The European Socio-Economic Classification (ESeC) is quite popular in social science research, especially as an indicator of social class. The EU Statistics on Income and Living Conditions (EU-SILC) provides the opportunity to study the relation between ESeC and a long list of socio-economic variables (including income, employment, material deprivation, …) in a comparative and longitudinal perspective. However, to the best of my knowledge, very few people work with ESeC in EU-SILC.
In this research note, I document the data quality of EU-SILC (2004-2017) in terms of measuring ESeC, and propose a slightly modified version of computing ESeC compared to the routines one can find on the GESIS webiste.
- Read the research note
- Download an excel file with background tables, accompanying the note
- Download the STATA do-file (applicable to EU-SILC 2004-2017)
Please cite the research note and STATA do-file as:
Goedemé, 2019, A note on the replication of the European Socio-economic Classification (ESeC) in the EU Statistics on Income and Living Conditions (EU-SILC). INET Oxford Working Paper No. 2019-17, Oxford: Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
The STATA do-file is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. It can be changed and re-shared for non-commercial use, as long as our original work is recognised and the revised work is made available under the same conditions.
This paper is part of a project on social class and earnings inequality, in collaboration with Marii Paskov, David Weisstanner and Brian Nolan at the University of Oxford. I am very grateful to them for comments and discussions, and to Joan Madia who did similar research on a previous project.
Further research on social class with EU-SILC:
- Goedemé, T., Paskov, M., Weisstanner, D. and Nolan, B., (2020) Social class and earnings: a cross-national study, INET Oxford Working Paper No . 2020-03, Oxford: Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.