nep-mic New Economics Papers
on Microeconomics
Issue of 2023‒03‒20
seven papers chosen by
Jing-Yuan Chiou
National Taipei University

  1. Revenue Maximization with Partially Verifiable Information By Marco Reuter
  2. Bicriteria Multidimensional Mechanism Design with Side Information By Maria-Florina Balcan; Siddharth Prasad; Tuomas Sandholm
  3. Cases and States * By Ani Guerdjikova; Jürgen Eichberger
  4. Conversations By Mats Köster; Paul Voss
  5. Organizing for Collective Action: Olson Revisited By Marco Battaglini; Thomas R. Palfrey
  6. Downstream Cross-Holdings and Upstream Collusion By Konstantinos Charistos; Ioannis Pinopoulos; Panagiotis Skartados
  7. From bounded rationality to limited consideration: representation and behavioral analysis By Davide Carpentiere; Angelo Petralia

  1. By: Marco Reuter
    Abstract: I consider a seller selling a good to bidders with two-dimensional private information: their valuation for a good and their characteristic. While valuationsare non-verifiable, characteristics are partially verifiable and convey information about the distribution of a bidder's valuation. I derive the revenue-maximizing mechanism and show that it can be implemented by introducing a communication stage before an auction. I show that granting bidders a right to remain anonymous, i.e., to refuse participation in the communication stage, leaves the optimal mechanism unchanged and provides no benefits for the bidders.
    Keywords: Mechanism Design, Auctions, Partially Verifiable Types, Communication
    JEL: D44 D82 D83
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2023_395&r=mic
  2. By: Maria-Florina Balcan; Siddharth Prasad; Tuomas Sandholm
    Abstract: We develop a versatile new methodology for multidimensional mechanism design that incorporates side information about agent types with the bicriteria goal of generating high social welfare and high revenue simultaneously. Side information can come from a variety of sources -- examples include advice from a domain expert, predictions from a machine-learning model trained on historical agent data, or even the mechanism designer's own gut instinct -- and in practice such sources are abundant. In this paper we adopt a prior-free perspective that makes no assumptions on the correctness, accuracy, or source of the side information. First, we design a meta-mechanism that integrates input side information with an improvement of the classical VCG mechanism. The welfare, revenue, and incentive properties of our meta-mechanism are characterized by a number of novel constructions we introduce based on the notion of a weakest competitor, which is an agent that has the smallest impact on welfare. We then show that our meta-mechanism -- when carefully instantiated -- simultaneously achieves strong welfare and revenue guarantees that are parameterized by errors in the side information. When the side information is highly informative and accurate, our mechanism achieves welfare and revenue competitive with the total social surplus, and its performance decays continuously and gradually as the quality of the side information decreases. Finally, we apply our meta-mechanism to a setting where each agent's type is determined by a constant number of parameters. Specifically, agent types lie on constant-dimensional subspaces (of the potentially high-dimensional ambient type space) that are known to the mechanism designer. We use our meta-mechanism to obtain the first known welfare and revenue guarantees in this setting.
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2302.14234&r=mic
  3. By: Ani Guerdjikova (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Jürgen Eichberger (Universität Heidelberg [Heidelberg])
    Abstract: In this paper, we provide a novel framework for decision making under uncertainty based on information available in the form of a data set of cases. A case contains information about an action taken, an outcomes obtained, and other circumstances that were recorded with the action and the outcome. The set of actions, the set of outcomes and the set of possibly relevant recorded characteristics are derived from the cases in the data set. The information from the data set induces a belief function over outcomes for each action. From a decision maker's preferences over belief functions one can derive a representation evaluating outcomes according to the α-max min criterion. New data affects behavioral parameters, such as awareness, ambiguity and ambiguity attitude, and may suggest a classifications of data into states.
    Keywords: partial information case-based decisions data objective ambiguity subjective ambiguity attitudes JEL Classification: D81, partial information, case-based decisions, data, objective ambiguity, subjective ambiguity attitudes JEL Classification: D81
    Date: 2023–01–21
    URL: http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03962412&r=mic
  4. By: Mats Köster; Paul Voss
    Abstract: We develop a theory of conversations. Two agents with different interests take turns choosing the topic of the conversation. Talking about a single topic allows them to delve deeper, making the conversation more informative (or enjoyable). To capture this dynamic, we assume that the marginal utility from conversing increases when the agents stay on topic. The equilibrium conversation is extreme: it either maximizes or minimizes welfare. Long conversations are deep and thus efficient. Short ones are often superficial. The topic of a deep conversation depends in subtle ways on who speaks when. Applications range from echo chambers to team production.
    Keywords: communication, information acquisition, team production
    JEL: D83
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_10275&r=mic
  5. By: Marco Battaglini; Thomas R. Palfrey
    Abstract: We study a standard collective action problem in which successful achievement of a group interest requires costly participation by some fraction of its members. How should we model the internal organization of these groups when there is asymmetric information about the preferences of their members? How effective should we expect it to be as we increase the group’s size n? We model it as an optimal honest and obedient communication mechanism and we show that for large n it can be implemented with a very simple mechanism that we call the Voluntary Based Organization. Two new results emerge from this analysis. Independently of the assumptions on the underlying technology, the limit probability of success in the best honest and obedient mechanism is the same as in an unorganized group, a result that is not generally true if obedience is omitted. An optimal organization, however, provides a key advantage: when the probability of success converges to zero, it does so at a much slower rate than in an unorganized group. Because of this, significant probabilities of success are achievable with simple honest and obedient organizations even in very large groups.
    JEL: C72 D71 D82
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30991&r=mic
  6. By: Konstantinos Charistos; Ioannis Pinopoulos; Panagiotis Skartados
    Abstract: We examine the effects of (passive) cross-holdings in the downstream market on the sustainability of upstream collusion. We consider two competing vertical chains with downstream Cournot and homogeneous goods. Each downstream firm holds a (symmetric) non-controlling share of its rival.
    Keywords: competing vertical chains; cross-holdings; passive ownership; tacit collusion
    JEL: D43 L13 L40 L81
    Date: 2023–02–05
    URL: http://d.repec.org/n?u=RePEc:crt:wpaper:2303&r=mic
  7. By: Davide Carpentiere; Angelo Petralia
    Abstract: Many bounded rationality approaches discussed in the literature are models of limited consideration. We provide a novel representation and data interpretation for some of the analyzed behavioral patterns. Moreover, we characterize a testable choice procedure that allows the experimenter to uniquely infer limited consideration from irrational features of the observed behavior.
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2302.00978&r=mic

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