nep-mic New Economics Papers
on Microeconomics
Issue of 2023‒05‒01
twelve papers chosen by
Jing-Yuan Chiou
National Taipei University

  1. Should They Compete or Should They Cooperate? The View of Agency Theory By Fleckinger, Pierre; Martimort, David; Roux, Nicolas
  2. Platform Design Biases in Ad-Funded Two-Sided Markets By Jay Pil Choi; Doh-Shin Jeon
  3. Endogenous Lemon Markets: Risky Choices and Adverse Selection By Avi Lichtig; Ran Weksler
  4. More Ambiguous or More Complex? An Investigation of Individual Preferences under Uncertainty. By Ilke Aydogan; Loïc Berger; Vincent Théroude
  5. On the Stochasticity of Ultimatum Games By Tianxiao Qi; Bin Xu; Jinshan Wu; Nicolaas J. Vriend
  6. Recursive Preferences and Ambiguity Attitudes By Marinacci Massimo; Principi Giulio; Stanca Lorenzo
  7. Cooperative dilemmas with binary actions and multiple players By Peña, Jorge; Nöldeke, Georg
  8. Fighting Free with Free: Freemium vs. Piracy By Antoine Dubus; Christine Halmenschlager; Patrick Waelbroeck
  9. The punctuality stability of the Nash equilibrium: the advantage of a late player in potential and aggregative games By Vasily V. Gusev
  10. The shirker’s dilemma and the prospect of cooperation in large groups By Peña, Jorge; Heifetz, Aviad; Nöldeke, Georg
  11. Information Transmission in Voluntary Disclosure Games By Avi Lichtig; Ran Weksler
  12. Prediction, human decision and liability rules, CRED Working paper No 2022-06 By Marie Obidzinski; Yves Oytana

  1. By: Fleckinger, Pierre; Martimort, David; Roux, Nicolas
    Abstract: What is the most efficient way of designing incentives for a group of agents? Over the past five decades, agency theory has provided various answers to this crucial question. This line of research has argued that, depending on the specific organizational context, the best channel for providing incentives involves either relying on collective compen-sations or, on the contrary, employing relative performance evaluations. In the first scenario, cooperation among agents is the key aspect of the organization. In the second, competition among agents prevails. This paper provides a comprehensive overview of this extensive literature, with the aim of understanding the conditions under which one or the other type of incentive scheme is more desirable for the principal of the organiza-tion. To achieve this, we use a flexible workhorse model that is capable of addressing a wide range of scenarios characterized by different technologies, information constraints, and behavioral norms.
    JEL: D20 D86 J33 L23 M12 M50
    Date: 2023–03
  2. By: Jay Pil Choi (Michigan State University [East Lansing] - Michigan State University System); Doh-Shin Jeon (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
    Abstract: We investigate how platform market power affects platforms' design choices in ad-funded two-sided markets, where platforms may find it optimal to charge zero price on the consumer side and to extract surplus on the advertising side. We consider design choices affecting both sides in opposite ways and compare private incentives with social incentives. Platforms' design biases depend crucially on whether they can charge any price on the consumer side. We apply the framework to technology adoption, privacy, and ad load choices. Our results provide a rationale for a tougher competition policy to curb market power of ad-funded platforms with free services.
    Date: 2022–02–25
  3. By: Avi Lichtig; Ran Weksler
    Abstract: The severity of adverse selection depends, to a great extent, on the underlying distribution of the asset. This distribution is commonly modeled as exogenous; however, in many realworld applications, it is determined endogenously. A natural question in this context is whether one can predict the severity of the adverse selection problem in such environments. In this paper, we study a bilateral trade model in which the distribution of the asset is affected by pre-trade unobservable actions of the seller. Analyzing general trade mechanisms, we show that the seller’s actions are characterized by a riskseeking disposition. In addition, we show that (location-independent) riskier underlying distributions of the asset induce lower social welfare. That is, “lemon markets†arise endogenously in these environments.
    JEL: C72 D83 L15
    Date: 2023–03
  4. By: Ilke Aydogan; Loïc Berger; Vincent Théroude
    Abstract: This paper explores the drivers of individual preferences under uncertainty. We propose a characterization of the situations of model uncertainty such as the ones introduced by Ellsberg (1961) by building on the more ambiguous relations of Jewitt and Mukerji (2017) and Izhakian (2020) and on two new more complex relations. Reconsidering existing data sets from the recent literature and combining them with new experimental evidence, we show that uncertainty preferences can be driven by considerations regarding both the degree of complexity and ambiguity that a situation entails.
