if this message does not display correctly, click here | Table of Contents Michele Cantarella, Università degli studi di Modena e Reggio Emilia (UNIMORE), European Central Bank (ECB) - Directorate General Statistics
Nicolò Fraccaroli, University of Rome Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions, Bank of England
Roberto Volpe, Italian Ministry of Economic Development Alessandra Pasquini, CEIS, University of Rome Tor Vergata
Furio Camillo Rosati, University of Rome Tor Vergata Roy Cerqueti, University Sapienza Rome
Rocco Ciciretti, Tor Vergata University of Rome - Department of Economics and Finance
Ambrogio Dalò, University of Groningen - Faculty of Economics and Business
Marco Nicolosi, University of Perugia - Department of Economics | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Does Fake News Affect Voting Behaviour?" 
CEIS Working Paper No. 493 MICHELE CANTARELLA, Università degli studi di Modena e Reggio Emilia (UNIMORE), European Central Bank (ECB) - Directorate General Statistics
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NICOLÃ’ FRACCAROLI, University of Rome Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions, Bank of England
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ROBERTO VOLPE, Italian Ministry of Economic Development
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We study the impact of fake news on votes for populist parties in the Italian elections of 2018. Our empirical strategy exploits the presence of Italian- and German-speaking voters in the Italian region of Trentino Alto-Adige/Südtirol as an exogenous source of assignment to fake news exposure. Using municipal data, we compare the effect of exposure to fake news on the vote for populist parties in the 2013 and 2018 elections. To do so, we introduce a novel indicator of populism using text mining on the Facebook posts of Italian parties before the elections. We find that exposure to fake news is positively correlated with vote for populist parties, but that less than half of this correlation is causal. Our findings support the view that exposure to fake news (i) favours populist parties, but also that (ii) it is positively correlated with prior support for populist parties, suggesting a self-selection mechanism. "A Human Capital Index for the Italian Provinces"
CEIS Working Paper No. 494 ALESSANDRA PASQUINI, CEIS, University of Rome Tor Vergata
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FURIO CAMILLO ROSATI, University of Rome Tor Vergata Good health conditions and high quality education are crucial for children development and for their future contribution to the society. Human capital has been recognized as one of the crucial engines of economic growth. Nonetheless, it is often hard to establish a metric that allows to monitor its evolution and contribute to assess the effects of policies. In Italy, the use of such an index at national level may not be enough to have a clear picture of the human capital conditions. Socio-economic characteristics and public services are highly heterogeneous across the Country. There is, therefore, good ground to believe that also the human capital presents substantial differences across the Italian Provinces. To take such a high heterogeneity into consideration, we develop a Human Capital Index for Italy disaggregated at provincial level. The results show very large differences across Italian Provinces in terms of human capital, mostly driven by the variation in the quality of educational. Strikingly, the differences among Italian Provinces span a range that goes from best performers among high income countries to middle and low income countries. Finally, we classify the Italian Provinces in three main clusters according to their HCI and show how the clusters differ in terms of several socio-economic characteristics "The Resilience of the Socially Responsible Investment Networks"
CEIS Working Paper No. 495 ROY CERQUETI, University Sapienza Rome
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ROCCO CICIRETTI, Tor Vergata University of Rome - Department of Economics and Finance
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AMBROGIO DALÃ’, University of Groningen - Faculty of Economics and Business
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MARCO NICOLOSI, University of Perugia - Department of Economics
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A network model is introduced and developed to compare portfolios of funds which are high ranked in Environmental Social and Governance (ESG) aspects with those with a poor ESG compliance. The nodes in the network represent funds and the edges are weighted on the basis of the capitalization due to the common components of the connected nodes. We specifically deal with the reactions of the considered financial networks to exogenous shocks of negative financial nature. To this aim, we provide a novel definition of the resilience of a financial network in terms of stability of its community structure. We test the theoretical proposal on different networks characterized by different ESG scores. We find that the high ranked funds networks are more resilient than the corresponding networks of low ranked funds. | | ^top
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