Financial contagion among countries can arise from different channels, the most important of which are financial markets and bank lending. The paper aims to build an econometric network approach to understand the extent to which contagion spillovers (from one country to another) arise from...

This paper investigates how to improve statistical-based credit scoring of SMEs involved in P2P lending. The methodology discussed in the paper is a factor network-based segmentation for credit score modeling. The approach first constructs a network of SMEs where links emerge from comovement of...

The assessment of the health impacts of the COVID-19 pandemic requires the consideration of mobility networks. To this aim, we propose to augment spatio-temporal point process models with mobility network covariates. We show how the resulting model can be employed to predict contagion patterns...

We propose a statistical measure, based on correlation networks, to evaluate the systemic risk that could arise from the resolution of a failing or likely-to-fail financial institution, under three alternative scenarios: liquidation, private recapitalization, or bail-in. The measure enhances the...

The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess their strength on spreading economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with...

The paper investigates the role of network centrality in predicting borrowers' and lenders' behavior in peer-to-peer (P2P) lending. The empirical analysis of data from Renrendai, a leading lending platform in the People's Republic of China, reveals that the lenders who are at the center of a...