nep-mic New Economics Papers
on Microeconomics
Issue of 2022‒04‒11
sixteen papers chosen by
Jing-Yuan Chiou
National Taipei University

  1. Dynamic Privacy Choices By Shota Ichihashi
  2. Is Selling Complete Information (Approximately) Optimal? By Dirk Bergemann; Yang Cai; Grigoris Velegkas; Mingfei Zhao
  3. Disagreement Aversion By Antoine Bommier; Adrien Fabre; Arnaud Goussebaïle; Daniel Heyen
  4. A case for transparency in principal-agent relationships By Emiliano Catonini; Sergey Stepanov
  5. Information Design in Concave Games By Yamashita, Takuro; Smolin, Alex
  6. Market-Minded Informational Intermediary and Unintended Welfare Loss By Wenji Xu; Kai Hao Yang
  7. Order of Commitments in Bayesian Persuasion with Partial-informed Senders By Shih-Tang Su; Vijay G. Subramanian
  8. Dynamic Electoral Competition with Voter Loss-Aversion and Imperfect Recall By Lockwood, Ben; Le, Minh; Rockey, James
  9. Signaling under Double-Crossing Preferences: The Case of Discrete Types By Chia-Hui Chen; Junichiro Ishida; Wing Suen
  10. On market prices in double auctions By Simon Jantschgi; Heinrich H. Nax; Bary S. R. Pradelski; Marek Pycia
  11. Fees, incentives, and efficiency in large double auctions By Simon Jantschgi; Heinrich H. Nax; Bary S. R. Pradelski; Marek Pycia
  12. Artificial Intelligence and Auction Design By Martino Banchio; Andrzej Skrzypacz
  13. Vertical Bargaining and Obfuscation By Edona Reshidi
  14. Information Design for Differential Privacy By Ian M. Schmutte; Nathan Yoder
  15. Games of Artificial Intelligence: A Continuous-Time Approach By Martino Banchio; Giacomo Mantegazza
  16. Information vs Competition : How Platform Design Affects Profits and Surplus By Piolatto, A.; Schuett, Florian

  1. By: Shota Ichihashi
    Abstract: I study a dynamic model of consumer privacy and platform data collection. In each period, consumers choose their level of platform activity. Greater activity generates more information about the consumer, thereby increasing platform profits. When the platform can commit to the future privacy policy, it collects information by committing to gradually decrease the level of privacy protection. In the long run, consumers lose privacy and receive low payoffs but choose high activity levels. In contrast, the platform with weaker commitment power may attain the commitment outcome or fail to collect any data, depending on consumer expectations regarding future privacy protection.
    Keywords: Economic models
    JEL: D8 D82 D83
    Date: 2022–03
  2. By: Dirk Bergemann (Cowles Foundation, Yale University); Yang Cai (Cowles Foundation, Yale University); Grigoris Velegkas (Yale University); Mingfei Zhao (Google Research)
    Abstract: We study the problem of selling information to a data-buyer who faces a decision problem under uncertainty. We consider the classic Bayesian decision-theoretic model pioneered by Blackwell [Bla51, Bla53]. Initially, he data buyer has only partial information about the payoff-relevant state of the world. A data seller offers additional information about the state of the world. The information is revealed through signaling schemes, also referred to as experiments. In the single-agent setting, any mechanism can be represented as a menu of experiments. A recent paper by Bergemann et al.[BBS18] present a complete characterization of the revenue-optimal mechanism in a binary state and binary action environment. By contrast, no characterization is known for the case with more actions. In this paper, we consider more general environments and study arguably the simplest mechanism, which only sells the fully informative experiment. In the environment with binary state and m = 3 actions, we provide an O(m)-approximation to the optimal revenue by selling only the fully informative experiment and show that the approximation ratio is tight up to an absolute constant factor. An important corollary of our lower bound is that the size of the optimal menu must grow at least linearly in the number of available actions, so no universal upper bound exists for the size of the optimal menu in the general single-dimensional setting. We also provide a sufficient condition under which selling only the fully informative experiment achieves the optimal revenue. For multi-dimensional environments, we prove that even in arguably the simplest matching utility environment with 3 states and 3 actions, the ratio between the optimal revenue and the revenue by selling only the fully informative experiment can grow immediately to a polynomial of the number of agent types. Nonetheless, if the distribution is uniform, we show that selling only the fully informative experiment is indeed the optimal mechanism.
