Screening with Network Externalities

Shi, Fanqi; Xing, Yiqing

doi:10.2139/ssrn.3286427

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…In a contemporaneous paper, Shi and Xing (2018) study screening with the same demand specification as our application to network goods and assume a continuum type space. Consequently, the optimal allocation is constant in influence and the solution is one-dimensional.…”

Section: Literaturementioning

confidence: 99%

Screening while controlling an externality

Ostrizek

Sartori

2023

Games and Economic Behavior

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Section: Literaturementioning

confidence: 99%

Screening while controlling an externality

Ostrizek

Sartori

2023

Games and Economic Behavior

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“…The seller can observe past purchasing decisions only of the group of observable agents and can try to deduce from these observations information on influence patterns. Finally, in a paper which shares our motivation about the planner's incentives to elicit information about the network, Shi and Xing [13] consider a model where buyers draw their in and out-degrees independently from a common distribution. They characterize the optimal contracts in the framework of random graphs.…”

Section: Introductionmentioning

confidence: 99%

Targeting in social networks with anonymized information

Bloch¹,

Shabayek²

2020

Preprint

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This paper studies whether a planner who only has information about the network topology can discriminate among agents according to their network position. The planner proposes a simple menu of contracts, one for each location, in order to maximize total welfare, and agents choose among the menu. This mechanism is immune to deviations by single agents, and to deviations by groups of agents of sizes 2, 3 and 4 if side-payments are ruled out. However, if compensations are allowed, groups of agents may have an incentive to jointly deviate from the optimal contract in order to exploit other agents. We identify network topologies for which the optimal contract is group incentive compatible with transfers: undirected networks and regular oriented trees, and network topologies for which the planner must assign uniform quantities: single root and nested neighborhoods directed networks.

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Screening while Controlling an Externality

Ostrizek

Sartori

2021

SSRN Journal

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We propose a tractable framework to introduce externalities into a monopolist screening model. Agents differ both in their payoff type and their influence, i.e. how strongly their action affects the aggregate externality. Applications range from non-linear pricing of a network good, to taxation or subsidization of industries that produce externalities (e.g. pollution and human capital formation). When both dimensions are unobserved (full screening) the optimal allocation satisfies lexicographic monotonicity: within a payoff-type, the monopolist optimally tilts the allocation towards influential agents to increase the externality, while standard IC drives monotonicity across payoff-types. We characterize the solution through a two-step ironing procedure that addresses the nonmonotonicity in virtual values arising from the countervailing impact of payoff-types and influence. The allocation is inefficient if and only if the payoff-type is unobservable. Only influence is observable, equilibrium utility can vary across the latter as it is used as a signal of the payoff-type. We provide sufficient conditions for (expected) rents from influence to emerge.

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Screening with Network Externalities

Cited by 3 publications

References 24 publications

Screening while controlling an externality

Screening while controlling an externality

Targeting in social networks with anonymized information

Screening while Controlling an Externality

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