Aislinn Bohren's paper "The Dynamics of Discrimination: Theory and Evidence" won the 2020 Exeter Prize

Aislinn Bohren's paper "The Dynamics of Discrimination: Theory and Evidence" (with Alex Imas and Michael Rosenberg, AER 2019) won the 2020 Exeter Prize for the best paper published in the previous calendar year in a peer-reviewed journal in the fields of Experimental Economics, Behavioural Economics and Decision Theory. 

This paper contains an original natural field experiment on a large online platform with a dynamic manipulation of beliefs and reputation about men and women’s contributions. At the onset, members of the platform are invited to evaluate seeded contributions, differing in male and female characteristics and high or low subjectivity measures, yet containing no history qualification and thus no reputation. The authors find only discrimination against females in evaluations under high subjectivity measures, interpreted as stereotypical belief-based judgments. At a later date, new accounts for female and male “members” are planted with reputation data about ability through real evaluations from the platform members. Now a reversal takes place. Females with high enough reputation receive higher evaluations than their male counterparts, given high subjectivity measures. This switch is modeled through the presence of two evaluators’ belief types: 1. gender-biased types who are unaware of biases and think that others have the same beliefs will evaluate similarly in both phases. 2. Gender-neutral types who believe that others are gender-biased. If the proportion of neutral evaluators is high enough, this will offset discrimination since these react with higher evaluations to those females with a high enough reputation in the second period offsetting the biases of the other types. Within the labor market, this can mean that women with good reputations have better possibilities to climb up the ladder than comparable man. Overcoming stereotypical biases does not work immediately with too little reputation but can flip over time. As a robustness check, the authors evaluate also the corresponding non-seeded data from the platform and find similar results.

The paper makes an important contribution to a question of high social relevance. It highlights a need for studies of dynamics of performance and judgment within female discrimination literature. Furthermore, it demonstrates the importance of the presence of objective evidence regarding performance at early stages of the interaction to offset biases and prejudices – an observation with important policy implication in many organizations.