SIdE Postgraduate Courses

29 June - 3 July 2026, Venice, Italy

Summer School on Network Econometrics

Coordinator: Roberto Casarin (University Ca' Foscari of Venice). E-mail: r.casarin@unive.it

Location: Meeting Room 7, San Giobbe Campus, Department of Economics, Ca' Foscari University of Venice.

Instructors: Emanuele Aliverti (University of Padova), Monica Billio (Ca' Foscari University of Venice), Ovielt Baltodano (Ca' Foscari University of Venice), Matteo Iacopini (LUISS University, Rome), Mariangela Guidolin (University of Padova), Luca Rossini (University of Milan).

The summer school is organised in collaboration with the Venice Center for Risk Analytics for Public Policies (VERA) and the Italian Society of Econometrics (SIdE). Bank of Italy funded scholarships for female students or young researchers.

The course aims to provide students with models and tools from graph theory to analyse various social, economic, financial and political interaction effects. The organization of the course can be split into three main parts. The first introduces some background in graph theory applied to social and economic networks. The second part deals with network models, and the third with the practical issues of extracting latent networks and analysing networks in economics and finance. The third part focuses mainly on stochastic models for networks and temporal networks. The main focus of the practical examples will be on social, economic and financial networks. Participants will learn to deal with network analysis in R, MATLAB and Gephi.

Lecture notes and material of this school are subject to copyright and are intended for internal use only.

Information

Timetable: Link to file.xlsx

School Location: The course will be held in Meeting Room 7 at San Giobbe Economics Campus, Ca' Foscari University of Venice. Address: Dipartimento di Economia - S. Giobbe, 873 - 30121 Venezia.

Softwares: Before the beginning of the course, you should install and familiarise yourself with

R software and RStudio the instructions/tutorials at the following links: i) Install R & R Studio ii) Familiarize with the interface (Chapter 1 & 2)
MATLAB
Gephi (link)

Zoom: Link to SIdE Zoom Classes.

Password: 02VQKk

Instructions: link and course presentation

You don’t need to download or buy Zoom to participate in the webinars. It will be enough to click on the link and follow the instructions on the screen. Please be reminded that recording lectures is not permitted. Access will be denied to non-registered participants.

Office Hours: Scheduled every day between 14.00 and 15.00. To attend office hours, use a private room, "Office Hour Room", in the main Zoom session.

Lecture Notes

1. Graph Theoretic Foundation of Networks

1.1 Financial Networks 1 (slides1)

1.2 Financial Networks 2 (slides2)

1.3 Financial Networks 3 (slides3)

1.4 Graph Theory (slides4)

1.5 Connectivity (slides5)

1.6 Random Graphs (slides6)

Tutorial 1: Network visualization with Gephi (assignment1, assignment2, data)

2. Multi-layer Network Models

2.1 Graphical Models (slides, papers)

2.2 Multi-layer Graphical Models (slides)

3. Network Analysis and Models

3.1 Introduction to network models (slides, paper)

3.2 Additive and multiplicative effects network models (AMEN) (slides and code)

3.3 Computational approaches for AMEN models (slides)

Tutorial 3: Networks with R: visualization, manipulation and description (code)

Tutorial 4: AMEN : lab session with R (code)

4. Network Extraction Methods

4.1 Parametric sparse regression models (slides)

4.2 Nonparametric sparse regression models (slides)

Tutorial 6: Extraction of Financial Networks in Matlab (code)

5. Temporal Network Models (slides, code)

5.1 Tensor decomposition

5.2 Temporal networks

5.3 Dynamic Tensor Models

5.4 Matrix-t network models

Tutorial 7: COMTRADE and Financial Networks in Matlab

6. Stochastic Block Models (SBM)

6.1 Communities and Network Modularity

6.2 Static SBM

6.3 Dynamic SBM

6.4 Bayesian Inference for SBM

Tutorial 8: Application of SBM to COMTRADE Networks

Tutorial 9: Application of SBM to GDP/Debt Networks

<-- Drop Area, click on the image

Google Sites

Report abuse