    Keywords: Ambiguity, model uncertainty, complexity, Ellsberg paradox.
    JEL: D81
    Date: 2023
  5. By: Tianxiao Qi (Beijing Normal University); Bin Xu (Zhejiang Gongshang University); Jinshan Wu (Beijing Normal University); Nicolaas J. Vriend (Queen Mary University of London)
    Abstract: Brenner and Vriend (2006) argued (experimentally and theoretically) that one should not expect proposers in ultimatum games to learn to converge to the subgame perfect Nash equilibrium offer, as finding the optimal offer is a hard learning problem for (boundedly-rational) proposers. In this paper we show that providing the proposers with given (fixed) acceptance probabilities (essentially eliminating the learning task) leads to somewhat lower offers, but still substantially above the monetary payoff-maximizing offer. By using a Risk Attitude test and a Probability Matching test, we show experimentally that the proposers’ attitude with respect to risk, as well as their ability to interpret and deal with probabilities may matter when it comes to making UG offers. Thus, we argue that the lack of convergence to the minimum offers in ultimatum games may be related to the inherent stochasticity of typical UG experiments, highlighting a possible cause of such deviations that seems a complementary explanation to existing ones.
    Keywords: Ultimatum game, Stochasticity, Risk Attitude, Probability Matching
    JEL: C72 C73
    Date: 2021–04–12
  6. By: Marinacci Massimo (Department of Decision Sciences and IGIER, Bocconi University, Italy;); Principi Giulio (Department of Economics, New York University, USA;); Stanca Lorenzo (Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) and Collegio Carlo Alberto, University of Torino, Italy;)
    Abstract: We illustrate the strong implications of recursivity, a standard assumption in dynamic environments, on attitudes toward uncertainty. In intertemporal consumption choice problems, recursivity always implies constant absolute ambiguity aversion (CAAA) when applying the standard dynamic extension of monotonicity. Our analysis also yields a functional equation called ``generalized rectangularity", as it generalizes the standard notion of rectangularity for recursive maxmin preferences to general certainty equivalents. Our results highlight that if uncertainty aversion is modeled as a form of convexity of preferences, recursivity limits us to only recursive variational preferences.
    Keywords: Dynamic choice, Recursive utility, uUncertainty aversion, Absolute attitudes, Generalized rectangularity.
    JEL: C61 D81
    Date: 2023–04
  7. By: Peña, Jorge; Nöldeke, Georg
    Abstract: The prisoners’ dilemma, the snowdrift game, and the stag hunt are simple two-player games that are often considered as prototypical examples of cooperative dilemmas across disciplines. However, surprisingly little consensus exists about the precise mathematical meaning of the words “cooperation” and “cooperative dilemma” for these and other binary-action games, in particular when considering interactions among more than two players. Here, we propose new definitions of these terms and explore their consequences on the equilibrium structure of cooperative dilemmas in relation to social optimality. We find that a large class of multi-player prisoners’ dilemmas and snowdrift games behave as their two-player counterparts, namely, they are characterized by a unique equilibrium where cooperation is always underprovided, regardless of the number of players. Multi-player stag hunts allow for the peculiarity of excessive cooperation at equilibrium, unless cooperation is such that it induces positive individual externalities. Our framework and results unify, simplify, and extend previous work on the structure and properties of binary-action multi-player cooperative dilemmas.
    Date: 2023–04–11
  8. By: Antoine Dubus (D-MTEC - Department of Management, Technology, and Economics [ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]); Christine Halmenschlager; Patrick Waelbroeck
    Abstract: In this article, we show how freemium business models can deter piracy. We analyze a simple freemium model in which a firm offers both a free version and a premium version. The firm can restrict the use of the free version. Consumers can choose between the free and the premium version, but can also get an illegal digital copy. More restrictions can increase the number of premium users but divert other users to piracy. On the contrary, fewer restrictions deter online piracy. We show that with a low level of piracy, the firm sets a high level of restrictions on the free version, which makes the traditional premium business model more profitable than the freemium model. We therefore challenge the idea that strong copyright laws are necessary to protect digital markets. We argue that there are market solutions to fight free with free that better segment consumer audiences according to their willingness to pay for digital music.
