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Metadata for Official Statistics

Data Handling & Analysis: EU-SILC

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Adding information on at-risk-of-poverty thresholds to longitudinal EU-SILC data

Author Barbara Binder, Alexander Mack (GESIS)
Description This Stata .do file generates poverty threshholds for the longitudinal EU-SILC microdata.
Download [.zip]

This tool was produced as part of the Data without Boundaries project.

Data Handling in EU-SILC

Author Alexander Mack
Description Technical report on data handling in EU-SILC. The SPSS and Stata files can be downloaded below.
Download Technical Report [.pdf]
Syntaxfile (SPSS) [.sps]
Syntaxfile (Stata) [.do]

ESeC - European Socioeconomic Classification in EU-SILC - Paper & Syntax: SPSS, stata, R

Author Heike Wirth
Description

ESeC - European Socioeconomic Classification in EU-SILC - GESIS Paper & Syntax: SPSS, stata, R

European inequality research often follows the tradition of using occupational based categorical classification to identify the socioeconomic position of individuals or households (e.g., classes, strata, milieus, occupational groups). In the past, European studies have often used the Erikson-Goldthorpe-Portocarero class (EGP) scheme (cf. Erikson & Goldthorpe 1992). However, the EGP scheme has only been validated for Great Britain (cf. Evans 1992). Variants for other countries are largely based on informed plausibility, following the British model, though operationalisation may vary by country. As an alternative to the EGP, two other currently available categorical concepts are the ESeC (European Socioeconomic Classification) and the ESeG (European Socioeconomic Groups), both based on the International Standard Classification of Occupation (ISCO). Both concepts are intended to improve cross-country comparative analysis of social inequality in Europe. However, the ESeC and ESeG differ in their theoretical basis and should not be confused with each other, and the ESeC and ESeG also cannot readily be transferred into each other. The ESeC is available for ISCO-88 (ESeC88) and ISCO-08 (ESeC08). The ESeG is available for ISCO-08. In this paper, we focus on the operationalisation of ESeC with EU-SILC cross-sectional data (2004-2020). Alongside this report, we have published syntax files (SPSS, Stata, and R) which can be used for the operationalisation of ESeC and ESeG.

Download

Paper:
Wirth, Heike (2023): EU-SILC Tools: European Socioeconomic Classification - ESeC88 and ESeC08. GESIS Papers 2023/01 [.pdf]

Syntax:
esec_silc_2004_2020_R [.zip]
esec_silc_2004_2020_stata [.zip]
esec_silc_2004_2020_spss [.zip]

More information

For details on ESeC please visit the homepage of Eric Harrison: https://www.ericharrison.co.uk/european-socio-economic-classification-esec.html

For ESeC in EU-SILC see also Tim Goedemé: https://timgoedeme.com/tools/esec-in-eu-silc/

ESeG - European Socioeconomic Groups in EU-SILC (cross/long) - Syntax: SPSS, stata, R

Author Heike Wirth
Description

This syntax (SPSS; Stata; R) generates European Socio-Economic Groups (ESeG) based on ISCO08 for EU-SILC - cross-sectional and longitudinal data**) - using the P-File (personal data) & R-FILE (personal register data):

ESEG_1 (less detailed)

ESEG_2 (detailed)

**) Starting with EU-SILC longitudinal 2019 only ISCO-08 one-digit is available, therefore no ESeG is operationalized (yet).