    Date: 2022–02
  3. By: Antoine Bommier (Center of Economic Research (CER-ETH), ETH Zürich, Zürichbergstrasse 18, 8032 Zürich, Switzerland); Adrien Fabre (Center of Economic Research (CER-ETH), ETH Zürich, Zürichbergstrasse 18, 8032 Zürich, Switzerland); Arnaud Goussebaïle (Center of Economic Research (CER-ETH), ETH Zürich, Zürichbergstrasse 18, 8032 Zürich, Switzerland); Daniel Heyen (University of Kaiserslautern and ETH Zürich)
    Abstract: Experts often disagree. A decision-maker may be averse to such expert disagreement. Existing models of aversion to expert disagreement rest on ambiguity-averse preferences adopting a unanimity principle: If all experts consider one choice better than another, so should the decision-maker. Such unanimity among experts, however, can be spurious, masking substantial disagreement on the underlying reasons. We introduce a novel notion of disagreement aversion to distinguish spurious from genuine unanimity and develop a model that can capture disagreement aversion in our sense. The central element of our model is the cautious aggregation of experts’ beliefs.
    Keywords: Disagreement Aversion; Ambiguity Aversion; Belief Aggregation; Decision under Uncertainty; Precautionary Principle
    JEL: D81 D83 D71
    Date: 2022–04
  4. By: Emiliano Catonini; Sergey Stepanov
    Abstract: When is transparency optimal in principal-agent relationships? We consider the following setting. The principal has private, payoff-relevant information about the potential of the project. She can share this information with the agent and can commit to any information structure. Positive news motivate the agent, while bad news depress effort. Under rather mild and natural restrictions on the utility functions of the parties, we obtain interpretable and easily verifiable sufficient conditions for the optimality of full disclosure. We also show that full disclosure is optimal under some modeling assumptions commonly used in applied principal-agent papers.
    Date: 2022–02
  5. By: Yamashita, Takuro; Smolin, Alex
    Abstract: We study information design in games with a continuum of actions such that the players’ payoffs are concave in their own actions. A designer chooses an information structure–a joint distribution of a state and a private signal of each player. The information structure induces a Bayesian game and is evaluated according to the expected designer’s payoff under the equilibrium play. We develop a method that facilitates the search for an optimal information structure, i.e., one that cannot be outperformed by any other information structure, however complex. We show an information structure is optimal whenever it induces the strategies that can be implemented by an incentive contract in a dual, principal-agent problem which aggregates marginal payoffs of the players in the original game. We use this result to establish the optimality of Gaussian information structures in settings with quadratic payoffs and a multivariate normally distributed state. We analyze the details of optimal structures in a differentiated Bertrand competition and in a prediction game.
    Keywords: Information design ; Bayesian persuasion ; Concave games ; Duality ; First-order approach
    JEL: D42 D82 D83
    Date: 2022–03–08
  6. By: Wenji Xu (College of Business, City University of Hong Kong); Kai Hao Yang (Cowles Foundation and School of Management, Yale University)
    Abstract: This paper examines the welfare effects of informational intermediation. A (short-lived) seller sets the price of a product that is sold through a (long-lived) informational intermediary. The intermediary can disclose information about the product to consumers, earns a fixed percentage of the sales revenue in each period, and has concerns about its prominence—the market size it faces in the future, which in turn is increasing in past consumer surplus. We characterize the Markov perfect equilibria and the set of subgame perfect equilibrium payoffs of this game and show that when the market feedback (i.e., how much past consumer surplus affects future market sizes) increases, welfare may decrease in the Pareto sense.
