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SUMMARY:Reveal or Conceal? Employer Learning in the Labor Market for Compu
 ter Scientists - Alice Wu (University of Wisconsin–Madison)
DTSTART;VALUE=DATE-TIME:20250225T160000Z
DTEND;VALUE=DATE-TIME:20250225T171500Z
UID:https://talks.ox.ac.uk/talks/id/3d1178c1-8dde-4b67-9b94-b0d9bbf2e6de/
DESCRIPTION:How does employer learning affect the allocation of talent in 
 the market for research scientists? I study this question using the job hi
 stories of 40\,000 Ph.D.'s in computer science (CS) matched to their scien
 tific publications and patent applications. Authorship of a CS conference 
 proceeding doubles the probability that a researcher moves to one of the t
 op tech firms in the following year\, controlling for her origin firm and 
 experience\, implying a strong role for public learning in the matching pr
 ocess between more productive workers and more productive firms. Many high
 er-quality papers are accompanied by a related patent application\, but th
 e existence of an application is private information for 18 months. Author
 s of such papers are somewhat less likely to move up the firm ladder in th
 e following year\, but are more likely to end up at a top firm within thre
 e years\, as predicted by a model of employer wage setting with asymmetric
  information. I estimate a structural version of the model and find that i
 n the absence of employer learning from scientific publications\, the inno
 vation output of early-career computer scientists would drop by 16%. Discl
 osing patent applications one year faster would increase innovation by 1%\
 , driven by a faster rate of assortative matching.\nSpeakers:\nAlice Wu (U
 niversity of Wisconsin–Madison)
LOCATION:Manor Road Building (Seminar Room A)\, Manor Road OX1 3UQ
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/3d1178c1-8dde-4b67-9b94-b0d9bbf2e6de/
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DESCRIPTION:Talk:Reveal or Conceal? Employer Learning in the Labor Market 
 for Computer Scientists - Alice Wu (University of Wisconsin–Madison)
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