Measuring Technological Innovation Over the Long Run

47 Pages Posted: 5 Dec 2018 Last revised: 11 Jun 2020

See all articles by Bryan T. Kelly

Bryan T. Kelly

Yale SOM; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)

Dimitris Papanikolaou

Northwestern University - Kellogg School of Management - Department of Finance; National Bureau of Economic Research (NBER)

Amit Seru

Stanford University

Matt Taddy

University of Chicago

Multiple version iconThere are 2 versions of this paper

Date Written: January 1, 2020

Abstract

We use textual analysis of high-dimensional data from patent documents to create new indicators of technological innovation. We identify important patents based on textual similarity of a given patent to previous and subsequent work: these patents are distinct from previous work but are related to subsequent innovations. Our importance indicators correlate with existing measures of patent quality but also provide complementary information. We identify breakthrough innovations as the most important patents—those in the right tail of our measure—and construct time-series indices of technological change at the aggregate and sectoral level. Our technology indices capture the evolution of technological waves over a long time span (1840 to the present) and cover innovation by private and public firms, as well as non-profit organizations and the US government. Advances in electricity and transportation drive the index in the 1880s; chemicals and electricity in the 1920s and 1930s; and computers and communication in the post-1980s.

Suggested Citation

Kelly, Bryan T. and Papanikolaou, Dimitris and Seru, Amit and Taddy, Matt, Measuring Technological Innovation Over the Long Run (January 1, 2020). Yale ICF Working Paper No. 2018-19, Available at SSRN: https://ssrn.com/abstract=3279254 or http://dx.doi.org/10.2139/ssrn.3279254

Bryan T. Kelly

Yale SOM ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

AQR Capital Management, LLC ( email )

Greenwich, CT
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Dimitris Papanikolaou (Contact Author)

Northwestern University - Kellogg School of Management - Department of Finance ( email )

Evanston, IL 60208
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Amit Seru

Stanford University ( email )

Stanford, CA 94305
United States

Matt Taddy

University of Chicago ( email )

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