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A Discrimination Report Card

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Listed:
  • Patrick Kline
  • Evan K. Rose
  • Christopher R. Walters

Abstract

We develop an Empirical Bayes grading scheme that balances the informativeness of the assigned grades against the expected frequency of ranking errors. Applying the method to a massive correspondence experiment, we grade the racial biases of 97 U.S. employers. A four-grade ranking limits the chances that a randomly selected pair of firms is mis-ranked to 5% while explaining nearly half of the variation in firms' racial contact gaps. The grades are presented alongside measures of uncertainty about each firm's contact gap in an accessible rubric that is easily adapted to other settings where ranks and levels are of simultaneous interest.

Suggested Citation

  • Patrick Kline & Evan K. Rose & Christopher R. Walters, 2023. "A Discrimination Report Card," Papers 2306.13005, arXiv.org.
    • Handle: RePEc:arx:papers:2306.13005
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    References listed on IDEAS

    as
    1. Jonathan T. Kolstad, 2013. "Information and Quality when Motivation is Intrinsic: Evidence from Surgeon Report Cards," NBER Working Papers 18804, National Bureau of Economic Research, Inc.
    2. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood," American Economic Review, American Economic Association, vol. 104(9), pages 2633-2679, September.
    3. Bergman, Peter & Chan, Eric & Kapor, Adam, 2020. "Housing Search Frictions: Evidence from Detailed Search Data and a Field Experiment," IZA Discussion Papers 13006, Institute of Labor Economics (IZA).
    4. Smith, John H, 1973. "Aggregation of Preferences with Variable Electorate," Econometrica, Econometric Society, vol. 41(6), pages 1027-1041, November.
    5. Amanda Y. Agan & Diag Davenport & Jens Ludwig & Sendhil Mullainathan, 2023. "Automating Automaticity: How the Context of Human Choice Affects the Extent of Algorithmic Bias," NBER Working Papers 30981, National Bureau of Economic Research, Inc.
    6. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    7. Raj Chetty & John N. Friedman & Nathaniel Hendren & Maggie R. Jones & Sonya R. Porter, 2018. "The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility," Working Papers 18-42, Center for Economic Studies, U.S. Census Bureau.
    8. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    9. Patrick Kline, 2023. "A Comment on: “Invidious Comparisons: Ranking and Selection as Compound Decisions” by Jiaying Gu and Roger Koenker," Econometrica, Econometric Society, vol. 91(1), pages 47-52, January.
    10. Bergman, Peter & Hill, Matthew J., 2018. "The effects of making performance information public: Regression discontinuity evidence from Los Angeles teachers," Economics of Education Review, Elsevier, vol. 66(C), pages 104-113.
    11. Jiaying Gu & Roger Koenker, 2022. "Ranking and Selection from Pairwise Comparisons: Empirical Bayes Methods for Citation Analysis," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 624-629, May.
    12. Jonathan T. Kolstad, 2013. "Information and Quality When Motivation Is Intrinsic: Evidence from Surgeon Report Cards," American Economic Review, American Economic Association, vol. 103(7), pages 2875-2910, December.
    13. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
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    Cited by:

    1. Christopher Walters, 2024. "Empirical Bayes Methods in Labor Economics," RF Berlin - CReAM Discussion Paper Series 2422, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    2. Melo, Vitor & Rocha, Hugo Vaca Pereira & Sigaud, Liam & Warren, Patrick L. & Gaddis, S. Michael, 2024. "Understanding Discrimination in College Admissions: A Field Experiment," SocArXiv 5ctms, Center for Open Science.

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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