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What Marginal Outcome Tests Can Tell Us About Racially Biased Decision-Making

Peter Hull ()

No 28503, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Marginal outcome tests compare the expected effects of a decision on individuals who are of different races but at the same indifference point of the decision-maker. I present a simple formalization of how such tests can detect racial bias, defined as a deviation from accurate statistical discrimination. Namely, the tests can reject that the decision-maker ranks individuals according to some accurate prediction of a mandated outcome, given some unspecified race-inclusive information set. The frontier of marginal effects can furthermore rule out canonical taste-based discrimination. I relate this analysis to other interpretations of marginal outcome tests, other notions of racial discrimination, and recent identification strategies.

JEL-codes: C21 C36 J15 J71 (search for similar items in EconPapers)
Date: 2021-02
New Economics Papers: this item is included in nep-lma and nep-ure
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