We develop a two-stage oligopoly model of price competition in markets with both informed and uninformed (captive) consumers. The model introduces a novel mechanism through which interfirm collaborative R D influences market outcomes. In particular, the second stage of the game where firms set prices is a supermodular game allowing us to analyze strategic complementarities in pricing behavior. We show that this type of market friction creates a new channel of influence for collaborative R D. Our analysis reveals how consumer heterogeneity and cost heterogeneity jointly shape the incentives for collaboration among firms, offering new insights into the design of efficient innovation networks in oligopolistic markets.

We consider a pure exchange asset model with a finite number of agents and a finite number of states of nature where short sells are allowed. We present the definition of weak no-arbitrage price, a weaker notion of noarbitrage price than the one of Werner, and prove that if the utility functions satisfy the maximal and closed gradients conditions we propose in this paper, then there exists an equivalence between existence of a general equilibrium and existence of a price which is weak no-arbitrage price for all the agents.

How does concern about genetic data privacy compare with other concerns? We conduct behavioral experiments to compare risk attitudes towards sharing genetic data with a healthcare provider with risk attitudes towards sharing financial data with a money manager. Both scenarios involve identical decisions and monetary stakes, permitting us to focus on how the framing of data sharing influences attitudes. To delve deeper into individual motivations to share data, we provide treatments that study how data sharers' altruism and trust affect their decisions. Our findings (with 162 subjects) indicate that individuals are more willing to risk a loss to privacy of genetic data (for an anticipated return framed as health benefits) than they are to risk loss of financial data (for an anticipated return in financial benefits). We also find that 50%–60% of data recipients choose to protect another person's data, with no significant differences between frames.

As recreational genomics continues to grow in its popularity, many people are afforded the opportunity to share their genomes in exchange for various services, including third-party interpretation (TPI) tools, to understand their predisposition to health problems and, based on genome similarity, to find extended family members. At the same time, these services have increasingly been reused by law enforcement to track down potential criminals through family members who disclose their genomic information. While it has been observed that many potential users shy away from such data sharing when they learn that their privacy cannot be assured, it remains unclear how potential users’ valuations of the service will affect a population’s behavior. In this paper, we present a game theoretic framework to model interdependent privacy challenges in genomic data sharing online. Through simulations, we find that in addition to the boundary cases when (1) no player and (2) every player joins, there exist pure-strategy Nash equilibria when a relatively small portion of players choose to join the genomic database. The result is consistent under different parametric settings. We further examine the stability of Nash equilibria and illustrate that the only equilibrium that is resistant to a random dropping of players is when all players join the genomic database. Finally, we show that when players consider the impact that their data sharing may have on their relatives, the only pure strategy Nash equilibria are when either no player or every player shares their genomic data.

We analyze a dynamic game where players can each make offers to other players to form coalitions. We show that these games have a unique subgame perfect equilibrium outcome that is individually rational and, when players can make enough proposals, Pareto optimal. We also provide sufficient conditions for equilibrium to implement core coalition structures.

Abstract As recreational genomics continues to grow in its popularity, many people are afforded the opportunity to share their genomes in exchange for various services, including third-party interpretation (TPI) tools, to understand their predisposition to health problems and, based on genome similarity, to find extended family members. At the same time, these services have increasingly been reused by law enforcement to track down potential criminals through family members who disclose their genomic information. While it has been observed that many potential users shy away from such data sharing when they learn that their privacy cannot be assured, it remains unclear how potential users’ valuations of the service will affect a population’s behavior. In this paper, we present a game theoretic framework to model interdependent privacy challenges in genomic data sharing online. Through simulations, we find that in addition to the boundary cases when 1) no player and 2) every player joins, there exist pure-strategy Nash equilibria when a relatively small portion of players choose to join the genomic database. The result is consistent under different parametric settings. We further examine the stability of Nash equilibria and illustrate that the only equilibrium that is resistant to a random dropping of players is when all players join the genomic database. Finally, we show that when players consider the impact that their data sharing may have on their relatives, the only pure strategy Nash equilibria are when either no player or every player shares their genomic data.

We implement a laboratory experiment to study how strategy advice affects participant decisions in a school choice game. In the Deferred Acceptance (DA) mechanism, advice to choose the dominant strategy of truth-telling induces participants to do so. In the Immediate Acceptance (IA) mechanism, advice to implement one of two heuristic strategies induces participants to choose one of those strategies. We develop a new partially-ordered typology of DA strategies to study the suboptimal strategies chosen by participants under advice versus no advice. Then, using the varying proportions of participants choosing sub-optimal strategies in our data, we perform exploratory analyses on mechanism performance. We find that DA outperforms IA in efficiency, stability, and proportion of participants assigned their most preferred school. These performance differences are larger under strategy advice. (school choice, experiment, strategy advice, mechanism design, suboptimal play)

