On the Origin and Persistence of Identity-Driven Choice Behavior
Recent literature shows how a priori identical individuals belonging to different social groups make different choices. This paper proposes a novel explanation for this identity-driven choice behavior. Agents choose whether to undertake a task with a probability of success driven by an ability. They have a noisy perception of this ability and observe social cues that stem from the prevalence of their subgroup among the successful individuals. Although the noise in their perception is unbiased, it has an asymmetric effect on expected utility. This makes it optimal for certain agents to bias their noisy perception with social cues, even when these cues are irrelevant in a Bayesian sense. I show the existence of a stable population equilibrium in which both task allocation and the use of social cues differ between a priori identical subgroups.
Keywords: Social Identity, Belief Formation, Decision Making, Diversity
Intersectionality and Individual Choice Behavior
Intersectionality refers to the interconnection of social organizations, such as gender and race, that create interdependent systems of disadvantage. This paper introduces intersectionality in individual decision making, analyzing the phenomenon in a setting without interaction between agents. I extend the model presented in Liqui Lung (2022) to analyze agents with multidimensional social identities. I show how an intersectional lens sheds light on choice behavior and inequalities that are not visible when using a one-dimensional perspective on social identity. I discuss the effects of social constraints, such as stigmatization, and use the framework to analyze the effects of affirmative action policy on choice behavior. I show how an intersectional view leads to novel insights that are important for the development of the adequate policies to achieve diversity and fight harmful stereotypes.
Keywords: Social Identity, Belief Formation, Decision Making, Intersectionality
Work In progress
The role of Irrelevant Information in improving Decision Making: An Experiment
This paper analyzes how the use of information that is irrelevant in a Bayesian sense can improve decision making on average. I design an experiment in which participants learn about a state of the world. Throughout the experiment, participants choose actions that translate in a bonus payment. They maximize their expected earnings by choosing actions that reflect a correct belief about the state of the world. Although the experiment in designed so that participants should be able to learn their true state of the world over time, the environment makes them prone to making mistakes in their choice of action. I test whether and how participants use an irrelevant statistic regarding the outcomes of another participant to limit the negative effects of potentially making these mistakes.
Keywords: Information, Decision Making under Uncertainty, Motivated Beliefs
De nieuwe DNB conjunctuur indicator voorspelt afvlakking groei in 2019 (The New Dutch Central Bank Business Cycle Indicator Predicts decrease in Economic Growth for 2019) with Bas Butler and Maikel Volkerink, Economisch Statistisch Bulletin, Feb 28 (2019)