    Keywords: Informational intermediary, market size, market feedback, consumer surplus, Pareto-inferior outcomes, Markov perfect equilibrium, subgame perfect equilibrium.
    JEL: C73 D61 D82 D83 L15 M37
    Date: 2022–01
  7. By: Shih-Tang Su; Vijay G. Subramanian
    Abstract: The commitment power of senders distinguishes Bayesian persuasion problems from other games with (strategic) communication. Persuasion games with multiple senders have largely studied simultaneous commitment and signalling settings. However, many real-world instances with multiple senders have sequential signalling. In such contexts, commitments can also be made sequentially, and then the order of commitment by the senders -- the sender signalling last committing first or last -- could significantly impact the equilibrium payoffs and strategies. For a two-sender persuasion game where the senders are partially aware of the state of the world, we find necessary and sufficient conditions to determine when different commitment orders yield different payoff profiles. In particular, for the two-sender setting, we show that different payoff profiles arise if two properties hold: 1) the two senders are willing to collaborate in persuading the receiver in some state(s); and 2) the sender signalling second can carry out a credible threat when committing first such that the other sender's room to design signals gets constrained.
    Date: 2022–02
  8. By: Lockwood, Ben (University of Warwick); Le, Minh (University of Warwick); Rockey, James (University of Birmingham)
    Abstract: This paper explores the implications of voter loss-aversion and imperfect recall for the dynamics of electoral competition in a simple Downsian model of repeated elections. We first establish a benchmark result: when the voters’ reference point is forward-looking, there are a continuum of rational expectations equilibria (REE). When voters are backward-looking i.e. the reference point is last period’s recalled policy, interesting dynamics only emerge when voters have imperfect recall about that policy. Then, the interplay between the median voter’s reference point and political parties’ choice of platforms generates a dynamic process of polarization (or de-polarization). Under the assumption that parties are risk-neutral, platforms monotonically converge over time to a long-run equilibrium, which is always a REE. When parties are risk-averse, dynamic incentives also come into play, and generally lead to more policy moderation, resulting in equilibria that are more moderate than the most moderate REE JEL Classification: D72 ; D81
    Keywords: electoral competition ; repeated elections ; loss-aversion ; imperfect recall ; advantage
    Date: 2021
  9. By: Chia-Hui Chen; Junichiro Ishida; Wing Suen
    Abstract: The class of double-crossing preferences, where signaling is cheaper for higher types than for lower types at low signaling levels and the opposite is true at high signaling levels, underlines the phenomenon of countersignaling. We show that under the D1 refinement, the equilibrium signaling action must be quasi-concave in type and generally exhibits pooling, with intermediate types choosing higher actions than higher and lower types. We provide an algorithm to systematically construct an equilibrium and use this algorithm to establish its existence for this general class of preferences with an arbitrary discrete-type distribution.
    Date: 2022–03
  10. By: Simon Jantschgi; Heinrich H. Nax; Bary S. R. Pradelski; Marek Pycia
    Abstract: We address some open issues regarding the characterization of double auctions. Our model is a two-sided commodity market with either finitely or infinitely many traders. We first unify existing formulations for both finite and infinite markets and generalize the characterization of market clearing in the presence of ties. Second, we define a mechanism that achieves market clearing in any, finite or infinite, market instance and show that it coincides with the k-double auction by Rustichini et al. (1994) in the former case. In particular, it clarifies the consequences of ties in submissions and makes common regularity assumptions obsolete. Finally, we show that the resulting generalized mechanism implements Walrasian competitive equilibrium.
