Research Topics


Agent-based Computational Economics

Networks: Models and Empirics

Industrial Dynamics

Statistical Properties of Micro and Macro-Dynamics

Giorgio Fagiolo

Giorgio Fagiolo

Welcome

Teaching

Publications

Slides

Agent-Based Computational Economics (ACE)


Agent-Based Computational Economics (ACE) is a relatively recent field of research that addresses the study of economic dynamics by means of bottom-up micro-macro models with boundedly-rational, heterogeneous, interacting agents, often labeled as Agent-Based Models (ABMs). See Leigh Tesfatsion's ACE Website for introductory materials, papers, people and software related to ACE.


Within this broad field, my research interests focus in particular on:


  1. •Development and analysis of micro-macro ABMs of industry and market dynamics. Applications include models of growth, labor market dynamics, firm investment and business-cycle theory.

  2. •Methodology of ABMS. A peculiar feature of ABMs is that, in general, they are not analytically solvable. This means that computer simulations are required in order to analyze ABMs' outcomes. My research here aims at designing protocols and procedures required to analyze the output of ABMs and empirically validate them.


Selected Publications


  1. •Fagiolo, G. and Roventini, A. (2012), " Macroeconomic policy in DSGE and agent-based models”, Revue de l’OFCE, 124: 67-116.

  2. •Napoletano, M., Dosi G., Fagiolo, G. and Roventini, A. (2012), “Wage Formation, Investment Behavior and Growth Regimes: An Agent-Based Analysis”, Revue de l’OFCE, 124: 235-262.

  3. •Fagiolo, G. and Roventini, A. (2012), "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms", Knowledge Engineering Review, 27: 163-185.

  4. •Dosi, G., Fagiolo, G. and Roventini, A. (2010), "Schumpeter Meeting Keynes: A Policy-Friendly Model of Endogenous Growth and Business Cycles", Journal of Economics Dynamics and Control, 34: 1748–1767.

  5. •Fagiolo, G. and Roventini, A. (2009), "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms", Knowledge Engineering Review, forthcoming. Also published in Russian as "O nauchnom statuse economicheskoy politiki: povest' ob al'ternativnykh paradigmakh", Voprosy Economiki, 6:24.

  6. •Dawid, H. and Fagiolo, G. (Eds.), Special Issue on "Agent-Based Models for Economic Policy Design", Journal of Economic Behavior and Organization, 2008, Volume 67, Issue 2.

  7. •Dosi, G., Fagiolo, G. and Roventini, A. (2008), "The Microfoundations of Business Cycles: An Evolutionary, Multi-Agent Model", Journal of Evolutionary Economics, 18: 413-432.

  8. •Fagiolo, G., Birchenhall, C. and Windrum, P. (Eds.), Special Issue on "Empirical Validation in Agent-Based Models", Computational Economics, 2007, Volume 30, Number 3.

  9. •Dosi, G., Fagiolo, G. and Roventini, A. (2007), "Lumpy investment and endogenous business cycles in an evolutionary multi-agent model", Cybernetics and Systems, 38: 631-666.

  10. •Fagiolo, G., Moneta, A. and Windrum, P. (2007), "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems", Computational Economics, 30:195-226.

  11. •Windrum, P., Fagiolo, G. and Moneta, A. (2007), "Empirical Validation of Agent-Based Models: Alternatives and Prospects", Journal of Artificial Societies and Social Simulation, 10, 2, available at: http://jasss.soc.surrey.ac.uk/10/2/8.html .

  12. •Pyka, A. and Fagiolo, G. (2007), "Agent-Based Modelling: A Methodology for Neo-Schumpeterian Economics". In: Hanusch, H. and Pyka, A. (Eds.), The Elgar Companion to Neo-Schumpeterian Economics, Edward Elgar, Cheltenham.

  13. •Fagiolo, G., Moneta, A. and Windrum, P. (2006), "Confronting Agent-Based Models with Data: Methodological Issues and Open Problems", in Bruun, C. (Ed.), Advances in Artificial Economics. The Economy as a Complex Dynamic System, Lecture Notes in Economics and Mathematical Systems, Springer-Verlag Berlin Heidelberg, Vol. 584, pp. 255-267.

  14. •Dosi, G., Fagiolo, G. and Roventini, A. (2006), "An Evolutionary Model of Endogenous Business Cycles", Computational Economics, 27, 1: 3-34.

  15. •Fagiolo, G., Dosi, G. and Gabriele, R. (2004), "Matching, Bargaining, and Wage Setting in an Evolutionary Model of Labor Market and Output Dynamics", Advances in Complex Systems, 14: 237-273.

  16. •Fagiolo, G. and Dosi, G. (2003), "Exploitation, Exploration and Innovation in a Model of Endogenous Growth with Locally Interacting Agents", Structural Change and Economic Dynamics, 14: 237-273.

  17. •Aversi, R., Dosi, G., Fagiolo, G., Meacci, M. and Olivetti, C. (1999), "Demand Dynamics with Socially Evolving Preferences", Industrial and Corporate Change, 8, 2: 353-408.