Reconstruction methods for networks: the case of economic and financial systems

TL;DR

This paper reviews various network reconstruction methods for economic and financial systems, emphasizing their importance in understanding systemic resilience despite limited data access.

Contribution

It provides a unifying framework to compare and analyze existing network reconstruction techniques applied to economic and financial networks.

Findings

Highlights the importance of network reconstruction in financial systems

Provides a systematic comparison of different reconstruction methods

Identifies gaps and future directions in the field

Abstract

When studying social, economic and biological systems, one has often access to only limited information about the structure of the underlying networks. An example of paramount importance is provided by financial systems: information on the interconnections between financial institutions is privacy-protected, dramatically reducing the possibility of correctly estimating crucial systemic properties such as the resilience to the propagation of shocks. The need to compensate for the scarcity of data, while optimally employing the available information, has led to the birth of a research field known as network reconstruction. Since the latter has benefited from the contribution of researchers working in disciplines as different as mathematics, physics and economics, the results achieved so far are still scattered across heterogeneous publications. Most importantly, a systematic comparison of the network reconstruction methods proposed up to now is currently missing. This review aims at providing a unifying framework to present all these studies, mainly focusing on their application to economic and financial networks.