Research

After the Federal Reserve's creation, nonmember “shadow” banks (i) held less liquidity, (ii) borrowed more, increasingly from local partners, and (iii) relied on public liquidity passed through member banks, which made them more vulnerable.

Abstract

How does public liquidity provision reshape shadow banks’ portfolios and interbank networks? We study this question using new data from Virginia state-bank examination reports around the creation of the Federal Reserve in 1913. After the Fed’s creation, nonmember “shadow” banks held fewer liquid assets, borrowed more from other banks, and shifted correspondent relationships away from national financial centers toward local partners. We develop a model in which indirect access to public liquidity weakens the value of private liquidity insurance, explaining these portfolio and network changes. Consistent with this mechanism, we document that during the 1921 recession, Fed member banks passed Federal Reserve liquidity to nonmembers, especially through rural links. We then use the model to quantify the trade-off between public liquidity provision and regulation, and to study its implications for financial stability and investments.

Competing financial platforms overinvest in security while market shares are even, but as network effects consolidate the market, competition stops disciplining security, and past a tipping point the dominant platform underinvests in resiliency, leaving the system exposed to cyberattacks.

Abstract

We develop a theory of technological resiliency of financial system architecture. Financial platforms compete with services that play critical functions along various stages of financial trade, and make investments in technological resiliency. Network effects relax competition on security, which are exploited by cyber adversaries. Vulnerabilities evolve over time, but generically reach a tipping point at which technological resiliency is too low and creates technological drag on the financial system. We find support in tri-party repo settlement: the exit of a duopolist resulted in a significant drop in IT-related investment by the sole provider, even as peer firms ramp up investment.

The same friendships a surveillance state mines for information are what let citizens rise against it, so a government can divide and conquer by targeting an arbitrary group, citizens segregate in response, and strong civil liberties and civic values preserve social cohesion by committing the state to restraint.

Abstract

Governments use coercion to aggregate distributed information relevant to objectives such as the containment of regime-stability threats or the prosecution of terrorism. A cohesive social structure facilitates this task, as reliable information will often come from friends and acquaintances. But a cohesive citizenry can more easily exercise collective action to resist such intrusions. We present an equilibrium theory where this tension mediates the joint determination of social structure and civil liberties. Segregation and unequal treatment sustain each other as coordination failures: citizens segregate along the lines of an arbitrary trait when the government exercises unequal treatment as a function of the trait, and the government engages in unequal treatment when citizens segregate based on the trait. Civil liberties can serve as a commitment device that benefits both citizens and the government, particularly when information-aggregation technologies are accurate. We characterize when unequal treatment against a minority or a majority can be sustained, and how equilibrium social cohesiveness and civil liberties respond to surveillance technologies, shocks to threat perceptions or privacy preferences, or community norms such as codes of silence.

Insiders can game any fixed enforcement rule, so effective regulation requires ambiguity, and insiders respond by forming tor-periphery networks in which a small core of intermediaries relays most tips from tippers to tippees.

Abstract

How do insiders respond to regulatory oversight on the use of insider information? History suggests that they form more sophisticated networks to circumvent regulation. We develop a theory of the formation and regulation of insider information networks. We show that agents with sufficiently complex networks bypass any given regulatory environment. In response, regulators employ broad regulatory boundaries to combat gaming. Tighter regulation induces agents to migrate activity from existing social networks to a tor-periphery network, a novel core-periphery network topology with a layered core of agents specialized in specific roles along transmission chains. A small group of agents endogenously arise as intermediaries for the bulk of transmissions.

Threshold contagion in large networks sampled from a graphon closely tracks contagion in the graphon itself, which yields closed-form solutions to seeding problems and seeding policies that significantly outperform greedy or random seeding.

Abstract

The analysis of threshold contagion processes in large networks is challenging. While the lack of accurate network data is often a major obstacle, finding optimal interventions is computationally intractable even in well-measured large networks. To obviate these issues we consider threshold contagion over networks sampled from a graphon—a flexible stochastic network formation model—and show that in this case the contagion outcome can be predicted by only exploiting information about the graphon. To this end, we exploit a second interpretation of graphons as graph limits to formally define a threshold contagion process on a graphon for infinite populations. We then show that contagion in large but finite sampled networks is well approximated by graphon contagion. This convergence result suggests that one can design interventions for large sampled networks by first solving the equivalent problem for an infinite population interacting according to the limiting graphon. We show that, under suitable regularity assumptions, the latter is a tractable problem and we provide analytical characterizations for the extent of contagion and for optimal seeding policies in graphons with both finite and infinite agent types.

Extended abstract: EC’20

Difficulty adjustment rules substantially raise the mining power a longest-chain (51%) attack requires when block timestamps are verifiable, but offer far less protection when timestamps can be misreported.

