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EU-SILC from a Research Perspective Heike Wirth & Christof Wolf.

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Presentation on theme: "EU-SILC from a Research Perspective Heike Wirth & Christof Wolf."— Presentation transcript:

1 EU-SILC from a Research Perspective Heike Wirth & Christof Wolf

2 Strengths of EU-SILC Flexible implementation of EU-SILC Selected issues regarding data comparability Opportunities for longitudinal analysis with EU-SILC Topics covered 2

3 Coverage of countries Coverage of topics (Private) Household survey Cross-sectional and longitudinal data Good and improving data documentation Access for research purposes free of charge (but more demanding under new regulation) Strengths of EU-SILC 3

4 Flexibility 4

5 EU-SILC is based on a common framework guidelines: concepts, definitions, classifications, procedures Target variables, i.e. ex ante harmonization Within this framework high flexibility regarding data generation Accommodates the national conditions and needs (+) Potential to limit cross-national comparability (–) While the input side might be diverse, the output side is harmonized (standardized microdata set) i.e. problems of data comparability are not directly visible Flexible implementation of EU-SILC 5

6 Some potential sources of non-comparability (1) Different sampling strategies (2) Different survey designs (3) Different modes of data collection (4) Different field work periods and procedures (5) Different national questionnaires (6) Different reference periods (7) Different nonresponse rates (8) Different attrition rates … Flexible implementation of EU-SILC 6

7 Comparability 7

8 EU-SILC is the central data source for social reporting in Europe Social indicators based on EU-SILC are used to assess countries places in relation to each other to learn from others best practices to evaluate policy measures Why is comparability so important? 8

9 1. Different survey designs and response rates 2. Different modes of data collection 3. Ex-ante output harmonization: Wording of questions Selected issues regarding data comparability 9

10 Survey design Rotational panel: variations across countries in the number of rotations. Most countries 4, but 8 in NO, 9 in FR and full panel in LU (in the future possibly 6 or more waves) Response rates and attrition vary throughout Europe Comparability 1: Survey design and response rates 10

11 SILC response rates 2007 (only new rotational group) 11 Source: Eurostat: Proposal for revising the design of EU-SILC longitudinal component. Item 4; 5 th Meeting of the Task-Force on the revision of the EU-SILC legal basis.

12 EU-SILC retention rates (a) households, (b) individuals re-interviewed the following year, in % 12 Source: Iacovou et al (2012) from EU-SILC longitudinal files, release 2008-4, unweighted

13 Sources of EU-SILC data could be: survey(s) register(s) combination of survey(s) & register(s) Data could come from one source or two sources Issue of concern: Substantial findings of EU-SILC such as indicators used in social reporting may differ due to the diversity in the data collection across countries Comparability 2: Different modes of data collection 13

14 Different modes of data collection (2010) 14 Information/ Interview completed from Survey 73.1% Survey countries BE, BG, CY, CZ, DE, GR, ES, EE, FR, HU, IT,LT, LU, MT; AT, PL, PT, RO, SK, UK Register 3.4% Both: Survey & Register 22.8% Register countries DK, FI, SE, NL, IS, LV, SI, IE Full Record Imputation 0.7%

15 Use of registers for different domains 15

16 Measures in surveys and registers may be based on different concepts, e.g. Earnings information in registers tax-based (non taxed earnings?) different points in time when income and tax are collected (self-employed, temporary workers) Employment, Unemployment evidence that information on unemployment in survey and registers differ in a significant way at the individual level survey: e.g. memory errors regarding employment situation in the past Consistency problems if combining information from different sources? Different modes of data collection 16

17 Mixed modes of data collection in surveys Personal interview (respondent) CATI (Computer Assisted Telefon Interview) CAPI (Computer Assisted Personal Interview) PAPI (Paper and Pencil Personal Interview) self-administered (respondent completes the questionnaire him/herself) Proxy-interview (respondent has someone else answer the questions for him/her) Type of interview might affect the response and thus reduce the comparability between countries and for countries with sequential mixed mode between waves Different modes of data collection 17

18 Different modes of data collection (2010) 18 SURVEY COUNTRIES Interview 73.1% Face to Face CAPI 29.1% PAPI 42.3% CATI 3.9% Self- administered 5.5% Proxy Interview 18.3% REGISTER COUNTRIES Register & Interviews 22.8% Face to Face CAPI 0.4% PAPI 11.7% CATI 65.6% Self- administered 0.4% Proxy Interview 22.0%

