Calibrating limits for large interbank exposures from a system-wide perspective

We examine the role of imposing tighter limits on interbank exposures in reducing contagion and aggregate losses. In our model contagion risk arises as a result of the individual idiosyncratic failure of each bank in the banking system. Following Guerrero-Gomez and Lopez-Gallo (2004), we use a sequential default algorithm that is useful for tracing the path of contagion from a trigger bank to other banks during several contagion rounds. We test different types of limits on inter-SIB (systematically important banks) exposures, SIB to non-SIB exposures, and non-SIB to all other banks; and we study three different assumptions about banks’ behavioural responses under a stricter regulatory lending regime. We also “stress test” all banks within the banking system and extend the analysis on the benefits of using tighter limits in a fragile banking system. Calibrating the model to Mexican banking sector data, this network model shows that tighter limits for inter-SIB exposures are a useful tool for reducing contagion risk. Moreover, we find that tighter limits may lead to an increase in contagion risk under specific allocation assumptions.