Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research.
This paper assesses the validity and accuracy of firms' backward patent citations as a measure of knowledge flows from public research by employing a newly constructed dataset that matches patents to survey data at the level of the R&D lab. Using survey-based measures of the dimensions of knowledge flows, we identify sources of systematic measurement error associated with backward citations to both patent and nonpatent references. We find that patent citations reflect the codified knowledge flows from public research, but they appear to miss knowledge flows that are more private and contract-based in nature, as well as those used in firm basic research. We also find that firms' patenting and citing strategies affect patent citations, making citations less indicative of knowledge flows. In addition, an illustrative analysis examining the magnitude and direction of measurement error bias suggests that measuring knowledge flows with patent citations can lead to substantial underestimation of the effect of public research on firms' innovative performance. Throughout our analyses we find that nonpatent references (e.g., journals, conferences, etc.), not the more commonly used patent references, are a better measure of knowledge originating from public research.
The Fuqua School of Business, Duke University, michael.roach@duke.edu.
Michael
M
Roach
The Fuqua School of Business, Duke University, National Bureau of Economic Research, wcohen@duke.edu.
Wesley M
WM
Cohen
innovation; knowledge flows; measurement; patent citations; universities