On the distribution of links in financial networks: structural heterogeneity and functional form

We investigate the distribution of links in three large data sets: one of these covering interbank loans in the electronic trading platform e-MID, and the other two covering a large part of the loans of banks to non-financial companies in the Spanish and Japanese economies, respectively. In contrast to all the previous literature, we do not assume homogeneity of the link distribution over time and across different categories of agents (banks, firms) but apply our hypothesized distributions as regression models. As it turns out, many of the tested sources of heterogeneity turn out to be significant regressors. For instance, we find pervasive time heterogeneity of link formation in all three data sets, and also heterogeneity for different categories of banks/firms that can be identified in the data as well as some explanatory power of balance sheet statistics in the case of the Japanese data set. Across all networks, the Negative Binomial model almost always outperforms all alternative models confirming its good performance as a model of economic count data in many previous applications.