Proceedings of the fifteenth ACM conference on Economics and computation最新文献

{"title":"A dynamic network game for the adoption of new technologies","authors":"Mathieu V. Leduc","doi":"10.1145/2600057.2602891","DOIUrl":"https://doi.org/10.1145/2600057.2602891","url":null,"abstract":"When a product or technology is first introduced, there is uncertainty about its value or quality. This quality can be learned by trying the product, at a risk. It can also be learned by letting others try it and free-riding on the information that they generate. We propose a class of dynamic games to study the adoption of technologies of uncertain value, when agents are connected by a network. This class of games allows for referral incentives, whereby an agent can earn rewards by encouraging his neighbors to adopt. Dynamic network games can pose important tractability issues. To circumvent such problems, we derive a mean-field equilibrium (MFE) and show that a pricing policy that involves referral incentives leads to a double-threshold strategy by which both low and high-degree agents may choose to experiment with the technology of uncertain value whereas the middle-degree agents free-ride on the information revealed by that experimentation. We characterize how different dynamic pricing mechanisms affect the pattern of early/late adoption and information diffusion. Pricing mechanisms that allow a monopolist to guarantee early adoption by agents of high or low degrees are proposed. We show that dynamic pricing policies that do not involve referral incentives (i.e. price discounts for early adopters) always result in lower-degree agents adopting early. Likewise, dynamic pricing policies involving referral incentives that are high enough always result in higher-degree agents adopting early. The only network information needed to implement such pricing mechanisms is the degree distribution. We illustrate how referral incentives can be preferable on certain networks while price discounts may be preferable on others.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130690270","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 performance of deferred-acceptance auctions","authors":"Paul Dütting, Vasilis Gkatzelis, T. Roughgarden","doi":"10.1145/2600057.2602861","DOIUrl":"https://doi.org/10.1145/2600057.2602861","url":null,"abstract":"Deferred-acceptance auctions are auctions for binary single-parameter mechanism design problems whose allocation rule can be implemented using an adaptive reverse greedy algorithm. Milgrom and Segal [2014] recently introduced these auctions and proved that they satisfy a remarkable list of incentive guarantees: in addition to being dominant-strategy incentive-compatible, they are weakly group-strategyproof, can be implemented by ascending-clock auctions, and admit outcome-equivalent full-information pay-as-bid versions. Neither forward greedy mechanisms nor the VCG mechanism generally possess any of these additional incentive properties. The goal of this paper is to initiate the study of deferred-acceptance auctions from an approximation standpoint. We study these auctions through the lens of two canonical welfare-maximization problems, in knapsack auctions and in combinatorial auctions with single-minded bidders. For knapsack auctions, we prove a separation between deferred-acceptance auctions and arbitrary dominant-strategy incentive-compatible mechanisms. While the more general class can achieve an arbitrarily good approximation in polynomial time, and a constant-factor approximation via forward greedy algorithms, the former class cannot obtain an approximation guarantee sub-logarithmic in the number of items m, even with unbounded computation. We also give a polynomial-time deferred-acceptance auction that achieves an approximation guarantee of O(log m) for knapsack auctions.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124981722","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":"Towards a better measure of business proximity: topic modeling for analyzing M As","authors":"Zhan Shi, G. Lee, Andrew Whinston","doi":"10.1145/2600057.2602832","DOIUrl":"https://doi.org/10.1145/2600057.2602832","url":null,"abstract":"In this article, we propose a new measure of firms' dyadic business proximity. Specifically, we analyze the unstructured texts that describe firms' businesses using the natural language processing technique of topic modeling, and develop a novel business proximity measure based on the output. When compared with the existent methods, our approach provides finer granularity on quantifying firms' similarity in the spaces of product, market, and technology. We then show our measure's effectiveness through an empirical analysis using a unique dataset of recent mergers and acquisitions in the U.S. high technology industry. Building upon the literature, our model relates the likelihood of matching of two firms in a merger or acquisition transaction to their business proximity and other characteristics. We particularly employ a class of statistical network analysis methods called exponential random graph models to accommodate the relational nature of the data.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884287","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":"Strategic trading in informationally complex environments","authors":"Nicolas S. Lambert, M. Ostrovsky, Mikhail Panov","doi":"10.1145/2600057.2602842","DOIUrl":"https://doi.org/10.1145/2600057.2602842","url":null,"abstract":"We study trading behavior and the properties of prices in informationally complex markets. Our model is based on the single-period version of the linear-normal framework of [Kyle 1985]. We allow for essentially arbitrary correlations among the random variables involved in the model: the true value of the traded asset, the signals of strategic traders, the signals of competitive market makers, and the demand coming from liquidity traders. We first show that there always exists a unique linear equilibrium, characterize it analytically, and illustrate its properties in a series of examples. We then use this equilibrium characterization to study the informational efficiency of prices as the number of strategic traders becomes large. If the demand from liquidity traders is uncorrelated with the true value of the asset or is positively correlated with it (conditional on other signals), then prices in large markets aggregate all available information. If, however, the demand from liquidity traders is negatively correlated with the true value of the asset, then prices in large markets aggregate all available information except that contained in liquidity demand.