How to Measure and Draw Causal Inferences with Patent Scope

38 Pages Posted: 30 May 2017 Last revised: 29 Jul 2019

See all articles by Jeffrey M. Kuhn

Jeffrey M. Kuhn

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School

Neil Thompson

MIT Computer Science and Artificial Intelligence Lab (CSAIL); MIT Initiative on the Digital Economy

Date Written: October 9, 2017

Abstract

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 behaviour 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.

Keywords: patent scope, patents, causal inference, innovation, measurement, patent examiners, examiner toughness

JEL Classification: O3, O30, O31, O32, O34, L11, K12, D4, D49

Suggested Citation

Kuhn, Jeffrey M. and Thompson, Neil, How to Measure and Draw Causal Inferences with Patent Scope (October 9, 2017). International Journal of the Economics of Business, 26(1) 5-38 (2019). Available at SSRN: https://ssrn.com/abstract=2977273 or http://dx.doi.org/10.2139/ssrn.2977273

Jeffrey M. Kuhn (Contact Author)

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School ( email )

McColl Building
Chapel Hill, NC 27599-3490
United States

Neil Thompson

MIT Computer Science and Artificial Intelligence Lab (CSAIL) ( email )

32 Vassar Street
G766
Cambridge, MA 02142
United States
617-324-6029 (Phone)

HOME PAGE: http://www.neil-t.com

MIT Initiative on the Digital Economy ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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