nep-mic New Economics Papers
on Microeconomics
Issue of 2024‒01‒22
seventeen papers chosen by
Jing-Yuan Chiou, National Taipei University

  1. Persuasion with Non-Linear Preferences By Anton Kolotilin; Roberto Corrao; Alexander Wolitzky
  2. Persuasion and Matching: Optimal Productive Transport By Anton Kolotilin; Roberto Corrao; Alexander Wolitzky
  3. LQG Information Design By Masaki Miyashita; Takashi Ui
  4. The Economics of Partisan Gerrymandering By Anton Kolotilin; Alexander Wolitzky
  5. Optimal Large Population Tullock Contests By Ratul Lahkar; Saptarshi Mukherjee
  6. Information nudges and self control By Thomas Mariotti; Nikolaus Schweizer; Nora Szech; Jonas von Wangenheim
  7. Nash equilibria for dividend distribution with competition By Tiziano De Angelis; Fabien Gensbittel; St\'ephane Villeneuve
  8. Social preferences and expected utility By Mehmet S. Ismail; Ronald Peeters
  9. Revealing Sequential Rationality and Forward Induction By Pierfrancesco Guarino
  10. Personalized Pricing and Distribution Strategies By Bruno Jullien; Markus Reisinger; Patrick Rey
  11. Better Foundations for Subjective Probability By Sven Neth
  12. The Newsroom Dilemma By Ayush Pant; Federico Trombetta
  13. Reference-dependent self-control: Menu effects and behavioral choices By Abhinash Borah; Raghvi Garg
  14. Spontaneous Coupling of Q-Learning Algorithms in Equilibrium By Ivan Conjeaud
  15. Identification in Search Models with Social Information By Niccolò Lomys; Emanuele Tarantino
  16. An extension of May's Theorem to three alternatives: axiomatizing Minimax voting By Wesley H. Holliday; Eric Pacuit
  17. Transaction Ordering Auctions By Jan Christoph Schlegel

  1. By: Anton Kolotilin (School of Economics, UNSW); Roberto Corrao (Department of Economics, MIT); Alexander Wolitzky (Department of Economics, MIT)
    Abstract: In persuasion problems where the receiver’s utility is single-peaked in a one-dimensional action, optimal signals are characterized by duality, based on a first-order approach to the receiver’s problem. A signal that pools at most two states in each realization is always optimal, and such pairwise signals are the only solutions under a non-singularity condition on utilities (the twist condition). Our core results provide conditions under which higher actions are induced at more or less extreme pairs of states, so that the induced action is single-dipped or single-peaked on each set of nested pairs of states. We also provide conditions for the optimality of either full disclosure or negative assortative disclosure, where signal realizations can be ordered from least to most extreme. Methodologically, our proofs rely on a novel complementary slackness theorem for persuasion problems.
    Keywords: persuasion, information design, duality, optimal transport, first-order approach, pairwise signals, twist condition, single-dipped disclosure, negative assortative disclosure, complementary slackness
    JEL: C78 D82 D83
    Date: 2023–02
  2. By: Anton Kolotilin (School of Economics, UNSW); Roberto Corrao (Department of Economics, MIT); Alexander Wolitzky (Department of Economics, MIT)
    Abstract: We consider general Bayesian persuasion problems where the receiver’s utility is single-peaked in a one-dimensional action. We show that a signal that pools at most two states in each realization is always optimal, and that such pairwise signals are the only solutions under a non-singularity condition (the twist condition). Our core results provide conditions under which riskier prospects induce higher or lower actions, so that the induced action is single-dipped or single-peaked on each set of nested prospects. We also provide conditions for the optimality of either full disclosure or negative assortative disclosure, where all prospects are nested. Methodologically, our results rely on novel duality and complementary slackness theorems. Our analysis extends to a general problem of assigning one-dimensional inputs to productive units, which we call optimal productive transport. This problem covers additional applications including club economies (assigning workers to firms, or students to schools), robust option pricing (assigning future asset prices to price distributions), and partisan gerrymandering (assigning voters to districts).
    Keywords: Bayesian persuasion, information design, first-order approach, optimal transport, duality, complementary slackness, pairwise signal, single-dipped signal, negative assortative disclosure, club economies, option pricing, gerrymandering
    JEL: C78 D82 D83
    Date: 2023–10
  3. By: Masaki Miyashita; Takashi Ui
    Abstract: A linear-quadratic-Gaussian (LQG) game is an incomplete information game with quadratic payoff functions and Gaussian payoff states. This study addresses an information design problem to identify an information structure that maximizes a quadratic objective function. Gaussian information structures are found to be optimal among all information structures. Furthermore, the optimal Gaussian information structure can be determined by semidefinite programming, which is a natural extension of linear programming. This paper provides sufficient conditions for the optimality and suboptimality of both no and full information disclosure. In addition, we characterize optimal information structures in symmetric LQG games and optimal public information structures in asymmetric LQG games, with each structure presented in a closed-form expression.
