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Prof. Alice Wu
Postdoctoral Fellow of Economics
University of Wisconsin, Madison

This paper tests for employer learning about worker ability and quantifies the role of learning in improving the allocation of talent in the labor market for computer scientists. We match the job history of over 40,000 Ph.D. computer scientists (CS) with publications and patent applications that signal their research ability. Workers who publish at CS conferences are twice as likely to move to a top tech firm in the next year as similar coworkers without a publication. Higher-quality papers are often filed as patent applications, but the fact of filing remains private information at the incumbent employer for 18 months. Authors of such papers experience a delayed increase in inter-firm and upward mobility. Without employer learning from public research records, the innovation output of early career computer scientists would drop by 16%, 30% of which is due to less efficient sorting between firms and 70% due to greater misallocation within firms.