    Keywords: Online piracy, versioning, freemium, streaming, copyright, music
    Date: 2023–02–16
  9. By: Vasily V. Gusev (National Research University Higher School of Economics)
    Abstract: If all players in a game employ Nash-equilibrium strategies, then no single player benefits from changing their strategy alone. In real games however, some players may intentionally arrive late and get a payoff greater than at the equilibrium. To wit, it sometimes pays to wait for competitors to announce their prices and then set the price for one’s own product. The motivation for intentional tardiness is the advantage of making the last move. Can it be arranged so that no player arrives in the game late intentionally? Responding to this challenge, we suggest forming a punctually stable Nash-equilibrium strategy profile. In this study, we investigate whether such a strategy profile exists in potential, aggregative, and symmetric games. What is remarkable about this study is that in some game-theoretical settings all-player punctuality can be achieved without penalizing late arrivals.
    Keywords: Nash equilibrium, punctuality stability, potential games, aggregative games, symmetric games
    JEL: C70 C72 C79
    Date: 2023
  10. By: Peña, Jorge; Heifetz, Aviad; Nöldeke, Georg
    Abstract: Cooperation usually becomes harder to sustain as groups become larger because in-centives to shirk increase with the number of potential contributors to a collective action. But is this always the case? Here we study a binary-action cooperative dilemma where a public good is provided only when at most a fixed number of players shirk from a costly, cooperative task. An example is a group of prey which succeeds to drive a predator away only if few group members refrain from engaging in conspicuous mobbing. We find that at the stable polymorphic equilibrium, which exists when the cost of cooperation is low enough, the probability of cooperating increases with group size and reaches a limit of one when the group size tends to infinity. Nevertheless, increasing the group size may increase or decrease the probability that the public good is provided at such equilibrium. We also prove that the expected payoff to individuals at the stable equilibrium (i.e., their fitness) decreases with group size. For costs of cooperation that are low enough, both the probability of provision of the public good and the expected payoff converge to positive values in the limit of large group sizes. However, we also find that the basin of attraction of the stable polymorphic equilibrium is a decreasing function of group size and shrinks to zero in the limit of very large groups. Overall, we demonstrate non-trivial comparative statics with respect to group size in a simple collective action problem.
    Date: 2023–04–11
  11. By: Avi Lichtig; Ran Weksler
    Abstract: Does a better-informed sender transmit more accurate information in equilibrium? We show that, in a general class of voluntary disclosure games, unlike other strategic communication environments, the answer is positive. If the sender’s evidence is more Blackwell informative, then the receiver’s equilibrium utility increases. We apply our main result to show that an uninformed sender who chooses a test from a Blackwell-ordered set does so efficiently.
    Keywords: Evidence, Informativeness
    JEL: D82 D83 L15
    Date: 2023–03
  12. By: Marie Obidzinski (CRED - Centre de Recherche en Economie et Droit - Université Paris-Panthéon-Assas); Yves Oytana (CRESE - Centre de REcherches sur les Stratégies Economiques (UR 3190) - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE])
    Abstract: We study the design of optimal liability rules when the use of a prediction by a human operator (she) may generate an external harm. This setting is common when using artificial intelligence (AI) to make a decision. An AI manufacturer (he) chooses the level of quality with which the algorithm is developed and the price at which it is distributed. The AI makes a prediction about the state of the world to the human operator who buys it, who can then decide to exert a judgment effort to learn the payoffs in each possible state of the world. We show that when the human operator overestimates the algorithm's accuracy (overestimation bias), imposing a strict liability rule on her is not optimal, because the AI manufacturer will exploit the bias by under-investing in the quality of the algorithm. Conversely, imposing a strict liability rule on the AI manufacturer may not be optimal either, since it has the adverse effect of preventing the human operator from exercising her judgment effort. We characterize the liability sharing rule that achieves the highest possible quality level of the algorithm, while ensuring that the human operator exercises a judgment effort. We then show that, when it can be used, a negligence rule generally achieves the first best optimum. To conclude, we discuss the pros and cons of each type of liability rule.
    Keywords: Liability rules, Decision-making, Artificial intelligence, Cognitive bias, Judgment, Prediction, Algorithm
    Date: 2022–11–22

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