Patents and knowledge diffusion: The impact of machine translation

Benjamin Buettner*, M. Firat, Emilio Raiteri*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Web of Science)


One of the main rationales for the existence of the patent system is to encourage knowledge diffusion through the full disclosure of the technical knowledge embodied in a patented invention. Yet, economists and legal scholars cast doubts on the validity of the disclosure theory. The empirical evidence on the actual benefits of the disclosure function remains limited. The present paper aims to expand our understanding of how information spreads via patent disclosure and exploits recent improvements in machine translation (MT) to identify the effect of broader access to patented knowledge. More specifically, the paper uses a unique natural experiment. In September 2013, Google launched a major upgrade to its Google Patents service and added patent applications from the China National Intellectual Property Agency (CNIPA) to its searchable patent database. Using a difference-in-differences approach, we show that the translation of the Chinese patents into English resulted in an increase in citations received from patents filed by US inventors compared to a suitable control group comprising patents that Google translated only in 2016. Our results suggest that improved access to patented knowledge fosters knowledge diffusion.
Original languageEnglish
Article number104584
Number of pages18
JournalResearch Policy
Issue number10
Early online date6 Jul 2022
Publication statusPublished - Dec 2022


  • Google patents
  • Knowledge diffusion
  • Machine translation
  • Patent disclosure


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