Data and Code for: Experience-based Discrimination

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Project Citation:

Lepage, Louis-Pierre. Data and Code for: Experience-based Discrimination. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-08-16. https://doi.org/10.3886/E192292V1

Project Description

Summary: I present and test a mechanism through which discrimination arises from individual experiences of employers with worker groups. I propose a model in which employers are initially uncertain about the productivity of one of two groups, for example a minority group, and learn through hiring. Learning is endogenous, because hiring experiences of an employer shape their subsequent decisions to hire from the group and therefore learn about its productivity. Positive experiences with the uncertain group lead to positive biases which correct themselves by leading employers to hire more from the group and learn more. In contrast, negative experiences decrease hiring and learning which preserves negative biases, leads to a negatively-skewed belief distribution about the group's productivity across employers, and can cause persistent discrimination in the form of a wage gap. The model explains apparent prejudice as "inaccurate" statistical discrimination and generates novel predictions and policy implications. I then illustrate the formation of biased beliefs from experience in an experimental labor market and find support for key model predictions.

Funding Sources: Russel Sage Foundation (G-2103-31077); Michigan Institute for Teaching and Research in Economics

Scope of Project

JEL Classification:
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      J70 Labor Discrimination: General
      J71 Labor Discrimination

Geographic Coverage: US

Time Period(s): 12/1/2018 – 3/31/2022

Collection Date(s): 12/1/2018 – 3/31/2022

Universe: US adults

Data Type(s): experimental data

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Published Versions

V1 [2024-08-16]

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