate is 2.0 for 15 to 
74 years old reference persons. 
As Finland is using persons as 
sampling units, this variable is 
optional for other members of the 
household. 

Col_102 - 
Employed 

SEEKDUR 

. 

. 

. 

Col_112 - 
Employed 

Col_113 - 
Employed 

METHODJ 

C 

. 

METHODK 

. 

C 

C 

C 

10.6  According to our calculations Q3 
non-response rate is 7.6 for 15 to 
74 years old reference persons. 
As Finland is using persons as 
sampling units, this variable is 
optional for other members of the 
household. 
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. 

C 

. 

Quality report of the European Union Labour Force Survey — 2014 

35

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

Col_114 - 
Employed 

METHODL 

C 

Col_114 - Not 
employed 
compulsory  Col_001/2 

SE 

METHODL 

C 

HHSEQNUM  C 

C 

C 

C 

C 

C 

C 

Col_054 

TEMPDUR 

17.2 

13.7 

12.4 

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

NA 

C 

C 

C 

The household supplement for 
the Swedish LFS is added to the 
8th rotation where all household 
members are included in the 
sample. Persons aged 15–74 
years of age are interviewed with 
regard to the labour market. Data 
for 2014 has been delivered to 
Eurostat separately from 
individual data. 
Respondents do not always 
remember start and end of work 
11.2  High item non response. People 

16 

Col_102 - 
Employed 

Col_102 - Not 
employed 

SEEKDUR 

12.2 

12.5 

11.1 

SEEKDUR 

25.3 

37.7 

17.2 

19 

Col_114 - 
Employed 

METHODL 

Col_114 - Not 
employed 

METHODL 

. 

. 

. 

C 

. 

. 

C 

C 

UK 

compulsory  Col_054 

TEMPDUR 

54.2 

54.7 

51.5 

52.7 

Col_065/66 

HWOVERP 

90.4 

90.3 

90.3 

89.6 

Col_067/68 

HWOVERPU  83.8 

83.9 

84.9 

84.1 

Col_073/74 

HWWISH 

88.4 

89 

89.2 

89.4 

Col_109 - 
Employed 

Col_109 - Not 
employed 

Col_113 - 
Employed 

Col_113 - Not 
employed 

Col_114 - 
Employed 

METHODG 

C 

C 

. 

C 

METHODG 

C 

C 

C 

. 

METHODK 

C 

C 

. 

C 

METHODK 

C 

C 

C 

. 

METHODL 

C 

C 

. 

C 

tend to forget how long they have 
been looking for work. 
High item non response. People 
tend to forget how long they have 
been looking for work. 
Very infrequent that this variable 
has value 1. Checked against 
micro-data. 

There is a high-level of non-
response due to a relatively small 
proportion of the employed 
sample working in a temporary 
job in the reference week. 
There is a high level of non-
response due to a relatively small 
proportion of the employed 
sample working overtime in the 
reference week 
There is a high level of non-
response due to a relatively small 
proportion of the employed 
sample working overtime in the 
reference week 
This variable is only computed for 
those who wish to work more 
hours. The non-response is due 
to only 4 % of the sample wishing 
to work more hours 
The UK-LFS does not collect 
information on whether 
respondents took a test, interview 
or examination. Only ‘no’ 
responses can be computed. 
The UK-LFS does not collect 
information on whether 
respondents took a test, interview 
or examination. Only ‘no’ 
responses can be computed. 
The UK-LFS does not collect 
information on whether 
respondents are waiting for a call 
from a public employment office 
The UK-LFS does not collect 
information on whether 
respondents are waiting for a call 
from a public employment office 
The UK-LFS does not collect 
information on whether 
respondents are awaiting results 

Quality report of the European Union Labour Force Survey — 2014 

36

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

Col_114 - Not 
employed 

METHODL 

C 

C 

C 

. 

Col_129/131 

COURLEN 

70.9 

70.3 

69.6 

69.6 

Col_209 

EDUCLEVL 

. 

. 

10.9 

. 

