24019 - Methods for Economic Analysis

Learning outcomes

This course aims to provide the basic instruments for identifying methods and models oriented to the quantitative analysis of phenomena, as well as to the related spatial and economic applications. In this context, particular emphasis will be paid to: - identification of equilibria/disequilibria of dynamic spatial systems in both discrete and continuous time; - construction of dynamic spatial economic models and simulation analyses;- identification of (complex) spatial economic network topologies/typologies in order to carry out forecast analyses, according to different economic and policy scenarios.

Course contents

The content of the Course – mainly organized in the laboratory – is the following:

1. Dynamic models and systems:

- non-linear models with reference to dynamic (in)stability (equilibria and dis-equilibria) of spatial economic phenomena, in both discrete and continuous time;

- chaos models;

- prey-predator systems, competition/cooperation models and space-temporal systems;

- niche models and interrelated logistics.

2. Complexity of spatial-economic networks:

- modelling complex networks

- scale-free networks and small world networks

- complex network indicators: connectivity, centrality, clustering, etc.

- spatio-temporal economic complexity vs. simplicity.

Simulation experiments and applications to spatial-economic case studies will be carried out, with references to the above topics.

Readings/Bibliography

Main References:

a) Necessary (only for a few chapters indicated during the lectures)

Tu P.N.V., Dynamical Systems, Springer-Verlag, Berlin, 1994.

b) Suggested

Batty M., Cities and Complexity, MIT Press, London, 2005.

Caldarelli G., A. Vespignani, Large Scale Structure and Dynamics of Complex Networks, World Scientific Publishing, Singapore, 2007.

Vega-Redondo F., Complex Social Networks, Cambridge University Press, NY, 2007.

c) Additional Reading

Additional updated reading (in English) will be provided during the lectures.

Teaching methods

Laboratory and lectures: empirical applications and scenarios/simulation experiments will be carried out, with reference to the analysed theories and topics.

Assessment methods

Knowledge and competences acquired will be assessed through an oral (power point) presentation concerning the empirical application carried out in the laboratory, jointly with a possible (short) written essay. At the end of the course students are expected to hold the following competences:

• knowledge of methodologies suitable to describe and identify the dynamics of spatial-economic phenomena, by means of applications and simulations in the laboratory;

• knowledge of methodologies suitable to describe and identify complex economic networks, by means of applications and simulations in the laborator;

• ability to integrate methods and empirical tools presented during the course;

• ability to design “Research Questions” concerning the use of the adopted instruments to analyse dynamic systems, as well as complex networks, in the spatial-economic field;

• ability to discuss the emerging findings, in order to interpret the spatial-economic phenomenon under analysis, in the light of recent literature and current decision strategies.

Teaching tools

Reading materials, grouped according to the topics of the Course, will be made available at the end of each lecture, on IOL platform.

In the laboratory of informatics, specific software, with reference to following topics: a) dynamic models; b) complex network models (with the related indicators), will be provided and utilized.

Office hours

See the website of Aura Reggiani