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Replication data for: Expertise versus Bias in Evaluation: Evidence from the NIH

Version
1
Resource Type
Dataset
Creator
  • Li, Danielle
Publication Date
2017-04-01
Description
  • Abstract

    Evaluators with expertise in a particular field may have an informational advantage in separating good projects from bad. At the same time, they may also have personal preferences that impact their objectivity. This paper examines these issues in the context of peer review at the US National Institutes of Health. I show that evaluators are both better informed and more biased about the quality of projects in their own area. On net, the benefits of expertise weakly dominate the costs of bias. As such, policies designed to limit bias by seeking impartial evaluators may reduce the quality of funding decisions.
Availability
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Relations
  • Is supplement to
    DOI: 10.1257/app.20150421 (Text)
Publications
  • Li, Danielle. “Expertise versus Bias in Evaluation: Evidence from the NIH.” American Economic Journal: Applied Economics 9, no. 2 (April 2017): 60–92. https://doi.org/10.1257/app.20150421.
    • ID: 10.1257/app.20150421 (DOI)

Update Metadata: 2020-05-18 | Issue Number: 2 | Registration Date: 2019-10-12

Li, Danielle (2017): Replication data for: Expertise versus Bias in Evaluation: Evidence from the NIH. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E113662V1