Short comments on reasons 
for non-available statistics and 
prospects for future solutions 
of a competition for recruitment to 
the public sector 
The UK-LFS does not collect 
information on whether 
respondents are awaiting 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 
Seasonal, i.e. higher proportion of 
cases where EDUCSTAT = 3 in 
summer 

IS 

compulsory  Col_001/2 

Col_039/40 
Col_041/42 
Col_065/66 
Col_067/68 
Col_069/70 
Col_073/74 
Col_101 - 
Employed 
Col_101 - Not 
employed 
Col_102 - 
Employed 
Col_102 - Not 
employed 
Col_103 - 
Employed 
Col_104 - 
Employed 
Col_105 - 
Employed 
Col_106 - 
Employed 
Col_107 - 
Employed 
Col_108 - 
Employed 
Col_109 - 
Employed 
Col_109 - Not 
employed 
Col_110 - 
Employed 
Col_111 - 
Employed 
Col_112 - 
Employed 
Col_113 - 
Employed 
Col_113 - Not 
employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
Col_115 - 
Employed 
Col_116 
Col_117 - 

HHSEQNUM 
. 
COUNTRYW  C 
C 
REGIONW 
HWOVERP 
66.2 
HWOVERPU  64.9 
16.2 
HOURREAS 
100 
HWWISH 
100 
SEEKTYPE 

C 
. 
. 
69.6 
68.7 
16.5 
100 
100 

C 
. 
. 
71.4 
70.9 
16.1 
100 
100 

. 
C 
C 
67.3 
66.8 
14.7 
99.9 
100 

SEEKTYPE 

. 

14.2 

. 

. 

SEEKDUR 

100 

100 

100 

100 

SEEKDUR 

METHODA 

METHODB 

METHODC 

METHODD 

METHODE 

METHODF 

METHODG 

. 

. 

. 

. 

. 

. 

. 

. 

METHODG 

C 

METHODH 

METHODI 

METHODJ 

METHODK 

. 

. 

. 

. 

METHODK 

C 

METHODL 

. 

METHODL 

C 

METHODM 

. 

15.2 

. 

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 

. 

. 

. 

. 

. 

. 

. 

. 

C 

. 

. 

. 

. 

C 

. 

C 

. 

WANTWORK  26.3 
AVAILBLE 

C 

37.6 
C 

27 
. 

31.1 
C 

Quality report of the European Union Labour Force Survey — 2014 

37

 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

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

Employed 
Col_209 

compulsory  Col_039/40 
Col_047/48 
Col_054 
Col_071 
Col_076 
Col_082/83 
Col_089/90 
Col_102 - 
Employed 
Col_102 - Not 
employed 
Col_110 - 
Employed 
Col_110 - Not 
employed 
Col_111 - 
Employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 
compulsory  Col_001/2 

NO 

CH 

Col_110 - Not 
employed 
Col_111 - Not 
employed 
Col_114 - 
Employed 
Col_114 - Not 
employed 

Col_114 - 
Employed 
Col_114 - Not 
employed 
Col_115 - 
Employed 
Col_168 

TR 

compulsory  Col_017/18 

100 

EDUCLEVL 
COUNTRYW  C 
MSTARTWK 
TEMPDUR 
WISHMORE 
LOOKOJ 
HWACTUA2 
MONTHPR 
SEEKDUR 

28.6 
48 
13.6 
12.6 
11.3 
. 
. 

100 
C 
33.3 
49.7 
12.6 
11.3 
. 
. 
. 

100 
C 
35.4 
42.8 
13.7 
12.6 
. 
. 
10.1 

100 
C 
39.3 
49.8 
14.1 
12.9 
10.5 
10.5 
10.5 

SEEKDUR 

. 

10.8 

METHODH 

C 

METHODH 

. 

METHODI 

METHODL 

METHODL 

C 

C 

C 

HHSEQNUM  C 

METHODH 

C 

METHODI 

METHODL 

METHODL 

METHODL 

METHODL 

. 

C 

C 

C 

C 

C 

METHODM 

. 

. 

. 

. 

