Work package 5: ESeC and Education
In modern societies, life-chances and socio-economic positions of individuals depend to a large extent on the educational performance of these individuals. Advantageous socio-economic positions usually require certain educational degrees, whereas individuals with little education often have to accept lower positions in a society. Thus, educational systems in modern societies work – to various degrees – as ‘allocation machineries’ to different socio-economic positions. Given the close, but cross-nationally varying link between education and socio-economic positions, the European Socio-Economic Classification (ESeC) has to hold in three respects in terms of construct validation:
- Although the two constructs are related, the ESeC as a measure of socio-economic positions must measure something different from educational performance;
- Associations between ESeC and measures of educational performance have to be strong in all countries;
- These associations, however, are expected to vary among different national educational arrangements.
In order to test these basic hypotheses, we will analyse the association between ESeC and different measures of respondents’ education for different countries. We will use three different measures of education because education is in itself difficult to measure in ways that allow valid comparisons between countries. The measures of education will include the best national educational classifications and nomenclatures available for each country and two cross-nationally comparative measure of education (ISCED and the CASMIN educational classification). The use of a national educational classification is essential in order not to be constrained to the sometimes problematic recoding of national educational information into international educational codes.
For the first hypothesis we will compare the inter-relationship between the educational classifications and their association with ESeC. To prove discriminant validity, the associations among the educational classifications have to be stronger than the associations with ESeC. Concerning the second and the third hypothesis, we expect strong associations between ESeC and measures of education, but the associations should vary between countries in similar ways as found in studies that have used the EGP class schema and the CASMIN educational classification. For example, many studies have shown that in Germany, the association between education and socio-economic position is relatively strong, whereas in the UK, this association is relatively low and Sweden has an intermediate position. If ESeC is a valid measure of socio-economic positions, the associations between ESeC and well-established cross-national measures of education should reflect these patterns.
Data and analysis
The analyses will be performed with Labour Force Survey data for at least four of the following countries: Germany, UK, France, Sweden, Italy, Poland, and Hungary. The final list of countries will depend on the quality of national (individual level) microdata available with implemented measures for ESeC and detailed information (in original national educational classifications and nomenclatures) on educational attainment in the countries. For the empirical analyses, we are going to use a series of different statistical procedures including standard measures of associations as well as advanced log-linear modelling in order to detect differences between constructs and differences in the strengths of the association across countries.
- Step 4: UESSEX-ISER: Work package 6: Construct validation using the European Social Survey
- Step 4: INSEE: Work package 7: Criterion validation of ESeC using the ECT
- Step 4: EUR: Work package 8: Construct validation of the ESeC in relation to health inequalities
- Step 4: SOFI: Work package 9: ESeC and EGP compared
- Step 4: UNIMIB: Work Package 10: Unemployment and Earnings Inequalities
- Step 4: ESRI: Work Package 11: Poverty and the Deprivation