nep-mic New Economics Papers
on Microeconomics
Issue of 2022‒11‒28
twelve papers chosen by
Jing-Yuan Chiou
National Taipei University

  1. Fair cost sharing: big tech vs telcos By Bruno Jullien; Matthieu Bouvard
  2. Information Design in Allocation with Costly Verification By Yi-Chun Chen; Gaoji Hu; Xiangqian Yang
  3. Persuading crowds By Caio Lorecchio
  4. Persuasion without Priors By Alexei Parakhonyak; Anton Sobolev
  5. Evidence Disclosure in Competitive Markets By Péter Eso; Chris Wallace
  6. On the Welfare Effects of Adverse - Selection in Oligopolistic Markets By Marco de Pinto; Lazlo Goerke; Alberto Palermo
  7. Selecting the best when selection is hard By Mikhail Drugov; Margaret Meyer; Marc Möller
  8. Policymaking under Influence By Blumenthal, Benjamin
  9. Connecting the Dots: Loss Aversion, Sybil Attacks, and Welfare Maximization By Yotam Gafni; Moshe Tennenholtz
  10. Variable population manipulations of reallocation rules in economies with single-peaked preferences By Agustin G. Bonifacio
  11. Efficient Allocations under Ambiguous Model Uncertainty By Chiaki Hara; Sujoy Mukerji; Frank Riedel; Jean-Marc Marc Tallon
  12. Crowding Out the Truth? A Simple Model of Misinformation, Polarization and Meaningful Social Interactions By Fabrizio Germano; Vicenç Gómez; Francesco Sobbrio

