Lead Inventor Gender and Patent Citations : Evidence from Causal BERT Estimation

Implementing a state-of-the-art machine learning technique for causal identification of the effects of binary treatment from textual analysis, we document that women are under-cited relative to the quality of their patents. For the equivalent patent with a lead female inventor, a patent with a male lead inventor would have received 12% more citations. These effects are magnified for patents in emerging technology fields. Male lead inventors in particular tend to undercite patents with female lead inventors, while patent examiners of both genders appear to be more even-handed. The under-recognition of female-authored patents likely has economic implications for the allocation of talent in the economy