Skip to content

Biography

Dr. Giuseppe Ciccolini is a Researcher at the University of Milan.

He is currently involved in the ERC-funded project DESPO “Deindustrializing Societies and the Political Consequences” (Principal Investigator: Prof. Anne-Marie Jeannet), which investigates how manufacturing decline has reconfigured the way that citizens participate in politics and vote.

He holds a PhD in Political and Social Sciences from the European University Institute (EUI), a two-year MRes in Political Science from Sciences Po (Paris), a MA in European Studies from Sciences Po Strasbourg, and a BA in Political and Social Sciences from the University of Bologna.

He has freelanced for the OECD as a statistical analyst for the project “Drivers of Trust in Public Institutions”.  He was Adjunct Professor of Political Science at Heinrich Heine University Düsseldorf during the last two academic years.

His PhD dissertation studies the relation between socio-economic inequalities and electoral behavior in Europe, under the supervision of Prof. Juho Härkönen (EUI) and Prof. Nonna Mayer (Sciences Po). His project is funded by a four-year competitive grant from the EUI, which the European Commission supports through the EU budget.

The first study of his dissertation demonstrates that far-right parties are particularly successful among social classes whose economic status – meaning their objective economic position within the social hierarchy – has been worsening over time, based on ESS and EU-SILC data. The second study analyses class voting patterns in Europe from an intergenerational perspective, by investigating how social mobility influences voting choice, based on ESS-DEVO data. The third study provides evidence that economic decline causes a far-right response most likely in municipalities with stronger place-based community rootedness, which he measures based on a factor analysis exploiting a variety of data sources including administrative records and phone directory data.

His analyses rely on quantitative methods fit to large scale cross-national datasets (e.g., ESS, EVS, EU-SILC), longitudinal ones (e.g., SOEP), and aggregate geographic data (e.g. census data and official local-level statistics). 

He has worked as a teaching assistant at Sciences Po and EUI. Prior to commencing his doctoral studies, he worked as a MP assistant trainee at the European Parliament.

Native Italian speaker, he is fluent in English and French.  He has a working and conversational knowledge of Spanish, as well as a basic knowledge of Russian.

Twitter