    Date: 2023–12
  4. By: Anton Kolotilin (School of Economics, UNSW); Alexander Wolitzky (Department of Economics, MIT)
    Abstract: We study the problem of a partisan gerrymanderer who assigns voters to equipopulous districts so as to maximize his party’s expected seat share. The designer faces both aggregate uncertainty (how many votes his party will receive) and idiosyncratic, voter-level uncertainty (which voters will vote for his party). We argue that pack-and-pair districting, where weaker districts are “packed” with a single type of voter, while stronger districts contain two voter types, is typically optimal for the gerrymanderer. The optimal form of pack-and-pair districting depends on the relative amounts of aggregate and idiosyncratic uncertainty. When idiosyncratic uncertainty dominates, it is optimal to pack opposing voters and pair more favorable voters; this plan resembles traditional “packing-and-cracking.” When aggregate uncertainty dominates, it is optimal to pack moderate voters and pair extreme voters; this “matching slices” plan has received some attention in the literature. Estimating the model using precinct-level returns from recent US House elections indicates that, in practice, idiosyncratic uncertainty dominates and packing opponents is optimal; moreover, traditional pack-and-crack districting is approximately optimal. We discuss implications for redistricting reform and political polarization. Methodologically, we exploit a formal connection between gerrymandering—partitioning voters into districts—and information design—partitioning states of the world into signals.
    Keywords: Gerrymandering, pack-and-crack, matching slices, pack-and-pair, information design
    JEL: C78 D72 D82
    Date: 2023–04
  5. By: Ratul Lahkar (Ashoka University); Saptarshi Mukherjee (Indian Institute of Technology Delhi)
    Abstract: We consider large population Tullock contests in which agents are divided into different types according to their strategy cost function. A planner assigns type specific bias parameters to affect the likelihood of success with the objective of maximizing the Nash equilibrium level of aggregate strategy. We characterize such optimal bias parameters and identify conditions under which those parameters are increasing or decreasing according to the cost parameters. The parameters are biased in favor of high cost agents if the cost functions are strictly convex and the likelihood of success is sufficiently responsive to strategy. We also identify conditions under which a planner can truthfully implement the optimal parameters under incomplete information. In fact, under such conditions, dominant strategy implementation is equivalent to Nash implementation in our model. Hence, our mechanism double implements the optimal bias parameters.
    Date: 2022–07–20
  6. By: Thomas Mariotti (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); Nikolaus Schweizer (Tilburg University [Netherlands]); Nora Szech (KIT - Karlsruher Institut für Technologie); Jonas von Wangenheim (Universität Bonn = University of Bonn)
    Abstract: We study the optimal design of information nudges for present-biased consumers who make sequential consumption decisions without exact prior knowledge of their long-term consequences. For any distribution of risks, there exists a consumer-optimal information nudge that is of cutoff type, recommending abstinence if riskiness is high enough. Depending on the distribution of risks, more or less consumers may have to be sacriced in that they cannot be warned even though they would like to be. Under a stronger bias for the present, the target group receiving a credible warning to abstain must be tightened, but this need not increase the probability of harmful consumption. If some consumers are more strongly present-biased than others, traffic-light nudges turn out to be optimal and, when subgroups of consumers differ sufficiently, the optimal traffic-light nudge is also subgroup-optimal. We finally compare the consumer-optimal nudge with those a health authority or a lobbyist would favor.
    Keywords: Nudges, Information Design, Present-Biased Preferences, Self-Control
    Date: 2023
  7. By: Tiziano De Angelis; Fabien Gensbittel; St\'ephane Villeneuve
    Abstract: We construct a Nash equilibrium in feedback form for a class of two-person stochastic games with absorption arising from corporate finance. More precisely, the paper focusses on a strategic dynamic game in which two financially-constrained firms operate in the same market. The firms distribute dividends and are faced with default risk. The strategic interaction arises from the fact that if one firm defaults, the other one becomes a monopolist and increases its profitability. To determine a Nash equilibrium in feedback form, we develop two different concepts depending on the initial endowment of each firm. If one firm is richer than the other one, then we use a notion of control vs.\ strategy equilibrium. If the two firms have the same initial endowment (hence they are symmetric in our setup) then we need mixed strategies in order to construct a symmetric equilibrium.
