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Are patents with female inventors under-cited? Evidence from text estimation

Author

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  • Hochberg, Yael V.
  • Kakhbod, Ali
  • Li, Peiyao
  • Sachdeva, Kunal

Abstract

Utilizing leading machine learning techniques to analyze the textual content and quality of patents, we demonstrate that patents with female lead inventors are under-cited relative to what would be expected had the lead inventor been male. Male inventors are the greatest contributors to the undercitation of patents with female inventors, followed by female inventors and male examiners, while female patent examiners appear to be even-handed. Using market reactions to patents suggests no average difference in market value by the inventor’s gender. The results have potential implications for research conclusions that rely on citation-based assessments of patent quality.

Suggested Citation

  • Hochberg, Yael V. & Kakhbod, Ali & Li, Peiyao & Sachdeva, Kunal, 2026. "Are patents with female inventors under-cited? Evidence from text estimation," Journal of Financial Economics, Elsevier, vol. 183(C).
    • Handle: RePEc:eee:jfinec:v:183:y:2026:i:c:s0304405x26000784
    DOI: 10.1016/j.jfineco.2026.104307
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    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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