Christof Wolf, Andrea Lengerer, Heike Wirth

• Samples are usually very large
 Allowing for analysis of small groups
 Allowing for analysis of small regions
 Leading to higher precision
• Question programs are usually relatively stable
 Supporting comparison over time
 analysis of social change
• For surveys regulated at European level procedures and
(target) variables are partly standardized
 Supporting cross-national analysis
• Often high response rates (participation sometimes compulsory)
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• As a reference statistic
• Substantive research, e.g.
The Effects of Labour Market Regulations
Being a Eurpean wide repeated cross-sectional survey LFS allows analysising the development of the labour market in a comparative perspective. One example is the effect of changing employment protection legislation on age-specific labour market participation.
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e.g. Migration and Integration
• LFS offers possibility to conceptualize immigration by nationality and/or by country of birth and allows to differentiate between immigrants obtaining their education in their country of residency or abroad
(through years of residence)
• But: nationality and country of birth are both coarsened in the user data base
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• Research Question:
„The aim of our analyses is to evaluate country specific differences and similarities in the scope and characteristics of immigrant entrepreneurship. The analyses are expected to highlight the importance of macro-level factors, namely opportunity and institutional structures.”
• Data: EU-LFS 2005
* Kerstin Hermes and René Leicht, 2010: Scope and Characteristics of
Immigrant Entrepreneurship in Europe. Working Paper, Mannheim.
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• Authors base their definition of ‘immigrant’ on nationality because nationality and not country of birth matters from a legal point of view
• Further differentiation of non-nationals in:
Foreigners from other EU countries and from Non-EU countries
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45
40
35
30
25
20
15
10
5
0
Belgium Germany Portugal Spain
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Native
EU Foreigners
Non-EU Foreigners
7

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• LFS is a cross-national repeated cross-section for European
 Analysis of social change, Age-Period-Cohort analysis
 Multi-level modeling; cross-classified level 2 units: countries x time
 Alternatively: two-step modelling approach
 Country specific individual level modelling of interesting dependent variable, e.g. employment status
 Cross-country analysis of results from step 1, e.g. predicted probabilities
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Martina Dieckhoff and Nadia Steiber, 2012:
Institutional reforms and age-graded labour market inequalities in Europe. International Journal of
Comparative Sociology Online prepublication.
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Predicted probabilities for fixed-term employment
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I.
Comparability of design
II.
Comparability of variables
III.
Comparability over time
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1
• Mostly last censuses or population registers are used as frame
(LU: list of telefon numbers)
• Depending on country final sampling untits are persons, households, dwelling units, cluster of dwelling units or addresses
• Sampling rate per quarter varies from 0.24% (TR) to 3% (IE)
• Sex, age and region are used for adjustment weights; some countries also consider nationality, ethinic background, household size, employment status etc.
1 Data from 2009
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1
• LFS is conducted in different survey modes; often in mixed-mode; mostly CAPI/PAPI but also selfadministered and telephone interviews
• Workload of interviewers varies from 50 (PL) to 1,125
(NL) to interviews per quarter
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1 Data from 2009
15

1
• EU regulation allows that information on household members is provided by other household members
 proxy interviews
• EU average is 34 % (unweighted) but proxy rates vary from 2% (DK) to 58% (SI, TR)
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1 Data from 2009
16