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 

DEGURBA 
NATIONAL 

100 
100 

100 
100 

100 
100 

100 
100 

MK 

compulsory  Col_041/42 

REGIONW 

Col_039/40 

COUNTRYW 

. 

C 

C 

C 

Col_067/68 

HWOVERPU  100 

100 

100 

100 

In Switzerland only one person 
per household is interviewed (see 
derogation in annex II). For this 
person 
HHSEQNUM automatically 
equals 1. 
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. 

According to the 2010 Address 
Based Population 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. 
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. 

Quality report of the European Union Labour Force Survey — 2014 

38

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

Q1 

Q2 

Q3 

Q4 

Col_073/74 

HWWISH 

100 

100 

100 

100 

Col_104 - 
Employed 

METHODB 

C 

C 

C 

C 

Col_108 - 
Employed 
Col_111 - 
Employed 
Col_113 - 
Employed 
Col_114 - 
Employed 
Col_168 

METHODF 

METHODI 

METHODK 

METHODL 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

C 

DEGURBA 

100 

100 

100 

100 

Short comments on reasons 
for non-available statistics and 
prospects for future solutions 
This variable was dropped out 
from the questionnaire in 2009 
since it was observed that, results 
were not reliable. Respondents 
replied this question as they 
understand (some give the hours 
that would like to work in total 
while others only give the 
additional hours). 
For employed people all the 
methods are not asked in same 
detail, some of them are grouped 
looking at the frequency (for 
example, Public Employment 
Office and Private Employment 
Offices are combined in one 
code). So, while constituting the 
METHOD variables, there are 
some blank codes for employed 
people. 
See METHODB 

See METHODB 

See METHODB 

See METHODB 

Note: ‘C’ All records have the same value 
Source: Joint Standard Quality Report for Labour Force Survey and Regional Labour Market Statistics – Annual quality 
reports 2014 

Quality report of the European Union Labour Force Survey — 2014 

39

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Annual data 2014 

Variable 
status 

Column 

Identifier 

2014 

BE 

compulsory 

Col_118 - Not employed 

AVAIREAS 

90 

BG 

compulsory 

Col_118 - Employed 

AVAIREAS 

16.7 

optional 

Col_136 

COURWORH 

CZ 

compulsory 

Col_154/155 

INCDECIL 

optional 

Col_125/127 

EDUCFILD 

Col_132 

Col_136 

DK 

optional 

Col_132 

Col_133/134 

Col_136 

DE 

compulsory 

Col_036 

Col_049 

Col_053 

Col_055 

Col_120 

Col_121 

Col_150/151 

Col_122 

Col_136 

optional 

EE 

compulsory 

Col_053 

COURPURP 

COURWORH 

COURPURP 

COURFILD 

COURWORH 

SUPVISOR 

WAYJFOUN 

TEMPREAS 

TEMPAGCY 

NEEDCARE 

REGISTER 

COUNTR1Y 

MAINSTAT 

COURWORH 

TEMPREAS 

100 

100 

100 

100 

100 

100 

100 

100 

20 

11.5 

34.9 

24 

28.4 

93.9 

10 

100 

100 

16.3 

Short comments on 
reasons for non-available 
statistics and prospects 
for future solutions 
(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. 
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. 
Dataset with this variable 
will be sent 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 

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’ 

Problem will be solved in 
the future 

In the Eurostat’s study 
‘Analysis of questionnaires, 
explanatory notes and 
transcodification 
programmes for the 
national Labour Force 
Surveys’, it was pointed out 
that in the Estonian 
transcodification program, 
the EU LFS option 3 
(Person did not want a 
permanent job) of the 
variable TEMPREAS 

