G2TT
来源类型Discussion paper
规范类型论文
来源IDDP13790
DP13790 Inaccurate Statistical Discrimination: An Identification Problem
Aislinn Bohren; Kareem Haggag; Alex Imas; Devin G. Pope
发表日期2019-06-11
出版年2019
语种英语
摘要Discrimination---differential treatment by group identity---is widely studied in economics. Its source is often categorized as taste-based or statistical (belief-based)---a valuable distinction for policy design and welfare analysis. We argue that in many situations, individuals may have inaccurate beliefs about the relevant characteristics of different groups. This possibility creates an identification problem when isolating the source of discrimination. When not accounted for, we show both theoretically and experimentally that such inaccurate statistical discrimination will be misclassified as taste-based. A review of the empirical discrimination literature in economics reveals the scope of this issue: a small minority of papers---fewer than 7%---consider inaccurate beliefs. We then examine two alternative methodologies for differentiating between these three sources of discrimination---varying the amount of information presented to evaluators and eliciting evaluators' beliefs. We propose a possible intervention: when presented with accurate information, we show that inaccurate statistical discrimination decreases.
主题Industrial Organization ; Labour Economics
关键词Discrimination Inaccurate beliefs
URLhttps://cepr.org/publications/dp13790-0
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/542659
推荐引用方式
GB/T 7714
Aislinn Bohren,Kareem Haggag,Alex Imas,et al. DP13790 Inaccurate Statistical Discrimination: An Identification Problem. 2019.
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