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Statistical discrimination without knowing statistics: blame social interactions?

Emily Tanimura ()
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Emily Tanimura: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: We consider a model where decision makers repeatedly receive candidates and assign to them a binary decision that we can interpret as hire/not hire. The decision makers base their decision on the characteristics of the candidate but they are also sensitive to the social influence exerted by the observed past choices of their peers. We characterize the long run frequency of decisions in the model, and show in particular that for candidates belonging to a group with "unfavorable" characteristics, the dynamics increase the rejection rate compared to a scenario with independent decisions, suggesting that influence between decision makers can generate effects very similar to those that result from statistical discrimination. In our model, we then relate the long run outcomes, existence and magnitude of reinforcement to the properties of the characteristics distribution.

Keywords: JEL Classification: D83 D91 J70 C60 R30 Statistical discrimination; Social influence; Binary choice; Decision dynamics; Invariant measures; Reinforcement effects (search for similar items in EconPapers)
Date: 2021-01-04
New Economics Papers: this item is included in nep-mic
Note: View the original document on HAL open archive server: https://hal-paris1.archives-ouvertes.fr/hal-03096126
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