Quality report of the European Union Labour Force Survey — 2014 

40

 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
  
Variable 
status 

Column 

Identifier 

2014 

IE 

compulsory 

Col_037/38 

SIZEFIRM 

Col_053 

Col_093 

Col_118 - Employed 

Col_119 

Col_121 

Col_146 

Col_150/151 

Col_152/153 

Col_154/155 

TEMPREAS 

STAPROPR 

AVAIREAS 

PRESEEK 

REGISTER 

WSTAT1Y 

COUNTR1Y 

REGION1Y 

INCDECIL 

optional 

Col_132 

COURPURP 

Col_133/134 

Col_136 

COURFILD 

COURWORH 

EL 

compulsory 

Col_053 

TEMPREAS 

12.6 

18.2 

100 

97.4 

100 

100 

100 

100 

C 

70.9 

48.3 

100 

22 

20.9 

Col_118 - Employed 

AVAIREAS 

24.6 

Col_154/155 

INCDECIL 

optional 

Col_132 

COURPURP 

20.3 

10.9 

Short comments on 
reasons for non-available 
statistics and prospects 
for future solutions 
includes persons having ‘no 
preference’ (D15=3) 
between both categories 
‘Did not want permanent 
job’ and ‘Wanted 
permanent job, but have 
not found?’. To correct it, 
persons having ‘no 
preference’ (D15=3) are 
coded as ‘blank’ since 
2010. 
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 

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. 
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. 
The high non response in 
this (and the next 2 
variables) is probably due 
to the fact that a part of the 
respondents (specifically-
employed persons) is 
asked separately about 
participation in work-related 
educational activities. In 
several cases, these are 

Quality report of the European Union Labour Force Survey — 2014 

41

 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

2014 

Col_133/134 

Col_136 

COURFILD 

COURWORH 

ES 

compulsory 

Col_118 - Not employed 

AVAIREAS 

Col_120 

Col_154/155 

Col_132 

optional 

Col_133/134 

FR 

compulsory 

Col_136 

Col_049 
Col_053 
Col_119 

NEEDCARE 

INCDECIL 

COURPURP 

COURFILD 

COURWORH 

WAYJFOUN 
TEMPREAS 
PRESEEK 

optional 
compulsory 

HR 

Col_150/151 
Col_154/155 
Col_132 
Col_118 - Employed 

Col_150/151 

optional 
compulsory 

IT 

Col_154/155 

Col_133/134 
Col_150/151 

COUNTR1Y 
INCDECIL 
COURPURP 
AVAIREAS 

COUNTR1Y 

INCDECIL 

COURFILD 
COUNTR1Y 

CY 

compulsory 

Col_055 

Col_146 

TEMPAGCY 

WSTAT1Y 

optional 

Col_122 

MAINSTAT 

LT 

compulsory 

Col_152/153 

REGION1Y 

10.9 

10.9 

20.2 

10.2 

100 

16.4 

18.2 

100 

18.3 
12 
45.8 

19 
25.2 
9.7 
85 

14 

26 

100 
12.6 

C 

13.5 

13.5 

C 

Short comments on 
reasons for non-available 
statistics and prospects 
for future solutions 
proxies and the person who 
is answering is aware of the 
fact that the person 
participated in an activity 
but does not know the 
details (subject, etc) to 
report. We are trying to 
improve the situation 
See previous comment. 

See previous comment. 

It will be provided from 
registers in due time. 
People aged 15 

People aged 15 

Not provided 

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; Indeed, information 
are available in the 
questionnaire regarding the 
situation at each of the last 
twelve months and 
regarding the date since 
people have been seeking 
a job. 

One category of persons 
(persons under 15) did not 
answer at this question. It 
was changed from 2015. 

Item non-response is due 
to people aged less than 15 
years, for which this 
information is not collected 
in the national 
questionnaire 
No such agencies in 
Cyprus 
There aren't interviewed 
persons aged 75 or more 
included in filter (col.146). 
There aren't interviewed 
persons aged 75 or more 
included in filter (col.122). 
All records have two 
values: NUTS2 or 99. 
Statistics Lithuania collects 
statistics on NUTS 3 level 
for this variable. 

