{"title":"Attributes: Selective Learning and Influence","authors":"Arjada Bardhi","doi":"10.3982/ECTA18355","DOIUrl":null,"url":null,"abstract":"<p>An agent selectively samples attributes of a complex project so as to influence the decision of a principal. The players disagree about the weighting, or relevance, of attributes. The correlation across attributes is modeled through a Gaussian process, the covariance function of which captures pairwise attribute similarity. The key trade-off in sampling is between the alignment of the players' posterior values for the project and the variability of the principal's decision. Under a natural property of the attribute correlation—the <i>nearest-attribute property</i> (NAP)—each optimal attribute is relevant for some player and at most two optimal attributes are relevant for only one player. We derive comparative statics in the strength of attribute correlation and examine the robustness of our findings to violations of NAP for a tractable class of distance-based covariances. The findings carry testable implications for attribute-based product evaluation and strategic selection of pilot sites.</p>","PeriodicalId":50556,"journal":{"name":"Econometrica","volume":null,"pages":null},"PeriodicalIF":6.6000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrica","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.3982/ECTA18355","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
An agent selectively samples attributes of a complex project so as to influence the decision of a principal. The players disagree about the weighting, or relevance, of attributes. The correlation across attributes is modeled through a Gaussian process, the covariance function of which captures pairwise attribute similarity. The key trade-off in sampling is between the alignment of the players' posterior values for the project and the variability of the principal's decision. Under a natural property of the attribute correlation—the nearest-attribute property (NAP)—each optimal attribute is relevant for some player and at most two optimal attributes are relevant for only one player. We derive comparative statics in the strength of attribute correlation and examine the robustness of our findings to violations of NAP for a tractable class of distance-based covariances. The findings carry testable implications for attribute-based product evaluation and strategic selection of pilot sites.
代理人对复杂项目的属性进行选择性采样,以影响委托人的决策。双方对属性的权重或相关性存在分歧。属性间的相关性通过高斯过程来建模,其协方差函数反映了成对属性的相似性。采样中的关键权衡是项目参与者后验值的一致性与委托人决策的可变性之间的权衡。根据属性相关性的一个自然属性--最近属性属性(NAP)--每个最优属性都与某些参与者相关,而最多有两个最优属性只与一个参与者相关。我们推导出了属性相关性强度的比较统计量,并检验了我们的发现对违反 NAP 的稳健性,适用于一类基于距离的协方差。这些发现对基于属性的产品评估和试验场地的战略选择具有可检验的意义。
期刊介绍:
Econometrica publishes original articles in all branches of economics - theoretical and empirical, abstract and applied, providing wide-ranging coverage across the subject area. It promotes studies that aim at the unification of the theoretical-quantitative and the empirical-quantitative approach to economic problems and that are penetrated by constructive and rigorous thinking. It explores a unique range of topics each year - from the frontier of theoretical developments in many new and important areas, to research on current and applied economic problems, to methodologically innovative, theoretical and applied studies in econometrics.
Econometrica maintains a long tradition that submitted articles are refereed carefully and that detailed and thoughtful referee reports are provided to the author as an aid to scientific research, thus ensuring the high calibre of papers found in Econometrica. An international board of editors, together with the referees it has selected, has succeeded in substantially reducing editorial turnaround time, thereby encouraging submissions of the highest quality.
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