Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research
利用新构建的专利与研发实验室调查匹配数据，评估企业向后专利引用作为公共研究知识流动指标的准确性，发现专利引用主要反映编码化知识，但遗漏了私人、合同性质的知识及企业基础研究中的知识，且企业专利和引用策略会降低其指示性。
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 data set that matches patents to survey data at the level of the research and development 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. This paper was accepted by Lee Fleming, entrepreneurship and innovation.