Statistical-physics methods of reconstruction and analysis of inter-firm production networks

1 Research Collaborator position

(Deadline July 11^th, 2022 13:00 )

Fields

Network reconstruction, Economic networks, Statistical Physics, Maximum-entropy methods

Profile

The candidate has a MSc degree in physics, engineering, applied maths, or related. The candidate has experience in the field of network theory, especially in methods of statistical physics and information theory for the reconstruction of networks from partial information, as well as their application to the analysis of economic networks. The candidate has both a strong theoretical background and a documented experience in the analysis of big datasets, preferably of economic and/or financial nature. The candidate is open to a multidisciplinary approach at the crossroads of physics, economics and information theory.

Activity

This position is framed within the PRO3 program "Network analysis of economic and financial resilience" jointly supported by IMT School pf Advanced Studies Lucca, Sant'Anna School of Advanced Studies and Scuola Normale Superiore in Pisa.
The project aims on the one hand at developing novel quantitative tools for the data-driven analysis of systemic risk on complex networks, and on the other hand at using those methods for the study of financial stability and economic resilience. The main domains of application will be the structural impact of shocks on economic and financial networks (e.g. international and inter-firm trade, inter-bank networks).
The project will require a combination of design of theoretical models of complex networks within the framework of statistical physics, empirical data analysis with econometric and machine learning methods, and derivation of implications for policymaking and financial risk management. This position will in particular focus on the development of novel maximum-entropy tools for the inference and reconstruction of microscopic inter-firm production networks from partial information. The candidate will both develop new theoretical frameworks and analyse large datasets of economic interactions at different levels of resolution.

Formal requirements