Innovation Network

Innovation and Economic Growth, Intellectual Property and Patents

Article Snapshot


Daron Acemoglu, Ufuk Akcigit and William R. Kerr


Proceedings of the National Academy of Sciences of the United States of America, Vol. 113, No. 42, pp. 11483-11488, October 11, 2016


A survey of the citation patterns of United States patents from 1975 to 2004 shows that innovation levels in one decade strongly predict innovation levels in the next decade. When there is more past innovation in a technology class, more innovation in related technology classes follows.

Policy Relevance

Reduction in research and development funding one year will affect innovation years later.

Main Points

  • Many scholars have observed that innovation is cumulative, but exactly how past innovation affects innovation in the long run is not well understood.
  • 55 percent of the variation in patenting levels of different technology classes between 1995 and 2004 can be explained by differences in patenting levels in related technology classes between 1975 and 1994.
  • The technology classes "Chemicals: Coating" and "Nuclear & X-rays" displayed similar patenting rates from 1975 to 1984; the former class drew on innovation in "Chemicals: Misc." while the latter drew on innovation inputs from "Electrical Measuring & Testing."
    • From 1985 to 1994, the “Chemicals: Misc.” grew much more rapidly than “Electrical Measuring & Testing.”
    • From 1995 to 2005, "Chemicals: Coating" grew much faster than "Nuclear & X-rays."
  • Innovators cite older patents within their own field for a wide variety of reasons; to ensure that citation counts do not distort the final picture of cumulative innovation, one should assess cumulative innovation both with and without counting a patent’s citations to other patents within its own field.
  • Relationships between different categories of technologies are strong and stable; for example, patents in “Computers: Peripherals” consistently draw more from “Computers: Communications” than the reverse.
  • The finding that upstream innovation affects levels of downstream innovation years later suggests that a drop in research and development funding will continue to have effects years later.

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