• Participation in LFS is compulsory in some and voluntary in other countries
• Large variation in response rates: 31 % (LU) to
97 % (DE) (rates may not be stricly comparable)
• Institutional households and persons over 74 are not covered in all countries (UK & IS only from 16)
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• The regulation defines the mandatory variables for
EU-LFS
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• The regulation defines the mandatory variables for
EU-LFS
• These are so called target variables
• Data do not have to come from surveys but may come from administrative records and registers
• No common questionnaire
• Survey questions are not standardized/ harmonized
 large variation
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Italy
Hungary
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IT
Single
Married
Separated de facto
Lagally separated
Divorced
Widowed
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HU
Single
Married
Widowed
HR
Single
Married
Widowed
Divorced or legally separated Divorced
Cohabitating couple
Separated from spouse
User Data Base
0 Widowed, divorced or legally separated
1 Single
2 Married
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2
• Part of ‘quality-in-work’ indicators used to monitoring gender equality in the labour market
• Supervisory status also used in measures of sociostructural / class position, e.g.
 Ericson/Goldthorpe/Portocarero schema (EGP)
 Wright’s class schema
 European Socioeconomic Classification (ESeC)
18 Sept. 2014
2 Reinhard Pollak, Heike Wirth, Felix Weiss, Gerrit Bauer and Walter Müller. 2009. On the
Comparative Measurement of Supervisory Status using the Examples of the ESS and the EU-
LFS. In International vergleichende Sozialforschung. Ed. Birgit Pfau-Effinger, Sladana Sakac
Magdalenic and Christof Wolf,. Pp. 173-206 . Wiesbaden: VS Verlag für Sozialwissenschaften.
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• ESeC classes
1.
Large employers, higher managerial and professional occupations
2.
Lower managerial and professional occupations
3.
Intermediate occupations
4.
Small employers and own account workers
5.
Employers and self-employed in agriculture
6.
Lower supervisory and lower technician occupations
7.
Lower services occupations
8.
Lower technical occupations
9.
Routine occupations
• Supervisors are assumed to be different in their employment relations to
‘rank and file’ workers
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• ESeC classes
1.
Large employers, higher managerial and professional occupations
2.
Lower managerial and professional occupations
3.
Intermediate occupations
4.
Small employers and own account workers
5.
Employers and self-employed in agriculture
6.
Lower supervisory and lower technician occupations
7.
Lower services occupations
8.
Lower technical occupations
9.
Routine occupations
• Supervisors are assumed to be different in their employment relations to
‘rank and file’ workers
• Supervisory status used to allocate employees otherwise coded as ESeC
3,7,8,9 into ESeC 2 or 6
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• EU-LFS (explantory notes): “A person with supervisory responsibilities takes charge of the work , directs the work and sees that it is satisfactorily carried out ”
• EU-SILC (description target variables): “Supervisory responsibility includes formal responsibility for supervising a group of other employees (...), whom they supervise directly , sometimes doing some of the work they supervise”
• ESeC Draft User Guide: “Supervisors are neither managers nor professionals but are responsible as their main job task for supervising the work of other employees”
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Operationalisation of the ‚supervisory status‘: LFS – Examples
Country
Austria
Germany
German questionnaires – LFS questions English translation
Haben Sie in Ihrer Tätigkeit
Leitungsfunktion? (Das kann auch in weniger qualifizierten Berufen der Fall sein)
Do you have function
leading [managerial]
in your job? (This could also be the case in less qualified jobs)
Sind Sie in Ihrer (Haupt-)
Erwerbstätigkeit in einer leitenden
Position tätig?
Switzerland Wieviele Personen sind Ihnen direkt oder indirekt ingesamt unterstellt?
In your (main) job, are you in a leading [managerial] position ?
Belgium Trägt F/H Verantwortung, d.h. hat F/H die Aufsicht bzw. die Koordination über die Arbeit anderer Arbeitnehmer?
How many persons are altogether directly or indirectly responsible to you?
Does she/he have responsibility, that is does she/he supervise or coordinate the work of other employees?
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Operationalisation of the ‚supervisory status‘: LFS – Examples
Country
Belgium
Ireland
UK
Sweden
English questionnaires – EU-LFS questions
Do you have a responsible job , in other words, do you supervise other personnel
Do you supervise the work of other people on a regular basis?
Note: This does not include people who monitor quality control only or persons who only supervise on a temporary basis
In your job, do you have formal responsibility for supervising the work of other employees?
Do your tasks include managing and supervising the work of other employees?
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45
How comparable are these figures?
40
35
30
26 26
28 29
31
33
35
36
25
20
15
10
10
11 12
12 13
13
16 16
17 17 17
18 18
20 20 21
21 22
22 23
42
5
0
2
LV RO GR SK DK HU BG CZ ES PL LT FR CY EE PT SI FI DE BE IT NL AT IE SE MT CH NO LU UK IS
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• Eurostat’s LFS microdata starts from 1983
• Data for EU countries are usually available depending on when they joined the EU, and from 2000 for all countries
• Germany (anonymised microdata is provided from 2002 onwards only) and Malta (anonymised microdata is provided from 2009 onwards only) are exceptions
• For Iceland and Norway data are available from 1995
• For Switzerland data are available from 1996
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1.
Changing reference period, annual vs. continuous survey
2.
Changing classifications
3.
Changing codification
4.
Changing sample design
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• Annual surveys from 1983 to 1997 (conducted in spring)
• Continuous surveys starting in 1998 (reference weeks are spread uniformly throughout the year)
• Data for all quarters of a year are progressively available starting between 1998 and 2004 for all countries, except
Germany (quarterly data are available from 2005)
• The reference sample for yearly files corresponds to one reference quarter in spring until 2004, and to an annual sample covering all weeks of the year from 2005
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country
EE
ES
FI
FR
GR
HU
IE
CY
CZ
DE
DK
AT
BE
BG
CH
Austria
Belgium
Bulgaria
Switzerland
Cyprus
Czech Republic
Germany
Denmark
Estonia
Spain
Finland
France
Greece
Hungary
Ireland yearly quarterly country
1997
1986
1995
1983
1983
1996
1983
1995
1983
2000
1996
1999
1997
2002
1983
1999
1999
2000
2010
2004
1998
2005
1999
2000
1996
1998
2003
1998
1999
1999
PL
PT
RO
SE
SI
SK
UK
IS
IT
LT
LU
LV
MT
NL
NO
Iceland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Norway
Poland
Portugal
Romania
Sweden
Slovenia
Slovak Republic
United Kingdom yearly quarterly
1997
1986
1997
1995
1996
1998
1983
1995
1983
1998
1983
1998
2009
1983
1995
2000
1997
1999
2001
1999
1998
2000
2003
1997
2002
2003
2002
2009
2000
2000
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Region
Economic activity
Occupation
Education
NUTS
NACE
ISCO
ISCED
NUTS II (except for AT, DE and UK), several changes
NACE Rev. 2 from 2008
NACE Rev. 1.1 from 2005 to 2008
NACE Rev. 1 from 1992 to 2004
NACE 1970 from 1983 to 1991
ISCO 08 from 2011
ISCO 88 COM until 2010
ISCED 1997
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Two examples:
• Nationality
• Education
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NATIONAL, until 2003
0
111
911
800
-1
National / Native of own Country
EU15
Non EU15
Non-National / Non-Native (in case the distinction EU/Non-EU is not possible)
No answer, suppressed, other country or stateless
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NATIONAL, from 2004 onwards
8
9
10
5
6
7
2
3
4
0
1
11
12
13
18
19
20
21
-1
14
15
16
17
National / Native of own Country
EU15
NMS10 (10 new Member States of 2004)
NMS2 (2 new Member States of 2007)
NMS12 (code 2,3)
EU27 (code 1,2,3)
EFTA
Other Europe
Europe outside EU27 (code 6,7)
North Africa
Other Africa
Near and Middle East
East Asia
South and South East Asia
North Africa and Near and Middle East (code 9,11)
East and South Asia (code 12,13)
North America
Central America (and Caribbean)
South America
Australia and Oceania
Latin America (code 17,18)
North America and Australia / Oceania (code 16,19)
No answer, suppressed, other country or stateless 38

