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on Microeconomics |
| By: | Mira Frick; Ryota Iijima; Yuhta Ishii |
| Abstract: | A multi-product monopolist faces a buyer who is privately informed about his valuations for the goods. As is well-known, optimal mechanisms are in general complicated, while simple mechanisms -- such as pure bundling or separate sales -- can be far from optimal and do not admit clear-cut comparisons. We show that this changes if the monopolist observes sufficiently rich data about the buyer's valuations: Now, pure bundling always outperforms separate sales; moreover, there is a sense in which pure bundling performs essentially as well as the optimal mechanism. To formalize this, we characterize how fast the corresponding revenues converge to the first-best revenue as the monopolist's data grows rich: Pure bundling achieves the same convergence rate to the first-best as optimal mechanisms; in contrast, the convergence rate under separate sales is suboptimal. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.06312 |
| By: | Peiran Xiao |
| Abstract: | I study the optimal allocation of positional goods with externalities and one-sided transfers. Because consumers care about their relative positions in consumption, allocating an item to one buyer has externalities on others. Using a mechanism design approach, I characterize the externalities by a feasibility condition. I find the revenue-maximizing mechanism excludes some low types and fully separates the rest if and only if the buyer's type distribution satisfies Myerson's regularity. The seller can guarantee at least half the maximal revenue by offering one level of positional goods, and the approximation can be arbitrarily close if the distribution is sufficiently concave. Moreover, if the distribution has an increasing (decreasing) failure rate, total pooling (full separation) without exclusion maximizes the consumer surplus, and the consumer surplus is decreasing (increasing) in the number of positional good levels. Applications include education, priority services, luxury goods, and organizational design. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.06285 |
| By: | Yifan Dai; Andrew Koh |
| Abstract: | We develop a simple framework to analyze how targeted advertising interacts with market power. A designer chooses an advertising plan which allows it to flexibly manipulate the demand curve at some cost. A monopolist prices against this manipulated demand curve. We fully characterize the form and value of producer-optimal and consumer-optimal advertising plans under both ex-ante and ex-post measures of welfare. Flexibility is double-edged: producer-optimal plans substantially reduce consumer surplus vis-a-vis uniform advertising, but consumer-optimal plans can substantially improve consumer surplus. We discuss implications for the regulation of targeted advertising. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.24191 |
| By: | Philipp Denter; Boris Ginzburg |
| Abstract: | Political agents often aim to influence elections through troll farms -- organisations that disseminate messages emulating genuine information. We study the behaviour of a troll farm that faces a heterogeneous electorate of partially informed voters, and aims to achieve a desired political outcome by targeting each type of voter with a specific distribution of messages. We show that such tactics are more effective when voters are otherwise well-informed, for example, when the media is of high quality. At the same time, increased polarisation, as well as deviations from Bayesian rationality, can reduce the negative effect of troll farms and restore efficiency of electoral outcomes. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.03241 |
| By: | Gagan Aggarwal; Anupam Gupta; Andres Perlroth; Grigoris Velegkas |
| Abstract: | We study a setting where agents use no-regret learning algorithms to participate in repeated auctions. \citet{kolumbus2022auctions} showed, rather surprisingly, that when bidders participate in second-price auctions using no-regret bidding algorithms, no matter how large the number of interactions $T$ is, the runner-up bidder may not converge to bidding truthfully. Our first result shows that this holds for \emph{general deterministic} truthful auctions. We also show that the ratio of the learning rates of the bidders can \emph{qualitatively} affect the convergence of the bidders. Next, we consider the problem of revenue maximization in this environment. In the setting with fully rational bidders, \citet{myerson1981optimal} showed that revenue can be maximized by using a second-price auction with reserves.We show that, in stark contrast, in our setting with learning bidders, \emph{randomized} auctions can have strictly better revenue guarantees than second-price auctions with reserves, when $T$ is large enough. Finally, we study revenue maximization in the non-asymptotic regime. We define a notion of {\em auctioneer regret} comparing the revenue generated to the revenue of a second price auction with truthful bids. When the auctioneer has to use the same auction throughout the interaction, we show an (almost) tight regret bound of $\smash{\widetilde \Theta(T^{3/4})}.$ If the auctioneer can change auctions during the interaction, but in a way that is oblivious to the bids, we show an (almost) tight bound of $\smash{\widetilde \Theta(\sqrt{T})}.$ |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.09517 |
| By: | Dmitry Ryvkin; Qin Wu |
| Abstract: | We study the optimal allocation of prizes in rank-order tournaments with loss averse agents. Prize sharing becomes increasingly optimal with loss aversion because more equitable prizes reduce the marginal psychological cost of anticipated losses. Furthermore, loss aversion can boost effort if prizes are sufficiently equitable, but otherwise effort declines with loss aversion. Overall, these results give credence to more equitable allocations of competitive rewards. A win-win scenario is where optimal prizes are equitable even under loss neutrality, in which case the principal benefits from agents' loss aversion. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.01068 |
| By: | Jasmina Karabegovic |