  1. By: Bruno Jullien (TSE-R - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées - 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, CNRS - Centre National de la Recherche Scientifique); Matthieu Bouvard (TSE-R - Toulouse School of Economics - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées - 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, UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées)
    Abstract: We study a cost-sharing mechanism where a content provider contributes to covering the costs incurred by a network operator when delivering content to consumers. The costshare not only boosts the content provider's incentives to moderate trac but also aects the price composition for consumers buying access and content. We show the overall eect on consumer welfare depends on the content provider's ability to monetize users. When that ability is high, introducing a cost-share can lead to lower overall prices and higher consumer welfare. We study the robustness of this result to long-term investments in cost reduction by the operator and to heterogeneity in consumers' taste for content. In extensions with multiple contents and multiple operators, contractual externalities arise that suggest a role for regulation.
    Date: 2022–10–28
  2. By: Yi-Chun Chen; Gaoji Hu; Xiangqian Yang
    Abstract: A principal who values an object allocates it to one or more agents. Agents learn private information (signals) from an information designer about the allocation payoff to the principal. Monetary transfer is not available but the principal can costly verify agents' private signals. The information designer can influence the agents' signal distributions, based upon which the principal maximizes the allocation surplus. An agent's utility is simply the probability of obtaining the good. With a single agent, we characterize (i) the agent-optimal information, (ii) the principal-worst information, and (iii) the principal-optimal information. Even though the objectives of the principal and the agent are not directly comparable, we find that any agent-optimal information is principal-worst. Moreover, there exists a robust mechanism that achieves the principal's payoff under (ii), which is therefore an optimal robust mechanism. Many of our results extend to the multiple-agent case; if not, we provide counterexamples.
    Date: 2022–10
  3. By: Caio Lorecchio (Universitat de Barcelona and BEAT)
    Abstract: A sequence of short-lived agents must choose which action to take under a fixed, but unknown, state of the world. Prior to the realization of the state, the long-lived principal designs and commits to a dynamic information policy to persuade agents toward his most preferred action. The principal's persuasion power is potentially limited by the existence of conditionally independent and identically distributed private signals for the agents as well as their ability to observe the history of past actions. I characterize the problem for the principal in terms of a dynamic belief manipulation mechanism and analyze its implications for social learning. For a class of private information structure - the log-concave class, I derive conditions under which the principal should encourage some social learning and when he should induce herd behavior from the start (single disclosure). I also show that social learning is less valuable to a more patient principal: as his discount factor converges to one, the value of any optimal policy converges to the value of the single disclosure policy.
    Keywords: Observational learning, Bayesian persuasion, dynamic information design.
    JEL: D82 D83
    Date: 2022
  4. By: Alexei Parakhonyak; Anton Sobolev
    Abstract: We consider an information design problem when the sender faces ambiguity regarding the probability distribution over the states of the world, the utility function and the prior of the receiver. The solution concept is minimax loss (regret), that is, the sender minimizes the distance from the full information benchmark in the worst-case scenario. We show that in the binary states and binary actions setting the optimal strategy involves a mechanism with a continuum of messages, which admits a representation as a randomization over mechanisms consisting of two messages. A small level of uncertainty regarding the receiver’s prior makes the sender more truthful than in the full information benchmark, but as uncertainty increases at some point the sender starts to lie more. If the sender either knows the probability distribution over the states of the world, or knows that the receiver knows it, then the maximal loss is bounded from above by 1/e. This result generalizes to an infinite state model, provided that the set of admissible mechanisms is limited to cut-off strategies.
    Date: 2022–07–05
  5. By: Péter Eso; Chris Wallace
    Abstract: We introduce a model of competitive equilibrium in a market for a divisible good in which both buyer and seller may possess concealable hard information about the state of the market. When an agent knows the state he or she can verifiably disclose it, but an absence of evidence cannot be proved. Agents endogenously determine which states to disclose and conceal (if informed), and the market price at which they trade reflects that. Under general conditions we establish the existence of an equilibrium consisting of disclosure rules, consistent beliefs, contingent market prices, supply and demand decisions. In an extended example we fully characterize these objects. As an agent becomes better able to discover concealable evidence he or she discloses a larger set of states. The other side of the market becomes more suspicious that unfavourable evidence is being concealed; the resulting pressure on the market price alters the optimal disclosure rule on both sides, and trade can be reduced even when prices do not change.
    Date: 2022–07–14
  6. By: Marco de Pinto (University of Applied Labour Studies, Mannheim); Lazlo Goerke (Institute for Labour Law and Industrial Relations in the EC, University of Trier, IZA Bonn and CESifo Muenchen); Alberto Palermo (Institute for Labour Law and Industrial Relations in the EC, University of Trier)
    Abstract: We consider a principal-agent relationship with adverse selection. Principals pay informational rents due to asymmetric information and sell their output in a homogeneous Cournot-oligopoly. We find that asymmetric information may mitigate or more than compensate the welfare reducing impact of market power, irrespective of whether the number of firms is given exogenously or determined endogenously by a profit constraint. We further show that welfare in a setting with adverse selection may be higher than the maximized welfare level attainable in a world with perfect observability.
    Keywords: Adverse Selection, Oligopoly, Welfare
    JEL: D43 D82 L51
  7. By: Mikhail Drugov; Margaret Meyer; Marc Möller
    Abstract: In dynamic promotion contests, where performance measurement is noisy and constrained to be ordinal, selection of the most able agent can be improved by biasing later stages in favor of early performers. We show that even in the worst-case scenario, where external random factors swamp the difference in agents’ abilities in determining their relative performance, optimal bias is (i) strictly positive and (ii) locally insensitive to changes in the ratio of heterogeneity to noise. To explain these, arguably surprising, limiting results, we demonstrate a close relationship in the limit between optimal bias under ordinal information and the expected optimal bias when bias can be conditioned on cardinal information about relative performance. As a consequence of these two limiting properties, the simple rule of setting bias as if in the worst-case scenario achieves most of the potential gains in selective efficiency from biasing dynamic rank-order contests.
    Date: 2022–07–14
  8. By: Blumenthal, Benjamin
    Abstract: Policymaking is a fraught process: politicians often fail to change the status quo despite their best efforts. Influential players, e.g. interest groups, bureaucrats or legislators, can make politicians’ proposals more or less likely to be implemented. I consider a model of policymaking with an imperfectly effective politician and an influential player who, through costly effort, can make the politician’s proposal more or less likely to replace the status quo. Introducing and exploiting a simple taxonomy of influential players’ preferences over policies, I show how and when threats, sabotage, or support can affect policymaking, depending on the influential player’s cost and strength of effort. Subsequently, I show that the relationship between the influential player’s ability to shape proposals and her cost of effort can be non-monotonic, discuss empirical implications of the model, highlight the importance of status quo policies, and connect this work to related strands of the literature.
    Date: 2022–11–10
  9. By: Yotam Gafni; Moshe Tennenholtz
    Abstract: A celebrated known cognitive bias of individuals is that the pain of losing is psychologically higher than the pleasure of gaining. In robust decision making under uncertainty, this approach is typically associated with the selection of safety (aka security) level strategies. We consider a refined notion, which we term loss aversion, capturing the fact that when comparing two actions an agent should not care about payoffs in situations where they lead to identical payoffs, removing trivial equivalencies. We study the properties of loss aversion, its relations to other robust notions, and illustrate its use in auctions and other settings. Moreover, while loss aversion is a classical cognitive bias on the side of decision makers, the problem of economic design is to maximize social welfare when facing self-motivated participants. In online environments, such as the Web, participants' incentives take a novel form originating from the lack of clear agent identity -- the ability to create Sybil attacks, i.e., the ability of each participant to act using multiple identities. It is well-known that Sybil attacks are a major obstacle for welfare-maximization. Our major result proves that the celebrated VCG mechanism is welfare maximizing when agents are loss-averse, even under Sybil attacks. Altogether, our work shows a successful fundamental synergy between cognitive bias/robustness under uncertainty, economic design, and agents' strategic manipulations in online multi-agent systems.
    Date: 2022–10
  10. By: Agustin G. Bonifacio
    Abstract: In a one-commodity economy with single-peaked preferences and individual endowments, we study different ways in which reallocation rules can be strategically distorted by affecting the set of active agents. We introduce and characterize the family of monotonic reallocation rules and show that each rule in this class is withdrawal-proof and endowments-merging-proof, at least one is endowments-splitting-proof and that no such rule is pre-delivery-proof.
    Date: 2022–10
  11. By: Chiaki Hara (Kyoto University [Kyoto]); Sujoy Mukerji (QMUL - Queen Mary University of London); Frank Riedel (University of Bielefeld); Jean-Marc Marc Tallon (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
    Abstract: We investigate consequences of ambiguity on efficient allocations in an exchange economy. Ambiguity is embodied in the model uncertainty perceived by the consumers: they are unsure what would be the appropriate probability measure to apply to evaluate consumption and keep in consideration a set P of alternative probabilistic laws. Consumers are heterogeneously ambiguity averse with smooth
    Date: 2022–10
  12. By: Fabrizio Germano; Vicenç Gómez; Francesco Sobbrio
    Abstract: This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to online social interactions (e.g., likes and shares) and to personalized content may increase engagement on the social media platform, while at the same time increasing misinformation and/or polarization. By exploiting Facebook’s 2018 “Meaningful Social Interactions” algorithmic ranking update, we also provide direct empirical support for some of the main predictions of the model.
    Keywords: algorithmic gatekeeper, ranking algorithms, popularity ranking, personalized ranking, meaningful social interactions, engagement, polarization, misinformation
    JEL: D72 D83 L82 L86
    Date: 2022

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