Proceedings of the 24th ACM Conference on Economics and Computation最新文献

{"title":"Optimal Test Design for Knowledge-based Screening","authors":"Sulagna Dasgupta","doi":"10.2139/ssrn.4403119","DOIUrl":"https://doi.org/10.2139/ssrn.4403119","url":null,"abstract":"Individuals are evaluated on their factual knowledge in a myriad of settings such as job interviews and exams. In this paper I ask: How to optimally design such an evaluation scheme?","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132756199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confidence and College Applications: Evidence from a Randomized Intervention","authors":"R. Hakimov, Renke Schmacker, Camille Terrier","doi":"10.1145/3580507.3597715","DOIUrl":"https://doi.org/10.1145/3580507.3597715","url":null,"abstract":"Access to elite colleges varies drastically based on gender and socioeconomic status (SES). In the U.S., children from top 1% income families are 77 times more likely to attend an elite institution than those from the bottom 20% income bracket [Chetty et al. 2017]. At the same time, females disproportionately enter less selective colleges and lower-paying jobs than men [Blau and Kahn 2017]. We investigate \"misconfidence\" --- the difference between student perception of their rank in the grade distribution and their real rank in the distribution. It is very common for individuals to have biased beliefs about their own abilities [Möbius et al. 2022]. While several studies show a correlation between confidence and educational choices, there is a lack of causal evidence on the impact of misconfidence on college choices.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121320984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fair allocation in graphs","authors":"G. Christodoulou, A. Fiat, E. Koutsoupias, A. Sgouritsa","doi":"10.1145/3580507.3597764","DOIUrl":"https://doi.org/10.1145/3580507.3597764","url":null,"abstract":"We study envy freeness up to any good (EFX) in settings where valuations can be represented via a graph of arbitrary size where vertices correspond to agents and edges to items. An item (edge) has zero marginal value to all agents (vertices) not incident to the edge. Each vertex may have an arbitrary monotone valuation on the set of incident edges. We first consider allocations that correspond to orientations of the edges, where we show that EFX does not always exist, and furthermore that it is NP-complete to decide whether an EFX orientation exists. Our main result is that (EFX) allocations exist for this setting. This is one of the few cases where EFX allocations are known to exist for more than 3 agents.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124260892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drivers of Digital Attention: Evidence from a Social Media Experiment","authors":"Guy Aridor","doi":"10.2139/ssrn.4324213","DOIUrl":"https://doi.org/10.2139/ssrn.4324213","url":null,"abstract":"In this paper I report the results of an experiment where I continuously monitor how participants spend time on digital services and shut off their access to Instagram or YouTube on their phones for 1 or 2 weeks. I use the resulting data on how participants substitute their time during and after the restrictions in order to uncover a rich picture of the demand for social media and entertainment applications. I illustrate how the estimated substitution patterns can be used to guide questions of market definition that have troubled regulators.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125542108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combinatorial Inference on the Optimal Assortment in the Multinomial Logit Model","authors":"Shuting Shen, Xi Chen, Ethan X. Fang, Junwei Lu","doi":"10.1145/3580507.3597753","DOIUrl":"https://doi.org/10.1145/3580507.3597753","url":null,"abstract":"Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive literature dealing with optimization algorithms and latent score estimation, uncertainty quantification for the optimal assortment still needs to be explored and is of great practical significance. Instead of estimating and recovering the complete optimal offer set, decision-makers may only be interested in testing whether a given property holds true for the optimal assortment, such as whether they should include several products of interest in the optimal set, or how many categories of products the optimal set should include. This paper proposes a novel inferential framework for testing such properties. We consider the widely adopted multinomial logit (MNL) model, where we assume that each customer will purchase an item j within the offer set of products S with a probability proportional to the underlying preference score u*j associated with the product. For a full assortment of n products, our objective is to conduct a hypothesis test concerning a general optimal assortment property, given by: [EQUATION] where S* denotes the optimal offer set, and S0 is a set of offer sets satisfying the property of interest. We reduce inferring a general optimal assortment property to quantifying the uncertainty associated with the sign change point detection of the marginal revenue gaps defined as [EQUATION], where r1 ≥ ... ≥ rn are the revenue parameters associated with the n products. By plugging in the Newton-debiased maximum likelihood estimator (MLE) for the latent preference scores, we obtain the marginal revenue gap estimators [EQUATION] and show their asymptotic normality. Furthermore, we construct a maximum statistic via the gap estimators to detect the sign change point: [EQUATION] where [EQUATION] is a consistent estimator for the asymptotic variance of [EQUATION]. By approximating the distribution of the maximum statistic with multiplier bootstrap techniques, we propose a valid testing procedure. We also conduct numerical experiments to assess the performance of our method.