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How to Measure and Draw Causal Inferences with Patent Scope


  • Jeffrey M. Kuhn
  • Neil C. Thompson


This paper presents an easy-to-use measure of patent scope that is grounded both in patent law and in the practices of patent attorneys. We validate our measure by showing both that patent attorneys’ subjective assessments of scope agree with our estimates, and that the behavior of patenters is consistent with it. Using our validation exercise, we find that previous measures of patent scope (i.e., the number of patent classes, the number of citations made by future patents, and the number of claims in a patent) are uninformative or misleading. To facilitate drawing causal inferences with our measure, we show how it can be used to create an instrumental variable, patent examiner scope toughness, which we also validate. We then demonstrate the power of this instrument by examining standard-essential patents. We show that an (exogenous) diminishment of patent scope leads to patents being much less likely to be declared standard essential.

Suggested Citation

  • Jeffrey M. Kuhn & Neil C. Thompson, 2019. "How to Measure and Draw Causal Inferences with Patent Scope," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 26(1), pages 5-38, January.
  • Handle: RePEc:taf:ijecbs:v:26:y:2019:i:1:p:5-38
    DOI: 10.1080/13571516.2018.1553284

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