Download eseg08_silc_2010_2020_cross_stata[.zip]
eseg08_silc_2010_2020_cross_spss[.zip]
eseg08_silc_2010_2020_cross_R.[.zip]
eseg08_silc_2010_2018_long_stata[.zip]
eseg08_silc_2010_2018_long_spss[.zip]
eseg08_silc_2010_2018_long_R[.zip]
Contact heike.wirth@gesis.org
More information

For details on ESeG please see:

Meron, Monique et al. (2014): Final Report of the ESSnet on the harmonisation and implementation of a European socio-economic classification: European Socio-economic Groups (ESeG)

Links:
[0] https://ec.europa.eu/eurostat/cros/content/eseg-report-technicaldocuments_en
[1] https://ec.europa.eu/eurostat/cros/system/files/ESEG-Report-TechnicalAnnexes_0.zip_en
[2] https://ec.europa.eu/eurostat/cros/content/eseg_en

eusilcpanel_2020

Author Marwin Borst & Heike Wirth (GESIS)
Description eusilcpanel_2020: First computational steps towards a cumulative sample based on the EU-SILC longitudinal datasets - Update
Download ado [.ado]
population figures [.dta]
helpfile [.sthlp]
Technical report [.pdf]
Contact heike.wirth@gesis.org

Harmonization of Income data in EU-SILC - UPDATE

Author Alexander Mack, Barbara Binder, Valentina Ponomarenko (GESIS)
Description This technical report describes harmonization procedures for income data in EU-SILC and provides code and auxiliary macro data for SPSS and Stata.
Download Technical report [.pdf]

Datafile (SPSS) [.sav]
Datafile (SPSS without UK) [.sav]
Datafile (Stata) [.dta]
Datafile (Stata without UK) [.dta]

Syntaxfile (SPSS) [.sps]
Syntaxfile (Stata) [.do]

How to generate infl_weight (SPSS) [.sps] [.sav]
How to generate infl_weight (SPSS without UK) [.sps] [.sav]
How to generate infl_weight (Stata) [.do] [.dta]
How to generate infl_weight (Stata without UK) [.do] [.dta]

How to generate ppps (SPSS) [.sps] [.sav]
How to generate ppps (SPSS without UK) [.sps] [.sav]
How to generate ppps (Stata) [.do] [.dta]
How to generate ppps (Stata without UK) [.do] [.dta]

This tool was produced as part of the Data without Boundaries project.

MetaSILC 2015

Author Tim Goedemé
Description MetaSILC 2015 is both a report and a database that contains detailed information on the income variables in EU-SILC, the main source for statistics on income and living conditions in Europe, with a focus on the 2015 wave.
Link https://timgoedeme.com/tools/metasilc-2015/

Standard error estimates

Author Anika Herter & Heike Wirth
Description SPSS-files that prepare the sample design variables for the EU-SILC cross-sectional data (2010-2014).
Download [.zip]
Papers
  • Herter, A. and Wirth, H. (2018): 'EU-SILC Tools: Calculating Standard Errors for EU-SILC using SPSS.' [GESIS Papers 2018|16]



Author Johannes Gussenbauer
Description The R-Package surveysd: Estimating standard errors for Complex Surveys with a Rotating Panel Design.
Download [link]
Papers
  • Gussenbauer, J. (2020): 'Estimating standard errors for Complex Surveys with a Rotating Panel Design' [.pdf].



Author Tim Goedemé
Description Stata do-files that prepare the sample design variables for the EU-SILC cross-sectional data (2005-2011).
Download [link]
Papers
  • Goedemé, T. (2013): How much Confidence can we have in EU-SILC? Complex Sample Designs and the Standard Error of the Europe 2020 Poverty Indicators, in Social Indicators Research, 110(1): 89-110 [link].
  • Goedemé, T. (2013): The EU-SILC sample design variables: critical review and recommendations, CSB Working Paper Series, WP 13/02, Antwerp, Herman Deleeck Centre for Social Policy, University of Antwerp [.pdf].
  • Goedemé, T. (2010): The standard error of estimates based on EU-SILC. An exploration through the Europe 2020 poverty indicators, CSB Working Paper Series, WP 10/09, Antwerp, Herman Deleeck Centre for Social Policy, University of Antwerp [.pdf].
  • Verma, V., Betti, G. and Gagliardi, F. (2010): An assessment of survey errors in EU-SILC, Eurostat methodologies and working papers, Eurostat, Luxembourg [ .pdf].