Are Patents with Female Inventors Under-Cited? Evidence from Text Estimation

Mendeley Data 2026 Dataset Open access

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Authors: Yael V. Hochberg, Ali Kakhbod, Peiyao Li, Kunal Sachdeva
DOI: 10.17632/zz8g5nznhb
Cited by: 0

Abstract

This repository contains the replication data and code for the paper "Are Patents with Female Inventors Under-Cited? Evidence from Text Estimation," The dataset provides the quantitative metrics used to evaluate the citation deficit of patents with female inventors, specifically including our text-based expected citation measures, actual patent citation counts, and inventor gender classifications.

Fields of Study & Subjects

Intellectual Property and Patents scientometrics and bibliometrics research Diversity and Career in Medicine

Publication details

Journal / source
Mendeley Data
Publication date
3 March 2026
Language
EN
Document type
Dataset