Working Paper: CEPR ID: DP17474
Authors: Audinga Baltrunaite; Alessandra Casarico; Lucia Rizzica
Abstract: We study the presence and the extent of gender differences in reference letters for graduate students in economics and finance, and how they relate to early labor market outcomes. To these ends, we build a novel rich dataset and combine Natural Language Processing techniques with standard regression analysis. We find that men are described more often as brilliant and women as hardworking and diligent. We show that the former (latter) characteristics relate positively (negatively) with various subsequent career outcomes. We provide evidence that the observed differences in the way candidates are described are driven by implicit gender stereotypes.
Keywords: gender bias; research institutions; professional labor markets; word embeddings
JEL Codes: I23; J16; J44
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Implicit gender stereotypes (J16) | Early career outcomes (J24) |
| Men described as 'brilliant' (Y30) | Early career success (J62) |
| Women described as 'hardworking' and 'diligent' (J21) | Early career success (J62) |
| Similarity to standout descriptions (C52) | Likelihood of being hired at a top 20 institution (I23) |
| Similarity to grindstone terms (C60) | Likelihood of success (C52) |