This paper characterizes strongly stable networks under general threshold contagion. Among other applications, the theory is applied to interbank lending and financial contagion wherein a government can intervene to stop contagion. In the absence of intervention, banks form disjoined clusters to minimize contagion. In the presence of intervention, banks become less concerned with the counterparties of their counterparties, which we dub network hazard. Network hazard allows some banks to become systemically important and gives the network a core-periphery structure. The counterparty risk of a large part of the economy becomes correlated through the core banks’ solvency. Core banks serve as a buffer against contagion when solvent and an amplifier of contagion when insolvent. As such, bailouts create welfare volatility and increase systemic risk via network hazard. It is shown that network hazard is a novel force distinct from moral hazard. Results are historically relevant to the pyramiding of reserves and the establishment of the Federal Reserve.
This paper introduces a model of endogenous network formation and systemic risk. In the model a link represents a trading opportunity that yields benefits only if the counterparty does not subsequently default. After links are formed, they are subjected to exogenous shocks that are either good or bad. Bad shocks reduce returns from links and incentivize default. Good shocks, the reverse. Defaults triggered by bad shocks might propagate via links. The model yields three insights. First, a higher probability of good shocks generates a higher probability of system wide default because increased interconnectedness in the network offsets the effect of better fundamentals. Second, the network formed critically depends on the correlation between shocks to the links. As a consequence, an outside observer who misconceives the correlation structure of shocks, upon observing a highly interconnected network, will underestimate the probability of system wide default. Third, when the risk of contagion is high, the networks formed in the model are utilitarian efficient.