Great questions! Indeed, someone reading and (hopefully) learning from this answer is an example of a knowledge spillover. Generally, knowledge spillovers are characterized by a situation where the creators of knowledge cannot fully control how their knowledge is used and may not always be compensated for it. For instance, many answers posted on Quora can lead to knowledge spillovers. Therefore, the answer to the first question is a resounding yes.
The answer to the second question is more nuanced. While the existence of knowledge spillovers is readily apparent, quantifying and tracking them over time is challenging. Paul Krugman noted that such spillovers are “are invisible; they leave no paper trail by which they may be measured and tracked” (Krugman 1991). This inherent invisibility, however, has not deterred researchers!
In 1993, Adam Jaffe, Manuel Trajtenberg, and Rebecca Henderson (Jaffe et al. 1993) introduced the idea of using patent citations as a means to measure knowledge spillovers. The patent system operates on a quid pro quo basis, where inventors disclose their ideas to the public in exchange for exclusive rights to their invention. While replication of the patented idea is prohibited due to the inventor’s exclusive rights, others are free to learn from the disclosed idea and develop new technologies based on it. Paul Romer emphasized patents as a source of knowledge spillovers in his influential paper on economic growth (Romer 1990):
“[I]nventors are free to spend time studying the patent application for the widget and learn knowledge that helps in the design of a wodget. The inventor of the widget has no ability to stop the inventor of a wodget from learning from the design of a widget.”
According to the rules of the patent system, if patent B is developed using knowledge from patent A, it should cite patent A. Jaffe et al. (1993) utilized patent citations to trace the diffusion of knowledge spillovers across different geographical locations. Since their seminal paper, the use of patent citations has been expanded to various applications, such as estimating models of economic growth and providing policy recommendations.
A recent study by Fadeev (2023) highlights a decline in the number of firms citing a typical patent, which could be interpreted as a decrease in the diffusion of knowledge spillovers. However, this interpretation encounters a significant problem. The paper argues that citations may not accurately reflect knowledge spillovers in the way we have previously discussed. It shows that the majority of citations come from business partners of the patent owners, often originating from just one partner. For example, IBM’s patent 5877043 has 218 citations, yet 94% of these are from a single input supplier, Amkor Technology.
The paper argues that firms often do not disclose all their knowledge in patent filings, keeping certain aspects secret. A case in point is the complexity of mRNA technology used in COVID-19 vaccines. Simply reading the patent files does not reveal the entirety of the technology, as many trade secrets and technical know-how are not included in the patents (e.g., Price II et al. 2020). As a result, it becomes challenging for others to fully learn from the patent without access to these undisclosed secrets. Fadeev (2023) suggests that citations are predominantly from a few partners because only they have access to the confidential information surrounding the patent. While the patent system mandates certain disclosure requirements, firms have developed ways to circumvent these requirements, as noted by some legal scholars (Roin 2005).
Patent citations are not the only method for measuring knowledge spillovers. Nicholas Bloom, Mark Schankerman, and John Van Reenen (Bloom et al. 2013) have introduced an alternative approach. Imagine two firms, A and B, each filing patents in a similar area. If the productivity of firm B shows a positive response to the R&D expenditures of firm A, this could indicate a knowledge spillover from A to B. A subsequent study by Lucking et al. (2019) showed that the degree of knowledge spillovers, as measured in this manner, has not changed over time. However, a recent paper by Arqué-Castells & Spulber (2022) challenges this view. Their research reveals that the firms commonly used in such estimations (A and B) often engage in licensing agreements. As a result, the observed improvement in B’s productivity might not be an incidental benefit; rather, firm B could be paying firm A for this advantage.
In summary, the common measures of knowledge spillovers might actually capture cooperation and intentional knowledge sharing between business partners. While it is possible that the degree of knowledge spillovers has changed over time, the observed changes in citation patterns are more indicative of the decline in intentional cooperation among business partners rather than a decrease in knowledge spillovers.
The distinction between unintended spillovers and intentional knowledge sharing holds significant implications for various economic questions. For example, the rationale behind R&D subsidies is often anchored in the concept of knowledge spillovers: firms may under-invest in R&D if they cannot fully capture the value of their inventions. However, if firms are able to control the diffusion of their knowledge, such as by selectively sharing trade secrets with certain partners, then the effectiveness of R&D subsidies comes into question.
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