SIdE Postgraduate Courses
June, 28 - July, 3, 2021, Venice, Italy
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Summer School on Network Econometrics
Summer School on Network Econometrics
Coordinator: Roberto Casarin (University Ca' Foscari of Venice). E-mail: r.casarin@unive.it
Instructors: Monica Billio (University Ca' Foscari of Venice), Roberto Casarin (University Ca' Foscari of Venice), Matteo Iacopini (Vrije University of Amsterdam), Sergio Petralia (Utrecht Univeristy and LSE), Luca Rossini (University of Milan).
The summer school is organized in collaboration with the Venice Center for Risk Analytics for Public Policies (VERA) and the Italian Society of Econometrics (SIdE).
The aim of the course is to provide students with models and tools from network and graph theory for the analysis of a wide variety of social, economic, financial and political interaction effects. The organization of the course can be split into three main part. The first is an introduction to 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 main focus of the third part is on stochastic models for networks and temporal networks. The main focus of the practical examples will be on social, economics and financial networks. Partecipants will learn how to deal with network analysis in R, MATLAB and Gephi.
Information
Information
Program and Syllabus: Link to file .pdf
Timetable: Link to file.xlsx
Softwares: Prior the beginning of the course you should install and familiarize 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. Instructions on how to connect to the webinars via Zoom and rules are available at this link. Note that in order to participate in the webinars you don’t need to download or buy Zoom. 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
Lecture Notes
Welcome (Slides)
1. Graph Theoretic Foundation of Networks
1.1 Networks Extraction (Slides)
1.2 Graph Theory: Introduction (Slides)
1.1 Financial Networks (Slides, DataAdjMatFinNet)
1.3 Graph Theory: Connectivity (Slides, Code/Assignements, Data)
1.4 Random Graphs (Slides, Papers)
1.5 Tutorials on Network Visualization (Code/Assignements, Data)
Tutorial 1: Introduction to R (Data manipulation and regression) (Video)
Tutorial 2: Network mapping and visualisation in R (Video)
Tutorial 3: Text mining and visualization in R (Video)
2. Network Extraction Methods
2.1 Graphical Models (SlidesVAR, SlidesSUR, Papers, Code)
2.3 Parametric sparse regression models (Slides)
2.4 Nonparametric sparse regression models (Slides)
2.5 Tutorials on Network Extraction in Matlab
Tutorial 4: Extraction of Financial Networks in Matlab (Code)
Tutorial 5: Network visualization with Matlab and Gephi (Code)
3. Temporal Network Models
3.1 Temporal networks (Slides)
3.2 Tensor decomposition (Slides, Code)
3.3 Dynamic Tensor Models (Slides)
3.4 Robust Network Models (Slides)
Tutorial 6: Appliction to COMTRADE and Financial Networks in Matlab (Code)
4. Multi-layer Network Models
4.1 Definition and extraction (Slides)
4.2 Tutorial 7: Oil Linkages Networks in Matlab (Code)
5. Stochastic-Block Models
5.1 Definition and inference (Slides)
5.2 Application to Financial Networks (Slides)
Some pictures!!!
Some pictures!!!
Gephi!
Financial Networks!
Tensors!
... and tensors!
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