Riassunto analitico
In the last 20 years there has been a growing increase in the number of people who have obtained tertiary education, due, according to several sources, to the needs of more specialized skills in the job market. However, as the Gini index shows, such increase was not accompanied by a decrease in inequalities in developed countries. Thus, the main objective of this thesis is to demonstrate how socio-economic inequalities can be perpetuated in tertiary education, limiting one of the main functions of education that is of social elevator.
The thesis is structured as follows.
In the first chapter, the work starts introducing the tertiary education levels in the world and then focusing on Italy, which represents an interesting case study because of its education levels below the OECD average. Then, the theoretical background of the topic is investigated. In particular, it is shown how inequality and intergenerational mobility appear to be linked through the curve of the Great Gatsby and, how tertiary education can play the role of social elevator. The University will be described as both a place of human capital investment, a "parking", and a "signal" for companies. It will be shown the first regression that estimates returns of instruction, its developments, and the application of the Keynesian model of linkages in universities.
The second chapter, through extensive literature, analyses the parents as a proxy of socio-economic background that influence enrolments, dropout, performances, and achievements in university. Furthermore, the property value will be shown as a very different proxy of the background. Influences from other variables such as gender, nationality and other student characteristics are also exposed.
Moving to the third chapter, data and methodologies adopted in the empirical analysis are presented. Linear and discrete choice regression models will be used to estimate the effect of socio-economic background on the field of study, the degree grade and the delay to achieve the degree in a sample of graduated at University of Modena and Reggio Emilia between 2013 and 2021. Three sources of data are used to do that. The first is an AlmaLaurea database which contains data on social class and parental education of the graduates, firsts proxies of socio-economic background in the models. The second source is an Esse3 database which contains data on ISEE bands of contributions, used as a second proxy of the socio-economic background. Instead, the third database contains the average sale of real estate by Italian postcodes constructed with Immobiliare.it data, whose logarithmic version will be used as proxy in the third model. Furthermore, gender, nationality, a proxy for region of residence, type of high school and diploma final mark will be used as covariates.
The main results are presented in chapter four. In sum, the social science field presents more graduates from lower socio-economic background, followed by health-related field. Instead, medicine and law, generally more profitable courses than others, appear to be frequented mostly by higher socio-economic backgrounds. Moving forward, results on graduation final mark show that the latter increases for who comes from higher backgrounds, instead the delay in graduating is inversely proportional to each socio-economic proxy, apart from parental education where the more the parents are educated, the more students delay graduating.
In general, such results agree with what is seen in the literature, confirming that the influence of the socio-economic background persists in university choices and achievements, and it could become a potential limit in the future job market of the graduates from lower backgrounds, that may see their social climbing slowed.
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