Journal of Public Economic TheoryVolume 23, Issue 5 p. 765-771 INTRODUCTION Introduction to the special issue on markets, policies, and economic design: Theory and experiments Rabah Amir, Rabah Amir Department of Economics, University of Iowa, Iowa City, Iowa, USASearch for more papers by this authorMyrna Wooders, Corresponding Author Myrna Wooders myrna.wooders@gmail.com Department of Economics, Vanderbilt University, Nashville, Tennessee, USA Correspondence Myrna Wooders, Department of Economics, Vanderbilt University, Nashville, Tennessee, USA. Email: myrna.wooders@gmail.comSearch for more papers by this author Rabah Amir, Rabah Amir Department of Economics, University of Iowa, Iowa City, Iowa, USASearch for more papers by this authorMyrna Wooders, Corresponding Author Myrna Wooders myrna.wooders@gmail.com Department of Economics, Vanderbilt University, Nashville, Tennessee, USA Correspondence Myrna Wooders, Department of Economics, Vanderbilt University, Nashville, Tennessee, USA. Email: myrna.wooders@gmail.comSearch for more papers by this author First published: 16 September 2021 https://doi.org/10.1111/jpet.12544Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume23, Issue5October 2021Pages 765-771 RelatedInformation

We study iterated matching of soulmates [IMS], a recursive process of forming coalitions that are mutually preferred by members to any other coalition containing individuals as yet unmatched by this process. If all players can be matched this way, preferences are IMS-complete. A mechanism is a soulmate mechanism if it allows the formation of all soulmate coalitions. Our model follows Banerjee, Konishi and Sönmez (2001), except reported preferences are strategic variables. We investigate the incentive and stability properties of soulmate mechanisms. In contrast to prior literature, we do not impose conditions that ensure IMS-completeness. A fundamental result is that, (1) any group of players who could change their reported preferences and mutually benefit does not contain any players who were matched as soulmates and reported their preferences truthfully. As corollaries, (2) for any IMS-complete profile, soulmate mechanisms have a truthful strong Nash equilibrium, and (3) as long as all players matched as soulmates report their preferences truthfully, there is no incentive for any to deviate. Moreover, (4) soulmate coalitions are invariant core coalitions - that is, any soulmate coalition will be a coalition in every outcome in the core. To accompany our theoretical results, we present real-world data analysis and simulations that highlight the prevalence of situations in which many, but not all, players can be matched as soulmates. In an Appendix we relate IMS to other well-known coalition formation processes.

Person-specific biomedical data are now widely collected, but its sharing raises privacy concerns, specifically about the re-identification of seemingly anonymous records. Formal re-identification risk assessment frameworks can inform decisions about whether and how to share data; current techniques, however, focus on scenarios where the data recipients use only one resource for re-identification purposes. This is a concern because recent attacks show that adversaries can access multiple resources, combining them in a stage-wise manner, to enhance the chance of an attack’s success. In this work, we represent a re-identification game using a two-player Stackelberg game of perfect information, which can be applied to assess risk, and suggest an optimal data sharing strategy based on a privacy-utility tradeoff. We report on experiments with large-scale genomic datasets to show that, using game theoretic models accounting for adversarial capabilities to launch multistage attacks, most data can be effectively shared with low re-identification risk.

We propose a new solution concept for games in extensive form that incorporates both cooperation and subgame perfection. From its definition and properties, the new solution concept, named the subgame-perfect core, is a refinement of the core of an extensive game in the same sense as the set of subgame-perfect Nash equilibria is a refinement of the set of Nash equilibria. To further characterize the subgame-perfect core, we show that each subgame-perfect core payoff vector can be implemented as a non-cooperative solution, as it is a subgame-perfect Nash equilibrium payoff vector of an extensive form game that is closely related to the original game. We also motivate and introduce a related concept of subgame-perfect strong Nash equilibrium of an extensive game that is coalition proof.

Journal of Public Economic TheoryVolume 21, Issue 5 p. 799-803 INTRODUCTION Introduction to the JPET special issues commemorating works of James Andreoni, Theodore Bergstrom, Larry Blume, and Hal Varian Olivier Bochet, Olivier Bochet Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorNikos Nikiforakis, Nikos Nikiforakis Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorErnesto Reuben, Ernesto Reuben Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorJohn Wooders, John Wooders Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorMyrna Wooders, Corresponding Author Myrna Wooders myrna.wooders@gmail.com Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates Department of Economics, Vanderbilt University, Nashville, Tennessee Correspondence Myrna Wooders, Department of Economics, Vanderbilt University, Nashville, TN 37235-1819. Email: myrna.wooders@gmail.comSearch for more papers by this author Olivier Bochet, Olivier Bochet Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorNikos Nikiforakis, Nikos Nikiforakis Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorErnesto Reuben, Ernesto Reuben Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorJohn Wooders, John Wooders Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesSearch for more papers by this authorMyrna Wooders, Corresponding Author Myrna Wooders myrna.wooders@gmail.com Division of Social Sciences, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates Department of Economics, Vanderbilt University, Nashville, Tennessee Correspondence Myrna Wooders, Department of Economics, Vanderbilt University, Nashville, TN 37235-1819. Email: myrna.wooders@gmail.comSearch for more papers by this author First published: 17 September 2019 https://doi.org/10.1111/jpet.12398Citations: 2 The Journal of Public Economic Theory thanks New York University Abu Dhabi for its generous support of a workshop at which most of the papers in this issue were presented and also the Association for Public Economic Theory for its support. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume21, Issue5Special Issue: Commemorating works of James Andreoni, Theodore Bergstrom, Larry Blume and Hal VarianOctober 2019Pages 799-803 RelatedInformation

