|
on Microeconomics |
| By: | Chongwoo Choe (Monash University, Department of Economics); Shingo Ishiguro (Osaka University, Graduate School of Economics) |
| Abstract: | We study optimal organization design with one principal and two agents, who interact through long-term relational contracts. In centralization, the principal contracts with both agents. In hierarchy, the principal contracts with one agent, who is delegated authority to contract with the other agent. We derive necessary and sufficient conditions for each organizational structure to achieve the first best. Hierarchy outperforms centralization when players are sufficiently patient and business conditions are favorable enough to alleviate agents’ incentive problems. We apply our theory to evaluate the two contrasting models of supplier networks in the automotive industry in Japan and the US. |
| Keywords: | Relational Contracts, Centralization, Hierarchy, Supplier Networks |
| JEL: | D23 D82 D86 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:mos:moswps:2022-08&r= |
| By: | Rhodes, Andrew; Zhou, Jidong |
| Abstract: | We study personalized pricing (or first-degree price discrimination) in a general oligopoly model. In the short-run, when the market structure is fixed, the impact of personalized pricing hinges on the degree of market coverage (i.e., how many consumers buy). If coverage is high (e.g., because the production cost is low, or the number of firms is large), personalized pricing intensifies competition and so harms firms but benefits consumers, whereas the opposite is true if coverage is low. However in the long-run, when the market structure is endogenous, personalized pricing always benefits consumers because it induces the socially optimal level of firm entry. We also study the asymmetric case where some firms can use consumer data to price discriminate while others cannot, and show it can be worse for consumers than when either all or no firms can personalize prices. |
| JEL: | D43 D82 L13 |
| Date: | 2022–05–09 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:126889&r= |
| By: | Marco Sahm |
| Abstract: | I characterize the optimal accuracy level r of an unbiased Tullock contest between two players with heterogeneous prize valuations. The designer maximizes the winning probability of the strong player or the winner’s expected valuation by choosing a contest with an all-pay auction equilibrium (r ≥ 2). By contrast, if she aims at maximizing the expected aggregate effort or the winner’s expected effort, she will choose a contest with a pure-strategy equilibrium, and the optimal accuracy level r |
| Keywords: | Tullock contest, heterogeneous valuations, accuracy, discrimination, optimal design, all-pay auction |
| JEL: | C72 D72 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9601&r= |
| By: | Onur A. Koska; Frank Stähler |
| Abstract: | This paper discusses the role of secret versus public reserve prices when bidders’ valuations depend positively on the seller’s private signal. A public reserve price is announced before the auction starts, and a secret reserve price is disclosed after the highest bid has been reached. The public reserve price regime may warrant a distortion as a good seller type may have to increase the reserve price beyond payo˙-maximization in order to be able to credibly signal her type. We introduce and determine a rational signaling equilibrium which adds two domination-based conditions to the belief structure of a weak perfect Bayesian equilibrium. We show that a secret (public) reserve price design qualifies as an equilibrium if the distortion is large (small). |
| Keywords: | auctions, interdependent values, optimal reserve prices, rational signaling |
| JEL: | D44 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9581&r= |
| By: | Edith Elkind; Abheek Ghosh; Paul Goldberg |
| Abstract: | We study how to incentivize agents in a target group to produce a higher output in the context of incomplete information, by means of rank-order allocation contests. We describe a symmetric Bayes--Nash equilibrium for contests that have two types of rank-based prizes: prizes that are accessible only to the agents in the target group; prizes that are accessible to everyone. We also specialize this equilibrium characterization to two important sub-cases: (i) contests that do not discriminate while awarding the prizes, i.e., only have prizes that are accessible to everyone; (ii) contests that have prize quotas for the groups, and each group can compete only for prizes in their share. For these models, we also study the properties of the contest that maximizes the expected total output by the agents in the target group. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.14051&r= |
| By: | Marie Obidzinski (Université Paris Panthéon Assas, CRED EA 7321, 75005 Paris, France); Yves Oytana (CRESE EA3190, Univ. Bourgogne Franche-Comté, F-25000 Besançon, France) |
| Abstract: | We study the design of optimal liability rules when the use of an advisory algorithm by a human operator (she) may generate an external harm. An artificial intelligence (AI) manufacturer (he) chooses the level of quality with which the algorithm is developed and the price at which it is distributed. The AI gives 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 rule. |
| Keywords: | Liability rules, Decision-making, Artificial intelligence, Cognitive bias, Judgment, Prediction |
| JEL: | K4 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:crb:wpaper:2022-04&r= |
| By: | Diego Carrasco-Novoa (School of Economics, University of Queensland, Brisbane, Australia); Allan Hernández-Chanto (School of Economics, University of Queensland, Brisbane, Australia) |
