Work

Measuring Science: Performance Metrics and the Allocation of Talent

Year: 2024

Type: article

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.

Source: American Economic Review

DOI: 10.1257/aer.20230515

Authors: Sebastian Hager, Carlo Schwarz, Fabian Waldinger

Institutions: University of Oxford, Bocconi University, Ludwig-Maximilians-Universität München

Language: English

Topic: scientometrics and bibliometrics research

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: green

Funder: Economic and Social Research Council