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CURRENT RESEARCH

PAPERS

Networked Markets and Relational Contracts

joint with Matthew L. Elliott and Ben Golub

In preparation         Preliminary draft

Abstract: We consider a simple model of trade between organizations and their suppliers in which suppliers can act opportunistically – for example, not delivering goods as promised after payment has been made. Motivated by evidence from the sociology literature, we seek to explore the extent to which trust can be built between parties to overcome these problems. We do so by taking a relational contracting approach, and considering the repeated interactions of organizations (principals) with their suppliers (agents). A crucial feature of the interactions we wish to capture is that while the value of potential future trade (and the possibility of its withdrawal) makes promise-keeping compatible with suppliers’ interests, this in turn limits the number of relationships each organization can sustain. Intuitively, a principal must promise to trade sufficiently frequently in the future with an agent to incentivize the agent not to defect. As a consequence, the market naturally becomes networked – as opposed to “open” or “anonymous” – with each organization having some stable trading partners. We then propose studying how these equilibrium network structures affect allocative efficiency, and how they respond to shocks. Our preliminary results suggest interesting new effects. When shocks hit a networked market, making it impossible for some suppliers to meet their commitments, a destruction of social capital occurs and restoring it takes time. Indeed, principals are forced to terminate relationships with some agents in order to maintain incentive compatibility. Maintaining incentive compatibility also implies prioritizing the remaining relationships, which thus delays the rebuilding of terminated relationships. This creates a novel source of persistence for shocks. It also suggests new connections between the theory of relational contracting, on the one hand, and the macroeconomic analysis of recessions, on the other.

 

Complex and Fragile Production Networks   

joint with Matthew L. Elliott and Ben Golub

In preparation 

Pricing and Referrals in Diffusion on Networks    

Matt V. Leduc, Matthew O. Jackson and Ramesh Johari

In Games and Economic Behavior (2017)

paper:     Published Version                       SSRN              arXiv                                         In the news

Abstract: 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.

Strategic Investment in Protection in Networked Systems   

Matt V. Leduc and Ruslan Momot

In Network Science (2017)

paper:     Published Version (Open Access)                    SSRN               arXiv                      Slides

Abstract: 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).

Incentivizing Resilience in Financial Networks   

Matt V. Leduc and Stefan Thurner 

In Journal of Economic Dynamics and Control  (2017)

paper:     Published Version                       SSRN               arXiv                                         In the news

Abstract: 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.

Systemic Risk Management in Financial Networks with Credit Default Swaps  

Matt V. Leduc, Sebastian Poledna and Stefan Thurner

In Journal of Network Theory in Finance  (2017)

paper:       Published Version                      SSRN                 arXiv                                     In the news

Abstract: 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.

Systemic Risk in Multiplex Networks with Asymmetric Coupling and Threshold Feedback  

Rebekka Burkholz, Matt V. Leduc, Antonios Garas and Frank Schweitzer

In Physica D: Nonlinear Phenomena (2016)

paper:      Published Version                      arXiv

Abstract: 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. 

Mean-Field Models in Network Game Theory

Matt V. Leduc

Thesis, Stanford University  (PDF Version)

CONFERENCES AND WORKSHOPS 

Dynamic Market Relationships: Theory and Empirics. Elliott, M., Golub, B. and Leduc, M.V. Workshop on Dynamic Models of Interactions. Paris School of Economics, Paris,  France. August  2018.

Networked Markets and Relational Contracts. Elliott, M., Golub, B. and Leduc, M.V. 13th Conference on Web and Internet Economics WINE 2017. Bangalore, India. Decembrer 2017.

Dynamic Pricing, Referrals and Social Networks. Leduc, M.V., Jackson, M.O., Johari, R. 22^nd Coalition Network Theory Workshop. Glasgow, UK. May 2017.

Pricing and Referrals in Diffusion on Networks. Leduc, M.V., Jackson, M.O., Johari, R. Third Annual Conference on Network Science and Economics. St. Louis, USA. April 2017.

Matching and Resilience in Financial Networks. Leduc, M.V. and Thurner, S. 7th Annual Financial Market Liquidity Conference. Budapest, Hungary. November 2016.

Incentivizing Resilience in Financial Networks. Leduc, M.V. and Thurner, S. Financial Risk and Network Theory Conference 2016. Cambridge University, UK. September 2016.

Systemic Risk in Multiplex Networks with Asymmetric Coupling and Threshold Feedback. Burkholz, R., Leduc, M.V., Garas, A. and Schweitzer, F. 2016 Conference on Complex Systems CCS 2016. Amsterdam, The Netherlands. September 2016.

Systemic Risk Management in Financial Networks with Credit Default Swaps. Leduc, M.V., Poledna, S. and Thurner, S. NetSci-X 2016. Wroclaw, Poland. January 2016.

Strategic Investment in Protection in Networked Systems. Leduc, M.V. and Momot, R. Web and Internet Economics: 11th International Conference, WINE 2015. Amsterdam, The Netherlands. December 2015.

A Dynamic Network Game for the Adoption of New Technologies. Leduc, M.V. Fifteenth ACM Conference on Economics and Computation – EC ’14. Stanford, USA. June 2014.