{"title":"Belief updating among college students: Evidence from experimental variation in information","authors":"Matthew Wiswall, basit. zafar","doi":"10.2139/ssrn.1928642","DOIUrl":null,"url":null,"abstract":"We investigate how college students form and update their beliefs about future earnings using a unique ?information? experiment. We provide college students true information about the population distribution of earnings and observe how this information causes respondents to update their beliefs about their own future earnings. We show that college students are substantially misinformed about population earnings and logically revise their self-beliefs in response to the information we provide, with larger revisions when the information is more specific and is good news. We classify the updating behaviors observed and find that the majority of students are non-Bayesian updaters.","PeriodicalId":84751,"journal":{"name":"Field staff reports","volume":"108 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Field staff reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.1928642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
We investigate how college students form and update their beliefs about future earnings using a unique ?information? experiment. We provide college students true information about the population distribution of earnings and observe how this information causes respondents to update their beliefs about their own future earnings. We show that college students are substantially misinformed about population earnings and logically revise their self-beliefs in response to the information we provide, with larger revisions when the information is more specific and is good news. We classify the updating behaviors observed and find that the majority of students are non-Bayesian updaters.