giorgio Fagiolo

Contact

Istituto di Economia

Scuola Superiore Sant’Anna

Piazza Martiri della Libertà, 33

56127 PISA (Italy)

Email: giorgio.fagiolo at sssup.it

Follow me on Twitter @giorgiofagiolo

Short Bio

I am Full Professor of Economics at the Institute of Economics, Sant’Anna School of Advanced Studies

My research interests include agent-based computational economics; empirics and theory of economic networks; climate change and development economics, and the statistical properties of microeconomic and macroeconomic dynamics (see below for more info).

My papers have been published in: Science, Nature Scientific Data, J of Economic Geography, World Development, J of Applied Econometrics, PLoS ONE, J of Economic Dynamics & Control, Nature Scientific Reports, Environmental Research Letters, Physica A, New J of Physics, Physical Review E, J of Economic Behavior & Organization, Macroeconomic Dynamics, Industrial & Corporate Change, Advances in Complex Systems, Frontiers in Human Dynamics, Economies, Global Environmental Change, J of Evolutionary Economics, J of Economic Interaction & Coordination, European Physical J B, Network Science, Regional Studies, Empirical Economics, Knowledge Engineering Review, Applied Network Science, The J of International Trade & Economic Development, J of Artificial Societies and Social Simulations, Applied Economics Letters, Cybernetics and Systems, Economics Bulletin, Eastern European Economics.

Click here to download my CV.

Current Research

On the Spotlight 

Gortan, M., Testa, L., Fagiolo, G. and Lamperti, F. (2024), "A unified dataset for pre-processed climate indicators weighted by gridded economic activity", forthcoming in Scientific Data, Springer Nature. An earlier version of this article is available as Arxiv preprint here. 

⬇️  Check out the related data repository at: https://weightedclimatedata.streamlit.app    ⬇️

Additional Current Work  

Fagiolo, G. and Luzzati, D.S. (2023), Centrality in the macroeconomic multi-network explains the spatiotemporal distribution of country per-capita income, Applied Network Science, 8, 59.

Cresti, L. , Dosi, G. and Fagiolo, G. (2023), "Technological interdependencies and employment changes in European industries", Structural Change & Economic Dynamics, 64: 41-57. A previous version is available as LEM Working Paper Series, No. 2022/05.

Ferraresi, T., Ghezzi, L., Vanni, F., Caiani, A., Guerini, M., Lamperti, F., Reissl, S., Fagiolo, G., Napoletano, M. and Roventini, A. (2024), "On the economic and health impact of the COVID-19 shock on Italian regions: A value chain approach", Regional Studies, 58:3, 490-506, DOI: 10.1080/00343404.2023.2189508

Fagiolo, G. and Rughi, T. (2023), "Exploring the Macroeconomic Drivers of International Bilateral Remittance Flows: A Gravity-Model Approach", Economies, 11(7), 195.

Zema, S.M., Fagiolo, G., Squartini, T. and Garlaschelli, D. (2021), "Mesoscopic Structure of the Stock Market and Portfolio Optimization", LEM Working Paper Series, No. 2021/45. Also available as arXiv preprint.

Research topics

Agent-Based Computational Economics (ACE)

Complex Economic Networks

Climate Change and Development Economics

Statistical Properties of Micro and Macro-Dynamics

Industrial Dynamics

Publications

Books

Delli Gatti, D., Fagiolo, G., Gallegati, M., Richiardi, M. and Russo, A. (2018), Agent-Based Models in Economics: A Toolkit, Cambridge University Press, ISBN: 9781108400046.

Journal Articles

Book Chapters

Special Issues Edited

Teaching

Agent-Based Computational Economics

This course is intended to serve as a broad introduction to the huge literature using agent-based computational approaches to the study of economic dynamics. It is organized in three parts. The first one (“Why?”) will discuss the roots of the critiques to the mainstream paradigm from a methodological, empirical and experimental perspective. We shall briefly review the building blocks of mainstream models (rationality, equilibrium, interactions, etc.) and shortly present some of the evidence coming from cognitive psychology and experimental economics, network theory and empirical studies, supporting the idea that bounded rationality, non-trivial interactions, non-equilibrium dynamics, heterogeneity, etc. are irreducible features of modern economies. In the second part (“What?”) we shall discuss what ACE is and what are its main tools of analysis. We will define an ABM and present many examples of classes of ABMS, from the simplest (cellular automata, evolutionary games) to the most complicated ones (micro-founded macro models).The third part (“How?”) aims at understanding how ABMs can be designed, implemented and statistically analyzed. We shall briefly present the basics of programming, by both discussing the pros and cons of using simulation platforms (Matlab, NetLogo, Swarm, LSD, etc.) vs. computer languages (Java, C++, etc.) and providing some simple “hands-on” applications to cellular automata. Finally, we will see how the outputs of ABMs simulation should be treated from a statistical point of view (e.g., Montecarlo techniques) and we will discuss two hot topics in ABM research: empirical validation and policy analysis.

Economic Networks: Theory and Empirics

This course introduces the “science of networks” for economists. The first part of the course discusses examples of real-world networks in hard and social sciences. We ask why networks are important for economists and what are the main network-related questions as far as models and empirical analyses are concerned. We then present more formally graph theory and explore network statistics. We finally move to models of network formation and present some relevant applications to economics (e.g. trade networks).

International trade, human mobility, and finance: Empirical Modeling

This course is an introduction to the theory and empirics of gravity models. We will start describing stylized facts in international trade data. Then, we will introduce the empirical gravity model of trade and we will explore its theoretical foundations. Next, we will go through issues on estimation with the help of empirical applications. Finally, we will see how the gravity model can be applied to international finance, human migration and temporary mobility. Advanced topics discussed in the course cover spatial econometrics techniques in panel data and gravity model estimation, multilateral resistance and the econometrics of networks.

Partial and General Equilibrium Theory

This course is an introduction to the neoclassical theory of competitive markets. We will cover issues about existence, uniqueness, and stability of competitive equilibria, as well as their efficiency properties, in both partial and general equilibrium settings. Furthermore, we will discuss market-failure issues in presence of externalities and public goods.  

Last Update: December 2023