    Date: 2023–12
  8. By: Mehmet S. Ismail; Ronald Peeters
    Abstract: It is well known that ex ante social preferences and expected utility are not always compatible. In this note, we introduce a novel framework that naturally separates social preferences from selfish preferences to answer the following question: What specific forms of social preferences can be accommodated within the expected utility paradigm? In a departure from existing frameworks, our framework reveals that ex ante social preferences are not inherently in conflict with expected utility in games, provided a decision-maker's aversion to randomization in selfish utility "counterbalances" her social preference for randomization. We also show that when a player's preferences in both the game (against another player) and the associated decision problem (against Nature) conform to expected utility axioms, the permissible range of social preferences becomes notably restricted. Only under this condition do we reaffirm the existing literature's key insight regarding the incompatibility of ex ante inequality aversion with expected utility.
    Date: 2023–12
  9. By: Pierfrancesco Guarino
    Abstract: Given a dynamic ordinal game, we deem a strategy sequentially rational if there exist a Bernoulli utility function and a conditional probability system with respect to which the strategy is a maximizer. We establish a complete class theorem by characterizing sequential rationality via the new Conditional B-Dominance. Building on this notion, we introduce Iterative Conditional B-Dominance, which is an iterative elimination procedure that characterizes the implications of forward induction in the class of games under scrutiny and selects the unique backward induction outcome in dynamic ordinal games with perfect information satisfying a genericity condition. Additionally, we show that Iterative Conditional B-Dominance, as a `forward induction reasoning' solution concept, captures: $(i)$ the unique backward induction outcome obtained via sophisticated voting in binary agendas with sequential majority voting; $(ii)$ farsightedness in dynamic ordinal games derived from social environments; $(iii)$ a unique outcome in ordinal Money-Burning Games.
    Date: 2023–12
  10. By: Bruno Jullien (TSE-R - TSE-R Toulouse School of Economics – Recherche - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Markus Reisinger (Frankfurt School of Finance and Management); Patrick Rey (TSE-R - TSE-R Toulouse School of Economics – Recherche - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
    Abstract: The availability of consumer data is inducing a growing number of firms to adopt more personalized pricing policies. This affects both the performance of, and the competition between, alternative distribution channels, which in turn has implications for firms' distribution strategies. We develop a formal model to examine a brand manufacturer's choice between mono distribution (selling only through its own direct channel) or dual distribution (selling through an independent retailer as well). We consider different demand patterns, covering both horizontal and vertical differentiation and different pricing regimes, with the manufacturer and retailer each charging personalized prices or a uniform price. We show that dual distribution is optimal for a large number of cases. In particular, this is always the case when the channels are horizontally differentiated, regardless of the pricing regime; moreover, if both firms charge personalized prices, a well-designed wholesale tariff allows them to extract the entire consumer surplus. These insights obtained here for the case of intrabrand competition between vertically related firms are thus in stark contrast to those obtained for interbrand competition, where personalized pricing dissipates industry profit. With vertical differentiation, dual distribution remains optimal if the manufacturer charges a uniform price. By contrast, under personalized pricing, mono distribution can be optimal when the retailer does not expand demand sufficiently. Interestingly, the industry profit may be largest in a hybrid pricing regime, in which the manufacturer forgoes the use of personalized pricing and only the retailer charges personalized prices. This paper was accepted by Joshua Gans, business strategy. Funding: The financial support of the European Research Council under the European Union's Horizon 2020 research and innovation programme [Grant Agreement 670494] and of the Agence nationale de la recherche (ANR) [Grant ANITI (ANR Grant 3IA)] and [Grant CHESS ANR-17-EURE-0010] (Investissements d'Avenir program) is gratefully acknowledged. Supplemental Material: The online appendix is available at .
    Keywords: Personalized pricing, Distribution strategies, Vertical contracting, Downstream competition
    Date: 2023–03
  11. By: Sven Neth
    Abstract: How do we ascribe subjective probability? In decision theory, this question is often addressed by representation theorems, going back to Ramsey (1926), which tell us how to define or measure subjective probability by observable preferences. However, standard representation theorems make strong rationality assumptions, in particular expected utility maximization. How do we ascribe subjective probability to agents which do not satisfy these strong rationality assumptions? I present a representation theorem with weak rationality assumptions which can be used to define or measure subjective probability for partly irrational agents.
