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Was Electricity a General Purpose Technology? Evidence from Historical Patent Citations

General purpose technologies (GPTs) are credited with generating the increasing returns that drive endogenous growth. For example, Paul David (1991) explains the surge in U.S. productivity during the 1920’s as a delayed response to the introduction of the electric dynamo in the 1880’s. To the extent that GPTs yield large positive externalities on a wide range of industries some time after they are discovered, individual inventors are likely to underinvest in them, and government intervention may be necessary to reach optimal levels of investment in research and development. This theory assumes that GPTs can be identified. While the growth implications of GPTs are well documented in theory (Elhanan Helpman, 1998) empirical evidence remains sparse. With the exception of Nathan Rosenberg and Manuel Trajtenberg (2001), who analyze the example of the Corliss steam engine, existing empirical work is based largely on data with a high level of aggregation (Boyan Jovanovic and Peter Rousseau, 2003; N. F. R. Crafts and Terrence Mills, 2004). This leaves a gap in our understanding of the micro-foundations of GPTs. Although Richard Lipsey et al. (1998) define GPTs by four criteria (a wide scope for improvement and elaboration, applicability across a broad range of uses, potential for use in a wide variety of products and processes, and strong complementarities with existing or potential new technologies), these claims have not been verified systematically. This paper uses historical patent citation data to test whether electricity, as the canonical example of a General Purpose Technology, matches the current criteria of GPTs. We use a sample of American patents assigned to publicly traded companies in biennial years of the 1920’s to check which of four industry categories (electricity, chemicals, mechanical, and other) most closely matches the key elements of GPTs. We analyze the characteristics of our patents at their grant date and trace knowledge embodied in these patents through citations in patent grants between 1976 and 2002. Our sample consists of 1,867 U.S. patents from the 1920’s, and 3,400 forward citations to these patents. Our aim is both to help inform the way that growth theorists model the development of GPTs and to enhance our understanding of technological progress in the last century more generally. The 1920’s are an appropriate decade for our hypothesis test because they were a period of exceptional inventive activity and productivity increases. David (1991) credits electricity with a central role in U.S. productivity growth in the 1920’s, 40 years after Thomas Edison’s patent of the filament lamp. But the 1920’s was not just a decade of electrification. Alexander Field (2003) conjectures that a “larder stock” of 1920’s innovations may have accelerated productivity growth during the 1930’s, a period he describes as “the most technologically progressive decade of the [20th] century.” Electricity made it possible for workflows in the factory to be restructured away from traditional energy sources such as water power. However, other advances, especially those in fuel, automobiles, trucks, and tires, had a significant (possibly even greater) impact on spatial allocation and the structure of economic life. Benzene-powered motor vehicles, with rubber tires and lighter metal casings, depended on chemical rather than electrical inventions. Our results contradict the hypothesis that electricity was a GPT according to conventional definitions such as those of Timothy Bresnahan and Trajtenberg (1995) or Lipsey et al. (1998). We find that electricity patents were broader in * Moser: Sloan School of Management, Massachusetts Institute of Technology, 50 Memorial Drive, Cambridge, MA 02142-1347; Nicholas: The Brattle Group, 353 Sacramento Street, Suite 1140, San Francisco, CA 94111. We thank Bhaven Sampat for helpful comments and Ellyn Boukus for excellent research assistance.