Inventor Gender and Patent Undercitation: Evidence from Causal Text Estimation
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下载链接：
https://www.nber.org/papers/w31592
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资源简介：
Implementing a state-of-the-art machine learning technique for causal identification from text data (C-TEXT), we document that patents authored by female inventors are under-cited relative to those authored by males. Relative to what the same patent would be predicted to receive had the lead
提供机构：
美国国家经济研究局
创建时间：
2023-08-01