| Abstract: | We analyze security-bid auctions in which two risk-neutral sellers compete for riskaverse bidders. Sellers face a tradeoff in steepness because steeper securities extract more surplus but feature lower participation ex-ante. Nonetheless, steeper securities also provide higher insurance, making bidders more aggressive. We show that when bidders are homogeneously risk-averse, all equilibria are symmetric. Meanwhile, when they are heterogeneously risk-averse, there is always an equilibrium in which one seller chooses a steeper family to serve the more-risk-averse bidders, while the other chooses a flatter family to serve the less-risk-averse bidders. This result resembles a “Hotelling location” model in the steepness spectrum. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:qld:uq2004:655&r= |
| By: | Wanchang Zhang |
| Abstract: | I consider a mechanism design problem of selling multiple goods to multiple bidders when the designer has minimal amount of information. I assume that the designer only knows the upper bounds of bidders' values for each good and has no additional distributional information. The designer takes a minimax regret approach. The expected regret from a mechanism given a joint distribution over value profiles and an equilibrium is defined as the difference between the full surplus and the expected revenue. The designer seeks a mechanism, referred to as a minimax regret mechanism, that minimizes her worst-case expected regret across all possible joint distributions over value profiles and all equilibria. I find that a separate second-price auction with random reserves is a minimax regret mechanism for general upper bounds. Under this mechanism, the designer holds a separate auction for each good; the formats of these auctions are second-price auctions with random reserves. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.13726&r= |
| By: | Jerry Anunrojwong; Santiago Balseiro; Omar Besbes |
| Abstract: | Classical Bayesian mechanism design relies on the common prior assumption, but the common prior is often not available in practice. We study the design of prior-independent mechanisms that relax this assumption: the seller is selling an indivisible item to $n$ buyers such that the buyers' valuations are drawn from a joint distribution that is unknown to both the buyers and the seller; buyers do not need to form beliefs about competitors, and the seller assumes the distribution is adversarially chosen from a specified class. We measure performance through the worst-case regret, or the difference between the expected revenue achievable with perfect knowledge of buyers' valuations and the actual mechanism revenue. We study a broad set of classes of valuation distributions that capture a wide spectrum of possible dependencies: independent and identically distributed (i.i.d.) distributions, mixtures of i.i.d. distributions, affiliated and exchangeable distributions, exchangeable distributions, and all joint distributions. We derive in quasi closed form the minimax values and the associated optimal mechanism. In particular, we show that the first three classes admit the same minimax regret value, which is decreasing with the number of competitors, while the last two have the same minimax regret equal to that of the case $n = 1$. Furthermore, we show that the minimax optimal mechanisms have a simple form across all settings: a second-price auction with random reserve prices, which shows its robustness in prior-independent mechanism design. En route to our results, we also develop a principled methodology to determine the form of the optimal mechanism and worst-case distribution via first-order conditions that should be of independent interest in other minimax problems. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.10478&r= |
| By: | Alfio Giarlotta; Angelo Petralia; Stephen Watson |
| Abstract: | We describe a context-sensitive model of choice, in which the selection process is shaped not only by the attractiveness of items but also by their semantics ('salience'). All items are ranked according to a relation of salience, and a linear order is associated to each item. The selection of a single element from a menu is justified by one of the linear orders indexed by the most salient items in the menu. The general model provides a structured explanation for any observed behavior, and allows us to to model the 'moodiness' of a decision maker, which is typical of choices requiring as many distinct rationales as items. Asymptotically all choices are moody. We single out a model of linear salience, in which the salience order is transitive and complete, and characterize it by a behavioral property, called WARP(S). Choices rationalizable by linear salience can only exhibit non-conflicting violations of WARP. We also provide numerical estimates, which show the high selectivity of this testable model of bounded rationality. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.08798&r= |
| By: | Jacob Coreno; Ivan Balbuzanov |
| Abstract: | This paper considers the problem of allocating bundles of heterogeneous and indivisible objects to agents, when monetary transfers are not allowed and agents reveal only ordinal preferences over objects, e.g., allocating players' contract rights to teams in professional sporting leagues. Preferences over objects are extended to incomplete preferences over bundles using pairwise dominance. We provide a simple characterization of the class of draft rules: they are the only allocation rules satisfying $\textit{efficiency}$, $\textit{respectfulness of the priority}$, $\textit{envy-freeness up to one object}$ and $\textit{resource-monotonicity}$. We also prove two impossibility theorems: (i) $\textit{non-wastefulness}$, $\textit{respectfulness of the priority}$ and $\textit{envy-freeness up to one object}$ are incompatible with $\textit{weak strategy-proofness}$; (ii) $\textit{efficiency}$ and $\textit{envy-freeness up to one object}$ are incompatible with $\textit{weak strategy-proofness}$. If agents may declare some objects unacceptable, then draft rules are characterized by $\textit{efficiency}$, $\textit{respectfulness of the priority}$, $\textit{envy-freeness up to one object}$, $\textit{resource-monotonicity}$ together with a mild invariance property called $\textit{truncation-invariance}$. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.08300&r= |
