Measuring Technological Innovation over the Long Run

摘要

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 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 levels. 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 nonprofit 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.