Information Acquisition in Matching Markets: The Role of Price Discovery

Immorlica, Nicole; Leshno, Jacob D.; Lo, Irene; Lucier, Brendan

doi:10.2139/ssrn.3705049

Cited by 22 publications

(22 citation statements)

References 55 publications

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“…Our main insight for this stage of the proof lies in the third step, where we leverage structural properties of the agents' decision problem to show that the optimal stationary equilibrium in each submarket produces at least half the first-best welfare of that submarket. 16 These steps, together with Proposition 4.3, prove our approximation result Theorem 4.1.…”

Section: Designing An Approximately Optimal Equilibriummentioning

confidence: 56%

“…Taking a communication complexity approach, Gonczarowski et al [13] and Ashlagi et al [6] establish bounds on the the amount of communication, measured by the number of bits, needed to find a stable match in markets with private preferences. The recent work of Immorlica et al [16] focuses on a setting where learning preferences is costly and show how costly information acquisition impacts an agent's preference. Further, a few recent papers, such as Liu et al [20], use the multi-armed bandit framework to model the process of learning preferences as an online learning problem and develop efficient learning algorithms.…”

Section: Search and Matchingmentioning

confidence: 99%

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Designing Approximately Optimal Search on Matching Platforms

Immorlica

Lucier

Manshadi

et al. 2021

Preprint

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We study the design of a decentralized two-sided matching market in which agents' search is guided by the platform. There are finitely many agent types, each with (potentially random) preferences drawn from known type-specific distributions. Equipped with such distributional knowledge, the platform guides the search process by determining the meeting rate between each pair of types from the two sides. Focusing on symmetric pairwise preferences in a continuum model, we first characterize the unique stationary equilibrium that arises given a feasible set of meeting rates. We then introduce the platform's optimal directed search problem, which involves optimizing meeting rates to maximize equilibrium social welfare. We first show that incentive issues arising from congestion and cannibalization makes the design problem fairly intricate.Nonetheless, we develop an efficiently computable solution whose corresponding equilibrium achieves at least 1/4 of the optimal social welfare. Our directed search design is simple and easy-to-implement, as its corresponding bipartite graph consists of disjoint stars. Furthermore, our solution implies that the platform can substantially limit choice and yet induce an equilibrium with an approximately optimal welfare. Finally, we show that approximation is the likely best we can hope by establishing that the problem of designing optimal directed search is NP-hard to approximate beyond a certain constant factor.

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Section: Designing An Approximately Optimal Equilibriummentioning

confidence: 56%

Section: Search and Matchingmentioning

confidence: 99%

Designing Approximately Optimal Search on Matching Platforms

Immorlica

Lucier

Manshadi

et al. 2021

Preprint

Self Cite

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“…Our setting does not have pre-determined priorities. When students do have such priorities, e.g., priorities determined by siblings' school attendance or test score, they may have incentives to acquire information on others' preferences and priorities under DA as shown in Grenet et al (2019) and Immorlica et al (2020). The intuition is that others' preferences and priorities help a student assess the probability of being accepted by each school and that a student does not need to learn about schools that will never accept her.…”

Section: Literature Reviewmentioning

confidence: 99%

Information acquisition and provision in school choice: a theoretical investigation

Chen

2021

Econ Theory

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When participating in school choice, students may incur information acquisition costs to learn about school quality. This paper investigates how two popular school choice mechanisms, the (Boston) Immediate Acceptance and the Deferred Acceptance, incentivize students’ information acquisition. Specifically, we show that only the Immediate Acceptance mechanism incentivizes students to learn their own cardinal and others’ preferences. We demonstrate that information acquisition costs affect the efficiency of each mechanism and the welfare ranking between the two. In the case where everyone has the same ordinal preferences, we evaluate the welfare effects of various information provision policies by education authorities.

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“…identify optimal truncation strategies in a large class of markets. We illustrate cases in which truncation strategies are sub-optimal.3Immorlica et al (2020) examine how the design of school-choice systems affects information acquisition Fernandez (2020). shows that DA only supports stable outcomes when agents avoid regret.…”

mentioning

confidence: 99%

“…Recent literature has identified various conditions under which large markets entail small cores (see, e.g.,Immorlica andMahdian, 2005 andAshlagi et al, 2017). Our analysis speaks to such settings.8 These include α-reducibility(Clark, 2006), the co-ranking condition(Legros and Newman, 2010), the universality condition(Holzman and Samet, 2014), the aligned preferences condition(Ferdowsian, Niederle, and Yariv, 2021), and oriented preferences(Reny, 2021).…”

mentioning

confidence: 99%