| Abstract: | This paper introduces an explicit algorithm for computing perfect public equilibrium (PPE) payoffs in repeated games with imperfect public monitoring, public randomization, and discounting. The method adapts the established framework by Abreu, Pearce, and Stacchetti (1990) into a practical tool that balances theoretical accuracy with computational efficiency. The algorithm simplifies the complex task of identifying PPE payoff sets for any given discount factor {\delta}. A stand-alone implementation of the algorithm can be accessed at: https://github.com/jasmina-karabegovic/I RGames.git. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.01566 |
| By: | Tushar Shankar Walunj; Shiksha Singhal; Veeraruna Kavitha; Jayakrishnan Nair |
| Abstract: | The Nash equilibrium (NE) is fundamental game-theoretic concept for characterizing stability in static strategic form games. However, at times, NE fails to capture outcomes in dynamic settings, where players' actions evolve over time in response to one another. In such cases, game dynamics fail to converge to an NE, instead exhibiting cyclic or oscillatory patterns. To address this, we introduce the concept of an 'equilibrium cycle' (EC). Unlike NE, which defines a fixed point of mutual best responses, an EC is a set-valued solution concept designed to capture the asymptotic or long-term behavior of dynamic interactions, even when a traditional best response does not exist. The EC identifies a minimal rectangular set of action profiles that collectively capture oscillatory game dynamics, effectively generalizing the notion of stability beyond static equilibria. An EC satisfies three important properties: \textit{stability} against external deviations (ensuring robustness), \textit{unrest} with respect to internal deviations (driving oscillation), and \textit{minimality} (defining the solution's tightness). This set-valued outcome generalizes the minimal curb set to discontinuous games, where best responses may not exist. In finite games, the EC also relates to sink strongly connected components (SCCs) of the best response graph. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.08471 |
| By: | Yiding Feng; Yaonan Jin |
| Abstract: | A large proportion of the Bayesian mechanism design literature is restricted to the family of regular distributions $\mathbb{F}_{\tt reg}$ [Mye81] or the family of monotone hazard rate (MHR) distributions $\mathbb{F}_{\tt MHR}$ [BMP63], which overshadows this beautiful and well-developed theory. We (re-)introduce two generalizations, the family of quasi-regular distributions $\mathbb{F}_{\tt Q-reg}$ and the family of quasi-MHR distributions $\mathbb{F}_{\tt Q-MHR}$. All four families together form the following hierarchy: $\mathbb{F}_{\tt MHR} \subsetneq (\mathbb{F}_{\tt reg} \cap \mathbb{F}_{\tt Q-MHR}) \subsetneq \mathbb{F}_{\tt Q-reg}$ and $\mathbb{F}_{\tt Q-MHR} \subsetneq (\mathbb{F}_{\tt reg} \cup \mathbb{F}_{\tt Q-MHR}) \subsetneq \mathbb{F}_{\tt Q-reg}$. The significance of our new families is manifold. First, their defining conditions are immediate relaxations of the regularity/MHR conditions (i.e., monotonicity of the virtual value functions and/or the hazard rate functions), which reflect economic intuition. Second, they satisfy natural mathematical properties (about order statistics) that are violated by both original families $\mathbb{F}_{\tt reg}$ and $\mathbb{F}_{\tt MHR}$. Third but foremost, numerous results [BK96, HR09a, CD15, DRY15, HR14, AHN+19, JLTX20, JLQ+19b, FLR19, GHZ19b, JLX23, LM24] established before for regular/MHR distributions now can be generalized, with or even without quantitative losses. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.03583 |
| By: | Adriana Amieva; Agust\'in Bonifacio; Pablo Neme |
| Abstract: | We examine the problem of assigning teachers to public schools over time when teachers have tenured positions and can work simultaneously in multiple schools. To do this, we investigate a dynamic many-to-many school choice problem where public schools have priorities over teachers and teachers hold substitutable preferences over subsets of schools. We introduce a new concept of dynamic stability that recognizes the tenured positions of teachers and we prove that a dynamically stable matching always exists. We propose the Tenured-Respecting Deferred Acceptance $(TRDA)$ mechanism, which produces a dynamically stable matching that is constrained-efficient within the class of dynamically stable matchings and minimizes unjustified claims. To improve efficiency beyond this class, we also propose the Tenured-Respecting Efficiency-Adjusted Deferred Acceptance $(TREADA)$ mechanism, an adaptation of the Efficiency-Adjusted Deferred Acceptance mechanism to our dynamic context. We demonstrate that the outcome of the $TREADA$ mechanism Pareto-dominates any dynamically stable matching and achieves efficiency when all teachers consent. Additionally, we examine the issue of manipulability, showing that although the $TRDA$ and $TREADA$ mechanisms can be manipulated, they remain non-obviously dynamically manipulable under specific conditions on schools' priorities. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.07851 |
| By: | Awad, Emiel; Judd, Gleason; Riquelme, Nicolas |
| Abstract: | How do interest groups learn about and influence politicians over time? We develop a game-theoretic model where an interest group can lobby a politician while learning about their ideological alignment. Our analysis reveals a fundamental tradeoff: interest groups must balance gathering information against exerting immediate influence, while politicians strategically manage their reputations to shape future interactions. These strategic forces generate systematic dynamics: policies and transfers shift in tandem, with early-career politicians showing greater policy variance and extracting larger rents through reputation management than veterans. Uncertainty about alignment increases policy volatility as groups experiment with offers, while institutional features like committee power and revolving-door incentives systematically alter both learning incentives and influence strategies. Our results shed new light on how interest group influence evolves across political careers and varies with institutional context. |
| Date: | 2024–11–11 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:834vd |