19 Proxy interview by country – register countries 19 % of proxy interviews Countryproxy interview Iceland0.0 Nederland1.2 Sverige2.1 Ireland23.7 Latvia23.7 Norway23.8 Slovenia24.6 Suomi42.7 Danmark48.6 Datasource: UDB_c10R_ver 2010-2 from 01-08-12, own computation As a rule only 1 person in hh is interviewed, who answers also for all other hh members

20 Proxy interviews by country – survey countries 20 % of proxy interviews Slovak Republic 4.3Czech Republic19.3 Ellada 8.0Hungary19.8 Belgique 8.6Luxembourg20.1 United Kingdom10.7Bulgaria20.3 Oesterreich13.7Portugal20.5 Romania15.3Espana21.9 Lithuania15.6Cyprus23.0 Deutschland18.8Estonia24.3 Italia19.0France27.6 Poland19.2Malta28.9 Datasource: UDB_c10R_ver 2010-2 from 01-08-12, own computation

21 Quality of proxy interviews might depend on the reason of the proxy interview 1.a respondent is not accessible or willing to give an interview proxy interview are cofounded with other characteristics like age or sex 2.producers take proxy interviews as a mean to lower costs data producers might make efforts for a random selection of proxy respondents Flexibility in modes of data collection 21

22 SILC is ex ante harmonized, i.e. variables which are delivered by the NSIs to Eurostat are defined in regulations & guidelines (=> standard EU-SILC definition) But there is no common SILC questionnaire questionnaire design varies (e.g. order of questions) wording of questions varies (e.g. How often do you usually.. or 'How often during a usual year do you …?) Comparability 3 – Different questionnaires 22

23 Research example Gash (2011): Methodological issues in comparative research. European Workshop to Introduce the EU-SILC and EU-LFS Manchester Research interest How does unemployment affect social engagement? EU-SILC Module (2006) on Social Participation Frequency of contacts/getting together with friends &relatives Ability to ask relatives, friends, neighbours for help Participation in formal and informal activities Participation in cultural/sport events 23 Research example

24 Main findings: Broad agreement in the questionnaire wording across countries, but 1. Some countries provide examples of social participation others not 2. Some countries mention reference periods others not 3. Some countries prompt that respondents should exclude people they live with others not Might have an effect on the reported frequencies of contacts Research example 24

25 25 Source: Gash, Vanessa (2011): METHODOLOGICAL ISSUES in COMPARATIVE RESEARCH

26 When Eurostat knows about problems arising from different wording or other deviations in the questoinnaire it reports this Most national questionnaires are available Check documentation!!! Comparability 3 - Output harmonization 26

27 Opportunities for Longitudinal Analysis with EU-SILC 27

28 Main topics studied with SILC (Eiffe & Till 2013) Income studies Poverty studies Labour market studies Limitations arise because SILC is a short-term panel, i.e. a maximum of 3 transitions Opportunities for Longitudinal Analysis 28

29 Income distribution What are the consequences of income gains and losses on income inequality and poverty levels? How do regional economic and labour market structures as well as national institutions contribute to changes of income level and income distribution? Income dynamics How much does income mobility vary across European countries? Income studies 29 See: Franz F. Eiffe and Matthias Till. 2013. The Longitudinal Component of EU SILC Still Underused? NetSILC2: Working Paper 1/2013.

30 Impact of socio-economic events on income Impact of having a disabled person in a household Changes in womens contribution in Italian families Effect of partnership breakdown on individual income Income studies 30 See: Franz F. Eiffe and Matthias Till. 2013. The Longitudinal Component of EU SILC Still Underused? NetSILC2: Working Paper 1/2013.

31 How long do individuals or households remain in poor living conditions? How often do Europeans experience poverty over their life span (or at least over four years)? What are the profiles of households who remain in poverty for longer periods? What are the events/determinants that trigger poverty transitions? Poverty studies 31 See: Franz F. Eiffe and Matthias Till. 2013. The Longitudinal Component of EU SILC Still Underused? NetSILC2: Working Paper 1/2013.

32 What patterns of occupational mobility can be observed in Europe? How difficult is it to leave unemployment? How do labour market dynamics differ across countries? Can difference between countries be explained by different institutions, e.g. welfare state arrangements? Labour market studies 32 See: Franz F. Eiffe and Matthias Till. 2013. The Longitudinal Component of EU SILC Still Underused? NetSILC2: Working Paper 1/2013.

33 Different attrition rates could be a problem If there is a correlation between attrition and income or others variables this would be a problem However, income bias related to attrition seems to be low Possible problems of SILC longitudinal 33

34 Household participation in SILC by Income Quintiles in previous year 34 Source: Eurostat: Proposal for revising the design of EU-SILC longitudinal component. Item 4; 5 th Meeting of the Task-Force on the revision of the EU-SILC legal basis.

35 Thanks for listeing! 35


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