Trading Networks With Frictions

Fleiner, Tamás; Jagadeesan, Ravi; Jankó, Zsuzsanna; Teytelboym, Alexander

doi:10.3982/ecta14159

Cited by 39 publications

(23 citation statements)

References 39 publications

(169 reference statements)

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“…The generality of our model allows for a wide variety of special cases. For example, following the circulation of our original draft, Fleiner et al (2019) showed that stable outcomes are guaranteed to exist in trading network settings with income effects under full substitutability, so long as there are no frictions 4 . More recently, Andersson et al (forthcoming) developed a model of time banks in which agents exchange discrete units of time performing a particular task, and Manjunath and Westkamp (2019) considered the exchange of indivisible shifts among a group of workers.…”

Section: Introductionmentioning

confidence: 99%

“…99 If one dispenses with supply chain structure without assuming that prices can vary freely, then stable outcomes may not exist (Hatfield and Kominers 2012). Fleiner et al (2018) introduced a weaker concept, trail stability , for settings without supply chain structure. As Fleiner et al (2018) explained (emphasis in original): “In a trail‐stable outcome, no agent wants to drop his contracts and there exists no sequence of consecutive bilateral contracts […] such that any intermediate agent who is offered a downstream (upstream) contract […] wants to choose it alongside the subsequent upstream (downstream) contract […].…”

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confidence: 99%

“…Fleiner et al (2018) introduced a weaker concept, trail stability , for settings without supply chain structure. As Fleiner et al (2018) explained (emphasis in original): “In a trail‐stable outcome, no agent wants to drop his contracts and there exists no sequence of consecutive bilateral contracts […] such that any intermediate agent who is offered a downstream (upstream) contract […] wants to choose it alongside the subsequent upstream (downstream) contract […]. Importantly, [trail stability] require[s] that the first (final) agent wants to unilaterally offer (accept) the first (final) contract […].” Fleiner et al (2018) showed that trail‐stable outcomes are guaranteed to exist under full substitutability (in arbitrary trading networks).…”

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confidence: 99%

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Chain stability in trading networks

Hatfield

Kominers

Nichifor

et al. 2021

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In a general model of trading networks with bilateral contracts, we propose a suitably adapted chain stability concept that plays the same role as pairwise stability in two‐sided settings. We show that chain stability is equivalent to stability if all agents' preferences are jointly fully substitutable and satisfy the Laws of Aggregate Supply and Demand. In the special case of trading networks with transferable utility, an outcome is consistent with competitive equilibrium if and only if it is chain stable.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Chain stability in trading networks

Hatfield

Kominers

Nichifor

et al. 2021

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“…Hatfield, Kominers, Nichifor, Ostrovsky, and Westkamp (2013) obtain an equivalence result for trading networks where agents have quasi-linear utility functions. Fleiner, Jagadeesan, Jankó, and Teytelboym (2019) further generalize the analysis to cover general utility functions. They find an equivalence between competitive equilibrium and a cooperative solution concept called trail-stability.…”

Section: Introductionmentioning

confidence: 99%

Expectational Equilibria in Many-to-one Matching Models with Contracts - A Reformulation of Competitive Equilibrium

Herings

2020

SSRN Journal

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People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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“…Stable flows in the more general setting were defined by Fleiner [13], who reduced the stable flow problem to the stable allocation problem. Since then, the stable flow problem has been investigated in several papers [15,16,24,29]. Recently, stable flows have been used to derive conflict-free routings in multi-layer graphs [35].…”

Section: Introductionmentioning

confidence: 99%

New and Simple Algorithms for Stable Flow Problems

Cseh

Matuschke

2019

Algorithmica

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Stable flows generalize the well-known concept of stable matchings to markets in which transactions may involve several agents, forwarding flow from one to another. An instance of the problem consists of a capacitated directed network in which vertices express their preferences over their incident edges. A network flow is stable if there is no group of vertices that all could benefit from rerouting the flow along a walk. Fleiner [13] established that a stable flow always exists by reducing it to the stable allocation problem. We present an augmenting path algorithm for computing a stable flow, the first algorithm that achieves polynomial running time for this problem without using stable allocations as a blackbox subroutine. We further consider the problem of finding a stable flow such that the flow value on every edge is within a given interval. For this problem, we present an elegant graph transformation and based on this, we devise a simple and fast algorithm, which also can be used to find a solution to the stable marriage problem with forced and forbidden edges. Finally, we study the stable multicommodity flow model introduced by Király and Pap [27]. The original model is highly involved and allows for commodity-dependent preference lists at the vertices and commodityspecific edge capacities. We present several graph-based reductions that show equivalence to a significantly simpler model. We further show that it is NP-complete to decide whether an integral solution exists.it is without loss of generality to assume that no commodity-specific preferences at the vertices and no commodity-specific capacities on the edges exist. Then, we reduce 3-sat to the integral stable multicommodity flow problem and show that it is NP-complete to decide whether an integral solution exists even if the network in the input has integral capacities only. PreliminariesA network (D, c) consists of a directed graph D = (V, E) and a capacity function c : E → R ≥0 on its edges. The vertex set of D has two distinct elements, also called terminal vertices: a source s, which has outgoing edges only and a sink t, which has incoming edges only. Besides differentiating between the source and the sink, we will assume that D does not contain loops or parallel edges, and every vertex v ∈ V \ {s, t} has both incoming and outgoing edges. These three assumptions are without loss of generality and only for notational convenience. We denote the set of edges leaving a vertex v by δ + (v) and the set of edges running to v by δ − (v).Definition 1 (flow). Function f : E → R ≥0 is a flow if it fulfills both of the following requirements:A stable flow instance is a triple I = (D, c, r). It comprises a network (D, c) and r, a ranking function that induces for each vertex an ordering of their incident edges. Each non-terminal vertex ranks its incoming and also its outgoing edges strictly and separately. Formally, r = (r v ) v∈V \{s,t} , contains an injective functionWe say that v prefers edge e to e ′ if r v (e) < r v (e ′ ). Terminals do not rank their e...

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Trading Networks With Frictions

Cited by 39 publications

References 39 publications

Chain stability in trading networks

Chain stability in trading networks

Expectational Equilibria in Many-to-one Matching Models with Contracts - A Reformulation of Competitive Equilibrium

New and Simple Algorithms for Stable Flow Problems

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