Stereotypes

Pedro  Bordalo; Katherine Baldiga Coffman; Nicola  Gennaioli; Andrei  Shleifer

Article | Quarterly Journal of Economics | November 2016

Stereotypes

by Pedro Bordalo, Katherine Baldiga Coffman, Nicola Gennaioli and Andrei Shleifer

Abstract

We present a model of stereotypes based on Kahneman and Tversky's representativeness heuristic. A decision maker assesses a target group by overweighting its representative types, which we formally define to be the types that occur more frequently in that group than in a baseline reference group. Stereotypes formed in this way contain a "kernel of truth": they are rooted in true differences between groups. They are also context dependent: beliefs about a group depend on the characteristics of the reference group. Because stereotypes emphasize differences, they cause belief distortions, particularly when groups are similar. In line with our predictions, beliefs in the lab about abstract groups and beliefs in the field about political groups are context dependent and distorted in the direction of representative types.

Keywords: Prejudice and Bias;

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Bordalo, Pedro, Katherine Baldiga Coffman, Nicola Gennaioli, and Andrei Shleifer. "Stereotypes." Quarterly Journal of Economics 131, no. 4 (November 2016): 1753–1794.

We conduct laboratory experiments that explore how gender stereotypes shape beliefs about ability of oneself and others in different categories of knowledge. The data reveal two patterns. First, men’s and women’s beliefs about both oneself and others exceed observed ability on average, particularly in difficult tasks. Second, overestimation of ability by both men and women varies across categories. To understand these patterns, we develop a model that separates gender stereotypes from misestimation of ability related to the difficulty of the task. We find that stereotypes contribute to gender gaps in self-confidence, assessments of others, and behavior in a cooperative game.

We run an experiment that features a novel task with deliberation to explore how stereotypes shape group decision-making. We find that women are less likely to be rewarded for their ideas in male-typed domains when gender is known. This is partly due to discrimination and partly due to differences in self-promotion. External analysis of the chat data provides further insights. Though men and women do not vary in their communication styles, coders display pervasive stereotypes, associating warmth with women and competence and negativity with men. We also find that warmer participants, particularly warmer women, are under-rewarded by their groups.

We explore how beliefs respond to noisy information about own ability across a range of tasks, with a particular focus on how gender stereotypes impact belief updating. Participants in our experiments take tests of their ability across different domains. Absent feedback, beliefs of own ability are strongly influenced by gender stereotypes. We then provide noisy feedback about own absolute performance to participants and elicit posterior beliefs. Gender stereotypes have significant predictive power for posterior beliefs, both through their influence on prior beliefs (as predicted by a Bayesian model) and through their influence on updating. Both men and women’s beliefs are more responsive to information in gender congruent domains than gender incongruent domains. This is primarily driven by differential reactions to exogenously received good news about own ability: both men and women react more to good news when it arrives in a gender congruent domain than when it arrives in a gender incongruent domain. Our results have important implications for understanding how feedback shapes gender gaps in self-assessments.

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