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126885909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Power of Menus in Contract Design","authors":"Guru Guruganesh, Jon Schneider, Joshua Wang, Junyao Zhao","doi":"10.1145/3580507.3597735","DOIUrl":"https://doi.org/10.1145/3580507.3597735","url":null,"abstract":"We study the power of menus of contracts in principal-agent problems with adverse selection (agents can be one of several types) and moral hazard (we cannot observe agent actions directly). For principal-agent problems with T types and n actions, we show that the best menu of contracts can obtain a factor Ω (max(n, log T)) more utility for the principal than the best individual contract, partially resolving an open question of Guruganesh et al. [2021]. We then turn our attention to randomized menus of linear contracts, where we likewise show that randomized linear menus can be Ω(T) better than the best single linear contract. As a corollary, we show this implies an analogous gap between deterministic menus of (general) contracts and randomized menus of contracts (as introduced by Castiglioni et al. [2022]).","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122855387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nearly Optimal Committee Selection For Bias Minimization","authors":"Yang Cai, Eric Xue","doi":"10.1145/3580507.3597761","DOIUrl":"https://doi.org/10.1145/3580507.3597761","url":null,"abstract":"We study the model of metric voting initially proposed by Feldman et al. [2020]. In this model, experts and candidates are located in a metric space, and each candidate possesses a quality that is independent of her location. An expert evaluates each candidate as the candidate's quality less the distance between the candidate and the expert in the metric space. The expert votes for her favorite candidate. Naturally, the expert prefers candidates that are \"similar\" to herself, i.e., close to her location in the metric space, thus creating bias in the vote. The goal is to select a voting rule and a committee of experts to mitigate the bias. More specifically, given m candidates, what is the minimum number of experts needed to ensure that the voting rule selects a candidate whose quality is at most ε worse than the best one? Our first main result is a new way to select the committee using exponentially less experts compared to the method proposed in Feldman et al. [2020]. Our second main result is a novel construction that substantially improves the lower bound on the committee size. Indeed, our upper and lower bounds match in terms of m, the number of candidates, and ε, the desired accuracy, for general convex normed spaces, and differ by a multiplicative factor that only depends on the dimension of the underlying normed space but is independent of other parameters of the problem. We further extend the nearly matching upper and lower bounds to the setting in which each expert returns a ranking of her top k candidates and we wish to choose ℓ candidates with cumulative quality at most ε worse than that of the best set of ℓ candidates, settling an open problem of Feldman et al. [2020]. Finally, we consider the setting where there are multiple rounds of voting. We show that by introducing another round of voting, the number of experts needed to guarantee the selection of an ε-optimal candidate becomes independent of the number of candidates.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116283497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tâtonnement in Homothetic Fisher Markets","authors":"Denizalp Goktas, Jiayi Zhao, A. Greenwald","doi":"10.1145/3580507.3597746","DOIUrl":"https://doi.org/10.1145/3580507.3597746","url":null,"abstract":"A prevalent theme in the economics and computation literature is to identify natural price-adjustment processes by which sellers and buyers in a market can discover equilibrium prices. An example of such a process is tâtonnement, an auction-like algorithm first proposed in 1874 by French economist Walras in which sellers adjust prices based on the Marshallian demands of buyers, i.e., budget-constrained utility-maximizing demands. A dual concept in consumer theory is a buyer's Hicksian demand, i.e., consumptions that minimize expenditure while achieving a desired utility level. In this paper, we identify the maximum of the absolute value of the elasticity of the Hicksian demand, i.e., the maximum percentage change in the Hicksian demand of any good w.r.t. the change in the price of some other good, as an economic parameter sufficient to capture and explain a range of convergent and non-convergent tâtonnement behaviors in a broad class of markets. In particular, we prove the convergence of tâtonnement at a rate of O((1+ε2)/T), in homothetic Fisher markets with bounded price elasticity of Hicksian demand, i.e., Fisher markets in which consumers have preferences represented by homogeneous utility functions and the price elasticity of their Hicksian demand is bounded, where ε is the maximum absolute value of the price elasticity of Hicksian demand across all buyers. Our result not only generalizes known convergence results for CES Fisher markets, but extends them to mixed nested CES markets and Fisher markets with continuous, possibly non-concave, homogeneous utility functions. Our convergence rate covers the full spectrum of nested CES utilities, including Leontief and linear utilities, unifying previously existing disparate convergence and non-convergence results. In particular, for ε = 0, i.e., Leontief markets, we recover the best-known convergence rate of O(1/T), and as ε → ∞, e.g., linear Fisher markets, we obtain non-convergent behavior, as expected.