Measuring Science: Performance Metrics and the Allocation of Talent

• 成果类型: Article
• 署名作者: Hager, Sebastian; Schwarz, Carlo; Waldinger, Fabian
• 署名单位: University of Oxford; Bocconi University; Bocconi University; Centre for Economic Policy Research - UK; University of Munich; Leibniz Association; Ifo Institut
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20230515
• 发表日期: 2024
• 页码: 4052-4090
• 关键词: high wage workers; INFORMATION; CONSEQUENCES; scientists; KNOWLEDGE; collapse

摘要

We study how performance metrics affect the allocation of talent by exploiting the introduction of the first citation database in science. For technical reasons, it only covered citations from certain journals and years, creating quasi-random variation: some citations became visible, while others remained invisible. We identify the effects of citation metrics by comparing the predictiveness of visible to invisible citations. Citation metrics increased assortative matching between scientists and departments by reducing information frictions over geographic and intellectual distance. Highly cited scientists from lower-ranked departments ( hidden stars) and from minorities benefited more. Citation metrics also affected promotions and NSF grants, suggesting Matthew effects.