Patterns of earnings differentials across three conservative European welfare regimes with alternative education systems

Abstract

The aim of this paper is to investigate, from a generational perspective, the effect of human capital on individual earnings and earnings differences in Germany, France and Italy, three developed countries in Western Europe with similar conservative welfare regimes but with important differences in their education systems. Income inequalities between and within education levels are explored using a two-stage probit model with quantile regressions in the second stage. More precisely, drawing upon 2005 EU-SILC data, returns on schooling and experience are estimated separately for employees and self-employed full-time workers by means of Mincerian earnings equations with sample selection; the sample selection correction accounts for the potential individual self-selection into the two labour force types. Although some determinants appear to be relatively similar across countries, state-specific differentials are drawn in light of the institutional features of each national context. The study reveals how each dimension of human capital differently affects individuals’ earnings and earnings inequality and, most of all, how their impacts differ along the conditional earnings distribution and across countries. In the comparative perspective, the country's leading position in terms of the highest rewards on education also depends on which earnings distribution (employee vs. self-employed) is analysed.

Keywords:

• education systems
• human capital
• earnings differentials
• quantile regression

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Successful students from Gymnasiums, academically oriented high schools that offer a general education curriculum, earn the Abitur, a certificate that entitles them to attend university with an unrestricted choice of majors. Successful students from Realschules, more vocationally oriented schools that also offer general education, may qualify to attend an advanced vocational school (Fachoberschule), whereas students from Hauptschules, which more specifically prepare students for the world of work, have few options, although they can attend full-time vocational schools (Berufsfachschule).

2. During the 1960s, Italy's education system was reformed in two important respects. First, in 1963, the unified middle school was established and compulsory schooling was extended to the age of 14. Second, in 1961 and 1969, access to universities was progressively liberalised, enabling students in all upper-secondary tracks, including the vocational colleges attended primarily by the working classes, to sit for the matriculation examinations and continue on to university. The reforms were expected to reduce class inequality in university attendance by increasing the opportunities for working-class students to participate in higher education.

3. An employee is anyone who works for a public or private employer and receives compensation in the form of a wage, salary, fee, gratuity, payment in kind or based on results. The self-employed are those who work at their own businesses, professional practices or farms for the purpose of earning a profit; the self-employed includes both employers, if the self-employed person employs at least one other person, and people who strictly work for themselves. The analysis excludes young workers aged 16–24, whose incidence is rather negligible, because they could be still in the ‘almost exclusively’ educational periods of their lives and then retrospective parental information is not available. Based on international guidelines, the analysis also excludes workers in the primary sector, which traditionally consists of a high proportion of self-employed and unpaid family workers usually considered their assistants.

4. In the EU-SILC framework, formal education is measured along a simplified version of the International Standard Classification of Education (ISCED-97), which has six main categories of education attainment: pre-primary and primary education, lower and upper secondary education, post-secondary non-tertiary education, and first- and second-stage tertiary education. Individual education attainment refers to the highest level of formal education a person has successfully completed (e.g. a diploma was acquired or full attendance was demonstrated in the case of no certification).

5. This variable was approximated as the difference between the year when the highest level of education was attained and the year of birth minus six, which is the age at which individuals begin compulsory education in most countries. In order to evaluate the degree of approximation of this proxy, a similar variable was constructed by associating a number of years necessary to attain each level of formal education. Because the mean difference between these two variables was very close to zero, the approximation can be considered a good proxy of years of formal education.

6. This is a coexistence ratio between two groups of individuals with tertiary education: the former is composed of first-generation individuals (from families in which neither attain formal tertiary education) who attained higher education; the latter is composed of second-generation individuals (from families in which at least one parent attained tertiary educa­tion) who also attained higher education.

7. The Nomenclature of Territorial Units for Statistics (NUTS) is a hierarchical, exhaustive and non-overlapping territorial system of classification established by Eurostat to harmonise European regional statistics and frame community and regional policies and socio-economic analyses. The NUTS classification subdivides countries into NUTS1 regions, each of which is then subdivided into regions at the NUTS2 level and, in turn, into regions at the NUTS3 level. More details about NUTS classification can be found at the website: http://ec.europa.eu/eurostat/ramon/nuts/home_regions_en.html.

8. Gender is a dummy variable with value 1 if the worker is male and 0 otherwise; citizenship is 1 for workers with citizenship in the same country of residence and 0 otherwise. Marital status is a dummy with value 1 if married or in other condition linked to marriage (e.g. separated, widowed or divorced) and 0 if never married; children is 1 if the worker has dependent children and 0 otherwise; health status is 1 for workers who suffer from any chronic (long-standing) illness or condition and 0 otherwise. Regarding the two ‘generational’ variables, parents’ education level is expressed in terms of the highest ISCED-97 level attained, using the three categories of low (ISCED-97: 0;1;2), medium (3;4) and high (5), and parental work status is a derived variable that detects if neither or only one or both the parents are/were self-employed. Home ownership is 1 if the worker owns the house in which he lives and 0 otherwise.

9. Both for employees and, more markedly, for the self-employed, the earnings equations for the means show moderately good R² values adjusted (for employees: .4584, .0.4925 and .5123 for Germany, France and Italy, respectively; for the self-employed: 0.4151, 0.4511 and .4210), and this may reflect the importance of some unmeasured skills.

10. As in EU-SILC the variable ‘education’ is measured using a simplified version of the ISCED-97 classification that categorises only six levels, all distinctions within same education levels are neglected. When vocational or general education courses are not separated into each formal level, there may be heterogeneity within the same aggregated education levels and, consequently, underestimation of the explanatory power of education. As stressed by Koenker and Bassett [51], however, quantile regressions are also adopted to interpret the evidence of heteroscedasticity and test non-spherical errors.