Students Cohorts

Davide Zampatti

201512091727th zampatti

Topic of thesis: Social determinants of income inequality: An empirically calibrated agent-based model of segmented assimilation of immigrants
Abstract: Abstract Aim of this project is examine social income inequality determinants using an empirically calibrated agent-based-model. The goal is understand ifmigration phenomena creates structural problems of income inequality through a mix of social mechanism such as residential segregation patterns, their social network counterparts and related educational traps. After a review of literature in both Economics and Sociological fields, I can place project in Analytical Sociology branch of literature. In last thirty years, Europe has welcomed many immigrants. At least 9% of population is foreign born in main European countries. Many immigrants were subject of segmented assimilation and have great difficulties to have relationships outside of their community that is often residential segregated. This situation of segregation also reflects on education traps and social networks. These phenomena can concur to explain how immigrants’ ethnic penalty in job market can contribute on income inequality also for second generation. Methodologically the model will be implemented by an Agent Based Model, firstly for highlight micro-macro link and secondly for analyze inequality dynamics combining sociology and economics for dissect social mechanism that are concurrent causes of income inequality.
Research interests: Substantive: Inequality; Analytical Sociology; Institutional and New-Institutional Economics; Sport Management,Economics and Sociology; Migrations. Methodological: Methodological Individualism; Agent-Based Models; Econometrics; Simulated-based Econometrics methods; Mechanism Design.
Graduated from: BA: University of Brescia; MSc University of Brescia and as visitng student Mid Sweden University
Degrees obtained: BA in Economics; MSc in International Economics
E-mail address: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

 

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