OFRwp0009_GlassermanYoung_HowLikelyContagionFinancialNetworks

The original shortfall in payments can cascade

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: to pay its creditors in full, who may be unable to pay their creditors in full, and so forth. The original shortfall in payments can cascade through the system, causing more and more banks to default through a domino effect. The Eisenberg-Noe framework shows how to compute a set of payments that clear the network, and it identifies which nodes default as a result of an initial shock to the system. The number and magnitude of such defaults depend on the topological structure of the network, and there is now a substantial literature characterizing those structures that tend to propagate default or alternatively that tend to dampen it (Gai and Kapadia 2010, Gai, Haldane, and Kapadia 2011, Haldane and May, 2011, Acemoglu, Ozdaglar, and Tahbaz-Salehi 2013, and Elliott, Golub, and Jackson 2013). Much of this literature proceeds by examining the effects of fixed shocks applied to particular nodes rather than fully specifying the distribution that generates the shocks. In this paper we analyze the probability of contagion and the expected losses generated by contagion when the joint distribution of shocks is given. We then apply the framework to answer the following questions about the impact of network effects. First, how likely is it that a given set of banks will default due to contagion from another node, as compared to the likelihood that they default from direct shocks to their own assets? Second, how much does the network increase the probability and magnitude of losses compared to a situation where there are no connections? To compare systems with and without interconnections, we proceed as follows. First, we define our nodes to be financial institutions that borrow and lend on a significant scale, which together with their obligations to one another constitute the financial network. In addition, such institutions borrow and lend to the nonfinancial sector, which is composed of investors, households, and nonfinancial firms. We compare this system to one without connections that is constructed as follows. We remove all of the obligations between the financial nodes while keeping their links with the nonfinancial sector unchanged. We also keep node equity values as before by creating, for each node, a fictitious outside asset (or liability) whose value equals the net value of the connections at that node that were removed. We then apply the same shock distributions to both systems, with the shocks to real assets originating in the external sector and the fictitious assets (if any) assumed to be impervious to shocks. We can ascertain how much the network connections contribute to increased defaults and losses by comparing the outcomes in the two systems. One might suppose that the comparison hinges on what shock distribution we use, but this turns out not to be the case: we show how to compute general bounds on the increased losses attributable to network contagion that hold under a wide variety of distributions. The bounds also hold whether the 2 shocks are independent or positively assoc...
View Full Document

Ask a homework question - tutors are online