Quality report of the European Union Labour Force Survey — 2014 

42

 
 
 
 
 
 
 
  
 
 
  
 
 
 
 
 
 
 
  
 
 
  
 
 
 
 
  
 
 
  
 
  
  
 
 
 
 
  
 
 
 
 
 
Variable 
status 

Column 

Identifier 

2014 

Col_154/155 

INCDECIL 

30.9 

LU 

compulsory 

Col_118 - Not employed 

AVAIREAS 

HU 

compulsory 

Col_146 

Col_121 

REGISTER 

WSTAT1Y 

Col_154/155 

INCDECIL 

optional 

Col_122 

MAINSTAT 

MT 

compulsory 

Col_118 - Employed 

AVAIREAS 

optional 

Col_132 

COURPURP 

Col_133/134 

Col_136 

NL 

compulsory 

Col_049 

Col_051 

Col_053 

Col_093 

Col_094/95 

Col_096/98 

COURFILD 

COURWORH 

WAYJFOUN 

FTPTREAS 

TEMPREAS 

STAPROPR 

NACEPR2D 

ISCOPR3D 

Col_118 - Not employed 

AVAIREAS 

Col_119 

Col_146 

Col_136 

optional 

AT 

compulsory 

Col_121 

Col_154/155 

PRESEEK 

WSTAT1Y 

COURWORH 

REGISTER 

INCDECIL 

11.6 

13.3 

10.8 

100 

10.8 

84.8 

13.8 

100 

100 

62.6 

12.4 

32.7 

60.5 

65.8 

75.1 

30.9 

66.7 

18.3 

11.4 

100 

100 

Short comments on 
reasons for non-available 
statistics and prospects 
for future solutions 
Some respondents do not 
want to tell their monthly 
wage (salary). From IV 
quarter 2010 the Social 
Insurance Fund Board data 
 is used  for imputation  of 
wage (salary) from the 
main job for respondents 
who didn't answer this 
question. 

There is an upper-age limit 
(74 years) in HU-LFS for 
this variable. 
According to the Regulation 
(EC) No 1372/2007 of the 
European Parliament and 
the Council of 23 October 
2007 amending Council 
regulation (EC) No 577/98 
on the organization of a 
labour force sample survey 
in the Community 
transmission of the results 
— where administrative 
data are used to supply 
data corresponding to the 
survey characteristic wages 
from the main job, — may 
be forwarded to Eurostat 
within twenty-one months 
of the end of the reference 
period. And data always 
are transmitted to Eurostat 
to the end of the requested 
period. 
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. 
This variable has been 
recently included in the 
questionnaire.  Necessary 
analysis and imputations 
will be carried out if 
necessary in the future. 
Information is not collected. 

Information is not collected. 

Delivered yearly 

Delivered yearly 

Quality report of the European Union Labour Force Survey — 2014 

43

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Variable 
status 

Column 

Identifier 

2014 

PL 

compulsory 

Col_154/155 

INCDECIL 

PT 

compulsory 

Col_154/155 

optional 

Col_125/127 

Col_132 

Col_133/134 

Col_136 

SI 

compulsory 

Col_016 

Col_049 

Col_091/92 

Col_093 

Col_094/95 

Col_096/98 

INCDECIL 

EDUCFILD 

COURPURP 

COURFILD 

COURWORH 

MARSTAT 

WAYJFOUN 

LEAVREAS 

STAPROPR 

NACEPR2D 

ISCOPR3D 

Col_118 - Employed 

AVAIREAS 

Col_154/155 

INCDECIL 

optional 

Col_133/134 

SK 

compulsory 

Col_154/155 

FI 

compulsory 

Col_146 

COURFILD 

INCDECIL 

WSTAT1Y 

56.9 

34.3 

100 

100 

100 

100 

13.3 

19.8 

96.4 

96.2 

97.1 

98.3 

100 

100 

100 

41.5 

18.9 

Col_150/151 

COUNTR1Y 

41.8 

Col_154/155 

INCDECIL 

optional 

Col_133/134 

SE 

compulsory 

Col_118 - Employed 

Col_121 

COURFILD 

AVAIREAS 

REGISTER 

Col_146 

WSTAT1Y 

Col_154/155 

optional 

Col_132 

INCDECIL 

COURPURP 

Col_133/134 

COURFILD 

77.4 

100 

77.7 

19.3 

44.3 

100 

100 

100 

Short comments on 
reasons for non-available 
statistics and prospects 
for future solutions 
We are taking in account to 
apply imputation method for 
this variable in future. 
NC 

NC 

NC 

NC 

NC 

Problem will be solved in 
the future. 
Problem will be solved in 
the future. 

