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, defined as 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. However, in many situations individuals may have inaccurate beliefs about the relevant characteristics of different groups. This paper demonstrates that this possibility creates an identification problem when isolating the source of discrimination. A review of the empirical discrimination literature in economics reveals that a small minority of papers---fewer than 7%---consider inaccurate beliefs. We show both theoretically and experimentally that, if not accounted for, such inaccurate statistical discrimination will be misclassified as taste-based. We then examine three alternative methodologies for differentiating between different sources of discrimination: varying the amount of information presented to evaluators, eliciting their beliefs, and presenting them with accurate information. Importantly, the latter can be used to differentiate whether inaccurate beliefs are due to a lack of information or motivated factors.
主题Industrial Organization ; Labour Economics
关键词Discrimination Inaccurate beliefs Model misspecification
URLhttps://cepr.org/publications/dp13790-1
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/542660
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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