Strengths of OS microdata

Introduction to LFSfrom a research perspective

Christof Wolf, Andrea Lengerer, Heike WirthGerman Microdata Lab, GESIS

Strengths of OS microdata• Samples are usually very large

Allowing for analysis of small groupsAllowing 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)

18 Sept. 2014 4th DwB Trainings Course 2

Research done with LFS• As a reference statistic• Substantive research, e.g.

The Effects of Labour Market RegulationsBeing 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.


Research done with LFSe.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


Example 1: Hermes & Leicht 2010*• 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.

Defining Immigrant Groups• 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


Self-employment Rates


Belgium Germany Portugal Spain Polen0

5

10

15

20

25

30

35

40

45

NativeEU ForeignersNon-EU Foreigners

Poland

Self-Employment Rates in Europe by country of birth


Example 2: Methodological Possibilities• LFS is a cross-national repeated cross-section for European

Analysis of social change, Age-Period-Cohort analysisMulti-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


Time series used by Dieckhoff & Steiber


Martina Dieckhoff and Nadia Steiber, 2012: Institutional reforms and age-graded labour market inequalities in Europe. International Journal of Comparative Sociology Online prepublication.

Predicted probabilities for fixed-term employment


Comparability of LFS data

I. Comparability of designII. Comparability of variablesIII. Comparability over time


I. Comparability of Design

Sampling & Weighting1

• 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


Field Work1

• LFS is conducted in different survey modes; often in mixed-mode; mostly CAPI/PAPI but also self-administered and telephone interviews

• Workload of interviewers varies from 50 (PL) to 1,125 (NL) to interviews per quarter


1 Data from 2009

Proxy Interviews1

• 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)


1 Data from 2009

Response Rates and Coverage• 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)


II. Comparability of Variables

Ex-ante Output Harmonization• The regulation defines the mandatory variables for

EU-LFS



Ex-ante Output Harmonization• 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


Example 1: Marital Status

Italy

Hungary

Cro

atia


Example 1: Marital Status

IT HU HR

Single Single Single

Married Married Married

Separated de facto Widowed Widowed

Lagally separated Divorced or legally separated Divorced

Divorced Cohabitating couple

Widowed Separated from spouse

User Data Base

0 Widowed, divorced or legally separated

1 Single

2 Married


Example 2: Supervisory Status2

• Part of ‘quality-in-work’ indicators used to monitoring gender equality in the labour market

• Supervisory status also used in measures of socio-structural / class position, e.g.Ericson/Goldthorpe/Portocarero schema (EGP)Wright’s class schemaEuropean Socioeconomic Classification (ESeC)

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.


• ESeC classes

1. Large employers, higher managerial and professional occupations2. Lower managerial and professional occupations3. Intermediate occupations4. Small employers and own account workers5. Employers and self-employed in agriculture6. Lower supervisory and lower technician occupations7. Lower services occupations8. Lower technical occupations9. Routine occupations

• Supervisors are assumed to be different in their employment relations to ‘rank and file’ workers


• ESeC classes

1. Large employers, higher managerial and professional occupations2. Lower managerial and professional occupations3. Intermediate occupations4. Small employers and own account workers5. Employers and self-employed in agriculture6. Lower supervisory and lower technician occupations7. Lower services occupations8. Lower technical occupations9. 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


Supervisory Status: Concept • 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”



Operationalisation of the ‚supervisory status‘: LFS – Examples

Country German questionnaires – LFS questions English translation

Austria Haben Sie in Ihrer Tätigkeit Leitungsfunktion? (Das kann auch in weniger qualifizierten Berufen der Fall sein)

Do you have leading [managerial] function in your job? (This could also be the case in less qualified jobs)

Germany Sind Sie in Ihrer (Haupt-) Erwerbstätigkeit in einer leitenden Position tätig?

In your (main) job, are you in a leading [managerial] position?

Switzerland Wieviele Personen sind Ihnen direkt oder indirekt ingesamt unterstellt?

How many persons are altogether directly or indirectly responsible to you?

Belgium Trägt F/H Verantwortung, d.h. hat F/H die Aufsicht bzw. die Koordination über die Arbeit anderer Arbeitnehmer?

Does she/he have responsibility, that is does she/he supervise or coordinate the work of other employees?


