Dealing with pandemics, such as the recent COVID-19 virus, has highlighted the critical role of social distancing to avoid contagion and deaths. New technologies that allow replacing in-person for at-distance activities have blurred the mapping between social and economic distancing. In this paper we model how individuals react to social distancing guidelines by changing their network of economic relations, affecting total output, wealth inequality, and long-term growth.
Central banks provide public liquidity (through lending facilities and promises of bailouts) with the intent to stabilize the financial system. Even though this provision is restricted to member (regulated) banks, an interbank system can provide indirect access to nonmember (shadow) banks. We construct a model to understand how a banking network may change in the presence of central bank interventions and how those changes affect financial fragility. We provide evidence showing that the introduction of the Fed’s liquidity provision in 1913 increased systemic risk through three channels; it reduced aggregate liquidity, created a new source of financial contagion, and crowded out private insurance for smoothing cross-regional liquidity shocks (manifested through the geographic concentration of networks).
This paper studies a model of firms with endogenous bilateral exposures and government bailouts. It is shown that the anticipation of bailouts makes firms less concerned with the counterparty choices of their counterparties. This “network hazard” gives rise to large central firms. Bailouts can mitigate contagion but they can not restore output losses. Consequently, idiosyncratic bad shocks to large central firms generate large welfare losses. As such, bailouts create welfare volatility and systemic risk. Surprisingly, moral hazard on risk-return dimension is mitigated by bailouts. Ex-ante regulations can induce discontinuous changes in the network.
We consider a threshold contagion process over networks sampled from a graphon, which we interpret as a stochastic network formation model. We investigate whether the contagion outcome in the sampled networks can be predicted by only exploiting information about the graphon. To do so, we formally define a threshold contagion process on a graphon. Our main results show that contagion in large but finite sampled networks is well approximated by contagion in a graphon. We illustrate our results by providing analytical characterizations for the extent of contagion and for optimal seeding policies in graphons with finite and with infinite agent types.
Governments rely on a variety of forms of coercion to aggregate distributed information relevant to governmental objectives –from the prosecution of regime stability threats to terrorism or epidemics–. To do so, they exploit the existing social structure, as reliable information will often come from friends and acquaintances. Civil liberties, in turn, restrict the government’s ability to exercise such coercion. We present an equilibrium theory of the joint determination of social structure and civil liberties. The depth of civil liberties shapes citizens’ decisions on how intensely and with whom to socialize. Features of the social structure such as its cohesiveness and the extent of segregation, in turn, shape the government’s willingness to enforce civil liberties protections such as search and seizure restrictions, standards of proof, and equal treatment under the law. We show that the relationship between civil liberties and social structure is mediated by a commitment problem by the government, and that this commitment problem is in turn mediated by the strength of civil society. We also show that segregation and unequal treatment sustain each other, characterize when unequal treatment against a minority or a majority can be sustained, and how equilibrium social cohesiveness and civil liberties respond to the arrival of widespread surveillance technologies, shocks to collective perceptions about the likelihood of threats or the importance of privacy, or to community norms such as codes of silence.
We study a model of network externalities transmitted over links wherein the externalities stem from links themselves rather than nodes. For example, bilateral investments can fail and trigger cascading defaults of firms. Joint research projects can succeed and innovations can be diffused over the network. We characterize stable and efficient networks. Under negative externalities, disjoint cliques are stable and efficient. Under positive externalities complete networks and star networks are stable. Efficient networks feature are a mix: pineapple networks which consist of one large clique and a star network appended to each other.
How do insiders respond to regulatory oversight? History suggests that they form sophisticated networks to share information and circumvent regulation. We develop a theory of the formation and regulation of information transmission networks. We show that agents with sufficiently complex networks bypass any given regulatory environment. In response, regulators employ broad regulatory boundaries to combat gaming, giving rise to regulatory ambiguity. Tighter regulation induces agents to migrate transmission activity from existing social networks to a core-periphery insider network. A small group of agents endogenously arise as intermediaries for the bulk of information. We provide centrality measures that identify intermediaries.
This paper introduces a simple model of endogenous network formation and systemic risk. In the model, firms form joint ventures called ‘links’ which are subsequently subjected to shocks that are either good or bad. Bad shocks incentivize default. Links yield full benefits only if the counterparty does not subsequently default on the project. Accordingly, defaults triggered by bad shocks render firms insolvent and defaults propagate via links. The model yields three insights. First, stable networks with ex-ante identical agents exhibit a core-periphery structure. Second, an increase in the probability of good shocks increases systemic risk. Third, the network formed critically depends on the correlation between shocks to links. As a consequence, an observer who misconceives the correlation will significantly underestimate the probability of systemwide default.