{"title":"Disentangling Risk-Aversion and Loss Aversion in First-Price Auctions: An Empirical Approach","authors":"Dong-Hyuk Kim, Anmol Ratan","doi":"10.2139/ssrn.3522274","DOIUrl":null,"url":null,"abstract":"We develop a model which combines general risk-averse preferences with anticipated loss aversion to explain bidding behavior in the first-price auction, where both risk-aversion and loss aversion induce ‘overbidding.’ We then show that the nonparametric utility function and loss aversion coefficient are point-identified by the experiment data with exogenous variation in the number of bidders. Moreover, we develop a structural method with a flexible utility function based on Bernstein polynomials. Our method predicts the data well and the counterfactual analysis shows that loss aversion explains 85 ∼ 90% of overbidding in the data.","PeriodicalId":322168,"journal":{"name":"Human Behavior & Game Theory eJournal","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Behavior & Game Theory eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3522274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We develop a model which combines general risk-averse preferences with anticipated loss aversion to explain bidding behavior in the first-price auction, where both risk-aversion and loss aversion induce ‘overbidding.’ We then show that the nonparametric utility function and loss aversion coefficient are point-identified by the experiment data with exogenous variation in the number of bidders. Moreover, we develop a structural method with a flexible utility function based on Bernstein polynomials. Our method predicts the data well and the counterfactual analysis shows that loss aversion explains 85 ∼ 90% of overbidding in the data.