Country English questionnaires – EU-LFS questions

Belgium Do you have a responsible job, in other words, do you supervise other personnel

Ireland 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

UK In your job, do you have formal responsibility for supervising the work of other employees?

Sweden Do your tasks include managing and supervising the work of other employees?

Operationalisation of the ‚supervisory status‘: LFS – Examples


LV RO GR SK DK HU BG CZ ES PL LT FR CY EE PT SI FI DE BE IT NL AT IE SE MTCH NO LU UK IS0

5

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35

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45

2

10 11 12 12 13 1316 16 17 17 17 18 18 20 20 21 21 22 22 23

26 2628 29

3133 35 36

42

Supervisory Status: LFS 2010 in %How comparable are these figures?

III. Comparability over Time

Availability of microdata• 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


Reasons for limited comparability over time

1. Changing reference period, annual vs. continuous survey

2. Changing classifications

3. Changing codification

4. Changing sample design


(1) Changing reference period• 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


Availability of microdata since…


country yearly quarterly country yearly quarterly

ATBEBGCHCY CZDEDKEEESFIFRGRHUIE

AustriaBelgiumBulgariaSwitzerlandCyprusCzech RepublicGermanyDenmarkEstoniaSpainFinlandFranceGreeceHungaryIreland

199519832000199619991997200219831997198619951983198319961983

199919992000201020041998200519992000199619982003199819991999

ISITLTLULVMTNLNOPLPTROSESISKUK

IcelandItalyLithuaniaLuxembourgLatviaMaltaNetherlandsNorwayPolandPortugalRomaniaSwedenSloveniaSlovak RepublicUnited Kingdom

199519831998198319982009198319951997198619971995199619981983

200319972002200320022009200020002000199719992001199919982000

(2) Changing classifications


Region NUTS NUTS II (except for AT, DE and UK),several changes

Economic activity

NACE NACE Rev. 2 from 2008NACE Rev. 1.1 from 2005 to 2008NACE Rev. 1 from 1992 to 2004NACE 1970 from 1983 to 1991

Occupation ISCO ISCO 08 from 2011ISCO 88 COM until 2010

Education ISCED ISCED 1997

(3) Changing code schemesTwo examples:

• Nationality

• Education


Nationality


NATIONAL, until 2003 NATIONAL, from 2004 onwards

0111911800

-1

National / Native of own CountryEU15Non EU15Non-National / Non-Native (in case the distinction EU/Non-EUis not possible)No answer, suppressed, other country or stateless

0123456789

101112131415161718192021-1

National / Native of own CountryEU15NMS10 (10 new Member States of 2004)NMS2 (2 new Member States of 2007)NMS12 (code 2,3)EU27 (code 1,2,3)EFTAOther EuropeEurope outside EU27 (code 6,7)North AfricaOther AfricaNear and Middle EastEast AsiaSouth and South East AsiaNorth Africa and Near and Middle East (code 9,11)East and South Asia (code 12,13)North AmericaCentral America (and Caribbean)South AmericaAustralia and OceaniaLatin America (code 17,18)North America and Australia / Oceania (code 16,19)No answer, suppressed, other country or stateless

Education


HATLEV1D, from 1983 onwards HATLEVEL, from 1998 onwards

123

-1-2

Low: Lower secondaryMedium: Upper secondaryHigh: Third levelNo answerNot applicable (child less than 15 years)

01011212230

313233343536414243515260-1-2

No formal education or below ISCED 1ISCED 0-1ISCED 1ISCED 2ISCED 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,bISCED 3c (3 years or longer) or ISCED 4cISCED 3b or ISCED 4bISCED 3a or ISCED 4aISCED 3 or 4 (without distinction a, b or c possible)ISCED 4a,bISCED 4cISCED 4 (without distinction a, b or c possible)ISCED 5bISCED 5aISCED 6No answerNot applicable (child less than 15 years)

(4) Changing sample design• 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. multi-stage 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)


Other reasons for limited comparability • Changing concepts (i.e. revised employment and un-

employment 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)


Conclusion• 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 thestrengths of these data!


Thank you for your attention!

ContactGerman Microdata LabGESIS Leibniz-Institute for the Social Sciences

www.gesis.org/[email protected]


http://www.gesis.org/gml

mailto:[email protected]

Documents

Strengths of OS microdata