View syllabus
COMPUTATIONAL ECONOMICS
GIORGIO FAGIOLO
Academic year2023/24
CourseECONOMICS
Code433PP
Credits6
PeriodSemester 2
LanguageEnglish

ModulesAreaTypeHoursTeacher(s)
COMPUTATIONAL ECONOMICSSECS-P/01LEZIONI42
GIORGIO FAGIOLO unimap
ANDREA ROVENTINI unimap
Obiettivi di apprendimento
Learning outcomes
Conoscenze
  • Agent-based computational economics (ACE)
  • Agent-based models (ABMs)
  • Why ACE?
  • Coding of ABMs
  • Economic applications of ACE
Modalità di verifica delle conoscenze
  • Essay on selected topics
Assessment criteria of knowledge

The exam will consists in a written (short) essay (max 10 pages) on a topic covered during the course and chosen by the student. The writing of the essay requires the student to read a number of scientific papers on the chosen topic sent by the teachers after the student has selected the topic of her/his interest. Students have 2 weeks to complete the assignment after they receive the papers to read.  

Capacità
  • Coding
  • Building blocks of economic models
Modalità di verifica delle capacità
  • Essay on selected topics
Comportamenti

N/A

Modalità di verifica dei comportamenti

N/A

Prerequisiti (conoscenze iniziali)
  • Basic knowledge of neoclassical micro and macro economi models 
Corequisiti

N/A

Prerequisiti per studi successivi

N/A

Indicazioni metodologiche

N/A

Programma (contenuti dell'insegnamento)

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 2 parts. The first one is taught by Prof. Giorgio Fagiolo (Scuola Superiore Sant'Anna) and the second one by Prof. Andrea Roventini (Scuola Superiore Sant'Anna)

The first part (Fagiolo, 21 hours, 14 meetings) covers three themes. 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 (Python) 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.

The second part (Roventini) is dedicated to agent-based macroeconomics. First, the main differences between DSGE and ABMs will be discussed making the case for the adoption of agent-based models for macroeconomic policy analyses. Then, different macro ABMs accounting for endogenous growth and business cycles will be presented taking into account the main implications for innovation, monetary, and fiscal policies.

Syllabus

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 2 parts. The first one is taught by Prof. Giorgio Fagiolo (Scuola Superiore Sant'Anna) and the second one by Prof. Andrea Roventini (Scuola Superiore Sant'Anna)

The first part (Fagiolo, 21 hours, 14 meetings) covers three themes. 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.

The second part (Roventini) is dedicated to agent-based macroeconomics. First, the main differences between DSGE and ABMs will be discussed making the case for the adoption of agent-based models for macroeconomic policy analyses. Then, different macro ABMs accounting for endogenous growth and business cycles will be presented taking into account the main implications for innovation, monetary, and fiscal policies 

 

Teaching:

Both the first and the second part will be taught in presence only. Please go to https://sites.google.com/view/giorgiofagiolo/home to download video recorded lectures for all classes.

 

Topics and resources:

1) For the first part (Fagiolo): all resources and materials are available at

https://sites.google.com/view/giorgiofagiolo/home

(scroll down until you get to the section "Teaching", "Agent Based Computational Economics).

2) For the second part (Roventini): See material uploaded in this webpage during the course.

 

Office hours: 

Pls contact the instructors via email to set an appointment. 

Prof. Giorgio Fagiolo: giorgio.fagiolo@santannapisa.it

Prof. Andrea Roventini: andrea.roventini@santannapisa.it

 

Books and Readings

 

1) For the first part (Fagiolo): all resources and materials are available at

https://sites.google.com/view/giorgiofagiolo/home

(scroll down until you get to the section "Teaching", "Agent Based Computational Economics).

2) For the second part (Roventini): Readings will be given during the course.

Exams: 

The exam will consists in a written (short) essay (max 10 pages) on a topic covered during the course and chosen by the student. The writing of the essay requires the student to read a number of scientific papers on the chosen topic sent by the teachers after the student has selected the topic of her/his interest. Students have 2 weeks to complete the assignment after they receive the papers to read.  

 

Tutorials: 

Additional tutorial meetings will be scheduled. Tutorials are compulsory and consists in hands-on lectures where students can learn how to code and analyze agent-based models.

Bibliografia e materiale didattico

See https://sites.google.com/view/giorgiofagiolo/home

Bibliography

1) For the first part (Fagiolo): all resources and materials are available at

https://sites.google.com/view/giorgiofagiolo/home

(scroll down until you get to the section "Teaching", "Agent Based Computational Economics).

2) For the second part (Roventini): Readings will be given during the course.

Indicazioni per non frequentanti

N/A

Modalità d'esame

Essay on selected topics.

Stage e tirocini

N/A

Altri riferimenti web

https://sites.google.com/view/giorgiofagiolo/home

Updated: 01/02/2024 14:47