Matching to Produce Information

Kambhampati, Ashwin; Segura-Rodríguez, Carlos Luis; Shao, Peng

doi:10.2139/ssrn.3113594

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…Liang, Mu, and Syrgkanis (2017) study information acquisition patterns by two agents, a myopic one and a fully rational one, when the agents can decide sequentially which signals to acquire from a set of correlated signals that identify the state. Kambhampati, Segura-Rodriguez, and Shao (2018) study the inefficiency patterns that can arise in a stable matching, when individuals can decide with whom to match and how many signals to acquire from a correlated information structure after they are matched.…”

Section: Related Literaturementioning

confidence: 99%

Higher Order Information Complementarities and Polarization

Segura-Rodríguez¹

2019

SSRN Journal

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I study endogenous network formation in an environment in which individuals want to forecast a stochastic state and it is costly for them to communicate with others to exchange some exogenously observed information. Due to the existence of information complementarities, individuals' preferences for networks in which they have multiple neighbors cannot be characterized by a linear ranking of the pairwise correlations between their signals. Instead, these complementarities generate a counterintuitive result: for a fixed number of individuals, information structures exist in which all signals are conditionally positively correlated, and these are preferred to a structure in which all signals are conditionally independent. Therefore, it may be that the only strongly stable network consists of two cliques with signals that are highly positively correlated within each clique that generate different beliefs across cliques, even when there are opportunities to exchange information with individuals sharing less correlated signals. Thus, this model exemplifies how homophily and belief polarization can coexist in a rational environment.

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Section: Related Literaturementioning

confidence: 99%

Higher Order Information Complementarities and Polarization

Segura-Rodríguez¹

2019

SSRN Journal

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Too good to fire: Non-assortative matching to play a dynamic game

Sperisen

Wiseman

2020

Games and Economic Behavior

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The optimal assortativity of teams inside the firm

Kambhampati

Segura-Rodríguez²

2022

The RAND J of Economics

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How does a profit-maximizing manager form teams and compensate workers when workers have private information about their productivity and exert hidden effort once in a team? We study a team-production model in which positive assortative matching is both efficient and profitmaximizing under pure adverse selection and pure moral hazard. We show that the interaction of adverse selection and moral hazard can lead to nonassortative matching if complementarities are sufficiently weak. When this is the case, the manager may prefer to delegate matching, allowing workers to sort themselves into teams.

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Matching to Produce Information

Cited by 4 publications

References 25 publications

Higher Order Information Complementarities and Polarization

Higher Order Information Complementarities and Polarization

Too good to fire: Non-assortative matching to play a dynamic game

The optimal assortativity of teams inside the firm

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