Problem will be solved in 
the future. 
Problem will be solved in 
the future. 
Yearly files are sent 
separately by 31 March of 
the following year 

Very sensitive nature of 
question 
As Finland is using persons 
as sampling units, this 
variable is optional for other 
members of the household. 
The non-response rate is 
5.9 for the right target 
group with the yearly 
weighting factor COEFFY: 
INTWAVE=5 and 
HHLINK=1 and age=15-74. 
As Finland is using persons 
as sampling units, this 
variable is optional for other 
members of the household. 
The non-response rate is 
7.4 for the right target 
group with the yearly 
weighting factor COEFFY: 
INTWAVE=5 and 
HHLINK=1 and age=15–74. 
The non-response rate is 
7.4 for 15 to 74 years old 
reference persons. 
Optional variable. 

The variable has been 
adjusted 2010 
The high non-response is 
due to employed who 
doesn't look for another job. 
A new solution of collecting 
the data was used during 
2007. Some smaller 
improvements have been 
done since then. 
Register variable. 

Optional. Will not be 
collected 
Optional. Will not be 

Quality report of the European Union Labour Force Survey — 2014 

44

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

Optional. Will not be 
collected 
The current calculation of 
TEMPREAS assigns 
WHYTMP6 = 5 (some other 
reason) to blank (no 
answer). Eurostat 
codification only allows the 
four values covered by the 
first four response 
categories. It is not clear 
how those who answer 
‘some other reason’ should 
be coded. 
TEMPAGCY is derived 
from NSI var TMPCON 
(contract with employment 
agency). TMPCON only 
asked if HOWGET = 5 
(private employment 
agency). If filter HOWGET 
= 5 included in DV then 
item non response falls to < 
2 %. 
Further analysis to be 
undertaken. 
Further analysis to be 
undertaken. 
Further analysis to be 
undertaken. 
Revised to 4.3 % following 
error in Q1 and Q2 data. 
Refusal = 15.6 %, non-
contact (no proxy) = 4.1 %, 
no pay yet received = 
0.3 %, don't know = 5.9 %. 
Not currently included on 
UK LFS. 
The national questionnaire 
variable that informs 
COURPURP - T4PURP is 
asked only of specific forms 
of taught-learning. The UK 
training and taught learning 
questions are currently 
being reviewed and will 
change for 2016. 
As COURPURP. 

