RESEARCH STATEMENT

I have several research interests at the intersection of economics and the interdisciplinary science of complex systems, spanning the theoretical-empirical spectrum. Taking a complex systems approach to economics can mean multiple things. Broadly speaking, it is a focus on networks, heterogeneity, non-linear dynamics and bounded rationality, which have now become popular topics in economics. Narrowly speaking, it means building economic models from the bottom-up, without assuming equilibrium, such as Agent-Based Models (ABMs). In this latter sense, the complexity economics approach is still controversial and considered “heterodox” by the majority of economists. I think economics would greatly benefit from embracing non-equilibrium, complex systems models. So, as my main high-level research goal, I want to provide evidence of the usefulness of this approach.

On a purely theoretical level, this means investigating when the equilibrium assumption is reasonable. In one of my lines of research, I investigate when equilibrium is a valid assumption in games: Do players who learn from repeatedly playing a game converge to equilibrium, or do they chaotically keep changing their behavior? Our results suggest that equilibrium may be an unrealistic assumption in more situations than what might be thought. This provides a theoretical foundation for non-equilibrium models.

On a more applied level, non-equilibrium models can be useful first of all qualitatively. By qualitatively, I mean to mathematically formalize and explain a theoretical mechanism. Many economists would say that for these purposes the standard assumptions of economic theory — optimization and equilibrium — are ideal. Yet, there are situations in which non-equilibrium models provide simpler narratives and allow to more easily incorporate realistic assumptions. For example, we show that an ABM of the housing market accounts with a simple narrative for a wide range of phenomena related to income segregation, inequality and house prices, and that a simple reduced-form macroeconomic model makes it easy to analyze synchronization of endogenous business cycles.

However, where I think ABMs really have an edge is in assimilating the moltitude of economic micro-data that are becoming available. By “assimilating”, I mean that parameters and variables of agents can be easily mapped to individual observations, initializing and running the model with a granular description of the economy. This is not so easy in traditional models that must respect equilibrium constraints, which limit the amount of heterogeneity that models can handle. Initializing ABMs with detailed real-world data makes it possible to derive new insights and offer more sound policy recommendations. It also requires developing new techniques to dynamically estimate latent variables. Ultimately, being the assumptions in ABMs closer to reality than those of traditional economic models, ABMs should capture more signal of real economic processes, and so do a better job in quantitative prediction. This is my long-term research goal: comparing the out-of-sample predictive power of equilibrium models and ABMs. This does not mean that I think it is possible to predict economies far in the future with ABMs! I rather view short-run, out-of-sample prediction as an overfitting-free measure of realism. If it was possible to show explicitly that ABMs are, say, ten times more realistic than equilibrium models, policy makers would rather rely on ABMs for policy analysis.

BIO

I am a researcher at CENTAI, a newly founded research institute in Torino, Italy. Before, I was a James S. Mc Donnell Foundation Postdoctoral Fellow at the Institute of Economics and EMbeDS at the Sant’Anna School of Advanced Studies. I completed my DPhil (PhD) at the Mathematical Institute of the University of Oxford,  under the supervision of Professor Doyne Farmer, with an affiliation with the Complexity Economics group of INET Oxford. Prior to starting my PhD, I got a BSc in Physics and a MSc in Physics of Complex Systems from the University of Turin. At the same time, I studied Economics at the Scuola di Studi Superiori and Collegio Carlo Alberto in Turin. I prepared my master thesis at the Centre d’analyse et de mathematique sociales (CAMS) in Paris, under the supervision of Professors Jean-Pierre Nadal,  Pietro Terna and Annick Vignes.

For more information about my academic background and expertise, have a look at my CV (updated 03/04/2023).