Dimitris Kallioras (p), George Petrakos, Paschalis Arvanitidis, Spyros Niavis, Yiannis Saratsis

Ivan Etzo

Inequality has been a long-standing issue and a terrain of theoretical and empirical discussions and debates in many disciplines in economics, social sciences, and geography. Despite tremendous progress in welfare levels worldwide, the problem of unequal allocation of wealth and opportunities remains a top priority in policy and spurs waves of scientific discussions and policy debates. Inequality manifests itself in various types considering outcomes, opportunities, membership, and treatment and different dimensions such as social, economic, spatial, intergenerational, and perceptional. A key, though often neglected, characteristic of these types and dimensions of inequality is that they are interrelated with each other in a variety of ways. This makes it difficult to reach an academic and policy consensus on the actual meaning of inequalities as well as to clearly understand the causes and effects among the different types and dimensions of the phenomenon. The paper adopts a holistic and integrated approach and provides proper definitions and metrics of the various types of inequality. Up to now, scant attention has been paid to the distinction between desirable diversity and inequality. Indeed, the existing bodies of literature, in the various scientific fields, neither indicate at which point differentiation becomes a problem nor provides any criteria to decide what is the critical tolerance level where socially desirable diversity turns into socially undesirable inequality. Thus, the paper examines the dialectic relation between diversity and inequality under different market, institutional and social arrangements. To this end, the paper draws on a questionnaire survey addressed to various experts (i.e., scientists, policy-makers, businesspeople) worldwide in order to explore their views on a number of issues concerning inequality. Particularly, the following issues are going to be addressed: (a) to provide definitions of inequality, (b) to provide measures of inequality, (c) to evaluate the importance of inequality, (d) to evaluate dilemmas and trade-offs that relate to inequality, (e) to detect drivers of inequality, (f) to suggest policies for tackling inequality. Such issues have long troubled scholars; yet, even today, they remain unsettled despite the advanced techniques and theories that have been available to researchers. Gleaning the experts’ views through a questionnaire-based survey may shed new light on the above issues, in a manner that previous studies have not.

Adriana Di Liberto (p), Andrea Caria, Sara Pau

Dimitris Kallioras

This study investigates how Italian schools have been affected by the reorganization caused by the Covid-19 emergency, and if this shock has unequally affected Italian students during the pandemic period. To this aim, we conduct a three-level survey (students, teachers and school principals) and collect data from a representative sample of Italian upper secondary schools. The final sample includes information on 123 schools (5% of the Italian upper-secondary schools’ population) through a random selection stratified by Italian macro-area (NUTS 1 regions), and school types (Lyceum, Technical, and Vocational Schools).

Ivan Etzo (p), Raffaele Paci

Adriana Di Liberto

A huge flow of university students across the Italian regions has been detected over a long period of time exhibiting a clear spatial mobility pattern. The most relevant movements have been in the south-north direction, and they mainly involve the students with the highest quality in terms of competencies and skills (Columbu et al. 2020; Ballarino et al. 2021)). Moreover, once they achieve graduation, most of these students enter the local labour market (AlmaLaurea, 2021) of the region in which they attend the university, thus generating a brain drain that exacerbates income inequalities across regions. The study analyses to what extent the Covid-19 pandemic has changed students' mobility across the Italian regions. Students' mobility can be considered a pre-market driver influencing both human capital and income inequalities across regions. We use individual students’ data from the National student registry (Anagrafe Nazionale Studenti, ANS) to identify “mobile students” from origin to destination NUTS3 Italian provinces. We investigate, through a gravity model, the determinants of mobility flows using a set of Origin, Destination and O-D explanatory variables, such as economic and labour market conditions, universities’ quality and facilities, local amenities. Finally, we assess the effect of this North-South “brain drain” on territorial inequalities.