Research

We study a setting in which multiple agents (e.g. policymakers) play a dynamic coordination game, each having an opportunity to take a mutually beneficial action at a separate random time. A principal (e.g. a lobby or NGO), whose interests are diverging from those of the policymakers and who is endowed with a limited budget, is given opportunities, at random times, to dissuade the agents from coordinating by taking costly punitive actions against them. We show that the reaction speed of the principal is more important than the size of her budget to devise an effective punishment strategy. Moreover, recalling the order in which the agents took their actions can allow the principal to design a strategy that totally prevents the agents from coordinating, even with a trivially small budget and irrespectively of the intensity of the agents' activity. This brings a new perspective on the debate as to whether and how lobbies' funding resources should be regulated.

Complex organizations accomplish tasks through many steps of collaboration among workers. Corporate culture supports collaborations by establishing norms and reducing misunderstandings. Because a strong corporate culture relies on costly, voluntary investments by many workers, we model it as an organizational public good, subject to standard free-riding problems, which become severe in large organizations. Our main finding is that voluntary contributions to culture can nevertheless be sustained, because an organization’s equilibrium productivity is endogenously highly sensitive to individual contributions. However, the completion of complex tasks is then necessarily fragile to small shocks that damage the organization’s culture.

This article proposes a dynamic model to examine the structure of "€œsimple"€ relational contracts, obeying realistic properties that can be easily understood and audited by both parties. In such relationships, the need to offer each supplier a large enough share of future business to deter cheating limits the number of relationships a buyer can sustain. Trade is thus restricted to durable relationships, a form of social capital. Nevertheless, exogenous stochastic shocks sometimes prevent suppliers from fulfilling their promises and relationships are constantly dissolving and later renewed. Moreover, the coming of a crisis, where stochastic shocks are more probable, can lead to the quick rupture of some relationships as there is less expected future business to incentivize all suppliers. New relationships can later be formed, but this takes time due to search frictions. This suggests new connections between the theory of relational contracting and the macroeconomic analysis of recessions.

Successive decentralized policy makers must decide whether to implement a public policy aimed at improving the performance distribution of future generations of a targeted group. Employers do not observe district by district whether workers benefited from the policy, but take into account that possibility when deciding on a wage. Workers thus receive wages corresponding to their expected performance and suffer a feeling of injustice when getting less than their actual performance. We find that welfare-maximizing policy makers choose to implement the policy perpetually, despite the resulting feeling of injustice that eventually dominates the anticipated benefits to the targeted group’s performance. This contrasts with the first-best scenario, which requires the policy to be temporary.

We study a model of networked production of complex goods in a large economy. Firms source each of several essential inputs through relationships with other firms. Because relationships may fail, firms can invest in multisourcing to insure themselves against idiosyncratic risk. Aggregate production features precipices: small shocks to the costs of maintaining relationships can lead to discontinuous changes in aggregate output. We discuss several applications. First, at critical junctures, small improvements in institutional quality can qualitatively change an economy's production possibilities, enabling it to build more complex and valuable goods. Second, when firm entry into production is endogenous, parts of the economy tend naturally toward a precipice, becoming maximally fragile. Small institutional shocks can cause severe disruptions in these parts of the economy, and trigger new sorts of domino effects that propagate the shock.

When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when agents are connected by a network and a monopolist seller chooses a policy to maximize profits. Consumers with low degree (few friends) have incentives to adopt early, while consumers with high degree (many friends) have incentives to free ride. The seller can induce high degree consumers to adopt early by offering referral incentives - rewards to early adopters whose friends buy in the second period. Referral incentives thus lead to a `double-threshold strategy' by which low and high-degree agents adopt the product early while middle-degree agents wait. We show that referral incentives are optimal on certain networks while intertemporal price discrimination (i.e., a first-period price discount) is optimal on others.

We study the incentives that agents have to invest in costly protection against contagious random attacks in networked systems. Applications include vaccination, computer security and airport security. Agents are connected through a network and can fail either intrinsically or as a result of the failure of a subset of their neighbors. We characterize the equilibrium based on an agent's failure probability and derive conditions under which equilibrium strategies are monotone in degree (i.e. in how connected an agent is on the network). We show that different kinds of applications (e.g. vaccination, malware, airport security) lead to very different equilibrium patterns of investments in protection, with important welfare and risk implications. Our equilibrium concept is flexible enough to allow for comparative statics in terms of network properties and we show that it is also robust to the introduction of global externalities (e.g. price feedback, congestion).

When banks extend loans to each other, they generate a negative externality in the form of systemic risk: They create a network of interbank exposures by which they expose other banks to potential insolvency cascades. In this paper, we show how a regulator can use information about the financial network to devise a transaction-specific tax based on a network centrality measure that captures systemic importance. Since different transactions have different impact on creating systemic risk, they are taxed differently. We call this tax a Systemic Risk Tax (SRT). We use an equilibrium concept inspired by the matching markets literature to show that this SRT induces a unique equilibrium matching of lenders and borrowers that is systemic-risk efficient, i.e. it minimizes systemic risk given a certain transaction volume. This allows the regulator to effectively `rewire' the equilibrium interbank network so as to make it more resilient to insolvency cascades, without sacrificing transaction volume. On the other hand, we show that without this SRT multiple equilibrium matchings can exist and are generally inefficient.  Moreover, we show that a standard financial transaction tax (e.g. a Tobin-like tax) has no impact on reshaping the equilibrium financial network because it taxes all transactions indiscriminately. A Tobin-like tax is indeed shown to have a limited effect on reducing systemic risk while it decreases transaction volume.

We study insolvency cascades in an interbank system when banks are allowed to insure their interbank loans with credit default swaps (CDS) sold by other banks. Since a CDS has the effect of transferring the default risk from one bank to an other, we show that a CDS market can be designed to rewire the network of interbank exposures in a way that makes it more resilient to insolvency cascades: A regulator can use information about the topology of the interbank network to devise a systemic surcharge that is added to the CDS spread. CDS contracts are thus effectively taxed according to how much they contribute to increasing systemic risk. On the other hand, a CDS contract that decreases systemic risk remains untaxed. We simulate this regulated CDS market using an agent-based model (CRISIS macro-financial model) and we demonstrate that it leads to an interbank system that is more resilient to insolvency cascades. 

We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with the case of a single layer network that is an aggregated representation of the two layers. We find that systemic risk in the two-layer network is smaller than in the aggregated one only if the coupling strength between the two layers is small. Above a critical coupling strength, systemic risk is increased because of the mutual amplification of cascades in the two layers. We even observe sharp phase transitions in the cascade size that are less pronounced on the aggregated layer. Our insights can be applied to a scenario where firms decide whether they want to split their business into a less risky core business and a more risky subsidiary business. In most cases, this may lead to a drastic increase of systemic risk, which is underestimated in an aggregated approach.