A theory of network formation and contagion is presented and applied to various models of financial and economic contagion. Then the impact of bailouts are studied. Time-consistent bailouts eliminate second-order counterparty risk as a by-product, which is called “network hazard”. Agents become less concerned with the counterparties of their counterparties. Network hazard makes some agents too-big-to-fail and makes the network “more core-periphery”. A larger part of the economy becomes exposed to the core, which increases volatility via the solvency of the core. It is shown that network hazard is a novel force distinct from moral hazard. Results are historically relevant to the establishment of the FED and pyramiding of reserves. The general theory presented shows that strongly stable networks exist and are almost unique in a model of threshold contagion if -an infected node’s payoff does not depend on the number of its infected neighbors- and -an uninfected node’s payoff decreases in the number of its infected neighbors-.
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.