Giorgio Fagiolo

Giorgio Fagiolo

Giorgio Fagiolo

Teaching

Here you can find a list of the courses I am currently (or I have been) teaching. You can download syllabi, slides, and other stuff related to the courses.

Agent-Based Computational Economics

Overview

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

Overview

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).

The empirics of trade, migration and temporary mobility

Overview

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 in estimation with the help of empirical applications. Finally, we will see how the gravity model can be applied to 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.

Advanced Microeconomics: General Equilibrium Theory (M.Sc. in Economics)

Overview

In this module we present an introduction to general equilibrium theory. Textbook: Mas-Colell, Whinston, Green (1995), Microeconomic Theory, Oxford University Press. Relevant chapters: Compulsory: 10,15,16; Optional: 17.