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133612680","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":"Managing congestion in decentralized matching markets","authors":"N. Arnosti, Ramesh Johari, Yashodhan Kanoria","doi":"10.1145/2600057.2602893","DOIUrl":"https://doi.org/10.1145/2600057.2602893","url":null,"abstract":"We consider a decentralized two-sided matching market in which agents arrive and depart asynchronously. As a result, it is possible that an agent on one side of the market (a \"buyer\") identifies an agent on the other side of the market (a \"seller\") who is a suitable match, only to find that the seller is already matched. We find using a mean field approach that lack of knowledge about availability can create large welfare losses to both buyers and sellers. We consider a simple intervention available to the platform: limiting visibility of sellers. We find that this intervention can significantly improve the welfare of agents on both sides of the market; sellers pay lower application costs, while buyers are less likely to find that the sellers they screen have already matched. Somewhat counterintuitively, the benefits of showing fewer sellers to each buyer are greatest in markets in which there is a shortage of sellers.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133279848","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":"Finding approximate nash equilibria of bimatrix games via payoff queries","authors":"John Fearnley, Rahul Savani","doi":"10.1145/2600057.2602847","DOIUrl":"https://doi.org/10.1145/2600057.2602847","url":null,"abstract":"We study the deterministic and randomized query complexity of finding approximate equilibria in a k x k bimatrix game. We show that the deterministic query complexity of finding an ε-Nash equilibrium when ε < 1/2 is Ω(k2), even in zero-one constant-sum games. In combination with previous results, this provides a complete characterization of the deterministic query complexity of approximate Nash equilibria. We also study randomized querying algorithms. We give a randomized algorithm for finding a (3--√5/2 + ε)-Nash equilibrium using O(k . log k/ε2) payoff queries, which shows that the 1/2 barrier for deterministic algorithms can be broken by randomization. For well-supported Nash equilibria (WSNE), we first give a randomized algorithm for finding an ε-WSNE of a zero-sum bimatrix game O(k . log k/ε4) payoff queries, and we then use this to obtain a randomized algorithm for finding a (2/3 + ε)-WSNE in a general bimatrix game using O(k . log k /ε2) payoff queries. Finally, we initiate the study of lower bounds against randomized algorithms in the context of bimatrix games, by showing that randomized algorithms require Omega(k2) payoff queries in order to find a 1/6k-Nash equilibrium, even in zero-one constant-sum games. In particular, this rules out query-efficient randomized algorithms for finding exact Nash equilibria.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116532209","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":"Level-0 meta-models for predicting human behavior in games","authors":"J. R. Wright, Kevin Leyton-Brown","doi":"10.1145/2600057.2602907","DOIUrl":"https://doi.org/10.1145/2600057.2602907","url":null,"abstract":"Behavioral game theory seeks to describe the way actual people (as compared to idealized, ``rational'' agents) act in strategic situations. Our own recent work has identified iterative models (such as quantal cognitive hierarchy) as the state of the art for predicting human play in unrepeated, simultaneous-move games [Wright and Leyton-Brown 2012]. Iterative models predict that agents reason iteratively about their opponents, building up from a specification of nonstrategic behavior called level-0. The modeler is in principle free to choose any description of level-0 behavior that makes sense for the given setting; however, in practice almost all existing work specifies this behavior as a uniform distribution over actions. In most games it is not plausible that even nonstrategic agents would choose an action uniformly at random, nor that other agents would expect them to do so. A more accurate model for level-0 behavior has the potential to dramatically improve predictions of human behavior, since a substantial fraction of agents may play level-0 strategies directly, and furthermore since iterative models ground all higher-level strategies in responses to the level-0 strategy. Our work considers ``meta-models'' of level-0 behavior: models of the way in which level-0 agents construct a probability distribution over actions, given an arbitrary game. We evaluated many such meta-models, each of which makes its prediction based only on general features that can be computed from any normal form game. We evaluated the effects of combining each new level-0 meta-model with various iterative models, and in many cases observed large improvements in the models' predictive accuracies. In the end, we recommend a meta-model that achieved excellent performance across the board: a linear weighting of features that requires the estimation of five weights.