The determinants of interbank contagion: do patterns matter?

The recent financial crisis highlighted that interconnectedness between banks has a crucial role, and can push the effects of bank defaults to extreme levels. The distress of one bank can compromise the solvency of its creditor banks, possibly inducing a more general crisis that can even deeply affect the real economy. Several studies have focused on the role of the interbank market in causing contagion in financial crises. As only data on interbank credits and debts aggregated at bank level are publicly available, whereas the whole matrix of interbank linkages would be needed in order to estimate systemic risk correctly, some approximation is needed. One common solution is to assume that banks maximize the dispersion of their interbank credits and debts, so that the interbank matrix is approximated by its maximum entropy realization. The aim of this paper is to test the influence of this approximation on simulations, and verifying if variations in the structure of the interbank matrix systematically change the magnitude of contagion. In order to do this, an algorithm was developed for generating interbank matrices with higher concentration, and, via a Monte Carlo simulation, a counterfactual test was realized comparing results obtained using the maximum entropy approximated matrix with those obtained from more concentrated matrices. Performing numerical experiments on samples of banks from four European countries, resulted in small changes in the point estimation, but variability and confidence interval for the estimates are deeply affected, in particular in banking systems when contagion effects are more important.JRC.G.1-Financial and Economic Analysi