HATLEV1D, from 1983 onwards
3
-1
-2
1
2
Low: Lower secondary
Medium: Upper secondary
High: Third level
No answer
Not applicable (child less than 15 years)
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36
41
42
43
51
52
31
32
33
34
35
60
-1
-2
HATLEVEL, from 1998 onwards
0
10
11
21
22
30
No formal education or below ISCED 1
ISCED 0-1
ISCED 1
ISCED 2
ISCED 3c (shorter than 2 years)
ISCED 3 (without distinction a, b or c possible, 2 years and more)
ISCED 3c (2 years and more)
ISCED 3 a,b
ISCED 3c (3 years or longer) or ISCED 4c
ISCED 3b or ISCED 4b
ISCED 3a or ISCED 4a
ISCED 3 or 4 (without distinction a, b or c possible)
ISCED 4a,b
ISCED 4c
ISCED 4 (without distinction a, b or c possible)
ISCED 5b
ISCED 5a
ISCED 6
No answer
Not applicable (child less than 15 years)
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• Changing sampling frame (i.e. Central Population
Register in LU until 2008 and random digit dialling from 2009)
• Changing stratification of sampling units (i.e. multistage stratified sample of dwellings in HU from 2003)
• Changing sample size (i.e. significant increase of sample size in DK in 2007)
• Changing age range (i.e. restriction to age 15 and over in LT before 2002)
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• Changing concepts (i.e. revised employment and unemployment definition in some countries and years)
• Changing questionnaires (i.e. wording and order of questions)
• Changing population figures used for the population adjustment (on the basis of new population censuses)
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• Do not take comparability for granted
• Make use of the available documentation, e.g. quality reports, main characteristics report, national questionnaires
• But don‘t forget the strengths of these data!
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Contact
German Microdata Lab
GESIS Leibniz-Institute for the Social Sciences www.gesis.org/gml gml@gesis.org
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