    Date: 2023–12
  12. By: Ayush Pant (Ashoka University); Federico Trombetta (Universita Cattolica del Sacro Cuore)
    Abstract: Conventional wisdom suggests that competition in the modern digital environment pushes media outlets toward the early release of less accurate information. We show that this is not necessarily the case. We argue that two opposing forces determine the resolution of the speed-accuracy tradeoff: preemption and reputation. More competitive environments may be more conducive to reputation building, which may lead to better reporting. However, the audience may be worse off due to the outlets' better initial information. Finally, we show how a source may exploit the speed-accuracy tradeoff to quickly get "unverified facts" out to the audience.
    Keywords: media competition; preemption; reputation
    Date: 2023–01–30
  13. By: Abhinash Borah (Ashoka University); Raghvi Garg (Ashoka University)
    Abstract: As is well-known, choices of a decision maker (DM) who attempts self-control in the face of temptation may exhibit menu effects and “non-standard†patterns. Existing models can accommodate some of these patterns but not others; e.g., they can explain self-control undermining menu effects, but not self-control enhancing ones. We introduce a model of self-control with the goal of better understanding and accounting for such effects. The basic idea underlying our model is that the DM experiences a psychological cost if she succumbs to temptation and chooses in a manner that is totally antithetical to her commitment preferences. To mitigate such costs, in any menu, her expression of self-control involves, first, eliminating a subset of alternatives that are worst according to her commitment preferences, with the elimination process being reference-dependent. Then, amongst the remaining alternatives, she chooses the best one according to her temptation preferences. Besides studying menu effects, we characterize the model behaviorally based on a novel axiom called WARP with norms. We also show that the model is well-identified.
    Keywords: self control; temptation; normative elimination; reference dependence; menu effects
    Date: 2022–08–12
  14. By: Ivan Conjeaud
    Abstract: Most contributions in the algorithmic collusion literature only consider symmetric algorithms interacting with each other. We study a simple model of algorithmic collusion in which Q-learning algorithms repeatedly play a prisoner's dilemma and allow players to choose different exploration policies. We characterize behavior of such algorithms with asymmetric policies for extreme values and prove that any Nash equilibrium features some cooperative behavior. We further investigate the dynamics for general profiles of exploration policy by running extensive numerical simulations which indicate symmetry of equilibria, and give insight for their distribution.
    Date: 2023–12
  15. By: Niccolò Lomys (CSEF and Università degli Studi di Napoli Federico II.); Emanuele Tarantino (Luiss University, EIEF, and CEPR)
    Abstract: We theoretically study the problem of a researcher seeking to identify and estimate the search cost distribution when a share of agents in the population observes some peers’ choices. To begin with, we show that social information changes agents’ optimal search and, as a result, the distributions of observable outcomes identifying the search model. Consequently, neglecting social information leads to non-identification of the search cost distribution. Whether, as a result, search frictions are under or overestimated depends on the dataset’s content. Next, we present empirical strategies that restore identification and correct estimation. First, we show how to recover robust bounds on the search cost distribution by imposing only minimal assumptions on agents’ social information. Second, we explore how leveraging additional data or stronger assumptions can help obtain more informative estimates.
    Keywords: Search & Learning; Social Information; Identification; Networks; Robustness; Partial Identification.
    JEL: C1 C5 C8 D1 D6 D8
    Date: 2023–11–24
  16. By: Wesley H. Holliday; Eric Pacuit
    Abstract: May's Theorem [K. O. May, Econometrica 20 (1952) 680-684] characterizes majority voting on two alternatives as the unique preferential voting method satisfying several simple axioms. Here we show that by adding some desirable axioms to May's axioms, we can uniquely determine how to vote on three alternatives. In particular, we add two axioms stating that the voting method should mitigate spoiler effects and avoid the so-called strong no show paradox. We prove a theorem stating that any preferential voting method satisfying our enlarged set of axioms, which includes some weak homogeneity and preservation axioms, agrees with Minimax voting in all three-alternative elections, except perhaps in some improbable knife-edged elections in which ties may arise and be broken in different ways.
    Date: 2023–12
  17. By: Jan Christoph Schlegel
    Abstract: We study equilibrium investment into bidding and latency reduction for different sequencing policies. For a batch auction design, we observe that bidders shade bids according to the likelihood that competing bidders land in the current batch. Moreover, in equilibrium, in the ex-ante investment stage before the auction, bidders invest into latency until they make zero profit in expectation. We compare the batch auction design to continuous time bidding policies (time boost) and observe that (depending on the choice of parameters) they obtain similar revenue and welfare guarantees.
    Date: 2023–12

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