| By: | BOUCKAERT, Jan; STENNEK, Johan |
| Abstract: | We study how the legal profession manages representational conflicts of interest. Such conflicts arise when the same law firm represents clients with adverse interests. They may compromise the legal process, ultimately jeopardizing social welfare. We argue that current ethical standards, emphasizing disqualification over Chinese walls, may actually worsen the clients’ situation. Instead, the clients’ interests are today mainly protected by law firms being small. Despite low market concentration, law firms enjoy high earnings as representational conflicts create negative network externalities at the firm level. These profits are not eroded even in the long run as entry occurs through firm splitups. |
| Keywords: | Law firms, Professional services, Dual representation, Representational conflicts of interest, Ethical standards, Chinese walls, Recusals, Negative network externalities, Competition, Self-regulation |
| JEL: | K40 L13 L22 L44 L84 |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:ant:wpaper:2022002&r= |
| By: | Felix Brandt; Patrick Lederer; Warut Suksompong |
| Abstract: | Social decision schemes (SDSs) map the preferences of individual voters over multiple alternatives to a probability distribution over the alternatives. In order to study properties such as efficiency, strategyproofness, and participation for SDSs, preferences over alternatives are typically lifted to preferences over lotteries using the notion of stochastic dominance (SD). However, requiring strategyproofness or participation with respect to this preference extension only leaves room for rather undesirable SDSs such as random dictatorships. Hence, we focus on the natural but little understood pairwise comparison (PC) preference extension, which postulates that one lottery is preferred to another if the former is more likely to return a preferred outcome. In particular, we settle three open questions raised by Brandt (2017): (i) there is no Condorcet-consistent SDS that satisfies PC-strategyproofness; (ii) there is no anonymous and neutral SDS that satisfies PC-efficiency and PC-strategyproofness; and (iii) there is no anonymous and neutral SDS that satisfies PC-efficiency and strict PC-participation. All three impossibilities require m >= 4 alternatives and turn into possibilities when m |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.12436&r= |
| By: | Gregor Langus; Vilen Lipatov |
| Abstract: | We identify features of interactions on online platforms that make an ad-funded business model attractive for the platform, but also for consumers. We then show that ad-funded platforms heavily rely on data for their ability to create value for their users. Formally, we show that data restrictions may trigger a switch away from ad-funded to fee-funded model, resulting in a loss of consumer welfare. We also argue that restricting the effort to increase data quality weakens competition to the detriment of consumers. |
| Keywords: | ad-funded business model, data aggregation restrictions, targeted advertising, platform competition, merchant competition, transaction costs |
| JEL: | K21 L22 L40 M37 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9525&r= |
| By: | Jian Low; Chen Hajaj; Yevgeniy Vorobeychik |
| Abstract: | We present a rotating proposer mechanism for team formation, which implements a Pareto efficient subgame perfect Nash equilibrium of an extensive-form team formation game. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.04251&r= |
| By: | Xinyu Hua (Department of Economics, The Hong Kong University of Science and Technology); Kathryn E. Spier (Harvard Law School and NBER) |
| Abstract: | A firm licenses a product to overlapping generations of heterogeneous consumers. Consumers may purchase the product, pirate/steal it, or forego it. Higher consumer types enjoy higher gross benefits and are caught stealing at a higher rate. In this framework, the firm may commit to an out-of-court settlement policy that is “soft†on pirates, so high-types purchase the product and low-types steal the product until caught and subsequently settle. Settlement contracts, which include both cash payments and licenses for future product use, facilitate price discrimination. License duration is (weakly) longer when property rights are stronger, network externalities are significant, and entry threats exist. Settlement may either create social value by expanding the market or destroy social value by limiting market access and possibly deterring more efficient entrants. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:hke:wpaper:wp2021-04&r= |
| By: | Yongmin Chen (University of Colorado Boulder); Xinyu Hua (Hong Kong University of Science and Technology); Keith E. Maskus (University of Colorado Boulder) |
| Abstract: | We study the international protection of consumer data in a model where data from product sales generate additional revenue to firms but disutility to consumers. When data usage lacks transparency, a firm suffers a commitment problem and overuses consumer data. As transparency increases, the firm may adjust prices inefficiently across countries with different privacy preferences. Contrary to the result in the single-country case, more transparency can exacerbate data-usage and output distortions in the global economy, and unilaterally-imposed regulation on data usage may reduce global welfare. There can be substantial gains from international coordination – though not necessarily uniformity – of data regulations. |
| Keywords: | consumer data, privacy, multinational Örm, regulation, data localization, international coordination |
| JEL: | F23 D18 L15 |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:hke:wpaper:wp2020-04&r= |