Variable 
status 

Column 

Identifier 

2014 

Col_136 

COURWORH 

UK 

compulsory 

Col_053 

TEMPREAS 

100 

33.2 

Col_055 

TEMPAGCY 

98.6 

Col_118 - Employed 

AVAIREAS 

Col_118 - Not employed 

AVAIREAS 

Col_120 

Col_121 

NEEDCARE 

REGISTER 

Col_154/155 

INCDECIL 

optional 

Col_122 

Col_132 

MAINSTAT 

COURPURP 

IS 

compulsory 

Col_053 

Col_136 

Col_055 

Col_093 

Col_094/95 

Col_096/98 

Col_100 

Col_118 - Employed 

COURWORH 

TEMPREAS 

TEMPAGCY 

STAPROPR 

NACEPR2D 

ISCOPR3D 

SEEKREAS 

AVAIREAS 

Col_118 - Not employed 

AVAIREAS 

Col_121 

Col_150/151 

Col_152/153 

Col_154/155 

optional 

Col_122 

REGISTER 

COUNTR1Y 

REGION1Y 

INCDECIL 

MAINSTAT 

67.6 

34.7 

55.6 

52.4 

25.9 

100 

72.7 

72.7 

38.3 

C 

67.3 

49.2 

15.6 

29.9 

100 

71.7 

73.8 

84.9 

C 

100 

23.1 

Quality report of the European Union Labour Force Survey — 2014 

45

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
Variable 
status 

Column 

Identifier 

2014 

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

NO 

compulsory 

Col_049 

Col_133/134 

Col_051 

Col_053 

Col_094/95 

Col_096/98 

Col_100 

Col_118 - Employed 

Col_119 

Col_121 

Col_150/151 

Col_152/153 

Col_154/155 

optional 

Col_132 

Col_133/134 

Col_136 

CH 

compulsory 

Col_053 

COURFILD 

WAYJFOUN 

FTPTREAS 

TEMPREAS 

NACEPR2D 

ISCOPR3D 

SEEKREAS 

AVAIREAS 

PRESEEK 

REGISTER 

COUNTR1Y 

REGION1Y 

INCDECIL 

COURPURP 

COURFILD 

COURWORH 

TEMPREAS 

100 

30.8 

26.6 

21.2 

100 

100 

31.4 

24.2 

19.3 

100 

100 

C 

100 

100 

100 

100 

26.8 

Col_094/95 

NACEPR2D 

11.7 

Col_118 - Not employed 

AVAIREAS 

Col_120 

NEEDCARE 

optional 

Col_072 

Col_132 

Col_133/134 

Col_136 

WAYMORE 

COURPURP 

COURFILD 

COURWORH 

MK 

compulsory 

Col_118 - Not employed 

AVAIREAS 

Col_119 

Col_120 

Col_121 

PRESEEK 

NEEDCARE 

REGISTER 

Col_150/151 

COUNTR1Y 

Col_152/153 

Col_154/155 

optional 

Col_122 

TR 

compulsory 

Col_055 

REGION1Y 

INCDECIL 

MAINSTAT 

TEMPAGCY 

17.6 

29.4 

33 

35.7 

100 

100 

93.1 

100 

100 

83.4 

15.3 

C 

100 

100 

100 

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 error, modification of 
the questionnaire made for 
2016 
Filter error, modification of 
the questionnaire made for 
2016 
Filter/codification error, 
adaptation planned 
Filter error, modification of 
the questionnaire made for 
2016 
Not asked in the SLFS. 

Not asked in the SLFS. 

This variable is planned to 
be introduced in the future. 
This variable is planned to 
be introduced in the future. 

This variable is not asked 
since temporary working 
agencies are not common 

Quality report of the European Union Labour Force Survey — 2014 

46

 
 
 
 
 
  
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
 
  
 
  
 
 
  
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
  
 
 
  
 
 
 
 
 
 
  
 
 
  
 
 
Variable 
status 

Column 

Identifier 

2014 

Col_118 - Employed 

AVAIREAS 

C 

Col_121 

REGISTER 

100 

Col_150/151 

optional 

Col_132 

COUNTR1Y 

COURPURP 

100 

100 

Col_133/135 

COURFILD 

100 

Col_136 

COURWORH 

100 

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

Questions about attending 
any courses, seminars, 
conferences or receive 
private lessons or 
instructions outside the 
regular education system 
haven't asked since 2014. 
Questions about attending 
any courses, seminars, 
conferences or receive 
private lessons or 
instructions outside the 
regular education system 
haven't asked since 2014. 
Questions about attending 
any courses, seminars, 
conferences or receive 
private lessons or 
instructions outside the 
regular education system 
haven't asked since 2014. 

Note: ‘C’ All records have the same value  
Source: Joint Standard Quality Report for Labour Force Survey and Regional Labour Market Statistics – Annual quality 
reports 2014 

Quality report of the European Union Labour Force Survey — 2014 

47

 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
11  Annex II: Data presentation and abbreviations 

Data presentation 

The following symbols are used, where necessary: 
:  
– 

Not available; 
Not applicable. 

Geographical aggregates and country codes 

EU-28   
EU 
EA-19    
EEA 

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 (1)   
TR  

European Union of 28 Member States 
European Union 
Euro area of 19 Member States 
European Economic Area 

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 

(1)  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 — 2014 

48

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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