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The signal quality of grades across academic fields
Author(s) -
Thomas James
Publication year - 2019
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2684
Subject(s) - quality (philosophy) , science and engineering , field (mathematics) , signal (programming language) , mathematics education , computer science , psychology , mathematics , engineering ethics , physics , engineering , quantum mechanics , pure mathematics , programming language
Summary I use transcript data from Duke University and a correlated learning model to measure the signal quality of grades across academic fields. I find science, engineering, and economics grades are significantly more informative than humanities and social science grades. The correlated learning structure allows grades in one field to signal abilities in all fields. This sometimes generates information spillovers so powerful that science, engineering, and economics grades inform humanities and social science beliefs more than humanities and social science grades. I show that grade compression reduces signal quality but cannot explain the differences in signal quality across academic fields.