Measuring the Impact of Household Innovation Using Administrative Data
We link USPTO patent data to US Census Bureau administrative records on individuals and firms. The combined dataset provides us with a directory of
patenting household inventors as well as a time-series directory of self-employed businesses tied to household innovations. We describe the characteristics of household inventors by race, age, gender and US origin, as well as the types of patented innovations pursued by these inventors. Business data allows us to highlight how patents shape the early life-cycle dynamics of nonemployer businesses. We find household innovators are disproportionately US born, white and their age distribution has thicker tails relative to business innovators. Data shows there is a deficit of female and black inventors. Household inventors tend to work in consumer product areas compared to traditional business patents. While patented household innovations do not have the same impact of business innovations their uniqueness and impact remains surprisingly high. Back of the envelope calculations suggest patented household innovations granted between 2000 and 2011 might generate $5.0B in revenue (2000 dollars).
We would like to thank Scott Stern, Shawn Klimek, Eric von Hippel, Mark Leach and Dan Sichel for valuable comments. We also thank participants in the CRIW conference Measuring and Accounting for Innovation in the 21st Century and two anonymous referees for their comments. All errors or omissions are our own. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau or the National Bureau of Economic Research. All results have been reviewed to ensure that no confidential information is disclosed. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
In compliance with the requirement of the Journal’s disclosure policy, I would like to state that I, Javier Miranda, am an employee of the U.S. Census Bureau. I have received no direct financial support from any organization but I am one of the Principal Investigators on the grant from the Kauffman Foundation that we note in the acknowledgements section. The support from the Kauffman Foundation is directly related to this research as they have supported the development of the data infrastructure used in this paper as well as research analysis related to the topics in this paper. We are also using proprietary data in this paper housed at the U.S. Bureau of the Census. As we note in the acknowledgements section “All results have been reviewed to ensure that no confidential information is disclosed.”