Abstract

Various blockchain systems have been designed for dynamic networked systems. Due to the nature of the systems, the notion of “time” in such systems is somewhat subjective; hence, it is important to understand how the notion of time may impact these systems. This work focuses on an adversary who attacks a Proof-of-Work (POW) blockchain by selfishly constructing an alternative longest chain. We characterize optimal strategies employed by the adversary when a difficulty adjustment rule à la Bitcoin applies.

Full paper (arXiv)

Endogenous networks of ex-ante identical firms develop core-periphery structures, and improved fundamentals increase systemic tail risk because firms form more links that act as conduits of contagion.

Abstract

This paper introduces a model of endogenous network formation and systemic risk. In it, firms form joint ventures called ‘links’ which are subsequently subjected to either good or bad shocks. Bad shocks incentivize default. Links yield full benefits only if the counter-party 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, because the network formed depends on the correlation between shocks to links, an observer who misconceives the correlation will underestimate the probability of system-wide default by a factor of a half.

When network externalities originate from links rather than agents, disjoint cliques are stable and efficient under negative externalities, while efficient networks under positive externalities are “pineapples”: a large clique with a star attached.

Abstract

We propose a model of network formation where agents’ payoffs depend on the connected component they belong to in a way that is specific enough to be tractable yet general enough to accommodate a number of economically relevant settings. Among them are formation in the presence of contagion via links and collaboration with spillovers. A key feature of this setting is that the externalities stem from links rather than nodes. 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 a mix: pineapple networks which consist of one large clique and a star network appended to each other.

The network of bilateral relationships that facilitate liquidity sharing between banks is subject to a tipping point with respect to liquidity requirements, beyond which the network collapses.

Abstract

Optimal regulatory restrictions on banks have to solve a delicate balance. Tighter regulations reduce the likelihood of banks’ distress. Looser regulations foster the allocation of funds toward productive investments. With multiple banks, optimal regulation becomes even more challenging. Banks form partnerships in the interbank lending market in order to face liquidity needs and to meet investment possibilities. We show that the interbank network can suddenly collapse when regulations are pushed beyond a critical level, with a discontinuous increase in systemic risk as the cross-insurance of banks collapses.

A continuous and monotone preference over lotteries is constructed that satisfies negative certainty independence but violates betweenness, answering an open question from Dillenberger (2010).

Abstract

Dillenberger (2010) introduced the negative certainty independence (NCI) axiom, which captures the certainty effect phenomenon. He left open the question of whether there are continuous and monotone preference relations over simple lotteries that satisfy NCI but do not belong to the betweenness class of preferences considered by Chew (1989) and Dekel (1986). We answer this question in the affirmative.

Countries may fall into long-run poverty traps when agents discount the future at endogenous rates that depend on capital, even with strictly convex production technologies.

Abstract

This paper studies the dynamic implications of the endogenous rate of time preference depending on the stock of capital, in a one-sector growth model. The planner’s problem is presented and the optimal paths are characterized. We prove that there exists a critical value of initial stock, in the vicinity of which, small differences lead to permanent differences in the optimal path. Indeed, we show that a development trap can arise even under a strictly convex technology. In contrast with the early contributions that consider recursive preferences, the critical stock is not an unstable steady state so that if an economy starts at this stock, an indeterminacy will emerge. We also show that even under a convex–concave technology, the optimal path can exhibit global convergence to a unique stationary point. The multipliers system associated with an optimal path is proven to be the supporting price system of a competitive equilibrium under externality and detailed results concerning the properties of optimal (equilibrium) paths are provided. We show that the model exhibits globally monotone capital sequences yielding a richer set of potential dynamics than the classic model with exogenous discounting.

A confidence or conformal set can be read coherently as an ambiguity set only under conditions we characterize, and under that reading robust decisions converge to Bayesian ones as information accumulates.

Abstract

Confidence and conformal sets are used to inform decisions. To employ them, a decision maker must give it a probabilistic interpretation, and that interpretation determines an ambiguity set: the probability distributions over states she regards as possible. This paper characterizes when a proffered confidence/conformal set admits a coherent probabilistic interpretation, a property we call rationalizability. We then study decision making over a rationalizable confidence/conformal set. A common practice assigns zero probability to states outside the proffered set. This replaces the original coverage requirement with one that can become incompatible with additional probabilistic information. The rationalizable set, however, preserves the original guarantee and remains compatible with information refinements. As information accumulates and the ambiguity set shrinks toward a singleton, the associated robust decision rule converges to Bayesian expected-loss minimization. This consistency under information refinement is our normative justification for the coherent interpretation.

