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Chiara Conti
Data dell'evento: 
Lunedì, 27 Aprile, 2020 - 11:00
Pierfrancesco Reverberi, reverberi@diag.uniroma1.it

La dottoressa Chiara Conti terrà un seminario pubblico sulle attività di ricerca da lei svolte e in corso di svolgimento, come previsto dagli adempimenti richiesti per la chiamata del vincitore della procedura selettiva per il reclutamento di n. 1 ricercatore a tempo determinato di tipologia A per il settore concorsuale 13/A4 - Settore Scientifico-Disciplinare SECS-P/06 (Economia Applicata), presso il Dipartimento di Ingegneria Informatica Automatica e Gestionale Antonio Ruberti dell’Università degli Studi di Roma “La Sapienza”, bandita con D.D. N. 1/2019 del 08/10/2019. Il seminario sarà svolto in modalità telematica lunedì 27 aprile 2020, alle ore 11.00. Per partecipare, connettersi all’indirizzo https://meet.google.com/neb-mtdf-nex

Title: Technological innovation, externalities, and public policies

Abstract: In this talk, I will present an overview of my research activity about the drivers of firms’ and countries’ innovative performance, the role of externalities in innovation processes and the impact of public policies on R&D strategies and technological environment. Both theoretical and empirical models have been used to analyse strategic interactions and incentives to invest, to address policy measures and to evaluate their effectiveness. The talk will focus on two recent works analysing the relationship between EU policies and innovative activities, applied to different contexts and developed under different approaches. The first one addresses the problem of the fragmentation of EU technological base in the field of Renewable Energy Sources (RES) and investigate the role of EU environmental policies and support to the development of RES technologies in favouring higher technological integration. The applied methodology relies on the estimation of a double exponential knowledge diffusion model (Caballero and Jaffe (1993), Jaffe and Trajtenberg (1996, 1999) that describes the random process underlying the generation of citations using as dependent variable the expected frequency of citation. Bilateral coefficients are used as proxy for the intensity of knowledge flows. They also allow to identify the direction of knowledge flows (source of knowledge) and the changes in the patterns of citations over time. The second one focuses on the interplay between privacy regulation and incentives to innovate. It studies how opt-in privacy regulation (as implemented by EU GDPR), limiting firms’ ability to price discriminate, affects product quality and consumer welfare. The analysis is developed using a theoretical model of price discrimination characterized by (i) endogenous quality and (ii) heterogeneous consumers buying in online markets who have control over personal data and choose whether revealing information or not. Particular attention is devoted to the role of complementarity between information and quality, which favours enhanced consumption experiences. A brief discussion on future research directions will conclude the talk.

Short bio: Chiara Conti received her M.Sc. Degree in Economics from University of Milano-Bicocca and her Ph.D. in Economics from University of Milan. She was a visiting student at CORE-Universitè Catholique de Louvain. She has been a PostDoc researcher at the Department of Computer, Control, and Management Engineering “Antonio Ruberti” (DIAG) of the University of Rome “La Sapienza” since 2014. She has participated to several research projects, involving the evaluation of EU and national policies and the analysis of technology transfer (PRIN, Progetti di Ricerca Ateneo (Sapienza), RISIS Project (funded by European Commission), Idee di Ricerca ANVUR 2017). She has published in international peer reviewed journals such as Research Policy, Regional Studies, Economics of Innovation and New Technology. Her main research interests are in Industrial Organization, with a focus on innovation, regulation, and the economic impact of public policies. In her studies, she develops both theoretical models and micro-econometric analyses.



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