    Keywords: Double auction, Walrasian equilibrium, finite and infinite markets, axiomatization
    JEL: D44 D47 D50
    Date: 2022–02
  11. By: Simon Jantschgi; Heinrich H. Nax; Bary S. R. Pradelski; Marek Pycia
    Abstract: Fees are omnipresent in markets but, with few exceptions, are omitted in economic models— such as Double Auctions—of these markets. Allowing for general fee structures, we show that their impact on incentives and efficiency in large Double Auctions hinges on whether the fees are homogeneous (as, e.g., fixed fees and price fees) or heterogeneous (as, e.g., bid-ask spread fees). Double Auctions with homogeneous fees share the key advantages of Double Auctions without fees: markets with homogeneous fees are asymptotically strategyproof and efficient. We further show that these advantages are preserved even if traders have misspecified beliefs. In contrast, heterogeneous fees lead to complex strategic behavior (price guessing) and may result in severe market failures. Allowing for aggregate uncertainty, we extend these insights to market organizations other than the Double Auction.
    Keywords: Double auction, fees, transaction costs, incentives, strategyproofness, efficiency, robustness
    JEL: C72 D44 D47 D81 D82
    Date: 2022–02
  12. By: Martino Banchio; Andrzej Skrzypacz
    Abstract: Motivated by online advertising auctions, we study auction design in repeated auctions played by simple Artificial Intelligence algorithms (Q-learning). We find that first-price auctions with no additional feedback lead to tacit-collusive outcomes (bids lower than values), while second-price auctions do not. We show that the difference is driven by the incentive in first-price auctions to outbid opponents by just one bid increment. This facilitates re-coordination on low bids after a phase of experimentation. We also show that providing information about lowest bid to win, as introduced by Google at the time of switch to first-price auctions, increases competitiveness of auctions.
    Date: 2022–02
  13. By: Edona Reshidi
    Abstract: Manufacturers often engage in practices that impede consumer search. Examples include proliferating product varieties, imposing vertical informational restraints, and banning online sales to make it more difficult for consumers to compare prices. This paper models vertical bargaining over wholesale prices and obfuscation levels and finds that obfuscation arises in equilibrium whenever retailers have some bargaining power. Once the bargaining power rests with the manufacturer, the equilibrium involves no obfuscation. The final consumers, however, are worse off compared with settings when retailers have all the bargaining power. We show that in vertical markets, policies that impose caps on obfuscation may induce higher wholesale and retail prices. Instead, we propose caps on wholesale prices as an effective consumer protection policy.
    Keywords: Economic models; Market structure and pricing
    JEL: C70 L42 L13
    Date: 2022–03
  14. By: Ian M. Schmutte; Nathan Yoder
    Abstract: Firms and statistical agencies that publish aggregate data face practical and legal requirements to protect the privacy of individuals. Increasingly, these organizations meet these standards by using publication mechanisms which satisfy differential privacy. We consider the problem of choosing such a mechanism so as to maximize the value of its output to end users. We show that this is equivalent to a constrained information design problem, and characterize its solution. Moreover, by introducing a new order on information structures and showing that it ranks them by their usefulness to agents with supermodular payoffs, we show that the simple geometric mechanism is optimal whenever data users face supermodular decision problems.
    Date: 2022–02
  15. By: Martino Banchio; Giacomo Mantegazza
    Abstract: This paper studies the strategic interaction of algorithms in economic games. We analyze games where learning algorithms play against each other while searching for the best strategy. We first establish a fluid approximation technique that enables us to characterize the learning outcomes in continuous time. This tool allows to identify the equilibria of games played by Artificial Intelligence algorithms and perform comparative statics analysis. Thus, our results bridge a gap between traditional learning theory and applied models, allowing quantitative analysis of traditionally experimental systems. We describe the outcomes of a social dilemma, and we provide analytical guidance for the design of pricing algorithms in a Bertrand game. We uncover a new phenomenon, the coordination bias, which explains how algorithms may fail to learn dominant strategies.
    Date: 2022–02
  16. By: Piolatto, A. (Tilburg University, School of Economics and Management); Schuett, Florian (Tilburg University, School of Economics and Management)
    Date: 2022

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