The Italian Econometric Association (SIdE-IEA) in collaboration with the Venice centre in Economic and Risk Analytics for Public Policies (VERA) organizes the course for PhD students in:
Network Econometrics
29 June - 3 July, 2026
Università Ca' Foscari Venezia
The Summer School aims to provide participants with models and tools from graph theory to analyse various effects of social, economic, and political interaction. The school will host leading scholars developing relevant network modelling and inference research and their applications to various fields. It is organised by the Department of Economics in collaboration with the Venice Center for Risk Analytics for Public Policies (VERA) , and the Italian Econometrics Association (SIdE).
Coordinator
Roberto Casarin
Address: Dept. of Economics, University Ca' Foscari of Venice,
San Giobbe 873/b, 30121 Venezia, Italy
Phone: +39 041.234.91.49
E-mail: r.casarin@unive.it
Lecturers
- Emanuele Aliverti, University of Padova
- Monica Billio, Ca' Foscari University of Venice
- Matteo Iacopini, LUISS University
- Mariangela Guidolin, University of Padova
- Luca Rossini, University of Milan
- Ovielt Baltodano Lopez ,Ca' Foscari University of Venice
The maximum number of allowed participants in presence is 20.
Requirements
Intermediate knowledge of statistical inference and econometrics
Course Outline
1. Graph Theoretic Foundation of Networks
1.1 Definitions
1.2 Graph Connectivity
1.3 Multilayer-networks
1.4 Tutorial 1: Introduction to R (Data manipulation and regression)
1.5 Tutorial 2: Network mapping and visualization in R
1.6 Tutorial 3: Text mining and visualization in R
2. Network Extraction Methods
2.1 Graphical Models
2.2 Parametric sparse regression models
2.3 Nonparametric sparse regression models
Tutorial 3: Extraction of Financial Networks in Matlab
Tutorial 4: Network visualization with Gephi
3. Temporal Network Models
3.1 Tensor decomposition
3.1 Dynamic Tensor Models
3.2 Markov-switching Tensor Models
Tutorial 6: Application to COMTRADE and Financial Networks in Matlab
4. Multi-layer Network Models
4.1 Definition and analysis
4.2 Exctraction
Tutorial 7: Application to Oil Linkages Networks in Matlab
5. Stochastic Block Models (SBM)
5.1 Communities and Network Modularity
5.2 Static SBM
5.3 Dynamic SBM
5.4 Bayesian Inference for SBM
Tutorial 8: Application of SBM to COMTRADE Networks
Tutorial 9: Application of SBM to GDP/Debt Networks
Reference textbooks and suggested readings:
Introductory references
- Jackson, M.O. (2008) Social and Economic Networks, Priceton University Press.
- Diebold, F. and Yilmaz, K. (2015), Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring, Oxford University Press.
- Bollobas, B. (1998), Modern Graph Theory, Springer.
Further references
- Jensen, F. (1996), An Introduction to Bayesian Networks, Springer-Verlag
- Lauritzen, S. (1996). Graphical Models, Oxford University Press
- Pearl, J. (1998). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.
- Whittaker, H. (1990). Graphical Models in Applied Multivariate Statistics, John Wiley.
Software:
Participants will use their laptops with MATLAB, R and GEPHI already installed on them.
Venue and timetables
The Course requires a full-time attendance and participation is not compatible with other jobs at the same time (e.g. preparation of other exams). Lectures and tutorials will be in English, with the following schedule (provisional):
- Monday to Friday: lectures: 9.30-13.00, 15.00-18.30.
The course will be held in the Campus Economico San Giobbe at Università Ca’ Foscari, Venezia, Italy. Address: Dipartimento di Scienze Economiche - S. Giobbe, 873 - 30121 Venezia.
Participants will be hosted in StayCity Apart Hotel. For in-person participants who do not require accommodation, the online course fees apply.
Contacts
- For more information: Roberta Partisani phone: +39 0543446554 ; e-mail: info@side-iea.it
- For administrative issues: Fabrizio Zanotti (admin@side-iea.it), phone:0543446561;
- Local organizing contact: Centro VERA veraschool@unive.it, phone: +39 041 234 6844
Sponsors
