Herman Deleeck Centre for Social Policy

MetaSILC 2015

MetaSILC 2015

Introduction

MetaSILC 2015 documents and analyse how individual income components are aggregated into the EU-SILC target variables. Even though general and country-specific descriptions of income target variables are available in the EU-SILC methodological guidelines and in the national quality reports, it is often not clear how exactly each of the national income components is classified and aggregated into a target variable in practice. Therefore, on the basis of a survey among national statistical institutes, we compiled a database which maps detailed information on the collection, processing and aggregation of EU-SILC income components. MetaSILC 2015 was supported by the Third Network for the Analysis of EU-SILC (Net-SILC3), funded by Eurostat.

The survey

Survey among national statistical institutes (NSIs)/ EU-SILC data producers.

  • Online questionnaire (using Qualtrics)
  • Two rounds between July 2016 to January 2017

Focus on 35 variables related to income from EU-SILC 2015 cross-sectional data.

  • Total income before and after transfers; income from benefits, work and capital; social contributions and taxes
  • More detailed target variables related to benefits that make a distinction between contributory and means-tested, contributory and non-means-tested, non-contributory and means-tested, non-contributory and nonmeans-tested

The response rate for completed surveys was 76% (26 of 34 countries).

  • Austria, Belgium, Bulgaria, Republic of Cyprus, Czech Republic, Germany, Denmark, Estonia, Greece, Spain, Finland, France, Croatia, Hungary, Italy, Luxembourg, Latvia, Malta, the Netherlands, Poland, Portugal, Serbia, Sweden, Slovenia, Slovakia and the United Kingdom.

Content of the survey

For each of the income components used to compute the target variables, we collected:

  • official name (national language) and the equivalent name in English
  • code and name of the target variable
  • source of data (register data, survey, imputation)
  • information on gross-net conversion.

Changes in the definition and computation of income target variables across time were also investigated. NSIs were asked to report whether there were any important changes between wave 2010 and wave 2015 and if there are important changes planned for future waves.

Some additional information was requested about the computation of income from self-employment, imputed rent and production for own consumption, as well as outlier detection and data error correction.

In addition to the information provided in the survey, we asked follow-up questions for clarification and asked NSIs to review a draft version of the report. All additional information received was included in this report and in the dataset when appropriate.

The data

  • The data file is available as easily searchable database in excel and is structured as follows:
  • Income components for variables on total income before and after transfers (data 1)
  • Income components for variables on income from benefits, work, taxes and social contributions (data 2)
  • Past and future changes and additional information on the computation of target variable (data 3)
  • Additional information on imputed rent (HY030), company car (PY021) and cash benefits or losses from self-employment (PY050) (data 4)
  • Procedures used for outlier detection and data treatment (data 5).

The report

For each income component reported, we look at compliance with Eurostat guidelines, misclassifications and omitted income sources, all potentially undermining cross-national comparability.

  • Focus on 20 variables used to compute HY020, detailed information by country.
  • Complementing information from national and comparative quality reports, national questionnaires and other sources (e.g. ESSPROS, MISSOC and EUROMOD country reports).

The report is accompanied by a paper which brings together the main findings regarding challenges for crosscountry comparability and recommendations for improving further the quality and comparability of the EUSILC income variables (see Publications).

Data access

The MetaSILC 2015 dataset has been made freely available in excel to data users and other interested parties.

Goedemé, T. & Zardo Trindade, L. (2020). MetaSILC 2015: A database on the contents and comparability of the EU-SILC income variables [Data file], Antwerp: Herman Deleeck Centre for Social Policy, University of Antwerp & Oxford: Institute for New Economic Thinking, University of Oxford. DOI:10.7910/DVN/TLSZ4S.

Documentation and publications

Goedemé, T. & Zardo Trindade, L. (2020). MetaSILC 2015: A database on the contents and comparability of the EU-SILC income variables [Data file], Antwerp: Herman Deleeck Centre for Social Policy, University of Antwerp & Oxford: Institute for New Economic Thinking, University of Oxford. DOI:10.7910/DVN/TLSZ4S

Goedemé, T. & Zardo Trindade, L. (eds.) (2020). MetaSILC 2015: A report on the contents and comparability of the EU-SILC income variables, INET Working Paper 2020-1 & CSB Working Paper WP 20/01. Oxford: Institute for New Economic Thinking, University of Oxford & Antwerp: Herman Deleeck Centre for Social Policy, University of Antwerp.

Zardo Trindade, L. & Goedemé, T. (2020). The comparability of the EU-SILC income variables: review and recommendations, Statistical Working Paper Series, 2020 Edition, Eurostat, Luxembourg: Publication Office of the European Union. DOI:10.2785/047001

Zardo Trindade, L. & Goedemé, T. (2020). The comparability of the EU-SILC income variables: review and recommendations - 2020 edition. Eurostat statistical working papers, pp. 1-54. DOI:10.2785/047001

Zardo Trindade, L. & Goedemé, T. (2020). A new database on the contents and comparability of the income variables in EU- SILC: MetaSILC 2015. International Journal of Microsimulation 2019; 12(3); 62–67 DOI:10.34196/ijm.00207