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123601765","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":"Corporate prediction markets: evidence from google, ford, and firm X","authors":"Bo Cowgill, Eric Zitzewitz","doi":"10.1145/2600057.2602901","DOIUrl":"https://doi.org/10.1145/2600057.2602901","url":null,"abstract":"Despite the popularity of prediction markets among economists, businesses and policymakers have been slow to adopt them in decision making. Most studies of prediction markets outside the lab are from public markets with large trading populations. Corporate prediction markets face additional issues, such as thin- ness, weak incentives, limited entry and the potential for traders with ulterior motives raising questions about how well these markets will perform. We examine data from prediction markets run by Google, Ford and Firm X (a large private materials company). Despite theoretically adverse conditions, we find these markets are relatively efficient, and improve upon the forecasts of experts at all three firms by as much as a 25% reduction in mean squared error. The most notable inefficiency is an optimism bias in the markets at Google and Ford. The inefficiencies that do exist generally become smaller over time. More experienced traders and those with higher past performance trade against the identified inefficiencies, suggesting that the markets efficiency improves because traders gain experience and less skilled traders exit the market.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128470235","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":"Cryptographically blinded games: leveraging players' limitations for equilibria and profit","authors":"Pavel Hubácek, Sunoo Park","doi":"10.1145/2600057.2602903","DOIUrl":"https://doi.org/10.1145/2600057.2602903","url":null,"abstract":"In this work we apply methods from cryptography to enable mutually distrusting players to implement broad classes of mediated equilibria of strategic games without trusted mediation. Our implementation uses a pre-play 'cheap talk' phase, consisting of non- binding communication between players prior to play in the original game. In the cheap talk phase, the players run a secure multi-party computation protocol to sample from an equilibrium of a \"cryptographically blinded\" version of the game, in which actions are encrypted. Coarse correlated equilibrium. Coarse correlated equilibria (CCE) are a generalization of correlated equilibria (CE), invoking a notion of commitment. Suppose a mediator samples an action profile a from a distribution α. We say α is a CCE if no player has incentive not to \"promise\" in advance -- before seeing his advice ai -- to play according to the advice, if he believes that all other players will commit to do the same. Note that players who do not commit will not see the advice at all, and hence must play an independent strategy. In this paper, we address the following question: How can the players of a strategic game implement any CCE via (cryptographic) pre-play communication without trusting each other or a mediator? In the computational setting, we give an implementation for general strategic games, in the form of an extended game comprising a cryptographic protocol in the pre-play phase, which securely samples an action profile for a \"cryptographically blinded\" version of the game. The blinded game's action space consists of encryptions of the original game's actions. Our implementation has the strong property that any computational CCE of the original game corresponds to a payoff-equivalent Nash equilibrium of the extended game. Furthermore, it achieves strategic equivalence, in that every computational Nash equilibrium of the extended game corresponds to a computational CCE of the original game. In the information-theoretic setting, we give an implementation for strategic games with four or more players, using a similar cryptographically blinded pre-play phase given pairwise communication channels. This also achieves strategic equivalence. Both the restriction to four or more players and the need for a stronger communication model are unavoidable in this setting, as shown by impossibility results of [Bárány 1992; Ben-Or et al. 1988; Pease et al. 1980; Aumann and Hart 2003]. Relation to prior work. The pre-play literature considers the problem of implementing equilibria without mediation. Our work generalizes that of [Bárány 1992] in the information-theoretic setting and [Dodis et al. 2000] in the computational setting. It has long been recognized that the possibility to commit to strategies in advance can increase payoffs achievable in a game, starting with [von Stackelberg 1934]; in this work, we achieve the payoffs of CCE without resorting to the usual assumption of binding contracts. Our results are achieved usin","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127478554","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 wisdom of smaller, smarter crowds","authors":"D. Goldstein, R. McAfee, Siddharth Suri","doi":"10.1145/2600057.2602886","DOIUrl":"https://doi.org/10.1145/2600057.2602886","url":null,"abstract":"The \"wisdom of crowds\" refers to the phenomenon that aggregated predictions from a large group of people can rival or even beat the accuracy of experts. In domains with substantial stochastic elements, such as stock picking, crowd strategies (e.g. indexing) are difficult to beat. However, in domains in which some crowd members have demonstrably more skill than others, smart sub-crowds could possibly outperform the whole. The central question this work addresses is whether such smart subsets of a crowd can be identified a priori in a large-scale prediction contest that has substantial skill and luck components. We study this question with data obtained from fantasy soccer, a game in which millions of people choose professional players from the English Premier League to be on their fantasy soccer teams. The better the professional players do in real life games, the more points fantasy teams earn. Fantasy soccer is ideally suited to this investigation because it comprises millions of individual-level, within-subject predictions, past performance indicators, and the ability to test the effectiveness of arbitrary player-selection strategies. We find that smaller, smarter crowds can be identified in advance and that they beat the wisdom of the larger crowd. We also show that many players would do better by simply imitating the strategy of a player who has done well in the past. Finally, we provide a theoretical model that explains the results we see from our empirical analyses.","PeriodicalId":203155,"journal":{"name":"Proceedings of the fifteenth ACM conference on Economics and computation","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127630006","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}