We develop a model with which to explore how an individuals own experience in the labor market may influence her assessment of the efforts of other individuals. Specifically, we consider a two stage process in which individuals first learn, through experience, whether effort is rewarded and then subsequently have to estimate the effort of others. We derive a theoretical benchmark based on rational inference and then explore how own experience may lead to systematic bias from this benchmark. Our theoretical results suggest that those who are not rewarded for high effort will underestimate the effort of other individuals while those for whom effort is rewarded will (slightly) overestimate the effort of others. We empirically test and confirm this prediction in the lab. (C) 2020 Published by Elsevier B.V.

We develop a model with which to explore discrimination and prejudice within labor markets. Our approach emphasizes the role of an individual’s own experience in the assessment of efforts of other individuals. Specifically, we consider a two stage process in which individuals first learn, through experience, whether effort is rewarded and then subsequently have to estimate the effort of others. Our theoretical results suggest that those who are not rewarded for high effort ∗This research was partly funded by: Nuffield Foundation Social Sciences Small Research Grant SGS/36604, ‘An experimental investigation of prejudice and economic discrimination’; NSF Grant 1526860; the Douglas May Funds for Economics at Vanderbilt University; and an Equity, Diversity and Inclusion Grant at Vanderbilt University.

We introduce a price oligopoly model with informed and uninformed consumers, thus creating a new channel of influence for collaborative R&D. Firms can establish pair-wise collaborative research links with other firms to lower production costs. Informed consumers buy from the lowest cost firms while uninformed consumers buy from any firm whose price does not exceed their reservation prices. In contrast to earlier models of price setting oligopolies which result in no R&D, our model can lead to positive levels of R&D collaborations. It also leads to increased social welfare, since increased R&D collaborations lower productions costs. Although uninformed consumers pay higher prices, informed consumers are better off as higher R&D leads to lower marginal costs and prices. We then allow for heterogeneity in consumers reservation prices or firm profits and again find higher levels of R&D. Interestingly, under such heterogeneity, the size of the stable collaborative group increases as R&D costs increase. Finally, we extend the model by introducing different markets where several firms compete for the uninformed consumers. We now find an interesting pattern of R&D activity; in equilibrium, each market has only one active firm and firms collaborate only with (active) firms that do not operate in their own markets.

We consider an exchange economy with a finite number of assets and a finite number of agents. The utility functions of the agents are concave, strictly increasing and their suprema equal infity. We use weak no-arbitrage prices a la Dana and Le Van [5]. Our main result is: an equilibrium exists if, and only if, their exists a weak no-arbitrage price common to all the agents.

We develop a model with which to explore discrimination and prejudice within labor markets. Our approach emphasizes the role of an individual's own experience in the assessment of efforts of other individuals. Specifically, we consider a two stage process in which individuals first learn, through experience, whether effort is rewarded and then subsequently have to estimate the effort of others. Our theoretical results suggest that those who are not rewarded for high effort will underestimate the effort of other individuals while those for whom effort is rewarded will (slightly) overestimate the effort of others. We empirically test and confirm this prediction.

We model decentralized team formation as a game in which players make offers to potential teams whose members then either accept or reject the offers. The games induce no-delay subgame perfect equilibria with unique outcomes that are individually rational and match soulmates. We provide sufficient conditions for equilibria to implement core coalition structures, and show that when each player can make a sufficiently large number of proposals, outcomes are Pareto optimal. We then design a mechanism to implement equilibrium of this game and provide sufficient conditions to ensure that truthful reporting of preferences is a strong ex post Nash equilibrium. Moreover, we show empirically that players rarely have an incentive to misreport preferences more generally. Furthermore, for the problem with cardinal preferences, we show empirically that the resulting mechanism results in significantly higher social welfare than serial dictatorship, and the outcomes are highly equitable.

We provide a new proof of the nonemptiness of approximate cores of games with many players of a finite number of types. Earlier papers in the literature proceed by showing that, for games with many players, equal-treatment cores of their “balanced cover games,” which are nonempty, can be approximated by equal-treatment \(\varepsilon \)-cores of the games themselves. Our proof is novel in that we develop a limiting payoff possibilities set and rely on a fixed point theorem.