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衡量科学:绩效指标与人才配置

Measuring Science: Performance Metrics and the Allocation of Talent
American Economic Review · 2024 · Sebastian Hager、Carlo Schwarz、Fabian Waldinger

中文摘要

本文利用科学界首个引文数据库的推出,研究绩效指标如何影响人才配置。由于技术原因,该数据库仅收录特定期刊和年份的引文,从而产生了准随机变异:一些引文变得可见,而另一些仍不可见。我们通过比较可见引文与不可见引文的预测能力来识别引文指标的影响。引文指标通过减少地理和学术距离上的信息摩擦,提高了科学家与院系之间的正向匹配程度。来自排名较低院系的高被引科学家(“隐匿之星”)以及少数群体科学家获益更多。引文指标还影响了晋升和美国国家科学基金会(NSF)的资助,表明存在马太效应。(JEL A14、I23、J44)

Abstract

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. (JEL A14, I23, J44)
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