COMPUTATIONAL ECONOMICS

Il dottorato in Economia offre corsi avanzati in economia, econometria e finanza e si propone di dare a studenti selezionati le capacità per condurre ricerche innovative, aprendo prospettive di carriera universitaria o presso istituzioni ed enti economici e finanziari. Questo corso mira a dare competenze quantitative e computazionali esplorando idee fondamentali di modellistica, i modelli ad agenti e le loro applicazioni computazionali.

a) Knowledge and understanding:
- know terminology and concepts related to modelling issues;
- know terminology and ideas to describe agent-based models;
- know terminology and main features of NetLogo programming.

b) Applying knowledge and understanding:
- ability to setup a simple model and its main goals;
- ability to formally define an agent-based model fitting the given purpose;
- ability to use, re-use or develop some computational draft of the model using NetLogo.

c) Making judgements:
- understand and critically assess the merits and problems of any modelling effort;
- make sense of the structure and internal consitency of an agent-based models, suggesting, if appropriate, revision and further invetigations;
- write reports/papers on models and results, positioning the content in the literature and assessing the novelty and importance of the outcome.

Gli studenti devono conoscere i contenuti dei corsi di primo anno del dottorato. La conoscenza di un lingiaggio di programmazione è utile (e tuttavia NetLogo è tipicamente "diverso" da altri linguaggi e non disperate se non avete esperienza di programmazione!)

Tentatively, the following topics/material will be covered:
- several fundamental Agent-Based Models are presented and we discuss how they shed light on interesting emerging phenomena in complex economic, financial, and social systems. We will introduce the Shelling Segregation Model, the El Farol Problem (Minority game), the Santa Fe artificial stock exchange model, and cooperation models. These models reveal important idea related to inductive thinking and economic outcomes, emergent phenomena, and agents' self-organization.
- programming in Netlogo. Working versions of most the previously listed models will be analyzed and studied, many models described in the textbook by Railsback and Grimm will be coded from scratch and modified/generalized. If time permits, an epidemiological SIRD model will be used as a programming testbed.
- ideas taken from complexity theory and genetic algorithms (e.g., related to variation, interaction and selection).

[RG] Railsback and Grimm, “A Course in Individual-based and Agent-based Modeling”, Princeton University Press, 2012.
[A] Ashlock, “Evolutionary Computation for Modeling and Optimization”, Springer, 2006.
[AC] Axelrod and Cohen, “Harnessing Complexity”, Basic Books, 2000.
[N] Netlogo website e documentazione, si veda http://ccl.northwestern.edu/netlogo/ I file necessari saranno installati col programma NetLogo.

In the past, grading was based on:
- three presentations in Pechakucha style, see http://www.pechakucha.org/ to be done in couples (week 1, 2 and 5): 30%
- one individual working paper describing an agent-based model and related NetLogo code (expected at the end of week 4): 30%
- final written or oral or practical exam: 30%
- active participation in class and online discussions: 10%

More information will be given at the beginning of the course or whenever possible.

scritto e orale

Lezioni, esercitazioni pratiche al calcolatore, presentazioni. Il prof. Righi terrà 5 incontri su ABM, il prof. Pellizzari presenterà la programmazione in NetLogo nei rimanenti 10 incontri.

The course will present well-known and insightful agent-based models taken from economics and social sciences, as well as fundamental ideas and computational methods to develop your own models. The student will also become familiar with NetLogo, an object-oriented programming language, coding platform and state-of-the-art tool in computational economics (download the code at http://ccl.northwestern.edu/netlogo/ ). The student will reach the level needed to select his/her modelling ideas, implement an agent-based model in NetLogo, verify and document the code using the ODD protocol and improve the presentation skills needed to demonstrate the functioning of the computational model and its scientific use.