The Vilfredo Pareto Prize, established by the EUI Department of Economics, honours Vilfredo Pareto, an Italian sociologist, economist, political scientist, and philosopher who lived and worked in Florence and Fiesole between 1882 and 1892 and is considered one of the pioneers of modern scientific research in economics.
The prize is awarded annually for the best doctoral thesis in economics defended at the EUI in the 12 months preceding the Conferring Ceremony.
Lukas Nord has been awarded the Vilfredo Pareto Prize for the Best Doctoral Thesis in Economics for his dissertation, Essays on Household Heterogeneity in Macroeconomics, under the supervision of Professors Arpad Abraham and Russell Cooper.
Nord's dissertation contains four excellent papers that study how different aspects of inequality across households shape macroeconomic trends and the desirability and effectiveness of different policy interventions.
His first chapter is pathbreaking on exploring the link between income (or wealth) inequality and price dispersion of identical or similar products. Another chapter studies how monetary policy that uses forward guidance to manage inflation expectation may be misguided if it ignores that households of different wealth levels pay different attention to news regarding future inflation. All chapters combine empirical and theoretical work on the very frontier of economic research.
Nord will join the Minneapolis Fed as a Junior Scholar for the 2023/24 academic year before heading to the University of Pennsylvania as an Assistant Professor in 2024.
Zheng Wang has been awarded the Vilfredo Pareto Prize for the Best Doctoral Thesis in Economics for her dissertation, Essays in the Economics and Econometrics of Networks and Peer Effect, under the supervision of Professors Andrea Ichino and Sule Alan.
Estimating the causal effect of peer relationships on the outcomes of an individual is a difficult task because of the endogeneity of the choice of peers. In her thesis, Wang makes a significant step forward in the solution of this problem, by proposing to study the causal effect of each single peer relationship, defining potential outcomes accordingly. By proceeding in this way, she connected the literature on peer effects to the literature on multiple treatments.
Once this connection was made (and it was not obvious to make it), Wang used the results of this literature in the context of networks. These results allowed her to identify, for example, the average causal effect of having a certain kind of friends (e.g., high achievers as opposed to low achievers). Wang also showed that her approach requires fewer identifying assumptions than the ones needed in previous approaches.
Wang will be a post-doctoral researcher at CREST in 2023-2024 and join NYU Abu Dhabi as an Assistant Professor starting in 2024.