J. Aislinn Bohren, Kareem Haggag, Alex Imas, Devin G. Pope
{"title":"不准确的统计歧视:一个识别问题","authors":"J. Aislinn Bohren, Kareem Haggag, Alex Imas, Devin G. Pope","doi":"10.1162/rest_a_01367","DOIUrl":null,"url":null,"abstract":"Abstract We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. While individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using theory and a labor market experiment, we show that failing to account for inaccurate beliefs leads to a misclassification of source. We outline three methods to identify source: varying observed signals, belief elicitation, and an intervention to target inaccurate beliefs.","PeriodicalId":275408,"journal":{"name":"The Review of Economics and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inaccurate Statistical Discrimination: An Identification Problem\",\"authors\":\"J. Aislinn Bohren, Kareem Haggag, Alex Imas, Devin G. Pope\",\"doi\":\"10.1162/rest_a_01367\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. While individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using theory and a labor market experiment, we show that failing to account for inaccurate beliefs leads to a misclassification of source. We outline three methods to identify source: varying observed signals, belief elicitation, and an intervention to target inaccurate beliefs.\",\"PeriodicalId\":275408,\"journal\":{\"name\":\"The Review of Economics and Statistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Review of Economics and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1162/rest_a_01367\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Review of Economics and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/rest_a_01367","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inaccurate Statistical Discrimination: An Identification Problem
Abstract We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. While individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using theory and a labor market experiment, we show that failing to account for inaccurate beliefs leads to a misclassification of source. We outline three methods to identify source: varying observed signals, belief elicitation, and an intervention to target inaccurate beliefs.