More central clearing does not guarantee less systemic risk: after the reforms, cycles among core banks persist while the periphery becomes more exposed to central counterparties, which are in turn more exposed to the core.

Abstract

Recent U.S. and European regulations promote centrally clearing derivatives to reduce complexity and systemic risk in the financial system. We argue that more clearing does not guarantee less systemic risk. We identify conditions under which the core clears less intensively than the periphery, which increases systemic risk by substituting multilateral netting for bilateral netting and making contagion less likely to start in the core but more likely to spread from the core. We study confidential derivatives regulatory data and find evidence of such clearing patterns. We further explore the implications of complexity and centrality within the financial system for stability.

Capital rules favoring central clearing push collateral-poor peripheral banks to clear but can leave well-collateralized core banks trading over the counter, so the contagion-prone exposure cycles in the core persist.

Abstract

Financial stability depends on the network of financial exposures. Even though its anatomy is usually taken as exogenous, it reacts not only to changes in the environment but also to changes in regulations introduced to tame financial fragility. We construct a model with heterogeneous banks that choose how much to insure through derivative contracts and whether to be exposed to a centralized (CCP) or bilateral (OTC) counterpart, weighing the collateral and transparency costs of these choices. By modeling the optimal decisions of atomistic members of finite banks, we use a network taking approach that bypasses strategic considerations and allows us to simultaneously capture optimal contracts and the endogenous network of financial exposures among banks. We characterize how the equilibrium network of financial exposures changes with capital requirement regulations, and how regulations may backfire if not taking this endogenous reaction into account.

Up to a threshold, more effective or widespread vaccination can raise infection rates by drawing more people to crowded central locations, a mechanism supported by U.S. Covid-19 vaccination and foot-traffic data.

Abstract

The January 2022 spike in COVID-19 infection rates in the U.S. was three times higher than the December 2020 spike despite widespread vaccination by January 2022 and minimal vaccination in December 2020. Moreover, infection rates continued to rise throughout 2021 even as vaccine distribution expanded and coverage increased. To explore this paradox, we develop a model in which agents choose their socialization patterns in the presence of an infectious disease and an imperfectly effective protective measure. As the protective measure becomes more effective or more widely adopted, up to a threshold, infection rates increase due to higher socialization rates, despite higher effectiveness and adoption rate of the protective measure. Superspreader agents such as individuals at central points of interest (e.g., schools, gyms, grocery stores) or those in highly connected roles (e.g., teachers, trainers, cashiers) facilitate the transmissions. We provide supporting evidence using U.S. foot traffic data (2021–2022) and historical COVID-19 vaccination and community transmission rates.

Anticipated interventions that mitigate contagion lead agents to form more interconnected and concentrated networks, which increases contagion and volatility and reduces welfare and resilience.

Abstract

I develop a novel framework for studying network formation with continuum populations. I use the framework to examine contagion and resilience in endogenous networks, with applications to misinformation, supply chains, financial contagion, and epidemics. I examine the equilibrium effects of policies that mitigate contagion externalities and find that interconnectedness and concentration increase in response to interventions. This general equilibrium response negates the benefits of interventions and creates a “network hazard.” Despite interventions that mitigate contagion ex post, contagion and volatility are exacerbated and welfare and resilience are reduced ex ante.

During the 1920–21 recession, Virginia member banks lent about 20% of their Federal Reserve discount-window borrowing to nonmember “shadow” banks, which helped stabilize banks facing heavy deposit outflows.

Abstract

During the 1920-1921 recession, the Richmond Fed provided liquidity to its member banks to prevent a banking crisis. Using newly digitized data on interbank borrowing and deposits for Virginia state banks, we analyze how the Richmond Fed’s liquidity provision affected the interactions between the funding role and the payment role of the interbank system and financial stability. We show that the Richmond Fed’s liquidity provision enabled members to lend discount window liquidity to nonmembers that experienced large deposit outflows and prevented the mass withdrawal of interbank deposits. Interestingly, the banks with interbank borrowing reduced interbank deposits placed in lending banks, implying that these correspondents provided liquidity to nonmembers through both interbank loans and deposits. Our study shows that understanding the interaction between different types of networks is important to promote the stability of the banking system.

People respond to social distancing by changing both how they work (in person or remotely) and whom they work with, which cushions output losses but widens inequality and may speed lasting adoption of remote work.

Abstract

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.

Anticipated bailouts make firms less concerned with their counterparties' counterparties, so networks concentrate around large firms, which raises systemic risk and welfare volatility even as average welfare rises.

Abstract

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 cannot 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 the risk-return dimension is mitigated by bailouts. Ex-ante regulations can induce discontinuous changes in the network.