Abstract

ABSTRACT The current literature provides little empirical evidence on the study of salaries for young faculty members in the economic department, possibly because effective recognition of their research productivity remains a difficult challenge. To address this research gap, we analyse the effects of gender, PhD graduation school rank and undergraduate major on the salaries of young economics professors with varying experience levels. We create a novel dataset by manually collecting detailed and time-varying research productivity measures and demographic information of young economics professors from the top 50 public research universities in the U.S. We use double machine learning to obtain consistent estimators, which allows us to account for non-parametric features associated with the high-dimensional control variable set. Our findings indicate that in experience years 4 to 8, which is the time most faculty tenured, the gender effect estimates are statistically significant and large enough in magnitude to have practical implications. For PhD graduation school rank and undergraduate major, the effects in experience years 7 to 9 are large in magnitude but do not have statistical significance.

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