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When studying social, economic and biological systems, one has often accessto only limited information about the structure of the underlying networks. Anexample of paramount importance is provided by financial systems: informationon the interconnections between financial institutions is privacy-protected,dramatically reducing the possibility of correctly estimating crucial systemicproperties such as the resilience to the propagation of shocks. The need tocompensate for the scarcity of data, while optimally employing the availableinformation, has led to the birth of a research field known as networkreconstruction. Since the latter has benefited from the contribution ofresearchers working in disciplines as different as mathematics, physics andeconomics, the results achieved so far are still scattered across heterogeneouspublications. Most importantly, a systematic comparison of the networkreconstruction methods proposed up to now is currently missing. This reviewaims at providing a unifying framework to present all these studies, mainlyfocusing on their application to economic and financial networks.

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