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Deadly Stigma

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  • Manasvini Singh

Abstract

How harmful is stigma in the “real world”? Answers are elusive because stigma is difficult to measure in observational data, and isolating its effects requires exogenous variation in stigma without variation in the stigmatized trait. This study addresses these challenges by focusing on a widespread form of stigma — weight stigma — in the high-stakes setting of inpatient healthcare. BMI categories are displayed prominently to providers in electronic medical records, and obesity is heavily stigmatized socially. Thus, at the "obese" cutoff, stigma may shift discretely while the underlying trait (BMI) does not. Using a regression discontinuity design that exploits this institutional feature, I find a discontinuous increase in in-hospital mortality at this cutoff, though patient health does not change. Two patterns suggest stigma-based discrimination as the mechanism. First, just-obese patients receive less diagnostic effort than almost-obese patients. Second, a physician-validated LLM identifies at the cutoff a rise in stigmatizing language in clinical notes — specifically, language that imposes moral judgment, undermines patient credibility, and stereotypes patients — among the most stigmatizing providers, who also drive the mortality result. Overall, these results suggest that stigma is a powerful social force with potentially life-or-death consequences.

Suggested Citation

  • Manasvini Singh, 2026. "Deadly Stigma," NBER Working Papers 35277, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:35277
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    More about this item

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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