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131322899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Causal Estimation of User Learning in Personalized Systems","authors":"Evan Munro, David Jones, Jennifer Brennan, Roland Nelet, V. Mirrokni, Jean Pouget-Abadie","doi":"10.1145/3580507.3597702","DOIUrl":"https://doi.org/10.1145/3580507.3597702","url":null,"abstract":"In online platforms, the impact of a treatment on an observed outcome may change over time as 1) users learn about the intervention, and 2) the system personalization, such as individualized recommendations, change over time. We introduce a non-parametric causal model of user actions in a personalized system. We show that the Cookie-Cookie-Day (CCD) experiment, designed for the measurement of the user learning effect, is biased when there is personalization. We derive new experimental designs that intervene in the personalization system to generate the variation necessary to separately identify the causal effect mediated through user learning and personalization. Making parametric assumptions allows for the estimation of long-term causal effects based on medium-term experiments. In simulations, we show that our new designs successfully recover the dynamic causal effects of interest.","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generalized Veto Core and a Practical Voting Rule with Optimal Metric Distortion","authors":"Fatih Erdem Kizilkaya, D. Kempe","doi":"10.1145/3580507.3597798","DOIUrl":"https://doi.org/10.1145/3580507.3597798","url":null,"abstract":"We revisit the recent breakthrough result of Gkatzelis et al. on (single-winner) metric voting, which showed that the optimal distortion of 3 can be achieved by a mechanism called PluralityMatching. The rule picks an arbitrary candidate for whom a certain candidate-specific bipartite graph contains a perfect matching. Subsequently, a much simpler rule called PluralityVeto was shown to achieve distortion 3 as well; this rule only constructs such a matching implicitly, but it, too, makes some arbitrary decisions affecting the outcome. Our point of departure is the question whether there is an intuitive interpretation of this matching, with the goal of identifying the underlying source of arbitrariness in these rules. We first observe directly from Hall's condition that a matching for candidate c certifies that there is no coalition of voters that can jointly counterbalance the number of first-place votes c received, along with the first-place votes of all candidates ranked lower than c by any voter in this coalition. This condition closely mirrors the classical definition of the (proportional) veto core in social choice theory, except that coalitions can veto a candidate c whenever their size exceeds the plurality score of c, rather than the average number of voters per candidate. Based on this connection, we define a general notion of the veto core with arbitrary weights for voters and candidates which respectively represent the veto power and the public support they have. This connection opens up a number of immediate consequences. Previous methods for electing a candidate from the veto core can be interpreted simply as matching algorithms. Different election methods realize different matchings, in turn witnessing different sets of candidates as winners. Viewed through this lens, we first resolve nontrivial tie breaking issues contributing to the inherent arbitrariness of the above rules. Our approach to ties reveals a novel characterization of the (general) veto core, showing it to be identical to the set of candidates who can emerge as winners under a natural class of matching algorithms reminiscent of SerialDictatorship. Then, we extend this class of voting rules into continuous time, and obtain a highly practical voting rule with optimal distortion 3, which is also intuitive and easy to explain: Each candidate starts off with public support equal to his plurality score. From time 0 to 1, every voter continuously brings down, at rate 1, the support of her bottom choice among not-yet-eliminated candidates. A candidate is eliminated if he is opposed by a voter after his support reaches 0. On top of being anonymous and neutral, the absence of arbitrary non-deterministic choices in this rule allows for the study of other axiomatic properties that are desirable in practice. We show that the canonical voting rule we propose for electing from the (plurality) veto core also satisfies resolvability, monotonicity, majority, majority loser, mutual majori","PeriodicalId":210555,"journal":{"name":"Proceedings of the 24th ACM Conference on Economics and Computation","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126220262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}